Merge branch 'main' into docs-publish-v0

.github/changes-filter.yaml

@@ -25,6 +25,7 @@ starter-projects:
   - "src/backend/base/langflow/components/**"
   - "src/backend/base/langflow/services/**"
   - "src/backend/base/langflow/custom/**"
+  - "src/backend/base/langflow/api/v1/chat.py"
   - "src/frontend/src/pages/MainPage/**"
   - "src/frontend/src/utils/reactflowUtils.ts"
   - "src/frontend/tests/extended/features/**"

.github/workflows/codeflash.yml

@@ -29,6 +29,7 @@ jobs:
       - run: uv sync --extra dev
       - name: Run Codeflash Optimizer
         working-directory: ./src/backend/base
+        continue-on-error: true
         run: uv run codeflash
       - name: Minimize uv cache
         run: uv cache prune --ci

Makefile

@@ -463,3 +463,51 @@ alembic-check: ## check migration status
 alembic-stamp: ## stamp the database with a specific revision
 	@echo 'Stamping the database with revision $(revision)'
 	cd src/backend/base/langflow/ && uv run alembic stamp $(revision)
+
+######################
+# LOAD TESTING
+######################
+
+# Default values for locust configuration
+locust_users ?= 10
+locust_spawn_rate ?= 1
+locust_host ?= http://localhost:7860
+locust_headless ?= true
+locust_time ?= 300s
+locust_api_key ?= your-api-key
+locust_flow_id ?= your-flow-id
+locust_file ?= src/backend/tests/locust/locustfile.py
+locust_min_wait ?= 2000
+locust_max_wait ?= 5000
+locust_request_timeout ?= 30.0
+
+locust: ## run locust load tests (options: locust_users=10 locust_spawn_rate=1 locust_host=http://localhost:7860 locust_headless=true locust_time=300s locust_api_key=your-api-key locust_flow_id=your-flow-id locust_file=src/backend/tests/locust/locustfile.py locust_min_wait=2000 locust_max_wait=5000 locust_request_timeout=30.0)
+	@if [ ! -f "$(locust_file)" ]; then \
+		echo "$(RED)Error: Locustfile not found at $(locust_file)$(NC)"; \
+		exit 1; \
+	fi
+	@echo "Starting Locust with $(locust_users) users, spawn rate of $(locust_spawn_rate)"
+	@echo "Testing host: $(locust_host)"
+	@echo "Using locustfile: $(locust_file)"
+	@export API_KEY=$(locust_api_key) && \
+	export FLOW_ID=$(locust_flow_id) && \
+	export LANGFLOW_HOST=$(locust_host) && \
+	export MIN_WAIT=$(locust_min_wait) && \
+	export MAX_WAIT=$(locust_max_wait) && \
+	export REQUEST_TIMEOUT=$(locust_request_timeout) && \
+	cd $$(dirname "$(locust_file)") && \
+	if [ "$(locust_headless)" = "true" ]; then \
+		uv run locust \
+			--headless \
+			-u $(locust_users) \
+			-r $(locust_spawn_rate) \
+			--run-time $(locust_time) \
+			--host $(locust_host) \
+			-f $$(basename "$(locust_file)"); \
+	else \
+		uv run locust \
+			-u $(locust_users) \
+			-r $(locust_spawn_rate) \
+			--host $(locust_host) \
+			-f $$(basename "$(locust_file)"); \
+	fi

README.ES.md

@@ -31,6 +31,7 @@
   <a href="./README.ja.md"><img alt="README en Japonés" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
   <a href="./README.KR.md"><img alt="README en Coreano" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
   <a href="./README.FR.md"><img alt="README en Francès" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README.RU.md"><img alt="README en Russian" src="https://img.shields.io/badge/Русский"></a>
 </div>
 
 <p align="center">

README.KR.md

@@ -38,6 +38,7 @@
   <a href="./README.ja.md"><img alt="README in Japanese" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
   <a href="./README.KR.md"><img alt="README in KOREAN" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
   <a href="./README.FR.md"><img alt="README in French" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README.RU.md"><img alt="README in Russian" src="https://img.shields.io/badge/Русский"></a>
 </div>
 
 <p align="center">

README.PT.md

@@ -33,6 +33,7 @@
   <a href="./README.ja.md"><img alt="README em Japonês" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
   <a href="./README.KR.md"><img alt="README em Coreano" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
   <a href="./README.FR.md"><img alt="README em Francês" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README.RU.md"><img alt="README in Russian" src="https://img.shields.io/badge/Русский"></a>
 </div>
 
 <p align="center">

README.RU.md

@@ -0,0 +1,78 @@
+<!-- markdownlint-disable MD030 -->
+
+![Langflow](./docs/static/img/hero.png)
+
+<p align="center" style="font-size: 12px;">
+    Langflow — это инструмент для создания приложений с низким уровнем кода для RAG и многоагентных ИИ-приложений. Он основан на Python и не зависит от конкретных моделей, API или баз данных.
+</p>
+
+<p align="center" style="font-size: 12px;">
+    <a href="https://docs.langflow.org" style="text-decoration: underline;">Документация</a> -
+    <a href="https://astra.datastax.com/signup?type=langflow" style="text-decoration: underline;">Бесплатный облачный сервис</a> -
+    <a href="https://docs.langflow.org/get-started-installation" style="text-decoration: underline;">Самостоятельное развертывание</a>
+
+</p>
+
+<div align="center">
+  <a href="./README.md"><img alt="README на английском" src="https://img.shields.io/badge/English-d9d9d9"></a>
+  <a href="./README.PT.md"><img alt="README на португальском" src="https://img.shields.io/badge/Portuguese-d9d9d9"></a>
+  <a href="./README.ES.md"><img alt="README на испанском" src="https://img.shields.io/badge/Spanish-d9d9d9"></a>
+  <a href="./README.zh_CN.md"><img alt="README на упрощенном китайском" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
+  <a href="./README.ja.md"><img alt="README на японском" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
+  <a href="./README.KR.md"><img alt="README на корейском" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README.FR.md"><img alt="README на французском" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README.RU.md"><img alt="README на русском" src="https://img.shields.io/badge/Русский-d9d9d9"></a>
+</div>
+
+## ✨ Основные возможности
+
+1. **Основан на Python** и не зависит от моделей, API, источников данных или баз данных.
+2. **Визуальная IDE** для построения и тестирования рабочих процессов методом drag-and-drop.
+3. **Песочница** для мгновенного тестирования и итерации процессов с поэтапным контролем.
+4. **Оркестрация многоагентных систем** с управлением диалогами и извлечением информации.
+5. **Бесплатный облачный сервис**, позволяющий начать работу за считанные минуты без настройки.
+6. **Публикация в виде API** или экспорт в виде Python-приложения.
+7. **Наблюдаемость** с интеграцией LangSmith, LangFuse или LangWatch.
+8. **Безопасность и масштабируемость уровня предприятия** с бесплатным облачным сервисом DataStax Langflow.
+9. **Настройка рабочих процессов** или создание потоков исключительно на Python.
+10. **Интеграция с экосистемами** через повторно используемые компоненты для любых моделей, API или баз данных.
+
+![Интеграции](./docs/static/img/integrations.png)
+
+## 📦 Быстрый старт
+
+- **Установка через uv (рекомендуется)** (Python 3.10–3.12):
+
+```shell
+uv pip install langflow
+```
+
+- **Установка через pip** (Python 3.10–3.12):
+
+```shell
+pip install langflow
+```
+
+- **Облако:** DataStax Langflow — это управляемая среда без необходимости настройки. [Зарегистрируйтесь бесплатно.](https://astra.datastax.com/signup?type=langflow)
+- **Самостоятельное развертывание:** Запустите Langflow в своей среде. [Установите Langflow](https://docs.langflow.org/get-started-installation), чтобы запустить локальный сервер Langflow, а затем воспользуйтесь [руководством по быстрому старту](https://docs.langflow.org/get-started-quickstart) для создания и выполнения потока.
+- **Hugging Face:** [Клонируйте пространство по этой ссылке](https://huggingface.co/spaces/Langflow/Langflow?duplicate=true), чтобы создать рабочее пространство Langflow.
+
+[![Начало работы](https://github.com/user-attachments/assets/f1adfbe7-3c35-43a4-b265-661f3d4f875f)](https://www.youtube.com/watch?v=kinngWhaUKM)
+
+## ⭐ Будьте в курсе обновлений
+
+Добавьте Langflow в избранное на GitHub, чтобы мгновенно узнавать о новых релизах.
+
+![Star Langflow](https://github.com/user-attachments/assets/03168b17-a11d-4b2a-b0f7-c1cce69e5a2c)
+
+## 👋 Внесите свой вклад
+
+Мы приветствуем вклад разработчиков любого уровня. Если хотите помочь в развитии проекта, ознакомьтесь с нашими [руководящими принципами для участников](./CONTRIBUTING.md) и сделайте Langflow еще доступнее.
+
+---
+
+[![График истории звезд](https://api.star-history.com/svg?repos=langflow-ai/langflow&type=Timeline)](https://star-history.com/#langflow-ai/langflow&Date)
+
+## ❤️ Соавторы
+
+[![Соавторы Langflow](https://contrib.rocks/image?repo=langflow-ai/langflow)](https://github.com/langflow-ai/langflow/graphs/contributors)

README.ja.md

@@ -38,6 +38,7 @@
   <a href="./README.ja.md"><img alt="README in Japanese" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
   <a href="./README.KR.md"><img alt="README in KOREAN" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
   <a href="./README.FR.md"><img alt="README in French" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README.RU.md"><img alt="README in Russian" src="https://img.shields.io/badge/Русский"></a>
 </div>
 
 <p align="center">

README.md

@@ -21,6 +21,7 @@
   <a href="./README.ja.md"><img alt="README in Japanese" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
   <a href="./README.KR.md"><img alt="README in KOREAN" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
   <a href="./README.FR.md"><img alt="README in French" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README.RU.md"><img alt="README in Russian" src="https://img.shields.io/badge/Русский"></a>
 </div>
 
 ## ✨ Core features

README.zh_CN.md

@@ -33,6 +33,7 @@
   <a href="./README.ja.md"><img alt="README in Japanese" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
   <a href="./README.KR.md"><img alt="README in KOREAN" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
   <a href="./README.FR.md"><img alt="README in French" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README.RU.md"><img alt="README in Russian" src="https://img.shields.io/badge/Русский"></a>
 </div>
 
 <p align="center">

pyproject.toml

@@ -191,6 +191,7 @@ dev-dependencies = [
     "types-aiofiles>=24.1.0.20240626",
     "codeflash>=0.8.4",
     "hypothesis>=6.123.17",
+    "locust>=2.32.9",
 ]
 
 

src/backend/base/langflow/api/build.py

@@ -0,0 +1,428 @@
+import asyncio
+import json
+import time
+import traceback
+import uuid
+from collections.abc import AsyncIterator
+
+from fastapi import BackgroundTasks, HTTPException
+from fastapi.responses import JSONResponse
+from loguru import logger
+from sqlmodel import select
+
+from langflow.api.disconnect import DisconnectHandlerStreamingResponse
+from langflow.api.utils import (
+    CurrentActiveUser,
+    build_graph_from_data,
+    build_graph_from_db,
+    format_elapsed_time,
+    format_exception_message,
+    get_top_level_vertices,
+    parse_exception,
+)
+from langflow.api.v1.schemas import (
+    FlowDataRequest,
+    InputValueRequest,
+    ResultDataResponse,
+    VertexBuildResponse,
+)
+from langflow.events.event_manager import EventManager
+from langflow.exceptions.component import ComponentBuildError
+from langflow.graph.graph.base import Graph
+from langflow.graph.utils import log_vertex_build
+from langflow.schema.message import ErrorMessage
+from langflow.schema.schema import OutputValue
+from langflow.services.database.models.flow import Flow
+from langflow.services.deps import get_chat_service, get_telemetry_service, session_scope
+from langflow.services.job_queue.service import JobQueueService
+from langflow.services.telemetry.schema import ComponentPayload, PlaygroundPayload
+
+
+async def start_flow_build(
+    *,
+    flow_id: uuid.UUID,
+    background_tasks: BackgroundTasks,
+    inputs: InputValueRequest | None,
+    data: FlowDataRequest | None,
+    files: list[str] | None,
+    stop_component_id: str | None,
+    start_component_id: str | None,
+    log_builds: bool,
+    current_user: CurrentActiveUser,
+    queue_service: JobQueueService,
+) -> str:
+    """Start the flow build process by setting up the queue and starting the build task.
+
+    Returns:
+        the job_id.
+    """
+    job_id = str(uuid.uuid4())
+    try:
+        _, event_manager = queue_service.create_queue(job_id)
+        task_coro = generate_flow_events(
+            flow_id=flow_id,
+            background_tasks=background_tasks,
+            event_manager=event_manager,
+            inputs=inputs,
+            data=data,
+            files=files,
+            stop_component_id=stop_component_id,
+            start_component_id=start_component_id,
+            log_builds=log_builds,
+            current_user=current_user,
+        )
+        queue_service.start_job(job_id, task_coro)
+    except Exception as e:
+        logger.exception("Failed to create queue and start task")
+        raise HTTPException(status_code=500, detail=str(e)) from e
+    return job_id
+
+
+async def get_flow_events_response(
+    *,
+    job_id: str,
+    queue_service: JobQueueService,
+    stream: bool = True,
+):
+    """Get events for a specific build job, either as a stream or single event."""
+    try:
+        main_queue, event_manager, event_task = queue_service.get_queue_data(job_id)
+        if stream:
+            if event_task is None:
+                raise HTTPException(status_code=404, detail="No event task found for job")
+            return await create_flow_response(
+                queue=main_queue,
+                event_manager=event_manager,
+                event_task=event_task,
+            )
+
+        # Polling mode - get exactly one event
+        _, value, _ = await main_queue.get()
+        if value is None:
+            # End of stream, trigger end event
+            if event_task is not None:
+                event_task.cancel()
+            event_manager.on_end(data={})
+
+        return JSONResponse({"event": value.decode("utf-8") if value else None})
+
+    except ValueError as exc:
+        raise HTTPException(status_code=404, detail=str(exc)) from exc
+
+
+async def create_flow_response(
+    queue: asyncio.Queue,
+    event_manager: EventManager,
+    event_task: asyncio.Task,
+) -> DisconnectHandlerStreamingResponse:
+    """Create a streaming response for the flow build process."""
+
+    async def consume_and_yield() -> AsyncIterator[str]:
+        while True:
+            try:
+                event_id, value, put_time = await queue.get()
+                if value is None:
+                    break
+                get_time = time.time()
+                yield value.decode("utf-8")
+                logger.debug(f"Event {event_id} consumed in {get_time - put_time:.4f}s")
+            except Exception as exc:  # noqa: BLE001
+                logger.exception(f"Error consuming event: {exc}")
+                break
+
+    def on_disconnect() -> None:
+        logger.debug("Client disconnected, closing tasks")
+        event_task.cancel()
+        event_manager.on_end(data={})
+
+    return DisconnectHandlerStreamingResponse(
+        consume_and_yield(),
+        media_type="application/x-ndjson",
+        on_disconnect=on_disconnect,
+    )
+
+
+async def generate_flow_events(
+    *,
+    flow_id: uuid.UUID,
+    background_tasks: BackgroundTasks,
+    event_manager: EventManager,
+    inputs: InputValueRequest | None,
+    data: FlowDataRequest | None,
+    files: list[str] | None,
+    stop_component_id: str | None,
+    start_component_id: str | None,
+    log_builds: bool,
+    current_user: CurrentActiveUser,
+) -> None:
+    """Generate events for flow building process.
+
+    This function handles the core flow building logic and generates appropriate events:
+    - Building and validating the graph
+    - Processing vertices
+    - Handling errors and cleanup
+    """
+    chat_service = get_chat_service()
+    telemetry_service = get_telemetry_service()
+    if not inputs:
+        inputs = InputValueRequest(session=str(flow_id))
+
+    async def build_graph_and_get_order() -> tuple[list[str], list[str], Graph]:
+        start_time = time.perf_counter()
+        components_count = 0
+        graph = None
+        try:
+            flow_id_str = str(flow_id)
+            # Create a fresh session for database operations
+            async with session_scope() as fresh_session:
+                graph = await create_graph(fresh_session, flow_id_str)
+
+            graph.validate_stream()
+            first_layer = sort_vertices(graph)
+
+            if inputs is not None and getattr(inputs, "session", None) is not None:
+                graph.session_id = inputs.session
+
+            for vertex_id in first_layer:
+                graph.run_manager.add_to_vertices_being_run(vertex_id)
+
+            # Now vertices is a list of lists
+            # We need to get the id of each vertex
+            # and return the same structure but only with the ids
+            components_count = len(graph.vertices)
+            vertices_to_run = list(graph.vertices_to_run.union(get_top_level_vertices(graph, graph.vertices_to_run)))
+
+            await chat_service.set_cache(flow_id_str, graph)
+            await log_telemetry(start_time, components_count, success=True)
+
+        except Exception as exc:
+            await log_telemetry(start_time, components_count, success=False, error_message=str(exc))
+
+            if "stream or streaming set to True" in str(exc):
+                raise HTTPException(status_code=400, detail=str(exc)) from exc
+            logger.exception("Error checking build status")
+            raise HTTPException(status_code=500, detail=str(exc)) from exc
+        return first_layer, vertices_to_run, graph
+
+    async def log_telemetry(
+        start_time: float, components_count: int, *, success: bool, error_message: str | None = None
+    ):
+        background_tasks.add_task(
+            telemetry_service.log_package_playground,
+            PlaygroundPayload(
+                playground_seconds=int(time.perf_counter() - start_time),
+                playground_component_count=components_count,
+                playground_success=success,
+                playground_error_message=str(error_message) if error_message else "",
+            ),
+        )
+
+    async def create_graph(fresh_session, flow_id_str: str) -> Graph:
+        if not data:
+            return await build_graph_from_db(flow_id=flow_id, session=fresh_session, chat_service=chat_service)
+
+        result = await fresh_session.exec(select(Flow.name).where(Flow.id == flow_id))
+        flow_name = result.first()
+
+        return await build_graph_from_data(
+            flow_id=flow_id_str,
+            payload=data.model_dump(),
+            user_id=str(current_user.id),
+            flow_name=flow_name,
+        )
+
+    def sort_vertices(graph: Graph) -> list[str]:
+        try:
+            return graph.sort_vertices(stop_component_id, start_component_id)
+        except Exception:  # noqa: BLE001
+            logger.exception("Error sorting vertices")
+            return graph.sort_vertices()
+
+    async def _build_vertex(vertex_id: str, graph: Graph, event_manager: EventManager) -> VertexBuildResponse:
+        flow_id_str = str(flow_id)
+        next_runnable_vertices = []
+        top_level_vertices = []
+        start_time = time.perf_counter()
+        error_message = None
+        try:
+            vertex = graph.get_vertex(vertex_id)
+            try:
+                lock = chat_service.async_cache_locks[flow_id_str]
+                vertex_build_result = await graph.build_vertex(
+                    vertex_id=vertex_id,
+                    user_id=str(current_user.id),
+                    inputs_dict=inputs.model_dump() if inputs else {},
+                    files=files,
+                    get_cache=chat_service.get_cache,
+                    set_cache=chat_service.set_cache,
+                    event_manager=event_manager,
+                )
+                result_dict = vertex_build_result.result_dict
+                params = vertex_build_result.params
+                valid = vertex_build_result.valid
+                artifacts = vertex_build_result.artifacts
+                next_runnable_vertices = await graph.get_next_runnable_vertices(lock, vertex=vertex, cache=False)
+                top_level_vertices = graph.get_top_level_vertices(next_runnable_vertices)
+
+                result_data_response = ResultDataResponse.model_validate(result_dict, from_attributes=True)
+            except Exception as exc:  # noqa: BLE001
+                if isinstance(exc, ComponentBuildError):
+                    params = exc.message
+                    tb = exc.formatted_traceback
+                else:
+                    tb = traceback.format_exc()
+                    logger.exception("Error building Component")
+                    params = format_exception_message(exc)
+                message = {"errorMessage": params, "stackTrace": tb}
+                valid = False
+                error_message = params
+                output_label = vertex.outputs[0]["name"] if vertex.outputs else "output"
+                outputs = {output_label: OutputValue(message=message, type="error")}
+                result_data_response = ResultDataResponse(results={}, outputs=outputs)
+                artifacts = {}
+                background_tasks.add_task(graph.end_all_traces, error=exc)
+
+            result_data_response.message = artifacts
+
+            # Log the vertex build
+            if not vertex.will_stream and log_builds:
+                background_tasks.add_task(
+                    log_vertex_build,
+                    flow_id=flow_id_str,
+                    vertex_id=vertex_id,
+                    valid=valid,
+                    params=params,
+                    data=result_data_response,
+                    artifacts=artifacts,
+                )
+            else:
+                await chat_service.set_cache(flow_id_str, graph)
+
+            timedelta = time.perf_counter() - start_time
+            duration = format_elapsed_time(timedelta)
+            result_data_response.duration = duration
+            result_data_response.timedelta = timedelta
+            vertex.add_build_time(timedelta)
+            inactivated_vertices = list(graph.inactivated_vertices)
+            graph.reset_inactivated_vertices()
+            graph.reset_activated_vertices()
+            # graph.stop_vertex tells us if the user asked
+            # to stop the build of the graph at a certain vertex
+            # if it is in next_vertices_ids, we need to remove other
+            # vertices from next_vertices_ids
+            if graph.stop_vertex and graph.stop_vertex in next_runnable_vertices:
+                next_runnable_vertices = [graph.stop_vertex]
+
+            if not graph.run_manager.vertices_being_run and not next_runnable_vertices:
+                background_tasks.add_task(graph.end_all_traces)
+
+            build_response = VertexBuildResponse(
+                inactivated_vertices=list(set(inactivated_vertices)),
+                next_vertices_ids=list(set(next_runnable_vertices)),
+                top_level_vertices=list(set(top_level_vertices)),
+                valid=valid,
+                params=params,
+                id=vertex.id,
+                data=result_data_response,
+            )
+            background_tasks.add_task(
+                telemetry_service.log_package_component,
+                ComponentPayload(
+                    component_name=vertex_id.split("-")[0],
+                    component_seconds=int(time.perf_counter() - start_time),
+                    component_success=valid,
+                    component_error_message=error_message,
+                ),
+            )
+        except Exception as exc:
+            background_tasks.add_task(
+                telemetry_service.log_package_component,
+                ComponentPayload(
+                    component_name=vertex_id.split("-")[0],
+                    component_seconds=int(time.perf_counter() - start_time),
+                    component_success=False,
+                    component_error_message=str(exc),
+                ),
+            )
+            logger.exception("Error building Component")
+            message = parse_exception(exc)
+            raise HTTPException(status_code=500, detail=message) from exc
+
+        return build_response
+
+    async def build_vertices(
+        vertex_id: str,
+        graph: Graph,
+        event_manager: EventManager,
+    ) -> None:
+        """Build vertices and handle their events.
+
+        Args:
+            vertex_id: The ID of the vertex to build
+            graph: The graph instance
+            event_manager: Manager for handling events
+        """
+        try:
+            vertex_build_response: VertexBuildResponse = await _build_vertex(vertex_id, graph, event_manager)
+        except asyncio.CancelledError as exc:
+            logger.exception(exc)
+            raise
+
+        # send built event or error event
+        try:
+            vertex_build_response_json = vertex_build_response.model_dump_json()
+            build_data = json.loads(vertex_build_response_json)
+        except Exception as exc:
+            msg = f"Error serializing vertex build response: {exc}"
+            raise ValueError(msg) from exc
+
+        event_manager.on_end_vertex(data={"build_data": build_data})
+
+        if vertex_build_response.valid and vertex_build_response.next_vertices_ids:
+            tasks = []
+            for next_vertex_id in vertex_build_response.next_vertices_ids:
+                task = asyncio.create_task(
+                    build_vertices(
+                        next_vertex_id,
+                        graph,
+                        event_manager,
+                    )
+                )
+                tasks.append(task)
+            await asyncio.gather(*tasks)
+
+    try:
+        ids, vertices_to_run, graph = await build_graph_and_get_order()
+    except Exception as e:
+        error_message = ErrorMessage(
+            flow_id=flow_id,
+            exception=e,
+        )
+        event_manager.on_error(data=error_message.data)
+        raise
+
+    event_manager.on_vertices_sorted(data={"ids": ids, "to_run": vertices_to_run})
+
+    tasks = []
+    for vertex_id in ids:
+        task = asyncio.create_task(build_vertices(vertex_id, graph, event_manager))
+        tasks.append(task)
+    try:
+        await asyncio.gather(*tasks)
+    except asyncio.CancelledError:
+        background_tasks.add_task(graph.end_all_traces)
+        raise
+    except Exception as e:
+        logger.error(f"Error building vertices: {e}")
+        custom_component = graph.get_vertex(vertex_id).custom_component
+        trace_name = getattr(custom_component, "trace_name", None)
+        error_message = ErrorMessage(
+            flow_id=flow_id,
+            exception=e,
+            session_id=graph.session_id,
+            trace_name=trace_name,
+        )
+        event_manager.on_error(data=error_message.data)
+        raise
+    event_manager.on_end(data={})
+    await event_manager.queue.put((None, None, time.time()))

src/backend/base/langflow/api/disconnect.py

@@ -0,0 +1,31 @@
+import asyncio
+import typing
+
+from fastapi.responses import StreamingResponse
+from starlette.background import BackgroundTask
+from starlette.responses import ContentStream
+from starlette.types import Receive
+
+
+class DisconnectHandlerStreamingResponse(StreamingResponse):
+    def __init__(
+        self,
+        content: ContentStream,
+        status_code: int = 200,
+        headers: typing.Mapping[str, str] | None = None,
+        media_type: str | None = None,
+        background: BackgroundTask | None = None,
+        on_disconnect: typing.Callable | None = None,
+    ):
+        super().__init__(content, status_code, headers, media_type, background)
+        self.on_disconnect = on_disconnect
+
+    async def listen_for_disconnect(self, receive: Receive) -> None:
+        while True:
+            message = await receive()
+            if message["type"] == "http.disconnect":
+                if self.on_disconnect:
+                    coro = self.on_disconnect()
+                    if asyncio.iscoroutine(coro):
+                        await coro
+                break

src/backend/base/langflow/api/limited_background_tasks.py

@@ -0,0 +1,29 @@
+from fastapi import BackgroundTasks
+
+from langflow.graph.utils import log_vertex_build
+from langflow.services.deps import get_settings_service
+
+
+class LimitVertexBuildBackgroundTasks(BackgroundTasks):
+    """A subclass of FastAPI BackgroundTasks that limits the number of tasks added per vertex_id.
+
+    If more than max_vertex_builds_per_vertex tasks are added for a given vertex_id,
+    the oldest task is removed so that only the most recent remain.
+    This only applies to log_vertex_build tasks.
+    """
+
+    def add_task(self, func, *args, **kwargs):
+        # Only apply limiting logic to log_vertex_build tasks
+        if func == log_vertex_build:
+            vertex_id = kwargs.get("vertex_id")
+            if vertex_id is not None:
+                # Filter tasks that are log_vertex_build calls with the same vertex_id
+                relevant_tasks = [
+                    t for t in self.tasks if t.func == log_vertex_build and t.kwargs.get("vertex_id") == vertex_id
+                ]
+                if len(relevant_tasks) >= get_settings_service().settings.max_vertex_builds_per_vertex:
+                    # Remove the oldest task for this vertex_id
+                    oldest_task = relevant_tasks[0]
+                    self.tasks.remove(oldest_task)
+
+        super().add_task(func, *args, **kwargs)

src/backend/base/langflow/api/utils.py

@@ -14,6 +14,7 @@ from langflow.graph.graph.base import Graph
 from langflow.services.auth.utils import get_current_active_user
 from langflow.services.database.models import User
 from langflow.services.database.models.flow import Flow
+from langflow.services.database.models.message import MessageTable
 from langflow.services.database.models.transactions.model import TransactionTable
 from langflow.services.database.models.vertex_builds.model import VertexBuildTable
 from langflow.services.deps import get_session, session_scope
@@ -281,16 +282,16 @@ def parse_value(value: Any, input_type: str) -> Any:
 
 async def cascade_delete_flow(session: AsyncSession, flow_id: uuid.UUID) -> None:
     try:
-        await session.exec(delete(TransactionTable).where(TransactionTable.flow_id == flow_id))
-        await session.exec(delete(VertexBuildTable).where(VertexBuildTable.flow_id == flow_id))
         # TODO: Verify if deleting messages is safe in terms of session id relevance
         # If we delete messages directly, rather than setting flow_id to null,
         # it might cause unexpected behaviors because the session id could still be
         # used elsewhere to search for these messages.
-        # await session.exec(delete(MessageTable).where(MessageTable.flow_id == flow_id))
+        await session.exec(delete(MessageTable).where(MessageTable.flow_id == flow_id))
+        await session.exec(delete(TransactionTable).where(TransactionTable.flow_id == flow_id))
+        await session.exec(delete(VertexBuildTable).where(VertexBuildTable.flow_id == flow_id))
         await session.exec(delete(Flow).where(Flow.id == flow_id))
     except Exception as e:
-        msg = f"Unable to cascade delete flow: ${flow_id}"
+        msg = f"Unable to cascade delete flow: {flow_id}"
         raise RuntimeError(msg, e) from e
 
 

src/backend/base/langflow/api/v1/chat.py

@@ -1,26 +1,23 @@
 from __future__ import annotations
 
-import asyncio
-import json
 import time
 import traceback
-import typing
 import uuid
 from typing import TYPE_CHECKING, Annotated
 
-from fastapi import APIRouter, BackgroundTasks, Body, HTTPException
+from fastapi import APIRouter, BackgroundTasks, Body, Depends, HTTPException
 from fastapi.responses import StreamingResponse
 from loguru import logger
-from sqlmodel import select
-from starlette.background import BackgroundTask
-from starlette.responses import ContentStream
-from starlette.types import Receive
 
+from langflow.api.build import (
+    get_flow_events_response,
+    start_flow_build,
+)
+from langflow.api.limited_background_tasks import LimitVertexBuildBackgroundTasks
 from langflow.api.utils import (
     CurrentActiveUser,
     DbSession,
     build_and_cache_graph_from_data,
-    build_graph_from_data,
     build_graph_from_db,
     format_elapsed_time,
     format_exception_message,
@@ -35,16 +32,21 @@ from langflow.api.v1.schemas import (
     VertexBuildResponse,
     VerticesOrderResponse,
 )
-from langflow.events.event_manager import EventManager, create_default_event_manager
 from langflow.exceptions.component import ComponentBuildError
 from langflow.graph.graph.base import Graph
 from langflow.graph.utils import log_vertex_build
-from langflow.schema.message import ErrorMessage
 from langflow.schema.schema import OutputValue
 from langflow.services.cache.utils import CacheMiss
 from langflow.services.chat.service import ChatService
 from langflow.services.database.models.flow.model import Flow
-from langflow.services.deps import get_chat_service, get_session, get_telemetry_service, session_scope
+from langflow.services.deps import (
+    get_chat_service,
+    get_queue_service,
+    get_session,
+    get_telemetry_service,
+    session_scope,
+)
+from langflow.services.job_queue.service import JobQueueService
 from langflow.services.telemetry.schema import ComponentPayload, PlaygroundPayload
 
 if TYPE_CHECKING:
@@ -53,22 +55,6 @@ if TYPE_CHECKING:
 router = APIRouter(tags=["Chat"])
 
 
-async def try_running_celery_task(vertex, user_id):
-    # Try running the task in celery
-    # and set the task_id to the local vertex
-    # if it fails, run the task locally
-    try:
-        from langflow.worker import build_vertex
-
-        task = build_vertex.delay(vertex)
-        vertex.task_id = task.id
-    except Exception:  # noqa: BLE001
-        logger.opt(exception=True).debug("Error running task in celery")
-        vertex.task_id = None
-        await vertex.build(user_id=user_id)
-    return vertex
-
-
 @router.post("/build/{flow_id}/vertices", deprecated=True)
 async def retrieve_vertices_order(
     *,
@@ -143,331 +129,52 @@ async def retrieve_vertices_order(
 @router.post("/build/{flow_id}/flow")
 async def build_flow(
     *,
-    background_tasks: BackgroundTasks,
     flow_id: uuid.UUID,
+    background_tasks: LimitVertexBuildBackgroundTasks,
     inputs: Annotated[InputValueRequest | None, Body(embed=True)] = None,
     data: Annotated[FlowDataRequest | None, Body(embed=True)] = None,
     files: list[str] | None = None,
     stop_component_id: str | None = None,
     start_component_id: str | None = None,
-    log_builds: bool | None = True,
+    log_builds: bool = True,
     current_user: CurrentActiveUser,
+    queue_service: Annotated[JobQueueService, Depends(get_queue_service)],
 ):
-    chat_service = get_chat_service()
-    telemetry_service = get_telemetry_service()
-    if not inputs:
-        inputs = InputValueRequest(session=str(flow_id))
+    """Build and process a flow, returning a job ID for event polling."""
+    # First verify the flow exists
+    async with session_scope() as session:
+        flow = await session.get(Flow, flow_id)
+        if not flow:
+            raise HTTPException(status_code=404, detail=f"Flow with id {flow_id} not found")
 
-    async def build_graph_and_get_order() -> tuple[list[str], list[str], Graph]:
-        start_time = time.perf_counter()
-        components_count = 0
-        graph = None
-        try:
-            flow_id_str = str(flow_id)
-            # Create a fresh session for database operations
-            async with session_scope() as fresh_session:
-                graph = await create_graph(fresh_session, flow_id_str)
-
-            graph.validate_stream()
-            first_layer = sort_vertices(graph)
-
-            if inputs is not None and hasattr(inputs, "session") and inputs.session is not None:
-                graph.session_id = inputs.session
-
-            for vertex_id in first_layer:
-                graph.run_manager.add_to_vertices_being_run(vertex_id)
-
-            # Now vertices is a list of lists
-            # We need to get the id of each vertex
-            # and return the same structure but only with the ids
-            components_count = len(graph.vertices)
-            vertices_to_run = list(graph.vertices_to_run.union(get_top_level_vertices(graph, graph.vertices_to_run)))
-
-            await chat_service.set_cache(flow_id_str, graph)
-            await log_telemetry(start_time, components_count, success=True)
-
-        except Exception as exc:
-            await log_telemetry(start_time, components_count, success=False, error_message=str(exc))
-
-            if "stream or streaming set to True" in str(exc):
-                raise HTTPException(status_code=400, detail=str(exc)) from exc
-            logger.exception("Error checking build status")
-            raise HTTPException(status_code=500, detail=str(exc)) from exc
-        return first_layer, vertices_to_run, graph
-
-    async def log_telemetry(
-        start_time: float, components_count: int, *, success: bool, error_message: str | None = None
-    ):
-        background_tasks.add_task(
-            telemetry_service.log_package_playground,
-            PlaygroundPayload(
-                playground_seconds=int(time.perf_counter() - start_time),
-                playground_component_count=components_count,
-                playground_success=success,
-                playground_error_message=str(error_message) if error_message else "",
-            ),
-        )
-
-    async def create_graph(fresh_session, flow_id_str: str) -> Graph:
-        if not data:
-            return await build_graph_from_db(flow_id=flow_id, session=fresh_session, chat_service=chat_service)
-
-        result = await fresh_session.exec(select(Flow.name).where(Flow.id == flow_id))
-        flow_name = result.first()
-
-        return await build_graph_from_data(
-            flow_id=flow_id_str,
-            payload=data.model_dump(),
-            user_id=str(current_user.id),
-            flow_name=flow_name,
-        )
-
-    def sort_vertices(graph: Graph) -> list[str]:
-        try:
-            return graph.sort_vertices(stop_component_id, start_component_id)
-        except Exception:  # noqa: BLE001
-            logger.exception("Error sorting vertices")
-            return graph.sort_vertices()
-
-    async def _build_vertex(vertex_id: str, graph: Graph, event_manager: EventManager) -> VertexBuildResponse:
-        flow_id_str = str(flow_id)
-        next_runnable_vertices = []
-        top_level_vertices = []
-        start_time = time.perf_counter()
-        error_message = None
-        try:
-            vertex = graph.get_vertex(vertex_id)
-            try:
-                lock = chat_service.async_cache_locks[flow_id_str]
-                vertex_build_result = await graph.build_vertex(
-                    vertex_id=vertex_id,
-                    user_id=str(current_user.id),
-                    inputs_dict=inputs.model_dump() if inputs else {},
-                    files=files,
-                    get_cache=chat_service.get_cache,
-                    set_cache=chat_service.set_cache,
-                    event_manager=event_manager,
-                )
-                result_dict = vertex_build_result.result_dict
-                params = vertex_build_result.params
-                valid = vertex_build_result.valid
-                artifacts = vertex_build_result.artifacts
-                next_runnable_vertices = await graph.get_next_runnable_vertices(lock, vertex=vertex, cache=False)
-                top_level_vertices = graph.get_top_level_vertices(next_runnable_vertices)
-
-                result_data_response = ResultDataResponse.model_validate(result_dict, from_attributes=True)
-            except Exception as exc:  # noqa: BLE001
-                if isinstance(exc, ComponentBuildError):
-                    params = exc.message
-                    tb = exc.formatted_traceback
-                else:
-                    tb = traceback.format_exc()
-                    logger.exception("Error building Component")
-                    params = format_exception_message(exc)
-                message = {"errorMessage": params, "stackTrace": tb}
-                valid = False
-                error_message = params
-                output_label = vertex.outputs[0]["name"] if vertex.outputs else "output"
-                outputs = {output_label: OutputValue(message=message, type="error")}
-                result_data_response = ResultDataResponse(results={}, outputs=outputs)
-                artifacts = {}
-                background_tasks.add_task(graph.end_all_traces, error=exc)
-
-            result_data_response.message = artifacts
-
-            # Log the vertex build
-            if not vertex.will_stream and log_builds:
-                background_tasks.add_task(
-                    log_vertex_build,
-                    flow_id=flow_id_str,
-                    vertex_id=vertex_id,
-                    valid=valid,
-                    params=params,
-                    data=result_data_response,
-                    artifacts=artifacts,
-                )
-            else:
-                await chat_service.set_cache(flow_id_str, graph)
-
-            timedelta = time.perf_counter() - start_time
-            duration = format_elapsed_time(timedelta)
-            result_data_response.duration = duration
-            result_data_response.timedelta = timedelta
-            vertex.add_build_time(timedelta)
-            inactivated_vertices = list(graph.inactivated_vertices)
-            graph.reset_inactivated_vertices()
-            graph.reset_activated_vertices()
-            # graph.stop_vertex tells us if the user asked
-            # to stop the build of the graph at a certain vertex
-            # if it is in next_vertices_ids, we need to remove other
-            # vertices from next_vertices_ids
-            if graph.stop_vertex and graph.stop_vertex in next_runnable_vertices:
-                next_runnable_vertices = [graph.stop_vertex]
-
-            if not graph.run_manager.vertices_being_run and not next_runnable_vertices:
-                background_tasks.add_task(graph.end_all_traces)
-
-            build_response = VertexBuildResponse(
-                inactivated_vertices=list(set(inactivated_vertices)),
-                next_vertices_ids=list(set(next_runnable_vertices)),
-                top_level_vertices=list(set(top_level_vertices)),
-                valid=valid,
-                params=params,
-                id=vertex.id,
-                data=result_data_response,
-            )
-            background_tasks.add_task(
-                telemetry_service.log_package_component,
-                ComponentPayload(
-                    component_name=vertex_id.split("-")[0],
-                    component_seconds=int(time.perf_counter() - start_time),
-                    component_success=valid,
-                    component_error_message=error_message,
-                ),
-            )
-        except Exception as exc:
-            background_tasks.add_task(
-                telemetry_service.log_package_component,
-                ComponentPayload(
-                    component_name=vertex_id.split("-")[0],
-                    component_seconds=int(time.perf_counter() - start_time),
-                    component_success=False,
-                    component_error_message=str(exc),
-                ),
-            )
-            logger.exception("Error building Component")
-            message = parse_exception(exc)
-            raise HTTPException(status_code=500, detail=message) from exc
-
-        return build_response
-
-    async def build_vertices(
-        vertex_id: str,
-        graph: Graph,
-        client_consumed_queue: asyncio.Queue,
-        event_manager: EventManager,
-    ) -> None:
-        build_task = asyncio.create_task(_build_vertex(vertex_id, graph, event_manager))
-        try:
-            await build_task
-            vertex_build_response: VertexBuildResponse = build_task.result()
-        except asyncio.CancelledError as exc:
-            logger.exception(exc)
-            build_task.cancel()
-            return
-
-        # send built event or error event
-        try:
-            vertex_build_response_json = vertex_build_response.model_dump_json()
-            build_data = json.loads(vertex_build_response_json)
-        except Exception as exc:
-            msg = f"Error serializing vertex build response: {exc}"
-            raise ValueError(msg) from exc
-        event_manager.on_end_vertex(data={"build_data": build_data})
-        await client_consumed_queue.get()
-        if vertex_build_response.valid and vertex_build_response.next_vertices_ids:
-            tasks = []
-            for next_vertex_id in vertex_build_response.next_vertices_ids:
-                task = asyncio.create_task(build_vertices(next_vertex_id, graph, client_consumed_queue, event_manager))
-                tasks.append(task)
-            try:
-                await asyncio.gather(*tasks)
-            except asyncio.CancelledError:
-                for task in tasks:
-                    task.cancel()
-                return
-
-    async def event_generator(event_manager: EventManager, client_consumed_queue: asyncio.Queue) -> None:
-        try:
-            ids, vertices_to_run, graph = await build_graph_and_get_order()
-        except Exception as e:
-            error_message = ErrorMessage(
-                flow_id=flow_id,
-                exception=e,
-            )
-            event_manager.on_error(data=error_message.data)
-            raise
-        event_manager.on_vertices_sorted(data={"ids": ids, "to_run": vertices_to_run})
-        await client_consumed_queue.get()
-        tasks = []
-        for vertex_id in ids:
-            task = asyncio.create_task(build_vertices(vertex_id, graph, client_consumed_queue, event_manager))
-            tasks.append(task)
-        try:
-            await asyncio.gather(*tasks)
-        except asyncio.CancelledError:
-            background_tasks.add_task(graph.end_all_traces)
-            for task in tasks:
-                task.cancel()
-            return
-        except Exception as e:
-            logger.error(f"Error building vertices: {e}")
-            custom_component = graph.get_vertex(vertex_id).custom_component
-            trace_name = getattr(custom_component, "trace_name", None)
-            error_message = ErrorMessage(
-                flow_id=flow_id,
-                exception=e,
-                session_id=graph.session_id,
-                trace_name=trace_name,
-            )
-            event_manager.on_error(data=error_message.data)
-            raise
-        event_manager.on_end(data={})
-        await event_manager.queue.put((None, None, time.time))
-
-    async def consume_and_yield(queue: asyncio.Queue, client_consumed_queue: asyncio.Queue) -> typing.AsyncGenerator:
-        while True:
-            event_id, value, put_time = await queue.get()
-            if value is None:
-                break
-            get_time = time.time()
-            yield value
-            get_time_yield = time.time()
-            client_consumed_queue.put_nowait(event_id)
-            logger.debug(
-                f"consumed event {event_id} "
-                f"(time in queue, {get_time - put_time:.4f}, "
-                f"client {get_time_yield - get_time:.4f})"
-            )
-
-    asyncio_queue: asyncio.Queue = asyncio.Queue()
-    asyncio_queue_client_consumed: asyncio.Queue = asyncio.Queue()
-    event_manager = create_default_event_manager(queue=asyncio_queue)
-    main_task = asyncio.create_task(event_generator(event_manager, asyncio_queue_client_consumed))
-
-    def on_disconnect() -> None:
-        logger.debug("Client disconnected, closing tasks")
-        main_task.cancel()
-
-    return DisconnectHandlerStreamingResponse(
-        consume_and_yield(asyncio_queue, asyncio_queue_client_consumed),
-        media_type="application/x-ndjson",
-        on_disconnect=on_disconnect,
+    job_id = await start_flow_build(
+        flow_id=flow_id,
+        background_tasks=background_tasks,
+        inputs=inputs,
+        data=data,
+        files=files,
+        stop_component_id=stop_component_id,
+        start_component_id=start_component_id,
+        log_builds=log_builds,
+        current_user=current_user,
+        queue_service=queue_service,
     )
+    return {"job_id": job_id}
 
 
-class DisconnectHandlerStreamingResponse(StreamingResponse):
-    def __init__(
-        self,
-        content: ContentStream,
-        status_code: int = 200,
-        headers: typing.Mapping[str, str] | None = None,
-        media_type: str | None = None,
-        background: BackgroundTask | None = None,
-        on_disconnect: typing.Callable | None = None,
-    ):
-        super().__init__(content, status_code, headers, media_type, background)
-        self.on_disconnect = on_disconnect
-
-    async def listen_for_disconnect(self, receive: Receive) -> None:
-        while True:
-            message = await receive()
-            if message["type"] == "http.disconnect":
-                if self.on_disconnect:
-                    coro = self.on_disconnect()
-                    if asyncio.iscoroutine(coro):
-                        await coro
-                break
+@router.get("/build/{job_id}/events")
+async def get_build_events(
+    job_id: str,
+    queue_service: Annotated[JobQueueService, Depends(get_queue_service)],
+    *,
+    stream: bool = True,
+):
+    """Get events for a specific build job."""
+    return await get_flow_events_response(
+        job_id=job_id,
+        queue_service=queue_service,
+        stream=stream,
+    )
 
 
 @router.post("/build/{flow_id}/vertices/{vertex_id}", deprecated=True)

src/backend/base/langflow/api/v1/endpoints.py

@@ -44,7 +44,7 @@ from langflow.services.database.models.flow import Flow
 from langflow.services.database.models.flow.model import FlowRead
 from langflow.services.database.models.flow.utils import get_all_webhook_components_in_flow
 from langflow.services.database.models.user.model import User, UserRead
-from langflow.services.deps import get_session_service, get_settings_service, get_task_service, get_telemetry_service
+from langflow.services.deps import get_session_service, get_settings_service, get_telemetry_service
 from langflow.services.settings.feature_flags import FEATURE_FLAGS
 from langflow.services.telemetry.schema import RunPayload
 from langflow.utils.version import get_version_info
@@ -599,29 +599,16 @@ async def process() -> None:
     )
 
 
-@router.get("/task/{task_id}")
-async def get_task_status(task_id: str) -> TaskStatusResponse:
-    task_service = get_task_service()
-    task = task_service.get_task(task_id)
-    result = None
-    if task is None:
-        raise HTTPException(status_code=404, detail="Task not found")
-    if task.ready():
-        result = task.result
-        # If result isinstance of Exception, can we get the traceback?
-        if isinstance(result, Exception):
-            logger.exception(task.traceback)
+@router.get("/task/{_task_id}", deprecated=True)
+async def get_task_status(_task_id: str) -> TaskStatusResponse:
+    """Get the status of a task by ID (Deprecated).
 
-        if isinstance(result, dict) and "result" in result:
-            result = result["result"]
-        elif hasattr(result, "result"):
-            result = result.result
-
-    if task.status == "FAILURE":
-        result = str(task.result)
-        logger.error(f"Task {task_id} failed: {task.traceback}")
-
-    return TaskStatusResponse(status=task.status, result=result)
+    This endpoint is deprecated and will be removed in a future version.
+    """
+    raise HTTPException(
+        status_code=status.HTTP_400_BAD_REQUEST,
+        detail="The /task endpoint is deprecated and will be removed in a future version. Please use /run instead.",
+    )
 
 
 @router.post(

src/backend/base/langflow/api/v1/mcp.py

@@ -3,7 +3,6 @@ import base64
 import json
 import logging
 import traceback
-from contextlib import suppress
 from contextvars import ContextVar
 from typing import Annotated
 from urllib.parse import quote, unquote, urlparse
@@ -266,8 +265,9 @@ async def handle_call_tool(
                     return collected_results
                 finally:
                     progress_task.cancel()
-                    with suppress(asyncio.CancelledError):
-                        await progress_task
+                    await asyncio.wait([progress_task])
+                    if not progress_task.cancelled() and (exc := progress_task.exception()) is not None:
+                        raise exc
             except Exception as e:
                 msg = f"Error in async session: {e}"
                 logger.exception(msg)
@@ -333,6 +333,7 @@ async def handle_sse(request: Request, current_user: Annotated[User, Depends(get
                 logger.info("Client disconnected from SSE connection")
             except asyncio.CancelledError:
                 logger.info("SSE connection was cancelled")
+                raise
             except Exception as e:
                 msg = f"Error in MCP: {e!s}"
                 logger.exception(msg)

src/backend/base/langflow/api/v1/monitor.py

@@ -35,6 +35,7 @@ async def get_vertex_builds(flow_id: Annotated[UUID, Query()], session: DbSessio
 async def delete_vertex_builds(flow_id: Annotated[UUID, Query()], session: DbSession) -> None:
     try:
         await delete_vertex_builds_by_flow_id(session, flow_id)
+        await session.commit()
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e)) from e
 

src/backend/base/langflow/api/v1/schemas.py

@@ -1,7 +1,7 @@
 from datetime import datetime, timezone
 from enum import Enum
 from pathlib import Path
-from typing import Any
+from typing import Any, Literal
 from uuid import UUID
 
 from pydantic import BaseModel, ConfigDict, Field, field_serializer, field_validator, model_serializer
@@ -376,3 +376,4 @@ class ConfigResponse(BaseModel):
     auto_saving_interval: int
     health_check_max_retries: int
     max_file_size_upload: int
+    event_delivery: Literal["polling", "streaming"]

src/backend/base/langflow/base/agents/agent.py

@@ -169,8 +169,9 @@ class LCAgentComponent(Component):
                 cast("SendMessageFunctionType", self.send_message),
             )
         except ExceptionWithMessageError as e:
-            msg_id = e.agent_message.id
-            await delete_message(id_=msg_id)
+            if hasattr(e, "agent_message") and hasattr(e.agent_message, "id"):
+                msg_id = e.agent_message.id
+                await delete_message(id_=msg_id)
             await self._send_message_event(e.agent_message, category="remove_message")
             logger.error(f"ExceptionWithMessageError: {e}")
             raise

src/backend/base/langflow/components/embeddings/huggingface_inference_api.py

@@ -73,7 +73,7 @@ class HuggingFaceInferenceAPIEmbeddingsComponent(LCEmbeddingsModel):
 
     def get_api_url(self) -> str:
         if "huggingface" in self.inference_endpoint.lower():
-            return f"{self.inference_endpoint}{self.model_name}"
+            return f"{self.inference_endpoint}"
         return self.inference_endpoint
 
     @retry(stop=stop_after_attempt(3), wait=wait_fixed(2))

src/backend/base/langflow/components/firecrawl/firecrawl_crawl_api.py

@@ -26,6 +26,7 @@ class FirecrawlCrawlApi(Component):
             display_name="URL",
             required=True,
             info="The URL to scrape.",
+            tool_mode=True,
         ),
         IntInput(
             name="timeout",

src/backend/base/langflow/components/firecrawl/firecrawl_scrape_api.py

@@ -30,6 +30,7 @@ class FirecrawlScrapeApi(Component):
             display_name="URL",
             required=True,
             info="The URL to scrape.",
+            tool_mode=True,
         ),
         IntInput(
             name="timeout",

src/backend/base/langflow/components/helpers/batch_run.py

@@ -1,9 +1,18 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Any
+
+from loguru import logger
 
 from langflow.custom import Component
-from langflow.io import DataFrameInput, HandleInput, MultilineInput, Output, StrInput
+from langflow.io import (
+    BoolInput,
+    DataFrameInput,
+    HandleInput,
+    MessageTextInput,
+    MultilineInput,
+    Output,
+)
 from langflow.schema import DataFrame
 
 if TYPE_CHECKING:
@@ -14,8 +23,8 @@ class BatchRunComponent(Component):
     display_name = "Batch Run"
     description = (
         "Runs a language model over each row of a DataFrame's text column and returns a new "
-        "DataFrame with two columns: 'text_input' (the original text) and 'model_response' "
-        "containing the model's response."
+        "DataFrame with three columns: '**text_input**' (the original text),  "
+        "'**model_response**' (the model's response),and '**batch_index**' (the processing order)."
     )
     icon = "List"
     beta = True
@@ -26,6 +35,7 @@ class BatchRunComponent(Component):
             display_name="Language Model",
             info="Connect the 'Language Model' output from your LLM component here.",
             input_types=["LanguageModel"],
+            required=True,
         ),
         MultilineInput(
             name="system_message",
@@ -37,12 +47,23 @@ class BatchRunComponent(Component):
             name="df",
             display_name="DataFrame",
             info="The DataFrame whose column (specified by 'column_name') we'll treat as text messages.",
+            required=True,
         ),
-        StrInput(
+        MessageTextInput(
             name="column_name",
             display_name="Column Name",
             info="The name of the DataFrame column to treat as text messages. Default='text'.",
             value="text",
+            required=True,
+            advanced=True,
+        ),
+        BoolInput(
+            name="enable_metadata",
+            display_name="Enable Metadata",
+            info="If True, add metadata to the output DataFrame.",
+            value=True,
+            required=False,
+            advanced=True,
         ),
     ]
 
@@ -51,51 +72,123 @@ class BatchRunComponent(Component):
             display_name="Batch Results",
             name="batch_results",
             method="run_batch",
-            info="A DataFrame with two columns: 'text_input' and 'model_response'.",
+            info="A DataFrame with columns: 'text_input', 'model_response', 'batch_index', and 'metadata'.",
         ),
     ]
 
-    async def run_batch(self) -> DataFrame:
-        """For each row in df[column_name], combine that text with system_message, then invoke the model asynchronously.
+    def _create_base_row(self, text_input: str = "", model_response: str = "", batch_index: int = -1) -> dict[str, Any]:
+        """Create a base row with optional metadata."""
+        return {
+            "text_input": text_input,
+            "model_response": model_response,
+            "batch_index": batch_index,
+        }
 
-        Returns a new DataFrame of the same length, with columns 'text_input' and 'model_response'.
+    def _add_metadata(
+        self, row: dict[str, Any], *, success: bool = True, system_msg: str = "", error: str | None = None
+    ) -> None:
+        """Add metadata to a row if enabled."""
+        if not self.enable_metadata:
+            return
+
+        if success:
+            row["metadata"] = {
+                "has_system_message": bool(system_msg),
+                "input_length": len(row["text_input"]),
+                "response_length": len(row["model_response"]),
+                "processing_status": "success",
+            }
+        else:
+            row["metadata"] = {
+                "error": error,
+                "processing_status": "failed",
+            }
+
+    async def run_batch(self) -> DataFrame:
+        """Process each row in df[column_name] with the language model asynchronously.
+
+        Returns:
+            DataFrame: A new DataFrame containing:
+                - text_input: The original input text
+                - model_response: The model's response
+                - batch_index: The processing order
+                - metadata: Additional processing information
+
+        Raises:
+            ValueError: If the specified column is not found in the DataFrame
+            TypeError: If the model is not compatible or input types are wrong
         """
         model: Runnable = self.model
         system_msg = self.system_message or ""
         df: DataFrame = self.df
         col_name = self.column_name or "text"
 
+        # Validate inputs first
+        if not isinstance(df, DataFrame):
+            msg = f"Expected DataFrame input, got {type(df)}"
+            raise TypeError(msg)
+
         if col_name not in df.columns:
-            msg = f"Column '{col_name}' not found in the DataFrame."
+            msg = f"Column '{col_name}' not found in the DataFrame. Available columns: {', '.join(df.columns)}"
             raise ValueError(msg)
 
-        # Convert the specified column to a list of strings
-        user_texts = df[col_name].astype(str).tolist()
+        try:
+            # Convert the specified column to a list of strings
+            user_texts = df[col_name].astype(str).tolist()
+            total_rows = len(user_texts)
 
-        # Prepare the batch of conversations
-        conversations = [
-            [{"role": "system", "content": system_msg}, {"role": "user", "content": text}]
-            if system_msg
-            else [{"role": "user", "content": text}]
-            for text in user_texts
-        ]
-        model = model.with_config(
-            {
-                "run_name": self.display_name,
-                "project_name": self.get_project_name(),
-                "callbacks": self.get_langchain_callbacks(),
-            }
-        )
+            logger.info(f"Processing {total_rows} rows with batch run")
 
-        responses = await model.abatch(conversations)
+            # Prepare the batch of conversations
+            conversations = [
+                [{"role": "system", "content": system_msg}, {"role": "user", "content": text}]
+                if system_msg
+                else [{"role": "user", "content": text}]
+                for text in user_texts
+            ]
 
-        # Build the final data, each row has 'text_input' + 'model_response'
-        rows = []
-        for original_text, response in zip(user_texts, responses, strict=False):
-            resp_text = response.content if hasattr(response, "content") else str(response)
+            # Configure the model with project info and callbacks
+            model = model.with_config(
+                {
+                    "run_name": self.display_name,
+                    "project_name": self.get_project_name(),
+                    "callbacks": self.get_langchain_callbacks(),
+                }
+            )
 
-            row = {"text_input": original_text, "model_response": resp_text}
-            rows.append(row)
+            # Process batches and track progress
+            responses_with_idx = [
+                (idx, response)
+                for idx, response in zip(
+                    range(len(conversations)), await model.abatch(list(conversations)), strict=True
+                )
+            ]
 
-        # Convert to a new DataFrame
-        return DataFrame(rows)  # Langflow DataFrame from a list of dicts
+            # Sort by index to maintain order
+            responses_with_idx.sort(key=lambda x: x[0])
+
+            # Build the final data with enhanced metadata
+            rows: list[dict[str, Any]] = []
+            for idx, response in responses_with_idx:
+                resp_text = response.content if hasattr(response, "content") else str(response)
+                row = self._create_base_row(
+                    text_input=user_texts[idx],
+                    model_response=resp_text,
+                    batch_index=idx,
+                )
+                self._add_metadata(row, success=True, system_msg=system_msg)
+                rows.append(row)
+
+                # Log progress
+                if (idx + 1) % max(1, total_rows // 10) == 0:
+                    logger.info(f"Processed {idx + 1}/{total_rows} rows")
+
+            logger.info("Batch processing completed successfully")
+            return DataFrame(rows)
+
+        except (KeyError, AttributeError) as e:
+            # Handle data structure and attribute access errors
+            logger.error(f"Data processing error: {e!s}")
+            error_row = self._create_base_row()
+            self._add_metadata(error_row, success=False, error=str(e))
+            return DataFrame([error_row])

src/backend/base/langflow/components/helpers/store_message.py

@@ -61,10 +61,10 @@ class MessageStoreComponent(Component):
             self.memory.session_id = message.session_id
             lc_message = message.to_lc_message()
             await self.memory.aadd_messages([lc_message])
-            stored_message = await self.memory.aget_messages()
-            stored_message = [Message.from_lc_message(m) for m in stored_message]
+            stored_messages = await self.memory.aget_messages()
+            stored_messages = [Message.from_lc_message(m) for m in stored_messages]
             if message.sender:
-                stored_message = [m for m in stored_message if m.sender == message.sender]
+                stored_messages = [m for m in stored_messages if m.sender == message.sender]
         else:
             await astore_message(message, flow_id=self.graph.flow_id)
             stored_messages = await aget_messages(

src/backend/base/langflow/components/olivya/__init__.py

@@ -0,0 +1,3 @@
+from .olivya import OlivyaComponent
+
+__all__ = ["OlivyaComponent"]

src/backend/base/langflow/components/olivya/olivya.py

@@ -0,0 +1,116 @@
+import json
+
+import httpx
+from loguru import logger
+
+from langflow.custom import Component
+from langflow.io import MessageTextInput, Output
+from langflow.schema import Data
+
+
+class OlivyaComponent(Component):
+    display_name = "Place Call"
+    description = "A component to create an outbound call request from Olivya's platform."
+    documentation: str = "http://docs.langflow.org/components/olivya"
+    icon = "Olivya"
+    name = "OlivyaComponent"
+
+    inputs = [
+        MessageTextInput(
+            name="api_key",
+            display_name="API Key",
+            info="Your API key for authentication",
+            value="",
+            required=True,
+        ),
+        MessageTextInput(
+            name="from_number",
+            display_name="From Number",
+            info="The Agent's phone number",
+            value="",
+            required=True,
+        ),
+        MessageTextInput(
+            name="to_number",
+            display_name="To Number",
+            info="The recipient's phone number",
+            value="",
+            required=True,
+        ),
+        MessageTextInput(
+            name="first_message",
+            display_name="First Message",
+            info="The Agent's introductory message",
+            value="",
+            required=False,
+            tool_mode=True,
+        ),
+        MessageTextInput(
+            name="system_prompt",
+            display_name="System Prompt",
+            info="The system prompt to guide the interaction",
+            value="",
+            required=False,
+        ),
+        MessageTextInput(
+            name="conversation_history",
+            display_name="Conversation History",
+            info="The summary of the conversation",
+            value="",
+            required=False,
+            tool_mode=True,
+        ),
+    ]
+
+    outputs = [
+        Output(display_name="Output", name="output", method="build_output"),
+    ]
+
+    async def build_output(self) -> Data:
+        try:
+            payload = {
+                "variables": {
+                    "first_message": self.first_message.strip() if self.first_message else None,
+                    "system_prompt": self.system_prompt.strip() if self.system_prompt else None,
+                    "conversation_history": self.conversation_history.strip() if self.conversation_history else None,
+                },
+                "from_number": self.from_number.strip(),
+                "to_number": self.to_number.strip(),
+            }
+
+            headers = {
+                "Authorization": self.api_key.strip(),
+                "Content-Type": "application/json",
+            }
+
+            logger.info("Sending POST request with payload: %s", payload)
+
+            # Send the POST request with a timeout
+            async with httpx.AsyncClient() as client:
+                response = await client.post(
+                    "https://phone.olivya.io/create_zap_call",
+                    headers=headers,
+                    json=payload,
+                    timeout=10.0,
+                )
+                response.raise_for_status()
+
+                # Parse and return the successful response
+                response_data = response.json()
+                logger.info("Request successful: %s", response_data)
+
+        except httpx.HTTPStatusError as http_err:
+            logger.exception("HTTP error occurred")
+            response_data = {"error": f"HTTP error occurred: {http_err}", "response_text": response.text}
+        except httpx.RequestError as req_err:
+            logger.exception("Request failed")
+            response_data = {"error": f"Request failed: {req_err}"}
+        except json.JSONDecodeError as json_err:
+            logger.exception("Response parsing failed")
+            response_data = {"error": f"Response parsing failed: {json_err}", "raw_response": response.text}
+        except Exception as e:  # noqa: BLE001
+            logger.exception("An unexpected error occurred")
+            response_data = {"error": f"An unexpected error occurred: {e!s}"}
+
+        # Return the response as part of the output
+        return Data(value=response_data)

src/backend/base/langflow/components/processing/data_to_dataframe.py

@@ -0,0 +1,68 @@
+from langflow.custom import Component
+from langflow.io import DataInput, Output
+from langflow.schema import Data, DataFrame
+
+
+class DataToDataFrameComponent(Component):
+    display_name = "Data → DataFrame"
+    description = (
+        "Converts one or multiple Data objects into a DataFrame. "
+        "Each Data object corresponds to one row. Fields from `.data` become columns, "
+        "and the `.text` (if present) is placed in a 'text' column."
+    )
+    icon = "table"
+    name = "DataToDataFrame"
+
+    inputs = [
+        DataInput(
+            name="data_list",
+            display_name="Data or Data List",
+            info="One or multiple Data objects to transform into a DataFrame.",
+            is_list=True,
+        ),
+    ]
+
+    outputs = [
+        Output(
+            display_name="DataFrame",
+            name="dataframe",
+            method="build_dataframe",
+            info="A DataFrame built from each Data object's fields plus a 'text' column.",
+        ),
+    ]
+
+    def build_dataframe(self) -> DataFrame:
+        """Builds a DataFrame from Data objects by combining their fields.
+
+        For each Data object:
+          - Merge item.data (dictionary) as columns
+          - If item.text is present, add 'text' column
+
+        Returns a DataFrame with one row per Data object.
+        """
+        data_input = self.data_list
+
+        # If user passed a single Data, it might come in as a single object rather than a list
+        if not isinstance(data_input, list):
+            data_input = [data_input]
+
+        rows = []
+        for item in data_input:
+            if not isinstance(item, Data):
+                msg = f"Expected Data objects, got {type(item)} instead."
+                raise TypeError(msg)
+
+            # Start with a copy of item.data or an empty dict
+            row_dict = dict(item.data) if item.data else {}
+
+            # If the Data object has text, store it under 'text' col
+            text_val = item.get_text()
+            if text_val:
+                row_dict["text"] = text_val
+
+            rows.append(row_dict)
+
+        # Build a DataFrame from these row dictionaries
+        df_result = DataFrame(rows)
+        self.status = df_result  # store in self.status for logs
+        return df_result

src/backend/base/langflow/components/processing/parse_data.py

@@ -10,9 +10,18 @@ class ParseDataComponent(Component):
     description = "Convert Data objects into Messages using any {field_name} from input data."
     icon = "message-square"
     name = "ParseData"
+    metadata = {
+        "legacy_name": "Parse Data",
+    }
 
     inputs = [
-        DataInput(name="data", display_name="Data", info="The data to convert to text.", is_list=True, required=True),
+        DataInput(
+            name="data",
+            display_name="Data",
+            info="The data to convert to text.",
+            is_list=True,
+            required=True,
+        ),
         MultilineInput(
             name="template",
             display_name="Template",

