aidlab/lc_stylist_agent
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移除类变量self.stylist_agent_kwages 和 self.outfit_ids 避免出现同时调用模型导致参数复用

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litserve 单实例复用setup() 方法只会被调用一次（在 Worker 启动时）
This commit is contained in:
zhh
2025-11-18 16:04:19 +08:00
parent cde7357df8
commit 9579d498c9
1 changed files with 19 additions and 13 deletions
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32
app/server/ChatbotAgent/agent_server.py
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@@ -44,7 +44,6 @@ class LCAgent(ls.LitAPI):
'max_len': 9, 'max_len': 9,
'gemini_model_name': settings.LLM_MODEL_NAME 'gemini_model_name': settings.LLM_MODEL_NAME
} }
self.outfit_ids = []
async def decode_request(self, request: AgentRequestModel): async def decode_request(self, request: AgentRequestModel):
""" """
@@ -62,15 +61,17 @@ class LCAgent(ls.LitAPI):
async def predict(self, request): async def predict(self, request):
self.outfit_ids = [str(uuid.uuid4()) for _ in range(request.num_outfits)] outfit_ids = [str(uuid.uuid4()) for _ in range(request.num_outfits)]
asyncio.create_task(self.background_run(request)) asyncio.create_task(self.background_run(request, outfit_ids))
return {"status": "Task initiated in background.", "outfit_ids": self.outfit_ids}
logger.info({"status": "Task initiated in background.", "outfit_ids": outfit_ids})
return {"status": "Task initiated in background.", "outfit_ids": outfit_ids}
async def encode_response(self, output): async def encode_response(self, output):
return output return output
async def background_run(self, request: AgentRequestModel): async def background_run(self, request: AgentRequestModel, outfit_ids):
# 1. 根据用户ID查询对话历史，总结对话内容 # 1. 根据用户ID查询对话历史，总结对话内容
request_summary = await self.get_conversation_summary(request.session_id) request_summary = await self.get_conversation_summary(request.session_id)
logger.info(f"request_summary: {request_summary}") logger.info(f"request_summary: {request_summary}")
@@ -83,7 +84,8 @@ class LCAgent(ls.LitAPI):
user_id=request.user_id, user_id=request.user_id,
gender=request.gender, gender=request.gender,
callback_url=request.callback_url, callback_url=request.callback_url,
max_len=request.max_len) max_len=request.max_len,
outfit_ids=outfit_ids)
logger.info("--- Final Recommendation Results ---") logger.info("--- Final Recommendation Results ---")
for i, path in enumerate(recommendation_results.get("successful_outfits", [])): for i, path in enumerate(recommendation_results.get("successful_outfits", [])):
logger.info(f"✅ Outfit {i + 1} saved to: {path}") logger.info(f"✅ Outfit {i + 1} saved to: {path}")
@@ -104,7 +106,7 @@ class LCAgent(ls.LitAPI):
return summary return summary
async def recommend_outfit(self, request_summary: str, stylist_name: str, start_outfit=None, num_outfits: int = 1, async def recommend_outfit(self, request_summary: str, stylist_name: str, start_outfit=None, num_outfits: int = 1,
user_id: str = "test", gender: str = "male", callback_url: str = None, max_len: int = 9): user_id: str = "test", gender: str = "male", callback_url: str = None, max_len: int = 9, outfit_ids=None):
""" """
基于用户的对话历史和需求，推荐一套搭配。 基于用户的对话历史和需求，推荐一套搭配。
@@ -112,14 +114,18 @@ class LCAgent(ls.LitAPI):
request_summary: 用户的request request_summary: 用户的request
start_outfit: 可选的初始搭配列表，每个元素包含 'item_id' 和 'category'。 start_outfit: 可选的初始搭配列表，每个元素包含 'item_id' 和 'category'。
""" """
if outfit_ids is None:
outfit_ids = []
if start_outfit is None: if start_outfit is None:
start_outfit = [] start_outfit = []
tasks = [] tasks = []
task_map = {} task_map = {}
stylist_agent_kwages = self.stylist_agent_kwages.copy()
for i in range(num_outfits): for i in range(num_outfits):
self.stylist_agent_kwages['outfit_id'] = self.outfit_ids[i] stylist_agent_kwages['outfit_id'] = outfit_ids[i]
self.stylist_agent_kwages['max_len'] = max_len stylist_agent_kwages['max_len'] = max_len
agent = AsyncStylistAgent(**self.stylist_agent_kwages) agent = AsyncStylistAgent(**stylist_agent_kwages)
task = agent.run_styling_process( task = agent.run_styling_process(
request_summary=request_summary, request_summary=request_summary,
stylist_path=stylist_name, stylist_path=stylist_name,
@@ -129,7 +135,7 @@ class LCAgent(ls.LitAPI):
gender=gender, gender=gender,
) )
tasks.append(task) tasks.append(task)
task_map[task] = {"outfit_id": self.outfit_ids[i], "retries": 0} task_map[task] = {"outfit_id": outfit_ids[i], "retries": 0}
logger.info(f"--- Starting {num_outfits} concurrent outfit generation tasks. ---") logger.info(f"--- Starting {num_outfits} concurrent outfit generation tasks. ---")
# 2. 任务执行与重试循环 # 2. 任务执行与重试循环
@@ -157,8 +163,8 @@ class LCAgent(ls.LitAPI):
logger.info(f"--- Retrying outfit {outfit_id} (Attempt {current_retries + 1}/{retry_limit}). ---") logger.info(f"--- Retrying outfit {outfit_id} (Attempt {current_retries + 1}/{retry_limit}). ---")
# 重新创建任务 (可能需要短暂延迟，例如 time.sleep(1)，但在此异步环境中，我们会通过重新创建 agent/task 来实现) # 重新创建任务 (可能需要短暂延迟，例如 time.sleep(1)，但在此异步环境中，我们会通过重新创建 agent/task 来实现)
self.stylist_agent_kwages['outfit_id'] = outfit_id stylist_agent_kwages['outfit_id'] = outfit_id
agent = AsyncStylistAgent(**self.stylist_agent_kwages) agent = AsyncStylistAgent(**stylist_agent_kwages)
new_task = agent.run_styling_process( new_task = agent.run_styling_process(
request_summary=request_summary, request_summary=request_summary,
stylist_path=stylist_name, stylist_path=stylist_name,