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@Matlan1 Matlan1 released this 04 Jul 17:03
· 2466 commits to master since this release
v0.1.0
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Learn about vigilant mode.

0.1.0 - 2026-07-04

First tagged release. A self-contained, offline local-LLM platform.

Added

  • Inference: run GGUF models via a bundled llama.cpp runtime, and HuggingFace
    models via a torch backend. GPU acceleration on AMD (ROCm), NVIDIA (CUDA or
    Vulkan), and Intel/Vulkan, with automatic hardware detection and a CPU fallback.
    Auto context-window sizing from free VRAM.
  • CLI: pull/search/add/list/rm for models, run (interactive or
    single-prompt, with image input), serve (OpenAI-compatible API), gui,
    doctor, benchmark, config, info, and shell completion.
  • GUI: an installable PWA served by the local server - chat with conversation
    history, assistant memory, and personas; the coder agent; model management; and
    per-plugin pages. Loopback by default; an optional network bind for phone access.
  • Coder agent: an offline AI coding agent with file, shell, search, and test
    tools, a project map, an agentic loop, and MCP interop, gated behind an explicit
    scope.
  • Plugins (everything but chat is a plugin): image / music / video generation
    (ComfyUI backends), a knowledge base for retrieval-augmented chat (RAG), a job
    scheduler, an MCP server, text-to-speech, speech-to-text, and web search/fetch.
  • Security: loopback-only by default; a network bind forces a strong API key
    and enables built-in TLS. Scoped API keys, an owner/admin model, HttpOnly session
    cookies with CSRF protection, path confinement, and an SSRF-guarded outbound
    fetch policy.
  • Privacy: an opt-in privacy mode that keeps sessions in memory and writes no
    traces to disk; a configurable network policy (off / ask / allow, allow/deny
    lists).
  • Networking: reach a network-bound instance by name over mDNS (localm.local)
    and Tailscale MagicDNS, folded into the TLS certificate.
  • Model tools: HuggingFace search and local model registration.

Known limitations

  • Media generation (image / music / video) requires a local ComfyUI backend; RAG's
    semantic mode requires the on-device embedding model (localm setup-embeddings).
  • The in-app bug-report upload and the self-updater require the maintainer's
    Cloudflare Worker to be deployed; until then those two features are inert.
  • The NVIDIA GPU path is validated by design and CI-adjacent testing; the primary
    development hardware is AMD.
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