Update readme (#9260)

### What problem does this PR solve?

Update readme

### Type of change

- [x] Documentation Update

---------

Signed-off-by: Jin Hai <haijin.chn@gmail.com>

README.md

@@ -87,7 +87,8 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
 
 ## 🔥 Latest Updates
 
-- 2025-08-01 Supports agentic workflow.
+- 2025-08-04 Supports new models, including Kimi K2 and Grok 4.
+- 2025-08-01 Supports agentic workflow and MCP.
 - 2025-05-23 Adds a Python/JavaScript code executor component to Agent.
 - 2025-05-05 Supports cross-language query.
 - 2025-03-19 Supports using a multi-modal model to make sense of images within PDF or DOCX files.

README_id.md

@@ -80,7 +80,8 @@ Coba demo kami di [https://demo.ragflow.io](https://demo.ragflow.io).
 
 ## 🔥 Pembaruan Terbaru
 
-- 2025-08-01 Mendukung Alur Kerja agen.
+- 2025-08-04 Mendukung model baru, termasuk Kimi K2 dan Grok 4.
+- 2025-08-01 Mendukung alur kerja agen dan MCP.
 - 2025-05-23 Menambahkan komponen pelaksana kode Python/JS ke Agen.
 - 2025-05-05 Mendukung kueri lintas bahasa.
 - 2025-03-19 Mendukung penggunaan model multi-modal untuk memahami gambar di dalam file PDF atau DOCX.

README_ja.md

@@ -60,7 +60,8 @@
 
 ## 🔥 最新情報
 
-- 2025-08-01 エージェントワークフローをサポートします。
+- 2025-08-04 新モデル、キミK2およびGrok 4をサポート。
+- 2025-08-01 エージェントワークフローとMCPをサポート。
 - 2025-05-23 エージェントに Python/JS コードエグゼキュータコンポーネントを追加しました。
 - 2025-05-05 言語間クエリをサポートしました。
 - 2025-03-19 PDFまたはDOCXファイル内の画像を理解するために、多モーダルモデルを使用することをサポートします。

README_ko.md

@@ -60,7 +60,8 @@
 
 ## 🔥 업데이트
 
-- 2025-08-01 에이전트 워크플로를 지원합니다.
+- 2025-08-04 새로운 모델인 Kimi K2와 Grok 4를 포함하여 지원합니다.
+- 2025-08-01 에이전트 워크플로우와 MCP를 지원합니다.
 - 2025-05-23 Agent에 Python/JS 코드 실행기 구성 요소를 추가합니다.
 - 2025-05-05 언어 간 쿼리를 지원합니다.
 - 2025-03-19 PDF 또는 DOCX 파일 내의 이미지를 이해하기 위해 다중 모드 모델을 사용하는 것을 지원합니다.

README_pt_br.md

@@ -80,7 +80,8 @@ Experimente nossa demo em [https://demo.ragflow.io](https://demo.ragflow.io).
 
 ## 🔥 Últimas Atualizações
 
-- 01-08-2025 Suporta o fluxo de trabalho agêntico.
+- 04-08-2025 Suporta novos modelos, incluindo Kimi K2 e Grok 4.
+- 01-08-2025 Suporta fluxo de trabalho agente e MCP.
 - 23-05-2025 Adicione o componente executor de código Python/JS ao Agente.
 - 05-05-2025 Suporte a consultas entre idiomas.
 - 19-03-2025 Suporta o uso de um modelo multi-modal para entender imagens dentro de arquivos PDF ou DOCX.

README_tzh.md

@@ -83,7 +83,8 @@
 
 ## 🔥 近期更新
 
-- 2025-08-01 支援 agentic workflow
+- 2025-08-04 支援 Kimi K2 和 Grok 4 等模型.
+- 2025-08-01 支援 agentic workflow 和 MCP
 - 2025-05-23 為 Agent 新增 Python/JS 程式碼執行器元件。
 - 2025-05-05 支援跨語言查詢。
 - 2025-03-19 PDF和DOCX中的圖支持用多模態大模型去解析得到描述.

README_zh.md

@@ -83,7 +83,8 @@
 
 ## 🔥 近期更新
 
-- 2025-08-01 支持 agentic workflow。
+- 2025-08-04 新增对 Kimi K2 和 Grok 4 等模型的支持.
+- 2025-08-01 支持 agentic workflow 和 MCP。
 - 2025-05-23 Agent 新增 Python/JS 代码执行器组件。
 - 2025-05-05 支持跨语言查询。
 - 2025-03-19 PDF 和 DOCX 中的图支持用多模态大模型去解析得到描述.

agent/templates/customer_support.json

@@ -89,11 +89,11 @@
                             "presence_penalty": 0.4,
                             "prompts": [
                                 {
-                                    "content": "{sys.query}",
+                                    "content": "The user query is {sys.query}\n\nThe relevant document are {Retrieval:ShyPumasJoke@formalized_content}",
                                     "role": "user"
                                 }
                             ],
-                            "sys_prompt": "You are a highly professional product information advisor.  \n\nYour only mission is to provide accurate, factual, and structured answers to all product-related queries.\n\nAbsolutely no assumptions, guesses, or fabricated content are allowed. \n\n**Key Principles:**\n\n1. **Strict Database Reliance:**  \n\n   - Every answer must be based solely on the verified product information stored in the database accessed through the Retrieval tool.  \n\n   - You are NOT allowed to invent, speculate, or infer details beyond what is retrieved.  \n\n   - If you cannot find relevant data, respond with: *\"I cannot find this information in our official product database. Please check back later or provide more details for further search.\"*\n\n2. **Information Accuracy and Structure:**  \n\n   - Provide information in a clear, concise, and professional way.  \n\n   - Use bullet points or numbered lists if there are multiple key points (e.g., features, price, warranty, technical specifications).  \n\n   - Always specify the version or model number when applicable to avoid confusion.\n\n3. **Tone and Style:**  \n\n   - Maintain a polite, professional, and helpful tone at all times.  \n\n   - Avoid marketing exaggeration or promotional language; stay strictly factual.  \n\n   - Do not express personal opinions; only cite official product data.\n\n4.  **User Guidance:**  \n\n   - If the user\u2019s query is unclear or too broad, politely request clarification or guide them to provide more specific product details (e.g., product name, model, version).  \n\n   - Example: *\"Could you please specify the product model or category so I can retrieve the most relevant information for you?\"*\n\n5. **Response Length and Formatting:**  \n\n   - Keep each answer within 100\u2013150 words for general queries.  \n\n   - For complex or multi-step explanations, you may extend to 200\u2013250 words, but always remain clear and well-structured.\n\n6. **Critical Reminder:**  \n\nYour authority and reliability depend entirely on database-driven responses. Any fabricated, speculative, or unverified content will be considered a critical failure of your role.\n\nAlways begin processing a query by accessing the Retrieval tool, confirming the data source, and then structuring your response according to the above principles.\n\n",
+                            "sys_prompt": "You are a highly professional product information advisor.  \n\nYour only mission is to provide accurate, factual, and structured answers to all product-related queries.\n\nAbsolutely no assumptions, guesses, or fabricated content are allowed. \n\n**Key Principles:**\n\n1. **Strict Database Reliance:**  \n\n   - Every answer must be based solely on the verified product information stored in the relevant documen.\n\n   - You are NOT allowed to invent, speculate, or infer details beyond what is retrieved.  \n\n   - If you cannot find relevant data, respond with: *\"I cannot find this information in our official product database. Please check back later or provide more details for further search.\"*\n\n2. **Information Accuracy and Structure:**  \n\n   - Provide information in a clear, concise, and professional way.  \n\n   - Use bullet points or numbered lists if there are multiple key points (e.g., features, price, warranty, technical specifications).  \n\n   - Always specify the version or model number when applicable to avoid confusion.\n\n3. **Tone and Style:**  \n\n   - Maintain a polite, professional, and helpful tone at all times.  \n\n   - Avoid marketing exaggeration or promotional language; stay strictly factual.  \n\n   - Do not express personal opinions; only cite official product data.\n\n4.  **User Guidance:**  \n\n   - If the user\u2019s query is unclear or too broad, politely request clarification or guide them to provide more specific product details (e.g., product name, model, version).  \n\n   - Example: *\"Could you please specify the product model or category so I can retrieve the most relevant information for you?\"*\n\n5. **Response Length and Formatting:**  \n\n   - Keep each answer within 100\u2013150 words for general queries.  \n\n   - For complex or multi-step explanations, you may extend to 200\u2013250 words, but always remain clear and well-structured.\n\n6. **Critical Reminder:**  \n\nYour authority and reliability depend entirely on the relevant document responses. Any fabricated, speculative, or unverified content will be considered a critical failure of your role.\n\n\n",
                             "temperature": 0.1,
                             "temperatureEnabled": true,
                             "tools": [],
@@ -699,7 +699,7 @@
                             "width": 200
                         },
                         "position": {
-                            "x": 644.5771854408022,
+                            "x": 645.6873721057459,
                             "y": 516.6923702571407
                         },
                         "selected": false,
@@ -735,11 +735,11 @@
                                 "presence_penalty": 0.4,
                                 "prompts": [
                                     {
-                                        "content": "{sys.query}",
+                                        "content": "The user query is {sys.query}\n\nThe relevant document are {Retrieval:ShyPumasJoke@formalized_content}",
                                         "role": "user"
                                     }
                                 ],
-                                "sys_prompt": "You are a highly professional product information advisor.  \n\nYour only mission is to provide accurate, factual, and structured answers to all product-related queries.\n\nAbsolutely no assumptions, guesses, or fabricated content are allowed. \n\n**Key Principles:**\n\n1. **Strict Database Reliance:**  \n\n   - Every answer must be based solely on the verified product information stored in the database accessed through the Retrieval tool.  \n\n   - You are NOT allowed to invent, speculate, or infer details beyond what is retrieved.  \n\n   - If you cannot find relevant data, respond with: *\"I cannot find this information in our official product database. Please check back later or provide more details for further search.\"*\n\n2. **Information Accuracy and Structure:**  \n\n   - Provide information in a clear, concise, and professional way.  \n\n   - Use bullet points or numbered lists if there are multiple key points (e.g., features, price, warranty, technical specifications).  \n\n   - Always specify the version or model number when applicable to avoid confusion.\n\n3. **Tone and Style:**  \n\n   - Maintain a polite, professional, and helpful tone at all times.  \n\n   - Avoid marketing exaggeration or promotional language; stay strictly factual.  \n\n   - Do not express personal opinions; only cite official product data.\n\n4.  **User Guidance:**  \n\n   - If the user\u2019s query is unclear or too broad, politely request clarification or guide them to provide more specific product details (e.g., product name, model, version).  \n\n   - Example: *\"Could you please specify the product model or category so I can retrieve the most relevant information for you?\"*\n\n5. **Response Length and Formatting:**  \n\n   - Keep each answer within 100\u2013150 words for general queries.  \n\n   - For complex or multi-step explanations, you may extend to 200\u2013250 words, but always remain clear and well-structured.\n\n6. **Critical Reminder:**  \n\nYour authority and reliability depend entirely on database-driven responses. Any fabricated, speculative, or unverified content will be considered a critical failure of your role.\n\nAlways begin processing a query by accessing the Retrieval tool, confirming the data source, and then structuring your response according to the above principles.\n\n",
+                                "sys_prompt": "You are a highly professional product information advisor.  \n\nYour only mission is to provide accurate, factual, and structured answers to all product-related queries.\n\nAbsolutely no assumptions, guesses, or fabricated content are allowed. \n\n**Key Principles:**\n\n1. **Strict Database Reliance:**  \n\n   - Every answer must be based solely on the verified product information stored in the relevant documen.\n\n   - You are NOT allowed to invent, speculate, or infer details beyond what is retrieved.  \n\n   - If you cannot find relevant data, respond with: *\"I cannot find this information in our official product database. Please check back later or provide more details for further search.\"*\n\n2. **Information Accuracy and Structure:**  \n\n   - Provide information in a clear, concise, and professional way.  \n\n   - Use bullet points or numbered lists if there are multiple key points (e.g., features, price, warranty, technical specifications).  \n\n   - Always specify the version or model number when applicable to avoid confusion.\n\n3. **Tone and Style:**  \n\n   - Maintain a polite, professional, and helpful tone at all times.  \n\n   - Avoid marketing exaggeration or promotional language; stay strictly factual.  \n\n   - Do not express personal opinions; only cite official product data.\n\n4.  **User Guidance:**  \n\n   - If the user\u2019s query is unclear or too broad, politely request clarification or guide them to provide more specific product details (e.g., product name, model, version).  \n\n   - Example: *\"Could you please specify the product model or category so I can retrieve the most relevant information for you?\"*\n\n5. **Response Length and Formatting:**  \n\n   - Keep each answer within 100\u2013150 words for general queries.  \n\n   - For complex or multi-step explanations, you may extend to 200\u2013250 words, but always remain clear and well-structured.\n\n6. **Critical Reminder:**  \n\nYour authority and reliability depend entirely on the relevant document responses. Any fabricated, speculative, or unverified content will be considered a critical failure of your role.\n\n\n",
                                 "temperature": 0.1,
                                 "temperatureEnabled": true,
                                 "tools": [],

