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service test
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‎multicache_serving.py

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# -*- coding: utf-8 -*-
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"""
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Alipay.com Inc.
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Copyright (c) 2004-2021 All Rights Reserved.
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------------------------------------------------------
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File Name : gptcache_serving.py
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Author : fuhui.phe
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Email: [email protected]
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Create Time : 2023/5/28 11:03
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Description : description what the main function of this file
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Change Activity:
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version0 : 2023/5/28 11:03 by fuhui.phe init
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"""
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from datetime import datetime
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from typing import Dict
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import time
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import json
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import uuid
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from gptcache import cache
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from gptcache.adapter import codegpt
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from gptcache.manager import CacheBase, VectorBase, get_data_manager
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from gptcache.similarity_evaluation.distance import SearchDistanceEvaluation
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from gptcache.processor.pre import insert_iat_dict
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from gptcache.processor.pre import query_iat_dict
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from gptcache.utils.env_config import get_table_suffix
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from concurrent.futures import ThreadPoolExecutor
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from gptcache.maya_embedding_service.maya_multi_embedding_service import get_embedding_multi
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from gptcache.maya_embedding_service.maya_multi_embedding_service import get_embedding_multi_concurrent_sin
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# from gptcache.utils.modle_version_manager import model_version_load
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# from gptcache.utils.modle_version_manager import get_all_collections
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# from gptcache.utils.collection_util import get_collection_iat_name
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# from gptcache.utils.collection_util import get_collection_iat_type
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def save_query_info(result, model, query, delta_time_log):
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print('执行 save_query_info!')
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cache.data_manager.save_query_resp(result, model=model, query=query,
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delta_time=delta_time_log)
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def response_text(cache_resp):
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# print('cache_resp: {}'.format(cache_resp))
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return cache_resp['data']
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def response_hitquery(cache_resp):
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# print('cache_resp: {}'.format(cache_resp))
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return cache_resp['hitQuery']
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# timm2vec = Timm()
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# text2vec = Data2VecAudio()
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# python类示例
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class UserBackend:
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def __init__(self):
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self.table_suffix = get_table_suffix()
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image_dimension = 768
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text_dimension = 768
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# data_manager = get_data_manager(CacheBase("oceanbase", table_suffix=self.table_suffix),
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# VectorBase("milvus", iat_dimension=image_dimension + text_dimension,
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# i_dimension=image_dimension, t_dimension=text_dimension,
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# table_suffix=self.table_suffix))
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data_manager = get_data_manager(CacheBase("oceanbase", table_suffix=self.table_suffix),
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VectorBase("redis", iat_dimension=image_dimension+text_dimension,
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i_dimension=image_dimension, t_dimension=text_dimension,
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table_suffix=self.table_suffix))
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cache.init(
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# embedding_func=get_cache_embedding_text2vec,
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# image_embedding_func=timm2vec.to_embeddings,
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# text_embedding_func=text2vec.to_embeddings,
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embedding_func=get_embedding_multi,
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embedding_concur_func=get_embedding_multi_concurrent_sin,
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data_manager=data_manager,
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similarity_evaluation=SearchDistanceEvaluation(),
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# iat_query_pre_embedding_func=query_multi_splicing,
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iat_insert_pre_embedding_func=insert_iat_dict,
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iat_query_pre_embedding_func=query_iat_dict,
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# insert_pre_embedding_miulti_func=insert_multimodal_splicing,
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# query_pre_embedding_miulti_func=query_multimodal_splicing,
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)
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# cache.set_openai_key()
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self.gptcache_version = datetime.now().strftime("%Y-%m-%d %H:%M")
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self.executor = ThreadPoolExecutor(max_workers=6)
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def __call__(self, param):
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print('gptcache_version: {}'.format(self.gptcache_version))
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# logging.info('gptcache_version: {}'.format(self.gptcache_version))
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print('call_time: {}'.format(datetime.now().strftime("%Y-%m-%d %H:%M:%S")))
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# logging.info('call_time: {}'.format(datetime.now().strftime("%Y-%m-%d %H:%M")))
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try:
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# print('param: {}'.format(param))
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param_dict = json.loads(param)
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except Exception as e:
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result = {"errorCode": 101, "errorDesc": str(e), "cacheHit": False, "delta_time": 0, "hit_query": '',
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"answer": ''}
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cache.data_manager.save_query_resp(result, model='', query='', delta_time=0)
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return json.dumps(result)
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request_type = param_dict.get("request_type")
