plano/demos/use_cases/langchain

Travel Booking Agent Demo (LangChain-first)

A lightweight LangChain-powered multi-agent travel booking system that runs two small agents behind Plano’s router: a weather agent and a flight agent. Each agent is implemented with LangChain tool-calling out of the box and kept minimal so you can read, tweak, and extend quickly.

Overview

This demo consists of two LangChain agents that work together seamlessly:

• Weather Agent - Real-time weather conditions and multi-day forecasts for any city worldwide
• Flight Agent - Live flight information between airports with real-time tracking

Both agents are plain LangChain tool-callers. Plano routes traffic based on intent and forwards to the right LangChain agent. Everything runs in Docker for quick start.

Features

• Lightweight code: Minimal prompts + tools you can read in one pass
• Intelligent routing: Plano auto-routes to weather vs flight
• Real-time data: Weather (Open-Meteo) + flights (FlightAware)
• Multi-day forecasts: Up to 16 days for weather

Prerequisites

• Docker and Docker Compose
• Plano CLI installed
• OpenAI API key

Quick Start

1. Set Environment Variables

Create a .env file or export environment variables:

export AEROAPI_KEY="your-flightaware-api-key"  # Optional, demo key included

2. Start All Agents with Docker

chmod +x start_agents.sh
./start_agents.sh

Or directly:

docker compose up --build

This starts:

• Weather Agent on port 10510
• Flight Agent on port 10520
• Open WebUI on port 8080

3. Start Plano Orchestrator

In a new terminal:

cd /path/to/travel_agents
planoai up config.yaml
# Or if installed with uv: uvx planoai up config.yaml

The gateway will start on port 8001 and route requests to the appropriate agents.

4. Test the System

Option 1: Use Open WebUI at http://localhost:8080

Option 2: Send requests directly to Plano Orchestrator:

curl http://localhost:8001/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "user", "content": "What is the weather like in Paris?"}
    ]
  }'

Example Conversations

Weather Query

User: What's the weather in Istanbul?
Assistant: [Weather Agent provides current conditions and forecast]

Flight Search

User: What flights go from London to Seattle?
Assistant: [Flight Agent shows available flights with schedules and status]

Multi-Agent Conversation

User: What's the weather in Istanbul?
Assistant: [Weather information]

User: Do they fly out from Seattle?
Assistant: [Flight information from Istanbul to Seattle]

The system understands context and pronouns, automatically routing to the right agent.

Multi-Intent Queries

User: What's the weather in Seattle, and do any flights go direct to New York?
Assistant: [Both weather_agent and flight_agent respond simultaneously]
  - Weather Agent: [Weather information for Seattle]
  - Flight Agent: [Flight information from Seattle to New York]

The orchestrator can select multiple agents simultaneously for queries containing multiple intents.

Agent Details (LangChain)

Weather Agent

• Port: 10510
• API: Open-Meteo (free, no API key)
• LangChain: Tool to fetch weather; LLM summarizes with provided data
• Capabilities: Current weather, multi-day forecasts, temperature, conditions, sunrise/sunset

Flight Agent

• Port: 10520
• API: FlightAware AeroAPI
• LangChain: Tool resolves cities → IATA and fetches flights
• Capabilities: Real-time flight status, schedules, delays, gates, terminals, live tracking

Architecture

    User Request
         ↓
    Plano (8001)
     [Orchestrator]
         |
    ┌────┴────┐
    ↓         ↓
Weather    Flight
Agent      Agent
(10510)    (10520)
[Docker]   [Docker]

Each agent:

1. Extracts intent using GPT-4o-mini (with OpenTelemetry tracing)
2. Fetches real-time data from APIs
3. Generates response using GPT-4o
4. Streams response back to user

Both agents run as Docker containers and communicate with Plano via host.docker.internal.

Project Structure

travel_agents/
├── config.yaml          # Plano configuration
├── docker-compose.yaml       # Docker services orchestration
├── Dockerfile               # Multi-agent container image
├── start_agents.sh          # Quick start script
├── pyproject.toml           # Python dependencies
└── src/
    └── travel_agents/
        ├── __init__.py      # CLI entry point
        ├── weather_agent.py # Weather forecast agent (multi-day support)
        └── flight_agent.py  # Flight information agent

Configuration Files

config.yaml

Defines the two agents, their descriptions, and routing configuration. The agent router uses these descriptions to intelligently route requests.

docker-compose.yaml

Orchestrates the deployment of:

• Weather Agent (builds from Dockerfile)
• Flight Agent (builds from Dockerfile)
• Open WebUI (for testing)
• Jaeger (for distributed tracing)

Troubleshooting

Docker containers won't start

• Verify Docker and Docker Compose are installed
• Check that ports 10510, 10520, 8080 are available
• Review container logs: docker compose logs weather-agent or docker compose logs flight-agent

Plano won't start

• Verify Plano is installed: plano --version
• Ensure you're in the travel_agents directory
• Check config.yaml is valid

No response from agents

• Verify all containers are running: docker compose ps
• Check that Plano is running on port 8001
• Review agent logs: docker compose logs -f
• Verify host.docker.internal resolves correctly (should point to host machine)

API Endpoints

All agents expose OpenAI-compatible chat completion endpoints:

• POST /v1/chat/completions - Chat completion endpoint
• GET /health - Health check endpoint