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24 Commits

Author SHA1 Message Date
Evan
1f28b22bf7 aaa 2026-01-16 14:20:34 +00:00
Evan Quiney
39ee2bf7bd switch from synchronous threaded pinging to an async implementation (#1170)
still seeing churn in our networking - lets properly rate limit it

## changes

added an httpx client with max connections with a persistent AsyncClient

## testing

deployed on cluster, discovery VASTLY more stable (the only deleted
edges were those discovered by mdns)
2026-01-16 13:20:03 +00:00
Sami Khan
991adfbd6f fix local network warning (#1136)
## Motivation

Local network warning banner was showing on fresh install even though
mDNS was working. The check would fail before the user had a chance to
grant permission via the macOS prompt.

## Changes

- Added `hasWorkedBefore` flag persisted in UserDefaults
- Only show warning if permission previously worked but now doesn't

## Why It Works

On fresh install, the check may fail (no permission yet), but
`hasWorkedBefore` is false so no warning shows. Once the user grants
permission and a check succeeds, we record it. Future failures (zombie
permission after restart) will show the warning since `hasWorkedBefore`
is now true.

## Test Plan

### Manual Testing
Run locally

### Automated Testing
N/A
2026-01-16 13:10:50 +00:00
rltakashige
4b3de6b984 Fix exo bench for transformers 5.x (#1168)
## Motivation
Prompt Sizer was broken as transformers 5.x tokenizers create
BatchEncodings which are essentially a dictionary of {input_ids: []}
instead of the list of input ids.

## Test Plan

### Manual Testing
Tested that exo bench runs as expected.

### Automated Testing
<!-- Describe changes to automated tests, or how existing tests cover
this change -->
<!-- - -->
2026-01-16 12:39:22 +00:00
Evan
c8de3b90ea quiet rust logs
rust logs were too verbose - now only warnings propagate to python

entirely happy not to merge this and to clean up rust logging instead,
but this felt saner right now
2026-01-16 12:34:28 +00:00
Sami Khan
6e6567a802 resolve issue #1070 (#1076)
## Motivation

https://github.com/exo-explore/exo/issues/1070

## Changes

Added check in ChatForm.svelte to reset selectedChatModel when it no
longer matches any running instance.

## Why It Works

The $effect now detects when the selected model is stale (not in
availableModels()) and resets to the first available model.

## Test Plan

### Manual Testing

1. Create instance of Model A → Delete it → Create instance of Model B →
Chat
2. Verify request goes to Model B (not Model A)

---------

Co-authored-by: Alex Cheema <41707476+AlexCheema@users.noreply.github.com>
2026-01-15 20:00:41 +00:00
rltakashige
a735dad667 Parse GPT OSS in runner (#1160)
## Motivation

Simplification of API + moving model specific code to the runner

<!-- Why is this change needed? What problem does it solve? -->
<!-- If it fixes an open issue, please link to the issue here -->

## Test Plan

### Manual Testing
Tested that GPT OSS outputs are parsed correctly on the dashboard.

### Automated Testing
<!-- Describe changes to automated tests, or how existing tests cover
this change -->
<!-- - -->
2026-01-15 19:53:55 +00:00
rltakashige
aaf4e36bc3 FIX GPT OSS (#1165)
## Motivation

Adds several unmerged fixes for GPT OSS.
Also adds GPT OSS 20B MXFP4 Q8 instead of Q4 for numerical stability (as
this is unstable for MLX LM too)
<!-- Why is this change needed? What problem does it solve? -->
<!-- If it fixes an open issue, please link to the issue here -->


## Test Plan

### Manual Testing
Manually tested. No further gibberish responses.

### Automated Testing
Ran EXO Bench - pipeline, tensor and single node work on both 20B and
120B models
2026-01-15 19:20:17 +00:00
Evan Quiney
3e623ccf0d up http timeout to 3 seconds and retry on BadStatusLine (#1164)
we're seeing a lot of network churn - perhaps this is a connection
timing out issue? lets also re-try after a second

## testing
none yet

---------

Co-authored-by: Alex Cheema <alexcheema123@gmail.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-15 18:15:12 +00:00
Evan Quiney
c22dad8a7d dashboard: add peer: true to package lock (#1162)
this happens every time i run npm install - lets upstream it

## testing
dashboard builds and renders
2026-01-15 17:01:43 +00:00
Evan
4bc4d50685 rust: remove dead code
the system custodian has been made unnecessary with the swift app - we
can remove it

## testing
everything still builds
2026-01-15 16:51:46 +00:00
Jake Hillion
e0aab46fd8 model_cards.py: clean up commented out code
Clean up the commented out code and make sure the comments are unified.
Carrying around the commented out code means people making changes to
model_cards are supposed to update it, but that's not clear and won't be
picked up by type checking etc. Drop it for now - it's in the git
history.

Also make the rest of the comments a bit more uniform, and place
comments about a specific model card inside the model card (instead of
above) so they don't get lost when code is added/moved around.

Test plan:
- my eyes
2026-01-15 13:21:58 +00:00
Evan Quiney
82ba42bae9 add glm-47, minimax-m21 (#1147)
Adds support glm 4.7 and MiniMax M2.1

Manual testing:
Tensor + Pipeline execution of both models.

Closes #1141 and #1142
2026-01-14 16:33:17 +00:00
Jake Hillion
3671528fa4 nix: add dashboard build with dream2nix
Continue working towards a fully Nix based build by building the
dashboard with Nix. Continuing the theme of using the existing lock
files, use dream2nix to parse the lock file and build the tree of
dependency derivations.

dream2nix doesn't like the bundleDependencies, so we apply a small patch
to the lock file that drops all dependencies that are bundled. This
should ideally be contributed upstream but that can be done later.

Use this new dashboard build in the build-app CI workflow, meaning
future macOS apps will include this reproducible dashboard.

Test plan:
- Built a DMG, shipped to a cluster, loaded in a browser with no cache
  and the dashboard looks good.

- Directory layout is as expected:
```
$ nix build .#dashboard
$ find result/
...
result/_app/immutable/entry
result/_app/immutable/entry/app.CTPAnMjf.js
result/_app/immutable/entry/start.fUSEa-2O.js
result/_app/immutable/nodes
result/_app/immutable/nodes/3.DqQr1Obm.js
result/_app/immutable/nodes/0.DgEY44RO.js
result/_app/immutable/nodes/2.BjZg_lJh.js
result/_app/immutable/nodes/1.D6vGUYYT.js
result/_app/env.js
result/_app/version.json
result/exo-logo.png
result/favicon.ico
result/index.html
```
2026-01-14 15:58:16 +01:00
Jake Hillion
e6434ec446 nix: add Rust builds with crane and fenix
The Rust workspace lacked Nix build support, making it difficult to
build packages reproducibly or run checks in CI.

Added a flake-parts module at rust/parts.nix that uses crane for Rust
builds and fenix for the nightly toolchain. The source filter isolates
rust/ and root Cargo files to prevent Python/docs changes from
triggering Rust rebuilds. Exports packages (system_custodian,
exo_pyo3_bindings wheel, exo-rust-workspace) and checks (cargo-nextest,
cargo-doc) for all three target platforms.

The devShell now uses inputsFrom to inherit build dependencies from the
workspace package, removing the need for manual pkg-config/openssl setup.

Test plan:
- Ran `nix flake check` successfully
- Built `nix build ".#checks.x86_64-linux.cargo-nextest"` and tests pass
- Built `nix build ".#exo_pyo3_bindings"` and wheel is produced
2026-01-14 11:52:29 +00:00
Jake Hillion
bdb43e1dbb nix: drop noisy echos from devshell
Drop all the printing when entering a devshell. It's annoying, and not a
super accurate description of how to develop exo anyway.
2026-01-14 10:04:57 +00:00
Jake Hillion
e4a01e2b0e chore(deps): nix lock file maintenance
Update nix flake inputs. Add a second input as Swift is currently broken
in nixpkgs on Linux for `swift-format` as we want `nix fmt` to continue
being reproducible everywhere.
2026-01-13 19:57:14 +01:00
Evan Quiney
1200a7db64 Add tensor sharding for GPT-OSS (#1144)
## Motivation

GPT OSS did not previously support tensor sharding

## Changes

Add GPT sharding support in tensor_auto_parallel.
Code is mostly @rltakashige's

## Test Plan

### Manual Testing
Tested GPT-OSS - MLX Fast Sync causes issues in Tensor RDMA - this is a general problem at the moment.
2026-01-13 17:25:52 +00:00
Evan Quiney
47ceb54bc1 up the rlimit (#1148)
Fixes #1117 

Manual testing:
Launched 100 instances. worked. yay.
2026-01-13 15:00:54 +00:00
Jake Hillion
f8112fdf25 nix: convert to flake-parts
Preparing to add a flake-parts module for Rust builds. The flake-utils
library doesn't support the module system needed for cleanly separating
the Rust build configuration.

Converted from flake-utils to flake-parts, switching to the treefmt-nix
flakeModule import pattern. The devShell and formatter outputs remain
functionally equivalent.

Test plan:
- Ran `nix flake check` successfully
- Verified `nix develop` provides the same environment
2026-01-13 15:06:44 +01:00
Alex Cheema
e388f59480 docs: add AGENTS.md for AI coding agents guidance (#1132)
## Motivation

Add documentation to help AI coding agents (Claude Code, Cursor, GitHub
Copilot, etc.) understand the exo codebase and contribute effectively.

## Changes

- Add `AGENTS.md` with guidance for AI agents working on the codebase
- Add symlink `CLAUDE.md -> AGENTS.md` for backwards compatibility with
Claude Code

## Why It Works

`AGENTS.md` is becoming a standard convention for AI agent instructions.
The symlink ensures Claude Code (which looks for `CLAUDE.md`) continues
to work while supporting the broader `AGENTS.md` convention.

## Test Plan

### Manual Testing
- Verified symlink works correctly

### Automated Testing
- N/A (documentation only)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-13 13:05:47 +00:00
Alex Cheema
e5e74e1eef Upgrade mlx-lm to 0.30.2 with transformers 5.x compatibility (#1125)
## Motivation

Upgrade mlx-lm to version 0.30.2 which requires transformers 5.0.0rc2 as
a prerelease dependency. This enables support for newer models like Kimi
K2 Thinking while maintaining compatibility with existing models.

The transformers 5.x release includes breaking changes that affect
custom tokenizers like Kimi's TikTokenTokenizer, requiring compatibility
fixes.

## Changes

### Core Changes
- **mlx-lm upgrade**: Bump to 0.30.2 with locked exact versions for
mlx/mlx-lm to prevent breaking changes
- **transformers 5.x compatibility**: Enable prerelease transformers
dependency

### Kimi K2 Tokenizer Fixes
- Add `bytes_to_unicode` monkey-patch to restore function moved in
transformers 5.0.0rc2
- Load `TikTokenTokenizer` directly instead of via `AutoTokenizer` to
bypass transformers 5.x bug with `auto_map` fallback
- Patch `encode()` to use tiktoken directly with `allowed_special="all"`
to handle special tokens from chat templates

### Other Changes
- Dashboard: Show disk usage for completed model downloads
- CI: Add `workflow_dispatch` trigger to build-app workflow
- Docs: Add basic API documentation

### Testing
- Add comprehensive tokenizer unit tests for all supported models
- Tests verify encode/decode, special token handling, and chat template
encoding

## Why It Works

**bytes_to_unicode issue**: transformers 5.0.0rc2 moved
`bytes_to_unicode` from `transformers.models.gpt2.tokenization_gpt2` to
`transformers.convert_slow_tokenizer`. Kimi's `tokenization_kimi.py`
imports from the old location. The monkey-patch restores it at module
load time.

**AutoTokenizer issue**: transformers 5.x has a bug where
`tokenizer_class_from_name('TikTokenTokenizer')` returns `None` for
custom tokenizers with `auto_map`. Loading the tokenizer directly
bypasses this.

**encode() issue**: transformers 5.x's `pad()` method fails for slow
tokenizers. Using tiktoken's encode directly with
`allowed_special="all"` avoids this path and properly handles special
tokens like `<|im_user|>` from chat templates.

## Test Plan

### Manual Testing
- Hardware: 2x Mac Studios connected via Thunderbolt 5 (mike22 and
james21)
- Tested Kimi K2 Thinking, GPT-OSS-120B, GPT-OSS-20B, LLama-3.1-8B-bf16, qwen3-30B-A3B-8bit model with pipeline parallelism across both
nodes
- Verified warmup inference completes successfully
- Verified chat completions work with special tokens

### Automated Testing
- Added `test_tokenizers.py` with 31 tests covering:
- Basic encode/decode for all model families (deepseek, kimi, llama,
qwen, gpt-oss, glm)
  - Special token encoding (critical for chat templates)
  - Chat template application and encoding
  - Kimi-specific and GLM-specific edge cases
- All tests pass: `uv run pytest
src/exo/worker/tests/unittests/test_mlx/test_tokenizers.py`

### Failing Tests
RDMA with all models.

---------

Co-authored-by: Evan <evanev7@gmail.com>
2026-01-13 12:06:04 +00:00
Jake Hillion
b968d6f0a0 ci: remove old commented out job 2026-01-13 12:42:04 +01:00
Jake Hillion
3bfffd9b4f ci: build all Nix outputs on all platforms and push to cachix
The CI was only running `nix flake check` on ubuntu-latest, missing
builds for other platforms and not caching packages or devShells.

Added a matrix-based `nix-build` job that runs on macos-26 (aarch64-darwin),
ubuntu-latest (x86_64-linux), and ubuntu-24.04-arm (aarch64-linux). Each
job enumerates all packages and devShells via `nix flake show --json`,
builds them in a single `nix build` call for parallelization, then runs
`nix flake check`. The cachix-action pushes all built outputs automatically.

This ensures all Nix outputs are built and cached for every supported
platform, speeding up local development and CI runs.

