chunkhound

ChunkHound is a modern tool for transforming your codebase into a searchable knowledge base for AI assistants. It utilizes semantic search via the cAST algorithm and regex search, integrating with AI assistants through the Model Context Protocol (MCP). With features like cAST Algorithm, Multi-Hop Semantic Search, Regex search, and support for 22 languages, ChunkHound offers a local-first approach to code analysis and discovery. It provides intelligent code discovery, universal language support, and real-time indexing capabilities, making it a powerful tool for developers looking to enhance their coding experience.

ChunkHound is a tool that transforms your codebase into a searchable knowledge base for AI assistants using semantic and regex search. It integrates with AI assistants via the Model Context Protocol (MCP) and offers features such as cAST algorithm for semantic code chunking, multi-hop semantic search, natural language queries, regex search without API keys, support for 22 languages, and local-first architecture. It provides intelligent code discovery by following semantic relationships and discovering related implementations. ChunkHound is built on the cAST algorithm from Carnegie Mellon University, ensuring structure-aware chunking that preserves code meaning. It supports universal language parsing and offers efficient updates for large codebases.

Haiku RAG is a Retrieval-Augmented Generation (RAG) library that utilizes LanceDB as a local vector database. It supports semantic and full-text search, hybrid search with Reciprocal Rank Fusion, multiple embedding and QA providers, default search result reranking, question answering, file monitoring, and various file formats. It can be used via CLI or Python API, and can serve as tools for AI assistants like Claude Desktop. The library offers features for document management and search, with detailed documentation available.

Vearch is a cloud-native distributed vector database designed for efficient similarity search of embedding vectors in AI applications. It supports hybrid search with vector search and scalar filtering, offers fast vector retrieval from millions of objects in milliseconds, and ensures scalability and reliability through replication and elastic scaling out. Users can deploy Vearch cluster on Kubernetes, add charts from the repository or locally, start with Docker-compose, or compile from source code. The tool includes components like Master for schema management, Router for RESTful API, and PartitionServer for hosting document partitions with raft-based replication. Vearch can be used for building visual search systems for indexing images and offers a Python SDK for easy installation and usage. The tool is suitable for AI developers and researchers looking for efficient vector search capabilities in their applications.

Official SDKs for the ScrapeGraph AI API - Intelligent web scraping and search powered by AI. Extract structured data from any webpage or perform AI-powered web searches with natural language prompts. The SDK offers features such as SmartScraper for data extraction, SearchScraper for AI-powered web search, Markdownify for converting webpages to markdown, SmartCrawler for intelligent crawling, AgenticScraper for automated browser actions, and more. It provides seamless integration with popular frameworks and tools, supports Python and JavaScript SDKs, LLM frameworks, low-code platforms, and offers core features like AI-powered extraction, structured output, multiple data formats, high performance, and enterprise-grade security.

AI Tagger Universe is a plugin for Obsidian that automatically generates intelligent tags for notes using AI. It offers flexible AI integration with various services, smart tagging system with multiple modes, tag network visualization, advanced management features, and support for multiple languages. Users can easily install the plugin, configure AI providers, generate tags, and visualize tag relationships. The plugin also supports nested tags, hierarchical tag generation, and tag format options. It includes bug fixes, major features, improvements, and language support for English and Chinese interfaces.

Mira is an agentic AI library designed for automating company research by gathering information from various sources like company websites, LinkedIn profiles, and Google Search. It utilizes a multi-agent architecture to collect and merge data points into a structured profile with confidence scores and clear source attribution. The core library is framework-agnostic and can be integrated into applications, pipelines, or custom workflows. Mira offers features such as real-time progress events, confidence scoring, company criteria matching, and built-in services for data gathering. The tool is suitable for users looking to streamline company research processes and enhance data collection efficiency.

Jetify's AI SDK for Go is a unified interface for interacting with multiple AI providers including OpenAI, Anthropic, and more. It addresses the challenges of fragmented ecosystems, vendor lock-in, poor Go developer experience, and complex multi-modal handling by providing a unified interface, Go-first design, production-ready features, multi-modal support, and extensible architecture. The SDK supports language models, embeddings, image generation, multi-provider support, multi-modal inputs, tool calling, and structured outputs.

