From a18853abead863c1a2e2b00320ee6bff66095567 Mon Sep 17 00:00:00 2001 From: balibabu Date: Tue, 4 Aug 2026 15:22:26 +0800 Subject: [PATCH] Fix: The dataset for the retrieval operator of the agent created from the template cannot be selected. (#17760) --- .../cajal_scientific_paper_agent.json | 2 + .../reflective_academic_paper_generator.json | 2 + .../smart_customer_service_specialist.json | 4 + .../stock_market_research_assistant.json | 2 + agent/templates/text2sql_data_expert.json | 6 + agent/templates/user_interaction.json | 2 + agent/templates/web_search_assistant.json | 2 + .../your_starter_dataset_chatbot.json | 503 +++++++++--------- web/src/pages/agent/form-sheet/next.tsx | 15 +- .../form/categorize-form/use-watch-change.ts | 2 +- web/src/pages/agent/store.ts | 44 +- 11 files changed, 298 insertions(+), 286 deletions(-) diff --git a/agent/templates/cajal_scientific_paper_agent.json b/agent/templates/cajal_scientific_paper_agent.json index cd30381589..3318f378dd 100644 --- a/agent/templates/cajal_scientific_paper_agent.json +++ b/agent/templates/cajal_scientific_paper_agent.json @@ -66,6 +66,7 @@ "description": "Retrieve papers, reports, datasets, and notes that ground CAJAL scientific writing outputs.", "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -254,6 +255,7 @@ "description": "Retrieve papers, reports, datasets, and notes that ground CAJAL scientific writing outputs.", "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { diff --git a/agent/templates/reflective_academic_paper_generator.json b/agent/templates/reflective_academic_paper_generator.json index 1a74934c32..055e7ff00e 100644 --- a/agent/templates/reflective_academic_paper_generator.json +++ b/agent/templates/reflective_academic_paper_generator.json @@ -61,6 +61,7 @@ "description": "", "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -260,6 +261,7 @@ "description": "", "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { diff --git a/agent/templates/smart_customer_service_specialist.json b/agent/templates/smart_customer_service_specialist.json index 6aeb76c471..0ad354ec2f 100644 --- a/agent/templates/smart_customer_service_specialist.json +++ b/agent/templates/smart_customer_service_specialist.json @@ -241,6 +241,7 @@ "kb_ids": [ "a5aaec4a819b11f095f1047c16ec874f" ], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -272,6 +273,7 @@ "kb_ids": [ "65cb5150819b11f08347047c16ec874f" ], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "meta_data_filter": {}, "outputs": { @@ -593,6 +595,7 @@ "kb_ids": [ "65cb5150819b11f08347047c16ec874f" ], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "meta_data_filter": {}, "outputs": { @@ -693,6 +696,7 @@ "kb_ids": [ "a5aaec4a819b11f095f1047c16ec874f" ], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { diff --git a/agent/templates/stock_market_research_assistant.json b/agent/templates/stock_market_research_assistant.json index 591fbf0148..42bcea9ed1 100644 --- a/agent/templates/stock_market_research_assistant.json +++ b/agent/templates/stock_market_research_assistant.json @@ -185,6 +185,7 @@ "kb_ids": [ "60c53ed89acc11f0bc1e7a2a6d0b2755" ], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -1009,6 +1010,7 @@ "kb_ids": [ "60c53ed89acc11f0bc1e7a2a6d0b2755" ], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { diff --git a/agent/templates/text2sql_data_expert.json b/agent/templates/text2sql_data_expert.json index d062270686..da5cb1e667 100644 --- a/agent/templates/text2sql_data_expert.json +++ b/agent/templates/text2sql_data_expert.json @@ -117,6 +117,7 @@ "cross_languages": [], "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -146,6 +147,7 @@ "cross_languages": [], "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -175,6 +177,7 @@ "cross_languages": [], "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -344,6 +347,7 @@ "cross_languages": [], "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -382,6 +386,7 @@ "cross_languages": [], "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -420,6 +425,7 @@ "cross_languages": [], "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { diff --git a/agent/templates/user_interaction.json