Update app.py

app.py

@@ -3,7 +3,6 @@ import fitz  # PyMuPDF
 from fastapi import FastAPI
 import docx
 import re
-import os
 
 def extract_text_from_pdf(file):
     doc = fitz.open(stream=file.read(), filetype="pdf")
@@ -27,8 +26,7 @@ def extract_info(text):
     data["name"] = name_match.group(1).strip() if name_match else ""
     data["email"] = email_match.group(0) if email_match else ""
     data["phone"] = phone_match.group(0) if phone_match else ""
-    
-    # Rough extraction for keywords
+
     skill_keywords = ["Python", "Java", "C++", "NLP", "Machine Learning", "Data Science", "SQL", "React"]
     found_skills = [skill for skill in skill_keywords if skill.lower() in text.lower()]
     data["skills"] = found_skills
@@ -44,23 +42,35 @@ def process_resume(file):
         return {"error": "Unsupported file format"}
 
     extracted_data = extract_info(text)
-    return extracted_data
+    return extracted_data, "✅ Resume processed successfully!"
 
-with gr.Blocks(css="body { max-width: 600px; margin: auto; }") as demo:
-    gr.Markdown("# 📄 Resume Parser")
-    gr.Markdown("Upload a **PDF** or **DOCX** resume. Extracted info will appear below in JSON.")
+with gr.Blocks(title="Smart Resume Parser - JSON Edition", css="body { max-width: 1100px; margin: auto; }") as demo:
+    gr.Markdown("## 📄 Smart Resume Parser – Extract structured info from PDF/DOCX (Deployable API)")
 
     with gr.Row():
-        with gr.Column():
-            file_input = gr.File(label="Upload Resume")
-            output = gr.JSON(label="Extracted Data")
-            submit_btn = gr.Button("Parse")
+        with gr.Column(scale=1):
+            file_input = gr.File(label="📎 Upload Resume (PDF or DOCX)")
+            with gr.Row():
+                analyze_button = gr.Button("🔍 Parse Resume", variant="primary")
+                reset_button = gr.Button("♻️ Reset", variant="stop")
+            status_box = gr.Textbox(label="📊 Status", value="⏳ Waiting for input...", interactive=False)
 
-    submit_btn.click(fn=process_resume, inputs=file_input, outputs=output)
+        with gr.Column(scale=2):
+            output_json = gr.JSON(label="🧠 Extracted Resume Data")
 
-app = gr.mount_gradio_app(app=FastAPI(), blocks=demo, path="/")
+    # State for reset
+    reset_flag = gr.State(False)
+
+    analyze_button.click(
+        fn=process_resume,
+        inputs=[file_input],
+        outputs=[output_json, status_box]
+    )
 
-# For local testing
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run("app:app", host="0.0.0.0", port=7860)
+    reset_button.click(
+        fn=lambda: (None, "⏳ Waiting for input..."),
+        inputs=[],
+        outputs=[output_json, status_box]
+    )
+
+app = gr.mount_gradio_app(app=FastAPI(), blocks=demo, path="/")