Saga Reader is an AI-driven think tank-style reader that automatically retrieves information from the internet based on user-specified topics and preferences. It uses cloud or local large models to summarize and provide guidance, and it includes an AI-driven interactive companion reading function, allowing you to discuss and exchange ideas with AI about the content you've read. Saga Reader is completely free and open-source, meaning all data is securely stored on your own computer and is not controlled by third-party service providers. Additionally, you can manage your subscription keywords based on your interests and preferences without being disturbed by advertisements and commercialized content.

Nexent is a powerful tool for analyzing and visualizing network traffic data. It provides comprehensive insights into network behavior, helping users to identify patterns, anomalies, and potential security threats. With its user-friendly interface and advanced features, Nexent is suitable for network administrators, cybersecurity professionals, and anyone looking to gain a deeper understanding of their network infrastructure.

MyDeviceAI is a personal AI assistant app for iPhone that brings the power of artificial intelligence directly to the device. It focuses on privacy, performance, and personalization by running AI models locally and integrating with privacy-focused web services. The app offers seamless user experience, web search integration, advanced reasoning capabilities, personalization features, chat history access, and broad device support. It requires macOS, Xcode, CocoaPods, Node.js, and a React Native development environment for installation. The technical stack includes React Native framework, AI models like Qwen 3 and BGE Small, SearXNG integration, Redux for state management, AsyncStorage for storage, Lucide for UI components, and tools like ESLint and Prettier for code quality.

Plandex is an open source, terminal-based AI coding engine designed for complex tasks. It uses long-running agents to break up large tasks into smaller subtasks, helping users work through backlogs, navigate unfamiliar technologies, and save time on repetitive tasks. Plandex supports various AI models, including OpenAI, Anthropic Claude, Google Gemini, and more. It allows users to manage context efficiently in the terminal, experiment with different approaches using branches, and review changes before applying them. The tool is platform-independent and runs from a single binary with no dependencies.

CORE is an open-source unified, persistent memory layer for all AI tools, allowing developers to maintain context across different tools like Cursor, ChatGPT, and Claude. It aims to solve the issue of context switching and information loss between sessions by creating a knowledge graph that remembers conversations, decisions, and insights. With features like unified memory, temporal knowledge graph, browser extension, chat with memory, auto-sync from apps, and MCP integration hub, CORE provides a seamless experience for managing and recalling context. The tool's ingestion pipeline captures evolving context through normalization, extraction, resolution, and graph integration, resulting in a dynamic memory that grows and changes with the user. When recalling from memory, CORE utilizes search, re-ranking, filtering, and output to provide relevant and contextual answers. Security measures include data encryption, authentication, access control, and vulnerability reporting.

Kollektiv is a Retrieval-Augmented Generation (RAG) system designed to enable users to chat with their favorite documentation easily. It aims to provide LLMs with access to the most up-to-date knowledge, reducing inaccuracies and improving productivity. The system utilizes intelligent web crawling, advanced document processing, vector search, multi-query expansion, smart re-ranking, AI-powered responses, and dynamic system prompts. The technical stack includes Python/FastAPI for backend, Supabase, ChromaDB, and Redis for storage, OpenAI and Anthropic Claude 3.5 Sonnet for AI/ML, and Chainlit for UI. Kollektiv is licensed under a modified version of the Apache License 2.0, allowing free use for non-commercial purposes.

CodeGPT is an extension for JetBrains IDEs that provides access to state-of-the-art large language models (LLMs) for coding assistance. It offers a range of features to enhance the coding experience, including code completions, a ChatGPT-like interface for instant coding advice, commit message generation, reference file support, name suggestions, and offline development support. CodeGPT is designed to keep privacy in mind, ensuring that user data remains secure and private.

Agent Zero is a personal and organic AI framework designed to be dynamic, organically growing, and learning as you use it. It is fully transparent, readable, comprehensible, customizable, and interactive. The framework uses the computer as a tool to accomplish tasks, with no single-purpose tools pre-programmed. It emphasizes multi-agent cooperation, complete customization, and extensibility. Communication is key in this framework, allowing users to give proper system prompts and instructions to achieve desired outcomes. Agent Zero is capable of dangerous actions and should be run in an isolated environment. The framework is prompt-based, highly customizable, and requires a specific environment to run effectively.

Nanobrowser is an open-source AI web automation tool that runs in your browser. It is a free alternative to OpenAI Operator with flexible LLM options and a multi-agent system. Nanobrowser offers premium web automation capabilities while keeping users in complete control, with features like a multi-agent system, interactive side panel, task automation, follow-up questions, and multiple LLM support. Users can easily download and install Nanobrowser as a Chrome extension, configure agent models, and accomplish tasks such as news summary, GitHub research, and shopping research with just a sentence. The tool uses a specialized multi-agent system powered by large language models to understand and execute complex web tasks. Nanobrowser is actively developed with plans to expand LLM support, implement security measures, optimize memory usage, enable session replay, and develop specialized agents for domain-specific tasks. Contributions from the community are welcome to improve Nanobrowser and build the future of web automation.

ProxyAI is an open-source AI copilot for JetBrains, offering advanced code assistance features powered by top-tier language models. Users can customize their coding experience, receive AI-suggested code changes, autocomplete suggestions, and context-aware naming suggestions. The tool also allows users to chat with images, reference project files and folders, web docs, git history, and search the web. ProxyAI prioritizes user privacy by not collecting sensitive information and only gathering anonymous usage data with consent.

Tuff is a local-first, AI-native, and infinitely extensible desktop command center designed to enhance workflow efficiency. It offers a seamless integration of core utilities, AI-powered search, contextual intelligence, and extensibility through custom plugins. With a beautiful UI design, rich functionality, simple operations, and a focus on security and reliability, Tuff provides users with a cross-platform desktop software that is easy to use and offers a good user experience.

TaskingAI brings Firebase's simplicity to **AI-native app development**. The platform enables the creation of GPTs-like multi-tenant applications using a wide range of LLMs from various providers. It features distinct, modular functions such as Inference, Retrieval, Assistant, and Tool, seamlessly integrated to enhance the development process. TaskingAI’s cohesive design ensures an efficient, intelligent, and user-friendly experience in AI application development.

Personal AI assistant/agent in your terminal, with tools for using the terminal, running code, editing files, browsing the web, using vision, and more. A great coding agent that is general-purpose to assist in all kinds of knowledge work, from a simple but powerful CLI. An unconstrained local alternative to ChatGPT with 'Code Interpreter', Cursor Agent, etc. Not limited by lack of software, internet access, timeouts, or privacy concerns if using local models.

An integration for Home Assistant that leverages AI models to understand your unique home environment and propose intelligent automations. By analyzing your entities, devices, areas, and existing automations, the AI Automation Suggester helps you discover new, context-aware use cases you might not have considered, ultimately streamlining your home management and improving efficiency, comfort, and convenience. The tool acts as a personal automation consultant, providing actionable YAML-based automations that can save energy, improve security, enhance comfort, and reduce manual intervention. It turns the complexity of a large Home Assistant environment into actionable insights and tangible benefits.

Qdrant is a vector similarity search engine and vector database. It is written in Rust, which makes it fast and reliable even under high load. Qdrant can be used for a variety of applications, including: * Semantic search * Image search * Product recommendations * Chatbots * Anomaly detection Qdrant offers a variety of features, including: * Payload storage and filtering * Hybrid search with sparse vectors * Vector quantization and on-disk storage * Distributed deployment * Highlighted features such as query planning, payload indexes, SIMD hardware acceleration, async I/O, and write-ahead logging Qdrant is available as a fully managed cloud service or as an open-source software that can be deployed on-premises.

The UltraRAG framework is a researcher and developer-friendly RAG system solution that simplifies the process from data construction to model fine-tuning in domain adaptation. It introduces an automated knowledge adaptation technology system, supporting no-code programming, one-click synthesis and fine-tuning, multidimensional evaluation, and research-friendly exploration work integration. The architecture consists of Frontend, Service, and Backend components, offering flexibility in customization and optimization. Performance evaluation in the legal field shows improved results compared to VanillaRAG, with specific metrics provided. The repository is licensed under Apache-2.0 and encourages citation for support.

AI Summer is a repository focused on providing workshops and resources for developing foundational skills in generative AI models and transformer models. The repository offers practical applications for inferencing and training, with a specific emphasis on understanding and utilizing advanced AI chat models like BingGPT. Participants are encouraged to engage in interactive programming environments, decide on projects to work on, and actively participate in discussions and breakout rooms. The workshops cover topics such as generative AI models, retrieval-augmented generation, building AI solutions, and fine-tuning models. The goal is to equip individuals with the necessary skills to work with AI technologies effectively and securely, both locally and in the cloud.

The Hume AI Python SDK allows users to integrate Hume APIs directly into their Python applications. Users can access complete documentation, quickstart guides, and example notebooks to get started. The SDK is designed to provide support for Hume's expressive communication platform built on scientific research. Users are encouraged to create an account at beta.hume.ai and stay updated on changes through Discord. The SDK may undergo breaking changes to improve tooling and ensure reliable releases in the future.

allAI is a toolbox for AI-related discussions and resources. It provides a platform for sharing knowledge, tutorials, and addressing common AI-related queries. The repository aims to foster a community for AI enthusiasts to engage in meaningful conversations and collaborations. Users can access Quark Cloud for downloads and instructional videos. Additionally, the repository encourages contributions and prohibits the dissemination of spam, advertisements, or unsolicited promotions. The project is supported by Pinokio and offers users the freedom to utilize, modify, and distribute the software within the specified conditions.

This repository documents the journey of integrating AI into frontend development workflow since the AI outbreak, aiming to explore the transformation path for some front-end developers in the AI era. It provides a systematic organization for AI-empowered frontend development, inviting readers to delve into the manual and engage in discussions, exploration, and learning. The repository is released under the CC BY-NC-ND 4.0 license.

Saga Reader is an AI-driven think tank-style reader that automatically retrieves information from the internet based on user-specified topics and preferences. It uses cloud or local large models to summarize and provide guidance, and it includes an AI-driven interactive companion reading function, allowing you to discuss and exchange ideas with AI about the content you've read. Saga Reader is completely free and open-source, meaning all data is securely stored on your own computer and is not controlled by third-party service providers. Additionally, you can manage your subscription keywords based on your interests and preferences without being disturbed by advertisements and commercialized content.

AgentScope is a multi-agent platform designed to empower developers to build multi-agent applications with large-scale models. It features three high-level capabilities: Easy-to-Use, High Robustness, and Actor-Based Distribution. AgentScope provides a list of `ModelWrapper` to support both local model services and third-party model APIs, including OpenAI API, DashScope API, Gemini API, and ollama. It also enables developers to rapidly deploy local model services using libraries such as ollama (CPU inference), Flask + Transformers, Flask + ModelScope, FastChat, and vllm. AgentScope supports various services, including Web Search, Data Query, Retrieval, Code Execution, File Operation, and Text Processing. Example applications include Conversation, Game, and Distribution. AgentScope is released under Apache License 2.0 and welcomes contributions.

LangChain for Swift. Optimized for iOS, macOS, watchOS (part) and visionOS.(beta) This is a pure client library, no server required

MemGPT is a system that intelligently manages different memory tiers in LLMs in order to effectively provide extended context within the LLM's limited context window. For example, MemGPT knows when to push critical information to a vector database and when to retrieve it later in the chat, enabling perpetual conversations. MemGPT can be used to create perpetual chatbots with self-editing memory, chat with your data by talking to your local files or SQL database, and more.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.

This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.