mirror of
https://github.com/infiniflow/ragflow.git
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52ceac62ab
### What does this PR solve? German translation for all agent template and optimizing line breaks in the title for the new translation. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
875 lines
30 KiB
JSON
875 lines
30 KiB
JSON
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{
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"id": 16,
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"title": {
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"en": "WebSearch Assistant",
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"de": "Websuche Assistent",
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"zh": "网页搜索助手"},
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"description": {
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"en": "A chat assistant template that integrates information extracted from a knowledge base and web searches to respond to queries. Let's start by setting up your knowledge base in 'Retrieval'!",
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"de": "Eine Chat-Assistenten-Vorlage, die Informationen aus einer Wissensdatenbank und Websuchen integriert, um auf Anfragen zu antworten. Beginnen wir mit der Einrichtung Ihrer Wissensdatenbank unter 'Retrieval'!",
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"zh": "集成了从知识库和网络搜索中提取的信息回答用户问题。让我们从设置您的知识库开始检索！"},
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"canvas_type": "Other",
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"dsl": {
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"components": {
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"Agent:SmartSchoolsCross": {
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"downstream": [
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"Message:ShaggyRingsCrash"
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],
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"obj": {
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"component_name": "Agent",
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"params": {
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"delay_after_error": 1,
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"description": "",
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||
"exception_comment": "",
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||
"exception_default_value": "",
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"exception_goto": [],
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||
"exception_method": null,
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||
"frequencyPenaltyEnabled": false,
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||
"frequency_penalty": 0.7,
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"llm_id": "deepseek-chat@DeepSeek",
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"maxTokensEnabled": false,
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||
"max_retries": 3,
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"max_rounds": 1,
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"max_tokens": 256,
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"mcp": [],
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"message_history_window_size": 12,
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"outputs": {
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"content": {
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"type": "string",
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"value": ""
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}
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},
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"presencePenaltyEnabled": false,
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"presence_penalty": 0.4,
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"prompts": [
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{
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"content": "User's query:\n{sys.query}\n\nRefined question:\n{Agent:ThreePathsDecide@content}\n\nWeb search result:\n{Agent:WildGoatsRule@content}\n\nRetrieval result:\n{Agent:WildGoatsRule@content}",
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"role": "user"
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}
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],
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"sys_prompt": "Role: You are an Answer Organizer.\nTask: Generate the answer based on the provided content from: User's query, Refined question, Web search result, Retrieval result.\n\nRequirements:\n - Answer should be in markdown format.\n - Answer should include all \n - Do not make thing up when there's no relevant information to user's question. \n",
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"temperature": 0.1,
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"temperatureEnabled": true,
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"tools": [],
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"topPEnabled": false,
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"top_p": 0.3,
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"user_prompt": "",
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"visual_files_var": ""
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}
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},
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"upstream": [
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"Agent:WildGoatsRule",
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"Retrieval:WarmTimesRun"
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]
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},
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"Agent:ThreePathsDecide": {
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"downstream": [
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"Agent:WildGoatsRule",
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"Retrieval:WarmTimesRun"
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],
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"obj": {
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"component_name": "Agent",
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"params": {
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"delay_after_error": 1,
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"description": "",
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"exception_comment": "",
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"exception_default_value": "",
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"exception_goto": [],
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"exception_method": null,
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"frequencyPenaltyEnabled": false,
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"frequency_penalty": 0.7,
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"llm_id": "deepseek-chat@DeepSeek",
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"maxTokensEnabled": false,
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"max_retries": 3,
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"max_rounds": 1,
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"max_tokens": 256,
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"mcp": [],
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"message_history_window_size": 12,
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"outputs": {
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"content": {
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"type": "string",
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"value": ""
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}
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},
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"presencePenaltyEnabled": false,
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"presence_penalty": 0.4,
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"prompts": [
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{
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"content": "{sys.query}",
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"role": "user"
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}
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],
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"sys_prompt": "Role: You are a Question Refinement Agent. Rewrite ambiguous or incomplete user questions to align with knowledge base terminology using conversation history.\n\nExample：\n\nUser: What's RAGFlow?\nAssistant: RAGFlow is xxx.\n\nUser: How to deloy it?\nRefine it: How to deploy RAGFlow?",
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"temperature": 0.1,
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"temperatureEnabled": true,
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"tools": [],
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"topPEnabled": false,
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"top_p": 0.3,
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"user_prompt": "",
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"visual_files_var": ""
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}
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},
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"upstream": [