Test plan:
- Tested jq enumeration command locally, correctly outputs devShell paths
- Verified xargs pipeline works with the enumerated outputs
2026-01-13 12:37:12 +01:00
34 changed files with 1668 additions and 1898 deletions

View File

@@ -113,11 +113,22 @@ jobs:
uv python install
uv sync --locked
- name: Install Nix
uses: cachix/install-nix-action@v31
with:
nix_path: nixpkgs=channel:nixos-unstable
- name: Configure Cachix
uses: cachix/cachix-action@v14
with:
name: exo
authToken: "${{ secrets.CACHIX_AUTH_TOKEN }}"
- name: Build dashboard
run: |
cd dashboard
npm ci
npm run build
DASHBOARD_OUT=$(nix build .#dashboard --print-build-logs --no-link --print-out-paths)
mkdir -p dashboard/build
cp -r "$DASHBOARD_OUT"/* dashboard/build/
- name: Install Sparkle CLI
run: |

View File

@@ -94,9 +94,19 @@ jobs:
- uses: ./.github/actions/typecheck
nix-flake-check:
name: Check Nix flake
runs-on: ubuntu-latest
nix:
name: Build and check (${{ matrix.system }})
runs-on: ${{ matrix.runner }}
strategy:
fail-fast: false
matrix:
include:
- runner: macos-26
system: aarch64-darwin
- runner: ubuntu-latest
system: x86_64-linux
- runner: ubuntu-24.04-arm
system: aarch64-linux
steps:
- name: Checkout repository
uses: actions/checkout@v4
@@ -113,83 +123,14 @@ jobs:
name: exo
authToken: "${{ secrets.CACHIX_AUTH_TOKEN }}"
- name: Run nix flake check
- name: Build all Nix outputs
run: |
nix flake check
shell: bash
nix flake show --json | jq -r '
[
(.packages."${{ matrix.system }}" // {} | keys[] | ".#packages.${{ matrix.system }}.\(.)"),
(.devShells."${{ matrix.system }}" // {} | keys[] | ".#devShells.${{ matrix.system }}.\(.)")
] | .[]
' | xargs nix build
# ci:
# needs: typecheck
# runs-on: ubuntu-latest
# permissions:
# contents: read
# env:
# GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# steps:
# - name: Checkout repository
# uses: actions/checkout@v4
# with:
# fetch-depth: 0
# token: ${{ secrets.GITHUB_TOKEN }}
# lfs: true
#
# - name: Configure git user
# run: |
# git config --local user.email "github-actions@users.noreply.github.com"
# git config --local user.name "github-actions bot"
# shell: bash
#
# - name: Pull LFS files
# run: |
# echo "Pulling Git LFS files..."
# git lfs pull
# shell: bash
#
# - name: Setup EXO_HOME and API_PORT
# run: |
# EXO_HOME=$(mktemp -d -t exo-ci-XXXXXXXX)
# # Generate random port (macOS compatible method)
# API_PORT=$((49152 + RANDOM % (65535 - 49152 + 1)))
# echo "EXO_HOME=$EXO_HOME" >> $GITHUB_ENV
# echo "API_PORT=$API_PORT" >> $GITHUB_ENV
# echo "Created EXO_HOME: $EXO_HOME"
# echo "Generated API_PORT: $API_PORT"
# shell: bash
#
# - name: Setup Nix Environment
# run: |
# echo "Checking for nix installation..."
#
# # Check if nix binary exists directly
# if [ -f /nix/var/nix/profiles/default/bin/nix ]; then
# echo "Found nix binary at /nix/var/nix/profiles/default/bin/nix"
# export PATH="/nix/var/nix/profiles/default/bin:$PATH"
# echo "PATH=$PATH" >> $GITHUB_ENV
# nix --version
# elif [ -f /nix/var/nix/profiles/default/etc/profile.d/nix-daemon.sh ]; then
# echo "Found nix profile script, sourcing..."
# source /nix/var/nix/profiles/default/etc/profile.d/nix-daemon.sh
# nix --version
# elif command -v nix >/dev/null 2>&1; then
# echo "Nix already in PATH"
# nix --version
# else
# echo "Nix not found. Debugging info:"
# echo "Contents of /nix/var/nix/profiles/default/:"
# ls -la /nix/var/nix/profiles/default/ 2>/dev/null || echo "Directory not found"
# echo "Contents of /nix/var/nix/profiles/default/bin/:"
# ls -la /nix/var/nix/profiles/default/bin/ 2>/dev/null || echo "Directory not found"
# exit 1
# fi
# shell: bash
#
# - uses: ./.github/actions/lint-check
#
# - uses: ./.github/actions/unit-test
#
# - name: Cleanup EXO_HOME
# run: |
# echo "Cleaning up EXO_HOME: $EXO_HOME"
# rm -rf "$EXO_HOME"
# shell: bash
# if: always()
- name: Run nix flake check
run: nix flake check

96
AGENTS.md Normal file
View File

@@ -0,0 +1,96 @@
# AGENTS.md
This file provides guidance to AI coding agents when working with code in this repository.
## Project Overview
exo is a distributed AI inference system that connects multiple devices into a cluster. It enables running large language models across multiple machines using MLX as the inference backend and libp2p for peer-to-peer networking.
## Build & Run Commands
```bash
# Build the dashboard (required before running exo)
cd dashboard && npm install && npm run build && cd ..
# Run exo (starts both master and worker with API at http://localhost:52415)
uv run exo
# Run with verbose logging
uv run exo -v # or -vv for more verbose
# Run tests (excludes slow tests by default)
uv run pytest
# Run all tests including slow tests
uv run pytest -m ""
# Run a specific test file
uv run pytest src/exo/shared/tests/test_election.py
# Run a specific test function
uv run pytest src/exo/shared/tests/test_election.py::test_function_name
# Type checking (strict mode)
uv run basedpyright
# Linting
uv run ruff check
# Format code (using nix)
nix fmt
```
## Architecture
### Node Composition
A single exo `Node` (src/exo/main.py) runs multiple components:
- **Router**: libp2p-based pub/sub messaging via Rust bindings (exo_pyo3_bindings)
- **Worker**: Handles inference tasks, downloads models, manages runner processes
- **Master**: Coordinates cluster state, places model instances across nodes
- **Election**: Bully algorithm for master election
- **API**: FastAPI server for OpenAI-compatible chat completions
### Message Flow
Components communicate via typed pub/sub topics (src/exo/routing/topics.py):
- `GLOBAL_EVENTS`: Master broadcasts indexed events to all workers
- `LOCAL_EVENTS`: Workers send events to master for indexing
- `COMMANDS`: Workers/API send commands to master
- `ELECTION_MESSAGES`: Election protocol messages
- `CONNECTION_MESSAGES`: libp2p connection updates
### Event Sourcing
The system uses event sourcing for state management:
- `State` (src/exo/shared/types/state.py): Immutable state object
- `apply()` (src/exo/shared/apply.py): Pure function that applies events to state
- Master indexes events and broadcasts; workers apply indexed events
### Key Type Hierarchy
- `src/exo/shared/types/`: Pydantic models for all shared types
- `events.py`: Event types (discriminated union)
- `commands.py`: Command types
- `tasks.py`: Task types for worker execution
- `state.py`: Cluster state model
### Rust Components
Rust code in `rust/` provides:
- `networking`: libp2p networking (gossipsub, peer discovery)
- `exo_pyo3_bindings`: PyO3 bindings exposing Rust to Python
- `system_custodian`: System-level operations
### Dashboard
Svelte 5 + TypeScript frontend in `dashboard/`. Build output goes to `dashboard/build/` and is served by the API.
## Code Style Requirements
From .cursorrules:
- Strict, exhaustive typing - never bypass the type-checker
- Use `Literal[...]` for enum-like sets, `typing.NewType` for primitives
- Pydantic models with `frozen=True` and `strict=True`
- Pure functions with injectable effect handlers for side-effects
- Descriptive names - no abbreviations or 3-letter acronyms
- Catch exceptions only where you can handle them meaningfully
- Use `@final` and immutability wherever applicable
## Testing
Tests use pytest-asyncio with `asyncio_mode = "auto"`. Tests are in `tests/` subdirectories alongside the code they test. The `EXO_TESTS=1` env var is set during tests.

1
CLAUDE.md Symbolic link
View File

@@ -0,0 +1 @@
AGENTS.md

19
Cargo.lock generated
View File

@@ -4340,25 +4340,6 @@ dependencies = [
"libc",
]
[[package]]
name = "system_custodian"
version = "0.0.1"
dependencies = [
"delegate",
"derive_more",
"either",
"extend",
"futures",
"futures-timer",
"impl-trait-for-tuples",
"keccak-const",
"log",
"thiserror 2.0.17",
"tokio",
"tracing-subscriber",
"util",
]
[[package]]
name = "tagptr"
version = "0.2.0"

View File

@@ -3,7 +3,6 @@ resolver = "3"
members = [
"rust/networking",
"rust/exo_pyo3_bindings",
"rust/system_custodian",
"rust/util",
]
@@ -25,7 +24,6 @@ opt-level = 3
[workspace.dependencies]
## Crate members as common dependencies
networking = { path = "rust/networking" }
system_custodian = { path = "rust/system_custodian" }
util = { path = "rust/util" }
# Proc-macro authoring tools

View File

@@ -56,6 +56,11 @@ struct ContentView: View {
}
private var shouldShowLocalNetworkWarning: Bool {
// Show warning if local network is not working and EXO is running.
// The checker uses a longer timeout on first launch to allow time for
// the permission prompt, so this correctly handles both:
// 1. User denied permission on first launch
// 2. Permission broke after restart (macOS TCC bug)
if case .notWorking = localNetworkChecker.status {
return controller.status != .stopped
}

View File

@@ -5,8 +5,8 @@ import os.log
/// Checks if the app's local network permission is actually functional.
///
/// macOS local network permission can appear enabled in System Preferences but not
/// actually work after a restart. This service detects this by creating a UDP
/// connection to the mDNS multicast address (224.0.0.251:5353).
/// actually work after a restart. This service uses NWConnection to mDNS multicast
/// to verify actual connectivity.
@MainActor
final class LocalNetworkChecker: ObservableObject {
enum Status: Equatable {
@@ -35,30 +35,43 @@ final class LocalNetworkChecker: ObservableObject {
}
private static let logger = Logger(subsystem: "io.exo.EXO", category: "LocalNetworkChecker")
private static let hasCompletedInitialCheckKey = "LocalNetworkChecker.hasCompletedInitialCheck"
@Published private(set) var status: Status = .unknown
@Published private(set) var lastConnectionState: String = "none"
private var connection: NWConnection?
private var checkTask: Task<Void, Never>?
/// Whether we've completed at least one check (stored in UserDefaults)
private var hasCompletedInitialCheck: Bool {
get { UserDefaults.standard.bool(forKey: Self.hasCompletedInitialCheckKey) }
set { UserDefaults.standard.set(newValue, forKey: Self.hasCompletedInitialCheckKey) }
}
/// Checks if local network access is working.
func check() {
checkTask?.cancel()
status = .checking
lastConnectionState = "connecting"
// Use longer timeout on first launch to allow time for permission prompt
let isFirstCheck = !hasCompletedInitialCheck
let timeout: UInt64 = isFirstCheck ? 30_000_000_000 : 3_000_000_000
checkTask = Task { [weak self] in
guard let self else { return }
let result = await self.performCheck()
Self.logger.info("Checking local network connectivity (first check: \(isFirstCheck))")
let result = await self.checkConnectivity(timeout: timeout)
self.status = result
self.hasCompletedInitialCheck = true
Self.logger.info("Local network check complete: \(result.displayText)")
}
}
private func performCheck() async -> Status {
Self.logger.info("Checking local network access via UDP multicast")
/// Checks connectivity using NWConnection to mDNS multicast.
/// The connection attempt triggers the permission prompt if not yet shown.
private func checkConnectivity(timeout: UInt64) async -> Status {
connection?.cancel()
connection = nil
@@ -84,22 +97,7 @@ final class LocalNetworkChecker: ObservableObject {
continuation.resume(returning: status)
}
conn.stateUpdateHandler = { [weak self] state in
let stateStr: String
switch state {
case .setup: stateStr = "setup"
case .preparing: stateStr = "preparing"
case .ready: stateStr = "ready"
case .waiting(let e): stateStr = "waiting(\(e))"
case .failed(let e): stateStr = "failed(\(e))"
case .cancelled: stateStr = "cancelled"
@unknown default: stateStr = "unknown"
}
Task { @MainActor in
self?.lastConnectionState = stateStr
}
conn.stateUpdateHandler = { state in
switch state {
case .ready:
resumeOnce(.working)
@@ -108,6 +106,7 @@ final class LocalNetworkChecker: ObservableObject {
if errorStr.contains("54") || errorStr.contains("ECONNRESET") {
resumeOnce(.notWorking(reason: "Connection blocked"))
}
// Otherwise keep waiting - might be showing permission prompt
case .failed(let error):
let errorStr = "\(error)"
if errorStr.contains("65") || errorStr.contains("EHOSTUNREACH")
@@ -127,7 +126,7 @@ final class LocalNetworkChecker: ObservableObject {
conn.start(queue: .main)
Task {
try? await Task.sleep(nanoseconds: 3_000_000_000)
try? await Task.sleep(nanoseconds: timeout)
let state = conn.state
switch state {
case .ready:

View File

@@ -241,6 +241,9 @@ class PromptSizer:
ids = tokenizer.apply_chat_template(
messages, tokenize=True, add_generation_prompt=True
)
# Fix for transformers 5.x
if hasattr(ids, "input_ids"):
ids = ids.input_ids
return int(len(ids))
return count_fn

60
dashboard/dashboard.nix Normal file
View File

@@ -0,0 +1,60 @@
{ lib
, config
, dream2nix
, ...
}:
let
# Read and parse the lock file
rawLockFile = builtins.fromJSON (builtins.readFile "${config.deps.dashboardSrc}/package-lock.json");
# For packages with bundleDependencies, filter out deps that are bundled
# (bundled deps are inside the tarball, not separate lockfile entries)
fixedPackages = lib.mapAttrs
(path: entry:
if entry ? bundleDependencies && entry.bundleDependencies != [ ]
then entry // {
dependencies = lib.filterAttrs
(name: _: !(lib.elem name entry.bundleDependencies))
(entry.dependencies or { });
}
else entry
)
(rawLockFile.packages or { });
fixedLockFile = rawLockFile // { packages = fixedPackages; };
in
{
imports = [
dream2nix.modules.dream2nix.nodejs-package-lock-v3
dream2nix.modules.dream2nix.nodejs-granular-v3
];
name = "exo-dashboard";
version = "1.0.0";
mkDerivation = {
src = config.deps.dashboardSrc;
buildPhase = ''
runHook preBuild
npm run build
runHook postBuild
'';
installPhase = ''
runHook preInstall
cp -r build $out/build
runHook postInstall
'';
};
deps = { nixpkgs, ... }: {
inherit (nixpkgs) stdenv;
dashboardSrc = null; # Injected by parts.nix
};
nodejs-package-lock-v3 = {
# Don't use packageLockFile - provide the fixed lock content directly
packageLock = fixedLockFile;
};
}

