Open archie-ai-code-explain-pr-review[bot] opened 1 month ago
🔍 Processing Issue [=== ] 𝙋𝙧𝙤𝙘𝙚𝙨𝙨𝙞𝙣𝙜...
Steps: [ ] Problem discovery: Understand the issue and find related files/code [ ] Determine approach: Decide higher level plan approach [ ] Implementation plan: Create a detailed plan of action [ ] Code generation: Write the code to solve the issue
This issue will be updated as we make progress.
Feature Request: Add Audio Input for Performance Reviews
Main Objective:
Technical Requirements:
Audio Recording:
streamlit-audio-recorder
library to implement audio recording in the app.Speech-to-Text Conversion:
convert_speech_to_text
function.Data Model Updates:
ReviewRequest
model to include an optional audio_review
field.SelfReviewRequest
model to include an optional audio_review
field.Application Logic Updates:
app.py
to handle the new audio_review
field.Implementation Steps:
streamlit-audio-recorder
for audio capture.convert_speech_to_text
function using Whisper model and Groq library.ReviewRequest
and SelfReviewRequest
) with audio_review
field.app.py
to process audio input and generate reviews accordingly.Note: Ensure that the existing text-based input functionality is maintained alongside the new audio input feature.
These existing files need to be updated:
These new files need to be created:
These files are important for context but don't need direct modification:
The implementation plan will be based on these files.
To address this issue effectively, I've broken it down into the following subtasks:
I'll work through these subtasks systematically to resolve the issue.
The root cause of this issue is the lack of audio input functionality in the current performance review system. The existing system only supports text-based input for reviews and self-reviews. To address this, we need to implement audio recording, speech-to-text conversion, and integrate these new features into the existing application logic. The most critical components to resolve this issue are:
By addressing these components, we can successfully add the requested audio input feature while maintaining the existing text-based functionality.
Example:
Example:
import groq
import whisper
def convert_speech_to_text(audio_file):
# Initialize the Whisper model
model = whisper.load_model("base")
# Transcribe the audio
result = model.transcribe(audio_file)
# Return the transcribed text
return result["text"]
Example:
Example:
Example:
with st.expander("Audio Input"):
audio_bytes = st_audiorec()
if audio_bytes:
st.audio(audio_bytes, format="audio/wav")
audio_text = None
if audio_bytes:
audio_text = convert_speech_to_text(audio_bytes)
st.write("Transcribed text:", audio_text)
Update the review generation logic:
# Combine text and audio inputs
combined_input = ""
if st.session_state.messages[-1]["content"]:
combined_input += st.session_state.messages[-1]["content"]
if audio_text:
combined_input += " " + audio_text
# Use combined_input for generating reviews
# Update the existing logic to use combined_input instead of just text input
Example:
import unittest
from src.speech_to_text import convert_speech_to_text
from src.review import ReviewRequest
from src.self_review import SelfReviewRequest
from src.app import process_audio_input # Assuming this function exists in app.py
class TestAudioFeatures(unittest.TestCase):
def test_speech_to_text_conversion(self):
# Test the convert_speech_to_text function
audio_file = "path/to/test/audio/file.wav"
result = convert_speech_to_text(audio_file)
self.assertIsInstance(result, str)
self.assertGreater(len(result), 0)
def test_review_request_with_audio(self):
# Test ReviewRequest with audio_review field
review = ReviewRequest(employee_name="John Doe", audio_review="Test audio review")
self.assertEqual(review.audio_review, "Test audio review")
def test_self_review_request_with_audio(self):
# Test SelfReviewRequest with audio_review field
self_review = SelfReviewRequest(employee_name="Jane Doe", audio_review="Test audio self-review")
self.assertEqual(self_review.audio_review, "Test audio self-review")
def test_app_audio_processing(self):
# Test audio processing in app.py
audio_input = b"dummy audio data"
result = process_audio_input(audio_input)
self.assertIsNotNone(result)
if __name__ == '__main__':
unittest.main()
Describe ALL changes to be made: Add the streamlit-audio-recorder library to the requirements.txt file.
# Existing requirements
streamlit==1.10.0
openai==0.27.0
python-dotenv==0.19.2
# Existing requirements
streamlit==1.10.0
openai==0.27.0
python-dotenv==0.19.2
streamlit-audio-recorder==0.0.3
Describe ALL changes to be made: Create a new file speech_to_text.py in the src directory. Implement the convert_speech_to_text function using the Whisper model from the Groq library.
import groq
import whisper
def convert_speech_to_text(audio_file):
# Initialize the Whisper model
model = whisper.load_model("base")
# Transcribe the audio
result = model.transcribe(audio_file)
# Return the transcribed text
return result["text"]
Describe ALL changes to be made: Update the ReviewRequest class to include the audio_review field and update the class docstring.
from typing import Optional
class ReviewRequest:
"""
Represents a request for a performance review.
