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conversation_app.py 17KB

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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 json
  17. import re
  18. import traceback
  19. from copy import deepcopy
  20. from api.db.db_models import APIToken
  21. from api.db.services.conversation_service import ConversationService, structure_answer
  22. from api.db.services.user_service import UserTenantService
  23. from flask import request, Response
  24. from flask_login import login_required, current_user
  25. from api.db import LLMType
  26. from api.db.services.dialog_service import DialogService, chat, ask
  27. from api.db.services.knowledgebase_service import KnowledgebaseService
  28. from api.db.services.llm_service import LLMBundle, TenantService
  29. from api import settings
  30. from api.utils.api_utils import get_json_result
  31. from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
  32. from graphrag.general.mind_map_extractor import MindMapExtractor
  33. from rag.app.tag import label_question
  34. @manager.route('/set', methods=['POST']) # noqa: F821
  35. @login_required
  36. def set_conversation():
  37. req = request.json
  38. conv_id = req.get("conversation_id")
  39. is_new = req.get("is_new")
  40. del req["is_new"]
  41. if not is_new:
  42. del req["conversation_id"]
  43. try:
  44. if not ConversationService.update_by_id(conv_id, req):
  45. return get_data_error_result(message="Conversation not found!")
  46. e, conv = ConversationService.get_by_id(conv_id)
  47. if not e:
  48. return get_data_error_result(
  49. message="Fail to update a conversation!")
  50. conv = conv.to_dict()
  51. return get_json_result(data=conv)
  52. except Exception as e:
  53. return server_error_response(e)
  54. try:
  55. e, dia = DialogService.get_by_id(req["dialog_id"])
  56. if not e:
  57. return get_data_error_result(message="Dialog not found")
  58. conv = {
  59. "id": conv_id,
  60. "dialog_id": req["dialog_id"],
  61. "name": req.get("name", "New conversation"),
  62. "message": [{"role": "assistant", "content": dia.prompt_config["prologue"]}]
  63. }
  64. ConversationService.save(**conv)
  65. return get_json_result(data=conv)
  66. except Exception as e:
  67. return server_error_response(e)
  68. @manager.route('/get', methods=['GET']) # noqa: F821
  69. @login_required
  70. def get():
  71. conv_id = request.args["conversation_id"]
  72. try:
  73. e, conv = ConversationService.get_by_id(conv_id)
  74. if not e:
  75. return get_data_error_result(message="Conversation not found!")
  76. tenants = UserTenantService.query(user_id=current_user.id)
  77. avatar =None
  78. for tenant in tenants:
  79. dialog = DialogService.query(tenant_id=tenant.tenant_id, id=conv.dialog_id)
  80. if dialog and len(dialog)>0:
  81. avatar = dialog[0].icon
  82. break
  83. else:
  84. return get_json_result(
  85. data=False, message='Only owner of conversation authorized for this operation.',
  86. code=settings.RetCode.OPERATING_ERROR)
  87. def get_value(d, k1, k2):
  88. return d.get(k1, d.get(k2))
  89. for ref in conv.reference:
  90. if isinstance(ref, list):
  91. continue
  92. ref["chunks"] = [{
  93. "id": get_value(ck, "chunk_id", "id"),
  94. "content": get_value(ck, "content", "content_with_weight"),
  95. "document_id": get_value(ck, "doc_id", "document_id"),
  96. "document_name": get_value(ck, "docnm_kwd", "document_name"),
  97. "dataset_id": get_value(ck, "kb_id", "dataset_id"),
  98. "image_id": get_value(ck, "image_id", "img_id"),
  99. "positions": get_value(ck, "positions", "position_int"),
  100. } for ck in ref.get("chunks", [])]
  101. conv = conv.to_dict()
  102. conv["avatar"]=avatar
  103. return get_json_result(data=conv)
  104. except Exception as e:
  105. return server_error_response(e)
  106. @manager.route('/getsse/<dialog_id>', methods=['GET']) # type: ignore # noqa: F821
  107. def getsse(dialog_id):
  108. token = request.headers.get('Authorization').split()
  109. if len(token) != 2:
  110. return get_data_error_result(message='Authorization is not valid!"')
  111. token = token[1]
  112. objs = APIToken.query(beta=token)
  113. if not objs:
  114. return get_data_error_result(message='Authentication error: API key is invalid!"')
  115. try:
  116. e, conv = DialogService.get_by_id(dialog_id)
  117. if not e:
  118. return get_data_error_result(message="Dialog not found!")
  119. conv = conv.to_dict()
  120. conv["avatar"]= conv["icon"]
  121. del conv["icon"]
  122. return get_json_result(data=conv)
  123. except Exception as e:
  124. return server_error_response(e)
  125. @manager.route('/rm', methods=['POST']) # noqa: F821
  126. @login_required
  127. def rm():
  128. conv_ids = request.json["conversation_ids"]
  129. try:
  130. for cid in conv_ids:
  131. exist, conv = ConversationService.get_by_id(cid)
  132. if not exist:
  133. return get_data_error_result(message="Conversation not found!")
  134. tenants = UserTenantService.query(user_id=current_user.id)
  135. for tenant in tenants:
  136. if DialogService.query(tenant_id=tenant.tenant_id, id=conv.dialog_id):
  137. break
  138. else:
  139. return get_json_result(
  140. data=False, message='Only owner of conversation authorized for this operation.',
  141. code=settings.RetCode.OPERATING_ERROR)
  142. ConversationService.delete_by_id(cid)
  143. return get_json_result(data=True)
  144. except Exception as e:
  145. return server_error_response(e)
  146. @manager.route('/list', methods=['GET']) # noqa: F821
  147. @login_required
  148. def list_convsersation():
  149. dialog_id = request.args["dialog_id"]
  150. try:
  151. if not DialogService.query(tenant_id=current_user.id, id=dialog_id):
  152. return get_json_result(
  153. data=False, message='Only owner of dialog authorized for this operation.',
  154. code=settings.RetCode.OPERATING_ERROR)
  155. convs = ConversationService.query(
  156. dialog_id=dialog_id,
  157. order_by=ConversationService.model.create_time,
  158. reverse=True)
  159. convs = [d.to_dict() for d in convs]
  160. return get_json_result(data=convs)
  161. except Exception as e:
  162. return server_error_response(e)
  163. @manager.route('/completion', methods=['POST']) # noqa: F821
  164. @login_required
  165. @validate_request("conversation_id", "messages")
  166. def completion():
  167. req = request.json
  168. msg = []
  169. for m in req["messages"]:
  170. if m["role"] == "system":
  171. continue
  172. if m["role"] == "assistant" and not msg:
  173. continue
  174. msg.append(m)
  175. message_id = msg[-1].get("id")
  176. try:
  177. e, conv = ConversationService.get_by_id(req["conversation_id"])
  178. if not e:
  179. return get_data_error_result(message="Conversation not found!")
  180. conv.message = deepcopy(req["messages"])
  181. e, dia = DialogService.get_by_id(conv.dialog_id)
  182. if not e:
  183. return get_data_error_result(message="Dialog not found!")
