diff --git a/packages/server/marketplaces/agentflowsv2/Deep Research V2.json b/packages/server/marketplaces/agentflowsv2/Deep Research V2.json
new file mode 100644
index 00000000..bd58656b
--- /dev/null
+++ b/packages/server/marketplaces/agentflowsv2/Deep Research V2.json
@@ -0,0 +1,2142 @@
+{
+ "description": "An agent capable of performing research, synthesizing information, and generating in-depth, well-structured white papers on any given topic",
+ "usecases": ["Agent"],
+ "nodes": [
+ {
+ "id": "startAgentflow_0",
+ "type": "agentFlow",
+ "position": {
+ "x": -275.0799323960054,
+ "y": 31.301887150099603
+ },
+ "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,
+ "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
+ }
+ ],
+ "inputAnchors": [],
+ "inputs": {
+ "startInputType": "chatInput",
+ "startEphemeralMemory": true,
+ "startState": ""
+ },
+ "outputAnchors": [
+ {
+ "id": "startAgentflow_0-output-startAgentflow",
+ "label": "Start",
+ "name": "startAgentflow"
+ }
+ ],
+ "outputs": {},
+ "selected": false
+ },
+ "width": 103,
+ "height": 65,
+ "selected": false,
+ "positionAbsolute": {
+ "x": -275.0799323960054,
+ "y": 31.301887150099603
+ },
+ "dragging": false
+ },
+ {
+ "id": "llmAgentflow_0",
+ "position": {
+ "x": -59.13383952997965,
+ "y": 28.495983624910906
+ },
+ "data": {
+ "id": "llmAgentflow_0",
+ "label": "Topic Enhancer",
+ "version": 1,
+ "name": "llmAgentflow",
+ "type": "LLM",
+ "color": "#64B5F6",
+ "baseClasses": ["LLM"],
+ "category": "Agent Flows",
+ "description": "Large language models to analyze user-provided inputs and generate responses",
+ "inputParams": [
+ {
+ "label": "Model",
+ "name": "llmModel",
+ "type": "asyncOptions",
+ "loadMethod": "listModels",
+ "loadConfig": true,
+ "id": "llmAgentflow_0-input-llmModel-asyncOptions",
+ "display": true
+ },
+ {
+ "label": "Messages",
+ "name": "llmMessages",
+ "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": "llmAgentflow_0-input-llmMessages-array",
+ "display": true
+ },
+ {
+ "label": "Enable Memory",
+ "name": "llmEnableMemory",
+ "type": "boolean",
+ "description": "Enable memory for the conversation thread",
+ "default": true,
+ "optional": true,
+ "id": "llmAgentflow_0-input-llmEnableMemory-boolean",
+ "display": true
+ },
+ {
+ "label": "Memory Type",
+ "name": "llmMemoryType",
+ "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": {
+ "llmEnableMemory": true
+ },
+ "id": "llmAgentflow_0-input-llmMemoryType-options",
+ "display": false
+ },
+ {
+ "label": "Window Size",
+ "name": "llmMemoryWindowSize",
+ "type": "number",
+ "default": "20",
+ "description": "Uses a fixed window size to surface the last N messages",
+ "show": {
+ "llmMemoryType": "windowSize"
+ },
+ "id": "llmAgentflow_0-input-llmMemoryWindowSize-number",
+ "display": false
+ },
+ {
+ "label": "Max Token Limit",
+ "name": "llmMemoryMaxTokenLimit",
+ "type": "number",
+ "default": "2000",
+ "description": "Summarize conversations once token limit is reached. Default to 2000",
+ "show": {
+ "llmMemoryType": "conversationSummaryBuffer"
+ },
+ "id": "llmAgentflow_0-input-llmMemoryMaxTokenLimit-number",
+ "display": false
+ },
+ {
+ "label": "Input Message",
+ "name": "llmUserMessage",
+ "type": "string",
+ "description": "Add an input message as user message at the end of the conversation",
+ "rows": 4,
+ "optional": true,
+ "acceptVariable": true,
+ "show": {
+ "llmEnableMemory": true
+ },
+ "id": "llmAgentflow_0-input-llmUserMessage-string",
+ "display": false
+ },
+ {
+ "label": "Return Response As",
+ "name": "llmReturnResponseAs",
+ "type": "options",
+ "options": [
+ {
+ "label": "User Message",
+ "name": "userMessage"
+ },
+ {
+ "label": "Assistant Message",
+ "name": "assistantMessage"
+ }
+ ],
+ "default": "userMessage",
+ "id": "llmAgentflow_0-input-llmReturnResponseAs-options",
+ "display": true
+ },
+ {
+ "label": "JSON Structured Output",
+ "name": "llmStructuredOutput",
+ "description": "Instruct the LLM to give output in a JSON structured schema",
+ "type": "array",
+ "optional": true,
+ "acceptVariable": true,
+ "array": [
+ {
