litellm/docs/my-website/docs/exception_mapping.md

Exception Mapping

LiteLLM maps the 3 most common exceptions across all providers.

• Rate Limit Errors
• Context Window Errors
• InvalidAuth errors (key rotation stuff)

Base case - we return the original exception.

For all 3 cases, the exception returned inherits from the original OpenAI Exception but contains 3 additional attributes:

• status_code - the http status code of the exception
• message - the error message
• llm_provider - the provider raising the exception

usage

from litellm import completion

os.environ["ANTHROPIC_API_KEY"] = "bad-key"
try: 
    # some code 
    completion(model="claude-instant-1", messages=[{"role": "user", "content": "Hey, how's it going?"}])
except Exception as e:
    print(e.llm_provider)

details

To see how it's implemented - check out the code

Create an issue or make a PR if you want to improve the exception mapping.

Note For OpenAI and Azure we return the original exception (since they're of the OpenAI Error type). But we add the 'llm_provider' attribute to them. See code

LLM Provider	Initial Status Code / Initial Error Message	Returned Exception	Returned Status Code
Anthropic	401	AuthenticationError	401
Anthropic	Could not resolve authentication method. Expected either api_key or auth_token to be set.	AuthenticationError	401
Anthropic	400	InvalidRequestError	400
Anthropic	429	RateLimitError	429
Replicate	Incorrect authentication token	AuthenticationError	401
Replicate	ModelError	InvalidRequestError	400
Replicate	Request was throttled	RateLimitError	429
Replicate	ReplicateError	ServiceUnavailableError	500
Cohere	invalid api token	AuthenticationError	401
Cohere	too many tokens	InvalidRequestError	400
Cohere	CohereConnectionError	RateLimitError	429
Huggingface	401	AuthenticationError	401
Huggingface	400	InvalidRequestError	400
Huggingface	429	RateLimitError	429