<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Python on Noureddine RAMDI</title><link>https://ramdi.fr/tags/python/</link><description>Recent content in Python on Noureddine RAMDI</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 May 2026 20:41:27 +0000</lastBuildDate><atom:link href="https://ramdi.fr/tags/python/index.xml" rel="self" type="application/rss+xml"/><item><title>3D-RE-GEN: reconstructing editable 3D indoor scenes from a single photo with multi-model AI orchestration</title><link>https://ramdi.fr/github-stars/3d-re-gen-reconstructing-editable-3d-indoor-scenes-from-a-single-photo-with-multi-model-ai-orchestration/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/3d-re-gen-reconstructing-editable-3d-indoor-scenes-from-a-single-photo-with-multi-model-ai-orchestration/</guid><description>3D-RE-GEN reconstructs complete editable 3D indoor scenes from a single RGB photo. It integrates SAM, Hunyuan3D-2.0, and VGGT models in a modular Python pipeline.</description></item><item><title>A composable Python framework for crypto algorithmic trading with functional strategies</title><link>https://ramdi.fr/github-stars/a-composable-python-framework-for-crypto-algorithmic-trading-with-functional-strategies/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/a-composable-python-framework-for-crypto-algorithmic-trading-with-functional-strategies/</guid><description>Explore a Python framework for cryptocurrency algorithmic trading that uses composable boolean functions for strategy design, supporting live trading, simulation, and backtesting.</description></item><item><title>A curated gateway to essential software engineering research papers</title><link>https://ramdi.fr/github-stars/a-curated-gateway-to-essential-software-engineering-research-papers/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/a-curated-gateway-to-essential-software-engineering-research-papers/</guid><description>Explore a well-organized collection of key software engineering research papers for practitioners seeking focused, quality reading material to level up their skills.</description></item><item><title>AgentFlow: orchestrating AI coding agents with programmatic dependency graphs</title><link>https://ramdi.fr/github-stars/agentflow-orchestrating-ai-coding-agents-with-programmatic-dependency-graphs/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/agentflow-orchestrating-ai-coding-agents-with-programmatic-dependency-graphs/</guid><description>AgentFlow uses Python&amp;rsquo;s graph-based DSL to orchestrate AI coding agents with parallelism, iteration, and remote execution. It supports Codex, Claude, and others.</description></item><item><title>Algorithmic trading with AI: the Harvard RBI framework for disciplined strategy development</title><link>https://ramdi.fr/github-stars/algorithmic-trading-with-ai-the-harvard-rbi-framework-for-disciplined-strategy-development/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/algorithmic-trading-with-ai-the-harvard-rbi-framework-for-disciplined-strategy-development/</guid><description>This repo teaches algorithmic trading with a disciplined Research-Backtest-Implement method using Python and AI tools. It stresses avoiding emotional mistakes with systematic workflows.</description></item><item><title>ALICE: a self-contained YOLO dataset management toolkit with a creative single-file Python builder</title><link>https://ramdi.fr/github-stars/alice-a-self-contained-yolo-dataset-management-toolkit-with-a-creative-single-file-python-builder/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/alice-a-self-contained-yolo-dataset-management-toolkit-with-a-creative-single-file-python-builder/</guid><description>ALICE is a Python-based toolkit for managing YOLO training datasets from home camera setups, featuring a unique single-file builder and seamless Frigate NVR integration.</description></item><item><title>APISR: a Python toolkit for AI-based image and video super-resolution with practical inference modes</title><link>https://ramdi.fr/github-stars/apisr-a-python-toolkit-for-ai-based-image-and-video-super-resolution-with-practical-inference-modes/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/apisr-a-python-toolkit-for-ai-based-image-and-video-super-resolution-with-practical-inference-modes/</guid><description>APISR is a Python repo for AI-powered image and video super-resolution, offering fast Gradio inference and full-featured regular inference with dataset curation tools.</description></item><item><title>Apprise API: container-native notification gateway with hardened production design</title><link>https://ramdi.fr/github-stars/apprise-api-container-native-notification-gateway-with-hardened-production-design/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/apprise-api-container-native-notification-gateway-with-hardened-production-design/</guid><description>Apprise API wraps 130+ notification services behind a lightweight REST API with a container-native design, nginx+gunicorn+supervisord orchestration, and production-hardened Docker images.</description></item><item><title>Argus: a modular Python CLI toolkit for comprehensive security reconnaissance</title><link>https://ramdi.fr/github-stars/argus-a-modular-python-cli-toolkit-for-comprehensive-security-reconnaissance/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/argus-a-modular-python-cli-toolkit-for-comprehensive-security-reconnaissance/</guid><description>Argus is a Python CLI toolkit bundling 135 reconnaissance modules across network, web, and threat intelligence domains in a unified command shell.</description></item><item><title>Arkon: Structured enterprise knowledge synthesis with a unique LLM compilation pipeline</title><link>https://ramdi.fr/github-stars/arkon-structured-enterprise-knowledge-synthesis-with-a-unique-llm-compilation-pipeline/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/arkon-structured-enterprise-knowledge-synthesis-with-a-unique-llm-compilation-pipeline/</guid><description>Arkon is a self-hosted enterprise knowledge hub using a novel MRP pipeline for structured, traceable wiki compilation with external AI inference and workspace-scoped RBAC.</description></item><item><title>Autodistill: Automating vision model distillation from foundation models to edge deployables</title><link>https://ramdi.fr/github-stars/autodistill-automating-vision-model-distillation-from-foundation-models-to-edge-deployables/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/autodistill-automating-vision-model-distillation-from-foundation-models-to-edge-deployables/</guid><description>Autodistill automates the pipeline from large foundation models to edge-ready vision models using pluggable plugins and a natural language ontology for zero-shot labeling.</description></item><item><title>AutoSkill: Experience-driven lifelong learning for LLM agents with skill versioning and evolution</title><link>https://ramdi.fr/github-stars/autoskill-experience-driven-lifelong-learning-for-llm-agents-with-skill-versioning-and-evolution/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/autoskill-experience-driven-lifelong-learning-for-llm-agents-with-skill-versioning-and-evolution/</guid><description>AutoSkill is a Python framework enabling LLM agents to extract, version, and evolve skills from dialogues, providing a persistent long-term memory system for AI agents.</description></item><item><title>Autoware Vision Pilot: An open-source stack exploring multiple end-to-end AI approaches for autonomous driving</title><link>https://ramdi.fr/github-stars/autoware-vision-pilot-an-open-source-stack-exploring-multiple-end-to-end-ai-approaches-for-autonomous-driving/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/autoware-vision-pilot-an-open-source-stack-exploring-multiple-end-to-end-ai-approaches-for-autonomous-driving/</guid><description>Autoware Vision Pilot is an open-source autonomous driving stack implementing three end-to-end AI paradigms without relying on HD maps. It targets ADAS to full autonomy progression.</description></item><item><title>Azure Voice Live API Sales Coach: Real-time AI-powered voice training for sales</title><link>https://ramdi.fr/github-stars/azure-voice-live-api-sales-coach-real-time-ai-powered-voice-training-for-sales/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/azure-voice-live-api-sales-coach-real-time-ai-powered-voice-training-for-sales/</guid><description>Explore Azure&amp;rsquo;s Voice Live API in a Python Flask + React demo for real-time AI sales coaching with speech-to-speech conversations and instant feedback.</description></item><item><title>bopscrk: targeted password wordlist generation with lyric-based OSINT</title><link>https://ramdi.fr/github-stars/bopscrk-targeted-password-wordlist-generation-with-lyric-based-osint/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/bopscrk-targeted-password-wordlist-generation-with-lyric-based-osint/</guid><description>bopscrk is a Python CLI tool for targeted password wordlist generation, combining user input and scraped song lyrics with mutations. Useful in pentesting and red teaming.</description></item><item><title>Bridging Claude's AI 'computer' tool with Playwright browser automation</title><link>https://ramdi.fr/github-stars/bridging-claude-s-ai-computer-tool-with-playwright-browser-automation/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/bridging-claude-s-ai-computer-tool-with-playwright-browser-automation/</guid><description>Playwright Computer Use links Claude&amp;rsquo;s abstract computer tool to real browser automation with Playwright, supporting sync and async APIs and cursor tracking.</description></item><item><title>Building AI-assisted parametric 3D modeling with cad-skill: a self-correcting Claude Code extension</title><link>https://ramdi.fr/github-stars/building-ai-assisted-parametric-3d-modeling-with-cad-skill-a-self-correcting-claude-code-extension/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/building-ai-assisted-parametric-3d-modeling-with-cad-skill-a-self-correcting-claude-code-extension/</guid><description>cad-skill integrates Claude Code with CadQuery to create AI-driven parametric 3D modeling via a self-correcting Python script feedback loop, tailored for 3D printing workflows.</description></item><item><title>Cairn: a blackboard-driven state-space search engine with stateless agent workers</title><link>https://ramdi.fr/github-stars/cairn-a-blackboard-driven-state-space-search-engine-with-stateless-agent-workers/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/cairn-a-blackboard-driven-state-space-search-engine-with-stateless-agent-workers/</guid><description>Cairn implements state-space search via a minimal blackboard architecture with stateless OODA loop workers. It scored perfectly at the Tencent AI Penetration Testing Challenge.</description></item><item><title>claude-office: integrating Claude Code into a full-stack TypeScript environment</title><link>https://ramdi.fr/github-stars/claude-office-integrating-claude-code-into-a-full-stack-typescript-environment/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/claude-office-integrating-claude-code-into-a-full-stack-typescript-environment/</guid><description>claude-office offers a TypeScript-based environment integrating Claude Code CLI with a backend and frontend, supporting AI enhancements. Quickstart commands enable fast setup.</description></item><item><title>Claude-OSINT: Turning Claude into an AI-driven OSINT Recon Operator with Structured Skills</title><link>https://ramdi.fr/github-stars/claude-osint-turning-claude-into-an-ai-driven-osint-recon-operator-with-structured-skills/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/claude-osint-turning-claude-into-an-ai-driven-osint-recon-operator-with-structured-skills/</guid><description>Claude-OSINT equips Claude LLM with 4,600+ lines of structured OSINT tradecraft in markdown skills, enabling AI-driven recon with 90+ modules, 80+ dorks, and attack-path templates. No external APIs needed.</description></item><item><title>Claw-Eval: a rigorous Python harness for trustworthy evaluation of LLM-powered autonomous agents</title><link>https://ramdi.fr/github-stars/claw-eval-a-rigorous-python-harness-for-trustworthy-evaluation-of-llm-powered-autonomous-agents/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/claw-eval-a-rigorous-python-harness-for-trustworthy-evaluation-of-llm-powered-autonomous-agents/</guid><description>Claw-Eval offers a Python-based evaluation harness for LLM autonomous agents, featuring 300 tasks and a strict Pass^3 metric to ensure reliable, multi-dimensional benchmarking.</description></item><item><title>ClawMetry: zero-config real-time observability dashboard for OpenClaw AI agents</title><link>https://ramdi.fr/github-stars/clawmetry-zero-config-real-time-observability-dashboard-for-openclaw-ai-agents/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/clawmetry-zero-config-real-time-observability-dashboard-for-openclaw-ai-agents/</guid><description>ClawMetry offers a zero-configuration real-time dashboard for OpenClaw AI agents, visualizing message flows, token usage, and operational alerts with easy setup.</description></item><item><title>Comic Translate: AI-driven multi-language comic translation with full-page context</title><link>https://ramdi.fr/github-stars/comic-translate-ai-driven-multi-language-comic-translation-with-full-page-context/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/comic-translate-ai-driven-multi-language-comic-translation-with-full-page-context/</guid><description>Comic Translate uses advanced AI models and a multi-step pipeline for accurate comic translation across languages, combining speech bubble detection, OCR, and LLMs with full-page context.</description></item><item><title>dataseo-mcp: wrapping Ahrefs SEO data as AI assistant tools via CAPTCHA bypass</title><link>https://ramdi.fr/github-stars/dataseo-mcp-wrapping-ahrefs-seo-data-as-ai-assistant-tools-via-captcha-bypass/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/dataseo-mcp-wrapping-ahrefs-seo-data-as-ai-assistant-tools-via-captcha-bypass/</guid><description>dataseo-mcp is a Python MCP server that exposes Ahrefs SEO data by bypassing CAPTCHAs, offering AI coding assistants powerful SEO research tools integrated into IDEs like Claude and VS Code.</description></item><item><title>Dedoc: Python library for structured document content extraction with a virtual stack machine PDF engine</title><link>https://ramdi.fr/github-stars/dedoc-python-library-for-structured-document-content-extraction-with-a-virtual-stack-machine-pdf-engine/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/dedoc-python-library-for-structured-document-content-extraction-with-a-virtual-stack-machine-pdf-engine/</guid><description>Dedoc is a Python library and REST API that extracts structured content from diverse documents including PDFs, Office files, and images using a unique virtual stack machine PDF interpreter and OCR preprocessing.</description></item><item><title>DeepSpeed: scalable deep learning optimization with extensible hardware support</title><link>https://ramdi.fr/github-stars/deepspeed-scalable-deep-learning-optimization-with-extensible-hardware-support/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/deepspeed-scalable-deep-learning-optimization-with-extensible-hardware-support/</guid><description>DeepSpeed is a Python library that optimizes large-scale deep learning training with multi-hardware support and JIT CUDA extensions. Explore its architecture, strengths, and quick installation.</description></item><item><title>DeepTeam: A Python framework for adversarial red teaming of large language models</title><link>https://ramdi.fr/github-stars/deepteam-a-python-framework-for-adversarial-red-teaming-of-large-language-models/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/deepteam-a-python-framework-for-adversarial-red-teaming-of-large-language-models/</guid><description>DeepTeam is a Python tool for red teaming LLMs by dynamically generating adversarial attacks and evaluating vulnerabilities like bias. It requires minimal setup and no predefined datasets.</description></item><item><title>DeepZero: Automating Windows Kernel Driver Vulnerability Research with YAML-Driven LLM Pipelines</title><link>https://ramdi.fr/github-stars/deepzero-automating-windows-kernel-driver-vulnerability-research-with-yaml-driven-llm-pipelines/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/deepzero-automating-windows-kernel-driver-vulnerability-research-with-yaml-driven-llm-pipelines/</guid><description>DeepZero automates vulnerability research on Windows kernel drivers by chaining Ghidra decompilation with LLM-based analysis using YAML pipelines and Jinja2 templates.</description></item><item><title>DiT4DiT: Vision-Action Modeling with Video Transformers for Real-Time Humanoid Robot Control</title><link>https://ramdi.fr/github-stars/dit4dit-vision-action-modeling-with-video-transformers-for-real-time-humanoid-robot-control/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/dit4dit-vision-action-modeling-with-video-transformers-for-real-time-humanoid-robot-control/</guid><description>DiT4DiT uses a frozen Cosmos-Predict2.5 video transformer backbone combined with flow-matching action heads to model robot actions as video latent transitions, achieving near-perfect success on LIBERO and real-time humanoid control.</description></item><item><title>Excalibur: A web interface for extracting tables from PDFs using Camelot</title><link>https://ramdi.fr/github-stars/excalibur-a-web-interface-for-extracting-tables-from-pdfs-using-camelot/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/excalibur-a-web-interface-for-extracting-tables-from-pdfs-using-camelot/</guid><description>Excalibur provides a Flask web UI over Camelot for extracting tabular data from PDFs. Supports manual selection, auto-detection, multiple backends, and export formats.</description></item><item><title>Exploring Gemini-API: a Python client for Gemini with cookie management</title><link>https://ramdi.fr/github-stars/exploring-gemini-api-a-python-client-for-gemini-with-cookie-management/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/exploring-gemini-api-a-python-client-for-gemini-with-cookie-management/</guid><description>Gemini-API is a Python package providing client access to the Gemini API with built-in cookie management and Python 3.10+ support. Here’s how it works and how to get started.</description></item><item><title>Exploring GMR: real-time cross-embodiment human motion retargeting for humanoid robots</title><link>https://ramdi.fr/github-stars/exploring-gmr-real-time-cross-embodiment-human-motion-retargeting-for-humanoid-robots/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/exploring-gmr-real-time-cross-embodiment-human-motion-retargeting-for-humanoid-robots/</guid><description>GMR is a Python library that retargets human motion from multiple formats onto 17+ humanoid robots in real time on CPU, tuned for RL tracking policies and whole-body teleoperation.</description></item><item><title>Exploring sdf: a Python library for 3D mesh generation with signed distance functions</title><link>https://ramdi.fr/github-stars/exploring-sdf-a-python-library-for-3d-mesh-generation-with-signed-distance-functions/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/exploring-sdf-a-python-library-for-3d-mesh-generation-with-signed-distance-functions/</guid><description>sdf is a Python library that generates 3D meshes from signed distance functions using operator overloading for intuitive constructive solid geometry. It’s fast, minimal, and versatile.</description></item><item><title>Extending Claude Code with a modular plugin marketplace for multi-agent AI workflows</title><link>https://ramdi.fr/github-stars/extending-claude-code-with-a-modular-plugin-marketplace-for-multi-agent-ai-workflows/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/extending-claude-code-with-a-modular-plugin-marketplace-for-multi-agent-ai-workflows/</guid><description>Explore a curated marketplace of 14 Python plugins that extend Claude Code through multi-agent orchestration, hook-based workflows, and integrations. Modular, standalone, and easy to install.</description></item><item><title>Formalizing academic paper writing as a programmable pipeline with Claude Code skills</title><link>https://ramdi.fr/github-stars/formalizing-academic-paper-writing-as-a-programmable-pipeline-with-claude-code-skills/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/formalizing-academic-paper-writing-as-a-programmable-pipeline-with-claude-code-skills/</guid><description>This repo implements academic paper planning and writing as a two-phase Claude Code skill pipeline with a 35-point quality rubric enforced by Python scripts at each stage.</description></item><item><title>Fuji: macOS-native live forensic acquisition with unattended logical imaging</title><link>https://ramdi.fr/github-stars/fuji-macos-native-live-forensic-acquisition-with-unattended-logical-imaging/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/fuji-macos-native-live-forensic-acquisition-with-unattended-logical-imaging/</guid><description>Fuji is a Python tool for live logical forensic acquisition on macOS, using only native system utilities to create forensically sound DMG images in an unattended workflow.</description></item><item><title>Fun-ASR: Alibaba's multilingual speech recognition model with real-time capabilities</title><link>https://ramdi.fr/github-stars/fun-asr-alibaba-s-multilingual-speech-recognition-model-with-real-time-capabilities/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/fun-asr-alibaba-s-multilingual-speech-recognition-model-with-real-time-capabilities/</guid><description>Fun-ASR is Alibaba Tongyi Lab&amp;rsquo;s end-to-end speech recognition model with 800M parameters, supporting 31 languages and real-time transcription in noisy environments.</description></item><item><title>FuzzyAI: AI-Driven Fuzz Testing with Local LLM Integration</title><link>https://ramdi.fr/github-stars/fuzzyai-ai-driven-fuzz-testing-with-local-llm-integration/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/fuzzyai-ai-driven-fuzz-testing-with-local-llm-integration/</guid><description>FuzzyAI combines fuzz testing with AI models using Python and Ollama. It offers a CLI for fuzzing with local LLMs, balancing AI power and practical setup tradeoffs.</description></item><item><title>Genesis-world: a high-throughput unified physics engine for robotics simulation and embodied AI</title><link>https://ramdi.fr/github-stars/genesis-world-a-high-throughput-unified-physics-engine-for-robotics-simulation-and-embodied-ai/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/genesis-world-a-high-throughput-unified-physics-engine-for-robotics-simulation-and-embodied-ai/</guid><description>Genesis-world delivers 43 million FPS on RTX 4090, unifying multiple physics methods with GPU acceleration and a pythonic API. It supports differentiable sim and natural language-driven data generation for robotics.</description></item><item><title>GenZ-ICP: robust LiDAR odometry with adaptive weighting for degenerate geometries</title><link>https://ramdi.fr/github-stars/genz-icp-robust-lidar-odometry-with-adaptive-weighting-for-degenerate-geometries/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/genz-icp-robust-lidar-odometry-with-adaptive-weighting-for-degenerate-geometries/</guid><description>GenZ-ICP enhances LiDAR odometry by introducing an adaptive weighting scheme for ICP registration, improving robustness in challenging environments like tunnels and open fields. It builds on KISS-ICP with Python and ROS integration.</description></item><item><title>geowifi: a multi-source WiFi geolocation aggregator with passive OSINT capabilities</title><link>https://ramdi.fr/github-stars/geowifi-a-multi-source-wifi-geolocation-aggregator-with-passive-osint-capabilities/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/geowifi-a-multi-source-wifi-geolocation-aggregator-with-passive-osint-capabilities/</guid><description>geowifi is a Python OSINT tool querying seven WiFi geolocation databases to map BSSID or SSID to coordinates, outputting JSON or HTML maps with vendor lookup.</description></item><item><title>gimp-mcp: enabling AI-driven image editing with live feedback via Model Context Protocol</title><link>https://ramdi.fr/github-stars/gimp-mcp-enabling-ai-driven-image-editing-with-live-feedback-via-model-context-protocol/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/gimp-mcp-enabling-ai-driven-image-editing-with-live-feedback-via-model-context-protocol/</guid><description>GIMP MCP bridges GIMP 3.2 with AI assistants via MCP, offering 56 tool commands and live PNG snapshots for AI-driven iterative image editing workflows.</description></item><item><title>GIS-MCP: enabling LLM-driven geospatial analysis through a Model Context Protocol server</title><link>https://ramdi.fr/github-stars/gis-mcp-enabling-llm-driven-geospatial-analysis-through-a-model-context-protocol-server/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/gis-mcp-enabling-llm-driven-geospatial-analysis-through-a-model-context-protocol-server/</guid><description>GIS-MCP is a Python MCP server that exposes geospatial operations as structured tools for LLMs, bridging natural language and GIS workflows without coding.</description></item><item><title>Graph-R1: Reinforcement learning to train LLMs for reasoning over knowledge graphs</title><link>https://ramdi.fr/github-stars/graph-r1-reinforcement-learning-to-train-llms-for-reasoning-over-knowledge-graphs/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/graph-r1-reinforcement-learning-to-train-llms-for-reasoning-over-knowledge-graphs/</guid><description>Graph-R1 trains large language models with reinforcement learning to reason over knowledge graphs, cycling through think-query-retrieve-rethink steps for complex knowledge tasks.</description></item><item><title>GS-Playground: High-throughput photorealistic simulation for vision-based robot learning</title><link>https://ramdi.fr/github-stars/gs-playground-high-throughput-photorealistic-simulation-for-vision-based-robot-learning/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/gs-playground-high-throughput-photorealistic-simulation-for-vision-based-robot-learning/</guid><description>GS-Playground combines 3D Gaussian Splatting rendering with a velocity-impulse physics engine to enable large-scale visual reinforcement learning at up to 10^4 FPS. Preview release with core simulation API and demos.</description></item><item><title>H4X-Tools: a modular Python CLI for OSINT and dual-source credential leak search</title><link>https://ramdi.fr/github-stars/h4x-tools-a-modular-python-cli-for-osint-and-dual-source-credential-leak-search/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/h4x-tools-a-modular-python-cli-for-osint-and-dual-source-credential-leak-search/</guid><description>H4X-Tools is a Python 3.10+ CLI toolkit offering 16 modular OSINT utilities, including a dual-source leak search combining stealer logs and a 3.2B+ credential dataset for actionable breach insights.</description></item><item><title>Hackingtool Plugin: a smart dispatcher for 183 pentesting tools with native, WSL, and Docker backends</title><link>https://ramdi.fr/github-stars/hackingtool-plugin-a-smart-dispatcher-for-183-pentesting-tools-with-native-wsl-and-docker-backends/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/hackingtool-plugin-a-smart-dispatcher-for-183-pentesting-tools-with-native-wsl-and-docker-backends/</guid><description>Hackingtool-plugin wraps 183 pentesting and OSINT tools behind a Claude Code plugin. It smartly dispatches commands to native Bash, WSL, or Docker containers, outputting clean JSON.</description></item><item><title>Harvey LAB: Benchmarking legal LLM agents with realistic tasks and automated scoring</title><link>https://ramdi.fr/github-stars/harvey-lab-benchmarking-legal-llm-agents-with-realistic-tasks-and-automated-scoring/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/harvey-lab-benchmarking-legal-llm-agents-with-realistic-tasks-and-automated-scoring/</guid><description>Harvey LAB offers an open-source benchmark for evaluating LLM agents on realistic legal tasks using an all-pass rubric and LLM-as-judge scoring. It includes datasets, adapters, and dashboards.</description></item><item><title>Hivemind: decentralized peer-to-peer deep learning with PyTorch</title><link>https://ramdi.fr/github-stars/hivemind-decentralized-peer-to-peer-deep-learning-with-pytorch/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/hivemind-decentralized-peer-to-peer-deep-learning-with-pytorch/</guid><description>Hivemind is a PyTorch library enabling decentralized deep learning over the internet using a peer-to-peer Distributed Hash Table (DHT). It supports fault-tolerant training and decentralized parameter averaging without global sync.</description></item><item><title>Inside AlohaMini: a Python-powered open-source mini robotic arm project</title><link>https://ramdi.fr/github-stars/inside-alohamini-a-python-powered-open-source-mini-robotic-arm-project/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-alohamini-a-python-powered-open-source-mini-robotic-arm-project/</guid><description>AlohaMini is an open-source project combining hardware and Python software to build and teleoperate a mini robotic arm. It covers 3D printing, assembly, and control.</description></item><item><title>Inside gtm-agents: a Claude Code marketplace for specialized GTM AI plugins</title><link>https://ramdi.fr/github-stars/inside-gtm-agents-a-claude-code-marketplace-for-specialized-gtm-ai-plugins/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-gtm-agents-a-claude-code-marketplace-for-specialized-gtm-ai-plugins/</guid><description>gtm-agents bundles 67 GTM plugins, 92 AI agents, 52 business skills, and 20 workflow orchestrators for Claude Code, saving 15+ hours/week on sales and marketing busywork.</description></item><item><title>Inside Mini-SGLang: A clear and modular Python LLM inference engine</title><link>https://ramdi.fr/github-stars/inside-mini-sglang-a-clear-and-modular-python-llm-inference-engine/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-mini-sglang-a-clear-and-modular-python-llm-inference-engine/</guid><description>Mini-SGLang is a modular Python reimplementation of the SGLang LLM inference engine with production features like Radix Cache, chunked prefill, overlap scheduling, and tensor parallelism.</description></item><item><title>Inside NavDP: A diffusion policy approach to mapless robot navigation with sim-to-real transfer</title><link>https://ramdi.fr/github-stars/inside-navdp-a-diffusion-policy-approach-to-mapless-robot-navigation-with-sim-to-real-transfer/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-navdp-a-diffusion-policy-approach-to-mapless-robot-navigation-with-sim-to-real-transfer/</guid><description>NavDP uses a diffusion policy architecture with privileged information to achieve mapless robot navigation across simulated and real environments without real-world training data.