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A small demo on combining AutoGen
and Semantic Kernel
to create a simple flight booking system that's powered by AI agents.
The application allows users to provide booking instructions once, e.g., "Book the cheapest flight from Tokyo to Toronto", and then lets AI agents determine how to complete the task without any additional user input.
The demo includes two agents: An LLM-powered assistant and a worker agent that is capable of executing Semantic Kernel plugins (formerly known as skills). In addition to the built-in TimeSkill
that gives the agent access to time and date operations, the agent also has access to a custom FlightsPlugin
that enables looking up flights between two cities and to issue a (simulated) booking request.
To make the agents' thought process transparent, the app visualizes their back-and-forth in a chat format. The interactions of the agents depend on the flights data and user instructions. An example:
Role | Message |
---|---|
๐ค User | Book the cheapest flight from Tokyo to Toronto |
๐ค Assistant | Making a call to GetFlights function with input "Tokyo, Toronto" |
๐ฅ๏ธ GetFlights | List of flights from Tokyo to Toronto, incl. details like time and price |
๐ค Assistant | Making a call to BookFlights function with the flight ID of the cheapest flight |
๐ฅ๏ธ BookFlight | The flight could not be booked. There are no free seats available. |
๐ค Assistant | I regret to inform you that the cheapest flight from Tokyo to Toronto is currently fully booked. Let's try to book the next available option for you. Making a call to BookFlights function with the flight ID of the next cheapest flight |
๐ฅ๏ธ BookFlight | Flight successfully booked. |
๐ค Assistant | Great news! I've successfully booked your flight from Tokyo to Toronto. This is your flight detail: [...] |
This project was inspired by John Maeda's devblog AutoGen Agents Meet Semantic Kernel.
This app utilizes Azure OpenAI for Large Language Models and Azure CosmosDB for data storage. You can run the application itself locally by following the steps below.
- Clone this repo to your machine.
- Create a Python virtual environment and activate it, e.g. by running
python3 -m venv .venv
andsource .venv/bin/activate
. - Install the libraries listed in requirements.txt by running
pip install -r app/requirements.txt
. - Rename the .env.example file to
.env
. You will populate it in the next section.
- Create an Azure OpenAI resource and deploy a
gpt-35-turbo
orgpt-4
model. - Add the deployment name, resource endpoint, and key to the
.env
file. - Create an Azure CosmosDB resource, specifically, "Azure Cosmos DB for NoSQL". Within, create a database
AirlineBooking
and a containerFlights
. - Add the read-write connection string for your CosmosDB resource to the
.env
file. - To populate the database, run populate_cosmos.py a few (e.g., 10) times (
python3 setup/populate_cosmos.py
). You might have to installpandas
if it's not present in your virtual environment (pip install pandas
). Every time you run it, the script adds three new flights to the database.
- In your terminal, switch to the
app
directory. - Run
flask run
to start the app. - Click the link in your terminal or navigate to
http://127.0.0.1:5000
in your browser to view the application. - Enter your instructions and click Send. The agents will react to your instructions and the final result is displayed. To see intermediate steps, click Show intermediate steps. You can try a new instruction by clicking Start over in the bottom of the page.
- Once the application is up and running, enter a promp such as
Book the cheapest flight from Brussels to Vienna
into the input box. Hit send. - It might take some seconds for the app to respond. You can watch the progress in your terminal to see what is happening behind the scenes.
- You should receive an output in your webbrowser saying that a flight has been successfully booked.
- You can have a look at the intermediate steps to see how the AI agents came to the conclusion to finally have a flight booked for you.
Please note: For the demo to run successfully, you'll need to verify that CosmosDB contains direct flights between the requested cities.