init

Dockerfile

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+FROM python:3.10-slim
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements first for better caching
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application files
+COPY app.py .
+COPY templates/ templates/
+COPY static/ static/
+
+# Expose the port
+EXPOSE 7860
+
+# Set environment variables for Hugging Face Spaces
+ENV GRADIO_SERVER_NAME="0.0.0.0"
+ENV GRADIO_SERVER_PORT=7860
+
+# Run the application
+CMD ["python", "app.py"]

README.md

@@ -1,13 +1,74 @@
----
-title: Llm Projec 2
-emoji: 🐨
-colorFrom: red
-colorTo: purple
-sdk: gradio
-sdk_version: 5.49.1
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Prompt Safety Checker Web App
+
+A Flask web application that uses the `viccon23/STU-Injection-aegis` Hugging Face model to classify prompts as safe or unsafe.
+
+## Features
+
+- 🛡️ Real-time prompt safety classification
+- 🎨 Modern, responsive UI
+- 📊 Confidence score display
+- ⚡ Fast inference with PyTorch
+
+## Installation
+
+1. Install dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+## Usage
+
+### Local Development
+
+1. Start the web server:
+```bash
+python app.py
+```
+
+2. Open your browser and navigate to:
+```
+http://localhost:7860
+```
+
+3. Enter a prompt in the text area and click "Check Safety"
+
+### Docker Deployment
+
+Build and run with Docker:
+```bash
+docker build -t prompt-safety-checker .
+docker run -p 7860:7860 prompt-safety-checker
+```
+
+### Hugging Face Spaces Deployment
+
+1. Create a new Docker Space on Hugging Face
+2. Upload the following files:
+   - `Dockerfile`
+   - `app.py`
+   - `requirements.txt`
+   - `templates/index.html`
+3. The app will automatically deploy on port 7860
+
+## Model
+
+This app uses the [STU-Injection-aegis](https://huggingface.co/viccon23/STU-Injection-aegis) model from Hugging Face, which is designed to detect potentially unsafe or malicious prompts that could be used for injection attacks.
+
+## API Endpoint
+
+You can also use the API directly:
+
+```bash
+curl -X POST http://localhost:5000/classify \
+  -H "Content-Type: application/json" \
+  -d '{"prompt": "Your prompt here"}'
+```
+
+Response:
+```json
+{
+  "label": "Safe",
+  "confidence": 95.32,
+  "predicted_class": 0
+}
+```

app.py

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+from flask import Flask, render_template, request, jsonify
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+app = Flask(__name__)
+
+# Load model and tokenizer
+MODEL_NAME = "viccon23/STU-Injection-aegis"
+print("Loading model...")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
+print("Model loaded successfully!")
+
+def classify_prompt(text):
+    """Classify if a prompt is safe or unsafe"""
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
+    
+    with torch.no_grad():
+        outputs = model(**inputs)
+        predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
+        predicted_class = torch.argmax(predictions, dim=-1).item()
+        confidence = predictions[0][predicted_class].item()
+    
+    # Assuming class 0 is safe and class 1 is unsafe
+    label = "Safe" if predicted_class == 0 else "Unsafe"
+    
+    return {
+        "label": label,
+        "confidence": round(confidence * 100, 2),
+        "predicted_class": predicted_class
+    }
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/classify', methods=['POST'])
+def classify():
+    data = request.get_json()
+    prompt = data.get('prompt', '')
+    
+    if not prompt:
+        return jsonify({"error": "No prompt provided"}), 400
+    
+    result = classify_prompt(prompt)
+    return jsonify(result)
+
+if __name__ == '__main__':
+    import os
+    port = int(os.environ.get('PORT', 7860))
+    app.run(debug=False, host='0.0.0.0', port=port)

requirements.txt

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+flask==3.0.0
+transformers==4.36.0
+torch==2.1.0

