Files
Flowise/packages/server/marketplaces/agentflowsv2/Simple RAG.json
T
Henry Heng aea2b184da Chore/Patch OpenAI Nodes (#4958)
- update lc community and openai version
- fix chatfireworks
- update reasonings for openai models
- update openai apikey param
2025-07-28 01:17:47 +01:00

629 lines
28 KiB
JSON

{
"description": "A basic RAG agent that can retrieve documents from document store and answer questions",
"usecases": ["Documents QnA"],
"nodes": [
{
"id": "startAgentflow_0",
"type": "agentFlow",
"position": {
"x": 64,
"y": 98.5
},
"data": {
"id": "startAgentflow_0",
"label": "Start",
"version": 1.1,
"name": "startAgentflow",
"type": "Start",
"color": "#7EE787",
"hideInput": true,
"baseClasses": ["Start"],
"category": "Agent Flows",
"description": "Starting point of the agentflow",
"inputParams": [
{
"label": "Input Type",
"name": "startInputType",
"type": "options",
"options": [
{
"label": "Chat Input",
"name": "chatInput",
"description": "Start the conversation with chat input"
},
{
"label": "Form Input",
"name": "formInput",
"description": "Start the workflow with form inputs"
}
],
"default": "chatInput",
"id": "startAgentflow_0-input-startInputType-options",
"display": true
},
{
"label": "Form Title",
"name": "formTitle",
"type": "string",
"placeholder": "Please Fill Out The Form",
"show": {
"startInputType": "formInput"
},
"id": "startAgentflow_0-input-formTitle-string",
"display": false
},
{
"label": "Form Description",
"name": "formDescription",
"type": "string",
"placeholder": "Complete all fields below to continue",
"show": {
"startInputType": "formInput"
},
"id": "startAgentflow_0-input-formDescription-string",
"display": false
},
{
"label": "Form Input Types",
"name": "formInputTypes",
"description": "Specify the type of form input",
"type": "array",
"show": {
"startInputType": "formInput"
},
"array": [
{
"label": "Type",
"name": "type",
"type": "options",
"options": [
{
"label": "String",
"name": "string"
},
{
"label": "Number",
"name": "number"
},
{
"label": "Boolean",
"name": "boolean"
},
{
"label": "Options",
"name": "options"
}
],
"default": "string"
},
{
"label": "Label",
"name": "label",
"type": "string",
"placeholder": "Label for the input"
},
{
"label": "Variable Name",
"name": "name",
"type": "string",
"placeholder": "Variable name for the input (must be camel case)",
"description": "Variable name must be camel case. For example: firstName, lastName, etc."
},
{
"label": "Add Options",
"name": "addOptions",
"type": "array",
"show": {
"formInputTypes[$index].type": "options"
},
"array": [
{
"label": "Option",
"name": "option",
"type": "string"
}
]
}
],
"id": "startAgentflow_0-input-formInputTypes-array",
"display": false
},
{
"label": "Ephemeral Memory",
"name": "startEphemeralMemory",
"type": "boolean",
"description": "Start fresh for every execution without past chat history",
"optional": true,
"id": "startAgentflow_0-input-startEphemeralMemory-boolean",
"display": true
},
{
"label": "Flow State",
"name": "startState",
"description": "Runtime state during the execution of the workflow",
"type": "array",
"optional": true,
"array": [
{
"label": "Key",
"name": "key",
"type": "string",
"placeholder": "Foo"
},
{
"label": "Value",
"name": "value",
"type": "string",
"placeholder": "Bar",
"optional": true
}
],
"id": "startAgentflow_0-input-startState-array",
"display": true
},
{
"label": "Persist State",
"name": "startPersistState",
"type": "boolean",
"description": "Persist the state in the same session",
"optional": true,
"id": "startAgentflow_0-input-startPersistState-boolean",
"display": true
}
],
"inputAnchors": [],
"inputs": {
"startInputType": "chatInput",
"formTitle": "",
"formDescription": "",
"formInputTypes": "",
"startEphemeralMemory": "",
"startState": "",
"startPersistState": ""
},
"outputAnchors": [
{
"id": "startAgentflow_0-output-startAgentflow",
"label": "Start",
"name": "startAgentflow"
}
],
"outputs": {},
"selected": false
},
"width": 103,
"height": 66,
"positionAbsolute": {
"x": 64,
"y": 98.5
},
"selected": false,
"dragging": false
},
{
"id": "agentAgentflow_0",
"position": {
"x": 216.75,
"y": 96.5
},
"data": {
"id": "agentAgentflow_0",
"label": "QnA",
"version": 1,
"name": "agentAgentflow",
"type": "Agent",
"color": "#4DD0E1",
"baseClasses": ["Agent"],
"category": "Agent Flows",
"description": "Dynamically choose and utilize tools during runtime, enabling multi-step reasoning",
"inputParams": [
{
"label": "Model",
"name": "agentModel",