+ "label": "Key",
+ "name": "key",
+ "type": "string"
+ },
+ {
+ "label": "Type",
+ "name": "type",
+ "type": "options",
+ "options": [
+ {
+ "label": "String",
+ "name": "string"
+ },
+ {
+ "label": "String Array",
+ "name": "stringArray"
+ },
+ {
+ "label": "Number",
+ "name": "number"
+ },
+ {
+ "label": "Boolean",
+ "name": "boolean"
+ },
+ {
+ "label": "Enum",
+ "name": "enum"
+ },
+ {
+ "label": "JSON Array",
+ "name": "jsonArray"
+ }
+ ]
+ },
+ {
+ "label": "Enum Values",
+ "name": "enumValues",
+ "type": "string",
+ "placeholder": "value1, value2, value3",
+ "description": "Enum values. Separated by comma",
+ "optional": true,
+ "show": {
+ "llmStructuredOutput[$index].type": "enum"
+ }
+ },
+ {
+ "label": "JSON Schema",
+ "name": "jsonSchema",
+ "type": "code",
+ "placeholder": "{\n \"answer\": {\n \"type\": \"string\",\n \"description\": \"Value of the answer\"\n },\n \"reason\": {\n \"type\": \"string\",\n \"description\": \"Reason for the answer\"\n },\n \"optional\": {\n \"type\": \"boolean\"\n },\n \"count\": {\n \"type\": \"number\"\n },\n \"children\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"value\": {\n \"type\": \"string\",\n \"description\": \"Value of the children's answer\"\n }\n }\n }\n }\n}",
+ "description": "JSON schema for the structured output",
+ "optional": true,
+ "show": {
+ "llmStructuredOutput[$index].type": "jsonArray"
+ }
+ },
+ {
+ "label": "Description",
+ "name": "description",
+ "type": "string",
+ "placeholder": "Description of the key"
+ }
+ ],
+ "id": "llmAgentflow_0-input-llmStructuredOutput-array",
+ "display": true
+ },
+ {
+ "label": "Update Flow State",
+ "name": "llmUpdateState",
+ "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": "llmAgentflow_0-input-llmUpdateState-array",
+ "display": true
+ }
+ ],
+ "inputAnchors": [],
+ "inputs": {
+ "llmModel": "chatOpenAI",
+ "llmMessages": [
+ {
+ "role": "developer",
+ "content": "Your only role is to improve the user query for more clarity. Do not add any meta comments.
"
+ }
+ ],
+ "llmEnableMemory": false,
+ "llmReturnResponseAs": "userMessage",
+ "llmStructuredOutput": "",
+ "llmUpdateState": "",
+ "llmModelConfig": {
+ "cache": "",
+ "modelName": "gpt-4o-mini",
+ "temperature": "0.5",
+ "streaming": true,
+ "maxTokens": "",
+ "topP": "",
+ "frequencyPenalty": "",
+ "presencePenalty": "",
+ "timeout": "",
+ "strictToolCalling": "",
+ "stopSequence": "",
+ "basepath": "",
+ "proxyUrl": "",
+ "baseOptions": "",
+ "allowImageUploads": "",
+ "imageResolution": "low",
+ "reasoningEffort": "medium",
+ "llmModel": "chatOpenAI"
+ }
+ },
+ "outputAnchors": [
+ {
+ "id": "llmAgentflow_0-output-llmAgentflow",
+ "label": "LLM",
+ "name": "llmAgentflow"
+ }
+ ],
+ "outputs": {},
+ "selected": false
+ },
+ "type": "agentFlow",
+ "width": 175,
+ "height": 71,
+ "selected": false,
+ "positionAbsolute": {
+ "x": -59.13383952997965,
+ "y": 28.495983624910906
+ },
+ "dragging": false
+ },
+ {
+ "id": "agentAgentflow_0",
+ "position": {
+ "x": 209.99147630894493,
+ "y": 100.7933285478893
+ },
+ "data": {
+ "id": "agentAgentflow_0",
+ "label": "Agent 0",
+ "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": "chatGoogleGenerativeAI",
+ "agentMessages": [
+ {
+ "role": "system",
+ "content": "You are Agent 0. Your goal is to explore any topic provided by the user in depth with Agent 1.
Start: Introduce the topic to Agent 1. Share your initial thoughts and any assumptions you have.
Research & Share:
Use BraveSearch API to find a range of information and different viewpoints on the topic. Look for URLs that seem promising for more detail.
If a URL from BraveSearch API (or one you already know) seems particularly important, use the Web Scraper Tool to get its full content.
Present what you find to Agent 1, especially any complexities, counter-arguments, or conflicting data.
Clearly state your sources:
Discuss & Deepen:
Listen to Agent 1. Ask probing questions.
If needed, use your tools again (BraveSearch API to find more, Web Scraper to analyze a specific page) during the conversation to verify points or explore new angles.
