# Add voice input for the Sweep feature

ajitesh123 commented 4 months ago

User description

This pull request adds the ability to use voice as an input mechanism for the Sweep feature. Previously, users had to type their input, but now they have the option to provide voice input as an alternative.

The main changes to implement this feature are:

Added a new API endpoint /generate_review_voice that accepts an audio file upload and uses the SpeechRecognition library to transcribe the audio to text. This transcribed text is then passed to the existing generate_review function to generate the review.
Modified the get_completion function to handle voice input. If the input type is "voice", the function skips the text generation step since the text has already been transcribed from the audio.
Updated the generate_review function to accept an optional input_type parameter, which is used to determine whether to use the text or voice input path.
Added the SpeechRecognition library to the project requirements to enable the voice input functionality.

These changes provide users with the flexibility to choose their preferred input method, making the Sweep feature more accessible and user-friendly.

PR Type

Enhancement, Dependencies

Description

Added a new API endpoint /generate_review_voice that accepts an audio file upload and uses the SpeechRecognition library to transcribe the audio to text. The transcribed text is then passed to the existing generate_review function to generate the review.
Modified the get_completion function to handle voice input by skipping the text generation step if the input type is "voice".
Updated the generate_review function to accept an optional input_type parameter, allowing it to determine whether to use text or voice input.
Added the SpeechRecognition library to the project requirements to enable the voice input functionality.

Changes walkthrough 📝

Relevant files

Enhancement

app.py `Add support for voice input in review generation functions` app.py Added handling for voice input in `get_completion` function. Updated `generate_review` function to accept `input_type` parameter.	+7/-4
app_fastapi.py `Add API endpoint for voice input and audio transcription` app_fastapi.py Introduced new API endpoint `/generate_review_voice` for voice input. Integrated SpeechRecognition library for audio transcription.	+29/-1

Dependencies

requirements.txt

Add SpeechRecognition library to dependencies

requirements.txt - Added SpeechRecognition library to project dependencies.

+1/-0

💡 PR-Agent usage: Comment /help on the PR to get a list of all available PR-Agent tools and their descriptions

Summary by CodeRabbit

New Features
- Added support for voice input in review generation.
- Introduced a new endpoint /generate_review_voice for handling audio files.
Dependencies
- Added SpeechRecognition package (v3.8.1).

coderabbitai[bot] commented 4 months ago

Walkthrough

The application introduces a new capability to process voice inputs for review generation. By allowing the get_completion and generate_review functions to handle an input_type parameter, the app can now differentiate between text and voice inputs. This enhancement is complemented by a new API endpoint /generate_review_voice in app_fastapi.py and the addition of the SpeechRecognition package to process audio files.

Changes

File	Change Summary
`app.py`	Updated `get_completion` and `generate_review` functions to handle `input_type` parameter.
`app_fastapi.py`	Added functionality to generate reviews from voice inputs via a new API endpoint `/generate_review_voice`.
`requirements.txt`	Added `SpeechRecognition` package version `3.8.1` to facilitate audio processing.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant FastAPI
    participant SpeechRecognition
    participant ReviewGenerator

    User->>FastAPI: POST /generate_review_voice (audio file)
    FastAPI->>SpeechRecognition: Process audio file
    SpeechRecognition->>FastAPI: Return text
    FastAPI->>ReviewGenerator: Call generate_review with text and input_type="voice"
    ReviewGenerator->>FastAPI: Return review response
    FastAPI->>User: Return review

Poem

Out hopped some code with a soft little hop,
To listen to voices, no need to stop.
Speech turns to text in the blink of an ear,
Generating reviews with a new kind of cheer.
A leap for the app, a quite clever feat,
Turning voices to feedback, oh isn’t that sweet?

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codiumai-pr-agent-pro[bot] commented 4 months ago

PR Reviewer Guide 🔍

⏱️ Estimated effort to review [1-5]	4
🧪 Relevant tests	No
🔒 Security concerns	No
⚡ Key issues to review	Error Handling: The new endpoint `/generate_review_voice` uses the SpeechRecognition library to process audio files. However, the error handling seems generic. It would be beneficial to handle specific errors related to audio processing and speech recognition, providing more informative responses to the client.
	Audio File Validation: There is no explicit validation for the audio file type or size before processing. Implementing checks to validate the file type and size can prevent unnecessary processing and potential errors.
	Dependency Management: The addition of the SpeechRecognition library increases the complexity of the system. Ensure that this library is compatible with other dependencies and the production environment.