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UUID = param_dict.get("UUID", None)
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print('request_type: {}'.format(request_type))
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# param parsing
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try:
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scope = param_dict.get("scope")
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print('scope: {}'.format(scope))
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if scope is not None:
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model = scope.get('model')
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model = model.replace('-', '_')
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model = model.replace('.', '_')
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print('model: {}'.format(model))
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if request_type in ['iat_query', 'iat_insert']:
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if request_type == 'iat_query':
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query = param_dict.get("query")
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elif request_type == 'iat_insert':
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chat_info = param_dict.get("chat_info")
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query = chat_info[-1]['query']
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if request_type is None or request_type not in ['iat_query', 'iat_remove', 'iat_insert', 'iat_register']:
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result = {"errorCode": 102,
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"errorDesc": "type exception, should one of ['iat_query', 'iat_insert', 'iat_remove', 'iat_register']",
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"cacheHit": False, "delta_time": 0, "hit_query": '', "answer": ''}
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cache.data_manager.save_query_resp(result, model=model, query='', delta_time=0)
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return json.dumps(result)
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except Exception as e:
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result = {"errorCode": 103, "errorDesc": str(e), "cacheHit": False, "delta_time": 0, "hit_query": '',
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"answer": ''}
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# cache.data_manager.save_query_resp(result, model='', query='', delta_time=0)
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return json.dumps(result)
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# --------分割线
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if request_type == 'iat_query':
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if UUID:
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try:
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uuid_list = UUID.split('==>')
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user_start = float(uuid_list[1])
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ray_http_cost = time.time()-user_start
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print('ray_http_cost: {}'.format(ray_http_cost))
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except Exception as e:
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print('uuid_e: {}'.format(e))
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try:
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start_time = time.time()
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response = codegpt.ChatCompletion.create_iat_query(
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scope={"model": model},
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query=query,
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)
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# print('response: {}'.format(response))
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delta_time = '{}s'.format(round(time.time() - start_time, 2))
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if response is None:
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result = {"errorCode": 0, "errorDesc": '', "cacheHit": False, "delta_time": delta_time,
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"hit_query": '', "answer": ''}
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elif isinstance(response, dict):
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answer = response_text(response)
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hit_query = response_hitquery(response)
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result = {"errorCode": 0, "errorDesc": '', "cacheHit": True, "delta_time": delta_time,
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"hit_query": hit_query, "answer": answer}
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else:
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result = {"errorCode": 201, "errorDesc": response, "cacheHit": False, "delta_time": delta_time,
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"hit_query": '', "answer": ''}
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delta_time_log = round(time.time() - start_time, 3)
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print('delta_time_log: {}'.format(delta_time_log))
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# modify at 20230807 20:51
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future = self.executor.submit(save_query_info, result, model, query, delta_time_log)
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query_time = round(time.time() - start_time, 2)
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print('query_time: {}'.format(query_time))
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except Exception as e:
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result = {"errorCode": 202, "errorDesc": str(e), "cacheHit": False, "delta_time": 0,
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"hit_query": '', "answer": ''}
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print('result: {}'.format(result))
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return json.dumps(result, ensure_ascii=False)
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# response = codegpt.ChatCompletion.create_iat_query(
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# scope={"model": model},
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# query=query,
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# )
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# print('response_query: {}'.format(response))
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if request_type == 'iat_insert':
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if UUID:
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try:
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uuid_list = UUID.split('==>')
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user_start = float(uuid_list[1])
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ray_http_cost = time.time()-user_start
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print('ray_http_cost: {}'.format(ray_http_cost))
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except Exception as e:
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print('uuid_e: {}'.format(e))
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try:
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start_time = time.time()
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try:
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response = codegpt.ChatCompletion.create_iat_insert(
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model=model,
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chat_info=chat_info,
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)
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except Exception as e:
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result = {"errorCode": 303, "errorDesc": e, "writeStatus": "exception"}
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return json.dumps(result, ensure_ascii=False)
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if response == 'success':
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result = {"errorCode": 0, "errorDesc": "", "writeStatus": "success"}
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else:
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result = {"errorCode": 301, "errorDesc": response, "writeStatus": "exception"}
