import gradio as gr
from huggingface_hub import InferenceClient
from gradio_client import Client, handle_file

# Gradio Client
client = Client("vikhyatk/moondream2")

# Resmi tanımlayan fonksiyon
def describe_image(image):
    result = client.predict(
        img=handle_file(image),
        prompt="Describe this image.",
        api_name="/answer_question"
    )
    return result

# ChatInterface ve resim işleme fonksiyonu
def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
    image
):
    # Sistem mesajını ve önceki sohbeti al
    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]})

    # Resim ile ilgili açıklamayı ekle
    image_description = describe_image(image)
    messages.append({"role": "assistant", "content": image_description})

    # Kullanıcı mesajını ekle
    messages.append({"role": "user", "content": message})

    response = ""
    # Modelden gelen yanıtı al ve döngüde token'ları birleştir
    for message in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content
        response += token
        yield response

# Gradio app arayüzünü oluştur
demo = gr.Interface(
    fn=respond,
    inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
        gr.Image(type="pil", label="Upload an Image")  # Resim girişi
    ],
    outputs="text",  # Çıktıyı metin olarak ver
)

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