Add HuggingFace Spaces deployment (16GB RAM free tier)

DEPLOY_HUGGINGFACE.md

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+# 🚀 Deploy LinkScout Backend on Hugging Face Spaces (FREE)
+
+## Why Hugging Face Spaces?
+
+- ✅ **16GB RAM FREE** (vs Render's 512MB)
+- ✅ **Perfect for ML models** (built for this)
+- ✅ **Free GPU option** available
+- ✅ **Persistent storage** for models
+- ✅ **No credit card** required
+- ✅ **Always on** (no sleep like Render)
+
+---
+
+## 📦 Step-by-Step Deployment
+
+### Step 1: Create Hugging Face Account
+
+1. Go to https://huggingface.co/join
+2. Sign up (free, no credit card)
+3. Verify your email
+
+### Step 2: Create a New Space
+
+1. Go to https://huggingface.co/new-space
+2. Fill in details:
+   - **Owner**: Your username
+   - **Space name**: `linkscout-backend`
+   - **License**: MIT
+   - **Select SDK**: **Gradio** (we'll use custom Docker)
+   - **Space hardware**: **CPU basic (free)** - 16GB RAM!
+   - **Visibility**: Public
+
+3. Click **"Create Space"**
+
+### Step 3: Prepare Files for HuggingFace
+
+We need to create a few HuggingFace-specific files:
+
+#### 3.1 Create `app.py` (Entry point for HuggingFace)
+
+Create `D:\LinkScout\app.py`:
+
+```python
+# This is a wrapper for HuggingFace Spaces
+# It imports and runs the Flask server from combined_server.py
+
+if __name__ == '__main__':
+    import combined_server
+    # Server will start automatically when combined_server is imported
+```
+
+#### 3.2 Create `Dockerfile` (for HuggingFace Spaces)
+
+Create `D:\LinkScout\Dockerfile`:
+
+```dockerfile
+FROM python:3.11-slim
+
+# Set working directory
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY . .
+
+# Create cache directory for models
+RUN mkdir -p ./models_cache
+
+# Expose port (HuggingFace uses port 7860 by default)
+EXPOSE 7860
+
+# Set environment variables
+ENV PORT=7860
+ENV PYTHONUNBUFFERED=1
+
+# Run the application
+CMD ["python", "combined_server.py"]
+```
+
+#### 3.3 Create `README.md` for HuggingFace Space
+
+Create `D:\LinkScout\README_SPACE.md`:
+
+```markdown
+---
+title: LinkScout Backend
+emoji: 🔍
+colorFrom: orange
+colorTo: yellow
+sdk: docker
+pinned: false
+---
+
+# LinkScout AI-Powered Misinformation Detection Backend
+
+This is the backend API for LinkScout, featuring:
+
+- 🤖 8 Pre-trained ML Models
+- 🔬 8-Phase Revolutionary Detection
+- 🧠 Groq AI Integration
+- 🌐 Real-time Fact Checking
+
+## API Endpoints
+
+- `POST /analyze` - Analyze text for misinformation
+- `GET /health` - Health check
+- `POST /feedback` - Submit RL feedback
+
+## Environment Variables Required
+
+Set these in Space Settings → Variables:
+
+- `GROQ_API_KEY` - Your Groq API key
+- `GOOGLE_API_KEY` - (Optional) Google Search API key
+- `GOOGLE_CSE_ID` - (Optional) Google Custom Search Engine ID
+```
+
+### Step 4: Update Port for HuggingFace
+
+HuggingFace Spaces use port **7860** by default. Update `combined_server.py`:
+
+Find the port configuration section and update:
+
+```python
+if __name__ == '__main__':
+    import os
+    # HuggingFace Spaces uses port 7860, Render uses env PORT
+    port = int(os.environ.get('PORT', 7860))
+    print(f"  🌐 Port: {port}")
+    app.run(host='0.0.0.0', port=port, debug=False, threaded=True, use_reloader=False)
+```
+
+### Step 5: Push to HuggingFace
+
+#### Option A: Using Git (Recommended)
+
+```powershell
+# Add HuggingFace as a remote
+cd D:\LinkScout
+git remote add hf https://huggingface.co/spaces/YOUR_USERNAME/linkscout-backend
