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
- 支持大规模异步请求 openai 接口
- 支持进度条
- 支持限制每分钟最大请求次数
- 支持限制异步容量 （类似于线程池的大小）
- 支持磁盘缓存
- 100% type hints
- 非常易用
- 支持 OpenAI, Azure, Minimax, MinimaxPro, 智谱, 百度文心, 腾讯混元
- 支持 FunctionCall
安装方式
支持 python3.8 及以上
pip install lmclient-core
使用方法
- 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)
- 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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