initia

Author: astorfi

.github/workflows/deploy.yml

@@ -0,0 +1,50 @@
+name: CI/CD Pipeline
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+    - name: Checkout Code
+      uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.8'
+
+    - name: Install Dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -r requirements.txt
+
+    - name: Lint Code
+      run: pylint app/**/*.py
+
+    - name: Run Unit Tests
+      run: pytest tests/
+
+    - name: Set up Docker Buildx
+      uses: docker/setup-buildx-action@v1
+
+    - name: Build and Push Docker Image
+      uses: docker/build-push-action@v2
+      with:
+        context: .
+        tags: user/repository:latest
+        push: true
+
+  deploy:
+    needs: build
+    runs-on: ubuntu-latest
+    steps:
+    - name: Deploy to Kubernetes
+      uses: azure/k8s-deploy@v1
+      with:
+        manifests: |
+          deployment/kubernetes/deployment.yml
+          deployment/kubernetes/service.yml

README.md

@@ -126,6 +126,45 @@ For hyperparameter tuning, **Optuna** has been integrated to provide automated e
 - **🔍 Explainability**: SHAP and LIME explainability metrics are added to the evaluation process, providing insights into model behavior.
 - **📜 Logging**: Centralized logging using **ELK Stack** (Elasticsearch, Logstash, Kibana).
 
+## 🚀 Cloud Deployment Instructions (AWS)
+
+To deploy the LLM Alignment Assistant on **AWS**, you can utilize **Elastic Kubernetes Service (EKS)** or **AWS Sagemaker** for model training:
+
+1. **AWS Elastic Kubernetes Service (EKS)**:
+   - Create an EKS cluster using AWS CLI or the console.
+   - Apply the Kubernetes deployment files:
+     ```bash
+     kubectl apply -f deployment/kubernetes/deployment.yml
+     kubectl apply -f deployment/kubernetes/service.yml
+     ```
+   - Configure the **Horizontal Pod Autoscaler (HPA)** to ensure scalability:
+     ```bash
+     kubectl apply -f deployment/kubernetes/hpa.yml
+     ```
+
+2. **AWS Sagemaker for Model Training**:
+   - Modify the `training/fine_tuning.py` to integrate with AWS Sagemaker.
+   - Use the Sagemaker Python SDK to launch a training job:
+     ```python
+     import sagemaker
+     from sagemaker.pytorch import PyTorch
+
+     role = "arn:aws:iam::your-account-id:role/service-role/AmazonSageMaker-ExecutionRole-2023"
+
+     pytorch_estimator = PyTorch(
+         entry_point='training/fine_tuning.py',
+         role=role,
+         instance_count=1,
+         instance_type='ml.p2.xlarge',
+         framework_version='1.8.0',
+         py_version='py3'
+     )
+
+     pytorch_estimator.fit({'training': 's3://your-bucket-name/training-data'})
+     ```
+   - Ensure IAM roles and permissions are properly set for accessing **S3** and **Sagemaker**.
+
+
 ## 🚀 Future Work
 
 - **🌍 Multi-Language Support**: Expand the LLM's training to support multiple languages.

app/auth.py

@@ -0,0 +1,67 @@
+# User Authentication using Flask-Login
+
+from flask import Flask, render_template, redirect, url_for, request, flash
+from flask_login import LoginManager, UserMixin, login_user, login_required, logout_user
+from werkzeug.security import generate_password_hash, check_password_hash
+
+app = Flask(__name__)
+app.secret_key = 'secret-key'
+
+# User session management setup
+login_manager = LoginManager()
+login_manager.init_app(app)
+login_manager.login_view = "login"
+
+# Mock database for users
+users = {}
+
+class User(UserMixin):
+    def __init__(self, id, username, password):
+        self.id = id
+        self.username = username
+        self.password_hash = generate_password_hash(password)
+
+@login_manager.user_loader
+def load_user(user_id):
+    return users.get(user_id)
+
+@app.route('/register', methods=['GET', 'POST'])
+def register():
+    if request.method == 'POST':
+        username = request.form['username']
+        password = request.form['password']
+        user_id = len(users) + 1
+        if username in [user.username for user in users.values()]:
+            flash("Username already exists. Please choose a different one.")
+        else:
+            users[user_id] = User(user_id, username, password)
+            flash("User registered successfully!")
+        return redirect(url_for('login'))
+    return render_template('register.html')
+
+@app.route('/login', methods=['GET', 'POST'])
+def login():
+    if request.method == 'POST':
+        username = request.form['username']
+        password = request.form['password']
+        user = next((u for u in users.values() if u.username == username), None)
+        if user and check_password_hash(user.password_hash, password):
+            login_user(user)
+            return redirect(url_for('dashboard'))
+        else:
+            flash("Invalid username or password.")
+    return render_template('login.html')
+
+@app.route('/dashboard')
+@login_required
+def dashboard():
+    return render_template('dashboard.html')
+
+@app.route('/logout')
+@login_required
+def logout():
+    logout_user()
+    return redirect(url_for('login'))
+
+if __name__ == '__main__':
+    app.run(debug=True)

