langchain_community.llms.pai_eas_endpoint.PaiEasEndpoint¶
class langchain_community.llms.pai_eas_endpoint.PaiEasEndpoint[source]¶
Bases: LLM
Langchain LLM class to help to access eass llm service.
To use this endpoint, must have a deployed eas chat llm service on PAI AliCloud.
One can set the environment variable eas_service_url and eas_service_token.
The environment variables can set with your eas service url and service token.
Example
from langchain_community.llms.pai_eas_endpoint import PaiEasEndpoint
eas_chat_endpoint = PaiEasChatEndpoint(
    eas_service_url="your_service_url",
    eas_service_token="your_service_token"
)
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¶
param callback_manager: Optional[BaseCallbackManager] = None¶
param callbacks: Callbacks = None¶
param eas_service_token: str [Required]¶
PAI-EAS Service Infer Params
param eas_service_url: str [Required]¶
PAI-EAS Service TOKEN
param max_new_tokens: Optional[int] = 512¶
param metadata: Optional[Dict[str, Any]] = None¶
Metadata to add to the run trace.
param model_kwargs: Optional[dict] = None¶
param stop_sequences: Optional[List[str]] = None¶
Enable stream chat mode.
param streaming: bool = False¶
Key/value arguments to pass to the model. Reserved for future use
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param temperature: Optional[float] = 0.95¶
param top_k: Optional[int] = 0¶