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llm_app.py 13KB

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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 logging
  17. import json
  18. import os
  19. from flask import request
  20. from flask_login import login_required, current_user
  21. from api.db.services.llm_service import LLMFactoriesService, TenantLLMService, LLMService
  22. from api import settings
  23. from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
  24. from api.db import StatusEnum, LLMType
  25. from api.db.db_models import TenantLLM
  26. from api.utils.api_utils import get_json_result
  27. from api.utils.file_utils import get_project_base_directory
  28. from rag.llm import EmbeddingModel, ChatModel, RerankModel, CvModel, TTSModel
  29. @manager.route('/factories', methods=['GET']) # noqa: F821
  30. @login_required
  31. def factories():
  32. try:
  33. fac = LLMFactoriesService.get_all()
  34. fac = [f.to_dict() for f in fac if f.name not in ["Youdao", "FastEmbed", "BAAI"]]
  35. llms = LLMService.get_all()
  36. mdl_types = {}
  37. for m in llms:
  38. if m.status != StatusEnum.VALID.value:
  39. continue
  40. if m.fid not in mdl_types:
  41. mdl_types[m.fid] = set([])
  42. mdl_types[m.fid].add(m.model_type)
  43. for f in fac:
  44. f["model_types"] = list(mdl_types.get(f["name"], [LLMType.CHAT, LLMType.EMBEDDING, LLMType.RERANK,
  45. LLMType.IMAGE2TEXT, LLMType.SPEECH2TEXT, LLMType.TTS]))
  46. return get_json_result(data=fac)
  47. except Exception as e:
  48. return server_error_response(e)
  49. @manager.route('/set_api_key', methods=['POST']) # noqa: F821
  50. @login_required
  51. @validate_request("llm_factory", "api_key")
  52. def set_api_key():
  53. req = request.json
  54. # test if api key works
  55. chat_passed, embd_passed, rerank_passed = False, False, False
  56. factory = req["llm_factory"]
  57. msg = ""
  58. for llm in LLMService.query(fid=factory):
  59. if not embd_passed and llm.model_type == LLMType.EMBEDDING.value:
  60. mdl = EmbeddingModel[factory](
  61. req["api_key"], llm.llm_name, base_url=req.get("base_url"))
  62. try:
  63. arr, tc = mdl.encode(["Test if the api key is available"])
  64. if len(arr[0]) == 0:
  65. raise Exception("Fail")
  66. embd_passed = True
  67. except Exception as e:
  68. msg += f"\nFail to access embedding model({llm.llm_name}) using this api key." + str(e)
  69. elif not chat_passed and llm.model_type == LLMType.CHAT.value:
  70. mdl = ChatModel[factory](
  71. req["api_key"], llm.llm_name, base_url=req.get("base_url"))
  72. try:
  73. m, tc = mdl.chat(None, [{"role": "user", "content": "Hello! How are you doing!"}],
  74. {"temperature": 0.9, 'max_tokens': 50})
  75. if m.find("**ERROR**") >= 0:
  76. raise Exception(m)
  77. chat_passed = True
  78. except Exception as e:
  79. msg += f"\nFail to access model({llm.llm_name}) using this api key." + str(
  80. e)
  81. elif not rerank_passed and llm.model_type == LLMType.RERANK:
  82. mdl = RerankModel[factory](
  83. req["api_key"], llm.llm_name, base_url=req.get("base_url"))
  84. try:
  85. arr, tc = mdl.similarity("What's the weather?", ["Is it sunny today?"])
