Project
Reverse Dependencies for ruby-openai
The projects listed here declare ruby-openai as a runtime or development dependency
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A command-line tool to create, edit, and review ES files, with AI integration for enhanced productivity.
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Activity
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Translate release notes or changelogs for iOS and Android apps using OpenAI GPT API
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Activity
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FuncBot is a Rails gem built on top of the ruby-openai gem. It helps you create chatbots that can answer questions by calling on functions you define. It's goal is to provide a simple interface to consume OpenAI's Function Calling API.
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Activity
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Use Generative AI to generate I18n translations.
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Activity
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A command line tool for translation.
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Output test code using LLM agents.
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Use ChatGPT to write your commit messages
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Gpt3 Builder provides builder pattern for creating GTP3 questions and answers against OPENAI
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Activity
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gpterm is a powerful, flexible and dangerous command-line tool designed to help you generate commands for your terminal using OpenAI's Chat Completions
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[DEPRECATED] gpterminal has been renamed to gpterm. Please use the gpterm gem instead.
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With this gem and Ruby Raider you can power your automation with AI.
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Activity
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A multi-language code generator to cope with Hyrum's law
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Activity
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Adds helpers modules, classes and methods to make it easier to use Anthropic and OpenAI API
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Jambots is a command-line interface (CLI) tool for interacting with chatbots powered by OpenAI's GPT. It allows you to create new chatbots, manage chatbot conversations, and send messages to chatbots.
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The Prompt testing library for LLM that allows comparing patterns of prompts.
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Activity
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用来做数据集的工具
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Activity
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A Ruby gem for managing OpenAI GPT assistants with Rails integration
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Activity
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Use ChatGPT to write your shell commands
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LLM Conductor provides a clean, unified interface for working with multiple Language Model providers including OpenAI GPT, OpenRouter, and Ollama. Features include prompt templating, token counting, and extensible client architecture.
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Use this 'compiler' to build software using LLMs in a controlled way. In classical terms, the LLM is the compiler, the context description is the programming language, and the generated output is the binary.
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