gubatron

Framework	Description	Key Features	Language Support	Integration Capabilities	Deployment Options	License
RaLLe	A framework for developing and optimizing retrieval-augmented large language models (R-LLMs) for knowledge-intensive tasks.	- Development and evaluation of R-LLMs - Optimization tools for knowledge-intensive applications	Python	- Compatible with various LLMs - Supports integration with external knowledge bases	Local and cloud deployment	MIT License
BERGEN	A benchmarking library that standardizes experiments and provides tools for evaluating RAG pipelines.	- Standardized benchmarking - Comprehensive evaluation tools - Support for various RAG components	Python	- Integrates with multiple retrieval and generation models	Local deployment	Apache 2.0 License
RAGFlow	An open-source RAG engine based on deep document un

gubatron

Building libbitcoin-network on macos arm64

$ clang --version
Apple clang version 16.0.0 (clang-1600.0.26.3)
Target: arm64-apple-darwin23.5.0
Thread model: posix
InstalledDir: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin

$ uname -a

gubatron

split_file() {
    local file="$1"
    if [[ ! -f "$file" ]]; then
        echo "File '$file' does not exist."
        return 1
    fi

    # Use short options compatible with your version of split
    split -b 50k -a 2 "$file" "${file}.part"

gubatron

git clone [email protected]:lurk-lab/lurk-rs.git
cd lurk-rs
git submodule update --init --recursive
rustup target add aarch64-apple-ios
cargo build --target aarch64-apple-ios --release
ls -l target/aarch64-apple-ios/release/
cd target/aarch64-apple-ios/release
ar x liblurk.rlib
ar rcs liblurk.a *.o
ls -l liblurk.a

gubatron

#
# This script uses the	github command line tool
# to delete the last 30 logs from your repository's workflow runs
#
# Requirements
#
# gh - github command line (brew install gh)
# you will need a GH_TOKEN, create it here: https://github.com/settings/tokens
#
# once you've created the personal access token with permission to manage your workflows

gubatron

How to build your Docker image using the same Dockerfile regardless of the host architecture

Problem

If you are now using docker on a Mac M1 (arm64 platform), you don't want to use amd64 as the architecture for your Linux Images.

You could have 2 lines on your Dockerfile and comment each one depending on where you're building the image

Dockerfile

# Building on Apple Silicon host

gubatron

sudo apt install build-essential autoconf libtool bison re2c pkg-config libwebp-dev libxml2-dev libsqlite3-dev libbz2-dev libcurl4-openssl-dev libpng-dev libjpeg-dev libfreetype-dev libonig-dev libedit-dev libreadline-dev libzip-dev
cd php-8.1.10

#builds configure file if there isn't one
./buildconf

#./configure --help for full list of options

./configure --with-curl \
 --disable-cgi \

gubatron

from random import shuffle
'''
This module tries to solve the 8 queens problem.
'''
identity_rows = [0, 1, 2, 3, 4, 5, 6, 7]


def queens_attack_each_other(queen_a, queen_b):
    '''True if 2 queens face each other'''
    return queen_a[0] == queen_b[0] or queen_a[1] == queen_b[1] or abs(queen_a[0] - queen_b[0]) == abs(queen_a[1] - queen_b[1])

gubatron

class Complex {
    constructor(real, imag) {
        this.real = real
        this.imag = imag
    }

    length() {
        return Math.sqrt(this.real * this.real + this.imag * this.imag)
    }

gubatron

import hashlib
import binascii

def H(data):
    if type(data) == str:
        data = str.encode(data)
    if type(data) == int:
        data = data.to_bytes(4, 'big')
    return hashlib.sha256(data).digest()