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oss(py): genai docs work (#1375)
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reference/python/uv.lock

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src/oss/langchain/models.mdx

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- **Method parameter**: Some providers support different methods (`'json_schema'`, `'function_calling'`, `'json_mode'`)
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- `'json_schema'` typically refers to dedicated structured output features offered by a provider
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- `'function_calling'` derives structured output by forcing a [tool call](#tool-calling) following the given schema
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- `'json_mode'` is a precursor to `'json_schema'` offered by some providers- it generates valid json, but the schema must be described in the prompt
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- `'json_mode'` is a precursor to `'json_schema'` offered by some providers - it generates valid json, but the schema must be described in the prompt
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- **Include raw**: Use `include_raw=True` to get both the parsed output and the raw AI message
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- **Validation**: Pydantic models provide automatic validation, while `TypedDict` and JSON Schema require manual validation
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</Note>

src/oss/langchain/structured-output.mdx

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## Provider strategy
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Some model providers support structured output natively through their APIs (currently only OpenAI and Grok). This is the most reliable method when available.
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Some model providers support structured output natively through their APIs (e.g. OpenAI, Grok, Gemini). This is the most reliable method when available.
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To use this strategy, configure a `ProviderStrategy`:
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src/oss/langgraph/add-memory.mdx

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<Warning>
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When deleting messages, **make sure** that the resulting message history is valid. Check the limitations of the LLM provider you're using. For example:
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* some providers expect message history to start with a `user` message
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* most providers require `assistant` messages with tool calls to be followed by corresponding `tool` result messages.
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* Some providers expect message history to start with a `user` message
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* Most providers require `assistant` messages with tool calls to be followed by corresponding `tool` result messages.
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</Warning>
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<Accordion title="Full example: delete messages">

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