landing_page/qdrant-landing/content/documentation/integrations/cheshire-cat.md

title, weight

title	weight
Cheshire Cat	600

Cheshire Cat

Cheshire Cat is an open-source framework that allows you to develop intelligent agents on top of many Large Language Models (LLM). You can develop your custom AI architecture to assist you in a wide range of tasks.

Cheshire Cat and Qdrant

Cheshire Cat uses Qdrant as the default Vector Memory for ingesting and retrieving documents.

# Decide host and port for your Cat. Default will be localhost:1865
CORE_HOST=localhost
CORE_PORT=1865

# Qdrant server
# QDRANT_HOST=localhost
# QDRANT_PORT=6333

Cheshire Cat takes great advantage of the following features of Qdrant:

• Collection Aliases to manage the change from one embedder to another.
• Quantization to obtain a good balance between speed, memory usage and quality of the results.
• Snapshots to not miss any information.
• Community

How to use the Cheshire Cat

Requirements

To run the Cheshire Cat, you need to have Docker and docker-compose already installed on your system.

docker run --rm -it -p 1865:80 ghcr.io/cheshire-cat-ai/core:latest

• Chat with the Cheshire Cat on localhost:1865/admin.
• You can also interact via REST API and try out the endpoints on localhost:1865/docs

Check the instructions on github for a more comprehensive quick start.

First configuration of the LLM

• Open the Admin Portal in your browser at localhost:1865/admin.
• Configure the LLM in the Settings tab.
• If you don't explicitly choose it using Settings tab, the Embedder follows the LLM.

Next steps

For more information, refer to the Cheshire Cat documentation and blog.

• Getting started
• How the Cat works
• Write Your First Plugin
• Cheshire Cat's use of Qdrant - Vector Space
• Cheshire Cat's use of Qdrant - Aliases
• Discord Community