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docs(groq): cleanup (#32043)

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Mason Daugherty 2025-07-15 10:37:37 -04:00 committed by GitHub
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1 changed files with 31 additions and 25 deletions
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libs/partners/groq/langchain_groq/chat_models.py
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@ -159,8 +159,7 @@ class ChatGroq(BaseChatModel):
.. code-block:: python .. code-block:: python
messages = [ messages = [
("system", "You are a helpful translator. Translate the user ("system", "You are a helpful translator. Translate the user sentence to French."),
sentence to French."),
("human", "I love programming."), ("human", "I love programming."),
] ]
llm.invoke(messages) llm.invoke(messages)
@ -244,14 +243,12 @@ class ChatGroq(BaseChatModel):
class GetWeather(BaseModel): class GetWeather(BaseModel):
'''Get the current weather in a given location''' '''Get the current weather in a given location'''
location: str = Field(..., description="The city and state, location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
e.g. San Francisco, CA")
class GetPopulation(BaseModel): class GetPopulation(BaseModel):
'''Get the current population in a given location''' '''Get the current population in a given location'''
location: str = Field(..., description="The city and state, location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
e.g. San Francisco, CA")
model_with_tools = llm.bind_tools([GetWeather, GetPopulation]) model_with_tools = llm.bind_tools([GetWeather, GetPopulation])
ai_msg = model_with_tools.invoke("What is the population of NY?") ai_msg = model_with_tools.invoke("What is the population of NY?")
@ -277,16 +274,14 @@ class ChatGroq(BaseChatModel):
setup: str = Field(description="The setup of the joke") setup: str = Field(description="The setup of the joke")
punchline: str = Field(description="The punchline to the joke") punchline: str = Field(description="The punchline to the joke")
rating: Optional[int] = Field(description="How funny the joke rating: Optional[int] = Field(description="How funny the joke is, from 1 to 10")
is, from 1 to 10")
structured_model = llm.with_structured_output(Joke) structured_model = llm.with_structured_output(Joke)
structured_model.invoke("Tell me a joke about cats") structured_model.invoke("Tell me a joke about cats")
.. code-block:: python .. code-block:: python
Joke(setup="Why don't cats play poker in the jungle?", Joke(setup="Why don't cats play poker in the jungle?", punchline='Too many cheetahs!', rating=None)
punchline='Too many cheetahs!', rating=None)
See ``ChatGroq.with_structured_output()`` for more. See ``ChatGroq.with_structured_output()`` for more.
@ -309,7 +304,7 @@ class ChatGroq(BaseChatModel):
'system_fingerprint': 'fp_c5f20b5bb1', 'system_fingerprint': 'fp_c5f20b5bb1',
'finish_reason': 'stop', 'finish_reason': 'stop',
'logprobs': None} 'logprobs': None}
""" """ # noqa: E501
client: Any = Field(default=None, exclude=True) #: :meta private: client: Any = Field(default=None, exclude=True) #: :meta private:
async_client: Any = Field(default=None, exclude=True) #: :meta private: async_client: Any = Field(default=None, exclude=True) #: :meta private:
@ -834,7 +829,7 @@ class ChatGroq(BaseChatModel):
"auto" to automatically determine which function to call "auto" to automatically determine which function to call
with the option to not call any function, "any" to enforce that some with the option to not call any function, "any" to enforce that some
function is called, or a dict of the form: function is called, or a dict of the form:
{"type": "function", "function": {"name": <<tool_name>>}}. ``{"type": "function", "function": {"name": <<tool_name>>}}``.
**kwargs: Any additional parameters to pass to the **kwargs: Any additional parameters to pass to the
:class:`~langchain.runnable.Runnable` constructor. :class:`~langchain.runnable.Runnable` constructor.
@ -876,10 +871,12 @@ class ChatGroq(BaseChatModel):
Args: Args:
schema: schema:
The output schema. Can be passed in as: The output schema. Can be passed in as:
- an OpenAI function/tool schema, - an OpenAI function/tool schema,
- a JSON Schema, - a JSON Schema,
- a TypedDict class (supported added in 0.1.9), - a TypedDict class (supported added in 0.1.9),
- or a Pydantic class. - or a Pydantic class.
If ``schema`` is a Pydantic class then the model output will be a 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 Pydantic instance of that class, and the model-generated fields will be
validated by the Pydantic class. Otherwise the model output will be a validated by the Pydantic class. Otherwise the model output will be a
@ -891,19 +888,27 @@ class ChatGroq(BaseChatModel):
Added support for TypedDict class. Added support for TypedDict class.
method: method:
The method for steering model generation, either "function_calling" The method for steering model generation, either ``'function_calling'``
or "json_mode". If "function_calling" then the schema will be converted or ``'json_mode'``. If ``'function_calling'`` then the schema will be converted
to an OpenAI function and the returned model will make use of the to an OpenAI function and the returned model will make use of the
function-calling API. If "json_mode" then OpenAI's JSON mode will be function-calling API. If ``'json_mode'`` then OpenAI's JSON mode will be
used. Note that if using "json_mode" then you must include instructions used.
for formatting the output into the desired schema into the model call.
.. note::
If using ``'json_mode'`` then you must include instructions for formatting
the output into the desired schema into the model call. (either via the
prompt itself or in the system message/prompt/instructions).
.. warning::
``'json_mode'`` does not support streaming responses stop sequences.
include_raw: include_raw:
If False then only the parsed structured output is returned. If If False then only the parsed structured output is returned. If
an error occurs during model output parsing it will be raised. If True 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 then both the raw model response (a BaseMessage) and the parsed model
response will be returned. If an error occurs during output parsing it 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 will be caught and returned as well. The final output is always a dict
with keys "raw", "parsed", and "parsing_error". with keys ``'raw'``, ``'parsed'``, and ``'parsing_error'``.
kwargs: kwargs:
Any additional parameters to pass to the Any additional parameters to pass to the
:class:`~langchain.runnable.Runnable` constructor. :class:`~langchain.runnable.Runnable` constructor.
@ -917,6 +922,7 @@ class ChatGroq(BaseChatModel):
Otherwise, if ``include_raw`` is False then Runnable outputs a dict. 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 - ``"raw"``: BaseMessage
- ``"parsed"``: None if there was a parsing error, otherwise the type depends on the ``schema`` as described above. - ``"parsed"``: None if there was a parsing error, otherwise the type depends on the ``schema`` as described above.
- ``"parsing_error"``: Optional[BaseException] - ``"parsing_error"``: Optional[BaseException]