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16 Commits

Author SHA1 Message Date
Evan
36dadd0082 add glm-47 and deepseek-v32 2026-01-13 13:24:25 +00:00
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
Jake Hillion
007eb80029 nix: enable cachix
Enable cachix and push to it in the pipeline.yml workflow. This won't
cache a huge amount yet but will automatically extend our caching as we
build more of the repo with Nix in CI. It can also be used by local
users by accepting our cache to improve the speed of local builds.

Test plan:
- CI
2026-01-12 17:24:59 +01:00
Jake Hillion
8d7b6789b3 dashboard: show disk usage for completed models
The downloads dashboard showed "Completed" for finished model downloads
but provided no indication of how much disk space each model or the
total models on a node were using.

Added total_bytes field to DownloadCompleted type so the size is
preserved when a download completes. Updated the dashboard to display
the model size next to "Completed" status (e.g., "Completed (251.1GB)")
and a total disk usage line below the model count for each node (e.g.,
"502.2GB on disk").

Test plan:
- Ran unit tests for download apply and planning logic
- Type checked all modified files with basedpyright
2026-01-12 16:34:29 +01:00
Jake Hillion
3c5b7ea670 ci: add workflow_dispatch trigger to build-app
Build app is the most convenient way to get a DMG for testing, but
currently it's a bit limited. You have to push to test-app every time
which is far from ideal and requires a bit too much force pushing for my
liking.

Add the workflow_dispatch trigger. This adds a button in the actions UI
to trigger a workflow for a named branch, which means you can use your
normal dev branch instead of having to push to test-app. We'll leave
that behaviour there for now too, though it may change in future.

Filter on `"${{ github.event_name }}" == "workflow_dispatch"` and set
those to alpha as well. Will verify by pushing the first version from
`main` just in case. Unfortunately we do have to merge this before we
can test it.

Test plan:
- Looking really hard.
2026-01-12 12:14:21 +01:00
PG
b74a610537 Add a basic documentation to the api interface (#1122)
## Motivation

Adds basic api documentation

## Changes

- Add docs/api.md
- Modify README.md
2026-01-11 18:44:40 +00:00
Jake Hillion
18c4e49f91 nix: put treefmt in devshell
treefmt is a useful to be able to access directly for some formatters like
`jj fix`. Expose it in the devshell.

Test plan:
- Used with `jj fix` on a large branch. It worked.
2026-01-09 17:53:50 +01:00
Sami Khan
d85b5d3781 feat: uninstall button (#1077)
## Motivation

https://github.com/exo-explore/exo/issues/1075

## Changes

- Added in-app "Uninstall" option under Advanced menu that cleanly
removes all system components
- Added NetworkSetupHelper.uninstall() to remove LaunchDaemon, scripts,
logs, and restore network settings
- Added LaunchAtLoginHelper.disable() to unregister from login items
- Created standalone uninstall-exo.sh script for users who already
deleted the app
- Added uninstall documentation to README

<img width="386" height="577" alt="image"
src="https://github.com/user-attachments/assets/6bbcd18a-992a-409d-8791-ed5e13bbcfe0"
/>
<img width="372" height="432" alt="image"
src="https://github.com/user-attachments/assets/ee76b45d-c111-4807-ab28-3f2f20e01140"
/>


## Why It Works

The in-app uninstaller runs a privileged shell script (via AppleScript)
to launchctl bootout the daemon, remove files, and restore the
"Automatic" network location. The standalone script provides the same
cleanup for users who already deleted the app.

## Test Plan

### Manual Testing
Hardware: MacBook Pro
- Built and ran app, verified LaunchDaemon and network location were
created
- Used in-app Uninstall, verified all components removed and network
restored to Automatic
- Rebuilt app, quit normally, ran sudo ./uninstall-exo.sh, verified same
cleanup

### Automated Testing
N/A

---------

Co-authored-by: Evan <evanev7@gmail.com>
2026-01-09 14:49:08 +00:00
Evan Quiney
caafc48693 Forward tools to the models chat template properly (#1106)
We did not properly forward tools to the chat template before. This is not a full tool calling impl - but it should improve things slightly.

## Changes made

Pass tools to the hf tokenizers chat template
Join message chunks into a larger message (opencode does this sometimes - we were ignoring before)

## Future work

We need to parse the model output and normalise the return format to be compatible with the openai api.
2026-01-09 13:28:41 +00:00
Evan
cca8c9984a cleanup unused dependencies
we have a lot of dependencies we have no intent of using. kill them with
fire!

## testing
exo still launches and does the worst inference known to man on my Qwen3
instance. tests pass too!!
2026-01-09 13:11:58 +00:00
Sami Khan
d1e88def42 scrollbars fixed (#1113)
## Motivation

Fixes https://github.com/exo-explore/exo/issues/1107 - Horizontal
scrollbar always appears in instances section, and vertical scrollbar
appears too early (with just 1-2 instances on large screens).


## Changes

- Added overflow-x-hidden to remove horizontal scrollbar
- Added xl:max-h-96 for responsive vertical height (384px on xl+ screens
vs 288px default)
- Added py-px to accommodate corner accent decorations that extend 1px
outside cards

## Why It Works

- overflow-x-hidden prevents horizontal scroll regardless of content
- Larger max-height on xl screens fits 2 instances without scrollbar;
3rd triggers it
- 1px vertical padding accommodates the -top-px/-bottom-px positioned
corner accents that caused tiny overflow

## Test Plan

### Manual Testing
<img width="1190" height="868" alt="image"
src="https://github.com/user-attachments/assets/2a582328-5b4f-4490-a488-52106f2e85ef"
/>

### Automated Testing
N/A
2026-01-09 12:51:05 +00:00
Sami Khan
59e7594e34 UNKNOWN to PREPARING (#1112)
## Motivation

The "UNKNOWN" status shown when first launching an instance is confusing
and unhelpful. "PREPARING" better describes what's actually happening.

![telegram-cloud-photo-size-4-5981245965962251168-x](https://github.com/user-attachments/assets/65b0802b-fb64-4fa7-bff7-c13757035b3a)


## Changes

- Renamed status from "UNKNOWN" to "PREPARING" in dashboard
(+page.svelte)
- Renamed unknown state to preparing in macOS app
(InstanceViewModel.swift, InstanceRowView.swift)

## Why It Works

The status appears when an instance exists but runners haven't reported
status yet. "PREPARING" accurately describes this transitional state.

## Test Plan

### Manual Testing
Hardware: MacBook Pro
<img width="319" height="200" alt="image"
src="https://github.com/user-attachments/assets/9a1c3caf-026d-47ea-80d1-63c6e41d93aa"
/>

### Automated Testing
N/A
2026-01-09 11:46:51 +00:00
Chris A
c65320acd3 Fix mlx seed (#1094)
## Motivation

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

## Changes

<!-- Describe what you changed in detail -->

## Why It Works

<!-- Explain why your approach solves the problem -->

## Test Plan

### Manual Testing
<!-- Hardware: (e.g., MacBook Pro M1 Max 32GB, Mac Mini M2 16GB,
connected via Thunderbolt 4) -->
<!-- What you did: -->
<!-- - -->

### Automated Testing
<!-- Describe changes to automated tests, or how existing tests cover
this change -->
<!-- - -->

---------

Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
Co-authored-by: Ryuichi Leo Takashige <leo@exolabs.net>
2026-01-09 01:40:15 +00:00
35 changed files with 2534 additions and 1365 deletions

View File

@@ -1,6 +1,7 @@
name: Build EXO macOS DMG
on:
workflow_dispatch:
push:
tags:
- "v*"
@@ -35,7 +36,7 @@ jobs:
- name: Derive release version from tag
run: |
if [[ "$GITHUB_REF_NAME" == "test-app" ]]; then
if [[ "$GITHUB_REF_NAME" == "test-app" || "${{ github.event_name }}" == "workflow_dispatch" ]]; then
VERSION="0.0.0-alpha.0"
echo "IS_ALPHA=true" >> $GITHUB_ENV
else

View File

@@ -20,6 +20,12 @@ jobs:
with:
nix_path: nixpkgs=channel:nixos-unstable
- uses: cachix/cachix-action@v14
name: Configure Cachix
with:
name: exo
authToken: "${{ secrets.CACHIX_AUTH_TOKEN }}"
- name: Configure git user
run: |
git config --local user.email "github-actions@users.noreply.github.com"
@@ -88,9 +94,19 @@ jobs:
- uses: ./.github/actions/typecheck
nix-flake-check:
name: Check Nix flake
runs-on: ubuntu-latest
nix:
name: Build and check (${{ matrix.system }})
runs-on: ${{ matrix.runner }}
strategy:
fail-fast: false
matrix:
include:
- runner: macos-26
system: aarch64-darwin
- runner: ubuntu-latest
system: x86_64-linux
- runner: ubuntu-24.04-arm
system: aarch64-linux
steps:
- name: Checkout repository
uses: actions/checkout@v4
@@ -101,83 +117,20 @@ jobs:
with:
nix_path: nixpkgs=channel:nixos-unstable
- name: Run nix flake check
run: |
nix flake check
shell: bash
- uses: cachix/cachix-action@v14
name: Configure Cachix
with:
name: exo
authToken: "${{ secrets.CACHIX_AUTH_TOKEN }}"
# 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: Build all Nix outputs
run: |
nix flake show --json | jq -r '
[
(.packages."${{ matrix.system }}" // {} | keys[] | ".#packages.${{ matrix.system }}.\(.)"),
(.devShells."${{ matrix.system }}" // {} | keys[] | ".#devShells.${{ matrix.system }}.\(.)")
] | .[]
' | xargs nix build
- name: Run nix flake check
run: nix flake check

1
.gitignore vendored
View File

@@ -16,6 +16,7 @@ digest.txt
*.xcuserdatad/
**/.DS_Store
app/EXO/build/
dist/
# rust