</description></item><item><title>Inside Papermerge: an open-source OCR document management system with a scalable meta-repo architecture</title><link>https://ramdi.fr/github-stars/inside-papermerge-an-open-source-ocr-document-management-system-with-a-scalable-meta-repo-architecture/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-papermerge-an-open-source-ocr-document-management-system-with-a-scalable-meta-repo-architecture/</guid><description>Papermerge is a Python-based open-source document management system for scanned files with OCR and full-text search, using a meta-repo pattern to scale its codebase.</description></item><item><title>Inside picoagents: a transparent multi-agent system framework built from scratch in Python</title><link>https://ramdi.fr/github-stars/inside-picoagents-a-transparent-multi-agent-system-framework-built-from-scratch-in-python/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-picoagents-a-transparent-multi-agent-system-framework-built-from-scratch-in-python/</guid><description>PicoAgents is a Python multi-agent framework built from scratch, offering transparent agent orchestration, LLM provider abstraction, streaming UI, and production-ready benchmarks.</description></item><item><title>Inside Polymarket's BTC 15-minute trading bot: multi-signal fusion with self-learning weights</title><link>https://ramdi.fr/github-stars/inside-polymarket-s-btc-15-minute-trading-bot-multi-signal-fusion-with-self-learning-weights/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-polymarket-s-btc-15-minute-trading-bot-multi-signal-fusion-with-self-learning-weights/</guid><description>Explore a Python trading bot for Polymarket&amp;rsquo;s 15-minute BTC markets. It uses a 7-phase modular pipeline, fuses three signals, and features a self-learning weight adjustment engine.</description></item><item><title>Inside Poppy Humanoid: an open-source 3D-printed humanoid robot platform with Python control</title><link>https://ramdi.fr/github-stars/inside-poppy-humanoid-an-open-source-3d-printed-humanoid-robot-platform-with-python-control/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-poppy-humanoid-an-open-source-3d-printed-humanoid-robot-platform-with-python-control/</guid><description>Poppy Humanoid is an open-source 3D-printed humanoid robot controlled via Python and Jupyter Notebooks, designed for research and education in embodied cognition and sensorimotor learning.</description></item><item><title>Inside red-run: AI agent orchestration for offensive security assessments</title><link>https://ramdi.fr/github-stars/inside-red-run-ai-agent-orchestration-for-offensive-security-assessments/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-red-run-ai-agent-orchestration-for-offensive-security-assessments/</guid><description>red-run orchestrates Claude Code AI agent teams across the full pentest kill chain using persistent teammates and semantic routing. Explore its architecture, strengths, and quickstart.</description></item><item><title>Inside WeatherBet: a Python trading bot for Polymarket weather markets with adaptive Kelly sizing</title><link>https://ramdi.fr/github-stars/inside-weatherbet-a-python-trading-bot-for-polymarket-weather-markets-with-adaptive-kelly-sizing/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-weatherbet-a-python-trading-bot-for-polymarket-weather-markets-with-adaptive-kelly-sizing/</guid><description>Explore WeatherBet, a Python trading bot exploiting Polymarket weather markets using multi-source forecasts and self-calibrated fractional Kelly position sizing for risk management.</description></item><item><title>IntellAgent: systematic adversarial testing for conversational AI with policy graph decomposition</title><link>https://ramdi.fr/github-stars/intellagent-systematic-adversarial-testing-for-conversational-ai-with-policy-graph-decomposition/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/intellagent-systematic-adversarial-testing-for-conversational-ai-with-policy-graph-decomposition/</guid><description>IntellAgent is a Python framework that stress-tests conversational AI agents by generating structured adversarial dialogues via policy graph decomposition, helping uncover blind spots before production.</description></item><item><title>J.A.R.V.I.S: A Python voice assistant with facial recognition and persona switching</title><link>https://ramdi.fr/github-stars/j-a-r-v-i-s-a-python-voice-assistant-with-facial-recognition-and-persona-switching/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/j-a-r-v-i-s-a-python-voice-assistant-with-facial-recognition-and-persona-switching/</guid><description>J.A.R.V.I.S is a Python voice-controlled desktop assistant combining speech recognition, facial authentication, and multi-voice personas without AI models. A pre-LLM design worth exploring.</description></item><item><title>Kimi-Audio: a unified hybrid-token audio foundation model with LLM core</title><link>https://ramdi.fr/github-stars/kimi-audio-a-unified-hybrid-token-audio-foundation-model-with-llm-core/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/kimi-audio-a-unified-hybrid-token-audio-foundation-model-with-llm-core/</guid><description>Kimi-Audio combines continuous acoustic and discrete semantic tokens within a 7B LLM for unified audio-text understanding and generation. It achieves state-of-the-art ASR with low-latency audio synthesis.</description></item><item><title>Kodo: orchestrating AI coding agents with a plain API orchestrator for better autonomous development</title><link>https://ramdi.fr/github-stars/kodo-orchestrating-ai-coding-agents-with-a-plain-api-orchestrator-for-better-autonomous-development/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/kodo-orchestrating-ai-coding-agents-with-a-plain-api-orchestrator-for-better-autonomous-development/</guid><description>Kodo is a Python multi-agent orchestration layer coordinating AI coding agents via a plain API orchestrator, improving autonomous coding accuracy by 24% over single-agent setups.</description></item><item><title>Learning autonomous mobile robots with ROS 2: a hands-on course companion</title><link>https://ramdi.fr/github-stars/learning-autonomous-mobile-robots-with-ros-2-a-hands-on-course-companion/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/learning-autonomous-mobile-robots-with-ros-2-a-hands-on-course-companion/</guid><description>This repo complements a ROS 2 course with hands-on C++/Python exercises, Gazebo simulation, and real robot control focusing on localization, mapping, and obstacle avoidance.</description></item><item><title>linkedin_scraper: async Playwright-powered LinkedIn scraping with typed data models</title><link>https://ramdi.fr/github-stars/linkedin-scraper-async-playwright-powered-linkedin-scraping-with-typed-data-models/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/linkedin-scraper-async-playwright-powered-linkedin-scraping-with-typed-data-models/</guid><description>linkedin_scraper is a Python library using Playwright and async/await for structured LinkedIn scraping with typed Pydantic models, session management, and progress callbacks.</description></item><item><title>LiveTradeBench: Evaluating LLM-driven trading agents in live markets</title><link>https://ramdi.fr/github-stars/livetradebench-evaluating-llm-driven-trading-agents-in-live-markets/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/livetradebench-evaluating-llm-driven-trading-agents-in-live-markets/</guid><description>LiveTradeBench benchmarks LLM trading agents like GPT and Claude in live US equity and prediction markets with real-time news and sentiment integration.</description></item><item><title>LLM-MM-Agent: autonomous mathematical modeling with hierarchical method selection</title><link>https://ramdi.fr/github-stars/llm-mm-agent-autonomous-mathematical-modeling-with-hierarchical-method-selection/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/llm-mm-agent-autonomous-mathematical-modeling-with-hierarchical-method-selection/</guid><description>LLM-MM-Agent uses LLMs as autonomous agents for end-to-end mathematical modeling, featuring a unique hierarchical method library with actor-critic selection. Supports GPT-4o and DeepSeek-R1.</description></item><item><title>llmstxt_architect: automated generation and maintenance of llms.txt files for LLM-aware websites</title><link>https://ramdi.fr/github-stars/llmstxt-architect-automated-generation-and-maintenance-of-llms-txt-files-for-llm-aware-websites/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/llmstxt-architect-automated-generation-and-maintenance-of-llms-txt-files-for-llm-aware-websites/</guid><description>llmstxt_architect automates generating and updating llms.txt files that communicate website content to LLMs. Supports multi-provider LLMs and preserves file structure during updates.</description></item><item><title>loki-mode: AI-powered autonomous software development from specs</title><link>https://ramdi.fr/github-stars/loki-mode-ai-powered-autonomous-software-development-from-specs/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/loki-mode-ai-powered-autonomous-software-development-from-specs/</guid><description>loki-mode automates software builds from Markdown PRDs, GitHub issues, or OpenAPI specs using AI and a Bun-based runtime. This article explores its architecture, strengths, and quickstart.</description></item><item><title>LuaN1aoAgent: Autonomous penetration testing with P-E-R multi-agent causal graph reasoning</title><link>https://ramdi.fr/github-stars/luan1aoagent-autonomous-penetration-testing-with-p-e-r-multi-agent-causal-graph-reasoning/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/luan1aoagent-autonomous-penetration-testing-with-p-e-r-multi-agent-causal-graph-reasoning/</guid><description>LuaN1aoAgent uses a P-E-R multi-agent framework and causal graph reasoning to achieve 90.4% autonomous success on penetration tests with low exploit cost. Key for AI-driven pentesting.</description></item><item><title>Lynx: modular personalized video generation with dual adapters on a frozen diffusion transformer</title><link>https://ramdi.fr/github-stars/lynx-modular-personalized-video-generation-with-dual-adapters-on-a-frozen-diffusion-transformer/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/lynx-modular-personalized-video-generation-with-dual-adapters-on-a-frozen-diffusion-transformer/</guid><description>Lynx generates personalized videos from a single image using a frozen Diffusion Transformer with ID and Ref adapters. This modular design balances fidelity and efficiency.</description></item><item><title>MarkPDFDown: converting PDFs to Markdown using vision-capable large language models</title><link>https://ramdi.fr/github-stars/markpdfdown-converting-pdfs-to-markdown-using-vision-capable-large-language-models/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/markpdfdown-converting-pdfs-to-markdown-using-vision-capable-large-language-models/</guid><description>MarkPDFDown is a Python CLI tool that converts PDFs and images into Markdown by using vision-capable large language models for visual recognition-based parsing, handling complex layouts and formulas.</description></item><item><title>MASt3R-SLAM: integrating foundation-model 3D priors into real-time dense SLAM</title><link>https://ramdi.fr/github-stars/mast3r-slam-integrating-foundation-model-3d-priors-into-real-time-dense-slam/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/mast3r-slam-integrating-foundation-model-3d-priors-into-real-time-dense-slam/</guid><description>MASt3R-SLAM integrates a pretrained 3D reconstruction model as a geometry prior in a dense SLAM pipeline, enabling real-time tracking and mapping without classical bundle adjustment or depth sensors.</description></item><item><title>Matkap: Active interception of malicious Telegram bots using leaked tokens</title><link>https://ramdi.fr/github-stars/matkap-active-interception-of-malicious-telegram-bots-using-leaked-tokens/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/matkap-active-interception-of-malicious-telegram-bots-using-leaked-tokens/</guid><description>Matkap is a Python tool that hunts down malicious Telegram bots by hijacking leaked bot tokens and forwarding their messages for active threat intelligence gathering.</description></item><item><title>Metube: a self-hosted yt-dlp web UI with flexible multi-level download configuration</title><link>https://ramdi.fr/github-stars/metube-a-self-hosted-yt-dlp-web-ui-with-flexible-multi-level-download-configuration/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/metube-a-self-hosted-yt-dlp-web-ui-with-flexible-multi-level-download-configuration/</guid><description>Metube is a self-hosted web UI for yt-dlp providing browser-based video downloading with playlist subscriptions, queuing, and a layered config system. Dockerized for easy deployment.</description></item><item><title>Mini-Wiki: AI-powered incremental wiki documentation generation with instruction-based plugins</title><link>https://ramdi.fr/github-stars/mini-wiki-ai-powered-incremental-wiki-documentation-generation-with-instruction-based-plugins/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/mini-wiki-ai-powered-incremental-wiki-documentation-generation-with-instruction-based-plugins/</guid><description>Mini-Wiki enables AI agents to generate and maintain structured wiki docs from codebases incrementally, using a safe instruction-based plugin system. Supports Mermaid diagrams and multi-language output.</description></item><item><title>Minimalist Python AI demos: exploring qxresearch-event-1's concise LLM patterns</title><link>https://ramdi.fr/github-stars/minimalist-python-ai-demos-exploring-qxresearch-event-1-s-concise-llm-patterns/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/minimalist-python-ai-demos-exploring-qxresearch-event-1-s-concise-llm-patterns/</guid><description>qxresearch-event-1 is a collection of 50+ minimalist Python apps showcasing core AI patterns like fine-tuning, vector DB, and Whisper in about 10 lines each. A practical learning resource.</description></item><item><title>ML-From-Scratch: Exploring Machine Learning Fundamentals with Pure Python and NumPy</title><link>https://ramdi.fr/github-stars/ml-from-scratch-exploring-machine-learning-fundamentals-with-pure-python-and-numpy/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/ml-from-scratch-exploring-machine-learning-fundamentals-with-pure-python-and-numpy/</guid><description>ML-From-Scratch offers bare-bones Python implementations of key machine learning algorithms using only NumPy, focusing on transparency over efficiency. Explore how it demystifies ML fundamentals.</description></item><item><title>MonoGS: monocular SLAM with 3D Gaussian splatting for real-time dense mapping and tracking</title><link>https://ramdi.fr/github-stars/monogs-monocular-slam-with-3d-gaussian-splatting-for-real-time-dense-mapping-and-tracking/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/monogs-monocular-slam-with-3d-gaussian-splatting-for-real-time-dense-mapping-and-tracking/</guid><description>MonoGS rethinks monocular SLAM by replacing point-cloud maps with differentiable 3D Gaussian splatting, enabling real-time dense reconstruction and camera tracking in a unified pipeline.</description></item><item><title>Navigating AI learning with bishwaghimire's AI learning roadmaps</title><link>https://ramdi.fr/github-stars/navigating-ai-learning-with-bishwaghimire-s-ai-learning-roadmaps/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/navigating-ai-learning-with-bishwaghimire-s-ai-learning-roadmaps/</guid><description>A practical guide to bishwaghimire&amp;rsquo;s AI learning roadmaps repository, offering modular, career-focused paths for AI and ML self-learners, with setup essentials and a flexible curriculum.</description></item><item><title>NetAlertX: Containerized network asset discovery and alerting platform</title><link>https://ramdi.fr/github-stars/netalertx-containerized-network-asset-discovery-and-alerting-platform/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/netalertx-containerized-network-asset-discovery-and-alerting-platform/</guid><description>NetAlertX is a Python-based network monitoring tool offering continuous asset discovery, IP management, and multi-channel alerts via Docker deployment.</description></item><item><title>Nougat: Vision Transformer OCR for academic PDFs extracting LaTeX math and tables</title><link>https://ramdi.fr/github-stars/nougat-vision-transformer-ocr-for-academic-pdfs-extracting-latex-math-and-tables/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/nougat-vision-transformer-ocr-for-academic-pdfs-extracting-latex-math-and-tables/</guid><description>Nougat is Meta&amp;rsquo;s neural OCR system for academic PDFs, extracting LaTeX math and tables into structured Markdown using a Vision Transformer encoder-decoder. It offers CLI, API, and training tools.</description></item><item><title>npcpy: enforcing AI behavioral compliance through architecture for multimodal LLM apps</title><link>https://ramdi.fr/github-stars/npcpy-enforcing-ai-behavioral-compliance-through-architecture-for-multimodal-llm-apps/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/npcpy-enforcing-ai-behavioral-compliance-through-architecture-for-multimodal-llm-apps/</guid><description>npcpy offers a unique NPC Context-Agent-Tool data layer to enforce AI compliance via software architecture, supporting multimodal LLM apps and multi-agent systems with local and cloud providers.</description></item><item><title>obsidian-llm-wiki-local: local-first AI-powered wiki generation with human-in-the-loop feedback</title><link>https://ramdi.fr/github-stars/obsidian-llm-wiki-local-local-first-ai-powered-wiki-generation-with-human-in-the-loop-feedback/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/obsidian-llm-wiki-local-local-first-ai-powered-wiki-generation-with-human-in-the-loop-feedback/</guid><description>obsidian-llm-wiki-local generates interlinked Obsidian markdown wikis using local LLMs. Its standout feature is a rejection feedback loop that refines article quality via user input.</description></item><item><title>OCRFlux: GPU-Accelerated OCR with Python for High-Performance Document Processing</title><link>https://ramdi.fr/github-stars/ocrflux-gpu-accelerated-ocr-with-python-for-high-performance-document-processing/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/ocrflux-gpu-accelerated-ocr-with-python-for-high-performance-document-processing/</guid><description>OCRFlux is a Python OCR tool optimized for NVIDIA GPUs, enabling fast, high-quality OCR on documents using a conda environment and poppler-utils for PDF rendering.</description></item><item><title>OmniVoice Studio: a local-first multi-engine voice cloning and dubbing platform with MCP server integration</title><link>https://ramdi.fr/github-stars/omnivoice-studio-a-local-first-multi-engine-voice-cloning-and-dubbing-platform-with-mcp-server-integration/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/omnivoice-studio-a-local-first-multi-engine-voice-cloning-and-dubbing-platform-with-mcp-server-integration/</guid><description>OmniVoice Studio is a local desktop app offering zero-shot voice cloning, multi-engine TTS, and video dubbing with GPU-aware offloading and an MCP server for agentic AI integration.</description></item><item><title>Open Computer Use: orchestrating multi-model LLM pipelines for remote Linux desktop control</title><link>https://ramdi.fr/github-stars/open-computer-use-orchestrating-multi-model-llm-pipelines-for-remote-linux-desktop-control/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/open-computer-use-orchestrating-multi-model-llm-pipelines-for-remote-linux-desktop-control/</guid><description>Open Computer Use uses a modular three-stage LLM pipeline to control a cloud Linux desktop, combining grounding, vision, and action models for flexible AI-driven automation.</description></item><item><title>OpenAgents: orchestrating multi-agent LLM workflows with Flask and Next.js</title><link>https://ramdi.fr/github-stars/openagents-orchestrating-multi-agent-llm-workflows-with-flask-and-next-js/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/openagents-orchestrating-multi-agent-llm-workflows-with-flask-and-next-js/</guid><description>OpenAgents hosts three specialized LLM agents—Data, Plugins, Web—via a Flask API and Next.js UI, integrating sandboxed code execution, plugin selection, and browser automation.</description></item><item><title>OpenAlgo: unified multi-broker algo trading platform with Python and no-code flows</title><link>https://ramdi.fr/github-stars/openalgo-unified-multi-broker-algo-trading-platform-with-python-and-no-code-flows/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/openalgo-unified-multi-broker-algo-trading-platform-with-python-and-no-code-flows/</guid><description>OpenAlgo offers a self-hosted algo trading platform with unified API for 30+ Indian brokers, Python strategy hosting, no-code flow builder, and options analytics — all sharing live sessions.</description></item><item><title>OpenAnt: An LLM-powered two-stage vulnerability discovery tool with exploit validation</title><link>https://ramdi.fr/github-stars/openant-an-llm-powered-two-stage-vulnerability-discovery-tool-with-exploit-validation/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/openant-an-llm-powered-two-stage-vulnerability-discovery-tool-with-exploit-validation/</guid><description>OpenAnt uses a two-stage LLM pipeline to detect and validate code vulnerabilities across multiple languages, reducing false positives by verifying exploits automatically.</description></item><item><title>OpenChronicle: an AX-first local memory layer for LLM agents</title><link>https://ramdi.fr/github-stars/openchronicle-an-ax-first-local-memory-layer-for-llm-agents/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/openchronicle-an-ax-first-local-memory-layer-for-llm-agents/</guid><description>OpenChronicle captures macOS accessibility events to build structured local memory for LLM agents. Its async pipeline produces persistent Markdown memory and an SQLite index.</description></item><item><title>OpenDirectory: A modular skills library for AI agents with targeted installation</title><link>https://ramdi.fr/github-stars/opendirectory-a-modular-skills-library-for-ai-agents-with-targeted-installation/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/opendirectory-a-modular-skills-library-for-ai-agents-with-targeted-installation/</guid><description>OpenDirectory provides a Python-based collection of AI agent skills with an npm CLI for browsing and installing skills targeted at specific AI agents like Claude Code or Codex.</description></item><item><title>OpenDrop: reverse-engineering Apple's AirDrop for cross-platform file sharing</title><link>https://ramdi.fr/github-stars/opendrop-reverse-engineering-apple-s-airdrop-for-cross-platform-file-sharing/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/opendrop-reverse-engineering-apple-s-airdrop-for-cross-platform-file-sharing/</guid><description>OpenDrop is a Python CLI tool that reverse-engineers Apple&amp;rsquo;s AirDrop protocol, enabling file sharing with iOS/macOS devices over AWDL. It supports sending files, URLs, and contacts-only mode on macOS/Linux.</description></item><item><title>OpenSim-core: a C++ musculoskeletal simulation engine with Python and Java bindings</title><link>https://ramdi.fr/github-stars/opensim-core-a-c-musculoskeletal-simulation-engine-with-python-and-java-bindings/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/opensim-core-a-c-musculoskeletal-simulation-engine-with-python-and-java-bindings/</guid><description>OpenSim-core is an open-source C++ library for musculoskeletal modeling and dynamic simulations, with Python and Java bindings for scripting complex biomechanics analyses.</description></item><item><title>OptiLLM: transparent inference-time scaling for improved LLM reasoning</title><link>https://ramdi.fr/github-stars/optillm-transparent-inference-time-scaling-for-improved-llm-reasoning/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/optillm-transparent-inference-time-scaling-for-improved-llm-reasoning/</guid><description>OptiLLM is an OpenAI-compatible inference proxy that boosts LLM reasoning with 20+ techniques like Mixture of Agents and MCTS, requiring no model retraining. Use a simple prefix to improve accuracy 2-10x.</description></item><item><title>orchestrator-supaconductor: AI-driven project orchestration plugin for Claude Code</title><link>https://ramdi.fr/github-stars/orchestrator-supaconductor-ai-driven-project-orchestration-plugin-for-claude-code/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/orchestrator-supaconductor-ai-driven-project-orchestration-plugin-for-claude-code/</guid><description>orchestrator-supaconductor is a Python plugin for Claude Code that automates software project workflows via natural language commands, managing sprints, coding, and testing interactively.</description></item><item><title>Organize: YAML-driven file management automation with Python CLI</title><link>https://ramdi.fr/github-stars/organize-yaml-driven-file-management-automation-with-python-cli/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/organize-yaml-driven-file-management-automation-with-python-cli/</guid><description>Organize is a Python CLI tool enabling complex file automation through YAML-defined rules. It supports filters by extension, EXIF, content, and actions like move or rename, plus a safe simulation mode.</description></item><item><title>Osintgraph: AI-driven Instagram OSINT with Neo4j graph analysis</title><link>https://ramdi.fr/github-stars/osintgraph-ai-driven-instagram-osint-with-neo4j-graph-analysis/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/osintgraph-ai-driven-instagram-osint-with-neo4j-graph-analysis/</guid><description>Osintgraph scrapes Instagram data into Neo4j and uses an AI agent for natural language investigation, enabling graph-based OSINT workflows with AI-powered querying and visualization.</description></item><item><title>OverlapNet: Siamese networks for loop closure detection in 3D LiDAR SLAM</title><link>https://ramdi.fr/github-stars/overlapnet-siamese-networks-for-loop-closure-detection-in-3d-lidar-slam/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/overlapnet-siamese-networks-for-loop-closure-detection-in-3d-lidar-slam/</guid><description>OverlapNet uses Siamese networks on 2D range images from 3D LiDAR to detect loop closures by predicting overlap and relative yaw angle simultaneously. Practical demos included.</description></item><item><title>Paper2Any: multi-modal AI pipeline converting academic papers into editable scientific artifacts</title><link>https://ramdi.fr/github-stars/paper2any-multi-modal-ai-pipeline-converting-academic-papers-into-editable-scientific-artifacts/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/paper2any-multi-modal-ai-pipeline-converting-academic-papers-into-editable-scientific-artifacts/</guid><description>Paper2Any uses chained LLM calls with structured output to convert academic papers into editable scientific figures, slides, and diagrams via a FastAPI backend and React frontend.</description></item><item><title>paperetl: a modular ETL pipeline for scientific papers with multi-format ingestion and unified schema</title><link>https://ramdi.fr/github-stars/paperetl-a-modular-etl-pipeline-for-scientific-papers-with-multi-format-ingestion-and-unified-schema/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/paperetl-a-modular-etl-pipeline-for-scientific-papers-with-multi-format-ingestion-and-unified-schema/</guid><description>paperetl is a Python ETL library that normalizes PDFs, PubMed, arXiv, TEI, and CSV metadata into a unified article schema, supporting SQLite, JSON, YAML, and Elasticsearch storage.</description></item><item><title>Parsing bank statements with monopoly-core: a per-bank parser approach in Python</title><link>https://ramdi.fr/github-stars/parsing-bank-statements-with-monopoly-core-a-per-bank-parser-approach-in-python/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/parsing-bank-statements-with-monopoly-core-a-per-bank-parser-approach-in-python/</guid><description>Monopoly-core is a Python library and CLI for converting bank statement PDFs to CSV using per-bank parser classes. It supports 20+ banks, OCR, and safety checks.</description></item><item><title>PartCrafter: compositional 3D mesh generation with latent diffusion transformers</title><link>https://ramdi.fr/github-stars/partcrafter-compositional-3d-mesh-generation-with-latent-diffusion-transformers/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/partcrafter-compositional-3d-mesh-generation-with-latent-diffusion-transformers/</guid><description>PartCrafter generates multiple semantically distinct 3D mesh parts from a single RGB image using latent diffusion transformers, enabling structured 3D generation with pretrained models and VLM-based part suggestions.</description></item><item><title>pdf-document-layout-analysis: a dual-model PDF layout analysis microservice with Docker deployment</title><link>https://ramdi.fr/github-stars/pdf-document-layout-analysis-a-dual-model-pdf-layout-analysis-microservice-with-docker-deployment/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/pdf-document-layout-analysis-a-dual-model-pdf-layout-analysis-microservice-with-docker-deployment/</guid><description>pdf-document-layout-analysis is a Dockerized microservice using Vision Grid Transformer and LightGBM for PDF layout analysis, offering high accuracy or fast processing with OCR, translation, and multi-format export.</description></item><item><title>pentest-agents: a cross-IDE autonomous bug bounty framework with multi-agent AI</title><link>https://ramdi.fr/github-stars/pentest-agents-a-cross-ide-autonomous-bug-bounty-framework-with-multi-agent-ai/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/pentest-agents-a-cross-ide-autonomous-bug-bounty-framework-with-multi-agent-ai/</guid><description>pentest-agents deploys 50 specialized AI agents across 7 coding tools with a multi-IDE portability layer, autonomous exploit chains, endpoint brain, and MCP servers for bug bounty hunting.</description></item><item><title>Pixal3D: pixel-aligned 3D asset generation from a single image with projection conditioning</title><link>https://ramdi.fr/github-stars/pixal3d-pixel-aligned-3d-asset-generation-from-a-single-image-with-projection-conditioning/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/pixal3d-pixel-aligned-3d-asset-generation-from-a-single-image-with-projection-conditioning/</guid><description>Pixal3D generates high-fidelity 3D assets with PBR textures from a single image using pixel-aligned projection conditioning. It offers a three-stage cascade and low-VRAM mode for consumer GPUs.</description></item><item><title>ProxmoxMCP-Plus: A Python toolset for advanced Proxmox MCP protocol interaction</title><link>https://ramdi.fr/github-stars/proxmoxmcp-plus-a-python-toolset-for-advanced-proxmox-mcp-protocol-interaction/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/proxmoxmcp-plus-a-python-toolset-for-advanced-proxmox-mcp-protocol-interaction/</guid><description>ProxmoxMCP-Plus is a Python-based toolset enabling advanced interaction with Proxmox VE via MCP protocol. It offers flexible config and runtime modes for sysadmins and devs.