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Basic Information

Cheshire Cat AI Core is a developer-focused framework to build and run custom AI agents as a microservice. It is API-first so teams can add a conversational layer to existing applications and provides both WebSocket chat and a customizable REST API for agent management. The project includes built-in retrieval-augmented generation (RAG) using Qdrant, pluggable extensions, event hooks, function-calling style tools, and conversational forms to manage goal-oriented dialogues. It ships with an admin panel for runtime management, supports any language model via LangChain, and is multiuser with granular permissions compatible with external identity providers. The repository is fully containerized for deployment with Docker and offers documentation and an active community to help developers extend and operate agents.

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App URL
https://github.com/cheshire-cat-ai/core
Github Repository
https://github.com/cheshire-cat-ai/core/blob/main/README.md

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App Details

Features
The README highlights an API-first architecture, WebSocket chat support, and a customizable REST API for programmatic control. Built-in RAG with Qdrant enables retrieval-backed responses. Extensibility is provided via a plugin system, decorators for event hooks, and LangChain-style tools that allow function calling. Conversational forms let developers define structured, goal-oriented interactions using Pydantic models. The project includes an admin panel for managing agents and multiuser support with permission controls and identity provider compatibility. The codebase is 100% Dockerized for simple deployment and the README includes minimal plugin examples and quickstart instructions to run the service locally.
Use Cases
This repository helps developers rapidly add conversational AI capabilities to applications by providing a ready-made microservice framework with both interactive and programmatic interfaces. Teams can leverage built-in RAG to enrich responses with external data, use plugins and hooks to integrate custom business logic, and define structured dialogues with conversational forms for guided workflows like orders or surveys. Docker packaging simplifies deployment and environment setup. The admin panel and REST API enable operational control, while multiuser and permission features support production use across teams. Documentation, examples, and an active Discord community lower the learning curve and accelerate building, extending, and managing agents in real projects.

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