adding gen ai support

app.py

@@ -381,7 +381,7 @@ if st.button('Generate Predictions'):
             print(
                 "Sorry, Current model couldn't provide predictions on the target variable you selected.")
         else:
-            st.markdown('##### Current Character Count in Your Email is: <span style="color:blue">{}</span>'.format(
+            st.markdown('##### Current Character Count in Your Email is: <span style="color:yellow">{}</span>'.format(
                 character_cnt), unsafe_allow_html=True)
             # st.info('The model predicts that it achieves a {} of {}%'.format(target, str(round(output_rate*100,2))))
             if target == 'conversion_rate':
@@ -389,7 +389,7 @@ if st.button('Generate Predictions'):
             else:
                 target_vis = 'Open_Rate'
                 
-            st.markdown('##### The model predicts that it achieves a <span style="color:blue">{}</span> of <span style="color:blue">{}</span>%'.format(
+            st.markdown('##### The model predicts that it achieves a <span style="color:yellow">{}</span> of <span style="color:yellow">{}</span>%'.format(
                 target_vis, str(round(output_rate*100, 3))), unsafe_allow_html=True)
             selected_industry_code = industry_code_dict.get(industry)
 
@@ -441,10 +441,10 @@ if st.button('Generate Predictions'):
             if selected_variable == "Click_Through_Rate":
                 selected_variable = "Conversion_Rate"
 
-            st.markdown('##### To get higher, <span style="color:blue">{}</span>, the model recommends the following options:'.format(
+            st.markdown('##### To get higher, <span style="color:yellow">{}</span>, the model recommends the following options:'.format(
                 selected_variable), unsafe_allow_html=True)
             if len(df_reco_opt_rank) == 0:
-                st.markdown('##### You ve already achieved the highest, <span style="color:blue">{}</span>, with the current character count!'.format(
+                st.markdown('##### You ve already achieved the highest, <span style="color:yellow">{}</span>, with the current character count!'.format(
                     selected_variable), unsafe_allow_html=True)
             else:
                 #for _, row in df_reco_opt_rank.iterrows():
@@ -498,26 +498,25 @@ if st.button('Generate Predictions'):
                     st.write("\n")
                     chars_out = dict(zip(chars, sel_var_values))
                     sorted_chars_out = sorted(chars_out.items(), key=lambda x: x[1], reverse=True)
+                    prefrence_variables=res=["charcter counts: "+str(x)+", Target Rate: "+str(y) for x,y in zip(chars,sel_var_values)]
+                    preference = st.selectbox(
+                                'Please select your preferences',
+                                prefrence_variables,
+                                index=1
+                            )
+                    if st.button('Generate AI Recommended Email'):
+                        if(preference is None):
+                            st.error('Please upload a email (HTML format)')
+                        else:
+                            ai_generated_email=generate_example_email_with_context(email_body, campaign, industry, target, sorted_chars_out, preference)
+                            st.markdown('##### Here is the recommended Generated Email for you:')
+                            st.markdown('####### {}:'.format(ai_generated_email),unsafe_allow_html=True)
                     preference= "charcter counts: "+str(573)+", Target Rate: "+str(37.2)
                     ai_generated_email=generate_example_email_with_context(email_body, campaign, industry, target, sorted_chars_out, preference)
                     print("ai_generated_email: ",ai_generated_email)
                     st.markdown('##### Here is the recommended Generated Email for you:')
                     st.markdown('####### {}'.format(ai_generated_email),unsafe_allow_html=True)
                     #st.write(np.array(chars))
-            # prefrence_variables=res=["charcter counts: "+str(x)+", Target Rate: "+str(y) for x,y in zip(chars,sel_var_values)]
-            # preference = st.selectbox(
-            #             'Please select your preferences',
-            #             prefrence_variables,
-            #             index=1
-            #         )
-            # if(preference):
-            # if st.button('Generate AI Recommended Email'):
-            #     if(preference is None):
-            #         st.error('Please upload a email (HTML format)')
-            #     else:
-            #         ai_generated_email=generate_example_email_with_context(email_body, campaign, industry, target, sorted_chars_out, preference)
-            #         st.markdown('##### Here is the recommended Generated Email for you:')
-            #         st.markdown('####### {}:'.format(ai_generated_email),unsafe_allow_html=True)
 
 
                 chars_out = dict(zip(chars, sel_var_values))

utils.py

@@ -24,7 +24,6 @@ def chat_gpt_user_input_loop():
 
 
 def generate_example_email_with_context(email_body, selected_campaign_type, selected_industry, selected_variable, chars_out, dropdown_cc):
-    print("I am here!")
     if len(chars_out) == 1:
         if str(chars_out[0][0]) in dropdown_cc:
             generate_email_prompt = "Rewrite this email keeping relevant information (people, date, location): " + email_body + "." "Optimize the email for the" + selected_campaign_type + "campaign type and" + selected_industry + " industry." + "The email body should be around" + str(chars_out[0][0]+200) + "characters in length."