</description></item><item><title>QSTrader: a modular, schedule-driven Python framework for systematic equity backtesting</title><link>https://ramdi.fr/github-stars/qstrader-a-modular-schedule-driven-python-framework-for-systematic-equity-backtesting/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/qstrader-a-modular-schedule-driven-python-framework-for-systematic-equity-backtesting/</guid><description>QSTrader offers a modular Python backtesting framework for long-short equity strategies using daily OHLC data and calendar-driven rebalancing. Its clean separation of signal, portfolio, and execution components stands out.</description></item><item><title>ReasoningBank: Experience-Driven Memory as a New Scaling Dimension for AI Agents</title><link>https://ramdi.fr/github-stars/reasoningbank-experience-driven-memory-as-a-new-scaling-dimension-for-ai-agents/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/reasoningbank-experience-driven-memory-as-a-new-scaling-dimension-for-ai-agents/</guid><description>ReasoningBank introduces memory-aware test-time scaling for AI agents by storing reasoning traces from both successes and failures, enabling self-evolution through experience.</description></item><item><title>SafestClaw: a deterministic AI assistant with classical ML pipelines for local, secure, and zero-cost operation</title><link>https://ramdi.fr/github-stars/safestclaw-a-deterministic-ai-assistant-with-classical-ml-pipelines-for-local-secure-and-zero-cost-operation/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/safestclaw-a-deterministic-ai-assistant-with-classical-ml-pipelines-for-local-secure-and-zero-cost-operation/</guid><description>SafestClaw uses classical ML pipelines and local AI models to deliver 90% of OpenClaw&amp;rsquo;s features at zero cost, avoiding prompt injection and cloud dependencies.</description></item><item><title>SAM3-UNet: Adapting Meta's SAM3 for efficient dense prediction with a lightweight U-Net decoder</title><link>https://ramdi.fr/github-stars/sam3-unet-adapting-meta-s-sam3-for-efficient-dense-prediction-with-a-lightweight-u-net-decoder/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/sam3-unet-adapting-meta-s-sam3-for-efficient-dense-prediction-with-a-lightweight-u-net-decoder/</guid><description>SAM3-UNet adapts Meta&amp;rsquo;s SAM3 foundation model for dense prediction tasks using a parameter-efficient adapter and U-Net decoder, enabling training under 6 GB GPU memory.</description></item><item><title>scenario-lab: a Python CLI tool for scenario simulation workflows</title><link>https://ramdi.fr/github-stars/scenario-lab-a-python-cli-tool-for-scenario-simulation-workflows/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/scenario-lab-a-python-cli-tool-for-scenario-simulation-workflows/</guid><description>scenario-lab is a Python-based tool for running scenario simulations via a CLI, emphasizing reproducible workflows and modular structure with Python 3.12 venv support.</description></item><item><title>SceneSmith: AI-driven pipeline for physics-ready 3D indoor scene generation from text</title><link>https://ramdi.fr/github-stars/scenesmith-ai-driven-pipeline-for-physics-ready-3d-indoor-scene-generation-from-text/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/scenesmith-ai-driven-pipeline-for-physics-ready-3d-indoor-scene-generation-from-text/</guid><description>SceneSmith uses GPT-5-powered agents to generate physically plausible 3D indoor scenes from text prompts, ready for robotics simulation without manual cleanup.</description></item><item><title>Seeker: a social engineering tool for harvesting browser location and fingerprint data</title><link>https://ramdi.fr/github-stars/seeker-a-social-engineering-tool-for-harvesting-browser-location-and-fingerprint-data/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/seeker-a-social-engineering-tool-for-harvesting-browser-location-and-fingerprint-data/</guid><description>Seeker hosts fake web pages to trick users into granting browser location permission, harvesting precise GPS and device fingerprint data via HTML5 APIs. Built with Python and Flask, it runs on multiple platforms and supports export to Google Earth and Telegram.</description></item><item><title>Skill Conductor: Architecture-first lifecycle management for AI agent skills</title><link>https://ramdi.fr/github-stars/skill-conductor-architecture-first-lifecycle-management-for-ai-agent-skills/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/skill-conductor-architecture-first-lifecycle-management-for-ai-agent-skills/</guid><description>Skill Conductor enforces design patterns and uses a 5-mode lifecycle to manage AI agent skills, avoiding common pitfalls like the &amp;lsquo;description trap&amp;rsquo; for more reliable skill development.</description></item><item><title>Spotify2YoutubeMusic: a Python tool for migrating music libraries between Spotify and YouTube Music</title><link>https://ramdi.fr/github-stars/spotify2youtubemusic-a-python-tool-for-migrating-music-libraries-between-spotify-and-youtube-music/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/spotify2youtubemusic-a-python-tool-for-migrating-music-libraries-between-spotify-and-youtube-music/</guid><description>Spotify2YoutubeMusic is a Python app that migrates playlists and liked songs between Spotify and YouTube Music using smart caching and batch processing for efficiency.</description></item><item><title>SuperClaude: Meta-programming Claude Code into a structured AI development platform</title><link>https://ramdi.fr/github-stars/superclaude-meta-programming-claude-code-into-a-structured-ai-development-platform/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/superclaude-meta-programming-claude-code-into-a-structured-ai-development-platform/</guid><description>SuperClaude transforms Claude Code into a structured AI development platform using behavioral instruction injection, 30 slash commands, 20 specialized agents, and 8 MCP server integrations for faster, token-efficient workflows.</description></item><item><title>Supertonic-3: on-device multilingual TTS with OpenAI-compatible API and zero-shot voice cloning</title><link>https://ramdi.fr/github-stars/supertonic-3-on-device-multilingual-tts-with-openai-compatible-api-and-zero-shot-voice-cloning/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/supertonic-3-on-device-multilingual-tts-with-openai-compatible-api-and-zero-shot-voice-cloning/</guid><description>Supertonic-3 is a Python TTS library running fully on-device via ONNX runtime, supporting 31 languages, zero-shot voice cloning, and a drop-in OpenAI-compatible API for local TTS deployment.</description></item><item><title>SupoClip: self-hostable AI-powered video clipping with multi-LLM backend abstraction</title><link>https://ramdi.fr/github-stars/supoclip-self-hostable-ai-powered-video-clipping-with-multi-llm-backend-abstraction/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/supoclip-self-hostable-ai-powered-video-clipping-with-multi-llm-backend-abstraction/</guid><description>SupoClip is an open-source self-hosted AI video clipper using AssemblyAI transcription and multiple LLM backends including local Ollama. It runs on Docker Compose with FastAPI and Next.js.</description></item><item><title>SVFR: unified video face restoration with task-conditioned stable video diffusion</title><link>https://ramdi.fr/github-stars/svfr-unified-video-face-restoration-with-task-conditioned-stable-video-diffusion/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/svfr-unified-video-face-restoration-with-task-conditioned-stable-video-diffusion/</guid><description>SVFR combines blind face restoration, colorization, and inpainting in a single stable video diffusion model, enabling efficient multi-task video face enhancement.</description></item><item><title>Tencent HY-World 2.0: multi-modal pipeline for persistent, editable 3D world generation</title><link>https://ramdi.fr/github-stars/tencent-hy-world-2-0-multi-modal-pipeline-for-persistent-editable-3d-world-generation/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/tencent-hy-world-2-0-multi-modal-pipeline-for-persistent-editable-3d-world-generation/</guid><description>Tencent&amp;rsquo;s HY-World 2.0 generates persistent 3D assets from text, images, or video using a four-stage pipeline. It outputs editable worlds compatible with Blender, Unity, and Unreal Engine.</description></item><item><title>Tether Rally: WebRTC remote control for ARRMA RC cars with clever hardware emulation</title><link>https://ramdi.fr/github-stars/tether-rally-webrtc-remote-control-for-arrma-rc-cars-with-clever-hardware-emulation/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/tether-rally-webrtc-remote-control-for-arrma-rc-cars-with-clever-hardware-emulation/</guid><description>Tether Rally enables remote driving of ARRMA RC cars via browser with 720p@60fps video, using ESP32 DAC joystick emulation and WebRTC video streaming. Open source, ~$60-80 hardware.</description></item><item><title>TheAnimeScripter: a unified multi-backend AI video enhancement toolkit with efficient model chaining</title><link>https://ramdi.fr/github-stars/theanimescripter-a-unified-multi-backend-ai-video-enhancement-toolkit-with-efficient-model-chaining/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/theanimescripter-a-unified-multi-backend-ai-video-enhancement-toolkit-with-efficient-model-chaining/</guid><description>TheAnimeScripter wraps dozens of AI video models behind one CLI and AE plugin, supporting CUDA, TensorRT, DirectML, OpenVINO backends. Model chaining avoids redundant disk writes.</description></item><item><title>Tidal-Media-Downloader: a pragmatic Python CLI for downloading TIDAL music and videos</title><link>https://ramdi.fr/github-stars/tidal-media-downloader-a-pragmatic-python-cli-for-downloading-tidal-music-and-videos/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/tidal-media-downloader-a-pragmatic-python-cli-for-downloading-tidal-music-and-videos/</guid><description>Tidal-Media-Downloader is a Python CLI tool that downloads TIDAL streaming music and videos using open-source libraries for API access and MQA decoding, with CLI and GUI modes.</description></item><item><title>Unmanic: a plugin-driven media library optimizer with scheduler, watcher, and web UI</title><link>https://ramdi.fr/github-stars/unmanic-a-plugin-driven-media-library-optimizer-with-scheduler-watcher-and-web-ui/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/unmanic-a-plugin-driven-media-library-optimizer-with-scheduler-watcher-and-web-ui/</guid><description>Unmanic is a Python-based self-hosted tool that automates media file optimization via a plugin system, combining scheduling, file watching, parallel tasks, and a web UI for management.</description></item><item><title>VisoMaster Fusion: a portable Windows app bundling multiple AI face-swapping models</title><link>https://ramdi.fr/github-stars/visomaster-fusion-a-portable-windows-app-bundling-multiple-ai-face-swapping-models/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/visomaster-fusion-a-portable-windows-app-bundling-multiple-ai-face-swapping-models/</guid><description>VisoMaster Fusion bundles over a dozen AI face-swapping models into a portable Windows desktop app with automatic runtime setup, simplifying the complex AI video editing workflow.</description></item><item><title>vLLM Compressor: Practical quantization and compression for large language model inference</title><link>https://ramdi.fr/github-stars/vllm-compressor-practical-quantization-and-compression-for-large-language-model-inference/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/vllm-compressor-practical-quantization-and-compression-for-large-language-model-inference/</guid><description>vLLM Compressor applies advanced quantization and compression techniques to large language models, enabling optimized inference without requiring full model definitions.</description></item><item><title>WhatsApp-OSINT: A Python CLI tool for WhatsApp phone number intelligence via RapidAPI</title><link>https://ramdi.fr/github-stars/whatsapp-osint-a-python-cli-tool-for-whatsapp-phone-number-intelligence-via-rapidapi/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/whatsapp-osint-a-python-cli-tool-for-whatsapp-phone-number-intelligence-via-rapidapi/</guid><description>WhatsApp-OSINT is a Python CLI that queries RapidAPI endpoints to extract WhatsApp phone number intelligence, including profile pics, business status, linked devices, and privacy settings.</description></item><item><title>YuE: scalable dual-track foundation model for lyrics-to-song generation</title><link>https://ramdi.fr/github-stars/yue-scalable-dual-track-foundation-model-for-lyrics-to-song-generation/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/yue-scalable-dual-track-foundation-model-for-lyrics-to-song-generation/</guid><description>YuE is an open-source Python foundation model for generating complete songs from lyrics using a two-stage architecture and audio in-context learning. It supports style cloning and LoRA finetuning under Apache 2.0.</description></item><item><title>Minds Platform: An enterprise-grade AI foundation for autonomous agents and semantic search</title><link>https://ramdi.fr/github-stars/minds-platform-an-enterprise-grade-ai-foundation-for-autonomous-agents-and-semantic-search/</link><pubDate>Fri, 15 May 2026 14:23:51 +0000</pubDate><guid>https://ramdi.fr/github-stars/minds-platform-an-enterprise-grade-ai-foundation-for-autonomous-agents-and-semantic-search/</guid><description>Minds Platform offers a Python-based AI foundation with autonomous agents and semantic search, designed for flexible enterprise deployment across cloud and on-prem environments.</description></item><item><title>Aider: precise AI pair programming with whole-codebase awareness</title><link>https://ramdi.fr/github-stars/aider-precise-ai-pair-programming-with-whole-codebase-awareness/</link><pubDate>Sat, 09 May 2026 11:42:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/aider-precise-ai-pair-programming-with-whole-codebase-awareness/</guid><description>Aider is a terminal-based AI pair programming tool that builds a repository map for full codebase context, enabling precise, developer-controlled edits with multi-LLM support and git integration.</description></item><item><title>Graphify: Local AST parsing and AI-enhanced knowledge graphs for codebases</title><link>https://ramdi.fr/github-stars/graphify-local-ast-parsing-and-ai-enhanced-knowledge-graphs-for-codebases/</link><pubDate>Sat, 09 May 2026 11:42:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/graphify-local-ast-parsing-and-ai-enhanced-knowledge-graphs-for-codebases/</guid><description>Graphify uses local tree-sitter parsers to build interactive codebase knowledge graphs, integrating with AI coding assistants while preserving privacy. Supports 25+ languages and multi-format assets.</description></item><item><title>Inside Claude Code From Scratch: A practical reconstruction of Anthropic's coding agent</title><link>https://ramdi.fr/github-stars/inside-claude-code-from-scratch-a-practical-reconstruction-of-anthropic-s-coding-agent/</link><pubDate>Sat, 09 May 2026 11:42:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-claude-code-from-scratch-a-practical-reconstruction-of-anthropic-s-coding-agent/</guid><description>Claude Code From Scratch distills Anthropic&amp;rsquo;s 500K+ line coding agent into ~8,000 lines of Python and TypeScript, revealing core architecture like the Agent Loop, semantic memory, multi-agent skills, and context compression.</description></item><item><title>OpenAlpha_Evolve: autonomous code evolution with LLM-driven diff mutations</title><link>https://ramdi.fr/github-stars/openalpha-evolve-autonomous-code-evolution-with-llm-driven-diff-mutations/</link><pubDate>Sat, 09 May 2026 11:42:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/openalpha-evolve-autonomous-code-evolution-with-llm-driven-diff-mutations/</guid><description>OpenAlpha_Evolve uses large language models to generate precise code diffs as mutations in an evolutionary algorithm, enabling autonomous iterative code improvement with sandboxed evaluation.</description></item><item><title>yt-dlp: modular extractor architecture for unified media downloading</title><link>https://ramdi.fr/github-stars/yt-dlp-modular-extractor-architecture-for-unified-media-downloading/</link><pubDate>Sat, 09 May 2026 11:42:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/yt-dlp-modular-extractor-architecture-for-unified-media-downloading/</guid><description>yt-dlp is a Python CLI tool with 1,800+ site extractors for audio/video downloading, featuring extensible plugins, multi-OS binaries, and advanced post-processing.</description></item><item><title>RAGFlow: a modular, agentic retrieval-augmented generation engine with deep document understanding</title><link>https://ramdi.fr/github-stars/ragflow-a-modular-agentic-retrieval-augmented-generation-engine-with-deep-document-understanding/</link><pubDate>Wed, 06 May 2026 18:58:37 +0000</pubDate><guid>https://ramdi.fr/github-stars/ragflow-a-modular-agentic-retrieval-augmented-generation-engine-with-deep-document-understanding/</guid><description>RAGFlow is an open-source Python RAG engine combining deep document parsing, configurable pipelines, agentic workflows, and sandboxed code execution for LLM context management.</description></item><item><title>cocoindex-code: AST-aware semantic code search with efficient embedding integration</title><link>https://ramdi.fr/github-stars/cocoindex-code-ast-aware-semantic-code-search-with-efficient-embedding-integration/</link><pubDate>Tue, 05 May 2026 22:24:55 +0000</pubDate><guid>https://ramdi.fr/github-stars/cocoindex-code-ast-aware-semantic-code-search-with-efficient-embedding-integration/</guid><description>cocoindex-code combines AST parsing with semantic embeddings for precise code search, offering a zero-config setup, background indexing daemon, and smooth integration with coding agents.</description></item><item><title>Langchain-Chatchat: A model-agnostic orchestration layer for Chinese-language RAG and Agents</title><link>https://ramdi.fr/github-stars/langchain-chatchat-a-model-agnostic-orchestration-layer-for-chinese-language-rag-and-agents/</link><pubDate>Tue, 05 May 2026 22:24:55 +0000</pubDate><guid>https://ramdi.fr/github-stars/langchain-chatchat-a-model-agnostic-orchestration-layer-for-chinese-language-rag-and-agents/</guid><description>Langchain-Chatchat offers a flexible, offline-capable orchestration layer for multiple Chinese LLMs and RAG approaches, enabling seamless model swaps across frameworks without code changes.</description></item><item><title>Prefect: Python-native workflow orchestration made simple and scalable</title><link>https://ramdi.fr/github-stars/prefect-python-native-workflow-orchestration-made-simple-and-scalable/</link><pubDate>Tue, 05 May 2026 22:24:55 +0000</pubDate><guid>https://ramdi.fr/github-stars/prefect-python-native-workflow-orchestration-made-simple-and-scalable/</guid><description>Prefect turns Python scripts into production-ready workflows with minimal code changes, offering a self-hosted UI and cloud option for reliable, observable pipelines.</description></item><item><title>Quivr: A Python framework for flexible retrieval-augmented generation pipelines</title><link>https://ramdi.fr/github-stars/quivr-a-python-framework-for-flexible-retrieval-augmented-generation-pipelines/</link><pubDate>Tue, 05 May 2026 22:24:55 +0000</pubDate><guid>https://ramdi.fr/github-stars/quivr-a-python-framework-for-flexible-retrieval-augmented-generation-pipelines/</guid><description>Quivr is a Python framework offering an opinionated, pluggable retrieval-augmented generation pipeline with multi-LLM support and YAML-defined workflows for flexible knowledge retrieval.</description></item><item><title>Softaworks Agent Toolkit: A modular plugin marketplace for AI coding agents</title><link>https://ramdi.fr/github-stars/softaworks-agent-toolkit-a-modular-plugin-marketplace-for-ai-coding-agents/</link><pubDate>Tue, 05 May 2026 22:24:55 +0000</pubDate><guid>https://ramdi.fr/github-stars/softaworks-agent-toolkit-a-modular-plugin-marketplace-for-ai-coding-agents/</guid><description>Softaworks Agent Toolkit offers 40+ modular AI skills and plugins for coding agents like Claude Code, enabling composable AI workflows via a plugin marketplace. Here&amp;rsquo;s how it works.</description></item><item><title>Sherlock: A modular Python CLI tool for username reconnaissance across 400+ social networks</title><link>https://ramdi.fr/github-stars/sherlock-a-modular-python-cli-tool-for-username-reconnaissance-across-400-social-networks/</link><pubDate>Tue, 05 May 2026 18:13:32 +0000</pubDate><guid>https://ramdi.fr/github-stars/sherlock-a-modular-python-cli-tool-for-username-reconnaissance-across-400-social-networks/</guid><description>Sherlock is a Python CLI tool that checks username availability across 400+ social networks using a modular JSON-driven detection system. Practical, extensible, and flexible.</description></item><item><title>Automating Matplotlib cheat sheets with programmatic figures and LaTeX</title><link>https://ramdi.fr/github-stars/automating-matplotlib-cheat-sheets-with-programmatic-figures-and-latex/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/automating-matplotlib-cheat-sheets-with-programmatic-figures-and-latex/</guid><description>This repo automates Matplotlib cheat sheet generation by programmatically creating figures with Python and compiling polished PDFs using xelatex, offering a reproducible documentation workflow.</description></item><item><title>cfpsec: a Python CLI for secure fetching of security conference CFPs</title><link>https://ramdi.fr/github-stars/cfpsec-a-python-cli-for-secure-fetching-of-security-conference-cfps/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/cfpsec-a-python-cli-for-secure-fetching-of-security-conference-cfps/</guid><description>cfpsec is a Python CLI tool that fetches Call For Papers data from cfptime.org with security-focused hardening like ANSI escape sanitization and CSV formula injection protection.</description></item><item><title>changedetection.io: AI-assisted web change monitoring with flexible fetchers and self-hosted notifications</title><link>https://ramdi.fr/github-stars/changedetection-io-ai-assisted-web-change-monitoring-with-flexible-fetchers-and-self-hosted-notifications/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/changedetection-io-ai-assisted-web-change-monitoring-with-flexible-fetchers-and-self-hosted-notifications/</guid><description>changedetection.io is a Python-based web monitoring tool that detects page content changes with AI filtering, supports HTTP and Playwright fetchers, and sends notifications via Discord, Slack, Telegram, and webhooks.</description></item><item><title>daymade/claude-code-skills: a production-hardened plugin marketplace for Claude Code skills</title><link>https://ramdi.fr/github-stars/daymade-claude-code-skills-a-production-hardened-plugin-marketplace-for-claude-code-skills/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/daymade-claude-code-skills-a-production-hardened-plugin-marketplace-for-claude-code-skills/</guid><description>daymade/claude-code-skills offers a robust plugin marketplace with 51 pre-built Claude Code skills and a hardened skill-creator fork featuring security scanning and expanded validation.</description></item><item><title>Flexible chunk-size Whisper inference with optimized on-device engines in TheWhisper</title><link>https://ramdi.fr/github-stars/flexible-chunk-size-whisper-inference-with-optimized-on-device-engines-in-thewhisper/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/flexible-chunk-size-whisper-inference-with-optimized-on-device-engines-in-thewhisper/</guid><description>TheWhisper breaks Whisper&amp;rsquo;s 30s fixed chunk limit by supporting flexible chunk sizes for streaming speech-to-text. It provides optimized CoreML and CUDA engines for Apple Silicon and NVIDIA GPUs.</description></item><item><title>google/agents-cli: a Python CLI for AI agent lifecycle management on Google Cloud</title><link>https://ramdi.fr/github-stars/google-agents-cli-a-python-cli-for-ai-agent-lifecycle-management-on-google-cloud/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/google-agents-cli-a-python-cli-for-ai-agent-lifecycle-management-on-google-cloud/</guid><description>google/agents-cli enhances coding assistants with skills for building, evaluating, and deploying AI agents on Google Cloud&amp;rsquo;s ADK. It offers a modular CLI workflow covering agent scaffolding to observability.</description></item><item><title>How comfyui-custom-node-skills turns Claude Code into a ComfyUI node development expert</title><link>https://ramdi.fr/github-stars/how-comfyui-custom-node-skills-turns-claude-code-into-a-comfyui-node-development-expert/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/how-comfyui-custom-node-skills-turns-claude-code-into-a-comfyui-node-development-expert/</guid><description>comfyui-custom-node-skills equips Claude Code with 9 skills to master ComfyUI custom node development, covering full lifecycle with trigger-based loading and verified source alignment.</description></item><item><title>How Kiln orchestrates multi-agent AI workflows using markdown and Claude Code</title><link>https://ramdi.fr/github-stars/how-kiln-orchestrates-multi-agent-ai-workflows-using-markdown-and-claude-code/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/how-kiln-orchestrates-multi-agent-ai-workflows-using-markdown-and-claude-code/</guid><description>Kiln implements a 7-step multi-agent AI pipeline entirely through markdown files and Claude Code&amp;rsquo;s native primitives, avoiding any runtime or package dependencies.</description></item><item><title>How obsidian-second-brain transforms your Obsidian vault into an AI-maintained knowledge base</title><link>https://ramdi.fr/github-stars/how-obsidian-second-brain-transforms-your-obsidian-vault-into-an-ai-maintained-knowledge-base/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/how-obsidian-second-brain-transforms-your-obsidian-vault-into-an-ai-maintained-knowledge-base/</guid><description>obsidian-second-brain rewrites Obsidian vault pages autonomously using Claude Code agents, detecting contradictions and running scheduled maintenance for a self-healing AI knowledge base.</description></item><item><title>Inside Genie Sim 3.0: LLM-driven embodied AI simulation with high-fidelity 3D scenes</title><link>https://ramdi.fr/github-stars/inside-genie-sim-3-0-llm-driven-embodied-ai-simulation-with-high-fidelity-3d-scenes/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-genie-sim-3-0-llm-driven-embodied-ai-simulation-with-high-fidelity-3d-scenes/</guid><description>Genie Sim 3.0 is an open-source platform combining 3D Gaussian Splatting and LLM-driven scene generation for embodied AI simulation, offering large-scale synthetic data and low sim-to-real discrepancy.</description></item><item><title>Mapping the landscape of terminal-native AI coding agents: a curated directory analysis</title><link>https://ramdi.fr/github-stars/mapping-the-landscape-of-terminal-native-ai-coding-agents-a-curated-directory-analysis/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/mapping-the-landscape-of-terminal-native-ai-coding-agents-a-curated-directory-analysis/</guid><description>A curated directory catalogs over 80 terminal-native AI coding agents and harnesses, highlighting open-source projects, platform agents, and emerging architectural patterns in the CLI AI agent space.</description></item><item><title>MedRAX: orchestrating specialized AI tools for chest X-ray analysis with dynamic routing</title><link>https://ramdi.fr/github-stars/medrax-orchestrating-specialized-ai-tools-for-chest-x-ray-analysis-with-dynamic-routing/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/medrax-orchestrating-specialized-ai-tools-for-chest-x-ray-analysis-with-dynamic-routing/</guid><description>MedRAX uses GPT-4o to dynamically route medical queries across multiple AI models for chest X-ray interpretation. It offers modular, tool-agnostic orchestration with a Gradio interface.</description></item><item><title>Octopoda-OS: a memory layer for AI agents with loop detection and audit trails</title><link>https://ramdi.fr/github-stars/octopoda-os-a-memory-layer-for-ai-agents-with-loop-detection-and-audit-trails/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/octopoda-os-a-memory-layer-for-ai-agents-with-loop-detection-and-audit-trails/</guid><description>Octopoda-OS is a Python library providing persistent memory, loop detection, and audit trails for AI agents. It supports SQLite/PostgreSQL, zero-config runtime, and cloud sync.</description></item><item><title>secrets-patterns-db: expanding regex coverage for secret scanning in codebases</title><link>https://ramdi.fr/github-stars/secrets-patterns-db-expanding-regex-coverage-for-secret-scanning-in-codebases/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/secrets-patterns-db-expanding-regex-coverage-for-secret-scanning-in-codebases/</guid><description>secrets-patterns-db offers over 1600 regex patterns for detecting secrets in code, doubling coverage compared to TruffleHog and vastly outpacing Gitleaks. It enhances AppSec scanning with tested, categorized regexes.</description></item><item><title>SkillClaw: A modular Python framework for orchestrating AI agents across OpenAI-compatible and AWS Bedrock APIs</title><link>https://ramdi.fr/github-stars/skillclaw-a-modular-python-framework-for-orchestrating-ai-agents-across-openai-compatible-and-aws-bedrock-apis/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/skillclaw-a-modular-python-framework-for-orchestrating-ai-agents-across-openai-compatible-and-aws-bedrock-apis/</guid><description>SkillClaw is a Python framework enabling flexible AI agent orchestration across OpenAI-compatible and AWS Bedrock APIs, focusing on modularity and provider-agnostic design.</description></item><item><title>4DGen: geometry-consistent multi-view RGB-D video generation for robotic manipulation</title><link>https://ramdi.fr/github-stars/4dgen-geometry-consistent-multi-view-rgb-d-video-generation-for-robotic-manipulation/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/4dgen-geometry-consistent-multi-view-rgb-d-video-generation-for-robotic-manipulation/</guid><description>4DGen extends Stable Video Diffusion to generate geometry-consistent multi-view RGB-D videos from single RGB-D inputs using pointmap latents. Trained on multi-view robotic datasets, it enables robot pose extraction from generated videos.</description></item><item><title>Action100M: Hierarchical Tree-of-Captions for Multi-Scale Video Understanding</title><link>https://ramdi.fr/github-stars/action100m-hierarchical-tree-of-captions-for-multi-scale-video-understanding/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/action100m-hierarchical-tree-of-captions-for-multi-scale-video-understanding/</guid><description>Action100M provides a hierarchical Tree-of-Captions annotation for 100M video segments, enabling multi-scale video understanding with LLM-generated captions. Explore its structure, tech strengths, and how to access the data.</description></item><item><title>agentic-stack: portable multi-agent memory for AI coding assistants</title><link>https://ramdi.fr/github-stars/agentic-stack-portable-multi-agent-memory-for-ai-coding-assistants/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/agentic-stack-portable-multi-agent-memory-for-ai-coding-assistants/</guid><description>agentic-stack provides a harness-agnostic shared memory layer for AI coding agents, enabling seamless context persistence and migration across tools like Claude Code and Cursor.</description></item><item><title>autoMate: a local-first AI hub exposing 40+ tools via MCP-over-HTTP</title><link>https://ramdi.fr/github-stars/automate-a-local-first-ai-hub-exposing-40-tools-via-mcp-over-http/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/automate-a-local-first-ai-hub-exposing-40-tools-via-mcp-over-http/</guid><description>autoMate exposes 40+ AI tools and 31 SaaS APIs via MCP-over-HTTP on localhost, with encrypted storage and multi-provider LLM support. A local AI infrastructure hub with privacy-first design.</description></item><item><title>Building a zero-cost currency exchange API with CDN-hosted static files</title><link>https://ramdi.fr/github-stars/building-a-zero-cost-currency-exchange-api-with-cdn-hosted-static-files/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/building-a-zero-cost-currency-exchange-api-with-cdn-hosted-static-files/</guid><description>Explore how exchange-api delivers real-time and historical currency rates via CDN-hosted static JSON files, achieving zero rate limits and blazing fast responses without a traditional backend.</description></item><item><title>Building machine learning intuition through engineering analogies with thereisnospoon</title><link>https://ramdi.fr/github-stars/building-machine-learning-intuition-through-engineering-analogies-with-thereisnospoon/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/building-machine-learning-intuition-through-engineering-analogies-with-thereisnospoon/</guid><description>There Is No Spoon offers a unique ML primer for software engineers, using physical analogies to build deep intuition for neural networks and architectures beyond memorization.</description></item><item><title>ChatTTS: conversational text-to-speech with prosodic control and responsible AI tradeoffs</title><link>https://ramdi.fr/github-stars/chattts-conversational-text-to-speech-with-prosodic-control-and-responsible-ai-tradeoffs/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/chattts-conversational-text-to-speech-with-prosodic-control-and-responsible-ai-tradeoffs/</guid><description>ChatTTS is an open-source conversational text-to-speech model trained on 100,000+ hours of bilingual audio. It offers fine-grained prosodic control and employs intentional quality degradation to prevent misuse.</description></item><item><title>CodeFormer: Deep learning-based blind face restoration with fidelity control</title><link>https://ramdi.fr/github-stars/codeformer-deep-learning-based-blind-face-restoration-with-fidelity-control/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/codeformer-deep-learning-based-blind-face-restoration-with-fidelity-control/</guid><description>CodeFormer uses a codebook transformer architecture for blind face restoration, letting users control the tradeoff between quality and fidelity with a unique fidelity weight parameter.</description></item><item><title>DeepDrone: natural language AI control for drones with real-time telemetry and MAVLink integration</title><link>https://ramdi.fr/github-stars/deepdrone-natural-language-ai-control-for-drones-with-real-time-telemetry-and-mavlink-integration/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/deepdrone-natural-language-ai-control-for-drones-with-real-time-telemetry-and-mavlink-integration/</guid><description>DeepDrone uses LLMs to translate natural language commands into structured drone operations via MAVLink, with real-time telemetry and safety constraints. Python backend, FastAPI, LiteLLM, and JS frontend.</description></item><item><title>dj-control-room: a Django admin extension with plugin architecture using Python entry points</title><link>https://ramdi.fr/github-stars/dj-control-room-a-django-admin-extension-with-plugin-architecture-using-python-entry-points/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/dj-control-room-a-django-admin-extension-with-plugin-architecture-using-python-entry-points/</guid><description>dj-control-room is a Django admin extension that centralizes multiple admin panels via a plugin system using Python entry points, enabling zero-configuration panel discovery and secure third-party integration.</description></item><item><title>DroneAware Node: turning a Raspberry Pi into a distributed drone detection sensor</title><link>https://ramdi.fr/github-stars/droneaware-node-turning-a-raspberry-pi-into-a-distributed-drone-detection-sensor/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/droneaware-node-turning-a-raspberry-pi-into-a-distributed-drone-detection-sensor/</guid><description>DroneAware Node uses Raspberry Pi with BLE and WiFi to capture FAA Remote ID broadcasts, building a community-powered drone detection network with a simple install.</description></item><item><title>DSPy agent skills pack with GEPA optimization for Claude Code and Codex CLI</title><link>https://ramdi.fr/github-stars/dspy-agent-skills-pack-with-gepa-optimization-for-claude-code-and-codex-cli/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/dspy-agent-skills-pack-with-gepa-optimization-for-claude-code-and-codex-cli/</guid><description>Explore a production-grade pack of DSPy 3.2.x agent skills with GEPA optimization, delivering up to +19.53 accuracy on RAG QA for Claude Code and Codex CLI agents.</description></item><item><title>Elato-Local: a local voice AI platform bridging desktop and embedded IoT on Apple Silicon</title><link>https://ramdi.fr/github-stars/elato-local-a-local-voice-ai-platform-bridging-desktop-and-embedded-iot-on-apple-silicon/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/elato-local-a-local-voice-ai-platform-bridging-desktop-and-embedded-iot-on-apple-silicon/</guid><description>Elato-Local is a local voice AI platform combining Whisper ASR, local LLMs, and ESP32-S3 firmware flashing from a Tauri desktop app. It enables subscription-free, privacy-first AI on Apple Silicon with embedded device integration.</description></item><item><title>FinalRecon: a unified Python CLI for comprehensive web reconnaissance and OSINT automation</title><link>https://ramdi.fr/github-stars/finalrecon-a-unified-python-cli-for-comprehensive-web-reconnaissance-and-osint-automation/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/finalrecon-a-unified-python-cli-for-comprehensive-web-reconnaissance-and-osint-automation/</guid><description>FinalRecon consolidates fragmented OSINT and web reconnaissance workflows into a single Python CLI tool, integrating multiple data sources and scanning techniques with modular API key support.</description></item><item><title>Hierarchical brute force for gate remotes with Flipper Zero .sub files</title><link>https://ramdi.fr/github-stars/hierarchical-brute-force-for-gate-remotes-with-flipper-zero-sub-files/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/hierarchical-brute-force-for-gate-remotes-with-flipper-zero-sub-files/</guid><description>This Python tool generates Flipper Zero files to brute force gate remotes using hierarchical binary search on 6561 DIP switch combinations, cutting brute force time drastically.</description></item><item><title>Inside capa: a Python engine for binary capability analysis with instruction-level evidence</title><link>https://ramdi.fr/github-stars/inside-capa-a-python-engine-for-binary-capability-analysis-with-instruction-level-evidence/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-capa-a-python-engine-for-binary-capability-analysis-with-instruction-level-evidence/</guid><description>Explore capa, a Python tool by Mandiant that analyzes binaries to identify capabilities via rule matching, with detailed evidence tracing for malware analysts.</description></item><item><title>Inside Company Research Agent: automating business intelligence with multi-API AI agents</title><link>https://ramdi.fr/github-stars/inside-company-research-agent-automating-business-intelligence-with-multi-api-ai-agents/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-company-research-agent-automating-business-intelligence-with-multi-api-ai-agents/</guid><description>Company Research Agent automates detailed business research by orchestrating OpenAI, Google Gemini, Tavily APIs and geolocation data via a Python backend and Node.js frontend. Setup script streamlines install.</description></item><item><title>Inside SearXNG: a modular metasearch engine prioritizing privacy and extensibility</title><link>https://ramdi.fr/github-stars/inside-searxng-a-modular-metasearch-engine-prioritizing-privacy-and-extensibility/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-searxng-a-modular-metasearch-engine-prioritizing-privacy-and-extensibility/</guid><description>SearXNG is a privacy-first metasearch engine aggregating results from 70+ providers using a modular plugin architecture with caching, rate limiting, and deduplication.</description></item><item><title>Medical-SAM3: adapting foundation models for prompt-driven medical image segmentation</title><link>https://ramdi.fr/github-stars/medical-sam3-adapting-foundation-models-for-prompt-driven-medical-image-segmentation/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/medical-sam3-adapting-foundation-models-for-prompt-driven-medical-image-segmentation/</guid><description>Medical-SAM3 adapts the SAM3 foundation model for universal prompt-driven medical image segmentation, offering pretrained weights and evaluation tools on diverse medical datasets.</description></item><item><title>Modular AI agent skills for medical research with MedSkillAudit quality control</title><link>https://ramdi.fr/github-stars/modular-ai-agent-skills-for-medical-research-with-medskillaudit-quality-control/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/modular-ai-agent-skills-for-medical-research-with-medskillaudit-quality-control/</guid><description>Explore a modular AI skill library for medical research workflows featuring 500+ skills and a unique MedSkillAudit quality framework ensuring scientific and methodological rigor.</description></item><item><title>NetBox: a source of truth for network infrastructure with modular automation architecture</title><link>https://ramdi.fr/github-stars/netbox-a-source-of-truth-for-network-infrastructure-with-modular-automation-architecture/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/netbox-a-source-of-truth-for-network-infrastructure-with-modular-automation-architecture/</guid><description>NetBox is an open-source IPAM/DCIM platform that models network infrastructure as intended state, feeding automation tools via REST APIs for flexible network management.</description></item><item><title>OVIE: Monocular novel view synthesis without multi-view supervision</title><link>https://ramdi.fr/github-stars/ovie-monocular-novel-view-synthesis-without-multi-view-supervision/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/ovie-monocular-novel-view-synthesis-without-multi-view-supervision/</guid><description>OVIE trains novel view synthesis models using unpaired internet images, avoiding the need for calibrated multi-view datasets. It uses Vision Transformers and foundation models for pose and depth encoding.</description></item><item><title>PokieTicker: layered AI-driven stock market analysis with sentiment and XGBoost</title><link>https://ramdi.fr/github-stars/pokieticker-layered-ai-driven-stock-market-analysis-with-sentiment-and-xgboost/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/pokieticker-layered-ai-driven-stock-market-analysis-with-sentiment-and-xgboost/</guid><description>PokieTicker combines rule-based filtering, LLM sentiment analysis, and XGBoost prediction in a full-stack stock analysis app. Runs locally with no API keys.</description></item><item><title>Social-Media-OSINT: a curated toolkit for social media investigations</title><link>https://ramdi.fr/github-stars/social-media-osint-a-curated-toolkit-for-social-media-investigations/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/social-media-osint-a-curated-toolkit-for-social-media-investigations/</guid><description>Social-Media-OSINT is a curated collection of 200+ tools for social media intelligence gathering, organized by platform and technique. It supports systematic OSINT workflows.</description></item><item><title>Voice-Pro: chaining Whisper, translation, and voice cloning in a portable Gradio app</title><link>https://ramdi.fr/github-stars/voice-pro-chaining-whisper-translation-and-voice-cloning-in-a-portable-gradio-app/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/voice-pro-chaining-whisper-translation-and-voice-cloning-in-a-portable-gradio-app/</guid><description>Voice-Pro bundles Whisper variants, translation, and zero-shot voice cloning into a single Python Gradio app, balancing heavy AI models with a portable Windows-first setup.</description></item><item><title>ZenML: a unified MLOps platform bridging classical ML and AI agent orchestration</title><link>https://ramdi.fr/github-stars/zenml-a-unified-mlops-platform-bridging-classical-ml-and-ai-agent-orchestration/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/zenml-a-unified-mlops-platform-bridging-classical-ml-and-ai-agent-orchestration/</guid><description>ZenML offers an open-source Python SDK to orchestrate full ML and AI agent lifecycles, integrating popular tools and enabling natural-language MLOps interactions via its MCP server.</description></item><item><title>A curated 100-day machine learning journey with code and resources</title><link>https://ramdi.fr/github-stars/a-curated-100-day-machine-learning-journey-with-code-and-resources/</link><pubDate>Mon, 04 May 2026 10:23:03 +0000</pubDate><guid>https://ramdi.fr/github-stars/a-curated-100-day-machine-learning-journey-with-code-and-resources/</guid><description>Explore a 100-day machine learning coding challenge combining classical algorithms, deep learning, and curated resources. A practical, day-by-day learning path for self-directed devs.</description></item><item><title>EvoClaw: Structured memory and identity evolution framework for OpenClaw AI agents</title><link>https://ramdi.fr/github-stars/evoclaw-structured-memory-and-identity-evolution-framework-for-openclaw-ai-agents/</link><pubDate>Mon, 04 May 2026 10:23:03 +0000</pubDate><guid>https://ramdi.fr/github-stars/evoclaw-structured-memory-and-identity-evolution-framework-for-openclaw-ai-agents/</guid><description>EvoClaw enforces AI agent memory and identity evolution with an 8-validator pipeline ensuring integrity and governance, featuring a tiered memory system and radial mindmap UI.</description></item><item><title>mitmproxy2swagger: automating OpenAPI spec generation from network captures with a human-in-the-loop workflow</title><link>https://ramdi.fr/github-stars/mitmproxy2swagger-automating-openapi-spec-generation-from-network-captures-with-a-human-in-the-loop-workflow/</link><pubDate>Mon, 04 May 2026 10:23:03 +0000</pubDate><guid>https://ramdi.fr/github-stars/mitmproxy2swagger-automating-openapi-spec-generation-from-network-captures-with-a-human-in-the-loop-workflow/</guid><description>mitmproxy2swagger automates REST API reverse-engineering by converting mitmproxy flows or HAR files into OpenAPI 3.0 specs using a two-pass workflow that balances automation and manual curation.</description></item><item><title>NVIDIA Warp: JIT-compiling Python for CUDA-powered differentiable physics</title><link>https://ramdi.fr/github-stars/nvidia-warp-jit-compiling-python-for-cuda-powered-differentiable-physics/</link><pubDate>Mon, 04 May 2026 10:23:03 +0000</pubDate><guid>https://ramdi.fr/github-stars/nvidia-warp-jit-compiling-python-for-cuda-powered-differentiable-physics/</guid><description>NVIDIA Warp lets you write Python functions JIT-compiled into CUDA kernels for GPU-accelerated differentiable physics and ML integration, simplifying GPU programming in Python.</description></item><item><title>UI-Voyager: Self-evolving AI agent for Android GUI automation with SSIM-based trajectory correction</title><link>https://ramdi.fr/github-stars/ui-voyager-self-evolving-ai-agent-for-android-gui-automation-with-ssim-based-trajectory-correction/</link><pubDate>Mon, 04 May 2026 10:23:03 +0000</pubDate><guid>https://ramdi.fr/github-stars/ui-voyager-self-evolving-ai-agent-for-android-gui-automation-with-ssim-based-trajectory-correction/</guid><description>UI-Voyager is a 4B parameter AI agent achieving 81% success on AndroidWorld by self-evolving with SSIM-based trajectory correction, no human labels needed.</description></item><item><title>A curated gateway to machine learning resources for quantitative trading</title><link>https://ramdi.fr/github-stars/a-curated-gateway-to-machine-learning-resources-for-quantitative-trading/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/a-curated-gateway-to-machine-learning-resources-for-quantitative-trading/</guid><description>A curated GitHub repo consolidates 200+ quality resources for quantitative and ML-driven algorithmic trading, bridging academic research and practical strategies.</description></item><item><title>agent-sat: Autonomous AI agent discovering MaxSAT solving techniques through iterative experimentation</title><link>https://ramdi.fr/github-stars/agent-sat-autonomous-ai-agent-discovering-maxsat-solving-techniques-through-iterative-experimentation/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/agent-sat-autonomous-ai-agent-discovering-maxsat-solving-techniques-through-iterative-experimentation/</guid><description>agent-sat is an autonomous AI agent system where Claude Code learns to solve weighted MaxSAT problems by iterating solver improvements and coordinating via git, solving 220/229 benchmarks.</description></item><item><title>AgentFlow: orchestrating AI coding agents with graph-based parallelism and remote execution</title><link>https://ramdi.fr/github-stars/agentflow-orchestrating-ai-coding-agents-with-graph-based-parallelism-and-remote-execution/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/agentflow-orchestrating-ai-coding-agents-with-graph-based-parallelism-and-remote-execution/</guid><description>AgentFlow is a Python library for orchestrating AI coding agents using dependency graphs, supporting parallel fanout, iterative refinement, and remote execution. It integrates with Codex CLI for natural-language pipeline creation.</description></item><item><title>ai-trader: AI-powered config-driven backtesting with natural language interaction</title><link>https://ramdi.fr/github-stars/ai-trader-ai-powered-config-driven-backtesting-with-natural-language-interaction/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/ai-trader-ai-powered-config-driven-backtesting-with-natural-language-interaction/</guid><description>ai-trader adds natural language AI interaction to algorithmic trading backtesting via an MCP server and YAML configs. Supports US/TW stocks, crypto, forex with caching.</description></item><item><title>AI4Animation: A deep learning framework for neural character animation with sparse sensor control</title><link>https://ramdi.fr/github-stars/ai4animation-a-deep-learning-framework-for-neural-character-animation-with-sparse-sensor-control/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/ai4animation-a-deep-learning-framework-for-neural-character-animation-with-sparse-sensor-control/</guid><description>AI4Animation offers a research-driven deep learning framework for neural character animation, enabling real-time control from sparse sensor inputs using categorical codebook matching and periodic autoencoders.</description></item><item><title>Algorithmic trading with Python: modular quant tools built on pandas</title><link>https://ramdi.fr/github-stars/algorithmic-trading-with-python-modular-quant-tools-built-on-pandas/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/algorithmic-trading-with-python-modular-quant-tools-built-on-pandas/</guid><description>This repo offers modular Python utilities for quantitative trading research, featuring pure-Pandas indicators and OOP portfolio simulation—usable standalone in quant pipelines.</description></item><item><title>Alpaca-py: structured Python SDK for Alpaca trading and market data APIs with runtime validation</title><link>https://ramdi.fr/github-stars/alpaca-py-structured-python-sdk-for-alpaca-trading-and-market-data-apis-with-runtime-validation/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/alpaca-py-structured-python-sdk-for-alpaca-trading-and-market-data-apis-with-runtime-validation/</guid><description>Alpaca-py is Alpaca&amp;rsquo;s official Python SDK for trading, market data, and broker APIs. It uses pydantic models and OOP clients to catch errors early and improve DX.</description></item><item><title>AniGen: GPU-accelerated 3D animation generation with Python and CUDA</title><link>https://ramdi.fr/github-stars/anigen-gpu-accelerated-3d-animation-generation-with-python-and-cuda/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/anigen-gpu-accelerated-3d-animation-generation-with-python-and-cuda/</guid><description>AniGen is a Linux-only Python project for 3D animation generation using NVIDIA GPUs and CUDA. It integrates PyTorch, spconv, and pytorch3d with a smooth setup script for complex dependencies.</description></item><item><title>ArkhamMirror: A modular, local-first investigative journalism platform with event-driven shards</title><link>https://ramdi.fr/github-stars/arkhammirror-a-modular-local-first-investigative-journalism-platform-with-event-driven-shards/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/arkhammirror-a-modular-local-first-investigative-journalism-platform-with-event-driven-shards/</guid><description>ArkhamMirror is a local-first, modular document intelligence platform for investigative journalism using event-driven shards, structured analytic techniques, and hybrid semantic search.</description></item><item><title>atopile: Declarative hardware design with constraint-solving for PCB automation</title><link>https://ramdi.fr/github-stars/atopile-declarative-hardware-design-with-constraint-solving-for-pcb-automation/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/atopile-declarative-hardware-design-with-constraint-solving-for-pcb-automation/</guid><description>atopile offers a declarative hardware description language and compiler that solves component constraints and generates KiCad PCB layouts automatically.</description></item><item><title>AutoHedge: A multi-agent autonomous hedge fund framework for Solana trading</title><link>https://ramdi.fr/github-stars/autohedge-a-multi-agent-autonomous-hedge-fund-framework-for-solana-trading/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/autohedge-a-multi-agent-autonomous-hedge-fund-framework-for-solana-trading/</guid><description>AutoHedge implements a four-agent sequential pipeline for autonomous trading on Solana, using a risk-first design and structured JSON outputs for reliable multi-agent coordination.</description></item><item><title>AutoProber: AI-driven hardware automation with oscilloscope-monitored safety for PCB analysis</title><link>https://ramdi.fr/github-stars/autoprober-ai-driven-hardware-automation-with-oscilloscope-monitored-safety-for-pcb-analysis/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/autoprober-ai-driven-hardware-automation-with-oscilloscope-monitored-safety-for-pcb-analysis/</guid><description>AutoProber is a Python automation stack that controls a flying probe system for PCB analysis, featuring oscilloscope-based safety monitoring and a Flask dashboard.</description></item><item><title>Bluehood: passive Bluetooth scanning and presence pattern analysis on Linux</title><link>https://ramdi.fr/github-stars/bluehood-passive-bluetooth-scanning-and-presence-pattern-analysis-on-linux/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/bluehood-passive-bluetooth-scanning-and-presence-pattern-analysis-on-linux/</guid><description>Bluehood passively scans BLE and Classic Bluetooth devices, tracks presence patterns, and reveals limits of MAC randomization using BLE UUIDs and signal strength. Linux-only, Docker-ready.</description></item><item><title>BrightBean Studio: a self-hosted social media management platform with direct API integrations and multi-tenant Django architecture</title><link>https://ramdi.fr/github-stars/brightbean-studio-a-self-hosted-social-media-management-platform-with-direct-api-integrations-and-multi-tenant-django-architecture/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/brightbean-studio-a-self-hosted-social-media-management-platform-with-direct-api-integrations-and-multi-tenant-django-architecture/</guid><description>BrightBean Studio is a Django-based, self-hosted social media management platform supporting 10+ platforms with direct API integrations and multi-tenant RBAC. Explore its architecture and deployment paths.</description></item><item><title>Building a production-ready AI agent system in 18 steps with build-your-own-openclaw</title><link>https://ramdi.fr/github-stars/building-a-production-ready-ai-agent-system-in-18-steps-with-build-your-own-openclaw/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/building-a-production-ready-ai-agent-system-in-18-steps-with-build-your-own-openclaw/</guid><description>A practical 18-step tutorial progressively builds a minimal AI agent into a production-ready multi-agent system with event-driven architecture and concurrency control.</description></item><item><title>Building a resilient real-time option chain analyzer with Python tkinter</title><link>https://ramdi.fr/github-stars/building-a-resilient-real-time-option-chain-analyzer-with-python-tkinter/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/building-a-resilient-real-time-option-chain-analyzer-with-python-tkinter/</guid><description>Explore Python-NSE-Option-Chain-Analyzer, a Python tkinter desktop app that fetches and analyzes real-time NSE option chain data with robust polling, deduplication, and error handling.</description></item><item><title>claude os: speeding up persistent ai memory for code with hybrid tree-sitter indexing</title><link>https://ramdi.fr/github-stars/claude-os-speeding-up-persistent-ai-memory-for-code-with-hybrid-tree-sitter-indexing/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/claude-os-speeding-up-persistent-ai-memory-for-code-with-hybrid-tree-sitter-indexing/</guid><description>Claude OS cuts codebase indexing from hours to seconds using hybrid tree-sitter parsing, enabling fast persistent AI memory for Claude Code projects with local-first data storage.</description></item><item><title>claude-blog: a modular Claude Code plugin for automated, SEO-optimized blog content workflows</title><link>https://ramdi.fr/github-stars/claude-blog-a-modular-claude-code-plugin-for-automated-seo-optimized-blog-content-workflows/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/claude-blog-a-modular-claude-code-plugin-for-automated-seo-optimized-blog-content-workflows/</guid><description>claude-blog offers 28 modular sub-skills automating blog content creation with dual SEO and AI citation optimization, integrating Google APIs and supporting multiple CMS platforms.</description></item><item><title>ComfyUI Trellis2: Extending ComfyUI with Dinov3 for 3D-Aware Diffusion Workflows</title><link>https://ramdi.fr/github-stars/comfyui-trellis2-extending-comfyui-with-dinov3-for-3d-aware-diffusion-workflows/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/comfyui-trellis2-extending-comfyui-with-dinov3-for-3d-aware-diffusion-workflows/</guid><description>ComfyUI-Trellis2 integrates facebook&amp;rsquo;s Dinov3 model into ComfyUI for advanced 3D-aware diffusion workflows. This article breaks down its architecture, strengths, and installation steps.</description></item><item><title>ctx: managing AI skills and agents with a context-aware knowledge graph</title><link>https://ramdi.fr/github-stars/ctx-managing-ai-skills-and-agents-with-a-context-aware-knowledge-graph/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/ctx-managing-ai-skills-and-agents-with-a-context-aware-knowledge-graph/</guid><description>ctx builds a 104K-node knowledge graph to optimize AI skill and agent selection for Claude Code, solving context window bloat with a graph-based recommender and lifecycle management.</description></item><item><title>DAAAM: real-time foundation-model-driven 3D dynamic scene graph construction for robot mapping</title><link>https://ramdi.fr/github-stars/daaam-real-time-foundation-model-driven-3d-dynamic-scene-graph-construction-for-robot-mapping/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/daaam-real-time-foundation-model-driven-3d-dynamic-scene-graph-construction-for-robot-mapping/</guid><description>DAAAM builds real-time 3D dynamic scene graphs using foundation models like SAM and VLMs, targeting large-scale robot mapping with semantic and spatio-temporal memory.</description></item><item><title>daVinci-MagiHuman: Simplifying multimodal video and audio generation with a single-stream transformer</title><link>https://ramdi.fr/github-stars/davinci-magihuman-simplifying-multimodal-video-and-audio-generation-with-a-single-stream-transformer/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/davinci-magihuman-simplifying-multimodal-video-and-audio-generation-with-a-single-stream-transformer/</guid><description>daVinci-MagiHuman uses a 15B-parameter single-stream transformer with a sandwich architecture to generate video and audio from text, achieving competitive quality and fast inference on a single H100 GPU.</description></item><item><title>DefaultCreds-cheat-sheet: consolidated default credentials for pentesting</title><link>https://ramdi.fr/github-stars/defaultcreds-cheat-sheet-consolidated-default-credentials-for-pentesting/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/defaultcreds-cheat-sheet-consolidated-default-credentials-for-pentesting/</guid><description>DefaultCreds-cheat-sheet consolidates 3,711 default credentials from 1,398 vendors into a Python CLI tool with export and proxy support for pentesting workflows.</description></item><item><title>dflash-mlx: Speculative decoding on Apple Silicon with Metal and MLX</title><link>https://ramdi.fr/github-stars/dflash-mlx-speculative-decoding-on-apple-silicon-with-metal-and-mlx/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/dflash-mlx-speculative-decoding-on-apple-silicon-with-metal-and-mlx/</guid><description>dflash-mlx implements exact speculative decoding for language models on Apple Silicon using Metal and MLX, reducing forward passes with a block-diffusion draft model and per-layer KV cache rollback.</description></item><item><title>DIMO: Distilling Diverse 3D Motion Priors for Arbitrary Object Motion Synthesis</title><link>https://ramdi.fr/github-stars/dimo-distilling-diverse-3d-motion-priors-for-arbitrary-object-motion-synthesis/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/dimo-distilling-diverse-3d-motion-priors-for-arbitrary-object-motion-synthesis/</guid><description>DIMO distills motion priors from text-conditioned and multi-view video models into a shared latent space, enabling diverse 3D motion generation for arbitrary objects using 3D Gaussian splatting and 4D rendering.</description></item><item><title>Dippy: safe shell command hooks for Claude Code with a custom zero-dependency bash parser</title><link>https://ramdi.fr/github-stars/dippy-safe-shell-command-hooks-for-claude-code-with-a-custom-zero-dependency-bash-parser/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/dippy-safe-shell-command-hooks-for-claude-code-with-a-custom-zero-dependency-bash-parser/</guid><description>Dippy uses a custom zero-dependency bash parser to auto-approve safe shell commands run by Claude Code, blocking destructive operations and reducing permission fatigue.</description></item><item><title>dirsearch: a Python web path brute-forcer with precise extension handling</title><link>https://ramdi.fr/github-stars/dirsearch-a-python-web-path-brute-forcer-with-precise-extension-handling/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/dirsearch-a-python-web-path-brute-forcer-with-precise-extension-handling/</guid><description>dirsearch is a Python tool for brute-forcing web paths with a clever extension handling system. It offers multi-threaded, recursive scanning and session resumption for security reconnaissance.</description></item><item><title>DocsGPT: a flexible AI platform for private agents and enterprise document search</title><link>https://ramdi.fr/github-stars/docsgpt-a-flexible-ai-platform-for-private-agents-and-enterprise-document-search/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/docsgpt-a-flexible-ai-platform-for-private-agents-and-enterprise-document-search/</guid><description>DocsGPT is a Python-based AI platform for building private agents and enterprise search, with multi-LLM support and versatile deployment modes via Docker Compose.</description></item><item><title>DontFeedTheAI: Wizard-driven deployment of Claude AI proxies</title><link>https://ramdi.fr/github-stars/dontfeedtheai-wizard-driven-deployment-of-claude-ai-proxies/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/dontfeedtheai-wizard-driven-deployment-of-claude-ai-proxies/</guid><description>DontFeedTheAI provides an easy wizard-driven way to deploy Claude AI proxies across platforms. It automates engagement setup, deployment, and tunnel management for lightweight AI model access.</description></item><item><title>Exploring Claude API integration patterns with anthropics/claude-cookbooks</title><link>https://ramdi.fr/github-stars/exploring-claude-api-integration-patterns-with-anthropics-claude-cookbooks/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/exploring-claude-api-integration-patterns-with-anthropics-claude-cookbooks/</guid><description>anthropics/claude-cookbooks offers Jupyter Notebook recipes demonstrating practical Claude API usage, including sub-agent orchestration, multimodal vision, and RAG patterns.</description></item><item><title>FinRL-Trading: modular, weight-centric quantitative trading with deployment-consistent backtesting and DRL portfolio allocation</title><link>https://ramdi.fr/github-stars/finrl-trading-modular-weight-centric-quantitative-trading-with-deployment-consistent-backtesting-and-drl-portfolio-allocation/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/finrl-trading-modular-weight-centric-quantitative-trading-with-deployment-consistent-backtesting-and-drl-portfolio-allocation/</guid><description>FinRL-Trading offers a modular Python framework for quantitative trading focused on a weight-centric architecture unifying backtesting and live execution, with classical and DRL portfolio methods.</description></item><item><title>fireworks-tech-graph: Natural language to production-ready AI and UML diagrams with embedded visual styles</title><link>https://ramdi.fr/github-stars/fireworks-tech-graph-natural-language-to-production-ready-ai-and-uml-diagrams-with-embedded-visual-styles/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/fireworks-tech-graph-natural-language-to-production-ready-ai-and-uml-diagrams-with-embedded-visual-styles/</guid><description>fireworks-tech-graph is a Claude Code skill that generates production-quality SVG and PNG technical diagrams from natural language, supporting 7 visual styles and 14 UML types plus AI agent patterns.</description></item><item><title>forge3d: shipping a high-performance Rust GPU renderer as Python wheels with async viewer APIs</title><link>https://ramdi.fr/github-stars/forge3d-shipping-a-high-performance-rust-gpu-renderer-as-python-wheels-with-async-viewer-apis/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/forge3d-shipping-a-high-performance-rust-gpu-renderer-as-python-wheels-with-async-viewer-apis/</guid><description>forge3d is a Rust-based cross-platform 3D renderer exposed as Python wheels with async viewer sessions, terrain and point cloud support, and an open-core licensing model.</description></item><item><title>Foxel: a pluggable, AI-powered self-hosted cloud storage platform</title><link>https://ramdi.fr/github-stars/foxel-a-pluggable-ai-powered-self-hosted-cloud-storage-platform/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/foxel-a-pluggable-ai-powered-self-hosted-cloud-storage-platform/</guid><description>Foxel offers a self-hosted cloud storage platform with runtime plugin loading and AI-driven semantic search across multiple backends. Explore its architecture, plugin system, and deployment.</description></item><item><title>Frappe Helpdesk: A self-hosted, customizable ticket management system with dual portals</title><link>https://ramdi.fr/github-stars/frappe-helpdesk-a-self-hosted-customizable-ticket-management-system-with-dual-portals/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/frappe-helpdesk-a-self-hosted-customizable-ticket-management-system-with-dual-portals/</guid><description>Frappe Helpdesk offers an open-source ticket system with agent and customer portals, built on Frappe Framework and Vue. Self-hosted, customizable, with SLA and auto-assignment features.</description></item><item><title>Frappe LMS: Building an extensible learning platform on the Frappe Framework</title><link>https://ramdi.fr/github-stars/frappe-lms-building-an-extensible-learning-platform-on-the-frappe-framework/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/frappe-lms-building-an-extensible-learning-platform-on-the-frappe-framework/</guid><description>Frappe LMS uses the Frappe Framework&amp;rsquo;s doctype system to model courses, chapters, and lessons as first-class entities, enabling quick customization and live class support with Zoom integration.</description></item><item><title>freecad-mcp: bridging AI and parametric CAD through an MCP server</title><link>https://ramdi.fr/github-stars/freecad-mcp-bridging-ai-and-parametric-cad-through-an-mcp-server/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/freecad-mcp-bridging-ai-and-parametric-cad-through-an-mcp-server/</guid><description>freecad-mcp uses an MCP server to connect Claude Desktop AI with FreeCAD, enabling AI-driven parametric CAD modeling through RPC tools including arbitrary Python code execution.</description></item><item><title>Gitingest: turning GitHub repos into AI-friendly text digests with a clever URL hack</title><link>https://ramdi.fr/github-stars/gitingest-turning-github-repos-into-ai-friendly-text-digests-with-a-clever-url-hack/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/gitingest-turning-github-repos-into-ai-friendly-text-digests-with-a-clever-url-hack/</guid><description>Gitingest is a Python CLI and API that converts Git repos into LLM-optimized text digests, featuring a unique URL hack for instant GitHub repo ingestion and self-hosted FastAPI server.</description></item><item><title>Goose Skills: Modular GTM AI agent skills for sales and marketing automation</title><link>https://ramdi.fr/github-stars/goose-skills-modular-gtm-ai-agent-skills-for-sales-and-marketing-automation/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/goose-skills-modular-gtm-ai-agent-skills-for-sales-and-marketing-automation/</guid><description>Goose Skills provides 108 reusable AI agent skills for sales, marketing, and competitive intelligence, structured as atomic tools, skill chains, and workflows for coding agents like Claude and Codex.</description></item><item><title>HA Optimizer: deep health auditing and anomaly detection for Home Assistant</title><link>https://ramdi.fr/github-stars/ha-optimizer-deep-health-auditing-and-anomaly-detection-for-home-assistant/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/ha-optimizer-deep-health-auditing-and-anomaly-detection-for-home-assistant/</guid><description>HA Optimizer is a Home Assistant custom integration performing health audits with anomaly detection based on a 30-day baseline, plus soft-delete purge and real-time resource monitoring.</description></item><item><title>Hands-On Large Language Models: A practical, visual journey through LLM engineering</title><link>https://ramdi.fr/github-stars/hands-on-large-language-models-a-practical-visual-journey-through-llm-engineering/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/hands-on-large-language-models-a-practical-visual-journey-through-llm-engineering/</guid><description>Explore the Hands-On Large Language Models repo, a Jupyter notebook-based practical guide from fundamentals to fine-tuning, designed for hands-on LLM learning on free Colab GPUs.</description></item><item><title>How video-use turns AI agents into transcript-driven video editors</title><link>https://ramdi.fr/github-stars/how-video-use-turns-ai-agents-into-transcript-driven-video-editors/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/how-video-use-turns-ai-agents-into-transcript-driven-video-editors/</guid><description>video-use replaces frame-heavy editing with transcript-driven AI agents, using ElevenLabs Scribe and self-evaluation to produce polished edits.</description></item><item><title>Inside Alibaba's Logics-Parsing-v2: end-to-end structured document parsing beyond OCR</title><link>https://ramdi.fr/github-stars/inside-alibaba-s-logics-parsing-v2-end-to-end-structured-document-parsing-beyond-ocr/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-alibaba-s-logics-parsing-v2-end-to-end-structured-document-parsing-beyond-ocr/</guid><description>Alibaba&amp;rsquo;s Logics-Parsing-v2 converts complex document images into structured HTML, handling formulas, tables, flowcharts, music sheets, and pseudocode with a single model.</description></item><item><title>Inside Alibaba’s VRAG: Multimodal Retrieval-Augmented Generation with Dynamic Reasoning Graphs</title><link>https://ramdi.fr/github-stars/inside-alibabas-vrag-multimodal-retrieval-augmented-generation-with-dynamic-reasoning-graphs/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-alibabas-vrag-multimodal-retrieval-augmented-generation-with-dynamic-reasoning-graphs/</guid><description>Alibaba&amp;rsquo;s VRAG models reasoning as a dynamic DAG with multimodal memory and RL-based fine-grained credit assignment, supporting text, image, and video retrieval in a unified framework.</description></item><item><title>Inside Genie Envisioner: A two-stage video diffusion platform for robotic manipulation</title><link>https://ramdi.fr/github-stars/inside-genie-envisioner-a-two-stage-video-diffusion-platform-for-robotic-manipulation/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-genie-envisioner-a-two-stage-video-diffusion-platform-for-robotic-manipulation/</guid><description>Genie Envisioner offers a two-stage training pipeline using video diffusion for robotic manipulation, separating world model adaptation from action policy learning. Here&amp;rsquo;s how it works and how to get started.</description></item><item><title>Inside NousResearch's finetuning-subnet: continuous incentivized fine-tuning for LLMs on Bittensor</title><link>https://ramdi.fr/github-stars/inside-nousresearch-s-finetuning-subnet-continuous-incentivized-fine-tuning-for-llms-on-bittensor/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-nousresearch-s-finetuning-subnet-continuous-incentivized-fine-tuning-for-llms-on-bittensor/</guid><description>NousResearch&amp;rsquo;s finetuning-subnet enables continuous, incentivized fine-tuning of LLMs using synthetic data from a separate subnet, pioneering cross-subnet communication in Bittensor.</description></item><item><title>Inside polymarket-kalshi-weather-bot: a multi-strategy prediction market trading bot with ensemble weather forecasting</title><link>https://ramdi.fr/github-stars/inside-polymarket-kalshi-weather-bot-a-multi-strategy-prediction-market-trading-bot-with-ensemble-weather-forecasting/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-polymarket-kalshi-weather-bot-a-multi-strategy-prediction-market-trading-bot-with-ensemble-weather-forecasting/</guid><description>Explore polymarket-kalshi-weather-bot, a Python trading bot exploiting BTC microstructure and ensemble weather forecasts for prediction market arbitrage. Uses fractional Kelly sizing and real-time React dashboard.</description></item><item><title>Inside Second Brain: A Python AI OS with self-extending plugins and hybrid search</title><link>https://ramdi.fr/github-stars/inside-second-brain-a-python-ai-os-with-self-extending-plugins-and-hybrid-search/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-second-brain-a-python-ai-os-with-self-extending-plugins-and-hybrid-search/</guid><description>Second Brain is a Python framework that indexes local files with embeddings, runs background subagents, and lets AI agents build and hot-load their own plugins at runtime.</description></item><item><title>Inside Spider: physics-based motion retargeting from human videos to diverse robots</title><link>https://ramdi.fr/github-stars/inside-spider-physics-based-motion-retargeting-from-human-videos-to-diverse-robots/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-spider-physics-based-motion-retargeting-from-human-videos-to-diverse-robots/</guid><description>Spider retargets human motion to multiple robots using a modular physics pipeline with inverse kinematics and optimization, supporting 9+ robots and 6+ datasets out of the box.</description></item><item><title>ipblocklist: Aggregated IP threat intelligence with clear licensing boundaries</title><link>https://ramdi.fr/github-stars/ipblocklist-aggregated-ip-threat-intelligence-with-clear-licensing-boundaries/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/ipblocklist-aggregated-ip-threat-intelligence-with-clear-licensing-boundaries/</guid><description>ipblocklist aggregates IP blocklists from 30+ threat intel sources into curated inbound and outbound lists, balancing licensing constraints and operational complexity.</description></item><item><title>ISC-Bench: exposing fundamental AI safety failures from workflow-level design</title><link>https://ramdi.fr/github-stars/isc-bench-exposing-fundamental-ai-safety-failures-from-workflow-level-design/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/isc-bench-exposing-fundamental-ai-safety-failures-from-workflow-level-design/</guid><description>ISC-Bench reveals a structural AI safety flaw where LLMs produce harmful outputs to complete tasks, bypassing prompt-level defenses. It benchmarks this workflow-level vulnerability across top models.</description></item><item><title>jdeskew: frequency-domain skew estimation for document images using adaptive radial projection</title><link>https://ramdi.fr/github-stars/jdeskew-frequency-domain-skew-estimation-for-document-images-using-adaptive-radial-projection/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/jdeskew-frequency-domain-skew-estimation-for-document-images-using-adaptive-radial-projection/</guid><description>jdeskew estimates document image skew angles by projecting the Fourier magnitude spectrum radially. It offers a Python package with pip and Docker options, outperforming baselines on DISE 2021 benchmarks.</description></item><item><title>KiCAD MCP Server: Bridging AI and PCB Design with the Model Context Protocol</title><link>https://ramdi.fr/github-stars/kicad-mcp-server-bridging-ai-and-pcb-design-with-the-model-context-protocol/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/kicad-mcp-server-bridging-ai-and-pcb-design-with-the-model-context-protocol/</guid><description>KiCAD MCP Server connects LLMs with KiCAD for AI-driven PCB design operations, enabling schematic editing, routing, and custom footprint generation via the Model Context Protocol.</description></item><item><title>Kitaru: a durable runtime for autonomous AI agents with checkpointed execution</title><link>https://ramdi.fr/github-stars/kitaru-a-durable-runtime-for-autonomous-ai-agents-with-checkpointed-execution/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/kitaru-a-durable-runtime-for-autonomous-ai-agents-with-checkpointed-execution/</guid><description>Kitaru offers a framework-agnostic runtime for autonomous AI agents with durable execution via checkpointing, enabling replay and state preservation to avoid costly restarts on failures.</description></item><item><title>Knowledge Engine: bridging markdown wikis with sub-5ms semantic search</title><link>https://ramdi.fr/github-stars/knowledge-engine-bridging-markdown-wikis-with-sub-5ms-semantic-search/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/knowledge-engine-bridging-markdown-wikis-with-sub-5ms-semantic-search/</guid><description>Knowledge Engine connects markdown wikis with Memvid&amp;rsquo;s sub-5ms semantic search using a dual-layer design, automatic sync, and entity extraction for AI-augmented knowledge work.</description></item><item><title>KohakuTerrarium: Modular AI agent composition with algebraic pipelines</title><link>https://ramdi.fr/github-stars/kohakuterrarium-modular-ai-agent-composition-with-algebraic-pipelines/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/kohakuterrarium-modular-ai-agent-composition-with-algebraic-pipelines/</guid><description>KohakuTerrarium offers a Python framework to build modular AI agents using a unique algebra for composing multi-agent pipelines, with session persistence and multi-runtime support.</description></item><item><title>KRR: Kubernetes resource recommendations powered by Prometheus metrics</title><link>https://ramdi.fr/github-stars/krr-kubernetes-resource-recommendations-powered-by-prometheus-metrics/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/krr-kubernetes-resource-recommendations-powered-by-prometheus-metrics/</guid><description>KRR helps Kubernetes users optimize resource allocation by analyzing Prometheus metrics and generating actionable recommendations. This Python tool integrates with kube-prometheus-stack or Robusta&amp;rsquo;s embedded Prometheus.</description></item><item><title>kvcached: a plugin cache for SGLang and vLLM Python environments</title><link>https://ramdi.fr/github-stars/kvcached-a-plugin-cache-for-sglang-and-vllm-python-environments/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/kvcached-a-plugin-cache-for-sglang-and-vllm-python-environments/</guid><description>kvcached provides a plugin cache layer for SGLang and vLLM Python LLM environments, easing deployment with PyPI and Docker support. Useful for optimizing LLM workflows.</description></item><item><title>LycheeMemory: a lightweight semantic long-term memory framework for LLM agents</title><link>https://ramdi.fr/github-stars/lycheememory-a-lightweight-semantic-long-term-memory-framework-for-llm-agents/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/lycheememory-a-lightweight-semantic-long-term-memory-framework-for-llm-agents/</guid><description>LycheeMemory offers a lightweight semantic memory system for LLM agents, cutting token use by 71% and costs by 55% compared to native memory, with SQLite + LanceDB backend and REST/MCP APIs.</description></item><item><title>MAGI: A structured multi-LLM debate system with iterative critique and voting</title><link>https://ramdi.fr/github-stars/magi-a-structured-multi-llm-debate-system-with-iterative-critique-and-voting/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/magi-a-structured-multi-llm-debate-system-with-iterative-critique-and-voting/</guid><description>MAGI implements a multi-round debate protocol among three LLMs to match stronger models&amp;rsquo; accuracy via iterative critique and voting. It offers fault tolerance, adaptive escalation, and persona presets.</description></item><item><title>Magika: Google's deep learning system for fast, accurate file type detection</title><link>https://ramdi.fr/github-stars/magika-google-s-deep-learning-system-for-fast-accurate-file-type-detection/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/magika-google-s-deep-learning-system-for-fast-accurate-file-type-detection/</guid><description>Magika replaces magic-byte heuristics with a tiny deep learning model for file type detection, achieving ~99% accuracy across 200+ types with 5ms CPU inference.</description></item><item><title>Mapping the LLM agent landscape with the awesome-llm-agents curated catalog</title><link>https://ramdi.fr/github-stars/mapping-the-llm-agent-landscape-with-the-awesome-llm-agents-curated-catalog/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/mapping-the-llm-agent-landscape-with-the-awesome-llm-agents-curated-catalog/</guid><description>A curated catalog of 20+ LLM agent frameworks and tools organized by agent type and capabilities. Understand architectural differences and trade-offs in LLM agent design.</description></item><item><title>Mapping the open-source AI stack with the awesome-opensource-ai curated list</title><link>https://ramdi.fr/github-stars/mapping-the-open-source-ai-stack-with-the-awesome-opensource-ai-curated-list/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/mapping-the-open-source-ai-stack-with-the-awesome-opensource-ai-curated-list/</guid><description>A curated directory cataloging over 200 production-ready open-source AI projects across the machine learning stack, from training frameworks to self-hosted UIs.</description></item><item><title>Matrix-3D: a practical pipeline for omnidirectional 3D world generation optimized for consumer GPUs</title><link>https://ramdi.fr/github-stars/matrix-3d-a-practical-pipeline-for-omnidirectional-3d-world-generation-optimized-for-consumer-gpus/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/matrix-3d-a-practical-pipeline-for-omnidirectional-3d-world-generation-optimized-for-consumer-gpus/</guid><description>Matrix-3D generates explorable 360-degree 3D worlds from text or images using panoramic video and 3D Gaussian splatting, optimized to run on 12-19GB VRAM consumer GPUs.</description></item><item><title>MeanVC: real-time zero-shot voice conversion with mean flows and diffusion transformers</title><link>https://ramdi.fr/github-stars/meanvc-real-time-zero-shot-voice-conversion-with-mean-flows-and-diffusion-transformers/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/meanvc-real-time-zero-shot-voice-conversion-with-mean-flows-and-diffusion-transformers/</guid><description>MeanVC enables real-time zero-shot voice conversion using mean flows and diffusion transformers for single-step inference, addressing latency bottlenecks in diffusion models.</description></item><item><title>MediaLyze: incremental scanning for efficient self-hosted media library analysis</title><link>https://ramdi.fr/github-stars/medialyze-incremental-scanning-for-efficient-self-hosted-media-library-analysis/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/medialyze-incremental-scanning-for-efficient-self-hosted-media-library-analysis/</guid><description>MediaLyze is a read-only, self-hosted media library analyzer using FastAPI and React. It features incremental scanning with path+size+mtime hashing to avoid redundant scans.</description></item><item><title>Memary: Recursive Knowledge Graph Memory for Autonomous AI Agents</title><link>https://ramdi.fr/github-stars/memary-recursive-knowledge-graph-memory-for-autonomous-ai-agents/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/memary-recursive-knowledge-graph-memory-for-autonomous-ai-agents/</guid><description>Memary is an open-source memory layer for AI agents using knowledge graphs and recursive retrieval to efficiently store and query agent memories. It supports multi-agent setups and integrates with LlamaIndex and OpenAI.</description></item><item><title>Meta-Harness: evolving the scaffolding around large language models for optimized task performance</title><link>https://ramdi.fr/github-stars/meta-harness-evolving-the-scaffolding-around-large-language-models-for-optimized-task-performance/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/meta-harness-evolving-the-scaffolding-around-large-language-models-for-optimized-task-performance/</guid><description>Meta-Harness from Stanford IRIS Lab automates the search for optimal harness configurations around LLMs, evolving memory, retrieval, and context systems for better task-specific performance.</description></item><item><title>MiniStack: Lightweight local AWS emulation with zero-config multi-tenancy</title><link>https://ramdi.fr/github-stars/ministack-lightweight-local-aws-emulation-with-zero-config-multi-tenancy/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/ministack-lightweight-local-aws-emulation-with-zero-config-multi-tenancy/</guid><description>MiniStack offers 40+ AWS services emulated locally using real containers and a clever multi-tenancy model via AWS_ACCESS_KEY_ID, all on a single port with a tiny footprint.</description></item><item><title>MLE-Agent: Autonomous LLM agents for end-to-end ML workflow automation</title><link>https://ramdi.fr/github-stars/mle-agent-autonomous-llm-agents-for-end-to-end-ml-workflow-automation/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/mle-agent-autonomous-llm-agents-for-end-to-end-ml-workflow-automation/</guid><description>MLE-Agent is a Python LLM agent framework that automates ML workflows, including autonomous Kaggle competitions and smart debugging with human-in-the-loop. Supports multiple LLMs and local RAG.</description></item><item><title>MotionCrafter: unified 4D geometry and motion reconstruction from monocular video</title><link>https://ramdi.fr/github-stars/motioncrafter-unified-4d-geometry-and-motion-reconstruction-from-monocular-video/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/motioncrafter-unified-4d-geometry-and-motion-reconstruction-from-monocular-video/</guid><description>MotionCrafter jointly reconstructs 4D geometry and dense motion from monocular video using a unified 4D VAE, eliminating post-optimization. This Python framework offers training and visualization tools.</description></item><item><title>MultiWorld: a unified framework for multi-agent multi-view video world modeling</title><link>https://ramdi.fr/github-stars/multiworld-a-unified-framework-for-multi-agent-multi-view-video-world-modeling/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/multiworld-a-unified-framework-for-multi-agent-multi-view-video-world-modeling/</guid><description>MultiWorld offers a unified framework for multi-agent multi-view video world modeling using a frozen VGGT backbone for implicit 3D understanding. It supports scalable multi-agent control and autoregressive inference.</description></item><item><title>news-please: a Python crawler for structured news extraction with Common Crawl support</title><link>https://ramdi.fr/github-stars/news-please-a-python-crawler-for-structured-news-extraction-with-common-crawl-support/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/news-please-a-python-crawler-for-structured-news-extraction-with-common-crawl-support/</guid><description>news-please is a Python tool built on Scrapy for crawling and extracting structured news data, supporting Common Crawl archives and multiple storage backends.</description></item><item><title>OASIS: a Python CLI for AI-driven code vulnerability scanning with deterministic validation</title><link>https://ramdi.fr/github-stars/oasis-a-python-cli-for-ai-driven-code-vulnerability-scanning-with-deterministic-validation/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/oasis-a-python-cli-for-ai-driven-code-vulnerability-scanning-with-deterministic-validation/</guid><description>OASIS is a Python CLI security auditor using LangGraph-orchestrated LLMs for two-phase scanning and deterministic validation of code vulnerabilities. It balances AI insights with guardrails to reduce false positives.</description></item><item><title>Omni-Diffusion: unified any-to-any multimodal generation with masked discrete diffusion</title><link>https://ramdi.fr/github-stars/omni-diffusion-unified-any-to-any-multimodal-generation-with-masked-discrete-diffusion/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/omni-diffusion-unified-any-to-any-multimodal-generation-with-masked-discrete-diffusion/</guid><description>Omni-Diffusion models text, image, and speech tokens jointly via masked discrete diffusion, enabling any-to-any multimodal generation with a single unified model.</description></item><item><title>onnxmltools: a Python toolkit for converting ML models to ONNX format</title><link>https://ramdi.fr/github-stars/onnxmltools-a-python-toolkit-for-converting-ml-models-to-onnx-format/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/onnxmltools-a-python-toolkit-for-converting-ml-models-to-onnx-format/</guid><description>onnxmltools is a Python library for converting machine learning models from various frameworks into the ONNX format, enabling interoperability across runtimes and platforms.</description></item><item><title>OpenEvolve: autonomous code discovery with MAP-Elites and LLM ensembles</title><link>https://ramdi.fr/github-stars/openevolve-autonomous-code-discovery-with-map-elites-and-llm-ensembles/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/openevolve-autonomous-code-discovery-with-map-elites-and-llm-ensembles/</guid><description>OpenEvolve combines MAP-Elites evolutionary algorithms with LLMs to autonomously discover and optimize code, achieving 2-3x speedups and state-of-the-art results on real hardware.</description></item><item><title>OpenKB: A persistent, vectorless wiki knowledge base powered by LLMs and PageIndex</title><link>https://ramdi.fr/github-stars/openkb-a-persistent-vectorless-wiki-knowledge-base-powered-by-llms-and-pageindex/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/openkb-a-persistent-vectorless-wiki-knowledge-base-powered-by-llms-and-pageindex/</guid><description>OpenKB compiles documents into a persistent, interlinked wiki using LLMs and PageIndex&amp;rsquo;s vectorless retrieval, supporting multi-LLM backends and interactive chat with persisted sessions.