View File

@@ -0,0 +1,156 @@
"""Type stubs for mlx_lm.models.deepseek_v3"""
from dataclasses import dataclass
from typing import Any, Dict, Optional
import mlx.core as mx
import mlx.nn as nn
from .base import BaseModelArgs
from .switch_layers import SwitchGLU
@dataclass
class ModelArgs(BaseModelArgs):
model_type: str
vocab_size: int
hidden_size: int
intermediate_size: int
moe_intermediate_size: int
num_hidden_layers: int
num_attention_heads: int
num_key_value_heads: int
n_shared_experts: Optional[int]
n_routed_experts: Optional[int]
routed_scaling_factor: float
kv_lora_rank: int
q_lora_rank: Optional[int]
qk_rope_head_dim: int
v_head_dim: int
qk_nope_head_dim: int
topk_method: str
scoring_func: str
norm_topk_prob: bool
n_group: int
topk_group: int
num_experts_per_tok: int
moe_layer_freq: int
first_k_dense_replace: int
max_position_embeddings: int
rms_norm_eps: float
rope_theta: float
rope_scaling: Optional[Dict[str, Any]]
attention_bias: bool
class DeepseekV3Attention(nn.Module):
config: ModelArgs
hidden_size: int
num_heads: int
max_position_embeddings: int
rope_theta: float
q_lora_rank: Optional[int]
qk_rope_head_dim: int
kv_lora_rank: int
v_head_dim: int
qk_nope_head_dim: int
q_head_dim: int
scale: float
q_proj: nn.Linear
q_a_proj: nn.Linear
q_a_layernorm: nn.RMSNorm
q_b_proj: nn.Linear
kv_a_proj_with_mqa: nn.Linear
kv_a_layernorm: nn.RMSNorm
kv_b_proj: nn.Linear
o_proj: nn.Linear
rope: Any
def __init__(self, config: ModelArgs) -> None: ...
def __call__(
self,
x: mx.array,
mask: Optional[mx.array] = None,
cache: Optional[Any] = None,
) -> mx.array: ...
class DeepseekV3MLP(nn.Module):
config: ModelArgs
hidden_size: int
intermediate_size: int
gate_proj: nn.Linear
up_proj: nn.Linear
down_proj: nn.Linear
def __init__(
self,
config: ModelArgs,
hidden_size: Optional[int] = None,
intermediate_size: Optional[int] = None,
) -> None: ...
def __call__(self, x: mx.array) -> mx.array: ...
class MoEGate(nn.Module):
config: ModelArgs
top_k: int
norm_topk_prob: bool
n_routed_experts: Optional[int]
routed_scaling_factor: float
n_group: int
topk_group: int
weight: mx.array
e_score_correction_bias: mx.array
def __init__(self, config: ModelArgs) -> None: ...
def __call__(self, x: mx.array) -> tuple[mx.array, mx.array]: ...
class DeepseekV3MoE(nn.Module):
config: ModelArgs
num_experts_per_tok: int
switch_mlp: SwitchGLU
gate: MoEGate
shared_experts: DeepseekV3MLP
sharding_group: Optional[mx.distributed.Group]
def __init__(self, config: ModelArgs) -> None: ...
def __call__(self, x: mx.array) -> mx.array: ...
class DeepseekV3DecoderLayer(nn.Module):
self_attn: DeepseekV3Attention
mlp: DeepseekV3MLP | DeepseekV3MoE
input_layernorm: nn.RMSNorm
post_attention_layernorm: nn.RMSNorm
def __init__(self, config: ModelArgs, layer_idx: int) -> None: ...
def __call__(
self,
x: mx.array,
mask: Optional[mx.array] = None,
cache: Optional[Any] = None,
) -> mx.array: ...
class DeepseekV3Model(nn.Module):
vocab_size: int
embed_tokens: nn.Embedding
layers: list[DeepseekV3DecoderLayer]
norm: nn.RMSNorm
def __init__(self, config: ModelArgs) -> None: ...
def __call__(
self,
x: mx.array,
cache: Optional[Any] = None,
) -> mx.array: ...
class Model(nn.Module):
model_type: str
model: DeepseekV3Model
lm_head: nn.Linear
def __init__(self, config: ModelArgs) -> None: ...
def __call__(
self,
inputs: mx.array,
cache: Optional[Any] = None,
) -> mx.array: ...
def sanitize(self, weights: dict[str, Any]) -> dict[str, Any]: ...
@property
def layers(self) -> list[DeepseekV3DecoderLayer]: ...

View File

@@ -57,6 +57,11 @@ class SwiGLU(nn.Module):
def __call__(self, x, gate): ...
class SwitchGLU(nn.Module):
gate_proj: SwitchLinear
up_proj: SwitchLinear
down_proj: SwitchLinear
activation: SwiGLU
def __init__(
self,
input_dims: int,

View File

@@ -4,6 +4,7 @@ This type stub file was generated by pyright.
from functools import partial
from pathlib import Path
from typing import Any
from transformers import PreTrainedTokenizerFast
@@ -103,37 +104,55 @@ class TokenizerWrapper:
Accessing any attribute other than the ``detokenizer`` is forwarded to the
huggingface tokenizer.
"""
def __init__(self, tokenizer, detokenizer_class=..., eos_token_ids=...) -> None: ...
def add_eos_token(self, token: str): # -> None:
...
@property
def has_thinking(self): # -> bool:
...
@property
def think_start(self): # -> str | None:
...
@property
def think_end(self): # -> str | None:
...
@property
def has_tool_calling(self): # -> bool:
...
@property
def tool_call_start(self): # -> str | None:
...
@property
def tool_call_end(self): # -> str | None:
...
@property
def detokenizer(self): # -> NaiveStreamingDetokenizer:
"""
Get a stateful streaming detokenizer.
"""
def __getattr__(self, attr): # -> set[Any] | Any:
...
def __setattr__(self, attr, value): # -> None:
...
_tokenizer: PreTrainedTokenizerFast
eos_token_id: int | None
eos_token: str | None
bos_token_id: int | None
bos_token: str | None
vocab_size: int
all_special_tokens: list[str]
def __init__(
self,
tokenizer: Any,
detokenizer_class: Any = ...,
eos_token_ids: list[int] | None = ...,
chat_template: Any = ...,
tool_parser: Any = ...,
tool_call_start: str | None = ...,
tool_call_end: str | None = ...,
) -> None: ...
def encode(self, text: str, **kwargs: Any) -> list[int]: ...
def decode(self, token_ids: list[int], **kwargs: Any) -> str: ...
def apply_chat_template(
self,
messages: list[dict[str, Any]],
tokenize: bool = False,
add_generation_prompt: bool = False,
tools: Any = None,
**kwargs: Any,
) -> str: ...
def get_vocab(self) -> dict[str, int]: ...
def add_eos_token(self, token: str) -> None: ...
@property
def has_thinking(self) -> bool: ...
@property
def think_start(self) -> str | None: ...
@property
def think_end(self) -> str | None: ...
@property
def has_tool_calling(self) -> bool: ...
@property
def tool_call_start(self) -> str | None: ...
@property
def tool_call_end(self) -> str | None: ...
@property
def detokenizer(self) -> NaiveStreamingDetokenizer:
"""Get a stateful streaming detokenizer."""
def __getattr__(self, attr: str) -> Any: ...
def __setattr__(self, attr: str, value: Any) -> None: ...
class NewlineTokenizer(PreTrainedTokenizerFast):
"""A tokenizer that replaces newlines with <n> and <n> with new line."""
@@ -146,18 +165,11 @@ class NewlineTokenizer(PreTrainedTokenizerFast):
def batch_decode(self, *args, **kwargs): # -> list[str]:
...
def load_tokenizer(
def load(
model_path: Path,
tokenizer_config_extra=...,
return_tokenizer=...,
eos_token_ids=...,
) -> (
TokenizerWrapper
| type[SPMStreamingDetokenizer]
| partial[SPMStreamingDetokenizer]
| type[BPEStreamingDetokenizer]
| type[NaiveStreamingDetokenizer]
):
tokenizer_config_extra: dict[str, Any] | None = None,
eos_token_ids: list[int] | int | None = None,
) -> TokenizerWrapper:
"""Load a huggingface tokenizer and try to infer the type of streaming
detokenizer to use.
@@ -165,4 +177,7 @@ def load_tokenizer(
a Hugging Face repo ID.
"""
def no_bos_or_eos(sequence: list, bos: int, eos: int) -> list: ...
# Alias for backward compatibility
load_tokenizer = load
def no_bos_or_eos(sequence: list[int], bos: int, eos: int) -> list[int]: ...

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

41
MISSED_THINGS.md Normal file
View File

@@ -0,0 +1,41 @@
# Missed things
[X] Log EXO_LIBP2P_NAMESPACE on start in exo/main.py
[X] Ordering of warmup was changed, which is wrong. It was changed to rank < n-1, then rank=n-1. It should be rank!=0 then rank=0 (this matches the auto_parallel implementation. NOTE: we use a different convention to mlx-lm, our terminal rank is rank=n-1 whereas mlx-lm is rank=0 hence i can see why this was changed wrongly).
[X] Downloads keying by model_id not shard_metadata (worker/plan.py, worker/main.py).
[X] Fetching download status of all models on start
[X] Deduplication of tasks in plan_step.
[X] resolve_allow_patterns should just be wildcard now.
[] no mx_barrier in genreate.py mlx_generate at the end.
[] cache assertion not needed in auto_parallel.py PipelineLastLayer.
[] GPTOSS support dropped in auto_parallel.py.
[] sharding changed "all-to-sharded" became _all_to_sharded in auto_parallel.py.
[] same as above with "sharded-to-all" became _sharded_to_all in auto_parallel.py.
[] Dropped support for Ministral3Model, DeepseekV32Model, Glm4MoeModel, Qwen3NextModel, GptOssMode in auto_parallel.py.
[] Dropped prefill/decode code in auto_parallel.py and utils_mlx.py.
[X] KV_CACHE_BITS should be None to disable quantized KV cache.
[] Dropped _set_nofile_limit in utils_mlx.py.
[] We have group optional in load_mlx_items in utils_mlx.py.
[] Dropped add_missing_chat_templates for GptOss in load_mlx_items in utils_mlx.py.
[] Dropped model.make_cache in make_kv_cache in utils_mlx.py.
[X] We put cache limit back in utils_mlx.py.
[] topology.py remove_node removes the connections after checking if node is is in self._node_id_to_rx_id_map. on beta_1 it checks after, so would remove stale connections I guess?
[] Missing Glm 4.7 model cards (this isn't ready yet but should be picked up, probably create an issue... the blocker is transforemrs version doesn't support the tokenizer for Glm 4.7. rc-1 does but we can't upgrade as it breaks other things.)
[] try-except in _command_processor only excepts ValueError. This was silently failing leading to un-debuggable errors (we had a KeyError that was happening ). Changed this to catch Exception instead of ValueError. See exo-v2 89ae38405e0052e3c22405daf094b065878aa873 and fb99fea69b5a39017efc90c5dad0072e677455f0.
[X] In placement.py, place_instance no longer looks at model_meta.supports_tensor and check if this tensor parallel number of nodes is supported by the model's tensor dimensions.
[X] In placement.py, place_instanec, we no longer have the special case to exclude DeepSeek v3.1 pipeline parallel (it doesn't work).
[] logger.warning("You have likely selected ibv for a single node instance; falling back to MlxRing") was changed to debug. That will spam this warning since it happens every time we query instance previews.
[X] In placement_utils.py, get_mlx_jaccl_coordinators, We no longer prioritise Jaccl Coordinator IP. Now it picks the first one, which is unstable (Jaccl coordinator over TB5 is unstable).
[X] Downloads keying by model_id not shard_metadata (worker/plan.py, worker/main.py).
[X] Fetching download status of all models on start
[X] Deduplication of tasks in plan_step.
[X] resolve_allow_patterns should just be wildcard now.
[X] KV_CACHE_BITS should be None to disable quantized KV cache.
[X] We put cache limit back in utils_mlx.py.
[X] In placement.py, place_instance no longer looks at model_meta.supports_tensor and check if this tensor parallel number of nodes is supported by the model's tensor dimensions.
[X] In placement.py, place_instanec, we no longer have the special case to exclude DeepSeek v3.1 pipeline parallel (it doesn't work).
[X] In placement_utils.py, get_mlx_jaccl_coordinators, We no longer prioritise Jaccl Coordinator IP. Now it picks the first one, which is unstable (Jaccl coordinator over TB5 is unstable).

