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# | |
# Copyright 2024 The InfiniFlow Authors. All Rights Reserved. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
# | |
from flask import request | |
from flask_login import login_required, current_user | |
from api.db.services.llm_service import LLMFactoriesService, TenantLLMService, LLMService | |
from api.utils.api_utils import server_error_response, get_data_error_result, validate_request | |
from api.db import StatusEnum, LLMType | |
from api.db.db_models import TenantLLM | |
from api.utils.api_utils import get_json_result | |
from rag.llm import EmbeddingModel, ChatModel, RerankModel,CvModel | |
import requests | |
import ast | |
def factories(): | |
try: | |
fac = LLMFactoriesService.get_all() | |
return get_json_result(data=[f.to_dict() for f in fac if f.name not in ["Youdao", "FastEmbed", "BAAI"]]) | |
except Exception as e: | |
return server_error_response(e) | |
def set_api_key(): | |
req = request.json | |
# test if api key works | |
chat_passed, embd_passed, rerank_passed = False, False, False | |
factory = req["llm_factory"] | |
msg = "" | |
for llm in LLMService.query(fid=factory): | |
if not embd_passed and llm.model_type == LLMType.EMBEDDING.value: | |
mdl = EmbeddingModel[factory]( | |
req["api_key"], llm.llm_name, base_url=req.get("base_url")) | |
try: | |
arr, tc = mdl.encode(["Test if the api key is available"]) | |
if len(arr[0]) == 0: | |
raise Exception("Fail") | |
embd_passed = True | |
except Exception as e: | |
msg += f"\nFail to access embedding model({llm.llm_name}) using this api key." + str(e) | |
elif not chat_passed and llm.model_type == LLMType.CHAT.value: | |
mdl = ChatModel[factory]( | |
req["api_key"], llm.llm_name, base_url=req.get("base_url")) | |
try: | |
m, tc = mdl.chat(None, [{"role": "user", "content": "Hello! How are you doing!"}], | |
{"temperature": 0.9,'max_tokens':50}) | |
if m.find("**ERROR**") >=0: | |
raise Exception(m) | |
except Exception as e: | |
msg += f"\nFail to access model({llm.llm_name}) using this api key." + str( | |
e) | |
chat_passed = True | |
elif not rerank_passed and llm.model_type == LLMType.RERANK: | |
mdl = RerankModel[factory]( | |
req["api_key"], llm.llm_name, base_url=req.get("base_url")) | |
try: | |
arr, tc = mdl.similarity("What's the weather?", ["Is it sunny today?"]) | |
if len(arr) == 0 or tc == 0: | |
raise Exception("Fail") | |
except Exception as e: | |
msg += f"\nFail to access model({llm.llm_name}) using this api key." + str( | |
e) | |
rerank_passed = True | |
if msg: | |
return get_data_error_result(retmsg=msg) | |
llm = { | |
"api_key": req["api_key"], | |
"api_base": req.get("base_url", "") | |
} | |
for n in ["model_type", "llm_name"]: | |
if n in req: | |
llm[n] = req[n] | |
if not TenantLLMService.filter_update( | |
[TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == factory], llm): | |
for llm in LLMService.query(fid=factory): | |
TenantLLMService.save( | |
tenant_id=current_user.id, | |
llm_factory=factory, | |
llm_name=llm.llm_name, | |
model_type=llm.model_type, | |
api_key=req["api_key"], | |
api_base=req.get("base_url", "") | |
) | |
return get_json_result(data=True) | |
def add_llm(): | |
req = request.json | |
factory = req["llm_factory"] | |
if factory == "VolcEngine": | |
# For VolcEngine, due to its special authentication method | |
# Assemble volc_ak, volc_sk, endpoint_id into api_key | |
temp = list(ast.literal_eval(req["llm_name"]).items())[0] | |
llm_name = temp[0] | |
endpoint_id = temp[1] | |
api_key = '{' + f'"volc_ak": "{req.get("volc_ak", "")}", ' \ | |
f'"volc_sk": "{req.get("volc_sk", "")}", ' \ | |
f'"ep_id": "{endpoint_id}", ' + '}' | |
elif factory == "Bedrock": | |
# For Bedrock, due to its special authentication method | |
# Assemble bedrock_ak, bedrock_sk, bedrock_region | |
llm_name = req["llm_name"] | |
api_key = '{' + f'"bedrock_ak": "{req.get("bedrock_ak", "")}", ' \ | |
f'"bedrock_sk": "{req.get("bedrock_sk", "")}", ' \ | |
f'"bedrock_region": "{req.get("bedrock_region", "")}", ' + '}' | |
elif factory == "LocalAI": | |
llm_name = req["llm_name"]+"___LocalAI" | |
api_key = "xxxxxxxxxxxxxxx" | |
elif factory == "OpenAI-API-Compatible": | |
llm_name = req["llm_name"]+"___OpenAI-API" | |
api_key = req.get("api_key","xxxxxxxxxxxxxxx") | |
else: | |
llm_name = req["llm_name"] | |
