Air-gapped Virtual Assistant / Personal Language Server

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.

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.

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.

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.

CortexON is an open-source, multi-agent AI system designed to automate and simplify everyday tasks. It integrates specialized agents like Web Agent, File Agent, Coder Agent, Executor Agent, and API Agent to accomplish user-defined objectives. CortexON excels at executing complex workflows, research tasks, technical operations, and business process automations by dynamically coordinating the agents' unique capabilities. It offers advanced research automation, multi-agent orchestration, integration with third-party APIs, code generation and execution, efficient file and data management, and personalized task execution for travel planning, market analysis, educational content creation, and business intelligence.

An AI-powered code documentation generator that automatically analyzes repositories and creates comprehensive documentation using advanced language models. The system employs a multi-agent architecture to perform specialized code analysis and generate structured documentation.

SystemSculpt AI is a comprehensive AI-powered plugin for Obsidian, integrating advanced AI capabilities into note-taking, task management, knowledge organization, and content creation. It offers modules for brain integration, chat conversations, audio recording and transcription, note templates, and task generation and management. Users can customize settings, utilize AI services like OpenAI and Groq, and access documentation for detailed guidance. The plugin prioritizes data privacy by storing sensitive information locally and offering the option to use local AI models for enhanced privacy.

This is an ideal Comfyui translation plugin that allows any long text input box in Comfyui to support Chinese input and automatic translation (using Baidu translation). It also includes error correction translation feature and keyword polishing feature for generating professional AI drawing prompts (using Zhipu AI big model). Additionally, it provides a one-click fix feature for correcting model references in workflows, greatly improving workflow model call correction efficiency (based on model name matching). The plugin requires Baidu translation API key for translation functionality and Zhipu AI API key for keyword polishing functionality. After installation, users can enable automatic translation mode and keyword polishing feature by double-clicking any long text input box in Comfyui.

AI Flow is an open-source, user-friendly UI application that empowers you to seamlessly connect multiple AI models together, specifically leveraging the capabilities of multiples AI APIs such as OpenAI, StabilityAI and Replicate. In a nutshell, AI Flow provides a visual platform for crafting and managing AI-driven workflows, thereby facilitating diverse and dynamic AI interactions.

Kelivo is a Flutter LLM Chat Client with modern design, dark mode, multi-language support, multi-provider support, custom assistants, multimodal input, markdown rendering, voice functionality, MCP support, web search integration, prompt variables, QR code sharing, data backup, and custom requests. It is built with Flutter and Dart, utilizes Provider for state management, Hive for local data storage, and supports dynamic theming and Markdown rendering. Kelivo is a versatile tool for creating and managing personalized AI assistants, supporting various input formats, and integrating with multiple search engines and AI providers.

ComfyUI-fal-API is a repository containing custom nodes for using Flux models with fal API in ComfyUI. It provides nodes for image generation, video generation, language models, and vision language models. Users can easily install and configure the repository to access various nodes for different tasks such as generating images, creating videos, processing text, and understanding images. The repository also includes troubleshooting steps and is licensed under the Apache License 2.0.

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.

PPTist is a web-based presentation application that replicates most features of Microsoft Office PowerPoint. It supports various elements like text, images, shapes, charts, tables, videos, audio, and formulas. Users can edit and present slides directly in a web browser. It offers easy development with Vue 3.x and TypeScript, user-friendly experience with context menu and keyboard shortcuts, and feature-rich functionalities including AI-generated PPTs and mobile editing. PPTist aims to provide a desktop application-level experience for creating presentations.

Pyloid is a Python backend version of Electron and Tauri, simplifying desktop application development. Built on QtWebEngine and PySide6, it offers seamless integration with Python features, enabling easy creation of powerful applications. It provides web-based GUI generation, system tray icon support, multi-window management, bridge API between Python and JavaScript, single/multi-instance application support, comprehensive desktop app features, clean code structure, live UI development experience, cross-platform support, integration with frontend libraries, window customization, direct utilization of PySide6 features, and detailed Numpy-style docstrings.

VeritasGraph is an enterprise-grade graph RAG framework designed for secure, on-premise AI applications. It leverages a knowledge graph to perform complex, multi-hop reasoning, providing transparent, auditable reasoning paths with full source attribution. The framework excels at answering complex questions that traditional vector search engines struggle with, ensuring trust and reliability in enterprise AI. VeritasGraph offers full control over data and AI models, verifiable attribution for every claim, advanced graph reasoning capabilities, and open-source deployment with sovereignty and customization.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

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.

