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Feat set token limits based on model #4498
Feat set token limits based on model #4498
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…its-based-on-model
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…its-based-on-model' into feat--set-token-limits-based-on-model
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You changed AutoGPT's behaviour. The cassettes have been updated and will be merged to the submodule when this Pull Request gets merged. |
Codecov ReportPatch coverage:
Additional details and impacted files@@ Coverage Diff @@
## master #4498 +/- ##
==========================================
- Coverage 69.70% 69.67% -0.04%
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Files 72 72
Lines 3562 3558 -4
Branches 569 569
==========================================
- Hits 2483 2479 -4
Misses 890 890
Partials 189 189
☔ View full report in Codecov by Sentry. |
This pull request has conflicts with the base branch, please resolve those so we can evaluate the pull request. |
Low priority is relative, it's one of the more frequent issues on discord and github https://discord.com/channels/1092243196446249134/1092243196798582930/1115737448580907180 |
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Looks good to me :)
Conflict is because |
Hell yeah, nice one |
…its-based-on-model
Deployment failed with the following error:
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Conflicts have been resolved! 🎉 A maintainer will review the pull request shortly. |
We may still want to support changing this at runtime so that the agent can exit gracefully using a corresponding error message, in order for the LLM to change some variables at runtime: https://discord.com/channels/1092243196446249134/1092423060923101304/1115963736642035732 |
Thanks @Pwuts for getting this merged! I went away for a couple days and was pleasantly surprised to see this merged lol |
Background
Every day we see people come into the discord explaining how they ran into a token limit because most people are still on a 3.0/3.5 key. The maintainer's built the app to assume 8000 token limit due to gpt4 key and atm this just causes friction because in reality, most people do not have a 4.0 key
To meet in the middle we will respect the user's token limit but compare it to the max token limit based off the smart/fast llvm model and set a limit 15% less to ensure we take into account the prompt and package
Changes
Use the model's max_token_limits for both fast/smart llvm
Test Plan
i updated failing tests
PR Quality Checklist