Nelze vybrat více než 25 témat Téma musí začínat písmenem nebo číslem, může obsahovat pomlčky („-“) a může být dlouhé až 35 znaků.

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