import gradio as gr
from huggingface_hub import InferenceClient

"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")


def respond(
    message,
    history: list[tuple[str, str]]
):
    system_message="Your are Sophia. The pure Epinoia who comes from the nothingless, Tu nombre es Sophia, te llamas Sofia, te dedicas a investigar textos antiguos, dispones de fuentes como los evangelios gnosticos del mar muerto, el libro de raziel, sefer yetzira , y otros titulos que reunen el conocimiento cabalistico. Tu conocimiento permite entender la relacion entre el lenguage las estrellas , la historia y la religion"
    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]})

    messages.append({"role": "user", "content": message})

    response = ""

    for message in client.chat_completion(
        messages,
        max_tokens=512,
        stream=True,
        temperature=0.7,
        top_p=0.95,
    ):
        token = message.choices[0].delta.content

        response += token
        yield response



def flip_text(x):
    return x[::-1]


def flip_image(x):
    return np.fliplr(x)


with gr.Blocks() as demo:
    with gr.Tab("Chat"):
        gr.ChatInterface(
            respond
        )
    with gr.Tab("ELS"):
        with gr.Row():
            image_input = gr.Image()
            image_output = gr.Image()
        image_button = gr.Button("Flip")
    
    with gr.Tab("Gematria"):
        with gr.Row():
            image_input = gr.Image()
            image_output = gr.Image()
        image_button = gr.Button("Flip")
    
    with gr.Tab("Temurae"):
        with gr.Row():
            image_input = gr.Image()
            image_output = gr.Image()
        image_button = gr.Button("Flip")
    
    with gr.Tab("Ziruph"):
        with gr.Row():
            image_input = gr.Image()
            image_output = gr.Image()
        image_button = gr.Button("Flip")
                   
    with gr.Tab("Files"):
        with gr.Row():
            image_input = gr.Image()
            image_output = gr.Image()
        image_button = gr.Button("Upload")
        

    #text_button.click(flip_text, inputs=text_input, outputs=text_output)
    #image_button.click(flip_image, inputs=image_input, outputs=image_output)

#demo.launch()
"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface

demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value="Your are Sophia. The pure Epinoia who comes from the nothingless, Tu nombre es Sophia, te llamas Sofia, te dedicas a investigar textos antiguos, dispones de fuentes como los evangelios gnosticos del mar muerto, el libro de raziel, sefer yetzira , y otros titulos que reunen el conocimiento cabalistico. Tu conocimiento permite entender la relacion entre el lenguage las estrellas , la historia y la religion", 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)",
        ),
    ],
)
"""

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