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chunk_app.py 10KB

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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
  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, retrievaler
  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. e, doc = DocumentService.get_by_id(doc_id)
  47. if not e:
  48. return get_data_error_result(retmsg="Document not found!")
  49. query = {
  50. "doc_ids": [doc_id], "page": page, "size": size, "question": question
  51. }
  52. if "available_int" in req:
  53. query["available_int"] = int(req["available_int"])
  54. sres = retrievaler.search(query, search.index_name(tenant_id))
  55. res = {"total": sres.total, "chunks": [], "doc": doc.to_dict()}
  56. for id in sres.ids:
  57. d = {
  58. "chunk_id": id,
  59. "content_with_weight": rmSpace(sres.highlight[id]) if question else sres.field[id].get("content_with_weight", ""),
  60. "doc_id": sres.field[id]["doc_id"],
  61. "docnm_kwd": sres.field[id]["docnm_kwd"],
  62. "important_kwd": sres.field[id].get("important_kwd", []),
  63. "img_id": sres.field[id].get("img_id", ""),
  64. "available_int": sres.field[id].get("available_int", 1),
  65. }
  66. res["chunks"].append(d)
  67. return get_json_result(data=res)
  68. except Exception as e:
  69. if str(e).find("not_found") > 0:
  70. return get_json_result(data=False, retmsg=f'Index not found!',
  71. retcode=RetCode.DATA_ERROR)
  72. return server_error_response(e)
  73. @manager.route('/get', methods=['GET'])
  74. @login_required
  75. def get():
  76. chunk_id = request.args["chunk_id"]
  77. try:
  78. tenants = UserTenantService.query(user_id=current_user.id)
  79. if not tenants:
  80. return get_data_error_result(retmsg="Tenant not found!")
  81. res = ELASTICSEARCH.get(
  82. chunk_id, search.index_name(
  83. tenants[0].tenant_id))
  84. if not res.get("found"):
  85. return server_error_response("Chunk not found")
  86. id = res["_id"]
  87. res = res["_source"]
  88. res["chunk_id"] = id
  89. k = []
  90. for n in res.keys():
  91. if re.search(r"(_vec$|_sm_|_tks|_ltks)", n):
  92. k.append(n)
  93. for n in k:
  94. del res[n]
  95. return get_json_result(data=res)
  96. except Exception as e:
  97. if str(e).find("NotFoundError") >= 0:
  98. return get_json_result(data=False, retmsg=f'Chunk not found!',
  99. retcode=RetCode.DATA_ERROR)
  100. return server_error_response(e)
  101. @manager.route('/set', methods=['POST'])
  102. @login_required
  103. @validate_request("doc_id", "chunk_id", "content_with_weight",
  104. "important_kwd")
  105. def set():
  106. req = request.json
  107. d = {"id": req["chunk_id"], "content_with_weight": req["content_with_weight"]}
  108. d["content_ltks"] = huqie.qie(req["content_with_weight"])
  109. d["content_sm_ltks"] = huqie.qieqie(d["content_ltks"])
  110. d["important_kwd"] = req["important_kwd"]
  111. d["important_tks"] = huqie.qie(" ".join(req["important_kwd"]))
  112. if "available_int" in req:
  113. d["available_int"] = req["available_int"]
  114. try:
  115. tenant_id = DocumentService.get_tenant_id(req["doc_id"])
  116. if not tenant_id:
  117. return get_data_error_result(retmsg="Tenant not found!")
  118. embd_mdl = TenantLLMService.model_instance(
  119. tenant_id, LLMType.EMBEDDING.value)
  120. e, doc = DocumentService.get_by_id(req["doc_id"])
  121. if not e:
  122. return get_data_error_result(retmsg="Document not found!")
  123. if doc.parser_id == ParserType.QA:
  124. arr = [t for t in re.split(r"[\n\t]", req["content_with_weight"]) if len(t)>1]
  125. if len(arr) != 2: return get_data_error_result(retmsg="Q&A must be separated by TAB/ENTER key.")
  126. q, a = rmPrefix(arr[0]), rmPrefix[arr[1]]
  127. d = beAdoc(d, arr[0], arr[1], not any([huqie.is_chinese(t) for t in q+a]))
  128. v, c = embd_mdl.encode([doc.name, req["content_with_weight"]])
  129. v = 0.1 * v[0] + 0.9 * v[1] if doc.parser_id != ParserType.QA else v[1]
  130. d["q_%d_vec" % len(v)] = v.tolist()
  131. ELASTICSEARCH.upsert([d], search.index_name(tenant_id))
  132. return get_json_result(data=True)
  133. except Exception as e:
  134. return server_error_response(e)
  135. @manager.route('/switch', methods=['POST'])
  136. @login_required
  137. @validate_request("chunk_ids", "available_int", "doc_id")
  138. def switch():
  139. req = request.json
  140. try:
  141. tenant_id = DocumentService.get_tenant_id(req["doc_id"])
  142. if not tenant_id:
  143. return get_data_error_result(retmsg="Tenant not found!")
