Update app.py

app.py

@@ -388,6 +388,30 @@ def style_metric_container(label, value):
 
 # --- OpenAI GPT-3 Assistant ---
 def generate_gpt_response(prompt):
+    """
+    First look up the dataset for relevant information. If no matches are found,
+    generate a GPT response.
+    """
+    # Extract make and model from the prompt (simplified NLP parsing)
+    prompt_lower = prompt.lower()
+    make = None
+    model = None
+    
+    # Example: Parse make and model from user query
+    for word in prompt_lower.split():
+        if word in dataset['Make'].str.lower().unique():
+            make = word
+        elif word in dataset['Model'].str.lower().unique():
+            model = word
+    
+    # If we find relevant data, use it to respond
+    if make:
+        dataset_response = search_dataset(dataset, make, model)
+        if dataset_response is not None:
+            st.write("### Dataset Match Found")
+            st.dataframe(dataset_response)  # Show results to the user
+            return f"I found some information in our dataset about {make.title()} {model.title() if model else ''}. Please see the details above."
+    
     # Ensure the API key is set securely
     # You can use Streamlit's secrets management or environment variables
     openai.api_key = os.getenv("GPT_TOKEN")