fix: local runs

api_server.py

@@ -9,16 +9,15 @@ os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 from tensorflow import keras
 from flask import Flask, jsonify, request
 
-LOCAL = False
+LOCAL = True
 
 # Load the saved model into memory
 if LOCAL is True:
+    model = keras.models.load_model('artifacts/models/mnist_model.h5')
+else:
     REPO_ID = "1vash/mnist-model"
     FILENAME = "mnist_model.h5"
     model = keras.models.load_model(hf_hub_download(repo_id=REPO_ID, filename=FILENAME))
-else:
-    model = keras.models.load_model('artifacts/models/mnist_model.h5')
-
 
 # Initialize the Flask application
 app = Flask(__name__)
@@ -117,4 +116,4 @@ if __name__ == '__main__':
 # 2. You can use Chain calls of OpenAI API
 # 3. Using your own ML model in combination with openAPI functionality
 # 4. ...
-##################
+##################