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3 Commits

Author SHA1 Message Date
Alex Cheema
e3465afae3 Split NodePerformanceProfile state storage into separate mappings
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-17 21:28:42 +00:00
rltakashige
5c8a237940 Handle model timeouts (#1177)
- Add eval with a timeout.
- Add fast synch flag

## Motivation

Because of the experimental FAST SYNCH flag, some models may not work.
This PR catches when this occurs and allows users to specify a run
without fast synch

## Changes

- Adds a flag to enable or disable fast synch (--fast-synch and
--no-fast-synch)
- Adds a heuristic timeout
- Reduces exo_bench default timeout to 10 minutes.

## Why It Works

Heuristic timeout assumes normal loading times on Mac devices (60 +
model size in gb / 5: e.g. DeepSeek takes up to 120 seconds to load on
tensor parallel, and timeout is set to 60 + 120 = 180s.

We could raise this value if necessary.

## Test Plan

### Manual Testing
Catches that GPT OSS fails to load in Tensor RDMA
Can launch with --no-fast-synch flag to launch GPT OSS.

**GPT OSS 20B**
TP with fast synch
<img width="3064" height="456" alt="image"
src="https://github.com/user-attachments/assets/f6e25cd8-8621-4e99-99fe-292ee05c4035"
/>

TP without fast synch
<img width="3098" height="496" alt="image"
src="https://github.com/user-attachments/assets/d36453d9-6686-4cfe-aa7c-a7d458369d4d"
/>
[Note: the performance is really not great as fast synch is off]

(As a sanity check)
PP with fast synch
<img width="3124" height="496" alt="image"
src="https://github.com/user-attachments/assets/e97d4547-c6fa-483d-badb-4b371b900b4c"
/>

PP without fast synch
<img width="3078" height="508" alt="image"
src="https://github.com/user-attachments/assets/b2e20dfd-4b0e-4295-8a92-417dfe745c28"
/>

PP without RDMA
<img width="3070" height="498" alt="image"
src="https://github.com/user-attachments/assets/a8509d68-0aef-4cda-bca5-a67d39a0801e"
/>

TP without RDMA
<img width="3068" height="496" alt="image"
src="https://github.com/user-attachments/assets/b5691429-89f4-4369-bcf2-8fde2ad7154a"
/>
2026-01-16 20:25:12 +00:00
rltakashige
745343c705 Return error responses for Chat Completions (#1173)
- Error chunks
- Use error handling in exo_bench.py

## Motivation

Return when an error occurs so that generation stops. Adding timeouts is
a separate TODO for model loading and chat completions.

## Changes

- Return HTTP exceptions as JSON responses in an OpenAI compatible
format.
- Context manager for generation to catch and return error messages.
- Use error handling in exo_bench.py.

## Test Plan

### Manual Testing
Manually tested that exo_bench returns on failures within and outside
generation

### Automated Testing
<!-- Describe changes to automated tests, or how existing tests cover
this change -->
<!-- - -->
2026-01-16 19:24:37 +00:00
21 changed files with 883 additions and 297 deletions

View File

@@ -3,6 +3,7 @@
from __future__ import annotations
import argparse
import contextlib
import http.client
import json
import os
@@ -26,7 +27,7 @@ class ExoHttpError(RuntimeError):
class ExoClient:
def __init__(self, host: str, port: int, timeout_s: float = 2400.0):
def __init__(self, host: str, port: int, timeout_s: float = 600.0):
self.host = host
self.port = port
self.timeout_s = timeout_s
@@ -104,22 +105,46 @@ def runner_ready(runner: dict[str, Any]) -> bool:
return "RunnerReady" in runner
def runner_failed(runner: dict[str, Any]) -> bool:
return "RunnerFailed" in runner
def get_runner_failed_message(runner: dict[str, Any]) -> str | None:
if "RunnerFailed" in runner:
return runner["RunnerFailed"].get("errorMessage")
return None
def wait_for_instance_ready(
client: ExoClient, instance_id: str, timeout: float = 24000.0
) -> None:
start_time = time.time()
instance_existed = False
while time.time() - start_time < timeout:
state = client.request_json("GET", "/state")
instances = state.get("instances", {})
if instance_id not in instances:
if instance_existed:
# Instance was deleted after being created - likely due to runner failure
raise RuntimeError(
f"Instance {instance_id} was deleted (runner may have failed)"
)
time.sleep(0.1)
continue
instance_existed = True
instance = instances[instance_id]
runner_ids = runner_ids_from_instance(instance)
runners = state.get("runners", {})
# Check for failed runners first
for rid in runner_ids:
runner = runners.get(rid, {})
if runner_failed(runner):
error_msg = get_runner_failed_message(runner) or "Unknown error"
raise RuntimeError(f"Runner {rid} failed: {error_msg}")
if all(runner_ready(runners.get(rid, {})) for rid in runner_ids):
return
@@ -299,6 +324,12 @@ def main() -> int:
default=4,
help="Only consider placements using <= this many nodes.",
)
ap.add_argument(
"--min-nodes",
type=int,
default=1,
help="Only consider placements using >= this many nodes.",
)
ap.add_argument(
"--instance-meta", choices=["ring", "jaccl", "both"], default="both"
)
@@ -320,7 +351,7 @@ def main() -> int:
help="Warmup runs per placement (uses first pp/tg).",
)
ap.add_argument(
"--timeout", type=float, default=2400.0, help="HTTP timeout (seconds)."
"--timeout", type=float, default=600.0, help="HTTP timeout (seconds)."
)
ap.add_argument(
"--json-out",
@@ -399,7 +430,7 @@ def main() -> int:
):
continue
if 0 < n <= args.max_nodes:
if args.min_nodes <= n <= args.max_nodes:
selected.append(p)
if not selected:
@@ -441,7 +472,13 @@ def main() -> int:
)
client.request_json("POST", "/instance", body={"instance": instance})
wait_for_instance_ready(client, instance_id)
try:
wait_for_instance_ready(client, instance_id)
except (RuntimeError, TimeoutError) as e:
logger.error(f"Failed to initialize placement: {e}")
with contextlib.suppress(ExoHttpError):
client.request_json("DELETE", f"/instance/{instance_id}")
continue
time.sleep(1)

