mirror of
https://github.com/RYDE-WORK/Langchain-Chatchat.git
synced 2026-01-19 21:37:20 +08:00
使用BootstrapWebBuilder适配RESTFulOpenAIBootstrapBaseWeb加载
This commit is contained in:
glide-the
parent
3ed9162392
commit
032dc8f58d
@ -1,3 +1,5 @@
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from model_providers.bootstrap_web.openai_bootstrap_web import RESTFulOpenAIBootstrapBaseWeb
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from model_providers.core.bootstrap import OpenAIBootstrapBaseWeb
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from model_providers.core.model_manager import ModelManager
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from omegaconf import OmegaConf, DictConfig
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@ -45,11 +47,41 @@ def _to_custom_provide_configuration(cfg: DictConfig):
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return provider_name_to_provider_records_dict, provider_name_to_provider_model_records_dict
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model_providers_cfg = OmegaConf.load("/media/gpt4-pdf-chatbot-langchain/langchain-ChatGLM/model-providers/model_providers.yaml")
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provider_name_to_provider_records_dict, provider_name_to_provider_model_records_dict = _to_custom_provide_configuration(
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cfg=model_providers_cfg)
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# 基于配置管理器创建的模型实例
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provider_manager = ModelManager(
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provider_name_to_provider_records_dict=provider_name_to_provider_records_dict,
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provider_name_to_provider_model_records_dict=provider_name_to_provider_model_records_dict
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)
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class BootstrapWebBuilder:
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"""
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创建一个模型实例创建工具
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"""
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_model_providers_cfg_path: str
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_host: str
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_port: int
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def model_providers_cfg_path(self, model_providers_cfg_path: str):
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self._model_providers_cfg_path = model_providers_cfg_path
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return self
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def host(self, host: str):
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self._host = host
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return self
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def port(self, port: int):
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self._port = port
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return self
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def build(self) -> OpenAIBootstrapBaseWeb:
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assert self._model_providers_cfg_path is not None and self._host is not None and self._port is not None
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# 读取配置文件
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cfg = OmegaConf.load(self._model_providers_cfg_path)
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# 转换配置文件
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provider_name_to_provider_records_dict, provider_name_to_provider_model_records_dict = _to_custom_provide_configuration(
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cfg)
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# 创建模型管理器
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provider_manager = ModelManager(provider_name_to_provider_records_dict,
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provider_name_to_provider_model_records_dict)
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# 创建web服务
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restful = RESTFulOpenAIBootstrapBaseWeb.from_config(cfg={
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"host": self._host,
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"port": self._port
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})
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restful.provider_manager = provider_manager
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return restful
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@ -23,44 +23,16 @@ from model_providers.core.bootstrap.openai_protocol import (
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FunctionAvailable,
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ModelList,
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)
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from model_providers.core.model_manager import ModelManager, ModelInstance
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from model_providers.core.model_runtime.entities.message_entities import (
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UserPromptMessage,
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)
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from model_providers.core.model_runtime.entities.model_entities import ModelType
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from model_providers.core.model_runtime.model_providers import model_provider_factory
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from model_providers.core.model_runtime.model_providers.__base.ai_model import AIModel
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from model_providers.core.model_runtime.model_providers.__base.large_language_model import (
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LargeLanguageModel,
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)
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from model_providers.core.utils.generic import dictify, jsonify
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logger = logging.getLogger(__name__)
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async def create_stream_chat_completion(
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model_type_instance: LargeLanguageModel, chat_request: ChatCompletionRequest
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):
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try:
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response = model_type_instance.invoke(
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model=chat_request.model,
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credentials={
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"openai_api_key": "sk-",
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"minimax_api_key": os.environ.get("MINIMAX_API_KEY"),
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"minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"),
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},
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prompt_messages=[UserPromptMessage(content="北京今天的天气怎么样")],
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model_parameters={**chat_request.to_model_parameters_dict()},
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stop=chat_request.stop,
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stream=chat_request.stream,
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user="abc-123",
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)
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return response
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except Exception as e:
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logger.exception(e)
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raise HTTPException(status_code=500, detail=str(e))
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class RESTFulOpenAIBootstrapBaseWeb(OpenAIBootstrapBaseWeb):
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"""
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Bootstrap Server Lifecycle
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@ -94,21 +66,21 @@ class RESTFulOpenAIBootstrapBaseWeb(OpenAIBootstrapBaseWeb):
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)
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self._router.add_api_route(
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"/v1/models",
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"/{provider}/v1/models",
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self.list_models,
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response_model=ModelList,
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methods=["GET"],
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)
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self._router.add_api_route(
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"/v1/embeddings",
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"/{provider}/v1/embeddings",
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self.create_embeddings,
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response_model=EmbeddingsResponse,
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status_code=status.HTTP_200_OK,
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methods=["POST"],
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)
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self._router.add_api_route(
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"/v1/chat/completions",
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"/{provider}/v1/chat/completions",
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self.create_chat_completion,
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response_model=ChatCompletionResponse,
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status_code=status.HTTP_200_OK,
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@ -137,78 +109,49 @@ class RESTFulOpenAIBootstrapBaseWeb(OpenAIBootstrapBaseWeb):
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if started_event is not None:
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started_event.set()
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async def list_models(self, request: Request):
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async def list_models(self, provider: str, request: Request):
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pass
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async def create_embeddings(
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self, request: Request, embeddings_request: EmbeddingsRequest
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self, provider: str, request: Request, embeddings_request: EmbeddingsRequest
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):
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logger.info(
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f"Received create_embeddings request: {pprint.pformat(embeddings_request.dict())}"
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)
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if os.environ["API_KEY"] is None:
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authorization = request.headers.get("Authorization")
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authorization = authorization.split("Bearer ")[-1]
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else:
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authorization = os.environ["API_KEY"]
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client = ZhipuAI(api_key=authorization)
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# 判断embeddings_request.input是否为list
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input = None
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if isinstance(embeddings_request.input, list):
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tokens = embeddings_request.input
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try:
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encoding = tiktoken.encoding_for_model(embeddings_request.model)
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except KeyError:
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logger.warning("Warning: model not found. Using cl100k_base encoding.")