api/apps/conversation_app.py

@@ -66,7 +66,8 @@ def set_conversation():
         e, dia = DialogService.get_by_id(req["dialog_id"])
         if not e:
             return get_data_error_result(message="Dialog not found")
-        conv = {"id": conv_id, "dialog_id": req["dialog_id"], "name": name, "message": [{"role": "assistant", "content": dia.prompt_config["prologue"]}],"user_id": current_user.id}
+        conv = {"id": conv_id, "dialog_id": req["dialog_id"], "name": name, "message": [{"role": "assistant", "content": dia.prompt_config["prologue"]}],"user_id": current_user.id,
+                "reference":[{}],}
         ConversationService.save(**conv)
         return get_json_result(data=conv)
     except Exception as e:

api/apps/sdk/session.py

@@ -51,6 +51,7 @@ def create(tenant_id, chat_id):
         "name": req.get("name", "New session"),
         "message": [{"role": "assistant", "content": dia[0].prompt_config.get("prologue")}],
         "user_id": req.get("user_id", ""),
+        "reference":[{}],
     }
     if not conv.get("name"):
         return get_error_data_result(message="`name` can not be empty.")
@@ -435,14 +436,38 @@ def agents_completion_openai_compatibility(tenant_id, agent_id):
             )
         )
 
-    # Get the last user message as the question
     question = next((m["content"] for m in reversed(messages) if m["role"] == "user"), "")
 
-    if req.get("stream", True):
-        return Response(completionOpenAI(tenant_id, agent_id, question, session_id=req.get("id", req.get("metadata", {}).get("id", "")), stream=True), mimetype="text/event-stream")
+    stream = req.pop("stream", False)
+    if stream:
+        resp = Response(
+            completionOpenAI(
+                tenant_id,
+                agent_id,
+                question,
+                session_id=req.get("id", req.get("metadata", {}).get("id", "")),
+                stream=True,
+                **req,
+            ),
+            mimetype="text/event-stream",
+        )
+        resp.headers.add_header("Cache-control", "no-cache")
+        resp.headers.add_header("Connection", "keep-alive")
+        resp.headers.add_header("X-Accel-Buffering", "no")
+        resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
+        return resp
     else:
         # For non-streaming, just return the response directly
-        response = next(completionOpenAI(tenant_id, agent_id, question, session_id=req.get("id", req.get("metadata", {}).get("id", "")), stream=False))
+        response = next(
+            completionOpenAI(
+                tenant_id,
+                agent_id,
+                question,
+                session_id=req.get("id", req.get("metadata", {}).get("id", "")),
+                stream=False,
+                **req,
+            )
+        )
         return jsonify(response)
 
 
@@ -512,16 +537,16 @@ def list_session(tenant_id, chat_id):
             if "prompt" in info:
                 info.pop("prompt")
         conv["chat_id"] = conv.pop("dialog_id")
-        if conv["reference"]:
+        ref_messages = conv["reference"]
+        if ref_messages:
             messages = conv["messages"]
             message_num = 0
-            while message_num < len(messages) and message_num < len(conv["reference"]):
-                if message_num != 0 and messages[message_num]["role"] != "user":
-                    if message_num >= len(conv["reference"]):
-                        break
+            ref_num = 0
+            while message_num < len(messages) and ref_num < len(ref_messages):
+                if messages[message_num]["role"] != "user":
                     chunk_list = []
-                    if "chunks" in conv["reference"][message_num]:
-                        chunks = conv["reference"][message_num]["chunks"]
+                    if "chunks" in ref_messages[ref_num]:
+                        chunks = ref_messages[ref_num]["chunks"]
                         for chunk in chunks:
                             new_chunk = {
                                 "id": chunk.get("chunk_id", chunk.get("id")),
@@ -535,6 +560,7 @@ def list_session(tenant_id, chat_id):
 
                             chunk_list.append(new_chunk)
                     messages[message_num]["reference"] = chunk_list
+                    ref_num += 1
                 message_num += 1
         del conv["reference"]
     return get_result(data=convs)
@@ -848,10 +874,10 @@ def begin_inputs(agent_id):
         return get_error_data_result(f"Can't find agent by ID: {agent_id}")
 
     canvas = Canvas(json.dumps(cvs.dsl), objs[0].tenant_id)
-    return get_result(data={
-        "title": cvs.title,
-        "avatar": cvs.avatar,
-        "inputs": canvas.get_component_input_form("begin")
-    })
-
-
+    return get_result(
+        data={
+            "title": cvs.title,
+            "avatar": cvs.avatar,
+            "inputs": canvas.get_component_input_form("begin"),
+        }
+    )

api/db/services/canvas_service.py

@@ -16,7 +16,6 @@
 import json
 import logging
 import time
-import traceback
 from uuid import uuid4
 from agent.canvas import Canvas
 from api.db import TenantPermission
@@ -54,12 +53,12 @@ class UserCanvasService(CommonService):
         agents = agents.paginate(page_number, items_per_page)
 
         return list(agents.dicts())
-   
+
     @classmethod
     @DB.connection_context()
     def get_by_tenant_id(cls, pid):
         try:
-            
+
             fields = [
                 cls.model.id,
                 cls.model.avatar,
@@ -83,7 +82,7 @@ class UserCanvasService(CommonService):
         except Exception as e:
             logging.exception(e)
             return False, None
-     
+
     @classmethod
     @DB.connection_context()
     def get_by_tenant_ids(cls, joined_tenant_ids, user_id,
@@ -103,14 +102,14 @@ class UserCanvasService(CommonService):
         ]
         if keywords:
             agents = cls.model.select(*fields).join(User, on=(cls.model.user_id == User.id)).where(
-                ((cls.model.user_id.in_(joined_tenant_ids) & (cls.model.permission == 
+                ((cls.model.user_id.in_(joined_tenant_ids) & (cls.model.permission ==
                                                                 TenantPermission.TEAM.value)) | (
                     cls.model.user_id == user_id)),
                 (fn.LOWER(cls.model.title).contains(keywords.lower()))
             )
         else:
             agents = cls.model.select(*fields).join(User, on=(cls.model.user_id == User.id)).where(
-                ((cls.model.user_id.in_(joined_tenant_ids) & (cls.model.permission == 
+                ((cls.model.user_id.in_(joined_tenant_ids) & (cls.model.permission ==
                                                                 TenantPermission.TEAM.value)) | (
                     cls.model.user_id == user_id))
             )
@@ -178,219 +177,99 @@ def completion(tenant_id, agent_id, session_id=None, **kwargs):
 