View File

@@ -166,6 +166,24 @@ Download the latest build here: [EXO-latest.dmg](https://assets.exolabs.net/EXO-
The app will ask for permission to modify system settings and install a new Network profile. Improvements to this are being worked on.
#### Uninstalling the macOS App
The recommended way to uninstall is through the app itself: click the menu bar icon → Advanced → Uninstall. This cleanly removes all system components.
If you've already deleted the app, you can run the standalone uninstaller script:
```bash
sudo ./app/EXO/uninstall-exo.sh
```
This removes:
- Network setup LaunchDaemon
- Network configuration script
- Log files
- The "exo" network location
**Note:** You'll need to manually remove EXO from Login Items in System Settings → General → Login Items.
---
### Enabling RDMA on macOS
@@ -287,7 +305,10 @@ curl -X DELETE http://localhost:52415/instance/YOUR_INSTANCE_ID
- List all models: `curl http://localhost:52415/models`
- Inspect instance IDs and deployment state: `curl http://localhost:52415/state`
For further details, see API types and endpoints in [src/exo/master/api.py](src/exo/master/api.py).
For further details, see:
- API basic documentation in [docs/api.md](docs/api.md).
- API types and endpoints in [src/exo/master/api.py](src/exo/master/api.py).
---

View File

@@ -18,10 +18,11 @@ struct ContentView: View {
@State private var deletingInstanceIDs: Set<String> = []
@State private var showAllNodes = false
@State private var showAllInstances = false
@State private var showAdvanced = false
@State private var showDebugInfo = false
@State private var bugReportInFlight = false
@State private var bugReportMessage: String?
@State private var showAdvancedOptions = false
@State private var uninstallInProgress = false
@State private var pendingNamespace: String = ""
var body: some View {
@@ -255,13 +256,7 @@ struct ContentView: View {
Divider()
.padding(.vertical, 4)
}
controlButton(title: "Check for Updates") {
updater.checkForUpdates()
}
.padding(.bottom, 8)
advancedOptionsSection
.padding(.bottom, 8)
debugSection
advancedSection
.padding(.bottom, 8)
controlButton(title: "Quit", tint: .secondary) {
controller.stop()
@@ -270,6 +265,54 @@ struct ContentView: View {
}
}
private var advancedSection: some View {
VStack(alignment: .leading, spacing: 6) {
HStack {
Text("Advanced")
.font(.caption)
.foregroundColor(.secondary)
Spacer()
collapseButton(isExpanded: $showAdvanced)
}
.animation(nil, value: showAdvanced)
if showAdvanced {
VStack(alignment: .leading, spacing: 8) {
VStack(alignment: .leading, spacing: 4) {
Text("Cluster Namespace")
.font(.caption2)
.foregroundColor(.secondary)
HStack {
TextField("optional", text: $pendingNamespace)
.textFieldStyle(.roundedBorder)
.font(.caption2)
.onAppear {
pendingNamespace = controller.customNamespace
}
Button("Save & Restart") {
controller.customNamespace = pendingNamespace
if controller.status == .running || controller.status == .starting {
controller.restart()
}
}
.font(.caption2)
.disabled(pendingNamespace == controller.customNamespace)
}
}
HoverButton(title: "Check for Updates", small: true) {
updater.checkForUpdates()
}
debugSection
HoverButton(title: "Uninstall", tint: .red, small: true) {
showUninstallConfirmationAlert()
}
.disabled(uninstallInProgress)
}
.transition(.opacity)
}
}
.animation(.easeInOut(duration: 0.25), value: showAdvanced)
}
private func controlButton(title: String, tint: Color = .primary, action: @escaping () -> Void)
-> some View
{
@@ -396,57 +439,16 @@ struct ContentView: View {
}
}
private var advancedOptionsSection: some View {
VStack(alignment: .leading, spacing: 6) {
HStack {
Text("Advanced Options")
.font(.caption)
.foregroundColor(.secondary)
Spacer()
collapseButton(isExpanded: $showAdvancedOptions)
}
.animation(nil, value: showAdvancedOptions)
if showAdvancedOptions {
VStack(alignment: .leading, spacing: 8) {
VStack(alignment: .leading, spacing: 4) {
Text("Cluster Namespace")
.font(.caption2)
.foregroundColor(.secondary)
HStack {
TextField("optional", text: $pendingNamespace)
.textFieldStyle(.roundedBorder)
.font(.caption2)
.onAppear {
pendingNamespace = controller.customNamespace
}
Button("Save & Restart") {
controller.customNamespace = pendingNamespace
if controller.status == .running || controller.status == .starting {
controller.restart()
}
}
.font(.caption2)
.disabled(pendingNamespace == controller.customNamespace)
}
}
}
.transition(.opacity)
}
}
.animation(.easeInOut(duration: 0.25), value: showAdvancedOptions)
}
private var debugSection: some View {
VStack(alignment: .leading, spacing: 6) {
HStack {
Text("Debug Info")
.font(.caption)
.foregroundColor(.secondary)
Spacer()
collapseButton(isExpanded: $showDebugInfo)
VStack(alignment: .leading, spacing: 4) {
HoverButton(
title: "Debug Info",
tint: .primary,
trailingSystemImage: showDebugInfo ? "chevron.up" : "chevron.down",
small: true
) {
showDebugInfo.toggle()
}
.animation(nil, value: showDebugInfo)
if showDebugInfo {
VStack(alignment: .leading, spacing: 4) {
Text("Version: \(buildTag)")
@@ -463,6 +465,7 @@ struct ContentView: View {
sendBugReportButton
.padding(.top, 6)
}
.padding(.leading, 8)
.transition(.opacity)
}
}
@@ -604,6 +607,88 @@ struct ContentView: View {
bugReportInFlight = false
}
private func showUninstallConfirmationAlert() {
let alert = NSAlert()
alert.messageText = "Uninstall EXO"
alert.informativeText = """
This will remove EXO and all its system components:
• Network configuration daemon
• Launch at login registration
• EXO network location
The app will be moved to Trash.
"""
alert.alertStyle = .warning
alert.addButton(withTitle: "Uninstall")
alert.addButton(withTitle: "Cancel")
// Style the Uninstall button as destructive
if let uninstallButton = alert.buttons.first {
uninstallButton.hasDestructiveAction = true
}
let response = alert.runModal()
if response == .alertFirstButtonReturn {
performUninstall()
}
}
private func performUninstall() {
uninstallInProgress = true
// Stop EXO process first
controller.cancelPendingLaunch()
controller.stop()
stateService.stopPolling()
// Run the privileged uninstall on a background thread
// Using .utility QoS to avoid priority inversion with NSAppleScript's subprocess
DispatchQueue.global(qos: .utility).async {
do {
// Remove network setup daemon and components (requires admin privileges)
try NetworkSetupHelper.uninstall()
DispatchQueue.main.async {
// Unregister from launch at login
LaunchAtLoginHelper.disable()
// Move app to trash
self.moveAppToTrash()
// Quit the app
DispatchQueue.main.asyncAfter(deadline: .now() + 0.5) {
NSApplication.shared.terminate(nil)
}
}
} catch {
DispatchQueue.main.async {
self.showErrorAlert(message: error.localizedDescription)
self.uninstallInProgress = false
}
}
}
}
private func showErrorAlert(message: String) {
let alert = NSAlert()
alert.messageText = "Uninstall Failed"
alert.informativeText = message
alert.alertStyle = .critical
alert.addButton(withTitle: "OK")
alert.runModal()
}
private func moveAppToTrash() {
guard let appURL = Bundle.main.bundleURL as URL? else { return }
do {
try FileManager.default.trashItem(at: appURL, resultingItemURL: nil)
} catch {
// If we can't trash the app, that's OK - user can do it manually
// The important system components have already been cleaned up
}
}
private var buildTag: String {
Bundle.main.infoDictionary?["EXOBuildTag"] as? String ?? "unknown"
}
@@ -617,14 +702,27 @@ private struct HoverButton: View {
let title: String
let tint: Color
let trailingSystemImage: String?
let small: Bool
let action: () -> Void
init(
title: String, tint: Color = .primary, trailingSystemImage: String? = nil,
small: Bool = false, action: @escaping () -> Void
) {
self.title = title
self.tint = tint
self.trailingSystemImage = trailingSystemImage
self.small = small
self.action = action
}
@State private var isHovering = false
var body: some View {
Button(action: action) {
HStack {
Text(title)
.font(small ? .caption : nil)
Spacer()
if let systemName = trailingSystemImage {
Image(systemName: systemName)
@@ -632,8 +730,8 @@ private struct HoverButton: View {
}
}
.frame(maxWidth: .infinity, alignment: .leading)
.padding(.vertical, 6)
.padding(.horizontal, 8)
.padding(.vertical, small ? 4 : 6)
.padding(.horizontal, small ? 6 : 8)
.background(
RoundedRectangle(cornerRadius: 6)
.fill(

View File

@@ -132,6 +132,24 @@ struct EXOApp: App {
}
}
/// Helper for managing EXO's launch-at-login registration
enum LaunchAtLoginHelper {
private static let logger = Logger(subsystem: "io.exo.EXO", category: "LaunchAtLogin")
/// Unregisters EXO from launching at login
static func disable() {
guard SMAppService.mainApp.status == .enabled else { return }
do {
try SMAppService.mainApp.unregister()
logger.info("Unregistered EXO from launch at login")
} catch {
logger.error(
"Failed to unregister EXO from launch at login: \(error.localizedDescription, privacy: .public)"
)
}
}
}
final class SparkleUpdater: NSObject, ObservableObject {
private let controller: SPUStandardUpdaterController
private let delegateProxy: ExoUpdaterDelegate

View File

@@ -63,7 +63,8 @@ enum NetworkSetupHelper {
"""
static func ensureLaunchDaemonInstalled() {
Task.detached {
// Use .utility priority to match NSAppleScript's internal QoS and avoid priority inversion
Task.detached(priority: .utility) {
do {
if daemonAlreadyInstalled() {
return
@@ -78,6 +79,63 @@ enum NetworkSetupHelper {
}
}
/// Removes all EXO network setup components from the system.
/// This includes the LaunchDaemon, scripts, logs, and network location.
/// Requires admin privileges.
static func uninstall() throws {
let uninstallScript = makeUninstallScript()
try runShellAsAdmin(uninstallScript)
logger.info("EXO network setup components removed successfully")
}
/// Checks if there are any EXO network components installed that need cleanup
static func hasInstalledComponents() -> Bool {
let manager = FileManager.default
let scriptExists = manager.fileExists(atPath: scriptDestination)
let plistExists = manager.fileExists(atPath: plistDestination)
return scriptExists || plistExists
}
private static func makeUninstallScript() -> String {
"""
set -euo pipefail
LABEL="\(daemonLabel)"
SCRIPT_DEST="\(scriptDestination)"
PLIST_DEST="\(plistDestination)"
LOG_OUT="/var/log/\(daemonLabel).log"
LOG_ERR="/var/log/\(daemonLabel).err.log"
# Unload the LaunchDaemon if running
launchctl bootout system/"$LABEL" 2>/dev/null || true
# Remove LaunchDaemon plist
rm -f "$PLIST_DEST"
# Remove the script and parent directory if empty
rm -f "$SCRIPT_DEST"
rmdir "$(dirname "$SCRIPT_DEST")" 2>/dev/null || true
# Remove log files
rm -f "$LOG_OUT" "$LOG_ERR"
# Switch back to Automatic network location
networksetup -switchtolocation Automatic 2>/dev/null || true
# Delete the exo network location if it exists
networksetup -listlocations | grep -q '^exo$' && {
networksetup -deletelocation exo 2>/dev/null || true
} || true
# Re-enable Thunderbolt Bridge if it exists
networksetup -listnetworkservices | grep -q "Thunderbolt Bridge" && {
networksetup -setnetworkserviceenabled "Thunderbolt Bridge" on 2>/dev/null || true
} || true
echo "EXO network components removed successfully"
"""
}
private static func daemonAlreadyInstalled() -> Bool {
let manager = FileManager.default
let scriptExists = manager.fileExists(atPath: scriptDestination)

