You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

conversation_app.py 17KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430
  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, TenantLLMService
  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.mind_map_extractor import MindMapExtractor
  33. @manager.route('/set', methods=['POST']) # noqa: F821
  34. @login_required
  35. def set_conversation():
  36. req = request.json
  37. conv_id = req.get("conversation_id")
  38. is_new = req.get("is_new")
  39. del req["is_new"]
  40. if not is_new:
  41. del req["conversation_id"]
  42. try:
  43. if not ConversationService.update_by_id(conv_id, req):
  44. return get_data_error_result(message="Conversation not found!")
  45. e, conv = ConversationService.get_by_id(conv_id)
  46. if not e:
  47. return get_data_error_result(
  48. message="Fail to update a conversation!")
  49. conv = conv.to_dict()
  50. return get_json_result(data=conv)
  51. except Exception as e:
  52. return server_error_response(e)
  53. try:
  54. e, dia = DialogService.get_by_id(req["dialog_id"])
  55. if not e:
  56. return get_data_error_result(message="Dialog not found")
  57. conv = {
  58. "id": conv_id,
  59. "dialog_id": req["dialog_id"],
  60. "name": req.get("name", "New conversation"),
  61. "message": [{"role": "assistant", "content": dia.prompt_config["prologue"]}]
  62. }
  63. ConversationService.save(**conv)
  64. e, conv = ConversationService.get_by_id(conv["id"])
  65. if not e:
  66. return get_data_error_result(message="Fail to new a conversation!")
  67. conv = conv.to_dict()
  68. return get_json_result(data=conv)
  69. except Exception as e:
  70. return server_error_response(e)
  71. @manager.route('/get', methods=['GET']) # noqa: F821
  72. @login_required
  73. def get():
  74. conv_id = request.args["conversation_id"]
  75. try:
  76. e, conv = ConversationService.get_by_id(conv_id)
  77. if not e:
  78. return get_data_error_result(message="Conversation not found!")
  79. tenants = UserTenantService.query(user_id=current_user.id)
  80. avatar =None
  81. for tenant in tenants:
  82. dialog = DialogService.query(tenant_id=tenant.tenant_id, id=conv.dialog_id)
  83. if dialog and len(dialog)>0:
  84. avatar = dialog[0].icon
  85. break
  86. else:
  87. return get_json_result(
  88. data=False, message='Only owner of conversation authorized for this operation.',
  89. code=settings.RetCode.OPERATING_ERROR)
  90. def get_value(d, k1, k2):
  91. return d.get(k1, d.get(k2))
  92. for ref in conv.reference:
  93. if isinstance(ref, list):
  94. continue
  95. ref["chunks"] = [{
  96. "id": get_value(ck, "chunk_id", "id"),
  97. "content": get_value(ck, "content", "content_with_weight"),
  98. "document_id": get_value(ck, "doc_id", "document_id"),
  99. "document_name": get_value(ck, "docnm_kwd", "document_name"),
  100. "dataset_id": get_value(ck, "kb_id", "dataset_id"),
  101. "image_id": get_value(ck, "image_id", "img_id"),
  102. "positions": get_value(ck, "positions", "position_int"),
  103. } for ck in ref.get("chunks", [])]
  104. conv = conv.to_dict()
  105. conv["avatar"]=avatar
  106. return get_json_result(data=conv)
  107. except Exception as e:
  108. return server_error_response(e)
  109. @manager.route('/getsse/<dialog_id>', methods=['GET']) # type: ignore # noqa: F821
  110. def getsse(dialog_id):
  111. token = request.headers.get('Authorization').split()
  112. if len(token) != 2:
  113. return get_data_error_result(message='Authorization is not valid!"')
  114. token = token[1]
  115. objs = APIToken.query(beta=token)
  116. if not objs:
  117. return get_data_error_result(message='Token is not valid!"')