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model = "cl100k_base"
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encoding = tiktoken.get_encoding(model)
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for i, token in enumerate(tokens):
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text = encoding.decode(token)
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input += text
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else:
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input = embeddings_request.input
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response = client.embeddings.create(
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model=embeddings_request.model,
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input=input,
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)
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response = None
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return EmbeddingsResponse(**dictify(response))
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async def create_chat_completion(
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self, request: Request, chat_request: ChatCompletionRequest
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self, provider: str, request: Request, chat_request: ChatCompletionRequest
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):
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logger.info(
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f"Received chat completion request: {pprint.pformat(chat_request.dict())}"
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)
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if os.environ["API_KEY"] is None:
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authorization = request.headers.get("Authorization")
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authorization = authorization.split("Bearer ")[-1]
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else:
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authorization = os.environ["API_KEY"]
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model_provider_factory.get_providers(provider_name="openai")
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provider_instance = model_provider_factory.get_provider_instance("openai")
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model_type_instance = provider_instance.get_model_instance(ModelType.LLM)
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model_instance = self._provider_manager.get_model_instance(
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provider=provider, model_type=ModelType.LLM, model=chat_request.model
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)
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if chat_request.stream:
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generator = create_stream_chat_completion(model_type_instance, chat_request)
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return EventSourceResponse(generator, media_type="text/event-stream")
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else:
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response = model_type_instance.invoke(
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model="gpt-4",
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credentials={
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"openai_api_key": "sk-",
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"minimax_api_key": os.environ.get("MINIMAX_API_KEY"),
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"minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"),
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},
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# Invoke model
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response = model_instance.invoke_llm(
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prompt_messages=[UserPromptMessage(content="北京今天的天气怎么样")],
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model_parameters={
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"temperature": 0.7,
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"top_p": 1.0,
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"top_k": 1,
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"plugin_web_search": True,
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},
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stop=["you"],
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stream=False,
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model_parameters={**chat_request.to_model_parameters_dict()},
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stop=chat_request.stop,
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stream=chat_request.stream,
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user="abc-123",
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)
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return EventSourceResponse(response, media_type="text/event-stream")
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else:
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# Invoke model
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response = model_instance.invoke_llm(
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prompt_messages=[UserPromptMessage(content="北京今天的天气怎么样")],
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model_parameters={**chat_request.to_model_parameters_dict()},
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stop=chat_request.stop,
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stream=chat_request.stream,
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user="abc-123",
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)
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@ -218,16 +161,12 @@ class RESTFulOpenAIBootstrapBaseWeb(OpenAIBootstrapBaseWeb):
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def run(
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cfg: Dict,
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logging_conf: Optional[dict] = None,
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started_event: mp.Event = None,
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cfg: Dict,
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logging_conf: Optional[dict] = None,
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started_event: mp.Event = None,
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):
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logging.config.dictConfig(logging_conf) # type: ignore
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try:
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import signal
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# 跳过键盘中断，使用xoscar的信号处理
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signal.signal(signal.SIGINT, lambda *_: None)
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api = RESTFulOpenAIBootstrapBaseWeb.from_config(
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cfg=cfg.get("run_openai_api", {})
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)
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@ -3,9 +3,11 @@ from collections import deque
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from fastapi import Request
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from model_providers.core.bootstrap.openai_protocol import ChatCompletionRequest, EmbeddingsRequest
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from model_providers.core.model_manager import ModelManager
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class Bootstrap:
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"""最大的任务队列"""
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_MAX_ONGOING_TASKS: int = 1
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@ -39,21 +41,31 @@ class Bootstrap:
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class OpenAIBootstrapBaseWeb(Bootstrap):
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_provider_manager: ModelManager
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def __init__(self):
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super().__init__()
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@property
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def provider_manager(self) -> ModelManager:
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return self._provider_manager
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@provider_manager.setter
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def provider_manager(self, provider_manager: ModelManager):
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self._provider_manager = provider_manager
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@abstractmethod
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async def list_models(self, request: Request):
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async def list_models(self, provider: str, request: Request):
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pass
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@abstractmethod
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async def create_embeddings(
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self, request: Request, embeddings_request: EmbeddingsRequest
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self, provider: str, request: Request, embeddings_request: EmbeddingsRequest
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):
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pass
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@abstractmethod
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async def create_chat_completion(
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self, request: Request, chat_request: ChatCompletionRequest
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self, provider: str, request: Request, chat_request: ChatCompletionRequest
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):
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pass
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@ -92,7 +92,7 @@ class ChatCompletionRequest(BaseModel):
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def to_model_parameters_dict(self, *args, **kwargs):
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# 调用父类的to_dict方法，并排除tools字段
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helper.dump_model
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return super().dict(
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exclude={"tools", "messages", "functions", "function_call"}, *args, **kwargs
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)
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