+
+# Push to HuggingFace
+git push hf main
+```
+
+**Replace `YOUR_USERNAME`** with your HuggingFace username!
+
+#### Option B: Upload Files Manually
+
+1. Go to your Space: `https://huggingface.co/spaces/YOUR_USERNAME/linkscout-backend`
+2. Click **"Files"** tab
+3. Click **"Add file"** → **"Upload files"**
+4. Upload all your files (drag & drop the entire `LinkScout` folder)
+
+### Step 6: Set Environment Variables
+
+1. Go to your Space settings
+2. Click **"Settings"** tab
+3. Scroll to **"Repository secrets"**
+4. Add secrets:
+   - Name: `GROQ_API_KEY`, Value: `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`
+   - Name: `GOOGLE_API_KEY`, Value: `AIzaSyA9yKthZUnPAHFnmsnCZoikpvfUteJiX0s`
+   - Name: `GOOGLE_CSE_ID`, Value: `11cbd494597034810`
+
+### Step 7: Wait for Build
+
+The Space will automatically build when you push files:
+
+1. Go to **"Logs"** tab to watch build progress
+2. First build takes **10-15 minutes** (downloads models)
+3. Look for:
+   ```
+   ✅ RoBERTa loaded
+   ✅ Emotion model loaded
+   ...
+   🚀 Starting LinkScout server on port 7860...
+   Running on http://0.0.0.0:7860
+   ```
+
+### Step 8: Get Your API URL
+
+Once deployed, your backend will be at:
+
+```
+https://YOUR_USERNAME-linkscout-backend.hf.space
+```
+
+**Example endpoints:**
+- Health check: `https://YOUR_USERNAME-linkscout-backend.hf.space/health`
+- Analyze: `https://YOUR_USERNAME-linkscout-backend.hf.space/analyze`
+
+---
+
+## 🎯 Advantages of HuggingFace Spaces
+
+| Feature | Render Free | HuggingFace Free |
+|---------|-------------|------------------|
+| **RAM** | 512MB ❌ | 16GB ✅ |
+| **ML Models** | Can't load ❌ | Perfect ✅ |
+| **Sleep** | After 15 min ⚠️ | Always on ✅ |
+| **Build Time** | Fast | Fast |
+| **Custom Domain** | Yes ✅ | Yes ✅ |
+| **For Your App** | Won't work ❌ | Perfect! ✅ |
+
+---
+
+## 🔧 Troubleshooting
+
+### Build Fails
+- Check logs for errors
+- Verify all files uploaded
+- Check Dockerfile syntax
+
+### Models Won't Load
+- Check you have 16GB RAM selected (CPU basic)
+- Verify requirements.txt has all dependencies
+- Check logs for download errors
+
+### API Not Responding
+- Check Space is "Running" (not building)
+- Verify port 7860 is used
+- Test health endpoint first
+
+### Environment Variables Not Working
+- Make sure they're set as "Repository secrets"
+- Restart the Space after adding secrets
+
+---
+
+## 🚀 Next Steps After Deployment
+
+1. **Test your backend:**
+   ```bash
+   curl https://YOUR_USERNAME-linkscout-backend.hf.space/health
+   ```
+
+2. **Update your frontend** to use new URL:
+   - Replace `http://localhost:5000` with your HF Space URL
+   - Update in `app/search/page.tsx`
+
+3. **Update extension** to use new URL:
+   - Update `extension/popup.js` API_URL
+
+4. **Deploy frontend on Vercel** (separate from backend)
+
+---
+
+## 💡 Cost Comparison
+
+- **Render Free**: Can't run your app (512MB limit)
+- **Railway Free**: $5/month credit, will run out
+- **HuggingFace Free**: Unlimited, perfect for ML
+- **Paid Options**: $7-20/month for more RAM
+
+**HuggingFace Spaces is the ONLY truly free option that will work for your ML-heavy backend!**
+
+---
+
+## 📚 Resources
+
+- HuggingFace Spaces Docs: https://huggingface.co/docs/hub/spaces
+- Docker SDK Guide: https://huggingface.co/docs/hub/spaces-sdks-docker
+- HuggingFace Git: https://huggingface.co/docs/hub/repositories-getting-started
+
+Good luck! 🚀