app/feedback.py

@@ -0,0 +1,30 @@
+# Flask route for handling feedback submission
+
+from flask import Flask, request, jsonify, render_template
+import csv
+
+app = Flask(__name__)
+
+# Route to render feedback form
+@app.route('/feedback', methods=['GET'])
+def feedback():
+    # You can dynamically pass the response to be rated in 'response' variable
+    response = "Example response from LLM to be rated"
+    return render_template('feedback.html', response=response)
+
+# Route to handle feedback submission
+@app.route('/submit-feedback', methods=['POST'])
+def submit_feedback():
+    rating = request.form['rating']
+    comments = request.form['comments']
+    model_response = request.form['model-response']
+    
+    # Save feedback to a CSV file
+    with open('feedback.csv', mode='a') as feedback_file:
+        feedback_writer = csv.writer(feedback_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
+        feedback_writer.writerow([model_response, rating, comments])
+    
+    return jsonify(status='success', message='Thank you for your feedback!')
+
+if __name__ == "__main__":
+    app.run(debug=True)

app/static/app.js

@@ -1 +1,46 @@
-console.log('App JS');
+// UI Enhancements - Adding Animations, Dark Mode Toggle, and Tooltips
+
+document.addEventListener('DOMContentLoaded', function() {
+    // Dark Mode Toggle
+    const darkModeToggle = document.getElementById('dark-mode-toggle');
+    const body = document.body;
+  
+    darkModeToggle.addEventListener('click', () => {
+      body.classList.toggle('dark-mode');
+      if (body.classList.contains('dark-mode')) {
+        localStorage.setItem('theme', 'dark');
+      } else {
+        localStorage.setItem('theme', 'light');
+      }
+    });
+  
+    // Persist Dark Mode Setting
+    if (localStorage.getItem('theme') === 'dark') {
+      body.classList.add('dark-mode');
+    }
+  
+    // Tooltip Initialization
+    const tooltips = document.querySelectorAll('.tooltip');
+    tooltips.forEach(tooltip => {
+      tooltip.addEventListener('mouseover', function() {
+        const tooltipText = document.createElement('span');
+        tooltipText.className = 'tooltip-text';
+        tooltipText.innerText = this.getAttribute('data-tooltip');
+        this.appendChild(tooltipText);
+      });
+      tooltip.addEventListener('mouseout', function() {
+        const tooltipText = this.querySelector('.tooltip-text');
+        if (tooltipText) this.removeChild(tooltipText);
+      });
+    });
+  
+    // GSAP Animations for Elements
+    gsap.from('.card', {
+      duration: 1,
+      y: 50,
+      opacity: 0,
+      stagger: 0.2,
+      ease: 'power2.out'
+    });
+  });
+  

app/static/chart.js

@@ -0,0 +1,60 @@
+// Interactive Chart.js Visualizations
+
+document.addEventListener('DOMContentLoaded', function() {
+    const ctx = document.getElementById('modelPerformanceChart').getContext('2d');
+    const modelPerformanceChart = new Chart(ctx, {
+      type: 'line',
+      data: {
+        labels: ['Epoch 1', 'Epoch 2', 'Epoch 3', 'Epoch 4', 'Epoch 5'],
+        datasets: [{
+          label: 'Training Loss',
+          data: [0.8, 0.6, 0.4, 0.3, 0.2],
+          borderColor: 'rgba(75, 192, 192, 1)',
+          backgroundColor: 'rgba(75, 192, 192, 0.2)',
+          fill: true,
+          tension: 0.4
+        }, {
+          label: 'Validation Loss',
+          data: [0.9, 0.7, 0.5, 0.4, 0.3],
+          borderColor: 'rgba(255, 99, 132, 1)',
+          backgroundColor: 'rgba(255, 99, 132, 0.2)',
+          fill: true,
+          tension: 0.4
+        }]
+      },
+      options: {
+        responsive: true,
+        plugins: {
+          legend: {
+            position: 'top',
+          },
+          tooltip: {
+            mode: 'index',
+            intersect: false,
+          }
+        },
+        interaction: {
+          mode: 'nearest',
+          axis: 'x',
+          intersect: false
+        },
+        scales: {
+          x: {
+            display: true,
+            title: {
+              display: true,
+              text: 'Epoch'
+            }
+          },
+          y: {
+            display: true,
+            title: {
+              display: true,
+              text: 'Loss'
+            }
+          }
+        }
+      }
+    });
+  });
+  

app/static/styles.css

@@ -1 +1,52 @@
-body { font-family: Arial; }
+/* Dark Mode Styles */
+body.dark-mode {
+    background-color: #121212;
+    color: #ffffff;
+  }
+  
+  button#dark-mode-toggle {
+    background-color: #333;
+    color: #fff;
+    border: none;
+    padding: 10px;
+    cursor: pointer;
+    border-radius: 5px;
+  }
+  
+  button#dark-mode-toggle:hover {
+    background-color: #555;
+  }
+  
+  /* Tooltip Styles */
+  .tooltip {
+    position: relative;
+    cursor: pointer;
+  }
+  
+  .tooltip .tooltip-text {
+    position: absolute;
+    bottom: 125%;
+    left: 50%;
+    transform: translateX(-50%);
+    background-color: #333;
+    color: #fff;
+    padding: 5px;
+    border-radius: 4px;
+    white-space: nowrap;
+    opacity: 0;
+    transition: opacity 0.3s;
+  }
+  
+  .tooltip:hover .tooltip-text {
+    opacity: 1;
+  }
+  
+  /* GSAP Animation Styles */
+  .card {
+    background: #f8f8f8;
+    padding: 20px;
+    margin: 20px;
+    border-radius: 10px;
+    box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
+  }
+