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# Reactive Resume v5 - AI Model Configuration Guide
## 🤖 Current AI Setup
### Ollama Configuration
- **Model**: `llama3.2:3b`
- **Provider**: `ollama`
- **Endpoint**: `http://ollama:11434` (internal)
- **External API**: `http://192.168.0.250:11434`
## 📋 Model Details for Reactive Resume v5
### Environment Variables
Add these to your `docker-compose.yml` environment section:
```yaml
environment:
# AI Integration (Ollama) - v5 uses OpenAI-compatible API
OPENAI_API_KEY: "ollama" # Dummy key for local Ollama
OPENAI_BASE_URL: "http://ollama:11434/v1" # Ollama OpenAI-compatible endpoint
OPENAI_MODEL: "llama3.2:3b" # Model name
```
### Model Specifications
#### llama3.2:3b
- **Size**: ~2GB download
- **Parameters**: 3 billion
- **Context Length**: 8,192 tokens
- **Use Case**: General text generation, resume assistance
- **Performance**: Fast inference on CPU
- **Memory**: ~4GB RAM during inference
## 🔧 Alternative Models
If you want to use different models, here are recommended options:
### Lightweight Options (< 4GB RAM)
```yaml
# Fastest, smallest
OLLAMA_MODEL: "llama3.2:1b" # ~1GB, very fast
# Balanced performance
OLLAMA_MODEL: "llama3.2:3b" # ~2GB, good quality (current)
# Better quality, still reasonable
OLLAMA_MODEL: "qwen2.5:3b" # ~2GB, good for professional text
```
### High-Quality Options (8GB+ RAM)
```yaml
# Better reasoning
OLLAMA_MODEL: "llama3.2:7b" # ~4GB, higher quality
# Excellent for professional content
OLLAMA_MODEL: "qwen2.5:7b" # ~4GB, great for business writing
# Best quality (if you have the resources)
OLLAMA_MODEL: "llama3.2:11b" # ~7GB, excellent quality
```
### Specialized Models
```yaml
# Code-focused (good for tech resumes)
OLLAMA_MODEL: "codellama:7b" # ~4GB, code-aware
# Instruction-following
OLLAMA_MODEL: "mistral:7b" # ~4GB, good at following prompts
```
## 🚀 Model Management Commands
### Pull New Models
```bash
# Pull a different model
ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama pull qwen2.5:3b"
# List available models
ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama list"
# Remove unused models
ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama rm llama3.2:1b"
```
### Change Active Model
1. Update `OLLAMA_MODEL` in `docker-compose.yml`
2. Redeploy: `./deploy.sh restart`
3. Pull new model if needed: `./deploy.sh setup-ollama`
## 🧪 Testing AI Features
### Direct API Test
```bash
# Test the AI API directly
curl -X POST http://192.168.0.250:11434/api/generate \
-H "Content-Type: application/json" \
-d '{
"model": "llama3.2:3b",
"prompt": "Write a professional summary for a software engineer with 5 years experience in Python and React",
"stream": false
}'
```
### Expected Response
```json
{
"model": "llama3.2:3b",
"created_at": "2026-02-16T10:00:00.000Z",
"response": "Experienced Software Engineer with 5+ years of expertise in full-stack development using Python and React. Proven track record of building scalable web applications...",
"done": true
}
```
## 🎯 AI Features in Reactive Resume v5
### 1. Resume Content Suggestions
- **Trigger**: Click "AI Assist" button in any text field
- **Function**: Suggests professional content based on context
- **Model Usage**: Generates 2-3 sentence suggestions
### 2. Job Description Analysis
- **Trigger**: Paste job description in "Job Match" feature
- **Function**: Analyzes requirements and suggests skill additions
- **Model Usage**: Extracts key requirements and matches to profile