  86. if len(arr) == 0 or tc == 0:
  87. raise Exception("Fail")
  88. rerank_passed = True
  89. logging.debug(f'passed model rerank {llm.llm_name}')
  90. except Exception as e:
  91. msg += f"\nFail to access model({llm.llm_name}) using this api key." + str(
  92. e)
  93. if any([embd_passed, chat_passed, rerank_passed]):
  94. msg = ''
  95. break
  96. if msg:
  97. return get_data_error_result(message=msg)
  98. llm_config = {
  99. "api_key": req["api_key"],
  100. "api_base": req.get("base_url", "")
  101. }
  102. for n in ["model_type", "llm_name"]:
  103. if n in req:
  104. llm_config[n] = req[n]
  105. for llm in LLMService.query(fid=factory):
  106. llm_config["max_tokens"]=llm.max_tokens
  107. if not TenantLLMService.filter_update(
  108. [TenantLLM.tenant_id == current_user.id,
  109. TenantLLM.llm_factory == factory,
  110. TenantLLM.llm_name == llm.llm_name],
  111. llm_config):
  112. TenantLLMService.save(
  113. tenant_id=current_user.id,
  114. llm_factory=factory,
  115. llm_name=llm.llm_name,
  116. model_type=llm.model_type,
  117. api_key=llm_config["api_key"],
  118. api_base=llm_config["api_base"],
  119. max_tokens=llm_config["max_tokens"]
  120. )
  121. return get_json_result(data=True)
  122. @manager.route('/add_llm', methods=['POST']) # noqa: F821
  123. @login_required
  124. @validate_request("llm_factory")
  125. def add_llm():
  126. req = request.json
  127. factory = req["llm_factory"]
  128. def apikey_json(keys):
  129. nonlocal req
  130. return json.dumps({k: req.get(k, "") for k in keys})
  131. if factory == "VolcEngine":
  132. # For VolcEngine, due to its special authentication method
  133. # Assemble ark_api_key endpoint_id into api_key
  134. llm_name = req["llm_name"]
  135. api_key = apikey_json(["ark_api_key", "endpoint_id"])
  136. elif factory == "Tencent Hunyuan":
  137. req["api_key"] = apikey_json(["hunyuan_sid", "hunyuan_sk"])
  138. return set_api_key()
  139. elif factory == "Tencent Cloud":
  140. req["api_key"] = apikey_json(["tencent_cloud_sid", "tencent_cloud_sk"])
  141. elif factory == "Bedrock":
  142. # For Bedrock, due to its special authentication method
  143. # Assemble bedrock_ak, bedrock_sk, bedrock_region
  144. llm_name = req["llm_name"]
  145. api_key = apikey_json(["bedrock_ak", "bedrock_sk", "bedrock_region"])
  146. elif factory == "LocalAI":
  147. llm_name = req["llm_name"] + "___LocalAI"
  148. api_key = "xxxxxxxxxxxxxxx"
  149. elif factory == "HuggingFace":
  150. llm_name = req["llm_name"] + "___HuggingFace"
  151. api_key = "xxxxxxxxxxxxxxx"
  152. elif factory == "OpenAI-API-Compatible":
  153. llm_name = req["llm_name"] + "___OpenAI-API"
  154. api_key = req.get("api_key", "xxxxxxxxxxxxxxx")
  155. elif factory == "XunFei Spark":
  156. llm_name = req["llm_name"]
  157. if req["model_type"] == "chat":
  158. api_key = req.get("spark_api_password", "xxxxxxxxxxxxxxx")
  159. elif req["model_type"] == "tts":
  160. api_key = apikey_json(["spark_app_id", "spark_api_secret", "spark_api_key"])
  161. elif factory == "BaiduYiyan":
  162. llm_name = req["llm_name"]
  163. api_key = apikey_json(["yiyan_ak", "yiyan_sk"])
  164. elif factory == "Fish Audio":
  165. llm_name = req["llm_name"]
  166. api_key = apikey_json(["fish_audio_ak", "fish_audio_refid"])
  167. elif factory == "Google Cloud":
  168. llm_name = req["llm_name"]
  169. api_key = apikey_json(["google_project_id", "google_region", "google_service_account_key"])
  170. elif factory == "Azure-OpenAI":
  171. llm_name = req["llm_name"]
  172. api_key = apikey_json(["api_key", "api_version"])
  173. else:
  174. llm_name = req["llm_name"]
  175. api_key = req.get("api_key", "xxxxxxxxxxxxxxx")
  176. llm = {
  177. "tenant_id": current_user.id,
  178. "llm_factory": factory,
  179. "model_type": req["model_type"],
  180. "llm_name": llm_name,
  181. "api_base": req.get("api_base", ""),
  182. "api_key": api_key,
  183. "max_tokens": req.get("max_tokens")
  184. }
  185. msg = ""
  186. mdl_nm = llm["llm_name"].split("___")[0]
  187. if llm["model_type"] == LLMType.EMBEDDING.value:
  188. mdl = EmbeddingModel[factory](
  189. key=llm['api_key'],
  190. model_name=mdl_nm,
  191. base_url=llm["api_base"])
  192. try:
  193. arr, tc = mdl.encode(["Test if the api key is available"])
  194. if len(arr[0]) == 0:
  195. raise Exception("Fail")
  196. except Exception as e:
  197. msg += f"\nFail to access embedding model({mdl_nm})." + str(e)
  198. elif llm["model_type"] == LLMType.CHAT.value:
  199. mdl = ChatModel[factory](
  200. key=llm['api_key'],
  201. model_name=mdl_nm,
  202. base_url=llm["api_base"]
  203. )
  204. try:
  205. m, tc = mdl.chat(None, [{"role": "user", "content": "Hello! How are you doing!"}], {
  206. "temperature": 0.9})
  207. if not tc and m.find("**ERROR**:") >= 0:
  208. raise Exception(m)
  209. except Exception as e:
  210. msg += f"\nFail to access model({mdl_nm})." + str(
  211. e)
  212. elif llm["model_type"] == LLMType.RERANK:
  213. mdl = RerankModel[factory](
  214. key=llm["api_key"],
  215. model_name=mdl_nm,
  216. base_url=llm["api_base"]
  217. )
  218. try:
  219. arr, tc = mdl.similarity("Hello~ Ragflower!", ["Hi, there!", "Ohh, my friend!"])