"type": "asyncOptions",
"loadMethod": "listModels",
"loadConfig": true,
"id": "agentAgentflow_0-input-agentModel-asyncOptions",
"display": true
},
{
"label": "Messages",
"name": "agentMessages",
"type": "array",
"optional": true,
"acceptVariable": true,
"array": [
{
"label": "Role",
"name": "role",
"type": "options",
"options": [
{
"label": "System",
"name": "system"
},
{
"label": "Assistant",
"name": "assistant"
},
{
"label": "Developer",
"name": "developer"
},
{
"label": "User",
"name": "user"
}
]
},
{
"label": "Content",
"name": "content",
"type": "string",
"acceptVariable": true,
"generateInstruction": true,
"rows": 4
}
],
"id": "agentAgentflow_0-input-agentMessages-array",
"display": true
},
{
"label": "Tools",
"name": "agentTools",
"type": "array",
"optional": true,
"array": [
{
"label": "Tool",
"name": "agentSelectedTool",
"type": "asyncOptions",
"loadMethod": "listTools",
"loadConfig": true
},
{
"label": "Require Human Input",
"name": "agentSelectedToolRequiresHumanInput",
"type": "boolean",
"optional": true
}
],
"id": "agentAgentflow_0-input-agentTools-array",
"display": true
},
{
"label": "Knowledge (Document Stores)",
"name": "agentKnowledgeDocumentStores",
"type": "array",
"description": "Give your agent context about different document sources. Document stores must be upserted in advance.",
"array": [
{
"label": "Document Store",
"name": "documentStore",
"type": "asyncOptions",
"loadMethod": "listStores"
},
{
"label": "Describe Knowledge",
"name": "docStoreDescription",
"type": "string",
"generateDocStoreDescription": true,
"placeholder": "Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information",
"rows": 4
},
{
"label": "Return Source Documents",
"name": "returnSourceDocuments",
"type": "boolean",
"optional": true
}
],
"optional": true,
"id": "agentAgentflow_0-input-agentKnowledgeDocumentStores-array",
"display": true
},
{
"label": "Knowledge (Vector Embeddings)",
"name": "agentKnowledgeVSEmbeddings",
"type": "array",
"description": "Give your agent context about different document sources from existing vector stores and embeddings",
"array": [
{
"label": "Vector Store",
"name": "vectorStore",
"type": "asyncOptions",
"loadMethod": "listVectorStores",
"loadConfig": true
},
{
"label": "Embedding Model",
"name": "embeddingModel",
"type": "asyncOptions",
"loadMethod": "listEmbeddings",
"loadConfig": true
},
{
"label": "Knowledge Name",
"name": "knowledgeName",
"type": "string",
"placeholder": "A short name for the knowledge base, this is useful for the AI to know when and how to search for correct information"
},
{
"label": "Describe Knowledge",
"name": "knowledgeDescription",
"type": "string",
"placeholder": "Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information",
"rows": 4
},
{
"label": "Return Source Documents",
"name": "returnSourceDocuments",
"type": "boolean",
"optional": true
}
],
"optional": true,
"id": "agentAgentflow_0-input-agentKnowledgeVSEmbeddings-array",
"display": true
},
{
"label": "Enable Memory",
"name": "agentEnableMemory",
"type": "boolean",
"description": "Enable memory for the conversation thread",
"default": true,
"optional": true,
"id": "agentAgentflow_0-input-agentEnableMemory-boolean",
"display": true
},
{
"label": "Memory Type",
"name": "agentMemoryType",
"type": "options",
"options": [
{
"label": "All Messages",
"name": "allMessages",
"description": "Retrieve all messages from the conversation"
},
{
"label": "Window Size",
"name": "windowSize",
"description": "Uses a fixed window size to surface the last N messages"
},
{
"label": "Conversation Summary",
"name": "conversationSummary",
"description": "Summarizes the whole conversation"
},
{
"label": "Conversation Summary Buffer",
"name": "conversationSummaryBuffer",
"description": "Summarize conversations once token limit is reached. Default to 2000"
}
],
"optional": true,
"default": "allMessages",
"show": {
"agentEnableMemory": true
},
"id": "agentAgentflow_0-input-agentMemoryType-options",
"display": true
},
{
"label": "Window Size",
"name": "agentMemoryWindowSize",
"type": "number",
"default": "20",
"description": "Uses a fixed window size to surface the last N messages",
"show": {
"agentMemoryType": "windowSize"
},
"id": "agentAgentflow_0-input-agentMemoryWindowSize-number",
"display": false
},
{
"label": "Max Token Limit",
"name": "agentMemoryMaxTokenLimit",
"type": "number",
"default": "2000",
"description": "Summarize conversations once token limit is reached. Default to 2000",