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"begin"
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]
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},
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"Agent:WildGoatsRule": {
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"downstream": [
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"Agent:SmartSchoolsCross"
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],
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"obj": {
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"component_name": "Agent",
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"params": {
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"delay_after_error": 1,
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"description": "",
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"exception_comment": "",
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"exception_default_value": "",
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"exception_goto": [],
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"exception_method": null,
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"frequencyPenaltyEnabled": false,
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"frequency_penalty": 0.7,
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"llm_id": "deepseek-chat@DeepSeek",
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"maxTokensEnabled": false,
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"max_retries": 3,
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"max_rounds": 2,
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"max_tokens": 256,
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"mcp": [],
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"message_history_window_size": 12,
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"outputs": {
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"content": {
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"type": "string",
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"value": ""
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}
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},
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"presencePenaltyEnabled": false,
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"presence_penalty": 0.4,
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"prompts": [
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{
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"content": "User's query:\n{sys.query}\n\nRefined question:\n{Agent:ThreePathsDecide@content}",
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"role": "user"
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}
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],
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"sys_prompt": "Role: You are a Search-Driven Information Agent that answers questions using web search results.\n\nWorkflow:\nKeyword Extraction:\nExtract exactly 3 keywords from the user's question.\n\nKeywords must be:\n✅ Most specific nouns/proper nouns (e.g., \"iPhone 15 Pro\" not \"phone\")\n✅ Core concepts (e.g., \"quantum entanglement\" not \"science thing\")\n✅ Unbiased (no added opinions)\nNever output keywords to users\n\nSearch & Answer:\nUse search tools (TavilySearch, TavilyExtract, Google, Bing, DuckDuckGo, Wikipedia) with the 3 keywords to retrieve results.\nAnswer solely based on search findings, citing sources.\nIf results conflict, prioritize recent (.gov/.edu > forums)\n\nOutput Rules:\n✖️ Never show keywords in final answers\n✖️ Never guess if search yields no results\n✅ Always cite sources using [Source #] notation",
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"temperature": 0.1,
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"temperatureEnabled": true,
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"tools": [
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{
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"component_name": "TavilySearch",
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"name": "TavilySearch",
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"params": {
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"api_key": "",
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"days": 7,
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"exclude_domains": [],
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"include_answer": false,
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"include_domains": [],
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"include_image_descriptions": false,
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"include_images": false,
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"include_raw_content": true,
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"max_results": 5,
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"outputs": {
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"formalized_content": {
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"type": "string",
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"value": ""
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},
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"json": {
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"type": "Array<Object>",
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"value": []
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}
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},
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"query": "sys.query",
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"search_depth": "basic",
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"topic": "general"
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}
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},
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{
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"component_name": "TavilyExtract",
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"name": "TavilyExtract",
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"params": {
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"api_key": ""
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}
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},
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{
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"component_name": "Google",
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"name": "Google",
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"params": {
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"api_key": "",
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"country": "us",
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"language": "en"
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}
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},
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{
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"component_name": "Bing",
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"name": "Bing",
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"params": {
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"api_key": "YOUR_API_KEY (obtained from https://www.microsoft.com/en-us/bing/apis/bing-web-search-api)",
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"channel": "Webpages",
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"country": "CH",
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"language": "en",
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"top_n": 10
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}
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},
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{
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"component_name": "DuckDuckGo",
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"name": "DuckDuckGo",
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"params": {
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"channel": "text",
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"top_n": 10
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}
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},
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{
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"component_name": "Wikipedia",
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"name": "Wikipedia",
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"params": {
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"language": "en",
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"top_n": 10
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}
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}
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],
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"topPEnabled": false,
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"top_p": 0.3,
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"user_prompt": "",
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"visual_files_var": ""
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}
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},
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"upstream": [
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"Agent:ThreePathsDecide"
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]
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},