DEPLOY_TO_HF.ps1

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+# Quick Deployment to HuggingFace Spaces
+
+Write-Host "🚀 LinkScout - HuggingFace Spaces Deployment" -ForegroundColor Cyan
+Write-Host "=" * 60
+
+# Get HuggingFace username
+$username = Read-Host "Enter your HuggingFace username"
+
+Write-Host "`n📝 Setting up HuggingFace remote..." -ForegroundColor Yellow
+git remote remove hf 2>$null  # Remove if exists
+git remote add hf "https://huggingface.co/spaces/$username/linkscout-backend"
+
+Write-Host "`n✅ Remote added: https://huggingface.co/spaces/$username/linkscout-backend" -ForegroundColor Green
+
+Write-Host "`n📦 Committing HuggingFace files..." -ForegroundColor Yellow
+git add app.py Dockerfile DEPLOY_HUGGINGFACE.md
+git commit -m "Add HuggingFace Spaces deployment files" 2>$null
+
+Write-Host "`n🚀 Pushing to HuggingFace..." -ForegroundColor Yellow
+Write-Host "You may be asked for your HuggingFace credentials:" -ForegroundColor Gray
+Write-Host "  Username: $username" -ForegroundColor Gray
+Write-Host "  Password: Use your HuggingFace ACCESS TOKEN (not password!)" -ForegroundColor Gray
+Write-Host "  Get token from: https://huggingface.co/settings/tokens" -ForegroundColor Gray
+Write-Host ""
+
+git push hf main
+
+Write-Host "`n✅ Deployment initiated!" -ForegroundColor Green
+Write-Host "`n📊 Next steps:" -ForegroundColor Cyan
+Write-Host "  1. Go to: https://huggingface.co/spaces/$username/linkscout-backend" -ForegroundColor White
+Write-Host "  2. Click 'Settings' tab" -ForegroundColor White
+Write-Host "  3. Add Repository secrets:" -ForegroundColor White
+Write-Host "     - GROQ_API_KEY = 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" -ForegroundColor Gray
+Write-Host "     - GOOGLE_API_KEY = AIzaSyA9yKthZUnPAHFnmsnCZoikpvfUteJiX0s" -ForegroundColor Gray
+Write-Host "     - GOOGLE_CSE_ID = 11cbd494597034810" -ForegroundColor Gray
+Write-Host "  4. Wait 10-15 minutes for build to complete" -ForegroundColor White
+Write-Host "  5. Your API will be at: https://$username-linkscout-backend.hf.space" -ForegroundColor White
+
+Write-Host "`n🎉 Done!" -ForegroundColor Green

Dockerfile

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+FROM python:3.11-slim
+
+# Set working directory
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY . .
+
+# Create cache directory for models
+RUN mkdir -p ./models_cache
+
+# Expose port (HuggingFace uses port 7860 by default)
+EXPOSE 7860
+
+# Set environment variables
+ENV PORT=7860
+ENV PYTHONUNBUFFERED=1
+
+# Run the application
+CMD ["python", "combined_server.py"]

app.py

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+# This is a wrapper for HuggingFace Spaces
+# It imports and runs the Flask server from combined_server.py
+
+if __name__ == '__main__':
+    import combined_server
+    # Server will start automatically when combined_server is imported