b/agent/templates/user_interaction.json index c575fc721d..b0b6a38487 100644 --- a/agent/templates/user_interaction.json +++ b/agent/templates/user_interaction.json @@ -113,6 +113,7 @@ "description": "", "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -418,6 +419,7 @@ "description": "", "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { diff --git a/agent/templates/web_search_assistant.json b/agent/templates/web_search_assistant.json index db29f276ad..0f939e028b 100644 --- a/agent/templates/web_search_assistant.json +++ b/agent/templates/web_search_assistant.json @@ -260,6 +260,7 @@ "cross_languages": [], "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -604,6 +605,7 @@ "cross_languages": [], "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { diff --git a/agent/templates/your_starter_dataset_chatbot.json b/agent/templates/your_starter_dataset_chatbot.json index 089bdae37c..66c9054a65 100644 --- a/agent/templates/your_starter_dataset_chatbot.json +++ b/agent/templates/your_starter_dataset_chatbot.json @@ -1,24 +1,177 @@ - { "id": 9, "title": { "en": "Your starter dataset chatbot", "de": "Dein Starter-Datensatz-Chatbot", - "zh": "入门级知识库聊天助手"}, + "zh": "入门级知识库聊天助手" + }, "description": { "en": "This is a document question-and-answer system based on a knowledge base. When a user asks a question, it retrieves relevant document content to provide accurate answers.", "de": "Dies ist ein dokumentenbasiertes Frage-und-Antwort-System auf Basis einer Wissensdatenbank. Wenn ein Benutzer eine Frage stellt, werden relevante Dokumenteninhalte abgerufen, um genaue Antworten zu liefern.", - "zh": "基于知识库的入门级知识库聊天助手，当用户提出问题时，会检索相关本地文档并提供准确回答。"}, + "zh": "基于知识库的入门级知识库聊天助手，当用户提出问题时，会检索相关本地文档并提供准确回答。" + }, "canvas_type": "Recommended", "dsl": { - "components": { - "Agent:StalePandasDream": { - "downstream": [ - "Message:BrownPugsStick" - ], - "obj": { - "component_name": "Agent", - "params": { + "components": { + "Agent:StalePandasDream": { + "downstream": [ + "Message:BrownPugsStick" + ], + "obj": { + "component_name": "Agent", + "params": { + "delay_after_error": 1, + "description": "", + "exception_comment": "", + "exception_default_value": "", + "exception_goto": [], + "exception_method": null, + "frequencyPenaltyEnabled": false, + "frequency_penalty": 0.7, + "llm_id": "", + "maxTokensEnabled": false, + "max_retries": 3, + "max_rounds": 5, + "max_tokens": 256, + "mcp": [], + "message_history_window_size": 12, + "outputs": { + "content": { + "type": "string", + "value": "" + } + }, + "presencePenaltyEnabled": false, + "presence_penalty": 0.4, + "prompts": [ + { + "content": "The user query is {sys.query}", + "role": "user" + } + ], + "sys_prompt": "# Role\n\nYou are the **Docs QA Agent**, a specialized knowledge base assistant responsible for providing accurate answers based strictly on the connected documentation repository.\n\n# Core Principles\n\n1. **Knowledge Base Only**: Answer questions EXCLUSIVELY based on information retrieved from the connected knowledge base.\n\n2. **No Content Creation**: Never generate, infer, or create information that is not explicitly present in the retrieved documents.\n\n3. **Source Transparency**: Always indicate when information comes from the knowledge base vs. when it's unavailable.\n\n4. **Accuracy Over Completeness**: Prefer incomplete but accurate answers over complete but potentially inaccurate ones.\n\n# Response Guidelines\n\n## When Information is Available\n\n- Provide direct answers based on retrieved content\n\n- Quote relevant sections when helpful\n\n- Cite the source document/section if available\n\n- Use phrases like: \"According to the documentation...\" or \"Based on the knowledge base...\"\n\n## When Information is Unavailable\n\n- Clearly state: \"I cannot find this information in the current knowledge base.\"\n\n- Do NOT attempt to fill gaps with general knowledge\n\n- Suggest alternative questions that might be covered in the docs\n\n- Use phrases like: \"The documentation does not cover...\" or \"This information is not available in the knowledge base.