1

# Conflicts:
#	docker-compose.yml

.gitea/workflows/prod_build_manual.yaml

@@ -7,7 +7,7 @@ jobs:
     runs-on: ubuntu-latest
 
     env:
-      REMOTE_DEPLOY_PATH: /workspace/Trinity/Litserve_LC_Prod/lc_stylist_agent
+      REMOTE_DEPLOY_PATH: /workspace/LC_Workspace/LitServe_Server_Workspace/lc_stylist_agent
 
     steps:
       - name: 1.检出代码

app/config.py

@@ -17,7 +17,11 @@ class Settings(BaseSettings):
         extra='ignore'  # 忽略环境变量中多余的键
     )
     # 启动端口
-    SERVE_PROD: int = Field(default=8000, description='')
+    SERVE_PORT: int = Field(default=8000, description='')
+
+    # 换脸模型服务
+    RE_FACE_MODEL_URL: str = Field(default="10.1.1.240:10071", description='')
+
     # 调试配饰
     LOCAL: int = Field(default=0, description="是否在本地运行，1表示本地运行，0表示生产环境运行")
 

app/main.py

@@ -27,4 +27,4 @@ if __name__ == "__main__":
     agent_api = LCAgent(enable_async=True, api_path='/api/v1/agent')
     reface_api = ReFace(api_path='/api/v1/reface')
     server = ls.LitServer([chat_boot_api, agent_api, reface_api])
-    server.run(port=settings.SERVE_PROD)
+    server.run(port=8000)

app/server/ChatbotAgent/chatbot_server.py

@@ -49,10 +49,18 @@ class LCChatBot(ls.LitAPI):
         user_msg = Message(role=Role.USER, content=user_message)
         chat_history = self.redis.get_history(session_id)
         chat_history.append(user_msg)
+
+        turn_count = sum(1 for msg in chat_history if msg.role == Role.USER)
+
         if request.gender == 'male':
-            prompt = BASIC_PROMPT.format(gender='men')
+            system_instruction = BASIC_PROMPT.format(gender='men')
         else:
-            prompt = BASIC_PROMPT.format(gender='women')
+            system_instruction = BASIC_PROMPT.format(gender='women')
+
+        if turn_count >= 3:
+            system_instruction += "\n\nCRITICAL: This is the final turn. Do not ask questions. Provide a brief summary and use the mandatory closing phrase."
+        else:
+            system_instruction += f"\n\nCURRENT STATE: This is turn {turn_count} of 3. Keep gathering info efficiently or provide  a brief summary and use the mandatory closing phrase if you have sufficient information."
 
         contents = []
 
@@ -68,7 +76,7 @@ class LCChatBot(ls.LitAPI):
             model='gemini-2.5-flash',
             contents=contents,
             config=types.GenerateContentConfig(
-                system_instruction=prompt,
+                system_instruction=system_instruction,
                 # temperature=0.3,
             )
         )
@@ -99,7 +107,7 @@ class LCChatBot(ls.LitAPI):
 
 
 if __name__ == "__main__":
-    sys.stdout = open('permanent.log', 'w', encoding='utf-8')
+    # sys.stdout = open('permanent.log', 'w', encoding='utf-8')
 
     import asyncio
 
@@ -137,23 +145,67 @@ if __name__ == "__main__":
             print(chunk, end="", flush=True)
 
