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chunk_app.py 9.7KB

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  1. #
  2. # Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
  3. #
  4. # Licensed under the Apache License, Version 2.0 (the "License");
  5. # you may not use this file except in compliance with the License.
  6. # You may obtain a copy of the License at
  7. #
  8. # http://www.apache.org/licenses/LICENSE-2.0
  9. #
  10. # Unless required by applicable law or agreed to in writing, software
  11. # distributed under the License is distributed on an "AS IS" BASIS,
  12. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13. # See the License for the specific language governing permissions and
  14. # limitations under the License.
  15. #
  16. import datetime
  17. from flask import request
  18. from flask_login import login_required, current_user
  19. from elasticsearch_dsl import Q
  20. from rag.app.qa import rmPrefix, beAdoc
  21. from rag.nlp import search, huqie, retrievaler
  22. from rag.utils import ELASTICSEARCH, rmSpace
  23. from api.db import LLMType, ParserType
  24. from api.db.services.knowledgebase_service import KnowledgebaseService
  25. from api.db.services.llm_service import TenantLLMService
  26. from api.db.services.user_service import UserTenantService
  27. from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
  28. from api.db.services.document_service import DocumentService
  29. from api.settings import RetCode
  30. from api.utils.api_utils import get_json_result
  31. import hashlib
  32. import re
  33. @manager.route('/list', methods=['POST'])
  34. @login_required
  35. @validate_request("doc_id")
  36. def list():
  37. req = request.json
  38. doc_id = req["doc_id"]
  39. page = int(req.get("page", 1))
  40. size = int(req.get("size", 30))
  41. question = req.get("keywords", "")
  42. try:
  43. tenant_id = DocumentService.get_tenant_id(req["doc_id"])
  44. if not tenant_id:
  45. return get_data_error_result(retmsg="Tenant not found!")
  46. query = {
  47. "doc_ids": [doc_id], "page": page, "size": size, "question": question
  48. }
  49. if "available_int" in req:
  50. query["available_int"] = int(req["available_int"])
  51. sres = retrievaler.search(query, search.index_name(tenant_id))
  52. res = {"total": sres.total, "chunks": []}
  53. for id in sres.ids:
  54. d = {
  55. "chunk_id": id,
  56. "content_with_weight": rmSpace(sres.highlight[id]) if question else sres.field[id]["content_with_weight"],
  57. "doc_id": sres.field[id]["doc_id"],
  58. "docnm_kwd": sres.field[id]["docnm_kwd"],
  59. "important_kwd": sres.field[id].get("important_kwd", []),
  60. "img_id": sres.field[id].get("img_id", ""),
  61. "available_int": sres.field[id].get("available_int", 1),
  62. }
  63. res["chunks"].append(d)
  64. return get_json_result(data=res)
  65. except Exception as e:
  66. if str(e).find("not_found") > 0:
  67. return get_json_result(data=False, retmsg=f'Index not found!',
  68. retcode=RetCode.DATA_ERROR)
  69. return server_error_response(e)
  70. @manager.route('/get', methods=['GET'])
  71. @login_required
  72. def get():
  73. chunk_id = request.args["chunk_id"]
  74. try:
  75. tenants = UserTenantService.query(user_id=current_user.id)
  76. if not tenants:
  77. return get_data_error_result(retmsg="Tenant not found!")
  78. res = ELASTICSEARCH.get(
  79. chunk_id, search.index_name(
  80. tenants[0].tenant_id))
  81. if not res.get("found"):
  82. return server_error_response("Chunk not found")
  83. id = res["_id"]
  84. res = res["_source"]
  85. res["chunk_id"] = id
  86. k = []
  87. for n in res.keys():
  88. if re.search(r"(_vec$|_sm_|_tks|_ltks)", n):
  89. k.append(n)
  90. for n in k:
  91. del res[n]
  92. return get_json_result(data=res)
  93. except Exception as e:
  94. if str(e).find("NotFoundError") >= 0:
  95. return get_json_result(data=False, retmsg=f'Chunk not found!',
  96. retcode=RetCode.DATA_ERROR)
  97. return server_error_response(e)
  98. @manager.route('/set', methods=['POST'])
  99. @login_required
  100. @validate_request("doc_id", "chunk_id", "content_with_weight",
  101. "important_kwd")
  102. def set():
  103. req = request.json
  104. d = {"id": req["chunk_id"]}
  105. d["content_ltks"] = huqie.qie(req["content_with_weight"])
  106. d["content_sm_ltks"] = huqie.qieqie(d["content_ltks"])
  107. d["important_kwd"] = req["important_kwd"]
  108. d["important_tks"] = huqie.qie(" ".join(req["important_kwd"]))
  109. if "available_int" in req:
  110. d["available_int"] = req["available_int"]
  111. try:
  112. tenant_id = DocumentService.get_tenant_id(req["doc_id"])
  113. if not tenant_id:
  114. return get_data_error_result(retmsg="Tenant not found!")
  115. embd_mdl = TenantLLMService.model_instance(
  116. tenant_id, LLMType.EMBEDDING.value)
  117. e, doc = DocumentService.get_by_id(req["doc_id"])
  118. if not e:
  119. return get_data_error_result(retmsg="Document not found!")
