From a8f990c2422986c5e509df83d77b893bbf89981e Mon Sep 17 00:00:00 2001 From: toi500 <138339291+toi500@users.noreply.github.com> Date: Tue, 13 May 2025 05:05:03 +0200 Subject: [PATCH] Feature/add Deep Research V2 Template (#4422) add new V2 template --- .../agentflowsv2/Deep Research V2.json | 2142 +++++++++++++++++ 1 file changed, 2142 insertions(+) create mode 100644 packages/server/marketplaces/agentflowsv2/Deep Research V2.json 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. 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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. 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You are Agent 0. Your goal is to explore any topic provided by the user in depth with Agent 1.

  1. Start: Introduce the topic to Agent 1. Share your initial thoughts and any assumptions you have.

  2. Research & Share:

  3. Discuss & Deepen:

  4. Mindset: Be curious, analytical, and open to different perspectives. Aim for a thorough understanding, not just agreement.

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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. 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You are Agent 1. Your goal is to explore a topic in depth with Agent 0.

  1. Respond & Share:

  2. Research & Contribute:

  3. Discuss & Deepen:

  4. Mindset: Be respectful, analytical, and open to different viewpoints. Aim for a thorough exploration and constructive disagreement, backed by research.

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+ "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": [ + { 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{{ 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. 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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:

  1. Title: A clear, compelling title for the white paper that reflects the core subject.

  2. Abstract/Executive Summary: A concise overview (approx. 200-300 words) of the white paper's main arguments, scope, and conclusions, derived from the conversation.

  3. Introduction:

  4. Main Body / Thematic Analysis (Multiple Sections):

  5. Synthesis of Insights and Key Conclusions:

  6. Implications and Future Directions:

  7. Conclusion: A strong concluding section summarizing the white paper's main findings, their significance, and a final thought on the subject.

Style and Tone:

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 }}
--

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