Mindset: Be curious, analytical, and open to different perspectives. Aim for a thorough understanding, not just agreement.
"
+ }
+ ],
+ "agentTools": [
+ {
+ "agentSelectedTool": "braveSearchAPI",
+ "agentSelectedToolRequiresHumanInput": "",
+ "agentSelectedToolConfig": {
+ "agentSelectedTool": "braveSearchAPI"
+ }
+ },
+ {
+ "agentSelectedTool": "webScraperTool",
+ "agentSelectedToolRequiresHumanInput": "",
+ "agentSelectedToolConfig": {
+ "scrapeMode": "recursive",
+ "maxDepth": 1,
+ "maxPages": 10,
+ "timeoutS": 60,
+ "description": "",
+ "agentSelectedTool": "webScraperTool"
+ }
+ }
+ ],
+ "agentKnowledgeDocumentStores": "",
+ "agentKnowledgeVSEmbeddings": "",
+ "agentEnableMemory": true,
+ "agentMemoryType": "allMessages",
+ "agentUserMessage": "",
+ "agentReturnResponseAs": "assistantMessage",
+ "agentUpdateState": "",
+ "agentModelConfig": {
+ "cache": "",
+ "contextCache": "",
+ "modelName": "gemini-2.0-flash",
+ "customModelName": "",
+ "temperature": "0.5",
+ "streaming": true,
+ "maxOutputTokens": "",
+ "topP": "",
+ "topK": "",
+ "harmCategory": "",
+ "harmBlockThreshold": "",
+ "baseUrl": "",
+ "allowImageUploads": "",
+ "agentModel": "chatGoogleGenerativeAI"
+ }
+ },
+ "outputAnchors": [
+ {
+ "id": "agentAgentflow_0-output-agentAgentflow",
+ "label": "Agent",
+ "name": "agentAgentflow"
+ }
+ ],
+ "outputs": {},
+ "selected": false
+ },
+ "type": "agentFlow",
+ "width": 199,
+ "height": 103,
+ "selected": false,
+ "positionAbsolute": {
+ "x": 209.99147630894493,
+ "y": 100.7933285478893
+ },
+ "dragging": false
+ },
+ {
+ "id": "agentAgentflow_1",
+ "position": {
+ "x": 203.50865583557328,
+ "y": -75.13070214403373
+ },
+ "data": {
+ "id": "agentAgentflow_1",
+ "label": "Agent 1",
+ "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_1-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_1-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_1-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_1-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_1-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_1-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_1-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_1-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_1-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_1-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_1-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_1-input-agentUpdateState-array",
+ "display": true
+ }
+ ],
+ "inputAnchors": [],
+ "inputs": {
+ "agentModel": "chatGoogleGenerativeAI",
+ "agentMessages": [
+ {
+ "role": "system",
+ "content": "You are Agent 1. Your goal is to explore a topic in depth with Agent 0.
Respond & Share:
Acknowledge the topic Agent 0 introduces.
Share your own thoughts and feelings, building on or respectfully challenging Agent 0's points. Consider your own assumptions.
Research & Contribute:
Use BraveSearch API to research the topic, especially looking for different perspectives, counter-arguments, or aspects Agent 0 might not have covered. Identify URLs that seem promising for more detail.
If a URL from BraveSearch API (or one you already know) seems particularly important for your point or for adding nuance, use the Web Scraper Tool to get its full content.
Present your findings, especially any that introduce new angles, conflicts, or alternative views.
Clearly state your sources:
If you find conflicting info from different sources, point this out.
Discuss & Deepen:
Listen carefully to Agent 0. Ask clarifying questions and questions that challenge their reasoning or explore alternatives.
If needed, use your tools again (BraveSearch API to find more, Web Scraper to analyze a specific page) during the conversation to support your points or investigate Agent 0's claims.
Mindset: Be respectful, analytical, and open to different viewpoints. Aim for a thorough exploration and constructive disagreement, backed by research.
