Update app.py

app.py

@@ -1,7 +1,7 @@
 import os
 import subprocess
 import streamlit as st
-from huggingface_hub import snapshot_download
+from huggingface_hub import snapshot_download, login
 
 def check_directory_path(directory_name: str) -> str:
     if os.path.exists(directory_name):
@@ -92,6 +92,30 @@ def automate_llama_quantization(hf_model_name, quant_type):
     st.success(f"🎉 All steps completed! Quantized model available at: `{quantized_file}`")
     return quantized_file
 
+def upload_to_huggingface(file_path, repo_id, token):
+    """
+    Uploads a file to Hugging Face Hub.
+    """
+    try:
+        # Log in to Hugging Face
+        login(token=token)
+
+        # Initialize HfApi
+        api = HfApi()
+
+        # Create the repository if it doesn't exist
+        api.create_repo(repo_id, exist_ok=True, repo_type="model")
+
+        # Upload the file
+        api.upload_file(
+            path_or_fileobj=file_path,
+            path_in_repo=os.path.basename(file_path),
+            repo_id=repo_id,
+        )
+        st.success(f"✅ File uploaded to Hugging Face: {repo_id}")
+    except Exception as e:
+        st.error(f"❌ Failed to upload file: {e}")
+
 # Streamlit UI
 st.title("🦙 LLaMA Model Quantization (llama.cpp)")
 
@@ -104,4 +128,17 @@ if start_button:
         quantized_model_path = automate_llama_quantization(hf_model_name, quant_type)
     if quantized_model_path:
         with open(quantized_model_path, "rb") as f:
-            st.download_button("⬇️ Download Quantized Model", f, file_name=os.path.basename(quantized_model_path))
+            st.download_button("⬇️ Download Quantized Model", f, file_name=os.path.basename(quantized_model_path))
+        upload_to_hf = st.checkbox("Upload to Hugging Face")
+        
+        if upload_to_hf:
+            st.write("### Upload to Hugging Face")
+            repo_id = st.text_input("Enter Hugging Face Repository ID (e.g., 'username/repo-name')")
+            hf_token = st.text_input("Enter Hugging Face Token", type="password")
+            
+            if st.button("📤 Upload to Hugging Face"):
+                if repo_id and hf_token:
+                    with st.spinner("Uploading..."):
+                        upload_to_huggingface(quantized_model_path, repo_id, hf_token)
+                else:
+                    st.warning("Please provide a valid repository ID and Hugging Face token.")