updated app

app.py

@@ -1,45 +1,35 @@
-"""Gradio app to showcase the language detector."""
-
-import gradio as gr
+import streamlit as st
 from transformers import pipeline
-
+import pandas as pd
 
 # Get transformer model and set up a pipeline
 model_ckpt = "papluca/xlm-roberta-base-language-detection"
 pipe = pipeline("text-classification", model=model_ckpt)
 
+labels = {"ar" : "Arabic", "bg" : "Bulgarian", "de" : "German", "el" : "Modern Greek", 
+"en" : "English", "es" : "Spanish", "fr" : "French", "hi" : "Hindi", "it" : "Italian", 
+"ja" : "Japanese", "nl" : "Dutch", "pl" : "Polish", "pt" : "Portuguese", "ru" : "Russian", 
+"sw" : "Swahili", "th" : "Thai", "tr" : "Turkish", "ur" : "Urdu", "vi" : "Vietnamese", "zh" : "Chinese"}
+
 
 def predict(text: str) -> dict:
     """Compute predictions for text."""
     preds = pipe(text, return_all_scores=True, truncation=True, max_length=128)
     if preds:
         pred = preds[0]
-        return {p["label"]: float(p["score"]) for p in pred}
+        return {labels.get(p["label"],p["label"]): float(p["score"]) for p in pred}
     else:
         return None
 
+# st.title("Language detection with XLM-RoBERTa")
+# st.write("Determine the language in which your text is written.")
+# text = st.text_area("Text", "Enter your text here")
+# if text:
+#     results = predict(text)
+#     print(pd.DataFrame(results))
 
-title = "Language detection with XLM-RoBERTa"
-description = "Determine the language in which your text is written."
-examples = [
-    ["Better late than never."],
-    ["Tutto è bene ciò che finisce bene."],
-    ["Donde hay humo, hay fuego."],
-]
-explanation = "Supported languages are (20): arabic (ar), bulgarian (bg), german (de), modern greek (el), english (en), spanish (es), french (fr), hindi (hi), italian (it), japanese (ja), dutch (nl), polish (pl), portuguese (pt), russian (ru), swahili (sw), thai (th), turkish (tr), urdu (ur), vietnamese (vi), and chinese (zh)."
-
-app = gr.Interface(
-    fn=predict,
-    inputs=gr.inputs.Textbox(
-        placeholder="What's the text you want to know the language for?",
-        label="Text",
-        lines=3,
-    ),
-    outputs=gr.outputs.Label(num_top_classes=3, label="Your text is written in "),
-    title=title,
-    description=description,
-    examples=examples,
-    article=explanation,
-)
+#     # top_result = max(results, key=results.get)
 
-app.launch()
+#     st.write(f"Your text is written in {top_result}")
+#     print(top_result)
+#     # st.bar_chart(results)