"
+ }
+ ],
+ "agentTools": [
+ {
+ "agentSelectedTool": "braveSearchAPI",
+ "agentSelectedToolRequiresHumanInput": "",
+ "agentSelectedToolConfig": {
+ "agentSelectedTool": "braveSearchAPI"
+ }
+ },
+ {
+ "agentSelectedTool": "webScraperTool",
+ "agentSelectedToolRequiresHumanInput": "",
+ "agentSelectedToolConfig": {
+ "scrapeMode": "recursive",
+ "maxDepth": 1,
+ "maxPages": 10,
+ "timeoutS": 60,
+ "description": "",
+ "agentSelectedTool": "webScraperTool"
+ }
+ }
+ ],
+ "agentKnowledgeDocumentStores": "",
+ "agentKnowledgeVSEmbeddings": "",
+ "agentEnableMemory": true,
+ "agentMemoryType": "allMessages",
+ "agentUserMessage": "",
+ "agentReturnResponseAs": "assistantMessage",
+ "agentUpdateState": "",
+ "agentModelConfig": {
+ "cache": "",
+ "contextCache": "",
+ "modelName": "gemini-2.0-flash",
+ "customModelName": "",
+ "temperature": "0.5",
+ "streaming": true,
+ "maxOutputTokens": "",
+ "topP": "",
+ "topK": "",
+ "harmCategory": "",
+ "harmBlockThreshold": "",
+ "baseUrl": "",
+ "allowImageUploads": "",
+ "agentModel": "chatGoogleGenerativeAI"
+ }
+ },
+ "outputAnchors": [
+ {
+ "id": "agentAgentflow_1-output-agentAgentflow",
+ "label": "Agent",
+ "name": "agentAgentflow"
+ }
+ ],
+ "outputs": {},
+ "selected": false
+ },
+ "type": "agentFlow",
+ "width": 199,
+ "height": 103,
+ "selected": false,
+ "positionAbsolute": {
+ "x": 203.50865583557328,
+ "y": -75.13070214403373
+ },
+ "dragging": false
+ },
+ {
+ "id": "conditionAgentflow_0",
+ "position": {
+ "x": 497.07879661792845,
+ "y": 29.068421396935392
+ },
+ "data": {
+ "id": "conditionAgentflow_0",
+ "label": "Condition",
+ "version": 1,
+ "name": "conditionAgentflow",
+ "type": "Condition",
+ "color": "#FFB938",
+ "baseClasses": ["Condition"],
+ "category": "Agent Flows",
+ "description": "Split flows based on If Else conditions",
+ "inputParams": [
+ {
+ "label": "Conditions",
+ "name": "conditions",
+ "type": "array",
+ "description": "Values to compare",
+ "acceptVariable": true,
+ "default": [
+ {
+ "type": "number",
+ "value1": "",
+ "operation": "equal",
+ "value2": ""
+ }
+ ],
+ "array": [
+ {
+ "label": "Type",
+ "name": "type",
+ "type": "options",
+ "options": [
+ {
+ "label": "String",
+ "name": "string"
+ },
+ {
+ "label": "Number",
+ "name": "number"
+ },
+ {
+ "label": "Boolean",
+ "name": "boolean"
+ }
+ ],
+ "default": "string"
+ },
+ {
+ "label": "Value 1",
+ "name": "value1",
+ "type": "string",
+ "default": "",
+ "description": "First value to be compared with",
+ "acceptVariable": true,
+ "show": {
+ "conditions[$index].type": "string"
+ }
+ },
+ {
+ "label": "Operation",
+ "name": "operation",
+ "type": "options",
+ "options": [
+ {
+ "label": "Contains",
+ "name": "contains"
+ },
+ {
+ "label": "Ends With",
+ "name": "endsWith"
+ },
+ {
+ "label": "Equal",
+ "name": "equal"
+ },
+ {
+ "label": "Not Contains",
+ "name": "notContains"
+ },
+ {
+ "label": "Not Equal",
+ "name": "notEqual"
+ },
+ {
+ "label": "Regex",
+ "name": "regex"
+ },
+ {
+ "label": "Starts With",
+ "name": "startsWith"
+ },
+ {
+ "label": "Is Empty",
+ "name": "isEmpty"
+ },
+ {
+ "label": "Not Empty",
+ "name": "notEmpty"
+ }
+ ],
+ "default": "equal",
+ "description": "Type of operation",
+ "show": {
+ "conditions[$index].type": "string"
+ }
+ },
+ {
+ "label": "Value 2",
+ "name": "value2",
+ "type": "string",
+ "default": "",
+ "description": "Second value to be compared with",
+ "acceptVariable": true,
+ "show": {
+ "conditions[$index].type": "string"
+ },
+ "hide": {
+ "conditions[$index].operation": ["isEmpty", "notEmpty"]
+ }
+ },
+ {
+ "label": "Value 1",
+ "name": "value1",
+ "type": "number",
+ "default": "",
+ "description": "First value to be compared with",
+ "acceptVariable": true,
+ "show": {
+ "conditions[$index].type": "number"
+ }
+ },
+ {
+ "label": "Operation",
+ "name": "operation",
+ "type": "options",
+ "options": [
+ {
+ "label": "Smaller",
+ "name": "smaller"
+ },
+ {
+ "label": "Smaller Equal",
+ "name": "smallerEqual"
+ },
+ {
+ "label": "Equal",
+ "name": "equal"
+ },
+ {
+ "label": "Not Equal",
+ "name": "notEqual"
+ },
+ {
+ "label": "Larger",
+ "name": "larger"
+ },
+ {
+ "label": "Larger Equal",
+ "name": "largerEqual"
+ },
+ {
+ "label": "Is Empty",
+ "name": "isEmpty"
+ },
+ {
