Best AI tools for< Rename Variables >

Bulk Rename Utility is a free online file renaming tool that combines AI and rule-based operations to efficiently rename multiple files or folders. Users can easily describe their renaming needs to the AI or apply customizable rules for batch renaming. The tool operates online, eliminating the need for file uploads and ensuring user privacy. With support for various file operations and diverse renaming rules, Bulk Rename Utility offers a user-friendly interface optimized for Chrome and Edge browsers on Windows and Mac systems.

Figma Autoname is an AI-powered plugin designed to simplify the process of renaming layers in Figma designs. By leveraging artificial intelligence, the tool automates the task of renaming layers, saving time and enhancing the overall design workflow. The plugin is community-driven, free to use, and open-source, allowing users to contribute and improve its functionality. Figma Autoname has received positive feedback from designers for its efficiency and ease of use.

Diagram is a suite of AI-powered design tools that help designers create beautiful and effective designs. With Diagram, you can generate SVG icons, create magical visuals, write and edit text, rename layers, and more. Diagram also offers a variety of features that make it easy to collaborate with other designers and share your work.

heyCLI is a command-line interface (CLI) tool that allows users to interact with their Linux systems using natural language. It is designed to make it easier for users to perform common tasks without having to memorize complex commands. heyCLI is still in its early stages of development, but it has the potential to be a valuable tool for both new and experienced Linux users.

DAILA is a unified interface for AI systems in decompilers, supporting various decompilers and AI systems. It allows users to utilize local and remote LLMs, like ChatGPT and Claude, and local models such as VarBERT. DAILA can be used as a decompiler plugin with GUI or as a scripting library. It also provides a Docker container for offline installations and supports tasks like summarizing functions and renaming variables in decompilation.

ReVA (Reverse Engineering Assistant) is a project aimed at building a disassembler agnostic AI assistant for reverse engineering tasks. It utilizes a tool-driven approach, providing small tools to the user to empower them in completing complex tasks. The assistant is designed to accept various inputs, guide the user in correcting mistakes, and provide additional context to encourage exploration. Users can ask questions, perform tasks like decompilation, class diagram generation, variable renaming, and more. ReVA supports different language models for online and local inference, with easy configuration options. The workflow involves opening the RE tool and program, then starting a chat session to interact with the assistant. Installation includes setting up the Python component, running the chat tool, and configuring the Ghidra extension for seamless integration. ReVA aims to enhance the reverse engineering process by breaking down actions into small parts, including the user's thoughts in the output, and providing support for monitoring and adjusting prompts.

AI-Driven Research Assistant is an advanced AI-powered system utilizing specialized agents for data analysis, visualization, and report generation. It integrates LangChain, OpenAI's GPT models, and LangGraph for complex research processes. Key features include hypothesis generation, data processing, web search, code generation, and report writing. The system's unique Note Taker agent maintains project state, reducing overhead and improving context retention. System requirements include Python 3.10+ and Jupyter Notebook environment. Installation involves cloning the repository, setting up a Conda virtual environment, installing dependencies, and configuring environment variables. Usage instructions include setting data, running Jupyter Notebook, customizing research tasks, and viewing results. Main components include agents for hypothesis generation, process supervision, visualization, code writing, search, report writing, quality review, and note-taking. Workflow involves hypothesis generation, processing, quality review, and revision. Customization is possible by modifying agent creation and workflow definition. Current issues include OpenAI errors, NoteTaker efficiency, runtime optimization, and refiner improvement. Contributions via pull requests are welcome under the MIT License.

ALog is an open-source project designed to facilitate the deployment of server-side code to Cloudflare. It provides a step-by-step guide on creating a Cloudflare worker, configuring environment variables, and updating API base URL. The project aims to simplify the process of deploying server-side code and interacting with OpenAI API. ALog is distributed under the GNU General Public License v2.0, allowing users to modify and distribute the app while adhering to App Store Review Guidelines.

Flowise is a tool that allows users to build customized LLM flows with a drag-and-drop UI. It is open-source and self-hostable, and it supports various deployments, including AWS, Azure, Digital Ocean, GCP, Railway, Render, HuggingFace Spaces, Elestio, Sealos, and RepoCloud. Flowise has three different modules in a single mono repository: server, ui, and components. The server module is a Node backend that serves API logics, the ui module is a React frontend, and the components module contains third-party node integrations. Flowise supports different environment variables to configure your instance, and you can specify these variables in the .env file inside the packages/server folder.

QANTA is a system and dataset for question answering tasks. It provides a script to download datasets, preprocesses questions, and matches them with Wikipedia pages. The system includes various datasets, training, dev, and test data in JSON and SQLite formats. Dependencies include Python 3.6, `click`, and NLTK models. Elastic Search 5.6 is needed for the Guesser component. Configuration is managed through environment variables and YAML files. QANTA supports multiple guesser implementations that can be enabled/disabled. Running QANTA involves using `cli.py` and Luigi pipelines. The system accesses raw Wikipedia dumps for data processing. The QANTA ID numbering scheme categorizes datasets based on events and competitions.

WebWhiz is an open-source tool that allows users to train ChatGPT on website data to build AI chatbots for customer queries. It offers easy integration, data-specific responses, regular data updates, no-code builder, chatbot customization, fine-tuning, and offline messaging. Users can create and train chatbots in a few simple steps by entering their website URL, automatically fetching and preparing training data, training ChatGPT, and embedding the chatbot on their website. WebWhiz can crawl websites monthly, collect text data and metadata, and process text data using tokens. Users can train custom data, but bringing custom open AI keys is not yet supported. The tool has no limitations on context size but may limit the number of pages based on the chosen plan. WebWhiz SDK is available on NPM, CDNs, and GitHub, and users can self-host it using Docker or manual setup involving MongoDB, Redis, Node, Python, and environment variables setup. For any issues, users can contact [email protected].

