greptile-apps[bot]
commented
2 months ago - In
app.py, add an audio file uploader to the Streamlit UI:import streamlit as st from review import ReviewRequest, generate_review, DEFAULT_QUESTIONS from self_review import SelfReviewRequest, generate_self_review import speech_recognition as sr
Streamlit UI
st.set_page_config(page_title="Performance Review Assistant", layout="wide")
Sidebar for common elements
with st.sidebar: st.title("Review Settings") review_type = st.radio("Select Review Type", ["Performance Review", "Self-Review"]) llm_type = st.selectbox('Select LLM Type', ['openai', 'google', 'anthropic', 'groq']) model_size = st.selectbox('Select Model Size', ['small', 'medium', 'large']) user_api_key = st.text_input('Your API Key', type="password")
if review_type == "Performance Review": st.title("Write Performance Review in a Minute")
st.text("""If no question is passed, the following are considered:
1. Describe example(s) of the topics selected. What was the context? What actions did they take?
2. In your opinion, what impact did their actions have?
3. What recommendations do you have for their growth and development? Your feedback can be about any area of their work.
""")
your_role = st.text_input('Your Role')
candidate_role = st.text_input('Candidate Role')
perf_question = st.text_area('Performance Review Questions (one per line)', height=100)
your_review = st.text_area('Briefly describe your experience of working with the candidate including project, responsibility of candidate, unique things they did etc., in free flow writing', height=200)
audio_file = st.file_uploader("Upload an audio file", type=["wav", "mp3"])
if st.button('Generate Performance Review'):
if not user_api_key:
st.error("Please enter your API key in the sidebar.")
elif not your_role or not candidate_role or not your_review:
st.error("Please fill in all required fields.")
else:
try:
if audio_file is not None:
recognizer = sr.Recognizer()
audio_data = sr.AudioFile(audio_file)
with audio_data as source:
audio = recognizer.record(source)
your_review += recognizer.recognize_google(audio)
questions = perf_question.split('\n') if perf_question else DEFAULT_QUESTIONS.split('\n')
review_request = ReviewRequest(
your_role=your_role,
candidate_role=candidate_role,
perf_question="\n".join(questions),
your_review=your_review,
llm_type=llm_type,
user_api_key=user_api_key,
model_size=model_size
)
review = generate_review(**review_request.model_dump())
for qa in review:
st.markdown(f"**{qa['question']}**")
st.markdown(qa['answer'])
st.markdown("---")
except Exception as e:
st.error(f"An error occurred: {str(e)}")else: # Self-Review st.title("Generate Your Self-Review") st.text("""Provide a text dump of your performance information, specific questions you want to address, and any additional instructions for the AI to consider while generating your self-review.""") text_dump = st.text_area('Text Dump (information about your performance)', height=200) questions = st.text_area('Questions to Answer in Self-Review (one per line)', height=100) instructions = st.text_area('Additional Instructions (optional)', height=100) audio_file = st.file_uploader("Upload an audio file", type=["wav", "mp3"])
if st.button('Generate Self-Review'):
if not user_api_key:
st.error("Please enter your API key in the sidebar.")
elif not text_dump or not questions:
st.error("Please provide both the text dump and questions.")
else:
try:
if audio_file is not None:
recognizer = sr.Recognizer()
audio_data = sr.AudioFile(audio_file)
with audio_data as source:
audio = recognizer.record(source)
text_dump += recognizer.recognize_google(audio)
question_list = [q.strip() for q in questions.split('\n') if q.strip()]
self_review_request = SelfReviewRequest(
text_dump=text_dump,
questions=question_list,
instructions=instructions if instructions else None,
llm_type=llm_type,
user_api_key=user_api_key,
model_size=model_size
)
self_review = generate_self_review(**self_review_request.model_dump())
for qa in self_review:
st.markdown(f"**{qa['question']}**")
st.markdown(qa['answer'])
st.markdown("---")
except Exception as e:
st.error(f"An error occurred: {str(e)}")2. In `app_fastapi.py`, add an endpoint to accept audio files:
```python
from fastapi import FastAPI, HTTPException, UploadFile, File
from review import ReviewRequest, generate_review
from self_review import SelfReviewRequest, generate_self_review
from fastapi.middleware.cors import CORSMiddleware
import speech_recognition as sr
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.post("/generate_review")
async def api_generate_review(request: ReviewRequest, audio_file: UploadFile = File(None)):
try:
if audio_file is not None:
recognizer = sr.Recognizer()
audio_data = sr.AudioFile(audio_file.file)
with audio_data as source:
audio = recognizer.record(source)
request.your_review += recognizer.recognize_google(audio)
review = generate_review(
request.your_role,
request.candidate_role,
request.perf_question,
request.your_review,
request.llm_type,
request.user_api_key,
request.model_size
)
return {"review": review}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/generate_self_review")
async def api_generate_self_review(request: SelfReviewRequest, audio_file: UploadFile = File(None)):
try:
if audio_file is not None:
recognizer = sr.Recognizer()
audio_data = sr.AudioFile(audio_file.file)
with audio_data as source:
audio = recognizer.record(source)
request.text_dump += recognizer.recognize_google(audio)
review = generate_self_review(
request.text_dump,
request.questions,
request.instructions,
request.llm_type,
request.user_api_key,
request.model_size
)
return {"self_review": review}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.get("/")
async def root():
return {"message": "Welcome to the Performance Review API"}
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)References
/app.py /app_fastapi.py /review.py /self_review.py
ajitesh123
dev-archie-ai-code-explain-pr[bot]
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