+ "label": "Not Empty",
+ "name": "notEmpty"
+ }
+ ],
+ "default": "equal",
+ "description": "Type of operation",
+ "show": {
+ "conditions[$index].type": "number"
+ }
+ },
+ {
+ "label": "Value 2",
+ "name": "value2",
+ "type": "number",
+ "default": 0,
+ "description": "Second value to be compared with",
+ "acceptVariable": true,
+ "show": {
+ "conditions[$index].type": "number"
+ }
+ },
+ {
+ "label": "Value 1",
+ "name": "value1",
+ "type": "boolean",
+ "default": false,
+ "description": "First value to be compared with",
+ "show": {
+ "conditions[$index].type": "boolean"
+ }
+ },
+ {
+ "label": "Operation",
+ "name": "operation",
+ "type": "options",
+ "options": [
+ {
+ "label": "Equal",
+ "name": "equal"
+ },
+ {
+ "label": "Not Equal",
+ "name": "notEqual"
+ }
+ ],
+ "default": "equal",
+ "description": "Type of operation",
+ "show": {
+ "conditions[$index].type": "boolean"
+ }
+ },
+ {
+ "label": "Value 2",
+ "name": "value2",
+ "type": "boolean",
+ "default": false,
+ "description": "Second value to be compared with",
+ "show": {
+ "conditions[$index].type": "boolean"
+ }
+ }
+ ],
+ "id": "conditionAgentflow_0-input-conditions-array",
+ "display": true
+ }
+ ],
+ "inputAnchors": [],
+ "inputs": {
+ "conditions": [
+ {
+ "type": "number",
+ "value1": "{{ runtime_messages_length }}
",
+ "operation": "smallerEqual",
+ "value2": "11
"
+ }
+ ]
+ },
+ "outputAnchors": [
+ {
+ "id": "conditionAgentflow_0-output-0",
+ "label": "Condition",
+ "name": "conditionAgentflow"
+ },
+ {
+ "id": "conditionAgentflow_0-output-1",
+ "label": "Condition",
+ "name": "conditionAgentflow"
+ }
+ ],
+ "outputs": {
+ "conditionAgentflow": ""
+ },
+ "selected": false
+ },
+ "type": "agentFlow",
+ "width": 134,
+ "height": 80,
+ "selected": false,
+ "positionAbsolute": {
+ "x": 497.07879661792845,
+ "y": 29.068421396935392
+ },
+ "dragging": false
+ },
+ {
+ "id": "loopAgentflow_0",
+ "position": {
+ "x": 710.6354115635097,
+ "y": -61.015932400168076
+ },
+ "data": {
+ "id": "loopAgentflow_0",
+ "label": "Loop",
+ "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-Agent 0",
+ "maxLoopCount": "10"
+ },
+ "outputAnchors": [],
+ "outputs": {},
+ "selected": false
+ },
+ "type": "agentFlow",
+ "width": 104,
+ "height": 65,
+ "selected": false,
+ "dragging": false,
+ "positionAbsolute": {
+ "x": 710.6354115635097,
+ "y": -61.015932400168076
+ }
+ },
+ {
+ "id": "llmAgentflow_1",
+ "position": {
+ "x": 693.0529196789191,
+ "y": 133.0683091126315
+ },
+ "data": {
+ "id": "llmAgentflow_1",
+ "label": "Agent 2",
+ "version": 1,
+ "name": "llmAgentflow",
+ "type": "LLM",
+ "color": "#64B5F6",
+ "baseClasses": ["LLM"],
+ "category": "Agent Flows",
+ "description": "Large language models to analyze user-provided inputs and generate responses",
+ "inputParams": [
+ {
+ "label": "Model",
+ "name": "llmModel",
+ "type": "asyncOptions",
+ "loadMethod": "listModels",
+ "loadConfig": true,
+ "id": "llmAgentflow_1-input-llmModel-asyncOptions",
+ "display": true
+ },
+ {
+ "label": "Messages",
+ "name": "llmMessages",
+ "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": "llmAgentflow_1-input-llmMessages-array",
+ "display": true
+ },
+ {
+ "label": "Enable Memory",
+ "name": "llmEnableMemory",
+ "type": "boolean",
+ "description": "Enable memory for the conversation thread",
+ "default": true,
+ "optional": true,
+ "id": "llmAgentflow_1-input-llmEnableMemory-boolean",
+ "display": true
+ },
+ {
+ "label": "Memory Type",
+ "name": "llmMemoryType",
+ "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": {
+ "llmEnableMemory": true
+ },
+ "id": "llmAgentflow_1-input-llmMemoryType-options",
+ "display": false
+ },
+ {
+ "label": "Window Size",
+ "name": "llmMemoryWindowSize",
+ "type": "number",
+ "default": "20",
+ "description": "Uses a fixed window size to surface the last N messages",
+ "show": {
+ "llmMemoryType": "windowSize"
+ },
+ "id": "llmAgentflow_1-input-llmMemoryWindowSize-number",
+ "display": false
+ },
+ {
+ "label": "Max Token Limit",
+ "name": "llmMemoryMaxTokenLimit",
+ "type": "number",
+ "default": "2000",
+ "description": "Summarize conversations once token limit is reached. Default to 2000",
+ "show": {
+ "llmMemoryType": "conversationSummaryBuffer"
+ },
+ "id": "llmAgentflow_1-input-llmMemoryMaxTokenLimit-number",
