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langchain-react-agent

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LangChain ReAct agent implementation with tool binding for reasoning and action loops

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Source SKILL.md: https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/ai-agents-conversational/skills/langchain-react-agent/SKILL.md

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LangChain ReAct Agent Skill

Capabilities

  • Implement ReAct (Reasoning + Acting) agent patterns using LangChain
  • Configure tool binding and function calling for agents
  • Design thought-action-observation loops
  • Integrate with various LLM providers (OpenAI, Anthropic, etc.)
  • Handle agent memory and state persistence
  • Implement error handling and retry logic for agent actions

Target Processes

  • react-agent-implementation
  • function-calling-agent

Implementation Details

Core Components

  1. Agent Executor Setup: Configure LangChain AgentExecutor with appropriate settings
  2. Tool Integration: Bind tools with proper schemas and descriptions
  3. Prompt Engineering: Design system prompts for ReAct reasoning patterns
  4. Output Parsing: Parse agent outputs and handle structured responses

Configuration Options

  • LLM model selection and parameters
  • Tool definitions and schemas
  • Memory type (buffer, summary, vector)
  • Max iterations and timeout settings
  • Verbose/debug mode configuration

Dependencies

  • langchain
  • langchain-openai / langchain-anthropic
  • Python 3.9+