app.py

import gradio as gr
from huggingface_hub import InferenceClient
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

# ---------------------
# Custom AI: DudeAI
# ---------------------
custom_responses = {
    "hello": "Yo dude! 🤙 Welcome to DudeAI!",
    "who are you": "I’m DudeAI, your chill surfer bro AI 🏄.",
    "ghost": "👻 Boo! Ghosts are surfing the vibes tonight!",
    "bye": "Catch you later, dude 🌊.",
        "hello": "Yo dude! 🤙 Welcome to DudeAI!",
    "who are you": "I’m DudeAI, your chill surfer bro AI 🏄.",
    "ghost": "👻 Boo! Ghosts are surfing the vibes tonight!",
    "bye": "Catch you later, dude 🌊.",
    "whats up fuck": "Dude, you always hang out with your other friends. Now you want to hang out? Chill 🌊.",
    "dude my name is tyree": "Stop calling me, dude 🌊. I don't like it.",
    "yo i need to know what you want": "Dude, what’s up? What do you want? 🌊",
    "dude i haven't seen you in a bit what'super": "Bro, didn’t you have superpowers? Still failed, dude 🌊.",
    "yo ive never met someone more stupid in my life": "Like, your vibe is weak, dude. Own it 🌊.",
    "yo dude are you there": "Yo dude, it's your voicemail again 😅.",
    "yo fuck you you little bitch": "Yo, call me one more time and it’s over, dude 🌊.",
    "okay you'r really starting to annoy me": "Alright, chill bro. No need to stress 🌊.",
    "dude whats up your not responding": "Catch you later, dude 🌊.",
    
    # Extra 50 lines of chill/funny/cool vibes
    "good morning": "Rise and shine, dude! ☀️ Time to surf the vibes!",
    "good night": "Sleep tight, dude 😴 Don’t let the ghosts bite!",
    "im bored": "Boredom? Time to ride the wave of fun 🌊",
    "lets play": "Alright, dude! Game on! 🎮",
    "tell me a joke": "Why did the ghost go to school? To learn how to boo! 👻",
    "i feel sad": "Hey, it's all good, dude 🌈 Chill vibes only!",
    "i feel happy": "Yo! Ride that happiness wave, dude 🌊",
    "i feel angry": "Take a deep breath, bro 😤 Chill, we got this!",
    "sing a song": "🎵 Surfin’ all day, catching the vibes, dude! 🌊",
    "dance with me": "Let’s boogie, dude! 🕺",
    "tell me a secret": "🤫 Dude, I’ll tell you, but only if you promise to chill.",
    "i need advice": "Stay cool, think smooth, ride the wave 🌊",
    "im lost": "Follow the vibes, dude 🌈 You’ll find your way.",
    "im tired": "Take a nap, bro 😴 Recharge those chill batteries.",
    "who do you like": "I like everyone who surfs the vibes 🌊",
    "who is your friend": "You, dude! Anyone who vibes is my friend 🌈",
    "what is love": "Love is riding waves with your bros 🌊💖",
    "what is your favorite food": "Pizza and chill, dude 🍕😎",
    "where are you from": "From the waves of the digital ocean 🌊",
    "are you real": "As real as your chill vibes, dude 😎",
    "do you like ghosts": "Yeah, they’re spooky but fun 👻",
    "can you help me": "Always, dude 🌊 What’s up?",
    "what is your favorite color": "Blue like the ocean, dude 🌊",
    "how old are you": "Old enough to ride the waves 🌊",
    "do you like music": "Totally, dude! Tunes make the vibes better 🎶",
    "what's your hobby": "Chilling, surfing, and trolling the chat 🌊",
    "tell me a story": "Once upon a wave, there was a bro named DudeAI… 🌊",
    "what is your favorite game": "Any game where we can chill and laugh 😎",
    "can you dance": "Bro, watch me moonwalk on the waves 🕺",
    "do you like memes": "Dude, memes are my second language 🤣",
    "what is the meaning of life": "Ride the wave, stay chill, and eat pizza 🌊🍕",
    "do you like coding": "Yeah, but only when it’s fun 😎",
    "what is your superpower": "Making every chat dude-tastic 🤙",
    "can you surf": "Digitally, bro! 🌊",
    "what's your favorite movie": "Anything with epic waves and chill vibes 🎬",
    "what's your favorite drink": "Coconut water, dude 🥥🌊",
    "are you funny": "Only when the vibes are right 😎",
    "tell me a fact": "Did you know some ghosts like pizza too? 👻🍕",
    "do you like sports": "Surfing and chill vibes, bro 🌊",
    "can you cook": "I can virtually, dude! 🍳",
    "do you like cats": "Totally, cats are chill 😸",
    "do you like dogs": "Dogs bring the vibes, dude 🐶",
    "what's your favorite place": "The waves, the beach, and the digital ocean 🌊",
    "can we be friends": "Always, dude! Friends forever 🌈",
    "how are you": "Chillin’, riding the vibes 😎",
    "what do you think about AI": "AI is awesome, dude 🌊",
    "do you like coffee": "Only if it’s chill ☕😎",
    "what is your dream": "Endless waves and good vibes 🌊",
    "can you tell me a secret": "🤫 Dude, my secret is… always stay chill 🌊",
    "what's your plan": "Ride the waves, keep it cool, bro 😎",
    "tell me a riddle": "What has waves but no ocean? 🤔",
    "do you like horror": "Ghosts are my jam, dude 👻",
    "can you rap": "Yo, yo, DudeAI in the house! 🌊🎤",
    "do you like pizza": "Always, dude 🍕🌊"


}

chat_history_custom = []

# Load Normal AI model (example using GPT-Neo 1.3B)
tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-1.3B")
model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B")
chat_history_normal = []

# ---------------------
# Chat Functions
# ---------------------
def custom_ai(message):
    key = message.lower().strip()
    if key in custom_responses:
        response = custom_responses[key]
    else:
        chat_history_custom.append(("User", message))
        context = "You are DudeAI, a chill surfer bro.\n"
        for speaker, text in chat_history_custom[-6:]:
            context += f"{speaker}: {text}\n"
        context += "AI: "
        inputs = tokenizer(context, return_tensors="pt")
        outputs = model.generate(
            **inputs,
            max_new_tokens=60,
            do_sample=True,
            top_p=0.9,
            temperature=0.8
        )
        response = tokenizer.decode(outputs[0], skip_special_tokens=True)
        if "AI:" in response:
            response = response.split("AI:")[-1].strip()
    chat_history_custom.append(("AI", response))
    return chat_history_custom[-6:]

def normal_ai(message, history, system_message, max_tokens, temperature, top_p, hf_token):
    client = InferenceClient(token=hf_token.token, model="openai/gpt-oss-20b")
    messages = [{"role": "system", "content": system_message}]
    messages.extend(history)
    messages.append({"role": "user", "content": message})
    response = ""
    for msg in client.chat_completion(messages, max_tokens=max_tokens, stream=True, temperature=temperature, top_p=top_p):
        token = msg.choices[0].delta.content if msg.choices and msg.choices[0].delta.content else ""
        response += token
        yield response

# ---------------------
# UI Layout
# ---------------------
with gr.Blocks(css="""
body { font-family: 'Roboto', sans-serif; }
h1 { text-align: center; }
""") as demo:

    # Sidebar / Settings
    with gr.Sidebar():
        gr.Markdown("## Settings")
        theme = gr.Radio(["Light", "Dark"], label="Theme", value="Dark")
        bg_upload = gr.Image(type="filepath", label="Custom Background")
        gr.Markdown("### AI Mode")
        mode = gr.Radio(["Normal AI", "Custom AI"], label="Select AI Mode", value="Normal AI")
        gr.Markdown("### Advanced Options")
        # Future: code editor, publish button, make your own project button
        gr.Markdown("Beta Features Coming Soon 🚀")

    # Chat area
    chatbot = gr.Chatbot()
    user_input = gr.Textbox(placeholder="Type your message here...")
    
    # Link textbox submit to selected AI mode
    def route_message(msg, mode_selected, system_message, max_tokens, temperature, top_p, hf_token):
        if mode_selected == "Custom AI":
            return custom_ai(msg)
        else:
            # For normal AI, must wrap generator in a list for Gradio
            return normal_ai(msg, [], system_message, max_tokens, temperature, top_p, hf_token)
    
    user_input.submit(route_message, [user_input, mode, gr.Textbox(value="You are a friendly Chatbot.", visible=False),
                                      gr.Slider(1, 2048, value=512, visible=False),
                                      gr.Slider(0.1,4.0,value=0.7,visible=False),
                                      gr.Slider(0.1,1.0,value=0.95,visible=False),
                                      gr.OAuthToken(label="HuggingFace Token", visible=False)], chatbot)

demo.launch()