260602

utils/agent.py

@@ -5,8 +5,8 @@
 
 # 列举导入模块
 from pathlib import Path
-from typing import List, Optional
+from sys import path
-from typing_extensions import is_protocol
+from typing import List, Optional, cast
 from uuid import uuid4
 
 from pydantic_ai import Agent as BaseAgent, AgentRunResult
@@ -15,14 +15,15 @@ from pydantic_ai.capabilities import AgentCapability
 from pydantic_ai.models.openai import OpenAIChatModel
 from pydantic_ai.output import OutputSpec
 from pydantic_ai.providers.openai import OpenAIProvider
+from pydantic_ai.settings import ModelSettings
 from pydantic_core.core_schema import is_subclass_schema
 from starlette.applications import Starlette
 from starlette.routing import Mount, Route
+from typing_extensions import is_protocol
 
-from sys import path
+from memory import Memory
 
 path.append(Path(__file__).resolve().parent.as_posix())
-from memory import Memory
 
 
 class Agent:
@@ -105,19 +106,144 @@ class Agent:
         )
         return result
 
-    def create_starlette_application(
+    def create_web_application(
         self,
         builtin_tools: Optional[List[AbstractBuiltinTool]] = None,
     ) -> Starlette:
         """
         创建 Starlette 应用，为智能体提供交互式对话界面
-        :param models: ModelsParam = None,
+        :param builtin_tools: 前端可选工具列表
-        :param builtin_tools: Sequence[AbstractBuiltinTool] | None = None,
         :return: Starlette 实例
         """
+        from starlette.requests import Request
+        from starlette.responses import JSONResponse, HTMLResponse, Response
 
+        def api(
+            self,
+            builtin_tools: Optional[List[AbstractBuiltinTool]] = None,
+        ) -> Starlette:
+            """
+            创建 API 应用
+            :param builtin_tools: 前端可选工具列表
+            :return: Starlette 实例
+            """
+            from pydantic_ai.models import Model
+            from pydantic_ai.ui._web.api import ModelInfo
+            from pydantic_ai.ui._web.api import (
+                ConfigureFrontend,
+                BuiltinToolInfo,
+                ChatRequestExtra,
+                validate_request_options,
+            )
+            from pydantic_ai.ui.vercel_ai import VercelAIAdapter
+            from typing import TypeVar
+
+            agent_model = cast(Model, self.agent.model)
+
+            # 前端可选工具列表
+            frontend_builtin_tools = [
+                t
+                for t in (builtin_tools or [])
+                if t.unique_id
+                not in {
+                    t.unique_id
+                    for t in self.agent._cap_builtin_tools
+                    if isinstance(t, AbstractBuiltinTool)
+                }
+            ]
+
+            async def options_chat(request: Request) -> Response:
+                """处理跨域预检请求"""
+                return Response()
+
+            async def configurations(request: Request) -> Response:
+                """处理前端模型与工具配置请求"""
+                configurations = ConfigureFrontend(
+                    models=[
+                        ModelInfo(
+                            id=agent_model.model_id,
+                            name=agent_model.label,
+                            builtin_tools=[
+                                t.unique_id
+                                for t in frontend_builtin_tools
+                                if type(t) in agent_model.supported_builtin_tools()
+                            ],
+                        )
+                    ],  # 前端仅可选择智能体配置的模型
+                    builtin_tools=[
+                        BuiltinToolInfo(id=t.unique_id, name=t.label)
+                        for t in frontend_builtin_tools
+                    ],
+                )
+                return JSONResponse(content=configurations.model_dump(by_alias=True))
+
+            async def chat(request: Request) -> Response:
+                """处理对话请求"""
+                # 实例 Vercel AI 适配器
+                adapter = await VercelAIAdapter[
+                    TypeVar("AgentDepsT"), TypeVar("OutputDataT")
+                ].from_request(request=request, agent=self.agent)
+
+                # 解析请求中额外数据，包括前端选择的模型标识、工具标识和其它配置等
+                extra_data = ChatRequestExtra.model_validate(
+                    adapter.run_input.__pydantic_extra__
+                )
+                if error := validate_request_options(
+                    extra_data=extra_data,
+                    model_ids={agent_model.model_id},  # 前端仅可选择智能体配置的模型
+                    builtin_tool_ids={t.unique_id for t in frontend_builtin_tools},
+                ):
+                    return JSONResponse(content={"error": error}, status_code=400)
+
+                streaming_response = await VercelAIAdapter[
+                    TypeVar("AgentDepsT"), TypeVar("OutputDataT")
+                ].dispatch_request(
+                    request=request,
+                    agent=self.agent,
+                    builtin_tools=[
+                        t
+                        for t in frontend_builtin_tools
+                        if t.unique_id in extra_data.builtin_tools
+                    ],
+                )
+                return streaming_response
+
+            async def health(request: Request) -> Response:
+                """处理健康检查请求"""
+                return JSONResponse(content={"ok": True})
+
+            return Starlette(
+                routes=[
+                    Route("/configure", configurations, methods=["GET"]),
+                    Route("/chat", options_chat, methods=["OPTIONS"]),
+                    Route("/chat", chat, methods=["POST"]),
+                    Route("/health", health, methods=["GET"]),
+                ]
+            )
+
+        async def ui(request: Request) -> Response:
+            """Serve the chat UI from filesystem cache or CDN."""
+            content = await _get_ui_html(html_source)
+
+            return HTMLResponse(
+                content=content,
+                headers={
+                    "Cache-Control": "public, max-age=3600",
+                },
+            )
+
+        application = Starlette(
+            routes=[
+                Mount(
+                    "/api",
+                    app=api(self, builtin_tools=builtin_tools),
+                )
+            ]
+        )
+
+        app.router.add_route("/", ui, methods=["GET"])
+        app.router.add_route("/{id}", ui, methods=["GET"])
 
