Update app.py

app.py

@@ -1,13 +1,18 @@
 import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 import pdfplumber
 import re
 import openpyxl
-from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
+import os
+from huggingface_hub import login
 
-# Authenticate Hugging Face API (ensure you're logged in already)
-model_name = "meta-llama/Llama-3.1-70B-Instruct"  # Replace with your actual model name
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+# Function to authenticate Hugging Face using token
+def authenticate_hf(token):
+    try:
+        login(token)
+        return "Authentication Successful"
+    except Exception as e:
+        return f"Error: {e}"
 
 # Function to extract text from PDF
 def extract_text_from_pdf(pdf_path):
@@ -82,16 +87,27 @@ def process_pdfs(pdfs):
 
     return output_file
 
-# Gradio interface setup with blank API space (Hugging Face integration)
-iface = gr.Interface(
-    fn=process_pdfs,
-    inputs=gr.File(file_count="multiple", type="file"),
-    outputs=gr.File(),
-    live=True,
-    title="AI Resume Parser",
-    description="Upload PDF resumes, and the app will parse and extract Name, Email, Phone, and Skills from them.",
-    examples=[["path_to_sample_resume.pdf"]]  # Provide sample files if necessary
-)
+# Gradio interface setup with Hugging Face API token input
+with gr.Blocks() as app:
+    gr.Markdown("### Hugging Face Authentication")
+    
+    # Input field for Hugging Face API token
+    hf_token = gr.Textbox(label="Hugging Face API Token", placeholder="Enter your Hugging Face token here", type="password")
+    login_button = gr.Button("Authenticate")
+    auth_status = gr.Textbox(label="Authentication Status", interactive=False)
+    
+    # Authenticate Hugging Face model when button is clicked
+    login_button.click(authenticate_hf, inputs=hf_token, outputs=auth_status)
+    
+    gr.Markdown("### Upload PDF Resumes")
+
+    # File input to upload resumes
+    pdfs_input = gr.File(file_count="multiple", type="file")
+    output_file = gr.File()
+
+    # Process the PDFs and parse them
+    process_button = gr.Button("Process Resumes")
+    process_button.click(process_pdfs, inputs=pdfs_input, outputs=output_file)
 
-# Launch the Gradio app
-iface.launch()
+# Launch the app
+app.launch()