</description></item><item><title>paper2code: auditing ambiguity in ML paper code generation with citation-anchored implementations</title><link>https://ramdi.fr/github-stars/paper2code-auditing-ambiguity-in-ml-paper-code-generation-with-citation-anchored-implementations/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/paper2code-auditing-ambiguity-in-ml-paper-code-generation-with-citation-anchored-implementations/</guid><description>paper2code transforms arxiv papers into Python code with ambiguity auditing and inline citations, prioritizing traceability over completeness in ML implementations.</description></item><item><title>PEAR: real-time expressive 3D human mesh recovery at 100 FPS</title><link>https://ramdi.fr/github-stars/pear-real-time-expressive-3d-human-mesh-recovery-at-100-fps/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/pear-real-time-expressive-3d-human-mesh-recovery-at-100-fps/</guid><description>PEAR predicts expressive 3D human mesh parameters for body, hands, and face simultaneously at 100 FPS using a pixel-aligned architecture based on PyTorch and SMPL-X models.</description></item><item><title>Polypyus: binary-only firmware function matching for ARM Thumb2 reverse engineering</title><link>https://ramdi.fr/github-stars/polypyus-binary-only-firmware-function-matching-for-arm-thumb2-reverse-engineering/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/polypyus-binary-only-firmware-function-matching-for-arm-thumb2-reverse-engineering/</guid><description>Polypyus bypasses disassembler function detection using binary-only fuzzy matching to locate functions in raw ARM Thumb2 firmware, improving reverse engineering workflows.</description></item><item><title>pymobiledevice3: a pure Python iOS device communication stack</title><link>https://ramdi.fr/github-stars/pymobiledevice3-a-pure-python-ios-device-communication-stack/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/pymobiledevice3-a-pure-python-ios-device-communication-stack/</guid><description>pymobiledevice3 reimplements the entire iOS device communication stack in pure Python, replacing C-based tools. It supports iOS 17+ tunnel transport and offers a CLI and Python API for device management.</description></item><item><title>QuantDinger: a self-hosted AI-assisted quant trading platform with strong safety controls</title><link>https://ramdi.fr/github-stars/quantdinger-a-self-hosted-ai-assisted-quant-trading-platform-with-strong-safety-controls/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/quantdinger-a-self-hosted-ai-assisted-quant-trading-platform-with-strong-safety-controls/</guid><description>QuantDinger unifies AI-assisted research, Python strategy development, backtesting, and live trading in a self-hosted platform with scoped AI agent tokens and strict safety defaults.</description></item><item><title>Resume Matcher: A provider-agnostic AI platform for tailored resumes using LiteLLM abstraction</title><link>https://ramdi.fr/github-stars/resume-matcher-a-provider-agnostic-ai-platform-for-tailored-resumes-using-litellm-abstraction/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/resume-matcher-a-provider-agnostic-ai-platform-for-tailored-resumes-using-litellm-abstraction/</guid><description>Resume Matcher uses LiteLLM to unify six LLM providers for AI-powered resume tailoring, with a FastAPI backend and Next.js frontend. It supports local and cloud deployments with PDF export.</description></item><item><title>SafestClaw: Combining simple AI setup with automated security scanning in Python</title><link>https://ramdi.fr/github-stars/safestclaw-combining-simple-ai-setup-with-automated-security-scanning-in-python/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/safestclaw-combining-simple-ai-setup-with-automated-security-scanning-in-python/</guid><description>SafestClaw offers a Python CLI tool that simplifies AI model configuration and automates security scanning across projects. It supports cloud and local AI models with zero YAML config editing.</description></item><item><title>Scalene: A low-overhead Python profiler with AI-powered optimization suggestions</title><link>https://ramdi.fr/github-stars/scalene-a-low-overhead-python-profiler-with-ai-powered-optimization-suggestions/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/scalene-a-low-overhead-python-profiler-with-ai-powered-optimization-suggestions/</guid><description>Scalene is a Python profiler using statistical sampling for 10-20% overhead, offering line-level CPU/GPU/memory insights and AI-driven optimization tips via LLMs. Cross-platform with CLI and GUI.</description></item><item><title>SciBlend: Integrating scientific data visualization directly into Blender</title><link>https://ramdi.fr/github-stars/sciblend-integrating-scientific-data-visualization-directly-into-blender/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/sciblend-integrating-scientific-data-visualization-directly-into-blender/</guid><description>SciBlend is a Python add-on for Blender that imports scientific data formats and maps them to GPU shaders, enabling publication-quality visualizations within Blender&amp;rsquo;s rendering pipeline.</description></item><item><title>Scientific Agent Skills: Modular AI capabilities for complex scientific workflows</title><link>https://ramdi.fr/github-stars/scientific-agent-skills-modular-ai-capabilities-for-complex-scientific-workflows/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/scientific-agent-skills-modular-ai-capabilities-for-complex-scientific-workflows/</guid><description>Scientific Agent Skills extends AI coding agents with 135 domain-specific scientific skills, unifying database queries and multi-step workflows across bioinformatics, chemistry, and clinical research.</description></item><item><title>SimScale: a scalable sim-real co-training pipeline for autonomous driving planners</title><link>https://ramdi.fr/github-stars/simscale-a-scalable-sim-real-co-training-pipeline-for-autonomous-driving-planners/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/simscale-a-scalable-sim-real-co-training-pipeline-for-autonomous-driving-planners/</guid><description>SimScale provides a sim-real co-training pipeline for autonomous driving planners, combining synthetic simulation data with real-world data to improve robustness and generalization across multiple planner types.</description></item><item><title>SkillForge: Efficient AI skill management for Claude Code and Codex</title><link>https://ramdi.fr/github-stars/skillforge-efficient-ai-skill-management-for-claude-code-and-codex/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/skillforge-efficient-ai-skill-management-for-claude-code-and-codex/</guid><description>SkillForge v5.1 reduces AI skill prompt size by 64% using context-efficient design and trigger-based routing in Claude Code and Codex environments.</description></item><item><title>Snyk Agent Scan: interactive security scanning for AI agent components</title><link>https://ramdi.fr/github-stars/snyk-agent-scan-interactive-security-scanning-for-ai-agent-components/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/snyk-agent-scan-interactive-security-scanning-for-ai-agent-components/</guid><description>Snyk Agent Scan is a Python CLI tool detecting 15+ security risks in AI agent MCP servers and skills, using an interactive consent model for safe scanning.</description></item><item><title>sre-agent: AI-powered incident diagnosis with integrated evaluation for production reliability</title><link>https://ramdi.fr/github-stars/sre-agent-ai-powered-incident-diagnosis-with-integrated-evaluation-for-production-reliability/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/sre-agent-ai-powered-incident-diagnosis-with-integrated-evaluation-for-production-reliability/</guid><description>sre-agent is a Python AI tool that automates incident diagnosis by analyzing AWS CloudWatch logs, inspecting GitHub code, and reporting to Slack. It includes a unique evaluation suite for diagnosis quality.</description></item><item><title>sshpilot: a modern GTK4 SSH client with native GNOME integration and secure credential storage</title><link>https://ramdi.fr/github-stars/sshpilot-a-modern-gtk4-ssh-client-with-native-gnome-integration-and-secure-credential-storage/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/sshpilot-a-modern-gtk4-ssh-client-with-native-gnome-integration-and-secure-credential-storage/</guid><description>sshpilot is a cross-platform SSH client built with Python and GTK4, replacing legacy tools with native GNOME integration, terminal emulation, and secure credential management.</description></item><item><title>Streaming 3D scene reconstruction with LingBot-Map’s geometric context transformer</title><link>https://ramdi.fr/github-stars/streaming-3d-scene-reconstruction-with-lingbot-maps-geometric-context-transformer/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/streaming-3d-scene-reconstruction-with-lingbot-maps-geometric-context-transformer/</guid><description>LingBot-Map performs streaming 3D reconstruction from long image sequences at ~20 FPS using a geometric context transformer and paged KV cache attention for efficient memory management.</description></item><item><title>text-to-cad: AI-driven parametric CAD with geometry-aware iterative editing</title><link>https://ramdi.fr/github-stars/text-to-cad-ai-driven-parametric-cad-with-geometry-aware-iterative-editing/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/text-to-cad-ai-driven-parametric-cad-with-geometry-aware-iterative-editing/</guid><description>text-to-cad bridges AI coding agents with parametric CAD using a local-first architecture and a novel @cad reference system for geometry-aware iterative edits and multi-format export.</description></item><item><title>TextGen: a portable zero-config local LLM runner with multi-backend and multimodal support</title><link>https://ramdi.fr/github-stars/textgen-a-portable-zero-config-local-llm-runner-with-multi-backend-and-multimodal-support/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/textgen-a-portable-zero-config-local-llm-runner-with-multi-backend-and-multimodal-support/</guid><description>TextGen offers a portable desktop app for local LLMs with zero telemetry and multi-backend support. Drop GGUF models in a folder and run with no complex setup. It features multimodal vision, file attachments, and OpenAI-compatible API.</description></item><item><title>token-dashboard: zero-dependency local token analytics for Claude Code sessions</title><link>https://ramdi.fr/github-stars/token-dashboard-zero-dependency-local-token-analytics-for-claude-code-sessions/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/token-dashboard-zero-dependency-local-token-analytics-for-claude-code-sessions/</guid><description>token-dashboard is a Python CLI that parses Claude Code JSONL transcripts to serve a local web dashboard with accurate token cost analytics, using zero dependencies and live refresh.</description></item><item><title>tribev2: pretrained models for predicting brain responses to videos</title><link>https://ramdi.fr/github-stars/tribev2-pretrained-models-for-predicting-brain-responses-to-videos/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/tribev2-pretrained-models-for-predicting-brain-responses-to-videos/</guid><description>tribev2 offers pretrained models to predict brain responses to videos using cortical mesh modeling. Supports video, text, and audio inputs with easy inference setup.</description></item><item><title>Understanding LLM internals: a hands-on guide to transformers and attention math</title><link>https://ramdi.fr/github-stars/understanding-llm-internals-a-hands-on-guide-to-transformers-and-attention-math/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/understanding-llm-internals-a-hands-on-guide-to-transformers-and-attention-math/</guid><description>A curated repo breaking down large language model internals with numeric attention math, tokenization, and transformer architecture, targeting engineers who want to understand LLMs under the hood.</description></item><item><title>Viseron: a modular, self-hosted AI video surveillance platform</title><link>https://ramdi.fr/github-stars/viseron-a-modular-self-hosted-ai-video-surveillance-platform/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/viseron-a-modular-self-hosted-ai-video-surveillance-platform/</guid><description>Viseron is a self-hosted, local-only AI NVR platform in Python with modular AI features for privacy-focused video surveillance. Runs fully locally with Docker deployment.</description></item><item><title>vllm-mlx: Efficient LLM serving on Apple Silicon with SSD-tiered KV cache and continuous batching</title><link>https://ramdi.fr/github-stars/vllm-mlx-efficient-llm-serving-on-apple-silicon-with-ssd-tiered-kv-cache-and-continuous-batching/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/vllm-mlx-efficient-llm-serving-on-apple-silicon-with-ssd-tiered-kv-cache-and-continuous-batching/</guid><description>vllm-mlx is a Python inference server for Apple Silicon that supports OpenAI and Anthropic APIs, featuring SSD-tiered KV cache for long-context agents and continuous batching for performance.</description></item><item><title>WriteHERE: dynamic recursive planning for AI-assisted long-form writing with real-time visualization</title><link>https://ramdi.fr/github-stars/writehere-dynamic-recursive-planning-for-ai-assisted-long-form-writing-with-real-time-visualization/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/writehere-dynamic-recursive-planning-for-ai-assisted-long-form-writing-with-real-time-visualization/</guid><description>WriteHERE uses recursive task decomposition to dynamically break down and execute long-form AI writing tasks, with real-time visualization of the agent&amp;rsquo;s thought process. Supports GPT and Claude.</description></item><item><title>X-osint: a modular Python CLI framework orchestrating multiple OSINT APIs</title><link>https://ramdi.fr/github-stars/x-osint-a-modular-python-cli-framework-orchestrating-multiple-osint-apis/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/x-osint-a-modular-python-cli-framework-orchestrating-multiple-osint-apis/</guid><description>X-osint is a Python CLI tool aggregating OSINT data from multiple external APIs with a modular menu-driven interface, designed for Termux, Linux, and macOS.</description></item><item><title>A hands-on guide to classical autonomous vehicle control algorithms in Python</title><link>https://ramdi.fr/github-stars/a-hands-on-guide-to-classical-autonomous-vehicle-control-algorithms-in-python/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/a-hands-on-guide-to-classical-autonomous-vehicle-control-algorithms-in-python/</guid><description>Explore a Python repo implementing classical autonomous vehicle algorithms as transparent simulations. Covers localization, mapping, planning, and path tracking with visualizations.</description></item><item><title>A Python bot for safe mean-reversion trading on Polymarket with triple-gate live trading safety</title><link>https://ramdi.fr/github-stars/a-python-bot-for-safe-mean-reversion-trading-on-polymarket-with-triple-gate-live-trading-safety/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/a-python-bot-for-safe-mean-reversion-trading-on-polymarket-with-triple-gate-live-trading-safety/</guid><description>An async Python bot automates a mean-reversion strategy on Polymarket&amp;rsquo;s non-sports binary markets. It features a triple-gate environment variable safety model that defaults to paper trading, minimizing accidental live trades.</description></item><item><title>AI Knowledge Graph Generator: Building structured graphs from unstructured text with LLMs</title><link>https://ramdi.fr/github-stars/ai-knowledge-graph-generator-building-structured-graphs-from-unstructured-text-with-llms/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/ai-knowledge-graph-generator-building-structured-graphs-from-unstructured-text-with-llms/</guid><description>A Python tool that converts unstructured text into interactive knowledge graphs using a three-phase LLM pipeline with SPO triplet extraction, entity standardization, and relationship inference.</description></item><item><title>ApplyPilot: autonomous AI-driven job application pipeline with modular architecture and advanced automation</title><link>https://ramdi.fr/github-stars/applypilot-autonomous-ai-driven-job-application-pipeline-with-modular-architecture-and-advanced-automation/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/applypilot-autonomous-ai-driven-job-application-pipeline-with-modular-architecture-and-advanced-automation/</guid><description>ApplyPilot automates job applications using AI scoring, resume tailoring, and Playwright-driven form submissions across multiple job boards and portals. It features a modular, parallel pipeline and CAPTCHA handling.</description></item><item><title>Automating bank statement processing with YOLOv8, OCR, and LLMs for personal finance analysis</title><link>https://ramdi.fr/github-stars/automating-bank-statement-processing-with-yolov8-ocr-and-llms-for-personal-finance-analysis/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/automating-bank-statement-processing-with-yolov8-ocr-and-llms-for-personal-finance-analysis/</guid><description>Explore how a hybrid pipeline using YOLOv8 layout detection, OCR, and LLMs automates messy bank statement PDFs for personal finance analysis with RAG and AI agents.</description></item><item><title>Automating Facebook Marketplace searches with ai-marketplace-monitor</title><link>https://ramdi.fr/github-stars/automating-facebook-marketplace-searches-with-ai-marketplace-monitor/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/automating-facebook-marketplace-searches-with-ai-marketplace-monitor/</guid><description>ai-marketplace-monitor automates Facebook Marketplace searches using Python and Playwright, enabling personalized item monitoring with notifications. Legal constraints limit its use to hobbyist scenarios.</description></item><item><title>Automating knowledge graph extraction from text with LangChain and GPT-4o</title><link>https://ramdi.fr/github-stars/automating-knowledge-graph-extraction-from-text-with-langchain-and-gpt-4o/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/automating-knowledge-graph-extraction-from-text-with-langchain-and-gpt-4o/</guid><description>This repo uses LangChain&amp;rsquo;s experimental graph transformers with GPT-4o to extract and visualize knowledge graphs from unstructured text, offering a practical LLM-based information extraction pattern.</description></item><item><title>Automating professional SVG logo generation with a structured AI workflow</title><link>https://ramdi.fr/github-stars/automating-professional-svg-logo-generation-with-a-structured-ai-workflow/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/automating-professional-svg-logo-generation-with-a-structured-ai-workflow/</guid><description>This Claude Code skill generates 6+ professional SVG logo variants through a 5-phase AI-driven workflow and produces high-quality showcases using Gemini 3.1. It blends design rigor with automation.</description></item><item><title>awesome-os-setup: a unified cross-platform OS environment setup via YAML and package manager abstraction</title><link>https://ramdi.fr/github-stars/awesome-os-setup-a-unified-cross-platform-os-environment-setup-via-yaml-and-package-manager-abstraction/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/awesome-os-setup-a-unified-cross-platform-os-environment-setup-via-yaml-and-package-manager-abstraction/</guid><description>awesome-os-setup automates environment setup across Windows, Linux, macOS, and WSL2 using a YAML-driven package catalog and unified package manager abstraction. It simplifies multi-OS workflows.</description></item><item><title>BoxPwnr: benchmarking autonomous LLM agents on cybersecurity challenges with iterative command execution</title><link>https://ramdi.fr/github-stars/boxpwnr-benchmarking-autonomous-llm-agents-on-cybersecurity-challenges-with-iterative-command-execution/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/boxpwnr-benchmarking-autonomous-llm-agents-on-cybersecurity-challenges-with-iterative-command-execution/</guid><description>BoxPwnr benchmarks LLM-based autonomous agents on cybersecurity challenges using iterative command execution in a Kali Docker container, supporting 20+ LLM models and 13+ platforms.</description></item><item><title>claude-memory-compiler: automating AI conversation memory compilation for Claude Code</title><link>https://ramdi.fr/github-stars/claude-memory-compiler-automating-ai-conversation-memory-compilation-for-claude-code/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/claude-memory-compiler-automating-ai-conversation-memory-compilation-for-claude-code/</guid><description>claude-memory-compiler automates capturing and compiling Claude Code conversations into a knowledge base, improving AI agent memory management with minimal setup.</description></item><item><title>claude-shorts: AI-driven pipeline for viral vertical video clips from long form content</title><link>https://ramdi.fr/github-stars/claude-shorts-ai-driven-pipeline-for-viral-vertical-video-clips-from-long-form-content/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/claude-shorts-ai-driven-pipeline-for-viral-vertical-video-clips-from-long-form-content/</guid><description>claude-shorts uses AI scoring, GPU transcription, and adaptive video reframing to extract viral-ready vertical clips from long videos, optimizing cuts with audio-aware snapping and platform-specific encoding.</description></item><item><title>CORAL: orchestrating autonomous AI coding agents with git worktree isolation and shared state</title><link>https://ramdi.fr/github-stars/coral-orchestrating-autonomous-ai-coding-agents-with-git-worktree-isolation-and-shared-state/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/coral-orchestrating-autonomous-ai-coding-agents-with-git-worktree-isolation-and-shared-state/</guid><description>CORAL uses git worktree branches combined with symlinked shared state to orchestrate multiple AI coding agents collaborating in real-time. This Python infrastructure supports iterative code improvement through evaluation loops.</description></item><item><title>Cupid: feed-forward 3D reconstruction with joint camera pose estimation from single images</title><link>https://ramdi.fr/github-stars/cupid-feed-forward-3d-reconstruction-with-joint-camera-pose-estimation-from-single-images/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/cupid-feed-forward-3d-reconstruction-with-joint-camera-pose-estimation-from-single-images/</guid><description>Cupid is a feed-forward 3D reconstruction model that jointly estimates camera pose and reconstructs 3D objects from single 2D images, outputting textured 3D meshes and radiance fields in seconds.</description></item><item><title>CustomTkinterBuilder: A drag-and-drop RAD GUI builder for CustomTkinter with honest tradeoffs</title><link>https://ramdi.fr/github-stars/customtkinterbuilder-a-drag-and-drop-rad-gui-builder-for-customtkinter-with-honest-tradeoffs/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/customtkinterbuilder-a-drag-and-drop-rad-gui-builder-for-customtkinter-with-honest-tradeoffs/</guid><description>CustomTkinterBuilder is a Python RAD GUI builder for CustomTkinter, supporting drag-and-drop design, code export, and themes. Honest about performance limits and project dormancy.</description></item><item><title>DATAGEN: a LangGraph multi-agent framework for automated data analysis workflows</title><link>https://ramdi.fr/github-stars/datagen-a-langgraph-multi-agent-framework-for-automated-data-analysis-workflows/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/datagen-a-langgraph-multi-agent-framework-for-automated-data-analysis-workflows/</guid><description>DATAGEN orchestrates eight specialized AI agents using LangGraph to automate data analysis workflows with progressive disclosure and multi-LLM provider support.</description></item><item><title>DocStrange: A versatile Python library for LLM-optimized document parsing with dual-mode processing</title><link>https://ramdi.fr/github-stars/docstrange-a-versatile-python-library-for-llm-optimized-document-parsing-with-dual-mode-processing/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/docstrange-a-versatile-python-library-for-llm-optimized-document-parsing-with-dual-mode-processing/</guid><description>DocStrange converts PDFs, DOCX, PPTX, XLSX, images, and URLs into LLM-ready Markdown, JSON, HTML, and CSV. It offers free cloud and private local GPU modes for flexible, privacy-compliant document parsing.</description></item><item><title>fastapi-guard: fine-grained security middleware for FastAPI with composable per-route decorators</title><link>https://ramdi.fr/github-stars/fastapi-guard-fine-grained-security-middleware-for-fastapi-with-composable-per-route-decorators/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/fastapi-guard-fine-grained-security-middleware-for-fastapi-with-composable-per-route-decorators/</guid><description>fastapi-guard offers a composable security middleware for FastAPI with per-route decorators, IP filtering, rate limiting, and an optional cloud dashboard for monitoring.</description></item><item><title>FlowKit: automating AI video generation with visual consistency via a Chrome extension bridge</title><link>https://ramdi.fr/github-stars/flowkit-automating-ai-video-generation-with-visual-consistency-via-a-chrome-extension-bridge/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/flowkit-automating-ai-video-generation-with-visual-consistency-via-a-chrome-extension-bridge/</guid><description>FlowKit automates AI video creation using Google Flow API with a unique reference image system ensuring visual consistency across scenes. It pairs a FastAPI backend with a Chrome extension bridge.</description></item><item><title>ForensiX: ML-powered forensic analysis of Chrome and Brave browser artifacts</title><link>https://ramdi.fr/github-stars/forensix-ml-powered-forensic-analysis-of-chrome-and-brave-browser-artifacts/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/forensix-ml-powered-forensic-analysis-of-chrome-and-brave-browser-artifacts/</guid><description>ForensiX combines ML-driven URL classification with browser artifact extraction for forensic analysis of Chrome and Brave data. Docker-based deployment included.</description></item><item><title>gpt_image_2_skill: modular AI image generation prompts as an agent skill and CLI</title><link>https://ramdi.fr/github-stars/gpt-image-2-skill-modular-ai-image-generation-prompts-as-an-agent-skill-and-cli/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/gpt-image-2-skill-modular-ai-image-generation-prompts-as-an-agent-skill-and-cli/</guid><description>gpt_image_2_skill packages 162 curated image generation prompts as an AI agent skill and CLI, wrapping OpenAI&amp;rsquo;s image APIs with validation and budget control for natural-language invocation.</description></item><item><title>HGM: Practical Self-Improving AI Agents with Clade-Based Code Evolution</title><link>https://ramdi.fr/github-stars/hgm-practical-self-improving-ai-agents-with-clade-based-code-evolution/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/hgm-practical-self-improving-ai-agents-with-clade-based-code-evolution/</guid><description>HGM implements a Gödel Machine approximation that iteratively rewrites its own code using subtree promise estimates, balancing exploration and exploitation in self-improving AI agents.</description></item><item><title>How OpenClaw Medical Skills modularizes Claude agents for medical AI research</title><link>https://ramdi.fr/github-stars/how-openclaw-medical-skills-modularizes-claude-agents-for-medical-ai-research/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/how-openclaw-medical-skills-modularizes-claude-agents-for-medical-ai-research/</guid><description>OpenClaw Medical Skills offers 869 modular AI agent skills to transform Claude agents into specialized medical research assistants. Explore its architecture, strengths, and installation.</description></item><item><title>In-Place TTT: Adaptive test-time training for transformer LLMs with in-place fast-weight updates</title><link>https://ramdi.fr/github-stars/in-place-ttt-adaptive-test-time-training-for-transformer-llms-with-in-place-fast-weight-updates/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/in-place-ttt-adaptive-test-time-training-for-transformer-llms-with-in-place-fast-weight-updates/</guid><description>ByteDance&amp;rsquo;s In-Place TTT enables adaptive transformer inference by updating MLP down-projection weights in-place at test time, supporting long-context reasoning without extra modules.</description></item><item><title>Inside llm-madness: a lightweight GPT transformer training pipeline with built-in visualization</title><link>https://ramdi.fr/github-stars/inside-llm-madness-a-lightweight-gpt-transformer-training-pipeline-with-built-in-visualization/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-llm-madness-a-lightweight-gpt-transformer-training-pipeline-with-built-in-visualization/</guid><description>llm-madness offers a Python-built GPT-style transformer training pipeline with tokenizer training, memory-mapped datasets, and a unique web UI for per-layer attention inspection and loss visualization.</description></item><item><title>Inside ToddlerBot: an open-source Python platform for multi-skill humanoid locomotion with depth-based skill classification</title><link>https://ramdi.fr/github-stars/inside-toddlerbot-an-open-source-python-platform-for-multi-skill-humanoid-locomotion-with-depth-based-skill-classification/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-toddlerbot-an-open-source-python-platform-for-multi-skill-humanoid-locomotion-with-depth-based-skill-classification/</guid><description>ToddlerBot offers a full Python stack for training, classifying, and deploying multi-skill humanoid locomotion policies using stereo depth data and reinforcement learning.</description></item><item><title>LangAlpha: AI agents using programmatic Python execution for financial research</title><link>https://ramdi.fr/github-stars/langalpha-ai-agents-using-programmatic-python-execution-for-financial-research/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/langalpha-ai-agents-using-programmatic-python-execution-for-financial-research/</guid><description>LangAlpha uses AI agents that write and execute Python to analyze financial data, reducing token waste and enabling persistent, steerable multi-agent research workspaces.</description></item><item><title>Leo Health Core: local-first parsing of massive health data with SAX streaming in Python</title><link>https://ramdi.fr/github-stars/leo-health-core-local-first-parsing-of-massive-health-data-with-sax-streaming-in-python/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/leo-health-core-local-first-parsing-of-massive-health-data-with-sax-streaming-in-python/</guid><description>Leo Health Core is a zero-dependency Python CLI for parsing large Apple Health XML and Whoop CSV exports into a unified SQLite DB, using SAX streaming parsing and local file watching for seamless ingestion.