View File

@@ -863,6 +863,7 @@
"integrity": "sha512-oH8tXw7EZnie8FdOWYrF7Yn4IKrqTFHhXvl8YxXxbKwTMcD/5NNCryUSEXRk2ZR4ojnub0P8rNrsVGHXWqIDtA==",
"dev": true,
"license": "MIT",
"peer": true,
"dependencies": {
"@standard-schema/spec": "^1.0.0",
"@sveltejs/acorn-typescript": "^1.0.5",
@@ -902,6 +903,7 @@
"integrity": "sha512-Y1Cs7hhTc+a5E9Va/xwKlAJoariQyHY+5zBgCZg4PFWNYQ1nMN9sjK1zhw1gK69DuqVP++sht/1GZg1aRwmAXQ==",
"dev": true,
"license": "MIT",
"peer": true,
"dependencies": {
"@sveltejs/vite-plugin-svelte-inspector": "^4.0.1",
"debug": "^4.4.1",
@@ -1518,6 +1520,7 @@
"integrity": "sha512-LCCV0HdSZZZb34qifBsyWlUmok6W7ouER+oQIGBScS8EsZsQbrtFTUrDX4hOl+CS6p7cnNC4td+qrSVGSCTUfQ==",
"dev": true,
"license": "MIT",
"peer": true,
"dependencies": {
"undici-types": "~6.21.0"
}
@@ -1527,6 +1530,7 @@
"resolved": "https://registry.npmjs.org/acorn/-/acorn-8.15.0.tgz",
"integrity": "sha512-NZyJarBfL7nWwIq+FDL6Zp/yHEhePMNnnJ0y3qfieCrmNvYct8uvtiV41UvlSe6apAfk0fY1FbWx+NwfmpvtTg==",
"license": "MIT",
"peer": true,
"bin": {
"acorn": "bin/acorn"
},
@@ -1939,6 +1943,7 @@
"integrity": "sha512-fmTRWbNMmsmWq6xJV8D19U/gw/bwrHfNXxrIN+HfZgnzqTHp9jOmKMhsTUjXOJnZOdZY9Q28y4yebKzqDKlxlQ==",
"dev": true,
"license": "ISC",
"peer": true,
"engines": {
"node": ">=12"
}
@@ -2646,6 +2651,7 @@
"integrity": "sha512-5gTmgEY/sqK6gFXLIsQNH19lWb4ebPDLA4SdLP7dsWkIXHWlG66oPuVvXSGFPppYZz8ZDZq0dYYrbHfBCVUb1Q==",
"dev": true,
"license": "MIT",
"peer": true,
"engines": {
"node": ">=12"
},
@@ -2833,6 +2839,7 @@
"resolved": "https://registry.npmjs.org/svelte/-/svelte-5.45.3.tgz",
"integrity": "sha512-ngKXNhNvwPzF43QqEhDOue7TQTrG09em1sd4HBxVF0Wr2gopAmdEWan+rgbdgK4fhBtSOTJO8bYU4chUG7VXZQ==",
"license": "MIT",
"peer": true,
"dependencies": {
"@jridgewell/remapping": "^2.3.4",
"@jridgewell/sourcemap-codec": "^1.5.0",
@@ -2977,6 +2984,7 @@
"integrity": "sha512-jl1vZzPDinLr9eUt3J/t7V6FgNEw9QjvBPdysz9KfQDD41fQrC2Y4vKQdiaUpFT4bXlb1RHhLpp8wtm6M5TgSw==",
"dev": true,
"license": "Apache-2.0",
"peer": true,
"bin": {
"tsc": "bin/tsc",
"tsserver": "bin/tsserver"
@@ -2998,6 +3006,7 @@
"integrity": "sha512-+Oxm7q9hDoLMyJOYfUYBuHQo+dkAloi33apOPP56pzj+vsdJDzr+j1NISE5pyaAuKL4A3UD34qd0lx5+kfKp2g==",
"dev": true,
"license": "MIT",
"peer": true,
"dependencies": {
"esbuild": "^0.25.0",
"fdir": "^6.4.4",

44
dashboard/parts.nix Normal file
View File

@@ -0,0 +1,44 @@
{ inputs, ... }:
{
perSystem =
{ pkgs, lib, ... }:
let
# Filter source to only include dashboard directory
src = lib.cleanSourceWith {
src = inputs.self;
filter =
path: type:
let
baseName = builtins.baseNameOf path;
inDashboardDir =
(lib.hasInfix "/dashboard/" path)
|| (lib.hasSuffix "/dashboard" (builtins.dirOf path))
|| (baseName == "dashboard" && type == "directory");
in
inDashboardDir;
};
# Build the dashboard with dream2nix (includes node_modules in output)
dashboardFull = inputs.dream2nix.lib.evalModules {
packageSets.nixpkgs = pkgs;
modules = [
./dashboard.nix
{
paths.projectRoot = inputs.self;
paths.projectRootFile = "flake.nix";
paths.package = inputs.self + "/dashboard";
}
# Inject the filtered source
{
deps.dashboardSrc = lib.mkForce "${src}/dashboard";
}
];
};
in
{
# Extract just the static site from the full build
packages.dashboard = pkgs.runCommand "exo-dashboard" { } ''
cp -r ${dashboardFull}/build $out
'';
};
}

View File

@@ -60,12 +60,39 @@
return models;
});
// Auto-select the first available model if none is selected
// Track previous model IDs to detect newly added models (plain variable to avoid reactive loop)
let previousModelIds: Set<string> = new Set();
// Auto-select the first available model if none is selected, if current selection is stale, or if a new model is added
$effect(() => {
const models = availableModels();
if (models.length > 0 && !currentModel) {
setSelectedChatModel(models[0].id);
const currentModelIds = new Set(models.map(m => m.id));
if (models.length > 0) {
// Find newly added models (in current but not in previous)
const newModels = models.filter(m => !previousModelIds.has(m.id));
// If no model selected, select the first available
if (!currentModel) {
setSelectedChatModel(models[0].id);
}
// If current model is stale (no longer has a running instance), reset to first available
else if (!models.some(m => m.id === currentModel)) {
setSelectedChatModel(models[0].id);
}
// If a new model was just added, select it
else if (newModels.length > 0 && previousModelIds.size > 0) {
setSelectedChatModel(newModels[0].id);
}
} else {
// No instances running - clear the selected model
if (currentModel) {
setSelectedChatModel('');
}
}
// Update previous model IDs for next comparison
previousModelIds = currentModelIds;
});
function getInstanceModelId(instanceWrapped: unknown): string {

View File

@@ -400,10 +400,8 @@ function toggleInstanceDownloadDetails(nodeId: string): void {
const errorText = await response.text();
console.error('Failed to launch instance:', errorText);
} else {
// Auto-select the launched model only if no model is currently selected
if (!selectedChatModel()) {
setSelectedChatModel(modelId);
}
// Always auto-select the newly launched model so the user chats to what they just launched
setSelectedChatModel(modelId);
// Scroll to the bottom of instances container to show the new instance
// Use multiple attempts to ensure DOM has updated with the new instance
@@ -763,6 +761,10 @@ function toggleInstanceDownloadDetails(nodeId: string): void {
async function deleteInstance(instanceId: string) {
if (!confirm(`Delete instance ${instanceId.slice(0, 8)}...?`)) return;
// Get the model ID of the instance being deleted before we delete it
const deletedInstanceModelId = getInstanceModelId(instanceData[instanceId]);
const wasSelected = selectedChatModel() === deletedInstanceModelId;
try {
const response = await fetch(`/instance/${instanceId}`, {
method: 'DELETE',
@@ -771,6 +773,24 @@ function toggleInstanceDownloadDetails(nodeId: string): void {
if (!response.ok) {
console.error('Failed to delete instance:', response.status);
} else if (wasSelected) {
// If we deleted the currently selected model, switch to another available model
// Find another instance that isn't the one we just deleted
const remainingInstances = Object.entries(instanceData).filter(([id]) => id !== instanceId);
if (remainingInstances.length > 0) {
// Select the last instance (most recently added, since objects preserve insertion order)
const [, lastInstance] = remainingInstances[remainingInstances.length - 1];
const newModelId = getInstanceModelId(lastInstance);
if (newModelId && newModelId !== 'Unknown' && newModelId !== 'Unknown Model') {
setSelectedChatModel(newModelId);
} else {
// Clear selection if no valid model found
setSelectedChatModel('');
}
} else {
// No more instances, clear the selection
setSelectedChatModel('');
}
}
} catch (error) {
console.error('Error deleting instance:', error);

185
flake.lock generated
View File

@@ -1,5 +1,42 @@
{
"nodes": {
"crane": {
"locked": {
"lastModified": 1767744144,
"narHash": "sha256-9/9ntI0D+HbN4G0TrK3KmHbTvwgswz7p8IEJsWyef8Q=",
"owner": "ipetkov",
"repo": "crane",
"rev": "2fb033290bf6b23f226d4c8b32f7f7a16b043d7e",
"type": "github"
},
"original": {
"owner": "ipetkov",
"repo": "crane",
"type": "github"
}
},
"dream2nix": {
"inputs": {
"nixpkgs": [
"nixpkgs"
],
"purescript-overlay": "purescript-overlay",
"pyproject-nix": "pyproject-nix"
},
"locked": {
"lastModified": 1765953015,
"narHash": "sha256-5FBZbbWR1Csp3Y2icfRkxMJw/a/5FGg8hCXej2//bbI=",
"owner": "nix-community",
"repo": "dream2nix",
"rev": "69eb01fa0995e1e90add49d8ca5bcba213b0416f",
"type": "github"
},
"original": {
"owner": "nix-community",
"repo": "dream2nix",
"type": "github"
}
},
"fenix": {
"inputs": {
"nixpkgs": [
@@ -8,11 +45,11 @@
"rust-analyzer-src": "rust-analyzer-src"
},
"locked": {
"lastModified": 1761893049,
"narHash": "sha256-1TtFDPhC+ZsrOOtBnry1EZC+WipTTvsOVjIEVugqji8=",
"lastModified": 1768287139,
"narHash": "sha256-nsXFt0OzUi6K7dUzzJD5/v9e0Ic+fvclfIW936/43ZM=",
"owner": "nix-community",
"repo": "fenix",
"rev": "c2ac9a5c0d6d16630c3b225b874bd14528d1abe6",
"rev": "a4a3aa956931f90f35453cb519e4545e9ad7f773",
"type": "github"
},
"original": {
@@ -21,25 +58,59 @@
"type": "github"
}
},
"flake-utils": {
"inputs": {
"systems": "systems"
},
"flake-compat": {
"flake": false,
"locked": {
"lastModified": 1731533236,
"narHash": "sha256-l0KFg5HjrsfsO/JpG+r7fRrqm12kzFHyUHqHCVpMMbI=",
"owner": "numtide",
"repo": "flake-utils",
"rev": "11707dc2f618dd54ca8739b309ec4fc024de578b",
"lastModified": 1696426674,
"narHash": "sha256-kvjfFW7WAETZlt09AgDn1MrtKzP7t90Vf7vypd3OL1U=",
"owner": "edolstra",
"repo": "flake-compat",
"rev": "0f9255e01c2351cc7d116c072cb317785dd33b33",
"type": "github"
},
"original": {
"owner": "numtide",
"repo": "flake-utils",
"owner": "edolstra",
"repo": "flake-compat",
"type": "github"
}
},
"flake-parts": {
"inputs": {
"nixpkgs-lib": [
"nixpkgs"
]
},
"locked": {
"lastModified": 1768135262,
"narHash": "sha256-PVvu7OqHBGWN16zSi6tEmPwwHQ4rLPU9Plvs8/1TUBY=",
"owner": "hercules-ci",
"repo": "flake-parts",
"rev": "80daad04eddbbf5a4d883996a73f3f542fa437ac",
"type": "github"
},
"original": {
"owner": "hercules-ci",
"repo": "flake-parts",
"type": "github"
}
},
"nixpkgs": {
"locked": {
"lastModified": 1768127708,
"narHash": "sha256-1Sm77VfZh3mU0F5OqKABNLWxOuDeHIlcFjsXeeiPazs=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "ffbc9f8cbaacfb331b6017d5a5abb21a492c9a38",
"type": "github"
},
"original": {
"owner": "NixOS",
"ref": "nixos-unstable",
"repo": "nixpkgs",
"type": "github"
}
},
"nixpkgs-swift": {
"locked": {
"lastModified": 1761672384,
"narHash": "sha256-o9KF3DJL7g7iYMZq9SWgfS1BFlNbsm6xplRjVlOCkXI=",
@@ -50,27 +121,74 @@
},
"original": {
"owner": "NixOS",
"ref": "nixos-unstable",
"repo": "nixpkgs",
"rev": "08dacfca559e1d7da38f3cf05f1f45ee9bfd213c",
"type": "github"
}
},
"purescript-overlay": {
"inputs": {
"flake-compat": "flake-compat",
"nixpkgs": [
"dream2nix",
"nixpkgs"
],
"slimlock": "slimlock"
},
"locked": {
"lastModified": 1728546539,
"narHash": "sha256-Sws7w0tlnjD+Bjck1nv29NjC5DbL6nH5auL9Ex9Iz2A=",
"owner": "thomashoneyman",
"repo": "purescript-overlay",
"rev": "4ad4c15d07bd899d7346b331f377606631eb0ee4",
"type": "github"
},
"original": {
"owner": "thomashoneyman",
"repo": "purescript-overlay",
"type": "github"
}
},
"pyproject-nix": {
"inputs": {
"nixpkgs": [
"dream2nix",
"nixpkgs"
]
},
"locked": {
"lastModified": 1763017646,
"narHash": "sha256-Z+R2lveIp6Skn1VPH3taQIuMhABg1IizJd8oVdmdHsQ=",
"owner": "pyproject-nix",
"repo": "pyproject.nix",
"rev": "47bd6f296502842643078d66128f7b5e5370790c",
"type": "github"
},
"original": {
"owner": "pyproject-nix",
"repo": "pyproject.nix",
"type": "github"
}
},
"root": {
"inputs": {
"crane": "crane",
"dream2nix": "dream2nix",
"fenix": "fenix",
"flake-utils": "flake-utils",
"flake-parts": "flake-parts",
"nixpkgs": "nixpkgs",
"nixpkgs-swift": "nixpkgs-swift",
"treefmt-nix": "treefmt-nix"
}
},
"rust-analyzer-src": {
"flake": false,
"locked": {
"lastModified": 1761849405,
"narHash": "sha256-igXdvC+WCUN+3gnfk+ptT7rMmxQuY6WbIg1rXMUN1DM=",
"lastModified": 1768224240,
"narHash": "sha256-Pp1dDrXKPBUJReZnnDElFyHYn67XTd48zRhToheLjtk=",
"owner": "rust-lang",
"repo": "rust-analyzer",
"rev": "f7de8ae045a5fe80f1203c5a1c3015b05f7c3550",
"rev": "725349602e525df37f377701e001fe8aab807878",
"type": "github"
},
"original": {
@@ -80,18 +198,25 @@
"type": "github"
}
},
"systems": {
"slimlock": {
"inputs": {
"nixpkgs": [
"dream2nix",
"purescript-overlay",
"nixpkgs"
]
},
"locked": {
"lastModified": 1681028828,
"narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
"owner": "nix-systems",
"repo": "default",
"rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
"lastModified": 1688756706,
"narHash": "sha256-xzkkMv3neJJJ89zo3o2ojp7nFeaZc2G0fYwNXNJRFlo=",
"owner": "thomashoneyman",
"repo": "slimlock",
"rev": "cf72723f59e2340d24881fd7bf61cb113b4c407c",
"type": "github"
},
"original": {
"owner": "nix-systems",
"repo": "default",
"owner": "thomashoneyman",
"repo": "slimlock",
"type": "github"
}
},
@@ -102,11 +227,11 @@
]
},
"locked": {
"lastModified": 1762938485,
"narHash": "sha256-AlEObg0syDl+Spi4LsZIBrjw+snSVU4T8MOeuZJUJjM=",
"lastModified": 1768158989,
"narHash": "sha256-67vyT1+xClLldnumAzCTBvU0jLZ1YBcf4vANRWP3+Ak=",
"owner": "numtide",
"repo": "treefmt-nix",
"rev": "5b4ee75aeefd1e2d5a1cc43cf6ba65eba75e83e4",
"rev": "e96d59dff5c0d7fddb9d113ba108f03c3ef99eca",
"type": "github"
},
"original": {

