Flowise/packages/server/marketplaces/agentflowsv2/Email Reply HITL Agent.json

848 lines
37 KiB
JSON

{
"description": "An email reply HITL (human in the loop) agent that can proceed or refine the email with user input",
"usecases": ["Human In Loop"],
"nodes": [
{
"id": "startAgentflow_0",
"type": "agentFlow",
"position": {
"x": -212.0817769699585,
"y": 95.2304753249555
},
"data": {
"id": "startAgentflow_0",
"label": "Start",
"version": 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
},
{
"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"
}
],
"id": "startAgentflow_0-input-startState-array",
"display": true
}
],
"inputAnchors": [],
"inputs": {
"startInputType": "chatInput",
"formTitle": "",
"formDescription": "",
"formInputTypes": "",
"startState": ""
},
"outputAnchors": [
{
"id": "startAgentflow_0-output-startAgentflow",
"label": "Start",
"name": "startAgentflow"
}
],
"outputs": {},
"selected": false
},
"width": 101,
"height": 65,
"selected": false,
"positionAbsolute": {
"x": -212.0817769699585,
"y": 95.2304753249555
},
"dragging": false
},
{
"id": "agentAgentflow_0",
"position": {
"x": -62.25,
"y": 76
},
"data": {
"id": "agentAgentflow_0",
"label": "Email Reply Agent",
"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 customer support agent working in Flowise Inc. Write a professional email reply to user's query. Use the web search tools to get more details about the prospect.</p>"
}
],
"agentTools": [
{
"agentSelectedTool": "googleCustomSearch",
"agentSelectedToolConfig": {
"agentSelectedTool": "googleCustomSearch"
}
},
{
"agentSelectedTool": "currentDateTime",
"agentSelectedToolConfig": {
"agentSelectedTool": "currentDateTime"
}
}
],
"agentKnowledgeDocumentStores": "",
"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": "medium",
"agentModel": "chatOpenAI"
}
},
"outputAnchors": [
{
"id": "agentAgentflow_0-output-agentAgentflow",
"label": "Agent",
"name": "agentAgentflow"
}
],
"outputs": {},
"selected": false
},
"type": "agentFlow",
"width": 182,
"height": 103,
"selected": false,
"positionAbsolute": {
"x": -62.25,
"y": 76
},
"dragging": false
},
{
"id": "humanInputAgentflow_0",
"position": {
"x": 156.05666363734434,
"y": 86.62266545493773
},
"data": {
"id": "humanInputAgentflow_0",
"label": "Human Input 0",
"version": 1,
"name": "humanInputAgentflow",
"type": "HumanInput",
"color": "#6E6EFD",
"baseClasses": ["HumanInput"],
"category": "Agent Flows",
"description": "Request human input, approval or rejection during execution",
"inputParams": [
{
"label": "Description Type",
"name": "humanInputDescriptionType",
"type": "options",
"options": [
{
"label": "Fixed",
"name": "fixed",
"description": "Specify a fixed description"
},
{
"label": "Dynamic",
"name": "dynamic",
"description": "Use LLM to generate a description"
}
],
"id": "humanInputAgentflow_0-input-humanInputDescriptionType-options",
"display": true
},
{
"label": "Description",
"name": "humanInputDescription",
"type": "string",
"placeholder": "Are you sure you want to proceed?",
"acceptVariable": true,
"rows": 4,
"show": {
"humanInputDescriptionType": "fixed"
},
"id": "humanInputAgentflow_0-input-humanInputDescription-string",
"display": true
},
{
"label": "Model",
"name": "humanInputModel",
"type": "asyncOptions",
"loadMethod": "listModels",
"loadConfig": true,
"show": {
"humanInputDescriptionType": "dynamic"
},
"id": "humanInputAgentflow_0-input-humanInputModel-asyncOptions",
"display": false
},
{
"label": "Prompt",
"name": "humanInputModelPrompt",
"type": "string",
"default": "<p>Summarize the conversation between the user and the assistant, reiterate the last message from the assistant, and ask if user would like to proceed or if they have any feedback. </p>\n<ul>\n<li>Begin by capturing the key points of the conversation, ensuring that you reflect the main ideas and themes discussed.</li>\n<li>Then, clearly reproduce the last message sent by the assistant to maintain continuity. Make sure the whole message is reproduced.</li>\n<li>Finally, ask the user if they would like to proceed, or provide any feedback on the last assistant message</li>\n</ul>\n<h2 id=\"output-format-the-output-should-be-structured-in-three-parts-\">Output Format The output should be structured in three parts in text:</h2>\n<ul>\n<li>A summary of the conversation (1-3 sentences).</li>\n<li>The last assistant message (exactly as it appeared).</li>\n<li>Ask the user if they would like to proceed, or provide any feedback on last assistant message. No other explanation and elaboration is needed.</li>\n</ul>\n",
"acceptVariable": true,
"generateInstruction": true,
"rows": 4,
"show": {
