Update app.py

app.py

@@ -129,7 +129,7 @@ def communication_generator(resume_skills, job_description_skills, skills_simila
     return message
 
 # --- Sentiment Analysis --- #
-def sentiment_analysis(text):
+def analyze_sentiment(text):
     """Analyzes the sentiment of the text."""
     model_name = "mrm8488/distiluse-base-multilingual-cased-v2-finetuned-stsb_multi_mt-es"
     tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -173,53 +173,37 @@ def analyze_resume(resume_file, job_description_file):
 
     # 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)
+
     return {
-        "Resume Experience Summary": resume_experience_summary,
-        "Job Description Experience Summary": job_description_experience_summary,
-        "Skills Similarity": skills_similarity,
-        "Qualifications Similarity": qualifications_similarity,
-        "Experience Similarity": experience_similarity,
-        "Candidate Experience": candidate_experience,
-        "Response Message": response_message,
+        "skills_similarity": skills_similarity,
+        "qualifications_similarity": qualifications_similarity,
+        "experience_similarity": experience_similarity,
+        "resume_experience_summary": resume_experience_summary,
+        "job_description_experience_summary": job_description_experience_summary,
+        "response_message": response_message,
+        "sentiment": sentiment_analysis_result,
     }
 
-
-
-# --- Gradio Interface --- #
-def main():
-    """Runs the Gradio application for resume analysis."""
-    interface = gr.Interface(
-        fn=analyze_resume,
-        inputs=[
-            gr.File(label="Upload Resume (PDF/TXT)", type="filepath"),
-            gr.File(label="Upload Job Description (PDF/TXT)", type="filepath")
-        ],
-        outputs=[
-            gr.Textbox(label="Skills Similarity"),
-            gr.Textbox(label="Qualifications Similarity"),
-            gr.Textbox(label="Experience Similarity"),
-            gr.Textbox(label="Communication Response"),
-            gr.Textbox(label="Sentiment Analysis"),
-            gr.Textbox(label="Resume Skills"),
-            gr.Textbox(label="Job Description Skills"),
-            gr.Textbox(label="Resume Qualifications"),
-            gr.Textbox(label="Job Description Qualifications"),
-            gr.Textbox(label="Resume Experience"),
-            gr.Textbox(label="Job Description Experience")
-        ],
-        title="Resume and Job Description Analysis",
-        description="Analyze a resume against a job description to evaluate skills, qualifications, experience, and generate communication insights."
-    )
-
-    interface.launch()
-
-if __name__ == "__main__":
-    main()
+# --- 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()