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docs: Standardize ChatGroq (#22751)
Updated ChatGroq doc string as per issue https://github.com/langchain-ai/langchain/issues/22296:"langchain_groq: updated docstring for ChatGroq in langchain_groq to match that of the description (in the appendix) provided in issue https://github.com/langchain-ai/langchain/issues/22296. " Issue: This PR is in response to issue https://github.com/langchain-ai/langchain/issues/22296, and more specifically the ChatGroq model. In particular, this PR updates the docstring for langchain/libs/partners/groq/langchain_groq/chat_model.py by adding the following sections: Instantiate, Invoke, Stream, Async, Tool calling, Structured Output, and Response metadata. I used the template from the Anthropic implementation and referenced the Appendix of the original issue post. I also noted that: `usage_metadata `returns none for all ChatGroq models I tested; there is no mention of image input in the ChatGroq documentation; unlike that of ChatHuggingFace, `.stream(messages)` for ChatGroq returned blocks of output. --------- Co-authored-by: lucast2021 <lucast2021@headroyce.org> Co-authored-by: Bagatur <baskaryan@gmail.com>
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Lucas Tucker
GitHub
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@ -85,8 +85,8 @@ class ChatGroq(BaseChatModel):
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To use, you should have the
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environment variable ``GROQ_API_KEY`` set with your API key.
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Any parameters that are valid to be passed to the groq.create call can be passed
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in, even if not explicitly saved on this class.
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Any parameters that are valid to be passed to the groq.create call
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can be passed in, even if not explicitly saved on this class.
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Example:
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.. code-block:: python
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@ -94,6 +94,208 @@ class ChatGroq(BaseChatModel):
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from langchain_groq import ChatGroq
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model = ChatGroq(model_name="mixtral-8x7b-32768")
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Setup:
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Install ``langchain-groq`` and set environment variable
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``GROQ_API_KEY``.
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.. code-block:: bash
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pip install -U langchain-groq
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export GROQ_API_KEY="your-api-key"
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Key init args — completion params:
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model: str
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Name of Groq model to use. E.g. "mixtral-8x7b-32768".
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temperature: float
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Sampling temperature. Ranges from 0.0 to 1.0.
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max_tokens: Optional[int]
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Max number of tokens to generate.
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model_kwargs: Dict[str, Any]
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Holds any model parameters valid for create call not
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explicitly specified.
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Key init args — client params:
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timeout: Union[float, Tuple[float, float], Any, None]
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Timeout for requests.
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max_retries: int
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Max number of retries.
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api_key: Optional[str]
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Groq API key. If not passed in will be read from env var GROQ_API_KEY.
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base_url: Optional[str]
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Base URL path for API requests, leave blank if not using a proxy
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or service emulator.
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custom_get_token_ids: Optional[Callable[[str], List[int]]]
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Optional encoder to use for counting tokens.
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See full list of supported init args and their descriptions in the params
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section.
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Instantiate:
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.. code-block:: python
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from langchain_groq import ChatGroq
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model = ChatGroq(
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model="mixtral-8x7b-32768",
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temperature=0.0,
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max_retries=2,
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# other params...
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)
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Invoke:
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.. code-block:: python
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messages = [
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("system", "You are a helpful translator. Translate the user
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sentence to French."),
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("human", "I love programming."),
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]
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model.invoke(messages)
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.. code-block:: python
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AIMessage(content='The English sentence "I love programming" can
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be translated to French as "J\'aime programmer". The word
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"programming" is translated as "programmer" in French.',
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response_metadata={'token_usage': {'completion_tokens': 38,
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'prompt_tokens': 28, 'total_tokens': 66, 'completion_time':
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0.057975474, 'prompt_time': 0.005366091, 'queue_time': None,
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'total_time': 0.063341565}, 'model_name': 'mixtral-8x7b-32768',
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'system_fingerprint': 'fp_c5f20b5bb1', 'finish_reason': 'stop',
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'logprobs': None}, id='run-ecc71d70-e10c-4b69-8b8c-b8027d95d4b8-0')
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Stream:
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.. code-block:: python
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for chunk in model.stream(messages):
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print(chunk)
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.. code-block:: python
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content='' id='run-4e9f926b-73f5-483b-8ef5-09533d925853'
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content='The' id='run-4e9f926b-73f5-483b-8ef5-09533d925853'
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content=' English' id='run-4e9f926b-73f5-483b-8ef5-09533d925853'
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content=' sentence' id='run-4e9f926b-73f5-483b-8ef5-09533d925853'
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...