Persistent AI Memory System is a comprehensive tool that offers persistent, searchable storage for AI assistants. It includes features like conversation tracking, MCP tool call logging, and intelligent scheduling. The system supports multiple databases, provides enhanced memory management, and offers various tools for memory operations, schedule management, and system health checks. It also integrates with various platforms like LM Studio, VS Code, Koboldcpp, Ollama, and more. The system is designed to be modular, platform-agnostic, and scalable, allowing users to handle large conversation histories efficiently.

Alice is an open-source AI companion designed to live on your desktop, providing voice interaction, intelligent context awareness, and powerful tooling. More than a chatbot, Alice is emotionally engaging and deeply useful, assisting with daily tasks and creative work. Key features include voice interaction with natural-sounding responses, memory and context management, vision and visual output capabilities, computer use tools, function calling for web search and task scheduling, wake word support, dedicated Chrome extension, and flexible settings interface. Technologies used include Vue.js, Electron, OpenAI, Go, hnswlib-node, and more. Alice is customizable and offers a dedicated Chrome extension, wake word support, and various tools for computer use and productivity tasks.

AiderDesk is a desktop application that enhances coding workflow by leveraging AI capabilities. It offers an intuitive GUI, project management, IDE integration, MCP support, settings management, cost tracking, structured messages, visual file management, model switching, code diff viewer, one-click reverts, and easy sharing. Users can install it by downloading the latest release and running the executable. AiderDesk also supports Python version detection and auto update disabling. It includes features like multiple project management, context file management, model switching, chat mode selection, question answering, cost tracking, MCP server integration, and MCP support for external tools and context. Development setup involves cloning the repository, installing dependencies, running in development mode, and building executables for different platforms. Contributions from the community are welcome following specific guidelines.

SMRY.ai is a Next.js application that bypasses paywalls and generates AI-powered summaries by fetching content from multiple sources simultaneously. It provides a distraction-free reader with summary builder, cleans articles, offers multi-source fetching, built-in AI summaries in 14 languages, rich debug context, soft paywall access, smart extraction using Diffbot's AI, multi-source parallel fetching, type-safe error handling, dual caching strategy, intelligent source routing, content parsing pipeline, multilingual summaries, and more. The tool aims to make referencing reporting easier, provide original articles alongside summaries, and offer concise summaries in various languages.

Tingly Box is a tool that helps in deciding which model to call, compressing context, and routing requests efficiently. It offers secure, reliable, and customizable functional extensions. With features like unified API, smart routing, context compression, auto API translation, blazing fast performance, flexible authentication, visual control panel, and client-side usage stats, Tingly Box provides a comprehensive solution for managing AI models and tokens. It supports integration with various IDEs, CLI tools, SDKs, and AI applications, making it versatile and easy to use. The tool also allows seamless integration with OAuth providers like Claude Code, enabling users to utilize existing quotas in OpenAI-compatible tools. Tingly Box aims to simplify AI model management and usage by providing a single endpoint for multiple providers with minimal configuration, promoting seamless integration with SDKs and CLI tools.

Nuxt Editor Template is a Notion-like WYSIWYG editor built with Vue & Nuxt, featuring rich text editing, tables, AI-powered completions, real-time collaboration, and more. It includes features like inline completions, image upload, mentions, emoji picker, and markdown support. Users can deploy their own editor with Vercel and integrate AI assistance for writing. The template also supports Blob storage for image uploads and optional real-time collaboration using Y.js framework with PartyKit.

ORBIT (Open Retrieval-Based Inference Toolkit) is a middleware platform that provides a unified API for AI inference. It acts as a central gateway, allowing you to connect various local and remote AI models with your private data sources like SQL databases, vector stores, and local files. ORBIT uses a flexible adapter architecture to connect your data to AI models, creating specialized 'agents' for specific tasks. It supports scenarios like Knowledge Base Q&A and Chat with Your SQL Database, enabling users to interact with AI models seamlessly. The tool offers a RESTful API for programmatic access and includes features like authentication, API key management, system prompts, health monitoring, and file management. ORBIT is designed to streamline AI inference tasks and facilitate interactions between users and AI models.

CyberStrikeAI is an AI-native security testing platform built in Go that integrates 100+ security tools, an intelligent orchestration engine, role-based testing with predefined security roles, a skills system with specialized testing skills, and comprehensive lifecycle management capabilities. It enables end-to-end automation from conversational commands to vulnerability discovery, attack-chain analysis, knowledge retrieval, and result visualization, delivering an auditable, traceable, and collaborative testing environment for security teams. The platform features an AI decision engine with OpenAI-compatible models, native MCP implementation with various transports, prebuilt tool recipes, large-result pagination, attack-chain graph, password-protected web UI, knowledge base with vector search, vulnerability management, batch task management, role-based testing, and skills system.

