equipable v0.0.2

equipable

equipable is a Node.js framework for building LLM assistants on top of OpenAI's GPT Assistants API

Dependencies

• A working Node.js installation with version 20+
• Running Redis server
• OpenAI API Key

Optional (for Docker-based Redis installs)

• Docker

How to Use

Installing Dependencies

Node JS

To use equipable, you need Node.js version 20 or higher. You can check your current Node.js version by running node -v in your terminal. If you need to install Node.js, either download an installer for your operating system or install Node.js via command line

Redis

Option 1: Use Docker (Recommended)

If you prefer Docker for managing Redis, ensure Docker is installed on your machine. If you don't have Docker, download it from the official Docker website. After installing Docker, run the following command to pull and run the Redis image:

docker run --name equipable-redis -p 6379:6379 -d redis

This command downloads the latest Redis image, names the container equipable-redis, maps the default Redis port 6379 on the container to the same port on your host, and runs the container in detached mode.

Option 2: Local Redis Installation

For a local Redis installation, follow the instructions for your OS.

OpenAI API Key

Follow these steps to obtain one:

1. Sign up or log in to your OpenAI account.
2. Navigate to the API key page and "Create a new secret key".
3. Optionally name your secret key.

Setting your environment variables

Copy .env.example to .env by running

cp .env.example .env

Modify it by adding in your OPENAI_API_KEY and your REDIS_URL.

Run the Server

Run npm run equipable start to start the server. It will take requests through http://localhost:3000

Customize your assistants

1. Define your OpenAI Assistant parameters in assistants/ in a JSON file.

{
  "name": "Demo Assistant",
  "instructions": "You are a weather bot. Use the provided functions to answer questions.",
  "model": "gpt-4-turbo-preview",
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "getCurrentWeather",
        "description": "Get the weather in location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "The city and state e.g. San Francisco, CA"
            },
            "unit": { "type": "string", "enum": ["c", "f"] }
          },
          "required": ["location"]
        }
      }
    },
    {
      "type": "function",
      "function": {
        "name": "getNickname",
        "description": "Get the nickname of a city",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "The city and state e.g. San Francisco, CA"
            }
          },
          "required": ["location"]
        }
      }
    }
  ]
}

2. Define function tools in tools/functions. Each function file must be named EXACTLY the same as the function tool as defined in your assistants file.

// tools/functions/getCurrentWeather.ts

interface getCurrentWeatherArgs {
  location: string;
}

export default function getCurrentWeather(args: getCurrentWeatherArgs) {
  // Add your business logic here
  return "22C";
}

// tools/functions/getNickname.ts

interface getNicknameArgs {
  location: string;
}

export default function getNickname(args: getNicknameArgs) {
  // Add your business logic here
  return "LA";
}

3. Run npm run equipable sync to upload your OpenAI Assistant.