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content=' program' id='run-4e9f926b-73f5-483b-8ef5-09533d925853'
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content='".' id='run-4e9f926b-73f5-483b-8ef5-09533d925853'
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content='' response_metadata={'finish_reason': 'stop'}
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id='run-4e9f926b-73f5-483b-8ef5-09533d925853
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.. code-block:: python
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stream = model.stream(messages)
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full = next(stream)
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for chunk in stream:
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full += chunk
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full
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.. code-block:: python
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AIMessageChunk(content='The English sentence "I love programming"
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can be translated to French as "J\'aime programmer".
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Here\'s the breakdown of the sentence:\n\n* "J\'aime" is the
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French equivalent of "I love"\n* "programmer" is the French
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infinitive for "to program"\n\nSo, the literal translation
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is "I love to program". However, in English we often omit the
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"to" when talking about activities we love, and the same applies
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to French. Therefore, "J\'aime programmer" is the correct and
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natural way to express "I love programming" in French.',
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response_metadata={'finish_reason': 'stop'},
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id='run-a3c35ac4-0750-4d08-ac55-bfc63805de76')
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Async:
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.. code-block:: python
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await model.ainvoke(messages)
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.. code-block:: python
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AIMessage(content='The English sentence "I love programming" can
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be translated to French as "J\'aime programmer". The word
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"programming" is translated as "programmer" in French. I hope
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this helps! Let me know if you have any other questions.',
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response_metadata={'token_usage': {'completion_tokens': 53,
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'prompt_tokens': 28, 'total_tokens': 81, 'completion_time':
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0.083623752, 'prompt_time': 0.007365126, 'queue_time': None,
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'total_time': 0.090988878}, 'model_name': 'mixtral-8x7b-32768',
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'system_fingerprint': 'fp_c5f20b5bb1', 'finish_reason': 'stop',
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'logprobs': None}, id='run-897f3391-1bea-42e2-82e0-686e2367bcf8-0')
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Tool calling:
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.. code-block:: python
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from langchain_core.pydantic_v1 import BaseModel, Field
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class GetWeather(BaseModel):
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'''Get the current weather in a given location'''
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location: str = Field(..., description="The city and state,
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e.g. San Francisco, CA")
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class GetPopulation(BaseModel):
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'''Get the current population in a given location'''
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location: str = Field(..., description="The city and state,
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e.g. San Francisco, CA")
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model_with_tools = model.bind_tools([GetWeather, GetPopulation])
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ai_msg = model_with_tools.invoke("What is the population of NY?")
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ai_msg.tool_calls
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.. code-block:: python
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[{'name': 'GetPopulation',
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'args': {'location': 'NY'},
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'id': 'call_bb8d'}]
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See ``ChatGroq.bind_tools()`` method for more.
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Structured output:
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.. code-block:: python
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from typing import Optional
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from langchain_core.pydantic_v1 import BaseModel, Field
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class Joke(BaseModel):
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'''Joke to tell user.'''
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setup: str = Field(description="The setup of the joke")
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punchline: str = Field(description="The punchline to the joke")
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rating: Optional[int] = Field(description="How funny the joke
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is, from 1 to 10")
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structured_model = model.with_structured_output(Joke)
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structured_model.invoke("Tell me a joke about cats")
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.. code-block:: python
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Joke(setup="Why don't cats play poker in the jungle?",
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punchline='Too many cheetahs!', rating=None)
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See ``ChatGroq.with_structured_output()`` for more.
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Response metadata
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.. code-block:: python
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ai_msg = model.invoke(messages)
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ai_msg.response_metadata
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.. code-block:: python
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{'token_usage': {'completion_tokens': 70,
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'prompt_tokens': 28,
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'total_tokens': 98,
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'completion_time': 0.111956391,
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'prompt_time': 0.007518279,
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'queue_time': None,
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'total_time': 0.11947467},
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'model_name': 'mixtral-8x7b-32768',
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'system_fingerprint': 'fp_c5f20b5bb1',
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'finish_reason': 'stop',
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'logprobs': None}
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"""
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client: Any = Field(default=None, exclude=True) #: :meta private:
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@ -105,7 +307,7 @@ class ChatGroq(BaseChatModel):
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model_kwargs: Dict[str, Any] = Field(default_factory=dict)
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"""Holds any model parameters valid for `create` call not explicitly specified."""
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groq_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
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"""Automatically inferred from env var `groq_API_KEY` if not provided."""
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"""Automatically inferred from env var `GROQ_API_KEY` if not provided."""
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groq_api_base: Optional[str] = Field(default=None, alias="base_url")
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"""Base URL path for API requests, leave blank if not using a proxy or service
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emulator."""
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