src/backend/base/langflow/components/processing/save_to_file.py

@@ -0,0 +1,172 @@
+import json
+from collections.abc import AsyncIterator, Iterator
+from pathlib import Path
+
+import pandas as pd
+
+from langflow.custom import Component
+from langflow.io import (
+    DataFrameInput,
+    DataInput,
+    DropdownInput,
+    MessageInput,
+    Output,
+    StrInput,
+)
+from langflow.schema import Data, DataFrame, Message
+
+
+class SaveToFileComponent(Component):
+    display_name = "Save to File"
+    description = "Save DataFrames, Data, or Messages to various file formats."
+    icon = "save"
+    name = "SaveToFile"
+
+    # File format options for different types
+    DATA_FORMAT_CHOICES = ["csv", "excel", "json", "markdown"]
+    MESSAGE_FORMAT_CHOICES = ["txt", "json", "markdown"]
+
+    inputs = [
+        DropdownInput(
+            name="input_type",
+            display_name="Input Type",
+            options=["DataFrame", "Data", "Message"],
+            info="Select the type of input to save.",
+            value="DataFrame",
+            real_time_refresh=True,
+        ),
+        DataFrameInput(
+            name="df",
+            display_name="DataFrame",
+            info="The DataFrame to save.",
+            dynamic=True,
+            show=True,
+        ),
+        DataInput(
+            name="data",
+            display_name="Data",
+            info="The Data object to save.",
+            dynamic=True,
+            show=False,
+        ),
+        MessageInput(
+            name="message",
+            display_name="Message",
+            info="The Message to save.",
+            dynamic=True,
+            show=False,
+        ),
+        DropdownInput(
+            name="file_format",
+            display_name="File Format",
+            options=DATA_FORMAT_CHOICES,
+            info="Select the file format to save the input.",
+            real_time_refresh=True,
+        ),
+        StrInput(
+            name="file_path",
+            display_name="File Path (including filename)",
+            info="The full file path (including filename and extension).",
+            value="./output",
+        ),
+    ]
+
+    outputs = [
+        Output(
+            name="confirmation",
+            display_name="Confirmation",
+            method="save_to_file",
+            info="Confirmation message after saving the file.",
+        ),
+    ]
+
+    def update_build_config(self, build_config, field_value, field_name=None):
+        # Hide/show dynamic fields based on the selected input type
+        if field_name == "input_type":
+            build_config["df"]["show"] = field_value == "DataFrame"
+            build_config["data"]["show"] = field_value == "Data"
+            build_config["message"]["show"] = field_value == "Message"
+
+            if field_value in ["DataFrame", "Data"]:
+                build_config["file_format"]["options"] = self.DATA_FORMAT_CHOICES
+            elif field_value == "Message":
+                build_config["file_format"]["options"] = self.MESSAGE_FORMAT_CHOICES
+
+        return build_config
+
+    def save_to_file(self) -> str:
+        input_type = self.input_type
+        file_format = self.file_format
+        file_path = Path(self.file_path).expanduser()
+
+        # Ensure the directory exists
+        if not file_path.parent.exists():
+            file_path.parent.mkdir(parents=True, exist_ok=True)
+
+        if input_type == "DataFrame":
+            dataframe = self.df
+            return self._save_dataframe(dataframe, file_path, file_format)
+        if input_type == "Data":
+            data = self.data
+            return self._save_data(data, file_path, file_format)
+        if input_type == "Message":
+            message = self.message
+            return self._save_message(message, file_path, file_format)
+
+        error_msg = f"Unsupported input type: {input_type}"
+        raise ValueError(error_msg)
+
+    def _save_dataframe(self, dataframe: DataFrame, path: Path, fmt: str) -> str:
+        if fmt == "csv":
+            dataframe.to_csv(path, index=False)
+        elif fmt == "excel":
+            dataframe.to_excel(path, index=False, engine="openpyxl")
+        elif fmt == "json":
+            dataframe.to_json(path, orient="records", indent=2)
+        elif fmt == "markdown":
+            path.write_text(dataframe.to_markdown(index=False), encoding="utf-8")
+        else:
+            error_msg = f"Unsupported DataFrame format: {fmt}"
+            raise ValueError(error_msg)
+
+        return f"DataFrame saved successfully as '{path}'"
+
+    def _save_data(self, data: Data, path: Path, fmt: str) -> str:
+        if fmt == "csv":
+            pd.DataFrame(data.data).to_csv(path, index=False)
+        elif fmt == "excel":
+            pd.DataFrame(data.data).to_excel(path, index=False, engine="openpyxl")
+        elif fmt == "json":
+            path.write_text(json.dumps(data.data, indent=2), encoding="utf-8")
+        elif fmt == "markdown":
+            path.write_text(pd.DataFrame(data.data).to_markdown(index=False), encoding="utf-8")
+        else:
+            error_msg = f"Unsupported Data format: {fmt}"
+            raise ValueError(error_msg)
+
+        return f"Data saved successfully as '{path}'"
+
+    def _save_message(self, message: Message, path: Path, fmt: str) -> str:
+        if message.text is None:
+            content = ""
+        elif isinstance(message.text, AsyncIterator):
+            # AsyncIterator needs to be handled differently
+            error_msg = "AsyncIterator not supported"
+            raise ValueError(error_msg)
+        elif isinstance(message.text, Iterator):
+            # Convert iterator to string
+            content = " ".join(str(item) for item in message.text)
+        else:
+            content = str(message.text)
+
+        if fmt == "txt":
+            path.write_text(content, encoding="utf-8")
+        elif fmt == "json":
+            path.write_text(json.dumps({"message": content}, indent=2), encoding="utf-8")
+        elif fmt == "markdown":
+            path.write_text(f"**Message:**\n\n{content}", encoding="utf-8")
+        else:
+            error_msg = f"Unsupported Message format: {fmt}"
+            raise ValueError(error_msg)
+
+        return f"Message saved successfully as '{path}'"

src/backend/base/langflow/components/vectorstores/astradb.py

@@ -1,8 +1,8 @@
-import os
 from collections import defaultdict
-from dataclasses import dataclass, field
+from dataclasses import asdict, dataclass, field
 
 from astrapy import AstraDBAdmin, DataAPIClient, Database
+from astrapy.info import CollectionDescriptor
 from langchain_astradb import AstraDBVectorStore, CollectionVectorServiceOptions
 
 from langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store
@@ -36,22 +36,24 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
             default_factory=lambda: {
                 "data": {
                     "node": {
-                        "description": "Create a new database in Astra DB.",
-                        "display_name": "Create New Database",
+                        "name": "create_database",
+                        "description": "",
+                        "display_name": "Create new database",
                         "field_order": ["new_database_name", "cloud_provider", "region"],
                         "template": {
                             "new_database_name": StrInput(
                                 name="new_database_name",
-                                display_name="New Database Name",
+                                display_name="Name",
                                 info="Name of the new database to create in Astra DB.",
                                 required=True,
                             ),
                             "cloud_provider": DropdownInput(
                                 name="cloud_provider",
-                                display_name="Cloud Provider",
+                                display_name="Cloud provider",
                                 info="Cloud provider for the new database.",
                                 options=["Amazon Web Services", "Google Cloud Platform", "Microsoft Azure"],
                                 required=True,
+                                real_time_refresh=True,
                             ),
                             "region": DropdownInput(
                                 name="region",
@@ -73,8 +75,9 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
             default_factory=lambda: {
                 "data": {
                     "node": {
-                        "description": "Create a new collection in Astra DB.",
-                        "display_name": "Create New Collection",
+                        "name": "create_collection",
+                        "description": "",
+                        "display_name": "Create new collection",
                         "field_order": [
                             "new_collection_name",
                             "embedding_generation_provider",
@@ -83,23 +86,31 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
                         "template": {
                             "new_collection_name": StrInput(
                                 name="new_collection_name",
-                                display_name="New Collection Name",
+                                display_name="Name",
                                 info="Name of the new collection to create in Astra DB.",
                                 required=True,
                             ),
                             "embedding_generation_provider": DropdownInput(
                                 name="embedding_generation_provider",
-                                display_name="Embedding Generation Provider",
+                                display_name="Embedding generation method",
                                 info="Provider to use for generating embeddings.",
-                                options=[],
+                                real_time_refresh=True,
                                 required=True,
+                                options=["Bring your own", "Nvidia"],
                             ),
                             "embedding_generation_model": DropdownInput(
                                 name="embedding_generation_model",
-                                display_name="Embedding Generation Model",
+                                display_name="Embedding model",
                                 info="Model to use for generating embeddings.",
-                                options=[],
                                 required=True,
+                                options=[],
+                            ),
+                            "dimension": IntInput(
+                                name="dimension",
+                                display_name="Dimensions (Required only for `Bring your own`)",
+                                info="Dimensions of the embeddings to generate.",
+                                required=False,
+                                value=1024,
                             ),
                         },
                     },
@@ -125,17 +136,18 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
             real_time_refresh=True,
         ),
         DropdownInput(
-            name="api_endpoint",
+            name="database_name",
             display_name="Database",
-            info="The Database / API Endpoint for the Astra DB instance.",
+            info="The Database name for the Astra DB instance.",
             required=True,
             refresh_button=True,
             real_time_refresh=True,
+            dialog_inputs=asdict(NewDatabaseInput()),
             combobox=True,
         ),
         StrInput(
-            name="d_api_endpoint",
-            display_name="Database API Endpoint",
+            name="api_endpoint",
+            display_name="Astra DB API Endpoint",
             info="The API Endpoint for the Astra DB instance. Supercedes database selection.",
             advanced=True,
         ),
@@ -146,8 +158,9 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
             required=True,
             refresh_button=True,
             real_time_refresh=True,
-            # dialog_inputs=asdict(NewCollectionInput()),
+            dialog_inputs=asdict(NewCollectionInput()),
             combobox=True,
+            advanced=True,
         ),
         StrInput(
             name="keyspace",
@@ -238,6 +251,7 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
 
     @classmethod
     def map_cloud_providers(cls):
+        # TODO: Programmatically fetch the regions for each cloud provider
         return {
             "Amazon Web Services": {
                 "id": "aws",
@@ -254,54 +268,87 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
         }
 
     @classmethod
-    def create_database_api(
+    def get_vectorize_providers(cls, token: str, environment: str | None = None, api_endpoint: str | None = None):
+        try:
+            # Get the admin object
+            admin = AstraDBAdmin(token=token, environment=environment)
+            db_admin = admin.get_database_admin(api_endpoint=api_endpoint)
+
+            # Get the list of embedding providers
+            embedding_providers = db_admin.find_embedding_providers().as_dict()
+
+            vectorize_providers_mapping = {}
+            # Map the provider display name to the provider key and models
+            for provider_key, provider_data in embedding_providers["embeddingProviders"].items():
+                # Get the provider display name and models
+                display_name = provider_data["displayName"]
+                models = [model["name"] for model in provider_data["models"]]
+
+                # Build our mapping
+                vectorize_providers_mapping[display_name] = [provider_key, models]
+
+            # Sort the resulting dictionary
+            return defaultdict(list, dict(sorted(vectorize_providers_mapping.items())))
+        except Exception as e:
+            msg = f"Error fetching vectorize providers: {e}"
+            raise ValueError(msg) from e
+
+    @classmethod
+    async def create_database_api(
         cls,
-        token: str,
         new_database_name: str,
         cloud_provider: str,
         region: str,
+        token: str,
+        environment: str | None = None,
+        keyspace: str | None = None,
     ):
-        client = DataAPIClient(token=token)
+        client = DataAPIClient(token=token, environment=environment)
 
         # Get the admin object
         admin_client = client.get_admin(token=token)
 
         # Call the create database function
-        return admin_client.create_database(
+        return await admin_client.async_create_database(
             name=new_database_name,
-            cloud_provider=cloud_provider,
+            cloud_provider=cls.map_cloud_providers()[cloud_provider]["id"],
             region=region,
+            keyspace=keyspace,
+            wait_until_active=False,
         )
 
     @classmethod
-    def create_collection_api(
+    async def create_collection_api(
         cls,
-        token: str,
-        database_name: str,
         new_collection_name: str,
+        token: str,
+        api_endpoint: str,
+        environment: str | None = None,
+        keyspace: str | None = None,
         dimension: int | None = None,
         embedding_generation_provider: str | None = None,
         embedding_generation_model: str | None = None,
     ):
+        # Create the data API client
         client = DataAPIClient(token=token)
-        api_endpoint = cls.get_api_endpoint_static(token=token, database_name=database_name)
 
         # Get the database object
-        database = client.get_database(api_endpoint=api_endpoint, token=token)
+        database = client.get_async_database(api_endpoint=api_endpoint, token=token)
 
         # Build vectorize options, if needed
         vectorize_options = None
         if not dimension:
             vectorize_options = CollectionVectorServiceOptions(
-                provider=embedding_generation_provider,
+                provider=cls.get_vectorize_providers(
+                    token=token, environment=environment, api_endpoint=api_endpoint
+                ).get(embedding_generation_provider, [None, []])[0],
                 model_name=embedding_generation_model,
-                authentication=None,
-                parameters=None,
             )
 
         # Create the collection
-        return database.create_collection(
+        return await database.create_collection(
             name=new_collection_name,
+            keyspace=keyspace,
             dimension=dimension,
             service=vectorize_options,
         )
@@ -325,16 +372,28 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
         db_info_dict = {}
         for db in db_list:
             try:
+                # Get the API endpoint for the database
                 api_endpoint = f"https://{db.info.id}-{db.info.region}.apps.astra{env_string}.datastax.com"
-                db_info_dict[db.info.name] = {
-                    "api_endpoint": api_endpoint,
-                    "collections": len(
+
+                # Get the number of collections
+                try:
+                    num_collections = len(
                         list(
                             client.get_database(
                                 api_endpoint=api_endpoint, token=token, keyspace=db.info.keyspace
                             ).list_collection_names(keyspace=db.info.keyspace)
                         )
-                    ),
+                    )
+                except Exception:  # noqa: BLE001
+                    num_collections = 0
+                    if db.status != "PENDING":
+                        continue
+
+                # Add the database to the dictionary
+                db_info_dict[db.info.name] = {
+                    "api_endpoint": api_endpoint,
+                    "collections": num_collections,
+                    "status": db.status if db.status != "ACTIVE" else None,
                 }
             except Exception:  # noqa: BLE001, S110
                 pass
@@ -364,15 +423,20 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
         if not database_name:
             return None
 
-        # Otherwise, get the URL from the database list
-        return cls.get_database_list_static(token=token, environment=environment).get(database_name).get("api_endpoint")
+        # Grab the database object
+        db = cls.get_database_list_static(token=token, environment=environment).get(database_name)
+        if not db:
+            return None
 
-    def get_api_endpoint(self, *, api_endpoint: str | None = None):
+        # Otherwise, get the URL from the database list
+        return db.get("api_endpoint")
+
+    def get_api_endpoint(self):
         return self.get_api_endpoint_static(
             token=self.token,
             environment=self.environment,
-            api_endpoint=api_endpoint or self.d_api_endpoint,
-            database_name=self.api_endpoint,
+            api_endpoint=self.api_endpoint,
+            database_name=self.database_name,
         )
 
     def get_keyspace(self):
@@ -388,7 +452,7 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
             client = DataAPIClient(token=self.token, environment=self.environment)
 
             return client.get_database(
-                api_endpoint=self.get_api_endpoint(api_endpoint=api_endpoint),
+                api_endpoint=api_endpoint or self.get_api_endpoint(),
                 token=self.token,
                 keyspace=self.get_keyspace(),
             )
@@ -415,40 +479,15 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
 
             return None
 
-    def get_vectorize_providers(self):
-        try:
-            self.log("Dynamically updating list of Vectorize providers.")
-
-            # Get the admin object
-            admin = AstraDBAdmin(token=self.token)
-            db_admin = admin.get_database_admin(api_endpoint=self.get_api_endpoint())
-
-            # Get the list of embedding providers
-            embedding_providers = db_admin.find_embedding_providers().as_dict()
-
-            vectorize_providers_mapping = {}
-            # Map the provider display name to the provider key and models
-            for provider_key, provider_data in embedding_providers["embeddingProviders"].items():
-                display_name = provider_data["displayName"]
-                models = [model["name"] for model in provider_data["models"]]
-
-                # TODO: https://astra.datastax.com/api/v2/graphql
-                vectorize_providers_mapping[display_name] = [provider_key, models]
-
-            # Sort the resulting dictionary
-            return defaultdict(list, dict(sorted(vectorize_providers_mapping.items())))
-        except Exception as e:  # noqa: BLE001
-            self.log(f"Error fetching Vectorize providers: {e}")
-
-            return {}
-
     def _initialize_database_options(self):
         try:
             return [
                 {
                     "name": name,
+                    "status": info["status"],
                     "collections": info["collections"],
                     "api_endpoint": info["api_endpoint"],
+                    "icon": "data",
                 }
                 for name, info in self.get_database_list().items()
             ]
@@ -456,7 +495,35 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
             msg = f"Error fetching database options: {e}"
             raise ValueError(msg) from e
 
+    @classmethod
+    def get_provider_icon(cls, collection: CollectionDescriptor | None = None, provider_name: str | None = None) -> str:
+        # Get the provider name from the collection
+        provider_name = provider_name or (
+            collection.options.vector.service.provider
+            if collection and collection.options and collection.options.vector and collection.options.vector.service
+            else None
+        )
+
+        # If there is no provider, use the vector store icon
+        if not provider_name or provider_name == "bring your own":
+            return "vectorstores"
+
+        # Special case for certain models
+        # TODO: Add more icons
+        if provider_name == "nvidia":
+            return "NVIDIA"
+        if provider_name == "openai":
+            return "OpenAI"
+
+        # Title case on the provider for the icon if no special case
+        return provider_name.title()
+
     def _initialize_collection_options(self, api_endpoint: str | None = None):
+        # Nothing to generate if we don't have an API endpoint yet
+        api_endpoint = api_endpoint or self.get_api_endpoint()
+        if not api_endpoint:
+            return []
+
         # Retrieve the database object
         database = self.get_database_object(api_endpoint=api_endpoint)
 
@@ -471,7 +538,7 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
                 "provider": (
                     col.options.vector.service.provider if col.options.vector and col.options.vector.service else None
                 ),
-                "icon": "",
+                "icon": self.get_provider_icon(collection=col),
                 "model": (
                     col.options.vector.service.model_name if col.options.vector and col.options.vector.service else None
                 ),
@@ -479,9 +546,53 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
             for col in collection_list
         ]
 
+    def reset_provider_options(self, build_config: dict):
+        # Get the list of vectorize providers
+        vectorize_providers = self.get_vectorize_providers(
+            token=self.token,
+            environment=self.environment,
+            api_endpoint=build_config["api_endpoint"]["value"],
+        )
+
+        # If the collection is set, allow user to see embedding options
+        build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
+            "embedding_generation_provider"
+        ]["options"] = ["Bring your own", "Nvidia", *[key for key in vectorize_providers if key != "Nvidia"]]
+
+        # For all not Bring your own or Nvidia providers, add metadata saying configure in Astra DB Portal
+        provider_options = build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
+            "embedding_generation_provider"
+        ]["options"]
+
+        # Go over each possible provider and add metadata to configure in Astra DB Portal
+        for provider in provider_options:
+            # Skip Bring your own and Nvidia, automatically configured
+            if provider in ["Bring your own", "Nvidia"]:
+                build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
+                    "embedding_generation_provider"
+                ]["options_metadata"].append({"icon": self.get_provider_icon(provider_name=provider.lower())})
+                continue
+
+            # Add metadata to configure in Astra DB Portal
+            build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
+                "embedding_generation_provider"
+            ]["options_metadata"].append({" ": "Configure in Astra DB Portal"})
+
+        # And allow the user to see the models based on a selected provider
+        embedding_provider = build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
+            "embedding_generation_provider"
+        ]["value"]
+
+        # Set the options for the embedding model based on the provider
+        build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
+            "embedding_generation_model"
+        ]["options"] = vectorize_providers.get(embedding_provider, [[], []])[1]
+
+        return build_config
+
     def reset_collection_list(self, build_config: dict):
         # Get the list of options we have based on the token provided
-        collection_options = self._initialize_collection_options()
+        collection_options = self._initialize_collection_options(api_endpoint=build_config["api_endpoint"]["value"])
 
         # If we retrieved options based on the token, show the dropdown
         build_config["collection_name"]["options"] = [col["name"] for col in collection_options]
@@ -490,7 +601,11 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
         ]
 
         # Reset the selected collection
-        build_config["collection_name"]["value"] = ""
+        if build_config["collection_name"]["value"] not in build_config["collection_name"]["options"]:
+            build_config["collection_name"]["value"] = ""
+
+        # If we have a database, collection name should not be advanced
+        build_config["collection_name"]["advanced"] = not build_config["database_name"]["value"]
 
         return build_config
 
@@ -499,84 +614,171 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
         database_options = self._initialize_database_options()
 
         # If we retrieved options based on the token, show the dropdown
-        build_config["api_endpoint"]["options"] = [db["name"] for db in database_options]
-        build_config["api_endpoint"]["options_metadata"] = [
+        build_config["database_name"]["options"] = [db["name"] for db in database_options]
+        build_config["database_name"]["options_metadata"] = [
             {k: v for k, v in db.items() if k not in ["name"]} for db in database_options
         ]
 
         # Reset the selected database
-        build_config["api_endpoint"]["value"] = ""
+        if build_config["database_name"]["value"] not in build_config["database_name"]["options"]:
+            build_config["database_name"]["value"] = ""
+            build_config["api_endpoint"]["value"] = ""
+            build_config["collection_name"]["advanced"] = True
+
+        # If we have a token, database name should not be advanced
+        build_config["database_name"]["advanced"] = not build_config["token"]["value"]
 
         return build_config
 
     def reset_build_config(self, build_config: dict):
         # Reset the list of databases we have based on the token provided
-        build_config["api_endpoint"]["options"] = []
-        build_config["api_endpoint"]["options_metadata"] = []
+        build_config["database_name"]["options"] = []
+        build_config["database_name"]["options_metadata"] = []
+        build_config["database_name"]["value"] = ""
+        build_config["database_name"]["advanced"] = True
         build_config["api_endpoint"]["value"] = ""
-        build_config["api_endpoint"]["name"] = "Database"
 
         # Reset the list of collections and metadata associated
         build_config["collection_name"]["options"] = []
         build_config["collection_name"]["options_metadata"] = []
         build_config["collection_name"]["value"] = ""
+        build_config["collection_name"]["advanced"] = True
 
         return build_config
 
-    def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):
-        # When the component first executes, this is the update refresh call
-        first_run = field_name == "collection_name" and not field_value and not build_config["api_endpoint"]["options"]
+    async def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):
+        # Callback for database creation
+        if field_name == "database_name" and isinstance(field_value, dict) and "new_database_name" in field_value:
+            try:
+                await self.create_database_api(
+                    new_database_name=field_value["new_database_name"],
+                    token=self.token,
+                    keyspace=self.get_keyspace(),
+                    environment=self.environment,
+                    cloud_provider=field_value["cloud_provider"],
+                    region=field_value["region"],
+                )
+            except Exception as e:
+                msg = f"Error creating database: {e}"
+                raise ValueError(msg) from e
 
-        # If the token has not been provided, simply return
+            # Add the new database to the list of options
+            build_config["database_name"]["options"] = build_config["database_name"]["options"] + [
+                field_value["new_database_name"]
+            ]
+            build_config["database_name"]["options_metadata"] = build_config["database_name"]["options_metadata"] + [
+                {"status": "PENDING"}
+            ]
+
+            return self.reset_collection_list(build_config)
+
+        # This is the callback required to update the list of regions for a cloud provider
+        if field_name == "database_name" and isinstance(field_value, dict) and "new_database_name" not in field_value:
+            cloud_provider = field_value["cloud_provider"]
+            build_config["database_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"]["region"][
+                "options"
+            ] = self.map_cloud_providers()[cloud_provider]["regions"]
+
+            return build_config
+
+        # Callback for the creation of collections
+        if field_name == "collection_name" and isinstance(field_value, dict) and "new_collection_name" in field_value:
+            try:
+                # Get the dimension if its a BYO provider
+                dimension = (
+                    field_value["dimension"]
+                    if field_value["embedding_generation_provider"] == "Bring your own"
+                    else None
+                )
+
+                # Create the collection
+                await self.create_collection_api(
+                    new_collection_name=field_value["new_collection_name"],
+                    token=self.token,
+                    api_endpoint=build_config["api_endpoint"]["value"],
+                    environment=self.environment,
+                    keyspace=self.get_keyspace(),
+                    dimension=dimension,
+                    embedding_generation_provider=field_value["embedding_generation_provider"],
+                    embedding_generation_model=field_value["embedding_generation_model"],
+                )
+            except Exception as e:
+                msg = f"Error creating collection: {e}"
+                raise ValueError(msg) from e
+
+            # Add the new collection to the list of options
+            build_config["collection_name"]["value"] = field_value["new_collection_name"]
+            build_config["collection_name"]["options"].append(field_value["new_collection_name"])
+
+            # Get the provider and model for the new collection
+            generation_provider = field_value["embedding_generation_provider"]
+            provider = generation_provider if generation_provider != "Bring your own" else None
+            generation_model = field_value["embedding_generation_model"]
+            model = generation_model if generation_model else None
+
+            # Add the new collection to the list of options
+            icon = "NVIDIA" if provider == "Nvidia" else "vectorstores"
+            build_config["collection_name"]["options_metadata"] = build_config["collection_name"][
+                "options_metadata"
+            ] + [{"records": 0, "provider": provider, "icon": icon, "model": model}]
+
+            return build_config
+
+        # Callback to update the model list based on the embedding provider
+        if (
+            field_name == "collection_name"
+            and isinstance(field_value, dict)
+            and "new_collection_name" not in field_value
+        ):
+            return self.reset_provider_options(build_config)
+
+        # When the component first executes, this is the update refresh call
+        first_run = field_name == "collection_name" and not field_value and not build_config["database_name"]["options"]
+
+        # If the token has not been provided, simply return the empty build config
         if not self.token:
             return self.reset_build_config(build_config)
 
         # If this is the first execution of the component, reset and build database list
         if first_run or field_name in ["token", "environment"]:
-            # Reset the build config to ensure we are starting fresh
-            build_config = self.reset_build_config(build_config)
-            build_config = self.reset_database_list(build_config)
-
-            # Get list of regions for a given cloud provider
-            """
-            cloud_provider = (
-                build_config["api_endpoint"]["dialog_inputs"]["fields"]["data"]["node"]["template"]["cloud_provider"][
-                    "value"
-                ]
-                or "Amazon Web Services"
-            )
-            build_config["api_endpoint"]["dialog_inputs"]["fields"]["data"]["node"]["template"]["region"][
-                "options"
-            ] = self.map_cloud_providers()[cloud_provider]["regions"]
-            """
-
-            return build_config
+            return self.reset_database_list(build_config)
 
         # Refresh the collection name options
-        if field_name == "api_endpoint":
+        if field_name == "database_name" and not isinstance(field_value, dict):
             # If missing, refresh the database options
-            if not build_config["api_endpoint"]["options"] or not field_value:
-                return self.update_build_config(build_config, field_value=self.token, field_name="token")
+            if field_value not in build_config["database_name"]["options"]:
+                build_config = await self.update_build_config(build_config, field_value=self.token, field_name="token")
+                build_config["database_name"]["value"] = ""
+            else:
+                # Find the position of the selected database to align with metadata
+                index_of_name = build_config["database_name"]["options"].index(field_value)
 
-            # Set the underlying api endpoint value of the database
-            if field_value in build_config["api_endpoint"]["options"]:
-                index_of_name = build_config["api_endpoint"]["options"].index(field_value)
-                build_config["d_api_endpoint"]["value"] = build_config["api_endpoint"]["options_metadata"][
+                # Initializing database condition
+                pending = build_config["database_name"]["options_metadata"][index_of_name]["status"] == "PENDING"
+                if pending:
+                    return self.update_build_config(build_config, field_value=self.token, field_name="token")
+
+                # Set the API endpoint based on the selected database
+                build_config["api_endpoint"]["value"] = build_config["database_name"]["options_metadata"][
                     index_of_name
                 ]["api_endpoint"]
-            else:
-                build_config["d_api_endpoint"]["value"] = ""
+
+                # Reset the provider options
+                build_config = self.reset_provider_options(build_config)
 
             # Reset the list of collections we have based on the token provided
             return self.reset_collection_list(build_config)
 
         # Hide embedding model option if opriona_metadata provider is not null
-        if field_name == "collection_name" and field_value:
+        if field_name == "collection_name" and not isinstance(field_value, dict):
             # Assume we will be autodetecting the collection:
             build_config["autodetect_collection"]["value"] = True
 
+            # Reload the collection list
+            build_config = self.reset_collection_list(build_config)
+
             # Set the options for collection name to be the field value if its a new collection
-            if field_value not in build_config["collection_name"]["options"]:
+            if field_value and field_value not in build_config["collection_name"]["options"]:
                 # Add the new collection to the list of options
                 build_config["collection_name"]["options"].append(field_value)
                 build_config["collection_name"]["options_metadata"].append(
@@ -598,36 +800,8 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
                 build_config["embedding_model"]["advanced"] = False
                 build_config["embedding_choice"]["value"] = "Embedding Model"
 
-        # For the final step, get the list of vectorize providers
-        """
-        vectorize_providers = self.get_vectorize_providers()
-        if not vectorize_providers:
             return build_config
 
-        # Allow the user to see the embedding provider options
-        provider_options = build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
-            "embedding_generation_provider"
-        ]["options"]
-        if not provider_options:
-            # If the collection is set, allow user to see embedding options
-            build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
-                "embedding_generation_provider"
-            ]["options"] = ["Bring your own", "Nvidia", *[key for key in vectorize_providers if key != "Nvidia"]]
-
-        # And allow the user to see the models based on a selected provider
-        model_options = build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
-            "embedding_generation_model"
-        ]["options"]
-        if not model_options:
-            embedding_provider = build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
-                "embedding_generation_provider"
-            ]["value"]
-
-            build_config["collection_name"]["dialog_inputs"]["fields"]["data"]["node"]["template"][
-                "embedding_generation_model"
-            ]["options"] = vectorize_providers.get(embedding_provider, [[], []])[1]
-        """
-
         return build_config
 
     @check_cached_vector_store
@@ -654,11 +828,11 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
         # Get Langflow version and platform information
         __version__ = get_version_info()["version"]
         langflow_prefix = ""
-        if os.getenv("AWS_EXECUTION_ENV") == "AWS_ECS_FARGATE":  # TODO: More precise way of detecting
-            langflow_prefix = "ds-"
+        # if os.getenv("AWS_EXECUTION_ENV") == "AWS_ECS_FARGATE":  # TODO: More precise way of detecting
+        #     langflow_prefix = "ds-"
 
         # Get the database object
-        database = self.get_database_object(api_endpoint=self.d_api_endpoint)
+        database = self.get_database_object()
         autodetect = self.collection_name in database.list_collection_names() and self.autodetect_collection
 
         # Bundle up the auto-detect parameters
@@ -714,7 +888,7 @@ class AstraDBVectorStoreComponent(LCVectorStoreComponent):
         if documents and self.deletion_field:
             self.log(f"Deleting documents where {self.deletion_field}")
             try:
-                database = self.get_database_object(api_endpoint=self.d_api_endpoint)
+                database = self.get_database_object()
                 collection = database.get_collection(self.collection_name, keyspace=database.keyspace)
                 delete_values = list({doc.metadata[self.deletion_field] for doc in documents})
                 self.log(f"Deleting documents where {self.deletion_field} matches {delete_values}.")

src/backend/base/langflow/custom/custom_component/component.py

@@ -981,9 +981,6 @@ class Component(CustomComponent):
         return {"repr": custom_repr, "raw": raw, "type": artifact_type}
 
     def _process_raw_result(self, result):
-        """Process the raw result of the component."""
-        if len(self.outputs) == 1:
-            return self.status or self.extract_data(result)
         return self.extract_data(result)
 
     def extract_data(self, result):

src/backend/base/langflow/events/event_manager.py

@@ -1,21 +1,26 @@
-import asyncio
+from __future__ import annotations
+
 import inspect
 import json
 import time
 import uuid
 from functools import partial
-from typing import Literal
+from typing import TYPE_CHECKING, Literal
 
 from fastapi.encoders import jsonable_encoder
 from loguru import logger
 from typing_extensions import Protocol
 
-from langflow.schema.log import LoggableType
 from langflow.schema.playground_events import create_event_by_type
 
+if TYPE_CHECKING:
+    import asyncio
+
+    from langflow.schema.log import LoggableType
+
 
 class EventCallback(Protocol):
-    def __call__(self, *, manager: "EventManager", event_type: str, data: LoggableType): ...
+    def __call__(self, *, manager: EventManager, event_type: str, data: LoggableType): ...
 
 
 class PartialEventCallback(Protocol):

src/backend/base/langflow/graph/graph/base.py

@@ -635,6 +635,15 @@ class Graph:
             raise ValueError(msg)
         return self._run_id
 
+    def set_tracing_session_id(self) -> None:
+        """Sets the ID of the current session.
+
+        Args:
+            session_id (str): The session ID.
+        """
+        if self.tracing_service:
+            self.tracing_service.set_session_id(self._session_id)
+
     def set_run_id(self, run_id: uuid.UUID | None = None) -> None:
         """Sets the ID of the current run.
 
@@ -647,6 +656,8 @@ class Graph:
         self._run_id = str(run_id)
         if self.tracing_service:
             self.tracing_service.set_run_id(run_id)
+        if self._session_id and self.tracing_service is not None:
+            self.tracing_service.set_session_id(self.session_id)
 
     def set_run_name(self) -> None:
         # Given a flow name, flow_id

src/backend/base/langflow/graph/utils.py

@@ -135,10 +135,12 @@ async def log_transaction(
             flow_id=flow_id if isinstance(flow_id, UUID) else UUID(flow_id),
         )
         async with session_getter(get_db_service()) as session:
-            inserted = await crud_log_transaction(session, transaction)
-            logger.debug(f"Logged transaction: {inserted.id}")
+            with session.no_autoflush:
+                inserted = await crud_log_transaction(session, transaction)
+                if inserted:
+                    logger.debug(f"Logged transaction: {inserted.id}")
     except Exception:  # noqa: BLE001
-        logger.exception("Error logging transaction")
+        logger.error("Error logging transaction")
 
 
 async def log_vertex_build(

src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json

@@ -8,16 +8,12 @@
             "dataType": "ChatInput",
             "id": "ChatInput-jFwUm",
             "name": "message",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-OcXkl",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -34,16 +30,12 @@
             "dataType": "Prompt",
             "id": "Prompt-3SM2g",
             "name": "prompt",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "system_message",
             "id": "OpenAIModel-OcXkl",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -60,16 +52,12 @@
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-OcXkl",
             "name": "text_output",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-gDYiJ",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -87,9 +75,7 @@
           "display_name": "Chat Input",
           "id": "ChatInput-jFwUm",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -120,9 +106,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -135,9 +119,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -156,9 +138,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -255,10 +235,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -272,9 +249,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -292,9 +267,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -329,9 +302,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -373,9 +344,7 @@
           "display_name": "Prompt",
           "id": "Prompt-3SM2g",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {
@@ -385,9 +354,7 @@
             "display_name": "Prompt",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "template"
-            ],
+            "field_order": ["template"],
             "frozen": false,
             "icon": "prompts",
             "legacy": false,
@@ -402,9 +369,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -453,9 +418,7 @@
                 "display_name": "Tool Placeholder",
                 "dynamic": false,
                 "info": "A placeholder input for tool mode.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "tool_placeholder",
@@ -570,9 +533,7 @@
         "data": {
           "id": "ChatOutput-gDYiJ",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -605,9 +566,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -620,9 +579,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -642,9 +599,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -682,9 +637,7 @@
                 "display_name": "Data Template",
                 "dynamic": false,
                 "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "data_template",
@@ -704,9 +657,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Message to be passed as output.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "input_value",
@@ -727,10 +678,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -746,9 +694,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -768,9 +714,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -806,9 +750,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -850,10 +792,7 @@
         "data": {
           "id": "OpenAIModel-OcXkl",
           "node": {
-            "base_classes": [
-              "LanguageModel",
-              "Message"
-            ],
+            "base_classes": ["LanguageModel", "Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -892,9 +831,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -903,14 +840,10 @@
                 "display_name": "Language Model",
                 "method": "build_model",
                 "name": "model_output",
-                "required_inputs": [
-                  "api_key"
-                ],
+                "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -923,10 +856,8 @@
                 "display_name": "OpenAI API Key",
                 "dynamic": false,
                 "info": "The OpenAI API Key to use for the OpenAI model.",
-                "input_types": [
-                  "Message"
-                ],
-                "load_from_db": false,
+                "input_types": ["Message"],
+                "load_from_db": true,
                 "name": "api_key",
                 "password": true,
                 "placeholder": "",
@@ -934,7 +865,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -960,9 +891,7 @@
                 "display_name": "Input",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1144,9 +1073,7 @@
                 "display_name": "System Message",
                 "dynamic": false,
                 "info": "System message to pass to the model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1243,7 +1170,5 @@
   "is_component": false,
   "last_tested_version": "1.0.19.post2",
   "name": "Basic Prompting",
-  "tags": [
-    "chatbots"
-  ]
-}
+  "tags": ["chatbots"]
+}

src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json

@@ -9,17 +9,12 @@
             "dataType": "ParseData",
             "id": "ParseData-4Sckw",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "references",
             "id": "Prompt-65R68",
-            "inputTypes": [
-              "Message",
-              "Text"
-            ],
+            "inputTypes": ["Message", "Text"],
             "type": "str"
           }
         },
@@ -37,17 +32,12 @@
             "dataType": "TextInput",
             "id": "TextInput-t88FI",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "instructions",
             "id": "Prompt-65R68",
-            "inputTypes": [
-              "Message",
-              "Text"
-            ],
+            "inputTypes": ["Message", "Text"],
             "type": "str"
           }
         },
@@ -64,16 +54,12 @@
             "dataType": "Prompt",
             "id": "Prompt-65R68",
             "name": "prompt",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-MyAsQ",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -90,16 +76,12 @@
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-MyAsQ",
             "name": "text_output",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-BE4YI",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -116,16 +98,12 @@
             "dataType": "URL",
             "id": "URL-EPEnt",
             "name": "data",
-            "output_types": [
-              "Data"
-            ]
+            "output_types": ["Data"]
           },
           "targetHandle": {
             "fieldName": "data",
             "id": "ParseData-4Sckw",
-            "inputTypes": [
-              "Data"
-            ],
+            "inputTypes": ["Data"],
             "type": "other"
           }
         },
@@ -143,9 +121,7 @@
           "display_name": "Parse Data",
           "id": "ParseData-4Sckw",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -153,16 +129,14 @@
             "display_name": "Parse Data",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "data",
-              "template",
-              "sep"
-            ],
+            "field_order": ["data", "template", "sep"],
             "frozen": false,
             "icon": "message-square",
             "legacy": false,
             "lf_version": "1.0.19.post2",
-            "metadata": {},
+            "metadata": {
+              "legacy_name": "Parse Data"
+            },
             "output_types": [],
             "outputs": [
               {
@@ -173,9 +147,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -186,9 +158,7 @@
                 "name": "data_list",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -211,16 +181,14 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n\n    inputs = [\n        DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\", is_list=True, required=True),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
+                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n    metadata = {\n        \"legacy_name\": \"Parse Data\",\n    }\n\n    inputs = [\n        DataInput(\n            name=\"data\",\n            display_name=\"Data\",\n            info=\"The data to convert to text.\",\n            is_list=True,\n            required=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
               },
               "data": {
                 "advanced": false,
                 "display_name": "Data",
                 "dynamic": false,
                 "info": "The data to convert to text.",
-                "input_types": [
-                  "Data"
-                ],
+                "input_types": ["Data"],
                 "list": true,
                 "name": "data",
                 "placeholder": "",
@@ -253,9 +221,7 @@
                 "display_name": "Template",
                 "dynamic": false,
                 "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -298,24 +264,17 @@
           "display_name": "Prompt",
           "id": "Prompt-65R68",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {
-              "template": [
-                "references",
-                "instructions"
-              ]
+              "template": ["references", "instructions"]
             },
             "description": "Create a prompt template with dynamic variables.",
             "display_name": "Prompt",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "template"
-            ],
+            "field_order": ["template"],
             "frozen": false,
             "icon": "prompts",
             "legacy": false,
@@ -331,9 +290,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -366,10 +323,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -390,10 +344,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -428,9 +379,7 @@
                 "display_name": "Tool Placeholder",
                 "dynamic": false,
                 "info": "A placeholder input for tool mode.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "tool_placeholder",
@@ -473,9 +422,7 @@
           "display_name": "Instructions",
           "id": "TextInput-t88FI",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -483,9 +430,7 @@
             "display_name": "Instructions",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "input_value"
-            ],
+            "field_order": ["input_value"],
             "frozen": false,
             "icon": "type",
             "legacy": false,
@@ -501,9 +446,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -534,9 +477,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Text to be passed as input.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -579,9 +520,7 @@
           "display_name": "Chat Output",
           "id": "ChatOutput-BE4YI",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -612,9 +551,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -627,9 +564,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -648,9 +583,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -686,9 +619,7 @@
                 "display_name": "Data Template",
                 "dynamic": false,
                 "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "data_template",
@@ -706,9 +637,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Message to be passed as output.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "input_value",
@@ -727,10 +656,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -744,9 +670,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -764,9 +688,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -801,9 +723,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -952,10 +872,7 @@
         "data": {
           "id": "OpenAIModel-MyAsQ",
           "node": {
-            "base_classes": [
-              "LanguageModel",
-              "Message"
-            ],
+            "base_classes": ["LanguageModel", "Message"],
             "beta": false,
             "category": "models",
             "conditional_paths": [],
@@ -994,9 +911,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1005,14 +920,10 @@
                 "display_name": "Language Model",
                 "method": "build_model",
                 "name": "model_output",
-                "required_inputs": [
-                  "api_key"
-                ],
+                "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1026,9 +937,7 @@
                 "display_name": "OpenAI API Key",
                 "dynamic": false,
                 "info": "The OpenAI API Key to use for the OpenAI model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "load_from_db": true,
                 "name": "api_key",
                 "password": true,
@@ -1037,7 +946,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -1063,9 +972,7 @@
                 "display_name": "Input",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1247,9 +1154,7 @@
                 "display_name": "System Message",
                 "dynamic": false,
                 "info": "System message to pass to the model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1334,11 +1239,7 @@
         "data": {
           "id": "URL-EPEnt",
           "node": {
-            "base_classes": [
-              "Data",
-              "DataFrame",
-              "Message"
-            ],
+            "base_classes": ["Data", "DataFrame", "Message"],
             "beta": false,
             "category": "data",
             "conditional_paths": [],
@@ -1347,10 +1248,7 @@
             "display_name": "URL",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "urls",
-              "format"
-            ],
+            "field_order": ["urls", "format"],
             "frozen": false,
             "icon": "layout-template",
             "key": "URL",
@@ -1367,9 +1265,7 @@
                 "name": "data",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1380,9 +1276,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1393,9 +1287,7 @@
                 "name": "dataframe",
                 "selected": "DataFrame",
                 "tool_mode": true,
-                "types": [
-                  "DataFrame"
-                ],
+                "types": ["DataFrame"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1430,10 +1322,7 @@
                 "dynamic": false,
                 "info": "Output Format. Use 'Text' to extract the text from the HTML or 'Raw HTML' for the raw HTML content.",
                 "name": "format",
-                "options": [
-                  "Text",
-                  "Raw HTML"
-                ],
+                "options": ["Text", "Raw HTML"],
                 "options_metadata": [],
                 "placeholder": "",
                 "required": false,
@@ -1450,9 +1339,7 @@
                 "display_name": "URLs",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": true,
                 "list_add_label": "Add URL",
                 "load_from_db": false,
@@ -1465,10 +1352,7 @@
                 "trace_as_input": true,
                 "trace_as_metadata": true,
                 "type": "str",
-                "value": [
-                  "https://langflow.org/",
-                  "https://docs.langflow.org/"
-                ]
+                "value": ["https://langflow.org/", "https://docs.langflow.org/"]
               }
             },
             "tool_mode": false
@@ -1504,8 +1388,5 @@
   "is_component": false,
   "last_tested_version": "1.0.19.post2",
   "name": "Blog Writer",
-  "tags": [
-    "chatbots",
-    "content-generation"
-  ]
-}
+  "tags": ["chatbots", "content-generation"]
+}

src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json

@@ -204,9 +204,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -490,9 +488,7 @@
                 "name": "messages",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -503,9 +499,7 @@
                 "name": "messages_text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -722,9 +716,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -950,9 +942,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1267,9 +1257,7 @@
                 "name": "data",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1280,9 +1268,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1293,9 +1279,7 @@
                 "name": "dataframe",
                 "selected": "DataFrame",
                 "tool_mode": true,
-                "types": [
-                  "DataFrame"
-                ],
+                "types": ["DataFrame"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1412,9 +1396,7 @@
                 "name": "data",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1425,9 +1407,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1438,9 +1418,7 @@
                 "name": "dataframe",
                 "selected": "DataFrame",
                 "tool_mode": true,
-                "types": [
-                  "DataFrame"
-                ],
+                "types": ["DataFrame"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1563,9 +1541,7 @@
                 "name": "data",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1576,9 +1552,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1589,9 +1563,7 @@
                 "name": "dataframe",
                 "selected": "DataFrame",
                 "tool_mode": true,
-                "types": [
-                  "DataFrame"
-                ],
+                "types": ["DataFrame"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1722,9 +1694,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1736,9 +1706,7 @@
                 "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1753,7 +1721,7 @@
                 "dynamic": false,
                 "info": "Your Anthropic API key.",
                 "input_types": ["Message"],
-                "load_from_db": false,
+                "load_from_db": true,
                 "name": "api_key",
                 "password": true,
                 "placeholder": "",
@@ -1762,7 +1730,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "ANTHROPIC_API_KEY"
               },
               "base_url": {
                 "_input_type": "MessageTextInput",

src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json

@@ -8,16 +8,12 @@
             "dataType": "File",
             "id": "File-GwJQZ",
             "name": "data",
-            "output_types": [
-              "Data"
-            ]
+            "output_types": ["Data"]
           },
           "targetHandle": {
             "fieldName": "data",
             "id": "ParseData-BbvKb",
-            "inputTypes": [
-              "Data"
-            ],
+            "inputTypes": ["Data"],
             "type": "other"
           }
         },
@@ -35,17 +31,12 @@
             "dataType": "ParseData",
             "id": "ParseData-BbvKb",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "Document",
             "id": "Prompt-yvZHT",
-            "inputTypes": [
-              "Message",
-              "Text"
-            ],
+            "inputTypes": ["Message", "Text"],
             "type": "str"
           }
         },
@@ -63,16 +54,12 @@
             "dataType": "ChatInput",
             "id": "ChatInput-li477",
             "name": "message",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-atkmo",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -90,16 +77,12 @@
             "dataType": "Prompt",
             "id": "Prompt-yvZHT",
             "name": "prompt",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "system_message",
             "id": "OpenAIModel-atkmo",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -117,16 +100,12 @@
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-atkmo",
             "name": "text_output",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-8pgwS",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -145,9 +124,7 @@
           "display_name": "Chat Input",
           "id": "ChatInput-li477",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -178,9 +155,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -193,9 +168,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -214,9 +187,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -313,10 +284,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -330,9 +298,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -350,9 +316,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -387,9 +351,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -431,9 +393,7 @@
           "display_name": "Chat Output",
           "id": "ChatOutput-8pgwS",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -467,9 +427,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -482,9 +440,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -504,9 +460,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -544,9 +498,7 @@
                 "display_name": "Data Template",
                 "dynamic": false,
                 "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "data_template",
@@ -566,9 +518,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Message to be passed as output.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "input_value",
@@ -589,10 +539,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -608,9 +555,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -630,9 +575,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -668,9 +611,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -714,9 +655,7 @@
           "display_name": "Parse Data",
           "id": "ParseData-BbvKb",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -724,16 +663,14 @@
             "display_name": "Parse Data",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "data",
-              "template",
-              "sep"
-            ],
+            "field_order": ["data", "template", "sep"],
             "frozen": false,
             "icon": "message-square",
             "legacy": false,
             "lf_version": "1.0.19.post2",
-            "metadata": {},
+            "metadata": {
+              "legacy_name": "Parse Data"
+            },
             "output_types": [],
             "outputs": [
               {
@@ -744,9 +681,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -757,9 +692,7 @@
                 "name": "data_list",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -782,16 +715,14 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n\n    inputs = [\n        DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\", is_list=True, required=True),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
+                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n    metadata = {\n        \"legacy_name\": \"Parse Data\",\n    }\n\n    inputs = [\n        DataInput(\n            name=\"data\",\n            display_name=\"Data\",\n            info=\"The data to convert to text.\",\n            is_list=True,\n            required=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
               },
               "data": {
                 "advanced": false,
                 "display_name": "Data",
                 "dynamic": false,
                 "info": "The data to convert to text.",
-                "input_types": [
-                  "Data"
-                ],
+                "input_types": ["Data"],
                 "list": true,
                 "name": "data",
                 "placeholder": "",
@@ -824,9 +755,7 @@
                 "display_name": "Template",
                 "dynamic": false,
                 "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -934,9 +863,7 @@
         "data": {
           "id": "File-GwJQZ",
           "node": {
-            "base_classes": [
-              "Data"
-            ],
+            "base_classes": ["Data"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -965,9 +892,7 @@
                 "required_inputs": [],
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1030,10 +955,7 @@
                 "display_name": "Server File Path",
                 "dynamic": false,
                 "info": "Data object with a 'file_path' property pointing to server file or a Message object with a path to the file. Supercedes 'Path' but supports same file types.",
-                "input_types": [
-                  "Data",
-                  "Message"
-                ],
+                "input_types": ["Data", "Message"],
                 "list": true,
                 "name": "file_path",
                 "placeholder": "",
@@ -1180,24 +1102,18 @@
           "display_name": "Prompt",
           "id": "Prompt-yvZHT",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {
-              "template": [
-                "Document"
-              ]
+              "template": ["Document"]
             },
             "description": "Create a prompt template with dynamic variables.",
             "display_name": "Prompt",
             "documentation": "",
             "edited": false,
             "error": null,
-            "field_order": [
-              "template"
-            ],
+            "field_order": ["template"],
             "frozen": false,
             "full_path": null,
             "icon": "prompts",
@@ -1218,9 +1134,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1234,10 +1148,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1290,9 +1201,7 @@
                 "display_name": "Tool Placeholder",
                 "dynamic": false,
                 "info": "A placeholder input for tool mode.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "tool_placeholder",
@@ -1334,10 +1243,7 @@
         "data": {
           "id": "OpenAIModel-atkmo",
           "node": {
-            "base_classes": [
-              "LanguageModel",
-              "Message"
-            ],
+            "base_classes": ["LanguageModel", "Message"],
             "beta": false,
             "category": "models",
             "conditional_paths": [],
@@ -1376,9 +1282,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1387,14 +1291,10 @@
                 "display_name": "Language Model",
                 "method": "build_model",
                 "name": "model_output",
-                "required_inputs": [
-                  "api_key"
-                ],
+                "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1408,9 +1308,7 @@
                 "display_name": "OpenAI API Key",
                 "dynamic": false,
                 "info": "The OpenAI API Key to use for the OpenAI model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "load_from_db": true,
                 "name": "api_key",
                 "password": true,
@@ -1419,7 +1317,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -1445,9 +1343,7 @@
                 "display_name": "Input",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1629,9 +1525,7 @@
                 "display_name": "System Message",
                 "dynamic": false,
                 "info": "System message to pass to the model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1727,9 +1621,5 @@
   "is_component": false,
   "last_tested_version": "1.0.19.post2",
   "name": "Document Q&A",
-  "tags": [
-    "rag",
-    "q-a",
-    "openai"
-  ]
-}
+  "tags": ["rag", "q-a", "openai"]
+}

src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json

@@ -9,16 +9,12 @@
             "dataType": "StructuredOutputComponent",
             "id": "StructuredOutputComponent-XYoUc",
             "name": "structured_output",
-            "output_types": [
-              "Data"
-            ]
+            "output_types": ["Data"]
           },
           "targetHandle": {
             "fieldName": "data",
             "id": "ParseData-HzweJ",
-            "inputTypes": [
-              "Data"
-            ],
+            "inputTypes": ["Data"],
             "type": "other"
           }
         },
@@ -37,16 +33,12 @@
             "dataType": "ParseData",
             "id": "ParseData-HzweJ",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-xQxLm",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -64,16 +56,12 @@
             "dataType": "ChatInput",
             "id": "ChatInput-rAWlE",
             "name": "message",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-cqeNw",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -91,16 +79,12 @@
             "dataType": "Prompt",
             "id": "Prompt-AzK6t",
             "name": "prompt",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "system_message",
             "id": "OpenAIModel-cqeNw",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -118,16 +102,12 @@
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-cqeNw",
             "name": "text_output",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "StructuredOutputComponent-XYoUc",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -145,16 +125,12 @@
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-cqeNw",
             "name": "model_output",
-            "output_types": [
-              "LanguageModel"
-            ]
+            "output_types": ["LanguageModel"]
           },
           "targetHandle": {
             "fieldName": "llm",
             "id": "StructuredOutputComponent-XYoUc",
-            "inputTypes": [
-              "LanguageModel"
-            ],
+            "inputTypes": ["LanguageModel"],
             "type": "other"
           }
         },
@@ -173,9 +149,7 @@
           "display_name": "Chat Input",
           "id": "ChatInput-rAWlE",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -209,9 +183,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -224,9 +196,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -246,9 +216,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -351,10 +319,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -370,9 +335,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -392,9 +355,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -430,9 +391,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -476,9 +435,7 @@
           "display_name": "Chat Output",
           "id": "ChatOutput-xQxLm",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -512,9 +469,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -527,9 +482,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -549,9 +502,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -589,9 +540,7 @@
                 "display_name": "Data Template",
                 "dynamic": false,
                 "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "data_template",
@@ -611,9 +560,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Message to be passed as output.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "input_value",
@@ -634,10 +581,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -653,9 +597,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -675,9 +617,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -713,9 +653,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -794,9 +732,7 @@
           "display_name": "Structured Output",
           "id": "StructuredOutputComponent-XYoUc",
           "node": {
-            "base_classes": [
-              "Data"
-            ],
+            "base_classes": ["Data"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -824,9 +760,7 @@
                 "method": "build_structured_output",
                 "name": "structured_output",
                 "selected": "Data",
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -857,9 +791,7 @@
                 "display_name": "Input message",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "input_value",
@@ -879,9 +811,7 @@
                 "display_name": "Language Model",
                 "dynamic": false,
                 "info": "The language model to use to generate the structured output.",
-                "input_types": [
-                  "LanguageModel"
-                ],
+                "input_types": ["LanguageModel"],
                 "list": false,
                 "name": "llm",
                 "placeholder": "",
@@ -1025,9 +955,7 @@
         "data": {
           "id": "ParseData-HzweJ",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -1035,16 +963,14 @@
             "display_name": "Parse Data",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "data",
-              "template",
-              "sep"
-            ],
+            "field_order": ["data", "template", "sep"],
             "frozen": false,
             "icon": "message-square",
             "legacy": false,
             "lf_version": "1.0.19.post2",
-            "metadata": {},
+            "metadata": {
+              "legacy_name": "Parse Data"
+            },
             "output_types": [],
             "outputs": [
               {
@@ -1055,9 +981,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1068,9 +992,7 @@
                 "name": "data_list",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1093,7 +1015,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n\n    inputs = [\n        DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\", is_list=True, required=True),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
+                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n    metadata = {\n        \"legacy_name\": \"Parse Data\",\n    }\n\n    inputs = [\n        DataInput(\n            name=\"data\",\n            display_name=\"Data\",\n            info=\"The data to convert to text.\",\n            is_list=True,\n            required=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
               },
               "data": {
                 "_input_type": "DataInput",
@@ -1101,9 +1023,7 @@
                 "display_name": "Data",
                 "dynamic": false,
                 "info": "The data to convert to text.",
-                "input_types": [
-                  "Data"
-                ],
+                "input_types": ["Data"],
                 "list": true,
                 "name": "data",
                 "placeholder": "",
@@ -1139,9 +1059,7 @@
                 "display_name": "Template",
                 "dynamic": false,
                 "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1186,9 +1104,7 @@
           "display_name": "Prompt",
           "id": "Prompt-AzK6t",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {
@@ -1198,9 +1114,7 @@
             "display_name": "Prompt",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "template"
-            ],
+            "field_order": ["template"],
             "frozen": false,
             "icon": "prompts",
             "legacy": false,
@@ -1216,9 +1130,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1267,9 +1179,7 @@
                 "display_name": "Tool Placeholder",
                 "dynamic": false,
                 "info": "A placeholder input for tool mode.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "tool_placeholder",
@@ -1311,10 +1221,7 @@
         "data": {
           "id": "OpenAIModel-cqeNw",
           "node": {
-            "base_classes": [
-              "LanguageModel",
-              "Message"
-            ],
+            "base_classes": ["LanguageModel", "Message"],
             "beta": false,
             "category": "models",
             "conditional_paths": [],
@@ -1353,9 +1260,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1364,14 +1269,10 @@
                 "display_name": "Language Model",
                 "method": "build_model",
                 "name": "model_output",
-                "required_inputs": [
-                  "api_key"
-                ],
+                "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1385,9 +1286,7 @@
                 "display_name": "OpenAI API Key",
                 "dynamic": false,
                 "info": "The OpenAI API Key to use for the OpenAI model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "load_from_db": true,
                 "name": "api_key",
                 "password": true,
@@ -1396,7 +1295,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -1422,9 +1321,7 @@
                 "display_name": "Input",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1606,9 +1503,7 @@
                 "display_name": "System Message",
                 "dynamic": false,
                 "info": "System message to pass to the model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1704,7 +1599,5 @@
   "is_component": false,
   "last_tested_version": "1.0.19.post2",
   "name": "Image Sentiment Analysis",
-  "tags": [
-    "classification"
-  ]
-}
+  "tags": ["classification"]
+}

src/backend/base/langflow/initial_setup/starter_projects/LoopTemplate.json

@@ -9,16 +9,12 @@
             "dataType": "ArXivComponent",
             "id": "ArXivComponent-LChQN",
             "name": "papers",
-            "output_types": [
-              "Data"
-            ]
+            "output_types": ["Data"]
           },
           "targetHandle": {
             "fieldName": "data",
             "id": "LoopComponent-3vpc1",
-            "inputTypes": [
-              "Data"
-            ],
+            "inputTypes": ["Data"],
             "type": "other"
           }
         },
@@ -36,16 +32,12 @@
             "dataType": "LoopComponent",
             "id": "LoopComponent-3vpc1",
             "name": "item",
-            "output_types": [
-              "Data"
-            ]
+            "output_types": ["Data"]
           },
           "targetHandle": {
             "fieldName": "data",
             "id": "ParseData-Pf12J",
-            "inputTypes": [
-              "Data"
-            ],
+            "inputTypes": ["Data"],
             "type": "other"
           }
         },
@@ -63,16 +55,12 @@
             "dataType": "ParseData",
             "id": "ParseData-Pf12J",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "AnthropicModel-beO6B",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -90,16 +78,12 @@
             "dataType": "AnthropicModel",
             "id": "AnthropicModel-beO6B",
             "name": "text_output",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "message",
             "id": "MessagetoData-QRSBb",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -117,17 +101,13 @@
             "dataType": "MessagetoData",
             "id": "MessagetoData-QRSBb",
             "name": "data",
-            "output_types": [
-              "Data"
-            ]
+            "output_types": ["Data"]
           },
           "targetHandle": {
             "dataType": "LoopComponent",
             "id": "LoopComponent-3vpc1",
             "name": "item",
-            "output_types": [
-              "Data"
-            ]
+            "output_types": ["Data"]
           }
         },
         "id": "xy-edge__MessagetoData-QRSBb{œdataTypeœ:œMessagetoDataœ,œidœ:œMessagetoData-QRSBbœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-LoopComponent-3vpc1{œdataTypeœ:œLoopComponentœ,œidœ:œLoopComponent-3vpc1œ,œnameœ:œitemœ,œoutput_typesœ:[œDataœ]}",
@@ -144,16 +124,12 @@
             "dataType": "LoopComponent",
             "id": "LoopComponent-3vpc1",
             "name": "done",
-            "output_types": [
-              "Data"
-            ]
+            "output_types": ["Data"]
           },
           "targetHandle": {
             "fieldName": "data",
             "id": "ParseData-igEkj",
-            "inputTypes": [
-              "Data"
-            ],
+            "inputTypes": ["Data"],
             "type": "other"
           }
         },
@@ -171,16 +147,12 @@
             "dataType": "ParseData",
             "id": "ParseData-igEkj",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-UZgon",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -198,16 +170,12 @@
             "dataType": "ChatInput",
             "id": "ChatInput-m10vc",
             "name": "message",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "search_query",
             "id": "ArXivComponent-LChQN",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -223,9 +191,7 @@
         "data": {
           "id": "ArXivComponent-LChQN",
           "node": {
-            "base_classes": [
-              "Data"
-            ],
+            "base_classes": ["Data"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -233,11 +199,7 @@
             "display_name": "arXiv",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "search_query",
-              "search_type",
-              "max_results"
-            ],
+            "field_order": ["search_query", "search_type", "max_results"],
             "frozen": false,
             "icon": "arXiv",
             "legacy": false,
@@ -254,9 +216,7 @@
                 "name": "papers",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -305,9 +265,7 @@
                 "display_name": "Search Query",
                 "dynamic": false,
                 "info": "The search query for arXiv papers (e.g., 'quantum computing')",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -331,13 +289,7 @@
                 "dynamic": false,
                 "info": "The field to search in",
                 "name": "search_type",
-                "options": [
-                  "all",
-                  "title",
-                  "abstract",
-                  "author",
-                  "cat"
-                ],
+                "options": ["all", "title", "abstract", "author", "cat"],
                 "options_metadata": [],
                 "placeholder": "",
                 "required": false,
@@ -371,9 +323,7 @@
         "data": {
           "id": "LoopComponent-3vpc1",
           "node": {
-            "base_classes": [
-              "Data"
-            ],
+            "base_classes": ["Data"],
             "beta": false,
             "category": "logic",
             "conditional_paths": [],
@@ -382,9 +332,7 @@
             "display_name": "Loop",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "data"
-            ],
+            "field_order": ["data"],
             "frozen": false,
             "icon": "infinity",
             "key": "LoopComponent",
@@ -402,9 +350,7 @@
                 "name": "item",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -415,9 +361,7 @@
                 "name": "done",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -449,9 +393,7 @@
                 "display_name": "Data",
                 "dynamic": false,
                 "info": "The initial list of Data objects to iterate over.",
-                "input_types": [
-                  "Data"
-                ],
+                "input_types": ["Data"],
                 "list": false,
                 "list_add_label": "Add More",
                 "name": "data",
@@ -488,10 +430,7 @@
         "data": {
           "id": "ParseData-Pf12J",
           "node": {
-            "base_classes": [
-              "Data",
-              "Message"
-            ],
+            "base_classes": ["Data", "Message"],
             "beta": false,
             "category": "processing",
             "conditional_paths": [],
@@ -500,17 +439,15 @@
             "display_name": "Data to Message",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "data",
-              "template",
-              "sep"
-            ],
+            "field_order": ["data", "template", "sep"],
             "frozen": false,
             "icon": "message-square",
             "key": "ParseData",
             "legacy": false,
             "lf_version": "1.1.5",
-            "metadata": {},
+            "metadata": {
+              "legacy_name": "Parse Data"
+            },
             "minimized": false,
             "output_types": [],
             "outputs": [
@@ -522,9 +459,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -535,9 +470,7 @@
                 "name": "data_list",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -561,7 +494,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n\n    inputs = [\n        DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\", is_list=True, required=True),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
+                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n    metadata = {\n        \"legacy_name\": \"Parse Data\",\n    }\n\n    inputs = [\n        DataInput(\n            name=\"data\",\n            display_name=\"Data\",\n            info=\"The data to convert to text.\",\n            is_list=True,\n            required=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
               },
               "data": {
                 "_input_type": "DataInput",
@@ -569,9 +502,7 @@
                 "display_name": "Data",
                 "dynamic": false,
                 "info": "The data to convert to text.",
-                "input_types": [
-                  "Data"
-                ],
+                "input_types": ["Data"],
                 "list": true,
                 "list_add_label": "Add More",
                 "name": "data",
@@ -610,9 +541,7 @@
                 "display_name": "Template",
                 "dynamic": false,
                 "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -651,10 +580,7 @@
         "data": {
           "id": "AnthropicModel-beO6B",
           "node": {
-            "base_classes": [
-              "LanguageModel",
-              "Message"
-            ],
+            "base_classes": ["LanguageModel", "Message"],
             "beta": false,
             "category": "models",
             "conditional_paths": [],
@@ -693,9 +619,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -704,14 +628,10 @@
                 "display_name": "Language Model",
                 "method": "build_model",
                 "name": "model_output",
-                "required_inputs": [
-                  "api_key"
-                ],
+                "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -725,9 +645,7 @@
                 "display_name": "Anthropic API Key",
                 "dynamic": false,
                 "info": "Your Anthropic API key.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "load_from_db": true,
                 "name": "api_key",
                 "password": true,
@@ -737,7 +655,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "ANTHROPIC_API_KEY"
               },
               "base_url": {
                 "_input_type": "MessageTextInput",
@@ -745,9 +663,7 @@
                 "display_name": "Anthropic API URL",
                 "dynamic": false,
                 "info": "Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -787,9 +703,7 @@
                 "display_name": "Input",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -858,9 +772,7 @@
                 "display_name": "Prefill",
                 "dynamic": false,
                 "info": "Prefill text to guide the model's response.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -899,9 +811,7 @@
                 "display_name": "System Message",
                 "dynamic": false,
                 "info": "System message to pass to the model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -987,9 +897,7 @@
         "data": {
           "id": "MessagetoData-QRSBb",
           "node": {
-            "base_classes": [
-              "Data"
-            ],
+            "base_classes": ["Data"],
             "beta": true,
             "category": "processing",
             "conditional_paths": [],
@@ -998,9 +906,7 @@
             "display_name": "Message to Data",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "message"
-            ],
+            "field_order": ["message"],
             "frozen": false,
             "icon": "message-square-share",
             "key": "MessagetoData",
@@ -1018,9 +924,7 @@
                 "name": "data",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1052,9 +956,7 @@
                 "display_name": "Message",
                 "dynamic": false,
                 "info": "The Message object to convert to a Data object",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1092,10 +994,7 @@
         "data": {
           "id": "ParseData-igEkj",
           "node": {
-            "base_classes": [
-              "Data",
-              "Message"
-            ],
+            "base_classes": ["Data", "Message"],
             "beta": false,
             "category": "processing",
             "conditional_paths": [],
@@ -1104,17 +1003,15 @@
             "display_name": "Data to Message",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "data",
-              "template",
-              "sep"
-            ],
+            "field_order": ["data", "template", "sep"],
             "frozen": false,
             "icon": "message-square",
             "key": "ParseData",
             "legacy": false,
             "lf_version": "1.1.5",
-            "metadata": {},
+            "metadata": {
+              "legacy_name": "Parse Data"
+            },
             "minimized": false,
             "output_types": [],
             "outputs": [
@@ -1126,9 +1023,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1139,9 +1034,7 @@
                 "name": "data_list",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1165,7 +1058,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n\n    inputs = [\n        DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\", is_list=True, required=True),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
+                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n    metadata = {\n        \"legacy_name\": \"Parse Data\",\n    }\n\n    inputs = [\n        DataInput(\n            name=\"data\",\n            display_name=\"Data\",\n            info=\"The data to convert to text.\",\n            is_list=True,\n            required=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
               },
               "data": {
                 "_input_type": "DataInput",
@@ -1173,9 +1066,7 @@
                 "display_name": "Data",
                 "dynamic": false,
                 "info": "The data to convert to text.",
-                "input_types": [
-                  "Data"
-                ],
+                "input_types": ["Data"],
                 "list": true,
                 "list_add_label": "Add More",
                 "name": "data",
@@ -1214,9 +1105,7 @@
                 "display_name": "Template",
                 "dynamic": false,
                 "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1255,9 +1144,7 @@
         "data": {
           "id": "ChatOutput-UZgon",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -1292,9 +1179,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1307,9 +1192,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1330,9 +1213,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1371,9 +1252,7 @@
                 "display_name": "Data Template",
                 "dynamic": false,
                 "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1394,9 +1273,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Message to be passed as output.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1420,10 +1297,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "options_metadata": [],
                 "placeholder": "",
                 "required": false,
@@ -1440,9 +1314,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1463,9 +1335,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1504,9 +1374,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1544,9 +1412,7 @@
         "data": {
           "id": "ChatInput-m10vc",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -1581,9 +1447,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1596,9 +1460,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1619,9 +1481,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1728,10 +1588,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "options_metadata": [],
                 "placeholder": "",
                 "required": false,
@@ -1748,9 +1605,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1771,9 +1626,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1812,9 +1665,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1919,8 +1770,5 @@
   "is_component": false,
   "last_tested_version": "1.1.5",
   "name": "Research Translation Loop",
-  "tags": [
-    "chatbots",
-    "content-generation"
-  ]
-}
+  "tags": ["chatbots", "content-generation"]
+}

src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json

@@ -8,17 +8,12 @@
             "dataType": "Memory",
             "id": "Memory-gWJrq",
             "name": "messages_text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "memory",
             "id": "Prompt-yhdMP",
-            "inputTypes": [
-              "Message",
-              "Text"
-            ],
+            "inputTypes": ["Message", "Text"],
             "type": "str"
           }
         },
@@ -36,16 +31,12 @@
             "dataType": "ChatInput",
             "id": "ChatInput-PEO9d",
             "name": "message",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-63o3Q",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -63,16 +54,12 @@
             "dataType": "Prompt",
             "id": "Prompt-yhdMP",
             "name": "prompt",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "system_message",
             "id": "OpenAIModel-63o3Q",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -90,16 +77,12 @@
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-63o3Q",
             "name": "text_output",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-BIXzI",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -116,9 +99,7 @@
         "data": {
           "id": "ChatInput-PEO9d",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -152,9 +133,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -167,9 +146,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -189,9 +166,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -294,10 +269,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -313,9 +285,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -335,9 +305,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -373,9 +341,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -419,9 +385,7 @@
           "display_name": "Chat Output",
           "id": "ChatOutput-BIXzI",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -455,9 +419,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -470,9 +432,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -492,9 +452,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -532,9 +490,7 @@
                 "display_name": "Data Template",
                 "dynamic": false,
                 "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "data_template",
@@ -554,9 +510,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Message to be passed as output.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "input_value",
@@ -577,10 +531,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -596,9 +547,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -618,9 +567,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -656,9 +603,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -767,10 +712,7 @@
         "data": {
           "id": "Memory-gWJrq",
           "node": {
-            "base_classes": [
-              "Data",
-              "Message"
-            ],
+            "base_classes": ["Data", "Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -802,9 +744,7 @@
                 "name": "messages",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -815,9 +755,7 @@
                 "name": "messages_text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -848,9 +786,7 @@
                 "display_name": "External Memory",
                 "dynamic": false,
                 "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
-                "input_types": [
-                  "Memory"
-                ],
+                "input_types": ["Memory"],
                 "list": false,
                 "name": "memory",
                 "placeholder": "",
@@ -885,10 +821,7 @@
                 "dynamic": false,
                 "info": "Order of the messages.",
                 "name": "order",
-                "options": [
-                  "Ascending",
-                  "Descending"
-                ],
+                "options": ["Ascending", "Descending"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -906,11 +839,7 @@
                 "dynamic": false,
                 "info": "Filter by sender type.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User",
-                  "Machine and User"
-                ],
+                "options": ["Machine", "User", "Machine and User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -926,9 +855,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Filter by sender name.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -948,9 +875,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -970,9 +895,7 @@
                 "display_name": "Template",
                 "dynamic": false,
                 "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1015,24 +938,18 @@
         "data": {
           "id": "Prompt-yhdMP",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {
-              "template": [
-                "memory"
-              ]
+              "template": ["memory"]
             },
             "description": "Create a prompt template with dynamic variables.",
             "display_name": "Prompt",
             "documentation": "",
             "edited": false,
             "error": null,
-            "field_order": [
-              "template"
-            ],
+            "field_order": ["template"],
             "frozen": false,
             "full_path": null,
             "icon": "prompts",
@@ -1053,9 +970,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1088,10 +1003,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1126,9 +1038,7 @@
                 "display_name": "Tool Placeholder",
                 "dynamic": false,
                 "info": "A placeholder input for tool mode.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "tool_placeholder",
@@ -1170,10 +1080,7 @@
         "data": {
           "id": "OpenAIModel-63o3Q",
           "node": {
-            "base_classes": [
-              "LanguageModel",
-              "Message"
-            ],
+            "base_classes": ["LanguageModel", "Message"],
             "beta": false,
             "category": "models",
             "conditional_paths": [],
@@ -1212,9 +1119,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1223,14 +1128,10 @@
                 "display_name": "Language Model",
                 "method": "build_model",
                 "name": "model_output",
-                "required_inputs": [
-                  "api_key"
-                ],
+                "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1244,9 +1145,7 @@
                 "display_name": "OpenAI API Key",
                 "dynamic": false,
                 "info": "The OpenAI API Key to use for the OpenAI model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "load_from_db": true,
                 "name": "api_key",
                 "password": true,
@@ -1255,7 +1154,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -1281,9 +1180,7 @@
                 "display_name": "Input",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1465,9 +1362,7 @@
                 "display_name": "System Message",
                 "dynamic": false,
                 "info": "System message to pass to the model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1563,9 +1458,5 @@
   "is_component": false,
   "last_tested_version": "1.0.19.post2",
   "name": "Memory Chatbot",
-  "tags": [
-    "chatbots",
-    "openai",
-    "assistants"
-  ]
-}
+  "tags": ["chatbots", "openai", "assistants"]
+}

src/backend/base/langflow/initial_setup/starter_projects/Portfolio Website Code Generator.json

@@ -9,16 +9,12 @@
             "dataType": "Prompt",
             "id": "Prompt-ysecC",
             "name": "prompt",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "StructuredOutput-TArXO",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -36,16 +32,12 @@
             "dataType": "StructuredOutput",
             "id": "StructuredOutput-TArXO",
             "name": "structured_output",
-            "output_types": [
-              "Data"
-            ]
+            "output_types": ["Data"]
           },
           "targetHandle": {
             "fieldName": "data",
             "id": "ParseData-x7Rgx",
-            "inputTypes": [
-              "Data"
-            ],
+            "inputTypes": ["Data"],
             "type": "other"
           }
         },
@@ -63,16 +55,12 @@
             "dataType": "ParseData",
             "id": "ParseData-sGhWo",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "resume",
             "id": "Prompt-ysecC",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -90,16 +78,12 @@
             "dataType": "AnthropicModel",
             "id": "AnthropicModel-sHFTc",
             "name": "model_output",
-            "output_types": [
-              "LanguageModel"
-            ]
+            "output_types": ["LanguageModel"]
           },
           "targetHandle": {
             "fieldName": "llm",
             "id": "StructuredOutput-TArXO",
-            "inputTypes": [
-              "LanguageModel"
-            ],
+            "inputTypes": ["LanguageModel"],
             "type": "other"
           }
         },
@@ -117,16 +101,12 @@
             "dataType": "ParseData",
             "id": "ParseData-x7Rgx",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "AnthropicModel-IrjAe",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -144,16 +124,12 @@
             "dataType": "TextInput",
             "id": "TextInput-CPTOR",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "system_message",
             "id": "AnthropicModel-IrjAe",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -171,16 +147,12 @@
             "dataType": "AnthropicModel",
             "id": "AnthropicModel-IrjAe",
             "name": "text_output",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-d1tmJ",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -197,16 +169,12 @@
             "dataType": "File",
             "id": "File-JgIx7",
             "name": "data",
-            "output_types": [
-              "Data"
-            ]
+            "output_types": ["Data"]
           },
           "targetHandle": {
             "fieldName": "data",
             "id": "ParseData-sGhWo",
-            "inputTypes": [
-              "Data"
-            ],
+            "inputTypes": ["Data"],
             "type": "other"
           }
         },
@@ -222,25 +190,18 @@
         "data": {
           "id": "Prompt-ysecC",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {
-              "template": [
-                "resume"
-              ]
+              "template": ["resume"]
             },
             "description": "Create a prompt template with dynamic variables.",
             "display_name": "Prompt",
             "documentation": "",
             "edited": false,
             "error": null,
-            "field_order": [
-              "template",
-              "tool_placeholder"
-            ],
+            "field_order": ["template", "tool_placeholder"],
             "frozen": false,
             "full_path": null,
             "icon": "prompts",
@@ -262,9 +223,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -297,9 +256,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -335,9 +292,7 @@
                 "display_name": "Tool Placeholder",
                 "dynamic": false,
                 "info": "A placeholder input for tool mode.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -375,10 +330,7 @@
         "data": {
           "id": "ParseData-sGhWo",
           "node": {
-            "base_classes": [
-              "Data",
-              "Message"
-            ],
+            "base_classes": ["Data", "Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -386,16 +338,14 @@
             "display_name": "Data to Message",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "data",
-              "template",
-              "sep"
-            ],
+            "field_order": ["data", "template", "sep"],
             "frozen": false,
             "icon": "message-square",
             "legacy": false,
             "lf_version": "1.1.4.post1",
-            "metadata": {},
+            "metadata": {
+              "legacy_name": "Parse Data"
+            },
             "minimized": false,
             "output_types": [],
             "outputs": [
@@ -407,9 +357,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -420,9 +368,7 @@
                 "name": "data_list",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -445,7 +391,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n\n    inputs = [\n        DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\", is_list=True, required=True),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
+                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n    metadata = {\n        \"legacy_name\": \"Parse Data\",\n    }\n\n    inputs = [\n        DataInput(\n            name=\"data\",\n            display_name=\"Data\",\n            info=\"The data to convert to text.\",\n            is_list=True,\n            required=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
               },
               "data": {
                 "_input_type": "DataInput",
@@ -453,9 +399,7 @@
                 "display_name": "Data",
                 "dynamic": false,
                 "info": "The data to convert to text.",
-                "input_types": [
-                  "Data"
-                ],
+                "input_types": ["Data"],
                 "list": true,
                 "list_add_label": "Add More",
                 "name": "data",
@@ -494,9 +438,7 @@
                 "display_name": "Template",
                 "dynamic": false,
                 "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -535,9 +477,7 @@
         "data": {
           "id": "StructuredOutput-TArXO",
           "node": {
-            "base_classes": [
-              "Data"
-            ],
+            "base_classes": ["Data"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -569,9 +509,7 @@
                 "name": "structured_output",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -602,9 +540,7 @@
                 "display_name": "Input Message",
                 "dynamic": false,
                 "info": "The input message to the language model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -625,9 +561,7 @@
                 "display_name": "Language Model",
                 "dynamic": false,
                 "info": "The language model to use to generate the structured output.",
-                "input_types": [
-                  "LanguageModel"
-                ],
+                "input_types": ["LanguageModel"],
                 "list": false,
                 "list_add_label": "Add More",
                 "name": "llm",
@@ -846,10 +780,7 @@
         "data": {
           "id": "ParseData-x7Rgx",
           "node": {
-            "base_classes": [
-              "Data",
-              "Message"
-            ],
+            "base_classes": ["Data", "Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -857,16 +788,14 @@
             "display_name": "Data to Message",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "data",
-              "template",
-              "sep"
-            ],
+            "field_order": ["data", "template", "sep"],
             "frozen": false,
             "icon": "message-square",
             "legacy": false,
             "lf_version": "1.1.4.post1",
-            "metadata": {},
+            "metadata": {
+              "legacy_name": "Parse Data"
+            },
             "minimized": false,
             "output_types": [],
             "outputs": [
@@ -878,9 +807,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -891,9 +818,7 @@
                 "name": "data_list",
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -916,7 +841,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n\n    inputs = [\n        DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\", is_list=True, required=True),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
+                "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text, data_to_text_list\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n    display_name = \"Data to Message\"\n    description = \"Convert Data objects into Messages using any {field_name} from input data.\"\n    icon = \"message-square\"\n    name = \"ParseData\"\n    metadata = {\n        \"legacy_name\": \"Parse Data\",\n    }\n\n    inputs = [\n        DataInput(\n            name=\"data\",\n            display_name=\"Data\",\n            info=\"The data to convert to text.\",\n            is_list=True,\n            required=True,\n        ),\n        MultilineInput(\n            name=\"template\",\n            display_name=\"Template\",\n            info=\"The template to use for formatting the data. \"\n            \"It can contain the keys {text}, {data} or any other key in the Data.\",\n            value=\"{text}\",\n            required=True,\n        ),\n        StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"text\",\n            info=\"Data as a single Message, with each input Data separated by Separator\",\n            method=\"parse_data\",\n        ),\n        Output(\n            display_name=\"Data List\",\n            name=\"data_list\",\n            info=\"Data as a list of new Data, each having `text` formatted by Template\",\n            method=\"parse_data_as_list\",\n        ),\n    ]\n\n    def _clean_args(self) -> tuple[list[Data], str, str]:\n        data = self.data if isinstance(self.data, list) else [self.data]\n        template = self.template\n        sep = self.sep\n        return data, template, sep\n\n    def parse_data(self) -> Message:\n        data, template, sep = self._clean_args()\n        result_string = data_to_text(template, data, sep)\n        self.status = result_string\n        return Message(text=result_string)\n\n    def parse_data_as_list(self) -> list[Data]:\n        data, template, _ = self._clean_args()\n        text_list, data_list = data_to_text_list(template, data)\n        for item, text in zip(data_list, text_list, strict=True):\n            item.set_text(text)\n        self.status = data_list\n        return data_list\n"
               },
               "data": {
                 "_input_type": "DataInput",
@@ -924,9 +849,7 @@
                 "display_name": "Data",
                 "dynamic": false,
                 "info": "The data to convert to text.",
-                "input_types": [
-                  "Data"
-                ],
+                "input_types": ["Data"],
                 "list": true,
                 "list_add_label": "Add More",
                 "name": "data",
@@ -965,9 +888,7 @@
                 "display_name": "Template",
                 "dynamic": false,
                 "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1006,9 +927,7 @@
         "data": {
           "id": "TextInput-CPTOR",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "category": "inputs",
             "conditional_paths": [],
@@ -1017,9 +936,7 @@
             "display_name": "Text Input",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "input_value"
-            ],
+            "field_order": ["input_value"],
             "frozen": false,
             "icon": "type",
             "key": "TextInput",
@@ -1037,9 +954,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1071,9 +986,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Text to be passed as input.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1112,10 +1025,7 @@
         "data": {
           "id": "AnthropicModel-sHFTc",
           "node": {
-            "base_classes": [
-              "LanguageModel",
-              "Message"
-            ],
+            "base_classes": ["LanguageModel", "Message"],
             "beta": false,
             "category": "models",
             "conditional_paths": [],
@@ -1154,9 +1064,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1165,14 +1073,10 @@
                 "display_name": "Language Model",
                 "method": "build_model",
                 "name": "model_output",
-                "required_inputs": [
-                  "api_key"
-                ],
+                "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1186,10 +1090,8 @@
                 "display_name": "Anthropic API Key",
                 "dynamic": false,
                 "info": "Your Anthropic API key.",
-                "input_types": [
-                  "Message"
-                ],
-                "load_from_db": false,
+                "input_types": ["Message"],
+                "load_from_db": true,
                 "name": "api_key",
                 "password": true,
                 "placeholder": "",
@@ -1198,7 +1100,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "ANTHROPIC_API_KEY"
               },
               "base_url": {
                 "_input_type": "MessageTextInput",
@@ -1206,9 +1108,7 @@
                 "display_name": "Anthropic API URL",
                 "dynamic": false,
                 "info": "Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1248,9 +1148,7 @@
                 "display_name": "Input",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1319,9 +1217,7 @@
                 "display_name": "Prefill",
                 "dynamic": false,
                 "info": "Prefill text to guide the model's response.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1360,9 +1256,7 @@
                 "display_name": "System Message",
                 "dynamic": false,
                 "info": "System message to pass to the model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1448,10 +1342,7 @@
         "data": {
           "id": "AnthropicModel-IrjAe",
           "node": {
-            "base_classes": [
-              "LanguageModel",
-              "Message"
-            ],
+            "base_classes": ["LanguageModel", "Message"],
             "beta": false,
             "category": "models",
             "conditional_paths": [],
@@ -1490,9 +1381,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1501,14 +1390,10 @@
                 "display_name": "Language Model",
                 "method": "build_model",
                 "name": "model_output",
-                "required_inputs": [
-                  "api_key"
-                ],
+                "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1522,10 +1407,8 @@
                 "display_name": "Anthropic API Key",
                 "dynamic": false,
                 "info": "Your Anthropic API key.",
-                "input_types": [
-                  "Message"
-                ],
-                "load_from_db": false,
+                "input_types": ["Message"],
+                "load_from_db": true,
                 "name": "api_key",
                 "password": true,
                 "placeholder": "",
@@ -1534,7 +1417,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "ANTHROPIC_API_KEY"
               },
               "base_url": {
                 "_input_type": "MessageTextInput",
@@ -1542,9 +1425,7 @@
                 "display_name": "Anthropic API URL",
                 "dynamic": false,
                 "info": "Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1584,9 +1465,7 @@
                 "display_name": "Input",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1655,9 +1534,7 @@
                 "display_name": "Prefill",
                 "dynamic": false,
                 "info": "Prefill text to guide the model's response.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1696,9 +1573,7 @@
                 "display_name": "System Message",
                 "dynamic": false,
                 "info": "System message to pass to the model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1784,9 +1659,7 @@
         "data": {
           "id": "ChatOutput-d1tmJ",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "category": "outputs",
             "conditional_paths": [],
@@ -1823,9 +1696,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1839,9 +1710,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1862,9 +1731,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1903,9 +1770,7 @@
                 "display_name": "Data Template",
                 "dynamic": false,
                 "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1926,9 +1791,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Message to be passed as output.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1952,10 +1815,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "options_metadata": [],
                 "placeholder": "",
                 "required": false,
@@ -1972,9 +1832,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1995,9 +1853,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -2036,9 +1892,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -2076,9 +1930,7 @@
         "data": {
           "id": "File-JgIx7",
           "node": {
-            "base_classes": [
-              "Data"
-            ],
+            "base_classes": ["Data"],
             "beta": false,
             "category": "data",
             "conditional_paths": [],
@@ -2114,9 +1966,7 @@
                 "required_inputs": [],
                 "selected": "Data",
                 "tool_mode": true,
-                "types": [
-                  "Data"
-                ],
+                "types": ["Data"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -2184,10 +2034,7 @@
                 "display_name": "Server File Path",
                 "dynamic": false,
                 "info": "Data object with a 'file_path' property pointing to server file or a Message object with a path to the file. Supercedes 'Path' but supports same file types.",
-                "input_types": [
-                  "Data",
-                  "Message"
-                ],
+                "input_types": ["Data", "Message"],
                 "list": true,
                 "list_add_label": "Add More",
                 "name": "file_path",
@@ -2491,8 +2338,5 @@
   "is_component": false,
   "last_tested_version": "1.1.4",
   "name": "Portfolio Website Code Generator",
-  "tags": [
-    "chatbots",
-    "coding"
-  ]
-}
+  "tags": ["chatbots", "coding"]
+}

src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json

@@ -8,16 +8,12 @@
             "dataType": "Prompt",
             "id": "Prompt-a6SIY",
             "name": "prompt",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "system_message",
             "id": "OpenAIModel-brPVM",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -35,16 +31,12 @@
             "dataType": "Prompt",
             "id": "Prompt-jkCpO",
             "name": "prompt",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-brPVM",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -62,16 +54,12 @@
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-brPVM",
             "name": "text_output",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-oE2ic",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -90,9 +78,7 @@
           "display_name": "Prompt",
           "id": "Prompt-jkCpO",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {
@@ -109,9 +95,7 @@
             "display_name": "Prompt",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "template"
-            ],
+            "field_order": ["template"],
             "frozen": false,
             "icon": "prompts",
             "legacy": false,
@@ -127,9 +111,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -162,10 +144,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -185,10 +164,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -208,10 +184,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -231,10 +204,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -254,10 +224,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -277,10 +244,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -316,9 +280,7 @@
                 "display_name": "Tool Placeholder",
                 "dynamic": false,
                 "info": "A placeholder input for tool mode.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "tool_placeholder",
@@ -397,9 +359,7 @@
           "display_name": "Prompt",
           "id": "Prompt-a6SIY",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {
@@ -409,9 +369,7 @@
             "display_name": "Prompt",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "template"
-            ],
+            "field_order": ["template"],
             "frozen": false,
             "icon": "prompts",
             "legacy": false,
@@ -427,9 +385,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -478,9 +434,7 @@
                 "display_name": "Tool Placeholder",
                 "dynamic": false,
                 "info": "A placeholder input for tool mode.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "tool_placeholder",
@@ -524,9 +478,7 @@
           "display_name": "Chat Output",
           "id": "ChatOutput-oE2ic",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -560,9 +512,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -575,9 +525,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -597,9 +545,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -637,9 +583,7 @@
                 "display_name": "Data Template",
                 "dynamic": false,
                 "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "data_template",
@@ -659,9 +603,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Message to be passed as output.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "input_value",
@@ -682,10 +624,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -701,9 +640,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -723,9 +660,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -761,9 +696,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -835,10 +768,7 @@
         "data": {
           "id": "OpenAIModel-brPVM",
           "node": {
-            "base_classes": [
-              "LanguageModel",
-              "Message"
-            ],
+            "base_classes": ["LanguageModel", "Message"],
             "beta": false,
             "category": "models",
             "conditional_paths": [],
@@ -877,9 +807,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -888,14 +816,10 @@
                 "display_name": "Language Model",
                 "method": "build_model",
                 "name": "model_output",
-                "required_inputs": [
-                  "api_key"
-                ],
+                "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -909,9 +833,7 @@
                 "display_name": "OpenAI API Key",
                 "dynamic": false,
                 "info": "The OpenAI API Key to use for the OpenAI model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "load_from_db": true,
                 "name": "api_key",
                 "password": true,
@@ -920,7 +842,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -946,9 +868,7 @@
                 "display_name": "Input",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1130,9 +1050,7 @@
                 "display_name": "System Message",
                 "dynamic": false,
                 "info": "System message to pass to the model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -1228,8 +1146,5 @@
   "is_component": false,
   "last_tested_version": "1.0.19.post2",
   "name": "SEO Keyword Generator",
-  "tags": [
-    "chatbots",
-    "assistants"
-  ]
-}
+  "tags": ["chatbots", "assistants"]
+}

src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json

@@ -109,9 +109,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -338,9 +336,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -654,9 +650,7 @@
                 "name": "response",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -745,7 +739,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,

src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json

@@ -152,9 +152,7 @@
                 "name": "response",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -243,7 +241,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -720,9 +718,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1002,9 +998,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],

src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json

@@ -199,9 +199,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -479,9 +477,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -760,9 +756,7 @@
                 "name": "response",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -851,7 +845,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -1353,9 +1347,7 @@
                 "name": "response",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1444,7 +1436,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -1946,9 +1938,7 @@
                 "name": "response",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -2037,7 +2027,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -3101,7 +3091,7 @@
                 "dynamic": false,
                 "info": "",
                 "input_types": ["Message"],
-                "load_from_db": false,
+                "load_from_db": true,
                 "name": "api_key",
                 "password": true,
                 "placeholder": "",
@@ -3109,7 +3099,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "SEARCHAPI_API_KEY"
               },
               "code": {
                 "advanced": true,

src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json

@@ -9,17 +9,12 @@
             "dataType": "TextInput",
             "id": "TextInput-eClq5",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "CONTENT_GUIDELINES",
             "id": "Prompt-AWZtN",
-            "inputTypes": [
-              "Message",
-              "Text"
-            ],
+            "inputTypes": ["Message", "Text"],
             "type": "str"
           }
         },
@@ -38,17 +33,12 @@
             "dataType": "TextInput",
             "id": "TextInput-IpoG7",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "OUTPUT_FORMAT",
             "id": "Prompt-AWZtN",
-            "inputTypes": [
-              "Message",
-              "Text"
-            ],
+            "inputTypes": ["Message", "Text"],
             "type": "str"
           }
         },
@@ -67,17 +57,12 @@
             "dataType": "TextInput",
             "id": "TextInput-npraC",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "OUTPUT_LANGUAGE",
             "id": "Prompt-AWZtN",
-            "inputTypes": [
-              "Message",
-              "Text"
-            ],
+            "inputTypes": ["Message", "Text"],
             "type": "str"
           }
         },
@@ -96,17 +81,12 @@
             "dataType": "TextInput",
             "id": "TextInput-EZaR7",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "PROFILE_DETAILS",
             "id": "Prompt-AWZtN",
-            "inputTypes": [
-              "Message",
-              "Text"
-            ],
+            "inputTypes": ["Message", "Text"],
             "type": "str"
           }
         },
@@ -125,17 +105,12 @@
             "dataType": "TextInput",
             "id": "TextInput-fKGcs",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "PROFILE_TYPE",
             "id": "Prompt-AWZtN",
-            "inputTypes": [
-              "Message",
-              "Text"
-            ],
+            "inputTypes": ["Message", "Text"],
             "type": "str"
           }
         },
@@ -154,17 +129,12 @@
             "dataType": "TextInput",
             "id": "TextInput-92vEK",
             "name": "text",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "TONE_AND_STYLE",
             "id": "Prompt-AWZtN",
-            "inputTypes": [
-              "Message",
-              "Text"
-            ],
+            "inputTypes": ["Message", "Text"],
             "type": "str"
           }
         },
@@ -182,16 +152,12 @@
             "dataType": "ChatInput",
             "id": "ChatInput-ECcN8",
             "name": "message",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-p0R9m",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -209,16 +175,12 @@
             "dataType": "Prompt",
             "id": "Prompt-AWZtN",
             "name": "prompt",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "system_message",
             "id": "OpenAIModel-p0R9m",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -236,16 +198,12 @@
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-p0R9m",
             "name": "text_output",
-            "output_types": [
-              "Message"
-            ]
+            "output_types": ["Message"]
           },
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-0jDYx",
-            "inputTypes": [
-              "Message"
-            ],
+            "inputTypes": ["Message"],
             "type": "str"
           }
         },
@@ -262,9 +220,7 @@
         "data": {
           "id": "ChatInput-ECcN8",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -298,9 +254,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -313,9 +267,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -334,9 +286,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -437,10 +387,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -455,9 +402,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -476,9 +421,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -513,9 +456,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -555,9 +496,7 @@
         "data": {
           "id": "TextInput-eClq5",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -565,9 +504,7 @@
             "display_name": "Content Guidelines",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "input_value"
-            ],
+            "field_order": ["input_value"],
             "frozen": false,
             "icon": "type",
             "legacy": false,
@@ -583,9 +520,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -616,9 +551,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Text to be passed as input.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -661,9 +594,7 @@
           "display_name": "Chat Output",
           "id": "ChatOutput-0jDYx",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -697,9 +628,7 @@
                 "name": "message",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -712,9 +641,7 @@
                 "display_name": "Background Color",
                 "dynamic": false,
                 "info": "The background color of the icon.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "background_color",
@@ -734,9 +661,7 @@
                 "display_name": "Icon",
                 "dynamic": false,
                 "info": "The icon of the message.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "chat_icon",
@@ -774,9 +699,7 @@
                 "display_name": "Data Template",
                 "dynamic": false,
                 "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "data_template",
@@ -796,9 +719,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Message to be passed as output.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "input_value",
@@ -819,10 +740,7 @@
                 "dynamic": false,
                 "info": "Type of sender.",
                 "name": "sender",
-                "options": [
-                  "Machine",
-                  "User"
-                ],
+                "options": ["Machine", "User"],
                 "placeholder": "",
                 "required": false,
                 "show": true,
@@ -838,9 +756,7 @@
                 "display_name": "Sender Name",
                 "dynamic": false,
                 "info": "Name of the sender.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "sender_name",
@@ -860,9 +776,7 @@
                 "display_name": "Session ID",
                 "dynamic": false,
                 "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "session_id",
@@ -898,9 +812,7 @@
                 "display_name": "Text Color",
                 "dynamic": false,
                 "info": "The text color of the name",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "text_color",
@@ -942,9 +854,7 @@
         "data": {
           "id": "TextInput-IpoG7",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -952,9 +862,7 @@
             "display_name": "Output Format",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "input_value"
-            ],
+            "field_order": ["input_value"],
             "frozen": false,
             "icon": "type",
             "legacy": false,
@@ -970,9 +878,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1003,9 +909,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Text to be passed as input.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1046,9 +950,7 @@
         "data": {
           "id": "TextInput-npraC",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -1056,9 +958,7 @@
             "display_name": "Output Language",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "input_value"
-            ],
+            "field_order": ["input_value"],
             "frozen": false,
             "icon": "type",
             "legacy": false,
@@ -1074,9 +974,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1107,9 +1005,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Text to be passed as input.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1150,9 +1046,7 @@
         "data": {
           "id": "TextInput-EZaR7",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -1160,9 +1054,7 @@
             "display_name": "Profile Details",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "input_value"
-            ],
+            "field_order": ["input_value"],
             "frozen": false,
             "icon": "type",
             "legacy": false,
@@ -1178,9 +1070,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1211,9 +1101,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Text to be passed as input.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1254,9 +1142,7 @@
         "data": {
           "id": "TextInput-92vEK",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -1264,9 +1150,7 @@
             "display_name": "Tone And Style",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "input_value"
-            ],
+            "field_order": ["input_value"],
             "frozen": false,
             "icon": "type",
             "legacy": false,
@@ -1282,9 +1166,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1315,9 +1197,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Text to be passed as input.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1358,9 +1238,7 @@
         "data": {
           "id": "TextInput-fKGcs",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {},
@@ -1368,9 +1246,7 @@
             "display_name": "Profile Type",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "input_value"
-            ],
+            "field_order": ["input_value"],
             "frozen": false,
             "icon": "type",
             "legacy": false,
@@ -1386,9 +1262,7 @@
                 "name": "text",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1419,9 +1293,7 @@
                 "display_name": "Text",
                 "dynamic": false,
                 "info": "Text to be passed as input.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1501,9 +1373,7 @@
           "display_name": "Prompt",
           "id": "Prompt-AWZtN",
           "node": {
-            "base_classes": [
-              "Message"
-            ],
+            "base_classes": ["Message"],
             "beta": false,
             "conditional_paths": [],
             "custom_fields": {
@@ -1520,9 +1390,7 @@
             "display_name": "Prompt",
             "documentation": "",
             "edited": false,
-            "field_order": [
-              "template"
-            ],
+            "field_order": ["template"],
             "frozen": false,
             "icon": "prompts",
             "legacy": false,
@@ -1538,9 +1406,7 @@
                 "name": "prompt",
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1554,10 +1420,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1577,10 +1440,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1600,10 +1460,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1623,10 +1480,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1646,10 +1500,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1669,10 +1520,7 @@
                 "fileTypes": [],
                 "file_path": "",
                 "info": "",
-                "input_types": [
-                  "Message",
-                  "Text"
-                ],
+                "input_types": ["Message", "Text"],
                 "list": false,
                 "load_from_db": false,
                 "multiline": true,
@@ -1727,9 +1575,7 @@
                 "display_name": "Tool Placeholder",
                 "dynamic": false,
                 "info": "A placeholder input for tool mode.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "load_from_db": false,
                 "name": "tool_placeholder",
@@ -1771,10 +1617,7 @@
         "data": {
           "id": "OpenAIModel-p0R9m",
           "node": {
-            "base_classes": [
-              "LanguageModel",
-              "Message"
-            ],
+            "base_classes": ["LanguageModel", "Message"],
             "beta": false,
             "category": "models",
             "conditional_paths": [],
@@ -1813,9 +1656,7 @@
                 "required_inputs": [],
                 "selected": "Message",
                 "tool_mode": true,
-                "types": [
-                  "Message"
-                ],
+                "types": ["Message"],
                 "value": "__UNDEFINED__"
               },
               {
@@ -1824,14 +1665,10 @@
                 "display_name": "Language Model",
                 "method": "build_model",
                 "name": "model_output",
-                "required_inputs": [
-                  "api_key"
-                ],
+                "required_inputs": ["api_key"],
                 "selected": "LanguageModel",
                 "tool_mode": true,
-                "types": [
-                  "LanguageModel"
-                ],
+                "types": ["LanguageModel"],
                 "value": "__UNDEFINED__"
               }
             ],
@@ -1845,9 +1682,7 @@
                 "display_name": "OpenAI API Key",
                 "dynamic": false,
                 "info": "The OpenAI API Key to use for the OpenAI model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "load_from_db": true,
                 "name": "api_key",
                 "password": true,
@@ -1856,7 +1691,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "str",
-                "value": ""
+                "value": "OPENAI_API_KEY"
               },
               "code": {
                 "advanced": true,
@@ -1882,9 +1717,7 @@
                 "display_name": "Input",
                 "dynamic": false,
                 "info": "",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -2066,9 +1899,7 @@
                 "display_name": "System Message",
                 "dynamic": false,
                 "info": "System message to pass to the model.",
-                "input_types": [
-                  "Message"
-                ],
+                "input_types": ["Message"],
                 "list": false,
                 "list_add_label": "Add More",
                 "load_from_db": false,
@@ -2164,8 +1995,5 @@
   "is_component": false,
   "last_tested_version": "1.0.19.post2",
   "name": "Twitter Thread Generator",
-  "tags": [
-    "chatbots",
-    "content-generation"
-  ]
-}
+  "tags": ["chatbots", "content-generation"]
+}

src/backend/base/langflow/inputs/inputs.py

@@ -37,20 +37,34 @@ class TableInput(BaseInputMixin, MetadataTraceMixin, TableMixin, ListableInputMi
     @field_validator("value")
     @classmethod
     def validate_value(cls, v: Any, _info):
-        # Check if value is a list of dicts
+        # Convert single dict or Data instance into a list.
+        if isinstance(v, dict | Data):
+            v = [v]
+        # Automatically convert DataFrame into a list of dictionaries.
         if isinstance(v, DataFrame):
             v = v.to_dict(orient="records")
+        # Verify the value is now a list.
         if not isinstance(v, list):
-            msg = f"TableInput value must be a list of dictionaries or Data. Value '{v}' is not a list."
-            raise ValueError(msg)  # noqa: TRY004
-
-        for item in v:
+            msg = (
+                "The table input must be a list of rows. You provided a "
+                f"{type(v).__name__}, which cannot be converted to table format. "
+                "Please provide your data as either:\n"
+                "- A list of dictionaries (each dict is a row)\n"
+                "- A pandas DataFrame\n"
+                "- A single dictionary (will become a one-row table)\n"
+                "- A Data object (Langflow's internal data structure)\n"
+            )
+            raise ValueError(msg)  # noqa: TRY004 Pydantic only catches ValueError or AssertionError
+        # Ensure each item in the list is either a dict or a Data instance.
+        for i, item in enumerate(v):
             if not isinstance(item, dict | Data):
                 msg = (
-                    "TableInput value must be a list of dictionaries or Data. "
-                    f"Item '{item}' is not a dictionary or Data."
+                    f"Row {i + 1} in your table has an invalid format. Each row must be either:\n"
+                    "- A dictionary containing column name/value pairs\n"
+                    "- A Data object (Langflow's internal data structure for passing data between components)\n"
+                    f"Instead, got a {type(item).__name__}. Please check the format of your input data."
                 )
-                raise ValueError(msg)  # noqa: TRY004
+                raise ValueError(msg)  # noqa: TRY004 Pydantic only catches ValueError or AssertionError
         return v
 
