zhanghongyu_0626
2945108f66
- Added new configuration for knowledge base root directory in `.env.example` and `settings.py`. - Implemented `find_products` method in `CoreReadOnlyRepository` for fuzzy product search based on user queries. - Introduced `search_cs_knowledge` function in `rag_service.py` to facilitate semantic search across new `fin_*` collections. - Updated document parsing to support Markdown and YAML front-matter for knowledge base entries. - Created multiple new FAQ and policy documents in the `data/kb_collections` directory to enrich the knowledge base. This update significantly improves the knowledge retrieval capabilities for customer service interactions, ensuring more relevant and accurate responses.
36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
"""快速测试 fin_* Milvus 检索（需先 build_collections 灌库）。"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[2]
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sys.path.insert(0, str(ROOT))
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from app.tool.embedding_tool import get_embedder
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from app.tool.milvus_tool import get_milvus_client
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e = get_embedder()
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m = get_milvus_client()
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try:
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v = e.embed("R3中风险产品有哪些")
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hits = m.search("fin_product", v, top_k=3)
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print("=== 产品检索 ===")
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for h in hits:
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print(f"score={h.get('score', 0):.4f} | {(h.get('chunk_text') or '')[:100]}")
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v2 = e.embed("开户需要什么材料")
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hits2 = m.search("fin_faq", v2, top_k=3)
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print("\n=== FAQ 检索 ===")
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for h in hits2:
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print(f"score={h.get('score', 0):.4f} | {(h.get('chunk_text') or '')[:100]}")
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v3 = e.embed("投资者适当性匹配规则")
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hits3 = m.search("fin_policy", v3, top_k=3)
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print("\n=== 政策检索 ===")
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for h in hits3:
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print(f"score={h.get('score', 0):.4f} | {(h.get('chunk_text') or '')[:100]}")
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finally:
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m.close()
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