Update app.py

app.py

@@ -39,6 +39,22 @@ def submit_questionnaire(name, age, location, gender, ethnicity, height, weight,
 
     return "Thank you for completing the questionnaire!"
 
+# Function to collect responses to additional fashion-related questions
+def collect_questionnaire_responses(style_preference, color_palette, everyday_style):
+    # Store additional responses in a DataFrame
+    additional_data = {
+        "Style Preference": style_preference,
+        "Color Palette": color_palette,
+        "Everyday Style": everyday_style
+    }
+
+    df = pd.DataFrame([additional_data])  # Create DataFrame from dictionary
+
+    # Append to CSV file
+    df.to_csv("additional_questionnaire_responses.csv", mode='a', header=not pd.io.common.file_exists("additional_questionnaire_responses.csv"), index=False)
+
+    return "Thank you for answering the additional questions!"
+
 # Function to handle chat
 def chat(user_input, messages):
     if user_input:
@@ -73,7 +89,7 @@ def chat(user_input, messages):
 
 # Gradio Interface
 with gr.Blocks() as demo:
-    gr.Markdown("## FRIDAY")
+    gr.Markdown("## Fashion Assistant Chatbot")
 
     # Sidebar for user inputs
     with gr.Row():
@@ -87,7 +103,7 @@ with gr.Blocks() as demo:
             weight = gr.Number(label="Weight (kg)", value=70, minimum=20, maximum=200)
 
         with gr.Column():
-            submit_btn = gr.Button("Submit Inputs")
+            submit_btn = gr.Button("Submit User Inputs")
             reset_btn = gr.Button("Reset Chat")
 
     # Questionnaire with fashion-related questions
@@ -101,55 +117,37 @@ with gr.Blocks() as demo:
         ("How often do you experiment with new trends?", ["Always", "Sometimes", "Rarely", "Never"]),
         ("What kind of accessories do you usually wear?", ["Watches", "Rings", "Necklaces", "Bracelets", "Earrings"]),
         ("Do you follow fashion trends?", ["Always", "Sometimes", "Never"]),
-        ("How satisfied are you with your wardrobe?", ["Very Satisfied", "Satisfied", "Neutral", "Unsatisfied"]),
+        ("How satisfied are you with your wardrobe?", ["Yes", "No"]),
         ("Do you consider your style unique?", ["Yes", "No"]),
         ("How confident do you feel in your style?", ["Very Confident", "Somewhat Confident", "Not Confident"]),
         ("Where do you look for fashion inspiration?", ["Social Media", "Fashion Magazines", "Friends", "Other"]),
         ("Do you have specific attire for special occasions?", ["Yes", "No"]),
         ("Do you wear gender-neutral clothing?", ["Yes", "No"]),
-        ("Which clothing materials do you prefer?", ["Cotton", "Silk", "Denim", "Synthetic", "Wool"]),
-        ("How important is sustainability in your fashion choices?", ["Very Important", "Somewhat Important", "Not Important"]),
-        ("Do you prefer shopping online or in physical stores?", ["Online", "Physical Stores"]),
-        ("How often do you update your wardrobe?", ["Seasonally", "Every Few Months", "Once a Year", "Rarely"]),
-        ("Do you participate in clothing swaps or second-hand shopping?", ["Yes", "No"]),
+        ("What influences your fashion choices the most?", ["Celebrities", "Social Media", "Friends", "Personal Preference"]),
+        ("Do you enjoy shopping for clothes?", ["Yes", "No"]),
+        ("How often do you declutter your wardrobe?", ["Regularly", "Occasionally", "Rarely"]),
+        ("Do you have a favorite fashion brand?", ["Yes", "No"]),
+        ("How do you feel about thrift shopping?", ["Love it", "Neutral", "Dislike it"]),
     ]
 
-    # Create a button for filling the questionnaire
+    # Create a separate button for the questionnaire
     fill_questionnaire_btn = gr.Button("Fill Questionnaire")
+    
+    for question, choices in fashion_questions:
+        gr.Radio(label=question, choices=choices)
 
-    # Output message for questionnaire submission
-    questionnaire_output = gr.Textbox(label="Questionnaire Submission", interactive=False)
-
-    # Function to collect all questionnaire responses
-    def collect_questionnaire_responses():
-        # Store questionnaire responses in a DataFrame
-        questionnaire_data = {
-            "Style Preference": style_preference.value,
-            "Color Palette": color_palette.value,
-            "Everyday Style": everyday_style.value
-        }
-
-        # Append additional responses
-        for question, choices in fashion_questions:
-            questionnaire_data[question] = gr.Radio(label=question, choices=choices).value
-
-        df = pd.DataFrame([questionnaire_data])  # Create DataFrame from dictionary
-
-        # Append to CSV file
-        df.to_csv("questionnaire_responses.csv", mode='a', header=not pd.io.common.file_exists("questionnaire_responses.csv"), index=False)
-
-        return "Thank you for completing the questionnaire!"
+    # Chat functionality
+    chatbox = gr.Chatbot(type='messages')
+    user_input = gr.Textbox(label="Your Message", placeholder="Type your message here...")
 
     # Connect the buttons to their respective functions
     submit_btn.click(submit_questionnaire, inputs=[name, age, location, gender, ethnicity, height, weight,
-                                                    style_preference, color_palette, everyday_style], outputs=questionnaire_output)
-
-    fill_questionnaire_btn.click(collect_questionnaire_responses, outputs=questionnaire_output)
-
-    reset_btn.click(reset_chat, outputs=[gr.Chatbot(type='messages'), "title"])
+                                                    style_preference, color_palette, everyday_style], outputs="Thank you for completing the questionnaire!")
     
-    user_input = gr.Textbox(label="Your Message", placeholder="Type your message here...")
-    chatbox = gr.Chatbot(type='messages')
+    fill_questionnaire_btn.click(collect_questionnaire_responses, inputs=[style_preference, color_palette, everyday_style], outputs="Thank you for answering the additional questions!")
+
+    # Corrected reset button output
+    reset_btn.click(reset_chat, outputs=[chatbox, "title"])
 
     user_input.submit(chat, inputs=[user_input, chatbox], outputs=[chatbox, user_input])