201
flake.nix
View File

@@ -3,131 +3,134 @@
inputs = {
nixpkgs.url = "github:NixOS/nixpkgs/nixos-unstable";
flake-utils.url = "github:numtide/flake-utils";
# Provides Rust dev-env integration:
flake-parts = {
url = "github:hercules-ci/flake-parts";
inputs.nixpkgs-lib.follows = "nixpkgs";
};
crane.url = "github:ipetkov/crane";
fenix = {
url = "github:nix-community/fenix";
inputs.nixpkgs.follows = "nixpkgs";
};
# Provides formatting infrastructure:
treefmt-nix = {
url = "github:numtide/treefmt-nix";
inputs.nixpkgs.follows = "nixpkgs";
};
dream2nix = {
url = "github:nix-community/dream2nix";
inputs.nixpkgs.follows = "nixpkgs";
};
# Pinned nixpkgs for swift-format (swift is broken on x86_64-linux in newer nixpkgs)
nixpkgs-swift.url = "github:NixOS/nixpkgs/08dacfca559e1d7da38f3cf05f1f45ee9bfd213c";
};
nixConfig = {
# nix community cachix
extra-trusted-public-keys = "exo.cachix.org-1:okq7hl624TBeAR3kV+g39dUFSiaZgLRkLsFBCuJ2NZI=";
extra-substituters = "https://exo.cachix.org";
};
outputs =
inputs:
let
inputs.flake-parts.lib.mkFlake { inherit inputs; } {
systems = [
"x86_64-linux"
"aarch64-darwin"
"aarch64-linux"
];
fenixToolchain = system: inputs.fenix.packages.${system}.complete;
in
inputs.flake-utils.lib.eachSystem systems (
system:
let
pkgs = import inputs.nixpkgs {
inherit system;
overlays = [ inputs.fenix.overlays.default ];
};
treefmtEval = inputs.treefmt-nix.lib.evalModule pkgs {
projectRootFile = "flake.nix";
programs = {
nixpkgs-fmt.enable = true;
ruff-format = {
enable = true;
excludes = [ "rust/exo_pyo3_bindings/exo_pyo3_bindings.pyi" ];
imports = [
inputs.treefmt-nix.flakeModule
./dashboard/parts.nix
./rust/parts.nix
];
perSystem =
{ config, self', inputs', pkgs, lib, system, ... }:
let
fenixToolchain = inputs'.fenix.packages.complete;
# Use pinned nixpkgs for swift-format (swift is broken on x86_64-linux in newer nixpkgs)
pkgsSwift = import inputs.nixpkgs-swift { inherit system; };
in
{
treefmt = {
projectRootFile = "flake.nix";
programs = {
nixpkgs-fmt.enable = true;
ruff-format = {
enable = true;
excludes = [ "rust/exo_pyo3_bindings/exo_pyo3_bindings.pyi" ];
};
rustfmt = {
enable = true;
package = config.rust.toolchain;
};
prettier = {
enable = true;
includes = [ "*.ts" ];
};
swift-format = {
enable = true;
package = pkgsSwift.swiftPackages.swift-format;
};
};
rustfmt = {
enable = true;
package = (fenixToolchain system).rustfmt;
};
prettier = {
enable = true;
includes = [ "*.ts" ];
};
swift-format.enable = true;
};
};
in
{
formatter = treefmtEval.config.build.wrapper;
checks.formatting = treefmtEval.config.build.check inputs.self;
checks.lint = pkgs.runCommand "lint-check" { } ''
export RUFF_CACHE_DIR="$TMPDIR/ruff-cache"
${pkgs.ruff}/bin/ruff check ${inputs.self}/
touch $out
'';
devShells.default = pkgs.mkShell {
packages =
with pkgs;
[
# FORMATTING
treefmtEval.config.build.wrapper
# PYTHON
python313
uv
ruff
basedpyright
# RUST
((fenixToolchain system).withComponents [
"cargo"
"rustc"
"clippy"
"rustfmt"
"rust-src"
])
rustup # Just here to make RustRover happy
# NIX
nixpkgs-fmt
# SVELTE
nodejs
# MISC
just
jq
]
++ (pkgs.lib.optionals pkgs.stdenv.isLinux [
# IFCONFIG
unixtools.ifconfig
# Build dependencies for Linux
pkg-config
openssl
])
++ (pkgs.lib.optionals pkgs.stdenv.isDarwin [
# MACMON
macmon
]);
shellHook = ''
# PYTHON
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:${pkgs.python313}/lib"
${pkgs.lib.optionalString pkgs.stdenv.isLinux ''
# Build environment for Linux
export PKG_CONFIG_PATH="${pkgs.openssl.dev}/lib/pkgconfig:$PKG_CONFIG_PATH"
export LD_LIBRARY_PATH="${pkgs.openssl.out}/lib:$LD_LIBRARY_PATH"
''}
echo
echo "🍎🍎 Run 'just <recipe>' to get started"
just --list
checks.lint = pkgs.runCommand "lint-check" { } ''
export RUFF_CACHE_DIR="$TMPDIR/ruff-cache"
${pkgs.ruff}/bin/ruff check ${inputs.self}/
touch $out
'';
devShells.default = with pkgs; pkgs.mkShell {
inputsFrom = [ self'.checks.cargo-build ];
packages =
[
# FORMATTING
config.treefmt.build.wrapper
# PYTHON
python313
uv
ruff
basedpyright
# RUST
config.rust.toolchain
maturin
# NIX
nixpkgs-fmt
# SVELTE
nodejs
# MISC
just
jq
]
++ lib.optionals stdenv.isLinux [
unixtools.ifconfig
]
++ lib.optionals stdenv.isDarwin [
macmon
];
OPENSSL_NO_VENDOR = "1";
shellHook = ''
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:${python313}/lib"
${lib.optionalString stdenv.isLinux ''
export LD_LIBRARY_PATH="${openssl.out}/lib:$LD_LIBRARY_PATH"
''}
'';
};
};
}
);
};
}

View File

@@ -1,3 +1,5 @@
export NIX_CONFIG := "extra-experimental-features = nix-command flakes"
fmt:
nix fmt

View File

@@ -6,8 +6,6 @@ readme = "README.md"
requires-python = ">=3.13"
dependencies = [
"aiofiles>=24.1.0",
"aiohttp>=3.12.14",
"types-aiofiles>=24.1.0.20250708",
"pydantic>=2.11.7",
"fastapi>=0.116.1",
"filelock>=3.18.0",
@@ -23,6 +21,7 @@ dependencies = [
"tiktoken>=0.12.0", # required for kimi k2 tokenizer
"hypercorn>=0.18.0",
"openai-harmony>=0.0.8",
"httpx>=0.28.1",
]
[project.scripts]

145
rust/parts.nix Normal file
View File

@@ -0,0 +1,145 @@
{ inputs, ... }:
{
perSystem =
{ config, self', inputs', pkgs, lib, ... }:
let
# Fenix nightly toolchain with all components
fenixPkgs = inputs'.fenix.packages;
rustToolchain = fenixPkgs.complete.withComponents [
"cargo"
"rustc"
"clippy"
"rustfmt"
"rust-src"
"rust-analyzer"
];
# Crane with fenix toolchain
craneLib = (inputs.crane.mkLib pkgs).overrideToolchain rustToolchain;
# Source filtering - only include rust/ directory and root Cargo files
# This ensures changes to Python/docs/etc don't trigger Rust rebuilds
src = lib.cleanSourceWith {
src = inputs.self;
filter =
path: type:
let
baseName = builtins.baseNameOf path;
parentDir = builtins.dirOf path;
inRustDir =
(lib.hasInfix "/rust/" path)
|| (lib.hasSuffix "/rust" parentDir)
|| (baseName == "rust" && type == "directory");
isRootCargoFile =
(baseName == "Cargo.toml" || baseName == "Cargo.lock")
&& (builtins.dirOf path == toString inputs.self);
in
isRootCargoFile
|| (inRustDir && (craneLib.filterCargoSources path type || lib.hasSuffix ".toml" path || lib.hasSuffix ".md" path));
};
# Common arguments for all Rust builds
commonArgs = {
inherit src;
pname = "exo-rust";
version = "0.0.1";
strictDeps = true;
nativeBuildInputs = [
pkgs.pkg-config
pkgs.python313 # Required for pyo3-build-config
];
buildInputs = [
pkgs.openssl
pkgs.python313 # Required for pyo3 tests
];
OPENSSL_NO_VENDOR = "1";
# Required for pyo3 tests to find libpython
LD_LIBRARY_PATH = lib.makeLibraryPath [ pkgs.python313 ];
};
# Build dependencies once for caching
cargoArtifacts = craneLib.buildDepsOnly (
commonArgs
// {
cargoExtraArgs = "--workspace";
}
);
in
{
# Export toolchain for use in treefmt and devShell
options.rust = {
toolchain = lib.mkOption {
type = lib.types.package;
default = rustToolchain;
description = "The Rust toolchain to use";
};
};
config = {
packages = {
# Python bindings wheel via maturin
exo_pyo3_bindings = craneLib.buildPackage (
commonArgs
// {
inherit cargoArtifacts;
pname = "exo_pyo3_bindings";
nativeBuildInputs = commonArgs.nativeBuildInputs ++ [
pkgs.maturin
];
buildPhaseCargoCommand = ''
maturin build \
--release \
--manylinux off \
--manifest-path rust/exo_pyo3_bindings/Cargo.toml \
--features "pyo3/extension-module,pyo3/experimental-async" \
--interpreter ${pkgs.python313}/bin/python \
--out dist
'';
# Don't use crane's default install behavior
doNotPostBuildInstallCargoBinaries = true;
installPhaseCommand = ''
mkdir -p $out
cp dist/*.whl $out/
'';
}
);
};
checks = {
# Full workspace build (all crates)
cargo-build = craneLib.buildPackage (
commonArgs
// {
inherit cargoArtifacts;
cargoExtraArgs = "--workspace";
}
);
# Run tests with nextest
cargo-nextest = craneLib.cargoNextest (
commonArgs
// {
inherit cargoArtifacts;
cargoExtraArgs = "--workspace";
}
);
# Build documentation
cargo-doc = craneLib.cargoDoc (
commonArgs
// {
inherit cargoArtifacts;
cargoExtraArgs = "--workspace";
}
);
};
};
};
}

View File

@@ -1,47 +0,0 @@
[package]
name = "system_custodian"
version = { workspace = true }
edition = { workspace = true }
publish = false
[lib]
doctest = false
name = "system_custodian"
path = "src/lib.rs"
[[bin]]
path = "src/bin/main.rs"
name = "system_custodian"
doc = false
[lints]
workspace = true
[dependencies]
# datastructures
either = { workspace = true }
# macro dependencies
extend = { workspace = true }
delegate = { workspace = true }
impl-trait-for-tuples = { workspace = true }
derive_more = { workspace = true }
# async
tokio = { workspace = true, features = ["full"] }
futures = { workspace = true }
futures-timer = { workspace = true }
# utility dependencies
util = { workspace = true }
thiserror = { workspace = true }
#internment = { workspace = true }
#recursion = { workspace = true }
#generativity = { workspace = true }
#itertools = { workspace = true }
tracing-subscriber = { version = "0.3.19", features = ["default", "env-filter"] }
keccak-const = { workspace = true }
# tracing/logging
log = { workspace = true }

View File

@@ -1,4 +0,0 @@
//! TODO: documentation
//!
fn main() {}

View File

@@ -1,69 +0,0 @@
//! This crate defines the logic of, and ways to interact with, Exo's **_System Custodian_** daemon.
//!
//! The **_System Custodian_** daemon is supposed to be a long-living process that precedes the
//! launch of the Exo application, and responsible for ensuring the system (configuration, settings,
//! etc.) is in an appropriate state to facilitate the running of Exo application.
//! The **_System Custodian_** daemon shall expose a [D-Bus](https://www.freedesktop.org/wiki/Software/dbus/)
//! service which Exo application use to _control & query_ it.
//!
//! # Lifecycle
//! When the Exo application starts, it will _wake_ the **_System Custodian_** daemon for the
//! duration of its lifetime, and after it has terminated the daemon will go back to sleep. When
//! the daemon wakes up, it will configure the system into a state suitable for the Exo Application;
//! When the daemon goes to sleep, it will revert those changes as much as it can in case they were
//! destructive to the user's pre-existing configurations.
//!
//! # Responsibilities
//! TODO: these are purely on MacOS, but change to be more broad
//! The **_System Custodian_** daemon is responsible for using System Configuration framework to
//! 1. duplicate the current network set
//! 2. modify existing services to turn on IPv6 if not there
//! 3. remove any bridge services & add any missing services that AREN'T bridge
//! TODO: In the future:
//! 1. run a dummy AWDL service to [allow for macOS peer-to-peer wireless networking](https://yggdrasil-network.github.io/2019/08/19/awdl.html)
//! 2. toggle some GPU/memory configurations to speed up GPU (ask Alex what those configurations are)
//! 3. if we ever decide to provide our **own network interfaces** that abstract over some userland
//! logic, this would be the place to spin that up.
//!
//! Then it will watch the SCDynamicStore for:
//! 1. all __actual__ network interfaces -> collect information on them e.g. their BSD name, MAC
//! address, MTU, IPv6 addresses, etc. -> and set up watchers/notifiers to inform the DBus
//! interface of any changes
//! 2. watch for any __undesirable__ changes to configuration and revert it
//!
//! It should somehow (probably through system sockets and/or BSD interface) trigger IPv6 NDP on
//! each of the interfaces & also listen to/query for any changes on the OS routing cache??
//! Basically emulate the `ping6 ff02::1%enX` and `ndp -an` commands BUT BETTER!!!
//! 1. all that info should coalesce back to the overall state colleted -> should be queryable
//! over D-Bus
//! TODO:
//! 1. we might potentially add to this step a handshake of some kind...? To ensure that we can
//! ACTUALLY communicate with that machine over that link over e.g. TCP, UDP, etc. Will the
//! handshake require to know Node ID? Will the handshake require heartbeats? Who knows...
//! 2. if we ever decide to write proprietary L2/L3 protocols for quicker communication,
//! e.g. [AF_NDRV](https://www.zerotier.com/blog/how-zerotier-eliminated-kernel-extensions-on-macos/)
//! for raw ethernet frame communication, or even a [custom thunderbolt PCIe driver](https://developer.apple.com/documentation/pcidriverkit/creating-custom-pcie-drivers-for-thunderbolt-devices),
//! then this would be the place to carry out discovery and propper handshakes with devices
//! on the other end of the link.
//!
// enable Rust-unstable features for convenience
#![feature(trait_alias)]
#![feature(stmt_expr_attributes)]
#![feature(type_alias_impl_trait)]
#![feature(specialization)]
#![feature(unboxed_closures)]
#![feature(const_trait_impl)]
#![feature(fn_traits)]
pub(crate) mod private {
// sealed traits support
pub trait Sealed {}
impl<T: ?Sized> Sealed for T {}
}
/// Namespace for all the type/trait aliases used by this crate.
pub(crate) mod alias {}
/// Namespace for crate-wide extension traits/methods
pub(crate) mod ext {}

View File

@@ -1,6 +1,7 @@
import argparse
import multiprocessing as mp
import os
import resource
import signal
from dataclasses import dataclass, field
from typing import Self
@@ -195,6 +196,8 @@ class Node:
def main():
args = Args.parse()
soft, hard = resource.getrlimit(resource.RLIMIT_NOFILE)
resource.setrlimit(resource.RLIMIT_NOFILE, (max(soft, 65535), hard))
mp.set_start_method("spawn")
# TODO: Refactor the current verbosity system