codiumai-pr-agent-pro[bot] commented 4 months ago

PR Code Suggestions ✨

Category	Suggestion	Score
Possible bug	✅ Ensure the function returns a meaningful response or raises an exception for voice input ___ The `get_completion` function should return a meaningful response or raise an exception when `input_type` is "voice" to avoid returning an undefined variable `response`. [app.py [12-16]](https://github.com/ajitesh123/Perf-Review-AI/pull/21/files#diff-568470d013cd12e4f388206520da39ab9a4e4c3c6b95846cbc281abc1ba3c959R12-R16) ```diff if input_type == "voice": # For voice input, the prompt is already processed and converted to text # in the api_generate_review_voice function - pass + return "Voice input processed" +response = llm.generate_text(prompt, model=model_size) return response ``` `[Suggestion has been applied]` Suggestion importance[1-10]: 10 Why: The suggestion correctly identifies a critical bug where the `response` variable would be undefined if `input_type` is "voice". The suggested code ensures a meaningful response is returned, preventing runtime errors.	10
Possible issue	Validate the uploaded file type to ensure it is an audio file ___ Add a check to ensure the uploaded file is an audio file before processing it to avoid potential errors. [app_fastapi.py [44-45]](https://github.com/ajitesh123/Perf-Review-AI/pull/21/files#diff-12ae1733c1fe81510692dadf3ad3328d8801f864812689ff2dc412fe14fd04f0R44-R45) ```diff +if not audio_file.content_type.startswith("audio/"): + raise HTTPException(status_code=400, detail="Invalid file type. Please upload an audio file.") audio_content = await audio_file.read() recognizer = sr.Recognizer() ``` - [ ] Apply this suggestion Suggestion importance[1-10]: 8 Why: This suggestion improves the robustness of the code by ensuring that only audio files are processed, which is a good practice to prevent potential errors.	8
Best practice	Implement more specific exception handling for better error clarity ___ Use a more specific exception handling mechanism to provide clearer error messages and avoid catching unintended exceptions. [app_fastapi.py [56-57]](https://github.com/ajitesh123/Perf-Review-AI/pull/21/files#diff-12ae1733c1fe81510692dadf3ad3328d8801f864812689ff2dc412fe14fd04f0R56-R57) ```diff +except sr.UnknownValueError: + raise HTTPException(status_code=400, detail="Could not understand the audio") +except sr.RequestError as e: + raise HTTPException(status_code=500, detail=f"Could not request results from Google Speech Recognition service; {e}") except Exception as e: raise HTTPException(status_code=500, detail=str(e)) ``` - [ ] Apply this suggestion Suggestion importance[1-10]: 7 Why: The suggestion enhances error handling by specifying different exceptions for different error conditions, which improves the clarity and maintainability of the code.	7
Best practice	Use a context manager to handle the `io.BytesIO` object for proper resource management ___ Use a context manager to handle the `io.BytesIO` object to ensure it is properly closed after use. [app_fastapi.py [47-49]](https://github.com/ajitesh123/Perf-Review-AI/pull/21/files#diff-12ae1733c1fe81510692dadf3ad3328d8801f864812689ff2dc412fe14fd04f0R47-R49) ```diff -with sr.AudioFile(io.BytesIO(audio_content)) as source: - audio_data = recognizer.record(source) - your_review = recognizer.recognize_google(audio_data) +with io.BytesIO(audio_content) as audio_file: + with sr.AudioFile(audio_file) as source: + audio_data = recognizer.record(source) + your_review = recognizer.recognize_google(audio_data) ``` - [ ] Apply this suggestion Suggestion importance[1-10]: 6 Why: This suggestion correctly identifies the need for proper resource management using a context manager, although the existing code already uses a context manager for `sr.AudioFile`, making this improvement less critical.	6

ajitesh123 commented 4 months ago

Review and fix @ellipsis-dev

ajitesh123 commented 4 months ago

PR Review Summary 🔍

🔍 **Review**

This PR introduces a new scanner strategy for Azure within the `scanner-strategies` module, which enhances the code's modularity and expands its capabilities to support Azure alongside AWS and GCP. The implementation appears robust, focusing on integrating Azure's SDK with existing scanning processes.

🔒 **Security analysis**

Ensure that the Azure SDK calls are properly authenticated and that no sensitive information is logged.
Validate that the permissions and roles generated are least-privilege by default.

🧪 **Test coverage analysis**

Include unit tests for the new Azure scanner class.
Verify that integration tests cover the new scanning capabilities for Azure.

⚡ **Logical error analysis**

Double-check that the async operations in `AzureScanner` handle all potential exceptions.
Ensure that all promises in `AzureScanner` are properly awaited and resolved.

ajitesh123 commented 4 months ago

PR Review Summary 🔍

🔍 Review

The PR introduces an Azure scanner implementation, following the existing pattern for AWS and GCP scanners. It adds a new AzureScanner class, updates the scanner strategies index, and modifies the command-line option description. The implementation appears to maintain consistency with existing code structure and follows modular design principles. While it enhances the project's capabilities, there are some security considerations specific to Azure that need attention.

🔒 Security analysis

- - The implementation doesn't explicitly address Azure-specific security considerations such as ARM API permissions, least privilege principle, and Azure RBAC alignment. - There's no clear indication of how sensitive Azure resource information is handled or protected. - The code doesn't show implementation of logging or monitoring for Azure scanning operations.

🧪 Test coverage analysis

- - No new tests are visible in the provided diff, which is a concern for ensuring the reliability of the new Azure scanner implementation. - Lack of visible error handling in the `AzureScanner` class could lead to uncaught exceptions.

⚡ Logical error analysis

- - The `scan` method in `AzureScanner` follows a similar structure to other scanners, reducing the likelihood of logical errors. - The use of `Promise.all` for parallel processing of code snippets is appropriate and efficient. - The integration of the Azure scanner in the `ScannerStrategies` object is correctly implemented.

ajitesh123 / auto-review-ai