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| import streamlit as st | |
| from datasets import load_dataset | |
| import pandas as pd | |
| import plotly.graph_objects as go | |
| from transformers import pipeline | |
| def fetch_counts(): | |
| dataset = load_dataset("atlasia/darija-translation", split="train") | |
| dataset = pd.DataFrame(dataset) | |
| n_eng = len(dataset["en"].dropna()) | |
| n_fr = len(dataset["fr"].dropna()) | |
| n = len(dataset) | |
| return {"n_eng": n_eng, "n_fr": n_fr, "n": n} | |
| def terjman(input_text: str) -> str: | |
| pipe = pipeline("text2text-generation", model="atlasia/Terjman-Large") | |
| result = pipe(input_text, max_length=512) | |
| return result[0]["generated_text"] | |
| def transliterate(input_text: str) -> str: | |
| pipe = pipeline("text2text-generation", model="atlasia/Transliteration-Moroccan-Darija") | |
| result = pipe(input_text, max_length=50) | |
| return result[0]["generated_text"] | |
| if __name__ == "__main__": | |
| st.image("atlasia_white_wtext_nobg.png") | |
| counts = fetch_counts() | |
| n_goal = 100000 | |
| total_submissions = counts["n"] | |
| st.text("") | |
| # center text | |
| st.markdown( | |
| """ | |
| <h1 style='text-align: center; font-size: 20px;'> | |
| Contribute now to help build a better Darija dataset for all Moroccans | |
| Contribute here: <a href="https://atlasia.ma" target="_blank">https://atlasia.ma</a> | |
| </h1> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| st.divider() | |
| # with st.container() as c: | |
| # # add a block where users can input text and get a translation | |
| # st.markdown( | |
| # """ | |
| # <div style='text-align: center;'> | |
| # <h3>🔠Keyboard: Transliterate Letters from Latin to Arabic</h3 | |
| # > | |
| # </div> | |
| # """, | |
| # unsafe_allow_html=True, | |
| # ) | |
| # col1, col2 = st.columns(2) | |
| # with col1: | |
| # input_text = st.text_area(":grey[Enter a word/letter in English ⬇]", "") | |
| # button = st.button("Transliterate") | |
| # with col2: | |
| # if button: | |
| # with st.spinner('Transliterating...'): | |
| # translation = transliterate(input_text) | |
| # st.text_area( | |
| # ":grey[Transliteration]", | |
| # translation, | |
| # ) | |
| # st.divider() | |
| with st.container() as c: | |
| # add a block where users can input text and get a translation | |
| st.markdown( | |
| """ | |
| <div style='text-align: center;'> | |
| <h3>💬Terjman: Translate to Darija</h3 | |
| > | |
| </div> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| st.caption( | |
| """ | |
| <div style='text-align: center;'> | |
| <h3>This model has been developed thanks to your contributions. | |
| While it's not perfect yet, your continued input is key for making it better.</h3> | |
| </div> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| input_text = st.text_area(":grey[Enter a sentence in English ⬇]", "") | |
| button = st.button("Translate") | |
| with col2: | |
| if button: | |
| with st.spinner('Translating...'): | |
| translation = terjman(input_text) | |
| st.text_area( | |
| ":grey[Translation in Darija]", | |
| translation, | |
| ) | |
| # add a separator | |
| st.divider() | |
| st.markdown( | |
| """ | |
| <div style='text-align: center;'> | |
| <h3>📊 Data statistics</h3 | |
| > | |
| </div> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| # make progress chart | |
| fig = go.Figure( | |
| go.Indicator( | |
| domain={"x": [0, 1], "y": [0, 1]}, | |
| value=total_submissions, | |
| mode="gauge+number+delta", | |
| title={"text": "Number of translations"}, | |
| delta={"reference": 42000}, | |
| gauge={ | |
| "axis": {"range": [0, n_goal]}, | |
| "steps": [ | |
| {"range": [0, total_submissions], "color": "gray"}, | |
| ], | |
| "threshold": { | |
| "line": {"color": "green", "width": 4}, | |
| "thickness": 0.75, | |
| "value": n_goal / 2, | |
| }, | |
| }, | |
| ) | |
| ) | |
| st.plotly_chart(fig, use_container_width=True) | |
| labels = ["English", "French"] | |
| values = [counts["n_eng"], counts["n_fr"]] | |
| # change color to blue and white | |
| fig = go.Figure(data=[go.Pie(labels=labels, values=values, pull=[0.2, 0])]) | |
| fig.update_traces(marker=dict(colors=["#46607b", "#FFFFFF"])) | |
| st.plotly_chart(fig, use_container_width=True) | |