chore: cleanup unused deployment docs

.github/workflows/docker-build.yml

@@ -1,34 +0,0 @@
-name: Build and Push Docker Image
-
-on:
-  push:
-    branches: [ "main", "master" ]
-  workflow_dispatch:
-
-jobs:
-  build-and-push:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v4
-
-      - name: Set up QEMU
-        uses: docker/setup-qemu-action@v3
-
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-
-      - name: Login to Docker Hub
-        uses: docker/login-action@v3
-        with:
-          username: ${{ secrets.DOCKERHUB_USERNAME }}
-          password: ${{ secrets.DOCKERHUB_TOKEN }}
-
-      - name: Build and push
-        uses: docker/build-push-action@v5
-        with:
-          context: .
-          push: true
-          tags: ${{ secrets.DOCKERHUB_USERNAME }}/enterprise-rag:latest
-          cache-from: type=gha
-          cache-to: type=gha,mode=max

AWS_APP_RUNNER_SETUP.md

@@ -1,48 +0,0 @@
-# AWS App Runner Deployment Guide
-
-Follow these steps to deploy your Enterprise RAG System to AWS App Runner for a recruiter-ready showcase.
-
-## 1. Local Verification
-First, build and run your image locally to ensure the index is properly packaged:
-```bash
-docker build -t enterprise-rag .
-docker run -p 8501:8501 -e GROQ_API_KEY=your_key_here enterprise-rag
-```
-Visit `http://localhost:8501` to verify.
-
-## 2. Push to AWS ECR
-You need to push your image to the Amazon Elastic Container Registry.
-
-1. **Create Repository**:
-   ```bash
-   aws ecr create-repository --repository-name enterprise-rag --region your-region
-   ```
-2. **Login to ECR**:
-   ```bash
-   aws ecr get-login-password --region your-region | docker login --username AWS --password-stdin <your-account-id>.dkr.ecr.<your-region>.amazonaws.com
-   ```
-3. **Tag & Push**:
-   ```bash
-   docker tag enterprise-rag:latest <your-account-id>.dkr.ecr.<your-region>.amazonaws.com/enterprise-rag:latest
-   docker push <your-account-id>.dkr.ecr.<your-region>.amazonaws.com/enterprise-rag:latest
-   ```
-
-## 3. Create App Runner Service
-1. Go to **AWS Console** → **App Runner**.
-2. Click **Create service**.
-3. **Source**:
-   - Repository type: **Container registry**.
-   - Provider: **Amazon ECR**.
-   - Container image: Select your `enterprise-rag` image.
-   - Deployment settings: **Manual** (or Automatic if you want CI/CD).
-4. **Configuration**:
-   - Service name: `enterprise-rag-showcase`.
-   - Virtual CPU & Memory: **1 vCPU & 2 GB** (Minimum recommended).
-   - **Environment variables**:
-     - `GROQ_API_KEY`: Paste your key here.
-5. **Connectivity**:
-   - Port: **8501**.
-6. **Review & Create**.
-
-## 4. Final Result
-Once deployed, AWS will provide a public URL like `https://xxxxxx.us-east-1.awsapprunner.com`. This is the URL you can share with recruiters!

