add secret

app.py

@@ -49,6 +49,9 @@ os.makedirs(LOG_DIR, exist_ok=True, mode=0o777)
 os.environ["HF_HOME"] = os.path.join(PERSISTENT_PATH, ".huggingface")
 os.makedirs(os.environ["HF_HOME"], exist_ok=True, mode=0o777)
 
+# Set Hugging Face token
+HF_TOKEN = os.getenv("HF_TOKEN")
+
 # Logging Setup
 logging.basicConfig(
     filename=os.path.join(LOG_DIR, "app.log"),
@@ -61,15 +64,22 @@ logger = logging.getLogger(__name__)
 model = None
 
 def initialize_model():
+    """
+    Initialize the sentence transformer model.
+
+    Returns:
+        bool: Whether the model was successfully initialized.
+    """
     global model
     try:
         if model is None:
             model_cache = os.path.join(PERSISTENT_PATH, "models")
             os.makedirs(model_cache, exist_ok=True, mode=0o777)
-            model = SentenceTransformer(EMBEDDING_MODEL_NAME, cache_folder=model_cache)
+            # Use the HF_TOKEN to load the model
+            model = SentenceTransformer(EMBEDDING_MODEL_NAME, cache_folder=model_cache, use_auth_token=HF_TOKEN)
             logger.info(f"Initialized model: {EMBEDDING_MODEL_NAME}")
         return True
-    except requests.exceptions.ConnectionError as e:
+    except requests.exceptions.RequestException as e:
         logger.error(f"Connection error during model download: {str(e)}\n{traceback.format_exc()}")
         return False
     except Exception as e:
@@ -116,7 +126,7 @@ def get_model():
 @spaces.GPU
 def process_files(files):
     if not files:
-        return "Please upload one or more .txt files.", "", ""
+        return "Please upload one or more.txt files.", "", ""
 
     try:
         if not initialize_model():
@@ -124,7 +134,7 @@ def process_files(files):
 
         valid_files = [f for f in files if f.name.lower().endswith('.txt')]
         if not valid_files:
-            return "No .txt files found. Please upload valid .txt files.", "", ""
+            return "No.txt files found. Please upload valid.txt files.", "", ""
 
         all_chunks = []
         processed_files = 0
@@ -180,7 +190,7 @@ def semantic_search(query, top_k=5):
     global model
     if model is None:
         return "Model not initialized. Please process files first."
-    
+
     try:
         # Load saved embeddings and chunks from OUTPUTS_DIR
         embeddings_file = os.path.join(OUTPUTS_DIR, "embeddings.npy")
@@ -277,7 +287,7 @@ def create_gradio_interface():
                 step=1,
                 label="Number of results to return"
             )
-            search_button = gr.Button("🔍 Search")
+            search_button = gr.Button(" Search")
             results_output = gr.Textbox(
                 label="Search Results",
                 lines=10,
@@ -289,14 +299,14 @@ def create_gradio_interface():
                 outputs=results_output
             )
 
-            download_button = gr.Button("⬇️ Download Results")
+            download_button = gr.Button(" Download Results")
             download_button.click(
                 fn=download_results,
                 outputs=[gr.File(label="Download Results")]
             )
 
         with gr.Tab("Outputs"):
-            browse_button = gr.Button("📁 Browse Outputs")
+            browse_button = gr.Button(" Browse Outputs")
             browse_button.click(
                 fn=browse_outputs,
                 outputs=[gr.Textbox(label="Browse Status")]
@@ -306,4 +316,4 @@ def create_gradio_interface():
 
 if __name__ == "__main__":
     demo = create_gradio_interface()
-    demo.launch(server_name="0.0.0.0")
+    demo.launch(server_name="0.0.0.0")