:param employee_name: Name of the employee being reviewed
:param review_period: Period for which the review is being conducted
:param achievements: Notable achievements during the review period
:param areas_for_improvement: Areas where the employee can improve
:param goals: Goals for the next review period
"""
def __init__(
self,
employee_name: str,
review_period: str,
achievements: Optional[str] = None,
areas_for_improvement: Optional[str] = None,
goals: Optional[str] = None
):
self.employee_name = employee_name
self.review_period = review_period
self.achievements = achievements
self.areas_for_improvement = areas_for_improvement
self.goals = goals
from typing import Optional
class ReviewRequest:
"""
Represents a request for a performance review.
:param employee_name: Name of the employee being reviewed
:param review_period: Period for which the review is being conducted
:param achievements: Notable achievements during the review period
:param areas_for_improvement: Areas where the employee can improve
:param goals: Goals for the next review period
:param audio_review: Optional audio review input
"""
def __init__(
self,
employee_name: str,
review_period: str,
achievements: Optional[str] = None,
areas_for_improvement: Optional[str] = None,
goals: Optional[str] = None,
audio_review: Optional[str] = None
):
self.employee_name = employee_name
self.review_period = review_period
self.achievements = achievements
self.areas_for_improvement = areas_for_improvement
self.goals = goals
self.audio_review = audio_review
Describe ALL changes to be made: Update the SelfReviewRequest class to include the audio_review field and update the class docstring.
from typing import Optional
class SelfReviewRequest:
"""
Represents a request for a self-review.
:param employee_name: Name of the employee conducting the self-review
:param review_period: Period for which the self-review is being conducted
:param achievements: Notable achievements during the review period
:param challenges: Challenges faced during the review period
:param goals: Goals for the next review period
"""
def __init__(
self,
employee_name: str,
review_period: str,
achievements: Optional[str] = None,
challenges: Optional[str] = None,
goals: Optional[str] = None
):
self.employee_name = employee_name
self.review_period = review_period
self.achievements = achievements
self.challenges = challenges
self.goals = goals
from typing import Optional
class SelfReviewRequest:
"""
Represents a request for a self-review.
:param employee_name: Name of the employee conducting the self-review
:param review_period: Period for which the self-review is being conducted
:param achievements: Notable achievements during the review period
:param challenges: Challenges faced during the review period
:param goals: Goals for the next review period
:param audio_review: Optional audio review input
"""
def __init__(
self,
employee_name: str,
review_period: str,
achievements: Optional[str] = None,
challenges: Optional[str] = None,
goals: Optional[str] = None,
audio_review: Optional[str] = None
):
self.employee_name = employee_name
self.review_period = review_period
self.achievements = achievements
self.challenges = challenges
self.goals = goals
self.audio_review = audio_review
Describe ALL changes to be made: Import necessary modules for audio recording and speech-to-text conversion.
import streamlit as st
from review import ReviewRequest
from self_review import SelfReviewRequest
# Other existing imports
import streamlit as st
from review import ReviewRequest
from self_review import SelfReviewRequest
from streamlit_audio_recorder import st_audiorec
from speech_to_text import convert_speech_to_text
# Other existing imports
Describe ALL changes to be made: Add audio recording functionality and implement speech-to-text conversion.
def main():
st.title("Performance Review Generator")
review_type = st.radio("Select review type:", ("Performance Review", "Self-Review"))
if review_type == "Performance Review":
employee_name = st.text_input("Employee Name")
review_period = st.text_input("Review Period")
achievements = st.text_area("Achievements")
areas_for_improvement = st.text_area("Areas for Improvement")
goals = st.text_area("Goals for Next Period")
if st.button("Generate Review"):
review_request = ReviewRequest(
employee_name=employee_name,
review_period=review_period,
achievements=achievements,
areas_for_improvement=areas_for_improvement,
goals=goals
)
# Generate and display review
elif review_type == "Self-Review":
employee_name = st.text_input("Employee Name")
review_period = st.text_input("Review Period")
achievements = st.text_area("Achievements")
challenges = st.text_area("Challenges")
goals = st.text_area("Goals for Next Period")
if st.button("Generate Self-Review"):
self_review_request = SelfReviewRequest(
employee_name=employee_name,
review_period=review_period,
achievements=achievements,
challenges=challenges,
goals=goals
)
# Generate and display self-review
if __name__ == "__main__":
main()
def main():
st.title("Performance Review Generator")
review_type = st.radio("Select review type:", ("Performance Review", "Self-Review"))
if review_type == "Performance Review":
employee_name = st.text_input("Employee Name")
review_period = st.text_input("Review Period")
achievements = st.text_area("Achievements")
areas_for_improvement = st.text_area("Areas for Improvement")
goals = st.text_area("Goals for Next Period")
with st.expander("Audio Input"):
audio_bytes = st_audiorec()
if audio_bytes:
st.audio(audio_bytes, format="audio/wav")
if st.button("Generate Review"):
audio_text = None
if audio_bytes:
audio_text = convert_speech_to_text(audio_bytes)
st.write("Transcribed text:", audio_text)
combined_input = ""
if achievements:
combined_input += f"Achievements: {achievements}\n"
if areas_for_improvement:
combined_input += f"Areas for Improvement: {areas_for_improvement}\n"
if goals:
combined_input += f"Goals: {goals}\n"
if audio_text:
combined_input += f"Audio Input: {audio_text}\n"
review_request = ReviewRequest(
employee_name=employee_name,
review_period=review_period,
achievements=achievements,
areas_for_improvement=areas_for_improvement,
goals=goals,
audio_review=audio_text
)
# Generate and display review using combined_input
elif review_type == "Self-Review":
employee_name = st.text_input("Employee Name")
review_period = st.text_input("Review Period")
achievements = st.text_area("Achievements")
challenges = st.text_area("Challenges")
goals = st.text_area("Goals for Next Period")
with st.expander("Audio Input"):
audio_bytes = st_audiorec()
if audio_bytes:
st.audio(audio_bytes, format="audio/wav")
if st.button("Generate Self-Review"):
audio_text = None
if audio_bytes:
audio_text = convert_speech_to_text(audio_bytes)
st.write("Transcribed text:", audio_text)
combined_input = ""
if achievements:
combined_input += f"Achievements: {achievements}\n"
if challenges:
combined_input += f"Challenges: {challenges}\n"
if goals:
combined_input += f"Goals: {goals}\n"
if audio_text:
combined_input += f"Audio Input: {audio_text}\n"
self_review_request = SelfReviewRequest(
employee_name=employee_name,
review_period=review_period,
achievements=achievements,
challenges=challenges,
goals=goals,
audio_review=audio_text
)
# Generate and display self-review using combined_input
if __name__ == "__main__":
main()
Describe ALL changes to be made: Create a new file test_audio_features.py in the tests directory and implement test cases for the new audio functionality.
import unittest
from unittest.mock import patch, MagicMock
from src.speech_to_text import convert_speech_to_text
from src.review import ReviewRequest
from src.self_review import SelfReviewRequest
class TestAudioFeatures(unittest.TestCase):
@patch('whisper.load_model')
def test_speech_to_text_conversion(self, mock_load_model):
mock_model = MagicMock()
mock_model.transcribe.return_value = {"text": "Test transcription"}
mock_load_model.return_value = mock_model
audio_file = b"dummy audio data"
result = convert_speech_to_text(audio_file)
self.assertEqual(result, "Test transcription")
mock_load_model.assert_called_once_with("base")
mock_model.transcribe.assert_called_once_with(audio_file)
def test_review_request_with_audio(self):
review = ReviewRequest(
employee_name="John Doe",
review_period="2023",
audio_review="Test audio review"
)
self.assertEqual(review.audio_review, "Test audio review")
def test_self_review_request_with_audio(self):
self_review = SelfReviewRequest(
employee_name="Jane Doe",
review_period="2023",
audio_review="Test audio self-review"
)
self.assertEqual(self_review.audio_review, "Test audio self-review")
if __name__ == '__main__':
unittest.main()
Code changes doesn't address the issue: The proposed changes do not effectively resolve the git issue for the following reasons:
streamlit-audio-recorder
library, which is crucial for the audio recording functionality, is not included in the requirements.txt
file.ReviewRequest
and SelfReviewRequest
) to include the audio_review
field.convert_speech_to_text
function implementation is not present.app.py
for handling audio input are evident.To resolve this issue, the following minimal changes are needed:
streamlit-audio-recorder
to the requirements.txt
file.streamlit-audio-recorder
.convert_speech_to_text
function using the Whisper model via Groq.audio_review
field.app.py
to handle audio input and generate reviews accordingly.Once these changes are implemented and visible for review, a more accurate assessment of the issue resolution can be made.
Please use the code suggestion above to manually apply.
streamlit-audio-recorder
library to allow audio recording in the app.convert_speech_to_text
function using the Whisper model on the Groq library to convert the audio to text.ReviewRequest
andSelfReviewRequest
models to include an optionalaudio_review
field, and use this input for generating the review and self-review.app.py
to handle the newaudio_review
field.