import os
import gradio as gr
import requests
import json
from urllib.parse import quote

auth_token = os.environ.get("kinit_mgt_access_token")
share = os.environ.get("GRADIO_SHARE")

def get_api_response(text):
   url = "https://mgt-detector.model.kinit.sk/prod/?q=" + quote(text)
   payload = {}
   headers = {
       'x-api-key': auth_token
   }
   response = requests.request("GET", url, headers=headers, data=payload)
   response = json.loads(response.text)
   return response

def predict(text):
    #return 'machine', 1.0
    res = get_api_response(text)
    if 'pred' not in res.keys():
        return "Waiting for the server startup (up to 1 min for the first request), try again!", "Waiting for the server startup (up to 1 min for the first request), try again!"
    pred = "Very likely human-written"
    if res['score'] > 0.05: pred = "Likely human-written"
    if res['score'] > 0.5: pred = "Likely machine-generated"
    if res['score'] > 0.95: pred = "Very likely machine-generated"
    return pred,res['score']

with gr.Blocks(analytics_enabled=False) as demo:
    gr.Markdown("""
## DEMO: KInIT Multilingual Machine-Generated Text Detector                
Trained on [MULTITuDE](https://aclanthology.org/2023.emnlp-main.616/) (news articles) and [MultiSocial](https://arxiv.org/abs/2406.12549) (social media texts) texts in 22 languages. 
                """)
    gr.Markdown("""
**Disclaimer: This is a DEMO for showcase, not the final tool. The detector is based on AI transformer model and is NOT 100% accurate! Usage is intended for research purpose only, as an indicator. Do not use it for direct decision making!**""")
    gr.Markdown("""To generate exemplar text by a large language model, you can use [HuggingFace Chat](https://huggingface.co/chat/).""")
    t1 = gr.Textbox(lines=10, label='Text',value="Put your text (in any language) in here to try out our multilingual machine-generated text detector.")
    button1 = gr.Button("Run detection")
    label1 = gr.Textbox(lines=1, label='Result')
    score1 = gr.Textbox(lines=1, label='Probability (closer to 0 means higher probability of text being written by a human, closer to 1 means higher probability of text being generated by an AI model)')
    
    button1.click(predict, inputs=[t1], outputs=[label1,score1], api_name=False)

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