IterateAI/lifeboat-releases

Lifeboat — downloads for macOS, Windows and Linux, plus Docker and Kubernetes install instructions. Run language models on your own hardware behind an OpenAI-compatible API.

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updated Sep 23, 2026

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README

Lifeboat Lifeboat

Run language models on your own hardware, behind an OpenAI-compatible API.

Download · Desktop · Docker · Kubernetes · Documentation


Lifeboat serves open-weight models on machines you control — a laptop, a workstation, a GPU server, or a cluster — and puts an OpenAI- and Anthropic-compatible API in front of them, with a load balancer, a web console and no data leaving your network.

This repository is downloads and install instructions only. The source is not public.


Download

Desktop — no Docker required

A native app with a tray icon, on all three platforms. No container runtime and no root. It serves models on whatever the machine has: Metal on Apple Silicon and Vulkan on Windows and Linux, which covers NVIDIA, AMD and Intel GPUs with one download — and the CPU otherwise.

The macOS and Windows builds are code-signed (macOS also notarized); the Linux builds are not, and ship a SHA256SUMS instead.

Desktop builds are cut per platform, so the newest version differs between them. Take the newest file for yours:

PlatformFileNotes
Windows 10/11 x64Lifeboat-2.2.51-setup.exesigned installer, no admin rights needed
macOS Apple Silicon (13+)Lifeboat-2.2.50-macos-arm64.dmgMetal + MLX
macOS Intel (13+)Lifeboat-2.2.50-macos-x86_64.dmgGGUF, no MLX
Linux Debian/Ubuntu x64lifeboat-desktop_2.2.50_amd64.debGPU offload via Vulkan
Linux Debian/Ubuntu arm64lifeboat-desktop_2.2.50_arm64.debGPU offload via Vulkan
Linux any distro, x64Lifeboat-2.2.50-linux-x86_64.tar.gzGPU offload via Vulkan
Linux any distro, arm64Lifeboat-2.2.50-linux-aarch64.tar.gzGPU offload via Vulkan

Because the platforms are cut separately, the newest build for yours may not be on the latest release — browse all releases and take the newest file bearing your platform's name.

docs/desktop.md is the full guide — requirements, GPU support, upgrading and uninstalling for each platform.

Windows

Download Lifeboat-<version>-setup.exe and double-click it. That is the whole procedure.

It installs for you rather than for the machine, so there is no administrator prompt: the app goes to %LOCALAPPDATA%\Programs\Lifeboat and your models to %LOCALAPPDATA%\Lifeboat. Start at sign-in and desktop shortcut are separate checkboxes; neither implies the other.

One prerequisite, which the installer checks for but cannot install:

winget install --id Microsoft.DotNet.DesktopRuntime.8 -e

The tray is a .NET application and does nothing without it. lifeboat-core.exe runs headless and does not need it.

The curl … | bash line in the welcome email is the Docker installer and is for Linux hosts. PowerShell has no bash, so it fails with "The term 'bash' is not recognized". On Windows, use setup.exe.

macOS

Open the .dmg, drag Lifeboat to Applications, and launch it.

The build is signed with a Developer ID, notarized by Apple and stapled, so there is no security warning and no need to right-click → Open — offline too, since the ticket travels inside the file. Lifeboat lives in the menu bar, not the Dock: there is no Dock icon and no window on launch.

Linux

Debian, Ubuntu and derivatives:

sudo apt install ./lifeboat-desktop_2.2.50_amd64.deb

Use apt install ./file.deb, not dpkg -i — the tray binding and the Vulkan loader are recommended packages and dpkg will not pull them in.

Any other distribution — the tarball unpacks to the same layout, rooted at /:

sudo tar -C / -xzf Lifeboat-2.2.50-linux-x86_64.tar.gz

Either way you get /opt/lifeboat plus two commands on PATH: lifeboat-core (the server and CLI, runs headless) and lifeboat-tray. Needs glibc 2.31+ (Debian 11+, Ubuntu 20.04+, RHEL 9+). For GPU offload install libvulkan1 and your vendor's Vulkan driver; for the tray icon on GNOME, gir1.2-ayatanaappindicator3-0.1 — without an AppIndicator it silently does not render.

lifeboat-core doctor     # what this machine can actually run, and why

Verifying a download

macOS and Windows builds are code-signed, so the OS checks them for you — that is the stronger check. Linux builds are not signed; where a release publishes a SHA256SUMS, check against it:

sha256sum -c SHA256SUMS --ignore-missing
System requirements
MinimumRecommended
macOS13 Ventura, Apple Silicon or IntelApple Silicon, 16 GB+
Windows10 build 17763 x64, .NET 8 Desktop Runtime16 GB+, any GPU with a Vulkan driver
Linuxglibc 2.31+, x64 or arm6416 GB+, libvulkan1 + vendor driver
Disk2 GB for the appplus whatever your models need

Decode speed is limited by memory bandwidth, not by core count. As a rule of thumb on a machine with 8 GB of RAM: a 1.5B–4B model at 4-bit is comfortable, 8B is the ceiling, and 14B will not fit. The app's Doctor (tray → Show Log, or lifeboat-core doctor) reports the limits for your actual machine.

NPUs and Intel XPU are not used. An "AI PC" NPU sits idle under Lifeboat: there is no inference path to it, and it shares system memory, so it would not lift the bandwidth ceiling that actually governs decode speed.

Which model format do I download?

Lifeboat picks for you and tells you why. The short version:

Your machineUse
Apple Silicon MacGGUF (default) or MLX — both run on the GPU
Windows / Linux desktopGGUF
Linux + NVIDIA/AMD server with the tensor engineSafetensors

Safetensors needs the tensor engine, which runs on Linux with CUDA or ROCm only. The desktop app will refuse a safetensors download on macOS or Windows before it starts, rather than after an hour — the model would never load.


pip — no Docker, no GPU

pip install lifeboat
lifeboat engine install
lifeboat up          # console on http://127.0.0.1:8001

The quickest way to evaluate Lifeboat: the console, model registry, load balancer and the full OpenAI-compatible API, with no container runtime and no accelerator. lifeboat serve <model> serves one model without the console, and lifeboat doctor reports what the machine can run before anything downloads.

Python 3.10–3.13, published for macOS (Apple Silicon), Linux x86-64 and ARM64, and Windows x64 — pypi.org/project/lifeboat, quickstart.

It carries the GGUF engine only, so the 2x concurrency, FP8 KV cache, speculative decoding and safetensors weights stay with the container image. Use the container on Intel Macs (no wheel is published) and on RHEL 9 and its rebuilds — Rocky, AlmaLinux, Oracle Linux — whose system C++ runtime is older than the prebuilt engine needs. Those also ship Python 3.9 as python3, below the floor; install 3.12 first.

Docker

The fastest path on a Linux GPU host. One command:

curl -sSL https://raw.githubusercontent.com/IterateAI/lifeboat-releases/main/install/get-lifeboat.sh | bash

It checks your host, picks the right image for your hardware, writes a .env, and starts the stack. Then open http://localhost:8001.

Prefer to read the script first? (Sensible — it is piped to a shell)
curl -sSLO https://raw.githubusercontent.com/IterateAI/lifeboat-releases/main/install/get-lifeboat.sh
less get-lifeboat.sh
bash get-lifeboat.sh

A copy is mirrored in this repository at install/get-lifeboat.sh so you can review it with history. The canonical copy is the one served from this repository.

Pick the right image

The tags are not interchangeable — this is the single most common mistake:

Your hardwareTagSize
NVIDIA GPUiterateai/lifeboat:latest~17 GB
AMD Instinct MI210 / MI250iterateai/lifeboat:amd~28 GB
AMD MI300X / MI325Xiterateai/lifeboat:amd-mi300x~28 GB
AMD MI350X / MI355Xiterateai/lifeboat:amd-mi355x~28 GB
No GPU, Intel/AMD integrated, or AWS Gravitoniterateai/lifeboat:lite~720 MB

:latest is the NVIDIA image and is multi-arch (amd64 + arm64). The arm64 half is built for NVIDIA arm64 parts such as Grace-Hopper and DGX Spark — on a CPU-only Graviton instance it is 17 GB of CUDA that cannot be used. Use :lite there.

An AMD customer pulling :latest gets a CUDA image that will not run on their GPU. There is no tag that serves both: a container manifest selects on CPU architecture, and both images are linux/amd64.

