Update README.md

README.md

@@ -142,7 +142,27 @@ def get_user_by_email(email):
 result = review_python_code(vulnerable_code)
 print(result)
 ```
-
+#### OR 
+```python
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+pipe = pipeline("text-generation", model="alenphilip/Code_Review_Assistant_Model")
+prompt = "Review this Python code and provide improvements with fixed code:\n\n```python\nclass LockManager:\n    def __init__(self, lock1, lock2):\n        self.lock1 = lock1\n        self.lock2 = lock2\n\n    def acquire_both(self):\n        self.lock1.acquire()\n        self.lock2.acquire() # This might fail\n\n    def release_both(self):\n        self.lock1.release()\n        self.lock2.release()\n```"
+messages = [
+    {"role": "system", "content": "You are a helpful AI assistant specialized in code review and security analysis."},
+    {"role": "user", "content": prompt},
+]
+result = pipe(messages)
+conversation = result[0]['generated_text']
+
+for message in conversation:
+    print(f"\n{message['role'].upper()}:")
+    print("-" * 50)
+    print(message['content'])
+    print()
+
+print("=" * 70)
+```
 # Training Details
 ## Training Data
 The model was trained on a comprehensive dataset of Python code review examples covering: