Gsoc_AI_API_EVAL_draft_proposal #733
Merged
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
initial idea_harsh_panchal_AI_API_EVAL.md
This reverts commit a1721a6.
|
Hi @GANGSTER0910 The proposal looks good. You can go ahead and submit it in the GSoC website. |
|
Hello @animator , I’ve submitted my GSoC proposal for the AI API Evaluation Framework. Please let me know if you have any suggestions for improvements that could enhance my chances of selection. |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
PR Description
This PR introduces the AI API Evaluation Framework for API Dash. The framework supports evaluating AI models across various media types (text, images, audio, and video) using customizable metrics. It offers both online evaluations via server-hosted models and offline evaluations using LoRA adapters with 4-bit quantized models. Users can upload datasets, visualize results using interactive charts, and generate detailed reports. Additionally, explainability features using SHAP and LIME provide insights into model decisions. This implementation enhances model assessment capabilities, offering transparency and flexibility.
Related Issues
Checklist
mainbranch before making this PRflutter upgradeand verify)flutter test) and all tests are passingOS on which you have developed and tested the feature?