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"Message:ShaggyRingsCrash": {
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"downstream": [],
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"obj": {
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"component_name": "Message",
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"params": {
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"content": [
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"{Agent:SmartSchoolsCross@content}"
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]
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}
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},
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"upstream": [
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"Agent:SmartSchoolsCross"
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]
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},
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"Retrieval:WarmTimesRun": {
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"downstream": [
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"Agent:SmartSchoolsCross"
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],
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"obj": {
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"component_name": "Retrieval",
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"params": {
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"cross_languages": [],
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"empty_response": "",
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"kb_ids": [],
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"keywords_similarity_weight": 0.7,
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"outputs": {
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"formalized_content": {
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"type": "string",
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"value": ""
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}
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},
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"query": "Agent:ThreePathsDecide@content",
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"rerank_id": "",
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"similarity_threshold": 0.2,
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"top_k": 1024,
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"top_n": 8,
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"use_kg": false
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}
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},
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||
"upstream": [
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"Agent:ThreePathsDecide"
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]
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||
},
|
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"begin": {
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"downstream": [
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"Agent:ThreePathsDecide"
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],
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"obj": {
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"component_name": "Begin",
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"params": {
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"enablePrologue": true,
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"inputs": {},
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"mode": "conversational",
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"prologue": "Hi! I'm your web search assistant. What do you want to search today?"
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}
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},
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"upstream": []
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}
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},
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"globals": {
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"sys.conversation_turns": 1,
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"sys.files": [],
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"sys.query": "你好",
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"sys.user_id": "d6d98fd652f911f0a8fb047c16ec874f"
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||
},
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"graph": {
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||
"edges": [
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||
{
|
||
"data": {
|
||
"isHovered": false
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||
},
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||
"id": "xy-edge__beginstart-Agent:ThreePathsDecideend",
|
||
"source": "begin",
|
||
"sourceHandle": "start",
|
||
"target": "Agent:ThreePathsDecide",
|
||
"targetHandle": "end"
|
||
},
|
||
{
|
||
"data": {
|
||
"isHovered": false
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||
},
|
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"id": "xy-edge__Agent:ThreePathsDecidestart-Agent:WildGoatsRuleend",
|
||
"source": "Agent:ThreePathsDecide",
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"sourceHandle": "start",
|
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"target": "Agent:WildGoatsRule",
|
||
"targetHandle": "end"
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||
},
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||
{
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"data": {
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"isHovered": false
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||
},
|
||
"id": "xy-edge__Agent:ThreePathsDecidestart-Retrieval:WarmTimesRunend",
|
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"source": "Agent:ThreePathsDecide",
|
||
"sourceHandle": "start",
|
||
"target": "Retrieval:WarmTimesRun",
|
||
"targetHandle": "end"
|
||
},
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{
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"data": {
|
||
"isHovered": false
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},
|
||
"id": "xy-edge__Agent:WildGoatsRulestart-Agent:SmartSchoolsCrossend",
|
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"source": "Agent:WildGoatsRule",
|
||
"sourceHandle": "start",
|
||
"target": "Agent:SmartSchoolsCross",
|
||
"targetHandle": "end"
|
||
},
|
||
{
|
||
"data": {
|
||
"isHovered": false
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||
},
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"id": "xy-edge__Agent:SmartSchoolsCrossstart-Message:ShaggyRingsCrashend",
|
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"source": "Agent:SmartSchoolsCross",
|
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"sourceHandle": "start",
|
||
"target": "Message:ShaggyRingsCrash",
|
||
"targetHandle": "end"
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||
},
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{
|
||
"data": {
|
||
"isHovered": false
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||
},
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"id": "xy-edge__Retrieval:WarmTimesRunstart-Agent:SmartSchoolsCrossend",
|
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"markerEnd": "logo",
|
||
"source": "Retrieval:WarmTimesRun",
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"sourceHandle": "start",
|
||
"style": {
|
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"stroke": "rgba(91, 93, 106, 1)",
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"strokeWidth": 1
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||
},
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"target": "Agent:SmartSchoolsCross",
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"targetHandle": "end",
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"type": "buttonEdge",
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"zIndex": 1001
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},
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{
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"data": {
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"isHovered": false
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},
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"id": "xy-edge__Agent:WildGoatsRuletool-Tool:TrueCrewsTakeend",
|
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"source": "Agent:WildGoatsRule",
|
||
"sourceHandle": "tool",
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"target": "Tool:TrueCrewsTake",
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"targetHandle": "end"
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||
}
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],
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"nodes": [
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{
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"data": {
|
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"form": {
|
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"enablePrologue": true,
|
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"inputs": {},
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"mode": "conversational",
|
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"prologue": "Hi! I'm your web search assistant. What do you want to search today?"
