graph_router.py 2.9 KB

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  1. import sys,os
  2. from agent.cdss.capbility import CDSSCapability
  3. from agent.cdss.models.schemas import CDSSInput, CDSSInt, CDSSText
  4. from model.response import StandardResponse
  5. current_path = os.getcwd()
  6. sys.path.append(current_path)
  7. import time
  8. from fastapi import APIRouter, Depends, Query
  9. from typing import Optional, List
  10. import sys
  11. sys.path.append('..')
  12. from utils.agent import call_chat_api,get_conversation_id
  13. import json
  14. router = APIRouter(prefix="/graph", tags=["Knowledge Graph"])
  15. @router.get("/nodes/recommend", response_model=StandardResponse)
  16. async def recommend(
  17. chief: str,
  18. sex: Optional[str] = None,
  19. age: Optional[int] = None,
  20. department: Optional[str] = None,
  21. ):
  22. start_time = time.time()
  23. app_id = "256fd853-60b0-4357-b11b-8114b4e90ae0"
  24. conversation_id = get_conversation_id(app_id)
  25. result = call_chat_api(app_id, conversation_id, chief)
  26. json_data = json.loads(result)
  27. keyword = " ".join(json_data["symptoms"])
  28. result = await neighbor_search(keyword=keyword,sex=sex,age=age, neighbor_type='Check', limit=10)
  29. end_time = time.time()
  30. print(f"recommend执行完成,耗时:{end_time - start_time:.2f}秒")
  31. return result;
  32. @router.get("/nodes/neighbor_search", response_model=StandardResponse)
  33. async def neighbor_search(
  34. keyword: str = Query(..., min_length=2),
  35. sex: Optional[str] = None,
  36. age: Optional[int] = None,
  37. department: Optional[str] = None,
  38. limit: int = Query(10, ge=1, le=100),
  39. node_type: Optional[str] = Query(None),
  40. neighbor_type: Optional[str] = Query(None),
  41. min_degree: Optional[int] = Query(None)
  42. ):
  43. """
  44. 根据关键词和属性过滤条件搜索图谱节点
  45. """
  46. try:
  47. print(f"开始执行neighbor_search,参数:keyword={keyword}, limit={limit}, node_type={node_type}, neighbor_type={neighbor_type}, min_degree={min_degree}")
  48. keywords = keyword.split(" ")
  49. record = CDSSInput(
  50. pat_age=CDSSInt(type="month", value=age),
  51. pat_sex=CDSSText(type="sex", value=sex),
  52. chief_complaint=keywords,
  53. department=CDSSText(type='department', value=department)
  54. )
  55. # 使用从main.py导入的capability实例处理CDSS逻辑
  56. output = capability.process(input=record)
  57. output.diagnosis.value = [{"name":key,"score":value["score"],"count":value["count"],
  58. "hasInfo": 1,
  59. "type": 1} for key,value in output.diagnosis.value.items()]
  60. return StandardResponse(
  61. success=True,
  62. data={"可能诊断":output.diagnosis.value,"症状":keywords,"推荐检验":output.checks.value}
  63. )
  64. except Exception as e:
  65. print(e)
  66. raise e
  67. return StandardResponse(
  68. success=False,
  69. error_code=500,
  70. error_msg=str(e)
  71. )
  72. capability = CDSSCapability()
  73. #def get_capability():
  74. #from main import capability
  75. #return capability
  76. graph_router = router