Create app.py

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# Load your model and tokenizer
+model_name = "your-hf-username/LexCAT-LexiLiksik-Final"  # ← REPLACE WITH YOUR MODEL REPO
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+# Define prediction function
+def predict_sentiment(text):
+    if not text.strip():
+        return "Please enter text."
+    
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=128)
+    outputs = model(**inputs)
+    predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
+    predicted_class = torch.argmax(predictions, dim=1).item()
+    
+    sentiment_map = {0: "❌ Negative", 1: "➖ Neutral", 2: "✅ Positive"}
+    confidence = predictions[0][predicted_class].item()
+    
+    result = f"**Predicted Sentiment**: {sentiment_map[predicted_class]}\n"
+    result += f"**Confidence**: {confidence:.3f}\n"
+    result += f"\n**Raw Probabilities**:\nNegative: {predictions[0][0]:.3f}\nNeutral: {predictions[0][1]:.3f}\nPositive: {predictions[0][2]:.3f}"
+    
+    return result
+
+# Define Gradio interface
+demo = gr.Interface(
+    fn=predict_sentiment,
+    inputs=gr.Textbox(placeholder="Type a Taglish sentence, e.g., 'Maganda pero expensive tlga'", label="Input Tagalog–English (Taglish) Text"),
+    outputs=gr.Textbox(label="Sentiment Prediction"),
+    title="🔍 LexCAT: Taglish Sentiment Analysis",
+    description="""
+    **LexCAT** is a lexicon-enhanced transformer model for sentiment analysis of **Tagalog–English code-switched text (Taglish)**.
+    Developed by Glenn Marcus D. Cinco for his BS/MS thesis at Mapúa University.
+    Trained on FiReCS dataset, enhanced with **LexiLiksik** lexicon for intra-sentential shift detection (e.g., “Maganda pero expensive” → ❌ Negative).
+    """,
+    examples=[
+        ["sobrang lambot ng burger pero expensive tlga"],
+        ["Ang ganda ng service, one star!"],
+        ["Super duper late delivery umabot ng 2 weeks metro manila area lang naman"],
+        ["Salamat sa nyo nagana nmn po sya kaya super thank you ako"],
+        ["Ganda legit, kumpleto... problema lang nainit ng sobra..."]
+    ],
+    theme="soft",
+    allow_flagging="never"
+)
+
+# Launch app
+if __name__ == "__main__":
+    demo.launch()