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docs: Add ChatBaichuan docstrings (#24348)
- **Description:** Add ChatBaichuan rich docstrings. - **Issue:** the issue #22296
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@ -106,10 +106,145 @@ async def aconnect_httpx_sse(
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class ChatBaichuan(BaseChatModel):
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"""Baichuan chat models API by Baichuan Intelligent Technology.
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"""Baichuan chat model integration.
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For more information, see https://platform.baichuan-ai.com/docs/api
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"""
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Setup:
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To use, you should have the environment variable``BAICHUAN_API_KEY`` set with
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your API KEY.
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.. code-block:: bash
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export BAICHUAN_API_KEY="your-api-key"
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Key init args — completion params:
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model: Optional[str]
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Name of Baichuan model to use.
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max_tokens: Optional[int]
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Max number of tokens to generate.
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streaming: Optional[bool]
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Whether to stream the results or not.
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temperature: Optional[float]
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Sampling temperature.
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top_p: Optional[float]
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What probability mass to use.
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top_k: Optional[int]
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What search sampling control to use.
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Key init args — client params:
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api_key: Optional[str]
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MiniMax API key. If not passed in will be read from env var BAICHUAN_API_KEY.
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base_url: Optional[str]
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Base URL for API requests.
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See full list of supported init args and their descriptions in the params section.
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Instantiate:
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.. code-block:: python
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from langchain_community.chat_models import ChatBaichuan
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chat = ChatBaichuan(
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api_key=api_key,
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model='Baichuan4',
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# temperature=...,
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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", "你是一名专业的翻译家,可以将用户的中文翻译为英文。"),
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("human", "我喜欢编程。"),
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]
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chat.invoke(messages)
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.. code-block:: python
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AIMessage(
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content='I enjoy programming.',
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response_metadata={
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'token_usage': {
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'prompt_tokens': 93,
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'completion_tokens': 5,
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'total_tokens': 98
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},
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'model': 'Baichuan4'
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},
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id='run-944ff552-6a93-44cf-a861-4e4d849746f9-0'
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)
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Stream:
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.. code-block:: python
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for chunk in chat.stream(messages):
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print(chunk)
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.. code-block:: python
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content='I' id='run-f99fcd6f-dd31-46d5-be8f-0b6a22bf77d8'
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content=' enjoy programming.' id='run-f99fcd6f-dd31-46d5-be8f-0b6a22bf77d8
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.. code-block:: python
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stream = chat.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(
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content='I like programming.',
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id='run-74689970-dc31-461d-b729-3b6aa93508d2'
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)
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Async:
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.. code-block:: python
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await chat.ainvoke(messages)
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# stream
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# async for chunk in chat.astream(messages):
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# print(chunk)
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# batch
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# await chat.abatch([messages])
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.. code-block:: python
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AIMessage(
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content='I enjoy programming.',
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response_metadata={
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'token_usage': {
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'prompt_tokens': 93,
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'completion_tokens': 5,
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'total_tokens': 98
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},
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'model': 'Baichuan4'
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},
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id='run-952509ed-9154-4ff9-b187-e616d7ddfbba-0'
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)
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Response metadata
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.. code-block:: python
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ai_msg = chat.invoke(messages)
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ai_msg.response_metadata
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.. code-block:: python
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{
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'token_usage': {
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'prompt_tokens': 93,
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'completion_tokens': 5,
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'total_tokens': 98
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},
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'model': 'Baichuan4'
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}
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""" # noqa: E501
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@property
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def lc_secrets(self) -> Dict[str, str]:
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