make format

model-providers/model_providers/__init__.py

@@ -1,9 +1,11 @@
-from model_providers.bootstrap_web.openai_bootstrap_web import RESTFulOpenAIBootstrapBaseWeb
+from omegaconf import DictConfig, OmegaConf
+
+from model_providers.bootstrap_web.openai_bootstrap_web import (
+    RESTFulOpenAIBootstrapBaseWeb,
+)
 from model_providers.core.bootstrap import OpenAIBootstrapBaseWeb
 from model_providers.core.model_manager import ModelManager
 
-from omegaconf import OmegaConf, DictConfig
-
 
 def _to_custom_provide_configuration(cfg: DictConfig):
     """
@@ -34,8 +36,8 @@ def _to_custom_provide_configuration(cfg: DictConfig):
     provider_name_to_provider_model_records_dict = {}
 
     for key, item in cfg.items():
-        model_credential = item.get('model_credential')
+        model_credential = item.get("model_credential")
-        provider_credential = item.get('provider_credential')
+        provider_credential = item.get("provider_credential")
         # 转换omegaconf对象为基本属性
         if model_credential:
             model_credential = OmegaConf.to_container(model_credential)
@@ -44,13 +46,17 @@ def _to_custom_provide_configuration(cfg: DictConfig):
             provider_credential = OmegaConf.to_container(provider_credential)
             provider_name_to_provider_records_dict[key] = provider_credential
 
-    return provider_name_to_provider_records_dict, provider_name_to_provider_model_records_dict
+    return (
+        provider_name_to_provider_records_dict,
+        provider_name_to_provider_model_records_dict,
+    )
 
 
 class BootstrapWebBuilder:
     """
     创建一个模型实例创建工具
     """
+
     _model_providers_cfg_path: str
     _host: str
     _port: int
@@ -68,20 +74,26 @@ class BootstrapWebBuilder:
         return self
 
     def build(self) -> OpenAIBootstrapBaseWeb:
-        assert self._model_providers_cfg_path is not None and self._host is not None and self._port is not None
+        assert (
+            self._model_providers_cfg_path is not None
+            and self._host is not None
+            and self._port is not None
+        )
         # 读取配置文件
         cfg = OmegaConf.load(self._model_providers_cfg_path)
         # 转换配置文件
-        provider_name_to_provider_records_dict, provider_name_to_provider_model_records_dict = _to_custom_provide_configuration(
+        (
-            cfg)
+            provider_name_to_provider_records_dict,
+            provider_name_to_provider_model_records_dict,
+        ) = _to_custom_provide_configuration(cfg)
         # 创建模型管理器
-        provider_manager = ModelManager(provider_name_to_provider_records_dict,
+        provider_manager = ModelManager(
-                                        provider_name_to_provider_model_records_dict)
+            provider_name_to_provider_records_dict,
+            provider_name_to_provider_model_records_dict,
+        )
         # 创建web服务
-        restful = RESTFulOpenAIBootstrapBaseWeb.from_config(cfg={
+        restful = RESTFulOpenAIBootstrapBaseWeb.from_config(
-            "host": self._host,
+            cfg={"host": self._host, "port": self._port}
-            "port": self._port
+        )
-
-        })
         restful.provider_manager = provider_manager
         return restful

model-providers/model_providers/bootstrap_web/openai_bootstrap_web.py

@@ -21,13 +21,17 @@ from model_providers.core.bootstrap.openai_protocol import (
     EmbeddingsRequest,
     EmbeddingsResponse,
     FunctionAvailable,
-    ModelList, ModelCard,
+    ModelCard,
+    ModelList,
 )
-from model_providers.core.model_manager import ModelManager, ModelInstance
+from model_providers.core.model_manager import ModelInstance, ModelManager
 from model_providers.core.model_runtime.entities.message_entities import (
     UserPromptMessage,
 )
-from model_providers.core.model_runtime.entities.model_entities import ModelType, AIModelEntity
+from model_providers.core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    ModelType,
+)
 from model_providers.core.utils.generic import dictify, jsonify
 
 logger = logging.getLogger(__name__)
@@ -115,24 +119,31 @@ class RESTFulOpenAIBootstrapBaseWeb(OpenAIBootstrapBaseWeb):
         llm_models: list[AIModelEntity] = []
         for model_type in ModelType.__members__.values():
             try:
-                provider_model_bundle = self._provider_manager.provider_manager.get_provider_model_bundle(
+                provider_model_bundle = (
-                    provider=provider, model_type=model_type
+                    self._provider_manager.provider_manager.get_provider_model_bundle(
+                        provider=provider, model_type=model_type
+                    )
+                )
+                llm_models.extend(
+                    provider_model_bundle.model_type_instance.predefined_models()
                 )
-                llm_models.extend(provider_model_bundle.model_type_instance.predefined_models())
             except Exception as e:
-                logger.error(f"Error while fetching models for provider: {provider}, model_type: {model_type}")
+                logger.error(
+                    f"Error while fetching models for provider: {provider}, model_type: {model_type}"
+                )
                 logger.error(e)
 
         # models list[AIModelEntity]转换称List[ModelCard]
 
-        models_list = [ModelCard(id=model.model, object=model.model_type.to_origin_model_type()) for model in llm_models]
+        models_list = [
+            ModelCard(id=model.model, object=model.model_type.to_origin_model_type())
+            for model in llm_models
+        ]
 
-        return ModelList(
+        return ModelList(data=models_list)
-            data=models_list
-        )
 
     async def create_embeddings(
-            self, provider: str, request: Request, embeddings_request: EmbeddingsRequest
+        self, provider: str, request: Request, embeddings_request: EmbeddingsRequest
     ):
         logger.info(
             f"Received create_embeddings request: {pprint.pformat(embeddings_request.dict())}"
@@ -142,7 +153,7 @@ class RESTFulOpenAIBootstrapBaseWeb(OpenAIBootstrapBaseWeb):
         return EmbeddingsResponse(**dictify(response))
 
     async def create_chat_completion(
-            self, provider: str, request: Request, chat_request: ChatCompletionRequest
+        self, provider: str, request: Request, chat_request: ChatCompletionRequest
     ):
         logger.info(
             f"Received chat completion request: {pprint.pformat(chat_request.dict())}"
@@ -180,9 +191,9 @@ class RESTFulOpenAIBootstrapBaseWeb(OpenAIBootstrapBaseWeb):
 
 
 def run(
-        cfg: Dict,
+    cfg: Dict,
-        logging_conf: Optional[dict] = None,
+    logging_conf: Optional[dict] = None,
-        started_event: mp.Event = None,
+    started_event: mp.Event = None,
 ):
     logging.config.dictConfig(logging_conf)  # type: ignore
     try:

model-providers/model_providers/core/bootstrap/base.py

@@ -3,7 +3,10 @@ from collections import deque
 
 from fastapi import Request
 
-from model_providers.core.bootstrap.openai_protocol import ChatCompletionRequest, EmbeddingsRequest
+from model_providers.core.bootstrap.openai_protocol import (
+    ChatCompletionRequest,
+    EmbeddingsRequest,
+)
 from model_providers.core.model_manager import ModelManager
 
 
@@ -60,12 +63,12 @@ class OpenAIBootstrapBaseWeb(Bootstrap):
 
     @abstractmethod
     async def create_embeddings(
-            self, provider: str, request: Request, embeddings_request: EmbeddingsRequest
+        self, provider: str, request: Request, embeddings_request: EmbeddingsRequest
     ):
         pass
 
     @abstractmethod
     async def create_chat_completion(
-            self, provider: str, request: Request, chat_request: ChatCompletionRequest
+        self, provider: str, request: Request, chat_request: ChatCompletionRequest
     ):
         pass

model-providers/model_providers/core/bootstrap/openai_protocol.py

@@ -22,7 +22,15 @@ class Finish(str, Enum):
 
 class ModelCard(BaseModel):
     id: str
-    object: Literal["text-generation","embeddings","reranking", "speech2text", "moderation", "tts", "text2img"] = "llm"
+    object: Literal[
+        "text-generation",
+        "embeddings",
+        "reranking",
+        "speech2text",
+        "moderation",
+        "tts",
+        "text2img",
+    ] = "llm"
     created: int = Field(default_factory=lambda: int(time.time()))
     owned_by: Literal["owner"] = "owner"
 

model-providers/model_providers/core/model_runtime/entities/model_entities.py

@@ -1,6 +1,6 @@
 from decimal import Decimal
 from enum import Enum
-from typing import Any, Optional, List
+from typing import Any, List, Optional
 
 from pydantic import BaseModel
 
@@ -74,7 +74,6 @@ class ModelType(Enum):
             raise ValueError(f"invalid model type {self}")
 
 
-
 class FetchFrom(Enum):
     """
     Enum class for fetch from.

model-providers/model_providers/core/provider_manager.py

@@ -253,9 +253,11 @@ class ProviderManager:
 
             custom_model_configurations.append(
                 CustomModelConfiguration(
-                    model=provider_model_record.get('model'),
+                    model=provider_model_record.get("model"),
-                    model_type=ModelType.value_of(provider_model_record.get('model_type')),
+                    model_type=ModelType.value_of(
-                    credentials=provider_model_credentials
+                        provider_model_record.get("model_type")
+                    ),
+                    credentials=provider_model_credentials,
                 )
             )
 

model-providers/model_providers/core/utils/utils.py

@@ -1,7 +1,6 @@
 import logging
-
-import time
 import os
+import time
 
 logger = logging.getLogger(__name__)
 