AWS_DEPLOYMENT.md

@@ -1,152 +0,0 @@
-# AWS Deployment Guide - Enterprise RAG System
-
-## Prerequisites
-- AWS Account
-- AWS CLI installed and configured
-- Docker installed locally
-
-## Deployment Options
-
-### Option 1: AWS EC2 (Recommended for Full Control)
-
-#### Step 1: Launch EC2 Instance
-1. Go to AWS Console → EC2
-2. Click **"Launch Instance"**
-3. Choose:
-   - **AMI**: Ubuntu 22.04 LTS
-   - **Instance Type**: t3.medium (4GB RAM minimum)
-   - **Storage**: 20GB
-4. Configure Security Group:
-   - Allow SSH (port 22) from your IP
-   - Allow HTTP (port 8501) from anywhere
-   - Allow HTTP (port 8000) from anywhere
-
-#### Step 2: Connect to Instance
-```bash
-ssh -i your-key.pem ubuntu@your-ec2-public-ip
-```
-
-#### Step 3: Install Docker
-```bash
-# Update system
-sudo apt update && sudo apt upgrade -y
-
-# Install Docker
-curl -fsSL https://get.docker.com -o get-docker.sh
-sudo sh get-docker.sh
-sudo usermod -aG docker ubuntu
-
-# Install Docker Compose
-sudo apt install docker-compose-plugin
-```
-
-#### Step 4: Clone Repository
-```bash
-git clone https://github.com/YuvrajSinghBhadoria2/Enterprise-RAG-System.git
-cd Enterprise-RAG-System
-```
-
-#### Step 5: Configure Environment
-```bash
-# Create .env file
-cat > .env << EOF
-GROQ_API_KEY=your_groq_api_key_here
-EOF
-```
-
-#### Step 6: Build and Run
-```bash
-# Using Docker Compose
-docker compose -f docker/docker-compose.yml up -d --build
-
-# Generate data (one-time)
-docker compose -f docker/docker-compose.yml exec api python3 tools/generate-dataset.py
-docker compose -f docker/docker-compose.yml exec api python3 src/ingestion/ingest.py
-```
-
-#### Step 7: Access Application
-- **UI**: `http://your-ec2-public-ip:8501`
-- **API**: `http://your-ec2-public-ip:8000/docs`
-
----
-
-### Option 2: AWS ECS (Fargate) - Serverless
-
-#### Step 1: Push Docker Image to ECR
-```bash
-# Create ECR repository
-aws ecr create-repository --repository-name enterprise-rag
-
-# Login to ECR
-aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin YOUR_ACCOUNT_ID.dkr.ecr.us-east-1.amazonaws.com
-
-# Build and push
-docker build -f docker/Dockerfile.api -t enterprise-rag .
-docker tag enterprise-rag:latest YOUR_ACCOUNT_ID.dkr.ecr.us-east-1.amazonaws.com/enterprise-rag:latest
-docker push YOUR_ACCOUNT_ID.dkr.ecr.us-east-1.amazonaws.com/enterprise-rag:latest
-```
-
-#### Step 2: Create ECS Task Definition
-1. Go to ECS Console
-2. Create new Task Definition (Fargate)
-3. Add container:
-   - Image: Your ECR image URI
-   - Memory: 4GB
-   - Port: 8501
-4. Add environment variable: `GROQ_API_KEY`
-
-#### Step 3: Create ECS Service
-1. Create ECS Cluster
-2. Create Service from Task Definition
-3. Configure Load Balancer (optional)
-
----
-
-### Option 3: AWS Lightsail (Simplest)
-
-#### Step 1: Create Lightsail Instance
-1. Go to Lightsail Console
-2. Create Instance:
-   - Platform: Linux/Unix
-   - Blueprint: Ubuntu 22.04
-   - Plan: $10/month (2GB RAM)
-
-#### Step 2: Deploy
-Same as EC2 steps 2-7 above
-
----
-
-## Cost Estimates
-
-| Service | Cost/Month | Best For |
-|---------|-----------|----------|
-| EC2 t3.medium | ~$30 | Full control, testing |
-| ECS Fargate | ~$40 | Production, auto-scaling |
-| Lightsail | $10-20 | Simple deployment |
-
-## Recommended: EC2 t3.medium
-
-For your use case, I recommend **EC2 t3.medium** because:
-- ✅ Full control
-- ✅ Easy to manage
-- ✅ Cost-effective
-- ✅ Can run Docker Compose easily
-
-## Maintenance
-
-**Update code:**
-```bash
-cd Enterprise-RAG-System
-git pull
-docker compose -f docker/docker-compose.yml up -d --build
-```
-
-**View logs:**
-```bash
-docker compose -f docker/docker-compose.yml logs -f
-```
-
-**Restart services:**
-```bash
-docker compose -f docker/docker-compose.yml restart
-```