Build your own conversation-based search with AI, a simple implementation with Node.js & Vue3. Live Demo Features: * Built-in support for LLM: OpenAI, Google, Lepton, Ollama(Free) * Built-in support for search engine: Bing, Sogou, Google, SearXNG(Free) * Customizable pretty UI interface * Support dark mode * Support mobile display * Support local LLM with Ollama * Support i18n * Support Continue Q&A with contexts.

This project implements a web API that offers a unified interface to Google Gemini and Claude 3. It provides a self-hosted, lightweight, and scalable solution for accessing these AI models through a streaming API. The API supports both Claude and Gemini models, allowing users to interact with them in real-time. The project includes a user-friendly web UI for configuration and documentation, making it easy to get started and explore the capabilities of the API.

The docs-mcp-server repository contains the server-side code for the documentation management system. It provides functionalities for managing, storing, and retrieving documentation files. Users can upload, update, and delete documents through the server. The server also supports user authentication and authorization to ensure secure access to the documentation system. Additionally, the server includes APIs for integrating with other systems and tools, making it a versatile solution for managing documentation in various projects and organizations.

Zotero MCP seamlessly connects your Zotero research library with AI assistants like ChatGPT and Claude via the Model Context Protocol. It offers AI-powered semantic search, access to library content, PDF annotation extraction, and easy updates. Users can search their library, analyze citations, and get summaries, making it ideal for research tasks. The tool supports multiple embedding models, intelligent search results, and flexible access methods for both local and remote collaboration. With advanced features like semantic search and PDF annotation extraction, Zotero MCP enhances research efficiency and organization.

LEANN is an innovative vector database that democratizes personal AI, transforming your laptop into a powerful RAG system that can index and search through millions of documents using 97% less storage than traditional solutions without accuracy loss. It achieves this through graph-based selective recomputation and high-degree preserving pruning, computing embeddings on-demand instead of storing them all. LEANN allows semantic search of file system, emails, browser history, chat history, codebase, or external knowledge bases on your laptop with zero cloud costs and complete privacy. It is a drop-in semantic search MCP service fully compatible with Claude Code, enabling intelligent retrieval without changing your workflow.

The ComfyUI Web Viewer by vrch.ai is a real-time AI-generated interactive art framework that integrates realtime streaming into ComfyUI workflows. It supports keyboard control nodes, OSC control nodes, sound input nodes, and more, accessible from any device with a web browser. It enables real-time interaction with AI-generated content, ideal for interactive visual projects and enhancing ComfyUI workflows with efficient content management and display.

TunaCode CLI is an AI-powered coding assistant that provides a command-line interface for developers to enhance their coding experience. It offers features like model selection, parallel execution for faster file operations, and various commands for code management. The tool aims to improve coding efficiency and provide a seamless coding environment for developers.

Probe is an AI-friendly, fully local, semantic code search tool designed to power the next generation of AI coding assistants. It combines the speed of ripgrep with the code-aware parsing of tree-sitter to deliver precise results with complete code blocks, making it perfect for large codebases and AI-driven development workflows. Probe supports various features like AI-friendly code extraction, fully local operation without external APIs, fast scanning of large codebases, accurate code structure parsing, re-rankers and NLP methods for better search results, multi-language support, interactive AI chat mode, and flexibility to run as a CLI tool, MCP server, or interactive AI chat.

CodeRAG is an AI-powered code retrieval and assistance tool that combines Retrieval-Augmented Generation (RAG) with AI to provide intelligent coding assistance. It indexes your entire codebase for contextual suggestions based on your complete project, offering real-time indexing, semantic code search, and contextual AI responses. The tool monitors your code directory, generates embeddings for Python files, stores them in a FAISS vector database, matches user queries against the code database, and sends retrieved code context to GPT models for intelligent responses. CodeRAG also features a Streamlit web interface with a chat-like experience for easy usage.

Zero is an open-source AI email solution that allows users to self-host their email app while integrating external services like Gmail. It aims to modernize and enhance emails through AI agents, offering features like open-source transparency, AI-driven enhancements, data privacy, self-hosting freedom, unified inbox, customizable UI, and developer-friendly extensibility. Built with modern technologies, Zero provides a reliable tech stack including Next.js, React, TypeScript, TailwindCSS, Node.js, Drizzle ORM, and PostgreSQL. Users can set up Zero using standard setup or Dev Container setup for VS Code users, with detailed environment setup instructions for Better Auth, Google OAuth, and optional GitHub OAuth. Database setup involves starting a local PostgreSQL instance, setting up database connection, and executing database commands for dependencies, tables, migrations, and content viewing.

Dexto is a lightweight runtime for creating and running AI agents that turn natural language into real-world actions. It serves as the missing intelligence layer for building AI applications, standalone chatbots, or as the reasoning engine inside larger products. Dexto features a powerful CLI and Web UI for running AI agents, supports multiple interfaces, allows hot-swapping of LLMs from various providers, connects to remote tool servers via the Model Context Protocol, is config-driven with version-controlled YAML, offers production-ready core features, extensibility for custom services, and enables multi-agent collaboration via MCP and A2A.

Gemini Coder is a free 2M context AI coding assistant that allows users to conveniently copy folders and files for chatbots. It provides FIM completions, file refactoring, and AI-suggested changes. The extension is versatile, private, and lightweight, offering unmatched accuracy, speed, and cost in AI assistance. Users have full control over the context and coding conventions included, ensuring high performance and signal to noise ratio. Gemini Coder supports various chatbots and provides quick start guides for chat and FIM completions. It also offers commands for FIM completions, refactoring, applying changes, chat, and context copying. Users can set up custom model providers for API features and contribute to the project through pull requests or discussions. The tool is licensed under the MIT License.

