Add hello world AI sentiment analysis app

Co-Authored-By: Oz <oz-agent@warp.dev>

README.md

@@ -1,15 +1,33 @@
 ---
-title: Testing Space
-emoji: 📚
-colorFrom: green
-colorTo: yellow
+title: Hello World AI Sentiment
+emoji: 🤗
+colorFrom: blue
+colorTo: green
 sdk: gradio
 sdk_version: 6.19.0
 python_version: '3.13'
 app_file: app.py
 pinned: false
 license: mit
-short_description: 'I am using this space to test and demonstrate '
+short_description: Hello World AI app — sentiment analysis with DistilBERT
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Hello World — AI Sentiment Analysis
+
+A minimal Hugging Face Space for students learning to build AI apps.
+
+## What it does
+Classifies any sentence as **Positive** or **Negative** using
+[DistilBERT](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english),
+a lightweight model fine-tuned on the Stanford Sentiment Treebank.
+
+## Stack
+- **UI**: Gradio
+- **Model**: `distilbert-base-uncased-finetuned-sst-2-english`
+- **Runtime**: 🤗 Transformers + PyTorch (CPU)
+
+## Run locally
+```bash
+pip install -r requirements.txt
+python app.py
+```

app.py

@@ -0,0 +1,43 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load a tiny, fast model — runs on CPU in seconds
+sentiment = pipeline(
+    "sentiment-analysis",
+    model="distilbert-base-uncased-finetuned-sst-2-english",
+)
+
+
+def analyze(text: str) -> str:
+    if not text.strip():
+        return "Please enter some text."
+    result = sentiment(text)[0]
+    label = result["label"].capitalize()
+    score = round(result["score"] * 100, 1)
+    emoji = "😊" if label == "Positive" else "😞"
+    return f"{emoji} **{label}** ({score}% confidence)"
+
+
+demo = gr.Interface(
+    fn=analyze,
+    inputs=gr.Textbox(
+        label="Your text",
+        placeholder="Type anything… e.g. 'I love building AI apps!'",
+        lines=3,
+    ),
+    outputs=gr.Markdown(label="Sentiment"),
+    title="🤗 Hello World — AI Sentiment Analysis",
+    description=(
+        "Type a sentence and the model will tell you whether it sounds "
+        "**positive** or **negative**. Powered by DistilBERT on 🤗 Transformers."
+    ),
+    examples=[
+        ["I love learning about machine learning!"],
+        ["This assignment is really frustrating."],
+        ["The weather is okay today."],
+    ],
+    cache_examples=False,
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+gradio>=4.0.0
+transformers>=4.40.0
+torch>=2.0.0