Update app.py

app.py

@@ -4,11 +4,10 @@ from parser import parse_python_code
 import os
 import json
 import io
-from database import init_chromadb, populate_sample_db, store_program, query_programs, load_chromadb_from_hf, HF_DATASET_NAME, HF_TOKEN, DB_NAME
+from database import init_chromadb, populate_sample_db, store_program, query_programs, load_chromadb_from_hf, HF_DATASET_NAME, HF_KEY, DB_NAME, USE_GPU
 
 # User-configurable variables
 UPLOAD_DIR = "./uploads"  # Directory for uploads
-USE_GPU = False  # Default to CPU, set to True for GPU if available
 
 app = Flask(__name__)
 
@@ -52,7 +51,7 @@ def index():
         elif 'query_ops' in request.form and request.form['query_ops'].strip():
             # Handle query for operations (category sequence)
             operations = [op.strip() for op in request.form['query_ops'].split(',')]
-            client = load_chromadb_from_hf(HF_DATASET_NAME, HF_TOKEN)  # Load from Hugging Face
+            client = load_chromadb_from_hf(HF_DATASET_NAME, HF_KEY)  # Load from Hugging Face
             query_results = query_programs(client, operations, DB_NAME)
             return render_template(
                 'results_partial.html',
@@ -65,7 +64,7 @@ def index():
         elif 'semantic_query' in request.form and request.form['semantic_query'].strip():
             # Handle semantic query (natural language description)
             semantic_query = request.form['semantic_query']
-            client = load_chromadb_from_hf(HF_DATASET_NAME, HF_TOKEN)  # Load from Hugging Face
+            client = load_chromadb_from_hf(HF_DATASET_NAME, HF_KEY)  # Load from Hugging Face
             query_results = query_programs(client, None, DB_NAME, semantic_query=semantic_query)
             return render_template(
                 'results_partial.html',
@@ -90,7 +89,7 @@ def index():
         return 'No file, code, or query provided', 400
 
     # Initial page load
-    client = load_chromadb_from_hf(HF_DATASET_NAME, HF_TOKEN)  # Load from Hugging Face on startup
+    client = load_chromadb_from_hf(HF_DATASET_NAME, HF_KEY)  # Load from Hugging Face on startup
     # If no dataset exists locally, populate with samples
     try:
         if not client.list_collections()[0].name == DB_NAME:
@@ -141,4 +140,4 @@ def generate_description_tokens(sequence, vectors):
 if __name__ == '__main__':
     if not os.path.exists(UPLOAD_DIR):
         os.makedirs(UPLOAD_DIR)
-    app.run(host="0.0.0.0", port=7860)
+    app.run(host="0.0.0.0", port=7860)  # Bind to all interfaces for Hugging Face Spaces