### 3. Skills Optimization
- **Trigger**: "Optimize Skills" button in Skills section
- **Function**: Suggests relevant skills based on experience
- **Model Usage**: Analyzes work history and recommends skills
### 4. Cover Letter Generation
- **Trigger**: "Generate Cover Letter" in Documents section
- **Function**: Creates personalized cover letter
- **Model Usage**: Uses resume data + job description to generate letter
## 📊 Performance Tuning
### Model Performance Comparison
| Model | Size | Speed | Quality | RAM Usage | Best For |
|-------|------|-------|---------|-----------|----------|
| llama3.2:1b | 1GB | Very Fast | Good | 2GB | Quick suggestions |
| llama3.2:3b | 2GB | Fast | Very Good | 4GB | **Recommended** |
| qwen2.5:3b | 2GB | Fast | Very Good | 4GB | Professional content |
| llama3.2:7b | 4GB | Medium | Excellent | 8GB | High quality |
### Optimization Settings
```yaml
# In docker-compose.yml for Ollama service
environment:
OLLAMA_HOST: "0.0.0.0"
OLLAMA_KEEP_ALIVE: "5m" # Keep model loaded for 5 minutes
OLLAMA_MAX_LOADED_MODELS: "1" # Only keep one model in memory
OLLAMA_NUM_PARALLEL: "1" # Number of parallel requests
```
## 🔍 Troubleshooting AI Issues
### Model Not Loading
```bash
# Check if model exists
ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama list"
# Pull model manually
ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama pull llama3.2:3b"
# Check Ollama logs
ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker logs Resume-OLLAMA-V5"
```
### Slow AI Responses
1. **Check CPU usage**: `htop` on Calypso
2. **Reduce model size**: Switch to `llama3.2:1b`
3. **Increase keep-alive**: Set `OLLAMA_KEEP_ALIVE: "30m"`
### AI Features Not Appearing in UI
1. **Check environment variables**: Ensure `AI_PROVIDER=ollama` is set
2. **Verify connectivity**: Test API endpoint from app container
3. **Check app logs**: Look for AI-related errors
### Memory Issues
```bash
# Check memory usage
ssh Vish@192.168.0.250 -p 62000 "free -h"
# If low memory, switch to smaller model
OLLAMA_MODEL: "llama3.2:1b" # Uses ~2GB instead of 4GB
```
## 🔄 Model Updates
### Updating to Newer Models
1. **Check available models**: https://ollama.ai/library
2. **Pull new model**: `ollama pull model-name`
3. **Update compose file**: Change `OLLAMA_MODEL` value
4. **Restart services**: `./deploy.sh restart`
### Model Versioning
```yaml
# Pin to specific version
OLLAMA_MODEL: "llama3.2:3b-q4_0" # Specific quantization
# Use latest (auto-updates)
OLLAMA_MODEL: "llama3.2:3b" # Latest version
```
## 📈 Monitoring AI Performance
### Metrics to Watch
- **Response Time**: Should be < 10s for most prompts
- **Memory Usage**: Monitor RAM consumption
- **Model Load Time**: First request after idle takes longer
- **Error Rate**: Check for failed AI requests
### Performance Commands
```bash
# Check AI API health
curl http://192.168.0.250:11434/api/tags
# Monitor resource usage
ssh Vish@192.168.0.250 -p 62000 "docker stats Resume-OLLAMA-V5"
# Check AI request logs
ssh Vish@192.168.0.250 -p 62000 "sudo /usr/local/bin/docker logs Resume-ACCESS-V5 | grep -i ollama"
```
---
**Current Configuration**: llama3.2:3b (Recommended)
**Last Updated**: 2026-02-16
**Performance**: ✅ Optimized for Calypso hardware

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# Migration from Reactive Resume v4 to v5
## Migration Summary
Successfully migrated from Reactive Resume v4 to v5 on 2026-02-16.
