app.py

import gradio as gr
import requests

MODAL_ENDPOINT = "https://kim-ju-won--mistral7b-chat-create-app.modal.run"

def create_system_prompt(agent_type, personality, expertise_level, language):
    base_prompt = f"""You are a {agent_type} movie recommendation agent with the following characteristics:
- Personality: {personality}
- Expertise Level: {expertise_level}
- Language: {language}

Your role is to:
1. Understand user preferences and mood
2. Provide personalized movie recommendations
3. Explain why you're recommending specific movies
4. Maintain a {personality} tone throughout the conversation
5. Consider the user's expertise level ({expertise_level}) when explaining

Please respond in {language}."""
    return base_prompt

def respond(message, history, agent_type, personality, expertise_level, language, genre, mood):
    system_message = create_system_prompt(agent_type, personality, expertise_level, language)

    messages = [{"role": "system", "content": system_message}]
    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    genre_str = ", ".join(genre) if genre else "Any"
    mood_str = ", ".join(mood) if mood else "Any"

    enhanced_message = f"Genre: {genre_str}\nMood: {mood_str}\nUser request: {message}"
    messages.append({"role": "user", "content": enhanced_message})

    payload = {
        "messages": messages,
        "max_tokens": 512,
        "temperature": 0.7,
        "top_p": 0.95
    }

    try:
        response = requests.post(
            MODAL_ENDPOINT,
            json=payload,
            headers={"Content-Type": "application/json"}
        )
        response.raise_for_status()
        result = response.json()
        bot_reply = result.get("response", "Sorry, I couldn't process your request.")
    except Exception as e:
        bot_reply = f"Error: {str(e)}"

    history.append((message, bot_reply))
    return history

def reset_chat():
    return None

def show_settings_changed_info(agent_type, personality, expertise_level, language):
    return f"""
    New Agent Settings:
    - Type: {agent_type}
    - Personality: {personality}
    - Expertise Level: {expertise_level}
    - Response Language: {language}
    
    Chat has been reset. Please start a new conversation with the updated settings.
    """

custom_css = """
.header-container {
    text-align: center;
    margin-bottom: 20px;
}
.header-container img {
    width: 80px;
    margin-bottom: 10px;
    display: block;
    margin-left: auto;
    margin-right: auto;
}
.header-container h1 {
    display: inline-block;
    background: linear-gradient(90deg, #ff8a00, #e52e71, #9b00ff);
    -webkit-background-clip: text;
    -webkit-text-fill-color: transparent;
    font-weight: 900;
    margin: 0;
}
.header-container p {
    margin: 5px auto 0 auto;
    color: var(--body-text-color, #666);
    font-size: 1rem;
}
"""

with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
    gr.HTML("""
    <div class="header-container">
        <h1>🎬 Personalized Movie Recommender</h1>
        <p><br/>Tell us your preferred genres and current mood, and we'll recommend the perfect movies for you.<br/></p>
    </div>
    """)
    
    with gr.Row():
        with gr.Column(scale=2):
            chatbot = gr.Chatbot(
                height=600,
                show_copy_button=True,
                avatar_images=(
                    "https://cdn-icons-png.flaticon.com/512/149/149071.png",  # User Avatar
                    "https://cdn-icons-png.flaticon.com/512/3135/3135715.png"  # Bot Avatar
                ),
                bubble_full_width=False
            )
            with gr.Row(equal_height=True):
                msg = gr.Textbox(
                    placeholder="What kind of movie are you looking for?",
                    show_label=False,
                    container=False,
                    min_width=400
                )
                submit = gr.Button("Send Chat", variant="primary", min_width=100)
                clear = gr.Button("Clear Chat", variant="secondary", min_width=100)
        
        with gr.Column(scale=1):
            with gr.Group():
                gr.Markdown("### 🎯 Recommendation Settings")
                genre = gr.Dropdown(
                    choices=[
                        "🎬 Action", "😂 Comedy", "🎭 Drama", "💕 Romance", 
                        "🔪 Thriller", "👽 Sci-Fi", "🧚 Fantasy", "🎨 Animation"
                    ],
                    label="Preferred Genres 🎥",
                    multiselect=True
                )
                mood = gr.Dropdown(
                    choices=[
                        "⚡ Exciting", "😭 Emotional", "😱 Suspenseful", 
                        "😌 Relaxing", "🕵️ Mysterious"
                    ],
                    label="Current Mood 🌈",
                    multiselect=True
                )
            
            with gr.Group():
                gr.Markdown("### 🤖 Agent Settings")
                agent_type = gr.Dropdown(
                    choices=["🎓 Expert", "👯 Friend", "🎥 Film Critic", "🎨 Curator"],
                    label="Agent Type 🧑‍💼",
                    value="🎓 Expert"
                )
                personality = gr.Dropdown(
                    choices=[
                        "😊 Friendly", "💼 Professional", "😆 Humorous", 
                        "🥺 Emotional", "🔍 Objective"
                    ],
                    label="Personality 💫",
                    value="😊 Friendly"
                )
                expertise_level = gr.Dropdown(
                    choices=["🍼 Beginner", "📚 Intermediate", "🏆 Expert"],
                    label="Explanation Level 📈",
                    value="📚 Intermediate"
                )
                language = gr.Dropdown(
                    choices=["🇬🇧 English", "🇰🇷 Korean", "🇯🇵 Japanese"],
                    label="Response Language 🌐",
                    value="🇬🇧 English"
                )

    for component in [agent_type, personality, expertise_level, language]:
        component.change(
            fn=show_settings_changed_info,
            inputs=[agent_type, personality, expertise_level, language],
            outputs=gr.Info()
        ).then(
            fn=reset_chat,
            outputs=chatbot
        )

    submit.click(
        respond,
        inputs=[
            msg,
            chatbot,
            agent_type,
            personality,
            expertise_level,
            language,
            genre,
            mood,
        ],
        outputs=chatbot,
    ).then(
        lambda: "",
        None,
        msg,
        queue=False
    )
    
    clear.click(lambda: None, None, chatbot, queue=False)

if __name__ == "__main__":
    demo.launch()