Docker image Build and deploy to HF Spaces Via CI/CD Steps

.github/workflows/README.md

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+# CI/CD Workflows
+
+Automated pipelines using GitHub Actions.
+
+## Workflows
+
+### 1. CI Pipeline (`ci.yaml`)
+**Triggers**: Push to main, Pull Requests
+**Actions**:
+- Lint code with flake8
+- Format check with black
+- Validate dependencies
+
+### 2. Docker Build (`docker-build.yaml`)
+**Triggers**: Push to main, Version tags
+**Actions**:
+- Build Docker image
+- Push to GitHub Container Registry (ghcr.io)
+- Tag with SHA and latest
+
+**Access image**:
+```bash
+docker pull ghcr.io/your-username/automl-mlops-pipeline:latest
+```
+
+### 3. HuggingFace Deploy (`deploy-hf-space.yaml`)
+**Triggers**: Version tags, Manual dispatch
+**Actions**:
+- Push code to HuggingFace Space
+- Auto-deploy live demo
+
+## Setup
+
+### Required Secrets
+
+Add these in GitHub Settings → Secrets:
+
+1. **For Docker Build**: None (uses `GITHUB_TOKEN` automatically)
+
+2. **For HuggingFace Deploy**:
+   - `HF_TOKEN`: Your HuggingFace access token
+   - `HF_SPACE_NAME`: Your space name (e.g., `username/automl-demo`)
+
+### Get HuggingFace Token
+1. Go to https://huggingface.co/settings/tokens
+2. Create "Write" access token
+3. Add as `HF_TOKEN` secret in GitHub
+
+## Manual Triggers
+
+Trigger HuggingFace deployment manually:
+```
+Actions tab → Deploy to HuggingFace Space → Run workflow
+```
+
+## View Container Images
+
+Visit: https://github.com/your-username/automl-mlops-pipeline/pkgs/container/automl-mlops-pipeline

.github/workflows/ci.yaml

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+name: CI Pipeline
+
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.11'
+      
+      - name: Install dependencies
+        run: |
+          pip install flake8 black
+      
+      - name: Lint with flake8
+        run: |
+          flake8 src/ app/ --count --select=E9,F63,F7,F82 --show-source --statistics
+          flake8 src/ app/ --count --max-line-length=120 --statistics --exit-zero
+      
+      - name: Check formatting with black
+        run: |
+          black --check src/ app/ --line-length=120 || true
+      
+      - name: Validate requirements
+        run: |
+          pip install -r requirements.txt --dry-run

.github/workflows/deploy-hf-space.yaml

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+name: Deploy to HuggingFace Space
+
+on:
+  push:
+    tags:
+      - 'v*'
+  workflow_dispatch:
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          lfs: true
+
+      - name: Push to HuggingFace Space
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: |
+          git config --global user.email "github-actions[bot]@users.noreply.github.com"
+          git config --global user.name "github-actions[bot]"
+          
+          # Add HuggingFace remote if not exists
+          git remote add hf https://huggingface.co/spaces/${{ secrets.HF_SPACE_NAME }} || true
+          
+          # Push to HuggingFace
+          git push https://user:$HF_TOKEN@huggingface.co/spaces/${{ secrets.HF_SPACE_NAME }} main:main
+
+      - name: Deployment Status
+        run: |
+          echo "✅ Deployed to: https://huggingface.co/spaces/${{ secrets.HF_SPACE_NAME }}"

.github/workflows/docker-build.yaml

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+name: Docker Build
+
+on:
+  push:
+    branches: [ main ]
+    tags:
+      - 'v*'
+
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
+    steps:
+      - uses: actions/checkout@v3
+
+      - name: Log in to Container Registry
+        uses: docker/login-action@v2
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
+          tags: |
+            type=sha,prefix={{branch}}-
+            type=ref,event=branch
+            type=ref,event=tag
+            type=raw,value=latest,enable={{is_default_branch}}
+
+      - name: Build and push
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          push: true
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}

HF_SPACE_README.md

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+---
+title: AutoML MLOps Pipeline
+emoji: 🤖
+colorFrom: blue
+colorTo: green
+sdk: docker
+app_port: 8000
+pinned: false
+license: mit
+---
+
+# AutoML MLOps Pipeline
+
+Production-ready AutoML pipeline with MLflow tracking, monitoring, and orchestration.
+
+## Features
+
+- 🤖 **AutoML**: AutoGluon, FLAML, PyCaret
+- 📊 **MLflow Tracking**: DagsHub integration
+- 🔍 **Monitoring**: Drift detection, performance tracking
+- 📈 **Observability**: Prometheus & Grafana
+- 🔄 **Orchestration**: Airflow scheduling
+- 🐳 **Docker**: Containerized deployment
+
+## API Endpoints
+
+Once deployed, access:
+- **API Documentation**: `/docs`
+- **Health Check**: `/health`
+- **Predictions**: `/predict`
+- **Monitoring**: `/monitoring/metrics`
+
+## Quick Test
+
+```bash
+curl -X POST https://abeshith-automl-mlops-pipeline.hf.space/predict \
+  -H "Content-Type: application/json" \
+  -d '{"age": 45, "sex": 1, "cp": 2, "trestbps": 130, "chol": 250, "fbs": 0, "restecg": 1, "thalach": 150, "exang": 0, "oldpeak": 2.5, "slope": 2, "ca": 0, "thal": 2}'
+```
+
+## Repository
+
+Full source code: [GitHub](https://github.com/Abeshith/AutoML-MLOps-PipeLine)