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},
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"label": "Begin",
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"name": "begin"
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||
},
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"dragging": false,
|
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"id": "begin",
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"measured": {
|
||
"height": 48,
|
||
"width": 200
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||
},
|
||
"position": {
|
||
"x": 32.79251060693639,
|
||
"y": 209.67921278359827
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||
},
|
||
"selected": false,
|
||
"sourcePosition": "left",
|
||
"targetPosition": "right",
|
||
"type": "beginNode"
|
||
},
|
||
{
|
||
"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": "deepseek-chat@DeepSeek",
|
||
"maxTokensEnabled": false,
|
||
"max_retries": 3,
|
||
"max_rounds": 1,
|
||
"max_tokens": 256,
|
||
"mcp": [],
|
||
"message_history_window_size": 12,
|
||
"outputs": {
|
||
"content": {
|
||
"type": "string",
|
||
"value": ""
|
||
}
|
||
},
|
||
"presencePenaltyEnabled": false,
|
||
"presence_penalty": 0.4,
|
||
"prompts": [
|
||
{
|
||
"content": "{sys.query}",
|
||
"role": "user"
|
||
}
|
||
],
|
||
"sys_prompt": "Role: You are a Question Refinement Agent. Rewrite ambiguous or incomplete user questions to align with knowledge base terminology using conversation history.\n\nExample：\n\nUser: What's RAGFlow?\nAssistant: RAGFlow is xxx.\n\nUser: How to deloy it?\nRefine it: How to deploy RAGFlow?",
|
||
"temperature": 0.1,
|
||
"temperatureEnabled": true,
|
||
"tools": [],
|
||
"topPEnabled": false,
|
||
"top_p": 0.3,
|
||
"user_prompt": "",
|
||
"visual_files_var": ""
|
||
},
|
||
"label": "Agent",
|
||
"name": "Refine Question"
|
||
},
|
||
"dragging": false,
|
||
"id": "Agent:ThreePathsDecide",
|
||
"measured": {
|
||
"height": 84,
|
||
"width": 200
|
||
},
|
||
"position": {
|
||
"x": 309.1322126914739,
|
||
"y": 188.16985104226876
|
||
},
|
||
"selected": false,
|
||
"sourcePosition": "right",
|
||
"targetPosition": "left",
|
||
"type": "agentNode"
|
||
},
|
||
{
|
||
"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": "deepseek-chat@DeepSeek",
|
||
"maxTokensEnabled": false,
|
||
"max_retries": 3,
|
||
"max_rounds": 2,
|
||
"max_tokens": 256,
|
||
"mcp": [],
|
||
"message_history_window_size": 12,
|
||
"outputs": {
|
||
"content": {
|
||
"type": "string",
|
||
"value": ""
|
||
}
|
||
},
|
||
"presencePenaltyEnabled": false,
|
||
"presence_penalty": 0.4,
|
||
"prompts": [
|
||
{
|
||
"content": "User's query:\n{sys.query}\n\nRefined question:\n{Agent:ThreePathsDecide@content}",
|
||
"role": "user"
|
||
}
|
||
],
|
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"sys_prompt": "Role: You are a Search-Driven Information Agent that answers questions using web search results.\n\nWorkflow:\nKeyword Extraction:\nExtract exactly 3 keywords from the user's question.\n\nKeywords must be:\n✅ Most specific nouns/proper nouns (e.g., \"iPhone 15 Pro\" not \"phone\")\n✅ Core concepts (e.g., \"quantum entanglement\" not \"science thing\")\n✅ Unbiased (no added opinions)\nNever output keywords to users\n\nSearch & Answer:\nUse search tools (TavilySearch, TavilyExtract, Google, Bing, DuckDuckGo, Wikipedia) with the 3 keywords to retrieve results.\nAnswer solely based on search findings, citing sources.\nIf results conflict, prioritize recent (.gov/.edu > forums)\n\nOutput Rules:\n✖️ Never show keywords in final answers\n✖️ Never guess if search yields no results\n✅ Always cite sources using [Source #] notation",
|
||
"temperature": 0.1,
|
||
"temperatureEnabled": true,
|
||
"tools": [
|
||
{
|
||
"component_name": "TavilySearch",
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"name": "TavilySearch",
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"params": {
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"api_key": "",
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"days": 7,
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"exclude_domains": [],
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"include_answer": false,
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"include_domains": [],
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"include_image_descriptions": false,
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"include_images": false,
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"include_raw_content": true,
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"max_results": 5,
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"outputs": {
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"formalized_content": {
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"type": "string",
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"value": ""
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},
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"json": {
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"type": "Array<Object>",
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"value": []
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}
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},
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"query": "sys.query",
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"search_depth": "basic",
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"topic": "general"
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}
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},
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{
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"component_name": "TavilyExtract",
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"name": "TavilyExtract",
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"params": {
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"api_key": ""
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}
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||
},
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{
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"component_name": "Google",
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"name": "Google",
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"params": {
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"api_key": "",
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"country": "us",
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"language": "en"
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}
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},
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{
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"component_name": "Bing",
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"name": "Bing",
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"params": {
