7d4722b62c
- 实现QA数据 - 优化现在创建知识库的体验 - 优化文件处理与加载方法 - 整体的格式检查与优化 - 优化 Embedding model 的加载逻辑，修复并行问题 - 优化整体的颜色布局 - 移除未使用的接口（前后端） - 优化知识库的 chunk 逻辑 - 添加新的 Embedding模型支持 - 修复新建知识库后，Agent无法reload的问题
44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
import os
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from dotenv import load_dotenv
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load_dotenv("src/.env", override=True)
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from concurrent.futures import ThreadPoolExecutor # noqa: E402
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executor = ThreadPoolExecutor()
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from src.config import Config # noqa: E402
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config = Config()
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# 导入知识库相关模块
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from src.knowledge.kb_factory import KnowledgeBaseFactory # noqa: E402
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from src.knowledge.kb_manager import KnowledgeBaseManager # noqa: E402
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from src.knowledge.lightrag_kb import LightRagKB # noqa: E402
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from src.knowledge.chroma_kb import ChromaKB # noqa: E402
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from src.knowledge.milvus_kb import MilvusKB # noqa: E402
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# 注册知识库类型
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KnowledgeBaseFactory.register("chroma", ChromaKB, {
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"chunk_size": 1000,
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"chunk_overlap": 200,
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"description": "基于 ChromaDB 的轻量级向量知识库，适合开发和小规模部署"
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})
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KnowledgeBaseFactory.register("milvus", MilvusKB, {
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"chunk_size": 1000,
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"chunk_overlap": 200,
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"description": "基于 Milvus 的生产级向量知识库，适合大规模高性能部署"
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})
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KnowledgeBaseFactory.register("lightrag", LightRagKB, {
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"description": "基于图检索的知识库，支持实体关系构建和复杂查询"
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})
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# 创建知识库管理器
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work_dir = os.path.join(config.save_dir, "knowledge_base_data")
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knowledge_base = KnowledgeBaseManager(work_dir)
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from src.knowledge import GraphDatabase # noqa: E402
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graph_base = GraphDatabase()
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