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insert_time = round(time.time() - start_time, 2)
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print('insert_time: {}'.format(insert_time))
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return json.dumps(result, ensure_ascii=False)
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except Exception as e:
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result = {"errorCode": 304, "errorDesc": e, "writeStatus": "exception"}
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print('result: {}'.format(result))
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return json.dumps(result, ensure_ascii=False)
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# response = codegpt.ChatCompletion.create_iat_insert(
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# model=model,
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# chat_info=chat_info,
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# milvus_collection_ins=collection_ins
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# )
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# print('response: {}'.format(response))
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if request_type == 'iat_remove':
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remove_type = param_dict.get("remove_type")
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id_list = param_dict.get("id_list", [])
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print('remove_type: {}'.format(remove_type))
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response = codegpt.ChatCompletion.create_iat_remove(
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model=model,
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remove_type=remove_type,
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id_list=id_list
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)
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if not isinstance(response, dict):
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result = {"errorCode": 401, "errorDesc": "", "response": response, "removeStatus": "exception"}
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return json.dumps(result)
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state = response.get('status')
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# if response == 'success':
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if state == 'success':
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result = {"errorCode": 0, "errorDesc": "", "response": response, "writeStatus": "success"}
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else:
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result = {"errorCode": 402, "errorDesc": "", "response": response, "writeStatus": "exception"}
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return json.dumps(result)
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if request_type == 'iat_register':
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iat_type = param_dict.get("iat_type")
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response = codegpt.ChatCompletion.create_iat_register(
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model=model,
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iat_type=iat_type,
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table_suffix=self.table_suffix
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)
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if response in ['create_success', 'already_exists']:
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result = {"errorCode": 0, "errorDesc": "", "response": response, "writeStatus": "success"}
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else:
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result = {"errorCode": 502, "errorDesc": "", "response": response, "writeStatus": "exception"}
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return json.dumps(result)
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def __update_config__(self, config: Dict[str, object]):
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"""
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可选
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"""
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pass
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def __health_check__(self):
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"""
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可选
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"""
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# logging.info(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
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return True
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if __name__ == '__main__':
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# ============01
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# request_type = 'iat_insert'
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# scope = {"model": "test_0313"}
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# # UUID = "820b0052-d9d8-11ee-95f1-52775e3e6fd1" + "==>" + str(time.time())
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# UUID = str(uuid.uuid1()) + "==>" + str(time.time())
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# print('UUID: {}'.format(UUID))
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# img_data = "http://resarch.oss-cn-hangzhou-zmf.aliyuncs.com/transFile%2Ftmp%2FLMM_test_image_coco%2FCOCO_train2014_000000332345.jpg"
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# query = {'text': ['父母带着孩子来这个地方可能会有什么顾虑'],
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# 'imageRaw': '',
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# 'imageUrl': img_data,
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# 'imageId': 'ccc'}
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# answer = "应该注意小孩不要跑到铁轨上"
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# chat_info = [{"query": query, "answer": answer}]
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# data_dict = {'request_type': request_type, 'scope': scope, 'chat_info': chat_info, 'UUID': UUID}
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# r1 = json.dumps(data_dict)
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# ============02
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request_type = 'iat_query'
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UUID = str(uuid.uuid1()) + "==>" + str(time.time())
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scope = {"model": "test_0313"}
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img_data = 'http://resarch.oss-cn-hangzhou-zmf.aliyuncs.com/transFile%2Ftmp%2FLMM_test_image_coco%2FCOCO_train2014_000000332345.jpg'
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query = {'text': ['父母带着孩子来这个地方可能会有什么顾虑'],
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'imageRaw': '',
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'imageUrl': img_data,
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'multiType': 'IMG_TEXT'}
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r1 = json.dumps({'request_type': request_type, 'scope': scope, 'query': query, 'UUID': UUID})
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# ============03
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# request_type = 'iat_remove'
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# scope = {"model": "test_0313"}
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# # iat_type = 'IMG_TEXT'
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# remove_type = 'truncate_by_model'
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# r1 = json.dumps({'request_type': request_type, 'scope': scope, 'remove_type': remove_type})
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# ============04
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# request_type = 'iat_register'
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# scope = {"model": "test_0313"}
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# iat_type = 'IMG_TEXT'
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# r1 = json.dumps({'request_type': request_type, 'scope': scope, 'iat_type': iat_type})
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user_backend = UserBackend()
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resp = user_backend(r1)
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print('resp: {}'.format(resp))

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