更新图形生成工具，优化返回格式并添加新功能

app/service/fashion_agent/graph_node/explorer_graph/tools.py

@@ -23,12 +23,14 @@ async def explor_tool(
         # 方式 1：从 configurable 获取
         user_id = config.get("configurable", {}).get("user_id", "agent")
 
+    results = []
     if method == "unsplash":
-        return await get_random_photos(query, count=per_page, user_id=user_id)
+        results = await get_random_photos(query, count=per_page, user_id=user_id)
     elif method == "pexels":
-        return await search_photos(query, per_page=per_page, user_id=user_id)
+        results = await search_photos(query, per_page=per_page, user_id=user_id)
     else:
-        pass
+        results = []
+    return results
 
 
 if __name__ == "__main__":

app/service/fashion_agent/graph_node/logo_graph/graph.py

@@ -6,7 +6,7 @@ from langchain_core.messages import HumanMessage, SystemMessage
 from langgraph.graph import END, START, StateGraph
 from langgraph.graph.message import add_messages
 from pydantic import BaseModel, Field
-from app.service.fashion_agent.graph_node.node_tools.generate_logo import generate_logo_tool
+from app.service.fashion_agent.graph_node.logo_graph.tools import generate_logo_tool
 from app.service.fashion_agent.init_llm import qwen_plus_llm
 
 """初始化 LLM TODO 将 API Key 替换为环境变量或者配置文件中的值，避免在代码中硬编码敏感信息"""

app/service/fashion_agent/graph_node/logo_graph/tools.py

@@ -71,7 +71,7 @@ async def generate_logo_tool(prompt: str, user_id: str = "agent") -> str:
     file_name = f"{uuid7()}.png"
     loop = asyncio.get_event_loop()
     image_url = await loop.run_in_executor(executor, upload_SDXL_image, image, user_id, "logo", file_name)
-    return image_url
+    return [image_url]
 
 
 if __name__ == "__main__":

app/service/fashion_agent/graph_node/print_graph/tools.py

@@ -20,7 +20,7 @@ async def generate_print_tool(prompt: str) -> str:
     bucket_name = "aida-users"
     object_name = f"agent_generate_print/{uuid7()}.png"
     image_url = await generate_image(prompt=prompt, bucket_name=bucket_name, object_name=object_name)
-    return image_url
+    return [image_url]
 
 
 @tool

app/service/fashion_agent/graph_node/sketch_graph/graph.py

@@ -79,21 +79,19 @@ def generate_sketch_prompt_node(state: SketchState) -> dict:
 async def generate_sketch_img_node(state: SketchState) -> dict:
     """根据生成的提示词，生成服装草图"""
     # 如果 sketch_need_prompt_generation=False 且 sketch_prompts 为空，使用模板生成 prompt
-    # if not state.get("sketch_need_prompt_generation", False) and not state.get("sketch_prompts"):
+    if not state.get("sketch_need_prompt_generation", False) and not state.get("sketch_prompts"):
 
-    #     input_text = state.get("input_text", "")
-    #     prompts = [build_sketch_template_prompt(input_text)]
-    # else:
-    #     prompts = state["sketch_prompts"] if state["sketch_prompts"] else [state["input_text"]]
+        input_text = state.get("input_text", "")
+        prompts = [build_sketch_template_prompt(input_text)]
+    else:
+        prompts = state["sketch_prompts"] if state["sketch_prompts"] else [state["input_text"]]
 
-    # sketch_img_urls = []
-    # for prompt in prompts:
-    #     image_url = await generate_sketch_tool.ainvoke({"prompt": prompt})
-    #     sketch_img_urls.append(image_url)
+    sketch_img_urls = []
+    for prompt in prompts:
+        image_url = await generate_sketch_tool.ainvoke({"prompt": prompt})
+        sketch_img_urls.append(image_url)
 
-    # result_text = f"服装草图生成完成，共生成 {len(sketch_img_urls)} 张图片：\n" + "\n".join(sketch_img_urls)
-    # return {"sketch_img_urls": sketch_img_urls, "messages": [AIMessage(content=result_text)]}
-    return {"messages": [AIMessage(content="hello")]}
+    return {"sketch_img_urls": sketch_img_urls}
 
 
 """条件分支 判断是否需要生成 prompt"""

app/service/fashion_agent/graph_node/sketch_graph/tools.py

@@ -20,7 +20,7 @@ async def generate_sketch_tool(prompt: str) -> str:
     bucket_name = "fida-public-bucket"
     object_name = f"test/{uuid7()}.png"
     image_url = await generate_image(prompt=prompt, bucket_name=bucket_name, object_name=object_name)
-    return image_url
+    return [image_url]
 
 
 async def run_test():

app/service/fashion_agent/init_llm.py

@@ -29,3 +29,5 @@ qwen_plus_llm = ChatQwen(
     top_p=0.8,
     api_key=QWEN_API_KEY_INTL,
 )
+# response = qwen_plus_llm.invoke("你好")
+# print(response)

app/service/fashion_agent/main_agent.py

@@ -12,7 +12,7 @@ from app.service.fashion_agent.graph_node.design_graph.graph import build_design
 from app.service.fashion_agent.graph_node.design_graph.tools import design_tool
 from app.service.fashion_agent.graph_node.explorer_graph.tools import explor_tool
 from app.service.fashion_agent.graph_node.logo_graph.graph import build_logo_graph
-from app.service.fashion_agent.graph_node.node_tools.generate_logo import generate_logo_tool
+from app.service.fashion_agent.graph_node.logo_graph.tools import generate_logo_tool
 from app.service.fashion_agent.graph_node.print_graph.graph import build_print_graph
 from app.service.fashion_agent.graph_node.print_graph.tools import generate_print_tool
 from app.service.fashion_agent.graph_node.sketch_graph.graph import build_sketch_graph

app/service/fashion_agent/service.py

@@ -6,7 +6,7 @@ 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 langchain_core.messages import HumanMessage, ToolMessage
 from app.schemas.fashion_agent import FashionAgentRequest
 
 logger = logging.getLogger()
@@ -71,6 +71,8 @@ class FashionAgentService:
 
                     data["tool_name"] = tool_name
 
+                    if isinstance(data["output"], ToolMessage):
+                        data["output"] = json.loads(data["output"].content)
                 response_event = {"event_type": "tool", "data": data}
                 yield f"data: {json.dumps(response_event, ensure_ascii=False)}\n\n"