import gradio as gr
from transformers import pipeline

model_pipeline = pipeline("text2text-generation", model="tribler/dsi-search-on-toy-dataset")

def process_query(query):
    results = model_pipeline(query, max_length=60)
    result_text = results[0]['generated_text'].strip()
    if result_text.startswith("http"):
        youtube_id = result_text.split('watch?v=')[-1]
        iframe = f'<iframe width="560" height="315" src="https://www.youtube.com/embed/{youtube_id}" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>'
        return gr.HTML(iframe)
    elif result_text.startswith("magnet"):
        return gr.HTML(f'<a href="{result_text}" target="_blank">{result_text}</a>')
    else:
      bitcoin_logo_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/4/46/Bitcoin.svg/800px-Bitcoin.svg.png"
      return gr.Textbox(f'<div style="display:flex;align-items:center;"><img src="{bitcoin_logo_url}" alt="Bitcoin Logo" style="width:20px;height:20px;margin-right:5px;"><span>{result_text}</span></div>')

interface = gr.Interface(fn=process_query,
                          inputs=gr.Textbox(label="Query"),
                          outputs="html",
                          title="Search Interface",
                          description="Search for movie trailers, music torrents, and bitcoin wallet addresses.",
                          article="This interface searches a toy dataset and returns a YouTube URL, magnet link, or Bitcoin wallet address.",
                          examples=[["spider man"], ["oceans 13"], ["sister starlight"], ["bitcoin address of xileno"]])

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