hookla/DreamTeamGPT

must handle rate limits from open ai

Opened this issue · 2 comments

hookla commented

openai.error.RateLimitError: Rate limit reached for gpt-4 in organization org-lDdTak03uNZ02kmY5m6ginja on tokens per min. Limit: 10000 / min. Please try again in 6ms. Contact us through our help center at help.openai.com if you continue to have issues.

so wait and retry when we see this...

Added retry logic with decorator in gpt_client
Although, need to decrease delay to 0.1 second - should be enough for 10k/min rate.

Alternatively, I can add 0.1-second delay before every request - but that would be less elegant
Or set up a timer and counter for requests, reset the counter every second - that feels like an overshoot

@lynxrv21 @hookla I'm the maintainer of LiteLLM - I believe we can help with this problem - I'd love your feedback if LiteLLM is missing something

Here's the quick start:
docs: https://docs.litellm.ai/docs/routing

from litellm import Router

model_list = [{ # list of model deployments 
    "model_name": "gpt-3.5-turbo", # model alias 
    "litellm_params": { # params for litellm completion/embedding call 
        "model": "azure/chatgpt-v-2", # actual model name
        "api_key": os.getenv("AZURE_API_KEY"),
        "api_version": os.getenv("AZURE_API_VERSION"),
        "api_base": os.getenv("AZURE_API_BASE")
    }
}, {
    "model_name": "gpt-3.5-turbo", 
    "litellm_params": { # params for litellm completion/embedding call 
        "model": "azure/chatgpt-functioncalling", 
        "api_key": os.getenv("AZURE_API_KEY"),
        "api_version": os.getenv("AZURE_API_VERSION"),
        "api_base": os.getenv("AZURE_API_BASE")
    }
}, {
    "model_name": "gpt-3.5-turbo", 
    "litellm_params": { # params for litellm completion/embedding call 
        "model": "gpt-3.5-turbo", 
        "api_key": os.getenv("OPENAI_API_KEY"),
    }
}]

router = Router(model_list=model_list)

# openai.ChatCompletion.create replacement
response = await router.acompletion(model="gpt-3.5-turbo", 
                messages=[{"role": "user", "content": "Hey, how's it going?"}])

print(response)