ConvoStack offers a free, open-source, plug-and-play AI chatbot widget and backend deployment framework designed for websites. It empowers developers to rapidly integrate conversational AI capabilities into their applications, providing a flexible and embeddable solution.

How It Works

The architecture combines a React frontend for the user-facing chat widget with an Express.js backend. Redis is utilized for production caching and managing real-time communication via publish/subscribe. ConvoStack integrates with the Langchain agent framework, enabling developers to connect and deploy various AI models, such as OpenAI's LLMs, through a defined agent reply function.

Quick Start & Requirements

Installation is performed using npm: npm install --save convostack. The project requires a Node.js environment. The quickstart example demonstrates integration with Langchain and OpenAI, necessitating environment variable configuration for API keys (e.g., OPENAI_API_KEY via dotenv). A live demo playground and a dedicated quickstart guide are available for immediate use and setup assistance.

Highlighted Details

• Features a "plug-and-play" embeddable AI chatbot widget.
• Provides a backend deployment framework for custom AI agent logic.
• Supports integration with Langchain for flexible AI model connections.
• Distributed as completely free and open-source software.

Maintenance & Community

The provided README does not specify details regarding maintainers, community support channels (e.g., Discord, Slack), or a public roadmap.

Licensing & Compatibility

The project is stated to be "completely free and open source," however, the README does not explicitly name the license type (e.g., MIT, Apache 2.0). This omission requires clarification regarding its terms, especially for commercial use or integration into closed-source projects.

Limitations & Caveats

The README does not detail specific limitations, unsupported platforms, or known bugs. The primary integration example relies on OpenAI, indicating a dependency on external LLM providers and their associated costs and terms of service. The lack of a clearly defined open-source license is a significant point requiring due diligence before adoption.