feat: 增加deepseek

pretor/adapter/model_adapter/agent_factory.py

@@ -19,13 +19,17 @@ from pydantic_ai.models.anthropic import AnthropicModel
 from pydantic_ai.providers.openai import OpenAIProvider
 from pydantic_ai.providers.google import GoogleProvider
 from pydantic_ai.providers.anthropic import AnthropicProvider
+from pretor.adapter.model_adapter.deepseek_reasoner import DeepSeekReasonerAgent
 from pretor.core.global_state_machine.model_provider import Provider
 from pretor.utils.agent_model import ResponseModel, DepsModel
 from pretor.utils.error import ModelNotExistError
 
 class AgentFactory:
     def __init__(self):
-        self._models_mapping = {"openai": (OpenAIChatModel, OpenAIProvider), "gemini": (GoogleModel, GoogleProvider), "claude": (AnthropicModel, AnthropicProvider)}
+        self._models_mapping = {"openai": (OpenAIChatModel, OpenAIProvider),
+                                "gemini": (GoogleModel, GoogleProvider),
+                                "claude": (AnthropicModel, AnthropicProvider),
+                                "deepseek": (OpenAIChatModel, OpenAIProvider),}
 
     def create_agent(self,
                      provider: Provider,
@@ -45,6 +49,7 @@ class AgentFactory:
             system_prompt: 系统提示词
             deps_type: 依赖类型，在agent运行时动态输入的格式化消息
             agent_name: agent的名字
+            tools: 工具列表
 
         Returns:
             返回被实例化的pydantic-ai的Agent对象
@@ -55,10 +60,19 @@ class AgentFactory:
             raise ValueError(f"不支持的协议类型: {provider.provider_type}")
         model_class, provider_class = self._models_mapping[provider.provider_type]
         model = model_class(model_id, provider=provider_class(api_key=provider.provider_apikey, base_url=provider.provider_url))
-        agent = Agent(model=model,
-                      name=agent_name,
-                      system_prompt=system_prompt,
-                      output_type=output_type,
-                      deps_type=deps_type,
-                      tools=tools)
+        match provider.provider_type:
+            case "deepseek":
+                agent = DeepSeekReasonerAgent(model=model,
+                                              name=agent_name,
+                                              output_type=output_type,
+                                              deps_type=deps_type,
+                                              system_prompt=system_prompt,
+                                              )
+            case _:
+                agent = Agent(model=model,
+                              name=agent_name,
+                              system_prompt=system_prompt,
+                              output_type=output_type,
+                              deps_type=deps_type,
+                              tools=tools)
         return agent

pretor/adapter/model_adapter/deepseek_reasoner.py

@@ -3,7 +3,6 @@ import os
 from typing import Type, TypeVar, Any, Generic
 from pydantic import BaseModel, ValidationError
 from pydantic_ai import Agent, RunContext
-from pydantic_ai.models.openai import OpenAIChatModel
 
 T = TypeVar('T', bound=BaseModel)
 
@@ -16,7 +15,8 @@ class DeepSeekReasonerAgent(Generic[T]):
 
     def __init__(
             self,
-            model_id: str = "deepseek-v4-pro",
+            model,
+            name,
             output_type: Type[T] = str,
             system_prompt: str = "",
             deps_type: Type[Any] = None
@@ -32,7 +32,8 @@ class DeepSeekReasonerAgent(Generic[T]):
         )
 
         self.agent = Agent(
-            model=OpenAIChatModel(model_id),
+            model=model,
+            name=name,
             output_type=str,  # 内部通信用字符串
             system_prompt=system_prompt + format_instruction,
             deps_type=deps_type,

pretor/core/global_state_machine/model_provider/deepseek_provider.py

@@ -0,0 +1,59 @@
+#  Copyright 2026 zhaoxi826
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+
+from pretor.utils.retry import retry_on_retryable_error
+from pretor.core.global_state_machine.model_provider.base_provider import BaseProvider, Provider, ProviderArgs
+import httpx
+from typing import List
+
+class OpenAIProvider(BaseProvider):
+    @staticmethod
+    async def create_provider(provider_args: ProviderArgs) -> Provider:
+        provider_models: List[str] = await OpenAIProvider._load_models(provider_args)
+        provider: Provider = OpenAIProvider._return_provider(provider_args, provider_models)
+        return provider
+
+    @staticmethod
+    @retry_on_retryable_error()
+    async def _load_models(provider_args: ProviderArgs) -> List[str]:
+        headers = {
+            "Authorization": f"Bearer {provider_args.provider_apikey}",
+            "Content-Type": "application/json"
+        }
+        url = f"{provider_args.provider_url}/models" if "/v1" in provider_args.provider_url else f"{provider_args.provider_url}/v1/models"
+        try:
+            async with httpx.AsyncClient(timeout=10.0) as client:
+                response = await client.get(url, headers=headers)
+                if response.status_code != 200:
+                    print(f"[{provider_args.provider_title}] 获取模型失败: {response.status_code}")
+                    return []
+                data = response.json()
+                raw_models = data.get("data", [])
+                model_ids = [m["id"] for m in raw_models]
+                return sorted(model_ids)
+        except httpx.RequestError as e:
+            from pretor.utils.error import RetryableError
+            print(f"[{provider_args.provider_title}] 网络请求异常: {e}")
+            raise RetryableError(f"[{provider_args.provider_title}] 网络请求异常: {e}") from e
+        except Exception as e:
+            print(f"[{provider_args.provider_title}] 解析模型列表时发生错误: {e}")
+            return []
+
+    @staticmethod
+    def _return_provider(provider_args: ProviderArgs, provider_models: List[str]) -> Provider:
+        return Provider(provider_title=provider_args.provider_title,
+                        provider_apikey=provider_args.provider_apikey,
+                        provider_url=provider_args.provider_url,
+                        provider_models=provider_models,
+                        provider_type="deepseek")

pretor/core/global_state_machine/model_provider/openai_provider.py

@@ -1,4 +1,3 @@
-from pretor.utils.retry import retry_on_retryable_error
 #  Copyright 2026 zhaoxi826
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
@@ -13,6 +12,7 @@ from pretor.utils.retry import retry_on_retryable_error
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 
+from pretor.utils.retry import retry_on_retryable_error
 from pretor.core.global_state_machine.model_provider.base_provider import BaseProvider, Provider, ProviderArgs
 import httpx
 from typing import List