LLM Chain - Symfony Demo Chatbot Application

Simple Symfony demo application on top of LLM Chain and its integration bundle.

Examples

Requirements

What you need to run this demo:

• Internet Connection
• Terminal & Browser
• Git & GitHub Account
• Docker with Docker Compose Plugin
• Your Favorite IDE or Editor
• An OpenAI API Key

Technology

This small demo sits on top of following technologies:

• PHP >= 8.4
• Symfony 7.2 incl. Twig, Asset Mapper & UX
• Bootstrap 5
• OpenAI's GPT & Embeddings
• ChromaDB Vector Store
• FrankenPHP

Setup

The setup is split into three parts, the Symfony application, the OpenAI configuration, and initializing the Chroma DB.

1. Symfony App

Checkout the repository, start the docker environment and install dependencies:

git clone [email protected]:php-llm/symfony-demo.git
cd symfony-demo
docker compose up -d
docker compose run composer install

Now you should be able to open https://localhost/ in your browser, and the chatbot UI should be available for you to start chatting.

2. OpenAI Configuration

For using GPT and embedding models from OpenAI, you need to configure an OpenAI API key as environment variable. This requires you to have an OpenAI account, create a valid API key and set it as OPENAI_API_KEY in .env.local file.

Verify the success of this step by running the following command:

docker compose exec app bin/console debug:dotenv

You should be able to see the OPENAI_API_KEY in the list of environment variables.

3. Chroma DB Initialization

The Chroma DB is a vector store that is used to store embeddings of the chatbot's context.

To initialize the Chroma DB, you need to run the following command:

docker compose exec app bin/console app:blog:embed -vv

Now you should be able to run the test command and get some results:

docker compose exec app bin/console app:chroma:test

Don't forget to set up the project in your favorite IDE or editor.

Functionality

• The chatbot application is a simple and small Symfony 7.2 application.
• The UI is coupled to a Twig LiveComponent, that integrates different Chat implementations on top of the user's session.
• You can reset the chat context by hitting the Reset button in the top right corner.
• You find three different usage scenarios in the upper navbar.