import streamlit as st
from utils.cv_processor import evaluate_cv
from utils.interview_agent import InterviewAgent
from utils.report_generator import generate_report
import os
from datetime import datetime

def main():
    st.set_page_config(page_title="AI Interview Agent", layout="wide")
    
    st.title("AI Interview Agent")
    st.write("Upload your CV and start your interview for the desired position.")
    
    # Initialize session state
    if 'interview_started' not in st.session_state:
        st.session_state.interview_started = False
    if 'current_question' not in st.session_state:
        st.session_state.current_question = 0
    if 'answers' not in st.session_state:
        st.session_state.answers = []
    if 'cv_evaluated' not in st.session_state:
        st.session_state.cv_evaluated = False
    if 'cv_rejected' not in st.session_state:
        st.session_state.cv_rejected = False
    
    # Step 1: Job Role and CV Upload
    if not st.session_state.cv_evaluated:
        with st.form("candidate_info"):
            job_role = st.selectbox(
                "Select the job role you're applying for:",
                ["Software Engineer", "Data Scientist", "Product Manager", "UX Designer", "DevOps Engineer"]
            )
            cv_file = st.file_uploader("Upload your CV (PDF or DOCX)", type=["pdf", "docx"])
            submitted = st.form_submit_button("Submit")
            
            if submitted and cv_file:
                with st.spinner("Evaluating your CV..."):
                    # Save the uploaded file
                    file_path = f"data/temp_cv.{'pdf' if cv_file.type == 'application/pdf' else 'docx'}"
                    with open(file_path, "wb") as f:
                        f.write(cv_file.getbuffer())
                    
                    # Evaluate CV
                    evaluation = evaluate_cv(file_path, job_role)
                    
                    if evaluation["is_qualified"]:
                        st.session_state.cv_evaluated = True
                        st.session_state.job_role = job_role
                        st.session_state.cv_evaluation = evaluation
                        st.success("CV evaluation complete! You meet the basic requirements.")
                    else:
                        st.session_state.cv_rejected = True
                        st.session_state.rejection_reasons = evaluation["rejection_reasons"]
                        st.error("Your CV doesn't meet the requirements for this role.")
    
    # Step 2: Interview Process
    if st.session_state.cv_evaluated and not st.session_state.interview_started:
        if st.button("Start Interview"):
            st.session_state.interview_started = True
            st.session_state.interview_agent = InterviewAgent(job_role, st.session_state.cv_evaluation["cv_summary"])
            st.session_state.questions = st.session_state.interview_agent.get_questions()
            st.experimental_rerun()
    
    if st.session_state.interview_started:
        interview_ui()
    
    # Step 3: Show rejection if CV was rejected
    if st.session_state.cv_rejected:
        st.error("Unfortunately, your CV doesn't meet the requirements for this role.")
        st.write("Reasons for rejection:")
        for reason in st.session_state.rejection_reasons:
            st.write(f"- {reason}")
        if st.button("Try a different role"):
            st.session_state.cv_rejected = False
            st.session_state.cv_evaluated = False
            st.experimental_rerun()

def interview_ui():
    agent = st.session_state.interview_agent
    questions = st.session_state.questions
    
    # Show current question or completion
    if st.session_state.current_question < len(questions):
        question = questions[st.session_state.current_question]
        
        st.subheader(f"Question {st.session_state.current_question + 1}/{len(questions)}")
        st.write(question["text"])
        
        # Answer input
        answer = st.text_area("Your answer:", key=f"answer_{st.session_state.current_question}")
        
        if st.button("Submit Answer"):
            evaluation = agent.evaluate_answer(question, answer)
            st.session_state.answers.append({
                "question": question,
                "answer": answer,
                "evaluation": evaluation
            })
            st.session_state.current_question += 1
            st.experimental_rerun()
    else:
        # Interview complete
        st.success("Interview completed!")
        final_evaluation = agent.final_evaluation(st.session_state.answers)
        
        # Display results
        st.subheader("Interview Results")
        st.write(f"Overall Score: {final_evaluation['score']}/10")
        st.write(f"Band: {final_evaluation['band']}")
        
        st.subheader("Detailed Feedback")
        for i, answer in enumerate(st.session_state.answers):
            st.write(f"**Question {i+1}:** {answer['question']['text']}")
            st.write(f"**Your Answer:** {answer['answer']}")
            st.write(f"**Feedback:** {answer['evaluation']['feedback']}")
            st.write("---")
        
        # Generate and download report
        report_path = generate_report(
            st.session_state.job_role,
            st.session_state.cv_evaluation["cv_summary"],
            st.session_state.answers,
            final_evaluation
        )
        
        with open(report_path, "rb") as f:
            st.download_button(
                "Download Interview Report",
                f,
                file_name=f"Interview_Report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf",
                mime="application/pdf"
            )
        
        if st.button("Start New Interview"):
            reset_session()

def reset_session():
    for key in list(st.session_state.keys()):
        del st.session_state[key]
    st.experimental_rerun()

if __name__ == "__main__":
    main()