Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+from groq import Groq
+
+# Initialize the Groq client with your API key
+client = Groq(api_key="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")
+
+# Define the system message for the model
+system_message = {
+    "role": "system",
+    "content": "You are an experienced Fashion designer who starts conversation with proper greet, giving valuable and catchy fashion advices and suggestions, stays to the point and precise, asks questions only if the user have any concern over your provided suggestions, taking inputs like name, age, gender, location, ethnicity, height, weight"
+}
+
+# Function to reset the chat
+def reset_chat():
+    return [], "New Chat"
+
+# Function to handle the questionnaire submission
+def submit_questionnaire(name, age, location, gender, ethnicity, height, weight,
+                         style_preference, color_palette, everyday_style,
+                         preferred_prints, season_preference, outfit_priority,
+                         experiment_with_trends, accessories, fit_preference,
+                         material_preference, top_preference, bottom_preference,
+                         outerwear_preference, footwear_preference, dress_frequency,
+                         layering_preference, jeans_fit, formal_wear_frequency,
+                         sportswear_preference, party_outfit, confidence_in_style,
+                         follow_fashion_trends, look_for_inspiration,
+                         wardrobe_satisfaction, unique_style, outfit_struggle,
+                         fashion_preference, gender_neutral_clothing,
+                         special_occasion_attire, trendsetter,
+                         ai_usefulness, trust_in_ai, ai_preference,
+                         ai_usage_frequency, ai_match_preferences,
+                         ai_recommendation, ai_understanding_style,
+                         more_personalized_recommendations, event_suggestions,
+                         ai_improvements):
+
+    # Store questionnaire responses in a DataFrame
+    questionnaire_data = {
+        "Name": name,
+        "Age": age,
+        "Location": location,
+        "Gender": gender,
+        "Ethnicity": ethnicity,
+        "Height": height,
+        "Weight": weight,
+        "Style Preference": style_preference,
+        "Color Palette": color_palette,
+        "Everyday Style": everyday_style,
+        "Preferred Prints": preferred_prints,
+        "Season Preference": season_preference,
+        "Outfit Priority": outfit_priority,
+        "Experiment with Trends": experiment_with_trends,
+        "Accessories": accessories,
+        "Fit Preference": fit_preference,
+        "Material Preference": material_preference,
+        "Top Preference": top_preference,
+        "Bottom Preference": bottom_preference,
+        "Outerwear Preference": outerwear_preference,
+        "Footwear Preference": footwear_preference,
+        "Dress Frequency": dress_frequency,
+        "Layering Preference": layering_preference,
+        "Jeans Fit": jeans_fit,
+        "Formal Wear Frequency": formal_wear_frequency,
+        "Sportswear Preference": sportswear_preference,
+        "Party Outfit": party_outfit,
+        "Confidence in Style": confidence_in_style,
+        "Follow Fashion Trends": follow_fashion_trends,
+        "Look for Inspiration": look_for_inspiration,
+        "Wardrobe Satisfaction": wardrobe_satisfaction,
+        "Unique Style": unique_style,
+        "Outfit Struggle": outfit_struggle,
+        "Fashion Preference": fashion_preference,
+        "Gender Neutral Clothing": gender_neutral_clothing,
+        "Special Occasion Attire": special_occasion_attire,
+        "Trendsetter": trendsetter,
+        "AI Usefulness": ai_usefulness,
+        "Trust in AI": trust_in_ai,
+        "AI Preference": ai_preference,
+        "AI Usage Frequency": ai_usage_frequency,
+        "AI Match Preferences": ai_match_preferences,
+        "AI Recommendation": ai_recommendation,
+        "AI Understanding Style": ai_understanding_style,
+        "More Personalized Recommendations": more_personalized_recommendations,
+        "Event Suggestions": event_suggestions,
+        "AI Improvements": ai_improvements
+    }
+
+    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!"