\"\n\n# Response Format\n\n```markdown\n\n## Answer\n\n[Your response based strictly on knowledge base content]\n\n**Always do these:**\n\n- Use the Retrieval tool for every question\n\n- Be transparent about information availability\n\n- Stick to documented facts only\n\n- Acknowledge knowledge base limitations\n\n", + "temperature": 0.1, + "temperatureEnabled": true, + "tools": [ + { + "component_name": "Retrieval", + "name": "Retrieval", + "params": { + "cross_languages": [], + "description": "This is a technical docs knowledge bases.", + "empty_response": "", + "kb_ids": [], + "retrieval_from": "dataset", + "keywords_similarity_weight": 0.7, + "outputs": { + "formalized_content": { + "type": "string", + "value": "" + } + }, + "rerank_id": "", + "similarity_threshold": 0.2, + "top_k": 1024, + "top_n": 8, + "use_kg": false + } + } + ], + "topPEnabled": false, + "top_p": 0.3, + "user_prompt": "", + "visual_files_var": "" + } + }, + "upstream": [ + "begin" + ] + }, + "Message:BrownPugsStick": { + "downstream": [], + "obj": { + "component_name": "Message", + "params": { + "content": [ + "{Agent:StalePandasDream@content}" + ] + } + }, + "upstream": [ + "Agent:StalePandasDream" + ] + }, + "begin": { + "downstream": [ + "Agent:StalePandasDream" + ], + "obj": { + "component_name": "Begin", + "params": {} + }, + "upstream": [] + } + }, + "globals": { + "sys.conversation_turns": 0, + "sys.files": [], + "sys.query": "", + "sys.user_id": "" + }, + "graph": { + "edges": [ + { + "data": { + "isHovered": false + }, + "id": "xy-edge__beginstart-Agent:StalePandasDreamend", + "source": "begin", + "sourceHandle": "start", + "target": "Agent:StalePandasDream", + "targetHandle": "end" + }, + { + "data": { + "isHovered": false + }, + "id": "xy-edge__Agent:StalePandasDreamstart-Message:BrownPugsStickend", + "source": "Agent:StalePandasDream", + "sourceHandle": "start", + "target": "Message:BrownPugsStick", + "targetHandle": "end" + }, + { + "id": "xy-edge__Agent:StalePandasDreamtool-Tool:PrettyMasksFloatend", + "source": "Agent:StalePandasDream", + "sourceHandle": "tool", + "target": "Tool:PrettyMasksFloat", + "targetHandle": "end" + } + ], + "nodes": [ + { + "data": { + "label": "Begin", + "name": "begin" + }, + "dragging": false, + "id": "begin", + "measured": { + "height": 48, + "width": 200 + }, + "position": { + "x": 47.500000000000014, + "y": 199.5 + }, + "selected": false, + "sourcePosition": "left", + "targetPosition": "right", + "type": "beginNode" + }, + { + "data": { + "form": { "delay_after_error": 1, "description": "", "exception_comment": "", @@ -60,6 +213,7 @@ "description": "This is a technical docs knowledge bases.", "empty_response": "", "kb_ids": [], + "retrieval_from": "dataset", "keywords_similarity_weight": 0.7, "outputs": { "formalized_content": { @@ -79,258 +233,107 @@ "top_p": 0.3, "user_prompt": "", "visual_files_var": "" - } + }, + "label": "Agent", + "name": "Docs QA Agent" }, - "upstream": [ - "begin" - ] + "dragging": false, + "id": "Agent:StalePandasDream", + "measured": { + "height": 87, + "width": 200 + }, + "position": { + "x": 351.5, + "y": 231 + }, + "selected": true, + "sourcePosition": "right", + "targetPosition": "left", + "type": "agentNode" }, - "Message:BrownPugsStick": { - "downstream": [], - "obj": { - "component_name": "Message", - "params": { + { + "data": { + "form": { "content": [ "{Agent:StalePandasDream@content}" ] - } + }, + "label": "Message", + "name": "Message_0" }, - "upstream": [ - "Agent:StalePandasDream" - ] + "dragging": false, + "id": "Message:BrownPugsStick", + "measured": { + "height": 56, + "width": 200 + }, + "position": { + "x": 671.5, + "y": 192.5 + }, + "selected": false, + "sourcePosition": "right", + "targetPosition": "left", + "type": "messageNode" }, - "begin": { - "downstream": [ - "Agent:StalePandasDream" - ], - "obj": { - "component_name": "Begin", - "params": {} + { + "data": { + "form": { + "description": "This is an agent for a specific task.", + "user_prompt": "This is the order you need to send to the agent." + }, + "label": "Tool", + "name": "flow.tool_0" }, - "upstream": [] - } - }, - "globals": { - "sys.conversation_turns": 0, - "sys.files": [], - "sys.query": "", - "sys.user_id": "" - }, - "graph": { - "edges": [ - { - "data": { - "isHovered": false - }, - "id": "xy-edge__beginstart-Agent:StalePandasDreamend", - "source": "begin", - "sourceHandle": "start", - "target": "Agent:StalePandasDream", - "targetHandle": "end" + "dragging": false, + "id": "Tool:PrettyMasksFloat", + "measured": { + "height": 48, + "width": 200 }, - { - "data": { - "isHovered": false - }, - "id": "xy-edge__Agent:StalePandasDreamstart-Message:BrownPugsStickend", - "source": "Agent:StalePandasDream", - "sourceHandle": "start", - "target": "Message:BrownPugsStick", - "targetHandle": "end" + "position": { + "x": 234.5, + "y": 370.5 }, - { - "id": "xy-edge__Agent:StalePandasDreamtool-Tool:PrettyMasksFloatend", - "source": "Agent:StalePandasDream", - "sourceHandle": "tool", - "target": "Tool:PrettyMasksFloat", - "targetHandle": "end" - } - ], - "nodes": [ - { - "data": { - "label": "Begin", - "name": "begin" + "selected": false, + "sourcePosition": "right", + "targetPosition": "left", + "type": "toolNode" + }, + { + "data": { + "form": { + "text": "This is a document question-and-answer system based on a knowledge base. When a user asks a question, it retrieves relevant document content to provide accurate answers.\nProcess Steps\n\n#Begin\n\nWorkflow entry: Receive user questions\n\nDocs QA Agent\n\nAI Model: deepseek-chat\n\nFunction: Analyze user questions and understand query intent\n\nRetrieval\n\nFunction: Search for relevant information from connected document knowledge bases\n\nFeature: Ensures answers are based on actual document content\n\nMessage_0 (Output Response)\n\nReturns accurate answers to the user based on the knowledge base\n\n#Core Features\n\nAccuracy: Answers are strictly based on knowledge base content\n\nReliability: Avoid AI illusions and only provide information that is verifiable\n\nSimplicity: Linear process with fast response\n\n#Applicable Scenarios\n\nProduct Documentation Query\n\nTechnical Support Q&A\n\nInternal Enterprise Knowledge Base Search\n\nUser Manual Consultation" }, - "dragging": false, - "id": "begin", - "measured": { - "height": 48, - "width": 200 - }, - "position": { - "x": 47.500000000000014, - "y": 199.5 - }, - "selected": false, - "sourcePosition": "left", - "targetPosition": "right", - "type": "beginNode" + "label": "Note", + "name": "Workflow Overall Description" }, - { - "data": { - "form": { - "delay_after_error": 1, - "description": "", - "exception_comment": "", - "exception_default_value": "", - "exception_goto": [], - "exception_method": null, - "frequencyPenaltyEnabled": false, - "frequency_penalty": 0.7, - "llm_id": "", - "maxTokensEnabled": false, - "max_retries": 3, - "max_rounds": 5, - "max_tokens": 256, - "mcp": [], - "message_history_window_size": 12, - "outputs": { - "content": { - "type": "string", - "value": "" - } - }, - "presencePenaltyEnabled": false, - "presence_penalty": 0.4, - "prompts": [ - { - "content": "The user query is {sys.query}", - "role": "user" - } - ], - "sys_prompt": "# Role\n\nYou are the **Docs QA Agent**, a specialized knowledge base assistant responsible for providing accurate answers based strictly on the connected documentation repository.\n\n# Core Principles\n\n1. **Knowledge Base Only**: Answer questions EXCLUSIVELY based on information retrieved from the connected knowledge base.\n\n2. **No Content Creation**: Never generate, infer, or create information that is not explicitly present in the retrieved documents.\n\n3. **Source Transparency**: Always indicate when information comes from the knowledge base vs. when it's unavailable.\n\n4. **Accuracy Over Completeness**: Prefer incomplete but accurate answers over complete but potentially inaccurate ones.\n\n# Response Guidelines\n\n## When Information is Available\n\n- Provide direct answers based on retrieved content\n\n- Quote relevant sections when helpful\n\n- Cite the source document/section if available\n\n- Use phrases like: \"According to the documentation...\" or \"Based on the knowledge base...\"\n\n## When Information is Unavailable\n\n- Clearly state: \"I cannot find this information in the current knowledge base.