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import re
import streamlit as st
from transformers import pipeline
from available_models import MODELS
st.set_page_config(page_title="Translator", page_icon="🗣️")
st.title("🗣️ Translator")
st.markdown("""
[](https://github.com/ChainYo)
[](https://huggingface.co/ChainYo)
[](https://www.linkedin.com/in/thomas-chaigneau-dev/)
[](https://discord.gg/)
""")
st.subheader("Translation made fast and easy.")
with st.expander("❓ How does it work"):
st.markdown("""
**Translator** is a **simple tool** that allows you to **translate text** from one language to another.
**Translator** is powered by the [Transformers library](https://huggingface.co/transformers) and uses the
[Helsinki-NLP](https://huggingface.co/Helsinki-NLP) models.
Choose the **source language** and the **target language** and the **text to translate**.
**Translator** will translate the text and **save the output in a text file**. It cuts the text following
punctuation marks.
The output file content will also be displayed in the browser to help you to understand the translation and choose
if you want to download it.
There is **no limit to the number of characters** that can be translated.
The only limit is the time you are ready to wait! 🤗
*P.S. I have built this tool to help me to start writing blog posts in different languages. I am a French native speaker
and I will use it to translate my potential future blog posts in English.*
*P.P.S. I am an **AI developer** passionate about **machine learning** and **data science**. Reach me by clicking on
the socials badges above.*
""")
lang1, lang2 = st.columns(2)
lang1.selectbox(
"Source Language", ["🇬🇧 English", "🇫🇷 French", "🇩🇪 German", "🇪🇸 Spanish", "🇷🇺 Russian"],
key="input_lang", index=1,
)
lang2.selectbox(
"Target Language", ["🇬🇧 English", "🇫🇷 French", "🇩🇪 German", "🇪🇸 Spanish", "🇷🇺 Russian"],
key="output_lang", index=0,
)
selected_model = MODELS[f"{st.session_state['input_lang']}->{st.session_state['output_lang']}"]
st.markdown(f"""
**Selected model:** [{selected_model[0]}]({selected_model[1]})
""")
if selected_model[0] == None:
st.write("No model available for this pair.")
elif selected_model[0] == 0:
st.write("No translation necessary.")
else:
input_text = st.text_area("Enter text to translate:", height=400, key="input")
translate_text = st.button("Translate")
if translate_text:
with st.spinner(text="⚙️ Model loading..."):
task = pipeline(
"translation",
model=selected_model[0],
tokenizer=selected_model[0],
)
progress_bar = st.progress(0)
with st.spinner(text="🔄 Translating..."):
text_to_translate = re.split('(?<=[.!?]) +', input_text)
total_progress = len(text_to_translate)
for i, text in enumerate(text_to_translate):
translation = task(text)
text_to_translate[i] = translation[0]["translation_text"]
progress_bar.progress((i + 1) / total_progress)
st.success("🗣️ Translated!")
st.session_state["translation_count"] += 1
st.write(f"**Translation:** {' '.join(text_to_translate)}")
st.download_button("Download translated text", "\n".join(text_to_translate), "text/plain")
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