Source code for langchain_community.chat_models.yandex

"""Wrapper around YandexGPT chat models."""
from __future__ import annotations

import logging
from typing import Any, Callable, Dict, List, Optional, cast

from langchain_core.callbacks import (
    AsyncCallbackManagerForLLMRun,
    CallbackManagerForLLMRun,
)
from langchain_core.language_models.chat_models import BaseChatModel
from langchain_core.messages import (
    AIMessage,
    BaseMessage,
    HumanMessage,
    SystemMessage,
)
from langchain_core.outputs import ChatGeneration, ChatResult
from tenacity import (
    before_sleep_log,
    retry,
    retry_if_exception_type,
    stop_after_attempt,
    wait_exponential,
)

from langchain_community.llms.utils import enforce_stop_tokens
from langchain_community.llms.yandex import _BaseYandexGPT

logger = logging.getLogger(__name__)


def _parse_message(role: str, text: str) -> Dict:
    return {"role": role, "text": text}


def _parse_chat_history(history: List[BaseMessage]) -> List[Dict[str, str]]:
    """Parse a sequence of messages into history.

    Returns:
        A list of parsed messages.
    """
    chat_history = []
    for message in history:
        content = cast(str, message.content)
        if isinstance(message, HumanMessage):
            chat_history.append(_parse_message("user", content))
        if isinstance(message, AIMessage):
            chat_history.append(_parse_message("assistant", content))
        if isinstance(message, SystemMessage):
            chat_history.append(_parse_message("system", content))
    return chat_history