@@ -26,7 +25,7 @@ def get_log_file(log_path: str, sub_dir: str):
 
 
 def get_config_dict(
-        log_level: str, log_file_path: str, log_backup_count: int, log_max_bytes: int
+    log_level: str, log_file_path: str, log_backup_count: int, log_max_bytes: int
 ) -> dict:
     # for windows, the path should be a raw string.
     log_file_path = (

model-providers/tests/server_unit_test/conftest.py

@@ -1,11 +1,16 @@
 """Configuration for unit tests."""
-from importlib import util
-from typing import Dict, Sequence, List
 import logging
+from importlib import util
+from typing import Dict, List, Sequence
+
 import pytest
 from pytest import Config, Function, Parser
 
-from model_providers.core.utils.utils import get_config_dict, get_timestamp_ms, get_log_file
+from model_providers.core.utils.utils import (
+    get_config_dict,
+    get_log_file,
+    get_timestamp_ms,
+)
 
 
 def pytest_addoption(parser: Parser) -> None:

model-providers/tests/server_unit_test/test_init_server.py

@@ -1,21 +1,26 @@
-from model_providers import BootstrapWebBuilder
-import logging
 import asyncio
+import logging
 
 import pytest
+
+from model_providers import BootstrapWebBuilder
+
 logger = logging.getLogger(__name__)
 
 
 @pytest.mark.requires("fastapi")
 def test_init_server(logging_conf: dict) -> None:
     try:
-        boot = BootstrapWebBuilder() \
+        boot = (
+            BootstrapWebBuilder()
             .model_providers_cfg_path(
-            model_providers_cfg_path="/media/gpt4-pdf-chatbot-langchain/langchain-ChatGLM/model-providers"
+                model_providers_cfg_path="/media/gpt4-pdf-chatbot-langchain/langchain-ChatGLM/model-providers"
-                                     "/model_providers.yaml") \
+                "/model_providers.yaml"
-            .host(host="127.0.0.1") \
+            )
-            .port(port=20000) \
+            .host(host="127.0.0.1")
+            .port(port=20000)
             .build()
+        )
         boot.set_app_event(started_event=None)
         boot.serve(logging_conf=logging_conf)
 

model-providers/tests/unit_test/conftest.py

@@ -1,11 +1,16 @@
 """Configuration for unit tests."""
-from importlib import util
-from typing import Dict, Sequence, List
 import logging
+from importlib import util
+from typing import Dict, List, Sequence
+
 import pytest
 from pytest import Config, Function, Parser
 
-from model_providers.core.utils.utils import get_config_dict, get_timestamp_ms, get_log_file
+from model_providers.core.utils.utils import (
+    get_config_dict,
+    get_log_file,
+    get_timestamp_ms,
+)
 
 
 def pytest_addoption(parser: Parser) -> None:

model-providers/tests/unit_test/test_provider_manager_models.py

@@ -1,11 +1,10 @@
+import asyncio
+import logging
+
+import pytest
 from omegaconf import OmegaConf
 
 from model_providers import BootstrapWebBuilder, _to_custom_provide_configuration
-import logging
-import asyncio
-
-import pytest
-
 from model_providers.core.model_manager import ModelManager
 from model_providers.core.model_runtime.entities.model_entities import ModelType
 from model_providers.core.provider_manager import ProviderManager
@@ -14,14 +13,17 @@ logger = logging.getLogger(__name__)
 
 
 def test_provider_manager_models(logging_conf: dict) -> None:
-
     logging.config.dictConfig(logging_conf)  # type: ignore
     # 读取配置文件
-    cfg = OmegaConf.load("/media/gpt4-pdf-chatbot-langchain/langchain-ChatGLM/model-providers"
+    cfg = OmegaConf.load(
-                         "/model_providers.yaml")
+        "/media/gpt4-pdf-chatbot-langchain/langchain-ChatGLM/model-providers"
+        "/model_providers.yaml"
+    )
     # 转换配置文件
-    provider_name_to_provider_records_dict, provider_name_to_provider_model_records_dict = _to_custom_provide_configuration(
+    (
-        cfg)
+        provider_name_to_provider_records_dict,
+        provider_name_to_provider_model_records_dict,
+    ) = _to_custom_provide_configuration(cfg)
     # 创建模型管理器
     provider_manager = ProviderManager(
         provider_name_to_provider_records_dict=provider_name_to_provider_records_dict,
@@ -34,6 +36,8 @@ def test_provider_manager_models(logging_conf: dict) -> None:
     provider_model_bundle_emb = provider_manager.get_provider_model_bundle(
         provider="openai", model_type=ModelType.TEXT_EMBEDDING
     )
-    predefined_models = provider_model_bundle_emb.model_type_instance.predefined_models()
+    predefined_models = (
+        provider_model_bundle_emb.model_type_instance.predefined_models()
+    )
 
     logger.info(f"predefined_models: {predefined_models}")