  220. if len(arr) == 0:
  221. raise Exception("Not known.")
  222. except Exception as e:
  223. msg += f"\nFail to access model({mdl_nm})." + str(
  224. e)
  225. elif llm["model_type"] == LLMType.IMAGE2TEXT.value:
  226. mdl = CvModel[factory](
  227. key=llm["api_key"],
  228. model_name=mdl_nm,
  229. base_url=llm["api_base"]
  230. )
  231. try:
  232. with open(os.path.join(get_project_base_directory(), "web/src/assets/yay.jpg"), "rb") as f:
  233. m, tc = mdl.describe(f.read())
  234. if not tc:
  235. raise Exception(m)
  236. except Exception as e:
  237. msg += f"\nFail to access model({mdl_nm})." + str(e)
  238. elif llm["model_type"] == LLMType.TTS:
  239. mdl = TTSModel[factory](
  240. key=llm["api_key"], model_name=mdl_nm, base_url=llm["api_base"]
  241. )
  242. try:
  243. for resp in mdl.tts("Hello~ Ragflower!"):
  244. pass
  245. except RuntimeError as e:
  246. msg += f"\nFail to access model({mdl_nm})." + str(e)
  247. else:
  248. # TODO: check other type of models
  249. pass
  250. if msg:
  251. return get_data_error_result(message=msg)
  252. if not TenantLLMService.filter_update(
  253. [TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == factory,
  254. TenantLLM.llm_name == llm["llm_name"]], llm):
  255. TenantLLMService.save(**llm)
  256. return get_json_result(data=True)
  257. @manager.route('/delete_llm', methods=['POST']) # noqa: F821
  258. @login_required
  259. @validate_request("llm_factory", "llm_name")
  260. def delete_llm():
  261. req = request.json
  262. TenantLLMService.filter_delete(
  263. [TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == req["llm_factory"],
  264. TenantLLM.llm_name == req["llm_name"]])
  265. return get_json_result(data=True)
  266. @manager.route('/delete_factory', methods=['POST']) # noqa: F821
  267. @login_required
  268. @validate_request("llm_factory")
  269. def delete_factory():
  270. req = request.json
  271. TenantLLMService.filter_delete(
  272. [TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == req["llm_factory"]])
  273. return get_json_result(data=True)
  274. @manager.route('/my_llms', methods=['GET']) # noqa: F821
  275. @login_required
  276. def my_llms():
  277. try:
  278. res = {}
  279. for o in TenantLLMService.get_my_llms(current_user.id):
  280. if o["llm_factory"] not in res:
  281. res[o["llm_factory"]] = {
  282. "tags": o["tags"],
  283. "llm": []
  284. }
  285. res[o["llm_factory"]]["llm"].append({
  286. "type": o["model_type"],
  287. "name": o["llm_name"],
  288. "used_token": o["used_tokens"]
  289. })
  290. return get_json_result(data=res)
  291. except Exception as e:
  292. return server_error_response(e)
  293. @manager.route('/list', methods=['GET']) # noqa: F821
  294. @login_required
  295. def list_app():
  296. self_deployed = ["Youdao", "FastEmbed", "BAAI", "Ollama", "Xinference", "LocalAI", "LM-Studio", "GPUStack"]
  297. weighted = ["Youdao", "FastEmbed", "BAAI"] if settings.LIGHTEN != 0 else []
  298. model_type = request.args.get("model_type")
  299. try:
  300. objs = TenantLLMService.query(tenant_id=current_user.id)
  301. facts = set([o.to_dict()["llm_factory"] for o in objs if o.api_key])
  302. llms = LLMService.get_all()
  303. llms = [m.to_dict()
  304. for m in llms if m.status == StatusEnum.VALID.value and m.fid not in weighted]
  305. for m in llms:
  306. m["available"] = m["fid"] in facts or m["llm_name"].lower() == "flag-embedding" or m["fid"] in self_deployed
  307. llm_set = set([m["llm_name"] + "@" + m["fid"] for m in llms])
  308. for o in objs:
  309. if not o.api_key:
  310. continue
  311. if o.llm_name + "@" + o.llm_factory in llm_set:
  312. continue
  313. llms.append({"llm_name": o.llm_name, "model_type": o.model_type, "fid": o.llm_factory, "available": True})
  314. res = {}
  315. for m in llms:
  316. if model_type and m["model_type"].find(model_type) < 0:
  317. continue
  318. if m["fid"] not in res:
  319. res[m["fid"]] = []
  320. res[m["fid"]].append(m)
  321. return get_json_result(data=res)
  322. except Exception as e:
  323. return server_error_response(e)