  118. try:
  119. e, conv = DialogService.get_by_id(dialog_id)
  120. if not e:
  121. return get_data_error_result(message="Dialog not found!")
  122. conv = conv.to_dict()
  123. conv["avatar"]= conv["icon"]
  124. del conv["icon"]
  125. return get_json_result(data=conv)
  126. except Exception as e:
  127. return server_error_response(e)
  128. @manager.route('/rm', methods=['POST']) # noqa: F821
  129. @login_required
  130. def rm():
  131. conv_ids = request.json["conversation_ids"]
  132. try:
  133. for cid in conv_ids:
  134. exist, conv = ConversationService.get_by_id(cid)
  135. if not exist:
  136. return get_data_error_result(message="Conversation not found!")
  137. tenants = UserTenantService.query(user_id=current_user.id)
  138. for tenant in tenants:
  139. if DialogService.query(tenant_id=tenant.tenant_id, id=conv.dialog_id):
  140. break
  141. else:
  142. return get_json_result(
  143. data=False, message='Only owner of conversation authorized for this operation.',
  144. code=settings.RetCode.OPERATING_ERROR)
  145. ConversationService.delete_by_id(cid)
  146. return get_json_result(data=True)
  147. except Exception as e:
  148. return server_error_response(e)
  149. @manager.route('/list', methods=['GET']) # noqa: F821
  150. @login_required
  151. def list_convsersation():
  152. dialog_id = request.args["dialog_id"]
  153. try:
  154. if not DialogService.query(tenant_id=current_user.id, id=dialog_id):
  155. return get_json_result(
  156. data=False, message='Only owner of dialog authorized for this operation.',
  157. code=settings.RetCode.OPERATING_ERROR)
  158. convs = ConversationService.query(
  159. dialog_id=dialog_id,
  160. order_by=ConversationService.model.create_time,
  161. reverse=True)
  162. convs = [d.to_dict() for d in convs]
  163. return get_json_result(data=convs)
  164. except Exception as e:
  165. return server_error_response(e)
  166. @manager.route('/completion', methods=['POST']) # noqa: F821
  167. @login_required
  168. @validate_request("conversation_id", "messages")
  169. def completion():
  170. req = request.json
  171. msg = []
  172. for m in req["messages"]:
  173. if m["role"] == "system":
  174. continue
  175. if m["role"] == "assistant" and not msg:
  176. continue
  177. msg.append(m)
  178. message_id = msg[-1].get("id")
  179. try:
  180. e, conv = ConversationService.get_by_id(req["conversation_id"])
  181. if not e:
  182. return get_data_error_result(message="Conversation not found!")
  183. conv.message = deepcopy(req["messages"])
  184. e, dia = DialogService.get_by_id(conv.dialog_id)
  185. if not e:
  186. return get_data_error_result(message="Dialog not found!")
