Closed ajitesh123 closed 4 months ago
The changes incorporate speech-to-text functionality for generating both review and self-review. Audio inputs are converted to text using the convert_speech_to_text
function. The updates span multiple files, ensuring audio inputs are handled, converted, and processed appropriately.
File | Change Summary |
---|---|
app_fastapi.py |
Integrated convert_speech_to_text for handling audio reviews in both review and self-review processes. |
audio_utils.py |
Introduced convert_speech_to_text function leveraging Groq API for audio transcription. |
requirements.txt |
Added streamlit-audiorec==0.1.3 as a new dependency. |
review.py |
Incorporated st_audiorec , modified ReviewRequest to include audio_review field, added main function. |
self_review.py |
Similar to review.py , added audio_review field and a main function for handling self-reviews. |
In lines of code, a rabbit's gift,
From speech to text, we now uplift.
ππ€
Reviews and more, now understand,
Audio to words, how grand a plan!
π
With clever bytes, the task is done,
Our journey's ripe, new dawn begun.
βοΈβ¨
[!TIP]
AI model upgrade
## `gpt-4o` model for reviews and chat is now live OpenAI claims that this model is better at understanding and generating code than the previous models. Please join our [Discord Community](https://discord.com/invite/GsXnASn26c) to provide any feedback or to report any issues.
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β±οΈ Estimated effort to review: 4 π΅π΅π΅π΅βͺ |
π§ͺ No relevant tests |
π No security concerns identified |
β‘ Key issues to review **Possible Bug:** The `convert_speech_to_text` function in `audio_utils.py` does not handle exceptions that may occur during the transcription process. It's recommended to add error handling to manage potential failures from the Groq client or file operations. **Performance Concern:** The audio file handling in `convert_speech_to_text` involves writing to a temporary file and then reading it back, which could be optimized. Consider processing the audio data directly from memory if the Groq API supports it. **Code Duplication:** Similar code blocks are used in both `api_generate_review` and `api_generate_self_review` for handling audio data. Consider refactoring this into a separate function to reduce duplication and improve maintainability. |
Category | Suggestion | Score |
Possible issue |
Add error handling for the speech-to-text conversion to improve reliability and error reporting___ **Consider handling the case whereconvert_speech_to_text might raise an exception due to API errors or invalid audio data. This will prevent the server from crashing and provide a way to return a meaningful error response to the client.** [app_fastapi.py [21]](https://github.com/ajitesh123/Perf-Review-AI/pull/25/files#diff-12ae1733c1fe81510692dadf3ad3328d8801f864812689ff2dc412fe14fd04f0R21-R21) ```diff -your_review = convert_speech_to_text(request.audio_review, request.user_api_key) +try: + your_review = convert_speech_to_text(request.audio_review, request.user_api_key) +except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) ``` - [ ] **Apply this suggestion** Suggestion importance[1-10]: 9Why: This suggestion is crucial as it adds error handling for potential exceptions that may arise during the speech-to-text conversion, thereby preventing the server from crashing and providing meaningful error responses to the client. | 9 |
Enhancement |
Add validation for
___
**Validate the | 8 |
Best practice |
Use the
___
**Instead of manually managing temporary files, use the | 7 |
/describe
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PR Description updated to latest commit (https://github.com/ajitesh123/Perf-Review-AI/commit/b5d042770688095755352e14589252e27a64fa2a)
Progress: 1/4 | Difficulty: π΄ Hard
This PR introduces a new feature that allows users to provide audio input for reviews and self-reviews. The system now supports converting speech to text, enabling users to record their reviews verbally.
from audio_utils import convert_speech_to_text
if request.audio_review:
your_review = convert_speech_to_text(request.audio_review, request.user_api_key)
Question: What is the primary benefit of adding audio input support?
Option 1Improved accessibility for users with visual impairments |
Option 2Faster input method for some users |
Option 3Enhanced accuracy in review content |
Progress: 2/4 | Difficulty: π΄ Hard
A new file, audio_utils.py, has been added to handle the conversion of speech to text. It uses the Groq API to transcribe audio files.
def convert_speech_to_text(audio_data: bytes, api_key: str) -> str:
client = Groq(api_key=api_key)
# ... (file handling and API call)
return transcription.text
Question: What potential issue should be considered when implementing speech-to-text conversion?
Option 1Increased API costs |
Option 2Longer processing time |
Option 3Accuracy of transcription |
Progress: 3/4 | Difficulty: π΄ Hard
The PR updates both review.py and self_review.py to include Streamlit components for audio recording. This allows for a seamless integration of the new audio feature in the user interface.
from st_audiorec import st_audiorec
def main():
# ... (other UI elements)
st.subheader("Audio Review (Optional)")
audio_data = st_audiorec()
if audio_data is not None:
st.audio(audio_data, format='audio/wav')
Question: What additional feature might improve the user experience with audio reviews?
Option 1A progress bar during transcription |
Option 2The ability to pause and resume recording |
Option 3Automatic language detection for multi-language support |
Progress: 4/4 | Difficulty: π’ Easy
The PR modifies the existing API endpoints and data models to accommodate the new audio input feature. This includes updates to ReviewRequest and SelfReviewRequest classes.
class ReviewRequest(BaseModel):
# ... (existing fields)
audio_review: Optional[bytes] = None
class SelfReviewRequest(BaseModel):
# ... (existing fields)
audio_review: Optional[bytes] = None
Question: What potential backward compatibility issue should be considered with these changes?
Option 1Existing clients might break if they don't expect the new field |
Option 2Database schema changes might be required |
Option 3Performance might degrade for non-audio reviews |
This PR introduces a new feature that allows users to provide audio input for reviews and self-reviews. The system now supports converting speech to text, enabling users to record their reviews verbally.
from audio_utils import convert_speech_to_text
if request.audio_review:
your_review = convert_speech_to_text(request.audio_review, request.user_api_key)
Question: What is the primary benefit of adding audio input support?
A new file, audio_utils.py, has been added to handle the conversion of speech to text. It uses the Groq API to transcribe audio files.
def convert_speech_to_text(audio_data: bytes, api_key: str) -> str:
client = Groq(api_key=api_key)
# ... (file handling and API call)
return transcription.text
Question: What potential issue should be considered when implementing speech-to-text conversion?
The PR updates both review.py and self_review.py to include Streamlit components for audio recording. This allows for a seamless integration of the new audio feature in the user interface.
from st_audiorec import st_audiorec
def main():
# ... (other UI elements)
st.subheader("Audio Review (Optional)")
audio_data = st_audiorec()
if audio_data is not None:
st.audio(audio_data, format='audio/wav')
Question: What additional feature might improve the user experience with audio reviews?
The PR modifies the existing API endpoints and data models to accommodate the new audio input feature. This includes updates to ReviewRequest and SelfReviewRequest classes.
class ReviewRequest(BaseModel):
# ... (existing fields)
audio_review: Optional[bytes] = None
class SelfReviewRequest(BaseModel):
# ... (existing fields)
audio_review: Optional[bytes] = None
Question: What potential backward compatibility issue should be considered with these changes?
User description
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:
PR Type
Enhancement, Other
Description
convert_speech_to_text
function using the Whisper model in the Groq library.ReviewRequest
andSelfReviewRequest
models to include an optionalaudio_review
field.api_generate_review
andapi_generate_self_review
endpoints to handle audio input.st_audiorec
for audio recording in the main functions ofreview.py
andself_review.py
.streamlit-audiorec
library to the project dependencies.Changes walkthrough π
app_fastapi.py
Add audio input handling in FastAPI endpoints
app_fastapi.py
convert_speech_to_text
function call to handle audio input.api_generate_review
andapi_generate_self_review
endpoints toprocess audio input.
audio_utils.py
Implement audio to text conversion utility
audio_utils.py
convert_speech_to_text
function using Groq's Whisper model.review.py
Add audio review support in review generation
review.py
audio_review
field toReviewRequest
model.st_audiorec
for audio recording in the main function.self_review.py
Add audio review support in self-review generation
self_review.py
audio_review
field toSelfReviewRequest
model.st_audiorec
for audio recording in the main function.requirements.txt
Add streamlit-audiorec dependency
requirements.txt - Added `streamlit-audiorec` library.