MindSearch is an open-source AI Search Engine Framework that mimics human minds to provide deep AI search capabilities. It allows users to deploy their own search engine using either close-source or open-source language models. MindSearch offers features such as answering any question using web knowledge, in-depth knowledge discovery, detailed solution paths, optimized UI experience, and dynamic graph construction process.

Langrila is a library that provides an easy way to use API-based LLM (Large Language Models) with an emphasis on simple architecture for readability. It supports various AI models for chat and embedding tasks, as well as retrieval functionalities using Qdrant, Chroma, and Usearch. Langrila also includes modules for function calling, conversation memory management, and prompt templates. It enforces coding policies for simplicity, responsibility independence, and minimum module implementation. The library requires Python version 3.10 to 3.13 and additional dependencies like OpenAI, Gemini, Qdrant, Chroma, and Usearch for specific functionalities.

Kuebiko is a Twitch Chat Bot that reads twitch chat and generates text-to-speech responses using Google Cloud API and OpenAI's GPT-3 text completion model. It allows users to set up their own VTuber AI similar to 'Neuro-Sama'. The project is built with Python and requires setting up various API keys and configurations to enable the bot functionality. Users can customize the voice of their VTuber and route audio using VBAudio Cable. Kuebiko provides a unique way to interact with viewers through chat responses and captions in OBS.

Discord AI Chatbot is a versatile tool that seamlessly integrates into your Discord server, offering a wide range of capabilities to enhance your communication and engagement. With its advanced language model, the bot excels at imaginative generation, providing endless possibilities for creative expression. Additionally, it offers secure credential management, ensuring the privacy of your data. The bot's hybrid command system combines the best of slash and normal commands, providing flexibility and ease of use. It also features mention recognition, ensuring prompt responses whenever you mention it or use its name. The bot's message handling capabilities prevent confusion by recognizing when you're replying to others. You can customize the bot's behavior by selecting from a range of pre-existing personalities or creating your own. The bot's web access feature unlocks a new level of convenience, allowing you to interact with it from anywhere. With its open-source nature, you have the freedom to modify and adapt the bot to your specific needs.

ALLCHAT is a Node.js backend and React MUI frontend for an application that interacts with the Gemini Pro 1.5 (and others), with history, image generating/recognition, PDF/Word/Excel upload, code run, model function calls and markdown support. It is a comprehensive tool that allows users to connect models to the world with Web Tools, run locally, deploy using Docker, configure Nginx, and monitor the application using a dockerized monitoring solution (Loki+Grafana).

DevChat is an open-source workflow engine that enables developers to create intelligent, automated workflows for engaging with users through a chat panel within their IDEs. It combines script writing flexibility, latest AI models, and an intuitive chat GUI to enhance user experience and productivity. DevChat simplifies the integration of AI in software development, unlocking new possibilities for developers.

Scriberr is a self-hostable AI audio transcription app that utilizes open-source Whisper models from OpenAI for transcribing audio files locally on user's hardware. It offers fast transcription with customizable compute settings, local transcription on device, API endpoints for automation, and integration with other tools. Users can optionally summarize transcripts using ChatGPT or Ollama, with support for custom prompts. The app is mobile-ready, simple, and easy to use, with planned features including speaker diarization, audio recording, file actions, full text fuzzy search, tag-based organization, follow-along text with playback, edit summaries, export options, and support for other languages. Despite being in beta, Scriberr is functional and usable, albeit with some rough edges and minor bugs.

Perplexica is an open-source AI-powered search engine that utilizes advanced machine learning algorithms to provide clear answers with sources cited. It offers various modes like Copilot Mode, Normal Mode, and Focus Modes for specific types of questions. Perplexica ensures up-to-date information by using SearxNG metasearch engine. It also features image and video search capabilities and upcoming features include finalizing Copilot Mode and adding Discover and History Saving features.

The Keras-llm-robot Web UI project is an open-source tool designed for offline deployment and testing of various open-source models from the Hugging Face website. It allows users to combine multiple models through configuration to achieve functionalities like multimodal, RAG, Agent, and more. The project consists of three main interfaces: chat interface for language models, configuration interface for loading models, and tools & agent interface for auxiliary models. Users can interact with the language model through text, voice, and image inputs, and the tool supports features like model loading, quantization, fine-tuning, role-playing, code interpretation, speech recognition, image recognition, network search engine, and function calling.

tgpt is a cross-platform command-line interface (CLI) tool that allows users to interact with AI chatbots in the Terminal without needing API keys. It supports various AI providers such as KoboldAI, Phind, Llama2, Blackbox AI, and OpenAI. Users can generate text, code, and images using different flags and options. The tool can be installed on GNU/Linux, MacOS, FreeBSD, and Windows systems. It also supports proxy configurations and provides options for updating and uninstalling the tool.

big-AGI is an AI suite designed for professionals seeking function, form, simplicity, and speed. It offers best-in-class Chats, Beams, and Calls with AI personas, visualizations, coding, drawing, side-by-side chatting, and more, all wrapped in a polished UX. The tool is powered by the latest models from 12 vendors and open-source servers, providing users with advanced AI capabilities and a seamless user experience. With continuous updates and enhancements, big-AGI aims to stay ahead of the curve in the AI landscape, catering to the needs of both developers and AI enthusiasts.

Agentok Studio is a visual tool built for AutoGen, a cutting-edge agent framework from Microsoft and various contributors. It offers intuitive visual tools to simplify the construction and management of complex agent-based workflows. Users can create workflows visually as graphs, chat with agents, and share flow templates. The tool is designed to streamline the development process for creators and developers working on next-generation Multi-Agent Applications.

Creates short, concise filenames from titles