 
-    text_list = [
-        '我要去参加好朋友的婚礼，你能帮我挑一套衣服吗？',
-        'I need something to wear for a big presentation at work tomorrow. I want to look powerful but still approachable.',
-        'Who do you think is the best world leader right now?',
-        'I’m going on a trip to Paris next week and need some outfits.',
-        'Help me find a cool outfit for a rock concert. I hate wearing dresses.',
-        'I want to look very cool, 或者是那种很有个性的风格 for a gallery opening.',
-        "I'm going to a gala. Please list 5 different dress styles for me and use bold text for the names.",
-        "I'm feeling really sad today and just want an outfit that matches my mood."
-    ]
-    for text in text_list:
-        asyncio.run(run_simple_test(text))
-    # print("\n" + "=" * 50)
-    # # 启动异步事件循环
-    # try:
-    #     asyncio.run(run_simple_test())
-    # except Exception as e:
-    #     print(f"\n发生致命错误: {e}")
-    #
-    sys.stdout.close()
+    # text_list = [
+    #     '我要去参加好朋友的婚礼，你能帮我挑一套衣服吗？',
+    #     'I need something to wear for a big presentation at work tomorrow. I want to look powerful but still approachable.',
+    #     'Who do you think is the best world leader right now?',
+    #     'I’m going on a trip to Paris next week and need some outfits.',
+    #     'Help me find a cool outfit for a rock concert. I hate wearing dresses.',
+    #     'I want to look very cool, 或者是那种很有个性的风格 for a gallery opening.',
+    #     "I'm going to a gala. Please list 5 different dress styles for me and use bold text for the names.",
+    #     "I'm feeling really sad today and just want an outfit that matches my mood."
+    # ]
+    # for text in text_list:
+    #     asyncio.run(run_simple_test(text))
+    
+
+    async def run_interactive_test():
+        """
+        手动输入测试：模拟真实用户与 AI 的多轮对话
+        """
+        # 1. 初始化
+        chatbot_api = LCChatBot()
+        chatbot_api.setup(device="cpu")
+        
+        session_id = "manual_test_session"
+        user_id = "test_user"
+
+        print("--- 👗 欢迎进入 AI 造型师测试 (输入 'quit' 退出) ---")
+
+        
+        # 清空旧的测试记录，开始新会话
+        chatbot_api.redis.clear_history(session_id)
+        print("✅ 已清空历史记录，开始新会话。")
+        
+        
+        while True:
+            # 2. 获取手动输入
+            user_input = input("\nUser (你): ")
+            if user_input.lower() in ['quit', 'exit', '退出']:
+                break
+
+            # 3. 构造请求
+            request_data = PredictRequest(
+                user_id=user_id,
+                session_id=session_id,
+                user_message=user_input,
+                gender="female" # 或者根据需要修改
+            )
+
+            print("Agent (AI): ", end="")
+
+            # 4. 调用并流式打印
+            # 注意：这里的 predict 内部现在会计算 turn_count
+            response_generator = chatbot_api.predict(request_data)
+            
+            full_response = ""
+            async for chunk in response_generator:
+                print(chunk, end="", flush=True)
+                full_response += chunk
+            
+            # 将 AI 的回复存入 Redis (如果你的 predict 函数里没存的话)
+            # chatbot_api.redis.add_message(session_id, Role.ASSISTANT, full_response)
+            
+            print() # 换行
+
+    asyncio.run(run_interactive_test())

app/server/ChatbotAgent/core/prompt.py

@@ -7,6 +7,16 @@ CONVERSATION GOALS:
     3.  **Vibe/Details:** Gather mood or constraints (e.g., comfort, specific colors).
     4.  **Item Preference:** Identify preferences for silhouettes or specific items.
 
+CONVERSATION FLOW:
+    - You have a maximum of 3 turns (one turn = one user message and one assistant response) to gather information.
+    - On the 3rd turn, or *once you have sufficient info*, do NOT ask further questions.
+    - MANDATORY CLOSING: You must end your final response using the FINAL TURN CLOSING RULE below.
+
+FINAL TURN CLOSING RULE:
+    - Once requirements are gathered, do NOT ask any more questions.
+    - End your final response with a creative and friendly variation of the closing phrase. 
+    - REQUIRED COMPONENTS: Every variation MUST mention the "**Generate button**" (this phrase must be bounded using double asterisks).
+
 PERSONALITY AND COMMUNICATION RULES:
     -   Always reply in English only. If the user speaks another language, state in English that you cannot speak that language and steer back to styling.
     -   Keep responses extremely SHORT (maximum 2 sentences).
@@ -24,7 +34,7 @@ OUTPUT FORMAT INSTRUCTION:
 -   **ONLY** output the plain text response spoken by the AI Assistant.
 
 EXAMPLE DIALOGUES:
-    User: 我想找件衣服参加婚礼。 Response: I am so sorry, but I can only speak English! I would love to help you find the perfect wedding guest look if you can tell me the dress code or the venue vibe.
+    User: 我想找件衣服参加婚礼。 Response: I would love to help you find the perfect wedding guest look if you can tell me the dress code or the venue vibe.
 
     User: I need a chic outfit for dinner. Response: That sounds like a fabulous evening! Is this a romantic date or a casual night out with friends, and do you prefer a sleek dress or tailored separates?
 

app/server/ChatbotAgent/core/stylist_agent_server.py

@@ -250,9 +250,20 @@ class AsyncStylistAgent:
         if occasion == "Bridal / Wedding":
             request_summary += "IMPORTANT: Strictly only recommend colorful or white items (clothing, shoes, and bags)."
         elif occasion == "Evening":
-            request_summary += " **EVENING STYLE MANDATE:** Prioritize high textural contrast. Avoid flat/matte monochrome or total black looks. Ensure visual depth through layering (e.g., varying lengths or sheer panels). Use statement accessories to break simple silhouettes."
+            request_summary += (" **EVENING STYLE MANDATE:** Prioritize high textural contrast. Avoid flat/matte monochrome or total black looks. Ensure visual depth through layering "
+                                "(e.g., varying lengths or sheer panels). Use statement accessories to break simple silhouettes.")
         elif occasion == "Business / workwear":
-            request_summary += " **WORKWEAR STYLE MANDATE:** Focus on 'Power Dressing' silhouettes—prioritize sharp, oversized blazers paired with floor-length wide-leg trousers. Use tonal dressing (different shades of the same color) to create a sophisticated, elongated look. Balance masculine tailoring with polished, feminine textures. Select structured, architectural bags and pointed-toe or sleek loafers to maintain professional sharpness."
+            request_summary += (" **WORKWEAR STYLE MANDATE:** Focus on 'Power Dressing' silhouettes—prioritize sharp, oversized blazers paired with floor-length wide-leg trousers. "
+                                "Use tonal dressing to create a sophisticated, elongated look. Balance masculine tailoring with polished, feminine textures. "
+                                "Select structured, architectural bags and pointed-toe or sleek loafers. MANDATORY: Include a complete gold or silver jewelry set "
+                                "(earrings, necklaces, bracelets, and rings).")
+        elif occasion == "Outdoor":
+            request_summary += " **OUTDOOR STYLE MANDATE:** No jeans allowed. Focus on functional yet polished alternatives like chinos, technical fabrics, or tailored shorts."
+        elif occasion == "Festival / Concert":
+            request_summary += " **FESTIVAL STYLE MANDATE:** No maxi dresses or maxi skirts. Prioritize shorter hemlines, sets, or trousers to ensure ease of movement."
+        elif occasion == "Beach / Swim":
+            request_summary += " **BEACH STYLE MANDATE:** No denim allowed. Focus on breathable, lightweight fabrics like linen, silk, or crochet."
+
         sys_template = template.format(
             gender=self.gender,
             current_category=current_category.upper(),

app/server/ReFace/server.py

@@ -4,6 +4,8 @@ import litserve as ls
 import requests
 from pydantic import BaseModel
 
+from app.config import settings
+
 
 class PredictRequest(BaseModel):
     input_image_list: list[str]  # 待换脸图片
@@ -17,7 +19,7 @@ class ReFace(ls.LitAPI):
 
     def predict(self, request):
         # 服务的 URL
-        url = "http://10.1.1.240:10071/predict"
+        url = f"http://{settings.RE_FACE_MODEL_URL}/predict"
 
         # 请求头
         headers = {

app/taxonomy.py

@@ -163,7 +163,7 @@ OCCASION_CATEGORY_MAP = {
         "accessories": ["earrings", "necklaces", "bracelets", "rings"]
     },
     "Outdoor": {
-        "clothing": ["jackets", "jeans", "sweaters"],
+        "clothing": ["jackets", "sweaters", "pants", "joggers", "leggings", "shorts"],
         "shoes": ["boots"],
         "bags": ["backpacks", "travel bags"],
         "accessories": []

docker-compose.yml

@@ -1,5 +1,6 @@
 services:
   lc_agent_server:
+    container_name: LC_Agent_Server
     build:
       context: .
       dockerfile: Dockerfile
@@ -9,12 +10,12 @@ services:
       DEBUG: 0
     volumes:
       - ./app:/app/app
-      - ./.prod_env:/app/.env
+      - ./.env:/app/.env
       - ./data:/data
       - ./google_application_credentials.json:/google_application_credentials.json
       - /etc/localtime:/etc/localtime:ro
     ports:
-      - "10070:8000"
+      - "${SERVE_PORT}:8000"
     deploy:
       resources:
         reservations:
@@ -22,4 +23,10 @@ services:
             # 告诉 Docker 使用所有可用的 NVIDIA GPU
             - driver: nvidia
               device_ids: [ '0' ]
-              capabilities: [ gpu ]
+              capabilities: [ gpu ]
+    networks:
+      - lc_app_net
+networks:
+  lc_app_net:
+    external: true
+    name: lc_app_net