  187. del req["conversation_id"]
  188. del req["messages"]
  189. if not conv.reference:
  190. conv.reference = []
  191. else:
  192. def get_value(d, k1, k2):
  193. return d.get(k1, d.get(k2))
  194. for ref in conv.reference:
  195. if isinstance(ref, list):
  196. continue
  197. ref["chunks"] = [{
  198. "id": get_value(ck, "chunk_id", "id"),
  199. "content": get_value(ck, "content", "content_with_weight"),
  200. "document_id": get_value(ck, "doc_id", "document_id"),
  201. "document_name": get_value(ck, "docnm_kwd", "document_name"),
  202. "dataset_id": get_value(ck, "kb_id", "dataset_id"),
  203. "image_id": get_value(ck, "image_id", "img_id"),
  204. "positions": get_value(ck, "positions", "position_int"),
  205. } for ck in ref.get("chunks", [])]
  206. if not conv.reference:
  207. conv.reference = []
  208. conv.reference.append({"chunks": [], "doc_aggs": []})
  209. def stream():
  210. nonlocal dia, msg, req, conv
  211. try:
  212. for ans in chat(dia, msg, True, **req):
  213. ans = structure_answer(conv, ans, message_id, conv.id)
  214. yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
  215. ConversationService.update_by_id(conv.id, conv.to_dict())
  216. except Exception as e:
  217. traceback.print_exc()
  218. yield "data:" + json.dumps({"code": 500, "message": str(e),
  219. "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
  220. ensure_ascii=False) + "\n\n"
  221. yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
  222. if req.get("stream", True):
  223. resp = Response(stream(), mimetype="text/event-stream")
  224. resp.headers.add_header("Cache-control", "no-cache")
  225. resp.headers.add_header("Connection", "keep-alive")
  226. resp.headers.add_header("X-Accel-Buffering", "no")
  227. resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
  228. return resp
  229. else:
  230. answer = None
  231. for ans in chat(dia, msg, **req):
  232. answer = structure_answer(conv, ans, message_id, req["conversation_id"])
  233. ConversationService.update_by_id(conv.id, conv.to_dict())
  234. break
  235. return get_json_result(data=answer)
  236. except Exception as e:
  237. return server_error_response(e)
  238. @manager.route('/tts', methods=['POST']) # noqa: F821
  239. @login_required
  240. def tts():
  241. req = request.json
  242. text = req["text"]
  243. tenants = TenantService.get_info_by(current_user.id)
  244. if not tenants:
  245. return get_data_error_result(message="Tenant not found!")
  246. tts_id = tenants[0]["tts_id"]
  247. if not tts_id:
  248. return get_data_error_result(message="No default TTS model is set")
  249. tts_mdl = LLMBundle(tenants[0]["tenant_id"], LLMType.TTS, tts_id)
  250. def stream_audio():
  251. try:
  252. for txt in re.split(r"[,。/《》?;:!\n\r:;]+", text):
  253. for chunk in tts_mdl.tts(txt):
  254. yield chunk
  255. except Exception as e:
  256. yield ("data:" + json.dumps({"code": 500, "message": str(e),
  257. "data": {"answer": "**ERROR**: " + str(e)}},
  258. ensure_ascii=False)).encode('utf-8')
  259. resp = Response(stream_audio(), mimetype="audio/mpeg")
  260. resp.headers.add_header("Cache-Control", "no-cache")
  261. resp.headers.add_header("Connection", "keep-alive")
  262. resp.headers.add_header("X-Accel-Buffering", "no")
  263. return resp
  264. @manager.route('/delete_msg', methods=['POST']) # noqa: F821
  265. @login_required
  266. @validate_request("conversation_id", "message_id")
  267. def delete_msg():
  268. req = request.json
  269. e, conv = ConversationService.get_by_id(req["conversation_id"])
  270. if not e:
  271. return get_data_error_result(message="Conversation not found!")
  272. conv = conv.to_dict()
  273. for i, msg in enumerate(conv["message"]):
  274. if req["message_id"] != msg.get("id", ""):
  275. continue
  276. assert conv["message"][i + 1]["id"] == req["message_id"]
  277. conv["message"].pop(i)
  278. conv["message"].pop(i)
  279. conv["reference"].pop(max(0, i // 2 - 1))
  280. break
  281. ConversationService.update_by_id(conv["id"], conv)
  282. return get_json_result(data=conv)
  283. @manager.route('/thumbup', methods=['POST']) # noqa: F821
  284. @login_required
  285. @validate_request("conversation_id", "message_id")
  286. def thumbup():
  287. req = request.json
  288. e, conv = ConversationService.get_by_id(req["conversation_id"])
  289. if not e:
  290. return get_data_error_result(message="Conversation not found!")