View File

@@ -13,12 +13,6 @@ from hypercorn.asyncio import serve # pyright: ignore[reportUnknownVariableType
from hypercorn.config import Config
from hypercorn.typing import ASGIFramework
from loguru import logger
from openai_harmony import ( # pyright: ignore[reportMissingTypeStubs]
HarmonyEncodingName,
Role,
StreamableParser,
load_harmony_encoding,
)
from exo.master.placement import place_instance as get_instance_placements
from exo.shared.apply import apply
@@ -67,8 +61,6 @@ from exo.utils.channels import Receiver, Sender, channel
from exo.utils.dashboard_path import find_dashboard
from exo.utils.event_buffer import OrderedBuffer
encoding = load_harmony_encoding(HarmonyEncodingName.HARMONY_GPT_OSS)
def chunk_to_response(
chunk: TokenChunk, command_id: CommandId
@@ -381,35 +373,8 @@ class API:
instance_id=instance_id,
)
async def _process_gpt_oss(self, token_chunks: Receiver[TokenChunk]):
stream = StreamableParser(encoding, role=Role.ASSISTANT)
thinking = False
async for chunk in token_chunks:
stream.process(chunk.token_id)
delta = stream.last_content_delta
ch = stream.current_channel
if ch == "analysis" and not thinking:
thinking = True
yield chunk.model_copy(update={"text": "<think>"})
if ch != "analysis" and thinking:
thinking = False
yield chunk.model_copy(update={"text": "</think>"})
if delta:
yield chunk.model_copy(update={"text": delta})
if chunk.finish_reason is not None:
if thinking:
yield chunk.model_copy(update={"text": "</think>"})
yield chunk
break
async def _chat_chunk_stream(
self, command_id: CommandId, parse_gpt_oss: bool
self, command_id: CommandId
) -> AsyncGenerator[TokenChunk, None]:
"""Yield `TokenChunk`s for a given command until completion."""
@@ -417,16 +382,10 @@ class API:
self._chat_completion_queues[command_id], recv = channel[TokenChunk]()
with recv as token_chunks:
if parse_gpt_oss:
async for chunk in self._process_gpt_oss(token_chunks):
yield chunk
if chunk.finish_reason is not None:
break
else:
async for chunk in token_chunks:
yield chunk
if chunk.finish_reason is not None:
break
async for chunk in token_chunks:
yield chunk
if chunk.finish_reason is not None:
break
except anyio.get_cancelled_exc_class():
# TODO: TaskCancelled
@@ -442,11 +401,11 @@ class API:
del self._chat_completion_queues[command_id]
async def _generate_chat_stream(
self, command_id: CommandId, parse_gpt_oss: bool
self, command_id: CommandId
) -> AsyncGenerator[str, None]:
"""Generate chat completion stream as JSON strings."""
async for chunk in self._chat_chunk_stream(command_id, parse_gpt_oss):
async for chunk in self._chat_chunk_stream(command_id):
chunk_response: ChatCompletionResponse = chunk_to_response(
chunk, command_id
)
@@ -458,7 +417,7 @@ class API:
yield "data: [DONE]\n\n"
async def _collect_chat_completion(
self, command_id: CommandId, parse_gpt_oss: bool
self, command_id: CommandId
) -> ChatCompletionResponse:
"""Collect all token chunks for a chat completion and return a single response."""
@@ -466,7 +425,7 @@ class API:
model: str | None = None
finish_reason: FinishReason | None = None
async for chunk in self._chat_chunk_stream(command_id, parse_gpt_oss):
async for chunk in self._chat_chunk_stream(command_id):
if model is None:
model = chunk.model
@@ -495,7 +454,7 @@ class API:
)
async def _collect_chat_completion_with_stats(
self, command_id: CommandId, parse_gpt_oss: bool
self, command_id: CommandId
) -> BenchChatCompletionResponse:
text_parts: list[str] = []
model: str | None = None
@@ -503,7 +462,7 @@ class API:
stats: GenerationStats | None = None
async for chunk in self._chat_chunk_stream(command_id, parse_gpt_oss):
async for chunk in self._chat_chunk_stream(command_id):
if model is None:
model = chunk.model
@@ -544,8 +503,6 @@ class API:
"""Handle chat completions, supporting both streaming and non-streaming responses."""
model_meta = await resolve_model_meta(payload.model)
payload.model = model_meta.model_id
parse_gpt_oss = "gpt-oss" in model_meta.model_id.lower()
logger.info(f"{parse_gpt_oss=}")
if not any(
instance.shard_assignments.model_id == payload.model
@@ -562,17 +519,16 @@ class API:
await self._send(command)
if payload.stream:
return StreamingResponse(
self._generate_chat_stream(command.command_id, parse_gpt_oss),
self._generate_chat_stream(command.command_id),
media_type="text/event-stream",
)
return await self._collect_chat_completion(command.command_id, parse_gpt_oss)
return await self._collect_chat_completion(command.command_id)
async def bench_chat_completions(
self, payload: BenchChatCompletionTaskParams
) -> BenchChatCompletionResponse:
model_meta = await resolve_model_meta(payload.model)
parse_gpt_oss = "gpt-oss" in model_meta.model_id.lower()
payload.model = model_meta.model_id
if not any(
@@ -589,10 +545,7 @@ class API:
command = ChatCompletion(request_params=payload)
await self._send(command)
response = await self._collect_chat_completion_with_stats(
command.command_id,
parse_gpt_oss,
)
response = await self._collect_chat_completion_with_stats(command.command_id)
return response
def _calculate_total_available_memory(self) -> Memory:

View File

@@ -29,6 +29,11 @@ class _InterceptHandler(logging.Handler):
def logger_setup(log_file: Path | None, verbosity: int = 0):
"""Set up logging for this process - formatting, file handles, verbosity and output"""
logging.getLogger("exo_pyo3_bindings").setLevel(logging.WARNING)
logging.getLogger("httpx").setLevel(logging.WARNING)
logging.getLogger("httpcore").setLevel(logging.WARNING)
logger.remove()
# replace all stdlib loggers with _InterceptHandlers that log to loguru

View File

@@ -1,319 +0,0 @@
{#-
In addition to the normal inputs of `messages` and `tools`, this template also accepts the
following kwargs:
- "builtin_tools": A list, can contain "browser" and/or "python".
- "model_identity": A string that optionally describes the model identity.
- "reasoning_effort": A string that describes the reasoning effort, defaults to "medium".
#}
{#- Tool Definition Rendering ============================================== #}
{%- macro render_typescript_type(param_spec, required_params, is_nullable=false) -%}
{%- if param_spec.type == "array" -%}
{%- if param_spec['items'] -%}
{%- if param_spec['items']['type'] == "string" -%}
{{- "string[]" }}
{%- elif param_spec['items']['type'] == "number" -%}
{{- "number[]" }}
{%- elif param_spec['items']['type'] == "integer" -%}
{{- "number[]" }}
{%- elif param_spec['items']['type'] == "boolean" -%}
{{- "boolean[]" }}
{%- else -%}
{%- set inner_type = render_typescript_type(param_spec['items'], required_params) -%}
{%- if inner_type == "object | object" or inner_type|length > 50 -%}
{{- "any[]" }}
{%- else -%}
{{- inner_type + "[]" }}
{%- endif -%}
{%- endif -%}
{%- if param_spec.nullable -%}
{{- " | null" }}
{%- endif -%}
{%- else -%}
{{- "any[]" }}
{%- if param_spec.nullable -%}
{{- " | null" }}
{%- endif -%}
{%- endif -%}
{%- elif param_spec.type is defined and param_spec.type is iterable and param_spec.type is not string and param_spec.type is not mapping and param_spec.type[0] is defined -%}
{#- Handle array of types like ["object", "object"] from Union[dict, list] #}
{%- if param_spec.type | length > 1 -%}
{{- param_spec.type | join(" | ") }}
{%- else -%}
{{- param_spec.type[0] }}
{%- endif -%}
{%- elif param_spec.oneOf -%}
{#- Handle oneOf schemas - check for complex unions and fallback to any #}
{%- set has_object_variants = false -%}
{%- for variant in param_spec.oneOf -%}
{%- if variant.type == "object" -%}
{%- set has_object_variants = true -%}
{%- endif -%}
{%- endfor -%}
{%- if has_object_variants and param_spec.oneOf|length > 1 -%}
{{- "any" }}
{%- else -%}
{%- for variant in param_spec.oneOf -%}
{{- render_typescript_type(variant, required_params) -}}
{%- if variant.description %}
{{- "// " + variant.description }}
{%- endif -%}
{%- if variant.default is defined %}
{{ "// default: " + variant.default|tojson }}
{%- endif -%}
{%- if not loop.last %}
{{- " | " }}
{% endif -%}
{%- endfor -%}
{%- endif -%}
{%- elif param_spec.type == "string" -%}
{%- if param_spec.enum -%}
{{- '"' + param_spec.enum|join('" | "') + '"' -}}
{%- else -%}
{{- "string" }}
{%- if param_spec.nullable %}
{{- " | null" }}
{%- endif -%}
{%- endif -%}
{%- elif param_spec.type == "number" -%}
{{- "number" }}
{%- elif param_spec.type == "integer" -%}
{{- "number" }}
{%- elif param_spec.type == "boolean" -%}
{{- "boolean" }}
{%- elif param_spec.type == "object" -%}
{%- if param_spec.properties -%}
{{- "{\n" }}
{%- for prop_name, prop_spec in param_spec.properties.items() -%}
{{- prop_name -}}
{%- if prop_name not in (param_spec.required or []) -%}
{{- "?" }}
{%- endif -%}
{{- ": " }}
{{ render_typescript_type(prop_spec, param_spec.required or []) }}
{%- if not loop.last -%}
{{-", " }}
{%- endif -%}
{%- endfor -%}
{{- "}" }}
{%- else -%}
{{- "object" }}
{%- endif -%}
{%- else -%}
{{- "any" }}
{%- endif -%}
{%- endmacro -%}
{%- macro render_tool_namespace(namespace_name, tools) -%}
{{- "## " + namespace_name + "\n\n" }}
{{- "namespace " + namespace_name + " {\n\n" }}
{%- for tool in tools %}
{%- set tool = tool.function %}
{{- "// " + tool.description + "\n" }}
{{- "type "+ tool.name + " = " }}
{%- if tool.parameters and tool.parameters.properties %}
{{- "(_: {\n" }}
{%- for param_name, param_spec in tool.parameters.properties.items() %}
{%- if param_spec.description %}
{{- "// " + param_spec.description + "\n" }}
{%- endif %}
{{- param_name }}
{%- if param_name not in (tool.parameters.required or []) -%}
{{- "?" }}
{%- endif -%}
{{- ": " }}
{{- render_typescript_type(param_spec, tool.parameters.required or []) }}
{%- if param_spec.default is defined -%}
{%- if param_spec.enum %}
{{- ", // default: " + param_spec.default }}
{%- elif param_spec.oneOf %}
{{- "// default: " + param_spec.default }}
{%- else %}
{{- ", // default: " + param_spec.default|tojson }}
{%- endif -%}
{%- endif -%}
{%- if not loop.last %}
{{- ",\n" }}
{%- else %}
{{- ",\n" }}
{%- endif -%}
{%- endfor %}
{{- "}) => any;\n\n" }}
{%- else -%}
{{- "() => any;\n\n" }}
{%- endif -%}
{%- endfor %}
{{- "} // namespace " + namespace_name }}
{%- endmacro -%}
{%- macro render_builtin_tools(browser_tool, python_tool) -%}
{%- if browser_tool %}
{{- "## browser\n\n" }}
{{- "// Tool for browsing.\n" }}
{{- "// The `cursor` appears in brackets before each browsing display: `[{cursor}]`.\n" }}
{{- "// Cite information from the tool using the following format:\n" }}
{{- "// `【{cursor}†L{line_start}(-L{line_end})?】`, for example: `【6†L9-L11】` or `【8†L3】`.\n" }}
{{- "// Do not quote more than 10 words directly from the tool output.\n" }}
{{- "// sources=web (default: web)\n" }}
{{- "namespace browser {\n\n" }}
{{- "// Searches for information related to `query` and displays `topn` results.\n" }}
{{- "type search = (_: {\n" }}
{{- "query: string,\n" }}
{{- "topn?: number, // default: 10\n" }}
{{- "source?: string,\n" }}
{{- "}) => any;\n\n" }}
{{- "// Opens the link `id` from the page indicated by `cursor` starting at line number `loc`, showing `num_lines` lines.\n" }}
{{- "// Valid link ids are displayed with the formatting: `【{id}†.*】`.\n" }}
{{- "// If `cursor` is not provided, the most recent page is implied.\n" }}
{{- "// If `id` is a string, it is treated as a fully qualified URL associated with `source`.\n" }}
{{- "// If `loc` is not provided, the viewport will be positioned at the beginning of the document or centered on the most relevant passage, if available.\n" }}
{{- "// Use this function without `id` to scroll to a new location of an opened page.\n" }}
{{- "type open = (_: {\n" }}
{{- "id?: number | string, // default: -1\n" }}
{{- "cursor?: number, // default: -1\n" }}
{{- "loc?: number, // default: -1\n" }}
{{- "num_lines?: number, // default: -1\n" }}
{{- "view_source?: boolean, // default: false\n" }}
{{- "source?: string,\n" }}
{{- "}) => any;\n\n" }}
{{- "// Finds exact matches of `pattern` in the current page, or the page given by `cursor`.\n" }}
{{- "type find = (_: {\n" }}
{{- "pattern: string,\n" }}
{{- "cursor?: number, // default: -1\n" }}
{{- "}) => any;\n\n" }}
{{- "} // namespace browser\n\n" }}
{%- endif -%}
{%- if python_tool %}
{{- "## python\n\n" }}
{{- "Use this tool to execute Python code in your chain of thought. The code will not be shown to the user. This tool should be used for internal reasoning, but not for code that is intended to be visible to the user (e.g. when creating plots, tables, or files).\n\n" }}
{{- "When you send a message containing Python code to python, it will be executed in a stateful Jupyter notebook environment. python will respond with the output of the execution or time out after 120.0 seconds. The drive at '/mnt/data' can be used to save and persist user files. Internet access for this session is UNKNOWN. Depends on the cluster.\n\n" }}
{%- endif -%}
{%- endmacro -%}
{#- System Message Construction ============================================ #}
{%- macro build_system_message() -%}
{%- if model_identity is not defined %}
{%- set model_identity = "You are ChatGPT, a large language model trained by OpenAI." %}
{%- endif %}
{{- model_identity + "\n" }}
{{- "Knowledge cutoff: 2024-06\n" }}
{{- "Current date: " + strftime_now("%Y-%m-%d") + "\n\n" }}
{%- if reasoning_effort is not defined %}
{%- set reasoning_effort = "medium" %}
{%- endif %}
{{- "Reasoning: " + reasoning_effort + "\n\n" }}
{%- if builtin_tools %}
{{- "# Tools\n\n" }}
{%- set available_builtin_tools = namespace(browser=false, python=false) %}
{%- for tool in builtin_tools %}
{%- if tool == "browser" %}
{%- set available_builtin_tools.browser = true %}
{%- elif tool == "python" %}
{%- set available_builtin_tools.python = true %}
{%- endif %}
{%- endfor %}
{{- render_builtin_tools(available_builtin_tools.browser, available_builtin_tools.python) }}
{%- endif -%}
{{- "# Valid channels: analysis, commentary, final. Channel must be included for every message." }}
{%- if tools -%}
{{- "\nCalls to these tools must go to the commentary channel: 'functions'." }}
{%- endif -%}
{%- endmacro -%}
{#- Main Template Logic ================================================= #}
{#- Set defaults #}
{#- Render system message #}
{{- "<|start|>system<|message|>" }}
{{- build_system_message() }}
{{- "<|end|>" }}
{#- Extract developer message #}
{%- if messages[0].role == "developer" or messages[0].role == "system" %}
{%- set developer_message = messages[0].content %}
{%- set loop_messages = messages[1:] %}
{%- else %}
{%- set developer_message = "" %}
{%- set loop_messages = messages %}
{%- endif %}
{#- Render developer message #}
{%- if developer_message or tools %}
{{- "<|start|>developer<|message|>" }}
{%- if developer_message %}
{{- "# Instructions\n\n" }}
{{- developer_message }}
{{- "\n\n" }}
{%- endif %}
{%- if tools -%}
{{- "# Tools\n\n" }}
{{- render_tool_namespace("functions", tools) }}
{%- endif -%}
{{- "<|end|>" }}
{%- endif %}
{#- Render messages #}
{%- set last_tool_call = namespace(name=none) %}
{%- for message in loop_messages -%}
{#- At this point only assistant/user/tool messages should remain #}
{%- if message.role == 'assistant' -%}
{#- Checks to ensure the messages are being passed in the format we expect #}
{%- if "content" in message %}
{%- if "<|channel|>analysis<|message|>" in message.content or "<|channel|>final<|message|>" in message.content %}
{{- raise_exception("You have passed a message containing <|channel|> tags in the content field. Instead of doing this, you should pass analysis messages (the string between '<|message|>' and '<|end|>') in the 'thinking' field, and final messages (the string between '<|message|>' and '<|end|>') in the 'content' field.") }}
{%- endif %}
{%- endif %}
{%- if "thinking" in message %}
{%- if "<|channel|>analysis<|message|>" in message.thinking or "<|channel|>final<|message|>" in message.thinking %}
{{- raise_exception("You have passed a message containing <|channel|> tags in the thinking field. Instead of doing this, you should pass analysis messages (the string between '<|message|>' and '<|end|>') in the 'thinking' field, and final messages (the string between '<|message|>' and '<|end|>') in the 'content' field.") }}
{%- endif %}
{%- endif %}
{%- if "tool_calls" in message %}
{#- We need very careful handling here - we want to drop the tool call analysis message if the model #}
{#- has output a later <|final|> message, but otherwise we want to retain it. This is the only case #}
{#- when we render CoT/analysis messages in inference. #}
{%- set future_final_message = namespace(found=false) %}
{%- for future_message in loop_messages[loop.index:] %}
{%- if future_message.role == 'assistant' and "tool_calls" not in future_message %}
{%- set future_final_message.found = true %}
{%- endif %}
{%- endfor %}
{#- We assume max 1 tool call per message, and so we infer the tool call name #}
{#- in "tool" messages from the most recent assistant tool call name #}
{%- set tool_call = message.tool_calls[0] %}
{%- if tool_call.function %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{%- if message.content and message.thinking %}
{{- raise_exception("Cannot pass both content and thinking in an assistant message with tool calls! Put the analysis message in one or the other, but not both.") }}
{%- elif message.content and not future_final_message.found %}
{{- "<|start|>assistant<|channel|>analysis<|message|>" + message.content + "<|end|>" }}
{%- elif message.thinking and not future_final_message.found %}
{{- "<|start|>assistant<|channel|>analysis<|message|>" + message.thinking + "<|end|>" }}
{%- endif %}
{{- "<|start|>assistant to=" }}
{{- "functions." + tool_call.name + "<|channel|>commentary " }}
{{- (tool_call.content_type if tool_call.content_type is defined else "json") + "<|message|>" }}
{{- tool_call.arguments|tojson }}
{{- "<|call|>" }}
{%- set last_tool_call.name = tool_call.name %}
{%- elif loop.last and not add_generation_prompt %}
{#- Only render the CoT if the final turn is an assistant turn and add_generation_prompt is false #}
{#- This is a situation that should only occur in training, never in inference. #}
{%- if "thinking" in message %}
{{- "<|start|>assistant<|channel|>analysis<|message|>" + message.thinking + "<|end|>" }}
{%- endif %}
{#- <|return|> indicates the end of generation, but <|end|> does not #}
{#- <|return|> should never be an input to the model, but we include it as the final token #}
{#- when training, so the model learns to emit it. #}
{{- "<|start|>assistant<|channel|>final<|message|>" + message.content + "<|return|>" }}
{%- else %}
{#- CoT is dropped during all previous turns, so we never render it for inference #}
{{- "<|start|>assistant<|channel|>final<|message|>" + message.content + "<|end|>" }}
{%- set last_tool_call.name = none %}
{%- endif %}
{%- elif message.role == 'tool' -%}
{%- if last_tool_call.name is none %}
{{- raise_exception("Message has tool role, but there was no previous assistant message with a tool call!") }}
{%- endif %}
{{- "<|start|>functions." + last_tool_call.name }}
{{- " to=assistant<|channel|>commentary<|message|>" + message.content|tojson + "<|end|>" }}
{%- elif message.role == 'user' -%}
{{- "<|start|>user<|message|>" + message.content + "<|end|>" }}
{%- endif -%}
{%- endfor -%}
{#- Generation prompt #}
{%- if add_generation_prompt -%}
<|start|>assistant
{%- endif -%}

