Popular GitHub Repositories for Assistants

A conversational Q&A agent configuration system, self-hosted deployment solutions, and a convenient all-in-one application SDK, allowing you to create intelligent Q&A bots for your GitHub repositories

Sample to envision intelligent apps with Microsoft's Copilot stack for AI-infused product experiences.

OpenAI Assistants based chatbots — with GPT-4, Code Interpreter and Files

Self-hosted version of OpenAI’s new stateful Assistants API

AI-first Search & Answer Engine for work. Open-source alternative to Glean.

The Open Assistant API is a ready-to-use, open-source, self-hosted agent/gpts orchestration creation framework, supporting customized extensions for LLM, RAG, function call, and tools capabilities. It also supports seamless integration with the openai/langchain sdk.

Drop in replacement for the OpenAI Assistants API

Akeru is an open source AI platform built on top of the Akeru AI edge network. The network runs as a Bittensor Subnet, providing a transparent, safe and highly available AI capacities.

AI Assistant that can get stock prices

All-in-One LLM AI Assistant

A Swift library for integrating with the OpenAI Assistants API, enabling the creation and management of assistants, message processing, and AI runs.

Fluent GPT App, an open-source, multi-platform desktop application that brings the power of GPT models to your fingertips. Designed with a sleek Fluent interface, it offers a unique and customizable chat experience on Windows, macOS, and Linux.

Play with OpenAI API's using your own API Key. Your API Key is stored and used only from your browser.

A Rasa (www.rasa.com) Chatbot for Instill Distilling

Go package for OpenAI Assistants integration

xiaohui 是个 用python 写的面向任务的对话系统

These are the Microsoft Semantic Kernel Workshop notebooks. It addresses AI agents, agents collaboration and, of course, kernel, plugins, planners and function calling

This project showcases the implementation of a prompt engineering using the OpenAI Assistant API, specifically leveraging the Retrieval-Augmented Generation (RAG) system. By integrating cutting-edge language models, the system demonstrates advanced natural language understanding and generation capabilities.

Structured, composable intelligence

My playground for Semantic Kernel Console Demos