import streamlit as st
from ats_optimizer.core import ResumeAnalyzer, ResumeOptimizer
from ats_optimizer.data_models import Resume, JobDescription
from ats_optimizer.utils.file_handlers import FileHandler  # Updated import
# from ats_optimizer.utils import FileHandler, Config
from ats_optimizer.utils.config_manager import Config
from pathlib import Path
import tempfile
import sys

# Fix module imports for Hugging Face
sys.path.append(str(Path(__file__).parent))

# def main():
#     # Initialize components
#     config = Config('config.yaml')
#     analyzer = ResumeAnalyzer()
#     optimizer = ResumeOptimizer(config.deepseek_api_key)
    
#     # Streamlit UI
#     st.title("🚀 ATS Optimizer Pro")
#     st.markdown("Upload your resume and job description to analyze and optimize for ATS compatibility")

#     # File upload section
#     with st.expander("Upload Files", expanded=True):
#         col1, col2 = st.columns(2)
#         with col1:
#             resume_file = st.file_uploader("Resume", type=["pdf", "docx"], key="resume_upload")
#         with col2:
#             jd_file = st.file_uploader("Job Description", type=["pdf", "docx", "txt"], key="jd_upload")

#     if st.button("Analyze", type="primary"):
#         if resume_file and jd_file:
#             with st.spinner("Processing files..."):
#                 try:
#                     # Save uploaded files
#                     with tempfile.TemporaryDirectory() as temp_dir:
#                         resume_path = FileHandler.save_uploaded_file(resume_file, temp_dir)
#                         jd_path = FileHandler.save_uploaded_file(jd_file, temp_dir)
                        
#                         if not resume_path or not jd_path:
#                             st.error("Failed to process uploaded files")
#                             return
                        
#                         # Analyze documents
#                         resume = analyzer.parse_resume(resume_path)
#                         jd = analyzer.parse_jd(jd_path)
                        
#                         # Calculate score
#                         score = analyzer.calculate_ats_score(resume, jd)
                        
#                         # Display results
#                         st.subheader("📊 Analysis Results")
#                         st.metric("Overall ATS Score", f"{score['overall_score']:.1f}%")
                        
#                         with st.expander("Detailed Scores"):
#                             st.write(f"Keyword Match: {score['keyword_score']:.1f}%")
#                             st.write(f"Section Completeness: {score['section_score']:.1f}%")
#                             st.write(f"Experience Match: {score['experience_score']:.1f}%")
                        
#                         # Optimization section
#                         st.subheader("🛠 Optimization")
#                         if st.button("Optimize Resume", key="optimize_btn"):
#                             with st.spinner("Rewriting resume..."):
#                                 optimized = optimizer.rewrite_resume(resume, jd)
#                                 temp_output = Path(temp_dir) / "optimized_resume.docx"
#                                 FileHandler.save_resume(optimized, str(temp_output))
                                
#                                 st.success("Optimization complete!")
#                                 with open(temp_output, "rb") as f:
#                                     st.download_button(
#                                         "Download Optimized Resume",
#                                         data=f,
#                                         file_name="optimized_resume.docx",
#                                         mime="application/vnd.openxmlformats-officedocument.wordprocessingml.document"
#                                     )
                
#                 except Exception as e:
#                     st.error(f"An error occurred: {str(e)}")
#                     st.stop()
#         else:
#             st.warning("Please upload both resume and job description files")

# if __name__ == "__main__":
#     main()

def main():
    # Initialize components
    config = Config('config.yaml')
    analyzer = ResumeAnalyzer()
    optimizer = ResumeOptimizer(config.deepseek_api_key)
    
    # Streamlit UI
    st.title("ATS Optimizer Pro")
    
    # File upload
    resume_file = st.file_uploader("Upload Resume", type=["pdf", "docx"])
    jd_file = st.file_uploader("Upload Job Description", type=["pdf", "docx", "txt"])
    
    if st.button("Analyze"):
        if resume_file and jd_file:
            with st.spinner("Processing..."):
                try:
                    # Create temp directory
                    with tempfile.TemporaryDirectory() as temp_dir:
                        # Save uploaded files
                        resume_path = FileHandler.save_uploaded_file(resume_file, temp_dir)
                        jd_path = FileHandler.save_uploaded_file(jd_file, temp_dir)
                        
                        if not resume_path or not jd_path:
                            st.error("Failed to process uploaded files")
                            return
                        
                        # Analyze documents
                        resume = analyzer.parse_resume(resume_path)
                        jd = analyzer.parse_jd(jd_path)
                        
                        # Calculate score
                        score = analyzer.calculate_ats_score(resume, jd)
                        
                        # Display results
                        st.subheader("Analysis Results")
                        st.json(score)
                        
                        # Optimization
                        if st.button("Optimize Resume"):
                            optimized = optimizer.rewrite_resume(resume, jd)
                            output_path = os.path.join(temp_dir, "optimized_resume.docx")
                            if FileHandler.save_resume(optimized, output_path):
                                with open(output_path, "rb") as f:
                                    st.download_button(
                                        "Download Optimized Resume",
                                        data=f,
                                        file_name="optimized_resume.docx"
                                    )
                except Exception as e:
                    st.error(f"An error occurred: {str(e)}")
        else:
            st.warning("Please upload both resume and job description files")