Create app.py

app.py

@@ -0,0 +1,62 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load models
+sentiment = pipeline(
+    "sentiment-analysis",
+    model="cardiffnlp/twitter-roberta-base-sentiment-latest"
+)
+
+classifier = pipeline(
+    "zero-shot-classification",
+    model="facebook/bart-large-mnli"
+)
+
+labels = [
+    "Sports",
+    "Education",
+    "Technology",
+    "Politics",
+    "Finance",
+    "Health",
+    "Entertainment",
+    "Business",
+    "Travel",
+    "Food"
+]
+
+def analyze(text):
+    if not text.strip():
+        return "Please enter some text.", "", "", ""
+
+    # Sentiment
+    s = sentiment(text)[0]
+    sent = s["label"]
+    score = round(s["score"] * 100, 2)
+
+    # Category
+    c = classifier(text, labels)
+    category = c["labels"][0]
+
+    explanation = f"The sentence is classified as '{sent}' and belongs to the '{category}' category."
+
+    return sent, category, f"{score}%", explanation
+
+
+demo = gr.Interface(
+    fn=analyze,
+    inputs=gr.Textbox(
+        lines=4,
+        placeholder="Enter a sentence or paragraph..."
+    ),
+    outputs=[
+        gr.Text(label="Sentiment"),
+        gr.Text(label="Category"),
+        gr.Text(label="Confidence"),
+        gr.Textbox(label="Explanation")
+    ],
+    title="🧠 AI Sentiment & Topic Analyzer",
+    description="Analyze text to determine its sentiment and topic using Hugging Face Transformers."
+)
+
+demo.launch()