Epictetus
a14f09bec2
New skills: - langgraph-workflow-creation (from LangGraphProjects) - agent-supervisor (from multi_agent_workflow_demo_in_langgraph) Fixes: - Publisher dedup: skip existing skills - Older repos: pushed_after 2024-06-01 (was 2026-05-01) - Lower stars: 10 (was 15)
85 lines
3.9 KiB
Markdown
85 lines
3.9 KiB
Markdown
---
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name: agent-supervisor
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version: 1.0.0
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description: Demonstrate a supervisor-worker architecture for intelligent task delegation
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and real-time decision-making.
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inputs:
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- name: OPENAI_API_KEY
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description: OpenAI API key for language models.
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- name: TAVILY_API_KEY
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description: Tavily API key for search functionality.
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steps:
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- step: 1
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action: Load environment variables.
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details: Set the OPENAI_API_KEY and TAVILY_API_KEY environment variables.
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- step: 2
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action: Configure LangChain tools.
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details: Initialize TavilySearchResults and PythonREPLTool.
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- step: 3
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action: Define agent nodes.
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details: Create functions for the Researcher and Coder agents that process state
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through their respective tasks.
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- step: 4
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action: Set up supervisor agent.
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details: Create a supervisor agent function that decides which worker should act
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next based on user input.
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- step: 5
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action: Build state graph.
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details: Construct the state graph with nodes for each agent and edges connecting
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them to the supervisor node.
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- step: 6
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action: Add conditional edges.
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details: Define conditions for transitioning between agents based on their responses.
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- step: 7
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action: Compile graph.
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details: Compile the state graph into a runnable workflow.
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- step: 8
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action: Run example queries.
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details: Stream through the workflow with example inputs to demonstrate its functionality.
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outputs:
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- name: 'Example 1: Code Hello World'
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description: A demonstration of coding a simple hello world program.
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- name: 'Example 2: Research Report'
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description: A demonstration of researching and writing a brief report on pikas.
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tags: []
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metadata:
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source_repo: https://github.com/extrawest/multi_agent_workflow_demo_in_langgraph.git
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extracted_at: ''
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confidence: 0.9
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---
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# agent-supervisor
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Demonstrate a supervisor-worker architecture for intelligent task delegation and real-time decision-making.
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## Steps
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1. {'step': 1, 'action': 'Load environment variables.', 'details': 'Set the OPENAI_API_KEY and TAVILY_API_KEY environment variables.'}
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2. {'step': 2, 'action': 'Configure LangChain tools.', 'details': 'Initialize TavilySearchResults and PythonREPLTool.'}
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3. {'step': 3, 'action': 'Define agent nodes.', 'details': 'Create functions for the Researcher and Coder agents that process state through their respective tasks.'}
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4. {'step': 4, 'action': 'Set up supervisor agent.', 'details': 'Create a supervisor agent function that decides which worker should act next based on user input.'}
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5. {'step': 5, 'action': 'Build state graph.', 'details': 'Construct the state graph with nodes for each agent and edges connecting them to the supervisor node.'}
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6. {'step': 6, 'action': 'Add conditional edges.', 'details': 'Define conditions for transitioning between agents based on their responses.'}
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7. {'step': 7, 'action': 'Compile graph.', 'details': 'Compile the state graph into a runnable workflow.'}
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8. {'step': 8, 'action': 'Run example queries.', 'details': 'Stream through the workflow with example inputs to demonstrate its functionality.'}
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## Inputs
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- {'name': 'OPENAI_API_KEY', 'description': 'OpenAI API key for language models.'}
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- {'name': 'TAVILY_API_KEY', 'description': 'Tavily API key for search functionality.'}
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## Outputs
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- {'name': 'Example 1: Code Hello World', 'description': 'A demonstration of coding a simple hello world program.'}
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- {'name': 'Example 2: Research Report', 'description': 'A demonstration of researching and writing a brief report on pikas.'}
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## Failure Modes
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- {'mode': 'Invalid API keys', 'description': 'The workflow may fail if the provided API keys are invalid or expired.'}
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- {'mode': 'Insufficient permissions', 'description': 'The workflow may fail if the user does not have sufficient permissions to use the Tavily search functionality.'}
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## Source
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Extracted from: [https://github.com/extrawest/multi_agent_workflow_demo_in_langgraph.git](https://github.com/extrawest/multi_agent_workflow_demo_in_langgraph.git)
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Confidence: 0.9
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