Offline Private AI Library app analytics for January 26

Offline Private AI Library lets you run modern large language models completely offline on your device. Browse curated MLX-compatible Hugging Face repos, download models with pause/resume, and chat in a clean SwiftUI workspace—no accounts, no telemetry, and no internet required after install. Why offline? • Your prompts, responses, and custom prompts never leave your device. • Works in airplane mode once a model is downloaded to disk. • Perfect for sensitive research, travel, or teams with strict data policies. Download and manage MLX models • Curated Qwen, Llama, Phi, and coder variants grouped by use case, with size and language indicators. • Save your own Hugging Face repo IDs or open Hugging Face in-app to grab new ones. • Resume interrupted downloads and get reminder alerts to keep the app open during large installs. • Delete models with a single swipe to reclaim storage. Chat smarter • Markdown conversation view with headings, lists, and code blocks. • Quick suggestion starters to kick off new chats. • Share or export conversations to Markdown with timestamps. • Stop and resume streaming while a response is generating. • Copy individual replies and delete specific rows from history. • Inline status banners show when a model is loading or busy. • Optional safety disclaimer to keep expectations grounded. Tune it your way • Theme and accent color customization. • Prompt profiles for reusable system and starter prompts. • Forced language: Auto, English, or Russian. • Controls for temperature, top-p, max tokens, context window, and repetition guard. • Reset parameters back to defaults at any time. On-device processing • Powered by MLX and LocalLLMClient for local inference. • After download, all model runs stay offline—no cloud calls. • System info view shows RAM usage and entitlement status so you know which models fit your device. Offline Private AI Library is a tool for experimentation and learning. It is not a replacement for professional advice and may produce incorrect or outdated information.