langchain-react-agent

# 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+