ONNX Runtime Generative AI is a library that provides the generative AI loop for ONNX models, including inference with ONNX Runtime, logits processing, search and sampling, and KV cache management. Users can call a high level `generate()` method, or run each iteration of the model in a loop. It supports greedy/beam search and TopP, TopK sampling to generate token sequences, has built in logits processing like repetition penalties, and allows for easy custom scoring.

Jupyter AI connects generative AI with Jupyter notebooks. It provides a user-friendly and powerful way to explore generative AI models in notebooks and improve your productivity in JupyterLab and the Jupyter Notebook. Specifically, Jupyter AI offers: * An `%%ai` magic that turns the Jupyter notebook into a reproducible generative AI playground. This works anywhere the IPython kernel runs (JupyterLab, Jupyter Notebook, Google Colab, Kaggle, VSCode, etc.). * A native chat UI in JupyterLab that enables you to work with generative AI as a conversational assistant. * Support for a wide range of generative model providers, including AI21, Anthropic, AWS, Cohere, Gemini, Hugging Face, NVIDIA, and OpenAI. * Local model support through GPT4All, enabling use of generative AI models on consumer grade machines with ease and privacy.

Khoj is an open-source, personal AI assistant that extends your capabilities by creating always-available AI agents. You can share your notes and documents to extend your digital brain, and your AI agents have access to the internet, allowing you to incorporate real-time information. Khoj is accessible on Desktop, Emacs, Obsidian, Web, and Whatsapp, and you can share PDF, markdown, org-mode, notion files, and GitHub repositories. You'll get fast, accurate semantic search on top of your docs, and your agents can create deeply personal images and understand your speech. Khoj is self-hostable and always will be.

LangChain.dart is a Dart port of the popular LangChain Python framework created by Harrison Chase. LangChain provides a set of ready-to-use components for working with language models and a standard interface for chaining them together to formulate more advanced use cases (e.g. chatbots, Q&A with RAG, agents, summarization, extraction, etc.). The components can be grouped into a few core modules: * **Model I/O:** LangChain offers a unified API for interacting with various LLM providers (e.g. OpenAI, Google, Mistral, Ollama, etc.), allowing developers to switch between them with ease. Additionally, it provides tools for managing model inputs (prompt templates and example selectors) and parsing the resulting model outputs (output parsers). * **Retrieval:** assists in loading user data (via document loaders), transforming it (with text splitters), extracting its meaning (using embedding models), storing (in vector stores) and retrieving it (through retrievers) so that it can be used to ground the model's responses (i.e. Retrieval-Augmented Generation or RAG). * **Agents:** "bots" that leverage LLMs to make informed decisions about which available tools (such as web search, calculators, database lookup, etc.) to use to accomplish the designated task. The different components can be composed together using the LangChain Expression Language (LCEL).

Danswer is an open-source Gen-AI Chat and Unified Search tool that connects to your company's docs, apps, and people. It provides a Chat interface and plugs into any LLM of your choice. Danswer can be deployed anywhere and for any scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your own control. Danswer is MIT licensed and designed to be modular and easily extensible. The system also comes fully ready for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for configuring Personas (AI Assistants) and their Prompts. Danswer also serves as a Unified Search across all common workplace tools such as Slack, Google Drive, Confluence, etc. By combining LLMs and team specific knowledge, Danswer becomes a subject matter expert for the team. Imagine ChatGPT if it had access to your team's unique knowledge! It enables questions such as "A customer wants feature X, is this already supported?" or "Where's the pull request for feature Y?"

Infinity is an AI-native database designed for LLM applications, providing incredibly fast full-text and vector search capabilities. It supports a wide range of data types, including vectors, full-text, and structured data, and offers a fused search feature that combines multiple embeddings and full text. Infinity is easy to use, with an intuitive Python API and a single-binary architecture that simplifies deployment. It achieves high performance, with 0.1 milliseconds query latency on million-scale vector datasets and up to 15K QPS.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

AgentCloud is an open-source platform that enables companies to build and deploy private LLM chat apps, empowering teams to securely interact with their data. It comprises three main components: Agent Backend, Webapp, and Vector Proxy. To run this project locally, clone the repository, install Docker, and start the services. The project is licensed under the GNU Affero General Public License, version 3 only. Contributions and feedback are welcome from the community.

This framework generates fuzz targets for real-world `C`/`C++` projects with various Large Language Models (LLM) and benchmarks them via the `OSS-Fuzz` platform. It manages to successfully leverage LLMs to generate valid fuzz targets (which generate non-zero coverage increase) for 160 C/C++ projects. The maximum line coverage increase is 29% from the existing human-written targets.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.