⚡ supermemoryai/supermemory is making waves. Here's the full picture.

🔗 https://github.com/supermemoryai/supermemory
📝 Memory engine and app that is extremely fast, scalable. The Memory API for the AI era.
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Introducing Supermemory, the revolutionary memory and context engine for AI, designed to transform the way your AI tools learn, remember, and interact with you. This cutting-edge technology allows your AI to remember conversations, extract facts, and build user profiles, all while handling knowledge updates and contradictions with ease.

With Supermemory, you can enjoy a seamless experience, whether you're using AI tools or building your own AI products. The platform offers a single API for developers to integrate memory, RAG, user profiles, and connectors into their agents and apps, making it easy to get started.

Some of the key features of Supermemory include:

* Memory: Extracts facts from conversations and handles temporal changes, contradictions, and automatic forgetting
* User Profiles: Auto-maintained user context, including stable facts and recent activity
* Hybrid Search: Combines RAG and memory in a single query for a more comprehensive search experience
* Connectors: Real-time sync with Google Drive, Gmail, Notion, and other platforms

To get started with Supermemory, you can use the Supermemory App, browser extension, or plugins, which provide a consumer-facing experience and allow you to give your AI persistent memory. For developers, the platform offers a range of framework integrations, including Vercel AI SDK, LangChain, and Mastra, making it easy to integrate Supermemory into your existing workflow.

Don't just take our word for it - Supermemory is state of the art across all major AI memory benchmarks, including LongMemEval, LoCoMo, and ConvoMem. With its powerful features, ease of use, and exceptional performance, Supermemory is the perfect solution for anyone looking to take their AI to the next level. Give your AI the gift of memory and discover a whole new world of possibilities - your AI will thank you!

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🧠 Channel: https://t.me/GithubRe

🚀 Meet harry0703/MoneyPrinterTurbo: a gem from today's GitHub trending list.

🔗 https://github.com/harry0703/MoneyPrinterTurbo
📝 利用AI大模型，一键生成高清短视频 Generate short videos with one click using AI LLM.
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MoneyPrinterTurbo is a fascinating tool that generates high-definition videos with just a theme or keyword. This project offers a range of features, including AI-generated video scripts, batch video generation, and customizable subtitles. The tool supports various video sizes, languages, and voice synthesis options.

The project is built with a clear MVC architecture, making it easy to maintain and extend. It also provides a Web interface and API for easy access.

To get started, users can deploy the project using Docker or manually install the required dependencies. The project also supports various LLM providers, including OpenAI and AIHubMix.

MoneyPrinterTurbo is suitable for developers, content creators, and anyone interested in AI-generated video content.

One-liner takeaway: MoneyPrinterTurbo is a powerful tool that simplifies video content creation with AI-powered automation.

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🧠 Channel: https://t.me/GithubRe

🎯 D4Vinci/Scrapling landed on trending. Worth a proper look.

🔗 https://github.com/D4Vinci/Scrapling
📝 🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!
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The Scrapling framework is designed for effortless web scraping, handling everything from single requests to full-scale crawls. Its key features include adaptive parsing, which learns from website changes, and fetchers that bypass anti-bot systems like Cloudflare Turnstile. The framework also includes a spider framework for scaling up to concurrent, multi-session crawls with pause/resume and automatic proxy rotation.

To use Scrapling, you can start with a simple Fetcher or StealthyFetcher to fetch a website, and then use css selectors to scrape data. For larger crawls, you can define a Spider class and use the start method to begin the crawl.

Some technical highlights of Scrapling include its use of real-time stats and streaming for fast crawls, as well as its support for proxy rotation and anti-bot bypass. The framework is designed for web scrapers and regular users alike, with a simple and intuitive API.

Scrapling is suitable for a wide range of users, from beginner web scrapers to experienced developers. Whether you're looking to scrape a single website or build a large-scale web crawling application, Scrapling has the tools and features you need.