  184. del req["conversation_id"]
  185. del req["messages"]
  186. if not conv.reference:
  187. conv.reference = []
  188. else:
  189. def get_value(d, k1, k2):
  190. return d.get(k1, d.get(k2))
  191. for ref in conv.reference:
  192. if isinstance(ref, list):
  193. continue
  194. ref["chunks"] = [{
  195. "id": get_value(ck, "chunk_id", "id"),
  196. "content": get_value(ck, "content", "content_with_weight"),
  197. "document_id": get_value(ck, "doc_id", "document_id"),
  198. "document_name": get_value(ck, "docnm_kwd", "document_name"),
  199. "dataset_id": get_value(ck, "kb_id", "dataset_id"),
  200. "image_id": get_value(ck, "image_id", "img_id"),
  201. "positions": get_value(ck, "positions", "position_int"),
  202. } for ck in ref.get("chunks", [])]
  203. if not conv.reference:
  204. conv.reference = []
  205. conv.reference.append({"chunks": [], "doc_aggs": []})
  206. def stream():
  207. nonlocal dia, msg, req, conv
  208. try:
  209. for ans in chat(dia, msg, True, **req):
  210. ans = structure_answer(conv, ans, message_id, conv.id)
  211. yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
  212. ConversationService.update_by_id(conv.id, conv.to_dict())
  213. except Exception as e:
  214. traceback.print_exc()
  215. yield "data:" + json.dumps({"code": 500, "message": str(e),
  216. "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
  217. ensure_ascii=False) + "\n\n"
  218. yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
  219. if req.get("stream", True):
  220. resp = Response(stream(), mimetype="text/event-stream")
  221. resp.headers.add_header("Cache-control", "no-cache")
  222. resp.headers.add_header("Connection", "keep-alive")
  223. resp.headers.add_header("X-Accel-Buffering", "no")
  224. resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
  225. return resp
  226. else:
  227. answer = None
  228. for ans in chat(dia, msg, **req):
  229. answer = structure_answer(conv, ans, message_id, req["conversation_id"])
  230. ConversationService.update_by_id(conv.id, conv.to_dict())
  231. break
  232. return get_json_result(data=answer)
  233. except Exception as e:
  234. return server_error_response(e)
  235. @manager.route('/tts', methods=['POST']) # noqa: F821
  236. @login_required
  237. def tts():
  238. req = request.json
  239. text = req["text"]
  240. tenants = TenantService.get_info_by(current_user.id)
  241. if not tenants:
  242. return get_data_error_result(message="Tenant not found!")
  243. tts_id = tenants[0]["tts_id"]
  244. if not tts_id:
  245. return get_data_error_result(message="No default TTS model is set")
  246. tts_mdl = LLMBundle(tenants[0]["tenant_id"], LLMType.TTS, tts_id)
  247. def stream_audio():
  248. try:
  249. for txt in re.split(r"[,。/《》?;:!\n\r:;]+", text):
  250. for chunk in tts_mdl.tts(txt):
  251. yield chunk
  252. except Exception as e:
  253. yield ("data:" + json.dumps({"code": 500, "message": str(e),
  254. "data": {"answer": "**ERROR**: " + str(e)}},
  255. ensure_ascii=False)).encode('utf-8')
  256. resp = Response(stream_audio(), mimetype="audio/mpeg")
  257. resp.headers.add_header("Cache-Control", "no-cache")
  258. resp.headers.add_header("Connection", "keep-alive")
  259. resp.headers.add_header("X-Accel-Buffering", "no")
  260. return resp
  261. @manager.route('/delete_msg', methods=['POST']) # noqa: F821
  262. @login_required
  263. @validate_request("conversation_id", "message_id")
  264. def delete_msg():
  265. req = request.json
  266. e, conv = ConversationService.get_by_id(req["conversation_id"])
  267. if not e:
  268. return get_data_error_result(message="Conversation not found!")
  269. conv = conv.to_dict()
  270. for i, msg in enumerate(conv["message"]):
  271. if req["message_id"] != msg.get("id", ""):
  272. continue
  273. assert conv["message"][i + 1]["id"] == req["message_id"]
  274. conv["message"].pop(i)
  275. conv["message"].pop(i)
  276. conv["reference"].pop(max(0, i // 2 - 1))
  277. break
  278. ConversationService.update_by_id(conv["id"], conv)
  279. return get_json_result(data=conv)
  280. @manager.route('/thumbup', methods=['POST']) # noqa: F821
  281. @login_required
  282. @validate_request("conversation_id", "message_id")
  283. def thumbup():
  284. req = request.json
  285. e, conv = ConversationService.get_by_id(req["conversation_id"])
  286. if not e:
  287. return get_data_error_result(message="Conversation not found!")