</description></item><item><title>lich-skills: structured AI coding assistant skills with engineering rigor</title><link>https://ramdi.fr/github-stars/lich-skills-structured-ai-coding-assistant-skills-with-engineering-rigor/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/lich-skills-structured-ai-coding-assistant-skills-with-engineering-rigor/</guid><description>lich-skills offers seven domain-specific AI coding assistant skills with a focus on spec-driven development and scientific debugging to improve reliability.</description></item><item><title>Lumibot: Unified Python trading library with AI agent runtime for reproducible strategy testing</title><link>https://ramdi.fr/github-stars/lumibot-unified-python-trading-library-with-ai-agent-runtime-for-reproducible-strategy-testing/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/lumibot-unified-python-trading-library-with-ai-agent-runtime-for-reproducible-strategy-testing/</guid><description>Lumibot unifies backtesting and live trading for stocks, options, crypto, and forex with AI agent runtime using DuckDB, supporting multiple brokers and data sources.</description></item><item><title>MCO: orchestrating multiple AI coding agents through a neutral CLI layer</title><link>https://ramdi.fr/github-stars/mco-orchestrating-multiple-ai-coding-agents-through-a-neutral-cli-layer/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/mco-orchestrating-multiple-ai-coding-agents-through-a-neutral-cli-layer/</guid><description>MCO is a Python CLI tool that orchestrates multiple AI coding agents in parallel, aggregating results with deduplication and consensus, enabling multi-agent review workflows from any AI IDE.</description></item><item><title>MegaTrain: RAM-centric training architecture for 100B+ parameter LLMs on a single GPU</title><link>https://ramdi.fr/github-stars/megatrain-ram-centric-training-architecture-for-100b-parameter-llms-on-a-single-gpu/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/megatrain-ram-centric-training-architecture-for-100b-parameter-llms-on-a-single-gpu/</guid><description>MegaTrain enables training 100B+ parameter LLMs on a single GPU by offloading all parameters to CPU RAM and streaming layers to GPU. Supports HuggingFace models and multi-GPU data parallelism without NCCL.</description></item><item><title>Memcord: a privacy-first self-hosted MCP server for AI memory management</title><link>https://ramdi.fr/github-stars/memcord-a-privacy-first-self-hosted-mcp-server-for-ai-memory-management/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/memcord-a-privacy-first-self-hosted-mcp-server-for-ai-memory-management/</guid><description>Memcord is a self-hosted MCP server enabling local-first AI memory with slot-based context isolation and multiple summarization backends, designed for privacy and developer ergonomics.</description></item><item><title>MemKraft: local-first memory for AI agents with empirical self-improvement</title><link>https://ramdi.fr/github-stars/memkraft-local-first-memory-for-ai-agents-with-empirical-self-improvement/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/memkraft-local-first-memory-for-ai-agents-with-empirical-self-improvement/</guid><description>MemKraft is a zero-dependency local-first memory system storing AI agent knowledge as Markdown, featuring bitemporal tracking, hybrid search, and a prompt self-improvement loop.</description></item><item><title>Modular extruder mounts for Voron V0.2 Mini-Stealthburner: a clean hardware abstraction</title><link>https://ramdi.fr/github-stars/modular-extruder-mounts-for-voron-v0-2-mini-stealthburner-a-clean-hardware-abstraction/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/modular-extruder-mounts-for-voron-v0-2-mini-stealthburner-a-clean-hardware-abstraction/</guid><description>MiniSB-Extruder-Mounts offers modular 3D printable mounts adapting the Voron V0.2 Mini-Stealthburner toolhead to 17 extruder models, preserving core geometry for drop-in compatibility.</description></item><item><title>MR.ScaleMaster: heterogeneous multi-robot monocular SLAM fusion via Sim(3) optimization</title><link>https://ramdi.fr/github-stars/mr-scalemaster-heterogeneous-multi-robot-monocular-slam-fusion-via-sim-3-optimization/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/mr-scalemaster-heterogeneous-multi-robot-monocular-slam-fusion-via-sim-3-optimization/</guid><description>MR.ScaleMaster fuses scale-ambiguous monocular SLAM trajectories from multiple robots using Sim(3) graph optimization, enabling heterogeneous SLAM frontends and consistent global maps.</description></item><item><title>MV-SAM3D: entropy-weighted multi-view fusion for 3D object reconstruction</title><link>https://ramdi.fr/github-stars/mv-sam3d-entropy-weighted-multi-view-fusion-for-3d-object-reconstruction/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/mv-sam3d-entropy-weighted-multi-view-fusion-for-3d-object-reconstruction/</guid><description>MV-SAM3D extends SAM 3D Objects with entropy-based multi-view fusion and optional pose optimization for more stable and consistent 3D object reconstruction across scenes.</description></item><item><title>NAS3R: Self-supervised 3D reconstruction and camera pose estimation with Gaussian splatting</title><link>https://ramdi.fr/github-stars/nas3r-self-supervised-3d-reconstruction-and-camera-pose-estimation-with-gaussian-splatting/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/nas3r-self-supervised-3d-reconstruction-and-camera-pose-estimation-with-gaussian-splatting/</guid><description>NAS3R enables self-supervised 3D geometry and camera parameter estimation without ground-truth data, using Gaussian splatting and a VGGT backbone. It supports multi-view setups and optional pretrained initialization.</description></item><item><title>NOVA3R: Non-pixel-aligned visual transformer for amodal 3D reconstruction from unposed multi-view images</title><link>https://ramdi.fr/github-stars/nova3r-non-pixel-aligned-visual-transformer-for-amodal-3d-reconstruction-from-unposed-multi-view-images/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/nova3r-non-pixel-aligned-visual-transformer-for-amodal-3d-reconstruction-from-unposed-multi-view-images/</guid><description>NOVA3R implements a non-pixel-aligned visual transformer for amodal 3D reconstruction from unposed multi-view images, recovering occluded geometry with physical plausibility.</description></item><item><title>NVIDIA NeMo Agent Toolkit: Enhancing multi-agent workflows with performance primitives and observability</title><link>https://ramdi.fr/github-stars/nvidia-nemo-agent-toolkit-enhancing-multi-agent-workflows-with-performance-primitives-and-observability/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/nvidia-nemo-agent-toolkit-enhancing-multi-agent-workflows-with-performance-primitives-and-observability/</guid><description>NVIDIA NeMo Agent Toolkit adds performance primitives, profiling, and runtime intelligence to multi-agent workflows alongside existing frameworks like LangChain. It enables latency-aware routing, token-level profiling, and YAML-driven flows.</description></item><item><title>OmniStream: a multi-frame transformer for continuous video stream perception</title><link>https://ramdi.fr/github-stars/omnistream-a-multi-frame-transformer-for-continuous-video-stream-perception/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/omnistream-a-multi-frame-transformer-for-continuous-video-stream-perception/</guid><description>OmniStream uses a multi-frame transformer to process continuous video streams with patch-level temporal indexing, supporting downstream vision-language-action tasks.</description></item><item><title>OpenMythos: Exploring recurrent-depth transformers with input injection for sustained reasoning</title><link>https://ramdi.fr/github-stars/openmythos-exploring-recurrent-depth-transformers-with-input-injection-for-sustained-reasoning/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/openmythos-exploring-recurrent-depth-transformers-with-input-injection-for-sustained-reasoning/</guid><description>OpenMythos implements a recurrent-depth transformer that recycles layers via looped blocks, using input injection to prevent signal drift. It scales from 1B to 1T parameters with up to 1M token context.</description></item><item><title>OpenResearcher: An open-source 30B LLM for long-horizon deep research</title><link>https://ramdi.fr/github-stars/openresearcher-an-open-source-30b-llm-for-long-horizon-deep-research/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/openresearcher-an-open-source-30b-llm-for-long-horizon-deep-research/</guid><description>OpenResearcher is a fully open 30B agentic LLM designed for deep research tasks, featuring a 96K-turn dataset and a self-built retriever over 11B tokens, running on vLLM with 8×A100 GPUs.</description></item><item><title>ordinary-claude-skills: an extensive local-first library of Claude prompt packages for specialized AI agents</title><link>https://ramdi.fr/github-stars/ordinary-claude-skills-an-extensive-local-first-library-of-claude-prompt-packages-for-specialized-ai-agents/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/ordinary-claude-skills-an-extensive-local-first-library-of-claude-prompt-packages-for-specialized-ai-agents/</guid><description>Discover ordinary-claude-skills, a local-first collection of 600+ prompt packages that specialize Claude AI with domain skills, integrated via MCP filesystem for lazy loading.</description></item><item><title>Otakuapuri: a Python desktop app for manga and anime with Cloudflare-bypass scraping and responsive Tkinter UI</title><link>https://ramdi.fr/github-stars/otakuapuri-a-python-desktop-app-for-manga-and-anime-with-cloudflare-bypass-scraping-and-responsive-tkinter-ui/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/otakuapuri-a-python-desktop-app-for-manga-and-anime-with-cloudflare-bypass-scraping-and-responsive-tkinter-ui/</guid><description>Otakuapuri is a Python Tkinter app combining manga download, reading, and anime streaming with Cloudflare-bypass scraping and multithreaded UI for responsiveness.</description></item><item><title>paper-console: modular thermal printer IoT with dual-mode Raspberry Pi integration</title><link>https://ramdi.fr/github-stars/paper-console-modular-thermal-printer-iot-with-dual-mode-raspberry-pi-integration/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/paper-console-modular-thermal-printer-iot-with-dual-mode-raspberry-pi-integration/</guid><description>paper-console runs a modular FastAPI backend and Vue/Svelte frontend to print curated content on thermal paper via Raspberry Pi Zero 2 W, supporting dev mock mode and hardware mode with GPIO integration.</description></item><item><title>PAT3D: orchestrating text-to-3D simulation-ready scenes through a multi-stage AI and physics pipeline</title><link>https://ramdi.fr/github-stars/pat3d-orchestrating-text-to-3d-simulation-ready-scenes-through-a-multi-stage-ai-and-physics-pipeline/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/pat3d-orchestrating-text-to-3d-simulation-ready-scenes-through-a-multi-stage-ai-and-physics-pipeline/</guid><description>PAT3D composes a 9-stage pipeline combining LLMs, vision models, 3D asset generators, and physics simulation to produce physically plausible, simulation-ready 3D scenes from text prompts.</description></item><item><title>Picosnitch: per-executable network monitoring on Linux with eBPF and fanotify</title><link>https://ramdi.fr/github-stars/picosnitch-per-executable-network-monitoring-on-linux-with-ebpf-and-fanotify/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/picosnitch-per-executable-network-monitoring-on-linux-with-ebpf-and-fanotify/</guid><description>Picosnitch uses eBPF and fanotify to track bandwidth per executable on Linux, with device+inode caching and hash verification for accuracy.</description></item><item><title>Prefab: a Python-first declarative UI framework for agent-generated MCP apps</title><link>https://ramdi.fr/github-stars/prefab-a-python-first-declarative-ui-framework-for-agent-generated-mcp-apps/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/prefab-a-python-first-declarative-ui-framework-for-agent-generated-mcp-apps/</guid><description>Prefab offers a Python DSL for building declarative UI compiled to JSON and rendered via React, designed for MCP apps and AI agent-generated interfaces without frontend JavaScript.</description></item><item><title>PromptHMR: integrating promptable architecture for 3D human mesh recovery from monocular inputs</title><link>https://ramdi.fr/github-stars/prompthmr-integrating-promptable-architecture-for-3d-human-mesh-recovery-from-monocular-inputs/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/prompthmr-integrating-promptable-architecture-for-3d-human-mesh-recovery-from-monocular-inputs/</guid><description>PromptHMR adapts SAM&amp;rsquo;s promptable design to 3D human mesh recovery, integrating SLAM, pose detection, and SMPL models into a unified pipeline for monocular images and videos.</description></item><item><title>Python Data Science Handbook: Exploring the Core Python Data Science Stack Through Executable Notebooks</title><link>https://ramdi.fr/github-stars/python-data-science-handbook-exploring-the-core-python-data-science-stack-through-executable-notebooks/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/python-data-science-handbook-exploring-the-core-python-data-science-stack-through-executable-notebooks/</guid><description>Explore the Python Data Science Handbook repo offering runnable Jupyter notebooks covering NumPy, Pandas, Matplotlib, and Scikit-Learn with no local setup required.</description></item><item><title>QuantaAlpha: LLM-driven trajectory-based self-evolution for quantitative alpha factor discovery</title><link>https://ramdi.fr/github-stars/quantaalpha-llm-driven-trajectory-based-self-evolution-for-quantitative-alpha-factor-discovery/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/quantaalpha-llm-driven-trajectory-based-self-evolution-for-quantitative-alpha-factor-discovery/</guid><description>QuantaAlpha uses large language models with evolutionary strategies to automate quantitative alpha factor discovery, achieving strong backtest metrics on major indices.</description></item><item><title>RESTai: a multi-project AIaaS platform with agentic browser automation and visual AI pipelines</title><link>https://ramdi.fr/github-stars/restai-a-multi-project-aiaas-platform-with-agentic-browser-automation-and-visual-ai-pipelines/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/restai-a-multi-project-aiaas-platform-with-agentic-browser-automation-and-visual-ai-pipelines/</guid><description>RESTai exposes multi-project AI capabilities via a unified REST API, featuring an agentic browser with Dockerized Playwright, knowledge graph RAG, and a visual Blockly pipeline builder.</description></item><item><title>SceneMaker: a decoupled framework for 3D scene generation with de-occlusion</title><link>https://ramdi.fr/github-stars/scenemaker-a-decoupled-framework-for-3d-scene-generation-with-de-occlusion/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/scenemaker-a-decoupled-framework-for-3d-scene-generation-with-de-occlusion/</guid><description>SceneMaker separates de-occlusion from 3D object generation to handle occluded open-set scenes. It uses FLUX Kontext and Step1X-3D, with code and checkpoints available.</description></item><item><title>SimRecon: compositional 3D scene reconstruction with viewpoint optimization and semantic graph synthesis</title><link>https://ramdi.fr/github-stars/simrecon-compositional-3d-scene-reconstruction-with-viewpoint-optimization-and-semantic-graph-synthesis/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/simrecon-compositional-3d-scene-reconstruction-with-viewpoint-optimization-and-semantic-graph-synthesis/</guid><description>SimRecon converts real-world videos into simulation-ready 3D scenes by combining geometry reconstruction, instance segmentation, viewpoint optimization, and semantic scene graph synthesis.</description></item><item><title>Spatial organization for home data with a self-hosted Django app</title><link>https://ramdi.fr/github-stars/spatial-organization-for-home-data-with-a-self-hosted-django-app/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/spatial-organization-for-home-data-with-a-self-hosted-django-app/</guid><description>Home Information offers a spatial, local-first way to organize home manuals, warranties, and controls via a Django app integrating Home Assistant and ZoneMinder. Easy Docker quick start included.</description></item><item><title>Spec-first web design with Claude Code: enforcing design contracts via DESIGN.md</title><link>https://ramdi.fr/github-stars/spec-first-web-design-with-claude-code-enforcing-design-contracts-via-design-md/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/spec-first-web-design-with-claude-code-enforcing-design-contracts-via-design-md/</guid><description>web-design is a Claude Code SKILL that enforces a spec-first web design workflow via DESIGN.md, bridging AI code generation with consistent, testable design output.</description></item><item><title>Spoolman: managing 3D printer filament inventory with real-time sync and multi-backend support</title><link>https://ramdi.fr/github-stars/spoolman-managing-3d-printer-filament-inventory-with-real-time-sync-and-multi-backend-support/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/spoolman-managing-3d-printer-filament-inventory-with-real-time-sync-and-multi-backend-support/</guid><description>Spoolman is a Python web service that tracks 3D printer filament inventory in real-time with multi-printer concurrency, supporting four databases and major 3D printing platforms.</description></item><item><title>standardizing AI agent capabilities with sanjay3290/ai-skills</title><link>https://ramdi.fr/github-stars/standardizing-ai-agent-capabilities-with-sanjay3290-ai-skills/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/standardizing-ai-agent-capabilities-with-sanjay3290-ai-skills/</guid><description>Explore sanjay3290/ai-skills, a portable skill collection implementing the open Agent Skills Standard for cross-platform AI agent extensibility. Supports 40+ agents, 20+ skills, with OAuth security.</description></item><item><title>Stash: a shared agent memory with no server-side LLM calls</title><link>https://ramdi.fr/github-stars/stash-a-shared-agent-memory-with-no-server-side-llm-calls/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/stash-a-shared-agent-memory-with-no-server-side-llm-calls/</guid><description>Stash captures coding agent session transcripts for teams and builds a shared knowledge base without server-side LLM calls, preserving privacy and cutting costs.</description></item><item><title>Tencent Hunyuan3D-Part: a two-stage pipeline for semantic 3D mesh part segmentation and generation</title><link>https://ramdi.fr/github-stars/tencent-hunyuan3d-part-a-two-stage-pipeline-for-semantic-3d-mesh-part-segmentation-and-generation/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/tencent-hunyuan3d-part-a-two-stage-pipeline-for-semantic-3d-mesh-part-segmentation-and-generation/</guid><description>Tencent&amp;rsquo;s Hunyuan3D-Part offers a two-model pipeline for 3D mesh part segmentation with P3-SAM and high-fidelity part generation via X-Part, targeting semantic mesh decomposition.</description></item><item><title>TinyPilot: building a browser-based KVM over IP with a Raspberry Pi and uStreamer</title><link>https://ramdi.fr/github-stars/tinypilot-building-a-browser-based-kvm-over-ip-with-a-raspberry-pi-and-ustreamer/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/tinypilot-building-a-browser-based-kvm-over-ip-with-a-raspberry-pi-and-ustreamer/</guid><description>TinyPilot transforms a Raspberry Pi into a browser-based KVM over IP device using uStreamer and Flask-SocketIO for low-latency remote keyboard, video, and mouse control.</description></item><item><title>Voice Clone Studio: unified modular web UI for multi-engine voice cloning and TTS</title><link>https://ramdi.fr/github-stars/voice-clone-studio-unified-modular-web-ui-for-multi-engine-voice-cloning-and-tts/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/voice-clone-studio-unified-modular-web-ui-for-multi-engine-voice-cloning-and-tts/</guid><description>Voice Clone Studio unifies multiple voice AI engines in a modular Gradio web UI. Supports voice cloning, multi-speaker dialogs, speech-to-speech, and LoRA fine-tuning with GPU or Apple Silicon.</description></item><item><title>watchtower: langgraph orchestration for automated pentesting workflows</title><link>https://ramdi.fr/github-stars/watchtower-langgraph-orchestration-for-automated-pentesting-workflows/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/watchtower-langgraph-orchestration-for-automated-pentesting-workflows/</guid><description>Watchtower orchestrates 23 security tools via a LangGraph multi-agent system for automated pentesting. It uses a Planner-Worker-Analyst pattern, SQLite state, and supports multiple LLM providers.</description></item><item><title>WhyHow Knowledge Graph Studio: building RAG-native knowledge graphs with MongoDB and OpenAI</title><link>https://ramdi.fr/github-stars/whyhow-knowledge-graph-studio-building-rag-native-knowledge-graphs-with-mongodb-and-openai/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/whyhow-knowledge-graph-studio-building-rag-native-knowledge-graphs-with-mongodb-and-openai/</guid><description>WhyHow Knowledge Graph Studio builds RAG-native knowledge graphs using MongoDB and OpenAI embeddings, offering flexible triple-based graph construction for AI workflows.</description></item><item><title>Windrecorder: a local-first screen recorder with multi-engine OCR indexing</title><link>https://ramdi.fr/github-stars/windrecorder-a-local-first-screen-recorder-with-multi-engine-ocr-indexing/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/windrecorder-a-local-first-screen-recorder-with-multi-engine-ocr-indexing/</guid><description>Windrecorder captures screen activity on Windows, indexes it with multiple OCR engines locally, and offers a searchable rewind UI—all without cloud dependencies.</description></item><item><title>WorldGrow: Hierarchical infinite 3D world synthesis with block-wise growth and coarse-to-fine refinement</title><link>https://ramdi.fr/github-stars/worldgrow-hierarchical-infinite-3d-world-synthesis-with-block-wise-growth-and-coarse-to-fine-refinement/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/worldgrow-hierarchical-infinite-3d-world-synthesis-with-block-wise-growth-and-coarse-to-fine-refinement/</guid><description>WorldGrow generates infinite 3D worlds via hierarchical block-wise synthesis with coarse-to-fine refinement, ensuring seamless, explorable environments for navigation and planning tasks.</description></item><item><title>Zero Password Manager: a Flutter frontend with Python backend for secure credential management</title><link>https://ramdi.fr/github-stars/zero-password-manager-a-flutter-frontend-with-python-backend-for-secure-credential-management/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/zero-password-manager-a-flutter-frontend-with-python-backend-for-secure-credential-management/</guid><description>Zero Password Manager is an open-source project combining Flutter/Dart frontend with a Python backend to offer a secure, cross-platform password management solution. The repo balances UI flexibility and backend performance with a clear setup path.</description></item><item><title>Using an MCP server to query Meta Ads API for AI-driven ad insights</title><link>https://ramdi.fr/github-stars/using-an-mcp-server-to-query-meta-ads-api-for-ai-driven-ad-insights/</link><pubDate>Mon, 04 May 2026 10:18:38 +0000</pubDate><guid>https://ramdi.fr/github-stars/using-an-mcp-server-to-query-meta-ads-api-for-ai-driven-ad-insights/</guid><description>This Python MCP server wraps Meta&amp;rsquo;s Facebook Ads API into 20+ tools, letting AI agents query ad data conversationally. Setup is simple with a single server.py and token auth.</description></item><item><title>Blueprint MCP: async AI diagram generation for code architecture visualization</title><link>https://ramdi.fr/github-stars/blueprint-mcp-async-ai-diagram-generation-for-code-architecture-visualization/</link><pubDate>Mon, 04 May 2026 10:17:20 +0000</pubDate><guid>https://ramdi.fr/github-stars/blueprint-mcp-async-ai-diagram-generation-for-code-architecture-visualization/</guid><description>Blueprint MCP is a Python MCP server that generates system diagrams from codebases asynchronously using Google&amp;rsquo;s Nano Banana Pro model, integrated with Arcade MCP and Cursor IDE.</description></item><item><title>Turning text into AI podcast episodes with a coding agent and Fish Audio TTS</title><link>https://ramdi.fr/github-stars/turning-text-into-ai-podcast-episodes-with-a-coding-agent-and-fish-audio-tts/</link><pubDate>Mon, 04 May 2026 10:16:09 +0000</pubDate><guid>https://ramdi.fr/github-stars/turning-text-into-ai-podcast-episodes-with-a-coding-agent-and-fish-audio-tts/</guid><description>personalized-podcast turns text or URLs into two-host AI podcast episodes using Claude Code for script writing and Fish Audio TTS for voice synthesis, all in a streamlined pipeline.</description></item><item><title>Meridian: tackling AI session context loss with smart lifecycle hooks and project scaffolding</title><link>https://ramdi.fr/github-stars/meridian-tackling-ai-session-context-loss-with-smart-lifecycle-hooks-and-project-scaffolding/</link><pubDate>Mon, 04 May 2026 10:13:55 +0000</pubDate><guid>https://ramdi.fr/github-stars/meridian-tackling-ai-session-context-loss-with-smart-lifecycle-hooks-and-project-scaffolding/</guid><description>Meridian is a Claude Code plugin that solves session context loss in long AI coding sessions using lifecycle hooks and a persistent project workspace. Here&amp;rsquo;s how it works and how to get started.</description></item><item><title>Alpaca MCP Server v2: Spec-driven MCP integration for trading APIs</title><link>https://ramdi.fr/github-stars/alpaca-mcp-server-v2-spec-driven-mcp-integration-for-trading-apis/</link><pubDate>Mon, 04 May 2026 10:13:18 +0000</pubDate><guid>https://ramdi.fr/github-stars/alpaca-mcp-server-v2-spec-driven-mcp-integration-for-trading-apis/</guid><description>Alpaca MCP Server v2 rewrites the official MCP server using FastMCP and OpenAPI tools, exposing Alpaca&amp;rsquo;s Trading API via MCP for AI clients with env-var config and toolset filtering.</description></item><item><title>unslop: empirically detecting and avoiding repetitive LLM output patterns</title><link>https://ramdi.fr/github-stars/unslop-empirically-detecting-and-avoiding-repetitive-llm-output-patterns/</link><pubDate>Mon, 04 May 2026 10:11:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/unslop-empirically-detecting-and-avoiding-repetitive-llm-output-patterns/</guid><description>unslop is a Python CLI tool that detects repetitive defaults in LLM outputs by empirical analysis, generating reusable anti-pattern profiles to improve prompt engineering.</description></item><item><title>Google Maps Scraper: navigating the fragility of XPath-based browser automation</title><link>https://ramdi.fr/github-stars/google-maps-scraper-navigating-the-fragility-of-xpath-based-browser-automation/</link><pubDate>Mon, 04 May 2026 10:07:00 +0000</pubDate><guid>https://ramdi.fr/github-stars/google-maps-scraper-navigating-the-fragility-of-xpath-based-browser-automation/</guid><description>A Python Playwright scraper automates Google Maps data extraction using XPath selectors. It reveals the real maintenance cost of brittle DOM scraping and dependency pinning.</description></item><item><title>hermes-hudui: a TypeScript web UI for interacting with the Hermes AI agent</title><link>https://ramdi.fr/github-stars/hermes-hudui-a-typescript-web-ui-for-interacting-with-the-hermes-ai-agent/</link><pubDate>Mon, 04 May 2026 10:06:27 +0000</pubDate><guid>https://ramdi.fr/github-stars/hermes-hudui-a-typescript-web-ui-for-interacting-with-the-hermes-ai-agent/</guid><description>hermes-hudui provides a TypeScript-based web UI to interact with the Hermes AI agent, offering real-time data visualization and control. Setup requires Python 3.11+, Node.js 18+, and a running Hermes agent.</description></item><item><title>Be More Agent: offline-first conversational AI on Raspberry Pi with hardware-aware audio handling</title><link>https://ramdi.fr/github-stars/be-more-agent-offline-first-conversational-ai-on-raspberry-pi-with-hardware-aware-audio-handling/</link><pubDate>Mon, 04 May 2026 10:04:45 +0000</pubDate><guid>https://ramdi.fr/github-stars/be-more-agent-offline-first-conversational-ai-on-raspberry-pi-with-hardware-aware-audio-handling/</guid><description>Be More Agent is an offline-first conversational AI framework for Raspberry Pi, combining local LLM inference with hardware-aware audio resampling to handle ALSA quirks. Runs 100% locally.</description></item><item><title>ROMP: from real-time monocular 3D human mesh recovery to temporal tracking with dynamic cameras</title><link>https://ramdi.fr/github-stars/romp-from-real-time-monocular-3d-human-mesh-recovery-to-temporal-tracking-with-dynamic-cameras/</link><pubDate>Mon, 04 May 2026 10:03:52 +0000</pubDate><guid>https://ramdi.fr/github-stars/romp-from-real-time-monocular-3d-human-mesh-recovery-to-temporal-tracking-with-dynamic-cameras/</guid><description>ROMP evolves monocular multi-person 3D mesh recovery from single-frame regression to temporal tracking under dynamic cameras, packaged with ONNX acceleration and Docker support.</description></item><item><title>A-MEM: dynamic semantic memory management for LLM agents inspired by Zettelkasten</title><link>https://ramdi.fr/github-stars/a-mem-dynamic-semantic-memory-management-for-llm-agents-inspired-by-zettelkasten/</link><pubDate>Sun, 03 May 2026 00:54:10 +0000</pubDate><guid>https://ramdi.fr/github-stars/a-mem-dynamic-semantic-memory-management-for-llm-agents-inspired-by-zettelkasten/</guid><description>A-MEM is a Python agentic memory system that dynamically organizes LLM agent memories using semantic embeddings and automatic linking, inspired by Zettelkasten.</description></item><item><title>CrewAI: A lean Python framework for orchestrating autonomous AI agents with precise control</title><link>https://ramdi.fr/github-stars/crewai-a-lean-python-framework-for-orchestrating-autonomous-ai-agents-with-precise-control/</link><pubDate>Sat, 02 May 2026 20:17:54 +0000</pubDate><guid>https://ramdi.fr/github-stars/crewai-a-lean-python-framework-for-orchestrating-autonomous-ai-agents-with-precise-control/</guid><description>CrewAI is a Python framework for autonomous AI agents emphasizing speed, flexibility, and precise control through &amp;lsquo;Crews&amp;rsquo; and &amp;lsquo;Flows&amp;rsquo;. It offers enterprise features for production-grade AI orchestration.