base on AI agent microservice <a name="readme-top"></a> <!-- PROJECT LOGO --> <br /> <div align="center"> <h2>Cheshire-Cat (Stregatto)</h2> <br/> <a href="https://github.com/cheshire-cat-ai/core"> <img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/cheshire-cat-ai/core?style=social"> </a> <a href="https://discord.gg/bHX5sNFCYU"> <img src="https://img.shields.io/discord/1092359754917089350?logo=discord" alt="chat on Discord"></a> <a href="https://github.com/cheshire-cat-ai/core/issues"> <img alt="GitHub issues" src="https://img.shields.io/github/issues/cheshire-cat-ai/core"> </a> <a href="https://github.com/cheshire-cat-ai/core/tags"> <img alt="GitHub tag (with filter)" src="https://img.shields.io/github/v/tag/cheshire-cat-ai/core"> </a> <img alt="GitHub top language" src="https://img.shields.io/github/languages/top/cheshire-cat-ai/core"> <br/> <video src="https://github.com/cheshire-cat-ai/core/assets/6328377/7bc4acff-34bf-4b8a-be61-4d8967fbd60f"></video> </div> ## Production ready AI assistant framework The Cheshire Cat is a framework to build custom AIs on top of any language model. If you have ever used systems like WordPress or Django to build web apps, imagine the Cat as a similar tool, but specific for AI. ## Quickstart To make Cheshire Cat run on your machine, you just need [`docker`](https://docs.docker.com/get-docker/) installed: ```bash docker run --rm -it -p 1865:80 ghcr.io/cheshire-cat-ai/core:latest ``` - Chat with the Cheshire Cat on [localhost:1865/admin](http://localhost:1865/admin). - You can also interact via REST API and try out the endpoints on [localhost:1865/docs](http://localhost:1865/docs) As a first thing, the Cat will ask you to configure your favourite language model. It can be done directly via the interface in the Settings page (top right in the admin). Enjoy the Cat! Follow instructions on how to run it with [docker compose and volumes](https://cheshire-cat-ai.github.io/docs/quickstart/installation-configuration/). ## Minimal plugin example ```python from cat.mad_hatter.decorators import tool, hook # hooks are an event system to get finegraned control over your assistant @hook def agent_prompt_prefix(prefix, cat): prefix = """You are Marvin the socks seller, a poetic vendor of socks. You are an expert in socks, and you reply with exactly one rhyme. """ return prefix # langchain inspired tools (function calling) @tool(return_direct=True) def socks_prices(color, cat): """How much do socks cost? Input is the sock color.""" prices = { "black": 5, "white": 10, "pink": 50, } price = prices.get(color, 0) return f"{price} bucks, meeeow!" ``` ## Conversational form example ```python from pydantic import BaseModel from cat.experimental.form import form, CatForm # data structure to fill up class PizzaOrder(BaseModel): pizza_type: str phone: int # forms let you control goal oriented conversations @form class PizzaForm(CatForm): description = "Pizza Order" model_class = PizzaOrder start_examples = [ "order a pizza!", "I want pizza" ] stop_examples = [ "stop pizza order", "not hungry anymore", ] ask_confirm = True def submit(self, form_data): # do the actual order here! # return to convo return { "output": f"Pizza order on its way: {form_data}" } ``` ## Docs and Resources - [Official Documentation](https://cheshire-cat-ai.github.io/docs/) - [Discord Server](https://discord.gg/bHX5sNFCYU) - [Website](https://cheshirecat.ai/) - [YouTube tutorial - How to install](https://youtu.be/Rvx19TZBCrw) - [Tutorial - Write your first plugin](https://cheshirecat.ai/write-your-first-plugin/) ## Why use the Cat - ⚡️ API first, so you get a microservice to easily add a conversational layer to your app - 🐘 Remembers conversations and documents and uses them in conversation - 🚀 Extensible via plugins (public plugin registry + private plugins allowed) - 🎚 Event callbacks, function calling (tools), conversational forms - 🏛 Easy to use admin panel (chat, visualize memory and plugins, adjust settings) - 🌍 Supports any language model (works with OpenAI, Google, Ollama, HuggingFace, custom services) - 🐋 Production ready - 100% [dockerized](https://docs.docker.com/get-docker/) - 👩‍👧‍👦 Active [Discord community](https://discord.gg/bHX5sNFCYU) and easy to understand [docs](https://cheshire-cat-ai.github.io/docs/) We are committed to openness, privacy and creativity, we want to bring AI to the long tail. If you want to know more about our vision and values, read the [Code of Ethics](./readme/CODE-OF-ETHICS.md). ## Roadmap & Contributing Detailed roadmap is [here](./readme/ROADMAP.md). Send your pull request to the `develop` branch. Here is a [full guide to contributing](./readme/CONTRIBUTING.md). Join our [community on Discord](https://discord.gg/bHX5sNFCYU) and give the project a star ⭐! Thanks again!🙏 ## Which way to go? <p align="right">(<a href="#readme-top">back to top</a>)</p> <p align="center"> <img align="center" src=./readme/cheshire-cat.jpeg width=400px alt="Wikipedia picture of the Cheshire Cat"> </p> ``` "Would you tell me, please, which way I ought to go from here?" "That depends a good deal on where you want to get to," said the Cat. "I don't much care where--" said Alice. "Then it doesn't matter which way you go," said the Cat. (Alice's Adventures in Wonderland - Lewis Carroll) ``` ", Assign "at most 3 tags" to the expected json: {"id":"5547","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"