"""封装了对YandexGPT聊天模型的调用。"""
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]]:
"""将一系列消息解析为历史记录。
返回：
解析后的消息列表。
"""
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大型语言模型。
服务帐户有两种身份验证选项，具有“ai.languageModels.user”角色：
- 您可以在构造函数参数`iam_token`中指定令牌，也可以在环境变量`YC_IAM_TOKEN`中指定。
- 您可以在构造函数参数`api_key`中指定密钥，也可以在环境变量`YC_API_KEY`中指定。
示例：
.. 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:
"""生成对话中的下一轮。
参数：
messages: 对话历史，以消息列表的形式。
stop: 停用词列表（可选）。
run_manager: 用于LLM运行的CallbackManager，目前未使用。
返回：
包含模型生成输出的ChatResult。
引发：
ValueError: 如果列表中的最后一条消息不是来自人类。
"""
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:
"""生成对话中下一个回合的异步方法。
参数：
messages: 对话历史，以消息列表的形式。
stop: 停止词列表（可选）。
run_manager: LLM运行的CallbackManager，目前未使用。
返回：
包含模型生成输出的ChatResult。
异常：
ValueError: 如果列表中的最后一条消息不是来自人类。
"""
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:
"""使用tenacity来重试完成调用。"""
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:
"""使用tenacity来重试异步完成调用。"""
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)