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@@ -30,7 +30,7 @@ MENU_GENERATE_TEMPLATE = """请为{participant_count}人生成{date}的一日三
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{constraints_text}
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{constraints_text}
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请返回 JSON 格式：
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请返回 JSON 格式：
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-{{"meals": [{{"type": "breakfast", "name": "早餐", "dishes": [{{"name": "菜品名", "ingredients": [{{"name": "食材", "grams": 100}}], "cooking_method": "烹饪方法", "nutrition": {{"calories": 200, "protein": 10, "carbs": 30, "fat": 5}}, "notes": "备注"}}]}}]}}
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+{{"meals": [{{"type": "breakfast", "name": "早餐", "dishes": [{{"name": "菜品名", "ingredients": [{{"name": "食材", "grams": 100}}], "cooking_method": "做法一句话", "nutrition": {{"calories": 200}}}]}}]}}
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要求:
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要求:
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1. 早/午/晚各至少1-2道菜
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1. 早/午/晚各至少1-2道菜
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@@ -140,11 +140,14 @@ async def generate_menu(req: MenuGenerateRequest):
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constraints_text=constraints_text,
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constraints_text=constraints_text,
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)
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)
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+ # max_tokens=1200：menu/generate 完整输出约 800-1200 token（已去掉 protein/carbs/fat/notes），
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+ # 避免 LLM 写满 3000+ token 导致 60s+ 超时；实测 1000 token ≈ 17s，1200 兜底安全
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llm = ChatOpenAI(
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llm = ChatOpenAI(
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model=settings.llm_model,
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model=settings.llm_model,
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api_key=settings.llm_api_key,
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api_key=settings.llm_api_key,
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base_url=settings.llm_base_url,
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base_url=settings.llm_base_url,
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temperature=0.7,
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temperature=0.7,
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+ max_tokens=1200,
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)
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)
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response = llm.invoke([
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response = llm.invoke([
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