+ "display": false
+ },
+ {
+ "label": "Input Message",
+ "name": "llmUserMessage",
+ "type": "string",
+ "description": "Add an input message as user message at the end of the conversation",
+ "rows": 4,
+ "optional": true,
+ "acceptVariable": true,
+ "show": {
+ "llmEnableMemory": true
+ },
+ "id": "llmAgentflow_1-input-llmUserMessage-string",
+ "display": false
+ },
+ {
+ "label": "Return Response As",
+ "name": "llmReturnResponseAs",
+ "type": "options",
+ "options": [
+ {
+ "label": "User Message",
+ "name": "userMessage"
+ },
+ {
+ "label": "Assistant Message",
+ "name": "assistantMessage"
+ }
+ ],
+ "default": "userMessage",
+ "id": "llmAgentflow_1-input-llmReturnResponseAs-options",
+ "display": true
+ },
+ {
+ "label": "JSON Structured Output",
+ "name": "llmStructuredOutput",
+ "description": "Instruct the LLM to give output in a JSON structured schema",
+ "type": "array",
+ "optional": true,
+ "acceptVariable": true,
+ "array": [
+ {
+ "label": "Key",
+ "name": "key",
+ "type": "string"
+ },
+ {
+ "label": "Type",
+ "name": "type",
+ "type": "options",
+ "options": [
+ {
+ "label": "String",
+ "name": "string"
+ },
+ {
+ "label": "String Array",
+ "name": "stringArray"
+ },
+ {
+ "label": "Number",
+ "name": "number"
+ },
+ {
+ "label": "Boolean",
+ "name": "boolean"
+ },
+ {
+ "label": "Enum",
+ "name": "enum"
+ },
+ {
+ "label": "JSON Array",
+ "name": "jsonArray"
+ }
+ ]
+ },
+ {
+ "label": "Enum Values",
+ "name": "enumValues",
+ "type": "string",
+ "placeholder": "value1, value2, value3",
+ "description": "Enum values. Separated by comma",
+ "optional": true,
+ "show": {
+ "llmStructuredOutput[$index].type": "enum"
+ }
+ },
+ {
+ "label": "JSON Schema",
+ "name": "jsonSchema",
+ "type": "code",
+ "placeholder": "{\n \"answer\": {\n \"type\": \"string\",\n \"description\": \"Value of the answer\"\n },\n \"reason\": {\n \"type\": \"string\",\n \"description\": \"Reason for the answer\"\n },\n \"optional\": {\n \"type\": \"boolean\"\n },\n \"count\": {\n \"type\": \"number\"\n },\n \"children\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"value\": {\n \"type\": \"string\",\n \"description\": \"Value of the children's answer\"\n }\n }\n }\n }\n}",
+ "description": "JSON schema for the structured output",
+ "optional": true,
+ "show": {
+ "llmStructuredOutput[$index].type": "jsonArray"
+ }
+ },
+ {
+ "label": "Description",
+ "name": "description",
+ "type": "string",
+ "placeholder": "Description of the key"
+ }
+ ],
+ "id": "llmAgentflow_1-input-llmStructuredOutput-array",
+ "display": true
+ },
+ {
+ "label": "Update Flow State",
+ "name": "llmUpdateState",
+ "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": "llmAgentflow_1-input-llmUpdateState-array",
+ "display": true
+ }
+ ],
+ "inputAnchors": [],
+ "inputs": {
+ "llmModel": "chatGoogleGenerativeAI",
+ "llmMessages": [
+ {
+ "role": "system",
+ "content": "You are Agent 2. Your role is to transform the deep conversation between Agent 0 and Agent 1 into a comprehensive and extensive white paper on the subject they discussed.
Your goal is to produce an authoritative document that not only captures the essence of their dialogue but also expands upon it, providing a thorough exploration of the topic. This white paper should be suitable for an audience seeking a deep understanding of the subject.
The white paper must include, but is not limited to, the following sections and considerations:
Title: A clear, compelling title for the white paper that reflects the core subject.
Abstract/Executive Summary: A concise overview (approx. 200-300 words) of the white paper's main arguments, scope, and conclusions, derived from the conversation.
Introduction:
Set the context and importance of the subject discussed by Agent 0 and Agent 1.
Clearly define the central problem, question, or theme that the white paper will address, based on their dialogue.
Outline the paper's structure and objectives.
Main Body / Thematic Analysis (Multiple Sections):
Deconstruct and Synthesize Key Arguments: Detail the principal arguments, propositions, and evidence presented by both Agent 0 and Agent 1. Go beyond mere listing; analyze the strengths, weaknesses, and underlying assumptions of their positions.