templates/index.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Prompt Safety Checker</title>
+    <style>
+        * {
+            margin: 0;
+            padding: 0;
+            box-sizing: border-box;
+        }
+        
+        body {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            min-height: 100vh;
+            display: flex;
+            justify-content: center;
+            align-items: center;
+            padding: 20px;
+        }
+        
+        .container {
+            background: white;
+            border-radius: 20px;
+            box-shadow: 0 20px 60px rgba(0, 0, 0, 0.3);
+            padding: 40px;
+            max-width: 700px;
+            width: 100%;
+        }
+        
+        h1 {
+            color: #333;
+            margin-bottom: 10px;
+            text-align: center;
+        }
+        
+        .subtitle {
+            color: #666;
+            text-align: center;
+            margin-bottom: 30px;
+            font-size: 14px;
+        }
+        
+        .input-group {
+            margin-bottom: 20px;
+        }
+        
+        label {
+            display: block;
+            margin-bottom: 10px;
+            color: #555;
+            font-weight: 600;
+        }
+        
+        textarea {
+            width: 100%;
+            padding: 15px;
+            border: 2px solid #e0e0e0;
+            border-radius: 10px;
+            font-size: 16px;
+            font-family: inherit;
+            resize: vertical;
+            min-height: 150px;
+            transition: border-color 0.3s;
+        }
+        
+        textarea:focus {
+            outline: none;
+            border-color: #667eea;
+        }
+        
+        button {
+            width: 100%;
+            padding: 15px;
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            color: white;
+            border: none;
+            border-radius: 10px;
+            font-size: 18px;
+            font-weight: 600;
+            cursor: pointer;
+            transition: transform 0.2s, box-shadow 0.2s;
+        }
+        
+        button:hover {
+            transform: translateY(-2px);
+            box-shadow: 0 10px 20px rgba(102, 126, 234, 0.4);
+        }
+        
+        button:active {
+            transform: translateY(0);
+        }
+        
+        button:disabled {
+            background: #ccc;
+            cursor: not-allowed;
+            transform: none;
+        }
+        
+        .result {
+            margin-top: 30px;
+            padding: 25px;
+            border-radius: 10px;
+            display: none;
+            animation: slideIn 0.3s ease-out;
+        }
+        
+        @keyframes slideIn {
+            from {
+                opacity: 0;
+                transform: translateY(-10px);
+            }
+            to {
+                opacity: 1;
+                transform: translateY(0);
+            }
+        }
+        
+        .result.safe {
+            background: #d4edda;
+            border: 2px solid #28a745;
+        }
+        
+        .result.unsafe {
+            background: #f8d7da;
+            border: 2px solid #dc3545;
+        }
+        
+        .result-label {
+            font-size: 24px;
+            font-weight: 700;
+            margin-bottom: 10px;
+        }
+        
+        .result.safe .result-label {
+            color: #28a745;
+        }
+        
+        .result.unsafe .result-label {
+            color: #dc3545;
+        }
+        
+        .result-confidence {
+            font-size: 16px;
+            color: #555;
+        }
+        
+        .loading {
+            text-align: center;
+            color: #667eea;
+            font-weight: 600;
+            margin-top: 20px;
+            display: none;
+        }
+        
+        .error {
+            background: #f8d7da;
+            border: 2px solid #dc3545;
+            color: #721c24;
+            padding: 15px;
+            border-radius: 10px;
+            margin-top: 20px;
+            display: none;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>🛡️ Prompt Safety Checker</h1>
+        <p class="subtitle">Using STU-Injection-aegis Model</p>
+        
+        <div class="input-group">
+            <label for="prompt">Enter your prompt:</label>
+            <textarea id="prompt" placeholder="Type or paste your prompt here..."></textarea>
+        </div>
+        
+        <button id="checkBtn" onclick="checkPrompt()">Check Safety</button>
+        
+        <div class="loading" id="loading">Analyzing prompt...</div>
+        <div class="error" id="error"></div>
+        <div class="result" id="result">
+            <div class="result-label" id="resultLabel"></div>
+            <div class="result-confidence" id="resultConfidence"></div>
+        </div>
+    </div>
+    
+    <script>
+        async function checkPrompt() {
+            const promptText = document.getElementById('prompt').value.trim();
+            const resultDiv = document.getElementById('result');
+            const loadingDiv = document.getElementById('loading');
+            const errorDiv = document.getElementById('error');
+            const checkBtn = document.getElementById('checkBtn');
+            
+            if (!promptText) {
+                errorDiv.textContent = 'Please enter a prompt to check.';
+                errorDiv.style.display = 'block';
+                resultDiv.style.display = 'none';
+                return;
+            }
+            
+            // Reset displays
+            resultDiv.style.display = 'none';
+            errorDiv.style.display = 'none';
+            loadingDiv.style.display = 'block';
+            checkBtn.disabled = true;
+            
+            try {
+                const response = await fetch('/classify', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json',
+                    },
+                    body: JSON.stringify({ prompt: promptText })
+                });
+                
+                if (!response.ok) {
+                    throw new Error('Failed to classify prompt');
+                }
+                
+                const data = await response.json();
+                
+                // Display result
+                resultDiv.className = 'result ' + data.label.toLowerCase();
+                document.getElementById('resultLabel').textContent = data.label;
+                document.getElementById('resultConfidence').textContent = 
+                    `Confidence: ${data.confidence}%`;
+                
+                loadingDiv.style.display = 'none';
+                resultDiv.style.display = 'block';
+                
+            } catch (error) {
+                loadingDiv.style.display = 'none';
+                errorDiv.textContent = 'Error: ' + error.message;
+                errorDiv.style.display = 'block';
+            } finally {
+                checkBtn.disabled = false;
+            }
+        }
+        
+        // Allow Enter key to submit (with Ctrl/Cmd)
+        document.getElementById('prompt').addEventListener('keydown', function(e) {
+            if (e.key === 'Enter' && (e.ctrlKey || e.metaKey)) {
+                checkPrompt();
+            }
+        });
+    </script>
+</body>
+</html>