View File

@@ -57,7 +57,7 @@ struct InstanceViewModel: Identifiable, Equatable {
case waiting
case failed
case idle
case unknown
case preparing
var label: String {
switch self {
@@ -68,7 +68,7 @@ struct InstanceViewModel: Identifiable, Equatable {
case .waiting: return "Waiting"
case .failed: return "Failed"
case .idle: return "Idle"
case .unknown: return "Unknown"
case .preparing: return "Preparing"
}
}
}
@@ -185,7 +185,7 @@ extension InstanceViewModel.State {
} else if statuses.isEmpty {
self = .idle
} else {
self = .unknown
self = .preparing
}
}
}

View File

@@ -83,7 +83,7 @@ struct InstanceRowView: View {
case .ready: return .teal
case .waiting, .idle: return .gray
case .failed: return .red
case .unknown: return .secondary
case .preparing: return .secondary
}
}

154
app/EXO/uninstall-exo.sh Executable file
View File

@@ -0,0 +1,154 @@
#!/usr/bin/env bash
#
# EXO Uninstaller Script
#
# This script removes all EXO system components that persist after deleting the app.
# Run with: sudo ./uninstall-exo.sh
#
# Components removed:
# - LaunchDaemon: /Library/LaunchDaemons/io.exo.networksetup.plist
# - Network script: /Library/Application Support/EXO/
# - Log files: /var/log/io.exo.networksetup.*
# - Network location: "exo"
# - Launch at login registration
#
set -euo pipefail
LABEL="io.exo.networksetup"
SCRIPT_DEST="/Library/Application Support/EXO/disable_bridge_enable_dhcp.sh"
PLIST_DEST="/Library/LaunchDaemons/io.exo.networksetup.plist"
LOG_OUT="/var/log/${LABEL}.log"
LOG_ERR="/var/log/${LABEL}.err.log"
APP_BUNDLE_ID="io.exo.EXO"
# Colors for output
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
NC='\033[0m' # No Color
echo_info() {
echo -e "${GREEN}[INFO]${NC} $1"
}
echo_warn() {
echo -e "${YELLOW}[WARN]${NC} $1"
}
echo_error() {
echo -e "${RED}[ERROR]${NC} $1"
}
# Check if running as root
if [[ $EUID -ne 0 ]]; then
echo_error "This script must be run as root (use sudo)"
exit 1
fi
echo ""
echo "========================================"
echo " EXO Uninstaller"
echo "========================================"
echo ""
# Unload the LaunchDaemon if running
echo_info "Stopping network setup daemon..."
if launchctl list | grep -q "$LABEL"; then
launchctl bootout system/"$LABEL" 2>/dev/null || true
echo_info "Daemon stopped"
else
echo_warn "Daemon was not running"
fi
# Remove LaunchDaemon plist
if [[ -f "$PLIST_DEST" ]]; then
rm -f "$PLIST_DEST"
echo_info "Removed LaunchDaemon plist"
else
echo_warn "LaunchDaemon plist not found (already removed?)"
fi
# Remove the script and parent directory
if [[ -f "$SCRIPT_DEST" ]]; then
rm -f "$SCRIPT_DEST"
echo_info "Removed network setup script"
else
echo_warn "Network setup script not found (already removed?)"
fi
# Remove EXO directory if empty
if [[ -d "/Library/Application Support/EXO" ]]; then
rmdir "/Library/Application Support/EXO" 2>/dev/null && \
echo_info "Removed EXO support directory" || \
echo_warn "EXO support directory not empty, leaving in place"
fi
# Remove log files
if [[ -f "$LOG_OUT" ]] || [[ -f "$LOG_ERR" ]]; then
rm -f "$LOG_OUT" "$LOG_ERR"
echo_info "Removed log files"
else
echo_warn "Log files not found (already removed?)"
fi
# Switch back to Automatic network location
echo_info "Restoring network configuration..."
if networksetup -listlocations | grep -q "^Automatic$"; then
networksetup -switchtolocation Automatic 2>/dev/null || true
echo_info "Switched to Automatic network location"
else
echo_warn "Automatic network location not found"
fi
# Delete the exo network location if it exists
if networksetup -listlocations | grep -q "^exo$"; then
networksetup -deletelocation exo 2>/dev/null || true
echo_info "Deleted 'exo' network location"
else
echo_warn "'exo' network location not found (already removed?)"
fi
# Re-enable Thunderbolt Bridge if it exists
if networksetup -listnetworkservices 2>/dev/null | grep -q "Thunderbolt Bridge"; then
networksetup -setnetworkserviceenabled "Thunderbolt Bridge" on 2>/dev/null || true
echo_info "Re-enabled Thunderbolt Bridge"
fi
# Note about launch at login registration
# SMAppService-based login items cannot be removed from a shell script.
# They can only be unregistered from within the app itself or manually via System Settings.
echo_warn "Launch at login must be removed manually:"
echo_warn " System Settings → General → Login Items → Remove EXO"
# Check if EXO.app exists in common locations
APP_FOUND=false
for app_path in "/Applications/EXO.app" "$HOME/Applications/EXO.app"; do
if [[ -d "$app_path" ]]; then
if [[ "$APP_FOUND" == false ]]; then
echo ""
APP_FOUND=true
fi
echo_warn "EXO.app found at: $app_path"
echo_warn "You may want to move it to Trash manually."
fi
done
echo ""
echo "========================================"
echo_info "EXO uninstall complete!"
echo "========================================"
echo ""
echo "The following have been removed:"
echo " • Network setup LaunchDaemon"
echo " • Network configuration script"
echo " • Log files"
echo " • 'exo' network location"
echo ""
echo "Your network has been restored to use the 'Automatic' location."
echo "Thunderbolt Bridge has been re-enabled (if present)."
echo ""
echo "Manual step required:"
echo " Remove EXO from Login Items in System Settings → General → Login Items"
echo ""

View File

@@ -593,7 +593,7 @@ function toggleInstanceDownloadDetails(nodeId: string): void {
// Unwrap the instance
const [instanceTag, instance] = getTagged(instanceWrapped);
if (!instance || typeof instance !== 'object') {
return { isDownloading: false, progress: null, statusText: 'UNKNOWN', perNode: [] };
return { isDownloading: false, progress: null, statusText: 'PREPARING', perNode: [] };
}
const inst = instance as { shardAssignments?: { nodeToRunner?: Record<string, string>; runnerToShard?: Record<string, unknown>; modelId?: string } };
@@ -706,7 +706,7 @@ function toggleInstanceDownloadDetails(nodeId: string): void {
function deriveInstanceStatus(instanceWrapped: unknown): { statusText: string; statusClass: string } {
const [, instance] = getTagged(instanceWrapped);
if (!instance || typeof instance !== 'object') {
return { statusText: 'UNKNOWN', statusClass: 'inactive' };
return { statusText: 'PREPARING', statusClass: 'inactive' };
}
const inst = instance as { shardAssignments?: { runnerToShard?: Record<string, unknown> } };
@@ -735,7 +735,7 @@ function toggleInstanceDownloadDetails(nodeId: string): void {
const has = (s: string) => statuses.includes(s);
if (statuses.length === 0) return { statusText: 'UNKNOWN', statusClass: 'inactive' };
if (statuses.length === 0) return { statusText: 'PREPARING', statusClass: 'inactive' };
if (has('Failed')) return { statusText: 'FAILED', statusClass: 'failed' };
if (has('Shutdown')) return { statusText: 'SHUTDOWN', statusClass: 'inactive' };
if (has('Loading')) return { statusText: 'LOADING', statusClass: 'starting' };
@@ -1267,9 +1267,9 @@ function toggleInstanceDownloadDetails(nodeId: string): void {
<div class="flex-1 h-px bg-gradient-to-r from-exo-yellow/30 to-transparent"></div>
</div>
<div
<div
bind:this={instancesContainerRef}
class="max-h-72 space-y-3 overflow-y-auto"
class="max-h-72 xl:max-h-96 space-y-3 overflow-y-auto overflow-x-hidden py-px"
>
{#each Object.entries(instanceData) as [id, instance]}
{@const downloadInfo = getInstanceDownloadStatus(id, instance)}
@@ -1773,7 +1773,7 @@ function toggleInstanceDownloadDetails(nodeId: string): void {
<h3 class="text-xs text-exo-yellow font-mono tracking-[0.2em] uppercase">Instances</h3>
<div class="flex-1 h-px bg-gradient-to-r from-exo-yellow/30 to-transparent"></div>
</div>
<div class="space-y-3 max-h-72 overflow-y-auto pr-1">
<div class="space-y-3 max-h-72 xl:max-h-96 overflow-y-auto overflow-x-hidden py-px pr-1">
{#each Object.entries(instanceData) as [id, instance]}
{@const downloadInfo = getInstanceDownloadStatus(id, instance)}
{@const statusText = downloadInfo.statusText}