Here's an example of how to use Scrapling:

from scrapling.fetchers import StealthyFetcher
StealthyFetcher.adaptive = True
p = StealthyFetcher.fetch('https://example.com', headless=True, network_idle=True)
products = p.css('.product', auto_save=True)

In short, Scrapling is the ultimate web scraping framework - scrape the web, effortlessly.

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🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into pbakaus/impeccable — fresh off the trending list.

🔗 https://github.com/pbakaus/impeccable
📝 The design language that makes your AI harness better at design.
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The Impeccable project is a curated design skill that elevates your frontend design game with 7 domain-specific references and 23 commands. It helps you avoid common design pitfalls by including 27 deterministic anti-pattern rules. The impeccable skill can be used through a CLI installer, or by downloading from the website, and is compatible with a range of tools such as Cursor, Claude Code, and Codex CLI.

Key features include polish, audit, critique, and distill commands, as well as a standalone CLI for detecting anti-patterns. The project is designed for developers, designers, and anyone looking to improve their design skills.

To get started, simply run

npx impeccable skills install

and access the commands through /impeccable. With Impeccable, you can design like you mean it.

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🧠 Channel: https://t.me/GithubRe

🎯 p-e-w/heretic landed on trending. Worth a proper look.

🔗 https://github.com/p-e-w/heretic
📝 Fully automatic censorship removal for language models
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Heretic is a tool that automatically removes censorship from transformer-based language models. It uses a combination of directional ablation and a TPE-based parameter optimizer powered by Optuna. The approach enables Heretic to work completely automatically, finding high-quality abliteration parameters to produce a decensored model that retains the original model's intelligence.

Key Features:
- Supports most dense models, including multimodal models and MoE architectures
- Automatically decensors models without requiring configuration or understanding of transformer internals
- Provides features for research into model interpretability, including generating plots of residual vectors and printing residual geometry details

Usage:
To use Heretic, prepare a Python 3.10+ environment with PyTorch 2.2+ installed, then run pip install -U heretic-llm and heretic [model_name] to decensor a model.

Technical Highlights:
- Combines advanced directional ablation with TPE-based parameter optimization
- Co-minimizes the number of refusals and KL divergence from the original model
- Supports model quantization with bitsandbytes to reduce VRAM requirements

Audience:
- Researchers and developers working with language models
- Users looking to decensor language models without requiring extensive technical knowledge

Takeaway:
With Heretic, you can automatically decensor language models and unlock their full potential, all without needing to be an expert in transformer internals.

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🧠 Channel: https://t.me/GithubRe

⚡ EveryInc/compound-engineering-plugin is making waves. Here's the full picture.

🔗 https://github.com/EveryInc/compound-engineering-plugin
📝 Official Compound Engineering plugin for Claude Code, Codex, Cursor, and more
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The Compound Engineering Plugin is a game-changer for software development. Its philosophy is to make each unit of engineering work easier than the last, inverting the traditional approach that accumulates technical debt. This plugin provides a set of AI skills and agents that assist in planning, review, and execution, ensuring that knowledge is codified and reusable.

Key features include:

* /ce-brainstorm for interactive Q&A to think through a feature or problem
* /ce-plan to turn feature ideas into detailed implementation plans
* /ce-code-review for multi-agent code review before merging
* /ce-compound to document learnings and make future work easier

To get started, simply install the plugin and run /ce-setup in your project. The plugin currently ships with 37 skills and 51 agents, and is available for various platforms, including Claude Code, Cursor, Codex, and more.

With the Compound Engineering Plugin, you can compound your knowledge and expertise, making each subsequent unit of work easier and more efficient. As the plugin's philosophy states, "a good brainstorm makes the plan sharper, a good plan makes execution smaller, and a good review catches the pattern, not just the bug."
The takeaway: Work smarter, not harder, with the Compound Engineering Plugin.

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🧠 Channel: https://t.me/GithubRe