Botticelli: Open-Source .NET Core Bot Framework

Botticelli is an open-source .NET Core framework designed to simplify the creation of universal bots that can run across multiple platforms and messaging services. Rather than reinventing the wheel for every bot project, developers can tap into Botticelli's modular ecosystem, which includes dedicated packages for AI (Botticelli.AI), speech synthesis (Botticelli.Talks), message queuing (Botticelli.Bus), and task scheduling (Botticelli.Scheduler). This modularity lets teams pick and choose the functionality they need without bloating their projects. Built with reliability and developer experience in mind, Botticelli offers native Docker support, making deployment straightforward regardless of your infrastructure. It also integrates with powerful AI engines like Gpt-j and ChatGPT, enabling bots that can hold natural conversations, answer questions, or process complex requests. Combined with database and queue broker support, Botticelli gives developers the backbone needed to build production-ready bots rather than simple scripted responders. Whether you're building a customer service bot for Telegram, a WhatsApp assistant, a VK Messenger integration, or even a specialized tool like an air quality monitoring bot, Botticelli provides the cross-platform flexibility to deploy once and adapt widely. As a fully open-source project hosted on GitHub, it's freely available for developers, system architects, and AI engineers looking to accelerate bot development without licensing costs.

1. Clone the repository from GitHub with the command: `git clone https://github.com/devgopher/botticelli.git`. 2. Review the official documentation on the Botticelli website to understand the framework's architecture and modules. 3. Configure the integrations you need (database, AI engine, speech, queue broker, or scheduler) based on your bot's requirements. 4. Build your bot logic using the .NET Core framework conventions supported by Botticelli. 5. Use the included Docker support to containerize and deploy your bot to your preferred environment. 6. Test across your target messaging platforms (Telegram, WhatsApp, VK Messenger, etc.) before going live.