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

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

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@@ -44,7 +44,6 @@ class LCAgent(ls.LitAPI):
'max_len': 9,
'gemini_model_name': settings.LLM_MODEL_NAME
}
self.outfit_ids = []
async def decode_request(self, request: AgentRequestModel):
"""
@@ -62,15 +61,17 @@ class LCAgent(ls.LitAPI):
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))
return {"status": "Task initiated in background.", "outfit_ids": self.outfit_ids}
asyncio.create_task(self.background_run(request, 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):
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
request_summary = await self.get_conversation_summary(request.session_id)
logger.info(f"request_summary: {request_summary}")
@@ -83,7 +84,8 @@ class LCAgent(ls.LitAPI):
user_id=request.user_id,
gender=request.gender,
callback_url=request.callback_url,
max_len=request.max_len)
max_len=request.max_len,
outfit_ids=outfit_ids)
logger.info("--- Final Recommendation Results ---")
for i, path in enumerate(recommendation_results.get("successful_outfits", [])):
logger.info(f"✅ Outfit {i + 1} saved to: {path}")
@@ -104,7 +106,7 @@ class LCAgent(ls.LitAPI):
return summary
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。
@@ -112,14 +114,18 @@ class LCAgent(ls.LitAPI):
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''category'
"""
if outfit_ids is None:
outfit_ids = []
if start_outfit is None:
start_outfit = []
tasks = []
task_map = {}
stylist_agent_kwages = self.stylist_agent_kwages.copy()
for i in range(num_outfits):
self.stylist_agent_kwages['outfit_id'] = self.outfit_ids[i]
self.stylist_agent_kwages['max_len'] = max_len
agent = AsyncStylistAgent(**self.stylist_agent_kwages)
stylist_agent_kwages['outfit_id'] = outfit_ids[i]
stylist_agent_kwages['max_len'] = max_len
agent = AsyncStylistAgent(**stylist_agent_kwages)
task = agent.run_styling_process(
request_summary=request_summary,
stylist_path=stylist_name,
@@ -129,7 +135,7 @@ class LCAgent(ls.LitAPI):
gender=gender,
)
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. ---")
# 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}). ---")
# 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
agent = AsyncStylistAgent(**self.stylist_agent_kwages)
stylist_agent_kwages['outfit_id'] = outfit_id
agent = AsyncStylistAgent(**stylist_agent_kwages)
new_task = agent.run_styling_process(
request_summary=request_summary,
stylist_path=stylist_name,