Mohamed Bassem writes about Karakeep, a self-hostable bookmarking application designed for "data hoarders." The app allows users to save links, notes, images, and PDFs with features like automatic metadata fetching, semantic search, LLM-based tagging/summarization (including support for local models via Ollama), and full page archiving. It is built primarily with TypeScript and NextJS, offering cross-platform access through browser extensions, mobile apps, and a web interface.
- Supports local model integration using Ollama for private AI processing
- Includes OCR capabilities to extract text from saved images
- Provides automated video archiving via yt-dlp
- Features full page archival using monolith to prevent link rot
- Supports local model integration using Ollama for private AI processing
- Includes OCR capabilities to extract text from saved images
- Provides automated video archiving via yt-dlp
- Features full page archival using monolith to prevent link rot
Anubhab Banerjee writes that three Qwen2.5-Coder agents of different sizes can share pre-computed token IDs instead of re-tokenizing the same text, using a Google Open Knowledge Format-inspired Markdown+YAML hand-off with an added token_pointer field to /dev/shm, cutting median TTFT by 28% on 3B and 37.8% on 1.5B while avoiding KV-cache sharing.
- Uses /dev/shm/qwen_tokens/ with NumPy .npy int64 arrays for zero-copy hand-off
- Agents run as separate OS processes to release VRAM automatically between models
- Runtime guardrail verifies full ~151,936-entry get_vocab() dict equality across models
- OKF files add non-standard token_pointer and tokenizer_model_id fields for provenance
- Savings apply to input side only; each agent still tokenizes its own output
- Uses /dev/shm/qwen_tokens/ with NumPy .npy int64 arrays for zero-copy hand-off
- Agents run as separate OS processes to release VRAM automatically between models
- Runtime guardrail verifies full ~151,936-entry get_vocab() dict equality across models
- OKF files add non-standard token_pointer and tokenizer_model_id fields for provenance
- Savings apply to input side only; each agent still tokenizes its own output
A self-hosted tool designed to manage personal or team link collections using a version-controlled YAML file. The application serves these links as a clean, searchable web page without the need for a database.
- YAML-driven configuration for easy human-readable management
- Support for grouped links and named sections
- Client-side live search functionality
- Docker-ready deployment via official images
- Responsive design optimized for mobile and desktop
- High accessibility with a 100% Lighthouse score
- Lightweight architecture built on Flask and Tailwind CSS
- YAML-driven configuration for easy human-readable management
- Support for grouped links and named sections
- Client-side live search functionality
- Docker-ready deployment via official images
- Responsive design optimized for mobile and desktop
- High accessibility with a 100% Lighthouse score
- Lightweight architecture built on Flask and Tailwind CSS
Cloudflare is now returning RFC 9457-compliant structured Markdown and JSON error payloads to AI agents, replacing verbose HTML error pages with machine-readable instructions. This significantly reduces payload size and token usage – by over 98% in measured tests – which is crucial for cost-effective AI agent operation. The new responses include actionable guidance, allowing agents to understand *why* an error occurred and *how* to proceed, whether that means retrying with backoff, escalating the issue, or stopping altogether.
This is a network-wide change, automatically available without any site owner configuration.
- `Accept: text/markdown` returns a yaml header and human readable markdown
- `Accept: application/json` returns JSON
- `Accept: application/problem+json` returns JSON with the `application/problem+json` content type.
This is a network-wide change, automatically available without any site owner configuration.
- `Accept: text/markdown` returns a yaml header and human readable markdown
- `Accept: application/json` returns JSON
- `Accept: application/problem+json` returns JSON with the `application/problem+json` content type.
Plural is bringing AI into the DevOps lifecycle with a new release that leverages a unified GitOps platform as a RAG engine. This provides AI-powered troubleshooting, natural language infrastructure querying, autonomous upgrade assistance, and agentic workflows for infrastructure modification, all with enterprise-grade guardrails.
This GitHub repository contains a directory named 'examples' within the 'gpt-5-coding-examples' project. It lists numerous YAML files, likely representing coding examples or configurations for GPT-5 applications. The initial commit was made on August 7, 2025.
The article discusses the potential shift away from YAML in Kubernetes 2.0, citing a leaked dashboard photo and the high percentage of production outages linked to YAML misconfigurations. It suggests a new command-line interface is being used for deployments.
A library for working with prompt templates locally or on the Hugging Face Hub. It aims to provide a standardized way of sharing and using prompt templates, with a focus on interoperability and modularity.
yq is a command-line tool that processes YAML, XML, and TOML files by converting them to JSON and using jq for further processing. It supports various options for preserving YAML tags and styles, and can be used as a module for in-place edits.
The article discusses the use of jq, xq, and yq tools for processing JSON, XML, and YAML data from the command line. It includes examples of how to use these tools to extract and manipulate data, as well as converting GPX files to CSV format.
