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docs: more fixes for refs (#33554)

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Mason Daugherty
2025-10-16 22:54:16 -04:00
committed by GitHub
parent 9dd494ddcd
commit 1d2273597a
41 changed files with 1305 additions and 1238 deletions
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53
libs/partners/deepseek/langchain_deepseek/chat_models.py
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@@ -38,20 +38,20 @@ class ChatDeepSeek(BaseChatOpenAI):
```
Key init args — completion params:
model: str
Name of DeepSeek model to use, e.g. "deepseek-chat".
temperature: float
model:
Name of DeepSeek model to use, e.g. `"deepseek-chat"`.
temperature:
Sampling temperature.
max_tokens: int | None
max_tokens:
Max number of tokens to generate.
Key init args — client params:
timeout: float | None
timeout:
Timeout for requests.
max_retries: int
max_retries:
Max number of retries.
api_key: str | None
DeepSeek API key. If not passed in will be read from env var DEEPSEEK_API_KEY.
api_key:
DeepSeek API key. If not passed in will be read from env var `DEEPSEEK_API_KEY`.
See full list of supported init args and their descriptions in the params section.
@@ -378,15 +378,17 @@ class ChatDeepSeek(BaseChatOpenAI):
- an OpenAI function/tool schema,
- a JSON Schema,
- a `TypedDict` class (support added in 0.1.20),
- a `TypedDict` class,
- or a Pydantic class.
If `schema` is a Pydantic class then the model output will be a
Pydantic instance of that class, and the model-generated fields will be
validated by the Pydantic class. Otherwise the model output will be a
dict and will not be validated. See `langchain_core.utils.function_calling.convert_to_openai_tool`
for more on how to properly specify types and descriptions of
schema fields when specifying a Pydantic or `TypedDict` class.
dict and will not be validated.
See `langchain_core.utils.function_calling.convert_to_openai_tool` for
more on how to properly specify types and descriptions of schema fields
when specifying a Pydantic or `TypedDict` class.
method: The method for steering model generation, one of:
@@ -400,8 +402,10 @@ class ChatDeepSeek(BaseChatOpenAI):
an error occurs during model output parsing it will be raised. If `True`
then both the raw model response (a `BaseMessage`) and the parsed model
response will be returned. If an error occurs during output parsing it
will be caught and returned as well. The final output is always a dict
with keys `'raw'`, `'parsed'`, and `'parsing_error'`.
will be caught and returned as well.
The final output is always a `dict` with keys `'raw'`, `'parsed'`, and
`'parsing_error'`.
strict:
Whether to enable strict schema adherence when generating the function
@@ -413,18 +417,19 @@ class ChatDeepSeek(BaseChatOpenAI):
kwargs: Additional keyword args aren't supported.
Returns:
A Runnable that takes same inputs as a `langchain_core.language_models.chat.BaseChatModel`.
A `Runnable` that takes same inputs as a
`langchain_core.language_models.chat.BaseChatModel`. If `include_raw` is
`False` and `schema` is a Pydantic class, `Runnable` outputs an instance
of `schema` (i.e., a Pydantic object). Otherwise, if `include_raw` is
`False` then `Runnable` outputs a `dict`.
If `include_raw` is False and `schema` is a Pydantic class, Runnable outputs
an instance of `schema` (i.e., a Pydantic object). Otherwise, if `include_raw` is False then Runnable outputs a dict.
If `include_raw` is `True`, then `Runnable` outputs a `dict` with keys:
If `include_raw` is True, then Runnable outputs a dict with keys:
- `'raw'`: BaseMessage
- `'parsed'`: None if there was a parsing error, otherwise the type depends on the `schema` as described above.
- `'parsing_error'`: BaseException | None
""" # noqa: E501
- `'raw'`: `BaseMessage`
- `'parsed'`: `None` if there was a parsing error, otherwise the type
depends on the `schema` as described above.
- `'parsing_error'`: `BaseException | None`
"""
# Some applications require that incompatible parameters (e.g., unsupported
# methods) be handled.
if method == "json_schema":