Update app.py

app.py

@@ -2,6 +2,18 @@ import streamlit as st
 from utils import extract_text, anonymize_text, score_synopsis
 from llama_cpp import Llama
 import os
+from huggingface_hub import snapshot_download
+import os
+
+# Choose a directory to store the model
+model_dir = "./gemma-3-4b-it-qat-q4_0"
+
+# Download the GGUF model
+snapshot_download(
+    repo_id="google/gemma-3-4b-it-qat-q4_0-gguf",
+    local_dir=model_dir,
+    local_dir_use_symlinks=False  # Ensures real files are written, not symlinks
+)
 
 st.set_page_config(page_title="Synopsis Scorer", layout="wide")
 
@@ -45,10 +57,10 @@ if article_file and synopsis_file:
             
             # LLM feedback
             try:
-                llm = Llama.from_pretrained(
-                    repo_id="google/gemma-3-4b-it-qat-q4_0-gguf",
-                    filename="gemma-3-4b-it-q4_0.gguf"
+                llm = Llama(
+                model_path="gemma-3-4b-it-q4_0.gguf"  
                 )
+                
                 prompt = (
                     "You are an expert writing evaluator. The user has uploaded two text documents: "
                     "1) a short synopsis, and 2) a longer article (source content). "