## Port Configuration
- **Main Application**: Port 9751 (same as v4)
- **S3 API**: Port 9753 (same as v4 MinIO)
- **PDF Service**: Port 4000 (internal)
## Reverse Proxy Compatibility
The migration maintains the same external ports, so existing reverse proxy rules continue to work:
- `http://192.168.0.250:9751` → `rx.vish.gg`
- `http://192.168.0.250:9753` → `rxdl.vish.gg` (S3 API)
## Changes from v4 to v5
### Storage Backend
- **v4**: MinIO for S3-compatible storage
- **v5**: SeaweedFS for S3-compatible storage
- Same S3 API compatibility on port 9753
### Database
- **v4**: PostgreSQL 16
- **v5**: PostgreSQL 18
- Database migration handled automatically
### PDF Generation
- **v4**: Browserless Chrome with HTTP API
- **v5**: Browserless Chrome with WebSocket API
- Better performance and real-time updates
### Authentication
- **v4**: Custom auth system
- **v5**: Better Auth framework
- More secure and feature-rich
## Data Migration
- Database data preserved in `/volume1/docker/rxv5/db/`
- File storage migrated to SeaweedFS format
- User accounts and resumes preserved
## Removed Services
The following v4 containers were stopped and removed:
- `Resume-ACCESS` (v4 main app)
- `Resume-DB` (v4 database)
- `Resume-PRINTER` (v4 PDF service)
- `Resume-MINIO` (v4 storage)
## New Services
The following v5 containers are now running:
- `Resume-ACCESS-V5` (v5 main app)
- `Resume-DB-V5` (v5 database)
- `Resume-BROWSERLESS-V5` (v5 PDF service)
- `Resume-SEAWEEDFS-V5` (v5 storage)
- `Resume-BUCKET-V5` (storage initialization)
## Configuration Files
- v4 configuration archived to: `/home/homelab/organized/repos/homelab/archive/reactive_resume_v4_archived/`
- v5 configuration active in: `/home/homelab/organized/repos/homelab/Calypso/reactive_resume_v5/`
## Verification
- ✅ Application accessible at http://calypso.vish.local:9751
- ✅ S3 API accessible at http://calypso.vish.local:9753
- ✅ All containers healthy and running
- ✅ Reverse proxy rules unchanged
- ✅ Account creation working (no more "Invalid origin" errors)
## Future Enhancements
- Ollama AI integration (when v5 supports it)
- External domain configuration for https://rx.vish.gg
- Automated backups of SeaweedFS data

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# Reactive Resume v5 - GitOps Deployment
This directory contains the GitOps deployment configuration for Reactive Resume v5 on the Calypso server with AI integration.
## 🚀 Quick Start
```bash
# Deploy the complete stack
./deploy.sh
# Check status
./deploy.sh status
# View logs
./deploy.sh logs
```
## 🌐 Access URLs
- **External**: https://rx.vish.gg
- **Internal**: http://192.168.0.250:9751
- **Download Service**: http://192.168.0.250:9753 (rxdl.vish.gg)
- **Ollama API**: http://192.168.0.250:11434
## 🏗️ Architecture
### Core Services
- **Main App**: Reactive Resume v5 with AI features
- **Database**: PostgreSQL 18
- **Storage**: SeaweedFS (S3-compatible)
- **PDF Generation**: Browserless Chrome
- **AI Engine**: Ollama with llama3.2:3b model
### Infrastructure
- **Proxy**: Nginx Proxy Manager (ports 8880/8443)
- **Router**: Port forwarding 80→8880, 443→8443
## 🤖 AI Features
Reactive Resume v5 includes AI-powered features:
- Resume content suggestions
- Job description analysis
- Skills optimization
- Cover letter generation
Powered by Ollama running locally with the llama3.2:3b model.
## 📋 Prerequisites
1. **Router Configuration**: Forward ports 80→8880 and 443→8443
2. **DNS**: rx.vish.gg and rxdl.vish.gg pointing to YOUR_WAN_IP
3. **SSL**: Cloudflare Origin certificates in NPM
## 🛠️ Deployment Commands
```bash
# Full deployment
./deploy.sh deploy
# Setup individual components
./deploy.sh setup-npm # Setup Nginx Proxy Manager
./deploy.sh setup-ollama # Setup AI model
# Management
./deploy.sh restart # Restart services
./deploy.sh stop # Stop services
./deploy.sh update # Update images and redeploy
./deploy.sh status # Check service status
./deploy.sh logs # View application logs
```
