Update app.py

app.py

@@ -1,12 +1,13 @@
+import time
 import gradio as gr
-from sentence_transformers import SentenceTransformer, util
+from sentence_transformers import SentenceTransformer
 import os
 from PyPDF2 import PdfReader
 import docx
 import re
 import google.generativeai as genai
 import pandas as pd
-import concurrent.futures  # For parallel processing
+import concurrent.futures
 
 # Load pre-trained embedding model for basic analysis
 sentence_model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
@@ -155,9 +156,13 @@ def process_resumes(job_desc_file, resumes):
     # Define the key leadership and management skills you're looking for
     required_skills = ["strategic planning", "team management", "project management", "decision making", "communication"]
 
-    # Use ThreadPoolExecutor for concurrent processing
-    with concurrent.futures.ThreadPoolExecutor() as executor:
-        results = list(executor.map(lambda resume: process_resume(resume, job_desc, required_skills), resumes))
+    results = []
+    for idx, resume in enumerate(resumes):
+        # Add a small delay between requests to avoid rate-limiting
+        if idx > 0:  # Skip delay for the first request
+            time.sleep(5)  # Adjust the delay to suit your needs (e.g., 5 seconds)
+        
+        results.append(process_resume(resume, job_desc, required_skills))
 
     # Create a pandas DataFrame for better formatting and downloadable output
     df = pd.DataFrame(results)