openai.ChatOpenAI.completion_with_retry.<locals>._completion_with_retry in 1.0 seconds as it raised RateLimitError: That model is currently overloaded with other requests. You can retry your request, or contact us through our help center at help.openai.com if the error persists. (Please includ...
Retrying langchain.chat_models.openai.ChatOpenAI.completion_with_retry.<locals>._completion_with_retry in 8.0 seconds as it raised RateLimitError: Rate limit reached for default-gpt-3.5-turbo in organization org-FDYSniIsv0FIQBi9p4P9Dinn on requests per min. Limit: 3 / min. Please try again...
streaming: if len(_prompts) > 1: raise ValueError("Cannot stream results with multiple prompts.") params["stream"] = True response = _streaming_response_template() for stream_resp in completion_with_retry( self, prompt=_prompts, **params ): self.callback_manager.on_llm_new_token( stream...
File "/public/home/robertchen/anaconda3/envs/lmfchatchat/lib/python3.10/site-packages/langchain_community/chat_models/openai.py", line 105, in acompletion_with_retry return await llm.async_client.create(**kwargs) File "/public/home/robertchen/anaconda3/envs/lmfchatchat/lib/python3.10/site-...
如今各类AI模型层出不穷,百花齐放,大佬们开发的速度永远遥遥领先于学习者的学习速度。。为了解放生产力,不让应用层开发人员受限于各语言模型的生产部署中..LangChain横空出世界。
async for chunk in await acompletion_with_retry( File "F:\Anaconda\envs\ChatGLM\lib\site-packages\openai_streaming.py", line 116, inaiter async for item in self._iterator: File "F:\Anaconda\envs\ChatGLM\lib\site-packages\openai_streaming.py", line 129, instream ...
verbose=True ) with get_openai_callback() as cb: response = agent.run("王菲现在的年龄是多少?") print(f"Total Tokens: {cb.total_tokens}") print(f"Prompt Tokens: {cb.prompt_tokens}") print(f"Completion Tokens: {cb.completion_tokens}") print(f"Total Cost (USD): ${cb.total_cost}...
本文为笔者学习LangChain时对官方文档以及一系列资料进行一些总结～覆盖对Langchain的核心六大模块的理解与核心使用方法,全文篇幅较长,共计50000+字,可先码住辅助用于学习Langchain。 一、Langchain是什么? 如今各类AI模型层出不穷,百花齐放,大佬们开发的速度永远遥遥领先于学习者的学习速度。。为了解放生产力,不让应用...
从上述例子,可以直观的看到ChatPromptTemplate可以将prompt中声明的输入变量style和text准确提取出来,使prompt更清晰。当然,Langchain对于prompt的优化不止这一种方式,它还提供了各类其他接口将prompt进一步优化,这里只是举例一个较为基础且直观的方法,让大家感受一下。