  120. if doc.parser_id == ParserType.QA:
  121. arr = [t for t in re.split(r"[\n\t]", req["content_with_weight"]) if len(t)>1]
  122. if len(arr) != 2: return get_data_error_result(retmsg="Q&A must be separated by TAB/ENTER key.")
  123. q, a = rmPrefix(arr[0]), rmPrefix[arr[1]]
  124. d = beAdoc(d, arr[0], arr[1], not any([huqie.is_chinese(t) for t in q+a]))
  125. v, c = embd_mdl.encode([doc.name, req["content_with_weight"]])
  126. v = 0.1 * v[0] + 0.9 * v[1] if doc.parser_id != ParserType.QA else v[1]
  127. d["q_%d_vec" % len(v)] = v.tolist()
  128. ELASTICSEARCH.upsert([d], search.index_name(tenant_id))
  129. return get_json_result(data=True)
  130. except Exception as e:
  131. return server_error_response(e)
  132. @manager.route('/switch', methods=['POST'])
  133. @login_required
  134. @validate_request("chunk_ids", "available_int", "doc_id")
  135. def switch():
  136. req = request.json
  137. try:
  138. tenant_id = DocumentService.get_tenant_id(req["doc_id"])
  139. if not tenant_id:
  140. return get_data_error_result(retmsg="Tenant not found!")
  141. if not ELASTICSEARCH.upsert([{"id": i, "available_int": int(req["available_int"])} for i in req["chunk_ids"]],
  142. search.index_name(tenant_id)):
  143. return get_data_error_result(retmsg="Index updating failure")
  144. return get_json_result(data=True)
  145. except Exception as e:
  146. return server_error_response(e)
  147. @manager.route('/rm', methods=['POST'])
  148. @login_required
  149. @validate_request("chunk_ids")
  150. def rm():
  151. req = request.json
  152. try:
  153. if not ELASTICSEARCH.deleteByQuery(Q("ids", values=req["chunk_ids"]), search.index_name(current_user.id)):
  154. return get_data_error_result(retmsg="Index updating failure")
  155. return get_json_result(data=True)
  156. except Exception as e:
  157. return server_error_response(e)
  158. @manager.route('/create', methods=['POST'])
  159. @login_required
  160. @validate_request("doc_id", "content_with_weight")
  161. def create():
  162. req = request.json
  163. md5 = hashlib.md5()
  164. md5.update((req["content_with_weight"] + req["doc_id"]).encode("utf-8"))
  165. chunck_id = md5.hexdigest()
  166. d = {"id": chunck_id, "content_ltks": huqie.qie(req["content_with_weight"])}
  167. d["content_sm_ltks"] = huqie.qieqie(d["content_ltks"])
  168. d["important_kwd"] = req.get("important_kwd", [])
  169. d["important_tks"] = huqie.qie(" ".join(req.get("important_kwd", [])))
  170. d["create_time"] = str(datetime.datetime.now()).replace("T", " ")[:19]
  171. try:
  172. e, doc = DocumentService.get_by_id(req["doc_id"])
  173. if not e:
  174. return get_data_error_result(retmsg="Document not found!")
  175. d["kb_id"] = [doc.kb_id]
  176. d["docnm_kwd"] = doc.name
  177. d["doc_id"] = doc.id
  178. tenant_id = DocumentService.get_tenant_id(req["doc_id"])
  179. if not tenant_id:
  180. return get_data_error_result(retmsg="Tenant not found!")
  181. embd_mdl = TenantLLMService.model_instance(
  182. tenant_id, LLMType.EMBEDDING.value)
  183. v, c = embd_mdl.encode([doc.name, req["content_with_weight"]])
  184. DocumentService.increment_chunk_num(req["doc_id"], doc.kb_id, c, 1, 0)
  185. v = 0.1 * v[0] + 0.9 * v[1]
  186. d["q_%d_vec" % len(v)] = v.tolist()
  187. ELASTICSEARCH.upsert([d], search.index_name(tenant_id))
  188. return get_json_result(data={"chunk_id": chunck_id})
  189. except Exception as e:
  190. return server_error_response(e)
  191. @manager.route('/retrieval_test', methods=['POST'])
  192. @login_required
  193. @validate_request("kb_id", "question")
  194. def retrieval_test():
  195. req = request.json
  196. page = int(req.get("page", 1))
  197. size = int(req.get("size", 30))
  198. question = req["question"]
  199. kb_id = req["kb_id"]
  200. doc_ids = req.get("doc_ids", [])
  201. similarity_threshold = float(req.get("similarity_threshold", 0.2))
  202. vector_similarity_weight = float(req.get("vector_similarity_weight", 0.3))
  203. top = int(req.get("top", 1024))
  204. try:
  205. e, kb = KnowledgebaseService.get_by_id(kb_id)
  206. if not e:
  207. return get_data_error_result(retmsg="Knowledgebase not found!")
  208. embd_mdl = TenantLLMService.model_instance(
  209. kb.tenant_id, LLMType.EMBEDDING.value)
  210. ranks = retrievaler.retrieval(question, embd_mdl, kb.tenant_id, [kb_id], page, size, similarity_threshold,
  211. vector_similarity_weight, top, doc_ids)
  212. return get_json_result(data=ranks)
  213. except Exception as e:
  214. if str(e).find("not_found") > 0:
  215. return get_json_result(data=False, retmsg=f'Index not found!',
  216. retcode=RetCode.DATA_ERROR)
  217. return server_error_response(e)