import gradio as gr
from transformers import pipeline
from huggingface_hub import notebook_login
import re
import requests
import json
import detectlanguage
from detectlanguage import simple_detect
# use this link to get your api key https://detectlanguage.com/
detectlanguage.configuration.api_key = "d0aeb9f0050c99468ee7e3319ff4695f"
detectlanguage.configuration.secure = True
def preprocessing(sentence):
  # remove @user and adjust the sentence
  text = sentence.lower().strip()
  # remove punctuations
  text = re.sub(r'[^\w\s]', '', str(text)).strip()
  # remove links
  text = re.sub(r'https?://\S+|www\.\S+', '',text).strip()
  # remove hidden links
  text = re.sub(r'(?:https?\S+)','',text).strip()
  # remove emojis
  text = re.sub(r'[\U0001f600-\U0001f650]', '', text).strip()
  # remove digits
  text = re.sub(r'[\d]','',text).strip()
  return text
def translate(text : str , target_lang : str, source_lang : str):
  """
  Params: Receives Texts, target language, source language code
  ruturn: translated Text
  """
  api_url = "https://translate.googleapis.com/translate_a/single"
  client = "?client=gtx&dt=t"
  dt = "&dt=t"
  sl = f"&sl={source_lang}"
  tl = f"&tl={target_lang}"
  r = requests.get(api_url+ client + dt + sl + tl + "&q=" + text)
  return json.loads(r.text)[0][0][0]
specific_model = pipeline("sentiment-analysis", model="RogerB/kin-sentiC")
def greet(sentence):
  text = preprocessing(sentence)
  source_lang = simple_detect(text)
  if text == 'rw':
    label = specific_model(text)
    return {label[0]['label']:label[0]['score']}
  else:
    try:
      text = translate(text, target_lang='rw', source_lang=source_lang)
      label = specific_model(text)
      return {label[0]['label']:label[0]['score']}
    except json.JSONDecodeError:
      label = specific_model(text)
      return {label[0]['label']:label[0]['score']}

demo = gr.Interface(fn=greet, inputs="text", outputs="label",title="Multilingual Sentiment Anaysis context of Kinyarwanda Tweets")

demo.launch(debug=False)