Update Dockerfile for Hugging Face Spaces deployment

- Use PORT environment variable (Hugging Face standard)
- Default to port 7860 (Hugging Face default)
- Include content directory for data file
- Add deployment documentation for Docker SDK

DEPLOYMENT_STEPS.md

@@ -0,0 +1,59 @@
+# 🚀 Hugging Face Spaces Deployment - Quick Steps
+
+## ✅ Select Docker SDK
+
+When creating your Hugging Face Space:
+1. **SDK Options**: You'll see 3 options
+   - **Gradio** ❌ (for Gradio apps)
+   - **Docker** ✅ **SELECT THIS ONE!** (for Streamlit)
+   - **Static** ❌ (for static HTML)
+
+2. **Select "Docker"** - This will use your Dockerfile automatically
+
+## 📋 Deployment Steps
+
+### Step 1: Create Space
+1. Go to: https://huggingface.co/spaces
+2. Click **"Create new Space"**
+3. Fill in:
+   - **Space name**: `heart-attack-risk-predictor`
+   - **SDK**: **Docker** ✅
+   - **Visibility**: **Public**
+   - **Hardware**: **CPU basic** (free)
+4. Click **"Create Space"**
+
+### Step 2: Connect GitHub
+1. Go to **"Settings"** tab in your space
+2. Scroll to **"Repository"** section
+3. Select **"GitHub"**
+4. Repository: `KBSSRIKARVIT/heart-attack-risk-ensemble`
+5. Branch: `main`
+6. Click **"Save"**
+
+### Step 3: Wait for Build
+- Hugging Face will build your Docker image
+- Takes 5-10 minutes (first time)
+- Watch progress in **"Logs"** tab
+
+### Step 4: Access Your App
+Once built, your app is live at:
+```
+https://huggingface.co/spaces/KBSSRIKARVIT/heart-attack-risk-predictor
+```
+
+## ✅ What's Configured
+
+- ✅ Dockerfile updated for Hugging Face (uses PORT env var)
+- ✅ Port 7860 (Hugging Face standard)
+- ✅ All model files included
+- ✅ Content directory included
+- ✅ All dependencies in requirements.txt
+
+## 🎯 That's It!
+
+Select **Docker SDK** and deploy! Your Streamlit app will run in the Docker container.
+
+---
+
+**Need help?** Check `HUGGINGFACE_DEPLOY_DOCKER.md` for detailed instructions.
+

Dockerfile

@@ -27,11 +27,19 @@ COPY .streamlit /app/.streamlit
 RUN mkdir -p /app/model_assets
 COPY model_assets/ /app/model_assets/
 
+# Copy content directory (for data file used in feature encoding)
+RUN mkdir -p /app/content
+COPY content/ /app/content/
+
 # Optional: copy test script for quick in-container verification
 COPY test_predict.py /app/test_predict.py
 
+# Hugging Face Spaces uses PORT environment variable or defaults to 7860
+# Expose both ports for compatibility
+EXPOSE 7860
 EXPOSE 8051
 
-CMD ["streamlit", "run", "streamlit_app.py", "--server.headless=true", "--server.address=0.0.0.0", "--server.port=8051"]
+# Use PORT environment variable if set, otherwise default to 7860 (Hugging Face standard)
+CMD ["sh", "-c", "streamlit run streamlit_app.py --server.headless=true --server.address=0.0.0.0 --server.port=${PORT:-7860}"]
 
 