View File

@@ -199,7 +199,13 @@
const rawProgress = (downloadPayload as Record<string, unknown>).download_progress
?? (downloadPayload as Record<string, unknown>).downloadProgress
?? {};
const totalBytes = getBytes((rawProgress as Record<string, unknown>).total_bytes ?? (rawProgress as Record<string, unknown>).totalBytes);
// For DownloadCompleted, total_bytes is at top level; for DownloadOngoing, it's inside download_progress
const totalBytes = getBytes(
(downloadPayload as Record<string, unknown>).total_bytes
?? (downloadPayload as Record<string, unknown>).totalBytes
?? (rawProgress as Record<string, unknown>).total_bytes
?? (rawProgress as Record<string, unknown>).totalBytes
);
const downloadedBytes = getBytes((rawProgress as Record<string, unknown>).downloaded_bytes ?? (rawProgress as Record<string, unknown>).downloadedBytes);
const speed = (rawProgress as Record<string, unknown>).speed as number ?? 0;
const etaMs = (rawProgress as Record<string, unknown>).eta_ms as number ?? (rawProgress as Record<string, unknown>).etaMs as number ?? 0;
@@ -332,8 +338,13 @@
<div class="text-lg font-mono text-white truncate">{node.nodeName}</div>
<div class="text-xs text-exo-light-gray font-mono truncate">{node.nodeId}</div>
</div>
<div class="text-xs font-mono uppercase tracking-wider whitespace-nowrap shrink-0">
<span class="text-green-400">{node.models.filter(m => m.status === 'completed').length}</span><span class="text-exo-yellow"> /{node.models.length} models</span>
<div class="text-xs font-mono uppercase tracking-wider whitespace-nowrap shrink-0 text-right">
<div>
<span class="text-green-400">{node.models.filter(m => m.status === 'completed').length}</span><span class="text-exo-yellow"> / {node.models.length} models</span>
</div>
<div class="text-exo-light-gray normal-case tracking-normal">
{formatBytes(node.models.filter(m => m.status === 'completed').reduce((sum, m) => sum + m.totalBytes, 0))} on disk
</div>
</div>
</div>
@@ -385,7 +396,7 @@
</div>
<div class="flex items-center justify-between text-xs font-mono text-exo-light-gray">
<span>{model.status === 'completed' ? 'Completed' : `${formatSpeed(model.speed)} ETA ${formatEta(model.etaMs)}`}</span>
<span>{model.status === 'completed' ? `Completed (${formatBytes(model.totalBytes)})` : `${formatSpeed(model.speed)} ETA ${formatEta(model.etaMs)}`}</span>
{#if model.status !== 'completed'}
<span>{model.files.length} file{model.files.length === 1 ? '' : 's'}</span>
{/if}

212
docs/api.md Normal file
View File

@@ -0,0 +1,212 @@
# EXO API Technical Reference
This document describes the REST API exposed by the **EXO ** service, as implemented in:
`src/exo/master/api.py`
The API is used to manage model instances in the cluster, inspect cluster state, and perform inference using an OpenAI-compatible interface.
Base URL example:
```
http://localhost:52415
```
## 1. General / Meta Endpoints
### Get Master Node ID
**GET** `/node_id`
Returns the identifier of the current master node.
**Response (example):**
```json
{
"node_id": "node-1234"
}
```
### Get Cluster State
**GET** `/state`
Returns the current state of the cluster, including nodes and active instances.
**Response:**
JSON object describing topology, nodes, and instances.
### Get Events
**GET** `/events`
Returns the list of internal events recorded by the master (mainly for debugging and observability).
**Response:**
Array of event objects.
## 2. Model Instance Management
### Create Instance
**POST** `/instance`
Creates a new model instance in the cluster.
**Request body (example):**
```json
{
"instance": {
"model_id": "llama-3.2-1b",
"placement": { }
}
}
```
**Response:**
JSON description of the created instance.
### Delete Instance
**DELETE** `/instance/{instance_id}`
Deletes an existing instance by ID.
**Path parameters:**
* `instance_id`: string, ID of the instance to delete
**Response:**
Status / confirmation JSON.
### Get Instance
**GET** `/instance/{instance_id}`
Returns details of a specific instance.
**Path parameters:**
* `instance_id`: string
**Response:**
JSON description of the instance.
### Preview Placements
**GET** `/instance/previews?model_id=...`
Returns possible placement previews for a given model.
**Query parameters:**
* `model_id`: string, required
**Response:**
Array of placement preview objects.
### Compute Placement
**GET** `/instance/placement`
Computes a placement for a potential instance without creating it.
**Query parameters (typical):**
* `model_id`: string
* `sharding`: string or config
* `instance_meta`: JSON-encoded metadata
* `min_nodes`: integer
**Response:**
JSON object describing the proposed placement / instance configuration.
### Place Instance (Dry Operation)
**POST** `/place_instance`
Performs a placement operation for an instance (planning step), without necessarily creating it.
**Request body:**
JSON describing the instance to be placed.
**Response:**
Placement result.
## 3. Models
### List Models
**GET** `/models`
**GET** `/v1/models` (alias)
Returns the list of available models and their metadata.
**Response:**
Array of model descriptors.
## 4. Inference / Chat Completions
### OpenAI-Compatible Chat Completions
**POST** `/v1/chat/completions`
Executes a chat completion request using an OpenAI-compatible schema. Supports streaming and non-streaming modes.
**Request body (example):**
```json
{
"model": "llama-3.2-1b",
"messages": [
{ "role": "system", "content": "You are a helpful assistant." },
{ "role": "user", "content": "Hello" }
],
"stream": false
}
```
**Response:**
OpenAI-compatible chat completion response.
### Benchmarked Chat Completions
**POST** `/bench/chat/completions`
Same as `/v1/chat/completions`, but also returns performance and generation statistics.
**Request body:**
Same schema as `/v1/chat/completions`.
**Response:**
Chat completion plus benchmarking metrics.
## 5. Complete Endpoint Summary
```
GET /node_id
GET /state
GET /events
POST /instance
GET /instance/{instance_id}
DELETE /instance/{instance_id}
GET /instance/previews
GET /instance/placement
POST /place_instance
GET /models
GET /v1/models
POST /v1/chat/completions
POST /bench/chat/completions
```
## 6. Notes
* The `/v1/chat/completions` endpoint is compatible with the OpenAI API format, so existing OpenAI clients can be pointed to EXO by changing the base URL.
* The instance placement endpoints allow you to plan and preview cluster allocations before actually creating instances.
* The `/events` and `/state` endpoints are primarily intended for operational visibility and debugging.

View File

@@ -16,12 +16,11 @@
};
};
# TODO: figure out caching story
# nixConfig = {
# # nix community cachix
# extra-trusted-public-keys = "nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=";
# extra-substituters = "https://nix-community.cachix.org";
# };
nixConfig = {
# nix community cachix
extra-trusted-public-keys = "exo.cachix.org-1:okq7hl624TBeAR3kV+g39dUFSiaZgLRkLsFBCuJ2NZI=";
extra-substituters = "https://exo.cachix.org";
};
outputs =
inputs:
@@ -73,6 +72,9 @@
packages =
with pkgs;
[
# FORMATTING
treefmtEval.config.build.wrapper
# PYTHON
python313
uv

View File

@@ -8,30 +8,18 @@ dependencies = [
"aiofiles>=24.1.0",
"aiohttp>=3.12.14",
"types-aiofiles>=24.1.0.20250708",
"typeguard>=4.4.4",
"pydantic>=2.11.7",
"base58>=2.1.1",
"cryptography>=45.0.5",
"fastapi>=0.116.1",
"filelock>=3.18.0",
"aiosqlite>=0.21.0",
"networkx>=3.5",
"protobuf>=6.32.0",
"rich>=14.1.0",
"rustworkx>=0.17.1",
"sqlmodel>=0.0.24",
"sqlalchemy[asyncio]>=2.0.43",
"greenlet>=3.2.4",
"huggingface-hub>=0.33.4",
"psutil>=7.0.0",
"loguru>=0.7.3",
"textual>=5.3.0",
"exo_pyo3_bindings", # rust bindings
"anyio==4.11.0",
"bidict>=0.23.1",
"mlx>=0.30.1; sys_platform == 'darwin'",
"mlx[cpu]>=0.30.1; sys_platform == 'linux'",
"mlx-lm>=0.28.3",
"mlx==0.30.1; sys_platform == 'darwin'",
"mlx[cpu]==0.30.1; sys_platform == 'linux'",
"mlx-lm @ git+https://github.com/AlexCheema/mlx-lm.git@fix-transformers-5.0.0rc2",
"tiktoken>=0.12.0", # required for kimi k2 tokenizer
"hypercorn>=0.18.0",
"openai-harmony>=0.0.8",
@@ -45,6 +33,7 @@ exo = "exo.main:main"
# dependencies only required for development
[dependency-groups]
dev = [
"basedpyright>=1.29.0",
"pyinstaller>=6.17.0",
"pytest>=8.4.0",
"pytest-asyncio>=1.0.0",
@@ -110,6 +99,7 @@ root = "src"
# supported platforms for this project
[tool.uv]
prerelease = "allow"
environments = [
"sys_platform == 'darwin'",
"sys_platform == 'linux'",

View File

@@ -70,34 +70,36 @@ 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-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,
supports_tensor=True,
),
),
"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,
supports_tensor=True,
),
),
# deepseek r1
# "deepseek-r1-0528-4bit": ModelCard(
# short_id="deepseek-r1-0528-4bit",
@@ -554,6 +556,36 @@ MODEL_CARDS: dict[str, ModelCard] = {
supports_tensor=True,
),
),
"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-4.7-8bit-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,
),
),
# "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"),

View File

@@ -2,6 +2,7 @@ from exo.shared.apply import apply_node_download_progress
from exo.shared.tests.conftest import get_pipeline_shard_metadata
from exo.shared.types.common import NodeId
from exo.shared.types.events import NodeDownloadProgress
from exo.shared.types.memory import Memory
from exo.shared.types.state import State
from exo.shared.types.worker.downloads import DownloadCompleted
from exo.worker.tests.constants import MODEL_A_ID, MODEL_B_ID
@@ -13,6 +14,7 @@ def test_apply_node_download_progress():
event = DownloadCompleted(
node_id=NodeId("node-1"),
shard_metadata=shard1,
total_bytes=Memory(),
)
new_state = apply_node_download_progress(
@@ -28,10 +30,12 @@ def test_apply_two_node_download_progress():
event1 = DownloadCompleted(
node_id=NodeId("node-1"),
shard_metadata=shard1,
total_bytes=Memory(),
)
event2 = DownloadCompleted(
node_id=NodeId("node-1"),
shard_metadata=shard2,
total_bytes=Memory(),
)
state = State(downloads={NodeId("node-1"): [event1]})

View File

@@ -28,7 +28,7 @@ class DownloadPending(BaseDownloadProgress):
class DownloadCompleted(BaseDownloadProgress):
pass
total_bytes: Memory
class DownloadFailed(BaseDownloadProgress):

View File

@@ -289,8 +289,7 @@ class DeepSeekShardingStrategy(TensorParallelShardingStrategy):
model = cast(DeepseekV3Model, model)
for layer in model.layers:
# Shard the self attention
if layer.self_attn.q_lora_rank is None: # pyright: ignore[reportUnnecessaryComparison]
# Unfortunately, q_lora_rank can be None despite typing hints.
if layer.self_attn.q_lora_rank is None:
layer.self_attn.q_proj = self.all_to_sharded_linear(
layer.self_attn.q_proj
)

