43 lines
1.6 KiB
Python
43 lines
1.6 KiB
Python
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# -*- coding: utf-8 -*-
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"""
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NBA球迷大全 - 全局配置
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所有环境相关配置集中在此，便于迁移与扩展（新增 CBA / 足球等只需扩展数据库，不改代码）
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"""
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import os
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BASE_DIR = os.path.dirname(os.path.abspath(__file__))
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DATA_DIR = os.path.join(BASE_DIR, "data")
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LOG_DIR = os.path.join(BASE_DIR, "logs")
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STATIC_DIR = os.path.join(BASE_DIR, "static")
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DB_PATH = os.path.join(DATA_DIR, "nba_fan.db")
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os.makedirs(DATA_DIR, exist_ok=True)
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os.makedirs(LOG_DIR, exist_ok=True)
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# ---------------- 大模型（DeepSeek） ----------------
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LLM_BASE_URL = "https://api.deepseek.com"
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LLM_API_KEY = "sk-edb9df58ff574f8c98df1cd6a425e97c"
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LLM_MODEL = "deepseek-v4-flash"
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LLM_TIMEOUT = 90 # 单次请求超时（秒）
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LLM_MAX_TOKENS = 2048
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LLM_TEMPERATURE = 0.3 # 事实问答，低温度更准确
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# ---------------- Embedding 服务（本地 16011，OpenAI 兼容） ----------------
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EMBEDDING_API_URL = "http://121.40.164.32:16011/v1/embeddings"
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EMBEDDING_MODEL = "bge-large-zh-v1.5" # 容器内白名单模型名（1024 维）
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EMBEDDING_DIM = 1024
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# ---------------- Rerank 服务（本地 16011，Cohere 兼容，可选） ----------------
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RERANK_API_URL = "http://121.40.164.32:16011/v1/rerank"
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RERANK_MODEL = "bge-reranker-v2-m3"
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USE_RERANK = True
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# ---------------- Chroma 向量库（本地 16010） ----------------
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CHROMA_HOST = "121.40.164.32"
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CHROMA_PORT = 16010
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CHROMA_COLLECTION = "nba_fan_knowledge_v1" # 集合名（升级可换 v2，平滑迁移）
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# ---------------- 服务 ----------------
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SERVICE_PORT = 16090
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SERVICE_HOST = "0.0.0.0"
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SERVICE_NAME = "NBA球迷大全"
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