Update app.py

app.py

@@ -9,7 +9,8 @@ data = pd.read_csv("Injury_History.csv")
 embedding_model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
 
 # Load language model for generation
-generator = pipeline("text-generation", model="gpt-3.5-turbo")  # Example model
+generator = pipeline("text-generation", model="gpt2")  # Lightweight option
+
 
 # Step 1: Create embeddings of injury data
 data['embedding'] = data['Notes'].apply(lambda x: embedding_model.encode(x, convert_to_tensor=True))