app.py

import gradio as gr
from huggingface_hub import hf_hub_download
from llama_cpp import Llama

# --- 1. MODEL LOADING ---
print("===== Downloading model... =====")
model_path = hf_hub_download(
    repo_id="bartowski/Dolphin3.0-Llama3.2-3B-GGUF",
    filename="Dolphin3.0-Llama3.2-3B-Q4_K_M.gguf"
)
print(f"Model downloaded to: {model_path}")

print("===== Loading model... =====")
llm = Llama(
    model_path=model_path,
    n_ctx=1096,
    n_threads=8,
    n_gpu_layers=0
)
print("Model loaded.")


# --- 2. UPGRADED CHAT & STREAMING LOGIC ---
default_system_prompt = "You are Dolphin 3.0, a helpful and friendly AI assistant."

def chat_stream(user_message, chat_history, system_prompt, temperature, top_p):
    messages = [{"role": "system", "content": system_prompt}]
    for human, ai in chat_history:
        messages.append({"role": "user", "content": human})
        messages.append({"role": "assistant", "content": ai})
    messages.append({"role": "user", "content": user_message})

    chat_history.append([user_message, ""])

    stream = llm.create_chat_completion(
        messages=messages,
        temperature=temperature,
        top_p=top_p,
        max_tokens=1024,
        stream=True,
    )

    for chunk in stream:
        delta = chunk['choices'][0]['delta']
        if 'content' in delta:
            chat_history[-1][1] += delta['content']
            yield chat_history


# --- 3. ADVANCED GRADIO UI ---
with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"), css="#chatbot { min-height: 600px; }") as demo:
    gr.Markdown("## 🐬 Dolphin 3.0 - Upgraded Chat Interface")

    with gr.Row():
        with gr.Column(scale=4):
            chatbot = gr.Chatbot(
                [],
                elem_id="chatbot",
                bubble_full_width=False,
                avatar_images=(("human.png", "dolphin.png")),
                label="Chat with Dolphin 3.0"
            )
            chat_history = gr.State([])

            with gr.Row():
                message = gr.Textbox(
                    label="Type your message here...",
                    placeholder="What's on your mind?",
                    lines=1,
                    scale=7,
                )
                send_button = gr.Button("Send", variant="primary", scale=1)

        with gr.Column(scale=1):
            with gr.Accordion("Advanced Settings", open=False):
                system_prompt = gr.Textbox(value=default_system_prompt, label="System Prompt", lines=3)
                temperature = gr.Slider(minimum=0.1, maximum=1.5, value=0.7, label="Temperature")
                top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.9, label="Top-p")
            
            clear_button = gr.Button("🗑️ Clear Chat")
            regenerate_button = gr.Button("🔄 Regenerate")


    # --- 4. EVENT HANDLERS ---
    def user_submit(user_message, history, system, temp, top_p):
        yield gr.update(value=""), history + [[user_message, None]]
        for updated_history in chat_stream(user_message, history, system, temp, top_p):
             yield gr.update(value=""), updated_history

    message.submit(user_submit, [message, chat_history, system_prompt, temperature, top_p], [message, chatbot])
    send_button.click(user_submit, [message, chat_history, system_prompt, temperature, top_p], [message, chatbot])

    def clear_chat():
        return [], []

    clear_button.click(clear_chat, [], [chatbot, chat_history], queue=False)
    
    def regenerate_response(history, system, temp, top_p):
        if not history:
            return
        last_user_message = history[-1][0]
        reduced_history = history[:-1]
        for updated_history in chat_stream(last_user_message, reduced_history, system, temp, top_p):
            yield updated_history

    regenerate_button.click(
        regenerate_response,
        [chat_history, system_prompt, temperature, top_p],
        [chatbot]
    )

# --- 5. LAUNCH THE APP (WITH THE BUG FIX) ---
if __name__ == "__main__":
    demo.queue()
    # The show_api=False parameter tells Gradio to not build the API page, avoiding the bug.
    demo.launch(debug=True, show_api=False)