litellm/docs/my-website/docs/exception_mapping.md
2023-12-19 19:29:05 +05:30

109 lines
5.5 KiB
Markdown

# Exception Mapping
LiteLLM maps exceptions across all providers to their OpenAI counterparts.
| Status Code | Error Type |
|-------------|--------------------------|
| 400 | BadRequestError |
| 401 | AuthenticationError |
| 403 | PermissionDeniedError |
| 404 | NotFoundError |
| 422 | UnprocessableEntityError |
| 429 | RateLimitError |
| >=500 | InternalServerError |
| N/A | ContextWindowExceededError|
| N/A | APIConnectionError |
Base case we return APIConnectionError
All our exceptions inherit from OpenAI's exception types, so any error-handling you have for that, should work out of the box with LiteLLM.
For all 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
```python
import litellm
import openai
try:
response = litellm.completion(
model="gpt-4",
messages=[
{
"role": "user",
"content": "hello, write a 20 pageg essay"
}
],
timeout=0.01, # this will raise a timeout exception
)
except openai.APITimeoutError as e:
print("Passed: Raised correct exception. Got openai.APITimeoutError\nGood Job", e)
print(type(e))
pass
```
## Usage - Catching Streaming Exceptions
```python
import litellm
try:
response = litellm.completion(
model="gpt-3.5-turbo",
messages=[
{
"role": "user",
"content": "hello, write a 20 pg essay"
}
],
timeout=0.0001, # this will raise an exception
stream=True,
)
for chunk in response:
print(chunk)
except openai.APITimeoutError as e:
print("Passed: Raised correct exception. Got openai.APITimeoutError\nGood Job", e)
print(type(e))
pass
except Exception as e:
print(f"Did not raise error `openai.APITimeoutError`. Instead raised error type: {type(e)}, Error: {e}")
```
## Details
To see how it's implemented - [check out the code](https://github.com/BerriAI/litellm/blob/a42c197e5a6de56ea576c73715e6c7c6b19fa249/litellm/utils.py#L1217)
[Create an issue](https://github.com/BerriAI/litellm/issues/new) **or** [make a PR](https://github.com/BerriAI/litellm/pulls) 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](https://github.com/BerriAI/litellm/blob/a42c197e5a6de56ea576c73715e6c7c6b19fa249/litellm/utils.py#L1221)
## Custom mapping list
Base case - we return the original exception.
| | ContextWindowExceededError | AuthenticationError | InvalidRequestError | RateLimitError | ServiceUnavailableError |
|---------------|----------------------------|---------------------|---------------------|---------------|-------------------------|
| Anthropic | ✅ | ✅ | ✅ | ✅ | |
| OpenAI | ✅ | ✅ |✅ |✅ |✅|
| Azure OpenAI | ✅ | ✅ |✅ |✅ |✅|
| Replicate | ✅ | ✅ | ✅ | ✅ | ✅ |
| Cohere | ✅ | ✅ | ✅ | ✅ | ✅ |
| Huggingface | ✅ | ✅ | ✅ | ✅ | |
| Openrouter | ✅ | ✅ | ✅ | ✅ | |
| AI21 | ✅ | ✅ | ✅ | ✅ | |
| VertexAI | | |✅ | | |
| Bedrock | | |✅ | | |
| Sagemaker | | |✅ | | |
| TogetherAI | ✅ | ✅ | ✅ | ✅ | |
| AlephAlpha | ✅ | ✅ | ✅ | ✅ | ✅ |
> For a deeper understanding of these exceptions, you can check out [this](https://github.com/BerriAI/litellm/blob/d7e58d13bf9ba9edbab2ab2f096f3de7547f35fa/litellm/utils.py#L1544) implementation for additional insights.
The `ContextWindowExceededError` is a sub-class of `InvalidRequestError`. It was introduced to provide more granularity for exception-handling scenarios. Please refer to [this issue to learn more](https://github.com/BerriAI/litellm/issues/228).
Contributions to improve exception mapping are [welcome](https://github.com/BerriAI/litellm#contributing)