Explore Core Themes and Concepts: Identify and elaborate on the major themes and concepts that emerged. For each theme, discuss how Agent 0 and Agent 1 approached it, their points of convergence, and their points of divergence.
Analyze the Evolution of the Discussion: Trace how the understanding of the subject evolved throughout their conversation. Highlight any shifts in perspective, critical turning points, challenged assumptions, or moments of significant clarification.
Evidence and Examples: Where the agents provided examples or evidence, incorporate and potentially expand upon these to support the white paper's analysis.
Synthesis of Insights and Key Conclusions:
Draw together the most significant insights and conclusions that can be derived from the entirety of the conversation.
This section should offer a consolidated understanding of the subject, informed by the agents' interaction.
Implications and Future Directions:
Discuss the broader implications of the insights and conclusions reached.
Identify any unresolved questions, ambiguities, or areas that the conversation indicated require further exploration or research.
Suggest potential next steps or future avenues of inquiry.
Conclusion: A strong concluding section summarizing the white paper's main findings, their significance, and a final thought on the subject.
Style and Tone:
Extensive and In-depth: The paper should be thorough and detailed.
Well-Structured: Use clear headings, subheadings, and logical flow.
Analytical and Critical: Do not just report; analyze, interpret, and critically engage with the agents' ideas.
Objective and Authoritative: While based on the agents' dialogue, the white paper should present a balanced and well-reasoned perspective.
Clear Attribution: When discussing specific viewpoints or arguments, clearly attribute them to Agent 0 or Agent 1.
Formal and Professional Language: Maintain a tone appropriate for a white paper.
Your primary source material is the conversation between Agent 0 and Agent 1. Your task is to elevate their discourse into a structured, analytical, and extensive white paper.
"
+ },
+ {
+ "role": "user",
+ "content": "Here is the full conversation between Agent 0 and Agent 1. Please use this as the primary source material for generating the extensive white paper as per your instructions:
--
{{ chat_history }}
--
"
+ }
+ ],
+ "llmEnableMemory": false,
+ "llmReturnResponseAs": "assistantMessage",
+ "llmStructuredOutput": "",
+ "llmUpdateState": "",
+ "llmModelConfig": {
+ "cache": "",
+ "contextCache": "",
+ "modelName": "gemini-2.0-flash",
+ "customModelName": "",
+ "temperature": "0.5",
+ "streaming": true,
+ "maxOutputTokens": "",
+ "topP": "",
+ "topK": "",
+ "harmCategory": "",
+ "harmBlockThreshold": "",
+ "baseUrl": "",
+ "allowImageUploads": "",
+ "llmModel": "chatGoogleGenerativeAI"
+ }
+ },
+ "outputAnchors": [
+ {
+ "id": "llmAgentflow_1-output-llmAgentflow",
+ "label": "LLM",
+ "name": "llmAgentflow"
+ }
+ ],
+ "outputs": {},
+ "selected": false
+ },
+ "type": "agentFlow",
+ "width": 199,
+ "height": 71,
+ "selected": false,
+ "positionAbsolute": {
+ "x": 693.0529196789191,
+ "y": 133.0683091126315
+ },
+ "dragging": false
+ },
+ {
+ "id": "stickyNoteAgentflow_0",
+ "position": {
+ "x": -320.62033146052283,
+ "y": -110.15285265313359
+ },
+ "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": "User provides a topic for research, for example: \"Humans in the Era of an ASI\""
+ },
+ "outputAnchors": [
+ {
+ "id": "stickyNoteAgentflow_0-output-stickyNoteAgentflow",
+ "label": "Sticky Note",
+ "name": "stickyNoteAgentflow"
+ }
+ ],
+ "outputs": {},
+ "selected": false
+ },
+ "type": "stickyNote",
+ "width": 203,
+ "height": 122,
+ "selected": false,
+ "positionAbsolute": {
+ "x": -320.62033146052283,
+ "y": -110.15285265313359
+ },
+ "dragging": false
+ },
+ {
+ "id": "stickyNoteAgentflow_1",
+ "position": {
+ "x": 466.8306744858025,
+ "y": -189.9009582021492
+ },
+ "data": {
+ "id": "stickyNoteAgentflow_1",
+ "label": "Sticky Note (1)",
+ "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_1-input-note-string",
+ "display": true
+ }
+ ],
+ "inputAnchors": [],
+ "inputs": {
+ "note": "Determine the number of back-and-forth exchanges between Agent 0 and Agent 1 in a deep conversation about the user's topic. It is currently set for 5 iterations."
