feat：1.移除所有明文服务密钥，采用环境变量方式读取

2.回调信息简化 \ stylist_agent_server.py中 一部分逻辑更新

.env_local

@@ -1,2 +0,0 @@
-GEMINI_API_KEY=AIzaSyAO4zXFke1bqyrXd9-RGfKJTLerwLSFKww
-GOOGLE_APPLICATION_CREDENTIALS="/workspace/lc_stylist_agent/app/request.json"

.gitignore

@@ -4,3 +4,6 @@ __pycache__/
 data/
 .idea/
 *.log
+*.toml
+.prod_env
+google_application_credentials.json

app/config.py

@@ -3,8 +3,8 @@ import os
 from pydantic_settings import BaseSettings, SettingsConfigDict
 from pydantic import Field
 
+
 # ⚠️ 注意: 您需要安装 pydantic-settings: pip install pydantic-settings
-DEBUG = os.environ.get("DEBUG", 1)
 
 
 class Settings(BaseSettings):
@@ -35,13 +35,17 @@ class Settings(BaseSettings):
     STYLIST_GUIDE_DIR: str = Field(default="/workspace/lc_stylist_agent/data/stylist_guide", description="风格指南文本目录")
 
     # 向量数据库配置参数
-    if DEBUG == 1:
-        VECTOR_DB_DIR: str = Field(default="/workspace/lc_stylist_agent/db", description="向量数据库目录")
-    else:
     VECTOR_DB_DIR: str = Field(default="/db", description="向量数据库目录")
     COLLECTION_NAME: str = Field(default="lc_clothing_embedding", description="向量数据库集合名称")
     EMBEDDING_MODEL_NAME: str = Field(default="openai/clip-vit-base-patch32", description="CLIP嵌入模型名称")
 
+    # minio配置
+    MINIO_URL: str = Field(default="", description="URL")
+    MINIO_ACCESS: str = Field(default="", description="ACCESS")
+    MINIO_SECRET: str = Field(default="", description="SECRET")
+    MINIO_SECURE: bool = Field(default=True, description="SECRET")
+    MINIO_LC_DATA_PATH: str = Field(default="", description="图片数据路径")
+
 
 # 创建配置实例，供应用其他部分使用
 settings = Settings()

app/main.py

@@ -1,7 +1,7 @@
 import logging.config
 import os
 import litserve as ls
-from app.config import DEBUG, settings
+from app.config import settings
 from app.server.ChatbotAgent.agent_server import LCAgent
 from app.server.ChatbotAgent.chatbot_server import LCChatBot
 from app.server.ReFace.server import ReFace
@@ -21,7 +21,7 @@ logging.config.dictConfig(LOGGER_CONFIG_DICT)
 
 # STEP 2: START THE SERVER
 if __name__ == "__main__":
-    logger.info(f"DEBUG -> :{DEBUG}")
+    logger.info(f"运行环境 1表示本地运行，0表示生产环境运行 ： -> :{settings.LOCAL}")
     logger.info(f"VECTOR_DB_DIR -> :{settings.VECTOR_DB_DIR}")
     chat_boot_api = LCChatBot(enable_async=True, stream=True, api_path='/api/v1/chatbot')
     agent_api = LCAgent(enable_async=True, api_path='/api/v1/agent')

app/request.json

@@ -1,13 +0,0 @@
-{
-  "type": "service_account",
-  "project_id": "aida-461108",
-  "private_key_id": "b4afaabebb84da24502b318a5fa175f1dc5c096a",
-  "private_key": "-----BEGIN PRIVATE KEY-----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\nqlXBUbmHHzamo5DPYL8S/w==\n-----END PRIVATE KEY-----\n",
-  "client_email": "aida-239@aida-461108.iam.gserviceaccount.com",
-  "client_id": "103102077955178349079",
-  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
-  "token_uri": "https://oauth2.googleapis.com/token",
-  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
-  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/aida-239%40aida-461108.iam.gserviceaccount.com",
-  "universe_domain": "googleapis.com"
-}

app/server/ChatbotAgent/agent_server.py

@@ -38,6 +38,7 @@ class OccasionEnum(str, Enum):
     SKI_SNOW_MOUNTAIN = "Ski / Snow / Mountain"
     GARDEN_PARTY_DAYTIME = "Garden Party / Daytime Event"
 
+
 class StylistResponse(BaseModel):
     occasions: List[OccasionEnum] = Field(
         description="A list of **applicable** occasions that are most strongly implied or explicitly requested by the user's conversation history. These occasions are used later in item retrieval for filtering and must strictly match the predefined OccasionEnum list."
@@ -55,6 +56,7 @@ class AgentRequestModel(BaseModel):
     batch_sources: List[str]
     callback_url: str
     gender: str
+    is_first_request: bool
 
 
 class LCAgent(ls.LitAPI):
@@ -118,7 +120,8 @@ class LCAgent(ls.LitAPI):
             user_id=request.user_id,
             gender=request.gender,
             callback_url=request.callback_url,
-            outfit_ids=outfit_ids
+            outfit_ids=outfit_ids,
+            is_first_request=request.is_first_request
         )
         logger.info("--- Final Recommendation Results ---")
         for i, path in enumerate(recommendation_results.get("successful_outfits", [])):
@@ -171,7 +174,8 @@ class LCAgent(ls.LitAPI):
             user_id: str = "test",
             gender: str = "male",
             callback_url: str = None,
-        outfit_ids=None
+            outfit_ids=None,
+            is_first_request=False
     ):
         """
         基于用户的对话历史和需求，推荐一套搭配。
@@ -191,6 +195,18 @@ class LCAgent(ls.LitAPI):
             stylist_agent_kwages['stylist_name'] = stylist_name
             stylist_agent_kwages['gender'] = gender
             agent = AsyncStylistAgent(**stylist_agent_kwages)
+            if is_first_request:
+                # 第一套搭配使用快速方法 一次跑出所有单品
+                task = agent.run_quick_batch_styling(
+                    request_summary=request_summary,
+                    occasions=occasions,
+                    start_outfit=start_outfit,
+                    batch_sources=batch_sources,
+                    user_id=user_id,
+                    callback_url=callback_url,
+                )
+            else:
+                # 后续
                 task = agent.run_iterative_styling(
                     request_summary=request_summary,
                     occasions=occasions,
@@ -232,7 +248,7 @@ class LCAgent(ls.LitAPI):
                             stylist_agent_kwages['stylist_name'] = stylist_name
                             stylist_agent_kwages['gender'] = gender
                             agent = AsyncStylistAgent(**stylist_agent_kwages)
-                            new_task = agent.run_iterative_styling(
+                            new_task = agent.run_quick_batch_styling(
                                 request_summary=request_summary,
                                 occasions=occasions,
                                 start_outfit=start_outfit,
@@ -288,7 +304,7 @@ if __name__ == "__main__":
         # 2. 准备请求数据
         import json
         stylist_agent_kwages = agent_api.stylist_agent_kwages.copy()
-        with open("./data/2025_q4/request_test.json", "r") as f:
+        with open("/mnt/data/workspace/Code/lc_stylist_agent/data/2025_q4/request_test.json", "r") as f:
             request_data = json.load(f)
 
         tasks_with_metadata = []
@@ -300,14 +316,14 @@ if __name__ == "__main__":
                 stylist_agent_kwages['stylist_name'] = stylist_name
                 stylist_agent_kwages['gender'] = "female"
                 agent = AsyncStylistAgent(**stylist_agent_kwages)
-                coro = agent.run_iterative_styling(
-                # coro = agent.run_quick_batch_styling(
+                # coro = agent.run_iterative_styling(
+                coro = agent.run_quick_batch_styling(
                     request_summary=request_summary,
                     occasions=occasions,
                     start_outfit=[],
                     batch_sources=["2025_q4"],
                     user_id=test_content['test_case_id'],
-                    callback_url="http://mock-callback.com/result",
+                    callback_url="http://18.167.251.121:10095",
                 )
                 # 记录任务开始前的单调时间，并将元数据添加到列表中
                 description = f"Batch mode - Case {test_content['test_case_id']} - Stylist {stylist_name}"
@@ -331,6 +347,7 @@ if __name__ == "__main__":
 
         print(f"Average time consumption is {sum(time_samples) / len(time_samples)}")
 
+
     try:
         # 使用 asyncio.run() 来执行顶层异步函数
         asyncio.run(test())

app/server/ChatbotAgent/core/stylist_agent_server.py

@@ -131,7 +131,6 @@ class AsyncStylistAgent:
         """
         if not self.outfit_items:
             return "", None
-
         merged_image = merge_images_to_square(self.outfit_items, max_len=9, add_text=False)
         image_bytes_io = io.BytesIO()
         image_format = 'JPEG'
@@ -146,7 +145,8 @@ class AsyncStylistAgent:
                 f.write(image_bytes)
             return local_file_path, image_bytes
         else:
-            blob_name = f"lc_stylist_agent_outfit_items/{user_id}/{file_name}.jpg"
+            # minio文件地址需保持变动，否则前端缓存导致无法更新图片
+            blob_name = f"lc_stylist_agent_outfit_items/{user_id}/{file_name}-{len(self.outfit_items)}.jpg"
             responses = oss_upload_image(oss_client=minio_client, bucket=self.minio_bucket, object_name=blob_name, image_bytes=image_bytes)
             minio_path = f"{responses.bucket_name}/{responses.object_name}"
             return minio_path, image_bytes
@@ -207,7 +207,7 @@ class AsyncStylistAgent:
             "image_path": os.path.join(settings.DATA_ROOT, batch_source, 'image_data', f"{item_id}.jpg")
         }
 
-    def _build_system_prompt(self, template: str, request_summary: str = "", stylist_guide: str = "", current_category: str = "clothing", max_len: int=4) -> str:
+    def _build_system_prompt(self, template: str, request_summary: str = "", stylist_guide: str = "", current_category: str = "clothing", max_len: int = 4) -> str:
         # Insert the style_guide content into the template
         sys_template = template.format(
             gender=self.gender,
@@ -242,15 +242,24 @@ class AsyncStylistAgent:
     def post_operation(self, status: str, message: str, callback_url: str, img_path: str):
         """处理完成后的回调操作。"""
         if settings.LOCAL == 0:
+            # 生产回调请求数据处理
+            items = []
+            for item in self.outfit_items:
+                items.append(
+                    {
+                        "item_id": item['item_id'],
+                        "category": item['subcategory']
+                    }
+                )
             response_data = {
-                'items': deepcopy(self.outfit_items),
+                'items': items,
                 'status': status,
-                'message': message,
+                # 'message': message,
                 'path': img_path,
                 'outfit_id': self.outfit_id
             }
             response = post_request(url=callback_url, data=json.dumps(response_data), headers=self.headers)
-            logger.info(f"request data ：{response_data} | JAVA callback info -> status:{response.status_code} | message:{response.text}")
+            logger.info(f"request data ：{json.dumps(response_data, ensure_ascii=False, indent=2)} | JAVA callback info -> status:{response.status_code} | message:{response.text}")
             return response_data
         else:
             return {}
@@ -350,7 +359,6 @@ class AsyncStylistAgent:
                     )
                     print(f"Stage {current_category.upper()}, Step {recommend_timestep}: {gemini_data}, found item: {new_item['item_id']}")
 
-         
     async def _execute_batch_recommendation(
             self,
             current_category: str,  # this can be any category or all
@@ -362,8 +370,9 @@ class AsyncStylistAgent:
             url: str
     ):
         user_input = self._build_user_input(current_category, existing_subcategories=", ".join([x['subcategory'] for x in self.outfit_items]))
+        # 合并图片
         merged_image_path, image_bytes = await self._merge_images(self.outfit_id, user_id, self.stylist_name)
-
+        # 调用Gemini API
         gemini_response_text = await self._call_gemini(
             user_input,
             user_id,
@@ -372,9 +381,11 @@ class AsyncStylistAgent:
             image_bytes,
             system_prompt
         )
+        # 解析响应
         gemini_data = self._parse_gemini_response(gemini_response_text)
         recommended_items = gemini_data.get('recommended_items', [])
         reason = gemini_data.get('reason', '')
+
         if not recommended_items or not isinstance(recommended_items, List):
             print("No recommended item from Gemini, terminating process.")
             self.post_operation(
@@ -411,11 +422,14 @@ class AsyncStylistAgent:
                     print(f"Item {idx + 1}: ({subcategory}) {rec_item}, found item: {new_item}")
         return reason
 
-
-    async def run_iterative_styling(self, request_summary, occasions, start_outfit=[], batch_sources=[], user_id="test", callback_url=""):
+    async def run_iterative_styling(self, request_summary, occasions, start_outfit: Optional[List] = None, batch_sources: List = [], user_id="test", callback_url=""):
         start_time = time.monotonic()
         STAGES = ['clothing', 'shoes', 'bags']
-        self.outfit_items = start_outfit
+        # 深拷贝start_outfit 避免实例之间的参数泄漏 确保每个实例都有自己的 start_outfit 副本
+        if start_outfit is None:
+            self.outfit_items = []
+        else:
+            self.outfit_items = deepcopy(start_outfit)
         stylist_guide, accessories_guide = self._load_style_guide(self.stylist_name)
         url = f'{callback_url}/api/style/callback'
 
@@ -449,7 +463,7 @@ class AsyncStylistAgent:
             url
         )
 
-        final_image_path = await self._merge_images(self.outfit_id, user_id, self.stylist_name)
+        final_image_path, _ = await self._merge_images(self.outfit_id, user_id, self.stylist_name)
         response_data = self.post_operation(
             status="stop",
             message=reason,
@@ -458,17 +472,20 @@ class AsyncStylistAgent:
         )
         if settings.LOCAL == 1:
             with open(os.path.join(settings.OUTFIT_OUTPUT_DIR, self.stylist_name, f'{self.outfit_id}.json'), 'w') as f:
-                json.dump({"request_summary": request_summary,"occasions": occasions, "items": self.outfit_items}, f, indent=2)
+                json.dump({"request_summary": request_summary, "occasions": occasions, "items": self.outfit_items}, f, indent=2)
 
         end_time = time.monotonic()
         total_duration = end_time - start_time
 
         return response_data, total_duration
 
-    async def run_quick_batch_styling(self, request_summary, occasions, start_outfit=[], batch_sources=[], user_id="test", callback_url=""):
+    async def run_quick_batch_styling(self, request_summary, occasions, start_outfit: Optional[List] = None, batch_sources: List = [], user_id="test", callback_url=""):
         start_time = time.monotonic()
-
-        self.outfit_items = start_outfit
+        # 深拷贝start_outfit 避免实例之间的参数泄漏 确保每个实例都有自己的 start_outfit 副本
+        if start_outfit is None:
+            self.outfit_items = []
+        else:
+            self.outfit_items = deepcopy(start_outfit)
         stylist_guide, accessories_guide = self._load_style_guide(self.stylist_name)
         url = f'{callback_url}/api/style/callback'
 
@@ -486,7 +503,7 @@ class AsyncStylistAgent:
             url
         )
 
-        final_image_path = await self._merge_images(self.outfit_id, user_id, self.stylist_name)
+        final_image_path, _ = await self._merge_images(self.outfit_id, user_id, self.stylist_name)
         response_data = self.post_operation(
             status="stop",
             message=reason,
@@ -495,7 +512,7 @@ class AsyncStylistAgent:
         )
         if settings.LOCAL == 1:
             with open(os.path.join(settings.OUTFIT_OUTPUT_DIR, self.stylist_name, f'{self.outfit_id}.json'), 'w') as f:
-                json.dump({"request_summary": request_summary,"occasions": occasions, "items": self.outfit_items}, f, indent=2)
+                json.dump({"request_summary": request_summary, "occasions": occasions, "items": self.outfit_items}, f, indent=2)
 
         end_time = time.monotonic()
         total_duration = end_time - start_time

app/server/utils/img_operation.py

@@ -3,7 +3,6 @@ import os
 from typing import List, Dict
 from PIL import Image, ImageDraw, ImageFont
 from app.server.utils.minio_client import oss_get_image, minio_client
-from app.server.utils.minio_config import MINIO_LC_DATA_PATH
 from app.config import settings
 
 logger = logging.getLogger(__name__)
@@ -79,7 +78,8 @@ def merge_images_to_square(outfit_items: List[Dict[str, str]], max_len=9, add_te
             if settings.LOCAL == 1:
                 img = Image.open(path).convert('RGB')
             else:
-                img = oss_get_image(oss_client=minio_client, path=f"{MINIO_LC_DATA_PATH}/{path}", data_type="PIL").convert('RGB')
+                img_name = path.rsplit('/', 1)[-1]
+                img = oss_get_image(oss_client=minio_client, path=f"{settings.MINIO_LC_DATA_PATH}/{img_name}", data_type="PIL").convert('RGB')
             # img = Image.open(path).convert('RGB')
             valid_images.append(img)
         except Exception as e:

app/server/utils/minio_client.py

@@ -10,9 +10,9 @@ import urllib3
 from PIL import Image
 from minio import Minio
 
-from app.server.utils.minio_config import MINIO_ACCESS, MINIO_SECRET, MINIO_URL, MINIO_SECURE
+from app.config import settings
 
-minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
+minio_client = Minio(settings.MINIO_URL, access_key=settings.MINIO_ACCESS, secret_key=settings.MINIO_SECRET, secure=settings.MINIO_SECURE)
 
 
 # 自定义 Retry 类

app/server/utils/minio_config.py

@@ -1,6 +0,0 @@
-# minio 配置
-MINIO_URL = "www.minio-api.aida.com.hk"
-MINIO_ACCESS = 'vXKFLSJkYeEq2DrSZvkB'
-MINIO_SECRET = 'uKTZT3x7C43WvPN9QTc99DiRkwddWZrG9Uh3JVlR'
-MINIO_SECURE = True
-MINIO_LC_DATA_PATH = "lanecarford/lc_image_data"

docker-compose.yml

@@ -5,12 +5,13 @@ services:
       dockerfile: Dockerfile
     working_dir: /app
     environment:
-      GOOGLE_APPLICATION_CREDENTIALS: /app/app/request.json
+      GOOGLE_APPLICATION_CREDENTIALS: /google_application_credentials.json
       DEBUG: 0
     volumes:
       - ./app:/app/app
-      - ./.env:/app/.env
-      - ./db:/db
+      - ./.prod_env:/app/.env
+      - ./data:/data
+      - ./google_application_credentials.json:/google_application_credentials.json
       - /etc/localtime:/etc/localtime:ro
     ports:
       - "10070:8000"
@@ -20,5 +21,5 @@ services:
           devices:
             # 告诉 Docker 使用所有可用的 NVIDIA GPU
             - driver: nvidia
-              device_ids: ['0']
+              device_ids: [ '0' ]
               capabilities: [ gpu ]