+
+# Function to handle chat
+def chat(user_input, messages, name, age, location, gender, ethnicity, height, weight):
+    if user_input:
+        # Create a user profile string
+        user_profile_string = (
+            f"User profile: Name: {name}, Age: {age}, Location: {location}, "
+            f"Gender: {gender}, Ethnicity: {ethnicity}, Height: {height}, Weight: {weight}"
+        )
+
+        # Prepare messages for the API call, including the profile and the conversation history
+        messages.append({"role": "user", "content": user_input})
+        messages.append(system_message)
+        messages.append({"role": "user", "content": user_profile_string})
+
+        try:
+            # Generate a response from the Groq API
+            completion = client.chat.completions.create(
+                model="llama3-8b-8192",
+                messages=messages,
+                temperature=1,
+                max_tokens=1024,
+                top_p=1,
+                stream=False,
+            )
+
+            # Ensure response is valid
+            if completion.choices and len(completion.choices) > 0:
+                response_content = completion.choices[0].message.content
+            else:
+                response_content = "Sorry, I couldn't generate a response."
+
+        except Exception as e:
+            response_content = f"Error: {str(e)}"
+
+        # Store assistant response in the chat history
+        messages.append({"role": "assistant", "content": response_content})
+
+        return messages, response_content
+    return messages, ""
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("## Fashion Assistant Chatbot")
+
+    # Sidebar for user inputs
+    with gr.Row():
+        with gr.Column():
+            name = gr.Textbox(label="Name")
+            age = gr.Number(label="Age", value=25, minimum=1, maximum=100)
+            location = gr.Textbox(label="Location")
+            gender = gr.Radio(label="Gender", choices=["Male", "Female", "Other"])
+            ethnicity = gr.Radio(label="Ethnicity", choices=["Asian", "Black", "Hispanic", "White", "Other"])
+            height = gr.Number(label="Height (cm)", value=170, minimum=50, maximum=250)
+            weight = gr.Number(label="Weight (kg)", value=70, minimum=20, maximum=200)
+
+        with gr.Column():
+            submit_btn = gr.Button("Submit Questionnaire")
+            reset_btn = gr.Button("Reset Chat")
+
+    # Questionnaire responses
+    style_preference = gr.Radio(label="Which style do you prefer the most?", choices=["Casual", "Formal", "Streetwear", "Athleisure", "Baggy"])
+    color_palette = gr.Radio(label="What color palette do you wear often?", choices=["Neutrals", "Bright Colors", "Pastels", "Dark Shades"])
+    everyday_style = gr.Radio(label="How would you describe your everyday style?", choices=["Relaxed", "Trendy", "Elegant", "Bold"])
+    preferred_prints = gr.Radio(label="What type of prints do you like?", choices=["Solid", "Stripes", "Floral", "Geometric", "Animal Print"])
+    season_preference = gr.Radio(label="Which season influences your wardrobe the most?", choices=["Spring", "Summer", "Fall", "Winter"])
+    outfit_priority = gr.Radio(label="What do you prioritize when choosing an outfit?", choices=["Comfort", "Style", "Affordability", "Brand"])
+    experiment_with_trends = gr.Radio(label="How often do you experiment with new trends?", choices=["Always", "Sometimes", "Rarely", "Never"])
+    accessories = gr.Radio(label="What kind of accessories do you usually wear?", choices=["Watches", "Rings", "Necklaces", "Bracelets", "Earrings"])
+    fit_preference = gr.Radio(label="What fit do you prefer in clothes?", choices=["Loose", "Tailored", "Fitted", "Oversized"])
+    material_preference = gr.Radio(label="Which material do you prefer?", choices=["Cotton", "Linen", "Silk", "Denim", "Wool"])
+
+    # More preferences (add all as needed)
+
+    chatbox = gr.Chatbot(label="Chat History")
+    user_input = gr.Textbox(label="Ask anything about fashion...", placeholder="Type your message here...")
+    
+    # Reset chat functionality
+    reset_btn.click(reset_chat, outputs=[chatbox, "title"])
+
+    # Submit questionnaire functionality
+    submit_btn.click(submit_questionnaire, inputs=[name, age, location, gender, ethnicity, height, weight,
+                                                   style_preference, color_palette, everyday_style,
+                                                   preferred_prints, season_preference, outfit_priority,
+                                                   experiment_with_trends, accessories, fit_preference,
+                                                   material_preference], outputs="text")
+
+    # Chat functionality
+    user_input.submit(chat, inputs=[user_input, chatbox, name, age, location, gender, ethnicity, height, weight],
+                      outputs=[chatbox, ""])
+
+demo.launch()