Browse

Panel .cursorrules prompt files

Panel is a group of individuals selected for analysis, consulting, or advising, providing diverse perspectives for informed decision-making.

Filters

All

React

Tailwind CSS

Filters

Tech

Clear

seaborn

Tauri

logging

Azure

MySQL

Go

Kafka

WebP.

next-safe-action

Phoenix LiveView

Ecto

File System Watcher

Plug

Finch

Gettext

Phoenix

Jason

Phoenix LiveDashboard

Sobelow

ExCoveralls

DNS Cluster

ExUnit

Release Please

Swoosh

Credo

LeftHook

npm

Wagmi

Viem

Next.js 14

Daisy UI

Express.js

Vercel AI SDK

Firebase

Slither

Hardhat

Mythril

Chainlink VRF

SOLID

OpenAI

SVG

SWR

Prometheus

Memcached

ELK Stack

Grafana

async/await

API

Grid

OpenAPI

React Server Components

Turborepo

None

TanStack React Query

Mongoose

virtual environments

dask

PyTorch

tqdm

Flask

joblib

NumPy

python-dotenv

pip

Django REST Framework

unittest

WhiteNoise

pytest-django

AWS

NoSQL

Kubernetes

Cypress

Axios

Next.js SSR.

Next.js 14 App Router

Angular

React Server Components (RSC)

Rell

Kotlin

Tailwind CSS.

Cairo

Biome

Composer

WebAssembly

yarn

Material UI

autoprefixer

bcryptjs

@types/react

Next.Js

@types/node

prisma

framer-motion

postcss

react-dom

Supabase Auth

WCAG

React.FC

React.ReactNode

fetch API

Graphical Apps Development .cursorrules prompt file

# Project Synopsis
Pyllments is a Python library for building graphical and API-based LLM applications through chaining together Elements in a potentially cyclic graph.

Elements and Payloads are a type of Components. A Component is composed of a Model and Views. The Model handles the underlying data and logic, while the Views are the UI components that are used to display display the interactive UI used to interact with the Model.
An Element is a type of Component that is responsible for a specific function. For instance, an Element can handle the LLM selection and generation by making calls to LLM providers. Another Element may handle the chat interface, whose Model would store the chat message history, and the Views would be the text boxes and buttons used to interact with the chat interface. Elements are meant to connect to other Elements through Ports. All that is necessary to link Elements together is to link the output port of one Element to the input port of Another. Each output port may have unlimited input ports it connects to, and each input port may have unlimited output ports it connects to. The ports follow an observer pattern where the output port is the subject and the input port is the observer. The subject notifies the observers when a certain event that we set within the Element is triggered.
In order to connect an input and and output port, they need to be setup in a manner that sends and receives the same type of Payload. A Payload is also a Component with a Model as well as views responsible for the display logic. Elements may receive payloads and use methods of the Payload to generate the views for the UI. The sending Element is responsible for packing data into the Payload.

I am currently working on making this a fully-fledged framework.

# Project Organization
Here is an example of the file structure of an individual element:
chat_interface:
  - __init__.py
  - chat_interface_element.py
  - chat_interface_model.py
  - css:
    - buttons.css
    - column.css
    - input.css

# Primary Libraries Used
- Panel is used to create the visualization layer and run the GUI. Views tend to consist of Panel objects which can be styled with Python and CSS.
- Param is used to create parameterized classes which help create parameters that handle type validation, default values, constraints, and most importantly, reactivity(setting event handlers to catch changes).
- Langchain is responsible for the specific functions pertaining to incorporating LLM workflows.

# Development Priorities
Pyllments code is prioritized on being developer-friendly, where extensibility and modularity are first-class citizens. Elements should be customizeable with clean and intuitive interfaces. It should also be easy to create new elements depending on the needs of the developer.

# Documentation
Docstrings should use a NumPy/SciPy style.

stack: