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A little curiosity. A world of open source.
THE FIRST COLLECTIONElasticsearch is a distributed, RESTful search and analytics engine and vector database. It supports full-text, vector, and hybrid search, logs, metrics, APM, security analytics, and RAG use cases. Includes quick local Docker setup, APIs, and Kibana.
A Clash-style desktop app for intelligent LLM routing that optimizes costs by maximizing prompt cache hits across multiple AI providers.
A cloud-based, passwordless facial recognition authentication system with AI-powered liveness detection, encrypted biometric storage, admin dashboard, and full Firebase integration.
LangExtract is a Python library from Google that uses LLMs to extract structured information from unstructured text, grounding every extraction to its exact source location and generating interactive HTML visualizations.
Optuna is an automatic hyperparameter optimization framework designed for machine learning, featuring a define-by-run API for dynamic search space construction.
HermesMade provides six CLI tools addressing common AI user pain points: censorship risk analysis, model quality monitoring, API cost optimization, local LLM deployment, code inspection, and task cost estimation.
Project AIRI is a self-hosted AI companion ("cyber living") inspired by Neuro-sama, supporting realtime voice chat, Live2D/VRM avatars, and game playing like Minecraft and Factorio. Runs in browser, macOS, Windows, and mobile.
LeRobot is an open-source PyTorch library for real-world robotics, offering hardware-agnostic control, standardized dataset formats, and state-of-the-art policies like SmolVLA and world models for training and deployment.
An open-source UFC fight prediction project: Elo ratings, a gradient-boosted ensemble and a multi-task neural network blended into one calibrated scorer, evaluated by expanding-window walk-forward over 2018-2026, with a Streamlit matchup explorer and a weekly self-updating data pipeline.
Wan2.2 is an open-source large-scale video generation model suite supporting text-to-video, image-to-video, speech-to-video, and character animation tasks with MoE architecture and 720P output.
Context is an MCP gateway that gives every AI client — ChatGPT, Claude, Codex, Notion AI — one endpoint to a personal knowledge base kept as plain Markdown in a Dropbox folder or S3-compatible bucket you own, with privacy tiers, workspaces and a session-end capture hook.
Open-source Finnish language resources and tools built on finite state transducers and Constraint Grammar, providing morphological analysers, spell checkers, and proofing tools for desktop and mobile platforms.
A curated list of machine learning frameworks, libraries, and software organized by programming language and topic—a useful index for researchers and developers exploring ML tools.
A lightweight deployment repository for running and managing Large Language Models using the LiteLLM unified API.
SGLang is a high-performance serving framework for large language models (LLMs) and multimodal models, designed for low-latency and high-throughput inference.
An agentic AI role-playing game framework where narration, NPCs, lore, and character creation run as composable plugin agents, with stage and text modes, portable world packs, and support for OpenAI, Anthropic, DeepSeek, and Qwen.
NVIDIA NeMo Speech is an Apache-2.0 PyTorch framework for building, customizing and deploying speech AI models, covering automatic speech recognition, text-to-speech and speech LLMs, with pre-trained checkpoints and Docker/uv install paths.
Valis is a virtual analog synthesis system that lets users build circuits using RDF/Turtle syntax, with UI views for controls, circuit diagrams, and code. It supports LLM-driven design via MCP and runs as a standalone app or DAW plugin.
AAMF is an AI-agent framework that migrates legacy codebases to other languages by deriving a deterministic task graph, running phased agents, and verifying build/test parity with resumable checkpoints.
bitnet.cpp is Microsoft's official inference framework for 1-bit and ternary (BitNet b1.58) large language models, offering optimized CPU and GPU kernels for fast, lossless inference with reduced energy use.
