How do you fix an embedding mismatch when integrating an AI code reviewer with GitHub actions

Question

With the help of proper code example can you explain me How do you fix an embedding mismatch when integrating an AI code reviewer with GitHub actions?

Answer 1

You can fix an embedding mismatch in an AI code reviewer integrated with GitHub Actions by ensuring consistent model-tokenizer pairing, normalizing text inputs, using fixed embedding dimensions, and caching model weights correctly.

Here is the code snippet you can refer to:

In the above code, we are using the following key points:

• Consistent Model-Tokenizer Pairing: Uses the same MODEL_NAME for both.
• Text Normalization: Ensures tokens are padded and truncated correctly.
• Fixed Embedding Dimensions: Uses mean(dim=1) to enforce consistent shape.
• GitHub Actions Integration: Automates AI review on pull requests.
• Dependency Caching: Prevents embedding mismatches due to outdated model versions.

Hence, resolving embedding mismatches in an AI-powered GitHub Actions code reviewer requires consistent tokenizer-model pairing, input normalization, and fixed embedding dimensions to ensure reliable and reproducible AI evaluations.