🧭 Dream Destiny — AI Travel Planner

🏛️ Architecture & Services

📦 Prerequisites

⚙️ Configuration

🚀 Running the Project

Start All Services

# Build and start all 6 containers in the background
docker compose up -d --build

Monitor & View Logs

# View aggregated live logs
docker compose logs -f
# View logs for a specific service
docker compose logs -f planner-service

Check Service Health & Status

docker compose ps

Restart or Stop

# Restart all containers
docker compose restart
# Stop all containers
docker compose down
# Stop and delete persistent cache volumes
docker compose down -v

🌐 Service Access & Endpoints

🧪 Development & Testing

# Run the test client against http://localhost:8000/plan
python test_plan.py

Example API Request

curl -X POST http://localhost:8000/plan \
 -H "Content-Type: application/json" \
 -d '{
 "origin": "Chennai",
 "destination": "Coimbatore",
 "start_date": "2026-08-29",
 "end_date": "2026-08-31",
 "travelers": 2,
 "preferences": {
 "budget": { "level": "medium" },
 "transport": { "mode": "train", "berth_preference": "3A" },
 "hotel": { "category": "mid_range" },
 "activities": { "pace": "moderate", "interests": ["history", "nature"] }
 }
 }'

📁 Project Structure

Dream-Destiny/
├── docker-compose.yml # Multi-container orchestration
├── .env.example # Template for environment variables
├── test_plan.py # Standalone test runner for planning endpoints
├── planner-service/ # Core orchestrator & AI planning agent (Port 8000)
│ ├── app/
│ │ ├── agents/ # Planning agent implementation
│ │ ├── api/ # FastAPI routes (/plan, /plan/context)
│ │ ├── business/ # Preference mapping & pre-filtering
│ │ ├── clients/ # Downstream HTTP service clients
│ │ ├── orchestration/ # Async data gathering pipeline
│ │ ├── schemas/ # Pydantic schemas (Request, Context, Itinerary)
│ │ └── services/llm/ # Gemini GenAI client & structured prompts
│ └── Dockerfile
├── tourism-service/ # Google Places attractions service (Port 8001)
│ └── Dockerfile
├── hotel-service/ # Google Hotels & SQLite cache service (Port 8002)
│ └── Dockerfile
├── route-service/ # Google Routes distance & time service (Port 8003)
│ └── Dockerfile
├── transport-service/
│ ├── bus/ # RedBus bus search & city resolver (Port 8004)
│ │ └── Dockerfile
│ └── train/ # Ixigo Indian rail search & live seats (Port 8005)
│ └── Dockerfile
└── shared/ # Reference shared Pydantic data schemas