Bump infinity to 0.6.2 (#10887)

### What problem does this PR solve?

Bump infinity to 0.6.2
https://github.com/infiniflow/infinity/issues/3052

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

agent/templates/advanced_ingestion_pipeline.json

@@ -2,10 +2,12 @@
     "id": 23,
     "title": {
         "en": "Advanced Ingestion Pipeline",
+        "de": "Erweiterte Ingestion Pipeline",
         "zh": "编排复杂的 Ingestion Pipeline"
     },
     "description": {
         "en": "This template demonstrates how to use an LLM to generate summaries, keywords, Q&A, and metadata for each chunk to support diverse retrieval needs.",
+        "de": "Diese Vorlage demonstriert, wie ein LLM verwendet wird, um Zusammenfassungen, Schlüsselwörter, Fragen & Antworten und Metadaten für jedes Segment zu generieren, um vielfältige Abrufanforderungen zu unterstützen.",
         "zh": "此模板演示如何利用大模型为切片生成摘要、关键词、问答及元数据，以满足多样化的召回需求。"
     },
     "canvas_type": "Ingestion Pipeline",

agent/templates/chunk_summary.json

@@ -2,10 +2,12 @@
     "id": 24,
     "title": {
         "en": "Chunk Summary",
+        "de": "Segmentzusammenfassung",
         "zh": "总结切片"
     },
     "description": {
         "en": "This template uses an LLM to generate chunk summaries for building text and vector indexes. During retrieval, summaries enhance matching, and the original chunks are returned as results.",
+        "de": "Diese Vorlage nutzt ein LLM zur Generierung von Segmentzusammenfassungen für den Aufbau von Text- und Vektorindizes. Bei der Abfrage verbessern die Zusammenfassungen die Übereinstimmung, während die ursprünglichen Segmente als Ergebnisse zurückgegeben werden.",
         "zh": "此模板利用大模型生成切片摘要，并据此建立全文索引与向量。检索时以摘要提升匹配效果，最终召回对应的原文切片。"
     },
     "canvas_type": "Ingestion Pipeline",

agent/templates/generate_SEO_blog.json

@@ -2,9 +2,11 @@
     "id": 8,
     "title": {
         "en": "Generate SEO Blog",
+        "de": "SEO Blog generieren",
         "zh": "生成SEO博客"},
     "description": {
         "en": "This is a multi-agent version of the SEO blog generation workflow. It simulates a small team of AI “writers”, where each agent plays a specialized role — just like a real editorial team.",
+        "de": "Dies ist eine Multi-Agenten-Version des Workflows zur Erstellung von SEO-Blogs. Sie simuliert ein kleines Team von KI-„Autoren“, in dem jeder Agent eine spezielle Rolle übernimmt – genau wie in einem echten Redaktionsteam.",
         "zh": "多智能体架构可根据简单的用户输入自动生成完整的SEO博客文章。模拟小型“作家”团队，其中每个智能体扮演一个专业角色——就像真正的编辑团队。"},
     "canvas_type": "Agent",
     "dsl": {

agent/templates/knowledge_base_report.json

@@ -2,9 +2,11 @@
     "id": 20,
     "title": {
         "en": "Report Agent Using Knowledge Base",
+        "de": "Berichtsagent mit Wissensdatenbank",
         "zh": "知识库检索智能体"},
     "description": {
         "en": "A report generation assistant using local knowledge base, with advanced capabilities in task planning, reasoning, and reflective analysis. Recommended for academic research paper Q&A",
+        "de": "Ein Berichtsgenerierungsassistent, der eine lokale Wissensdatenbank nutzt, mit erweiterten Fähigkeiten in Aufgabenplanung, Schlussfolgerung und reflektierender Analyse. Empfohlen für akademische Forschungspapier-Fragen und -Antworten.",
         "zh": "一个使用本地知识库的报告生成助手，具备高级能力，包括任务规划、推理和反思性分析。推荐用于学术研究论文问答。"},
     "canvas_type": "Agent",
     "dsl": {