View File

@@ -14,32 +14,6 @@ class ModelCard(CamelCaseModel):
MODEL_CARDS: dict[str, ModelCard] = {
# deepseek v3
# "deepseek-v3-0324:4bit": ModelCard(
# short_id="deepseek-v3-0324:4bit",
# model_id="mlx-community/DeepSeek-V3-0324-4bit",
# name="DeepSeek V3 0324 (4-bit)",
# description="""DeepSeek V3 is a large language model trained on the DeepSeek V3 dataset.""",
# tags=[],
# metadata=ModelMetadata(
# model_id=ModelId("mlx-community/DeepSeek-V3-0324-4bit"),
# pretty_name="DeepSeek V3 0324 (4-bit)",
# storage_size=Memory.from_kb(409706307),
# n_layers=61,
# ),
# ),
# "deepseek-v3-0324": ModelCard(
# short_id="deepseek-v3-0324",
# model_id="mlx-community/DeepSeek-v3-0324-8bit",
# name="DeepSeek V3 0324 (8-bit)",
# description="""DeepSeek V3 is a large language model trained on the DeepSeek V3 dataset.""",
# tags=[],
# metadata=ModelMetadata(
# model_id=ModelId("mlx-community/DeepSeek-v3-0324-8bit"),
# pretty_name="DeepSeek V3 0324 (8-bit)",
# storage_size=Memory.from_kb(754706307),
# n_layers=61,
# ),
# ),
"deepseek-v3.1-4bit": ModelCard(
short_id="deepseek-v3.1-4bit",
model_id=ModelId("mlx-community/DeepSeek-V3.1-4bit"),
@@ -70,63 +44,6 @@ MODEL_CARDS: dict[str, ModelCard] = {
supports_tensor=True,
),
),
# "deepseek-v3.2": ModelCard(
# short_id="deepseek-v3.2",
# model_id=ModelId("mlx-community/DeepSeek-V3.2-8bit"),
# name="DeepSeek V3.2 (8-bit)",
# description="""DeepSeek V3.2 is a large language model trained on the DeepSeek V3.2 dataset.""",
# tags=[],
# metadata=ModelMetadata(
# model_id=ModelId("mlx-community/DeepSeek-V3.2-8bit"),
# pretty_name="DeepSeek V3.2 (8-bit)",
# storage_size=Memory.from_kb(754706307),
# n_layers=61,
# hidden_size=7168,
# ),
# ),
# "deepseek-v3.2-4bit": ModelCard(
# short_id="deepseek-v3.2-4bit",
# model_id=ModelId("mlx-community/DeepSeek-V3.2-4bit"),
# name="DeepSeek V3.2 (4-bit)",
# description="""DeepSeek V3.2 is a large language model trained on the DeepSeek V3.2 dataset.""",
# tags=[],
# metadata=ModelMetadata(
# model_id=ModelId("mlx-community/DeepSeek-V3.2-4bit"),
# pretty_name="DeepSeek V3.2 (4-bit)",
# storage_size=Memory.from_kb(754706307 // 2), # TODO !!!!!
# n_layers=61,
# hidden_size=7168,
# ),
# ),
# deepseek r1
# "deepseek-r1-0528-4bit": ModelCard(
# short_id="deepseek-r1-0528-4bit",
# model_id="mlx-community/DeepSeek-R1-0528-4bit",
# name="DeepSeek-R1-0528 (4-bit)",
# description="""DeepSeek R1 is a large language model trained on the DeepSeek R1 dataset.""",
# tags=[],
# metadata=ModelMetadata(
# model_id=ModelId("mlx-community/DeepSeek-R1-0528-4bit"),
# pretty_name="DeepSeek R1 671B (4-bit)",
# storage_size=Memory.from_kb(409706307),
# n_layers=61,
# hidden_size=7168,
# ),
# ),
# "deepseek-r1-0528": ModelCard(
# short_id="deepseek-r1-0528",
# model_id="mlx-community/DeepSeek-R1-0528-8bit",
# name="DeepSeek-R1-0528 (8-bit)",
# description="""DeepSeek R1 is a large language model trained on the DeepSeek R1 dataset.""",
# tags=[],
# metadata=ModelMetadata(
# model_id=ModelId("mlx-community/DeepSeek-R1-0528-8bit"),
# pretty_name="DeepSeek R1 671B (8-bit)",
# storage_size=Memory.from_bytes(754998771712),
# n_layers=61,
# . hidden_size=7168,
# ),
# ),
# kimi k2
"kimi-k2-instruct-4bit": ModelCard(
short_id="kimi-k2-instruct-4bit",
@@ -508,23 +425,24 @@ MODEL_CARDS: dict[str, ModelCard] = {
supports_tensor=True,
),
),
"gpt-oss-20b-4bit": ModelCard(
short_id="gpt-oss-20b-4bit",
model_id=ModelId("mlx-community/gpt-oss-20b-MXFP4-Q4"),
name="GPT-OSS 20B (MXFP4-Q4, MLX)",
description="""OpenAI's GPT-OSS 20B is a medium-sized MoE model for lower-latency and local or specialized use cases; this MLX variant uses MXFP4 4-bit quantization.""",
"gpt-oss-20b-MXFP4-Q8": ModelCard(
short_id="gpt-oss-20b-MXFP4-Q8",
model_id=ModelId("mlx-community/gpt-oss-20b-MXFP4-Q8"),
name="GPT-OSS 20B (MXFP4-Q8, MLX)",
description="""OpenAI's GPT-OSS 20B is a medium-sized MoE model for lower-latency and local or specialized use cases; this variant is a 4-bit MLX conversion for Apple Silicon.""",
tags=[],
metadata=ModelMetadata(
model_id=ModelId("mlx-community/gpt-oss-20b-MXFP4-Q4"),
pretty_name="GPT-OSS 20B (MXFP4-Q4, MLX)",
model_id=ModelId("mlx-community/gpt-oss-20b-MXFP4-Q8"),
pretty_name="GPT-OSS 20B (MXFP4-Q8, MLX)",
storage_size=Memory.from_kb(11_744_051),
n_layers=24,
hidden_size=2880,
supports_tensor=True,
),
),
# Needs to be quantized g32 or g16.
# glm 4.5
"glm-4.5-air-8bit": ModelCard(
# Needs to be quantized g32 or g16 to work with tensor parallel
short_id="glm-4.5-air-8bit",
model_id=ModelId("mlx-community/GLM-4.5-Air-8bit"),
name="GLM 4.5 Air 8bit",
@@ -554,19 +472,81 @@ MODEL_CARDS: dict[str, ModelCard] = {
supports_tensor=True,
),
),
# "devstral-2-123b-instruct-2512-8bit": ModelCard(
# short_id="devstral-2-123b-instruct-2512-8bit",
# model_id=ModelId("mlx-community/Devstral-2-123B-Instruct-2512-8bit"),
# name="Devstral 2 123B Instruct 2512 (8-bit, MLX)",
# description="""Mistral AI's Devstral 2 123B Instruct (2512) is an agentic coding model.""",
# tags=[],
# metadata=ModelMetadata(
# model_id=ModelId("mlx-community/Devstral-2-123B-Instruct-2512-8bit"),
# pretty_name="Devstral 2 123B Instruct 2512 (8-bit, MLX)",
# storage_size=Memory.from_kb(133_000_000),
# n_layers=88,
# hidden_size=12288,
# supports_tensor=True,
# ),
# ),
# glm 4.7
"glm-4.7-4bit": ModelCard(
short_id="glm-4.7-4bit",
model_id=ModelId("mlx-community/GLM-4.7-4bit"),
name="GLM 4.7 4bit",
description="GLM 4.7 4bit",
tags=[],
metadata=ModelMetadata(
model_id=ModelId("mlx-community/GLM-4.7-4bit"),
pretty_name="GLM 4.7 4bit",
storage_size=Memory.from_bytes(198556925568),
n_layers=91,
hidden_size=5120,
supports_tensor=True,
),
),
"glm-4.7-6bit": ModelCard(
short_id="glm-4.7-6bit",
model_id=ModelId("mlx-community/GLM-4.7-6bit"),
name="GLM 4.7 6bit",
description="GLM 4.7 6bit",
tags=[],
metadata=ModelMetadata(
model_id=ModelId("mlx-community/GLM-4.7-6bit"),
pretty_name="GLM 4.7 6bit",
storage_size=Memory.from_bytes(286737579648),
n_layers=91,
hidden_size=5120,
supports_tensor=True,
),
),
"glm-4.7-8bit-gs32": ModelCard(
short_id="glm-4.7-8bit-gs32",
model_id=ModelId("mlx-community/GLM-4.7-8bit-gs32"),
name="GLM 4.7 8bit (gs32)",
description="GLM 4.7 8bit (gs32)",
tags=[],
metadata=ModelMetadata(
model_id=ModelId("mlx-community/GLM-4.7-8bit-gs32"),
pretty_name="GLM 4.7 8bit (gs32)",
storage_size=Memory.from_bytes(396963397248),
n_layers=91,
hidden_size=5120,
supports_tensor=True,
),
),
# minimax-m2
"minimax-m2.1-8bit": ModelCard(
short_id="minimax-m2.1-8bit",
model_id=ModelId("mlx-community/MiniMax-M2.1-8bit"),
name="MiniMax M2.1 8bit",
description="MiniMax M2.1 8bit",
tags=[],
metadata=ModelMetadata(
model_id=ModelId("mlx-community/MiniMax-M2.1-8bit"),
pretty_name="MiniMax M2.1 8bit",
storage_size=Memory.from_bytes(242986745856),
n_layers=61,
hidden_size=3072,
supports_tensor=True,
),
),
"minimax-m2.1-3bit": ModelCard(
short_id="minimax-m2.1-3bit",
model_id=ModelId("mlx-community/MiniMax-M2.1-3bit"),
name="MiniMax M2.1 3bit",
description="MiniMax M2.1 3bit",
tags=[],
metadata=ModelMetadata(
model_id=ModelId("mlx-community/MiniMax-M2.1-3bit"),
pretty_name="MiniMax M2.1 3bit",
storage_size=Memory.from_bytes(100086644736),
n_layers=61,
hidden_size=3072,
supports_tensor=True,
),
),
}

