Update app.py

app.py

@@ -235,41 +235,44 @@ def validate_analyst_output(analyst_output):
 def create_visualizations(analyst_output):
     chart_paths = []
     validated_data = validate_analyst_output(analyst_output)
-    if validated_data:
-        data = pd.DataFrame(validated_data)
-        try:
-            if data.empty:
-                raise ValueError("Data for visualizations is empty.")
 
-            bar_chart = px.bar(data, x="Category", y="Values", title="Patent Trends by Category")
-            st.plotly_chart(bar_chart)
-            with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_chart:
-                bar_chart.write_image(temp_chart.name)
-                chart_paths.append(temp_chart.name)
+    if validated_data:
+        for item in validated_data:
+            category = item["Category"]
+            values = item["Values"]
+
+            # Handle dictionary-type data for bar charts
+            if isinstance(values, dict):
+                df = pd.DataFrame(list(values.items()), columns=["Label", "Count"])
+                chart = px.bar(df, x="Label", y="Count", title=f"{category} Analysis")
+
+            # Handle list-type data for pie charts
+            elif isinstance(values, list):
+                df = pd.DataFrame(values, columns=["Label"])
+                df["Count"] = 1  # Assign count for visualization
+                chart = px.pie(df, names="Label", values="Count", title=f"{category} Distribution")
+
+            # Handle text data by converting it into a simple table
+            elif isinstance(values, str):
+                st.subheader(f"{category} Insights")
+                st.table(pd.DataFrame({"Insights": [values]}))
+                continue  # Skip visualization for text data
 
-            pie_chart = px.pie(data, names="Category", values="Values", title="Category Distribution")
-            st.plotly_chart(pie_chart)
-            with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_chart:
-                pie_chart.write_image(temp_chart.name)
-                chart_paths.append(temp_chart.name)
+            else:
+                st.warning(f"Unsupported data format in category: {category}")
+                continue
 
-            heatmap_chart = px.density_heatmap(data, x="Category", y="Values", title="Regional Patent Density")
-            st.plotly_chart(heatmap_chart)
-            with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_chart:
-                heatmap_chart.write_image(temp_chart.name)
-                chart_paths.append(temp_chart.name)
+            # Display the chart in Streamlit
+            st.plotly_chart(chart)
 
-            multi_line_chart = px.line(data, x="Category", y="Values", title="Trends Over Time")
-            st.plotly_chart(multi_line_chart)
+            # Save the chart for PDF generation
             with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_chart:
-                multi_line_chart.write_image(temp_chart.name)
+                chart.write_image(temp_chart.name)
                 chart_paths.append(temp_chart.name)
 
-        except Exception as e:
-            logging.error(f"Error generating visualization: {e}")
-            st.error(f"Error generating visualization: {e}")
     return chart_paths
 
+
 def display_table(analyst_output):
     table_data = []
     validated_data = validate_analyst_output(analyst_output)