Travel & Expense Assistant

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🗺️ Xpander.ai: An Overview

1. xpander-sdk – main SDK for interacting with Xpander.ai agents (Python, Node.js, C#, Java).
2. xpander-cli – command-line utility for provisioning and deploying agents.
3. xpander-mcp-remote – MCP bridge utility for IDE integrations (e.g. Cursor, Claude Desktop).
4. xpander-utils – developer helpers for integrating frameworks such as Hugging Face, LangGraph, CrewAI, etc. (Python).

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🎯 What We’re Building: Travel & Expense Assistant

1. Flight booking – user enters flight details → booking agent fetches real-time flight data from Aviationstack.
2. Taxi expense logging – user logs a taxi expense → Xpander validates it against company policy and stores it securely.
3. Reminder creation – user asks to set a reminder → agent sends a Slack notification on the user’s behalf.

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✨ Key Features

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1. Travel Management

• Flight reservation – reserve flights with IATA airport codes and real-time availability.
• Hotel reservations – book rooms based on date, location and budget.
• Trip planning – bundle flights and hotels into best-fit itineraries.

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2. Expense Management

• Expense logging – categorise expenses (meals, taxi, lodging, …).
• Policy compliance – auto-check spending against company rules.
• Summaries & reports – generate well-formatted expense reports.
• Automated reminders – Slack pings for pending reports.

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🛠️ Prerequisites

1. Python 3.12.1+ (required by xpander-utils).
2. Xpander SDK access (Backend orchestration, memory, tools).
3. Agno framework familiarity.
4. API keys: Aviationstack, Slack Bot, Nebius AI (or OpenAI).

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1. Clone the Repository

git clone <repository-url>
cd <repository_name>

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2. Create & Activate a Virtual Environment

# Windows (PowerShell)
python -m venv venv
venv\Scripts\activate

# macOS / Linux
python3 -m venv venv
source venv/bin/activate

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3. Install Dependencies

pip install xpander-sdk agno python-dotenv xpander-utils asyncio python-dateutil slack-sdk certifi requests openai sqlalchemy pygithub

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4. Configure Environment Variables

AVIATIONSTACK_KEY=<your_aviationstack_key>
NEBIUS_API_KEY=<your_nebius_key>
SLACK_BOT_TOKEN=<your_slack_bot_token>
SLACK_CHANNEL_ID=<your_channel_id>
OPENAI_API_KEY=<your_openai_key>  # if not using Nebius

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5. xpander_config.json

{
  "organization_id": "<YOUR_ORG_ID>",
  "api_key": "<YOUR_XPANDER_API_KEY>",
  "agent_id": "<YOUR_AGENT_ID>"
}

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🧑‍💻 Hands-on: Building the Assistant

import asyncio
import json
from pathlib import Path
from xpander_utils.sdk.adapters import AgnoAdapter
from orchestrator.agno_agent import AgnoAgentOrchestrator

CFG_PATH = Path("xpander_config.json")
xpander_cfg = json.loads(CFG_PATH.read_text())

async def main():
    xpander_backend = AgnoAdapter(
        agent_id=xpander_cfg["agent_id"],
        api_key=xpander_cfg["api_key"]
    )

    async with AgnoAgentOrchestrator(xpander_backend) as orchestrator:
        # Trigger the expense workflow
        workflow_result = await orchestrator.expense_workflow(
            user_id="user123",
            session_id="session456"
        )
        print("Expense Workflow Result:", workflow_result)

        # Interactive CLI loop
        while True:
            message = input("\nYou: ")
            if message.lower() in ["exit", "quit"]:
                break
            await orchestrator.run(
                message=message,
                user_id="user123",
                session_id="session456",
                cli=True
            )

if __name__ == "__main__":
    asyncio.run(main())

curl "https://api.aviationstack.com/v1/flights?access_key=<YOUR_KEY>"

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How the Xpander Handler Works?

• Loads xpander_config.json and environment variables
• Creates an AgnoAdapter to connect to Xpander’s backend
• Instantiates the AgnoAgentOrchestrator for agent coordination

1. Listens for execution requests via XpanderEventListener
2. Parses inputs (user messages, metadata)
3. Routes tasks to the orchestrator (agno_agent_orchestrator.run())
4. Tracks metrics (LLM token usage, performance)
5. Returns structured results (AgentExecutionResult)

• Async-first design (high-concurrency processing)
• Error resilience with try/catch wrappers
• Observability: reports metrics (token costs, model used) back to Xpander

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🧪 Quickly Test the Agent

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CLI Chat

python main.py

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Event Handler

python xpander_handler.py

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Docker

docker build -t xpander-travel .
docker run -p 8080:8080 xpander-travel

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Sample Run

Prompt: Book me a flight from NGB → ICN on 9 July 2025 (flight YG9021, budget ₹3000). Once booked, confirm details and log the expense.

Prompt: Please book a hotel for ₹2000 on the same date.

Prompt: Send a summary notification on Slack for all expenses.

Output: Slack notification

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🏁 Final Thoughts

• Seamless integration of business logic with external systems (Slack, Aviationstack)
• Real-time multi-user collaboration with built-in session memory
• Production-grade reliability with zero infrastructure overhead