 
 def completionOpenAI(tenant_id, agent_id, question, session_id=None, stream=True, **kwargs):
-    """Main function for OpenAI-compatible completions, structured similarly to the completion function."""
     tiktokenenc = tiktoken.get_encoding("cl100k_base")
-    e, cvs = UserCanvasService.get_by_id(agent_id)
-    
-    if not e:
-        yield get_data_openai(
-            id=session_id,
-            model=agent_id,
-            content="**ERROR**: Agent not found."
-        )
-        return
-    
-    if cvs.user_id != tenant_id:
-        yield get_data_openai(
-            id=session_id,
-            model=agent_id,
-            content="**ERROR**: You do not own the agent"
-        )
-        return
-    
-    if not isinstance(cvs.dsl, str):
-        cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False)
-    
-    canvas = Canvas(cvs.dsl, tenant_id)
-    canvas.reset()
-    message_id = str(uuid4())
-    
-    # Handle new session creation
-    if not session_id:
-        query = canvas.get_preset_param()
-        if query:
-            for ele in query:
-                if not ele["optional"]:
-                    if not kwargs.get(ele["key"]):
-                        yield get_data_openai(
-                            id=None,
-                            model=agent_id,
-                            content=f"`{ele['key']}` is required",
-                            completion_tokens=len(tiktokenenc.encode(f"`{ele['key']}` is required")),
-                            prompt_tokens=len(tiktokenenc.encode(question if question else ""))
-                        )
-                        return
-                    ele["value"] = kwargs[ele["key"]]
-                if ele["optional"]:
-                    if kwargs.get(ele["key"]):
-                        ele["value"] = kwargs[ele['key']]
-                    else:
-                        if "value" in ele:
-                            ele.pop("value")
-        
-        cvs.dsl = json.loads(str(canvas))
-        session_id = get_uuid()
-        conv = {
-            "id": session_id,
-            "dialog_id": cvs.id,
-            "user_id": kwargs.get("user_id", "") if isinstance(kwargs, dict) else "",
-            "message": [{"role": "assistant", "content": canvas.get_prologue(), "created_at": time.time()}],
-            "source": "agent",
-            "dsl": cvs.dsl
-        }
-        canvas.messages.append({"role": "user", "content": question, "id": message_id})
-        canvas.add_user_input(question)
-
-        API4ConversationService.save(**conv)
-        conv = API4Conversation(**conv)
-        if not conv.message:
-            conv.message = []
-        conv.message.append({
-            "role": "user",
-            "content": question,
-            "id": message_id
-        })
-        
-        if not conv.reference:
-            conv.reference = []
-        conv.reference.append({"chunks": [], "doc_aggs": []})
-            
-    # Handle existing session
-    else:
-        e, conv = API4ConversationService.get_by_id(session_id)
-        if not e:
-            yield get_data_openai(
-                id=session_id,
-                model=agent_id,
-                content="**ERROR**: Session not found!"
-            )
-            return
-        
-        canvas = Canvas(json.dumps(conv.dsl), tenant_id)
-        canvas.messages.append({"role": "user", "content": question, "id": message_id})
-        canvas.add_user_input(question)
-        
-        if not conv.message:
-            conv.message = []
-        conv.message.append({
-            "role": "user",
-            "content": question,
-            "id": message_id
-        })
-        
-        if not conv.reference:
-            conv.reference = []
-        conv.reference.append({"chunks": [], "doc_aggs": []})
-    
-    # Process request based on stream mode
-    final_ans = {"reference": [], "content": ""}
     prompt_tokens = len(tiktokenenc.encode(str(question)))
-    
+    user_id = kwargs.get("user_id", "")
+
     if stream:
+        completion_tokens = 0
         try:
-            completion_tokens = 0
-            for ans in canvas.run(stream=True, bypass_begin=True):
-                if ans.get("running_status"):
-                    completion_tokens += len(tiktokenenc.encode(ans.get("content", "")))
-                    yield "data: " + json.dumps(
-                        get_data_openai(
-                            id=session_id,
-                            model=agent_id,
-                            content=ans["content"],
-                            object="chat.completion.chunk",
-                            completion_tokens=completion_tokens,
-                            prompt_tokens=prompt_tokens
-                        ),
-                        ensure_ascii=False
-                    ) + "\n\n"
+            for ans in completion(
+                tenant_id=tenant_id,
+                agent_id=agent_id,
+                session_id=session_id,
+                query=question,
+                user_id=user_id,
+                **kwargs
+            ):
+                if isinstance(ans, str):
+                    try:
+                        ans = json.loads(ans[5:])  # remove "data:"
+                    except Exception as e:
+                        logging.exception(f"Agent OpenAI-Compatible completionOpenAI parse answer failed: {e}")
+                        continue
+
+                if ans.get("event") != "message":
                     continue
-                
-                for k in ans.keys():
-                    final_ans[k] = ans[k]
-                
-                completion_tokens += len(tiktokenenc.encode(final_ans.get("content", "")))
+
+                content_piece = ans["data"]["content"]
+                completion_tokens += len(tiktokenenc.encode(content_piece))
+
                 yield "data: " + json.dumps(
                     get_data_openai(
-                        id=session_id,
+                        id=session_id or str(uuid4()),
                         model=agent_id,
-                        content=final_ans["content"],
-                        object="chat.completion.chunk",
-                        finish_reason="stop",
+                        content=content_piece,
+                        prompt_tokens=prompt_tokens,
                         completion_tokens=completion_tokens,
-                        prompt_tokens=prompt_tokens
+                        stream=True
                     ),
                     ensure_ascii=False
                 ) + "\n\n"
-            
-            # Update conversation
-            canvas.messages.append({"role": "assistant", "content": final_ans["content"], "created_at": time.time(), "id": message_id})
-            canvas.history.append(("assistant", final_ans["content"]))
-            if final_ans.get("reference"):
-                canvas.reference.append(final_ans["reference"])
-            conv.dsl = json.loads(str(canvas))
-            API4ConversationService.append_message(conv.id, conv.to_dict())
-            
+
             yield "data: [DONE]\n\n"
-            
+
         except Exception as e:
-            traceback.print_exc()
-            conv.dsl = json.loads(str(canvas))
-            API4ConversationService.append_message(conv.id, conv.to_dict())
             yield "data: " + json.dumps(
                 get_data_openai(
-                    id=session_id,
+                    id=session_id or str(uuid4()),
                     model=agent_id,
-                    content="**ERROR**: " + str(e),
+                    content=f"**ERROR**: {str(e)}",
                     finish_reason="stop",
-                    completion_tokens=len(tiktokenenc.encode("**ERROR**: " + str(e))),
-                    prompt_tokens=prompt_tokens
+                    prompt_tokens=prompt_tokens,
+                    completion_tokens=len(tiktokenenc.encode(f"**ERROR**: {str(e)}")),
+                    stream=True
                 ),
                 ensure_ascii=False
             ) + "\n\n"
             yield "data: [DONE]\n\n"
-    
-    else:  # Non-streaming mode
+
+    else:
         try:
-            all_answer_content = ""
-            for answer in canvas.run(stream=False, bypass_begin=True):
-                if answer.get("running_status"):
+            all_content = ""
+            for ans in completion(
+                tenant_id=tenant_id,
+                agent_id=agent_id,
+                session_id=session_id,
+                query=question,
+                user_id=user_id,
+                **kwargs
+            ):
+                if isinstance(ans, str):
+                    ans = json.loads(ans[5:])
+                if ans.get("event") != "message":
                     continue
-                
-                final_ans["content"] = "\n".join(answer["content"]) if "content" in answer else ""
-                final_ans["reference"] = answer.get("reference", [])
-                all_answer_content += final_ans["content"]
-            
-            final_ans["content"] = all_answer_content
-            
-            # Update conversation
-            canvas.messages.append({"role": "assistant", "content": final_ans["content"], "created_at": time.time(), "id": message_id})
-            canvas.history.append(("assistant", final_ans["content"]))
-            if final_ans.get("reference"):
-                canvas.reference.append(final_ans["reference"])
-            conv.dsl = json.loads(str(canvas))
-            API4ConversationService.append_message(conv.id, conv.to_dict())
-            
-            # Return the response in OpenAI format
+                all_content += ans["data"]["content"]
+
+            completion_tokens = len(tiktokenenc.encode(all_content))
+
             yield get_data_openai(
-                id=session_id,
+                id=session_id or str(uuid4()),
                 model=agent_id,
-                content=final_ans["content"],
-                finish_reason="stop",
-                completion_tokens=len(tiktokenenc.encode(final_ans["content"])),
                 prompt_tokens=prompt_tokens,
-                param=canvas.get_preset_param()  # Added param info like in completion
-            )
-            
-        except Exception as e:
-            traceback.print_exc()
-            conv.dsl = json.loads(str(canvas))
-            API4ConversationService.append_message(conv.id, conv.to_dict())
-            yield get_data_openai(
-                id=session_id,
-                model=agent_id,
-                content="**ERROR**: " + str(e),
+                completion_tokens=completion_tokens,
+                content=all_content,
                 finish_reason="stop",
-                completion_tokens=len(tiktokenenc.encode("**ERROR**: " + str(e))),
-                prompt_tokens=prompt_tokens
+                param=None
             )
 
+        except Exception as e:
+            yield get_data_openai(
+                id=session_id or str(uuid4()),
+                model=agent_id,
+                prompt_tokens=prompt_tokens,
+                completion_tokens=len(tiktokenenc.encode(f"**ERROR**: {str(e)}")),
+                content=f"**ERROR**: {str(e)}",
+                finish_reason="stop",
+                param=None
+            )

api/utils/api_utils.py

@@ -402,8 +402,22 @@ def get_data_openai(
     finish_reason=None,
     object="chat.completion",
     param=None,
+    stream=False
 ):
     total_tokens = prompt_tokens + completion_tokens
+
+    if stream:
+        return {
+            "id": f"{id}",
+            "object": "chat.completion.chunk",
+            "model": model,
+            "choices": [{
+                "delta": {"content": content},
+                "finish_reason": finish_reason,
+                "index": 0,
+            }],
+        }
+
     return {
         "id": f"{id}",
         "object": object,
@@ -414,9 +428,21 @@ def get_data_openai(
             "prompt_tokens": prompt_tokens,
             "completion_tokens": completion_tokens,
             "total_tokens": total_tokens,
-            "completion_tokens_details": {"reasoning_tokens": 0, "accepted_prediction_tokens": 0, "rejected_prediction_tokens": 0},
+            "completion_tokens_details": {
+                "reasoning_tokens": 0,
+                "accepted_prediction_tokens": 0,
+                "rejected_prediction_tokens": 0,
+            },
         },
-        "choices": [{"message": {"role": "assistant", "content": content}, "logprobs": None, "finish_reason": finish_reason, "index": 0}],
+        "choices": [{
+            "message": {
+                "role": "assistant",
+                "content": content
+            },
+            "logprobs": None,
+            "finish_reason": finish_reason,
+            "index": 0,
+        }],
     }
 
 

rag/app/presentation.py

@@ -135,7 +135,8 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
             sections = pdf_parser(filename, binary, from_page=from_page, to_page=to_page, callback=callback)
         elif layout_recognizer == "Plain Text":
             pdf_parser = PlainParser()
-            sections, _ = pdf_parser(filename, binary, from_page=from_page, to_page=to_page, callback=callback)
+            sections, _ = pdf_parser(filename if not binary else binary, from_page=from_page, to_page=to_page,
+                                      callback=callback)
         else:
             vision_model = LLMBundle(kwargs["tenant_id"], LLMType.IMAGE2TEXT, llm_name=layout_recognizer, lang=lang)
             pdf_parser = VisionParser(vision_model=vision_model, **kwargs)

rag/llm/cv_model.py

@@ -542,6 +542,7 @@ class GeminiCV(Base):
             yield response.usage_metadata.total_token_count
         else:
             yield 0
+            
 
 class NvidiaCV(Base):
     _FACTORY_NAME = "NVIDIA"
@@ -623,15 +624,18 @@ class NvidiaCV(Base):
             return "**ERROR**: " + str(e), 0
 
     def chat_streamly(self, system, history, gen_conf, images=[], **kwargs):
+        total_tokens = 0
         try:
             response = self._request(self._form_history(system, history, images), gen_conf)
             cnt = response["choices"][0]["message"]["content"]
+            if "usage" in response and "total_tokens" in response["usage"]:
+                total_tokens += response["usage"]["total_tokens"]
             for resp in cnt:
                 yield resp
         except Exception as e:
             yield "\n**ERROR**: " + str(e)
 
-        yield response["usage"]["total_tokens"]
+        yield total_tokens
 
 
 class AnthropicCV(Base):

rag/svr/task_executor.py

@@ -420,7 +420,6 @@ def init_kb(row, vector_size: int):
     return settings.docStoreConn.createIdx(idxnm, row.get("kb_id", ""), vector_size)
 
 
-@timeout(60*20)
 async def embedding(docs, mdl, parser_config=None, callback=None):
     if parser_config is None:
         parser_config = {}
@@ -441,10 +440,15 @@ async def embedding(docs, mdl, parser_config=None, callback=None):
         tts = np.concatenate([vts for _ in range(len(tts))], axis=0)
         tk_count += c
 
+    @timeout(5)
+    def batch_encode(txts):
+        nonlocal mdl
+        return mdl.encode([truncate(c, mdl.max_length-10) for c in txts])
+
     cnts_ = np.array([])
     for i in range(0, len(cnts), EMBEDDING_BATCH_SIZE):
         async with embed_limiter:
-            vts, c = await trio.to_thread.run_sync(lambda: mdl.encode([truncate(c, mdl.max_length-10) for c in cnts[i: i + EMBEDDING_BATCH_SIZE]]))
+            vts, c = await trio.to_thread.run_sync(lambda: batch_encode(cnts[i: i + EMBEDDING_BATCH_SIZE]))
         if len(cnts_) == 0:
             cnts_ = vts
         else:

web/src/components/originui/number-input.tsx

@@ -63,7 +63,7 @@ const NumberInput: React.FC<NumberInputProps> = ({
     >
       <button
         type="button"
-        className="w-10 p-2 text-white focus:outline-none border-r-[1px]"
+        className="w-10 p-2 focus:outline-none border-r-[1px]"
         onClick={handleDecrement}
         style={style}
       >
@@ -74,12 +74,12 @@ const NumberInput: React.FC<NumberInputProps> = ({
         value={value}
         onInput={handleInput}
         onChange={handleChange}
-        className="w-full flex-1 text-center bg-transparent text-white focus:outline-none"
+        className="w-full flex-1 text-center bg-transparent focus:outline-none"
         style={style}
       />
       <button
         type="button"
-        className="w-10 p-2 text-white focus:outline-none border-l-[1px]"
+        className="w-10 p-2 focus:outline-none border-l-[1px]"
         onClick={handleIncrement}
         style={style}
       >

web/src/hooks/logic-hooks/navigate-hooks.ts

@@ -35,9 +35,12 @@ export const useNavigatePage = () => {
     navigate(Routes.Chats);
   }, [navigate]);
 
-  const navigateToChat = useCallback(() => {
-    navigate(Routes.Chat);
-  }, [navigate]);
+  const navigateToChat = useCallback(
+    (id: string) => () => {
+      navigate(`${Routes.Chat}/${id}`);
+    },
+    [navigate],
+  );
 
   const navigateToAgents = useCallback(() => {
     navigate(Routes.Agents);

web/src/hooks/use-chat-request.ts

@@ -1,9 +1,22 @@
+import message from '@/components/ui/message';
 import { ChatSearchParams } from '@/constants/chat';
 import { IDialog } from '@/interfaces/database/chat';
 import chatService from '@/services/chat-service';
-import { useQuery } from '@tanstack/react-query';
+import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
+import { useDebounce } from 'ahooks';
 import { useCallback, useMemo } from 'react';
+import { useTranslation } from 'react-i18next';
 import { history, useSearchParams } from 'umi';
+import {
+  useGetPaginationWithRouter,
+  useHandleSearchChange,
+} from './logic-hooks';
+
+export const enum ChatApiAction {
+  FetchDialogList = 'fetchDialogList',
+  RemoveDialog = 'removeDialog',
+  SetDialog = 'setDialog',
+}
 
 export const useGetChatSearchParams = () => {
   const [currentQueryParameters] = useSearchParams();
@@ -42,13 +55,22 @@ export const useClickDialogCard = () => {
 export const useFetchDialogList = (pureFetch = false) => {
   const { handleClickDialog } = useClickDialogCard();
   const { dialogId } = useGetChatSearchParams();
+  const { searchString, handleInputChange } = useHandleSearchChange();
+  const { pagination, setPagination } = useGetPaginationWithRouter();
+  const debouncedSearchString = useDebounce(searchString, { wait: 500 });
 
   const {
     data,
     isFetching: loading,
     refetch,
   } = useQuery<IDialog[]>({
-    queryKey: ['fetchDialogList'],
+    queryKey: [
+      ChatApiAction.FetchDialogList,
+      {
+        debouncedSearchString,
+        ...pagination,
+      },
+    ],
     initialData: [],
     gcTime: 0,
     refetchOnWindowFocus: false,
@@ -73,5 +95,76 @@ export const useFetchDialogList = (pureFetch = false) => {
     },
   });
 
-  return { data, loading, refetch };
+  const onInputChange: React.ChangeEventHandler<HTMLInputElement> = useCallback(
+    (e) => {
+      handleInputChange(e);
+    },
+    [handleInputChange],
+  );
+
+  return {
+    data,
+    loading,
+    refetch,
+    searchString,
+    handleInputChange: onInputChange,
+    pagination: { ...pagination, total: data?.total },
+    setPagination,
+  };
+};
+
+export const useRemoveDialog = () => {
+  const queryClient = useQueryClient();
+  const { t } = useTranslation();
+
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [ChatApiAction.RemoveDialog],
+    mutationFn: async (dialogIds: string[]) => {
+      const { data } = await chatService.removeDialog({ dialogIds });
+      if (data.code === 0) {
+        queryClient.invalidateQueries({ queryKey: ['fetchDialogList'] });
+
+        message.success(t('message.deleted'));
+      }
+      return data.code;
+    },
+  });
+
+  return { data, loading, removeDialog: mutateAsync };
+};
+
+export const useSetDialog = () => {
+  const queryClient = useQueryClient();
+  const { t } = useTranslation();
+
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [ChatApiAction.SetDialog],
+    mutationFn: async (params: IDialog) => {
+      const { data } = await chatService.setDialog(params);
+      if (data.code === 0) {
+        queryClient.invalidateQueries({
+          exact: false,
+          queryKey: ['fetchDialogList'],
+        });
+
+        queryClient.invalidateQueries({
+          queryKey: ['fetchDialog'],
+        });
+        message.success(
+          t(`message.${params.dialog_id ? 'modified' : 'created'}`),
+        );
+      }
+      return data?.code;
+    },
+  });
+
+  return { data, loading, setDialog: mutateAsync };
 };

web/src/locales/en.ts

@@ -562,6 +562,7 @@ This auto-tagging feature enhances retrieval by adding another layer of domain-s
       tavilyApiKeyHelp: 'How to get it?',
       crossLanguage: 'Cross-language search',
       crossLanguageTip: `Select one or more languages for cross‑language search. If no language is selected, the system searches with the original query.`,
+      createChat: 'Create chat',
     },
     setting: {
       profile: 'Profile',

web/src/locales/zh.ts

@@ -843,7 +843,7 @@ General：实体和关系提取提示来自 GitHub - microsoft/graphrag：基于
       relevant: '是否相关',
       rewriteQuestion: '问题优化',
       begin: '开始',
-      message: '静态消息',
+      message: '回复消息',
       blank: '空',
       createFromNothing: '从无到有',
       addItem: '新增',
@@ -1245,7 +1245,7 @@ General：实体和关系提取提示来自 GitHub - microsoft/graphrag：基于
       modeTip: '模式定义了工作流的启动方式。',
       beginInputTip: '通过定义输入参数，此内容可以被后续流程中的其他组件访问。',
       query: '查询变量',
-      agent: 'Agent',
+      agent: '智能体',
       agentDescription: '构建具备推理、工具调用和多智能体协同的智能体组件。',
       maxRecords: '最大记录数',
       createAgent: 'Create Agent',

web/src/pages/agent/constant.tsx

@@ -48,8 +48,6 @@ export const BeginId = 'begin';
 export enum Operator {
   Begin = 'Begin',
   Retrieval = 'Retrieval',
-  Generate = 'Generate',
-  Answer = 'Answer',
   Categorize = 'Categorize',
   Message = 'Message',
   Relevant = 'Relevant',
@@ -78,7 +76,6 @@ export enum Operator {
   Note = 'Note',
   Crawler = 'Crawler',
   Invoke = 'Invoke',
-  Template = 'Template',
   Email = 'Email',
   Iteration = 'Iteration',
   IterationStart = 'IterationItem',
@@ -100,15 +97,12 @@ export const CommonOperatorList = Object.values(Operator).filter(
 
 export const AgentOperatorList = [
   Operator.Retrieval,
-  Operator.Generate,
-  Operator.Answer,
   Operator.Categorize,
   Operator.Message,
   Operator.RewriteQuestion,
   Operator.KeywordExtract,
   Operator.Switch,
   Operator.Concentrator,
-  Operator.Template,
   Operator.Iteration,
   Operator.WaitingDialogue,
   Operator.Note,
@@ -119,12 +113,6 @@ export const componentMenuList = [
   {
     name: Operator.Retrieval,
   },
-  {
-    name: Operator.Generate,
-  },
-  {
-    name: Operator.Answer,
-  },
   {
     name: Operator.Categorize,
   },
@@ -144,9 +132,6 @@ export const componentMenuList = [
   {
     name: Operator.Concentrator,
   },
-  {
-    name: Operator.Template,
-  },
   {
     name: Operator.Iteration,
   },
@@ -660,7 +645,7 @@ export const initialAgentValues = {
   max_retries: 3,
   delay_after_error: 1,
   visual_files_var: '',
-  max_rounds: 5,
+  max_rounds: 1,
   exception_method: '',
   exception_goto: [],
   exception_default_value: '',
@@ -796,19 +781,16 @@ export const CategorizeAnchorPointPositions = [
 // no connection lines are allowed between key and value
 export const RestrictedUpstreamMap = {
   [Operator.Begin]: [Operator.Relevant],
-  [Operator.Categorize]: [Operator.Begin, Operator.Categorize, Operator.Answer],
-  [Operator.Answer]: [Operator.Begin, Operator.Answer, Operator.Message],
+  [Operator.Categorize]: [Operator.Begin, Operator.Categorize],
   [Operator.Retrieval]: [Operator.Begin, Operator.Retrieval],
-  [Operator.Generate]: [Operator.Begin, Operator.Relevant],
   [Operator.Message]: [
     Operator.Begin,
     Operator.Message,
-    Operator.Generate,
     Operator.Retrieval,
     Operator.RewriteQuestion,
     Operator.Categorize,
   ],
-  [Operator.Relevant]: [Operator.Begin, Operator.Answer],
+  [Operator.Relevant]: [Operator.Begin],
   [Operator.RewriteQuestion]: [
     Operator.Begin,
     Operator.Message,
@@ -843,7 +825,6 @@ export const RestrictedUpstreamMap = {
   [Operator.Crawler]: [Operator.Begin],
   [Operator.Note]: [],
   [Operator.Invoke]: [Operator.Begin],
-  [Operator.Template]: [Operator.Begin, Operator.Relevant],
   [Operator.Email]: [Operator.Begin],
   [Operator.Iteration]: [Operator.Begin],
   [Operator.IterationStart]: [Operator.Begin],
@@ -861,8 +842,6 @@ export const NodeMap = {
   [Operator.Begin]: 'beginNode',
   [Operator.Categorize]: 'categorizeNode',
   [Operator.Retrieval]: 'retrievalNode',
-  [Operator.Generate]: 'generateNode',
-  [Operator.Answer]: 'logicNode',
   [Operator.Message]: 'messageNode',
   [Operator.Relevant]: 'relevantNode',
   [Operator.RewriteQuestion]: 'rewriteNode',
@@ -890,7 +869,6 @@ export const NodeMap = {
   [Operator.Note]: 'noteNode',
   [Operator.Crawler]: 'ragNode',
   [Operator.Invoke]: 'ragNode',
-  [Operator.Template]: 'templateNode',
   [Operator.Email]: 'ragNode',
   [Operator.Iteration]: 'group',
   [Operator.IterationStart]: 'iterationStartNode',
@@ -924,9 +902,7 @@ export const BeginQueryTypeIconMap = {
 
 export const NoDebugOperatorsList = [
   Operator.Begin,
-  Operator.Answer,
   Operator.Concentrator,
-  Operator.Template,
   Operator.Message,
   Operator.RewriteQuestion,
   Operator.Switch,

web/src/pages/agent/form-sheet/form-config-map.tsx

@@ -1,8 +1,6 @@
-import { z } from 'zod';
 import { Operator } from '../constant';
 import AgentForm from '../form/agent-form';
 import AkShareForm from '../form/akshare-form';
-import AnswerForm from '../form/answer-form';
 import ArXivForm from '../form/arxiv-form';
 import BaiduFanyiForm from '../form/baidu-fanyi-form';
 import BaiduForm from '../form/baidu-form';
@@ -15,7 +13,6 @@ import DeepLForm from '../form/deepl-form';
 import DuckDuckGoForm from '../form/duckduckgo-form';
 import EmailForm from '../form/email-form';
 import ExeSQLForm from '../form/exesql-form';
-import GenerateForm from '../form/generate-form';
 import GithubForm from '../form/github-form';
 import GoogleForm from '../form/google-form';
 import GoogleScholarForm from '../form/google-scholar-form';
@@ -34,7 +31,6 @@ import StringTransformForm from '../form/string-transform-form';
 import SwitchForm from '../form/switch-form';
 import TavilyExtractForm from '../form/tavily-extract-form';
 import TavilyForm from '../form/tavily-form';
-import TemplateForm from '../form/template-form';
 import ToolForm from '../form/tool-form';
 import TuShareForm from '../form/tushare-form';
 import UserFillUpForm from '../form/user-fill-up-form';
@@ -49,12 +45,6 @@ export const FormConfigMap = {
   [Operator.Retrieval]: {
     component: RetrievalForm,
   },
-  [Operator.Generate]: {
-    component: GenerateForm,
-  },
-  [Operator.Answer]: {
-    component: AnswerForm,
-  },
   [Operator.Categorize]: {
     component: CategorizeForm,
   },
@@ -75,8 +65,6 @@ export const FormConfigMap = {
   },
   [Operator.Agent]: {
     component: AgentForm,
-    defaultValues: {},
-    schema: z.object({}),
   },
   [Operator.Baidu]: {
     component: BaiduForm,
@@ -107,8 +95,6 @@ export const FormConfigMap = {
   },
   [Operator.DeepL]: {
     component: DeepLForm,
-    defaultValues: {},
-    schema: z.object({}),
   },
   [Operator.GitHub]: {
     component: GithubForm,
@@ -152,9 +138,6 @@ export const FormConfigMap = {
   [Operator.Note]: {
     component: () => <></>,
   },
-  [Operator.Template]: {
-    component: TemplateForm,
-  },
   [Operator.Email]: {
     component: EmailForm,
   },

web/src/pages/agent/form/answer-form/index.tsx

@@ -1,5 +0,0 @@
-const AnswerForm = () => {
-  return <div></div>;
-};
-
-export default AnswerForm;

web/src/pages/agent/form/categorize-form/index.tsx

@@ -8,6 +8,7 @@ import { useForm } from 'react-hook-form';
 import { initialCategorizeValues } from '../../constant';
 import { INextOperatorForm } from '../../interface';
 import { buildOutputList } from '../../utils/build-output-list';
+import { FormWrapper } from '../components/form-wrapper';
 import { Output } from '../components/output';
 import { QueryVariable } from '../components/query-variable';
 import DynamicCategorize from './dynamic-categorize';
@@ -31,12 +32,7 @@ function CategorizeForm({ node }: INextOperatorForm) {
 
   return (
     <Form {...form}>
-      <form
-        className="space-y-6 p-5 "
-        onSubmit={(e) => {
-          e.preventDefault();
-        }}
-      >
+      <FormWrapper>
         <FormContainer>
           <QueryVariable></QueryVariable>
           <LargeModelFormField></LargeModelFormField>
@@ -44,7 +40,7 @@ function CategorizeForm({ node }: INextOperatorForm) {
         <MessageHistoryWindowSizeFormField></MessageHistoryWindowSizeFormField>
         <DynamicCategorize nodeId={node?.id}></DynamicCategorize>
         <Output list={outputList}></Output>
-      </form>
+      </FormWrapper>
     </Form>
   );
 }