Manual Compose

curl -sSLO https://raw.githubusercontent.com/IterateAI/lifeboat-releases/main/install/docker-compose.yaml
curl -sSL  https://raw.githubusercontent.com/IterateAI/lifeboat-releases/main/install/.env.example -o .env
$EDITOR .env          # optional: LIFEBOAT_ADMIN_PASSWORD, else the
                      # console asks you to create the account on first visit
docker compose up -d

Copies of all three compose files are mirrored in install/, and docs/docker.md has the full detail — tags, host requirements, sizing and upgrades.

NVIDIA host requirements
  • Driver 580.65.06 or newer — the image ships the CUDA 13 runtime
  • Docker Engine 25.0+, Compose 2.21+
  • NVIDIA Container Toolkit 1.17+

get-lifeboat.sh checks all of these before downloading anything and tells you exactly which one is missing.

AMD host requirements

ROCm 6.0+, and the container needs /dev/kfd and /dev/dri plus the video and render groups. Use docker-compose.rocm.yaml, which sets all of it — including ipc: host, which ROCm requires and without which the engine dies at its first GPU allocation with an error that mentions neither.


Kubernetes

helm repo add lifeboat https://raw.githubusercontent.com/IterateAI/lifeboat-releases/main/helm
helm repo update
helm install lifeboat lifeboat/lifeboat \
  --set admin.password='<choose-one>' \
  --set gpu.vendor=nvidia            # nvidia | amd | lite

admin.password is required and the install fails without it. gpu.vendor switches the image, the device resource and the runtime class together — set it to lite for CPU-only nodes.


First run

  1. Open the console — http://localhost:8001 (Docker) or http://127.0.0.1:30800 via the tray's Open Console (desktop).
  2. Create your administrator account. Lifeboat ships with no credentials: the first visit asks you to choose an email and password, and that account is the superadmin. (If you set LIFEBOAT_ADMIN_PASSWORD in .env before the first start, the account is created from that instead and you sign in normally.)
  3. Models → Add Model, pick something that fits your machine.
  4. Servers → New Server, choose the model, press Start.
  5. Point any OpenAI-compatible client at http://localhost:8001/v1.
curl http://localhost:8001/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer <your-api-key>' \
  -d '{"model":"<your-model>","messages":[{"role":"user","content":"Hello"}]}'

The Anthropic-compatible surface is at /v1/messages, so SDKs pointed at either vendor work unchanged.


Licensing

Every install runs for 24 hours with no key, so you can evaluate before deciding anything. After that an activation key is required to start inference servers — the console and the API stay reachable either way, so you can always activate from the same page that asked you to.

  • Free tier — for non-commercial and evaluation use. No card. Up to 2 concurrent inference servers, single node.
  • Paid — monthly or yearly.
  • Air-gapped — offline licence files are available; they never contact a licence server. Install first, read the Cluster ID off the License page, and quote it when you ask — the file is bound to that one cluster.

All of it goes through iterate.ai/lifeboat — free tier, trial, purchase, upgrades and offline files. That is the only address you need.


What Lifeboat reports back

A licensed install sends a heartbeat every 6 hours: the licence key, a cluster id, a pod count, a version, and a hardware description sent once. An unlicensed install sends a smaller daily message so support can see an evaluation exists.

No model names, no prompts, no completions, no token counts. That is enforced in code, not just intended. LIFEBOAT_TELEMETRY=off disables the hardware and census reporting; an air-gapped licence sends nothing at all, ever.

The full payload, byte for byte, is documented in docs/telemetry.md.


Documentation

Desktopinstalling on Windows, macOS and Linux; GPU support; upgrades
Dockerimage tags, host requirements, sizing, upgrades
User Guideinstallation, configuration, every console page
API Referencethe full /v1/* surface, OpenAPI and Postman
Telemetryexactly what is sent, and what never is
Benchmarksthe harness and the raw results behind our published figures
Securityreporting a vulnerability, signing keys
Changelogwhat changed in each release

Support

  • Issues with a download or an install — open an issue here.
  • Anything involving your licence, your data or your account — email support@iterate.ai rather than filing a public issue.
  • Security vulnerabilities — see SECURITY.md. Please do not open a public issue for these.

Lifeboat is built by iterate.ai. Source is not public; this repository carries releases and install instructions.

