Tired of the regular GPT chats? This one has sarcasm per default!

This project is a playground UI for Large Language Modals (LLMs). It utilizes:

• LangChain.js for model call abstraction and Retrieval-Augmented Generation (RAG)
• React and Next.js for UI and server

Prerequisites

To run this project you need

• Node.js® v20+
• Ollama

Recommended (if you want to contribute)

• pnpm 9+

Run locally

This playground supports a locally running Ollama server and the HuggingFace Inference API. Per default the chat will use Ollama with llama3.1 model. If it is the first time you are using the configured model, Ollama will download it when you send the first message in the conversation UI without any visible progress. You should pull the model first:

ollama pull llama3.1

You can also run a model deployed on Hugging Face by configuring an access token, see configuration options

To start the application in development mode run:

pnpm install
pnpm dev

With NPM

npm install
npm dev

With Yarn

yarn install
yarn dev

Open http://localhost:3000 in your browser to see the result.

Configuring the Playground

The playground can be customized via environment variables, with default settings defined in the .env file. To configure the playground for a local development environment, simply copy the contents of .env to a new file named .env.local, and update the values as needed. This file is excluded from version control.

Configuration variable	Description	Default value
SYSTEM_MESSAGE	System message that defines the behaviour of the AI	You are a helpful but sarcastic assistant
OLLAMA_MODEL	The model used by local Ollama server	llama3.1
HUGGINGFACEHUB_MODEL	Hugging Face model	microsoft/Phi-3-mini-4k-instruct
HUGGINGFACEHUB_API_KEY	Hugging Face access token
HUGGINGFACEHUB_ENDPOINT_URL	Hugging Face inference endpoint url
DB_URL	Database to use. Supported configuration are: - leve empty for local in memory storage - mongodb://xxx/xxx for Mongodb