 

src/backend/base/langflow/main.py

@@ -34,7 +34,7 @@ from langflow.interface.components import get_and_cache_all_types_dict
 from langflow.interface.utils import setup_llm_caching
 from langflow.logging.logger import configure
 from langflow.middleware import ContentSizeLimitMiddleware
-from langflow.services.deps import get_settings_service, get_telemetry_service
+from langflow.services.deps import get_queue_service, get_settings_service, get_telemetry_service
 from langflow.services.utils import initialize_services, teardown_services
 
 if TYPE_CHECKING:
@@ -43,6 +43,7 @@ if TYPE_CHECKING:
 # Ignore Pydantic deprecation warnings from Langchain
 warnings.filterwarnings("ignore", category=PydanticDeprecatedSince20)
 
+_tasks: list[asyncio.Task] = []
 
 MAX_PORT = 65535
 
@@ -127,6 +128,9 @@ def get_lifespan(*, fix_migration=False, version=None):
             await create_or_update_starter_projects(all_types_dict)
             telemetry_service.start()
             await load_flows_from_directory()
+            queue_service = get_queue_service()
+            if not queue_service.is_started():  # Start if not already started
+                queue_service.start()
             yield
 
         except Exception as exc:

src/backend/base/langflow/serialization/serialization.py

@@ -221,8 +221,8 @@ def _serialize_dispatcher(obj: Any, max_length: int | None, max_items: int | Non
 
 def serialize(
     obj: Any,
-    max_length: int | None = MAX_TEXT_LENGTH,
-    max_items: int | None = MAX_ITEMS_LENGTH,
+    max_length: int | None = None,
+    max_items: int | None = None,
     *,
     to_str: bool = False,
 ) -> Any:
@@ -275,7 +275,9 @@ def serialize(
 
 
 def serialize_or_str(
-    obj: Any, max_length: int | None = MAX_TEXT_LENGTH, max_items: int | None = MAX_ITEMS_LENGTH
+    obj: Any,
+    max_length: int | None = MAX_TEXT_LENGTH,
+    max_items: int | None = MAX_ITEMS_LENGTH,
 ) -> Any:
     """Calls serialize() and if it fails, returns a string representation of the object.
 

src/backend/base/langflow/services/auth/utils.py

@@ -375,13 +375,29 @@ def encrypt_api_key(api_key: str, settings_service: SettingsService):
 
 
 def decrypt_api_key(encrypted_api_key: str, settings_service: SettingsService):
+    """Decrypt the provided encrypted API key using Fernet decryption.
+
+    This function first attempts to decrypt the API key by encoding it,
+    assuming it is a properly encoded string. If that fails, it logs a detailed
+    debug message including the exception information and retries decryption
+    using the original string input.
+
+    Args:
+        encrypted_api_key (str): The encrypted API key.
+        settings_service (SettingsService): Service providing authentication settings.
+
+    Returns:
+        str: The decrypted API key, or an empty string if decryption cannot be performed.
+    """
     fernet = get_fernet(settings_service)
-    decrypted_key = ""
-    # Two-way decryption
     if isinstance(encrypted_api_key, str):
         try:
-            decrypted_key = fernet.decrypt(encrypted_api_key.encode()).decode()
-        except Exception:  # noqa: BLE001
-            logger.debug("Failed to decrypt API key")
-            decrypted_key = fernet.decrypt(encrypted_api_key).decode()
-    return decrypted_key
+            return fernet.decrypt(encrypted_api_key.encode()).decode()
+        except Exception as primary_exception:  # noqa: BLE001
+            logger.debug(
+                "Decryption using UTF-8 encoded API key failed. Error: %s. "
+                "Retrying decryption using the raw string input.",
+                primary_exception,
+            )
+            return fernet.decrypt(encrypted_api_key).decode()
+    return ""

src/backend/base/langflow/services/database/models/transactions/crud.py

@@ -1,5 +1,6 @@
 from uuid import UUID
 
+from loguru import logger
 from sqlmodel import col, delete, select
 from sqlmodel.ext.asyncio.session import AsyncSession
 
@@ -25,7 +26,7 @@ async def get_transactions_by_flow_id(
     return list(transactions)
 
 
-async def log_transaction(db: AsyncSession, transaction: TransactionBase) -> TransactionTable:
+async def log_transaction(db: AsyncSession, transaction: TransactionBase) -> TransactionTable | None:
     """Log a transaction and maintain a maximum number of transactions in the database.
 
     This function logs a new transaction into the database and ensures that the number of transactions
@@ -42,6 +43,9 @@ async def log_transaction(db: AsyncSession, transaction: TransactionBase) -> Tra
     Raises:
         IntegrityError: If there is a database integrity error
     """
+    if not transaction.flow_id:
+        logger.debug("Transaction flow_id is None")
+        return None
     table = TransactionTable(**transaction.model_dump())
 
     try:
@@ -63,7 +67,6 @@ async def log_transaction(db: AsyncSession, transaction: TransactionBase) -> Tra
         db.add(table)
         await db.exec(delete_older)
         await db.commit()
-        await db.refresh(table)
 
     except Exception:
         await db.rollback()

src/backend/base/langflow/services/database/models/transactions/model.py

@@ -5,7 +5,8 @@ from uuid import UUID, uuid4
 from pydantic import field_serializer, field_validator
 from sqlmodel import JSON, Column, Field, Relationship, SQLModel
 
-from langflow.services.database.utils import truncate_json
+from langflow.serialization.constants import MAX_ITEMS_LENGTH, MAX_TEXT_LENGTH
+from langflow.serialization.serialization import serialize
 
 if TYPE_CHECKING:
     from langflow.services.database.models.flow.model import Flow
@@ -36,11 +37,11 @@ class TransactionBase(SQLModel):
 
     @field_serializer("inputs")
     def serialize_inputs(self, data) -> dict:
-        return truncate_json(data)
+        return serialize(data, max_length=MAX_TEXT_LENGTH, max_items=MAX_ITEMS_LENGTH)
 
     @field_serializer("outputs")
     def serialize_outputs(self, data) -> dict:
-        return truncate_json(data)
+        return serialize(data, max_length=MAX_TEXT_LENGTH, max_items=MAX_ITEMS_LENGTH)
 
 
 class TransactionTable(TransactionBase, table=True):  # type: ignore[call-arg]

src/backend/base/langflow/services/database/models/vertex_builds/crud.py

@@ -143,4 +143,3 @@ async def delete_vertex_builds_by_flow_id(db: AsyncSession, flow_id: UUID) -> No
     """
     stmt = delete(VertexBuildTable).where(VertexBuildTable.flow_id == flow_id)
     await db.exec(stmt)
-    await db.commit()

src/backend/base/langflow/services/database/models/vertex_builds/model.py

@@ -6,13 +6,12 @@ from pydantic import BaseModel, field_serializer, field_validator
 from sqlalchemy import Text
 from sqlmodel import JSON, Column, Field, Relationship, SQLModel
 
-from langflow.services.database.utils import truncate_json
+from langflow.serialization.constants import MAX_ITEMS_LENGTH, MAX_TEXT_LENGTH
+from langflow.serialization.serialization import serialize
 
 if TYPE_CHECKING:
     from langflow.services.database.models.flow.model import Flow
 
-from langflow.utils.util_strings import truncate_long_strings
-
 
 class VertexBuildBase(SQLModel):
     timestamp: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
@@ -45,15 +44,15 @@ class VertexBuildBase(SQLModel):
 
     @field_serializer("data")
     def serialize_data(self, data) -> dict:
-        return truncate_json(data)
+        return serialize(data, max_length=MAX_TEXT_LENGTH, max_items=MAX_ITEMS_LENGTH)
 
     @field_serializer("artifacts")
     def serialize_artifacts(self, data) -> dict:
-        return truncate_json(data)
+        return serialize(data, max_length=MAX_TEXT_LENGTH, max_items=MAX_ITEMS_LENGTH)
 
     @field_serializer("params")
     def serialize_params(self, data) -> str:
-        return truncate_long_strings(data)
+        return serialize(data, max_length=MAX_TEXT_LENGTH, max_items=MAX_ITEMS_LENGTH)
 
 
 class VertexBuildTable(VertexBuildBase, table=True):  # type: ignore[call-arg]

src/backend/base/langflow/services/database/utils.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import json
 from contextlib import asynccontextmanager
 from dataclasses import dataclass
 from typing import TYPE_CHECKING
@@ -10,54 +9,10 @@ from loguru import logger
 from sqlmodel import text
 from sqlmodel.ext.asyncio.session import AsyncSession
 
-from langflow.serialization import constants
-
 if TYPE_CHECKING:
     from langflow.services.database.service import DatabaseService
 
 
-def truncate_json(data, *, max_size: int = constants.MAX_TEXT_LENGTH):
-    def calculate_size(data):
-        return len(json.dumps(data))
-
-    def shrink_to_size(data, remaining_size):
-        if isinstance(data, dict):
-            truncated = {}
-            for key, value in data.items():
-                key_size = len(json.dumps(key))
-                if remaining_size - key_size <= 0:
-                    break
-                truncated[key] = shrink_to_size(value, remaining_size - key_size)
-                remaining_size -= len(json.dumps({key: value})) - key_size
-            return truncated
-
-        if isinstance(data, list):
-            truncated = []
-            for item in data:
-                if remaining_size <= len('""'):
-                    break
-                truncated.append(shrink_to_size(item, remaining_size))
-                remaining_size -= len(json.dumps(item)) + 1
-            return truncated
-
-        if isinstance(data, str):
-            max_string_length = max(remaining_size - 2, 0)
-            return data[:max_string_length] + "…" if max_string_length > 0 else "…"
-
-        return data
-
-    try:
-        json.dumps(data)
-        is_serialized = True
-    except Exception:  # noqa: BLE001
-        is_serialized = False
-
-    if calculate_size(data) <= max_size or not is_serialized:
-        return data
-
-    return shrink_to_size(data, max_size)
-
-
 async def initialize_database(*, fix_migration: bool = False) -> None:
     logger.debug("Initializing database")
     from langflow.services.deps import get_db_service

src/backend/base/langflow/services/deps.py

@@ -15,6 +15,7 @@ if TYPE_CHECKING:
     from langflow.services.cache.service import AsyncBaseCacheService, CacheService
     from langflow.services.chat.service import ChatService
     from langflow.services.database.service import DatabaseService
+    from langflow.services.job_queue.service import JobQueueService
     from langflow.services.session.service import SessionService
     from langflow.services.settings.service import SettingsService
     from langflow.services.socket.service import SocketIOService
@@ -239,3 +240,10 @@ def get_store_service() -> StoreService:
         StoreService: The StoreService instance.
     """
     return get_service(ServiceType.STORE_SERVICE)
+
+
+def get_queue_service() -> JobQueueService:
+    """Retrieves the QueueService instance from the service manager."""
+    from langflow.services.job_queue.factory import JobQueueServiceFactory
+
+    return get_service(ServiceType.JOB_QUEUE_SERVICE, JobQueueServiceFactory())

src/backend/base/langflow/services/job_queue/factory.py

@@ -0,0 +1,11 @@
+from langflow.services.base import Service
+from langflow.services.factory import ServiceFactory
+from langflow.services.job_queue.service import JobQueueService
+
+
+class JobQueueServiceFactory(ServiceFactory):
+    def __init__(self):
+        super().__init__(JobQueueService)
+
+    def create(self) -> Service:
+        return JobQueueService()

src/backend/base/langflow/services/job_queue/service.py

@@ -0,0 +1,263 @@
+from __future__ import annotations
+
+import asyncio
+
+from loguru import logger
+
+from langflow.events.event_manager import EventManager, create_default_event_manager
+from langflow.services.base import Service
+
+
+class JobQueueService(Service):
+    """Asynchronous service for managing job-specific queues and their associated tasks.
+
+    This service allows clients to:
+      - Create dedicated asyncio queues for individual jobs.
+      - Associate each queue with an EventManager, enabling event-driven handling.
+      - Launch and manage asynchronous tasks that process these job queues.
+      - Safely clean up resources by cancelling active tasks and emptying queues.
+      - Automatically perform periodic cleanup of inactive or completed job queues.
+
+    Attributes:
+        name (str): Unique identifier for the service.
+        _queues (dict[str, tuple[asyncio.Queue, EventManager, asyncio.Task | None]]):
+            Dictionary mapping job IDs to a tuple containing:
+              * The job's asyncio.Queue instance.
+              * The associated EventManager instance.
+              * The asyncio.Task processing the job (if any).
+        _cleanup_task (asyncio.Task | None): Background task for periodic cleanup.
+        _closed (bool): Flag indicating whether the service is currently active.
+
+    Example:
+        service = JobQueueService()
+        await service.start()
+        queue, event_manager = service.create_queue("job123")
+        service.start_job("job123", some_async_coroutine())
+        # Retrieve and use the queue data as needed
+        data = service.get_queue_data("job123")
+        await service.cleanup_job("job123")
+        await service.stop()
+    """
+
+    name = "job_queue_service"
+
+    def __init__(self) -> None:
+        """Initialize the JobQueueService.
+
+        Sets up the internal registry for job queues, initializes the cleanup task, and sets the service state
+        to active.
+        """
+        self._queues: dict[str, tuple[asyncio.Queue, EventManager, asyncio.Task | None]] = {}
+        self._cleanup_task: asyncio.Task | None = None
+        self._closed = False
+        self.ready = False
+
+    def is_started(self) -> bool:
+        """Check if the JobQueueService has started.
+
+        Returns:
+            bool: True if the service has started, False otherwise.
+        """
+        return self._cleanup_task is not None
+
+    def set_ready(self) -> None:
+        if not self.is_started():
+            self.start()
+        super().set_ready()
+
+    def start(self) -> None:
+        """Start the JobQueueService and begin the periodic cleanup routine.
+
+        This method marks the service as active and launches a background task that
+        periodically checks and cleans up job queues whose tasks have been completed or cancelled.
+        """
+        self._closed = False
+        self._cleanup_task = asyncio.create_task(self._periodic_cleanup())
+        logger.debug("JobQueueService started: periodic cleanup task initiated.")
+
+    async def stop(self) -> None:
+        """Gracefully stop the JobQueueService by terminating background operations and cleaning up all resources.
+
+        This coroutine performs the following steps:
+            1. Marks the service as closed, preventing further job queue creation.
+            2. Cancels the background periodic cleanup task and awaits its termination.
+            3. Iterates over all registered job queues to clean up their resources—cancelling active tasks and
+            clearing queued items.
+        """
+        self._closed = True
+        if self._cleanup_task:
+            self._cleanup_task.cancel()
+            await asyncio.wait([self._cleanup_task])
+            if not self._cleanup_task.cancelled():
+                exc = self._cleanup_task.exception()
+                if exc is not None:
+                    raise exc
+
+        # Clean up each registered job queue.
+        for job_id in list(self._queues.keys()):
+            await self.cleanup_job(job_id)
+        logger.info("JobQueueService stopped: all job queues have been cleaned up.")
+
+    async def teardown(self) -> None:
+        await self.stop()
+
+    def create_queue(self, job_id: str) -> tuple[asyncio.Queue, EventManager]:
+        """Create and register a new queue along with its corresponding event manager for a job.
+
+        Args:
+            job_id (str): Unique identifier for the job.
+
+        Returns:
+            tuple[asyncio.Queue, EventManager]: A tuple containing:
+                - The asyncio.Queue instance for handling the job's tasks or messages.
+                - The EventManager instance for event handling tied to the queue.
+        """
+        if job_id in self._queues:
+            msg = f"Queue for job_id {job_id} already exists"
+            logger.error(msg)
+            raise ValueError(msg)
+
+        if self._closed:
+            msg = "Queue service is closed"
+            logger.error(msg)
+            raise RuntimeError(msg)
+
+        main_queue: asyncio.Queue = asyncio.Queue()
+        event_manager = create_default_event_manager(main_queue)
+
+        # Register the queue without an active task.
+        self._queues[job_id] = (main_queue, event_manager, None)
+        logger.debug(f"Queue and event manager successfully created for job_id {job_id}")
+        return main_queue, event_manager
+
+    def start_job(self, job_id: str, task_coro) -> None:
+        """Start an asynchronous task for a given job, replacing any existing active task.
+
+        The method performs the following:
+          - Verifies the presence of a registered queue for the job.
+          - Cancels any currently running task associated with the job.
+          - Launches a new asynchronous task using the provided coroutine.
+          - Updates the internal registry with the new task.
+
+        Args:
+            job_id (str): Unique identifier for the job.
+            task_coro: A coroutine representing the job's asynchronous task.
+        """
+        if job_id not in self._queues:
+            msg = f"No queue found for job_id {job_id}"
+            logger.error(msg)
+            raise ValueError(msg)
+
+        if self._closed:
+            msg = "Queue service is closed"
+            logger.error(msg)
+            raise RuntimeError(msg)
+
+        main_queue, event_manager, existing_task = self._queues[job_id]
+
+        if existing_task and not existing_task.done():
+            logger.debug(f"Existing task for job_id {job_id} detected; cancelling it.")
+            existing_task.cancel()
+
+        # Initiate the new asynchronous task.
+        task = asyncio.create_task(task_coro)
+        self._queues[job_id] = (main_queue, event_manager, task)
+        logger.debug(f"New task started for job_id {job_id}")
+
+    def get_queue_data(self, job_id: str) -> tuple[asyncio.Queue, EventManager, asyncio.Task | None]:
+        """Retrieve the complete data structure associated with a job's queue.
+
+        Args:
+            job_id (str): Unique identifier for the job.
+
+        Returns:
+            tuple[asyncio.Queue, EventManager, asyncio.Task | None]:
+                A tuple containing the job's main queue, its linked event manager, and the associated task (if any).
+        """
+        if job_id not in self._queues:
+            msg = f"No queue found for job_id {job_id}"
+            logger.error(msg)
+            raise ValueError(msg)
+
+        if self._closed:
+            msg = "Queue service is closed"
+            logger.error(msg)
+            raise RuntimeError(msg)
+
+        return self._queues[job_id]
+
+    async def cleanup_job(self, job_id: str) -> None:
+        """Clean up and release resources for a specific job.
+
+        The cleanup process includes:
+          1. Verifying if the job's queue is registered.
+          2. Cancelling the running task (if active) and awaiting its termination.
+          3. Clearing all items from the job's queue.
+          4. Removing the job's entry from the internal registry.
+
+        Args:
+            job_id (str): Unique identifier for the job to be cleaned up.
+        """
+        if job_id not in self._queues:
+            logger.debug(f"No queue found for job_id {job_id} during cleanup.")
+            return
+
+        logger.info(f"Commencing cleanup for job_id {job_id}")
+        main_queue, event_manager, task = self._queues[job_id]
+
+        # Cancel the associated task if it is still running.
+        if task and not task.done():
+            logger.debug(f"Cancelling active task for job_id {job_id}")
+            task.cancel()
+            await asyncio.wait([task])
+            # Log any exceptions that occurred during the task's execution.
+            if exc := task.exception():
+                logger.error(f"Error in task for job_id {job_id}: {exc}")
+            logger.debug(f"Task cancellation complete for job_id {job_id}")
+
+        # Clear the queue since we just cancelled the task or it has completed
+        items_cleared = 0
+        while not main_queue.empty():
+            try:
+                main_queue.get_nowait()
+                items_cleared += 1
+            except asyncio.QueueEmpty:
+                break
+
+        logger.debug(f"Removed {items_cleared} items from queue for job_id {job_id}")
+        # Remove the job entry from the registry
+        self._queues.pop(job_id, None)
+        logger.info(f"Cleanup successful for job_id {job_id}: resources have been released.")
+
+    async def _periodic_cleanup(self) -> None:
+        """Execute a periodic task that cleans up completed or cancelled job queues.
+
+        This internal coroutine continuously:
+          - Sleeps for a fixed interval (60 seconds).
+          - Initiates the cleanup of job queues by calling _cleanup_old_queues.
+          - Monitors and logs any exceptions during the cleanup cycle.
+
+        The loop terminates when the service is marked as closed.
+        """
+        while not self._closed:
+            try:
+                await asyncio.sleep(60)  # Sleep for 60 seconds before next cleanup attempt.
+                await self._cleanup_old_queues()
+            except asyncio.CancelledError:
+                logger.debug("Periodic cleanup task received cancellation signal.")
+                raise
+            except Exception as exc:  # noqa: BLE001
+                logger.error(f"Exception encountered during periodic cleanup: {exc}")
+
+    async def _cleanup_old_queues(self) -> None:
+        """Scan all registered job queues and clean up those with inactive tasks.
+
+        For each job:
+          - Check whether the associated task is either complete or cancelled.
+          - If so, execute the cleanup_job method to release the job's resources.
+        """
+        for job_id in list(self._queues.keys()):
+            _, _, task = self._queues[job_id]
+            if task and task.done():
+                logger.debug(f"Job queue for job_id {job_id} marked for cleanup.")
+                await self.cleanup_job(job_id)

src/backend/base/langflow/services/schema.py

@@ -19,3 +19,4 @@ class ServiceType(str, Enum):
     STATE_SERVICE = "state_service"
     TRACING_SERVICE = "tracing_service"
     TELEMETRY_SERVICE = "telemetry_service"
+    JOB_QUEUE_SERVICE = "job_queue_service"

src/backend/base/langflow/services/settings/base.py

@@ -76,14 +76,13 @@ class Settings(BaseSettings):
     `postgresql+psycopg` respectively)."""
     database_connection_retry: bool = False
     """If True, Langflow will retry to connect to the database if it fails."""
-    pool_size: int = 10
-    """DEPRECATED: Use db_connection_settings['pool_size'] instead.
-    The number of connections to keep open in the connection pool. If not provided, the default is 10."""
-    max_overflow: int = 20
-    """DEPRECATED: Use db_connection_settings['max_overflow'] instead.
-    The number of connections to allow that can be opened beyond the pool size.
-    If not provided, the default is 20."""
-    db_connect_timeout: int = 20
+    pool_size: int = 20
+    """The number of connections to keep open in the connection pool.
+    For high load scenarios, this should be increased based on expected concurrent users."""
+    max_overflow: int = 30
+    """The number of connections to allow that can be opened beyond the pool size.
+    Should be 2x the pool_size for optimal performance under load."""
+    db_connect_timeout: int = 30
     """The number of seconds to wait before giving up on a lock to released or establishing a connection to the
     database."""
 
@@ -92,12 +91,27 @@ class Settings(BaseSettings):
     """SQLite pragmas to use when connecting to the database."""
 
     db_connection_settings: dict | None = {
-        "pool_size": 10,
-        "max_overflow": 20,
-        "pool_timeout": 30,
-        "pool_pre_ping": True,
+        "pool_size": 20,  # Match the pool_size above
+        "max_overflow": 30,  # Match the max_overflow above
+        "pool_timeout": 30,  # Seconds to wait for a connection from pool
+        "pool_pre_ping": True,  # Check connection validity before using
+        "pool_recycle": 1800,  # Recycle connections after 30 minutes
+        "echo": False,  # Set to True for debugging only
     }
-    """Common database connection settings."""
+    """Database connection settings optimized for high load scenarios.
+    Note: These settings are most effective with PostgreSQL. For SQLite:
+    - Reduce pool_size and max_overflow if experiencing lock contention
+    - SQLite has limited concurrent write capability even with WAL mode
+    - Best for read-heavy or moderate write workloads
+
+    Settings:
+    - pool_size: Number of connections to maintain (increase for higher concurrency)
+    - max_overflow: Additional connections allowed beyond pool_size
+    - pool_timeout: Seconds to wait for an available connection
+    - pool_pre_ping: Validates connections before use to prevent stale connections
+    - pool_recycle: Seconds before connections are recycled (prevents timeouts)
+    - echo: Enable SQL query logging (development only)
+    """
 
     # cache configuration
     cache_type: Literal["async", "redis", "memory", "disk"] = "async"
@@ -205,6 +219,9 @@ class Settings(BaseSettings):
     mcp_server_enable_progress_notifications: bool = False
     """If set to False, Langflow will not send progress notifications in the MCP server."""
 
+    event_delivery: Literal["polling", "streaming"] = "streaming"
+    """How to deliver build events to the frontend. Can be 'polling' or 'streaming'."""
+
     @field_validator("dev")
     @classmethod
     def set_dev(cls, value):

src/backend/base/langflow/services/task/backends/anyio.py

@@ -1,19 +1,24 @@
+from __future__ import annotations
+
 import traceback
-from collections.abc import Callable
-from typing import Any
+from typing import TYPE_CHECKING, Any
 
 import anyio
-from loguru import logger
 
 from langflow.services.task.backends.base import TaskBackend
 
+if TYPE_CHECKING:
+    from collections.abc import Callable
+    from types import TracebackType
+
 
 class AnyIOTaskResult:
-    def __init__(self, scope) -> None:
-        self._scope = scope
+    def __init__(self) -> None:
         self._status = "PENDING"
         self._result = None
         self._exception: Exception | None = None
+        self._traceback: TracebackType | None = None
+        self.cancel_scope: anyio.CancelScope | None = None
 
     @property
     def status(self) -> str:
@@ -34,9 +39,11 @@ class AnyIOTaskResult:
     def ready(self) -> bool:
         return self._status == "DONE"
 
-    async def run(self, func, *args, **kwargs) -> None:
+    async def run(self, func: Callable[..., Any], *args: Any, **kwargs: Any) -> None:
         try:
-            self._result = await func(*args, **kwargs)
+            async with anyio.CancelScope() as scope:
+                self.cancel_scope = scope
+                self._result = await func(*args, **kwargs)
         except Exception as e:  # noqa: BLE001
             self._exception = e
             self._traceback = e.__traceback__
@@ -45,36 +52,66 @@ class AnyIOTaskResult:
 
 
 class AnyIOBackend(TaskBackend):
+    """Backend for handling asynchronous tasks using AnyIO."""
+
     name = "anyio"
 
     def __init__(self) -> None:
+        """Initialize the AnyIO backend with an empty task dictionary."""
         self.tasks: dict[str, AnyIOTaskResult] = {}
+        self._run_tasks: list[anyio.TaskGroup] = []
 
     async def launch_task(
         self, task_func: Callable[..., Any], *args: Any, **kwargs: Any
-    ) -> tuple[str | None, AnyIOTaskResult | None]:
+    ) -> tuple[str, AnyIOTaskResult]:
         """Launch a new task in an asynchronous manner.
 
-        Parameters:
+        Args:
             task_func: The asynchronous function to run.
             *args: Positional arguments to pass to task_func.
             **kwargs: Keyword arguments to pass to task_func.
 
         Returns:
-            A tuple containing a unique task ID and the task result object.
-        """
-        async with anyio.create_task_group() as tg:
-            try:
-                task_result = AnyIOTaskResult(tg)
-                tg.start_soon(task_result.run, task_func, *args, **kwargs)
-            except Exception:  # noqa: BLE001
-                logger.exception("An error occurred while launching the task")
-                return None, None
+            tuple[str, AnyIOTaskResult]: A tuple containing the task ID and task result object.
 
+        Raises:
+            RuntimeError: If task creation fails.
+        """
+        try:
+            task_result = AnyIOTaskResult()
+
+            # Create task ID before starting the task
             task_id = str(id(task_result))
             self.tasks[task_id] = task_result
-            logger.info(f"Task {task_id} started.")
-            return task_id, task_result
 
-    def get_task(self, task_id: str) -> Any:
+            # Start the task in the background using TaskGroup
+            async with anyio.create_task_group() as tg:
+                tg.start_soon(task_result.run, task_func, *args, **kwargs)
+                self._run_tasks.append(tg)
+
+        except Exception as e:
+            msg = f"Failed to launch task: {e!s}"
+            raise RuntimeError(msg) from e
+        return task_id, task_result
+
+    def get_task(self, task_id: str) -> AnyIOTaskResult | None:
+        """Retrieve a task by its ID.
+
+        Args:
+            task_id: The unique identifier of the task.
+
+        Returns:
+            AnyIOTaskResult | None: The task result object if found, None otherwise.
+        """
         return self.tasks.get(task_id)
+
+    async def cleanup_task(self, task_id: str) -> None:
+        """Clean up a completed task and its resources.
+
+        Args:
+            task_id: The unique identifier of the task to clean up.
+        """
+        if task := self.tasks.get(task_id):
+            if task.cancel_scope:
+                task.cancel_scope.cancel()
+            self.tasks.pop(task_id, None)

src/backend/base/langflow/services/task/service.py

@@ -3,45 +3,20 @@ from __future__ import annotations
 from collections.abc import Callable, Coroutine
 from typing import TYPE_CHECKING, Any
 
-from loguru import logger
-
 from langflow.services.base import Service
 from langflow.services.task.backends.anyio import AnyIOBackend
-from langflow.services.task.utils import get_celery_worker_status
 
 if TYPE_CHECKING:
     from langflow.services.settings.service import SettingsService
     from langflow.services.task.backends.base import TaskBackend
 
 
-def check_celery_availability():
-    try:
-        from langflow.worker import celery_app
-
-        status = get_celery_worker_status(celery_app)
-        logger.debug(f"Celery status: {status}")
-    except Exception:  # noqa: BLE001
-        logger.opt(exception=True).debug("Celery not available")
-        status = {"availability": None}
-    return status
-
-
 class TaskService(Service):
     name = "task_service"
 
     def __init__(self, settings_service: SettingsService):
         self.settings_service = settings_service
-        try:
-            if self.settings_service.settings.celery_enabled:
-                status = check_celery_availability()
-
-                use_celery = status.get("availability") is not None
-            else:
-                use_celery = False
-        except ImportError:
-            use_celery = False
-
-        self.use_celery = use_celery
+        self.use_celery = False
         self.backend = self.get_backend()
 
     @property
@@ -49,12 +24,6 @@ class TaskService(Service):
         return self.backend.name
 
     def get_backend(self) -> TaskBackend:
-        if self.use_celery:
-            from langflow.services.task.backends.celery import CeleryBackend
-
-            logger.debug("Using Celery backend")
-            return CeleryBackend()
-        logger.debug("Using AnyIO backend")
         return AnyIOBackend()
 
     # In your TaskService class
@@ -64,24 +33,8 @@ class TaskService(Service):
         *args: Any,
         **kwargs: Any,
     ) -> Any:
-        if not self.use_celery:
-            return None, await task_func(*args, **kwargs)
-        if not hasattr(task_func, "apply"):
-            msg = f"Task function {task_func} does not have an apply method"
-            raise ValueError(msg)
-        task = task_func.apply(args=args, kwargs=kwargs)
-
-        result = task.get()
-        # if result is coroutine
-        if isinstance(result, Coroutine):
-            result = await result
-        return task.id, result
+        return await task_func(*args, **kwargs)
 
     async def launch_task(self, task_func: Callable[..., Any], *args: Any, **kwargs: Any) -> Any:
-        logger.debug(f"Launching task {task_func} with args {args} and kwargs {kwargs}")
-        logger.debug(f"Using backend {self.backend}")
         task = self.backend.launch_task(task_func, *args, **kwargs)
         return await task if isinstance(task, Coroutine) else task
-
-    def get_task(self, task_id: str) -> Any:
-        return self.backend.get_task(task_id)

src/backend/base/langflow/services/telemetry/schema.py

@@ -21,6 +21,7 @@ class VersionPayload(BaseModel):
     auto_login: bool = Field(serialization_alias="autoLogin")
     cache_type: str = Field(serialization_alias="cacheType")
     backend_only: bool = Field(serialization_alias="backendOnly")
+    desktop: bool = False
 
 
 class PlaygroundPayload(BaseModel):

src/backend/base/langflow/services/telemetry/service.py

@@ -90,6 +90,10 @@ class TelemetryService(Service):
             return
         await self.telemetry_queue.put(payload)
 
+    def _get_langflow_desktop(self) -> bool:
+        # Coerce to bool, could be 1, 0, True, False, "1", "0", "True", "False"
+        return str(os.getenv("LANGFLOW_DESKTOP", "False")).lower() in ("1", "true")
+
     async def log_package_version(self) -> None:
         python_version = ".".join(platform.python_version().split(".")[:2])
         version_info = get_version_info()
@@ -104,6 +108,7 @@ class TelemetryService(Service):
             backend_only=self.settings_service.settings.backend_only,
             arch=self.architecture,
             auto_login=self.settings_service.auth_settings.AUTO_LOGIN,
+            desktop=self._get_langflow_desktop(),
         )
         await self._queue_event((self.send_telemetry_data, payload, None))
 

src/backend/base/langflow/services/tracing/arize_phoenix.py

@@ -39,7 +39,9 @@ class ArizePhoenixTracer(BaseTracer):
     chat_input_value: str
     chat_output_value: str
 
-    def __init__(self, trace_name: str, trace_type: str, project_name: str, trace_id: UUID):
+    def __init__(
+        self, trace_name: str, trace_type: str, project_name: str, trace_id: UUID, session_id: str | None = None
+    ):
         """Initializes the ArizePhoenixTracer instance and sets up a root span."""
         self.trace_name = trace_name
         self.trace_type = trace_type
@@ -49,6 +51,7 @@ class ArizePhoenixTracer(BaseTracer):
         self.flow_id = trace_name.split(" - ")[-1]
         self.chat_input_value = ""
         self.chat_output_value = ""
+        self.session_id = session_id
 
         try:
             self._ready = self.setup_arize_phoenix()
@@ -63,7 +66,7 @@ class ArizePhoenixTracer(BaseTracer):
                 name=self.flow_id,
                 start_time=self._get_current_timestamp(),
             )
-            self.root_span.set_attribute(SpanAttributes.SESSION_ID, self.flow_id)
+            self.root_span.set_attribute(SpanAttributes.SESSION_ID, self.session_id or self.flow_id)
             self.root_span.set_attribute(SpanAttributes.OPENINFERENCE_SPAN_KIND, self.trace_type)
             self.root_span.set_attribute("langflow.project.name", self.project_name)
             self.root_span.set_attribute("langflow.flow.name", self.flow_name)

src/backend/base/langflow/services/tracing/service.py

@@ -65,6 +65,7 @@ class TracingService(Service):
         self.worker_task: asyncio.Task | None = None
         self.end_trace_tasks: set[asyncio.Task] = set()
         self.deactivated = self.settings_service.settings.deactivate_tracing
+        self.session_id: str | None = None
 
     async def log_worker(self) -> None:
         while self.running or not self.logs_queue.empty():
@@ -163,6 +164,7 @@ class TracingService(Service):
             trace_type="chain",
             project_name=self.project_name,
             trace_id=self.run_id,
+            session_id=self.session_id,
         )
 
     def set_run_name(self, name: str) -> None:
@@ -241,7 +243,7 @@ class TracingService(Service):
             trace_id,
             trace_name,
             trace_type,
-            self._cleanup_inputs(inputs),
+            inputs,
             metadata,
             component._vertex,
         )
@@ -286,3 +288,7 @@ class TracingService(Service):
             if langchain_callback:
                 callbacks.append(langchain_callback)
         return callbacks
+
+    def set_session_id(self, session_id: str) -> None:
+        """Set the session ID for tracing."""
+        self.session_id = session_id

src/backend/base/pyproject.toml

@@ -170,7 +170,7 @@ dev-dependencies = [
 module-root = "langflow"
 tests-root = "../tests/unit"
 test-framework = "pytest"
-ignore-paths = []
+ignore-paths = ["src/backend/base/langflow/components/"]
 formatter-cmds = ["ruff check --exit-zero --fix $file", "ruff format $file"]
 #disable plugins that might interfere with runtime measurement
 pytest-cmd = "pytest -p no:profiling -p no:sugar -p no:xdist -p no:cov -p no:split"

src/backend/tests/conftest.py

@@ -135,11 +135,12 @@ def get_text():
 
 
 async def delete_transactions_by_flow_id(db: AsyncSession, flow_id: UUID):
+    if not flow_id:
+        return
     stmt = select(TransactionTable).where(TransactionTable.flow_id == flow_id)
     transactions = await db.exec(stmt)
     for transaction in transactions:
         await db.delete(transaction)
-    await db.commit()
 
 
 async def _delete_transactions_and_vertex_builds(session, flows: list[Flow]):
@@ -147,8 +148,14 @@ async def _delete_transactions_and_vertex_builds(session, flows: list[Flow]):
     for flow_id in flow_ids:
         if not flow_id:
             continue
-        await delete_vertex_builds_by_flow_id(session, flow_id)
-        await delete_transactions_by_flow_id(session, flow_id)
+        try:
+            await delete_vertex_builds_by_flow_id(session, flow_id)
+        except Exception as e:  # noqa: BLE001
+            logger.debug(f"Error deleting vertex builds for flow {flow_id}: {e}")
+        try:
+            await delete_transactions_by_flow_id(session, flow_id)
+        except Exception as e:  # noqa: BLE001
+            logger.debug(f"Error deleting transactions for flow {flow_id}: {e}")
 
 
 @pytest.fixture
@@ -433,12 +440,21 @@ async def active_user(client):  # noqa: ARG001
     yield user
     # Clean up
     # Now cleanup transactions, vertex_build
-    async with db_manager.with_session() as session:
-        user = await session.get(User, user.id, options=[selectinload(User.flows)])
-        await _delete_transactions_and_vertex_builds(session, user.flows)
-        await session.delete(user)
+    try:
+        async with db_manager.with_session() as session:
+            user = await session.get(User, user.id, options=[selectinload(User.flows)])
+            await _delete_transactions_and_vertex_builds(session, user.flows)
+            await session.commit()
+    except Exception as e:  # noqa: BLE001
+        logger.exception(f"Error deleting transactions and vertex builds for user: {e}")
 
-        await session.commit()
+    try:
+        async with db_manager.with_session() as session:
+            user = await session.get(User, user.id)
+            await session.delete(user)
+            await session.commit()
+    except Exception as e:  # noqa: BLE001
+        logger.exception(f"Error deleting user: {e}")
 
 
 @pytest.fixture

src/backend/tests/locust/locustfile.py

@@ -1,125 +1,125 @@
-import random
+import os
 import time
-from pathlib import Path
+from http import HTTPStatus
 
-import httpx
-import orjson
-from locust import FastHttpUser, between, task
-from rich import print  # noqa: A004
+from locust import FastHttpUser, between, events, task
 
 
-class NameTest(FastHttpUser):
-    wait_time = between(1, 5)
+@events.quitting.add_listener
+def _(environment, **_kwargs):
+    """Print stats at test end for analysis."""
+    if environment.stats.total.fail_ratio > 0.01:
+        environment.process_exit_code = 1
+    environment.runner.quit()
 
-    with Path("names.txt").open(encoding="utf-8") as file:
-        names = [line.strip() for line in file]
 
-    headers: dict = {}
+class FlowRunUser(FastHttpUser):
+    """FlowRunUser simulates users sending requests to the Langflow run endpoint.
 
-    def poll_task(self, task_id, sleep_time=1):
-        while True:
-            with self.rest(
-                "GET",
-                f"/task/{task_id}",
-                name="task_status",
-                headers=self.headers,
-            ) as response:
-                status = response.js.get("status")
-                print(f"Poll Response: {response.js}")
-                if status == "SUCCESS":
-                    return response.js.get("result")
-                if status in {"FAILURE", "REVOKED"}:
-                    msg = f"Task failed with status: {status}"
-                    raise ValueError(msg)
-            time.sleep(sleep_time)
+    Designed for high-load testing with proper wait times and connection handling.
+    Uses FastHttpUser for better performance with keep-alive connections and connection pooling.
 
-    def process(self, name, flow_id, payload):
-        task_id = None
-        print(f"Processing {payload}")
-        with self.rest(
-            "POST",
-            f"/process/{flow_id}",
-            json=payload,
-            name="process",
-            headers=self.headers,
-        ) as response:
-            print(response.js)
-            if response.status_code != 200:
-                response.failure("Process call failed")
-                msg = "Process call failed"
-                raise ValueError(msg)
-            task_id = response.js.get("id")
-            session_id = response.js.get("session_id")
-            assert task_id, "Inner Task ID not found"
+    Environment Variables:
+      - LANGFLOW_HOST: Base URL for the Langflow server (default: http://localhost:7860)
+      - FLOW_ID: UUID or endpoint name of the flow to test (default: 62c21279-f7ca-43e2-b5e3-326ac573db04)
+      - API_KEY: API key for authentication, sent as header 'x-api-key' (Required)
+      - MIN_WAIT: Minimum wait time between requests in ms (default: 2000)
+      - MAX_WAIT: Maximum wait time between requests in ms (default: 5000)
+      - REQUEST_TIMEOUT: Timeout for each request in seconds (default: 30.0)
+    """
 
-        assert task_id, "Task ID not found"
-        result = self.poll_task(task_id)
-        print(f"Result for {name}: {result}")
+    abstract = False  # This user class can be instantiated
+    connection_timeout = float(os.getenv("REQUEST_TIMEOUT", "30.0"))  # Configurable timeout
+    network_timeout = float(os.getenv("REQUEST_TIMEOUT", "30.0"))
 
-        return result, session_id
+    # Dynamic wait time based on environment variables or defaults
+    # Increased default minimum wait to reduce database pressure
+    wait_time = between(
+        float(os.getenv("MIN_WAIT", "2000")) / 1000,
+        float(os.getenv("MAX_WAIT", "5000")) / 1000,
+    )
 
-    @task
-    def send_name_and_check(self):
-        name = random.choice(self.names)  # noqa: S311
+    # Use the host provided by environment variable or default
+    host = os.getenv("LANGFLOW_HOST", "http://localhost:7860")
 
-        payload1 = {
-            "inputs": {"text": f"Hello, My name is {name}"},
-            "sync": False,
-        }
-        _result1, session_id = self.process(name, self.flow_id, payload1)
+    # Flow ID from environment variable or default example UUID
+    flow_id = os.getenv("FLOW_ID")
 
-        payload2 = {
-            "inputs": {"text": "What is my name? Please, answer like this: Your name is <name>"},
-            "session_id": session_id,
-            "sync": False,
-        }
-        result2, session_id = self.process(name, self.flow_id, payload2)
-
-        assert f"Your name is {name}" in str(result2), "Name not found in response"
+    def __init__(self, *args, **kwargs) -> None:
+        super().__init__(*args, **kwargs)
+        self._last_response: dict | None = None
+        self._consecutive_failures = 0
 
     def on_start(self):
-        print("Starting")
-        login_data = {"username": "superuser", "password": "superuser"}
-        response = httpx.post(f"{self.host}/login", data=login_data)
-        print(response.json())
+        """Setup and validate required configurations."""
+        if not os.getenv("API_KEY"):
+            msg = "API_KEY environment variable is required for load testing"
+            raise ValueError(msg)
 
-        tokens = response.json()
-        print(tokens)
-        a_token = tokens["access_token"]
-        logged_in_headers = {"Authorization": f"Bearer {a_token}"}
-        print("Logged in")
-        json_flow = (Path(__file__).parent.parent / "data" / "BasicChatwithPromptandHistory.json").read_text(
-            encoding="utf-8"
-        )
-        flow = orjson.loads(json_flow)
-        data = flow["data"]
-        # Create test data
-        flow = {"name": "Flow 1", "description": "description", "data": data}
-        print("Creating flow")
-        # Make request to endpoint
-        response = httpx.post(
-            f"{self.host}/flows/",
-            json=flow,
-            headers=logged_in_headers,
-        )
-        self.flow_id = response.json()["id"]
-        print(f"Flow ID: {self.flow_id}")
+        # Test connection and auth before starting
+        with self.client.get("/health", catch_response=True) as response:
+            if response.status_code != HTTPStatus.OK:
+                msg = f"Initial health check failed: {response.status_code}"
+                raise ConnectionError(msg)
 
-        # read all users
-        response = httpx.get(
-            f"{self.host}/users/",
-            headers=logged_in_headers,
-        )
-        print(response.json())
-        user_id = next(
-            (user["id"] for user in response.json()["users"] if user["username"] == "superuser"),
-            None,
-        )
-        # Create api key
-        response = httpx.post(
-            f"{self.host}/api_key/",
-            json={"user_id": user_id},
-            headers=logged_in_headers,
-        )
-        print(response.json())
-        self.headers["x-api-key"] = response.json()["api_key"]
+    def log_error(self, name: str, exc: Exception, response_time: float):
+        """Helper method to log errors in a format Locust expects.
+
+        Args:
+            name: The name/endpoint of the request
+            exc: The exception that occurred
+            response_time: The response time in milliseconds
+        """
+        # Log error in stats
+        self.environment.stats.log_error("ERROR", name, str(exc))
+        # Log request with error
+        self.environment.stats.log_request("ERROR", name, response_time, 0)
+
+    @task(1)
+    def run_flow_endpoint(self):
+        """Sends a POST request to the run endpoint using a realistic payload.
+
+        Includes basic error handling.
+        """
+        if not self.flow_id:
+            msg = "FLOW_ID environment variable is required for load testing"
+            raise ValueError(msg)
+        endpoint = f"/api/v1/run/{self.flow_id}?stream=false"
+
+        # Realistic payload that exercises the system
+        payload = {
+            "input_value": (
+                "Hey, Could you check https://docs.langflow.org for me? Later, could you calculate 1390 / 192 ?"
+            ),
+            "output_type": "chat",
+            "input_type": "chat",
+            "tweaks": {},
+        }
+
+        headers = {
+            "Content-Type": "application/json",
+            "x-api-key": os.getenv("API_KEY"),
+            "Accept": "application/json",
+        }
+
+        start_time = time.time()
+        try:
+            with self.client.post(
+                endpoint, json=payload, headers=headers, catch_response=True, timeout=self.connection_timeout
+            ) as response:
+                response_time = (time.time() - start_time) * 1000
+                if response.status_code == HTTPStatus.OK:
+                    try:
+                        self._last_response = response.json()
+                    except ValueError as e:
+                        response.failure("Invalid JSON response")
+                        self.log_error(endpoint, e, response_time)
+                else:
+                    error_text = response.text or "No response text"
+                    error_msg = f"Unexpected status code: {response.status_code}, Response: {error_text[:200]}"
+                    response.failure(error_msg)
+                    self.log_error(endpoint, Exception(error_msg), response_time)
+        except Exception as e:  # noqa: BLE001
+            response_time = (time.time() - start_time) * 1000
+            self.log_error(endpoint, e, response_time)
+            response.failure(f"Error: {e}")

src/backend/tests/unit/base/tools/test_component_toolkit.py

@@ -35,17 +35,21 @@ def test_component_tool():
 
 
 @pytest.mark.api_key_required
-def test_component_tool_with_api_key():
+@pytest.mark.usefixtures("client")
+async def test_component_tool_with_api_key():
     chat_output = ChatOutput()
     openai_llm = OpenAIModelComponent()
     openai_llm.set(api_key=os.environ["OPENAI_API_KEY"])
     tool_calling_agent = ToolCallingAgentComponent()
+    tools = await chat_output.to_toolkit()
     tool_calling_agent.set(
-        llm=openai_llm.build_model, tools=[chat_output], input_value="Which tools are available? Please tell its name."
+        llm=openai_llm.build_model,
+        tools=tools,
+        input_value="Which tools are available? Please tell its name.",
     )
 
     g = Graph(start=tool_calling_agent, end=tool_calling_agent)
     assert g is not None
-    results = list(g.start())
+    results = [result async for result in g.async_start()]
     assert len(results) == 4
     assert "message_response" in tool_calling_agent._outputs_map["response"].value.get_text()

src/backend/tests/unit/build_utils.py

@@ -0,0 +1,75 @@
+import json
+from typing import Any
+from uuid import UUID
+
+from httpx import AsyncClient, codes
+
+
+async def create_flow(client: AsyncClient, flow_data: str, headers: dict[str, str]) -> UUID:
+    """Create a flow and return its ID."""
+    response = await client.post("api/v1/flows/", json=json.loads(flow_data), headers=headers)
+    assert response.status_code == codes.CREATED
+    return UUID(response.json()["id"])
+
+
+async def build_flow(
+    client: AsyncClient, flow_id: UUID, headers: dict[str, str], json: dict[str, Any] | None = None
+) -> dict[str, Any]:
+    """Start a flow build and return the job_id."""
+    if json is None:
+        json = {}
+    response = await client.post(f"api/v1/build/{flow_id}/flow", json=json, headers=headers)
+    assert response.status_code == codes.OK
+    return response.json()
+
+
+async def get_build_events(client: AsyncClient, job_id: str, headers: dict[str, str]):
+    """Get events for a build job."""
+    return await client.get(f"api/v1/build/{job_id}/events", headers=headers)
+
+
+async def consume_and_assert_stream(response, job_id):
+    """Consume the event stream and assert the expected event structure."""
+    count = 0
+    lines = []
+    async for line in response.aiter_lines():
+        # Skip empty lines (ndjson uses double newlines)
+        if not line:
+            continue
+
+        lines.append(line)
+        parsed = json.loads(line)
+        if "job_id" in parsed:
+            assert parsed["job_id"] == job_id
+            continue
+
+        if count == 0:
+            # First event should be vertices_sorted
+            assert parsed["event"] == "vertices_sorted", (
+                "Invalid first event. Expected 'vertices_sorted'. Full event stream:\n" + "\n".join(lines)
+            )
+            ids = parsed["data"]["ids"]
+            ids.sort()
+            assert ids == ["ChatInput-CIGht"], "Invalid ids in first event. Full event stream:\n" + "\n".join(lines)
+
+            to_run = parsed["data"]["to_run"]
+            to_run.sort()
+            assert to_run == ["ChatInput-CIGht", "ChatOutput-QA7ej", "Memory-amN4Z", "Prompt-iWbCC"], (
+                "Invalid to_run list in first event. Full event stream:\n" + "\n".join(lines)
+            )
+        elif count > 0 and count < 5:
+            # Next events should be end_vertex events
+            assert parsed["event"] == "end_vertex", (
+                f"Invalid event at position {count}. Expected 'end_vertex'. Full event stream:\n" + "\n".join(lines)
+            )
+            assert parsed["data"]["build_data"] is not None, (
+                f"Missing build_data at position {count}. Full event stream:\n" + "\n".join(lines)
+            )
+        elif count == 5:
+            # Final event should be end
+            assert parsed["event"] == "end", "Invalid final event. Expected 'end'. Full event stream:\n" + "\n".join(
+                lines
+            )
+        else:
+            raise ValueError(f"Unexpected event at position {count}. Full event stream:\n" + "\n".join(lines))
+        count += 1

src/backend/tests/unit/components/agents/test_agent_component.py

@@ -78,9 +78,8 @@ class TestAgentComponent(ComponentTestBaseWithoutClient):
         assert all(provider in updated_config["agent_llm"]["options"] for provider in MODEL_PROVIDERS_DICT)
         assert "Anthropic" in updated_config["agent_llm"]["options"]
         assert updated_config["agent_llm"]["input_types"] == []
-        assert any("sonnet" in option.lower() for option in updated_config["model_name"]["options"]), (
-            f"Options: {updated_config['model_name']['options']}"
-        )
+        options = updated_config["model_name"]["options"]
+        assert any("sonnet" in option.lower() for option in options), f"Options: {options}"
 
         # Test updating build config for Custom
         updated_config = await component.update_build_config(build_config, "Custom", "agent_llm")
@@ -113,6 +112,7 @@ async def test_agent_component_with_calculator():
         model_name="gpt-4o",
         llm_type="OpenAI",
         temperature=temperature,
+        _session_id=str(uuid4()),
     )
 
     response = await agent.message_response()

src/backend/tests/unit/components/data/test_url_component.py

@@ -19,7 +19,7 @@ class TestURLComponent(ComponentTestBaseWithoutClient):
     def default_kwargs(self):
         """Return the default kwargs for the component."""
         return {
-            "urls": ["https://example.com"],
+            "urls": ["https://google.com"],
             "format": "Text",
         }
 

src/backend/tests/unit/components/helpers/test_batch_run_component.py

@@ -21,6 +21,7 @@ class TestBatchRunComponent(ComponentTestBaseWithoutClient):
             "model": MockLanguageModel(),
             "df": DataFrame({"text": ["Hello"]}),
             "column_name": "text",
+            "enable_metadata": True,
         }
 
     @pytest.fixture
@@ -33,7 +34,11 @@ class TestBatchRunComponent(ComponentTestBaseWithoutClient):
         test_df = DataFrame({"text": ["Hello", "World", "Test"]})
 
         component = BatchRunComponent(
-            model=MockLanguageModel(), system_message="You are a helpful assistant", df=test_df, column_name="text"
+            model=MockLanguageModel(),
+            system_message="You are a helpful assistant",
+            df=test_df,
+            column_name="text",
+            enable_metadata=True,
         )
 
         # Run the batch process
@@ -43,46 +48,188 @@ class TestBatchRunComponent(ComponentTestBaseWithoutClient):
         assert isinstance(result, DataFrame)
         assert "text_input" in result.columns
         assert "model_response" in result.columns
+        assert "metadata" in result.columns
         assert len(result) == 3
         assert all(isinstance(resp, str) for resp in result["model_response"])
+        # Convert DataFrame to list of dicts for easier testing
+        result_dicts = result.to_dict("records")
+        # Verify metadata
+        assert all(row["metadata"]["has_system_message"] for row in result_dicts)
+        assert all(row["metadata"]["processing_status"] == "success" for row in result_dicts)
 
-    async def test_batch_run_without_system_message(self):
+    async def test_batch_run_without_metadata(self):
         test_df = DataFrame({"text": ["Hello", "World"]})
 
-        component = BatchRunComponent(model=MockLanguageModel(), df=test_df, column_name="text")
+        component = BatchRunComponent(
+            model=MockLanguageModel(),
+            df=test_df,
+            column_name="text",
+            enable_metadata=False,
+        )
 
         result = await component.run_batch()
 
         assert isinstance(result, DataFrame)
         assert len(result) == 2
+        assert "metadata" not in result.columns
         assert all(isinstance(resp, str) for resp in result["model_response"])
 
+    async def test_batch_run_error_with_metadata(self):
+        component = BatchRunComponent(
+            model=MockLanguageModel(),
+            df="not_a_dataframe",  # This will cause a TypeError
+            column_name="text",
+            enable_metadata=True,
+        )
+
+        with pytest.raises(TypeError, match=re.escape("Expected DataFrame input, got <class 'str'>")):
+            await component.run_batch()
+
+    async def test_batch_run_error_without_metadata(self):
+        component = BatchRunComponent(
+            model=MockLanguageModel(),
+            df="not_a_dataframe",  # This will cause a TypeError
+            column_name="text",
+            enable_metadata=False,
+        )
+
+        with pytest.raises(TypeError, match=re.escape("Expected DataFrame input, got <class 'str'>")):
+            await component.run_batch()
+
+    async def test_operational_error_with_metadata(self):
+        # Create a mock model that raises an AttributeError during processing
+        class ErrorModel:
+            def with_config(self, *_, **__):
+                return self
+
+            async def abatch(self, *_):
+                msg = "Mock error during batch processing"
+                raise AttributeError(msg)
+
+        component = BatchRunComponent(
+            model=ErrorModel(),
+            df=DataFrame({"text": ["test1", "test2"]}),
+            column_name="text",
+            enable_metadata=True,
+        )
+
+        result = await component.run_batch()
+        assert isinstance(result, DataFrame)
+        assert len(result) == 1  # Component returns a single error row
+        error_row = result.iloc[0]
+        # Verify error metadata
+        assert error_row["metadata"]["processing_status"] == "failed"
+        assert "Mock error during batch processing" in error_row["metadata"]["error"]
+        # Verify base row structure
+        assert error_row["text_input"] == ""
+        assert error_row["model_response"] == ""
+        assert error_row["batch_index"] == -1
+
+    async def test_operational_error_without_metadata(self):
+        # Create a mock model that raises an AttributeError during processing
+        class ErrorModel:
+            def with_config(self, *_, **__):
+                return self
+
+            async def abatch(self, *_):
+                msg = "Mock error during batch processing"
+                raise AttributeError(msg)
+
+        component = BatchRunComponent(
+            model=ErrorModel(),
+            df=DataFrame({"text": ["test1", "test2"]}),
+            column_name="text",
+            enable_metadata=False,
+        )
+
+        result = await component.run_batch()
+        assert isinstance(result, DataFrame)
+        assert len(result) == 1  # Component returns a single error row
+        error_row = result.iloc[0]
+        # Verify no metadata
+        assert "metadata" not in error_row
+        # Verify base row structure
+        assert error_row["text_input"] == ""
+        assert error_row["model_response"] == ""
+        assert error_row["batch_index"] == -1
+
+    def test_create_base_row(self):
+        component = BatchRunComponent()
+        row = component._create_base_row(text_input="test_input", model_response="test_response", batch_index=1)
+
+        assert row == {
+            "text_input": "test_input",
+            "model_response": "test_response",
+            "batch_index": 1,
+        }
+
+    def test_add_metadata_success(self):
+        component = BatchRunComponent(enable_metadata=True)
+        row = component._create_base_row(text_input="test_input", model_response="test_response", batch_index=1)
+        component._add_metadata(row, success=True, system_msg="test_system")
+
+        assert "metadata" in row
+        assert row["metadata"]["has_system_message"] is True
+        assert row["metadata"]["processing_status"] == "success"
+        assert row["metadata"]["input_length"] == len("test_input")
+        assert row["metadata"]["response_length"] == len("test_response")
+
+    def test_add_metadata_failure(self):
+        component = BatchRunComponent(enable_metadata=True)
+        row = component._create_base_row()
+        component._add_metadata(row, success=False, error="test_error")
+
+        assert "metadata" in row
+        assert row["metadata"]["processing_status"] == "failed"
+        assert row["metadata"]["error"] == "test_error"
+
+    def test_metadata_disabled(self):
+        component = BatchRunComponent(enable_metadata=False)
+        row = component._create_base_row(text_input="test")
+        component._add_metadata(row, success=True)
+
+        assert "metadata" not in row
+
     async def test_invalid_column_name(self):
         component = BatchRunComponent(
-            model=MockLanguageModel(), df=DataFrame({"text": ["Hello"]}), column_name="nonexistent_column"
+            model=MockLanguageModel(),
+            df=DataFrame({"text": ["Hello"]}),
+            column_name="nonexistent_column",
+            enable_metadata=True,
         )
 
-        with pytest.raises(ValueError, match=re.escape("Column 'nonexistent_column' not found in the DataFrame.")):
+        with pytest.raises(
+            ValueError,
+            match=re.escape("Column 'nonexistent_column' not found in the DataFrame. Available columns: text"),
+        ):
             await component.run_batch()
 
     async def test_empty_dataframe(self):
-        component = BatchRunComponent(model=MockLanguageModel(), df=DataFrame({"text": []}), column_name="text")
+        component = BatchRunComponent(
+            model=MockLanguageModel(),
+            df=DataFrame({"text": []}),
+            column_name="text",
+            enable_metadata=True,
+        )
 
         result = await component.run_batch()
         assert isinstance(result, DataFrame)
         assert len(result) == 0
 
     async def test_non_string_column_conversion(self):
-        test_df = DataFrame(
-            {
-                "text": [123, 456, 789]  # Numeric values
-            }
-        )
+        test_df = DataFrame({"text": [123, 456, 789]})  # Numeric values
 
-        component = BatchRunComponent(model=MockLanguageModel(), df=test_df, column_name="text")
+        component = BatchRunComponent(
+            model=MockLanguageModel(),
+            df=test_df,
+            column_name="text",
+            enable_metadata=True,
+        )
 
         result = await component.run_batch()
 
         assert isinstance(result, DataFrame)
         assert all(isinstance(text, str) for text in result["text_input"])
         assert all(str(num) in text for num, text in zip(test_df["text"], result["text_input"], strict=False))
+        result_dicts = result.to_dict("records")
+        assert all(row["metadata"]["processing_status"] == "success" for row in result_dicts)

src/backend/tests/unit/components/logic/test_loop.py

@@ -1,14 +1,15 @@
 from uuid import UUID
 
+import orjson
 import pytest
 from httpx import AsyncClient
 from langflow.components.logic.loop import LoopComponent
 from langflow.memory import aget_messages
 from langflow.schema.data import Data
 from langflow.services.database.models.flow import FlowCreate
-from orjson import orjson
 
 from tests.base import ComponentTestBaseWithClient
+from tests.unit.build_utils import build_flow, get_build_events
 
 TEXT = (
     "lorem ipsum dolor sit amet lorem ipsum dolor sit amet lorem ipsum dolor sit amet. "
@@ -62,15 +63,25 @@ class TestLoopComponentWithAPI(ComponentTestBaseWithClient):
         assert len(messages[1].text) > 0
 
     async def test_build_flow_loop(self, client, json_loop_test, logged_in_headers):
-        # TODO: Add a test for the loop where the loop component gets updated even the component in json
+        """Test building a flow with a loop component."""
+        # Create the flow
         flow_id = await self._create_flow(client, json_loop_test, logged_in_headers)
 
