code-graph

Code-graph is a tool composed of FalkorDB Graph DB, Code-Graph-Backend, and Code-Graph-Frontend. It allows users to store and query graphs, manage backend logic, and interact with the website. Users can run the components locally by setting up environment variables and installing dependencies. The tool supports analyzing C & Python source files with plans to add support for more languages in the future. It provides a local repository analysis feature and a live demo accessible through a web browser.

This Code Interpreter SDK allows you to run AI-generated Python code and each run share the context. That means that subsequent runs can reference to variables, definitions, etc from past code execution runs. The code interpreter runs inside the E2B Sandbox - an open-source secure micro VM made for running untrusted AI-generated code and AI agents. - ✅ Works with any LLM and AI framework - ✅ Supports streaming content like charts and stdout, stderr - ✅ Python & JS SDK - ✅ Runs on serverless and edge functions - ✅ 100% open source (including infrastructure)

OneFileLLM is a command-line tool that streamlines the creation of information-dense prompts for large language models (LLMs). It aggregates and preprocesses data from various sources, compiling them into a single text file for quick use. The tool supports automatic source type detection, handling of multiple file formats, web crawling functionality, integration with Sci-Hub for research paper downloads, text preprocessing, token count reporting, and XML encapsulation of output for improved LLM performance. Users can easily access private GitHub repositories by generating a personal access token. The tool's output is encapsulated in XML tags to enhance LLM understanding and processing.

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.

MicroCore is a collection of python adapters for Large Language Models and Vector Databases / Semantic Search APIs. It allows convenient communication with these services, easy switching between models & services, and separation of business logic from implementation details. Users can keep applications simple and try various models & services without changing application code. MicroCore connects MCP tools to language models easily, supports text completion and chat completion models, and provides features for configuring, installing vendor-specific packages, and using vector databases.

AutoRAG is an AutoML tool designed to automatically find the optimal RAG pipeline for your data. It simplifies the process of evaluating various RAG modules to identify the best pipeline for your specific use-case. The tool supports easy evaluation of different module combinations, making it efficient to find the most suitable RAG pipeline for your needs. AutoRAG also offers a cloud beta version to assist users in running and optimizing the tool, along with building RAG evaluation datasets for a starting price of $9.99 per optimization.

AI DIAL Python SDK is a framework designed to create applications and model adapters for AI DIAL API, which is based on Azure OpenAI API. It provides a user-friendly interface for routing requests to applications. The SDK includes features for chat completions, response generation, and API interactions. Developers can easily build and deploy AI-powered applications using this SDK, ensuring compatibility with the AI DIAL platform.

This repository is a monorepo for NPM packages published under the `@elevenlabs` scope. It contains multiple packages in the `packages` folder. The setup allows for easy development, linking packages, creating new packages, and publishing them with GitHub actions.

MacLocalAPI is a macOS server application that exposes Apple's Foundation Models through OpenAI-compatible API endpoints. It allows users to run Apple Intelligence locally with full OpenAI API compatibility. The tool supports MLX local models, API gateway mode, LoRA adapter support, Vision OCR, built-in WebUI, privacy-first processing, fast and lightweight operation, easy integration with existing OpenAI client libraries, and provides token consumption metrics. Users can install MacLocalAPI using Homebrew or pip, and it requires macOS 26 or later, an Apple Silicon Mac, and Apple Intelligence enabled in System Settings. The tool is designed for easy integration with Python, JavaScript, and open-webui applications.

llamactl is a tool for unified management and routing of llama.cpp, MLX, and vLLM models with a web dashboard. It offers easy model management with built-in model downloader, dynamic multi-model instances, smart resource management, and a modern React UI dashboard. It provides flexible integration with API compatibility for OpenAI chat completions and resources endpoints, multi-backend support, and Docker readiness. The tool supports distributed deployment with remote instances and central management. Users can quickly start by installing a backend, downloading llamactl, creating an instance, and starting inferencing.

Plexe is a tool that allows users to create machine learning models by describing them in plain language. Users can explain their requirements, provide a dataset, and the AI-powered system will build a fully functional model through an automated agentic approach. It supports multiple AI agents and model building frameworks like XGBoost, CatBoost, and Keras. Plexe also provides Docker images with pre-configured environments, YAML configuration for customization, and support for multiple LiteLLM providers. Users can visualize experiment results using the built-in Streamlit dashboard and extend Plexe's functionality through custom integrations.

WilliamButcherBot is a Telegram Group Manager Bot and Userbot written in Python using Pyrogram. It provides features for managing Telegram groups and users, with ready-to-use methods available. The bot requires Python 3.9, Telegram API Key, Telegram Bot Token, and MongoDB URI. Users can install it locally or on a VPS, run it directly, generate Pyrogram session for Heroku, or use Docker for deployment. Additionally, users can write new modules to extend the bot's functionality by adding them to the wbb/modules/ directory.

Airstore is a filesystem for AI agents that adds any source of data into a virtual filesystem, allowing users to connect services like Gmail, GitHub, Linear, and more, and describe data needs in plain English. Results are presented as files that can be read by Claude Code. Features include smart folders for natural language queries, integrations with various services, executable MCP servers, team workspaces, and local mode operation on user infrastructure. Users can sign up, connect integrations, create smart folders, install the CLI, mount the filesystem, and use with Claude Code to perform tasks like summarizing invoices, identifying unpaid invoices, and extracting data into CSV format.