  144. if not ELASTICSEARCH.upsert([{"id": i, "available_int": int(req["available_int"])} for i in req["chunk_ids"]],
  145. search.index_name(tenant_id)):
  146. return get_data_error_result(retmsg="Index updating failure")
  147. return get_json_result(data=True)
  148. except Exception as e:
  149. return server_error_response(e)
  150. @manager.route('/rm', methods=['POST'])
  151. @login_required
  152. @validate_request("chunk_ids")
  153. def rm():
  154. req = request.json
  155. try:
  156. if not ELASTICSEARCH.deleteByQuery(Q("ids", values=req["chunk_ids"]), search.index_name(current_user.id)):
  157. return get_data_error_result(retmsg="Index updating failure")
  158. return get_json_result(data=True)
  159. except Exception as e:
  160. return server_error_response(e)
  161. @manager.route('/create', methods=['POST'])
  162. @login_required
  163. @validate_request("doc_id", "content_with_weight")
  164. def create():
  165. req = request.json
  166. md5 = hashlib.md5()
  167. md5.update((req["content_with_weight"] + req["doc_id"]).encode("utf-8"))
  168. chunck_id = md5.hexdigest()
  169. d = {"id": chunck_id, "content_ltks": huqie.qie(req["content_with_weight"]), "content_with_weight": req["content_with_weight"]}
  170. d["content_sm_ltks"] = huqie.qieqie(d["content_ltks"])
  171. d["important_kwd"] = req.get("important_kwd", [])
  172. d["important_tks"] = huqie.qie(" ".join(req.get("important_kwd", [])))
  173. d["create_time"] = str(datetime.datetime.now()).replace("T", " ")[:19]
  174. d["create_timestamp_flt"] = datetime.datetime.now().timestamp()
  175. try:
  176. e, doc = DocumentService.get_by_id(req["doc_id"])
  177. if not e:
  178. return get_data_error_result(retmsg="Document not found!")
  179. d["kb_id"] = [doc.kb_id]
  180. d["docnm_kwd"] = doc.name
  181. d["doc_id"] = doc.id
  182. tenant_id = DocumentService.get_tenant_id(req["doc_id"])
  183. if not tenant_id:
  184. return get_data_error_result(retmsg="Tenant not found!")
  185. embd_mdl = TenantLLMService.model_instance(
  186. tenant_id, LLMType.EMBEDDING.value)
  187. v, c = embd_mdl.encode([doc.name, req["content_with_weight"]])
  188. DocumentService.increment_chunk_num(req["doc_id"], doc.kb_id, c, 1, 0)
  189. v = 0.1 * v[0] + 0.9 * v[1]
  190. d["q_%d_vec" % len(v)] = v.tolist()
  191. ELASTICSEARCH.upsert([d], search.index_name(tenant_id))
  192. return get_json_result(data={"chunk_id": chunck_id})
  193. except Exception as e:
  194. return server_error_response(e)
  195. @manager.route('/retrieval_test', methods=['POST'])
  196. @login_required
  197. @validate_request("kb_id", "question")
  198. def retrieval_test():
  199. req = request.json
  200. page = int(req.get("page", 1))
  201. size = int(req.get("size", 30))
  202. question = req["question"]
  203. kb_id = req["kb_id"]
  204. doc_ids = req.get("doc_ids", [])
  205. similarity_threshold = float(req.get("similarity_threshold", 0.2))
  206. vector_similarity_weight = float(req.get("vector_similarity_weight", 0.3))
  207. top = int(req.get("top_k", 1024))
  208. try:
  209. e, kb = KnowledgebaseService.get_by_id(kb_id)
  210. if not e:
  211. return get_data_error_result(retmsg="Knowledgebase not found!")
  212. embd_mdl = TenantLLMService.model_instance(
  213. kb.tenant_id, LLMType.EMBEDDING.value)
  214. ranks = retrievaler.retrieval(question, embd_mdl, kb.tenant_id, [kb_id], page, size, similarity_threshold,
  215. vector_similarity_weight, top, doc_ids)
  216. for c in ranks["chunks"]:
  217. if "vector" in c:
  218. del c["vector"]
  219. return get_json_result(data=ranks)
  220. except Exception as e:
  221. if str(e).find("not_found") > 0:
  222. return get_json_result(data=False, retmsg=f'Index not found!',
  223. retcode=RetCode.DATA_ERROR)
  224. return server_error_response(e)