Describer is a tool that analyzes codebases using AI to generate architectural overviews, documentation, explanations, bug reports, and more. It scans all files in a directory and uses Google's Gemini AI to provide insights such as markdown architectural overviews, codebase summaries, code pattern analysis, codebase structure documentation, bug identification, and test idea generation. The tool respects .gitignore rules by default but allows users to include/exclude specific files or patterns for analysis.

ChunkHound is a modern tool for transforming your codebase into a searchable knowledge base for AI assistants. It utilizes semantic search via the cAST algorithm and regex search, integrating with AI assistants through the Model Context Protocol (MCP). With features like cAST Algorithm, Multi-Hop Semantic Search, Regex search, and support for 22 languages, ChunkHound offers a local-first approach to code analysis and discovery. It provides intelligent code discovery, universal language support, and real-time indexing capabilities, making it a powerful tool for developers looking to enhance their coding experience.

ChunkHound is a tool that transforms your codebase into a searchable knowledge base for AI assistants using semantic and regex search. It integrates with AI assistants via the Model Context Protocol (MCP) and offers features such as cAST algorithm for semantic code chunking, multi-hop semantic search, natural language queries, regex search without API keys, support for 22 languages, and local-first architecture. It provides intelligent code discovery by following semantic relationships and discovering related implementations. ChunkHound is built on the cAST algorithm from Carnegie Mellon University, ensuring structure-aware chunking that preserves code meaning. It supports universal language parsing and offers efficient updates for large codebases.

ApeRAG is a production-ready platform for Retrieval-Augmented Generation (RAG) that combines Graph RAG, vector search, and full-text search with advanced AI agents. It is ideal for building Knowledge Graphs, Context Engineering, and deploying intelligent AI agents for autonomous search and reasoning across knowledge bases. The platform offers features like advanced index types, intelligent AI agents with MCP support, enhanced Graph RAG with entity normalization, multimodal processing, hybrid retrieval engine, MinerU integration for document parsing, production-grade deployment with Kubernetes, enterprise management features, MCP integration, and developer-friendly tools for customization and contribution.

Env-Doctor is a tool designed to diagnose and fix mismatched CUDA versions between NVIDIA driver, system toolkit, cuDNN, and Python libraries, providing a quick solution to the common frustration in GPU computing. It offers one-command diagnosis, safe install commands, extension library support, AI model compatibility checks, WSL2 GPU support, deep CUDA analysis, container validation, MCP server integration, and CI/CD readiness. The tool helps users identify and resolve environment issues efficiently, ensuring smooth operation of AI libraries on their GPUs.

Distill is a reliability layer for LLM context that provides deterministic deduplication to remove redundancy before reaching the model. It aims to reduce redundant data, lower costs, provide faster responses, and offer more efficient and deterministic results. The tool works by deduplicating, compressing, summarizing, and caching context to ensure reliable outputs. It offers various installation methods, including binary download, Go install, Docker usage, and building from source. Distill can be used for tasks like deduplicating chunks, connecting to vector databases, integrating with AI assistants, analyzing files for duplicates, syncing vectors to Pinecone, querying from the command line, and managing configuration files. The tool supports self-hosting via Docker, Docker Compose, building from source, Fly.io deployment, Render deployment, and Railway integration. Distill also provides monitoring capabilities with Prometheus-compatible metrics, Grafana dashboard, and OpenTelemetry tracing.

A configurable, concurrent, and resumable web crawler written in Go, specifically designed to scrape technical documentation websites, extract core content, convert it cleanly to Markdown format suitable for ingestion by Large Language Models (LLMs), and save the results locally. The tool is built for LLM training and RAG systems, preserving documentation structure, offering production-ready features like resumable crawls and rate limiting, and using Go's concurrency model for efficient parallel processing. It automates the process of gathering and cleaning web-based documentation for use with Large Language Models, providing a dataset that is text-focused, structured, cleaned, and locally accessible.

Deciduous is a decision graph tool for AI-assisted development that helps track and query every decision made during software development. It creates a persistent graph of decisions, goals, and outcomes, allowing users to query past reasoning, see what was tried and rejected, trace outcomes back to goals, and recover context after sessions end. The tool integrates with AI coding assistants and provides a structured way to understand a codebase. It includes features like a Q&A interface, document attachments, multi-user sync, and visualization options for decision graphs.

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.