Contributors

arul329

25 commits

IterateAI/lifeboat-releases

Lifeboat — downloads for macOS, Windows and Linux, plus Docker and Kubernetes install instructions. Run language models on your own hardware behind an OpenAI-compatible API.

Shell

0

25 commits

updated Sep 23, 2026

See the code

See what people are saying

README

Lifeboat Lifeboat

Run language models on your own hardware, behind an OpenAI-compatible API.

Download · Desktop · Docker · Kubernetes · Documentation


Lifeboat serves open-weight models on machines you control — a laptop, a workstation, a GPU server, or a cluster — and puts an OpenAI- and Anthropic-compatible API in front of them, with a load balancer, a web console and no data leaving your network.

This repository is downloads and install instructions only. The source is not public.


Download

Desktop — no Docker required

A native app with a tray icon, on all three platforms. No container runtime and no root. It serves models on whatever the machine has: Metal on Apple Silicon and Vulkan on Windows and Linux, which covers NVIDIA, AMD and Intel GPUs with one download — and the CPU otherwise.

The macOS and Windows builds are code-signed (macOS also notarized); the Linux builds are not, and ship a SHA256SUMS instead.

Desktop builds are cut per platform, so the newest version differs between them. Take the newest file for yours:

PlatformFileNotes
Windows 10/11 x64Lifeboat-2.2.51-setup.exesigned installer, no admin rights needed
macOS Apple Silicon (13+)Lifeboat-2.2.50-macos-arm64.dmgMetal + MLX
macOS Intel (13+)Lifeboat-2.2.50-macos-x86_64.dmgGGUF, no MLX
Linux Debian/Ubuntu x64lifeboat-desktop_2.2.50_amd64.debGPU offload via Vulkan
Linux Debian/Ubuntu arm64lifeboat-desktop_2.2.50_arm64.debGPU offload via Vulkan
Linux any distro, x64Lifeboat-2.2.50-linux-x86_64.tar.gzGPU offload via Vulkan
Linux any distro, arm64Lifeboat-2.2.50-linux-aarch64.tar.gzGPU offload via Vulkan

Because the platforms are cut separately, the newest build for yours may not be on the latest release — browse all releases and take the newest file bearing your platform's name.

docs/desktop.md is the full guide — requirements, GPU support, upgrading and uninstalling for each platform.

Windows

Download Lifeboat-<version>-setup.exe and double-click it. That is the whole procedure.

It installs for you rather than for the machine, so there is no administrator prompt: the app goes to %LOCALAPPDATA%\Programs\Lifeboat and your models to %LOCALAPPDATA%\Lifeboat. Start at sign-in and desktop shortcut are separate checkboxes; neither implies the other.

One prerequisite, which the installer checks for but cannot install:

winget install --id Microsoft.DotNet.DesktopRuntime.8 -e

The tray is a .NET application and does nothing without it. lifeboat-core.exe runs headless and does not need it.

The curl … | bash line in the welcome email is the Docker installer and is for Linux hosts. PowerShell has no bash, so it fails with "The term 'bash' is not recognized". On Windows, use setup.exe.

macOS

Open the .dmg, drag Lifeboat to Applications, and launch it.

The build is signed with a Developer ID, notarized by Apple and stapled, so there is no security warning and no need to right-click → Open — offline too, since the ticket travels inside the file. Lifeboat lives in the menu bar, not the Dock: there is no Dock icon and no window on launch.

Linux

Debian, Ubuntu and derivatives:

sudo apt install ./lifeboat-desktop_2.2.50_amd64.deb

Use apt install ./file.deb, not dpkg -i — the tray binding and the Vulkan loader are recommended packages and dpkg will not pull them in.

Any other distribution — the tarball unpacks to the same layout, rooted at /:

sudo tar -C / -xzf Lifeboat-2.2.50-linux-x86_64.tar.gz

Either way you get /opt/lifeboat plus two commands on PATH: lifeboat-core (the server and CLI, runs headless) and lifeboat-tray. Needs glibc 2.31+ (Debian 11+, Ubuntu 20.04+, RHEL 9+). For GPU offload install libvulkan1 and your vendor's Vulkan driver; for the tray icon on GNOME, gir1.2-ayatanaappindicator3-0.1 — without an AppIndicator it silently does not render.

