Update app.py

app.py

@@ -27,12 +27,12 @@ def process_file(file, instructions, api_key):
             
             Based on this, create 3 appropriate visualizations that provide meaningful insights. For each visualization:
             1. Choose the most suitable plot type (bar, line, scatter, hist, pie, heatmap)
-            2. Determine appropriate data aggregation (e.g., top 5 categories, monthly averages)
+            2. Determine appropriate data aggregation (e.g., top 5 categories, yearly averages)
             3. Select relevant columns for x-axis, y-axis, and any additional dimensions (color, size)
             4. Provide a clear, concise title that explains the insight
 
             Consider data density and choose visualizations that simplify and clarify the information.
-            Limit the number of data points displayed to ensure readability (e.g., top 5, top 10).
+            Limit the number of data points displayed to ensure readability (e.g., top 5, top 10, yearly).
             
             Return your response as a Python list of dictionaries:
             [