test_es.py 1.1 KB

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  1. from agent.core.es import es
  2. from agent.core.vector import get_embeddings
  3. query = '职业:电动机加工制造,投向:电动机加工制造,用途:电动机加工制造'
  4. resp_bm25 = es.search(
  5. index='ai-tagging',
  6. size=10,
  7. query={
  8. "multi_match": {
  9. "query": query,
  10. "fields": ["tag_path", "tag_remark", "tag_prompt"]
  11. }
  12. }
  13. )
  14. for rank, hit in enumerate(resp_bm25['hits']['hits'], start=1):
  15. hit["_source"]["tag_vector"] = None
  16. doc_id = hit['_id']
  17. tag_nm = hit['_source']['tag_name']
  18. print(doc_id,tag_nm)
  19. print('-----------------')
  20. query_vector = get_embeddings([query])[0]
  21. resp_vector = es.search(
  22. index='ai-tagging',
  23. size=10,
  24. knn={
  25. "field": "tag_vector",
  26. "query_vector": query_vector,
  27. "k": 10,
  28. "num_candidates": 100
  29. }
  30. )
  31. for rank, hit in enumerate(resp_vector['hits']['hits'], start=1):
  32. hit["_source"]["tag_vector"] = None
  33. doc_id = hit['_id']
  34. tag_nm = hit['_source']['tag_name']
  35. print(doc_id,tag_nm)