lifeboat-core doctor     # what this machine can actually run, and why

Verifying a download

macOS and Windows builds are code-signed, so the OS checks them for you — that is the stronger check. Linux builds are not signed; where a release publishes a SHA256SUMS, check against it:

sha256sum -c SHA256SUMS --ignore-missing
System requirements
MinimumRecommended
macOS13 Ventura, Apple Silicon or IntelApple Silicon, 16 GB+
Windows10 build 17763 x64, .NET 8 Desktop Runtime16 GB+, any GPU with a Vulkan driver
Linuxglibc 2.31+, x64 or arm6416 GB+, libvulkan1 + vendor driver
Disk2 GB for the appplus whatever your models need

Decode speed is limited by memory bandwidth, not by core count. As a rule of thumb on a machine with 8 GB of RAM: a 1.5B–4B model at 4-bit is comfortable, 8B is the ceiling, and 14B will not fit. The app's Doctor (tray → Show Log, or lifeboat-core doctor) reports the limits for your actual machine.

NPUs and Intel XPU are not used. An "AI PC" NPU sits idle under Lifeboat: there is no inference path to it, and it shares system memory, so it would not lift the bandwidth ceiling that actually governs decode speed.

Which model format do I download?

Lifeboat picks for you and tells you why. The short version:

Your machineUse
Apple Silicon MacGGUF (default) or MLX — both run on the GPU
Windows / Linux desktopGGUF
Linux + NVIDIA/AMD server with the tensor engineSafetensors

Safetensors needs the tensor engine, which runs on Linux with CUDA or ROCm only. The desktop app will refuse a safetensors download on macOS or Windows before it starts, rather than after an hour — the model would never load.


pip — no Docker, no GPU

pip install lifeboat
lifeboat engine install
lifeboat up          # console on http://127.0.0.1:8001

The quickest way to evaluate Lifeboat: the console, model registry, load balancer and the full OpenAI-compatible API, with no container runtime and no accelerator. lifeboat serve <model> serves one model without the console, and lifeboat doctor reports what the machine can run before anything downloads.

Python 3.10–3.13, published for macOS (Apple Silicon), Linux x86-64 and ARM64, and Windows x64 — pypi.org/project/lifeboat, quickstart.

It carries the GGUF engine only, so the 2x concurrency, FP8 KV cache, speculative decoding and safetensors weights stay with the container image. Use the container on Intel Macs (no wheel is published) and on RHEL 9 and its rebuilds — Rocky, AlmaLinux, Oracle Linux — whose system C++ runtime is older than the prebuilt engine needs. Those also ship Python 3.9 as python3, below the floor; install 3.12 first.

Docker

The fastest path on a Linux GPU host. One command:

curl -sSL https://raw.githubusercontent.com/IterateAI/lifeboat-releases/main/install/get-lifeboat.sh | bash

It checks your host, picks the right image for your hardware, writes a .env, and starts the stack. Then open http://localhost:8001.

Prefer to read the script first? (Sensible — it is piped to a shell)
curl -sSLO https://raw.githubusercontent.com/IterateAI/lifeboat-releases/main/install/get-lifeboat.sh
less get-lifeboat.sh
bash get-lifeboat.sh

A copy is mirrored in this repository at install/get-lifeboat.sh so you can review it with history. The canonical copy is the one served from this repository.

Pick the right image

The tags are not interchangeable — this is the single most common mistake:

Your hardwareTagSize
NVIDIA GPUiterateai/lifeboat:latest~17 GB
AMD Instinct MI210 / MI250iterateai/lifeboat:amd~28 GB
AMD MI300X / MI325Xiterateai/lifeboat:amd-mi300x~28 GB
AMD MI350X / MI355Xiterateai/lifeboat:amd-mi355x~28 GB
No GPU, Intel/AMD integrated, or AWS Gravitoniterateai/lifeboat:lite~720 MB

:latest is the NVIDIA image and is multi-arch (amd64 + arm64). The arm64 half is built for NVIDIA arm64 parts such as Grace-Hopper and DGX Spark — on a CPU-only Graviton instance it is 17 GB of CUDA that cannot be used. Use :lite there.

An AMD customer pulling :latest gets a CUDA image that will not run on their GPU. There is no tag that serves both: a container manifest selects on CPU architecture, and both images are linux/amd64.

