add main fuc

Author: Joshua Levi

.vscode/launch.json

@@ -1,6 +1,7 @@
 {
   "version": "0.2.0",
   "configurations": [
+    
     {
       "name": "Excel Desktop (Edge Chromium)",
       "type": "msedge",

.vscode/settings.json

@@ -0,0 +1,22 @@
+
+import formulas_extraction
+import metadata_generator
+
+
+def main():
+    """
+    Runs all the scripts in the llm_alpha_models directory.
+    """
+    print("Running formulas_extraction.py...")
+    formulas_extraction.main()
+    print("\n" + "="*20 + "\n")
+    
+    print("Running metadata_generator.py...")
+    metadata_generator.main()
+    print("\n" + "="*20 + "\n")  
+    
+   
+
+
+if __name__ == "__main__":
+    main()

llm_alpha_models/__pycache__/formulas_extraction.cpython-313.pyc

@@ -1,5 +1,6 @@
 import json
 import os
+import time
 from collections import defaultdict
 from dotenv import load_dotenv
 from xai_sdk import Client
@@ -10,12 +11,10 @@
 from formulas_extraction import get_absolute_references
 
 # Path to your existing JSON
-input_path_MAC = "/Users/joshualevi/git_projects/playground_reg/jsonformatter.JSON"
-input_path_WIN = "D:\\Entrepreneurship\\ProJets Venture\\Upwork - Alessandro Baccini\\excel-addin-react\\llm_alpha_models\\jsonformatter.JSON"
+# Construct the path to jsonformatter.JSON relative to the current script
+script_dir = os.path.dirname(__file__)
+input_path = os.path.join(script_dir, "jsonformatter.JSON")
 
-# Determine which path to use based on OS
-import platform
-input_path = input_path_MAC if platform.system() == 'Darwin' else input_path_WIN
 
 # Load JSON
 with open(input_path, "r", encoding='utf-8') as f:
@@ -302,4 +301,7 @@ def main():
     print(f"✅ Metadata with dependencies saved to {output_path}")
 
 if __name__ == "__main__":
-    main()
+    start_time = time.time()
+    main()
+    end_time = time.time()
+    print(f"✅ Script finished in {end_time - start_time:.2f} seconds")

llm_alpha_models/__pycache__/metadata_generator.cpython-313.pyc

@@ -8,9 +8,9 @@ def main():
     Main function to initialize the client, send a prompt to the AI,
     and print the response.
     """
-    # Build the path to the .env file relative to this script's location
-    script_dir = os.path.dirname(__file__)
-    dotenv_path = os.path.join(script_dir, '.env')
+    # Build the path to the .env file in the project root
+    parent_dir = os.path.dirname(os.path.dirname(__file__))
+    dotenv_path = os.path.join(parent_dir, '.env')
 
     if not os.path.exists(dotenv_path):
         raise FileNotFoundError(f".env file not found at {dotenv_path}")