View File

@@ -3,6 +3,7 @@ from typing import Any, Callable, Generator, cast, get_args
import mlx.core as mx
from mlx_lm import stream_generate
from mlx_lm.models.cache import KVCache
from mlx_lm.sample_utils import make_sampler
from mlx_lm.tokenizer_utils import TokenizerWrapper
# from exo.engines.mlx.cache import KVPrefixCache
@@ -47,7 +48,6 @@ def maybe_quantize_kv_cache(
def warmup_inference(
model: Model,
tokenizer: TokenizerWrapper,
sampler: Callable[[mx.array], mx.array],
) -> int:
content = "Prompt to warm up the inference engine. Repeat this."
@@ -70,6 +70,9 @@ def warmup_inference(
model=model,
)
# Use a default sampler for warmup
sampler = make_sampler(temp=0.7)
logger.info("Generating warmup tokens")
for _r in stream_generate(
model=model,
@@ -115,7 +118,6 @@ def eos_ids_from_tokenizer(tokenizer: TokenizerWrapper) -> list[int]:
def mlx_generate(
model: Model,
tokenizer: TokenizerWrapper,
sampler: Callable[[mx.array], mx.array],
task: ChatCompletionTaskParams,
) -> Generator[GenerationResponse]:
# Ensure that generation stats only contains peak memory for this generation
@@ -125,6 +127,9 @@ def mlx_generate(
# Currently we support chat-completion tasks only.
logger.info(f"task_params: {task}")
if task.seed is not None:
mx.random.seed(task.seed)
prompt = apply_chat_template(
tokenizer=tokenizer,
chat_task_data=task,
@@ -138,6 +143,11 @@ def mlx_generate(
eos_ids = eos_ids_from_tokenizer(tokenizer)
logits_processors = [ban_token_ids(eos_ids)]
sampler = make_sampler(
temp=task.temperature if task.temperature is not None else 0.7,
top_p=task.top_p if task.top_p is not None else 1.0,
)
max_tokens = task.max_tokens or MAX_TOKENS
for out in stream_generate(
model=model,

View File

@@ -1,13 +1,25 @@
import json
import os
import resource
import sys
import time
from pathlib import Path
from typing import Any, Callable, 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
# which was moved in transformers 5.0.0rc2
try:
import transformers.models.gpt2.tokenization_gpt2 as gpt2_tokenization
from transformers.convert_slow_tokenizer import bytes_to_unicode
if not hasattr(gpt2_tokenization, "bytes_to_unicode"):
gpt2_tokenization.bytes_to_unicode = bytes_to_unicode # type: ignore[attr-defined]
except ImportError:
pass # transformers < 5.0 or bytes_to_unicode not available
from mlx_lm.models.cache import KVCache, QuantizedKVCache, RotatingKVCache
from mlx_lm.models.deepseek_v3 import DeepseekV3Model
from mlx_lm.sample_utils import make_sampler
from mlx_lm.tokenizer_utils import TokenizerWrapper
from exo.worker.engines.mlx.constants import (
@@ -19,7 +31,7 @@ from exo.worker.engines.mlx.constants import (
try:
from mlx_lm.tokenizer_utils import load_tokenizer
except ImportError:
from mlx_lm.tokenizer_utils import load as load_tokenizer # type: ignore
from mlx_lm.tokenizer_utils import load as load_tokenizer
import contextlib
import mlx.core as mx
@@ -176,11 +188,7 @@ def initialize_mlx(
def load_mlx_items(
bound_instance: BoundInstance, group: Group | None
) -> tuple[Model, TokenizerWrapper, Callable[[mx.array], mx.array]]:
# TODO: pass temperature
sampler: Callable[[mx.array], mx.array] = make_sampler(temp=0.7)
logger.info("Created a sampler")
) -> tuple[Model, TokenizerWrapper]:
if group is None:
logger.info(f"Single device used for {bound_instance.instance}")
model_path = build_model_path(bound_instance.bound_shard.model_meta.model_id)
@@ -201,7 +209,7 @@ def load_mlx_items(
set_wired_limit_for_model(get_weights_size(bound_instance.bound_shard))
return cast(Model, model), tokenizer, sampler
return cast(Model, model), tokenizer
def shard_and_load(
@@ -257,26 +265,70 @@ def shard_and_load(
return model, tokenizer
def get_tokenizer(model_path: Path, shard_metadata: ShardMetadata):
# TODO: Let's move away from this custom logic to mlx_lm.load()
if "kimi-k2" in shard_metadata.model_meta.model_id.lower():
eos_token_ids = [163586]
def get_tokenizer(model_path: Path, shard_metadata: ShardMetadata) -> TokenizerWrapper:
"""Load tokenizer for a model shard. Delegates to load_tokenizer_for_model_id."""
return load_tokenizer_for_model_id(shard_metadata.model_meta.model_id, model_path)
elif "glm" in shard_metadata.model_meta.model_id.lower():
eos_token_ids = [151336, 151329, 151338]
else:
eos_token_ids = None
def get_eos_token_ids_for_model(model_id: str) -> list[int] | None:
"""
Get the EOS token IDs for a model based on its ID.
tokenizer = cast(
TokenizerWrapper,
load_tokenizer(
model_path,
tokenizer_config_extra={"trust_remote_code": TRUST_REMOTE_CODE},
eos_token_ids=eos_token_ids,
),
Some models require explicit EOS token configuration that isn't in their
tokenizer config. This function returns the known EOS token IDs for such models.
Args:
model_id: The HuggingFace model ID
Returns:
List of EOS token IDs, or None if the model uses standard tokenizer config
"""
model_id_lower = model_id.lower()
if "kimi-k2" in model_id_lower:
return [163586]
elif "glm" in model_id_lower:
return [151336, 151329, 151338]
return None
def load_tokenizer_for_model_id(model_id: str, model_path: Path) -> TokenizerWrapper:
"""
Load tokenizer for a model given its ID and local path.
This is the core tokenizer loading logic, handling special cases for different
model families (Kimi, GLM, etc.) and transformers 5.x compatibility.
Args:
model_id: The HuggingFace model ID (e.g., "moonshotai/Kimi-K2-Instruct")
model_path: Local path where the model/tokenizer files are stored
Returns:
TokenizerWrapper instance configured for the model
"""
model_id_lower = model_id.lower()
eos_token_ids = get_eos_token_ids_for_model(model_id)
# Kimi uses a custom TikTokenTokenizer that transformers 5.x can't load via AutoTokenizer
if "kimi-k2" in model_id_lower:
sys.path.insert(0, str(model_path))
from tokenization_kimi import TikTokenTokenizer # type: ignore[import-not-found] # noqa: I001
hf_tokenizer: Any = TikTokenTokenizer.from_pretrained(model_path) # pyright: ignore[reportUnknownVariableType,reportUnknownMemberType]
# Patch encode to use internal tiktoken model directly
# transformers 5.x has a bug in the encode->pad path for slow tokenizers
def _patched_encode(text: str, **_kwargs: object) -> list[int]:
# Pass allowed_special="all" to handle special tokens like <|im_user|>
return list(hf_tokenizer.model.encode(text, allowed_special="all")) # pyright: ignore[reportUnknownMemberType,reportUnknownArgumentType]
hf_tokenizer.encode = _patched_encode
return TokenizerWrapper(hf_tokenizer, eos_token_ids=eos_token_ids)
tokenizer = load_tokenizer(
model_path,
tokenizer_config_extra={"trust_remote_code": TRUST_REMOTE_CODE},
eos_token_ids=eos_token_ids,
)
assert isinstance(tokenizer, TokenizerWrapper)
return tokenizer
@@ -289,15 +341,15 @@ def apply_chat_template(
messages = chat_task_data.messages
formatted_messages: list[dict[str, Any]] = []
for _, message in enumerate(messages):
for message in messages:
if isinstance(message.content, ChatCompletionMessageText):
message.content = message.content.text
if isinstance(message.content, list):
if len(message.content) != 1:
logger.warning("Received malformed prompt")
if len(message.content) == 0:
logger.warning("Received prompt with no content, skipping")
continue
message.content = message.content[0].text
message.content = "\n".join(c.text for c in message.content).strip()
if message.content is None and message.thinking is None:
continue
@@ -306,13 +358,14 @@ def apply_chat_template(
{k: v for k, v in message.model_dump().items() if v is not None} # type: ignore
)
prompt: str = tokenizer.apply_chat_template( # type: ignore
prompt: str = tokenizer.apply_chat_template(
formatted_messages,
tokenize=False,
add_generation_prompt=True,
tools=chat_task_data.tools,
)
return prompt # type: ignore
return prompt
class NullKVCache(KVCache):

View File

@@ -217,7 +217,9 @@ class Worker:
)
if initial_progress.status == "complete":
progress = DownloadCompleted(
shard_metadata=shard, node_id=self.node_id
shard_metadata=shard,
node_id=self.node_id,
total_bytes=initial_progress.total_bytes,
)
self.download_status[shard.model_meta.model_id] = progress
await self.event_sender.send(
@@ -364,7 +366,11 @@ class Worker:
nonlocal self
nonlocal last_progress_time
if progress.status == "complete":
status = DownloadCompleted(shard_metadata=shard, node_id=self.node_id)
status = DownloadCompleted(
shard_metadata=shard,
node_id=self.node_id,
total_bytes=progress.total_bytes,
)
self.download_status[shard.model_meta.model_id] = status
# Footgun!
self.event_sender.send_nowait(
@@ -457,7 +463,9 @@ class Worker:
) in self.shard_downloader.get_shard_download_status():
if progress.status == "complete":
status = DownloadCompleted(
node_id=self.node_id, shard_metadata=progress.shard
node_id=self.node_id,
shard_metadata=progress.shard,
total_bytes=progress.total_bytes,
)
elif progress.status in ["in_progress", "not_started"]:
if progress.downloaded_bytes_this_session.in_bytes == 0:

View File

@@ -68,7 +68,6 @@ def main(
model = None
tokenizer = None
sampler = None
group = None
current_status: RunnerStatus = RunnerIdle()
@@ -110,14 +109,13 @@ def main(
)
)
model, tokenizer, sampler = load_mlx_items(bound_instance, group)
model, tokenizer = load_mlx_items(bound_instance, group)
current_status = RunnerLoaded()
logger.info("runner loaded")
case StartWarmup() if isinstance(current_status, RunnerLoaded):
assert model
assert tokenizer
assert sampler
current_status = RunnerWarmingUp()
logger.info("runner warming up")
event_sender.send(
@@ -130,7 +128,6 @@ def main(
toks = warmup_inference(
model=model,
tokenizer=tokenizer,
sampler=sampler,
# kv_prefix_cache=kv_prefix_cache, # supply for warmup-time prefix caching
)
logger.info(f"warmed up by generating {toks} tokens")
@@ -144,7 +141,6 @@ def main(
):
assert model
assert tokenizer
assert sampler
logger.info(f"received chat request: {str(task)[:500]}")
current_status = RunnerRunning()
logger.info("runner running")
@@ -160,7 +156,6 @@ def main(
for response in mlx_generate(
model=model,
tokenizer=tokenizer,
sampler=sampler,
task=task_params,
):
match response:
@@ -204,7 +199,7 @@ def main(
RunnerStatusUpdated(runner_id=runner_id, runner_status=current_status)
)
if isinstance(current_status, RunnerShutdown):
del model, tokenizer, group, sampler
del model, tokenizer, group
mx.clear_cache()
import gc

