Github Top Repositories

⚡ TencentCloud/TencentDB-Agent-Memory is making waves. Here's the full picture. 🔗 https://github.com/TencentCloud/TencentDB-Agent-Memory 📝 TencentDB Agent Memory is a team-level memory hub for AI Agents — turning conversations, docs, and code into four reusable memory assets (Chat Memory, Skill, LLM-Wiki, Code-Graph) that are governed, shared, and equipped across agents and frameworks. ────────────────────────────── The TencentDB Agent Memory is a powerful tool designed to enhance the memory capabilities of AI agents. Its primary purpose is to help agents learn from workflows, retain task context, and reuse past experiences, thereby sparing humans from repetitive tasks. The key features of this tool include symbolic short-term memory and layered long-term memory, which enable agents to condense heavy tool logs into compact symbols and distill fragmented conversations into structured personas and scenes. From a technical standpoint, the tool employs a heterogeneous storage strategy and progressive disclosure, allowing for robust full-text retrieval and high information density. The Mermaid symbol graph is used to encode task state transitions, providing a concise and readable format for both humans and LLMs. To get started with the TencentDB Agent Memory, users can follow the Quick Start guide, which provides instructions for installing the plugin, enabling zero-config, and applying runtime patches. The tool supports both OpenClaw and Hermes agents, making it a versatile solution for various deployment scenarios. The target audience for this tool includes developers, researchers, and professionals working with AI agents and seeking to improve their memory and performance. With the TencentDB Agent Memory, users can unlock the full potential of their AI agents and focus on high-level tasks that require human judgment and creativity. In summary, the TencentDB Agent Memory is a game-changing tool that revolutionizes the way AI agents learn, remember, and interact with their environment. By leveraging its powerful features and capabilities, users can supercharge their AI agents and achieve unprecedented levels of productivity and efficiency: let the agents remember, so humans can innovate. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into jamiepine/voicebox — fresh off the trending list. 🔗 https://github.com/jamiepine/voicebox 📝 The open-source AI voice studio. Clone, dictate, create. ────────────────────────────── Voicebox is an open-source AI voice studio that allows you to clone any voice, generate speech, dictate into any app, and talk to agents in voices you own. This local-first app offers complete privacy, as models, voice data, and captures never leave your machine. Key features include: - 7 TTS engines with different strengths - voice cloning and preset voices from a reference sample or 50+ curated preset voices - 23 languages supported, from English to Arabic, Japanese, Hindi, and more - post-processing effects like pitch shift, reverb, delay, and filters - unlimited length with auto-chunking and crossfade for scripts, articles, and chapters Voicebox is designed for anyone looking for a free and open-source alternative to cloud-based voice solutions, with a focus on privacy, customization, and control. The app is API-first, with a built-in MCP server for integrating voice I/O into your own apps and agents. It also features native performance, built with Tauri (Rust), and runs on multiple platforms, including macOS, Windows, Linux, and Docker. In short, Voicebox gives you the power to take control of your voice, with endless possibilities: You can clone, create, and converse - all in the voice you want! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 usekaneo/kaneo is trending — and it deserves your attention. 🔗 https://github.com/usekaneo/kaneo 📝 🎯 All you need. Nothing you don't. Open source project management that works for you, not against you. ────────────────────────────── Kaneo is a project management platform designed to be simple, fast, and self-hosted. Its purpose is to help teams focus on building great products without unnecessary distractions. Key features include a clean interface, self-hosted option for data control, and open-source code with a permissive MIT license. To get started, you can use the drim CLI tool for a one-click deployment or set up Kaneo with Docker Compose. For development, follow the Environment Setup Guide and configure environment variables. Kaneo is suitable for teams and individuals looking for a minimalistic yet effective project management tool. The platform is highly customizable and has a growing community of users and contributors. Technical highlights include a comprehensive Helm chart for Kubernetes deployment and support for PostgreSQL. In short, Kaneo is perfect for those who want to keep it simple and get work done - it's a tool that stays out of your way. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🔍 Deep-diving into livekit/agents — fresh off the trending list. 