agent/templates/knowledge_base_report_r.json

@@ -1,10 +1,12 @@
 {
     "id": 21,
     "title": {
-        "en": "Report Agent Using Knowledge Base", 
+        "en": "Report Agent Using Knowledge Base",
+        "de": "Berichtsagent mit Wissensdatenbank",
         "zh": "知识库检索智能体"},
     "description": {
         "en": "A report generation assistant using local knowledge base, with advanced capabilities in task planning, reasoning, and reflective analysis. Recommended for academic research paper Q&A",
+        "de": "Ein Berichtsgenerierungsassistent, der eine lokale Wissensdatenbank nutzt, mit erweiterten Fähigkeiten in Aufgabenplanung, Schlussfolgerung und reflektierender Analyse. Empfohlen für akademische Forschungspapier-Fragen und -Antworten.",
         "zh": "一个使用本地知识库的报告生成助手，具备高级能力，包括任务规划、推理和反思性分析。推荐用于学术研究论文问答。"},
     "canvas_type": "Recommended",
     "dsl": {

agent/templates/market_generate_seo_blog.json

@@ -2,9 +2,11 @@
     "id": 12,
     "title": {
         "en": "Generate SEO Blog",
+        "de": "SEO Blog generieren",
         "zh": "生成SEO博客"},
     "description": {
-        "en": "This workflow automatically generates a complete SEO-optimized blog article based on a simple user input. You don’t need any writing experience. Just provide a topic or short request — the system will handle the rest.",
+        "en": "This workflow automatically generates a complete SEO-optimized blog article based on a simple user input. You don't need any writing experience. Just provide a topic or short request — the system will handle the rest.",
+        "de": "Dieser Workflow generiert automatisch einen vollständigen SEO-optimierten Blogartikel basierend auf einer einfachen Benutzereingabe. Sie benötigen keine Schreiberfahrung. Geben Sie einfach ein Thema oder eine kurze Anfrage ein – das System übernimmt den Rest.",
         "zh": "此工作流根据简单的用户输入自动生成完整的SEO博客文章。你无需任何写作经验，只需提供一个主题或简短请求，系统将处理其余部分。"},
     "canvas_type": "Marketing",
     "dsl": {
@@ -916,4 +918,4 @@
             "retrieval": []
         },
     "avatar": "data:image/jpeg;base64,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"
-}
+}

agent/templates/seo_blog.json

@@ -2,9 +2,11 @@
     "id": 4,
     "title": {
         "en": "Generate SEO Blog",
+        "de": "SEO Blog generieren",
         "zh": "生成SEO博客"},
     "description": {
-        "en": "This workflow automatically generates a complete SEO-optimized blog article based on a simple user input. You don’t need any writing experience. Just provide a topic or short request — the system will handle the rest.",
+        "en": "This workflow automatically generates a complete SEO-optimized blog article based on a simple user input. You don't need any writing experience. Just provide a topic or short request — the system will handle the rest.",
+        "de": "Dieser Workflow generiert automatisch einen vollständigen SEO-optimierten Blogartikel basierend auf einer einfachen Benutzereingabe. Sie benötigen keine Schreiberfahrung. Geben Sie einfach ein Thema oder eine kurze Anfrage ein – das System übernimmt den Rest.",
         "zh": "此工作流根据简单的用户输入自动生成完整的SEO博客文章。你无需任何写作经验，只需提供一个主题或简短请求，系统将处理其余部分。"},
     "canvas_type": "Recommended",
     "dsl": {
@@ -916,4 +918,4 @@
             "retrieval": []
         },
     "avatar": "data:image/jpeg;base64,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"
-}
+}

agent/templates/sql_assistant.json

@@ -2,10 +2,12 @@
     "id": 17,
     "title": {
         "en": "SQL Assistant",
+        "de": "SQL Assistent",
         "zh": "SQL助理"},
     "description": {
-        "en": "SQL Assistant is an AI-powered tool that lets business users turn plain-English questions into fully formed SQL queries. Simply type your question (e.g., “Show me last quarter’s top 10 products by revenue”) and SQL Assistant generates the exact SQL, runs it against your database, and returns the results in seconds. ",
-        "zh": "用户能够将简单文本问题转化为完整的SQL查询并输出结果。只需输入您的问题（例如，“展示上个季度前十名按收入排序的产品”），SQL助理就会生成精确的SQL语句，对其运行您的数据库，并几秒钟内返回结果。"},
+        "en": "SQL Assistant is an AI-powered tool that lets business users turn plain-English questions into fully formed SQL queries. Simply type your question (e.g., 'Show me last quarter's top 10 products by revenue') and SQL Assistant generates the exact SQL, runs it against your database, and returns the results in seconds. ",
+        "de": "SQL-Assistent ist ein KI-gestütztes Tool, mit dem Geschäftsanwender einfache englische Fragen in vollständige SQL-Abfragen umwandeln können. Geben Sie einfach Ihre Frage ein (z.B. 'Zeige mir die Top 10 Produkte des letzten Quartals nach Umsatz') und der SQL-Assistent generiert das exakte SQL, führt es gegen Ihre Datenbank aus und liefert die Ergebnisse in Sekunden.",
+        "zh": "用户能够将简单文本问题转化为完整的SQL查询并输出结果。只需输入您的问题（例如，展示上个季度前十名按收入排序的产品），SQL助理就会生成精确的SQL语句，对其运行您的数据库，并几秒钟内返回结果。"},
     "canvas_type": "Marketing",
     "dsl": {
             "components": {
@@ -713,4 +715,4 @@
             "retrieval": []
         },
     "avatar": "data:image/jpeg;base64,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"
-}
+}

agent/templates/title_chunker.json

@@ -2,10 +2,12 @@
     "id": 25,
     "title": {
         "en": "Title Chunker",
+        "de": "Titel basierte Segmentierung",
         "zh": "标题切片"
     },
     "description": {
         "en": "This template slices the parsed file based on its title structure. It is ideal for documents with well-defined headings, such as product manuals, legal contracts, research reports, and academic papers.",
+        "de": "Diese Vorlage segmentiert die geparste Datei basierend auf ihrer Titelstruktur. Sie eignet sich ideal für Dokumente mit klar definierten Überschriften, wie Produkthandbücher, Verträge, Forschungsberichte und wissenschaftliche Arbeiten.",
         "zh": "此模板将解析后的文件按标题结构进行切片，适用于具有清晰标题层级的文档类型，如产品手册、合同法规、研究报告和学术论文等。"
     },
     "canvas_type": "Ingestion Pipeline",

api/apps/api_app.py

@@ -59,7 +59,7 @@ def new_token():
             return get_data_error_result(message="Tenant not found!")
 
         tenant_id = tenants[0].tenant_id
-        obj = {"tenant_id": tenant_id, "token": generate_confirmation_token(tenant_id),
+        obj = {"tenant_id": tenant_id, "token": generate_confirmation_token(),
                "create_time": current_timestamp(),
                "create_date": datetime_format(datetime.now()),
                "update_time": None,
@@ -868,7 +868,7 @@ def retrieval():
     similarity_threshold = float(req.get("similarity_threshold", 0.2))
     vector_similarity_weight = float(req.get("vector_similarity_weight", 0.3))
     top = int(req.get("top_k", 1024))
-    highlight = bool(req.get("highlight", False)) 
+    highlight = bool(req.get("highlight", False))
 
     try:
         kbs = KnowledgebaseService.get_by_ids(kb_ids)

api/apps/system_app.py

@@ -217,8 +217,8 @@ def new_token():
         tenant_id = [tenant for tenant in tenants if tenant.role == 'owner'][0].tenant_id
         obj = {
             "tenant_id": tenant_id,
-            "token": generate_confirmation_token(tenant_id),
-            "beta": generate_confirmation_token(generate_confirmation_token(tenant_id)).replace("ragflow-", "")[:32],
+            "token": generate_confirmation_token(),
+            "beta": generate_confirmation_token().replace("ragflow-", "")[:32],
             "create_time": current_timestamp(),
             "create_date": datetime_format(datetime.now()),
             "update_time": None,
@@ -274,7 +274,7 @@ def token_list():
         objs = [o.to_dict() for o in objs]
         for o in objs:
             if not o["beta"]:
-                o["beta"] = generate_confirmation_token(generate_confirmation_token(tenants[0].tenant_id)).replace(
+                o["beta"] = generate_confirmation_token().replace(
                     "ragflow-", "")[:32]
                 APITokenService.filter_update([APIToken.tenant_id == tenant_id, APIToken.token == o["token"]], o)
         return get_json_result(data=objs)

api/utils/api_utils.py

@@ -43,7 +43,6 @@ from flask_login import current_user
 from flask import (
     request as flask_request,
 )
-from itsdangerous import URLSafeTimedSerializer
 from peewee import OperationalError
 from werkzeug.http import HTTP_STATUS_CODES
 
@@ -52,7 +51,6 @@ from api.constants import REQUEST_MAX_WAIT_SEC, REQUEST_WAIT_SEC
 from api.db import ActiveEnum
 from api.db.db_models import APIToken
 from api.utils.json_encode import CustomJSONEncoder, json_dumps
-from api.utils import get_uuid
 from rag.utils.mcp_tool_call_conn import MCPToolCallSession, close_multiple_mcp_toolcall_sessions
 
 requests.models.complexjson.dumps = functools.partial(json.dumps, cls=CustomJSONEncoder)
@@ -410,9 +408,9 @@ def get_error_operating_result(message="Operating error"):
     return get_result(code=settings.RetCode.OPERATING_ERROR, message=message)
 
 
-def generate_confirmation_token(tenant_id):
-    serializer = URLSafeTimedSerializer(tenant_id)
-    return "ragflow-" + serializer.dumps(get_uuid(), salt=tenant_id)[2:34]
+def generate_confirmation_token():
+    import secrets
+    return "ragflow-" + secrets.token_urlsafe(32)
 
 
 def get_parser_config(chunk_method, parser_config):

docker/.env

@@ -99,8 +99,11 @@ REDIS_PASSWORD=infini_rag_flow
 
 # The port used to expose RAGFlow's HTTP API service to the host machine,
 # allowing EXTERNAL access to the service running inside the Docker container.
+SVR_WEB_HTTP_PORT=80
+SVR_WEB_HTTPS_PORT=443
 SVR_HTTP_PORT=9380
 ADMIN_SVR_HTTP_PORT=9381
+SVR_MCP_PORT=9382
 
 # The RAGFlow Docker image to download. v0.22+ doesn't include embedding models.
 # Defaults to the v0.21.1-slim edition, which is the RAGFlow Docker image without embedding models.

docker/docker-compose-base.yml

@@ -72,7 +72,7 @@ services:
   infinity:
     profiles:
       - infinity
-    image: infiniflow/infinity:v0.6.1
+    image: infiniflow/infinity:v0.6.2
     volumes:
       - infinity_data:/var/infinity
       - ./infinity_conf.toml:/infinity_conf.toml

docker/infinity_conf.toml

@@ -1,5 +1,5 @@
 [general]
-version                  = "0.6.1"
+version                  = "0.6.2"
 time_zone                = "utc-8"
 
 [network]

helm/values.yaml

@@ -96,7 +96,7 @@ ragflow:
 infinity:
   image:
     repository: infiniflow/infinity
-    tag: v0.6.1
+    tag: v0.6.2
     pullPolicy: IfNotPresent
     pullSecrets: []
   storage:

pyproject.toml

@@ -46,7 +46,7 @@ dependencies = [
     "html-text==0.6.2",
     "httpx[socks]>=0.28.1,<0.29.0",
     "huggingface-hub>=0.25.0,<0.26.0",
-    "infinity-sdk==0.6.1",
+    "infinity-sdk==0.6.2",
     "infinity-emb>=0.0.66,<0.0.67",
     "itsdangerous==2.1.2",
     "json-repair==0.35.0",

rag/utils/redis_conn.py

@@ -71,16 +71,21 @@ class RedisDB:
 
     def __open__(self):
         try:
-            self.REDIS = redis.StrictRedis(
-                host=self.config["host"].split(":")[0],
-                port=int(self.config.get("host", ":6379").split(":")[1]),
-                db=int(self.config.get("db", 1)),
-                password=self.config.get("password"),
-                decode_responses=True,
-            )
+            conn_params = {
+                "host": self.config["host"].split(":")[0],
+                "port": int(self.config.get("host", ":6379").split(":")[1]),
+                "db": int(self.config.get("db", 1)),
+                "decode_responses": True,
+            }
+            password = self.config.get("password")
+            if password:
+                conn_params["password"] = password
+
+            self.REDIS = redis.StrictRedis(**conn_params)
+
             self.register_scripts()
-        except Exception:
-            logging.warning("Redis can't be connected.")
+        except Exception as e:
+            logging.warning(f"Redis can't be connected. Error: {str(e)}")
         return self.REDIS
 
     def health(self):

uv.lock

@@ -2654,7 +2654,7 @@ wheels = [
 
 [[package]]
 name = "infinity-sdk"
-version = "0.6.1"
+version = "0.6.2"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
 dependencies = [
     { name = "numpy" },
@@ -2671,7 +2671,7 @@ dependencies = [
     { name = "thrift" },
 ]
 wheels = [
-    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/44/0e/7a596a41a79d15bb6c87e76862aa287bb98243a40fa7a31096b57df01613/infinity_sdk-0.6.1-py3-none-any.whl", hash = "sha256:b9cb1f7fee28569de8b763c353aa299fa141af70e67ceadc70562c84237229e4", size = 75260, upload-time = "2025-10-21T13:11:06.265Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/b3/bc/3b8404a1aa5732bdcfbb1026bfc2a944cba8b7f810c420cde8e7b14be91b/infinity_sdk-0.6.2-py3-none-any.whl", hash = "sha256:29d3e7fa4152a5d959a70539ca1a15ad4c00162b6d6d1da4a8766b9d05879874", size = 75263, upload-time = "2025-10-29T15:07:10.682Z" },
 ]
 
 [[package]]
@@ -3724,12 +3724,12 @@ name = "onnxruntime-gpu"
 version = "1.19.2"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
 dependencies = [
-    { name = "coloredlogs" },
-    { name = "flatbuffers" },
-    { name = "numpy" },
-    { name = "packaging" },
-    { name = "protobuf" },
-    { name = "sympy" },
+    { name = "coloredlogs", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "flatbuffers", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "numpy", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "packaging", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "protobuf", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "sympy", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
 ]
 wheels = [
     { url = "https://pypi.tuna.tsinghua.edu.cn/packages/d0/9c/3fa310e0730643051eb88e884f19813a6c8b67d0fbafcda610d960e589db/onnxruntime_gpu-1.19.2-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a49740e079e7c5215830d30cde3df792e903df007aa0b0fd7aa797937061b27a", size = 226178508, upload-time = "2024-09-04T06:43:40.83Z" },
@@ -5385,7 +5385,7 @@ requires-dist = [
     { name = "httpx", extras = ["socks"], specifier = ">=0.28.1,<0.29.0" },
     { name = "huggingface-hub", specifier = ">=0.25.0,<0.26.0" },
     { name = "infinity-emb", specifier = ">=0.0.66,<0.0.67" },
-    { name = "infinity-sdk", specifier = "==0.6.1" },
+    { name = "infinity-sdk", specifier = "==0.6.2" },
     { name = "itsdangerous", specifier = "==2.1.2" },
     { name = "json-repair", specifier = "==0.35.0" },
     { name = "langfuse", specifier = ">=2.60.0" },
@@ -6513,9 +6513,9 @@ source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
 dependencies = [
     { name = "requests" },
 ]
-sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/3a/47/05163b257f6c0e60aed4272d48bdb816567ab3c805d3e8770430f0cc1be2/tencentcloud-sdk-python-3.0.1478.tar.gz", hash = "sha256:89996462d53a672946aa32d01673a4818ebcd8bc72b024f35ebe96cebe2df179", size = 12297889, upload_time = "2025-10-20T20:54:40.603Z" }
+sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/3a/47/05163b257f6c0e60aed4272d48bdb816567ab3c805d3e8770430f0cc1be2/tencentcloud-sdk-python-3.0.1478.tar.gz", hash = "sha256:89996462d53a672946aa32d01673a4818ebcd8bc72b024f35ebe96cebe2df179", size = 12297889, upload-time = "2025-10-20T20:54:40.603Z" }
 wheels = [
-    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/c5/db/daa85799b9af2aa50539b27eeb0d6a2a0ac35465f62683107847830dbe4d/tencentcloud_sdk_python-3.0.1478-py2.py3-none-any.whl", hash = "sha256:10ddee1c1348f49e2b54af606f978d4cb17fca656639e8d99b6527e6e4793833", size = 12984723, upload_time = "2025-10-20T20:54:27.767Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/c5/db/daa85799b9af2aa50539b27eeb0d6a2a0ac35465f62683107847830dbe4d/tencentcloud_sdk_python-3.0.1478-py2.py3-none-any.whl", hash = "sha256:10ddee1c1348f49e2b54af606f978d4cb17fca656639e8d99b6527e6e4793833", size = 12984723, upload-time = "2025-10-20T20:54:27.767Z" },
 ]
 
 [[package]]

web/src/interfaces/database/flow.ts

@@ -52,12 +52,14 @@ export interface IFlowTemplate {
   description: {
     en: string;
     zh: string;
+    de: string;
   };
   dsl: DSL;
   id: string;
   title: {
     en: string;
     zh: string;
+    de: string;
   };
   update_date: string;
   update_time: number;

web/src/pages/agent/constant/index.tsx

@@ -584,6 +584,8 @@ export const initialCodeValues = {
 
 export const initialWaitingDialogueValues = {};
 
+export const AgentStructuredOutputField = 'structured';
+
 export const initialAgentValues = {
   ...initialLlmBaseValues,
   description: '',
@@ -615,7 +617,7 @@ export const initialAgentValues = {
       type: 'string',
       value: '',
     },
-    structured: {},
+    [AgentStructuredOutputField]: {},
   },
 };
 

web/src/pages/agent/form/agent-form/structured-output-dialog.tsx

@@ -34,7 +34,7 @@ export function StructuredOutputDialog({
         <DialogHeader>
           <DialogTitle> {t('flow.structuredOutput.configuration')}</DialogTitle>
         </DialogHeader>
-        <section className="flex">
+        <section className="flex overflow-auto">
           <div className="flex-1">
             <SchemaVisualEditor schema={schema} onChange={setSchema} />
           </div>

web/src/pages/agent/form/components/prompt-editor/index.css

@@ -28,10 +28,10 @@
   cursor: pointer;
   line-height: 16px;
   font-size: 15px;
-  display: flex;
+  /* display: flex;
   align-content: center;
   flex-direction: row;
-  flex-shrink: 0;
+  flex-shrink: 0; */
   border: 0;
 }
 

web/src/pages/agent/form/components/prompt-editor/utils.ts

@@ -0,0 +1,44 @@
+import { JSONSchema } from '@/components/jsonjoy-builder';
+import { Operator } from '@/constants/agent';
+import { isPlainObject } from 'lodash';
+
+export function filterAgentStructuredOutput(
+  structuredOutput: JSONSchema,
+  operator?: string,
+) {
+  if (typeof structuredOutput === 'boolean') {
+    return structuredOutput;
+  }
+  if (
+    structuredOutput.properties &&
+    isPlainObject(structuredOutput.properties)
+  ) {
+    const filterByPredicate = (predicate: (value: JSONSchema) => boolean) => {
+      const properties = Object.entries({
+        ...structuredOutput.properties,
+      }).reduce(
+        (pre, [key, value]) => {
+          if (predicate(value)) {
+            pre[key] = value;
+          }
+          return pre;
+        },
+        {} as Record<string, JSONSchema>,
+      );
+
+      return { ...structuredOutput, properties };
+    };
+
+    if (operator === Operator.Iteration) {
+      return filterByPredicate(
+        (value) => typeof value !== 'boolean' && value.type === 'array',
+      );
+    } else {
+      return filterByPredicate(
+        (value) => typeof value !== 'boolean' && value.type !== 'array',
+      );
+    }
+  }
+
+  return structuredOutput;
+}

web/src/pages/agent/form/components/prompt-editor/variable-picker-plugin.tsx

@@ -30,10 +30,21 @@ import * as ReactDOM from 'react-dom';
 
 import { $createVariableNode } from './variable-node';
 