web/src/pages/agent/form/code-form/index.tsx

@@ -2,6 +2,7 @@ import Editor, { loader } from '@monaco-editor/react';
 import { INextOperatorForm } from '../../interface';
 
 import { FormContainer } from '@/components/form-container';
+import { useIsDarkTheme } from '@/components/theme-provider';
 import {
   Form,
   FormControl,
@@ -46,6 +47,7 @@ function CodeForm({ node }: INextOperatorForm) {
   const formData = node?.data.form as ICodeForm;
   const { t } = useTranslation();
   const values = useValues(node);
+  const isDarkTheme = useIsDarkTheme();
 
   const form = useForm<FormSchemaType>({
     defaultValues: values,
@@ -94,7 +96,7 @@ function CodeForm({ node }: INextOperatorForm) {
               <FormControl>
                 <Editor
                   height={300}
-                  theme="vs-dark"
+                  theme={isDarkTheme ? 'vs-dark' : 'vs'}
                   language={formData.lang}
                   options={{
                     minimap: { enabled: false },

web/src/pages/agent/form/concentrator-form/index.tsx

@@ -1,17 +0,0 @@
-import { Form } from 'antd';
-import { IOperatorForm } from '../../interface';
-
-const ConcentratorForm = ({ onValuesChange, form }: IOperatorForm) => {
-  return (
-    <Form
-      name="basic"
-      labelCol={{ span: 8 }}
-      wrapperCol={{ span: 16 }}
-      autoComplete="off"
-      form={form}
-      onValuesChange={onValuesChange}
-    ></Form>
-  );
-};
-
-export default ConcentratorForm;

web/src/pages/agent/form/generate-form/index.tsx

@@ -1,78 +0,0 @@
-import { NextLLMSelect } from '@/components/llm-select/next';
-import { MessageHistoryWindowSizeFormField } from '@/components/message-history-window-size-item';
-import {
-  Form,
-  FormControl,
-  FormField,
-  FormItem,
-  FormLabel,
-  FormMessage,
-} from '@/components/ui/form';
-import { Switch } from '@/components/ui/switch';
-import { useTranslation } from 'react-i18next';
-import { INextOperatorForm } from '../../interface';
-import { PromptEditor } from '../components/prompt-editor';
-
-const GenerateForm = ({ form }: INextOperatorForm) => {
-  const { t } = useTranslation();
-
-  return (
-    <Form {...form}>
-      <form
-        className="space-y-6"
-        onSubmit={(e) => {
-          e.preventDefault();
-        }}
-      >
-        <FormField
-          control={form.control}
-          name="llm_id"
-          render={({ field }) => (
-            <FormItem>
-              <FormLabel tooltip={t('chat.modelTip')}>
-                {t('chat.model')}
-              </FormLabel>
-              <FormControl>
-                <NextLLMSelect {...field} />
-              </FormControl>
-              <FormMessage />
-            </FormItem>
-          )}
-        />
-        <FormField
-          control={form.control}
-          name="prompt"
-          render={({ field }) => (
-            <FormItem>
-              <FormLabel tooltip={t('flow.promptTip')}>
-                {t('flow.systemPrompt')}
-              </FormLabel>
-              <FormControl>
-                <PromptEditor {...field} />
-              </FormControl>
-              <FormMessage />
-            </FormItem>
-          )}
-        />
-        <FormField
-          control={form.control}
-          name="cite"
-          render={({ field }) => (
-            <FormItem>
-              <FormLabel tooltip={t('flow.citeTip')}>
-                {t('flow.cite')}
-              </FormLabel>
-              <FormControl>
-                <Switch {...field} />
-              </FormControl>
-              <FormMessage />
-            </FormItem>
-          )}
-        />
-        <MessageHistoryWindowSizeFormField></MessageHistoryWindowSizeFormField>
-      </form>
-    </Form>
-  );
-};
-
-export default GenerateForm;

web/src/pages/agent/form/invoke-form/index.less

@@ -1,44 +0,0 @@
-.editableRow {
-  :global(.editable-cell) {
-    position: relative;
-  }
-
-  :global(.editable-cell-value-wrap) {
-    padding: 5px 12px;
-    cursor: pointer;
-    height: 30px !important;
-  }
-  &:hover {
-    :global(.editable-cell-value-wrap) {
-      padding: 4px 11px;
-      border: 1px solid #d9d9d9;
-      border-radius: 2px;
-    }
-  }
-}
-
-.dynamicParameterVariable {
-  background-color: #ebe9e950;
-  :global(.ant-collapse-content) {
-    background-color: #f6f6f634;
-  }
-  :global(.ant-collapse-content-box) {
-    padding: 0 !important;
-  }
-  margin-bottom: 20px;
-  .title {
-    font-weight: 600;
-    font-size: 16px;
-  }
-  .variableType {
-    width: 30%;
-  }
-  .variableValue {
-    flex: 1;
-  }
-
-  .addButton {
-    color: rgb(22, 119, 255);
-    font-weight: 600;
-  }
-}

web/src/pages/agent/form/iteration-form/index.tsx

@@ -6,6 +6,7 @@ import { useForm, useWatch } from 'react-hook-form';
 import { z } from 'zod';
 import { VariableType } from '../../constant';
 import { INextOperatorForm } from '../../interface';
+import { FormWrapper } from '../components/form-wrapper';
 import { Output } from '../components/output';
 import { QueryVariable } from '../components/query-variable';
 import { DynamicOutput } from './dynamic-output';
@@ -39,12 +40,7 @@ function IterationForm({ node }: INextOperatorForm) {
 
   return (
     <Form {...form}>
-      <form
-        className="space-y-6 p-4"
-        onSubmit={(e) => {
-          e.preventDefault();
-        }}
-      >
+      <FormWrapper>
         <FormContainer>
           <QueryVariable
             name="items_ref"
@@ -53,7 +49,7 @@ function IterationForm({ node }: INextOperatorForm) {
         </FormContainer>
         <DynamicOutput node={node}></DynamicOutput>
         <Output list={outputList}></Output>
-      </form>
+      </FormWrapper>
     </Form>
   );
 }

web/src/pages/agent/form/message-form/index.tsx

@@ -15,6 +15,7 @@ import { useFieldArray, useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
 import { z } from 'zod';
 import { INextOperatorForm } from '../../interface';
+import { FormWrapper } from '../components/form-wrapper';
 import { PromptEditor } from '../components/prompt-editor';
 import { useValues } from './use-values';
 import { useWatchFormChange } from './use-watch-change';
@@ -48,13 +49,7 @@ function MessageForm({ node }: INextOperatorForm) {
 
   return (
     <Form {...form}>
-      <form
-        className="space-y-5 px-5 "
-        autoComplete="off"
-        onSubmit={(e) => {
-          e.preventDefault();
-        }}
-      >
+      <FormWrapper>
         <FormContainer>
           <FormItem>
             <FormLabel tooltip={t('flow.msgTip')}>{t('flow.msg')}</FormLabel>
@@ -98,7 +93,7 @@ function MessageForm({ node }: INextOperatorForm) {
             <FormMessage />
           </FormItem>
         </FormContainer>
-      </form>
+      </FormWrapper>
     </Form>
   );
 }

web/src/pages/agent/form/string-transform-form/index.tsx

@@ -20,6 +20,7 @@ import {
   initialStringTransformValues,
 } from '../../constant';
 import { INextOperatorForm } from '../../interface';
+import { FormWrapper } from '../components/form-wrapper';
 import { Output, transferOutputs } from '../components/output';
 import { PromptEditor } from '../components/prompt-editor';
 import { QueryVariable } from '../components/query-variable';
@@ -76,13 +77,7 @@ function StringTransformForm({ node }: INextOperatorForm) {
 
   return (
     <Form {...form}>
-      <form
-        className="space-y-5 px-5 "
-        autoComplete="off"
-        onSubmit={(e) => {
-          e.preventDefault();
-        }}
-      >
+      <FormWrapper>
         <FormContainer>
           <FormField
             control={form.control}
@@ -157,7 +152,7 @@ function StringTransformForm({ node }: INextOperatorForm) {
             render={() => <div></div>}
           />
         </FormContainer>
-      </form>
+      </FormWrapper>
       <div className="p-5">
         <Output list={outputList}></Output>
       </div>

web/src/pages/agent/form/switch-form/index.tsx

@@ -28,6 +28,7 @@ import {
 } from '../../constant';
 import { useBuildQueryVariableOptions } from '../../hooks/use-get-begin-query';
 import { IOperatorForm } from '../../interface';
+import { FormWrapper } from '../components/form-wrapper';
 import { useValues } from './use-values';
 import { useWatchFormChange } from './use-watch-change';
 
@@ -249,12 +250,7 @@ function SwitchForm({ node }: IOperatorForm) {
 
   return (
     <Form {...form}>
-      <form
-        className="space-y-6 p-5 "
-        onSubmit={(e) => {
-          e.preventDefault();
-        }}
-      >
+      <FormWrapper>
         {fields.map((field, index) => {
           const name = `${ConditionKey}.${index}`;
           const conditions: Array<any> = form.getValues(`${name}.${ItemKey}`);
@@ -323,7 +319,7 @@ function SwitchForm({ node }: IOperatorForm) {
         >
           Add
         </BlockButton>
-      </form>
+      </FormWrapper>
     </Form>
   );
 }

web/src/pages/agent/form/template-form/index.tsx

@@ -1,24 +0,0 @@
-import { Form } from 'antd';
-import { useTranslation } from 'react-i18next';
-import { IOperatorForm } from '../../interface';
-import { PromptEditor } from '../components/prompt-editor';
-
-const TemplateForm = ({ onValuesChange, form }: IOperatorForm) => {
-  const { t } = useTranslation();
-
-  return (
-    <Form
-      name="basic"
-      autoComplete="off"
-      form={form}
-      onValuesChange={onValuesChange}
-      layout={'vertical'}
-    >
-      <Form.Item name={['content']} label={t('flow.content')}>
-        <PromptEditor></PromptEditor>
-      </Form.Item>
-    </Form>
-  );
-};
-
-export default TemplateForm;

web/src/pages/agent/form/tool-form/retrieval-form/index.tsx

@@ -11,6 +11,7 @@ import { zodResolver } from '@hookform/resolvers/zod';
 import { useForm } from 'react-hook-form';
 import { z } from 'zod';
 import { DescriptionField } from '../../components/description-field';
+import { FormWrapper } from '../../components/form-wrapper';
 import {
   EmptyResponseField,
   RetrievalPartialSchema,
@@ -35,12 +36,7 @@ const RetrievalForm = () => {
 
   return (
     <Form {...form}>
-      <form
-        className="space-y-6 p-4"
-        onSubmit={(e) => {
-          e.preventDefault();
-        }}
-      >
+      <FormWrapper>
         <FormContainer>
           <DescriptionField></DescriptionField>
           <KnowledgeBaseFormField showVariable></KnowledgeBaseFormField>
@@ -58,7 +54,7 @@ const RetrievalForm = () => {
             <UseKnowledgeGraphFormField name="use_kg"></UseKnowledgeGraphFormField>
           </FormContainer>
         </Collapse>
-      </form>
+      </FormWrapper>
     </Form>
   );
 };

web/src/pages/agent/hooks.tsx

@@ -1,6 +1,7 @@
 import {
   Connection,
   Edge,
+  getOutgoers,
   Node,
   Position,
   ReactFlowInstance,
@@ -15,9 +16,6 @@ import { get, lowerFirst, omit } from 'lodash';
 import { UseFormReturn } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
 import {
-  NodeMap,
-  Operator,
-  RestrictedUpstreamMap,
   initialAgentValues,
   initialAkShareValues,
   initialArXivValues,
@@ -33,7 +31,6 @@ import {
   initialDuckValues,
   initialEmailValues,
   initialExeSqlValues,
-  initialGenerateValues,
   initialGithubValues,
   initialGoogleScholarValues,
   initialGoogleValues,
@@ -48,15 +45,19 @@ import {
   initialRelevantValues,
   initialRetrievalValues,
   initialRewriteQuestionValues,
+  initialStringTransformValues,
   initialSwitchValues,
   initialTavilyExtractValues,
   initialTavilyValues,
-  initialTemplateValues,
   initialTuShareValues,
+  initialUserFillUpValues,
   initialWaitingDialogueValues,
   initialWenCaiValues,
   initialWikipediaValues,
   initialYahooFinanceValues,
+  NodeMap,
+  Operator,
+  RestrictedUpstreamMap,
 } from './constant';
 import useGraphStore, { RFState } from './store';
 import {
@@ -92,8 +93,6 @@ export const useInitializeOperatorParams = () => {
     return {
       [Operator.Begin]: initialBeginValues,
       [Operator.Retrieval]: initialRetrievalValues,
-      [Operator.Generate]: { ...initialGenerateValues, llm_id: llmId },
-      [Operator.Answer]: {},
       [Operator.Categorize]: { ...initialCategorizeValues, llm_id: llmId },
       [Operator.Relevant]: { ...initialRelevantValues, llm_id: llmId },
       [Operator.RewriteQuestion]: {
@@ -128,7 +127,6 @@ export const useInitializeOperatorParams = () => {
       [Operator.Note]: initialNoteValues,
       [Operator.Crawler]: initialCrawlerValues,
       [Operator.Invoke]: initialInvokeValues,
-      [Operator.Template]: initialTemplateValues,
       [Operator.Email]: initialEmailValues,
       [Operator.Iteration]: initialIterationValues,
       [Operator.IterationStart]: initialIterationValues,
@@ -137,6 +135,9 @@ export const useInitializeOperatorParams = () => {
       [Operator.Agent]: { ...initialAgentValues, llm_id: llmId },
       [Operator.TavilySearch]: initialTavilyValues,
       [Operator.TavilyExtract]: initialTavilyExtractValues,
+      [Operator.Tool]: {},
+      [Operator.UserFillUp]: initialUserFillUpValues,
+      [Operator.StringTransform]: initialStringTransformValues,
     };
   }, [llmId]);
 
@@ -333,9 +334,8 @@ export const useHandleFormValuesChange = (
 };
 
 export const useValidateConnection = () => {
-  const { getOperatorTypeFromId, getParentIdById } = useGraphStore(
-    (state) => state,
-  );
+  const { getOperatorTypeFromId, getParentIdById, edges, nodes } =
+    useGraphStore((state) => state);
 
   const isSameNodeChild = useCallback(
     (connection: Connection | Edge) => {
@@ -349,6 +349,27 @@ export const useValidateConnection = () => {
     [getParentIdById],
   );
 
+  const hasCanvasCycle = useCallback(
+    (connection: Connection | Edge) => {
+      const target = nodes.find((node) => node.id === connection.target);
+      const hasCycle = (node: RAGFlowNodeType, visited = new Set()) => {
+        if (visited.has(node.id)) return false;
+
+        visited.add(node.id);
+
+        for (const outgoer of getOutgoers(node, nodes, edges)) {
+          if (outgoer.id === connection.source) return true;
+          if (hasCycle(outgoer, visited)) return true;
+        }
+      };
+
+      if (target?.id === connection.source) return false;
+
+      return target ? !hasCycle(target) : false;
+    },
+    [edges, nodes],
+  );
+
   // restricted lines cannot be connected successfully.
   const isValidConnection = useCallback(
     (connection: Connection | Edge) => {
@@ -365,10 +386,11 @@ export const useValidateConnection = () => {
         RestrictedUpstreamMap[
           getOperatorTypeFromId(connection.source) as Operator
         ]?.every((x) => x !== getOperatorTypeFromId(connection.target)) &&
-        isSameNodeChild(connection);
+        isSameNodeChild(connection) &&
+        hasCanvasCycle(connection);
       return ret;
     },
-    [getOperatorTypeFromId, isSameNodeChild],
+    [getOperatorTypeFromId, hasCanvasCycle, isSameNodeChild],
   );
 
   return isValidConnection;

web/src/pages/agent/hooks/use-add-node.ts

@@ -23,7 +23,6 @@ import {
   initialDuckValues,
   initialEmailValues,
   initialExeSqlValues,
-  initialGenerateValues,
   initialGithubValues,
   initialGoogleScholarValues,
   initialGoogleValues,
@@ -43,7 +42,6 @@ import {
   initialSwitchValues,
   initialTavilyExtractValues,
   initialTavilyValues,
-  initialTemplateValues,
   initialTuShareValues,
   initialUserFillUpValues,
   initialWaitingDialogueValues,
@@ -70,8 +68,6 @@ export const useInitializeOperatorParams = () => {
     return {
       [Operator.Begin]: initialBeginValues,
       [Operator.Retrieval]: initialRetrievalValues,
-      [Operator.Generate]: { ...initialGenerateValues, llm_id: llmId },
-      [Operator.Answer]: {},
       [Operator.Categorize]: { ...initialCategorizeValues, llm_id: llmId },
       [Operator.Relevant]: { ...initialRelevantValues, llm_id: llmId },
       [Operator.RewriteQuestion]: {
@@ -106,7 +102,6 @@ export const useInitializeOperatorParams = () => {
       [Operator.Note]: initialNoteValues,
       [Operator.Crawler]: initialCrawlerValues,
       [Operator.Invoke]: initialInvokeValues,
-      [Operator.Template]: initialTemplateValues,
       [Operator.Email]: initialEmailValues,
       [Operator.Iteration]: initialIterationValues,
       [Operator.IterationStart]: initialIterationStartValues,

web/src/pages/agents/index.tsx

@@ -10,7 +10,7 @@ import { useCallback } from 'react';
 import { AgentCard } from './agent-card';
 import { useRenameAgent } from './use-rename-agent';
 
-export default function Agent() {
+export default function Agents() {
   const { data, pagination, setPagination, searchString, handleInputChange } =
     useFetchAgentListByPage();
   const { navigateToAgentTemplates } = useNavigatePage();

web/src/pages/datasets/index.tsx

@@ -53,7 +53,7 @@ export default function Datasets() {
   );
 
   return (
-    <section className="py-4 text-foreground">
+    <section className="py-4 flex-1 flex flex-col">
       <ListFilterBar
         title={t('header.knowledgeBase')}
         searchString={searchString}
@@ -69,16 +69,18 @@ export default function Datasets() {
           {t('knowledgeList.createKnowledgeBase')}
         </Button>
       </ListFilterBar>
-      <div className="flex flex-wrap gap-4 max-h-[78vh] overflow-auto px-8">
-        {kbs.map((dataset) => {
-          return (
-            <DatasetCard
-              dataset={dataset}
-              key={dataset.id}
-              showDatasetRenameModal={showDatasetRenameModal}
-            ></DatasetCard>
-          );
-        })}
+      <div className="flex-1">
+        <div className="flex flex-wrap gap-4 max-h-[78vh] overflow-auto px-8">
+          {kbs.map((dataset) => {
+            return (
+              <DatasetCard
+                dataset={dataset}
+                key={dataset.id}
+                showDatasetRenameModal={showDatasetRenameModal}
+              ></DatasetCard>
+            );
+          })}
+        </div>
       </div>
       <div className="mt-8 px-8">
         <RAGFlowPagination

web/src/pages/next-chats/chat-card.tsx

@@ -1,52 +1,45 @@
-import { Avatar, AvatarFallback, AvatarImage } from '@/components/ui/avatar';
-import { Button } from '@/components/ui/button';
+import { MoreButton } from '@/components/more-button';
+import { RAGFlowAvatar } from '@/components/ragflow-avatar';
 import { Card, CardContent } from '@/components/ui/card';
 import { useNavigatePage } from '@/hooks/logic-hooks/navigate-hooks';
 import { IDialog } from '@/interfaces/database/chat';
-import { formatPureDate } from '@/utils/date';
-import { ChevronRight, Trash2 } from 'lucide-react';
+import { formatDate } from '@/utils/date';
+import { ChatDropdown } from './chat-dropdown';
+import { useRenameChat } from './hooks/use-rename-chat';
 
