aida agent (基础版)搭建完成

app/service/fashion_agent/service.py

@@ -0,0 +1,132 @@
+import json
+import logging
+import sys
+from pathlib import Path
+from langgraph.stream import ProtocolEvent, StreamChannel, StreamTransformer
+from app.service.fashion_agent.main_agent import build_main_graph
+from langgraph.prebuilt import ToolCallTransformer
+from typing import AsyncGenerator, TypedDict
+from langchain_core.messages import HumanMessage
+from app.schemas.fashion_agent import FashionAgentRequest
+
+logger = logging.getLogger()
+
+
+class CustomTransformer(StreamTransformer):
+    required_stream_modes = ("custom",)
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        super().__init__(scope)
+        self.log = StreamChannel()
+
+    def init(self) -> dict:
+        return {"custom": self.log}
+
+    def process(self, event: ProtocolEvent) -> bool:
+        if event["method"] == "custom":
+            self.log.push(event["params"]["data"])
+        return True
+
+
+class FashionAgentService:
+
+    async def run_stream(self, request: FashionAgentRequest) -> AsyncGenerator[str, None]:
+        """流式运行 agent - 使用 v3 projections"""
+
+        config = {"configurable": {"user_id": request.user_id}}
+
+        agent = build_main_graph(enable_thinking=request.enable_thinking)
+        state = {
+            "messages": [HumanMessage(content=request.message)],
+            "call_print": request.call_print,
+            "call_logo": request.call_logo,
+            "call_sketch": request.call_sketch,
+            "call_design": request.call_design,
+            "call_trending": request.call_trending,
+            "call_explor": request.call_explor,
+            "print_need_prompt_generation": request.print_need_prompt_generation,
+            "sketch_need_prompt_generation": request.sketch_need_prompt_generation,
+            "design_request_data": request.design_request_data,
+        }
+
+        stream = await agent.astream_events(state, config=config, version="v3", transformers=[ToolCallTransformer, CustomTransformer])
+
+        tool_names = {}
+        filter_tool_name = ["design_tool"]
+        async for event in stream:
+            if event["method"] == "tools":
+                data = event["params"]["data"]
+                tool_call_id = data.get("tool_call_id")
+
+                # 记录 tool_name
+                if data.get("event") == "tool-started":
+                    tool_names[tool_call_id] = data.get("tool_name")
+
+                # 通过 ID 查找 tool_name
+                elif data.get("event") == "tool-finished":
+                    tool_name = tool_names.get(tool_call_id, "unknown")
+
+                    if tool_name in filter_tool_name:
+                        continue
+
+                    data["tool_name"] = tool_name
+
+                response_event = {"event_type": "tool", "data": data}
+                yield f"data: {json.dumps(response_event, ensure_ascii=False)}\n\n"
+
+            elif event["method"] == "custom":
+                data = event["params"]["data"]
+                response_event = {"event_type": "tool", "data": data}
+                yield f"data: {json.dumps(response_event, ensure_ascii=False)}\n\n"
+
+            elif event["method"] == "messages":
+                data = event["params"]["data"][0]
+                if not isinstance(data, dict):
+                    continue
+                if data.get("event") != "content-block-delta":
+                    continue
+                block = data.get("delta") or {}
+
+                if block.get("type") == "text-delta":
+                    response_event = {"event_type": "messages", "data": {"event": data["event"]} | block}
+                    yield f"data: {json.dumps(response_event, ensure_ascii=False)}\n\n"
+                elif block.get("type") == "reasoning-delta":
+                    response_event = {"event_type": "messages", "data": {"event": data["event"]} | block}
+                    yield f"data: {json.dumps(response_event, ensure_ascii=False)}\n\n"
+                else:
+                    pass
+                    # print(f"----------------{event}")
+        response_event = {"event_type": "done"}
+        yield f"data: {response_event}"
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    async def test_stream():
+        """测试流式调用"""
+
+        with open("app/service/fashion_agent/graph_node/design_graph/design_request_data.json", encoding="utf-8") as f:
+            request_data = json.load(f)
+
+        service = FashionAgentService()
+
+        print("=" * 50)
+        print("测试流式输出")
+        print("=" * 50)
+        request = FashionAgentRequest(
+            message="生成一张草莓图案",
+            call_print=True,
+            # print_need_prompt_generation=False,
+            # call_sketch=True,
+            # sketch_need_prompt_generation=False,
+            # call_logo=True,
+            # call_explor=True,
+            # call_design=True,
+            # design_request_data=request_data,
+        )
+        async for chunk in service.run_stream(request):
+            print(chunk, end="")
+
+    # 运行测试
+    asyncio.run(test_stream())