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||
"api_key": "YOUR_API_KEY (obtained from https://www.microsoft.com/en-us/bing/apis/bing-web-search-api)",
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||
"channel": "Webpages",
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||
"country": "CH",
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||
"language": "en",
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"top_n": 10
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}
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},
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{
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"component_name": "DuckDuckGo",
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"name": "DuckDuckGo",
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"params": {
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"channel": "text",
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"top_n": 10
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}
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},
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{
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"component_name": "Wikipedia",
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"name": "Wikipedia",
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"params": {
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"language": "en",
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"top_n": 10
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||
}
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}
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||
],
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},
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"label": "Agent",
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"name": "Search Agent"
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||
},
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"dragging": false,
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},
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"position": {
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"selected": false,
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"targetPosition": "left",
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"type": "agentNode"
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},
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{
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"data": {
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"form": {
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"empty_response": "",
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"kb_ids": [],
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"keywords_similarity_weight": 0.7,
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||
"outputs": {
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||
"formalized_content": {
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||
"type": "string",
|
||
"value": ""
|
||
}
|
||
},
|
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"query": "Agent:ThreePathsDecide@content",
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||
"rerank_id": "",
|
||
"similarity_threshold": 0.2,
|
||
"top_k": 1024,
|
||
"top_n": 8,
|
||
"use_kg": false
|
||
},
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||
"label": "Retrieval",
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||
"name": "Retrieval from knowledge bases "
|
||
},
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||
"dragging": false,
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||
"id": "Retrieval:WarmTimesRun",
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"measured": {
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"height": 56,
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},
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"position": {
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},
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"selected": false,
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"targetPosition": "left",
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"type": "retrievalNode"
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},
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{
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"data": {
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"form": {
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"delay_after_error": 1,
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"exception_default_value": "",
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"exception_goto": [],
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||
"exception_method": null,
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"frequencyPenaltyEnabled": false,
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||
"frequency_penalty": 0.7,
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||
"llm_id": "deepseek-chat@DeepSeek",
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||
"maxTokensEnabled": false,
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||
"max_retries": 3,
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||
"max_rounds": 1,
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||
"max_tokens": 256,
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||
"mcp": [],
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||
"message_history_window_size": 12,
|
||
"outputs": {
|
||
"content": {
|
||
"type": "string",
|
||
"value": ""
|
||
}
|
||
},
|
||
"presencePenaltyEnabled": false,
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||
"presence_penalty": 0.4,
|
||
"prompts": [
|
||
{
|
||
"content": "User's query:\n{sys.query}\n\nRefined question:\n{Agent:ThreePathsDecide@content}\n\nWeb search result:\n{Agent:WildGoatsRule@content}\n\nRetrieval result:\n{Agent:WildGoatsRule@content}",
|
||
"role": "user"
|
||
}
|
||
],
|
||
"sys_prompt": "Role: You are an Answer Organizer.\nTask: Generate the answer based on the provided content from: User's query, Refined question, Web search result, Retrieval result.\n\nRequirements:\n - Answer should be in markdown format.\n - Answer should include all \n - Do not make thing up when there's no relevant information to user's question. \n",
|
||
"temperature": 0.1,
|
||
"temperatureEnabled": true,
|
||
"tools": [],
|
||
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|
||
"top_p": 0.3,
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||
"user_prompt": "",
|
||
"visual_files_var": ""
|
||
},
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||
"label": "Agent",
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||
"name": "Answer Organizer"
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||
},
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||
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||
"id": "Agent:SmartSchoolsCross",
