Update app.py

sentiment for different languages

app.py

@@ -1,32 +1,59 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
 
-# Load model
-MODEL = "cardiffnlp/twitter-roberta-base-sentiment-latest"
+# Multilingual model (10+ languages)
+MODEL = "nlptown/bert-base-multilingual-uncased-sentiment"
 tokenizer = AutoTokenizer.from_pretrained(MODEL)
 model = AutoModelForSequenceClassification.from_pretrained(MODEL)
 sentiment_model = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
 
-# Function for Gradio
+# Map stars (1–5) to emotion labels with emojis
+STAR_EMOJIS = {
+    1: "😡 Very Negative",
+    2: "☹️ Negative",
+    3: "😐 Neutral",
+    4: "🙂 Positive",
+    5: "🤩 Very Positive"
+}
+
 def analyze_sentiment(text):
     result = sentiment_model(text)[0]
-    return f"Sentiment: {result['label']} | Confidence: {result['score']:.2f}"
+    stars = int(result["label"][0])   # "1 star" → 1
+    sentiment = STAR_EMOJIS.get(stars, result["label"])
+    confidence = f"{result['score']:.2f}"
+    return [[sentiment, confidence]]
 
-# Example texts
+# Example texts in different languages
 examples = [
-    ["I absolutely love this new phone, the camera is stunning!"],
-    ["I hate the way this app keeps crashing."],
-    ["It’s fine, nothing special but not terrible either."],
-] 
+    ["I absolutely love this new phone, the camera is stunning!"],       # English
+    ["Je déteste quand cette application plante sans cesse."],           # French
+    ["Das Essen in diesem Restaurant war fantastisch!"],                 # German
+    ["Este producto es muy malo y no funciona."],                        # Spanish
+    ["Questo film è stato noioso e troppo lungo."],                      # Italian
+    ["Eu gostei muito do serviço, foi excelente!"],                      # Portuguese
+    ["Эта книга ужасна, я еле её дочитал."],                             # Russian
+    ["هذا الهاتف رائع للغاية، أنا سعيد جدًا به."],                        # Arabic
+    ["この映画は本当に面白かった！"],                                       # Japanese
+    ["De app werkt prima, maar kan beter."],                             # Dutch
+]
 
 # Gradio UI
 demo = gr.Interface(
     fn=analyze_sentiment,
-    inputs=gr.Textbox(lines=3, placeholder="Type a sentence here..."),
-    outputs="text",
+    inputs=gr.Textbox(lines=3, placeholder="Type a sentence here in one of 10 languages..."),
+    outputs=gr.Dataframe(
+        headers=["Emotion (1–5 Stars)", "Confidence"],
+        row_count=1,
+        col_count=(2, "fixed"),
+    ),
     examples=examples,
-    title="Sentiment Analyzer",
-    description="A simple Hugging Face Space to analyze sentiment in tweets using CardiffNLP's RoBERTa model."
+    title="🌍 Multilingual Emotion & Sentiment Analyzer",
+    description=(
+        "Supports 10+ languages (English, French, German, Spanish, Italian, Dutch, "
+        "Portuguese, Russian, Arabic, Japanese). Detects fine-grained emotions "
+        "with 5 levels:\n\n"
+        "😡 Very Negative | ☹️ Negative | 😐 Neutral | 🙂 Positive | 🤩 Very Positive"
+    ),
 )
 
 if __name__ == "__main__":