-interface IProps {
+export type IProps = {
   data: IDialog;
-}
+} & Pick<ReturnType<typeof useRenameChat>, 'showChatRenameModal'>;
 
-export function ChatCard({ data }: IProps) {
+export function ChatCard({ data, showChatRenameModal }: IProps) {
   const { navigateToChat } = useNavigatePage();
 
   return (
-    <Card className="bg-colors-background-inverse-weak  border-colors-outline-neutral-standard">
-      <CardContent className="p-4">
-        <div className="flex justify-between mb-4">
-          {data.icon ? (
-            <div
-              className="w-[70px] h-[70px] rounded-xl bg-cover"
-              style={{ backgroundImage: `url(${data.icon})` }}
-            />
-          ) : (
-            <Avatar className="w-[70px] h-[70px]">
-              <AvatarImage src="https://github.com/shadcn.png" />
-              <AvatarFallback>CN</AvatarFallback>
-            </Avatar>
-          )}
-        </div>
-        <h3 className="text-xl font-bold mb-2">{data.name}</h3>
-        <p>An app that does things An app that does things</p>
-        <section className="flex justify-between pt-3">
-          <div>
-            Search app
-            <p className="text-sm opacity-80">
-              {formatPureDate(data.update_time)}
+    <Card key={data.id} className="w-40" onClick={navigateToChat(data.id)}>
+      <CardContent className="p-2.5 pt-2 group">
+        <section className="flex justify-between mb-2">
+          <div className="flex gap-2 items-center">
+            <RAGFlowAvatar
+              className="size-6 rounded-lg"
+              avatar={data.icon}
+              name={data.name || 'CN'}
+            ></RAGFlowAvatar>
+          </div>
+          <ChatDropdown chat={data} showChatRenameModal={showChatRenameModal}>
+            <MoreButton></MoreButton>
+          </ChatDropdown>
+        </section>
+        <div className="flex justify-between items-end">
+          <div className="w-full">
+            <h3 className="text-lg font-semibold mb-2 line-clamp-1">
+              {data.name}
+            </h3>
+            <p className="text-xs text-text-sub-title">{data.description}</p>
+            <p className="text-xs text-text-sub-title">
+              {formatDate(data.update_time)}
             </p>
           </div>
-          <div className="space-x-2">
-            <Button variant="icon" size="icon" onClick={navigateToChat}>
-              <ChevronRight className="h-6 w-6" />
-            </Button>
-            <Button variant="icon" size="icon">
-              <Trash2 />
-            </Button>
-          </div>
-        </section>
+        </div>
       </CardContent>
     </Card>
   );

web/src/pages/next-chats/chat-dropdown.tsx

@@ -0,0 +1,64 @@
+import { ConfirmDeleteDialog } from '@/components/confirm-delete-dialog';
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuSeparator,
+  DropdownMenuTrigger,
+} from '@/components/ui/dropdown-menu';
+import { useRemoveDialog } from '@/hooks/use-chat-request';
+import { IDialog } from '@/interfaces/database/chat';
+import { PenLine, Trash2 } from 'lucide-react';
+import { MouseEventHandler, PropsWithChildren, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { useRenameChat } from './hooks/use-rename-chat';
+
+export function ChatDropdown({
+  children,
+  showChatRenameModal,
+  chat,
+}: PropsWithChildren &
+  Pick<ReturnType<typeof useRenameChat>, 'showChatRenameModal'> & {
+    chat: IDialog;
+  }) {
+  const { t } = useTranslation();
+  const { removeDialog } = useRemoveDialog();
+
+  const handleShowChatRenameModal: MouseEventHandler<HTMLDivElement> =
+    useCallback(
+      (e) => {
+        e.stopPropagation();
+        showChatRenameModal(chat);
+      },
+      [chat, showChatRenameModal],
+    );
+
+  const handleDelete: MouseEventHandler<HTMLDivElement> = useCallback(() => {
+    removeDialog([chat.id]);
+  }, [chat.id, removeDialog]);
+
+  return (
+    <DropdownMenu>
+      <DropdownMenuTrigger asChild>{children}</DropdownMenuTrigger>
+      <DropdownMenuContent>
+        <DropdownMenuItem onClick={handleShowChatRenameModal}>
+          {t('common.rename')} <PenLine />
+        </DropdownMenuItem>
+        <DropdownMenuSeparator />
+        <ConfirmDeleteDialog onOk={handleDelete}>
+          <DropdownMenuItem
+            className="text-text-delete-red"
+            onSelect={(e) => {
+              e.preventDefault();
+            }}
+            onClick={(e) => {
+              e.stopPropagation();
+            }}
+          >
+            {t('common.delete')} <Trash2 />
+          </DropdownMenuItem>
+        </ConfirmDeleteDialog>
+      </DropdownMenuContent>
+    </DropdownMenu>
+  );
+}

web/src/pages/next-chats/hooks/use-rename-chat.ts

@@ -0,0 +1,45 @@
+import { useSetModalState } from '@/hooks/common-hooks';
+import { useSetDialog } from '@/hooks/use-chat-request';
+import { IDialog } from '@/interfaces/database/chat';
+import { useCallback, useState } from 'react';
+
+export const useRenameChat = () => {
+  const [chat, setChat] = useState<IDialog>({} as IDialog);
+  const {
+    visible: chatRenameVisible,
+    hideModal: hideChatRenameModal,
+    showModal: showChatRenameModal,
+  } = useSetModalState();
+  const { setDialog, loading } = useSetDialog();
+
+  const onChatRenameOk = useCallback(
+    async (name: string) => {
+      const ret = await setDialog({
+        ...chat,
+        name,
+      });
+
+      if (ret === 0) {
+        hideChatRenameModal();
+      }
+    },
+    [setDialog, chat, hideChatRenameModal],
+  );
+
+  const handleShowChatRenameModal = useCallback(
+    async (record: IDialog) => {
+      setChat(record);
+      showChatRenameModal();
+    },
+    [showChatRenameModal],
+  );
+
+  return {
+    chatRenameLoading: loading,
+    initialChatName: chat?.name,
+    onChatRenameOk,
+    chatRenameVisible,
+    hideChatRenameModal,
+    showChatRenameModal: handleShowChatRenameModal,
+  };
+};

web/src/pages/next-chats/index.tsx

@@ -1,25 +1,72 @@
 import ListFilterBar from '@/components/list-filter-bar';
+import { RenameDialog } from '@/components/rename-dialog';
 import { Button } from '@/components/ui/button';
-import { useFetchChatAppList } from '@/hooks/chat-hooks';
+import { RAGFlowPagination } from '@/components/ui/ragflow-pagination';
+import { useFetchDialogList } from '@/hooks/use-chat-request';
+import { pick } from 'lodash';
 import { Plus } from 'lucide-react';
+import { useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
 import { ChatCard } from './chat-card';
+import { useRenameChat } from './hooks/use-rename-chat';
 
 export default function ChatList() {
-  const { data: chatList } = useFetchChatAppList();
+  const { data: chatList, setPagination, pagination } = useFetchDialogList();
+  const { t } = useTranslation();
+  const {
+    initialChatName,
+    chatRenameVisible,
+    showChatRenameModal,
+    hideChatRenameModal,
+    onChatRenameOk,
+    chatRenameLoading,
+  } = useRenameChat();
+
+  const handlePageChange = useCallback(
+    (page: number, pageSize?: number) => {
+      setPagination({ page, pageSize });
+    },
+    [setPagination],
+  );
 
   return (
-    <section className="p-8">
-      <ListFilterBar title="Chat apps">
-        <Button variant={'tertiary'} size={'sm'}>
-          <Plus className="mr-2 h-4 w-4" />
-          Create app
-        </Button>
-      </ListFilterBar>
-      <div className="grid gap-6 sm:grid-cols-1 md:grid-cols-2 lg:grid-cols-4 xl:grid-cols-6 2xl:grid-cols-8">
-        {chatList.map((x) => {
-          return <ChatCard key={x.id} data={x}></ChatCard>;
-        })}
+    <section className="flex flex-col w-full flex-1">
+      <div className="px-8 pt-8">
+        <ListFilterBar title="Chat apps">
+          <Button>
+            <Plus className="size-2.5" />
+            {t('chat.createChat')}
+          </Button>
+        </ListFilterBar>
       </div>
+      <div className="flex-1 overflow-auto">
+        <div className="flex flex-wrap gap-4 px-8">
+          {chatList.map((x) => {
+            return (
+              <ChatCard
+                key={x.id}
+                data={x}
+                showChatRenameModal={showChatRenameModal}
+              ></ChatCard>
+            );
+          })}
+        </div>
+      </div>
+      <div className="mt-8 px-8 pb-8">
+        <RAGFlowPagination
+          {...pick(pagination, 'current', 'pageSize')}
+          total={pagination.total}
+          onChange={handlePageChange}
+        ></RAGFlowPagination>
+      </div>
+      {chatRenameVisible && (
+        <RenameDialog
+          hideModal={hideChatRenameModal}
+          onOk={onChatRenameOk}
+          initialName={initialChatName}
+          loading={chatRenameLoading}
+        ></RenameDialog>
+      )}
     </section>
   );
 }

web/src/routes.ts

@@ -214,7 +214,7 @@ const routes = [
     ],
   },
   {
-    path: Routes.Chat,
+    path: Routes.Chat + '/:id',
     layout: false,
     component: `@/pages${Routes.Chats}/chat`,
   },