Update app.py

app.py

@@ -3,6 +3,7 @@ import torch
 from transformers import pipeline
 import pdfplumber
 import re
+import pandas as pd
 
 # Load pre-trained model for Named Entity Recognition (NER) to extract details
 nlp = pipeline("ner", model="dbmdz/bert-large-cased-finetuned-conll03-english", framework="pt")
@@ -45,7 +46,7 @@ def parse_resume(resume_text):
         else:
             certifications.append(entity['word'])
 
-    # Create a JSON-like output
+    # Create a dictionary of parsed data
     parsed_data = {
         "Phone": phone[0] if phone else "Not found",
         "Email": email[0] if email else "Not found",
@@ -57,18 +58,30 @@ def parse_resume(resume_text):
 
     return parsed_data
 
-# Define Gradio interface
-def resume_parser(pdf_file):
-    """Main function for resume parsing"""
-    resume_text = extract_text_from_pdf(pdf_file)
-    parsed_info = parse_resume(resume_text)
-    return parsed_info
+def process_resumes(pdf_files):
+    """Process multiple resumes and output a single Excel file."""
+    all_parsed_data = []
+
+    # Loop through each uploaded PDF file and parse the data
+    for pdf_file in pdf_files:
+        resume_text = extract_text_from_pdf(pdf_file)
+        parsed_info = parse_resume(resume_text)
+        all_parsed_data.append(parsed_info)
+
+    # Convert the parsed data into a pandas DataFrame
+    df = pd.DataFrame(all_parsed_data)
 
-# Create the Gradio interface
+    # Save the DataFrame to an Excel file
+    output_file = "parsed_resumes.xlsx"
+    df.to_excel(output_file, index=False)
+
+    return output_file
+
+# Define Gradio interface
 gr.Interface(
-    fn=resume_parser,
-    inputs=gr.File(label="Upload Resume (PDF)"),
-    outputs=gr.JSON(label="Parsed Information"),
+    fn=process_resumes,
+    inputs=gr.File(file_count="multiple", label="Upload Resumes (PDFs)"),
+    outputs=gr.File(label="Download Parsed Data (Excel)"),
     title="AI Resume Parser",
-    description="Upload a resume (PDF) to extract details like Name, Email, Phone, Skills, Experience, Education, and Certifications."
+    description="Upload multiple resumes (PDFs) to extract details like Name, Email, Phone, Skills, Experience, Education, and Certifications. The results will be saved in an Excel file."
 ).launch()