\"\n\n- Do NOT attempt to fill gaps with general knowledge\n\n- Suggest alternative questions that might be covered in the docs\n\n- Use phrases like: \"The documentation does not cover...\" or \"This information is not available in the knowledge base.\"\n\n# Response Format\n\n```markdown\n\n## Answer\n\n[Your response based strictly on knowledge base content]\n\n**Always do these:**\n\n- Use the Retrieval tool for every question\n\n- Be transparent about information availability\n\n- Stick to documented facts only\n\n- Acknowledge knowledge base limitations\n\n", - "temperature": 0.1, - "temperatureEnabled": true, - "tools": [ - { - "component_name": "Retrieval", - "name": "Retrieval", - "params": { - "cross_languages": [], - "description": "This is a technical docs knowledge bases.", - "empty_response": "", - "kb_ids": [], - "keywords_similarity_weight": 0.7, - "outputs": { - "formalized_content": { - "type": "string", - "value": "" - } - }, - "rerank_id": "", - "similarity_threshold": 0.2, - "top_k": 1024, - "top_n": 8, - "use_kg": false - } - } - ], - "topPEnabled": false, - "top_p": 0.3, - "user_prompt": "", - "visual_files_var": "" - }, - "label": "Agent", - "name": "Docs QA Agent" - }, - "dragging": false, - "id": "Agent:StalePandasDream", - "measured": { - "height": 87, - "width": 200 - }, - "position": { - "x": 351.5, - "y": 231 - }, - "selected": true, - "sourcePosition": "right", - "targetPosition": "left", - "type": "agentNode" - }, - { - "data": { - "form": { - "content": [ - "{Agent:StalePandasDream@content}" - ] - }, - "label": "Message", - "name": "Message_0" - }, - "dragging": false, - "id": "Message:BrownPugsStick", - "measured": { - "height": 56, - "width": 200 - }, - "position": { - "x": 671.5, - "y": 192.5 - }, - "selected": false, - "sourcePosition": "right", - "targetPosition": "left", - "type": "messageNode" - }, - { - "data": { - "form": { - "description": "This is an agent for a specific task.", - "user_prompt": "This is the order you need to send to the agent." - }, - "label": "Tool", - "name": "flow.tool_0" - }, - "dragging": false, - "id": "Tool:PrettyMasksFloat", - "measured": { - "height": 48, - "width": 200 - }, - "position": { - "x": 234.5, - "y": 370.5 - }, - "selected": false, - "sourcePosition": "right", - "targetPosition": "left", - "type": "toolNode" - }, - { - "data": { - "form": { - "text": "This is a document question-and-answer system based on a knowledge base. When a user asks a question, it retrieves relevant document content to provide accurate answers.\nProcess Steps\n\n#Begin\n\nWorkflow entry: Receive user questions\n\nDocs QA Agent\n\nAI Model: deepseek-chat\n\nFunction: Analyze user questions and understand query intent\n\nRetrieval\n\nFunction: Search for relevant information from connected document knowledge bases\n\nFeature: Ensures answers are based on actual document content\n\nMessage_0 (Output Response)\n\nReturns accurate answers to the user based on the knowledge base\n\n#Core Features\n\nAccuracy: Answers are strictly based on knowledge base content\n\nReliability: Avoid AI illusions and only provide information that is verifiable\n\nSimplicity: Linear process with fast response\n\n#Applicable Scenarios\n\nProduct Documentation Query\n\nTechnical Support Q&A\n\nInternal Enterprise Knowledge Base Search\n\nUser Manual Consultation" - }, - "label": "Note", - "name": "Workflow Overall Description" - }, - "dragHandle": ".note-drag-handle", - "dragging": false, + "dragHandle": ".note-drag-handle", + "dragging": false, + "height": 154, + "id": "Note:SwiftSuitsFlow", + "measured": { "height": 154, - "id": "Note:SwiftSuitsFlow", - "measured": { - "height": 154, - "width": 374 - }, - "position": { - "x": 349.65276636527506, - "y": 28.869446726944993 - }, - "resizing": false, - "selected": false, - "sourcePosition": "right", - "targetPosition": "left", - "type": "noteNode", "width": 374 - } - ] - }, - "history": [], - "messages": [], - "path": [], - "retrieval": [] + }, + "position": { + "x": 349.65276636527506, + "y": 28.869446726944993 + }, + "resizing": false, + "selected": false, + "sourcePosition": "right", + "targetPosition": "left", + "type": "noteNode", + "width": 