Manual Compose

curl -sSLO https://raw.githubusercontent.com/IterateAI/lifeboat-releases/main/install/docker-compose.yaml
curl -sSL  https://raw.githubusercontent.com/IterateAI/lifeboat-releases/main/install/.env.example -o .env
$EDITOR .env          # optional: LIFEBOAT_ADMIN_PASSWORD, else the
                      # console asks you to create the account on first visit
docker compose up -d

Copies of all three compose files are mirrored in install/, and docs/docker.md has the full detail — tags, host requirements, sizing and upgrades.

NVIDIA host requirements
  • Driver 580.65.06 or newer — the image ships the CUDA 13 runtime
  • Docker Engine 25.0+, Compose 2.21+
  • NVIDIA Container Toolkit 1.17+

get-lifeboat.sh checks all of these before downloading anything and tells you exactly which one is missing.

AMD host requirements

ROCm 6.0+, and the container needs /dev/kfd and /dev/dri plus the video and render groups. Use docker-compose.rocm.yaml, which sets all of it — including ipc: host, which ROCm requires and without which the engine dies at its first GPU allocation with an error that mentions neither.


Kubernetes

helm repo add lifeboat https://raw.githubusercontent.com/IterateAI/lifeboat-releases/main/helm
helm repo update
helm install lifeboat lifeboat/lifeboat \
  --set admin.password='<choose-one>' \
  --set gpu.vendor=nvidia            # nvidia | amd | lite

admin.password is required and the install fails without it. gpu.vendor switches the image, the device resource and the runtime class together — set it to lite for CPU-only nodes.


First run

  1. Open the console — http://localhost:8001 (Docker) or http://127.0.0.1:30800 via the tray's Open Console (desktop).
  2. Create your administrator account. Lifeboat ships with no credentials: the first visit asks you to choose an email and password, and that account is the superadmin. (If you set LIFEBOAT_ADMIN_PASSWORD in .env before the first start, the account is created from that instead and you sign in normally.)
  3. Models → Add Model, pick something that fits your machine.
  4. Servers → New Server, choose the model, press Start.
  5. Point any OpenAI-compatible client at http://localhost:8001/v1.
curl http://localhost:8001/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer <your-api-key>' \
  -d '{"model":"<your-model>","messages":[{"role":"user","content":"Hello"}]}'

The Anthropic-compatible surface is at /v1/messages, so SDKs pointed at either vendor work unchanged.


Licensing

Every install runs for 24 hours with no key, so you can evaluate before deciding anything. After that an activation key is required to start inference servers — the console and the API stay reachable either way, so you can always activate from the same page that asked you to.

  • Free tier — for non-commercial and evaluation use. No card. Up to 2 concurrent inference servers, single node.
  • Paid — monthly or yearly.
  • Air-gapped — offline licence files are available; they never contact a licence server. Install first, read the Cluster ID off the License page, and quote it when you ask — the file is bound to that one cluster.

All of it goes through iterate.ai/lifeboat — free tier, trial, purchase, upgrades and offline files. That is the only address you need.


What Lifeboat reports back

A licensed install sends a heartbeat every 6 hours: the licence key, a cluster id, a pod count, a version, and a hardware description sent once. An unlicensed install sends a smaller daily message so support can see an evaluation exists.

No model names, no prompts, no completions, no token counts. That is enforced in code, not just intended. LIFEBOAT_TELEMETRY=off disables the hardware and census reporting; an air-gapped licence sends nothing at all, ever.

The full payload, byte for byte, is documented in docs/telemetry.md.


Documentation

Desktopinstalling on Windows, macOS and Linux; GPU support; upgrades
Dockerimage tags, host requirements, sizing, upgrades
User Guideinstallation, configuration, every console page
API Referencethe full /v1/* surface, OpenAPI and Postman
Telemetryexactly what is sent, and what never is
Benchmarksthe harness and the raw results behind our published figures
Securityreporting a vulnerability, signing keys
Changelogwhat changed in each release

Support

  • Issues with a download or an install — open an issue here.
  • Anything involving your licence, your data or your account — email support@iterate.ai rather than filing a public issue.
  • Security vulnerabilities — see SECURITY.md. Please do not open a public issue for these.

Lifeboat is built by iterate.ai. Source is not public; this repository carries releases and install instructions.

Contributors

arul329

25 commits

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