import streamlit as st
from ocr import extract_screen_text
from stt import transcribe_audio
from interview_engine import generate_question
from evaluation import evaluate_response

# Initialize session state
if "context_store" not in st.session_state:
    st.session_state.context_store = ""

st.title("🎤 AI-Driven Automated Project Interviewer")
st.write(
    "Upload a screenshot of your project (slides/code/diagrams) and explain it verbally. "
    "The AI will ask follow-up questions and provide feedback."
)

# Upload screen image
screen_file = st.file_uploader("Upload Screen / Slide / Code Screenshot", type=["png", "jpg", "jpeg"])

# Upload audio explanation
audio_file = st.file_uploader("Explain Your Project (Audio file)", type=["wav", "mp3", "m4a"])

if st.button("Submit"):

    # Process screen
    if screen_file is not None:
        screen_text = extract_screen_text(screen_file)
        st.session_state.context_store += "\n" + screen_text

    # Process audio
    if audio_file is not None:
        student_response = transcribe_audio(audio_file)

        # Generate follow-up question
        question = generate_question(st.session_state.context_store, student_response)

        # Evaluate response
        score = evaluate_response(st.session_state.context_store, student_response)

        # Display results
        st.subheader("AI Interviewer Question:")
        st.write(question)

        st.subheader("Evaluation & Feedback:")
        st.json(score)
    else:
        st.warning("Please upload an audio explanation to get a question and feedback.")