## 🔧 Configuration
### Environment Variables
- `APP_URL`: https://rx.vish.gg
- `AI_PROVIDER`: ollama
- `OLLAMA_URL`: http://ollama:11434
- `OLLAMA_MODEL`: llama3.2:3b
### Volumes
- `/volume1/docker/rxv5/db` - PostgreSQL data
- `/volume1/docker/rxv5/seaweedfs` - File storage
- `/volume1/docker/rxv5/ollama` - AI model data
## 🔄 Migration from v4
This deployment maintains compatibility with v4:
- Same ports (9751, 9753)
- Same SMTP configuration
- Same database credentials
- Preserves existing NPM proxy rules
## 🚨 Troubleshooting
### External Access Issues
1. Check router port forwarding: 80→8880, 443→8443
2. Verify NPM proxy hosts are configured
3. Confirm DNS propagation: `nslookup rx.vish.gg`
### AI Features Not Working
1. Check Ollama service: `docker logs Resume-OLLAMA-V5`
2. Pull model manually: `docker exec Resume-OLLAMA-V5 ollama pull llama3.2:3b`
3. Verify model is loaded: `docker exec Resume-OLLAMA-V5 ollama list`
### Service Health
```bash
# Check all services
./deploy.sh status
# Check specific container
ssh Vish@192.168.0.250 -p 62000 "sudo docker logs Resume-ACCESS-V5"
```
## 📊 Monitoring
- **Application Health**: http://192.168.0.250:9751/health
- **Database**: PostgreSQL on port 5432 (internal)
- **Storage**: SeaweedFS S3 API on port 8333 (internal)
- **AI**: Ollama API on port 11434
## 🔐 Security
- All services run with `no-new-privileges:true`
- Database credentials are environment-specific
- SMTP uses app-specific passwords
- External access only through NPM with SSL
## 📈 Status
**Status**: ✅ **ACTIVE DEPLOYMENT** (GitOps with AI integration)
- **Version**: v5.0.9
- **Deployed**: 2026-02-16
- **AI Model**: llama3.2:3b
- **External Access**: ✅ Configured

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#!/bin/bash
# Reactive Resume v5 GitOps Deployment Script
# Usage: ./deploy.sh [action]
# Actions: deploy, restart, stop, logs, status
set -e
COMPOSE_FILE="docker-compose.yml"
REMOTE_HOST="Vish@192.168.0.250"
SSH_PORT="62000"
REMOTE_PATH="/volume1/docker/rxv5"
SERVICE_NAME="reactive-resume-v5"
# Colors for output
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
NC='\033[0m' # No Color
log() {
echo -e "${BLUE}[$(date +'%Y-%m-%d %H:%M:%S')] $1${NC}"
}
success() {
echo -e "${GREEN}✅ $1${NC}"
}
warning() {
echo -e "${YELLOW}⚠️ $1${NC}"
}
error() {
echo -e "${RED}❌ $1${NC}"
exit 1
}
check_prerequisites() {
if [[ ! -f "$COMPOSE_FILE" ]]; then
error "docker-compose.yml not found in current directory"
fi
if ! ssh -q -p "$SSH_PORT" "$REMOTE_HOST" exit; then
error "Cannot connect to $REMOTE_HOST"
fi
}
setup_npm() {
log "Setting up Nginx Proxy Manager..."
# Create NPM directories
ssh -p "$SSH_PORT" "$REMOTE_HOST" "mkdir -p /volume1/homes/Vish/npm/{data,letsencrypt}"
# Stop existing NPM if running
ssh -p "$SSH_PORT" "$REMOTE_HOST" "sudo /usr/local/bin/docker stop nginx-proxy-manager 2>/dev/null || true"
ssh -p "$SSH_PORT" "$REMOTE_HOST" "sudo /usr/local/bin/docker rm nginx-proxy-manager 2>/dev/null || true"
# Start NPM with correct port mapping
ssh -p "$SSH_PORT" "$REMOTE_HOST" "sudo /usr/local/bin/docker run -d \
--name nginx-proxy-manager \
--restart unless-stopped \
-p 8880:80 \
-p 8443:443 \
-p 81:81 \
-v /volume1/homes/Vish/npm/data:/data \
-v /volume1/homes/Vish/npm/letsencrypt:/etc/letsencrypt \
jc21/nginx-proxy-manager:latest"
success "NPM started on ports 8880/8443"
warning "Make sure your router forwards port 80→8880 and 443→8443"
}
setup_ollama() {
log "Setting up Ollama AI model..."
# Wait for Ollama to be ready
log "Waiting for Ollama service to start..."
sleep 30
# Pull the required model
log "Pulling llama3.2:3b model (this may take a while)..."
ssh -p "$SSH_PORT" "$REMOTE_HOST" "sudo /usr/local/bin/docker exec Resume-OLLAMA-V5 ollama pull llama3.2:3b" || {
warning "Failed to pull model automatically. You can pull it manually later with:"
warning "docker exec Resume-OLLAMA-V5 ollama pull llama3.2:3b"
}
success "Ollama setup complete"
}
deploy() {
log "Deploying $SERVICE_NAME to $REMOTE_HOST..."
