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Structured output allows agents to return data in a specific, predictable format. Instead of parsing natural language responses, you get structured data in ...
Python API reference for language_models.chat_models.BaseChatModel.with_structured_output in langchain_core. Part of the LangChain ecosystem.
2025/9/10 -Structured output in LangChain is a powerful way to make LLM responses predictable, reliable, and directly usable in downstream systems. Instead ...
Structured output lets the agent return typed, machine-readable data instead of plain text. Instead of rendering a single string, you get a structured ...
2025/6/30 -Learn the best methods for working with LangChain structured outputs in real-world applications, from parsing to validation.
2026/6/29 -What is Structured Output in LangChain? ... Structured output means forcing an LLM to return data in a predefined format instead of plain text.
2024/6/3 -The cleanest way to do this in Python is to extend the BaseModel class with the type of output class you want.
2025/7/22 -I'm implementing a workflow where one of the nodes invokes an LLM that: Returns a structured output (written to state), and Conditionally ...
2025/7/19 -TypedDict is a lightweight way to define structured output using standard Python typing. It's ideal when you want just enough structure ...
The output schema. Can be passed in as: An OpenAI function/tool schema,; A JSON Schema,; A TypedDict class,; Or a Pydantic class.