From 218c554c4f9486d4facbd5549bed0e222f823546 Mon Sep 17 00:00:00 2001 From: Isaac Francisco <78627776+isahers1@users.noreply.github.com> Date: Thu, 25 Jul 2024 14:10:41 -0700 Subject: [PATCH] [docs]: add doctoring to ChatTogether (#24636) --- .../langchain_together/chat_models.py | 250 +++++++++++++++++- 1 file changed, 243 insertions(+), 7 deletions(-) diff --git a/libs/partners/together/langchain_together/chat_models.py b/libs/partners/together/langchain_together/chat_models.py index a3c5d604a62..ee3473eba40 100644 --- a/libs/partners/together/langchain_together/chat_models.py +++ b/libs/partners/together/langchain_together/chat_models.py @@ -19,19 +19,255 @@ from langchain_openai.chat_models.base import BaseChatOpenAI class ChatTogether(BaseChatOpenAI): - """ChatTogether chat model. + r"""ChatTogether chat model. - To use, you should have the environment variable `TOGETHER_API_KEY` - set with your API key or pass it as a named parameter to the constructor. + Setup: + Install ``langchain-together`` and set environment variable ``TOGETHER_API_KEY``. - Example: + .. code-block:: bash + + pip install -U langchain-together + export TOGETHER_API_KEY="your-api-key" + + + Key init args — completion params: + model: str + Name of model to use. + temperature: float + Sampling temperature. + max_tokens: Optional[int] + Max number of tokens to generate. + logprobs: Optional[bool] + Whether to return logprobs. + + Key init args — client params: + timeout: Union[float, Tuple[float, float], Any, None] + Timeout for requests. + max_retries: int + Max number of retries. + api_key: Optional[str] + Together API key. If not passed in will be read from env var OPENAI_API_KEY. + + Instantiate: .. code-block:: python - from langchain_together import ChatTogether + from langhcain_together import ChatTogether + + llm = ChatTogether( + model="meta-llama/Llama-3-70b-chat-hf", + temperature=0, + max_tokens=None, + timeout=None, + max_retries=2, + # api_key="...", + # other params... + ) + + Invoke: + .. code-block:: python + + messages = [ + ( + "system", + "You are a helpful translator. Translate the user sentence to French.", + ), + ("human", "I love programming."), + ] + llm.invoke(messages) + + .. code-block:: python + + AIMessage( + content="J'adore la programmation.", + response_metadata={ + 'token_usage': {'completion_tokens': 9, 'prompt_tokens': 32, 'total_tokens': 41}, + 'model_name': 'meta-llama/Llama-3-70b-chat-hf', + 'system_fingerprint': None, + 'finish_reason': 'stop', + 'logprobs': None + }, + id='run-168dceca-3b8b-4283-94e3-4c739dbc1525-0', + usage_metadata={'input_tokens': 32, 'output_tokens': 9, 'total_tokens': 41}) + + Stream: + .. code-block:: python + + for chunk in llm.stream(messages): + print(chunk) + + .. code-block:: python + + content='J' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' + content="'" id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' + content='ad' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' + content='ore' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' + content=' la' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' + content=' programm' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' + content='ation' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' + content='.' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' + content='' response_metadata={'finish_reason': 'stop', 'model_name': 'meta-llama/Llama-3-70b-chat-hf'} id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' - model = ChatTogether() - """ + Async: + .. code-block:: python + + await llm.ainvoke(messages) + + # stream: + # async for chunk in (await llm.astream(messages)) + + # batch: + # await llm.abatch([messages]) + + .. code-block:: python + + AIMessage( + content="J'adore la programmation.", + response_metadata={ + 'token_usage': {'completion_tokens': 9, 'prompt_tokens': 32, 'total_tokens': 41}, + 'model_name': 'meta-llama/Llama-3-70b-chat-hf', + 'system_fingerprint': None, + 'finish_reason': 'stop', + 'logprobs': None + }, + id='run-09371a11-7f72-4c53-8e7c-9de5c238b34c-0', + usage_metadata={'input_tokens': 32, 'output_tokens': 9, 'total_tokens': 41}) + + Tool calling: + .. code-block:: python + + from langchain_core.pydantic_v1 import BaseModel, Field + + # Only certain models support tool calling, check the together website to confirm compatibility + llm = ChatTogether(model="mistralai/Mixtral-8x7B-Instruct-v0.1") + + class GetWeather(BaseModel): + '''Get the current weather in a given location''' + + location: str = Field( + ..., description="The city and state, e.g. San Francisco, CA" + ) + + class GetPopulation(BaseModel): + '''Get the current population in a given location''' + + location: str = Field( + ..., description="The city and state, e.g. San Francisco, CA" + ) + + llm_with_tools = llm.bind_tools([GetWeather, GetPopulation]) + ai_msg = llm_with_tools.invoke( + "Which city is bigger: LA or NY?" + ) + ai_msg.tool_calls + + + .. code-block:: python + + [ + { + 'name': 'GetPopulation', + 'args': {'location': 'NY'}, + 'id': 'call_m5tstyn2004pre9bfuxvom8x', + 'type': 'tool_call' + }, + { + 'name': 'GetPopulation', + 'args': {'location': 'LA'}, + 'id': 'call_0vjgq455gq1av5sp9eb1pw6a', + 'type': 'tool_call' + } + ] + + Structured output: + .. code-block:: python + + from typing import Optional + + from langchain_core.pydantic_v1 import BaseModel, Field + + + class Joke(BaseModel): + '''Joke to tell user.''' + + setup: str = Field(description="The setup of the joke") + punchline: str = Field(description="The punchline to the joke") + rating: Optional[int] = Field(description="How funny the joke is, from 1 to 10") + + + structured_llm = llm.with_structured_output(Joke) + structured_llm.invoke("Tell me a joke about cats") + + .. code-block:: python + + Joke( + setup='Why was the cat sitting on the computer?', + punchline='To keep an eye on the mouse!', + rating=7 + ) + + JSON mode: + .. code-block:: python + + json_llm = llm.bind(response_format={"type": "json_object"}) + ai_msg = json_llm.invoke( + "Return a JSON object with key 'random_ints' and a value of 10 random ints in [0-99]" + ) + ai_msg.content + + .. code-block:: python + + ' {\\n"random_ints": [\\n13,\\n54,\\n78,\\n45,\\n67,\\n90,\\n11,\\n29,\\n84,\\n33\\n]\\n}' + + Token usage: + .. code-block:: python + + ai_msg = llm.invoke(messages) + ai_msg.usage_metadata + + .. code-block:: python + + {'input_tokens': 37, 'output_tokens': 6, 'total_tokens': 43} + + Logprobs: + .. code-block:: python + + logprobs_llm = llm.bind(logprobs=True) + messages=[("human","Say Hello World! Do not return anything else.")] + ai_msg = logprobs_llm.invoke(messages) + ai_msg.response_metadata["logprobs"] + + .. code-block:: python + + { + 'content': None, + 'token_ids': [22557, 3304, 28808, 2], + 'tokens': [' Hello', ' World', '!', ''], + 'token_logprobs': [-4.7683716e-06, -5.9604645e-07, 0, -0.057373047] + } + + + Response metadata + .. code-block:: python + + ai_msg = llm.invoke(messages) + ai_msg.response_metadata + + .. code-block:: python + + { + 'token_usage': { + 'completion_tokens': 4, + 'prompt_tokens': 19, + 'total_tokens': 23 + }, + 'model_name': 'mistralai/Mixtral-8x7B-Instruct-v0.1', + 'system_fingerprint': None, + 'finish_reason': 'eos', + 'logprobs': None + } + + """ # noqa: E501 @property def lc_secrets(self) -> Dict[str, str]: