记忆

LangChain

Builds and debugs LangChain apps in Python: LCEL chains, agents, tools, retrievers, streaming, and structured output. Use when writing or reviewing a chain, agent, tool, retriever, or prompt template; when a prompt raises KeyError or "missing variables"; when streaming arrives as one blob or astream_events yields nothing; when an agent loops until GraphRecursionError or repeats a tool; when tool calls fail validation or the provider rejects a tool_call_id; when chat history disappears or the context window overflows; when with_structured_output returns None or a parser crashes on valid JSON; when retrieval returns the wrong chunks; when LangSmith traces are empty; when retries, rate limits, or token cost need bounding; or when imports break after an upgrade. Covers LangGraph state, checkpointers, and middleware. Not for framework-agnostic agent architecture (agents), retrieval design (rag), or chunk tuning (rag-chunking).

它能做什么

Builds and debugs LangChain apps in Python: LCEL chains, agents, tools, retrievers, streaming, and structured output. Use when writing or reviewing a chain, agent, tool, retriever, or prompt template; when a prompt raises KeyError or "missing variables"; when streaming arrives as one blob or astream_events yields nothing; when an agent loops until GraphRecursionError or repeats a tool; when tool calls fail validation or the provider rejects a tool_call_id; when chat history disappears or the context window overflows; when with_structured_output returns None or a parser crashes on valid JSON; when retrieval returns the wrong chunks; when LangSmith traces are empty; when retries, rate limits, or token cost need bounding; or when imports break after an upgrade. Covers LangGraph state, checkpointers, and middleware. Not for framework-agnostic agent architecture (agents), retrieval design (rag), or chunk tuning (rag-chunking).

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