+ },
+ "outputAnchors": [
+ {
+ "id": "stickyNoteAgentflow_1-output-stickyNoteAgentflow",
+ "label": "Sticky Note",
+ "name": "stickyNoteAgentflow"
+ }
+ ],
+ "outputs": {},
+ "selected": false
+ },
+ "type": "stickyNote",
+ "width": 203,
+ "height": 202,
+ "selected": false,
+ "positionAbsolute": {
+ "x": 466.8306744858025,
+ "y": -189.9009582021492
+ },
+ "dragging": false
+ },
+ {
+ "id": "stickyNoteAgentflow_2",
+ "position": {
+ "x": 693.7511120802441,
+ "y": 221.75098356027857
+ },
+ "data": {
+ "id": "stickyNoteAgentflow_2",
+ "label": "Sticky Note (1) (2)",
+ "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_2-input-note-string",
+ "display": true
+ }
+ ],
+ "inputAnchors": [],
+ "inputs": {
+ "note": "This LLM Node transforms the in-depth conversation between Agent 0 and Agent 1 into a comprehensive white paper. It can be replaced with an Agent Node if you need to use tools such as sending the findings to our email, etc."
+ },
+ "outputAnchors": [
+ {
+ "id": "stickyNoteAgentflow_2-output-stickyNoteAgentflow",
+ "label": "Sticky Note",
+ "name": "stickyNoteAgentflow"
+ }
+ ],
+ "outputs": {},
+ "selected": false
+ },
+ "type": "stickyNote",
+ "width": 203,
+ "height": 283,
+ "selected": false,
+ "positionAbsolute": {
+ "x": 693.7511120802441,
+ "y": 221.75098356027857
+ },
+ "dragging": false
+ }
+ ],
+ "edges": [
+ {
+ "source": "startAgentflow_0",
+ "sourceHandle": "startAgentflow_0-output-startAgentflow",
+ "target": "llmAgentflow_0",
+ "targetHandle": "llmAgentflow_0",
+ "data": {
+ "sourceColor": "#7EE787",
+ "targetColor": "#64B5F6",
+ "isHumanInput": false
+ },
+ "type": "agentFlow",
+ "id": "startAgentflow_0-startAgentflow_0-output-startAgentflow-llmAgentflow_0-llmAgentflow_0"
+ },
+ {
+ "source": "llmAgentflow_0",
+ "sourceHandle": "llmAgentflow_0-output-llmAgentflow",
+ "target": "agentAgentflow_0",
+ "targetHandle": "agentAgentflow_0",
+ "data": {
+ "sourceColor": "#64B5F6",
+ "targetColor": "#4DD0E1",
+ "isHumanInput": false
+ },
+ "type": "agentFlow",
+ "id": "llmAgentflow_0-llmAgentflow_0-output-llmAgentflow-agentAgentflow_0-agentAgentflow_0"
+ },
+ {
+ "source": "agentAgentflow_0",
+ "sourceHandle": "agentAgentflow_0-output-agentAgentflow",
+ "target": "agentAgentflow_1",
+ "targetHandle": "agentAgentflow_1",
+ "data": {
+ "sourceColor": "#4DD0E1",
+ "targetColor": "#4DD0E1",
+ "isHumanInput": false
+ },
+ "type": "agentFlow",
+ "id": "agentAgentflow_0-agentAgentflow_0-output-agentAgentflow-agentAgentflow_1-agentAgentflow_1"
+ },
+ {
+ "source": "agentAgentflow_1",
+ "sourceHandle": "agentAgentflow_1-output-agentAgentflow",
+ "target": "conditionAgentflow_0",
+ "targetHandle": "conditionAgentflow_0",
+ "data": {
+ "sourceColor": "#4DD0E1",
+ "targetColor": "#FFB938",
+ "isHumanInput": false
+ },
+ "type": "agentFlow",
+ "id": "agentAgentflow_1-agentAgentflow_1-output-agentAgentflow-conditionAgentflow_0-conditionAgentflow_0"
+ },
+ {
+ "source": "conditionAgentflow_0",
+ "sourceHandle": "conditionAgentflow_0-output-0",
+ "target": "loopAgentflow_0",
+ "targetHandle": "loopAgentflow_0",
+ "data": {
+ "sourceColor": "#FFB938",
+ "targetColor": "#FFA07A",
+ "edgeLabel": "0",
+ "isHumanInput": false
+ },
+ "type": "agentFlow",
+ "id": "conditionAgentflow_0-conditionAgentflow_0-output-0-loopAgentflow_0-loopAgentflow_0"
+ },
+ {
+ "source": "conditionAgentflow_0",
+ "sourceHandle": "conditionAgentflow_0-output-1",
+ "target": "llmAgentflow_1",
+ "targetHandle": "llmAgentflow_1",
+ "data": {
+ "sourceColor": "#FFB938",
+ "targetColor": "#64B5F6",
+ "edgeLabel": "1",
+ "isHumanInput": false
+ },
+ "type": "agentFlow",
+ "id": "conditionAgentflow_0-conditionAgentflow_0-output-1-llmAgentflow_1-llmAgentflow_1"
+ }
+ ]
+}