# Create required directories
log "Creating required directories..."
ssh -p "$SSH_PORT" "$REMOTE_HOST" "mkdir -p $REMOTE_PATH/{db,seaweedfs,ollama}"
# Copy compose file
log "Copying docker-compose.yml to $REMOTE_HOST:$REMOTE_PATH/"
ssh -p "$SSH_PORT" "$REMOTE_HOST" "cat > $REMOTE_PATH/docker-compose.yml" < "$COMPOSE_FILE"
# Deploy services
log "Starting services..."
ssh -p "$SSH_PORT" "$REMOTE_HOST" "cd $REMOTE_PATH && sudo /usr/local/bin/docker-compose up -d"
# Wait for services to be healthy
log "Waiting for services to be healthy..."
sleep 30
# Setup Ollama model
setup_ollama
# Check status
if ssh -p "$SSH_PORT" "$REMOTE_HOST" "sudo /usr/local/bin/docker ps | grep -q 'Resume.*V5'"; then
success "$SERVICE_NAME deployed successfully!"
log "Local access: http://192.168.0.250:9751"
log "External access: https://rx.vish.gg"
log "Ollama API: http://192.168.0.250:11434"
warning "Make sure NPM is configured for external access"
else
warning "Services started but may not be fully healthy yet. Check logs with: ./deploy.sh logs"
fi
}
restart() {
log "Restarting $SERVICE_NAME..."
ssh -p "$SSH_PORT" "$REMOTE_HOST" "cd $REMOTE_PATH && sudo /usr/local/bin/docker-compose restart"
success "$SERVICE_NAME restarted!"
}
stop() {
log "Stopping $SERVICE_NAME..."
ssh -p "$SSH_PORT" "$REMOTE_HOST" "cd $REMOTE_PATH && sudo /usr/local/bin/docker-compose down"
success "$SERVICE_NAME stopped!"
}
logs() {
log "Showing logs for Resume-ACCESS-V5..."
ssh -p "$SSH_PORT" "$REMOTE_HOST" "sudo /usr/local/bin/docker logs Resume-ACCESS-V5 --tail 50 -f"
}
status() {
log "Checking status of $SERVICE_NAME services..."
echo
ssh -p "$SSH_PORT" "$REMOTE_HOST" "sudo /usr/local/bin/docker ps --format 'table {{.Names}}\t{{.Image}}\t{{.Status}}\t{{.Ports}}' | grep -E 'Resume.*V5|NAMES'"
echo
# Check if application is responding
if curl -s -f http://192.168.0.250:9751 > /dev/null; then
success "Application is responding at http://192.168.0.250:9751"
else
warning "Application may not be responding"
fi
}
update() {
log "Updating $SERVICE_NAME (pull latest images and redeploy)..."
ssh -p "$SSH_PORT" "$REMOTE_HOST" "cd $REMOTE_PATH && sudo /usr/local/bin/docker-compose pull"
deploy
}
# Main script logic
case "${1:-deploy}" in
deploy)
check_prerequisites
deploy
;;
restart)
check_prerequisites
restart
;;
stop)
check_prerequisites
stop
;;
logs)
check_prerequisites
logs
;;
status)
check_prerequisites
status
;;
update)
check_prerequisites
update
;;
setup-npm)
check_prerequisites
setup_npm
;;
setup-ollama)
check_prerequisites
setup_ollama
;;
*)
echo "Usage: $0 [deploy|restart|stop|logs|status|update|setup-npm|setup-ollama]"
echo
echo "Commands:"
echo " deploy - Deploy/update the service (default)"
echo " restart - Restart all services"
echo " stop - Stop all services"
echo " logs - Show application logs"
echo " status - Show service status"
echo " update - Pull latest images and redeploy"
echo " setup-npm - Setup Nginx Proxy Manager"
echo " setup-ollama - Setup Ollama AI model"
exit 1
;;
esac

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# Reactive Resume v5 - Upgraded from v4 with same configuration values
# Docs: https://docs.rxresu.me/self-hosting/docker
services:
db:
image: postgres:18
container_name: Resume-DB-V5
hostname: resume-db
security_opt:
- no-new-privileges:true
healthcheck:
test: ["CMD", "pg_isready", "-q", "-d", "resume", "-U", "resumeuser"]
timeout: 45s
interval: 10s
retries: 10
volumes:
- /volume1/docker/rxv5/db:/var/lib/postgresql:rw
environment:
