Update app.py

app.py

@@ -7,6 +7,9 @@ from transformers import pipeline
 import numpy as np
 from transformers import AutoFeatureExtractor
 from transformers import AutoModelForImageClassification
+import plotly.graph_objects as go
+import plotly
+import re
 
 st.set_page_config(layout='wide',
                    page_title='Food Category Classification & Recipes'
@@ -192,9 +195,23 @@ def main():
                 st.write("**Iron:** ", random_recipe['Iron'])
                 st.write("**Potassium:** ", random_recipe['Potassium'])
                 st.write("**Tags:** ", random_recipe['Tags'])
-                st.write("**Recipe URL:** ", random_recipe['Recipe URLs'])
+                st.write("**Recipe URL:** ", random_recipe['Recipe URLs'])  
+                # extract only numeric values
+                values = [float(re.sub(r'[^\d.]+', '', random_recipe['Total Fat'])), 
+                        float(re.sub(r'[^\d.]+', '', random_recipe['Saturated Fat'])), 
+                        float(re.sub(r'[^\d.]+', '', random_recipe['Cholesterol'])), 
+                        float(re.sub(r'[^\d.]+', '', random_recipe['Sodium'])), 
+                        float(re.sub(r'[^\d.]+', '', random_recipe['Total Carbohydrate'])), 
+                        float(re.sub(r'[^\d.]+', '', random_recipe['Dietary Fiber'])), 
+                        float(re.sub(r'[^\d.]+', '', random_recipe['Total Sugars'])), 
+                        float(re.sub(r'[^\d.]+', '', random_recipe['Protein']))]
+                # create pie chart
+                labels = ['Total Fat', 'Saturated Fat', 'Cholesterol', 'Sodium', 'Total Carbohydrate', 'Dietary Fiber', 'Total Sugars', 'Protein']
+                fig = go.Figure(data=[go.Pie(labels=labels, values=values)])
+                st.markdown("### Macronutrients Pie Chart ;)")
+                st.plotly_chart(fig)  
                 st.markdown("### JSON:")
-                st.write(response_json)                
+                st.write(response_json)                                   
             else:
                 st.markdown("### Recommended Recipe:")
                 st.write("**Title:** ", response_json[0]['Title'])
@@ -225,8 +242,22 @@ def main():
                 st.write("**Potassium:** ", response_json[0]['Potassium'])
                 st.write("**Tags:** ", response_json[0]['Tags'])
                 st.write("**Recipe URL:** ", response_json[0]['Recipe URLs'])
+                # extract only numeric values
+                values = [float(re.sub(r'[^\d.]+', '', response_json[0]['Total Fat'])), 
+                        float(re.sub(r'[^\d.]+', '', response_json[0]['Saturated Fat'])), 
+                        float(re.sub(r'[^\d.]+', '', response_json[0]['Cholesterol'])), 
+                        float(re.sub(r'[^\d.]+', '', response_json[0]['Sodium'])), 
+                        float(re.sub(r'[^\d.]+', '', response_json[0]['Total Carbohydrate'])), 
+                        float(re.sub(r'[^\d.]+', '', response_json[0]['Dietary Fiber'])), 
+                        float(re.sub(r'[^\d.]+', '', response_json[0]['Total Sugars'])), 
+                        float(re.sub(r'[^\d.]+', '', response_json[0]['Protein']))]
+                # create pie chart
+                labels = ['Total Fat', 'Saturated Fat', 'Cholesterol', 'Sodium', 'Total Carbohydrate', 'Dietary Fiber', 'Total Sugars', 'Protein']
+                fig = go.Figure(data=[go.Pie(labels=labels, values=values)])
+                st.markdown("### Macronutrients Pie Chart ;)")
+                st.plotly_chart(fig)   
                 st.markdown("### JSON:")
-                st.write(response_json)
+                st.write(response_json)           
 
         st.markdown("<hr style='text-align: center;'>", unsafe_allow_html=True)
         st.markdown("<p style='text-align: center'><a href='https://github.com/Kaludii'>Github</a> | <a href='https://huggingface.co/Kaludi'>HuggingFace</a></p>", unsafe_allow_html=True)