+import {
+  HoverCard,
+  HoverCardContent,
+  HoverCardTrigger,
+} from '@/components/ui/hover-card';
+import { Operator } from '@/constants/agent';
+import { cn } from '@/lib/utils';
+import { AgentStructuredOutputField } from '@/pages/agent/constant';
 import { useBuildQueryVariableOptions } from '@/pages/agent/hooks/use-get-begin-query';
+import useGraphStore from '@/pages/agent/store';
+import { get, isPlainObject } from 'lodash';
 import { PromptIdentity } from '../../agent-form/use-build-prompt-options';
 import { ProgrammaticTag } from './constant';
 import './index.css';
+import { filterAgentStructuredOutput } from './utils';
 class VariableInnerOption extends MenuOption {
   label: string;
   value: string;
@@ -71,6 +82,10 @@ class VariableOption extends MenuOption {
   }
 }
 
+function getNodeId(value: string) {
+  return value.split('@').at(0);
+}
+
 function VariablePickerMenuItem({
   index,
   option,
@@ -82,6 +97,59 @@ function VariablePickerMenuItem({
     option: VariableOption | VariableInnerOption,
   ) => void;
 }) {
+  const { getOperatorTypeFromId, getNode, clickedNodeId } = useGraphStore(
+    (state) => state,
+  );
+
+  const showSecondaryMenu = useCallback(
+    (value: string, outputLabel: string) => {
+      const nodeId = getNodeId(value);
+      return (
+        getOperatorTypeFromId(nodeId) === Operator.Agent &&
+        outputLabel === AgentStructuredOutputField
+      );
+    },
+    [getOperatorTypeFromId],
+  );
+
+  const renderAgentStructuredOutput = useCallback(
+    (values: any, option: VariableInnerOption) => {
+      if (isPlainObject(values) && 'properties' in values) {
+        return (
+          <ul className="border-l">
+            {Object.entries(values.properties).map(([key, value]) => {
+              const nextOption = new VariableInnerOption(
+                option.label + `.${key}`,
+                option.value + `.${key}`,
+                option.parentLabel,
+                option.icon,
+              );
+
+              const dataType = get(value, 'type');
+
+              return (
+                <li key={key} className="pl-1">
+                  <div
+                    onClick={() => selectOptionAndCleanUp(nextOption)}
+                    className="hover:bg-bg-card p-1 text-text-primary rounded-sm flex justify-between"
+                  >
+                    {key}
+                    <span className="text-text-secondary">{dataType}</span>
+                  </div>
+                  {dataType === 'object' &&
+                    renderAgentStructuredOutput(value, nextOption)}
+                </li>
+              );
+            })}
+          </ul>
+        );
+      }
+
+      return <div></div>;
+    },
+    [selectOptionAndCleanUp],
+  );
+
   return (
     <li
       key={option.key}
@@ -93,15 +161,56 @@ function VariablePickerMenuItem({
       <div>
         <span className="text text-text-secondary">{option.title}</span>
         <ul className="pl-2 py-1">
-          {option.options.map((x) => (
-            <li
-              key={x.value}
-              onClick={() => selectOptionAndCleanUp(x)}
-              className="hover:bg-bg-card p-1 text-text-primary rounded-sm"
-            >
-              {x.label}
-            </li>
-          ))}
+          {option.options.map((x) => {
+            const shouldShowSecondary = showSecondaryMenu(x.value, x.label);
+
+            if (shouldShowSecondary) {
+              const node = getNode(getNodeId(x.value));
+              const structuredOutput = get(
+                node,
+                `data.form.outputs.${AgentStructuredOutputField}`,
+              );
+
+              const filteredStructuredOutput = filterAgentStructuredOutput(
+                structuredOutput,
+                getOperatorTypeFromId(clickedNodeId),
+              );
+
+              return (
+                <HoverCard key={x.value} openDelay={100} closeDelay={100}>
+                  <HoverCardTrigger asChild>
+                    <li className="hover:bg-bg-card p-1 text-text-primary rounded-sm">
+                      {x.label}
+                    </li>
+                  </HoverCardTrigger>
+                  <HoverCardContent
+                    side="left"
+                    align="start"
+                    className={cn(
+                      'min-w-[140px]  border border-border rounded-md shadow-lg p-0',
+                    )}
+                  >
+                    <section className="p-2">
+                      <div className="p-1">
+                        {x.parentLabel} structured output:
+                      </div>
+                      {renderAgentStructuredOutput(filteredStructuredOutput, x)}
+                    </section>
+                  </HoverCardContent>
+                </HoverCard>
+              );
+            }
+
+            return (
+              <li
+                key={x.value}
+                onClick={() => selectOptionAndCleanUp(x)}
+                className="hover:bg-bg-card p-1 text-text-primary rounded-sm"
+              >
+                {x.label}
+              </li>
+            );
+          })}
         </ul>
       </div>
     </li>
@@ -130,6 +239,9 @@ export default function VariablePickerMenuPlugin({
   baseOptions,
 }: VariablePickerMenuPluginProps): JSX.Element {
   const [editor] = useLexicalComposerContext();
+  const getOperatorTypeFromId = useGraphStore(
+    (state) => state.getOperatorTypeFromId,
+  );
 
   // const checkForTriggerMatch = useBasicTypeaheadTriggerMatch('/', {
   //   minLength: 0,
@@ -200,9 +312,28 @@ export default function VariablePickerMenuPlugin({
         return pre.concat(cur.options);
       }, []);
 
+      // agent structured output
+      const fields = value.split('@');
+      if (
+        getOperatorTypeFromId(fields.at(0)) === Operator.Agent &&
+        fields.at(1)?.startsWith(AgentStructuredOutputField)
+      ) {
+        // is agent structured output
+        const agentOption = children.find((x) => value.includes(x.value));
+        const jsonSchemaFields = fields
+          .at(1)
+          ?.slice(AgentStructuredOutputField.length);
+
+        return {
+          ...agentOption,
+          label: (agentOption?.label ?? '') + jsonSchemaFields,
+          value: value,
+        };
+      }
+
       return children.find((x) => x.value === value);
     },
-    [options],
+    [getOperatorTypeFromId, options],
   );
 
   const onSelectOption = useCallback(

web/src/pages/agents/template-card.tsx

@@ -20,7 +20,7 @@ export function TemplateCard({ data, showModal }: IProps) {
 
   const language = useMemo(() => {
     return i18n.language || 'en';
-  }, []) as 'en' | 'zh';
+  }, []) as 'en' | 'zh' | 'de';
 
   return (
     <Card className="border-colors-outline-neutral-standard group relative min-h-40">
@@ -31,9 +31,9 @@ export function TemplateCard({ data, showModal }: IProps) {
             avatar={data.avatar ? data.avatar : 'https://github.com/shadcn.png'}
             name={data?.title[language] || 'CN'}
           ></RAGFlowAvatar>
-          <div className="text-[18px] font-bold ">{data?.title[language]}</div>
+          <div className="text-[18px] font-bold break-words hyphens-auto overflow-hidden"lang={language}>{data?.title[language]}</div>
         </div>
-        <p className="break-words">{data?.description[language]}</p>
+        <p className="break-words hypens-auto"lang={language}>{data?.description[language]}</p>
         <div className="group-hover:bg-gradient-to-t from-black/70 from-10% via-black/0 via-50% to-black/0 w-full h-full group-hover:block absolute top-0 left-0 hidden rounded-xl">
           <Button
             variant="default"