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CodeBy-HPCodeBy-HP
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CICD run - 11
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‎.github/workflows/deploy.yml‎

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if: success()
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env:
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CAPSTONE_TEST: ${{ secrets.CAPSTONE_TEST }}
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run: python -m unittest tests/test_fastapi_app.py
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run: python -m unittest tests/test_fastapi_app.py
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# - name: Login to AWS ECR
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# if: success()
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# run: |
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# aws configure set aws_access_key_id ${{ secrets.AWS_ACCESS_KEY_ID }}
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# aws configure set aws_secret_access_key ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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# aws configure set region ${{ secrets.AWS_REGION }}
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# aws ecr get-login-password --region ${{ secrets.AWS_REGION }} | docker login --username AWS --password-stdin ${{ secrets.AWS_ACCOUNT_ID }}.dkr.ecr.${{ secrets.AWS_REGION }}.amazonaws.com
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# - name: Build Docker image
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# run: |
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# docker build -t ${{ secrets.ECR_REPOSITORY }}:latest .
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# - name: Tag Docker image
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# run: |
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# docker tag ${{ secrets.ECR_REPOSITORY }}:latest \
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# ${{ secrets.AWS_ACCOUNT_ID }}.dkr.ecr.${{ secrets.AWS_REGION }}.amazonaws.com/${{ secrets.ECR_REPOSITORY }}:latest
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# - name: Check Docker Authentication
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# run: docker info
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# - name: Push Docker image to ECR
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# run: |
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# docker push ${{ secrets.AWS_ACCOUNT_ID }}.dkr.ecr.${{ secrets.AWS_REGION }}.amazonaws.com/${{ secrets.ECR_REPOSITORY }}:latest

‎Dockerfile‎

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FROM python:3.10-slim
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WORKDIR /app
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COPY fastapi_app/ /app/
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COPY models/vectorizer.pkl /app/models/vectorizer.pkl
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RUN pip install -r requirements.txt
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RUN python -m nltk.downloader stopwords wordnet
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EXPOSE 5000
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#local
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# CMD ["python", "app.py"]
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#Prod
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CMD ["gunicorn", "--bind", "0.0.0.0:5000", "--timeout", "120", "app:app"]

‎fastapi_app/app.py‎

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warnings.simplefilter("ignore", UserWarning)
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warnings.filterwarnings("ignore")
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from dotenv import load_dotenv
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load_dotenv()
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def lemmatization(text):
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"""Lemmatize the text."""
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lemmatizer = WordNetLemmatizer()

‎fastapi_app/templates/index.html‎

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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Sentiment Analysis AI</title>
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<!-- Tailwind CSS CDN -->
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<script src="https://cdn.jsdelivr.net/npm/@tailwindcss/browser@4"></script>
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<!-- Custom Tailwind Configuration -->
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<script>
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tailwind.config = {
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theme: {
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extend: {
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colors: {
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primary: '#3b82f6',
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secondary: '#8b5cf6',
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}
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}
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}
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<title>Sentiment Analysis</title>
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<script src="https://cdn.tailwindcss.com"></script>
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<style>
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@keyframes fadeIn {
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from { opacity: 0; transform: translateY(10px); }
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to { opacity: 1; transform: translateY(0); }
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}
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.fade-in {
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animation: fadeIn 0.5s ease-out forwards;
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}
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body {
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font-family: 'Inter', sans-serif;
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}
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</script>
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<!-- Font Awesome for Icons -->
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<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.5.1/css/all.min.css">
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.glass-card {
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background: rgba(255, 255, 255, 0.05);
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backdrop-filter: blur(10px);
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border: 1px solid rgba(255, 255, 255, 0.1);
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}
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.btn-gradient {
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background-image: linear-gradient(to right, #4f46e5, #c026d3);
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}
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</style>
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<link rel="preconnect" href="https://fonts.googleapis.com">
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<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
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<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap" rel="stylesheet">
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</head>
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<body class="bg-gradient-to-br from-blue-50 via-white to-purple-50 min-h-screen">
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<!-- Header -->
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<header class="bg-white shadow-md">
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<div class="container mx-auto px-4 py-6">
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<div class="flex items-center justify-between">
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<div class="flex items-center space-x-3">
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<div class="bg-gradient-to-r from-blue-500 to-purple-600 p-3 rounded-lg">
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<i class="fas fa-brain text-white text-2xl"></i>
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</div>
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<div>
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<h1 class="text-3xl font-bold bg-gradient-to-r from-blue-600 to-purple-600 bg-clip-text text-transparent">
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Sentiment Analysis AI
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</h1>
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<p class="text-sm text-gray-600">Powered by Machine Learning</p>
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</div>
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</div>
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<body class="bg-gray-900 text-white">
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<div class="min-h-screen flex flex-col items-center justify-center p-4">
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<div class="w-full max-w-2xl">
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<div class="text-center mb-8 fade-in">
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<h1 class="text-4xl md:text-5xl font-bold tracking-tight">Sentiment Analyzer</h1>
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<p class="text-gray-400 mt-3 text-lg">Instantly analyze the sentiment of your text.</p>
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</div>
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</div>
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</header>
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<!-- Main Content -->
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<main class="container mx-auto px-4 py-12">
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<div class="max-w-4xl mx-auto">
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<!-- Info Cards -->
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<div class="grid md:grid-cols-3 gap-6 mb-12">
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<div class="bg-white rounded-xl shadow-lg p-6 hover:shadow-xl transition-shadow">
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<div class="flex items-center justify-center w-12 h-12 bg-blue-100 rounded-lg mb-4">
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<i class="fas fa-robot text-blue-600 text-xl"></i>
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</div>
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<h3 class="text-lg font-semibold text-gray-800 mb-2">AI-Powered</h3>
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<p class="text-gray-600 text-sm">Advanced NLP model for accurate sentiment detection</p>
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</div>
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<div class="bg-white rounded-xl shadow-lg p-6 hover:shadow-xl transition-shadow">
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<div class="flex items-center justify-center w-12 h-12 bg-purple-100 rounded-lg mb-4">
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<i class="fas fa-bolt text-purple-600 text-xl"></i>
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<div class="glass-card rounded-2xl shadow-2xl p-8 fade-in" style="animation-delay: 0.2s;">
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<form action="/predict" method="POST">
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<div class="mb-6">
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<label for="text" class="sr-only">Your text</label>
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<textarea
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id="text"
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name="text"
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rows="6"
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required
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class="w-full bg-gray-800 border-2 border-gray-700 rounded-lg px-4 py-3 text-base text-white placeholder-gray-500 focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 transition-all duration-300 resize-none"
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placeholder="Enter text to analyze..."
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></textarea>
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</div>