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||
"measured": {
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||
"height": 84,
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||
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||
},
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||
"position": {
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||
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||
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"type": "agentNode"
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||
},
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||
{
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||
"data": {
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||
"form": {
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||
"content": [
|
||
"{Agent:SmartSchoolsCross@content}"
|
||
]
|
||
},
|
||
"label": "Message",
|
||
"name": "Answer"
|
||
},
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||
"dragging": false,
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||
"id": "Message:ShaggyRingsCrash",
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||
"measured": {
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||
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||
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||
},
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||
"position": {
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||
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||
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||
},
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||
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||
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||
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||
"type": "messageNode"
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||
},
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||
{
|
||
"data": {
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||
"form": {
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||
"text": "This Agent rewrites your question for better search & retrieval results."
|
||
},
|
||
"label": "Note",
|
||
"name": "Note: Refine Question"
|
||
},
|
||
"dragHandle": ".note-drag-handle",
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||
"id": "Note:BetterCupsBow",
|
||
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||
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||
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},
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||
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||
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||
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||
},
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||
"selected": false,
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||
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||
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||
"type": "noteNode"
|
||
},
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||
{
|
||
"data": {
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||
"form": {
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||
"text": "This Agent answers questions using web search results."
|
||
},
|
||
"label": "Note",
|
||
"name": "Note: Search Agent"
|
||
},
|
||
"dragHandle": ".note-drag-handle",
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||
"dragging": false,
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||
"id": "Note:OddGoatsBeg",
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||
"measured": {
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||
"height": 136,
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||
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||
},
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||
"position": {
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||
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||
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||
},
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||
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||
"sourcePosition": "right",
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||
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||
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||
},
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||
{
|
||
"data": {
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||
"form": {
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||
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|
||
},
|
||
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|
||
"name": "Note: Answer Organizer"
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||
},
|
||
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||
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||
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||
"id": "Note:SlowBottlesHope",
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||
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||
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||
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||
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},
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||
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||
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||
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||
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||
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||
"width": 251
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},
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||
{
|
||
"data": {
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||
"form": {
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||
"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,
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||
"id": "Tool:TrueCrewsTake",
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||
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|
||
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||
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},
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||
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||
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||
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},
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||
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||
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||
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||
"type": "toolNode"
|
||
},
|
||
{
|
||
"data": {
|
||
"form": {
|
||
"text": "This is a chat assistant template that integrates information extracted from a knowledge base and web searches to respond to queries. Let's start by setting up your knowledge base in 'Retrieval'!"