  288. up_down = req.get("set")
  289. feedback = req.get("feedback", "")
  290. conv = conv.to_dict()
  291. for i, msg in enumerate(conv["message"]):
  292. if req["message_id"] == msg.get("id", "") and msg.get("role", "") == "assistant":
  293. if up_down:
  294. msg["thumbup"] = True
  295. if "feedback" in msg:
  296. del msg["feedback"]
  297. else:
  298. msg["thumbup"] = False
  299. if feedback:
  300. msg["feedback"] = feedback
  301. break
  302. ConversationService.update_by_id(conv["id"], conv)
  303. return get_json_result(data=conv)
  304. @manager.route('/ask', methods=['POST']) # noqa: F821
  305. @login_required
  306. @validate_request("question", "kb_ids")
  307. def ask_about():
  308. req = request.json
  309. uid = current_user.id
  310. def stream():
  311. nonlocal req, uid
  312. try:
  313. for ans in ask(req["question"], req["kb_ids"], uid):
  314. yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
  315. except Exception as e:
  316. yield "data:" + json.dumps({"code": 500, "message": str(e),
  317. "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
  318. ensure_ascii=False) + "\n\n"
  319. yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
  320. resp = Response(stream(), mimetype="text/event-stream")
  321. resp.headers.add_header("Cache-control", "no-cache")
  322. resp.headers.add_header("Connection", "keep-alive")
  323. resp.headers.add_header("X-Accel-Buffering", "no")
  324. resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
  325. return resp
  326. @manager.route('/mindmap', methods=['POST']) # noqa: F821
  327. @login_required
  328. @validate_request("question", "kb_ids")
  329. def mindmap():
  330. req = request.json
  331. kb_ids = req["kb_ids"]
  332. e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
  333. if not e:
  334. return get_data_error_result(message="Knowledgebase not found!")
  335. embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING, llm_name=kb.embd_id)
  336. chat_mdl = LLMBundle(current_user.id, LLMType.CHAT)
  337. question = req["question"]
  338. ranks = settings.retrievaler.retrieval(question, embd_mdl, kb.tenant_id, kb_ids, 1, 12,
  339. 0.3, 0.3, aggs=False,
  340. rank_feature=label_question(question, [kb])
  341. )
  342. mindmap = MindMapExtractor(chat_mdl)
  343. mind_map = mindmap([c["content_with_weight"] for c in ranks["chunks"]]).output
  344. if "error" in mind_map:
  345. return server_error_response(Exception(mind_map["error"]))
  346. return get_json_result(data=mind_map)
  347. @manager.route('/related_questions', methods=['POST']) # noqa: F821
  348. @login_required
  349. @validate_request("question")
  350. def related_questions():
  351. req = request.json
  352. question = req["question"]
  353. chat_mdl = LLMBundle(current_user.id, LLMType.CHAT)
  354. prompt = """
  355. Objective: To generate search terms related to the user's search keywords, helping users find more valuable information.
  356. Instructions:
  357. - Based on the keywords provided by the user, generate 5-10 related search terms.
  358. - Each search term should be directly or indirectly related to the keyword, guiding the user to find more valuable information.
  359. - Use common, general terms as much as possible, avoiding obscure words or technical jargon.
  360. - Keep the term length between 2-4 words, concise and clear.
  361. - DO NOT translate, use the language of the original keywords.
  362. ### Example:
  363. Keywords: Chinese football
  364. Related search terms:
  365. 1. Current status of Chinese football
  366. 2. Reform of Chinese football
  367. 3. Youth training of Chinese football
  368. 4. Chinese football in the Asian Cup
  369. 5. Chinese football in the World Cup
  370. Reason:
  371. - When searching, users often only use one or two keywords, making it difficult to fully express their information needs.
  372. - Generating related search terms can help users dig deeper into relevant information and improve search efficiency.
  373. - At the same time, related terms can also help search engines better understand user needs and return more accurate search results.
  374. """
  375. ans = chat_mdl.chat(prompt, [{"role": "user", "content": f"""
  376. Keywords: {question}
  377. Related search terms:
  378. """}], {"temperature": 0.9})
  379. return get_json_result(data=[re.sub(r"^[0-9]\. ", "", a) for a in ans.split("\n") if re.match(r"^[0-9]\. ", a)])