Openai error handling for ratelimit, timeout and try again errors(fix #1255) #1361
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…le and its tests - Adds test for rate limit error handling in the llms/openai module - Adds error handling for rate limit error in the llms/openai module - Refactors code in llms/openai module to be readable and modular
…and its test - Adds test for timeout error handling in chat_completion in llms/openai module - Adds error handling for openai's timeout error in chat_completion in llms/openai module
…e and its test - Adds test for openai's try again error handling in chat_completion in llms/openai module - Adds error handling for openai's try again error in chat_completion in llms/openai module
…y attempts are exausted
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Codecov ReportAttention:
Additional details and impacted files@@ Coverage Diff @@
## main #1361 +/- ##
==========================================
+ Coverage 58.66% 58.73% +0.06%
==========================================
Files 230 230
Lines 11188 11202 +14
Branches 1206 1209 +3
==========================================
+ Hits 6563 6579 +16
+ Misses 4289 4286 -3
- Partials 336 337 +1
☔ View full report in Codecov by Sentry. |
luciferlinx101
approved these changes
Dec 13, 2023
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Description
With these changes the agent won't stop if a ratelimit error or timeout error or try again error is hit from the openai library, it will try again.
Related Issues
#1255
Solution and Design
The agent will attempt to wait 5 times with an exponential backoff strategy and try again, it will wait for a minimum of 30 seconds and max of 300 seconds.
If after 5 attempts the api call still fails it will return the error.
Test Plan
The code is tested by mocking the api calls to openai and having it return the errors mentioned above and checking if the function has called the api specified number of times and it returns the expected error as a dictionary object.
To reduce the time taken to test, the tencity library's wait_random_exponential function is mocked to only use 0.1 seconds
Type of change
Checklist