A fun CLI tool to see your GitHub contributions on this day throughout the years
The Memory Layer For Your AI Apps
Provides metadata and conversions from repository urls for GitHub, Bitbucket and GitLab
Get raw git commits out of your repository using git-log(1).
a util for spawning git from npm CLI contexts
Simple GIT interface for node.js
List of Git hooks
A high level git url parser for common git providers.
Mengubah waktu standar menjadi waktu moment
Local-first memory for your AI brain — a nervous system that turns engrams into curated, persistent memories in a folder you control. Bundles `think serve` for piping external events (GitHub, Linear, …) into memory.
March CLI — terminal-native coding agent with context reconstruction
A low level git url parser.
Get all git semver tags of your repository in reverse chronological order.
Biologically-inspired memory system for AI agents. Decay by default, strength through use.
Simple git client for conventional changelog packages.
Web UI for browsing, searching, and managing memories. Provides a full-featured dashboard to inspect memory storage, edit metadata, and review memories flagged for deduplication.
Persistent memory for AI coding sessions — Git-native, human-readable, safe to share
A pure JavaScript reimplementation of git for node and browsers
A brain-inspired hierarchical memory system for AI coding agents. Deep nested file structure that mimics human memory with time-decay and strength-based recall.
Get the remote origin URL of a Git repository
Some git helpers that changesets use to get information
Persistent cross-session memory with vector search for Pi coding agent
A local MCP memory server backed by markdown + JSON files, synced via git
Harness Attention. Orchestrate Agents. Ship.
GitStore implements a versioned data store based on the revision management system Git. You can store object hierarchies as nested hashes, which will be mapped on the directory structure of a git repository. GitStore checks out the repository into a in-memory representation, which can be modified and finally committed.
# CheckTCPMemory This is a simple Nagios/Sensu check that checks that the current TCP memory usage is below the maximum allowed in the Linux kernel. This will find leaking TCP sockets. ## Installation Add this line to your application's Gemfile: ```ruby gem 'check_tcp_memory' ``` And then execute: $ bundle Or install it yourself as: $ gem install check_tcp_memory ## Usage ``` $ check_tcp_memory -h Usage: check_tcp_memory -w <warn percent> -c <critical percent> -w, --warn-percent PERCENT Warning when percentage of total TCP memory is over this threashold. Default: 50% -c, --crit-percent PERCENT Critical when percentage of total TCP memory is over this threashold. Default: 60% -h, --help Show this message --version Show version ``` ## Development After checking out the repo, run `bin/setup` to install dependencies. Then, run `rake spec` to run the tests. You can also run `bin/console` for an interactive prompt that will allow you to experiment. To install this gem onto your local machine, run `bundle exec rake install`. To release a new version, update the version number in `version.rb`, and then run `bundle exec rake release`, which will create a git tag for the version, push git commits and tags, and push the `.gem` file to [rubygems.org](https://rubygems.org). ## Contributing Bug reports and pull requests are welcome on GitHub at https://github.com/Altiscale/check_tcp_memory. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the [Contributor Covenant](contributor-covenant.org) code of conduct.
# DECC 2050 CALCULATOR TOOL A C version and ruby wrapper for the www.decc.gov.uk 2050 energy and climate change excel calculator Further detail on the project: http://www.decc.gov.uk/2050 Canonical source: http://github.com/decc/decc_2050_model ## DEPENDENCIES 1. ruby 1.9.2 (including development headers) 2. basic c development headers This has ONLY been tested on OSX and on Ubuntu 64 bit EC2 ami. Grateful for reports from other platforms. In the util folder are two example scripts than can be helpful: 1. start-high-memory-instance.sh - is the script we use to setup an aws server to compile the model. You can't use it directly, because you won't have the right keys and certificates, but it can give clues. 2. setup-2050-model-builder-script.sh - is the script we use to get all the dependencies on that aws server correct, download this code, and then compile the model. Again, it may not be quite right for you but can server as inspiration ## INSTALLATION Note that this compiles the underlying c code, which might take 10-20 minutes or so gem install decc_2050_model ## UPDATING TO NEWER VERSIONS OF EXCEL MODEL First of all, you need to be working on the github version of the code, not the rubygem: git clone http://github.com/decc/decc_2050_model Then put the new spreadsheet in spreadsheet/2050Model.xlsx Then, from the top directory of the gem: bundle bundle exec rake The next step is to check whether lib/decc_2050_model/decc_2050_model_result.rb and lib/decc_2050_model/model_structure.rb need to be altered so that they pick up the correct places in the underlying excel. The final stage is to build and install the new gem: gem build decc_2050_model.gemspec gem install decc_2050_model-<version>.gem ... where <version> is the version number of the gem file that was created in the folder. Now follow the instructions in the twenty-fifty server directory in order to ensure that it is using this new version of the gem.