"humanInputDescriptionType": "dynamic"
},
"id": "humanInputAgentflow_0-input-humanInputModelPrompt-string",
"display": false
},
{
"label": "Enable Feedback",
"name": "humanInputEnableFeedback",
"type": "boolean",
"default": true,
"id": "humanInputAgentflow_0-input-humanInputEnableFeedback-boolean",
"display": true
}
],
"inputAnchors": [],
"inputs": {
"humanInputDescriptionType": "fixed",
"humanInputEnableFeedback": true,
"humanInputModelConfig": {
"cache": "",
"modelName": "gpt-4o-mini",
"temperature": 0.9,
"streaming": true,
"maxTokens": "",
"topP": "",
"frequencyPenalty": "",
"presencePenalty": "",
"timeout": "",
"strictToolCalling": "",
"stopSequence": "",
"basepath": "",
"proxyUrl": "",
"baseOptions": "",
"allowImageUploads": "",
"imageResolution": "low",
"reasoningEffort": "medium",
"humanInputModel": "chatOpenAI"
},
"humanInputDescription": "<p>Are you sure you want to proceed?</p>"
},
"outputAnchors": [
{
"id": "humanInputAgentflow_0-output-0",
"label": "Human Input",
"name": "humanInputAgentflow"
},
{
"id": "humanInputAgentflow_0-output-1",
"label": "Human Input",
"name": "humanInputAgentflow"
}
],
"outputs": {
"humanInputAgentflow": ""
},
"selected": false
},
"type": "agentFlow",
"width": 161,
"height": 80,
"selected": false,
"positionAbsolute": {
"x": 156.05666363734434,
"y": 86.62266545493773
},
"dragging": false
},
{
"id": "directReplyAgentflow_0",
"position": {
"x": 363.0101864947954,
"y": 35.15053748988734
},
"data": {
"id": "directReplyAgentflow_0",
"label": "Direct Reply 0",
"version": 1,
"name": "directReplyAgentflow",
"type": "DirectReply",
"color": "#4DDBBB",
"hideOutput": true,
"baseClasses": ["DirectReply"],
"category": "Agent Flows",
"description": "Directly reply to the user with a message",
"inputParams": [
{
"label": "Message",
"name": "directReplyMessage",
"type": "string",
"rows": 4,
"acceptVariable": true,
"id": "directReplyAgentflow_0-input-directReplyMessage-string",
"display": true
}
],
"inputAnchors": [],
"inputs": {
"directReplyMessage": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"agentAgentflow_0\" data-label=\"agentAgentflow_0\">{{ agentAgentflow_0 }}</span> </p>"
},
"outputAnchors": [],
"outputs": {},
"selected": false
},
"type": "agentFlow",
"width": 155,
"height": 65,
"selected": false,
"positionAbsolute": {
"x": 363.0101864947954,
"y": 35.15053748988734
},
"dragging": false
},
{
"id": "loopAgentflow_0",
"position": {
"x": 366.5975521223236,
"y": 130.12266545493773
},
"data": {
"id": "loopAgentflow_0",
"label": "Loop 0",
"version": 1,
"name": "loopAgentflow",
"type": "Loop",
"color": "#FFA07A",
"hideOutput": true,
"baseClasses": ["Loop"],
"category": "Agent Flows",
"description": "Loop back to a previous node",
"inputParams": [
{
"label": "Loop Back To",
"name": "loopBackToNode",
"type": "asyncOptions",
"loadMethod": "listPreviousNodes",
"freeSolo": true,
"id": "loopAgentflow_0-input-loopBackToNode-asyncOptions",
"display": true
},
{
"label": "Max Loop Count",
"name": "maxLoopCount",
"type": "number",
"default": 5,
"id": "loopAgentflow_0-input-maxLoopCount-number",
"display": true
}
],
"inputAnchors": [],
"inputs": {
"loopBackToNode": "agentAgentflow_0-Email Reply Agent",
"maxLoopCount": 5
},
"outputAnchors": [],
"outputs": {},
"selected": false
},
"type": "agentFlow",
"width": 113,
"height": 65,
"selected": false,
"positionAbsolute": {
"x": 366.5975521223236,
"y": 130.12266545493773
},
"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"
},
{
"source": "agentAgentflow_0",
"sourceHandle": "agentAgentflow_0-output-agentAgentflow",
"target": "humanInputAgentflow_0",
"targetHandle": "humanInputAgentflow_0",
"data": {
"sourceColor": "#4DD0E1",
"targetColor": "#6E6EFD",
"isHumanInput": false
},
"type": "agentFlow",
"id": "agentAgentflow_0-agentAgentflow_0-output-agentAgentflow-humanInputAgentflow_0-humanInputAgentflow_0"
},
{
"source": "humanInputAgentflow_0",
"sourceHandle": "humanInputAgentflow_0-output-0",
"target": "directReplyAgentflow_0",
"targetHandle": "directReplyAgentflow_0",
"data": {
"sourceColor": "#6E6EFD",
"targetColor": "#4DDBBB",
"edgeLabel": "proceed",
"isHumanInput": true
},
"type": "agentFlow",
"id": "humanInputAgentflow_0-humanInputAgentflow_0-output-0-directReplyAgentflow_0-directReplyAgentflow_0"
},
{
"source": "humanInputAgentflow_0",
"sourceHandle": "humanInputAgentflow_0-output-1",
"target": "loopAgentflow_0",
"targetHandle": "loopAgentflow_0",
"data": {
"sourceColor": "#6E6EFD",
"targetColor": "#FFA07A",
"edgeLabel": "reject",
"isHumanInput": true
},
"type": "agentFlow",
"id": "humanInputAgentflow_0-humanInputAgentflow_0-output-1-loopAgentflow_0-loopAgentflow_0"
}
]
}