View File

@@ -0,0 +1,386 @@
"""
Unit tests for tokenizer loading and functionality across all supported models.
This test downloads only tokenizer-related files (not full model weights) to verify
that tokenizers can be loaded and used correctly for encoding/decoding.
"""
import asyncio
import contextlib
from pathlib import Path
import pytest
from exo.shared.models.model_cards import MODEL_CARDS, ModelCard
from exo.worker.download.download_utils import (
download_file_with_retry,
ensure_models_dir,
fetch_file_list_with_cache,
)
from exo.worker.engines.mlx.utils_mlx import (
get_eos_token_ids_for_model,
load_tokenizer_for_model_id,
)
# Files needed for tokenizer functionality
TOKENIZER_FILE_PATTERNS = [
"tokenizer.json",
"tokenizer_config.json",
"special_tokens_map.json",
"vocab.json",
"vocab.txt",
"merges.txt",
"tiktoken.model",
"added_tokens.json",
"tokenizer.model",
"tokenization_*.py", # Custom tokenizer implementations
]
def is_tokenizer_file(filename: str) -> bool:
"""Check if a file is needed for tokenizer functionality."""
for pattern in TOKENIZER_FILE_PATTERNS:
if "*" in pattern:
prefix = pattern.split("*")[0]
suffix = pattern.split("*")[1]
if filename.startswith(prefix) and filename.endswith(suffix):
return True
elif filename == pattern:
return True
return False
async def download_tokenizer_files(model_id: str) -> Path:
"""Download only the tokenizer-related files for a model."""
target_dir = await ensure_models_dir() / model_id.replace("/", "--")
target_dir.mkdir(parents=True, exist_ok=True)
file_list = await fetch_file_list_with_cache(model_id, "main", recursive=True)
tokenizer_files = [f for f in file_list if is_tokenizer_file(f.path)]
if not tokenizer_files:
pytest.skip(f"No tokenizer files found for {model_id}")
for file_entry in tokenizer_files:
with contextlib.suppress(FileNotFoundError):
await download_file_with_retry(
model_id, "main", file_entry.path, target_dir
)
return target_dir
# Get a sample of models to test (one per family to keep tests fast)
def get_test_models() -> list[tuple[str, ModelCard]]:
"""Get a representative sample of models to test."""
# Pick one model from each family to test
families: dict[str, tuple[str, ModelCard]] = {}
for short_id, card in MODEL_CARDS.items():
# Extract family name (e.g., "llama-3.1" from "llama-3.1-8b")
parts = short_id.split("-")
family = "-".join(parts[:2]) if len(parts) >= 2 else parts[0]
if family not in families:
families[family] = (short_id, card)
return list(families.values())
TEST_MODELS: list[tuple[str, ModelCard]] = get_test_models()
@pytest.fixture(scope="module")
def event_loop():
"""Create event loop for async tests."""
loop = asyncio.new_event_loop()
yield loop
loop.close()
@pytest.mark.parametrize(
"short_id,model_card",
TEST_MODELS,
ids=[m[0] for m in TEST_MODELS],
)
@pytest.mark.asyncio
async def test_tokenizer_encode_decode(short_id: str, model_card: ModelCard) -> None:
"""Test that tokenizer can encode and decode text correctly."""
model_id = str(model_card.model_id)
# Download tokenizer files
model_path = await download_tokenizer_files(model_id)
# Verify required files exist
has_tokenizer = (
(model_path / "tokenizer.json").exists()
or (model_path / "tokenizer_config.json").exists()
or (model_path / "tiktoken.model").exists()
or (model_path / "tokenizer.model").exists()
)
if not has_tokenizer:
pytest.skip(f"Required tokenizer files not found for {model_id}")
# Load tokenizer
tokenizer = load_tokenizer_for_model_id(model_id, model_path)
# Test basic encoding
test_text = "Hello, world!"
encoded = tokenizer.encode(test_text)
assert isinstance(encoded, list), f"encode() should return a list for {model_id}"
assert len(encoded) > 0, f"encode() should return non-empty list for {model_id}"
assert all(isinstance(t, int) for t in encoded), (
f"All tokens should be integers for {model_id}"
)
# Test decoding
decoded = tokenizer.decode(encoded)
assert isinstance(decoded, str), f"decode() should return a string for {model_id}"
assert test_text in decoded or decoded.strip() == test_text.strip(), (
f"decode(encode(x)) should preserve text for {model_id}: got {decoded!r}"
)
# Test with longer text
long_text = "The quick brown fox jumps over the lazy dog. " * 10
long_encoded = tokenizer.encode(long_text)
assert len(long_encoded) > len(encoded), (
f"Longer text should produce more tokens for {model_id}"
)
# Test empty string
empty_encoded = tokenizer.encode("")
assert isinstance(empty_encoded, list), (
f"encode('') should return a list for {model_id}"
)
# Test special characters
special_text = 'Hello!\n\tWorld? <test> & "quotes"'
special_encoded = tokenizer.encode(special_text)
assert len(special_encoded) > 0, f"Special chars should encode for {model_id}"
# Test unicode
unicode_text = "Hello 世界 🌍"
unicode_encoded = tokenizer.encode(unicode_text)
assert len(unicode_encoded) > 0, f"Unicode should encode for {model_id}"
@pytest.mark.parametrize(
"short_id,model_card",
TEST_MODELS,
ids=[m[0] for m in TEST_MODELS],
)
@pytest.mark.asyncio
async def test_tokenizer_has_required_attributes(
short_id: str, model_card: ModelCard
) -> None:
"""Test that tokenizer has required attributes for inference."""
model_id = str(model_card.model_id)
model_path = await download_tokenizer_files(model_id)
has_tokenizer = (
(model_path / "tokenizer.json").exists()
or (model_path / "tokenizer_config.json").exists()
or (model_path / "tiktoken.model").exists()
or (model_path / "tokenizer.model").exists()
)
if not has_tokenizer:
pytest.skip(f"Required tokenizer files not found for {model_id}")
tokenizer = load_tokenizer_for_model_id(model_id, model_path)
eos_token_ids = get_eos_token_ids_for_model(model_id)
# Check for vocabulary size
empty_vocab: dict[str, int] = {}
vocab_size: int = getattr(tokenizer, "vocab_size", None) or len(
getattr(tokenizer, "get_vocab", lambda: empty_vocab)()
)
assert vocab_size > 0, f"Tokenizer should have vocab_size > 0 for {model_id}"
# Check for EOS token (either from tokenizer or explicitly provided)
has_eos = (
eos_token_ids is not None
or getattr(tokenizer, "eos_token_id", None) is not None
or getattr(tokenizer, "eos_token", None) is not None
)
assert has_eos, f"Tokenizer should have EOS token for {model_id}"
@pytest.mark.parametrize(
"short_id,model_card",
TEST_MODELS,
ids=[m[0] for m in TEST_MODELS],
)
@pytest.mark.asyncio
async def test_tokenizer_special_tokens(short_id: str, model_card: ModelCard) -> None:
"""Test that tokenizer can encode text containing special tokens.
This is critical because the actual inference path uses prompts with
special tokens from chat templates. If special tokens aren't handled
correctly, encoding will fail.
"""
model_id = str(model_card.model_id)
model_path = await download_tokenizer_files(model_id)
has_tokenizer = (
(model_path / "tokenizer.json").exists()
or (model_path / "tokenizer_config.json").exists()
or (model_path / "tiktoken.model").exists()
or (model_path / "tokenizer.model").exists()
)
assert has_tokenizer, f"Required tokenizer files not found for {model_id}"
tokenizer = load_tokenizer_for_model_id(model_id, model_path)
# Get special tokens from the tokenizer
special_tokens: list[str] = []
# Try to get special tokens from various sources
if hasattr(tokenizer, "all_special_tokens"):
special_tokens.extend(tokenizer.all_special_tokens)
elif hasattr(tokenizer, "_tokenizer") and hasattr(
tokenizer._tokenizer,
"all_special_tokens",
):
special_tokens.extend(tokenizer._tokenizer.all_special_tokens)
# Also check for common special token attributes
for attr in [
"bos_token",
"eos_token",
"pad_token",
"unk_token",
"sep_token",
"cls_token",
]:
token = getattr(tokenizer, attr, None)
if token is None and hasattr(tokenizer, "_tokenizer"):
token = getattr(tokenizer._tokenizer, attr, None)
if token and isinstance(token, str) and token not in special_tokens:
special_tokens.append(token)
# If we found special tokens, test encoding text that contains them
if special_tokens:
# Create text with special tokens interspersed
test_with_special = f"{special_tokens[0]}Hello world"
if len(special_tokens) > 1:
test_with_special += f"{special_tokens[1]}"
encoded = tokenizer.encode(test_with_special)
assert isinstance(encoded, list), (
f"encode() with special tokens should return list for {model_id}"
)
assert len(encoded) > 0, (
f"encode() with special tokens should return non-empty list for {model_id}"
)
assert all(isinstance(t, int) for t in encoded), (
f"All tokens should be integers for {model_id}"
)
# Verify we can decode
decoded = tokenizer.decode(encoded)
assert isinstance(decoded, str), f"decode() should return string for {model_id}"
# Test with angle-bracket tokens (common format for special tokens)
# These should not raise errors even if they're not actual special tokens
angle_bracket_text = "<|test|>Hello<|end|>"
encoded = tokenizer.encode(angle_bracket_text)
assert isinstance(encoded, list), (
f"encode() with angle brackets should return list for {model_id}"
)
assert len(encoded) > 0, (
f"encode() with angle brackets should be non-empty for {model_id}"
)
# Specifically test Kimi tokenizer since it has special handling
@pytest.mark.asyncio
async def test_kimi_tokenizer_specifically():
"""Test Kimi tokenizer with its specific patches and quirks."""
kimi_models = [
(short_id, card)
for short_id, card in MODEL_CARDS.items()
if "kimi" in short_id.lower()
]
if not kimi_models:
pytest.skip("No Kimi models found in MODEL_CARDS")
_, model_card = kimi_models[0]
model_id = str(model_card.model_id)
model_path = await download_tokenizer_files(model_id)
# Ensure the custom tokenizer file exists
if not (model_path / "tokenization_kimi.py").exists():
pytest.skip("tokenization_kimi.py not found")
tokenizer = load_tokenizer_for_model_id(model_id, model_path)
eos_token_ids = get_eos_token_ids_for_model(model_id)
# Test encode/decode cycle
test_text = "Hello, world!"
encoded = tokenizer.encode(test_text)
decoded = tokenizer.decode(encoded)
assert len(encoded) > 0, "Kimi tokenizer should encode text"
assert isinstance(decoded, str), "Kimi tokenizer should decode to string"
# Test that the patched encode works (returns list of ints)
assert all(isinstance(t, int) for t in encoded), "Tokens should be integers"
# Test encoding text with special tokens (like from chat templates)
# This is critical - the warmup inference uses prompts with special tokens
special_token_text = "<|im_user|>user<|im_middle|>Hello<|im_end|><|im_assistant|>"
special_encoded = tokenizer.encode(special_token_text)
assert len(special_encoded) > 0, "Kimi tokenizer should handle special tokens"
assert all(isinstance(t, int) for t in special_encoded), (
"Special token encoding should return integers"
)
# Verify EOS token is set
assert eos_token_ids == [163586], "Kimi EOS token should be [163586]"
# Test GLM tokenizer since it also has special handling
@pytest.mark.asyncio
async def test_glm_tokenizer_specifically():
"""Test GLM tokenizer with its specific EOS tokens."""
glm_models = [
(short_id, card)
for short_id, card in MODEL_CARDS.items()
if "glm" in short_id.lower()
]
if not glm_models:
pytest.skip("No GLM models found in MODEL_CARDS")
_, model_card = glm_models[0]
model_id = str(model_card.model_id)
model_path = await download_tokenizer_files(model_id)
has_tokenizer = (model_path / "tokenizer.json").exists() or (
model_path / "tokenizer_config.json"
).exists()
if not has_tokenizer:
pytest.skip("GLM tokenizer files not found")
tokenizer = load_tokenizer_for_model_id(model_id, model_path)
eos_token_ids = get_eos_token_ids_for_model(model_id)
# Test encode/decode
test_text = "Hello, world!"
encoded = tokenizer.encode(test_text)
decoded = tokenizer.decode(encoded)
assert len(encoded) > 0, "GLM tokenizer should encode text"
assert isinstance(decoded, str), "GLM tokenizer should decode to string"
# Verify EOS tokens
assert eos_token_ids == [
151336,
151329,
151338,
], "GLM EOS tokens should be correct"