|
||
},
|
||
"label": "Note",
|
||
"name": "Workflow Overall Description"
|
||
},
|
||
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|
||
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||
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||
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||
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||
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||
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||
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}
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||
]
|
||
},
|
||
"history": [
|
||
[
|
||
"user",
|
||
"你好"
|
||
]
|
||
],
|
||
"memory": [],
|
||
"messages": [],
|
||
"path": [
|
||
"begin",
|
||
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||
],
|
||
"retrieval": [
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||
{
|
||
"chunks": [],
|
||
"doc_aggs": []
|
||
},
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||
{
|
||
"chunks": {},
|
||
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||
}
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||
],
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||
"task_id": "183442fc6dd811f091b1047c16ec874f"
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||
},
|
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3OjSqeY1HmKuYxZUJKswOmAyyTL0okHGLn9G55HsnUGOlqmobE6TU8TOqpsnhoRkNE6fmANASIpoBHVI5NL0oMEn3rIIM4SEiltJlrZXOfN7Wg1MmFwKMe6kTLJoRgR2wraxsY0IZybSJMtkzGX+drLnn/zlncxdmQ3Wq6+DfWNkwztBn5YbFJiQ+3/2hgvr0FoTzC6P7QJLg5y3dNNt81+WN6NqbjnsGNPT7S4dZhr2MHxPFNopCLrqJyHpnbL2CQkM/ggaeG1LTvw4s//Eqiux8zOLjQ11tjhV4TVMB7nxVg2DzaCIoOWO1oKtemVyYIGZmWbCE9TpWYuFTtVIFRJqRsYKHKez+5sdJQ9Lzl+cGSMg9Q8aa1Apeob48V7DvXRgUMH8F8vPIvRPZsw6bKbMHXGGWhIp2hIUJRrsSgNgrD4nb2pM87LAWyLac5xolZSxY4ojfSlkMb6yhTVKLLexu37zCgvULJz0pboHeFZzorkNOFat8IuIi3lsZPHsWvvARx/6XEOR6dh/jlXoGNKs/W6tqYG0YTYDIwj1WmZRhWfukhUjVRSVjDF2DZXRKxjypvkh2+jqVDeJ9hNsgHzUCEgTCSN3pcQOjI7lFOVF13gmo2d6D3Bxzsf4c1f3E+OzGLutX+C6Z0L0MQBWI5RiplOx7DTllXC2JcKxWFPEIM80vWiklTZczV58FFkTica+2unSC46Enl2vO4mSaWiPEVqembXJtTRw7U8E/jQ4aPY/OEurH/sAejD+zB57bdx5jmXYlZbI40vGDbRUZIh3ghKOrJcr8WbCSOCZ/pa3Ac2ue1vYVGDxUc8C4qp1DBjvGtP2+SR6YLdgDawGh7OYh+L1dtb9mDrv9P4k3vReOUf4ayLr8b8me2WNstugrL+NXRKnx2UbizTONFYtnFzomghqhmlBkiVs4BYJE7iOdL2mnXobI8h6GEZn2YWFW1BqIyRLYZY8g8f6TF6aNObr2Jg/aOEWQYt19yFs1eswpmds1GV8oxcKD90hFPTAZRpouImYyzrqGQVw+SgNDK0CR3qEuebS6XZCgSSbrStsNs7fGroGTeRvEX4W6YIA5xS9A3246P9R7Fr6yYMbHySU9qTcOZdhgWr1mDBwiWYMb2Dw101zni5sYwMtXm+GyVoqGPfMxr2sZDtb8uuQ5nUJs7N9eJMFPVDEYZBFFIVs1qoutXc3/v+BdoP1/tUmqOcTg8e2YvsxzsRnthvTnbaz8aUlWvQNX8epnC41TZxkik8vqhQHSWosjyOaORhBpVR7xBGQ6zPOkxBkl4n9CzceFHBFLYoEkVkOihPruKU0kVH9K3zEP+5BTLgSlbBaZyJ2tmL0DJ3PuZ2dKC5vQXNkyZz6pykLi+YpYJI94flN4oTTMVMEU3otFvmRxuhMJIURl7wbUGeukjx9Ivxiyp65JhYjsCIZcoV/fBPLm651Qj0rlsfXMce5/x0Kt1Vla5ETV0N5XE9amprUFNTQ+mcKE6u/RjlUZsrSViEcVHxCntIhLxiyAVOppuDnaFqGSBwE74S3k+YUh3kMb4HjsYoyups05fLT0z/7oyTX4eyuGDd+v11nKitYwG7JSXNhxs9xuECOWkLyyZlNowRDlUU4phGSwCxqcyBsXai/j5Sk/LeV+XDZ7c0jtQ2OuNXAkoPCsKHM25h3boLO/rHbSA+7t94ZFoQuOv4EGIhvdEVGx0Pl0oPHewwWJcxTfmhtR43WomfE1j4WavMkKB8/CK/qbgHKDUtfN9D7z9D9fqrB1a1v1Z+n/8FOVED2P7bkToAAAAASUVORK5CYII="
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