  291. up_down = req.get("set")
  292. feedback = req.get("feedback", "")
  293. conv = conv.to_dict()
  294. for i, msg in enumerate(conv["message"]):
  295. if req["message_id"] == msg.get("id", "") and msg.get("role", "") == "assistant":
  296. if up_down:
  297. msg["thumbup"] = True
  298. if "feedback" in msg:
  299. del msg["feedback"]
  300. else:
  301. msg["thumbup"] = False
  302. if feedback:
  303. msg["feedback"] = feedback
  304. break
  305. ConversationService.update_by_id(conv["id"], conv)
  306. return get_json_result(data=conv)
  307. @manager.route('/ask', methods=['POST']) # noqa: F821
  308. @login_required
  309. @validate_request("question", "kb_ids")
  310. def ask_about():
  311. req = request.json
  312. uid = current_user.id
  313. def stream():
  314. nonlocal req, uid
  315. try:
  316. for ans in ask(req["question"], req["kb_ids"], uid):
  317. yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
  318. except Exception as e:
  319. yield "data:" + json.dumps({"code": 500, "message": str(e),
  320. "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
  321. ensure_ascii=False) + "\n\n"
  322. yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
  323. resp = Response(stream(), mimetype="text/event-stream")
  324. resp.headers.add_header("Cache-control", "no-cache")
  325. resp.headers.add_header("Connection", "keep-alive")
  326. resp.headers.add_header("X-Accel-Buffering", "no")
  327. resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
  328. return resp
  329. @manager.route('/mindmap', methods=['POST']) # noqa: F821
  330. @login_required
  331. @validate_request("question", "kb_ids")
  332. def mindmap():
  333. req = request.json
  334. kb_ids = req["kb_ids"]
  335. e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
  336. if not e:
  337. return get_data_error_result(message="Knowledgebase not found!")
  338. embd_mdl = TenantLLMService.model_instance(
  339. kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
  340. chat_mdl = LLMBundle(current_user.id, LLMType.CHAT)
  341. ranks = settings.retrievaler.retrieval(req["question"], embd_mdl, kb.tenant_id, kb_ids, 1, 12,
  342. 0.3, 0.3, aggs=False)
  343. mindmap = MindMapExtractor(chat_mdl)
  344. mind_map = mindmap([c["content_with_weight"] for c in ranks["chunks"]]).output
  345. if "error" in mind_map:
  346. return server_error_response(Exception(mind_map["error"]))
  347. return get_json_result(data=mind_map)
  348. @manager.route('/related_questions', methods=['POST']) # noqa: F821
  349. @login_required
  350. @validate_request("question")
  351. def related_questions():
  352. req = request.json
  353. question = req["question"]
  354. chat_mdl = LLMBundle(current_user.id, LLMType.CHAT)
  355. prompt = """
  356. Objective: To generate search terms related to the user's search keywords, helping users find more valuable information.
  357. Instructions:
  358. - Based on the keywords provided by the user, generate 5-10 related search terms.
  359. - Each search term should be directly or indirectly related to the keyword, guiding the user to find more valuable information.
  360. - Use common, general terms as much as possible, avoiding obscure words or technical jargon.
  361. - Keep the term length between 2-4 words, concise and clear.
  362. - DO NOT translate, use the language of the original keywords.
  363. ### Example:
  364. Keywords: Chinese football
  365. Related search terms:
  366. 1. Current status of Chinese football
  367. 2. Reform of Chinese football
  368. 3. Youth training of Chinese football
  369. 4. Chinese football in the Asian Cup
  370. 5. Chinese football in the World Cup
  371. Reason:
  372. - When searching, users often only use one or two keywords, making it difficult to fully express their information needs.
  373. - Generating related search terms can help users dig deeper into relevant information and improve search efficiency.
  374. - At the same time, related terms can also help search engines better understand user needs and return more accurate search results.
  375. """
  376. ans = chat_mdl.chat(prompt, [{"role": "user", "content": f"""
  377. Keywords: {question}
  378. Related search terms:
  379. """}], {"temperature": 0.9})
  380. return get_json_result(data=[re.sub(r"^[0-9]\. ", "", a) for a in ans.split("\n") if re.match(r"^[0-9]\. ", a)])