Kickstart your first AI-based product quicker with our open-source library!
The idea of giving back to the community is a fundamental aspect of Boldare’s mission. That’s why we’re excited to share something today that, developed by us, we believe belongs to everyone. Introducing the Boldare AI Assistant - a NestJS library designed to empower developers to efficiently, scalably, and swiftly create AI assistants and chatbots. It’s accessible through GitHub and npm.
Table of contents
Who is the Boldare AI Assistant for?
It’s a useful tool for anyone looking to launch their very first AI-based product using the OpenAI Assistant API. This library was built on our own experiences in developing apps and integrating Gen-AI into our own products, as well as those of our clients. We’re proud to say it’s a tool crafted by developers, for developers.
Based on our experience, this library can significantly reduce the time required to launch an AI-based app to an absolute minimum, saving developers between one to two weeks.
What does the Boldare AI Assistant offer?
It’s a NestJS library developed to use OpenAI’s Assistant capabilities. It’s designed for easy integration with the NestJS ecosystem, featuring an intuitive API, WebSockets, and tools that facilitate the development of AI-based interactions. Suitable for creating customer service bots, virtual assistants, or interactive chatbots to enhance user experiences, this library enables the use of advanced AI features with reduced effort.
Features of the Boldare AI Assistant Library:
- Function Calling: This feature allows for the creation of custom functions, enhancing the assistant’s capabilities with specialized logic.Text-to-Speech (TTS): Enables the conversion of text into spoken audio, facilitating voice interactions with the assistant.
- Speech-to-Text (STT): Converts spoken audio into text, also supporting voice interactions.
- File Support: Allows for the integration of files, enriching the assistant’s knowledge base with additional data.
- WebSockets: Supports real-time communication between the client and the assistant through a WebSocket server.
- REST API: Facilitates communication with the assistant via a RESTful API.
Additional Features in the Repository:
- Embedded Chatbot: Provides tools for embedding the chatbot into various websites using JavaScript.
- Chatbot Client Application: Includes a sample client application (SPA) featuring the chatbot.
Go to GitHub or npm to learn more details and … start working on your first AI-powered app!
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