nb2nn / app.py
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import os
import time
import requests
import streamlit as st
API_URL = "https://api-inference.huggingface.co/models/pere/nb-nn-translation"
def translate(text, wait=True):
headers = {"Authorization": f"Bearer {os.environ['BEARER']}"}
payload = {
"inputs": text,
"options": {
"wait_for_model": not wait
}
}
response = requests.post(API_URL, headers=headers, json=payload)
json_response = response.json()
if (isinstance(json_response, dict)
and "error" in json_response
and "estimated_time" in json_response):
st.write(json_response)
if wait:
with st.spinner(json_response["error"]):
bar = st.progress(0)
time_to_load = int(json_response["estimated_time"]) + 1
for progress in range(time_to_load):
bar.progress(progress / time_to_load)
time.sleep(1)
bar.empty()
return translate(text, wait=False)
else:
return "We could not load the model"
elif (isinstance(json_response, list)
and "translation_text" in json_response[0]):
return json_response[0]["translation_text"]
else:
return f"Oops, something went wrong: {str(json_response)}"
st.set_page_config(
page_title='Norwegian Bokmål to Nynorsk',
page_icon='translator-icon.png',
)
st.title("Bokmål ⇔ Nynorsk")
st.sidebar.write("""
# Sample text:
### Nynorsk
Dette er ei tekst.
### Bokmål
Dette er en tekst.
""")
masked_texts = [
"Min tekst",
"Din tekst"
]
input_text = st.sidebar.selectbox("Select a Text", options=masked_texts)
masked_text = st.text_input("Please type a masked sentence to fill", input_text)
text = st.text_area("Enter text:",
height=None,
max_chars=None,
key=None,
help="Enter your text here",
)
if st.button('Translate'):
if str(text).strip() == "":
st.warning('Please **enter text** for translation')
else:
st.info(str(translate(text)))