[docs]class ChatYandexGPT(_BaseYandexGPT, BaseChatModel): """YandexGPT large language models. There are two authentication options for the service account with the ``ai.languageModels.user`` role: - You can specify the token in a constructor parameter `iam_token` or in an environment variable `YC_IAM_TOKEN`. - You can specify the key in a constructor parameter `api_key` or in an environment variable `YC_API_KEY`. Example: .. code-block:: python from langchain_community.chat_models import ChatYandexGPT chat_model = ChatYandexGPT(iam_token="t1.9eu...") """ def _generate( self, messages: List[BaseMessage], stop: Optional[List[str]] = None, run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any, ) -> ChatResult: """Generate next turn in the conversation. Args: messages: The history of the conversation as a list of messages. stop: The list of stop words (optional). run_manager: The CallbackManager for LLM run, it's not used at the moment. Returns: The ChatResult that contains outputs generated by the model. Raises: ValueError: if the last message in the list is not from human. """ text = completion_with_retry(self, messages=messages) text = text if stop is None else enforce_stop_tokens(text, stop) message = AIMessage(content=text) return ChatResult(generations=[ChatGeneration(message=message)]) async def _agenerate( self, messages: List[BaseMessage], stop: Optional[List[str]] = None, run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, **kwargs: Any, ) -> ChatResult: """Async method to generate next turn in the conversation. Args: messages: The history of the conversation as a list of messages. stop: The list of stop words (optional). run_manager: The CallbackManager for LLM run, it's not used at the moment. Returns: The ChatResult that contains outputs generated by the model. Raises: ValueError: if the last message in the list is not from human. """ text = await acompletion_with_retry(self, messages=messages) text = text if stop is None else enforce_stop_tokens(text, stop) message = AIMessage(content=text) return ChatResult(generations=[ChatGeneration(message=message)])
def _make_request( self: ChatYandexGPT, messages: List[BaseMessage], ) -> str: try: import grpc from google.protobuf.wrappers_pb2 import DoubleValue, Int64Value try: from yandex.cloud.ai.foundation_models.v1.text_common_pb2 import ( CompletionOptions, Message, ) from yandex.cloud.ai.foundation_models.v1.text_generation.text_generation_service_pb2 import ( # noqa: E501 CompletionRequest, ) from yandex.cloud.ai.foundation_models.v1.text_generation.text_generation_service_pb2_grpc import ( # noqa: E501 TextGenerationServiceStub, ) except ModuleNotFoundError: from yandex.cloud.ai.foundation_models.v1.foundation_models_pb2 import ( CompletionOptions, Message, ) from yandex.cloud.ai.foundation_models.v1.foundation_models_service_pb2 import ( # noqa: E501 CompletionRequest, ) from yandex.cloud.ai.foundation_models.v1.foundation_models_service_pb2_grpc import ( # noqa: E501 TextGenerationServiceStub, ) except ImportError as e: raise ImportError( "Please install YandexCloud SDK with `pip install yandexcloud` \ or upgrade it to recent version." ) from e if not messages: raise ValueError("You should provide at least one message to start the chat!") message_history = _parse_chat_history(messages) channel_credentials = grpc.ssl_channel_credentials() channel = grpc.secure_channel(self.url, channel_credentials) request = CompletionRequest( model_uri=self.model_uri, completion_options=CompletionOptions( temperature=DoubleValue(value=self.temperature), max_tokens=Int64Value(value=self.max_tokens), ), messages=[Message(**message) for message in message_history], ) stub = TextGenerationServiceStub(channel) res = stub.Completion(request, metadata=self._grpc_metadata) return list(res)[0].alternatives[0].message.text async def _amake_request(self: ChatYandexGPT, messages: List[BaseMessage]) -> str: try: import asyncio import grpc from google.protobuf.wrappers_pb2 import DoubleValue, Int64Value try: from yandex.cloud.ai.foundation_models.v1.text_common_pb2 import ( CompletionOptions, Message, ) from yandex.cloud.ai.foundation_models.v1.text_generation.text_generation_service_pb2 import ( # noqa: E501 CompletionRequest, CompletionResponse, ) from yandex.cloud.ai.foundation_models.v1.text_generation.text_generation_service_pb2_grpc import ( # noqa: E501 TextGenerationAsyncServiceStub, ) except ModuleNotFoundError: from yandex.cloud.ai.foundation_models.v1.foundation_models_pb2 import ( CompletionOptions, Message, ) from yandex.cloud.ai.foundation_models.v1.foundation_models_service_pb2 import ( # noqa: E501 CompletionRequest, CompletionResponse, ) from yandex.cloud.ai.foundation_models.v1.foundation_models_service_pb2_grpc import ( # noqa: E501 TextGenerationAsyncServiceStub, ) from yandex.cloud.operation.operation_service_pb2 import GetOperationRequest from yandex.cloud.operation.operation_service_pb2_grpc import ( OperationServiceStub, ) except ImportError as e: raise ImportError( "Please install YandexCloud SDK with `pip install yandexcloud` \ or upgrade it to recent version." ) from e if not messages: raise ValueError("You should provide at least one message to start the chat!") message_history = _parse_chat_history(messages) operation_api_url = "operation.api.cloud.yandex.net:443" channel_credentials = grpc.ssl_channel_credentials() async with grpc.aio.secure_channel(self.url, channel_credentials) as channel: request = CompletionRequest( model_uri=self.model_uri, completion_options=CompletionOptions( temperature=DoubleValue(value=self.temperature), max_tokens=Int64Value(value=self.max_tokens), ), messages=[Message(**message) for message in message_history], ) stub = TextGenerationAsyncServiceStub(channel) operation = await stub.Completion(request, metadata=self._grpc_metadata) async with grpc.aio.secure_channel( operation_api_url, channel_credentials ) as operation_channel: operation_stub = OperationServiceStub(operation_channel) while not operation.done: await asyncio.sleep(1) operation_request = GetOperationRequest(operation_id=operation.id) operation = await operation_stub.Get( operation_request, metadata=self._grpc_metadata, ) completion_response = CompletionResponse() operation.response.Unpack(completion_response) return completion_response.alternatives[0].message.text def _create_retry_decorator(llm: ChatYandexGPT) -> Callable[[Any], Any]: from grpc import RpcError min_seconds = llm.sleep_interval max_seconds = 60 return retry( reraise=True, stop=stop_after_attempt(llm.max_retries), wait=wait_exponential(multiplier=1, min=min_seconds, max=max_seconds), retry=(retry_if_exception_type((RpcError))), before_sleep=before_sleep_log(logger, logging.WARNING), )
[docs]def completion_with_retry(llm: ChatYandexGPT, **kwargs: Any) -> Any: """Use tenacity to retry the completion call.""" retry_decorator = _create_retry_decorator(llm) @retry_decorator def _completion_with_retry(**_kwargs: Any) -> Any: return _make_request(llm, **_kwargs) return _completion_with_retry(**kwargs)
[docs]async def acompletion_with_retry(llm: ChatYandexGPT, **kwargs: Any) -> Any: """Use tenacity to retry the async completion call.""" retry_decorator = _create_retry_decorator(llm) @retry_decorator async def _completion_with_retry(**_kwargs: Any) -> Any: return await _amake_request(llm, **_kwargs) return await _completion_with_retry(**kwargs)