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README.md

@@ -1,12 +1,25 @@
 ---
 title: Sentiment Explorer
-emoji: 😻
-colorFrom: green
-colorTo: blue
+emoji: 🎭
+colorFrom: purple
+colorTo: pink
 sdk: gradio
-sdk_version: 6.0.2
+sdk_version: "6.0.2"
 app_file: app.py
 pinned: false
+license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🎭 Sentiment Explorer
+
+Analyze the emotional tone of any text using DistilBERT via the HuggingFace Inference API.
+
+## Features
+
+- Real-time sentiment analysis
+- Confidence scores with visual feedback
+- No model downloads - uses API
+
+## Setup
+
+Add your `HF_TOKEN` as a Secret in Space Settings.

app.py

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+import os
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+# Get token from environment (set in HF Space secrets)
+HF_TOKEN = os.environ.get("HF_TOKEN", "")
+client = InferenceClient(token=HF_TOKEN) if HF_TOKEN else InferenceClient()
+
+
+def analyze(text: str) -> tuple[str, dict]:
+    """Return emoji + label and confidence scores."""
+    if not text.strip():
+        return "🤔 Enter some text!", {}
+    
+    try:
+        result = client.text_classification(
+            text,
+            model="distilbert-base-uncased-finetuned-sst-2-english",
+        )[0]
+        
+        label = result.label
+        score = result.score
+        emoji = "😊" if label == "POSITIVE" else "😞"
+        return f"{emoji} {label} ({score:.1%})", {label: score, "OTHER": 1 - score}
+    except Exception as e:
+        return f"❌ Error: {e}", {}
+
+
+with gr.Blocks(title="Sentiment Explorer") as demo:
+    gr.Markdown("# 🎭 Sentiment Explorer\nType anything and see if it's positive or negative!")
+
+    inp = gr.Textbox(
+        label="Your text",
+        placeholder="I absolutely love learning about AI!",
+        lines=3,
+        autofocus=True,
+    )
+
+    with gr.Row(equal_height=True):
+        result_label = gr.Textbox(label="Verdict", interactive=False)
+        confidence = gr.Label(label="Confidence")
+
+    btn = gr.Button("Analyze", variant="primary")
+    btn.click(analyze, inputs=inp, outputs=[result_label, confidence])
+    inp.submit(analyze, inputs=inp, outputs=[result_label, confidence])
+
+    gr.Examples(
+        examples=[
+            ["This tutorial is amazing and super helpful!"],
+            ["I'm frustrated, nothing works today."],
+            ["The weather is okay, I guess."],
+        ],
+        inputs=inp,
+    )
+
+demo.queue()
+demo.launch()

requirements.txt

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+gradio>=6.0.0
+huggingface_hub>=0.23.0
+