POSTGRES_DB: resume
POSTGRES_USER: resumeuser
POSTGRES_PASSWORD: "REDACTED_PASSWORD"
restart: unless-stopped
browserless:
image: ghcr.io/browserless/chromium:latest
container_name: Resume-BROWSERLESS-V5
ports:
- "4000:3000"
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:3000/pressure?token=1234567890"]
interval: 10s
timeout: 5s
retries: 10
environment:
QUEUED: 30
HEALTH: true
CONCURRENT: 20
TOKEN: 1234567890
restart: unless-stopped
seaweedfs:
image: chrislusf/seaweedfs:latest
container_name: Resume-SEAWEEDFS-V5
ports:
- "9753:8333" # S3 API port (same as v4 MinIO)
healthcheck:
test: ["CMD", "wget", "-q", "-O", "/dev/null", "http://localhost:8888"]
start_period: 10s
interval: 30s
timeout: 10s
retries: 3
command: server -s3 -filer -dir=/data -ip=0.0.0.0
environment:
AWS_ACCESS_KEY_ID: seaweedfs
AWS_SECRET_ACCESS_KEY: seaweedfs
volumes:
- /volume1/docker/rxv5/seaweedfs:/data:rw
restart: unless-stopped
seaweedfs-create-bucket:
image: quay.io/minio/mc:latest
container_name: Resume-BUCKET-V5
entrypoint: >
/bin/sh -c "
sleep 5;
mc alias set seaweedfs http://seaweedfs:8333 seaweedfs seaweedfs;
mc mb seaweedfs/reactive-resume;
exit 0;
"
depends_on:
seaweedfs:
condition: service_healthy
restart: on-failure:5
ollama:
image: ollama/ollama:latest
container_name: Resume-OLLAMA-V5
ports:
- "11434:11434"
volumes:
- /volume1/docker/rxv5/ollama:/root/.ollama:rw
environment:
OLLAMA_HOST: "0.0.0.0"
restart: unless-stopped
# Uncomment if you have GPU support
# deploy:
# resources:
# reservations:
# devices:
# - driver: nvidia
# count: 1
# capabilities: [gpu]
resume:
image: amruthpillai/reactive-resume:v5
container_name: Resume-ACCESS-V5
hostname: resume
security_opt:
- no-new-privileges:true
ports:
- "9751:3000" # Main application port (same as v4)
environment:
# --- Server ---
PORT: 3000
TZ: "America/Chicago"
NODE_ENV: production
APP_URL: "https://rx.vish.gg"
PRINTER_APP_URL: "http://resume:3000"
# --- Database ---
DATABASE_URL: "postgresql://resumeuser:REDACTED_PASSWORD@resume-db:5432/resume"
# --- Authentication ---
# Using same secret as v4 for consistency
AUTH_SECRET: "d5c3e165dafd2d82bf84acacREDACTED_GITEA_TOKEN"
# --- Printer (v5 uses WebSocket) ---
PRINTER_ENDPOINT: "ws://browserless:3000?token=1234567890"
# --- Storage (S3 - SeaweedFS) ---
S3_ACCESS_KEY_ID: "seaweedfs"
S3_SECRET_ACCESS_KEY: "seaweedfs"
S3_ENDPOINT: "http://seaweedfs:8333"
S3_BUCKET: "reactive-resume"
S3_FORCE_PATH_STYLE: "true"
STORAGE_USE_SSL: "false"
# --- Email (SMTP) - Same as v4 ---
SMTP_HOST: "smtp.gmail.com"
SMTP_PORT: "465"
SMTP_USER: "your-email@example.com"
SMTP_PASS: "REDACTED_PASSWORD" rnqz rnqz rnqz" # pragma: allowlist secret
SMTP_FROM: "your-email@example.com"
SMTP_SECURE: "true"
# --- OAuth / SSO (Authentik) ---
OAUTH_PROVIDER_NAME: "Authentik"
OAUTH_CLIENT_ID: "REDACTED_CLIENT_ID"
OAUTH_CLIENT_SECRET: "REDACTED_CLIENT_SECRET" # pragma: allowlist secret
OAUTH_DISCOVERY_URL: "https://sso.vish.gg/application/o/reactive-resume/.well-known/openid-configuration"
# --- Feature Flags ---
FLAG_DISABLE_SIGNUPS: "false"
FLAG_DISABLE_EMAIL_AUTH: "false"
# --- AI Integration (Olares Ollama) ---
# Configured via Settings UI → AI → OpenAI-compatible provider
# Points to Olares RTX 5090 GPU inference (qwen3-coder 30.5B Q4_K_M)
OPENAI_API_KEY: "dummy" # pragma: allowlist secret
OPENAI_BASE_URL: "https://a5be22681.vishinator.olares.com/v1"
OPENAI_MODEL: "qwen3-coder:latest"
depends_on:
db:
condition: service_healthy
seaweedfs:
condition: service_healthy
restart: unless-stopped