Update app.py

Updated version

app.py

@@ -1,12 +1,16 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+from langdetect import detect
+from googletrans import Translator
 
-# Multilingual model (10+ languages)
+# Multilingual sentiment model
 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)
 
+translator = Translator()
+
 # Map stars (1–5) to emotion labels with emojis
 STAR_EMOJIS = {
     1: "😡 Very Negative",
@@ -16,46 +20,62 @@ STAR_EMOJIS = {
     5: "🤩 Very Positive"
 }
 
+# Suggested actions in English
+ACTIONS = {
+    1: "Take a break, reflect on the situation, or seek support.",
+    2: "Consider what’s bothering you and try to address it calmly.",
+    3: "Maintain balance; you’re feeling neutral, continue as usual.",
+    4: "Share your positive experience and stay motivated!",
+    5: "Celebrate and spread your joy; keep up the enthusiasm!"
+}
+
 def analyze_sentiment(text):
+    # Sentiment analysis
     result = sentiment_model(text)[0]
-    stars = int(result["label"][0])   # "1 star" → 1
+    stars = int(result["label"][0])
     sentiment = STAR_EMOJIS.get(stars, result["label"])
     confidence = f"{result['score']:.2f}"
-    return [[sentiment, confidence]]
 
-# Example texts in different languages including Yoruba
+    # Detect language
+    try:
+        lang = detect(text)
+    except:
+        lang = "en"
+
+    # Translate action to detected language
+    action_en = ACTIONS.get(stars, "")
+    if lang != "en":
+        try:
+            action_translated = translator.translate(action_en, dest=lang).text
+        except:
+            action_translated = action_en
+    else:
+        action_translated = action_en
+
+    return [[sentiment, confidence, action_translated]]
+
+# Example texts including Yoruba
 examples = [
     ["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
     ["Mo nifẹ́ fíìmù yìí gan-an!"],                                      # Yoruba Positive
-    ["Mo kọ́ láti rí ìrírí tó dáa nínú iṣẹ́ yìí."],                     # Yoruba Neutral
     ["Mo bínú gan-an sí ìṣẹ̀lẹ̀ náà."],                                   # Yoruba Negative
+    ["Je déteste quand cette application plante sans cesse."],           # French
 ]
 
 # Gradio UI
 demo = gr.Interface(
     fn=analyze_sentiment,
-    inputs=gr.Textbox(lines=3, placeholder="Type a sentence here in one of 11+ languages..."),
+    inputs=gr.Textbox(lines=3, placeholder="Type a sentence in any supported language..."),
     outputs=gr.Dataframe(
-        headers=["Emotion (1–5 Stars)", "Confidence"],
+        headers=["Emotion (1–5 Stars)", "Confidence", "What to do"],
         row_count=1,
-        col_count=(2, "fixed"),
+        col_count=(3, "fixed"),
     ),
     examples=examples,
-    title="🌍 Multilingual Emotion & Sentiment Analyzer",
+    title="🌍 Multilingual Emotion & Action Analyzer",
     description=(
-        "Supports 11+ languages (English, French, German, Spanish, Italian, Dutch, "
-        "Portuguese, Russian, Arabic, Japanese, Yoruba). Detects fine-grained emotions "
-        "with 5 levels:\n\n"
-        "😡 Very Negative | ☹️ Negative | 😐 Neutral | 🙂 Positive | 🤩 Very Positive"
+        "Supports multiple languages including English, Yoruba, French, German, Spanish, etc. "
+        "Detects emotion (1–5 stars) and provides suggested actions in the same language as input."
     ),
 )