-        async with client.stream("POST", f"api/v1/build/{flow_id}/flow", json={}, headers=logged_in_headers) as r:
-            async for line in r.aiter_lines():
-                # httpx split by \n, but ndjson sends two \n for each line
-                if line:
-                    # Process the line if needed
-                    pass
+        # Start the build and get job_id
+        build_response = await build_flow(client, flow_id, logged_in_headers)
+        job_id = build_response["job_id"]
+        assert job_id is not None
+
+        # Get the events stream
+        events_response = await get_build_events(client, job_id, logged_in_headers)
+        assert events_response.status_code == 200
+
+        # Process the events stream
+        async for line in events_response.aiter_lines():
+            if not line:  # Skip empty lines
+                continue
+            # Process events if needed
+            # We could add specific assertions here for loop-related events
 
         await self.check_messages(flow_id)
 

src/backend/tests/unit/components/processing/test_data_to_dataframe_component.py

@@ -0,0 +1,127 @@
+import pytest
+from langflow.components.processing.data_to_dataframe import DataToDataFrameComponent
+from langflow.schema import Data, DataFrame
+
+from tests.base import ComponentTestBaseWithoutClient
+
+
+class TestDataToDataFrameComponent(ComponentTestBaseWithoutClient):
+    @pytest.fixture
+    def component_class(self):
+        """Return the component class to test."""
+        return DataToDataFrameComponent
+
+    @pytest.fixture
+    def default_kwargs(self):
+        """Return the default kwargs for the component."""
+        return {
+            "data_list": [
+                Data(text="Row 1", data={"field1": "value1", "field2": 1}),
+                Data(text="Row 2", data={"field1": "value2", "field2": 2}),
+            ]
+        }
+
+    @pytest.fixture
+    def file_names_mapping(self):
+        """Return the file names mapping for different versions."""
+        # This is a new component, so we return an empty list
+        return []
+
+    def test_basic_setup(self, component_class, default_kwargs):
+        """Test basic component initialization."""
+        component = component_class()
+        component.set_attributes(default_kwargs)
+        assert component.data_list == default_kwargs["data_list"]
+
+    def test_build_dataframe_basic(self, component_class, default_kwargs):
+        """Test basic DataFrame construction."""
+        component = component_class()
+        component.set_attributes(default_kwargs)
+        result_df = component.build_dataframe()
+
+        assert isinstance(result_df, DataFrame)
+        assert len(result_df) == 2
+        assert list(result_df.columns) == ["field1", "field2", "text"]
+        assert result_df["text"].tolist() == ["Row 1", "Row 2"]
+        assert result_df["field1"].tolist() == ["value1", "value2"]
+        assert result_df["field2"].tolist() == [1, 2]
+
+    def test_single_data_input(self, component_class):
+        """Test handling single Data object input."""
+        single_data = Data(text="Single Row", data={"field1": "value"})
+        component = component_class()
+        component.set_attributes({"data_list": single_data})
+
+        result_df = component.build_dataframe()
+
+        assert len(result_df) == 1
+        assert result_df["text"].iloc[0] == "Single Row"
+        assert result_df["field1"].iloc[0] == "value"
+
+    def test_empty_data_list(self, component_class):
+        """Test behavior with empty data list."""
+        component = component_class()
+        component.set_attributes({"data_list": []})
+
+        result_df = component.build_dataframe()
+
+        assert len(result_df) == 0
+
+    def test_data_without_text(self, component_class):
+        """Test handling Data objects without text field."""
+        data_without_text = [Data(data={"field1": "value1"}), Data(data={"field1": "value2"})]
+        component = component_class()
+        component.set_attributes({"data_list": data_without_text})
+
+        result_df = component.build_dataframe()
+
+        assert len(result_df) == 2
+        assert "text" not in result_df.columns
+        assert result_df["field1"].tolist() == ["value1", "value2"]
+
+    def test_data_without_data_dict(self, component_class):
+        """Test handling Data objects without data dictionary."""
+        data_without_dict = [Data(text="Text 1"), Data(text="Text 2")]
+        component = component_class()
+        component.set_attributes({"data_list": data_without_dict})
+
+        result_df = component.build_dataframe()
+
+        assert len(result_df) == 2
+        assert list(result_df.columns) == ["text"]
+        assert result_df["text"].tolist() == ["Text 1", "Text 2"]
+
+    def test_mixed_data_fields(self, component_class):
+        """Test handling Data objects with different fields."""
+        mixed_data = [
+            Data(text="Row 1", data={"field1": "value1", "field2": 1}),
+            Data(text="Row 2", data={"field1": "value2", "field3": "extra"}),
+        ]
+        component = component_class()
+        component.set_attributes({"data_list": mixed_data})
+
+        result_df = component.build_dataframe()
+
+        assert len(result_df) == 2
+        assert set(result_df.columns) == {"field1", "field2", "field3", "text"}
+        assert result_df["field1"].tolist() == ["value1", "value2"]
+        assert result_df["field2"].iloc[1] != result_df["field2"].iloc[1]  # Check for NaN using inequality
+        assert result_df["field3"].iloc[0] != result_df["field3"].iloc[0]  # Check for NaN using inequality
+
+    def test_invalid_input_type(self, component_class):
+        """Test error handling for invalid input types."""
+        invalid_data = [{"not": "a Data object"}]
+        component = component_class()
+        component.set_attributes({"data_list": invalid_data})
+
+        with pytest.raises(TypeError) as exc_info:
+            component.build_dataframe()
+        assert "Expected Data objects" in str(exc_info.value)
+
+    def test_status_update(self, component_class, default_kwargs):
+        """Test that status is properly updated."""
+        component = component_class()
+        component.set_attributes(default_kwargs)
+        result = component.build_dataframe()
+
+        assert component.status is result  # Status should be set to the DataFrame

src/backend/tests/unit/components/processing/test_save_to_file_component.py

@@ -0,0 +1,165 @@
+import json
+from pathlib import Path
+from unittest.mock import MagicMock, patch
+
+import pandas as pd
+import pytest
+from langflow.components.processing.save_to_file import SaveToFileComponent
+from langflow.schema import Data, Message
+
+from tests.base import ComponentTestBaseWithoutClient
+
+
+class TestSaveToFileComponent(ComponentTestBaseWithoutClient):
+    @pytest.fixture(autouse=True)
+    def setup_and_teardown(self):
+        """Setup and teardown for each test."""
+        # Setup
+        test_files = [
+            "./test_output.csv",
+            "./test_output.xlsx",
+            "./test_output.json",
+            "./test_output.md",
+            "./test_output.txt",
+        ]
+        # Teardown
+        yield
+        # Delete test files after each test
+        for file_path in test_files:
+            path = Path(file_path)
+            if path.exists():
+                path.unlink()
+
+    @pytest.fixture
+    def component_class(self):
+        """Return the component class to test."""
+        return SaveToFileComponent
+
+    @pytest.fixture
+    def default_kwargs(self):
+        """Return the default kwargs for the component."""
+        sample_df = pd.DataFrame([{"col1": 1, "col2": "a"}, {"col1": 2, "col2": "b"}])
+        return {"input_type": "DataFrame", "df": sample_df, "file_format": "csv", "file_path": "./test_output.csv"}
+
+    @pytest.fixture
+    def file_names_mapping(self):
+        """Return the file names mapping for different versions."""
+        return []  # New component
+
+    def test_basic_setup(self, component_class, default_kwargs):
+        """Test basic component initialization."""
+        component = component_class()
+        component.set_attributes(default_kwargs)
+        assert component.input_type == "DataFrame"
+        assert component.file_format == "csv"
+        assert component.file_path == "./test_output.csv"
+
+    def test_update_build_config_dataframe(self, component_class):
+        """Test build config update for DataFrame input type."""
+        component = component_class()
+        build_config = {
+            "df": {"show": False},
+            "data": {"show": False},
+            "message": {"show": False},
+            "file_format": {"options": []},
+        }
+
+        updated_config = component.update_build_config(build_config, "DataFrame", "input_type")
+
+        assert updated_config["df"]["show"] is True
+        assert updated_config["data"]["show"] is False
+        assert updated_config["message"]["show"] is False
+        assert set(updated_config["file_format"]["options"]) == set(component.DATA_FORMAT_CHOICES)
+
+    def test_save_message(self, component_class):
+        """Test saving Message to different formats."""
+        test_cases = [
+            ("txt", "Test message"),
+            ("json", json.dumps({"message": "Test message"}, indent=2)),
+            ("markdown", "**Message:**\n\nTest message"),
+        ]
+
+        for fmt, expected_content in test_cases:
+            mock_file = MagicMock()
+            mock_parent = MagicMock()
+            mock_parent.exists.return_value = True
+            mock_file.parent = mock_parent
+            mock_file.expanduser.return_value = mock_file
+
+            # Mock Path at the module level where it's imported
+            with patch("langflow.components.processing.save_to_file.Path") as mock_path:
+                mock_path.return_value = mock_file
+
+                component = component_class()
+                component.set_attributes(
+                    {
+                        "input_type": "Message",
+                        "message": Message(text="Test message"),
+                        "file_format": fmt,
+                        "file_path": f"./test_output.{fmt}",
+                    }
+                )
+
+                result = component.save_to_file()
+
+                mock_file.write_text.assert_called_once_with(expected_content, encoding="utf-8")
+                assert "saved successfully" in result
+
+    def test_save_data(self, component_class):
+        """Test saving Data object to JSON."""
+        test_data = {"col1": ["value1"], "col2": ["value2"]}
+
+        mock_file = MagicMock()
+        mock_parent = MagicMock()
+        mock_parent.exists.return_value = True
+        mock_file.parent = mock_parent
+        mock_file.expanduser.return_value = mock_file
+
+        with patch("langflow.components.processing.save_to_file.Path") as mock_path:
+            mock_path.return_value = mock_file
+
+            component = component_class()
+            component.set_attributes(
+                {
+                    "input_type": "Data",
+                    "data": Data(data=test_data),
+                    "file_format": "json",
+                    "file_path": "./test_output.json",
+                }
+            )
+
+            result = component.save_to_file()
+
+            expected_json = json.dumps(test_data, indent=2)
+            mock_file.write_text.assert_called_once_with(expected_json, encoding="utf-8")
+            assert "saved successfully" in result
+
+    def test_directory_creation(self, component_class, default_kwargs):
+        """Test directory creation if it doesn't exist."""
+        mock_file = MagicMock()
+        mock_parent = MagicMock()
+        mock_parent.exists.return_value = False
+        mock_file.parent = mock_parent
+        mock_file.expanduser.return_value = mock_file
+
+        with patch("langflow.components.processing.save_to_file.Path") as mock_path:
+            mock_path.return_value = mock_file
+            with patch.object(pd.DataFrame, "to_csv") as mock_to_csv:
+                component = component_class()
+                component.set_attributes(default_kwargs)
+
+                result = component.save_to_file()
+
+                mock_parent.mkdir.assert_called_once_with(parents=True, exist_ok=True)
+                assert mock_to_csv.called
+                assert "saved successfully" in result
+
+    def test_invalid_input_type(self, default_kwargs):
+        """Test handling of invalid input type."""
+        component = SaveToFileComponent()
+        invalid_kwargs = default_kwargs.copy()  # Create a copy to modify
+        invalid_kwargs["input_type"] = "InvalidType"
+        component.set_attributes(invalid_kwargs)
+
+        with pytest.raises(ValueError, match="Unsupported input type"):
+            component.save_to_file()

src/backend/tests/unit/services/database/test_utils.py

@@ -1,110 +0,0 @@
-import json
-
-import pytest
-from langflow.services.database.utils import truncate_json
-
-
-@pytest.fixture
-def small_json():
-    return [
-        {"name": "Cole Ramos", "email": "egestas.fusce.aliquet@google.couk"},
-        {"name": "Chancellor Torres", "email": "lorem.eu@hotmail.com"},
-        {"name": "Deanna Lyons", "email": "neque.venenatis.lacus@outlook.couk"},
-        {"name": "Ruby O'connor", "email": "lectus.justo.eu@hotmail.couk"},
-        {"name": "Iona Dorsey", "email": "rutrum@yahoo.org"},
-    ]
-
-
-@pytest.fixture
-def large_json():
-    return [
-        {
-            "name": "Nash Briggs",
-            "phone": "1-827-252-5669",
-            "email": "magna.ut@icloud.edu",
-            "address": "847-2983 Vel Rd.",
-            "list": 5,
-            "country": "South Korea",
-            "region": "Gilgit Baltistan",
-            "postalZip": "6088-8521",
-            "text": "ipsum. Curabitur consequat, lectus sit amet luctus vulputate, nisi sem",
-            "alphanumeric": "OJG47QKX4DO",
-            "currency": "$46.88",
-            "numberrange": 6,
-        },
-        {
-            "name": "Keefe Cooley",
-            "phone": "(164) 954-5395",
-            "email": "congue.turpis.in@protonmail.ca",
-            "address": "Ap #674-3382 Egestas. St.",
-            "list": 3,
-            "country": "Spain",
-            "region": "Antioquia",
-            "postalZip": "42452",
-            "text": "nisl. Nulla eu neque pellentesque massa lobortis ultrices. Vivamus rhoncus.",
-            "alphanumeric": "FIE81ZDK2RI",
-            "currency": "$37.74",
-            "numberrange": 3,
-        },
-        {
-            "name": "Randall Booth",
-            "phone": "(762) 778-9833",
-            "email": "a@icloud.edu",
-            "address": "Ap #116-8418 Nec Ave",
-            "list": 9,
-            "country": "Norway",
-            "region": "Prince Edward Island",
-            "postalZip": "39155",
-            "text": "tempor arcu. Vestibulum ut eros non enim commodo hendrerit. Donec",
-            "alphanumeric": "GMF33SGB4XD",
-            "currency": "$87.24",
-            "numberrange": 0,
-        },
-        {
-            "name": "Aurora Mooney",
-            "phone": "(626) 435-3885",
-            "email": "morbi.sit.amet@icloud.org",
-            "address": "837-8038 Duis Rd.",
-            "list": 15,
-            "country": "United States",
-            "region": "West Sulawesi",
-            "postalZip": "84466-29328",
-            "text": "metus eu erat semper rutrum. Fusce dolor quam, elementum at,",
-            "alphanumeric": "CVK31QJA8GZ",
-            "currency": "$85.97",
-            "numberrange": 1,
-        },
-        {
-            "name": "Irma Snider",
-            "phone": "1-682-186-4584",
-            "email": "senectus.et@hotmail.org",
-            "address": "718-8593 Mauris. Avenue",
-            "list": 13,
-            "country": "Italy",
-            "region": "East Region",
-            "postalZip": "47178",
-            "text": "Cras convallis convallis dolor. Quisque tincidunt pede ac urna. Ut",
-            "alphanumeric": "KXR03TWX8QA",
-            "currency": "$65.54",
-            "numberrange": 3,
-        },
-    ]
-
-
-def test_truncate_json__small_case(small_json):
-    max_size = 400
-
-    result = truncate_json(small_json, max_size=max_size)
-
-    assert len(str(small_json)) < max_size, "small_json must be smaller than max_size"
-    assert result == small_json, "small_json should not be truncated"
-
-
-def test_truncate_json__large_case(large_json):
-    max_size = 1000
-
-    result = truncate_json(large_json, max_size=max_size)
-
-    assert len(str(large_json)) > max_size, "large_json must be larger than max_size"
-    assert len(str(result)) < len(str(large_json)), "result must be smaller than large_json"
-    assert json.dumps(result), "result must be a valid JSON object"

src/backend/tests/unit/test_chat_endpoint.py

@@ -1,42 +1,63 @@
-import json
+import asyncio
+import uuid
 from uuid import UUID
 
 import pytest
+from httpx import codes
 from langflow.memory import aget_messages
-from langflow.services.database.models.flow import FlowCreate, FlowUpdate
-from orjson import orjson
+from langflow.services.database.models.flow import FlowUpdate
+
+from tests.unit.build_utils import build_flow, consume_and_assert_stream, create_flow, get_build_events
 
 
 @pytest.mark.benchmark
 async def test_build_flow(client, json_memory_chatbot_no_llm, logged_in_headers):
-    flow_id = await _create_flow(client, json_memory_chatbot_no_llm, logged_in_headers)
+    """Test the build flow endpoint with the new two-step process."""
+    # First create the flow
+    flow_id = await create_flow(client, json_memory_chatbot_no_llm, logged_in_headers)
 
-    async with client.stream("POST", f"api/v1/build/{flow_id}/flow", json={}, headers=logged_in_headers) as r:
-        await consume_and_assert_stream(r)
+    # Start the build and get job_id
+    build_response = await build_flow(client, flow_id, logged_in_headers)
+    job_id = build_response["job_id"]
+    assert job_id is not None
 
-    await check_messages(flow_id)
+    # Get the events stream
+    events_response = await get_build_events(client, job_id, logged_in_headers)
+    assert events_response.status_code == codes.OK
+
+    # Consume and verify the events
+    await consume_and_assert_stream(events_response, job_id)
 
 
 @pytest.mark.benchmark
 async def test_build_flow_from_request_data(client, json_memory_chatbot_no_llm, logged_in_headers):
-    flow_id = await _create_flow(client, json_memory_chatbot_no_llm, logged_in_headers)
-    response = await client.get("api/v1/flows/" + str(flow_id), headers=logged_in_headers)
+    """Test building a flow from request data."""
+    flow_id = await create_flow(client, json_memory_chatbot_no_llm, logged_in_headers)
+    response = await client.get(f"api/v1/flows/{flow_id}", headers=logged_in_headers)
     flow_data = response.json()
 
-    async with client.stream(
-        "POST", f"api/v1/build/{flow_id}/flow", json={"data": flow_data["data"]}, headers=logged_in_headers
-    ) as r:
-        await consume_and_assert_stream(r)
+    # Start the build and get job_id
+    build_response = await build_flow(client, flow_id, logged_in_headers, json={"data": flow_data["data"]})
+    job_id = build_response["job_id"]
 
+    # Get the events stream
+    events_response = await get_build_events(client, job_id, logged_in_headers)
+    assert events_response.status_code == codes.OK
+
+    # Consume and verify the events
+    await consume_and_assert_stream(events_response, job_id)
     await check_messages(flow_id)
 
 
 async def test_build_flow_with_frozen_path(client, json_memory_chatbot_no_llm, logged_in_headers):
-    flow_id = await _create_flow(client, json_memory_chatbot_no_llm, logged_in_headers)
+    """Test building a flow with a frozen path."""
+    flow_id = await create_flow(client, json_memory_chatbot_no_llm, logged_in_headers)
 
-    response = await client.get("api/v1/flows/" + str(flow_id), headers=logged_in_headers)
+    response = await client.get(f"api/v1/flows/{flow_id}", headers=logged_in_headers)
     flow_data = response.json()
     flow_data["data"]["nodes"][0]["data"]["node"]["frozen"] = True
+
+    # Update the flow with frozen path
     response = await client.patch(
         f"api/v1/flows/{flow_id}",
         json=FlowUpdate(name="Flow", description="description", data=flow_data["data"]).model_dump(),
@@ -44,151 +65,131 @@ async def test_build_flow_with_frozen_path(client, json_memory_chatbot_no_llm, l
     )
     response.raise_for_status()
 
-    async with client.stream("POST", f"api/v1/build/{flow_id}/flow", json={}, headers=logged_in_headers) as r:
-        await consume_and_assert_stream(r)
+    # Start the build and get job_id
+    build_response = await build_flow(client, flow_id, logged_in_headers)
+    job_id = build_response["job_id"]
 
+    # Get the events stream
+    events_response = await get_build_events(client, job_id, logged_in_headers)
+    assert events_response.status_code == codes.OK
+
+    # Consume and verify the events
+    await consume_and_assert_stream(events_response, job_id)
     await check_messages(flow_id)
 
 
 async def check_messages(flow_id):
-    messages = await aget_messages(flow_id=UUID(flow_id), order="ASC")
+    if isinstance(flow_id, str):
+        flow_id = UUID(flow_id)
+    messages = await aget_messages(flow_id=flow_id, order="ASC")
+    flow_id_str = str(flow_id)
     assert len(messages) == 2
-    assert messages[0].session_id == flow_id
+    assert messages[0].session_id == flow_id_str
     assert messages[0].sender == "User"
     assert messages[0].sender_name == "User"
     assert messages[0].text == ""
-    assert messages[1].session_id == flow_id
+    assert messages[1].session_id == flow_id_str
     assert messages[1].sender == "Machine"
     assert messages[1].sender_name == "AI"
 
 
-async def consume_and_assert_stream(r):
-    count = 0
-    async for line in r.aiter_lines():
-        # httpx split by \n, but ndjson sends two \n for each line
-        if not line:
-            continue
-        parsed = json.loads(line)
-        if count == 0:
-            assert parsed["event"] == "vertices_sorted"
-            ids = parsed["data"]["ids"]
-            ids.sort()
-            assert ids == ["ChatInput-CIGht"]
-
-            to_run = parsed["data"]["to_run"]
-            to_run.sort()
-            assert to_run == ["ChatInput-CIGht", "ChatOutput-QA7ej", "Memory-amN4Z", "Prompt-iWbCC"]
-        elif count > 0 and count < 5:
-            assert parsed["event"] == "end_vertex"
-            assert parsed["data"]["build_data"] is not None
-        elif count == 5:
-            assert parsed["event"] == "end"
-        else:
-            msg = f"Unexpected line: {line}"
-            raise ValueError(msg)
-        count += 1
+@pytest.mark.benchmark
+async def test_build_flow_invalid_job_id(client, logged_in_headers):
+    """Test getting events for an invalid job ID."""
+    invalid_job_id = str(uuid.uuid4())
+    response = await get_build_events(client, invalid_job_id, logged_in_headers)
+    assert response.status_code == codes.NOT_FOUND
+    assert "No queue found for job_id" in response.json()["detail"]
 
 
-async def _create_flow(client, json_memory_chatbot_no_llm, logged_in_headers):
-    vector_store = orjson.loads(json_memory_chatbot_no_llm)
-    data = vector_store["data"]
-    vector_store = FlowCreate(name="Flow", description="description", data=data, endpoint_name="f")
-    response = await client.post("api/v1/flows/", json=vector_store.model_dump(), headers=logged_in_headers)
-    response.raise_for_status()
-    return response.json()["id"]
+@pytest.mark.benchmark
+async def test_build_flow_invalid_flow_id(client, logged_in_headers):
+    """Test starting a build with an invalid flow ID."""
+    invalid_flow_id = uuid.uuid4()
+    response = await client.post(f"api/v1/build/{invalid_flow_id}/flow", json={}, headers=logged_in_headers)
+    assert response.status_code == codes.NOT_FOUND
 
 
-# TODO: Fix this test
-# async def test_multiple_runs_with_no_payload_generate_max_vertex_builds(
-#     client, json_memory_chatbot_no_llm, logged_in_headers
-# ):
-#     """Test that multiple builds of a flow generate the correct number of vertex builds."""
-#     # Create the initial flow
-#     flow_id = await _create_flow(client, json_memory_chatbot_no_llm, logged_in_headers)
+@pytest.mark.benchmark
+async def test_build_flow_start_only(client, json_memory_chatbot_no_llm, logged_in_headers):
+    """Test only the build flow start endpoint."""
+    # First create the flow
+    flow_id = await create_flow(client, json_memory_chatbot_no_llm, logged_in_headers)
 
-#     # Get the flow data to count nodes before making requests
-#     response = await client.get(f"api/v1/flows/{flow_id}", headers=logged_in_headers)
-#     flow_data = response.json()
-#     num_nodes = len(flow_data["data"]["nodes"])
-#     max_vertex_builds = get_settings_service().settings.max_vertex_builds_per_vertex
+    # Start the build and get job_id
+    build_response = await build_flow(client, flow_id, logged_in_headers)
 
-#     logger.debug(f"Starting test with {num_nodes} nodes, max_vertex_builds={max_vertex_builds}")
+    # Assert response structure
+    assert "job_id" in build_response
+    assert isinstance(build_response["job_id"], str)
+    # Verify it's a valid UUID
+    assert uuid.UUID(build_response["job_id"])
 
-#     # Make multiple build requests - ensure we exceed max_vertex_builds significantly
-#     num_requests = max_vertex_builds * 3  # Triple the max to ensure rotation
-#     for i in range(num_requests):
-#         # Generate a random session ID for each request
-#         session_id = session_id_generator()
-#         payload = {"inputs": {"session": session_id, "type": "chat", "input_value": f"Test message {i + 1}"}}
 
-#         async with client.stream("POST", f"api/v1/build/{flow_id}/flow",
-# json=payload, headers=logged_in_headers) as r:
-#             await consume_and_assert_stream(r)
+@pytest.mark.benchmark
+async def test_build_flow_start_with_inputs(client, json_memory_chatbot_no_llm, logged_in_headers):
+    """Test the build flow start endpoint with input data."""
+    flow_id = await create_flow(client, json_memory_chatbot_no_llm, logged_in_headers)
 
-#         # Add a small delay between requests to ensure proper ordering
-#         await asyncio.sleep(0.1)
+    # Start build with some input data
+    test_inputs = {"inputs": {"session": "test_session", "input_value": "test message"}}
 
-#         # Track builds after each request
-#         async with session_scope() as session:
-#             builds = await get_vertex_builds_by_flow_id(db=session, flow_id=flow_id)
-#             by_vertex = {}
-#             for build in builds:
-#                 build_dict = build.model_dump()
-#                 vertex_id = build_dict.get("id")
-#                 by_vertex.setdefault(vertex_id, []).append(build_dict)
+    build_response = await build_flow(client, flow_id, logged_in_headers, json=test_inputs)
 
-#             # Log state of each vertex with more details
-#             for vertex_id, vertex_builds in by_vertex.items():
-#                 vertex_builds.sort(key=lambda x: x.get("timestamp"))
-#                 logger.debug(
-#                     f"Request {i + 1} (session={session_id}) - Vertex {vertex_id}: {len(vertex_builds)} builds "
-#                     f"(max allowed: {max_vertex_builds}), "
-#                     f"build_ids: {[b.get('build_id') for b in vertex_builds]}"
-#                 )
+    assert "job_id" in build_response
+    assert isinstance(build_response["job_id"], str)
+    assert uuid.UUID(build_response["job_id"])
 
-#     # Wait a bit before final verification to ensure all DB operations complete
-#     await asyncio.sleep(0.5)
 
-#     # Final verification with detailed logging
-#     async with session_scope() as session:
-#         vertex_builds = await get_vertex_builds_by_flow_id(db=session, flow_id=flow_id)
-#         assert len(vertex_builds) > 0, "No vertex builds found"
+@pytest.mark.benchmark
+async def test_build_flow_polling(client, json_memory_chatbot_no_llm, logged_in_headers):
+    """Test the build flow endpoint with polling (non-streaming)."""
+    # First create the flow
+    flow_id = await create_flow(client, json_memory_chatbot_no_llm, logged_in_headers)
 
-#         builds_by_vertex = {}
-#         for build in vertex_builds:
-#             build_dict = build.model_dump()
-#             vertex_id = build_dict.get("id")
-#             builds_by_vertex.setdefault(vertex_id, []).append(build_dict)
+    # Start the build and get job_id
+    build_response = await build_flow(client, flow_id, logged_in_headers)
+    job_id = build_response["job_id"]
+    assert job_id is not None
 
-#         # Log detailed final state
-#         logger.debug(f"\nFinal state after {num_requests} requests:")
-#         for vertex_id, builds in builds_by_vertex.items():
-#             builds.sort(key=lambda x: x.get("timestamp"))
-#             logger.debug(
-#                 f"Vertex {vertex_id}: {len(builds)} builds "
-#                 f"(oldest: {builds[0].get('timestamp')}, "
-#                 f"newest: {builds[-1].get('timestamp')}), "
-#                 f"build_ids: {[b.get('build_id') for b in builds]}"
-#             )
+    # Create a response object that mimics a streaming response but uses polling
+    class PollingResponse:
+        def __init__(self, client, job_id, headers):
+            self.client = client
+            self.job_id = job_id
+            self.headers = headers
+            self.status_code = codes.OK
 
-#             # Log individual build details for debugging
-#             for build in builds:
-#                 logger.debug(
-#                     f"  - Build {build.get('build_id')}: timestamp={build.get('timestamp')}, "
-#                     f"valid={build.get('valid')}"
-#                 )
+        async def aiter_lines(self):
+            try:
+                sleeps = 0
+                max_sleeps = 100
+                while True:
+                    response = await self.client.get(
+                        f"api/v1/build/{self.job_id}/events?stream=false", headers=self.headers
+                    )
+                    assert response.status_code == codes.OK
+                    data = response.json()
 
-#         # Verify each vertex has correct number of builds
-#         for vertex_id, vertex_builds_list in builds_by_vertex.items():
-#             assert len(vertex_builds_list) == max_vertex_builds, (
-#                 f"Vertex {vertex_id} has {len(vertex_builds_list)} builds, expected {max_vertex_builds}"
-#             )
+                    if data["event"] is None:
+                        # No event available, add delay to prevent tight polling
+                        await asyncio.sleep(0.1)
+                        sleeps += 1
+                        continue
 
-#         # Verify total number of builds
-#         total_builds = len(vertex_builds)
-#         expected_total = max_vertex_builds * num_nodes
-#         assert total_builds == expected_total, (
-#             f"Total builds ({total_builds}) doesn't match expected "
-#             f"({max_vertex_builds} builds/vertex * {num_nodes} nodes = {expected_total})"
-#         )
-#         assert all(vertex_build.get("valid") for vertex_build in vertex_builds)
+                    yield data["event"]
+
+                    # If this was the end event, stop polling
+                    if '"end"' in data["event"]:
+                        break
+                    if sleeps > max_sleeps:
+                        msg = "Build event polling timed out."
+                        raise TimeoutError(msg)
+            except asyncio.TimeoutError as e:
+                msg = "Build event polling timed out."
+                raise TimeoutError(msg) from e
+
+    polling_response = PollingResponse(client, job_id, logged_in_headers)
+
+    # Use the same consume_and_assert_stream function to verify the events
+    await consume_and_assert_stream(polling_response, job_id)

src/frontend/package-lock.json

@@ -46,7 +46,7 @@
         "class-variance-authority": "^0.7.0",
         "clsx": "^2.1.1",
         "cmdk": "^1.0.0",
-        "dompurify": "^3.1.5",
+        "dompurify": "^3.2.4",
         "dotenv": "^16.4.5",
         "elkjs": "^0.9.3",
         "emoji-regex": "^10.3.0",
@@ -7348,9 +7348,10 @@
       }
     },
     "node_modules/dompurify": {
-      "version": "3.2.3",
-      "resolved": "https://registry.npmjs.org/dompurify/-/dompurify-3.2.3.tgz",
-      "integrity": "sha512-U1U5Hzc2MO0oW3DF+G9qYN0aT7atAou4AgI0XjWz061nyBPbdxkfdhfy5uMgGn6+oLFCfn44ZGbdDqCzVmlOWA==",
+      "version": "3.2.4",
+      "resolved": "https://registry.npmjs.org/dompurify/-/dompurify-3.2.4.tgz",
+      "integrity": "sha512-ysFSFEDVduQpyhzAob/kkuJjf5zWkZD8/A9ywSp1byueyuCfHamrCBa14/Oc2iiB0e51B+NpxSl5gmzn+Ms/mg==",
+      "license": "(MPL-2.0 OR Apache-2.0)",
       "optionalDependencies": {
         "@types/trusted-types": "^2.0.7"
       }

src/frontend/package.json

@@ -41,7 +41,7 @@
     "class-variance-authority": "^0.7.0",
     "clsx": "^2.1.1",
     "cmdk": "^1.0.0",
-    "dompurify": "^3.1.5",
+    "dompurify": "^3.2.4",
     "dotenv": "^16.4.5",
     "elkjs": "^0.9.3",
     "emoji-regex": "^10.3.0",

src/frontend/src/App.css

@@ -66,8 +66,6 @@ body {
 }
 
 .jv-indent {
-  overflow-y: auto !important;
-  max-height: 310px !important;
   border-radius: 10px;
 }
 

src/frontend/src/CustomEdges/index.tsx

@@ -21,8 +21,8 @@ export function DefaultEdge({
   const targetHandleObject = scapeJSONParse(targetHandleId!);
 
   const sourceXNew =
-    (sourceNode?.position.x ?? 0) + (sourceNode?.measured?.width ?? 0);
-  const targetXNew = targetNode?.position.x ?? 0;
+    (sourceNode?.position.x ?? 0) + (sourceNode?.measured?.width ?? 0) + 7;
+  const targetXNew = (targetNode?.position.x ?? 0) - 7;
 
   const distance = 200 + 0.1 * ((sourceXNew - targetXNew) / 2);
 
@@ -42,15 +42,18 @@ export function DefaultEdge({
     200 * (1 - zeroOnNegative) +
     0.3 * Math.abs(sourceY - targetY) * zeroOnNegative;
 
-  const edgePathLoop = `M ${sourceXNew} ${sourceY} C ${sourceXNew + distance} ${sourceY + sourceDistanceY}, ${targetXNew - distance} ${targetY + distanceY}, ${targetXNew} ${targetY}`;
+  const targetYNew = targetY + 1;
+  const sourceYNew = sourceY + 1;
+
+  const edgePathLoop = `M ${sourceXNew} ${sourceYNew} C ${sourceXNew + distance} ${sourceYNew + sourceDistanceY}, ${targetXNew - distance} ${targetYNew + distanceY}, ${targetXNew} ${targetYNew}`;
 
   const [edgePath] = getBezierPath({
     sourceX: sourceXNew,
-    sourceY,
+    sourceY: sourceYNew,
     sourcePosition: Position.Right,
     targetPosition: Position.Left,
     targetX: targetXNew,
-    targetY,
+    targetY: targetYNew,
   });
 
   return (