Skip to content

Latest commit

 

History

History
 
 

plugin

TaskingAI-Plugin: Friendly Tools for LLMs

Docs Docker Image Version (latest semver) GitHub License X (formerly Twitter) URL YouTube Channel Subscribers

Tasking AI Plugin is part of the TaskingAI platform, an open-source platform for AI-native application development. Through a unified API, the Plugin service provides a set of tools and utilities to enhance the performance of LLM-based applications.

For a full list of integrations, please refer to the official documentation.

Key Features

  1. Unified API: Access hundreds of useful plugins through one API.
  2. Asynchronous Requests for High-Concurrency: Designed to handle high-concurrency scenarios efficiently through the support of asynchronous requests, ensuring performance stability.
  3. End-to-End Encryption: Ensures the security of data and API keys with robust end-to-end AES encryption, safeguarding credential information.

Quickstart with Docker

Prerequisites

  • Docker and Docker Compose installed on your machine.
  • Git installed for cloning the repository.
  • Curl or other HTTP client installed for testing and debugging.

Installation

A simple way to initiate a self-hosted TaskingAI-Plugin service is through Docker.

Pull the latest Docker image taskingai/taskingai-plugin:latest from Docker Hub (or the appropriate registry) by executing the following command in your terminal:

docker pull taskingai/taskingai-plugin:latest

Then, you can run a new container using the following command:

docker run -d -p 8003:8000 taskingai/taskingai-plugin:latest

Running through Source Code

First, download the TaskingAI GitHub repository with:

git clone https://github.com/TaskingAI/TaskingAI.git
cd TaskingAI/plugin

Then, install the required dependencies using:

pip install -r requirements.txt

Copy the .env.example file to .env and fill in the required environment variables, including object storage configurations (s3 or local) and necessary plugin credentials. We set SERVICE_PORT to 8003 by default.

cp .env.example .env

Finally, run the service using:

PYTHONPATH=$(pwd) python app/main.py

Usage

Once deployed, use tools like cURL, Postman, or any HTTP client to send requests to your local TaskingAI-Plugin service for testing and debugging.

Here's an example of requesting the CoinMarketCap API to get the latest Bitcoin price:

curl --location 'http://127.0.0.1:8003/v1/execute' \
--header 'Content-Type: application/json' \
--data '{
    "bundle_id": "coin_market_cap",
    "plugin_id": "get_latest_coin_data",
    "input_params": {
        "symbol": "BTC"
    },
    "credentials": {
        "COIN_MARKET_CAP_API_KEY":"YOUR_COIN_MARKET_CAP_API_KEY"
    }
}'

You may check the supported bundles and the plugins under each bundle by sending a GET request to the /v1/bundles and /v1/plugins?bundle_id={QUERY_BUNDLE_ID} endpoints, respectively.

You can explore the API reference in http://localhost:8003/redoc. For more usage details, please refer to the documentation