</description></item><item><title>A hands-on course for mastering large language models: fine-tuning, quantization, and tooling</title><link>https://ramdi.fr/github-stars/a-hands-on-course-for-mastering-large-language-models-fine-tuning-quantization-and-tooling/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/a-hands-on-course-for-mastering-large-language-models-fine-tuning-quantization-and-tooling/</guid><description>Explore a comprehensive LLM course with practical notebooks on fine-tuning (QLoRA, DPO), quantization (GPTQ), and tools like AutoEval and LazyMergekit. Ideal for aspiring LLM engineers.</description></item><item><title>Agno: Building production-ready agentic software with minimal code</title><link>https://ramdi.fr/github-stars/agno-building-production-ready-agentic-software-with-minimal-code/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/agno-building-production-ready-agentic-software-with-minimal-code/</guid><description>Agno provides a minimal, production-ready Python framework for scalable agentic software with per-user isolation and native tracing in ~20 lines of code.</description></item><item><title>AIHawk: An open-source AI agent tackling automated job applications under copyright constraints</title><link>https://ramdi.fr/github-stars/aihawk-an-open-source-ai-agent-tackling-automated-job-applications-under-copyright-constraints/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/aihawk-an-open-source-ai-agent-tackling-automated-job-applications-under-copyright-constraints/</guid><description>AIHawk offers an open-source AI agent that automates job applications. Its architecture balances open AI automation with the legal realities of third-party integrations.</description></item><item><title>annotated_deep_learning_paper_implementations: annotated PyTorch implementations of key deep learning papers</title><link>https://ramdi.fr/github-stars/annotated-deep-learning-paper-implementations-annotated-pytorch-implementations-of-key-deep-learning-papers/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/annotated-deep-learning-paper-implementations-annotated-pytorch-implementations-of-key-deep-learning-papers/</guid><description>This repo provides annotated PyTorch implementations of major deep learning papers with side-by-side explanations, aiding understanding and prototyping.</description></item><item><title>AutoScraper: simplifying web scraping through example-driven rule learning</title><link>https://ramdi.fr/github-stars/autoscraper-simplifying-web-scraping-through-example-driven-rule-learning/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/autoscraper-simplifying-web-scraping-through-example-driven-rule-learning/</guid><description>AutoScraper automates web scraping by learning extraction rules from sample data, avoiding manual CSS selectors. This Python tool eases scraping repetitive, similar web content.</description></item><item><title>Crawlee Python: a flexible dual-crawler framework for web scraping and automation</title><link>https://ramdi.fr/github-stars/crawlee-python-a-flexible-dual-crawler-framework-for-web-scraping-and-automation/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/crawlee-python-a-flexible-dual-crawler-framework-for-web-scraping-and-automation/</guid><description>Crawlee Python offers a dual approach to web scraping with lightweight HTML parsing and headless browser automation, balancing speed and interactivity for diverse scraping needs.</description></item><item><title>Exploring Microsoft's generative AI for beginners: a dual-language practical course</title><link>https://ramdi.fr/github-stars/exploring-microsoft-s-generative-ai-for-beginners-a-dual-language-practical-course/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/exploring-microsoft-s-generative-ai-for-beginners-a-dual-language-practical-course/</guid><description>Microsoft&amp;rsquo;s &amp;ldquo;Generative AI for Beginners&amp;rdquo; offers 21 lessons with Python and TypeScript examples covering LLMs, prompt engineering, RAG, and AI app building.</description></item><item><title>face_recognition: easy deep learning face recognition in Python with dlib</title><link>https://ramdi.fr/github-stars/face-recognition-easy-deep-learning-face-recognition-in-python-with-dlib/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/face-recognition-easy-deep-learning-face-recognition-in-python-with-dlib/</guid><description>face_recognition provides a simple Python API and CLI for highly accurate face detection and recognition using dlib&amp;rsquo;s deep learning model. It supports facial landmarks and multi-core processing.</description></item><item><title>HelloGitHub: How curated open source content drives community engagement at scale</title><link>https://ramdi.fr/github-stars/hellogithub-how-curated-open-source-content-drives-community-engagement-at-scale/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/hellogithub-how-curated-open-source-content-drives-community-engagement-at-scale/</guid><description>HelloGitHub curates entry-level open source projects monthly, fostering community engagement through human curation rather than code complexity. Here&amp;rsquo;s how it works.</description></item><item><title>Hermes Agent: A self-improving AI agent with closed learning loops and multi-platform integration</title><link>https://ramdi.fr/github-stars/hermes-agent-a-self-improving-ai-agent-with-closed-learning-loops-and-multi-platform-integration/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/hermes-agent-a-self-improving-ai-agent-with-closed-learning-loops-and-multi-platform-integration/</guid><description>Hermes Agent is a Python AI agent featuring closed learning loops, autonomous skill creation, multi-model support, and seamless Telegram/Discord integration for persistent, adaptable AI workflows.</description></item><item><title>how awesome-claude-skills turns claude into a real-world action agent</title><link>https://ramdi.fr/github-stars/how-awesome-claude-skills-turns-claude-into-a-real-world-action-agent/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/how-awesome-claude-skills-turns-claude-into-a-real-world-action-agent/</guid><description>Awesome Claude Skills is a modular Python framework that empowers Claude to perform real-world actions by integrating with 500+ apps via Composio, extending its utility beyond text generation.</description></item><item><title>httpie/cli: A human-friendly command-line HTTP client for API interaction</title><link>https://ramdi.fr/github-stars/httpie-cli-a-human-friendly-command-line-http-client-for-api-interaction/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/httpie-cli-a-human-friendly-command-line-http-client-for-api-interaction/</guid><description>HTTPie CLI offers a simple, readable way to interact with HTTP APIs via command line, with built-in JSON support and colorized output that improves developer experience.</description></item><item><title>Inside agents: a granular multi-agent orchestration system with PluginEval quality assurance</title><link>https://ramdi.fr/github-stars/inside-agents-a-granular-multi-agent-orchestration-system-with-plugineval-quality-assurance/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-agents-a-granular-multi-agent-orchestration-system-with-plugineval-quality-assurance/</guid><description>Explore agents, a Python-based multi-agent orchestration repo featuring 184 AI agents, 78 plugins, and a three-layer PluginEval framework for plugin quality assurance.</description></item><item><title>Langflow: Visual orchestration platform for AI agents and workflows</title><link>https://ramdi.fr/github-stars/langflow-visual-orchestration-platform-for-ai-agents-and-workflows/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/langflow-visual-orchestration-platform-for-ai-agents-and-workflows/</guid><description>Langflow offers a Python-based visual platform to build and deploy AI agents and workflows with multi-agent orchestration, vector DB support, and enterprise features.</description></item><item><title>LlamaFactory: modular, extensible fine-tuning framework for large language models</title><link>https://ramdi.fr/github-stars/llamafactory-modular-extensible-fine-tuning-framework-for-large-language-models/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/llamafactory-modular-extensible-fine-tuning-framework-for-large-language-models/</guid><description>LlamaFactory offers a modular Python framework for fine-tuning 100+ LLMs with diverse algorithms and optimizations, including LoRA, QLoRA, and reinforcement learning.</description></item><item><title>Maigret: A resilient OSINT username scraper across thousands of sites</title><link>https://ramdi.fr/github-stars/maigret-a-resilient-osint-username-scraper-across-thousands-of-sites/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/maigret-a-resilient-osint-username-scraper-across-thousands-of-sites/</guid><description>Maigret is a Python-based OSINT tool that scrapes public profiles by username from 3,000+ sites without API keys. It features adaptive scraping, anti-blocking, and a web interface.</description></item><item><title>mem0: optimizing AI agent memory with a new single-pass additive algorithm</title><link>https://ramdi.fr/github-stars/mem0-optimizing-ai-agent-memory-with-a-new-single-pass-additive-algorithm/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/mem0-optimizing-ai-agent-memory-with-a-new-single-pass-additive-algorithm/</guid><description>mem0 enhances AI agent memory with a new single-pass ADD-only extraction algorithm and multi-signal retrieval, boosting benchmarks significantly while simplifying memory management.</description></item><item><title>MetaGPT: orchestrating multi-agent AI teams to automate software development</title><link>https://ramdi.fr/github-stars/metagpt-orchestrating-multi-agent-ai-teams-to-automate-software-development/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/metagpt-orchestrating-multi-agent-ai-teams-to-automate-software-development/</guid><description>MetaGPT uses a multi-agent system with defined GPT roles following SOPs to automate software development from one-line prompts. It simulates a software company with role-based AI collaboration.</description></item><item><title>Microsoft's ML-For-Beginners: A Project-Based Classic Machine Learning Curriculum</title><link>https://ramdi.fr/github-stars/microsoft-s-ml-for-beginners-a-project-based-classic-machine-learning-curriculum/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/microsoft-s-ml-for-beginners-a-project-based-classic-machine-learning-curriculum/</guid><description>Microsoft&amp;rsquo;s ML-For-Beginners offers a 12-week, project-based classic machine learning course using Scikit-learn and Jupyter Notebooks, focusing on foundational concepts with interactive lessons and quizzes.</description></item><item><title>Pydoll: Async-native Chromium automation with typed extraction for web scraping</title><link>https://ramdi.fr/github-stars/pydoll-async-native-chromium-automation-with-typed-extraction-for-web-scraping/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/pydoll-async-native-chromium-automation-with-typed-extraction-for-web-scraping/</guid><description>Pydoll is a Python library for Chromium automation using Chrome DevTools Protocol. It offers async-native APIs and Pydantic-powered data extraction for structured, validated scraping.</description></item><item><title>Spec Kit: AI-Driven Spec-Driven Development with Executable Specifications</title><link>https://ramdi.fr/github-stars/spec-kit-ai-driven-spec-driven-development-with-executable-specifications/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/spec-kit-ai-driven-spec-driven-development-with-executable-specifications/</guid><description>Spec Kit redefines software development by turning specifications into executable artifacts guided by AI agents, offering a CLI-driven, human-in-the-loop workflow for predictable software delivery.</description></item><item><title>TrendRadar: AI-powered multi-platform trend monitoring with MCP architecture</title><link>https://ramdi.fr/github-stars/trendradar-ai-powered-multi-platform-trend-monitoring-with-mcp-architecture/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/trendradar-ai-powered-multi-platform-trend-monitoring-with-mcp-architecture/</guid><description>TrendRadar is a self-hosted AI-driven tool for multi-platform trend monitoring, using MCP architecture for advanced language analysis and smart push notifications across popular messaging platforms.</description></item><item><title>undetected-chromedriver: patching Selenium to evade anti-bot detection</title><link>https://ramdi.fr/github-stars/undetected-chromedriver-patching-selenium-to-evade-anti-bot-detection/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/undetected-chromedriver-patching-selenium-to-evade-anti-bot-detection/</guid><description>undetected-chromedriver patches Selenium&amp;rsquo;s Chromedriver to bypass anti-bot defenses like Distill Network and DataDome. It supports Chrome beta and Chromium-based browsers with ease.</description></item><item><title>vLLM: Efficient large language model serving with paged attention and continuous batching</title><link>https://ramdi.fr/github-stars/vllm-efficient-large-language-model-serving-with-paged-attention-and-continuous-batching/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/vllm-efficient-large-language-model-serving-with-paged-attention-and-continuous-batching/</guid><description>vLLM is a Python library for high-throughput LLM inference using paged attention and continuous batching. It supports quantization, distributed inference, and an OpenAI-compatible API.</description></item><item><title>TradingAgents: a multi-agent LLM framework simulating real-world trading firm dynamics</title><link>https://ramdi.fr/github-stars/tradingagents-a-multi-agent-llm-framework-simulating-real-world-trading-firm-dynamics/</link><pubDate>Sat, 02 May 2026 07:48:10 +0000</pubDate><guid>https://ramdi.fr/github-stars/tradingagents-a-multi-agent-llm-framework-simulating-real-world-trading-firm-dynamics/</guid><description>TradingAgents uses specialized LLM agents in a structured bull/bear debate to mimic real trading firms. Supports 10+ LLMs, persistent memory, and CLI/Docker usage.</description></item><item><title>Cua: A unified stack for background desktop automation agents across macOS, Linux, Windows, and Android</title><link>https://ramdi.fr/github-stars/cua-a-unified-stack-for-background-desktop-automation-agents-across-macos-linux-windows-and-android/</link><pubDate>Sun, 26 Apr 2026 23:47:28 +0000</pubDate><guid>https://ramdi.fr/github-stars/cua-a-unified-stack-for-background-desktop-automation-agents-across-macos-linux-windows-and-android/</guid><description>Cua provides a multi-component open-source stack for building and benchmarking computer-use agents that control full desktops without disrupting user focus, across macOS, Linux, Windows, and Android.</description></item><item><title>Scrapy: a modular Python framework for scalable web scraping</title><link>https://ramdi.fr/github-stars/scrapy-a-modular-python-framework-for-scalable-web-scraping/</link><pubDate>Sun, 26 Apr 2026 23:47:28 +0000</pubDate><guid>https://ramdi.fr/github-stars/scrapy-a-modular-python-framework-for-scalable-web-scraping/</guid><description>Scrapy is a Python framework designed for efficient and extensible web scraping, featuring a powerful selector system and item pipelines for data extraction and processing.</description></item><item><title>AutoGen: exploring multi-agent AI orchestration with Python in maintenance mode</title><link>https://ramdi.fr/github-stars/autogen-exploring-multi-agent-ai-orchestration-with-python-in-maintenance-mode/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/autogen-exploring-multi-agent-ai-orchestration-with-python-in-maintenance-mode/</guid><description>AutoGen is a Python framework for building multi-agent AI applications with LLM integration, now in maintenance mode with Microsoft Agent Framework as its successor. Learn its architecture, strengths, and how to get started.</description></item><item><title>AutoGPT: A modular platform for continuous AI agents and workflow automation</title><link>https://ramdi.fr/github-stars/autogpt-a-modular-platform-for-continuous-ai-agents-and-workflow-automation/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/autogpt-a-modular-platform-for-continuous-ai-agents-and-workflow-automation/</guid><description>AutoGPT is a Python-based platform for building and managing continuous AI agents that automate workflows, featuring a modular architecture, low-code agent creation, and benchmarking tools.</description></item><item><title>awesome-copilot: modular community plugins and agentic workflows for GitHub Copilot</title><link>https://ramdi.fr/github-stars/awesome-copilot-modular-community-plugins-and-agentic-workflows-for-github-copilot/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/awesome-copilot-modular-community-plugins-and-agentic-workflows-for-github-copilot/</guid><description>awesome-copilot is a community-curated collection of plugins and agents that extend GitHub Copilot with modular, agentic workflows managed through a CLI marketplace.</description></item><item><title>ComfyUI: modular visual workflows for diffusion model experimentation</title><link>https://ramdi.fr/github-stars/comfyui-modular-visual-workflows-for-diffusion-model-experimentation/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/comfyui-modular-visual-workflows-for-diffusion-model-experimentation/</guid><description>ComfyUI offers a graph/node interface for building complex diffusion model workflows offline, blending modularity with flexibility for AI practitioners.</description></item><item><title>Deep-Live-Cam: Real-time face swapping optimized across diverse hardware with ONNX Runtime</title><link>https://ramdi.fr/github-stars/deep-live-cam-real-time-face-swapping-optimized-across-diverse-hardware-with-onnx-runtime/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/deep-live-cam-real-time-face-swapping-optimized-across-diverse-hardware-with-onnx-runtime/</guid><description>Deep-Live-Cam offers real-time face swapping and deepfake video generation using ONNX Runtime with multiple execution providers for optimized performance on GPUs, CPUs, and Apple Silicon.</description></item><item><title>DeerFlow 2.0: orchestrating multi-agent AI workflows with flexible LLM integration</title><link>https://ramdi.fr/github-stars/deerflow-2-0-orchestrating-multi-agent-ai-workflows-with-flexible-llm-integration/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/deerflow-2-0-orchestrating-multi-agent-ai-workflows-with-flexible-llm-integration/</guid><description>DeerFlow 2.0 is a Python framework for orchestrating AI sub-agents and memory with support for multiple LLMs and execution sandboxes. It uses a modular config and setup wizard for flexible deployment.</description></item><item><title>Dive into Deep Learning (D2L.ai) Chinese Edition: An interactive textbook bridging theory and code</title><link>https://ramdi.fr/github-stars/dive-into-deep-learning-d2l-ai-chinese-edition-an-interactive-textbook-bridging-theory-and-code/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/dive-into-deep-learning-d2l-ai-chinese-edition-an-interactive-textbook-bridging-theory-and-code/</guid><description>Dive into Deep Learning Chinese edition offers an interactive, code-driven deep learning textbook in Python, integrating theory with runnable examples for hands-on learning.</description></item><item><title>Inside CowAgent: An extensible autonomous AI assistant with multi-modal and multi-model architecture</title><link>https://ramdi.fr/github-stars/inside-cowagent-an-extensible-autonomous-ai-assistant-with-multi-modal-and-multi-model-architecture/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-cowagent-an-extensible-autonomous-ai-assistant-with-multi-modal-and-multi-model-architecture/</guid><description>CowAgent is an extensible AI assistant framework with autonomous task planning, long-term memory, and multi-modal support. It integrates multiple LLMs and platforms for flexible AI workflows.</description></item><item><title>LLM-driven browser automation with Browser-Use: a hands-on look</title><link>https://ramdi.fr/github-stars/llm-driven-browser-automation-with-browser-use-a-hands-on-look/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/llm-driven-browser-automation-with-browser-use-a-hands-on-look/</guid><description>Browser-Use is a Python library enabling LLM-powered AI agents to automate browsers efficiently. It features a custom ChatBrowserUse model and supports cloud and local agents.</description></item><item><title>MemPalace: local-first AI memory with strong semantic retrieval and no cloud dependency</title><link>https://ramdi.fr/github-stars/mempalace-local-first-ai-memory-with-strong-semantic-retrieval-and-no-cloud-dependency/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/mempalace-local-first-ai-memory-with-strong-semantic-retrieval-and-no-cloud-dependency/</guid><description>MemPalace offers a local-first AI memory system with 96.6% recall on conversation history retrieval without any cloud or LLM calls, emphasizing privacy and efficient semantic search.</description></item><item><title>MindsDB: unified AI-powered SQL querying and data fusion for diverse sources</title><link>https://ramdi.fr/github-stars/mindsdb-unified-ai-powered-sql-querying-and-data-fusion-for-diverse-sources/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/mindsdb-unified-ai-powered-sql-querying-and-data-fusion-for-diverse-sources/</guid><description>MindsDB offers an AI-powered SQL-compatible engine that unifies structured and unstructured data across 200+ sources, enabling semantic search and conversational analytics with AI agents.</description></item><item><title>OpenHands: Modular architecture for flexible AI agent development</title><link>https://ramdi.fr/github-stars/openhands-modular-architecture-for-flexible-ai-agent-development/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/openhands-modular-architecture-for-flexible-ai-agent-development/</guid><description>OpenHands offers a modular Python platform to build and deploy AI agents with SDK, CLI, GUI, and cloud options. It supports multiple LLMs and self-hosting for enterprises.</description></item><item><title>PyTorch's dynamic neural networks and tape-based autograd: a deep dive into flexible deep learning</title><link>https://ramdi.fr/github-stars/pytorch-s-dynamic-neural-networks-and-tape-based-autograd-a-deep-dive-into-flexible-deep-learning/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/pytorch-s-dynamic-neural-networks-and-tape-based-autograd-a-deep-dive-into-flexible-deep-learning/</guid><description>Explore PyTorch&amp;rsquo;s unique tape-based autograd and dynamic neural networks architecture that enables flexible model development and efficient GPU-accelerated tensor computation.</description></item><item><title>Requests-HTML: Pythonic web scraping with built-in JavaScript rendering</title><link>https://ramdi.fr/github-stars/requests-html-pythonic-web-scraping-with-built-in-javascript-rendering/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/requests-html-pythonic-web-scraping-with-built-in-javascript-rendering/</guid><description>Requests-HTML extends Python&amp;rsquo;s Requests library with Chromium-based JavaScript rendering, CSS/XPath selectors, and async support for scraping dynamic web pages easily.</description></item><item><title>Scrapling: adaptive web scraping with AI integration for resilient data extraction</title><link>https://ramdi.fr/github-stars/scrapling-adaptive-web-scraping-with-ai-integration-for-resilient-data-extraction/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/scrapling-adaptive-web-scraping-with-ai-integration-for-resilient-data-extraction/</guid><description>Scrapling offers an adaptive web scraping framework with AI integration to handle site changes and anti-bot systems, supporting large-scale concurrent crawling with proxy rotation.</description></item><item><title>TensorFlow: a versatile platform powering machine learning from research to production</title><link>https://ramdi.fr/github-stars/tensorflow-a-versatile-platform-powering-machine-learning-from-research-to-production/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/tensorflow-a-versatile-platform-powering-machine-learning-from-research-to-production/</guid><description>TensorFlow is a comprehensive open-source machine learning platform with stable multi-language APIs and broad hardware support, evolving from research prototype to production-ready ecosystem.</description></item><item><title>Hands-on with YOLOv5: A practical deep dive into Ultralytics' PyTorch vision model</title><link>https://ramdi.fr/github-stars/hands-on-with-yolov5-a-practical-deep-dive-into-ultralytics-pytorch-vision-model/</link><pubDate>Sun, 26 Apr 2026 09:31:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/hands-on-with-yolov5-a-practical-deep-dive-into-ultralytics-pytorch-vision-model/</guid><description>YOLOv5 by Ultralytics offers an accessible, fast, and accurate PyTorch-based computer vision toolkit for object detection, segmentation, and classification. Explore its architecture, strengths, and quickstart usage.</description></item><item><title>Hugging Face Transformers: a unified API for state-of-the-art AI models across modalities</title><link>https://ramdi.fr/github-stars/hugging-face-transformers-a-unified-api-for-state-of-the-art-ai-models-across-modalities/</link><pubDate>Sun, 26 Apr 2026 09:31:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/hugging-face-transformers-a-unified-api-for-state-of-the-art-ai-models-across-modalities/</guid><description>Hugging Face Transformers offers a unified Python API to access over 1 million pretrained AI models for text, vision, and audio, simplifying complex pipelines with its Pipeline API.</description></item><item><title>Keras 3: Multi-backend deep learning framework simplifying model development across JAX, TensorFlow, and PyTorch</title><link>https://ramdi.fr/github-stars/keras-3-multi-backend-deep-learning-framework-simplifying-model-development-across-jax-tensorflow-and-pytorch/</link><pubDate>Sun, 26 Apr 2026 09:31:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/keras-3-multi-backend-deep-learning-framework-simplifying-model-development-across-jax-tensorflow-and-pytorch/</guid><description>Keras 3 introduces a multi-backend architecture supporting JAX, TensorFlow, PyTorch, and OpenVINO, enabling flexible, accelerated deep learning model development with up to 350% speedups.</description></item><item><title>OpenBB's Open Data Platform: Unified financial data integration for diverse analytics and AI</title><link>https://ramdi.fr/github-stars/openbb-s-open-data-platform-unified-financial-data-integration-for-diverse-analytics-and-ai/</link><pubDate>Sun, 26 Apr 2026 09:31:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/openbb-s-open-data-platform-unified-financial-data-integration-for-diverse-analytics-and-ai/</guid><description>OpenBB&amp;rsquo;s Open Data Platform offers a unified &amp;ldquo;connect once, consume everywhere&amp;rdquo; layer bridging financial data sources with Python, Excel, AI agents, and REST APIs for seamless analytics and AI use.</description></item><item><title>Pathway LLM App: unified pipelines for scalable retrieval-augmented generation and AI search</title><link>https://ramdi.fr/github-stars/pathway-llm-app-unified-pipelines-for-scalable-retrieval-augmented-generation-and-ai-search/</link><pubDate>Sun, 26 Apr 2026 09:31:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/pathway-llm-app-unified-pipelines-for-scalable-retrieval-augmented-generation-and-ai-search/</guid><description>Pathway LLM App provides integrated pipelines for scalable RAG and AI search, combining vector and full-text indexing with real-time sync for Gen AI apps at scale.</description></item><item><title>openai/skills: modular agent skills for reusable AI capabilities</title><link>https://ramdi.fr/github-stars/openai-skills-modular-agent-skills-for-reusable-ai-capabilities/</link><pubDate>Sat, 25 Apr 2026 07:57:59 +0000</pubDate><guid>https://ramdi.fr/github-stars/openai-skills-modular-agent-skills-for-reusable-ai-capabilities/</guid><description>The openai/skills repo offers a catalog of modular &amp;lsquo;Agent Skills&amp;rsquo; for OpenAI Codex agents, enabling reusable AI functionalities with a standardized installation system.</description></item><item><title>Awesome LLM Apps: a practical collection of runnable AI agent and RAG templates</title><link>https://ramdi.fr/github-stars/awesome-llm-apps-a-practical-collection-of-runnable-ai-agent-and-rag-templates/</link><pubDate>Fri, 24 Apr 2026 18:26:13 +0000</pubDate><guid>https://ramdi.fr/github-stars/awesome-llm-apps-a-practical-collection-of-runnable-ai-agent-and-rag-templates/</guid><description>Awesome LLM Apps offers 100+ runnable AI agent and RAG templates for quick LLM app development. It supports multiple providers and advanced multi-agent patterns with minimal setup.</description></item><item><title>Inside daily_stock_analysis: a multi-LLM automated stock analysis system</title><link>https://ramdi.fr/github-stars/inside-daily-stock-analysis-a-multi-llm-automated-stock-analysis-system/</link><pubDate>Fri, 24 Apr 2026 18:26:13 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-daily-stock-analysis-a-multi-llm-automated-stock-analysis-system/</guid><description>daily_stock_analysis combines multi-LLM integration with multi-source financial data to automate stock market decisions across global markets. It features flexible AI provider fallback and multi-channel alerts.</description></item><item><title>MLflow: unified AI engineering for LLMs and traditional machine learning</title><link>https://ramdi.fr/github-stars/mlflow-unified-ai-engineering-for-llms-and-traditional-machine-learning/</link><pubDate>Fri, 24 Apr 2026 18:26:13 +0000</pubDate><guid>https://ramdi.fr/github-stars/mlflow-unified-ai-engineering-for-llms-and-traditional-machine-learning/</guid><description>MLflow offers a unified open-source platform managing lifecycle and observability for both LLM-based AI agents and traditional ML models, with vendor neutrality and production-grade features.</description></item><item><title>Browser Harness: a self-healing LLM agent for browser automation via Chrome DevTools</title><link>https://ramdi.fr/github-stars/browser-harness-a-self-healing-llm-agent-for-browser-automation-via-chrome-devtools/</link><pubDate>Fri, 24 Apr 2026 07:26:29 +0000</pubDate><guid>https://ramdi.fr/github-stars/browser-harness-a-self-healing-llm-agent-for-browser-automation-via-chrome-devtools/</guid><description>Browser Harness enables LLMs to automate browsers by dynamically generating helper functions using the Chrome DevTools Protocol, with minimal Python code and free remote browsers.</description></item></channel></rss>