100d1a06eb
- 后端 API（Flask + Gunicorn） - RAG 引擎（混合检索 + 云端 Reranker + 引用溯源） - 文档解析（MinerU + 多格式支持） - Docker 生产部署配置 - 排除前端项目、敏感配置、模型文件
63 lines
1.4 KiB
Python
63 lines
1.4 KiB
Python
"""
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Agentic RAG - 基础模块
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包含常量、导入和共享配置
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"""
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import logging
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# 配置日志
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logger = logging.getLogger(__name__)
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# 尝试导入搜索API配置
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try:
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from config import SERPER_API_KEY
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HAS_SERPER = True
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except ImportError:
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HAS_SERPER = False
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SERPER_API_KEY = None
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# LLM 预算控制
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try:
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from core.llm_budget import get_budget_controller, should_use_agent, CallType
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HAS_BUDGET = True
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except ImportError:
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HAS_BUDGET = False
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CallType = None
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# 语义缓存
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try:
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from config import SEMANTIC_CACHE_ENABLED, SEMANTIC_CACHE_THRESHOLD
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HAS_SEMANTIC_CACHE_CONFIG = True
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except ImportError:
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SEMANTIC_CACHE_ENABLED = False
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SEMANTIC_CACHE_THRESHOLD = 0.92
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HAS_SEMANTIC_CACHE_CONFIG = False
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try:
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from core.semantic_cache import SemanticCache, get_semantic_cache
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HAS_SEMANTIC_CACHE = True
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except ImportError:
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HAS_SEMANTIC_CACHE = False
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SemanticCache = None
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# LLM 配置
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try:
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from config import API_KEY, BASE_URL, MODEL
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except ImportError:
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API_KEY = None
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BASE_URL = None
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MODEL = None
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# 来源标记
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SOURCE_KB = "知识库"
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SOURCE_WEB = "网络搜索"
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# Context Compression 配置
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MAX_CONTEXT_TOKENS = 8000 # 最大上下文 token 数（与生产路径对齐）
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MAX_CONTEXT_COUNT = 20 # 最大上下文数量
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RERANK_THRESHOLD = 0.3 # Rerank 过滤阈值
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# Answer Grounding 配置
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MAX_GROUNDING_RETRY = 1 # 幻觉修正最多重试次数
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