🔗 https://github.com/livekit/agents 📝 A framework for building realtime voice AI agents 🤖🎙️📹 ────────────────────────────── The livekit/agents GitHub repository provides a framework for building real-time, programmable voice agents that can see, hear, and understand. The key features of this framework include flexible integrations with various STT, LLM, TTS, and Realtime APIs, integrated job scheduling with dispatch APIs, and extensive WebRTC clients for building client applications. To use this framework, you can install the core Agents library using pip install "livekit-agents[openai,deepgram,cartesia]". The framework also includes a builtin test framework to ensure your agent is performing as expected. The target audience for this repository includes developers and data scientists who want to build conversational, multi-modal voice agents. With this framework, you can create complex voice agents that can handle various tasks, such as multi-user push to talk, background audio, and dynamic tool creation. In summary, the livekit/agents repository provides a powerful framework for building real-time voice agents, and with its flexible integrations and extensive features, it's an ideal choice for developers who want to create innovative voice-based applications - build your voice agent and give your users a voice. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 iv-org/invidious is trending — and it deserves your attention. 🔗 https://github.com/iv-org/invidious 📝 Invidious is an alternative front-end to YouTube ────────────────────────────── Invidious is an open source alternative front-end to YouTube, offering a lightweight and ad-free experience. With no tracking and no JavaScript required, it provides a unique way to watch YouTube videos. Key features include customizable homepage, subscriptions independent from Google, and notifications for all subscribed channels. Technical highlights include an embedded video support, a developer API, and the fact that it does not use official YouTube APIs. To get started, you can select a public instance or host Invidious yourself. The project is suitable for anyone looking for a private and ad-free YouTube experience. You can contribute to the code or help with translations. Invidious is the perfect alternative to YouTube - take back control of your video watching experience! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 Alishahryar1/free-claude-code landed on trending. Worth a proper look. 🔗 https://github.com/Alishahryar1/free-claude-code 📝 Use Claude Code, Codex and Pi for free from your terminal, app, IDE, or phone like OpenClaw (voice supported) ────────────────────────────── Get started with Free Claude Code, a powerful tool that lets you use Claude Code, Codex, Pi, or their IDE extensions through your own provider-backed proxy. This project offers a flexible and customizable way to work with various coding agents and models. Key features include: - Running coding agents with free, paid, or local models - Choosing and validating providers from a local Admin UI - Supporting 31 cloud and local providers - Using each coding agent's native model picker - Optional token authentication for the local proxy To get started, simply install or update Free Claude Code using the provided scripts, then start the server and configure your preferred provider in the Admin UI. The project is built with Python 3.14 and uses various tools like uv, Pytest, Ty, Ruff, and Loguru. Whether you're a developer, researcher, or enthusiast, Free Claude Code offers a user-friendly and extensible platform for exploring the world of coding agents and AI models. One-liner takeaway: With Free Claude Code, you can unleash the full potential of coding agents and AI models, all from the comfort of your own customizable proxy. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 Panniantong/Agent-Reach is trending — and it deserves your attention. 🔗 https://github.com/Panniantong/Agent-Reach 📝 Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees. ────────────────────────────── Agent Reach 是一个能力层，让你的 AI Agent 能够访问互联网。它可以帮助你的 Agent 读取网页、搜索推特、看 YouTube 视频、刷小红书 等。只需告诉你的 Agent "帮我安装 Agent Reach"，它就会自己完成安装和配置。 主要特点： * 零配置：安装后无需任何配置，即可使用 * 支持多平台：包括网页、YouTube、Twitter、Reddit、Facebook、Instagram 等 * 安全：Cookie 和 Token 只存储在本地，且支持安全模式 * 开源：完全开源，欢迎社区贡献 使用方法： 1. 告诉你的 Agent "帮我安装 Agent Reach" 2. 等待安装和配置完成 3. 即可使用 Agent Reach 的功能 注意：需要登录的平台（如 Twitter、小红书）需要配置 Cookie 或登录态。 One-liner takeaway: Agent Reach gives your AI Agent internet superpowers with zero configuration and top-notch security. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 shiyu-coder/Kronos caught my eye on GitHub Trending today. 🔗 https://github.com/shiyu-coder/Kronos 📝 Kronos: A Foundation Model for the Language of Financial Markets ────────────────────────────── Kronos is the first open-source foundation model for financial candlesticks, trained on data from over 45 global exchanges. It's a decoder-only model, designed to handle the unique characteristics of financial data. Key features include a novel two-stage framework, with a specialized tokenizer and a large autoregressive Transformer. To get started, you can install the dependencies with pip install -r requirements.txt, then load a pre-trained model and tokenizer from the Hugging Face Hub. The KronosPredictor class simplifies forecasting, handling data preprocessing, normalization, and prediction. Technical highlights include a family of pre-trained models with varying capacities, a live demo for visualizing forecasting results, and a model zoo with readily accessible models. The model is designed for diverse quantitative tasks, such as forecasting and backtesting. The target audience includes quantitative analysts, traders, and researchers interested in applying AI to financial markets. With Kronos, you can unlock new insights and make more informed investment decisions. Kronos is a game-changer: forecast your financial future with precision and ease! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: antirez/ds4 — let's break it down. 🔗 https://github.com/antirez/ds4 📝 DeepSeek 4 Flash and PRO local inference engine for Metal, CUDA and ROCm ────────────────────────────── DwarfStar is a native inference engine optimized for DeepSeek V4 Flash and also supporting GLM 5.2 and DeepSeek V4 PRO on high-memory machines. It's designed to be self-contained and narrow in scope, not a general-purpose GGUF runner. The engine includes tools and data for GGUF, imatrix, quality, and speed. The project supports multiple backends: Metal on Macs, NVIDIA CUDA including multi-GPU systems, and ROCm on Strix Halo systems. It's capable of running on consumer hardware, like MacBooks, and can also be used to turn servers into multi-user LLM servers with good results. Some of the key features include: - Running capable models on consumer hardware - Turning old servers into multi-user LLM servers - Supporting pipeline parallelism to glue multiple systems together - Experimental DSpark speculative decoding for faster generation The project is still in the beta stage and is very fast-changing, so instabilities are possible. The code is developed with strong assistance from AI, including GPT 5.5, 5.6, and Claude Fable, and is not suitable for those who are not comfortable with AI-developed code. In summary: DwarfStar is an optimized inference engine for select models, with a focus on speed and efficiency, making it a great tool for those looking to run capable models on consumer hardware - you can now run a super-smart AI model on your MacBook! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet donnemartin/system-design-primer: a gem from today's GitHub trending list. 🔗 https://github.com/donnemartin/system-design-primer 📝 Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards. ────────────────────────────── The System Design Primer is a comprehensive GitHub repository designed to help you learn how to build systems at scale. Its primary purpose is to provide an organized collection of resources, including system design topics, interview questions, and study guides, to aid in becoming a better engineer. The repository offers key features such as Anki flashcard decks for retaining key system design concepts, interactive coding challenges, and a vast array of system design topics, including performance, scalability, latency, and availability. To use this repository, you can start by reviewing the system design topics, practicing with interview questions, and utilizing the provided resources to improve your understanding of system design. From a technical standpoint, the repository covers a wide range of topics, including load balancers, reverse proxies, databases, caching, and security. It also provides information on communication protocols, such as TCP and UDP, and design patterns, such as microservices and service discovery. The repository is suitable for a broad audience, including software engineers, system architects, and anyone interested in learning about system design. Whether you're preparing for a system design interview or simply looking to improve your skills, the System Design Primer is an invaluable resource. In summary, the System Design Primer is a treasure trove of system design knowledge, and its contributions are welcome from the open-source community. So, dive in and explore the repository to take your system design skills to the next level: designing scalable systems is not just about handling traffic, it's about creating a better user experience. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 microsoft/generative-ai-for-beginners just hit the trending charts — here's why it matters. 🔗 https://github.com/microsoft/generative-ai-for-beginners 📝 21 Lessons, Get Started Building with Generative AI ────────────────────────────── Get started with Generative AI using the microsoft/generative-ai-for-beginners GitHub repository. This comprehensive course offers 21 lessons to teach you the fundamentals of building Generative AI applications. The course covers topics such as Introduction to Generative AI and LLMs, Exploring and comparing different LLMs, Using Generative AI Responsibly, and Understanding Prompt Engineering Fundamentals. You'll learn through a combination of video introductions, written lessons, and Python and TypeScript code samples. To get started, you'll need basic knowledge of Python or TypeScript and a Github account to fork the repository. You can use either Azure OpenAI Service, Microsoft Foundry Models, OpenAI API, or Foundry Local to run the code. The course is multi-language supported with translations available in over 50 languages. Join the Microsoft Foundry Discord server to meet other learners and get support. In summary, this course is perfect for beginners and experienced developers alike, providing a comprehensive introduction to Generative AI and hands-on experience with building applications. Dive in and start building your Generative AI skills today! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe