kai gouthro kaigouthro

This update significantly enhances the "Gramformer Demo" application by modernizing its architecture, improving performance, and refining the user interface. It transitions the application from a class-based structure to a more functional, modular design that is idiomatic for Streamlit, improving readability and maintainability.

The most critical improvement is the update from the legacy @st.cache to the current @st.cache_resource for loading the Gramformer model. This ensures the large model is loaded into memory only once and is efficiently reused across sessions, providing a much faster user experience after the initial startup.

The UI has been redesigned into a clean, two-column layout, allowing users to compare the original text and the corrected results side-by-side. Additionally, the code now includes logic to automatically detect and utilize a CUDA-enabled GPU if available, while gracefully falling back to CPU.

Feature Focus - Modular, High-Performance Design

sequenceDiagram

A Bash script for Debian/Ubuntu-based systems that will install Docker (if not already installed) and configure it to use a specified directory (presumably on your mounted external drive) for storing containers, images, volumes, etc.

Important Considerations BEFORE Running:

External Drive MUST be Mounted: This script assumes your external drive is already mounted before you run the script. It does not handle mounting the drive itself.
Persistent Mount: For Docker to start correctly after a reboot, the external drive must be mounted persistently (e.g., via an entry in /etc/fstab) at the same path every time.
Backup: If you have existing Docker data in /var/lib/docker and it's important, BACK IT UP before running this script. The script attempts to move existing data, but failures can happen.
Root Privileges: You need to run this script with sudo.
Distribution: This script is tailored for Debian/Ubuntu. The package manager (apt), repository s

Enhanced Quivr Usage Script

This introduces a Python script quivrtool.py designed to significantly simplify the use of the quivr-core library, both within Python scripts and for agent-based interactions. It provides streamlined functions for creating and querying Quivr brains, leveraging YAML configurations for workflow customization.

It includes:

Simplified brain creation from files.
User-friendly question answering with brain.
Functions for saving and loading brains.
Example functions designed for agent tool calls.
Clear documentation and usage examples within the script.

Oniguruma Regular Expressions v6.9.8 Reference

Version: 6.9.8 (2022/04/11) Syntax: ONIG_SYNTAX_ONIGURUMA (default)

This document provides a comprehensive reference for Oniguruma regular expressions syntax, version 6.9.8. It is intended for use as a quick guide and reference for AI language models and developers working with Oniguruma regex.

1. Syntax Elements

MEXC Futures API Documentation

This document provides a structured overview of the MEXC Futures API, focusing on clarity, conciseness, and practical examples.

Methods

The API offers a variety of methods to interact with the MEXC Futures exchange. Each method is categorized by its functionality and accompanied by its respective parameters and examples.

Market Data Endpoints

Instructions from PyFlowchart Documentation

Installation:

Install using pip:
```
$ pip install pyflowchart
```

Project Documentation

Overview

This document provides an overview and detailed explanation of the codebase, including its primary functions, settings management, and interaction with the AI model.

	from dataclasses import dataclass
	from typing import List, Union, Optional, Tuple

	# Data Classes for Logitech G HUB Lua API

	@dataclass
	class Event:
	name: str
	arg: Optional[Union[int, str]] = None
	family: Optional[str] = None

	import json
	import os


	def extract_source_code(map_file_path):
	"""
	Extracts source code from a webpack source map file.
	Args:
	map_file_path (str): Path to the source map file.
	Returns:

	class LuaScriptGenerator:
	def __init__(self):
	self.function_templates = {
	"PressAndReleaseKey": "PressAndReleaseKey({key})",
	"PressKey": "PressKey({key})",
	"ReleaseKey": "ReleaseKey({key})",
	"PressAndReleaseMouseButton": "PressAndReleaseMouseButton({button})",
	"PressMouseButton": "PressMouseButton({button})",
	"ReleaseMouseButton": "ReleaseMouseButton({button})",
	# Add more function templates as needed