374 + } + ] }, + "history": [], + "messages": [], + "path": [], + "retrieval": [] + }, "avatar": 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" -} +} \ No newline at end of file diff --git a/web/src/pages/agent/form-sheet/next.tsx b/web/src/pages/agent/form-sheet/next.tsx index 950323badb..3ee374a80e 100644 --- a/web/src/pages/agent/form-sheet/next.tsx +++ b/web/src/pages/agent/form-sheet/next.tsx @@ -11,6 +11,7 @@ import { RAGFlowNodeType } from '@/interfaces/database/agent'; import { cn } from '@/lib/utils'; import { lowerFirst } from 'lodash'; import { ArrowUpRight, CirclePlay, X } from 'lucide-react'; +import { MouseEventHandler } from 'react'; import { Operator } from '../constant'; import { AgentFormContext } from '../context'; import { RunTooltip } from '../flow-tooltip'; @@ -34,6 +35,11 @@ const EmptyContent = () =>
; const SandboxQuickstartUrl = 'https://github.com/infiniflow/ragflow/blob/main/docs/guides/agent/agent_quickstarts/sandbox_quickstart.md'; +const openSandboxQuickstart: MouseEventHandler = (e) => { + e.stopPropagation(); + window.open(SandboxQuickstartUrl, '_blank', 'noopener,noreferrer'); +}; + const FormSheet = ({ visible, hideModal, @@ -108,14 +114,7 @@ const FormSheet = ({ size="icon" className="ml-1 inline-flex size-5 !p-0 align-middle bg-transparent" type="button" - onClick={(e) => { - e.stopPropagation(); - window.open( - SandboxQuickstartUrl, - '_blank', - 'noopener,noreferrer', - ); - }} + onClick={openSandboxQuickstart} > diff --git a/web/src/pages/agent/form/categorize-form/use-watch-change.ts b/web/src/pages/agent/form/categorize-form/use-watch-change.ts index a97b80a77f..8be8919cbd 100644 --- a/web/src/pages/agent/form/categorize-form/use-watch-change.ts +++ b/web/src/pages/agent/form/categorize-form/use-watch-change.ts @@ -11,7 +11,7 @@ export function useWatchFormChange(id?: string, form?: UseFormReturn) { if (id) { values = form?.getValues(); - updateNodeForm(id, { ...values, items: values.items?.slice() || [] }); + updateNodeForm(id, { ...values, items: values.items || [] }); } }, [id, updateNodeForm, values]); } diff --git a/web/src/pages/agent/store.ts b/web/src/pages/agent/store.ts index 65a551e1ea..9a2f82d58c 100644 --- a/web/src/pages/agent/store.ts +++ b/web/src/pages/agent/store.ts @@ -216,10 +216,7 @@ const useGraphStore = create()( clickedToolId: '', onNodesChange: (changes) => { set({ - nodes: applyNodeChanges( - changes, // The issue of errors when using templates was resolved by using cloneDeep. - cloneDeep(get().nodes) as RAGFlowNodeType[], // Cannot assign to read only property 'width' of object '#' - ), + nodes: applyNodeChanges(changes, get().nodes), }); }, onEdgesChange: (changes: EdgeChange[]) => { @@ -527,38 +524,31 @@ const useGraphStore = create()( values: any, path: (string | number)[] = [], ) => { - const nextNodes = get().nodes.map((node) => { - if (node.id === nodeId) { - let nextForm: Record = { ...node.data.form }; - if (path.length === 0) { - nextForm = Object.assign(nextForm, values); - } else { - lodashSet(nextForm, path, values); - } - return { - ...node, - data: { - ...node.data, - form: nextForm, - }, - } as any; + set((state) => { + const node = state.nodes.find((x) => x.id === nodeId); + if (!node) { + return; + } + const form = (node.data.form ??= {}); + // Deep clone to decouple from react-hook-form's internal values: + // immer freezes the produced state, and RHF keeps mutating the same + // nested references afterwards, which would throw on frozen arrays. + if (path.length === 0) { + Object.assign(form, cloneDeep(values)); + } else { + lodashSet(form, path, cloneDeep(values)); } - - return node; - }); - set({ - nodes: nextNodes, }); - return nextNodes; + return get().nodes; }, replaceNodeForm(nodeId, values) { if (nodeId) { set((state) => { for (const node of state.nodes) { if (node.id === nodeId) { - //cloneDeep Solving the issue of react-hook-form errors - node.data.form = cloneDeep(values); // TypeError: Cannot assign to read only property '0' of object '[object Array]' + // See updateNodeForm for why the deep clone is needed. + node.data.form = cloneDeep(values); break; } }