         exit()
 
-        exit()
         return application

安全加密请求/main.py

@@ -225,18 +225,18 @@ if __name__ == "__main__":
     # 实例请求客户端
     request = Request()  # 不使用缓存
     response = request.post(
-        url="http://192.168.3.103:30380/api/v1/riskgateway/product/invokeSync.json",
+        url="https://risk-gw.pangjukeji.com/api/v1/riskgateway/product/invokeSync.json",
         headers={
-            "Authorization": "Bearer C52FB4D10BC424D9F",
+            "Authorization": "Bearer 337162980141699072",
             "Content-Type": "application/json;charset=utf-8",
         },
         json=encryptor.encrypt(
             payload={
                 "productId": "BANK_CARD_4",
                 "name": "刘弼仁",
-                "idNumber": "131002198705020000",
+                "certNo": "131002198705024619",
-                "bankCard": "1234567890123456",
+                "mobilephone": "18058798752",
-                "phone": "18058798752",
+                "bankCardNo": "6214835712066453",
             },
             fields_mapping={
                 "aes_key_encoded": "encryptedAesKey",
@@ -259,3 +259,16 @@ if __name__ == "__main__":
         tag_encoded=response.get("data").get("tag"),
     )
     print(data)
+
+"""
+{
+                "productId": "CREDIT_RISK_PRE_SCREEN",
+                "mobilephone": "13833652839",
+                "certNo": "131002196212124620"
+            }
+
+
+
+
+
+"""

安全加密请求/rsa_public_key.pem

@@ -1,3 +1,9 @@
 -----BEGIN PUBLIC KEY-----
-MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEApafHKXu1IwGJ1iQVT0susJ20MRl/6unJ+YMX6Lx9l43/+THA4VAJ8YQaZMH9+1eFeaFjwM9pT0ee+okBpKRuDWVkH8NxiKza4ohNHEtSUU37N3h8BEUBJHx74/6pDK8DwPsp4LzGhnUPof5/ZMqW2phqTrEYRwYOKGLYNnScNKkOWkQMSrUxGBkcMs1VsePChe0cJqrC03CTHJ/NRSyc62HqDZLp6G+DaR3VgWkhvhT4sN/3j/n9Ml5io/8I5ooPfBrYPNCfOaVqFWtqHqoG0uMLeROa8edqk6ZBBv2mERPllOG43f91FNmg/kF8XHij1LBNcf1WbO7rHg0Vo71j+wIDAQAB
+MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAqj/EwmmABQLKD7fh1ydL
+RDUqJjI+amaWPvX+urI9GFSl2cCJ6MlmtKgd0z/qDdJT+o5BjU0oU9wwnZSqu9HK
+rvrzdEjX+74sWxRDi8GuHjGfdWmJO7tF1lHApZw9rnZt1JTp1zBUBeVOLmWP2Ub0
+wjDOdYz2zKKZH6GShb1BUUqSi2hOD0S9iYMR4cz1smtMUTKzrJU8yIo6k26qXt5U
+RlhalT+vChYEh7QhCHbbJKdlbmtMvwE2alRKnqeXFRpDOR1JPQDUN+n3C2FEuM0a
+Hf2jmB93F4btqOFxZKSB+ZmXP0UMGeSGyuTOLn0QWWqkNBn1aYwO1rtPURR1y/mo
+QQIDAQAB
 -----END PUBLIC KEY-----

耐烧蚀合金智能体/main.py

@@ -30,5 +30,5 @@ if __name__ == "__main__":
             "严禁幻觉，保持专业严谨。"
         ),
     )
-    a = agent.create_starlette_application()
+    a = agent.create_web_application()
     uvicorn.run(app=a, host="127.0.0.1", port=7932)