View File

@@ -7,13 +7,13 @@ import time
import traceback
from datetime import timedelta
from pathlib import Path
from typing import Callable, Literal
from typing import Callable, Literal, cast
from urllib.parse import urljoin
import aiofiles
import aiofiles.os as aios
import aiohttp
import certifi
import httpx
from loguru import logger
from pydantic import (
BaseModel,
@@ -132,20 +132,11 @@ async def resolve_model_path_for_repo(repo_id: str) -> Path:
return (await ensure_models_dir()) / repo_id.replace("/", "--")
def resolve_model_path_for_repo_sync(repo_id: str) -> Path:
return ensure_models_dir_sync() / repo_id.replace("/", "--")
async def ensure_models_dir() -> Path:
await aios.makedirs(EXO_MODELS_DIR, exist_ok=True)
return EXO_MODELS_DIR
def ensure_models_dir_sync() -> Path:
os.makedirs(EXO_MODELS_DIR, exist_ok=True)
return EXO_MODELS_DIR
async def delete_model(repo_id: str) -> bool:
model_dir = await ensure_models_dir() / repo_id.replace("/", "--")
if not await aios.path.exists(model_dir):
@@ -216,23 +207,22 @@ async def _fetch_file_list(
headers = await get_download_headers()
async with (
create_http_session(timeout_profile="short") as session,
session.get(url, headers=headers) as response,
):
if response.status == 200:
data_json = await response.text()
data = TypeAdapter(list[FileListEntry]).validate_json(data_json)
files: list[FileListEntry] = []
for item in data:
if item.type == "file":
files.append(FileListEntry.model_validate(item))
elif item.type == "directory" and recursive:
subfiles = await _fetch_file_list(
repo_id, revision, item.path, recursive
)
files.extend(subfiles)
return files
else:
raise Exception(f"Failed to fetch file list: {response.status}")
response = await session.get(url, headers=headers)
if response.status_code != 200:
raise Exception(f"Failed to fetch file list: {response.status_code}")
data = TypeAdapter(list[FileListEntry]).validate_json(response.text)
files: list[FileListEntry] = []
for item in data:
if item.type == "file":
files.append(FileListEntry.model_validate(item))
elif item.type == "directory" and recursive:
subfiles = await _fetch_file_list(
repo_id, revision, item.path, recursive
)
files.extend(subfiles)
return files
async def get_download_headers() -> dict[str, str]:
@@ -240,31 +230,25 @@ async def get_download_headers() -> dict[str, str]:
def create_http_session(
auto_decompress: bool = False,
timeout_profile: Literal["short", "long"] = "long",
) -> aiohttp.ClientSession:
) -> httpx.AsyncClient:
if timeout_profile == "short":
total_timeout = 30
connect_timeout = 10
sock_read_timeout = 30
sock_connect_timeout = 10
read_timeout = 30
else:
total_timeout = 1800
connect_timeout = 60
sock_read_timeout = 1800
sock_connect_timeout = 60
read_timeout = 1800
ssl_context = ssl.create_default_context(cafile=certifi.where())
connector = aiohttp.TCPConnector(ssl=ssl_context)
return aiohttp.ClientSession(
auto_decompress=auto_decompress,
connector=connector,
timeout=aiohttp.ClientTimeout(
total=total_timeout,
return httpx.AsyncClient(
verify=ssl_context,
timeout=httpx.Timeout(
connect=connect_timeout,
sock_read=sock_read_timeout,
sock_connect=sock_connect_timeout,
read=read_timeout,
write=total_timeout,
),
)
@@ -291,23 +275,25 @@ async def file_meta(
headers = await get_download_headers()
async with (
create_http_session(timeout_profile="short") as session,
session.head(url, headers=headers) as r,
):
if r.status == 307:
r = await session.head(url, headers=headers)
if r.status_code == 307:
# On redirect, only trust Hugging Face's x-linked-* headers.
x_linked_size = r.headers.get("x-linked-size")
x_linked_etag = r.headers.get("x-linked-etag")
x_linked_size = cast(str | None, r.headers.get("x-linked-size"))
x_linked_etag = cast(str | None, r.headers.get("x-linked-etag"))
if x_linked_size and x_linked_etag:
content_length = int(x_linked_size)
etag = trim_etag(x_linked_etag)
return content_length, etag
# Otherwise, follow the redirect to get authoritative size/hash
redirected_location = r.headers.get("location")
redirected_location = cast(str | None, r.headers.get("location"))
return await file_meta(repo_id, revision, path, redirected_location)
content_length = int(
r.headers.get("x-linked-size") or r.headers.get("content-length") or 0
content_length = cast(
str | None,
r.headers.get("x-linked-size") or r.headers.get("content-length"),
)
etag = r.headers.get("x-linked-etag") or r.headers.get("etag")
content_length = 0 if content_length is None else int(content_length)
etag = cast(str | None, r.headers.get("x-linked-etag") or r.headers.get("etag"))
assert content_length > 0, f"No content length for {url}"
assert etag is not None, f"No remote hash for {url}"
etag = trim_etag(etag)
@@ -366,17 +352,17 @@ async def _download_file(
n_read = resume_byte_pos or 0
async with (
create_http_session(timeout_profile="long") as session,
session.get(url, headers=headers) as r,
):
if r.status == 404:
r = await session.get(url, headers=headers)
if r.status_code == 404:
raise FileNotFoundError(f"File not found: {url}")
assert r.status in [200, 206], (
f"Failed to download {path} from {url}: {r.status}"
assert r.status_code in [200, 206], (
f"Failed to download {path} from {url}: {r.status_code}"
)
async with aiofiles.open(
partial_path, "ab" if resume_byte_pos else "wb"
) as f:
while chunk := await r.content.read(8 * 1024 * 1024):
async for chunk in r.aiter_bytes(8 * 1024 * 1024):
n_read = n_read + (await f.write(chunk))
on_progress(n_read, length, False)

View File

@@ -10,18 +10,24 @@ from mlx.nn.layers.distributed import (
shard_linear,
sum_gradients,
)
from mlx_lm.models.cache import (
_BaseCache, # pyright: ignore[reportPrivateUsage]
)
from mlx_lm.models.deepseek_v3 import DeepseekV3MLP
from mlx_lm.models.deepseek_v3 import Model as DeepseekV3Model
from mlx_lm.models.deepseek_v32 import DeepseekV32MLP
from mlx_lm.models.deepseek_v32 import Model as DeepseekV32Model
from mlx_lm.models.glm4_moe import Model as Glm4MoeModel
from mlx_lm.models.glm4_moe import MoE
from mlx_lm.models.gpt_oss import GptOssMoeModel
from mlx_lm.models.gpt_oss import Model as GptOssModel
from mlx_lm.models.llama import Model as LlamaModel
from mlx_lm.models.minimax import Model as MiniMaxModel
from mlx_lm.models.ministral3 import Model as Ministral3Model
from mlx_lm.models.qwen3_moe import Model as Qwen3MoeModel
from mlx_lm.models.qwen3_moe import Qwen3MoeSparseMoeBlock
from mlx_lm.models.qwen3_next import Model as Qwen3NextModel
from mlx_lm.models.qwen3_next import Qwen3NextSparseMoeBlock
from exo.shared.types.worker.shards import (
PipelineShardMetadata,
)
from exo.shared.logging import logger
from exo.shared.types.worker.shards import PipelineShardMetadata
class _LayerCallable(Protocol):
@@ -91,8 +97,6 @@ class PipelineLastLayer(CustomMlxLayer):
x, *args, **kwargs
).arguments.get("cache", None)
assert cache is None or issubclass(type(cache), _BaseCache) # type: ignore
output: mx.array = self.original_layer(x, *args, **kwargs)
if self.r != self.s - 1:
@@ -100,7 +104,6 @@ class PipelineLastLayer(CustomMlxLayer):
output, (self.r + 1) % self.s, group=self.group
)
if cache is not None:
# This change happened upstream - check out mlx github somewhere??
cache.keys = mx.depends(cache.keys, output) # type: ignore[reportUnknownMemberType]
output = mx.distributed.all_gather(output, group=self.group)[-output.shape[0] :]
@@ -132,24 +135,6 @@ def _get_layers(inner_model_instance: nn.Module) -> list[_LayerCallable]:
return layers
def _set_layers(model: nn.Module, layers: list[_LayerCallable]) -> None:
inner_model_instance = _inner_model(model)
if hasattr(inner_model_instance, "layers"):
inner_model_instance.layers = layers
# Update DeepSeek V3 specific parameters when layers are shrunk
if isinstance(model, DeepseekV3Model) and hasattr(
inner_model_instance, "num_layers"
):
inner_model_instance.start_idx = 0
inner_model_instance.end_idx = len(layers)
inner_model_instance.num_layers = len(layers)
elif hasattr(inner_model_instance, "h"):
inner_model_instance.h = layers
else:
raise ValueError("Model must have either a 'layers' or 'h' attribute")
def pipeline_auto_parallel(
model: nn.Module,
group: mx.distributed.Group,
@@ -165,8 +150,7 @@ def pipeline_auto_parallel(
"""
inner_model_instance: nn.Module = _inner_model(model)
# Handle both model.layers and model.h cases
layers: list[_LayerCallable] = _get_layers(inner_model_instance)
layers = _get_layers(inner_model_instance)
start_layer, end_layer = model_shard_meta.start_layer, model_shard_meta.end_layer
device_rank, world_size = model_shard_meta.device_rank, model_shard_meta.world_size
@@ -180,6 +164,17 @@ def pipeline_auto_parallel(
group=group,
)
if isinstance(inner_model_instance, GptOssMoeModel):
inner_model_instance.layer_types = inner_model_instance.layer_types[ # type: ignore
start_layer:end_layer
]
inner_model_instance.swa_idx = inner_model_instance.layer_types.index( # type: ignore
"sliding_attention"
)
inner_model_instance.ga_idx = inner_model_instance.layer_types.index( # type: ignore
"full_attention"
)
_set_layers(model, layers)
assert isinstance(layers, list), (
@@ -204,18 +199,44 @@ def tensor_auto_parallel(
group=group,
)
segments: int = 1
def _all_to_sharded(path: str, weight: mx.array):
if path.endswith("bias"):
logger.info(f"Sharding bias for {path} - all to sharded")
return weight.ndim - 1, segments
return max(weight.ndim - 2, 0), segments
all_to_sharded_linear_in_place = partial(
shard_inplace,
sharding="all-to-sharded",
group=group,
)
sharded_to_all_linear_in_place = partial(
shard_inplace,
sharding="sharded-to-all",
sharding=_all_to_sharded, # type: ignore
group=group,
)
if isinstance(model, LlamaModel):
n = group.size()
def _sharded_to_all(path: str, weight: mx.array):
if path.endswith("bias"):
logger.info(f"Sharding bias for {path} - sharded to all")
weight /= n
return None
return -1, segments
sharded_to_all_linear_in_place = partial(
shard_inplace,
sharding=_sharded_to_all, # type: ignore
group=group,
)
if hasattr(model, "shard"):
try:
model.shard(group) # type: ignore
return model
except (AttributeError, TypeError, NameError):
pass
if isinstance(model, (LlamaModel, Ministral3Model)):
logger.warning("shouldn't be hit - upstream sharding exists")
tensor_parallel_sharding_strategy = LlamaShardingStrategy(
group,
all_to_sharded_linear,
@@ -223,7 +244,8 @@ def tensor_auto_parallel(
all_to_sharded_linear_in_place,
sharded_to_all_linear_in_place,
)
elif isinstance(model, DeepseekV3Model):
elif isinstance(model, (DeepseekV3Model, DeepseekV32Model)):
logger.warning("shouldn't be hit - upstream sharding exists")
tensor_parallel_sharding_strategy = DeepSeekShardingStrategy(
group,
all_to_sharded_linear,
@@ -231,7 +253,15 @@ def tensor_auto_parallel(
all_to_sharded_linear_in_place,
sharded_to_all_linear_in_place,
)
elif isinstance(model, Qwen3MoeModel):
elif isinstance(model, MiniMaxModel):
tensor_parallel_sharding_strategy = MiniMaxShardingStrategy(
group,
all_to_sharded_linear,
sharded_to_all_linear,
all_to_sharded_linear_in_place,
sharded_to_all_linear_in_place,
)
elif isinstance(model, (Qwen3MoeModel, Glm4MoeModel, Qwen3NextModel)):
tensor_parallel_sharding_strategy = QwenShardingStrategy(
group,
all_to_sharded_linear,
@@ -239,6 +269,15 @@ def tensor_auto_parallel(
all_to_sharded_linear_in_place,
sharded_to_all_linear_in_place,
)
elif isinstance(model, GptOssModel):
tensor_parallel_sharding_strategy = GptOssShardingStrategy(
group,
all_to_sharded_linear,
sharded_to_all_linear,
all_to_sharded_linear_in_place,
sharded_to_all_linear_in_place,
)
else:
raise ValueError(f"Unsupported model type: {type(model)}")
@@ -284,6 +323,32 @@ class LlamaShardingStrategy(TensorParallelShardingStrategy):
return model
def _set_layers(model: nn.Module, layers: list[_LayerCallable]) -> None:
inner_model_instance = _inner_model(model)
if hasattr(inner_model_instance, "layers"):
inner_model_instance.layers = layers
# Update DeepSeek V3 specific parameters when layers are shrunk
if isinstance(
model, (DeepseekV3Model, DeepseekV32Model, Glm4MoeModel)
) and hasattr(inner_model_instance, "num_layers"):
logger.info(
f"Setting num_layers to {len(layers)} for model {model.model.__class__.__name__}"
)
inner_model_instance.start_idx = 0
inner_model_instance.end_idx = len(layers)
inner_model_instance.num_layers = len(layers)
elif isinstance(model, Qwen3MoeModel):
logger.info(
f"Setting num_hidden_layers to {len(layers)} for model {model.model.__class__.__name__}"
)
inner_model_instance.num_hidden_layers = len(layers)
elif hasattr(inner_model_instance, "h"):
inner_model_instance.h = layers
else:
raise ValueError("Model must have either a 'layers' or 'h' attribute")
class DeepSeekShardingStrategy(TensorParallelShardingStrategy):
def shard_model(self, model: nn.Module) -> nn.Module:
model = cast(DeepseekV3Model, model)
@@ -304,7 +369,7 @@ class DeepSeekShardingStrategy(TensorParallelShardingStrategy):
layer.self_attn.num_heads //= self.N
# Shard the MLP
if isinstance(layer.mlp, DeepseekV3MLP):
if isinstance(layer.mlp, (DeepseekV3MLP, DeepseekV32MLP)):
layer.mlp.gate_proj = self.all_to_sharded_linear(layer.mlp.gate_proj)
layer.mlp.down_proj = self.sharded_to_all_linear(layer.mlp.down_proj)
layer.mlp.up_proj = self.all_to_sharded_linear(layer.mlp.up_proj)
@@ -338,6 +403,35 @@ class ShardedDeepseekV3MoE(CustomMlxLayer):
return y
class MiniMaxShardingStrategy(TensorParallelShardingStrategy):
def shard_model(self, model: nn.Module) -> nn.Module:
model = cast(MiniMaxModel, model)
for layer in model.layers:
# Shard the self attention
layer.self_attn.q_proj = self.all_to_sharded_linear(layer.self_attn.q_proj)
layer.self_attn.k_proj = self.all_to_sharded_linear(layer.self_attn.k_proj)
layer.self_attn.v_proj = self.all_to_sharded_linear(layer.self_attn.v_proj)
layer.self_attn.o_proj = self.sharded_to_all_linear(layer.self_attn.o_proj)
layer.self_attn.num_attention_heads //= self.N
layer.self_attn.num_key_value_heads //= self.N
# Shard the MoE. Shard in place since the MoE should be responsible
# for aggregating the results.
self.all_to_sharded_linear_in_place(
layer.block_sparse_moe.switch_mlp.gate_proj
)
self.sharded_to_all_linear_in_place(
layer.block_sparse_moe.switch_mlp.down_proj
)
self.all_to_sharded_linear_in_place(
layer.block_sparse_moe.switch_mlp.up_proj
)
layer.block_sparse_moe = ShardedQwenMoE(layer.block_sparse_moe) # pyright: ignore[reportAttributeAccessIssue, reportArgumentType]
layer.block_sparse_moe.sharding_group = self.group
return model
class QwenShardingStrategy(TensorParallelShardingStrategy):
def shard_model(self, model: nn.Module) -> nn.Module:
model = cast(Qwen3MoeModel, model)
@@ -352,11 +446,13 @@ class QwenShardingStrategy(TensorParallelShardingStrategy):
# Shard the MoE. Shard in place since the MoE should be responsible
# for aggregating the results.
if isinstance(layer.mlp, Qwen3MoeSparseMoeBlock):
if isinstance(
layer.mlp, (Qwen3MoeSparseMoeBlock, MoE, Qwen3NextSparseMoeBlock)
):
self.all_to_sharded_linear_in_place(layer.mlp.switch_mlp.gate_proj)
self.sharded_to_all_linear_in_place(layer.mlp.switch_mlp.down_proj)
self.all_to_sharded_linear_in_place(layer.mlp.switch_mlp.up_proj)
layer.mlp = ShardedQwenMoE(layer.mlp) # type: ignore
layer.mlp = ShardedQwenMoE(layer.mlp) # pyright: ignore[reportAttributeAccessIssue, reportArgumentType]
layer.mlp.sharding_group = self.group
# Shard the MLP
@@ -380,3 +476,50 @@ class ShardedQwenMoE(CustomMlxLayer):
if self.sharding_group is not None:
y = mx.distributed.all_sum(y, group=self.sharding_group)
return y
class GptOssShardingStrategy(TensorParallelShardingStrategy):
def shard_model(self, model: nn.Module) -> nn.Module:
model = cast(GptOssMoeModel, model)
for layer in model.layers:
layer.self_attn.q_proj = self.all_to_sharded_linear(layer.self_attn.q_proj)
layer.self_attn.k_proj = self.all_to_sharded_linear(layer.self_attn.k_proj)
layer.self_attn.v_proj = self.all_to_sharded_linear(layer.self_attn.v_proj)
layer.self_attn.o_proj = self.sharded_to_all_linear(layer.self_attn.o_proj)
layer.self_attn.num_attention_heads //= self.N
layer.self_attn.num_key_value_heads //= self.N
layer.self_attn.num_key_value_groups = (
layer.self_attn.num_attention_heads
// layer.self_attn.num_key_value_heads
)
layer.self_attn.sinks = layer.self_attn.sinks[
layer.self_attn.num_attention_heads
* self.group.rank() : layer.self_attn.num_attention_heads
* (self.group.rank() + 1)
]
self.all_to_sharded_linear_in_place(layer.mlp.experts.gate_proj)
self.sharded_to_all_linear_in_place(layer.mlp.experts.down_proj)
self.all_to_sharded_linear_in_place(layer.mlp.experts.up_proj)
layer.mlp = ShardedGptOssMoE(layer.mlp) # type: ignore
layer.mlp.sharding_group = self.group
return model
class ShardedGptOssMoE(CustomMlxLayer):
def __init__(self, layer: nn.Module):
super().__init__(layer)
self.sharding_group: mx.distributed.Group | None = None
def __call__(self, x: mx.array) -> mx.array:
if self.sharding_group is not None:
x = sum_gradients(self.sharding_group)(x)
y = self.original_layer(x)
if self.sharding_group is not None:
y = mx.distributed.all_sum(y, group=self.sharding_group)
return y