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<h3 class="text-lg font-semibold text-gray-800 mb-2">Lightning Fast</h3>
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<p class="text-gray-600 text-sm">Get instant sentiment analysis in milliseconds</p>
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</div>
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<div class="bg-white rounded-xl shadow-lg p-6 hover:shadow-xl transition-shadow">
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<div class="flex items-center justify-center w-12 h-12 bg-green-100 rounded-lg mb-4">
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<i class="fas fa-shield-alt text-green-600 text-xl"></i>
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</div>
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<h3 class="text-lg font-semibold text-gray-800 mb-2">Secure & Private</h3>
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<p class="text-gray-600 text-sm">Your data is processed securely and never stored</p>
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</div>
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</div>
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<!-- Main Analysis Card -->
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<div class="bg-white rounded-2xl shadow-2xl overflow-hidden">
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<div class="bg-gradient-to-r from-blue-600 to-purple-600 px-8 py-6">
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<h2 class="text-2xl font-bold text-white flex items-center">
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<i class="fas fa-comment-dots mr-3"></i>
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Analyze Your Text
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</h2>
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<p class="text-blue-100 mt-2">Enter your text below to analyze its sentiment</p>
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</div>
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<button
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type="submit"
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class="w-full btn-gradient text-white font-semibold py-3 rounded-lg transition-transform transform hover:scale-105 focus:outline-none focus:ring-4 focus:ring-purple-500 focus:ring-opacity-50"
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>
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Analyze Sentiment
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</button>
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</form>
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<div class="p-8">
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<form action="/predict" method="POST" class="space-y-6">
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{% if result is not none %}
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<div class="mt-8 pt-6 border-t border-gray-700 fade-in" style="animation-delay: 0.4s;">
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{% if result == 1 %}
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<div class="flex items-start space-x-4 bg-green-500/10 border border-green-500/30 text-green-300 px-5 py-4 rounded-lg">
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<svg class="w-6 h-6 flex-shrink-0 mt-1" fill="none" stroke="currentColor" viewBox="0 0 24 24" xmlns="http://www.w3.org/2000/svg"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M14.828 14.828a4 4 0 01-5.656 0M9 10h.01M15 10h.01M21 12a9 9 0 11-18 0 9 9 0 0118 0z"></path></svg>
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<div>
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<label for="text" class="block text-sm font-semibold text-gray-700 mb-3">
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<i class="fas fa-pencil-alt mr-2 text-blue-600"></i>Your Text
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</label>
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<textarea
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id="text"
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name="text"
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rows="6"
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required
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class="w-full px-4 py-3 border-2 border-gray-300 rounded-xl focus:ring-2 focus:ring-blue-500 focus:border-transparent transition-all resize-none text-gray-800 placeholder-gray-400"
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placeholder="Type or paste your text here... (e.g., 'I absolutely loved this movie! It was fantastic!')"></textarea>
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<p class="mt-2 text-xs text-gray-500">
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<i class="fas fa-info-circle mr-1"></i>
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Tip: The more context you provide, the better the analysis
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</p>
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</div>
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<button
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type="submit"
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class="w-full bg-gradient-to-r from-blue-600 to-purple-600 text-white font-semibold py-4 px-6 rounded-xl hover:from-blue-700 hover:to-purple-700 transform hover:scale-[1.02] transition-all duration-200 shadow-lg hover:shadow-xl flex items-center justify-center space-x-2">
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<i class="fas fa-chart-line"></i>
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<span>Analyze Sentiment</span>
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</button>
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</form>
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<!-- Result Display -->
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{% if result is not none %}
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<div class="mt-8 animate-fade-in">
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<div class="border-t-2 border-gray-200 pt-6">
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<h3 class="text-lg font-semibold text-gray-800 mb-4 flex items-center">
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<i class="fas fa-poll mr-2 text-gray-700"></i>Analysis Result
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</h3>
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{% if result == 1 %}
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<!-- Positive Result -->
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<div class="bg-gradient-to-r from-green-50 to-emerald-50 border-2 border-green-300 rounded-xl p-6">
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<div class="flex items-center justify-between">
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<div class="flex items-center space-x-4">
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<div class="bg-green-500 rounded-full p-4">
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<i class="fas fa-smile-beam text-white text-3xl"></i>
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</div>
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<div>
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<h4 class="text-2xl font-bold text-green-700">Positive Sentiment</h4>
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<p class="text-green-600 mt-1">This text expresses positive emotions</p>
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</div>
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</div>
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<div class="hidden md:block">
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<div class="text-6xl">😊</div>
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</div>
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</div>
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</div>
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{% else %}
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<!-- Negative Result -->
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<div class="bg-gradient-to-r from-red-50 to-pink-50 border-2 border-red-300 rounded-xl p-6">
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<div class="flex items-center justify-between">
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<div class="flex items-center space-x-4">
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<div class="bg-red-500 rounded-full p-4">
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<i class="fas fa-frown text-white text-3xl"></i>
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</div>
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<div>
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<h4 class="text-2xl font-bold text-red-700">Negative Sentiment</h4>
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<p class="text-red-600 mt-1">This text expresses negative emotions</p>
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</div>
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</div>
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<div class="hidden md:block">
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<div class="text-6xl">😞</div>
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</div>
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</div>
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</div>
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{% endif %}
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<h4 class="text-lg font-semibold">Positive Sentiment</h4>
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<p class="text-sm text-green-300/80">The analysis indicates a positive tone.</p>
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</div>
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</div>
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{% endif %}
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</div>
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</div>
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<!-- How It Works Section -->
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<div class="mt-12 bg-white rounded-xl shadow-lg p-8">
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<h3 class="text-2xl font-bold text-gray-800 mb-6 text-center">
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<i class="fas fa-lightbulb text-yellow-500 mr-2"></i>How It Works
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</h3>
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<div class="grid md:grid-cols-4 gap-6">
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<div class="text-center">
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<div class="bg-blue-100 rounded-full w-16 h-16 flex items-center justify-center mx-auto mb-3">
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<span class="text-2xl font-bold text-blue-600">1</span>
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</div>
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<p class="text-sm text-gray-600">Enter your text</p>
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</div>
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<div class="text-center">
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<div class="bg-purple-100 rounded-full w-16 h-16 flex items-center justify-center mx-auto mb-3">
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<span class="text-2xl font-bold text-purple-600">2</span>
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</div>
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<p class="text-sm text-gray-600">AI processes text</p>
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</div>
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<div class="text-center">
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<div class="bg-pink-100 rounded-full w-16 h-16 flex items-center justify-center mx-auto mb-3">
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<span class="text-2xl font-bold text-pink-600">3</span>
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</div>
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<p class="text-sm text-gray-600">Analyze sentiment</p>
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</div>
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<div class="text-center">
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<div class="bg-green-100 rounded-full w-16 h-16 flex items-center justify-center mx-auto mb-3">
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<span class="text-2xl font-bold text-green-600">4</span>
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{% else %}
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<div class="flex items-start space-x-4 bg-red-500/10 border border-red-500/30 text-red-300 px-5 py-4 rounded-lg">
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<svg class="w-6 h-6 flex-shrink-0 mt-1" fill="none" stroke="currentColor" viewBox="0 0 24 24" xmlns="http://www.w3.org/2000/svg"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9.172 16.172a4 4 0 015.656 0M9 10h.01M15 10h.01M21 12a9 9 0 11-18 0 9 9 0 0118 0z"></path></svg>
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<div>
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<h4 class="text-lg font-semibold">Negative Sentiment</h4>
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<p class="text-sm text-red-300/80">The analysis indicates a negative tone.</p>
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</div>
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<p class="text-sm text-gray-600">Get instant results</p>
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</div>
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{% endif %}
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</div>
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{% endif %}
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</div>
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</div>
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</main>
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<!-- Footer -->
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<footer class="bg-gray-900 text-white mt-20">
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<div class="container mx-auto px-4 py-8">
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<div class="text-center">
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<p class="text-gray-400">
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<i class="fas fa-code mr-2"></i>Built with FastAPI & MLflow |
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<i class="fas fa-brain ml-2 mr-2"></i>Powered by Advanced NLP
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</p>
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</div>
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</div>
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</footer>
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<!-- Add fade-in animation -->
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<style>
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@keyframes fadeIn {
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from { opacity: 0; transform: translateY(10px); }
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to { opacity: 1; transform: translateY(0); }
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}
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.animate-fade-in {
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animation: fadeIn 0.5s ease-out;
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}
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</style>
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</div>
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</body>
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</html>

‎params.yaml‎

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test_size: 0.25
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feature_engineering:
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max_features: 50
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max_features: 1000

‎sentiment_classification/data/data_ingestion.py‎

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test_size = params['data_ingestion']['test_size']
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# test_size = 0.2
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df = load_data(data_url='https://raw.githubusercontent.com/CodeBy-HP/Sentiment-Classification-Mlflow-DVC/refs/heads/main/notebooks/data.csv')
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df = load_data(data_url='https://raw.githubusercontent.com/CodeBy-HP/Sentiment-Classification-Mlflow-DVC/refs/heads/main/notebooks/IMDB.csv')
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# s3 = s3_connection.s3_operations(bucketname,accesskey,secretkey)
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# df = s3.fetch_file_from_s3("data.csv")

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