Update app.py

app.py

@@ -90,16 +90,6 @@ def calculate_semantic_similarity(text1, text2):
     similarity_percentage = similarity_score * 100
     return similarity_percentage
 
-# --- Thresholds --- #
-def categorize_similarity(score):
-    """Categorizes the similarity score into thresholds for better insights."""
-    if score >= 80:
-        return "High Match"
-    elif score >= 50:
-        return "Moderate Match"
-    else:
-        return "Low Match"
-
 # --- Communication Generation with Enhanced Response --- #
 def communication_generator(resume_skills, job_description_skills, skills_similarity, qualifications_similarity, experience_similarity, candidate_experience):
     """Generates a detailed communication response based on similarity scores and additional criteria."""
@@ -170,40 +160,72 @@ def analyze_resume(resume_file, job_description_file):
 
     # Assuming candidate experience is the total of years from the resume
     candidate_experience = sum(resume_experience)
+    required_experience = sum(job_description_experience)  # This assumes job description contains required experience as years
 
     # Generate communication based on analysis
     response_message = communication_generator(
-        resume_skills, job_description_skills,
-        skills_similarity, qualifications_similarity,
-        experience_similarity, candidate_experience
+        resume_skills,
+        job_description_skills,
+        skills_similarity,
+        qualifications_similarity,
+        experience_similarity,
+        candidate_experience
     )
 
-    # Perform sentiment analysis on the resume
-    sentiment_analysis_result = analyze_sentiment(resume_text)
+    # Analyze sentiment for the resume
+    sentiment = analyze_sentiment(resume_text)
 
     return {
         "skills_similarity": skills_similarity,
         "qualifications_similarity": qualifications_similarity,
         "experience_similarity": experience_similarity,
+        "response_message": response_message,
+        "sentiment": sentiment,
         "resume_experience_summary": resume_experience_summary,
         "job_description_experience_summary": job_description_experience_summary,
-        "response_message": response_message,
-        "sentiment": sentiment_analysis_result,
+        "resume_skills": resume_skills,
+        "job_description_skills": job_description_skills,
     }
 
-# --- Gradio Interface Setup --- #
-def upload_and_analyze(resume_file, job_description_file):
-    """Handles file upload and calls the analysis function."""
-    return analyze_resume(resume_file, job_description_file)
-
-# Create a Gradio interface for the application
-interface = gr.Interface(
-    fn=upload_and_analyze,
-    inputs=["file", "file"],
-    outputs=["json"],
-    title="Resume and Job Description Analyzer",
-    description="Upload a resume and a job description to analyze the fit.",
-)
-
-# Run the Gradio interface
-interface.launch()
+# --- Gradio Interface --- #
+def gradio_interface():
+    """Defines and runs the Gradio interface."""
+    with gr.Blocks() as demo:
+        gr.Markdown("# Resume Analyzer")
+        with gr.Row():
+            resume_file = gr.File(label="Upload Resume (PDF/TXT)")
+            job_description_file = gr.File(label="Upload Job Description (PDF/TXT)")
+            analyze_button = gr.Button("Analyze")
+
+        with gr.Tab("Results"):
+            output_message = gr.Textbox(label="Analysis Message", lines=10)
+            skills_similarity_output = gr.Number(label="Skills Similarity (%)")
+            qualifications_similarity_output = gr.Number(label="Qualifications Similarity (%)")
+            experience_similarity_output = gr.Number(label="Experience Similarity (%)")
+            sentiment_output = gr.Textbox(label="Sentiment Analysis")
+            resume_summary_output = gr.Textbox(label="Resume Experience Summary", lines=5)
+            job_description_summary_output = gr.Textbox(label="Job Description Experience Summary", lines=5)
+            resume_skills_output = gr.Textbox(label="Resume Skills", lines=5)
+            job_description_skills_output = gr.Textbox(label="Job Description Skills", lines=5)
+
+        # Link the button to the analysis function
+        analyze_button.click(
+            analyze_resume,
+            inputs=[resume_file, job_description_file],
+            outputs=[
+                output_message,
+                skills_similarity_output,
+                qualifications_similarity_output,
+                experience_similarity_output,
+                sentiment_output,
+                resume_summary_output,
+                job_description_summary_output,
+                resume_skills_output,
+                job_description_skills_output,
+            ]
+        )
+
+    demo.launch()
+
+# Execute the Gradio interface
+gradio_interface()