LangChain
Provide a standard, model-agnostic Python/TypeScript interface plus a prebuilt agent (create_agent) for building LLM applications that loop over tool calls in the ReAct shape, with first-class integrations for retrieval, structured output, MCP tools, and middleware-based human approval.
Description
LangChain is the MIT-licensed agent and LLM-application framework built by LangChain Inc., the same company that ships LangGraph and LangSmith. In its 1.x form the headline surface is create_agent, a prebuilt agent that runs a chat model in a ReAct loop over a developer-supplied list of tools, stopping when the model emits a final answer or an iteration limit is reached. The framework ships standard integrations for models, embeddings, vector stores, retrievers, MCP servers, and content-block citations; orchestration concerns beyond the loop (durable state, interrupts, multi-agent graphs) are delegated to LangGraph, which create_agent compiles down to internally.
Solution
ReAct tool-calling loop. The model is bound to a tool list; runtime alternates model-emit-tool-calls and tool-execute steps, and stops on final-answer-or-iteration-limit. Middleware hooks run before/after model and tool calls inside the compiled LangGraph that create_agent returns.
Primary use cases
- ReAct-shape agents calling provider-agnostic models and tools
- RAG via retrievers + cross-encoder reranking + EnsembleRetriever
- structured-output agents with ProviderStrategy / ToolStrategy
- MCP-tool integration via langchain-mcp-adapters
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