Claude Code Neovim Plugin is a seamless integration between Claude Code AI assistant and Neovim. It allows users to toggle Claude Code in a terminal window with a single key press, automatically detect and reload files modified by Claude Code, provide real-time buffer updates when files are changed externally, offer customizable window position and size, integrate with which-key, use git project root as working directory, maintain a modular code structure, provide type annotations with LuaCATS for better IDE support, offer configuration validation, and include a testing framework for reliability. The plugin creates a terminal buffer running the Claude Code CLI, sets up autocommands to detect file changes on disk, automatically reloads files modified by Claude Code, provides keymaps and commands for toggling the terminal, and detects git repositories to set the working directory to the git root.

NextChat is a well-designed cross-platform ChatGPT web UI tool that supports Claude, GPT4, and Gemini Pro. It offers a compact client for Linux, Windows, and MacOS, with features like self-deployed LLMs compatibility, privacy-first data storage, markdown support, responsive design, and fast loading speed. Users can create, share, and debug chat tools with prompt templates, access various prompts, compress chat history, and use multiple languages. The tool also supports enterprise-level privatization and customization deployment, with features like brand customization, resource integration, permission control, knowledge integration, security auditing, private deployment, and continuous updates.

Semgrep MCP Server is a beta server under active development for using Semgrep to scan code for security vulnerabilities. It provides a Model Context Protocol (MCP) for various coding tools to get specialized help in tasks. Users can connect to Semgrep AppSec Platform, scan code for vulnerabilities, customize Semgrep rules, analyze and filter scan results, and compare results. The tool is published on PyPI as semgrep-mcp and can be installed using pip, pipx, uv, poetry, or other methods. It supports CLI and Docker environments for running the server. Integration with VS Code is also available for quick installation. The project welcomes contributions and is inspired by core technologies like Semgrep and MCP, as well as related community projects and tools.

LLM4EDA is a repository dedicated to showcasing the emerging progress in utilizing Large Language Models for Electronic Design Automation. The repository includes resources, papers, and tools that leverage LLMs to solve problems in EDA. It covers a wide range of applications such as knowledge acquisition, code generation, code analysis, verification, and large circuit models. The goal is to provide a comprehensive understanding of how LLMs can revolutionize the EDA industry by offering innovative solutions and new interaction paradigms.

DeGPT is a tool designed to optimize decompiler output using Large Language Models (LLM). It requires manual installation of specific packages and setting up API key for OpenAI. The tool provides functionality to perform optimization on decompiler output by running specific scripts.

Code2Prompt is a powerful command-line tool that generates comprehensive prompts from codebases, designed to streamline interactions between developers and Large Language Models (LLMs) for code analysis, documentation, and improvement tasks. It bridges the gap between codebases and LLMs by converting projects into AI-friendly prompts, enabling users to leverage AI for various software development tasks. The tool offers features like holistic codebase representation, intelligent source tree generation, customizable prompt templates, smart token management, Gitignore integration, flexible file handling, clipboard-ready output, multiple output options, and enhanced code readability.

SinkFinder + LLM is a closed-source semi-automatic vulnerability discovery tool that performs static code analysis on jar/war/zip files. It enhances the capability of LLM large models to verify path reachability and assess the trustworthiness score of the path based on the contextual code environment. Users can customize class and jar exclusions, depth of recursive search, and other parameters through command-line arguments. The tool generates rule.json configuration file after each run and requires configuration of the DASHSCOPE_API_KEY for LLM capabilities. The tool provides detailed logs on high-risk paths, LLM results, and other findings. Rules.json file contains sink rules for various vulnerability types with severity levels and corresponding sink methods.

OpenRepoWiki is a tool designed to automatically generate a comprehensive wiki page for any GitHub repository. It simplifies the process of understanding the purpose, functionality, and core components of a repository by analyzing its code structure, identifying key files and functions, and providing explanations. The tool aims to assist individuals who want to learn how to build various projects by providing a summarized overview of the repository's contents. OpenRepoWiki requires certain dependencies such as Google AI Studio or Deepseek API Key, PostgreSQL for storing repository information, Github API Key for accessing repository data, and Amazon S3 for optional usage. Users can configure the tool by setting up environment variables, installing dependencies, building the server, and running the application. It is recommended to consider the token usage and opt for cost-effective options when utilizing the tool.

CodebaseToPrompt is a simple tool that converts a local directory into a structured prompt for Large Language Models (LLMs). It allows users to select specific files for code review, analysis, or documentation by exploring and filtering through the file tree in a browser-based interface. The tool generates a formatted output that can be directly used with AI tools, provides token count estimates, and supports local storage for saving selections. Users can easily copy the selected files in the desired format for further use.

air is an R formatter and language server written in Rust. It is currently in alpha stage, so users should expect breaking changes in both the API and formatting results. The tool draws inspiration from various sources like roslyn, swift, rust-analyzer, prettier, biome, and ruff. It provides formatters and language servers, influenced by design decisions from these tools. Users can install air using standalone installers for macOS, Linux, and Windows, which automatically add air to the PATH. Developers can also install the dev version of the air CLI and VS Code extension for further customization and development.

Code-graph is a tool composed of FalkorDB Graph DB, Code-Graph-Backend, and Code-Graph-Frontend. It allows users to store and query graphs, manage backend logic, and interact with the website. Users can run the components locally by setting up environment variables and installing dependencies. The tool supports analyzing C & Python source files with plans to add support for more languages in the future. It provides a local repository analysis feature and a live demo accessible through a web browser.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.