Update app.py

app.py

@@ -369,4 +369,102 @@ Upload a CV (PDF, DOCX, TXT) and paste the job description text to get an instan
 
 # Input for CV
 st.header("1. Upload Your CV")
-uploaded_cv_file = st.file_uploader("Choose a CV file (PDF, DOCX, TXT)", type=["pdf", "docx", "txt"],
+uploaded_cv_file = st.file_uploader("Choose a CV file (PDF, DOCX, TXT)", type=["pdf", "docx", "txt"], key="cv_uploader")
+cv_text_area = st.text_area("Or paste your CV text here (overrides file upload)", height=250, key="cv_text_area")
+
+cv_content = ""
+if uploaded_cv_file is not None:
+    if uploaded_cv_file.name.endswith('.pdf'):
+        cv_content = extract_text_from_pdf(uploaded_cv_file)
+    elif uploaded_cv_file.name.endswith('.docx'):
+        cv_content = extract_text_from_docx(uploaded_cv_file)
+    elif uploaded_cv_file.name.endswith('.txt'):
+        cv_content = uploaded_cv_file.read().decode("utf-8")
+    st.success("CV file uploaded and parsed successfully!")
+elif cv_text_area: # If text area has content and no file uploaded
+    cv_content = cv_text_area
+
+# Input for Job Description
+st.header("2. Input Job Description")
+job_desc_text_area = st.text_area("Paste the Job Description text here", height=250, key="jd_text_area")
+
+# Analyze Button
+st.markdown("---")
+if st.button("✨ Analyze CV Match ✨", use_container_width=True):
+    if not cv_content:
+        st.error("🚨 Please upload a CV file or paste your CV text to proceed.")
+    if not job_desc_text_area:
+        st.error("🚨 Please paste the Job Description text to proceed.")
+
+    if cv_content and job_desc_text_area:
+        with st.spinner("🚀 Analyzing your documents... This might take a moment!"):
+            try:
+                analysis_results = perform_cv_job_analysis(cv_content, job_desc_text_area)
+
+                st.subheader("💡 Analysis Results Summary 💡")
+
+                # Display KPIs in columns
+                col1, col2, col3 = st.columns(3)
+                with col1:
+                    st.metric(label="Overall Match Score", value=f"{analysis_results['overall_match_score']}%")
+                with col2:
+                    st.metric(label="Skill Match", value=f"{analysis_results['skill_match_percentage']}%")
+                with col3:
+                    exp_status = analysis_results['experience_match_status']
+                    if "Meets" in exp_status or "Exceeds" in exp_status:
+                        st.metric(label="Experience Match", value=exp_status, delta="Good!")
+                    else:
+                        st.metric(label="Experience Match", value=exp_status, delta="Needs attention")
+
+                st.markdown("---")
+
+                st.subheader("📊 Visual Insights")
+
+                # Overall Match Plot
+                fig_overall = create_overall_match_plot(analysis_results['overall_match_score'])
+                st.pyplot(fig_overall)
+                plt.close(fig_overall) # Close figure to free memory
+
+                # Skill Match Plot
+                fig_skill = create_skill_match_plot(analysis_results['matched_skills'], analysis_results['missing_skills'])
+                if fig_skill:
+                    st.pyplot(fig_skill)
+                    plt.close(fig_skill)
+                else:
+                    st.info("No specific skills identified in the job description for a detailed skill match breakdown.")
+
+                # Top Keywords Plot
+                fig_keywords = create_top_keywords_plot(analysis_results['top_cv_keywords'], analysis_results['top_jd_keywords'])
+                st.pyplot(fig_keywords)
+                plt.close(fig_keywords)
+
+                st.markdown("---")
+                st.subheader("📝 Detailed Breakdown")
+
+                st.markdown("#### Skills Analysis")
+                st.write(f"**✅ Matched Skills:**", ", ".join(analysis_results['matched_skills']) if analysis_results['matched_skills'] else "None found matching job description.")
+                st.write(f"**❌ Missing Skills (from Job Description):**", ", ".join(analysis_results['missing_skills']) if analysis_results['missing_skills'] else "🥳 None! Your CV has all specified skills.")
+                st.write(f"**💡 Extra Skills in CV (not in Job Description):**", ", ".join(analysis_results['extra_skills_in_cv']) if analysis_results['extra_skills_in_cv'] else "None. (This is often fine, showing broader capability.)")
+
+                st.markdown("#### Keyword Relevance (Top TF-IDF Terms)")
+                st.write(f"**🤝 Top Common Keywords:**", ", ".join(analysis_results['common_keywords']) if analysis_results['common_keywords'] else "No significant common keywords beyond skills.")
+                st.write(f"**🔍 Top Keywords in Your CV:**", ", ".join(analysis_results['top_cv_keywords']) if analysis_results['top_cv_keywords'] else "N/A")
+                st.write(f"**🎯 Top Keywords in Job Description:**", ", ".join(analysis_results['top_jd_keywords']) if analysis_results['top_jd_keywords'] else "N/A")
+
+
+                st.markdown("#### Experience & Education Comparison")
+                st.write(f"**👤 Your CV's Experience:** `{analysis_results['cv_years_experience']}` years")
+                st.write(f"**💼 Job's Required Experience:** `{analysis_results['jd_years_experience']}` years")
+                st.info(f"**Status:** {analysis_results['experience_match_status']}")
+
+                st.write(f"**🎓 Your CV's Education:** `{analysis_results['cv_education_level']}`")
+                st.write(f"**📚 Job's Required Education:** `{analysis_results['jd_education_level']}`")
+                st.info(f"**Status:** {analysis_results['education_match_status']}")
+
+
+            except Exception as e:
+                st.error(f"An unexpected error occurred during analysis: {e}")
+                st.exception(e) # Show full traceback in Streamlit debug logs
+
+st.markdown("---")
+st.markdown("Developed with ❤️ for Data Science by your mentor")