Closed ajitesh123 closed 4 months ago
This PR introduces audio input functionality for performance reviews and self-reviews, using the Groq library for speech-to-text conversion. The changes appear to be well-integrated with the existing codebase, adding the necessary fields and updating the relevant functions. However, there are some potential security and test coverage concerns that should be addressed.
๐ Security analysis |
- User-provided API keys are directly used without validation or sanitization. - No input validation for the new `audio_review` field in `ReviewRequest` and `SelfReviewRequest`. - Potential exposure of sensitive information in audio transcriptions. |
๐งช Test coverage analysis |
- No visible tests for the new audio functionality in the provided diff. - Lack of error handling for audio conversion failures. - Missing edge case tests for empty or invalid audio inputs. |
โก Logical error analysis |
- Inconsistent handling of `audio_review` when it's None or empty. - Potential performance issues with large audio files not addressed. - No clear distinction between text and audio inputs in the prompt generation. |
This change introduces the ability for users to provide audio input for performance reviews and self-reviews, in addition to text input. The audio is converted to text using the Whisper model integrated with the Groq library. This text is then used for generating reviews. Modifications include updates to request models, prompt generation, and handling the new audio_review
field.
File | Change Summary |
---|---|
app_fastapi.py |
Added audio_review parameter to api_generate_review and api_generate_self_review functions. |
review.py |
Added audio_review field to ReviewRequest class and updated relevant functions to handle it. |
self_review.py |
Added audio_review field to SelfReviewRequest class and updated relevant functions to handle it. |
requirements.txt |
Added streamlit-audiorec and groq dependencies. |
sequenceDiagram
participant User
participant StreamlitApp
participant FastAPI
participant WhisperGroq
participant ReviewModule
User ->> StreamlitApp: Record audio review
StreamlitApp ->> WhisperGroq: Convert audio to text
WhisperGroq -->> StreamlitApp: Text Review
StreamlitApp ->> FastAPI: Send ReviewRequest with audio_review
FastAPI ->> ReviewModule: Process ReviewRequest
ReviewModule -->> FastAPI: Generated Review
FastAPI -->> StreamlitApp: Return Generated Review
StreamlitApp -->> User: Display Generated Review
In fields where code and voices blend,
A rabbit hops, new paths to send.
From words we type to sounds we speak,
Reviews now soar, a brand-new peak.
With Groq and Whisper, clear and bright,
Performance shines in day and night.
๐โจ๐ค
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This pull request adds the ability for users to provide audio input for their performance reviews and self-reviews. Previously, users had to type their input, but now they can record their audio. The audio is converted from speech to text using the Whisper model on the Groq library, and the resulting text is used as input to the review generation process.
Main Changes:
convert_speech_to_text
function in thespeech_to_text.py
file, which uses the Groq library to transcribe the audio to text.ReviewRequest
andSelfReviewRequest
models to include an optionalaudio_review
field, and updated thegenerate_review
andgenerate_self_review
functions to use this field when generating the review.convert_speech_to_text
,generate_review
, andgenerate_self_review
functions with audio input.Summary by CodeRabbit
New Features
Dependencies
streamlit-audiorec
andgroq
to the project requirements.