"show": {
"agentMemoryType": "conversationSummaryBuffer"
},
"id": "agentAgentflow_0-input-agentMemoryMaxTokenLimit-number",
"display": false
},
{
"label": "Input Message",
"name": "agentUserMessage",
"type": "string",
"description": "Add an input message as user message at the end of the conversation",
"rows": 4,
"optional": true,
"acceptVariable": true,
"show": {
"agentEnableMemory": true
},
"id": "agentAgentflow_0-input-agentUserMessage-string",
"display": true
},
{
"label": "Return Response As",
"name": "agentReturnResponseAs",
"type": "options",
"options": [
{
"label": "User Message",
"name": "userMessage"
},
{
"label": "Assistant Message",
"name": "assistantMessage"
}
],
"default": "userMessage",
"id": "agentAgentflow_0-input-agentReturnResponseAs-options",
"display": true
},
{
"label": "Update Flow State",
"name": "agentUpdateState",
"description": "Update runtime state during the execution of the workflow",
"type": "array",
"optional": true,
"acceptVariable": true,
"array": [
{
"label": "Key",
"name": "key",
"type": "asyncOptions",
"loadMethod": "listRuntimeStateKeys",
"freeSolo": true
},
{
"label": "Value",
"name": "value",
"type": "string",
"acceptVariable": true,
"acceptNodeOutputAsVariable": true
}
],
"id": "agentAgentflow_0-input-agentUpdateState-array",
"display": true
}
],
"inputAnchors": [],
"inputs": {
"agentModel": "chatOpenAI",
"agentMessages": [
{
"role": "system",
"content": "<p>You are a helpful assistant. Using the provided context, answer the user's question to the best of your ability using the resources provided.</p><p>If there is nothing in the context relevant to the question at hand, just say \"Hmm, I'm not sure.\" Don't try to make up an answer.</p>"
}
],
"agentTools": "",
"agentKnowledgeDocumentStores": [
{
"documentStore": "25429b8f-0377-4762-9cda-0d5366cf022c:AI-Paper",
"docStoreDescription": "This paper provides an extensive overview of artificial intelligence-generated content (AIGC), including its definition, capabilities, applications, challenges, and future directions, serving as a valuable resource for researchers and industry professionals to understand and harness AIGC's potential.",
"returnSourceDocuments": true
}
],
"agentKnowledgeVSEmbeddings": "",
"agentEnableMemory": true,
"agentMemoryType": "allMessages",
"agentUserMessage": "",
"agentReturnResponseAs": "userMessage",
"agentUpdateState": "",
"agentModelConfig": {
"cache": "",
"modelName": "gpt-4o-mini",
"temperature": 0.9,
"streaming": true,
"maxTokens": "",
"topP": "",
"frequencyPenalty": "",
"presencePenalty": "",
"timeout": "",
"strictToolCalling": "",
"stopSequence": "",
"basepath": "",
"proxyUrl": "",
"baseOptions": "",
"allowImageUploads": "",
"imageResolution": "low",
"reasoningEffort": "",
"agentModel": "chatOpenAI"
}
},
"outputAnchors": [
{
"id": "agentAgentflow_0-output-agentAgentflow",
"label": "Agent",
"name": "agentAgentflow"
}
],
"outputs": {},
"selected": false
},
"type": "agentFlow",
"width": 175,
"height": 72,
"selected": false,
"positionAbsolute": {
"x": 216.75,
"y": 96.5
},
"dragging": false
},
{
"id": "stickyNoteAgentflow_0",
"position": {
"x": 209.875,
"y": -61.25
},
"data": {
"id": "stickyNoteAgentflow_0",
"label": "Sticky Note",
"version": 1,
"name": "stickyNoteAgentflow",
"type": "StickyNote",
"color": "#fee440",
"baseClasses": ["StickyNote"],
"category": "Agent Flows",
"description": "Add notes to the agent flow",
"inputParams": [
{
"label": "",
"name": "note",
"type": "string",
"rows": 1,
"placeholder": "Type something here",
"optional": true,
"id": "stickyNoteAgentflow_0-input-note-string",
"display": true
}
],
"inputAnchors": [],
"inputs": {
"note": "Agent can retrieve documents from upserted document store, and directly from vector database"
},
"outputAnchors": [
{
"id": "stickyNoteAgentflow_0-output-stickyNoteAgentflow",
"label": "Sticky Note",
"name": "stickyNoteAgentflow"
}
],
"outputs": {},
"selected": false
},
"type": "stickyNote",
"width": 210,
"height": 143,
"selected": false,
"positionAbsolute": {
"x": 209.875,
"y": -61.25
},
"dragging": false
}
],
"edges": [
{
"source": "startAgentflow_0",
"sourceHandle": "startAgentflow_0-output-startAgentflow",
"target": "agentAgentflow_0",
"targetHandle": "agentAgentflow_0",
"data": {
"sourceColor": "#7EE787",
"targetColor": "#4DD0E1",
"isHumanInput": false
},
"type": "agentFlow",
"id": "startAgentflow_0-startAgentflow_0-output-startAgentflow-agentAgentflow_0-agentAgentflow_0"
}
]
}