langchain.chat_models.google_palm.ChatGooglePalm¶
class langchain.chat_models.google_palm.ChatGooglePalm[source]¶
Bases: BaseChatModel, BaseModel
Google PaLM Chat models API.
To use you must have the google.generativeai Python package installed and
either:
The GOOGLE_API_KEY` environment variable set with your API key, or
Pass your API key using the google_api_key kwarg to the ChatGoogle
constructor.
Example
from langchain.chat_models import ChatGooglePalm
chat = ChatGooglePalm()
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param cache: Optional[bool] = None¶
Whether to cache the response.
param callback_manager: Optional[BaseCallbackManager] = None¶
Callback manager to add to the run trace.
param callbacks: Callbacks = None¶
Callbacks to add to the run trace.
param google_api_key: Optional[str] = None¶
param metadata: Optional[Dict[str, Any]] = None¶
Metadata to add to the run trace.
param model_name: str = 'models/chat-bison-001'¶
Model name to use.
param n: int = 1¶
Number of chat completions to generate for each prompt. Note that the API may
not return the full n completions if duplicates are generated.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param temperature: Optional[float] = None¶
Run inference with this temperature. Must by in the closed
interval [0.0, 1.0].
param top_k: Optional[int] = None¶
Decode using top-k sampling: consider the set of top_k most probable tokens.
Must be positive.