HUGGINGFACE_DEPLOY_DOCKER.md

@@ -0,0 +1,135 @@
+# 🐳 Deploy to Hugging Face Spaces Using Docker SDK
+
+## ✅ Select Docker SDK
+
+When creating your Hugging Face Space, select **"Docker"** as the SDK.
+
+Hugging Face will automatically detect and use your `Dockerfile`.
+
+## 🚀 Deployment Steps
+
+### Step 1: Create New Space
+
+1. Go to: https://huggingface.co/spaces
+2. Click **"Create new Space"**
+3. Fill in:
+   - **Space name**: `heart-attack-risk-predictor` (or your choice)
+   - **SDK**: Select **"Docker"** ✅
+   - **Visibility**: **Public** (required for free tier)
+   - **Hardware**: **CPU basic** (free tier)
+   - Click **"Create Space"**
+
+### Step 2: Connect GitHub Repository
+
+1. After creating the space, go to **"Settings"** tab
+2. Scroll to **"Repository"** section
+3. Select **"GitHub"** as source
+4. **Repository**: `KBSSRIKARVIT/heart-attack-risk-ensemble`
+5. **Branch**: `main`
+6. Click **"Save"**
+
+### Step 3: Verify Dockerfile
+
+Hugging Face will automatically use your `Dockerfile`. Verify it's correct:
+
+- ✅ Base image: `python:3.11-slim`
+- ✅ Port: `8051` (Hugging Face will map this automatically)
+- ✅ Streamlit command configured
+- ✅ All dependencies in `requirements.txt`
+
+### Step 4: Update Dockerfile for Hugging Face (if needed)
+
+Hugging Face Spaces automatically:
+- Maps port 8051 to the web interface
+- Sets environment variables
+- Handles HTTPS
+
+Your current Dockerfile should work, but we may need a small adjustment for Hugging Face's port expectations.
+
+### Step 5: Wait for Build
+
+1. Hugging Face will:
+   - Pull your code from GitHub
+   - Build the Docker image
+   - Deploy the container
+2. **Build time**: 5-10 minutes (first time)
+3. Watch progress in **"Logs"** tab
+
+### Step 6: Access Your App
+
+Once built, your app will be live at:
+```
+https://huggingface.co/spaces/KBSSRIKARVIT/heart-attack-risk-predictor
+```
+
+## 🔧 Dockerfile Configuration for Hugging Face
+
+Hugging Face Spaces expects the app to:
+- Listen on the port specified in `PORT` environment variable
+- Or use port 7860 (default)
+
+Let's check if we need to update the Dockerfile:
+
+```dockerfile
+# Current Dockerfile uses port 8051
+# Hugging Face can map this, but let's make it flexible
+```
+
+## 📝 Optional: Update Dockerfile for Hugging Face
+
+If the app doesn't start, we may need to update the Dockerfile to use Hugging Face's expected port:
+
+```dockerfile
+# Use PORT environment variable or default to 7860
+CMD ["sh", "-c", "streamlit run streamlit_app.py --server.headless=true --server.address=0.0.0.0 --server.port=${PORT:-7860}"]
+```
+
+But first, let's try with the current Dockerfile - Hugging Face should handle the port mapping.
+
+## ✅ Verification Checklist
+
+After deployment:
+
+- [ ] Build completes without errors
+- [ ] App loads at the Hugging Face URL
+- [ ] Streamlit interface displays correctly
+- [ ] Models load successfully
+- [ ] Predictions work
+
+## 🐛 Troubleshooting
+
+### Build Fails
+
+**Check logs** for specific errors:
+- Dependency installation issues
+- Dockerfile syntax errors
+- Port configuration issues
+
+### App Doesn't Start
+
+**Possible issues**:
+- Port mismatch (Hugging Face expects 7860 or PORT env var)
+- Missing model files
+- Path issues
+
+**Solution**: Update Dockerfile to use `PORT` environment variable.
+
+### Models Not Loading
+
+**Verify**:
+- Model files are in the repository
+- Paths in `streamlit_app.py` are correct
+- Files are copied in Dockerfile
+
+## 🎯 Summary
+
+1. **Select "Docker" SDK** when creating the space
+2. **Connect GitHub repository**
+3. **Hugging Face uses your Dockerfile automatically**
+4. **Wait for build** (5-10 minutes)
+5. **Access your app** at the Hugging Face URL
+
+---
+
+**Ready to deploy?** Follow these steps and your Streamlit app will be live on Hugging Face Spaces! 🚀
+

README_HUGGINGFACE.md

@@ -0,0 +1,62 @@
+# 🚀 Hugging Face Spaces Deployment
+
+## Quick Start
+
+1. **Go to**: https://huggingface.co/spaces
+2. **Click**: "Create new Space"
+3. **Select**: **Docker** SDK ✅
+4. **Connect**: Your GitHub repository `KBSSRIKARVIT/heart-attack-risk-ensemble`
+5. **Wait**: 5-10 minutes for build
+6. **Done**: Your app is live!
+
+## SDK Selection
+
+When creating the space, you'll see three options:
+
+1. **Gradio** - For Gradio apps (not this one)
+2. **Docker** - ✅ **Select this one!** (for Streamlit)
+3. **Static** - For static HTML sites (not this one)
+
+## Why Docker?
+
+- ✅ Your app is a Streamlit app
+- ✅ You have a `Dockerfile` ready
+- ✅ Docker SDK supports Streamlit
+- ✅ More control over the environment
+
+## What Happens
+
+1. Hugging Face pulls your code from GitHub
+2. Builds Docker image using your `Dockerfile`
+3. Runs the container with Streamlit
+4. Maps port 7860 to web interface
+5. Your app is accessible worldwide!
+
+## Files Needed
+
+- ✅ `Dockerfile` - Container configuration
+- ✅ `streamlit_app.py` - Main app
+- ✅ `requirements.txt` - Dependencies
+- ✅ `model_assets/` - Model files
+- ✅ All other app files
+
+## Port Configuration
+
+The Dockerfile is configured to:
+- Use `PORT` environment variable (set by Hugging Face)
+- Default to port 7860 (Hugging Face standard)
+- Also expose port 8051 for compatibility
+
+## After Deployment
+
+Your app will be available at:
+```
+https://huggingface.co/spaces/KBSSRIKARVIT/heart-attack-risk-predictor
+```
+
+Replace `KBSSRIKARVIT` with your Hugging Face username and `heart-attack-risk-predictor` with your space name.
+
+---
+
+**That's it!** Select Docker SDK and deploy! 🎉
+