PentAGI is an innovative tool for automated security testing that leverages cutting-edge artificial intelligence technologies. It is designed for information security professionals, researchers, and enthusiasts who need a powerful and flexible solution for conducting penetration tests. The tool provides secure and isolated operations in a sandboxed Docker environment, fully autonomous AI-powered agent for penetration testing steps, a suite of 20+ professional security tools, smart memory system for storing research results, web intelligence for gathering information, integration with external search systems, team delegation system, comprehensive monitoring and reporting, modern interface, API integration, persistent storage, scalable architecture, self-hosted solution, flexible authentication, and quick deployment through Docker Compose.

Eliza is a versatile AI agent operating system designed to support various models and connectors, enabling users to create chatbots, autonomous agents, handle business processes, create video game NPCs, and engage in trading. It offers multi-agent and room support, document ingestion and interaction, retrievable memory and document store, and extensibility to create custom actions and clients. Eliza is easy to use and provides a comprehensive solution for AI agent development.

Fast MCP is a Ruby gem that simplifies the integration of AI models with your Ruby applications. It provides a clean implementation of the Model Context Protocol, eliminating complex communication protocols, integration challenges, and compatibility issues. With Fast MCP, you can easily connect AI models to your servers, share data resources, choose from multiple transports, integrate with frameworks like Rails and Sinatra, and secure your AI-powered endpoints. The gem also offers real-time updates and authentication support, making AI integration a seamless experience for developers.

WebUI is a user-friendly tool built on Gradio that enhances website accessibility for AI agents. It supports various Large Language Models (LLMs) and allows custom browser integration for seamless interaction. The tool eliminates the need for re-login and authentication challenges, offering high-definition screen recording capabilities.

This sample shows how to build a serverless chat experience with Retrieval-Augmented Generation using LangChain.js and Azure. The application is hosted on Azure Static Web Apps and Azure Functions, with Azure Cosmos DB for MongoDB vCore as the vector database. You can use it as a starting point for building more complex AI applications.

ChatGPT Telegram Bot is a Telegram bot that provides a smooth AI experience. It supports both Azure OpenAI and native OpenAI, and offers real-time (streaming) response to AI, with a faster and smoother experience. The bot also has 15 preset bot identities that can be quickly switched, and supports custom bot identities to meet personalized needs. Additionally, it supports clearing the contents of the chat with a single click, and restarting the conversation at any time. The bot also supports native Telegram bot button support, making it easy and intuitive to implement required functions. User level division is also supported, with different levels enjoying different single session token numbers, context numbers, and session frequencies. The bot supports English and Chinese on UI, and is containerized for easy deployment.

SuperSonic is a next-generation BI platform that integrates Chat BI (powered by LLM) and Headless BI (powered by semantic layer) paradigms. This integration ensures that Chat BI has access to the same curated and governed semantic data models as traditional BI. Furthermore, the implementation of both paradigms benefits from the integration: * Chat BI's Text2SQL gets augmented with context-retrieval from semantic models. * Headless BI's query interface gets extended with natural language API. SuperSonic provides a Chat BI interface that empowers users to query data using natural language and visualize the results with suitable charts. To enable such experience, the only thing necessary is to build logical semantic models (definition of metric/dimension/tag, along with their meaning and relationships) through a Headless BI interface. Meanwhile, SuperSonic is designed to be extensible and composable, allowing custom implementations to be added and configured with Java SPI. The integration of Chat BI and Headless BI has the potential to enhance the Text2SQL generation in two dimensions: 1. Incorporate data semantics (such as business terms, column values, etc.) into the prompt, enabling LLM to better understand the semantics and reduce hallucination. 2. Offload the generation of advanced SQL syntax (such as join, formula, etc.) from LLM to the semantic layer to reduce complexity. With these ideas in mind, we develop SuperSonic as a practical reference implementation and use it to power our real-world products. Additionally, to facilitate further development we decide to open source SuperSonic as an extensible framework.

ChatOllama is an open-source chatbot based on LLMs (Large Language Models). It supports a wide range of language models, including Ollama served models, OpenAI, Azure OpenAI, and Anthropic. ChatOllama supports multiple types of chat, including free chat with LLMs and chat with LLMs based on a knowledge base. Key features of ChatOllama include Ollama models management, knowledge bases management, chat, and commercial LLMs API keys management.

ChatIDE is an AI assistant that integrates with your IDE, allowing you to converse with OpenAI's ChatGPT or Anthropic's Claude within your development environment. It provides a seamless way to access AI-powered assistance while coding, enabling you to get real-time help, generate code snippets, debug errors, and brainstorm ideas without leaving your IDE.

This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access the ChatGPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval.

xiaogpt is a tool that allows you to play ChatGPT and other LLMs with Xiaomi AI Speaker. It supports ChatGPT, New Bing, ChatGLM, Gemini, Doubao, and Tongyi Qianwen. You can use it to ask questions, get answers, and have conversations with AI assistants. xiaogpt is easy to use and can be set up in a few minutes. It is a great way to experience the power of AI and have fun with your Xiaomi AI Speaker.

GoogleGPT is a browser extension that brings the power of ChatGPT to Google Search. With GoogleGPT, you can ask ChatGPT questions and get answers directly in your search results. You can also use GoogleGPT to generate text, translate languages, and more. GoogleGPT is compatible with all major browsers, including Chrome, Firefox, Edge, and Safari.

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.

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.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.