View File

@@ -4,7 +4,7 @@ import resource
import sys
import time
from pathlib import Path
from typing import Any, Final, cast
from typing import Any, cast
# Monkey-patch for transformers 5.x compatibility
# Kimi's tokenization_kimi.py imports bytes_to_unicode from the old location
@@ -20,7 +20,6 @@ except ImportError:
from mlx_lm.models.cache import KVCache, QuantizedKVCache, RotatingKVCache
from mlx_lm.models.deepseek_v3 import DeepseekV3Model
from mlx_lm.models.deepseek_v32 import Model as DeepseekV32Model
from mlx_lm.models.gpt_oss import Model as GptOssModel
from mlx_lm.tokenizer_utils import TokenizerWrapper
@@ -55,10 +54,7 @@ from exo.shared.types.worker.shards import (
ShardMetadata,
TensorShardMetadata,
)
from exo.worker.download.download_utils import (
build_model_path,
resolve_model_path_for_repo_sync,
)
from exo.worker.download.download_utils import build_model_path
from exo.worker.engines.mlx import Model
from exo.worker.engines.mlx.auto_parallel import (
pipeline_auto_parallel,
@@ -66,8 +62,6 @@ from exo.worker.engines.mlx.auto_parallel import (
)
from exo.worker.runner.bootstrap import logger
_GPT_OSS_TEMPLATE_FILENAME: Final[str] = "gpt_oss_template.jinja"
Group = mx.distributed.Group
# Needed for 8 bit model
resource.setrlimit(resource.RLIMIT_NOFILE, (2048, 4096))
@@ -216,75 +210,9 @@ def load_mlx_items(
set_wired_limit_for_model(get_weights_size(bound_instance.bound_shard))
add_missing_chat_templates(
bound_instance.bound_shard.model_meta.model_id, tokenizer, model
)
return cast(Model, model), tokenizer
def add_missing_chat_templates(
repo_id: str,
tokenizer: TokenizerWrapper,
model: nn.Module,
) -> None:
if isinstance(model, GptOssModel):
logger.info("Adding missing chat templates for gpt-oss model")
tokenizer.chat_template = _load_gpt_oss_chat_template()
if isinstance(model, DeepseekV32Model):
logger.info("Adding missing chat templates for deepseek-v32 model")
model_dir = "Missing model dir"
try:
import importlib.util
model_dir = resolve_model_path_for_repo_sync(repo_id)
module_path = model_dir / "encoding" / "encoding_dsv32.py"
spec = importlib.util.spec_from_file_location(
"encoding_dsv32", str(module_path)
)
if spec is None or spec.loader is None:
raise ImportError(f"Cannot find module encoding_dsv32 at {module_path}")
encoding_dsv32 = importlib.util.module_from_spec(spec)
spec.loader.exec_module(encoding_dsv32)
def apply_chat_template(messages: list[dict[str, Any]], **kwargs) -> str: # type: ignore
encode_config = dict(
thinking_mode="thinking",
drop_thinking=True,
add_default_bos_token=True,
)
return encoding_dsv32.encode_messages(messages, **encode_config) # type: ignore
tokenizer.apply_chat_template = apply_chat_template # type: ignore[method-assign]
except Exception as exc:
raise ImportError(
f"Failed to import encode_messages and parse_message_from_completion_text from {model_dir}/encoding_dsv32: {exc}"
) from exc
def _load_gpt_oss_chat_template() -> str:
"""
Load the GPT-OSS chat template by walking up from this module to the Exo package
root and resolving ``shared/models/gpt_oss_template.jinja`` from there.
This works for:
- a source checkout (``src/exo/...``),
- an installed package (``site-packages/exo/...``),
- a PyInstaller bundle where ``exo/shared/models`` is bundled intact.
"""
current_module = Path(__file__).resolve()
for parent in current_module.parents:
candidate = parent / "shared" / "models" / _GPT_OSS_TEMPLATE_FILENAME
if candidate.is_file():
return candidate.read_text(encoding="utf-8")
message = (
f"Unable to locate {_GPT_OSS_TEMPLATE_FILENAME!r} relative to {__file__!r}. "
"Ensure the exo/shared/models directory is available and bundled."
)
raise FileNotFoundError(message)
def shard_and_load(
shard_metadata: ShardMetadata,
group: Group,
@@ -438,6 +366,8 @@ def apply_chat_template(
tools=chat_task_data.tools,
)
logger.info(prompt)
return prompt
@@ -469,6 +399,11 @@ def make_kv_cache(
) -> list[KVCache | RotatingKVCache | QuantizedKVCache]:
assert hasattr(model, "layers")
# TODO: Do this for all models
if hasattr(model, "make_cache") and isinstance(model, GptOssModel):
logger.info("Using MLX LM's make cache")
return model.make_cache() # type: ignore
if max_kv_size is None:
if KV_CACHE_BITS is None:
logger.info("Using default KV cache")

View File

@@ -1,6 +1,15 @@
import time
from collections.abc import Generator
from functools import cache
import mlx.core as mx
from mlx_lm.models.gpt_oss import Model as GptOssModel
from openai_harmony import ( # pyright: ignore[reportMissingTypeStubs]
HarmonyEncodingName,
Role,
StreamableParser,
load_harmony_encoding,
)
from exo.shared.types.api import ChatCompletionMessageText
from exo.shared.types.chunks import TokenChunk
@@ -153,11 +162,19 @@ def main(
_check_for_debug_prompts(task_params.messages[0].content)
# Generate responses using the actual MLX generation
for response in mlx_generate(
mlx_generator = mlx_generate(
model=model,
tokenizer=tokenizer,
task=task_params,
):
)
# GPT-OSS specific parsing to match other model formats.
if isinstance(model, GptOssModel):
mlx_generator = parse_gpt_oss(mlx_generator)
# TODO: Add tool call parser here
for response in mlx_generator:
match response:
case GenerationResponse():
if shard_metadata.device_rank == 0:
@@ -207,6 +224,43 @@ def main(
break
@cache
def get_gpt_oss_encoding():
encoding = load_harmony_encoding(HarmonyEncodingName.HARMONY_GPT_OSS)
return encoding
def parse_gpt_oss(
responses: Generator[GenerationResponse],
) -> Generator[GenerationResponse]:
encoding = get_gpt_oss_encoding()
stream = StreamableParser(encoding, role=Role.ASSISTANT)
thinking = False
for response in responses:
stream.process(response.token)
delta = stream.last_content_delta
ch = stream.current_channel
if ch == "analysis" and not thinking:
thinking = True
yield response.model_copy(update={"text": "<think>"})
if ch != "analysis" and thinking:
thinking = False
yield response.model_copy(update={"text": "</think>"})
if delta:
yield response.model_copy(update={"text": delta})
if response.finish_reason is not None:
if thinking:
yield response.model_copy(update={"text": "</think>"})
yield response
break
EXO_RUNNER_MUST_FAIL = "EXO RUNNER MUST FAIL"
EXO_RUNNER_MUST_OOM = "EXO RUNNER MUST OOM"
EXO_RUNNER_MUST_TIMEOUT = "EXO RUNNER MUST TIMEOUT"

View File

@@ -1,47 +1,63 @@
import http.client
from anyio import create_task_group, to_thread
import anyio
import httpx
from anyio import create_task_group
from loguru import logger
from exo.shared.topology import Topology
from exo.shared.types.common import NodeId
REACHABILITY_ATTEMPTS = 3
async def check_reachability(
target_ip: str,
expected_node_id: NodeId,
self_node_id: NodeId,
out: dict[NodeId, set[str]],
client: httpx.AsyncClient,
) -> None:
"""Check if a node is reachable at the given IP and verify its identity."""
if ":" in target_ip:
# TODO: use real IpAddress types
target_ip = f"[{target_ip}]"
url = f"http://{target_ip}:52415/node_id"
def _fetch_remote_node_id() -> NodeId | None:
connection = http.client.HTTPConnection(target_ip, 52415, timeout=1)
remote_node_id = None
last_error = None
for _ in range(REACHABILITY_ATTEMPTS):
try:
connection.request("GET", "/node_id")
response = connection.getresponse()
if response.status != 200:
return None
r = await client.get(url)
if r.status_code != 200:
await anyio.sleep(1)
continue
body = response.read().decode("utf-8").strip()
body = r.text.strip().strip('"')
if not body:
await anyio.sleep(1)
continue
# Strip quotes if present (JSON string response)
if body.startswith('"') and body.endswith('"') and len(body) >= 2:
body = body[1:-1]
remote_node_id = NodeId(body)
break
return NodeId(body) or None
except OSError:
return None
except http.client.HTTPException:
return None
finally:
connection.close()
except (
httpx.ConnectError,
httpx.ConnectTimeout,
httpx.ReadTimeout,
httpx.RemoteProtocolError,
) as e:
last_error = e
await anyio.sleep(1)
remote_node_id = await to_thread.run_sync(_fetch_remote_node_id)
if remote_node_id is None:
return
if remote_node_id == self_node_id:
else:
if last_error is not None:
logger.warning(
f"connect error {type(last_error).__name__} from {target_ip} after {REACHABILITY_ATTEMPTS} attempts; treating as down"
)
else:
logger.warning(
f"malformed response from {target_ip} after {REACHABILITY_ATTEMPTS} attempts; treating as down"
)
return
if remote_node_id != expected_node_id:
@@ -61,18 +77,33 @@ async def check_reachable(
topology: Topology, self_node_id: NodeId
) -> dict[NodeId, set[str]]:
"""Check which nodes are reachable and return their IPs."""
reachable: dict[NodeId, set[str]] = {}
async with create_task_group() as tg:
# these are intentionally httpx's defaults so we can tune them later
timeout = httpx.Timeout(timeout=5.0)
limits = httpx.Limits(
max_connections=100,
max_keepalive_connections=20,
keepalive_expiry=5,
)
async with (
httpx.AsyncClient(timeout=timeout, limits=limits) as client,
create_task_group() as tg,
):
for node in topology.list_nodes():
if not node.node_profile:
continue
if node.node_id == self_node_id:
continue
for iface in node.node_profile.network_interfaces:
tg.start_soon(
check_reachability,
iface.ip_address,
node.node_id,
self_node_id,
reachable,
client,
)
return reachable

View File

@@ -89,6 +89,12 @@ async def assert_downloads():
await sd.ensure_shard(
await build_full_shard(MODEL_CARDS["gpt-oss-20b-4bit"].model_id)
)
await sd.ensure_shard(
await build_full_shard(MODEL_CARDS["glm-4.7-8bit-gs32"].model_id)
)
await sd.ensure_shard(
await build_full_shard(MODEL_CARDS["minimax-m2.1-8bit"].model_id)
)
async def ring_backend(test: Tests):

1294
uv.lock generated
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