api_key = "xxxxxxxxxxxxxxx" | |
llm = { | |
"tenant_id": current_user.id, | |
"llm_factory": factory, | |
"model_type": req["model_type"], | |
"llm_name": llm_name, | |
"api_base": req.get("api_base", ""), | |
"api_key": api_key | |
} | |
msg = "" | |
if llm["model_type"] == LLMType.EMBEDDING.value: | |
mdl = EmbeddingModel[factory]( | |
key=llm['api_key'] if factory in ["VolcEngine", "Bedrock","OpenAI-API-Compatible"] else None, | |
model_name=llm["llm_name"], | |
base_url=llm["api_base"]) | |
try: | |
arr, tc = mdl.encode(["Test if the api key is available"]) | |
if len(arr[0]) == 0 or tc == 0: | |
raise Exception("Fail") | |
except Exception as e: | |
msg += f"\nFail to access embedding model({llm['llm_name']})." + str(e) | |
elif llm["model_type"] == LLMType.CHAT.value: | |
mdl = ChatModel[factory]( | |
key=llm['api_key'] if factory in ["VolcEngine", "Bedrock","OpenAI-API-Compatible"] else None, | |
model_name=llm["llm_name"], | |
base_url=llm["api_base"] | |
) | |
try: | |
m, tc = mdl.chat(None, [{"role": "user", "content": "Hello! How are you doing!"}], { | |
"temperature": 0.9}) | |
if not tc: | |
raise Exception(m) | |
except Exception as e: | |
msg += f"\nFail to access model({llm['llm_name']})." + str( | |
e) | |
elif llm["model_type"] == LLMType.RERANK: | |
mdl = RerankModel[factory]( | |
key=None, model_name=llm["llm_name"], base_url=llm["api_base"] | |
) | |
try: | |
arr, tc = mdl.similarity("Hello~ Ragflower!", ["Hi, there!"]) | |
if len(arr) == 0 or tc == 0: | |
raise Exception("Not known.") | |
except Exception as e: | |
msg += f"\nFail to access model({llm['llm_name']})." + str( | |
e) | |
elif llm["model_type"] == LLMType.IMAGE2TEXT.value: | |
mdl = CvModel[factory]( | |
key=llm["api_key"] if factory in ["OpenAI-API-Compatible"] else None, model_name=llm["llm_name"], base_url=llm["api_base"] | |
) | |
try: | |
img_url = ( | |
"https://upload.wikimedia.org/wikipedia/comm" | |
"ons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/256" | |
"0px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" | |
) | |
res = requests.get(img_url) | |
if res.status_code == 200: | |
m, tc = mdl.describe(res.content) | |
if not tc: | |
raise Exception(m) | |
else: | |
pass | |
except Exception as e: | |
msg += f"\nFail to access model({llm['llm_name']})." + str(e) | |
else: | |
# TODO: check other type of models | |
pass | |
if msg: | |
return get_data_error_result(retmsg=msg) | |
if not TenantLLMService.filter_update( | |
[TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == factory, TenantLLM.llm_name == llm["llm_name"]], llm): | |
TenantLLMService.save(**llm) | |
return get_json_result(data=True) | |
def delete_llm(): | |
req = request.json | |
TenantLLMService.filter_delete( | |
[TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == req["llm_factory"], TenantLLM.llm_name == req["llm_name"]]) | |
return get_json_result(data=True) | |
def my_llms(): | |
try: | |
res = {} | |
for o in TenantLLMService.get_my_llms(current_user.id): | |
if o["llm_factory"] not in res: | |
res[o["llm_factory"]] = { | |
"tags": o["tags"], | |
"llm": [] | |
} | |
res[o["llm_factory"]]["llm"].append({ | |
"type": o["model_type"], | |
"name": o["llm_name"], | |
"used_token": o["used_tokens"] | |
}) | |
return get_json_result(data=res) | |
except Exception as e: | |
return server_error_response(e) | |
def list_app(): | |
model_type = request.args.get("model_type") | |
try: | |
objs = TenantLLMService.query(tenant_id=current_user.id) | |
facts = set([o.to_dict()["llm_factory"] for o in objs if o.api_key]) | |
llms = LLMService.get_all() | |
llms = [m.to_dict() | |
for m in llms if m.status == StatusEnum.VALID.value] | |
for m in llms: | |
m["available"] = m["fid"] in facts or m["llm_name"].lower() == "flag-embedding" or m["fid"] in ["Youdao","FastEmbed", "BAAI"] | |
llm_set = set([m["llm_name"] for m in llms]) | |
for o in objs: | |
if not o.api_key:continue | |
if o.llm_name in llm_set:continue | |
llms.append({"llm_name": o.llm_name, "model_type": o.model_type, "fid": o.llm_factory, "available": True}) | |
res = {} | |
for m in llms: | |
if model_type and m["model_type"].find(model_type)<0: | |
continue | |
if m["fid"] not in res: | |
res[m["fid"]] = [] | |
res[m["fid"]].append(m) | |
return get_json_result(data=res) | |
except Exception as e: | |
return server_error_response(e) | |