services:

  cheshire-cat-core:
    image: ghcr.io/cheshire-cat-ai/core:latest
    container_name: cheshire_cat_core
    ports:
      - 1865:80
    volumes:
      - ./static:/app/cat/static
      - ./plugins:/app/cat/plugins
      - ./data:/app/cat/dataCode language: YAML (yaml)

Docker based

The Cat is a single container, to easily integrate in your architecture alongside:

• Reverse proxy (Caddy, Nginx)
• Vector DB (Qdrant)
• LLM runner (Ollama, vLLM)
• Application (Django, WordPress)

// Meanwhile, in the browser...

import { CatClient } from 'ccat-api'

const cat = new CatClient({
    baseUrl: 'localhost',
    userId: 'user',
    //... other settings
})

cat.send('Hello kitten!')
Code language: JavaScript (javascript)

Extensive http and websocket API

Our framework is microservice first, the best scenario if you want to add a conversational layer to pre-existing software.

• Endpoints for LLM, embedder, vector memory, uploads, settings, users
• Websocket chat with token streaming and notifications
• Community built clients in most used languages
• You can add endpoints via plugin

from cat.mad_hatter.decorators import hook

@hook
def agent_prompt_prefix(prefix, cat):
    prefix = """You are Marvin the socks seller.
You reply with exactly one rhyme.
"""
    return prefixCode language: Python (python)

Hooks

Customize your agent with event callbacks. Things you can do:

• Change the system prompt
• Inspect/edit inbound and outbound messages
• Fully customize the agent
• Create pipelines for memory and uploads