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LM Async Client, openai client, azure openai client ...

Project description

lmclient

面向于大规模异步请求 OpenAI 接口设计的客户端,使用场景 self-instruct, 大规模翻译等

Features

  1. 支持大规模异步请求 openai 接口
  2. 支持进度条
  3. 支持限制每分钟最大请求次数
  4. 支持限制异步容量 (类似于线程池的大小)
  5. 支持磁盘缓存
  6. 100% type hints
  7. 非常易用
  8. 支持 OpenAI, Azure, Minimax, MinimaxPro, 智谱, 百度文心, 腾讯混元
  9. 支持 FunctionCall

安装方式

支持 python3.8 及以上

pip install lmclient-core

使用方法

  1. CompletionEngine
from lmclient import CompletionEngine, OpenAIChat, OpenAIChatParameters

model = OpenAIChat('gpt-3.5-turbo',  parameters=OpenAIChatParameters(temperature=0))
# 控制每分钟最大请求次数为 20, 异步容量为 5
client = CompletionEngine(model, async_capacity=5, max_requests_per_minute=20)
prompts = [
    'Hello, my name is',
    'can you please tell me your name?',
    [{'role': 'user', 'content': 'hello, who are you?'}],
    'what is your name?',
]
outputs = client.async_run(prompts=prompts)
for output in outputs:
    print(output.reply)
  1. ChatEngine
from lmclient import ChatEngine, OpenAIChat

model = OpenAIChat('gpt-3.5-turbo')
chat_engine = ChatEngine(model)
print(chat_engine.chat('你好,我是 chat_engine'))
print(chat_engine.chat('我上一句话是什么?'))

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