import gradio as gr
from gradio_client import Client

MODELS = {"OLMo-2-1124-13B-Instruct": "akhaliq/olmo-anychat", "Llama-3.1-Tulu-3-8B": "akhaliq/allen-test"}


def create_chat_fn(client):
    def chat(message, history):
        response = client.predict(
            message=message,
            system_prompt="You are a helpful AI assistant.",
            temperature=0.7,
            max_new_tokens=1024,
            top_k=40,
            repetition_penalty=1.1,
            top_p=0.95,
            api_name="/chat",
        )
        return response

    return chat


def set_client_for_session(model_name, request: gr.Request):
    headers = {}
    if request and hasattr(request, "request") and hasattr(request.request, "headers"):
        x_ip_token = request.request.headers.get("x-ip-token")
        if x_ip_token:
            headers["X-IP-Token"] = x_ip_token

    return Client(MODELS[model_name], headers=headers)


def safe_chat_fn(message, history, client):
    if client is None:
        return "Error: Client not initialized. Please refresh the page."
    return create_chat_fn(client)(message, history)


with gr.Blocks() as demo:
    client = gr.State()

    model_dropdown = gr.Dropdown(
        choices=list(MODELS.keys()), value="OLMo-2-1124-13B-Instruct", label="Select Model", interactive=True
    )

    chat_interface = gr.ChatInterface(fn=safe_chat_fn, additional_inputs=[client])

    # Update client when model changes
    def update_model(model_name, request):
        return set_client_for_session(model_name, request)

    model_dropdown.change(
        fn=update_model,
        inputs=[model_dropdown],
        outputs=[client],
    )

    # Initialize client on page load
    demo.load(
        fn=set_client_for_session,
        inputs=gr.State("OLMo-2-1124-13B-Instruct"),
        outputs=client,
    )

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