View File

@@ -1,5 +1,6 @@
import exo.worker.plan as plan_mod
from exo.shared.types.common import NodeId
from exo.shared.types.memory import Memory
from exo.shared.types.models import ModelId
from exo.shared.types.tasks import LoadModel
from exo.shared.types.worker.downloads import DownloadCompleted, DownloadProgress
@@ -94,13 +95,23 @@ def test_plan_loads_model_when_all_shards_downloaded_and_waiting():
# Local node has already marked its shard as downloaded (not actually used by _load_model)
local_download_status = {
MODEL_A_ID: DownloadCompleted(shard_metadata=shard1, node_id=NODE_A)
MODEL_A_ID: DownloadCompleted(
shard_metadata=shard1, node_id=NODE_A, total_bytes=Memory()
)
}
# Global view has completed downloads for both nodes
global_download_status = {
NODE_A: [DownloadCompleted(shard_metadata=shard1, node_id=NODE_A)],
NODE_B: [DownloadCompleted(shard_metadata=shard2, node_id=NODE_B)],
NODE_A: [
DownloadCompleted(
shard_metadata=shard1, node_id=NODE_A, total_bytes=Memory()
)
],
NODE_B: [
DownloadCompleted(
shard_metadata=shard2, node_id=NODE_B, total_bytes=Memory()
)
],
}
result = plan_mod.plan(
@@ -140,7 +151,9 @@ def test_plan_does_not_request_download_when_shard_already_downloaded():
# Local status claims the shard is downloaded already
local_download_status = {
MODEL_A_ID: DownloadCompleted(shard_metadata=shard, node_id=NODE_A)
MODEL_A_ID: DownloadCompleted(
shard_metadata=shard, node_id=NODE_A, total_bytes=Memory()
)
}
# Global view hasn't caught up yet (no completed shards recorded for NODE_A)
@@ -192,10 +205,16 @@ def test_plan_does_not_load_model_until_all_shards_downloaded_globally():
# Only NODE_A's shard is recorded as downloaded globally
local_download_status = {
MODEL_A_ID: DownloadCompleted(shard_metadata=shard1, node_id=NODE_A)
MODEL_A_ID: DownloadCompleted(
shard_metadata=shard1, node_id=NODE_A, total_bytes=Memory()
)
}
global_download_status = {
NODE_A: [DownloadCompleted(shard_metadata=shard1, node_id=NODE_A)],
NODE_A: [
DownloadCompleted(
shard_metadata=shard1, node_id=NODE_A, total_bytes=Memory()
)
],
NODE_B: [], # NODE_B has no downloads completed yet
}
@@ -212,9 +231,15 @@ def test_plan_does_not_load_model_until_all_shards_downloaded_globally():
assert result is None
global_download_status = {
NODE_A: [DownloadCompleted(shard_metadata=shard1, node_id=NODE_A)],
NODE_A: [
DownloadCompleted(
shard_metadata=shard1, node_id=NODE_A, total_bytes=Memory()
)
],
NODE_B: [
DownloadCompleted(shard_metadata=shard2, node_id=NODE_B)
DownloadCompleted(
shard_metadata=shard2, node_id=NODE_B, total_bytes=Memory()
)
], # NODE_B has no downloads completed yet
}

View File

@@ -111,7 +111,7 @@ def assert_events_equal(test_events: Iterable[Event], true_events: Iterable[Even
def patch_out_mlx(monkeypatch: pytest.MonkeyPatch):
# initialize_mlx returns a "group" equal to 1
monkeypatch.setattr(mlx_runner, "initialize_mlx", make_nothin(1))
monkeypatch.setattr(mlx_runner, "load_mlx_items", make_nothin((1, 1, 1)))
monkeypatch.setattr(mlx_runner, "load_mlx_items", make_nothin((1, 1)))
monkeypatch.setattr(mlx_runner, "warmup_inference", make_nothin(1))
monkeypatch.setattr(mlx_runner, "_check_for_debug_prompts", nothin)

View File

@@ -49,14 +49,12 @@ class Tests(BaseModel):
kind: typing.Literal["init", "warmup", "inference"]
hn = socket.gethostname()
mp.set_start_method("spawn", force=True)
logger_setup(None)
async def main():
logger.info("starting cool server majig")
logger.info(hn)
await assert_downloads()
cfg = Config()
cfg.bind = "0.0.0.0:52415"
@@ -81,20 +79,39 @@ async def main():
async def assert_downloads():
sd = exo_shard_downloader()
# await sd.ensure_shard(await build_full_shard(MODEL_CARDS["qwen3-0.6b"].model_id))
await sd.ensure_shard(await build_full_shard(MODEL_CARDS["llama-3.2-1b"].model_id))
await sd.ensure_shard(
await build_full_shard(MODEL_CARDS["llama-3.1-8b-bf16"].model_id)
)
await sd.ensure_shard(await build_full_shard(MODEL_CARDS["qwen3-30b"].model_id))
await sd.ensure_shard(
await build_full_shard(MODEL_CARDS["gpt-oss-120b-MXFP4-Q8"].model_id)
)
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["deepseek-v3.2"].model_id))
await sd.ensure_shard(
await build_full_shard(MODEL_CARDS["glm-4.7-8bit-gs32"].model_id)
)
async def ring_backend(test: Tests):
iid = InstanceId(str(hash(str(test.devs))))
return await execute_test(test, ring_instance(test, iid))
weird_hn = socket.gethostname()
for dev in test.devs:
if weird_hn.startswith(dev[0]) or dev[0].startswith(weird_hn):
hn = dev[0]
break
else:
raise ValueError(f"{weird_hn} not in {test.devs}")
return await execute_test(test, ring_instance(test, iid, hn), hn)
def ring_instance(test: Tests, iid: InstanceId) -> Instance:
global hn
def ring_instance(test: Tests, iid: InstanceId, hn: str) -> Instance:
hbn = [Host(ip="i dont care", port=52416) for _ in test.devs]
world_size = len(test.devs)
for i in range(world_size):
if hn.startswith(test.devs[i][0]):
if test.devs[i][0] == hn:
hn = test.devs[i][0]
if i - 1 >= 0:
hbn[i - 1] = Host(ip=test.devs[i - 1][1], port=52416)
@@ -102,6 +119,8 @@ def ring_instance(test: Tests, iid: InstanceId) -> Instance:
hbn[i + 1] = Host(ip=test.devs[i + 1][1], port=52416)
hbn[i] = Host(ip="0.0.0.0", port=52416)
break
else:
raise ValueError(f"{hn} not in {test.devs}")
meta = MODEL_CARDS[test.model_id].metadata
instance = MlxRingInstance(
@@ -131,10 +150,10 @@ def ring_instance(test: Tests, iid: InstanceId) -> Instance:
return instance
async def execute_test(test: Tests, instance: Instance):
async def execute_test(test: Tests, instance: Instance, hn: str):
world_size = len(test.devs)
iid = InstanceId(str(hash(str(test.devs))))
_handle, recv, send = new_runner(instance)
_handle, recv, send = new_runner(instance, hn)
if world_size > 1:
send.send(ConnectToGroup(instance_id=iid))
send.send(LoadModel(instance_id=iid))
@@ -181,17 +200,19 @@ async def execute_test(test: Tests, instance: Instance):
async def jaccl_backend(test: Tests):
iid = InstanceId(str(hash(str(test.devs))))
return await execute_test(test, jaccl_instance(test, iid))
weird_hn = socket.gethostname()
for dev in test.devs:
if weird_hn.startswith(dev[0]) or dev[0].startswith(weird_hn):
hn = dev[0]
break
else:
raise ValueError(f"{weird_hn} not in {test.devs}")
return await execute_test(test, jaccl_instance(test, iid, hn), hn)
def jaccl_instance(test: Tests, iid: InstanceId):
global hn
def jaccl_instance(test: Tests, iid: InstanceId, hn: str):
meta = MODEL_CARDS[test.model_id].metadata
world_size = len(test.devs)
for name, _ in test.devs:
if hn.startswith(name):
hn = name
break
return MlxJacclInstance(
instance_id=iid,
@@ -220,6 +241,7 @@ def jaccl_instance(test: Tests, iid: InstanceId):
def new_runner(
instance: Instance,
hn: str,
) -> tuple[mp.Process, MpReceiver[Event], MpSender[Task]]:
bound_instance = BoundInstance(
instance=instance, bound_runner_id=RunnerId(hn), bound_node_id=NodeId(hn)

View File

@@ -34,19 +34,23 @@ done
devs_raw=$(printf "[\"%s\", \"%s\"], " "${weaved[@]}")
devs="[${devs_raw%, }]"
for i in "${!ips[@]}"; do
{
req="{
\"model_id\": \"llama-3.2-1b\",
\"devs\": ${devs},
\"kind\": \"inference\"
}"
echo "req $req"
curl -sN \
-X POST "http://${ips[$i]}:52415/${kind}" \
-H "Content-Type: application/json" -d "$req" \
2>&1 | sed "s/^/\n${hostnames[$i]}@${ips[$i]}: /" || echo "curl to ${hostnames[$i]} failed"
} &
model_ids=("qwen3-30b" "gpt-oss-120b-MXFP4-Q8" "kimi-k2-thinking")
for model_id in "${model_ids[@]}"; do
for i in "${!ips[@]}"; do
{
req="{
\"model_id\": \"${model_id}\",
\"devs\": ${devs},
\"kind\": \"inference\"
}"
echo "req $req"
curl -sN \
-X POST "http://${ips[$i]}:52415/${kind}" \
-H "Content-Type: application/json" -d "$req" \
2>&1 | sed "s/^/\n${hostnames[$i]}@${ips[$i]}: /" || echo "curl to ${hostnames[$i]} failed" && exit 1
} &
done
wait
done
wait

1860
uv.lock generated
View File

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