import re
import gradio as gr
from huggingface_hub import InferenceClient

client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")

system_instructions = """<s> [INST] You will be provided with text, and your task is to translate it into emojis. DO NOT USE ANY REGULAR TEXT. Do your best with emojis only. Translate this text: """


def generate_translation(prompt):
    generate_kwargs = dict(
        temperature=0.01,
        max_new_tokens=1024,
        top_p=0.95,
        repetition_penalty=1.0,
        do_sample=True,
        seed=42,
    )

    formatted_prompt = system_instructions + prompt + "[/INST]"
    stream = client.text_generation(
        formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
    output = ""

    for response in stream:
        output += response.token.text

    emoji_pattern = r"[^\u0021-\u007E\u00A0-\uD7FF\uE000-\uFDCF\uFF00-\uFFEF\u10000-\u10FFFF\u0300-\u036F\u1F00-\u1F1F\u1F20-\u1F7F\u2600-\u26FF\u2700-\u27BF]+?"

    filtered_output = re.findall(emoji_pattern, output)

    return ''.join(filtered_output)


with gr.Blocks() as demo:
    gr.HTML("""
<center><h1>Emoji Translator😊🤗</h1>
Translate any text into emojis!
</center>
""")
    with gr.Row():
        name = gr.Textbox(label="Enter text")
        output = gr.Textbox(label="Translation")
    translate_btn = gr.Button("Translate!")
    translate_btn.click(fn=generate_translation, inputs=name,
                        outputs=output, api_name="translate")

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