View File

@@ -71,35 +71,36 @@ export interface Instance {
};
}
interface RawNodeProfile {
modelId?: string;
chipId?: string;
friendlyName?: string;
networkInterfaces?: Array<{
name?: string;
ipAddress?: string;
addresses?: Array<{ address?: string } | string>;
ipv4?: string;
ipv6?: string;
ipAddresses?: string[];
ips?: string[];
}>;
memory?: {
ramTotal?: { inBytes: number };
ramAvailable?: { inBytes: number };
swapTotal?: { inBytes: number };
swapAvailable?: { inBytes: number };
};
system?: {
gpuUsage?: number;
temp?: number;
sysPower?: number;
};
// Split state interfaces
interface RawNodeIdentity {
modelId: string;
chipId: string;
friendlyName: string;
}
interface RawNodeMemory {
ramTotal: { inBytes: number };
ramAvailable: { inBytes: number };
swapTotal: { inBytes: number };
swapAvailable: { inBytes: number };
}
interface RawNodeSystem {
gpuUsage?: number;
temp?: number;
sysPower?: number;
pcpuUsage?: number;
ecpuUsage?: number;
anePower?: number;
}
interface RawNetworkInterface {
name: string;
ipAddress: string;
}
interface RawTopologyNode {
nodeId: string;
nodeProfile: RawNodeProfile;
}
interface RawTopologyConnection {
@@ -115,8 +116,6 @@ interface RawTopology {
connections?: RawTopologyConnection[];
}
type RawNodeProfiles = Record<string, RawNodeProfile>;
export interface DownloadProgress {
totalBytes: number;
downloadedBytes: number;
@@ -171,7 +170,11 @@ interface RawStateResponse {
>;
runners?: Record<string, unknown>;
downloads?: Record<string, unknown[]>;
nodeProfiles?: RawNodeProfiles;
// Split state fields
nodeIdentities?: Record<string, RawNodeIdentity>;
nodeMemories?: Record<string, RawNodeMemory>;
nodeSystems?: Record<string, RawNodeSystem>;
nodeNetworks?: Record<string, RawNetworkInterface[]>;
}
export interface MessageAttachment {
@@ -208,66 +211,41 @@ const STORAGE_KEY = "exo-conversations";
function transformTopology(
raw: RawTopology,
profiles?: RawNodeProfiles,
identities?: Record<string, RawNodeIdentity>,
memories?: Record<string, RawNodeMemory>,
systems?: Record<string, RawNodeSystem>,
networks?: Record<string, RawNetworkInterface[]>,
): TopologyData {
const nodes: Record<string, NodeInfo> = {};
const edges: TopologyEdge[] = [];
for (const node of raw.nodes || []) {
const mergedProfile = profiles?.[node.nodeId];
const profile = { ...(node.nodeProfile ?? {}), ...(mergedProfile ?? {}) };
const ramTotal = profile?.memory?.ramTotal?.inBytes ?? 0;
const ramAvailable = profile?.memory?.ramAvailable?.inBytes ?? 0;
// Get split state fields (may be undefined if events haven't arrived yet)
const identity = identities?.[node.nodeId];
const memory = memories?.[node.nodeId];
const system = systems?.[node.nodeId];
const network = networks?.[node.nodeId];
const ramTotal = memory?.ramTotal?.inBytes ?? 0;
const ramAvailable = memory?.ramAvailable?.inBytes ?? 0;
const ramUsage = Math.max(ramTotal - ramAvailable, 0);
const networkInterfaces = (profile?.networkInterfaces || []).map(
(iface) => {
const addresses: string[] = [];
if (iface.ipAddress && typeof iface.ipAddress === "string") {
addresses.push(iface.ipAddress);
}
if (Array.isArray(iface.addresses)) {
for (const addr of iface.addresses) {
if (typeof addr === "string") addresses.push(addr);
else if (addr && typeof addr === "object" && addr.address)
addresses.push(addr.address);
}
}
if (Array.isArray(iface.ipAddresses)) {
addresses.push(
...iface.ipAddresses.filter(
(a): a is string => typeof a === "string",
),
);
}
if (Array.isArray(iface.ips)) {
addresses.push(
...iface.ips.filter((a): a is string => typeof a === "string"),
);
}
if (iface.ipv4 && typeof iface.ipv4 === "string")
addresses.push(iface.ipv4);
if (iface.ipv6 && typeof iface.ipv6 === "string")
addresses.push(iface.ipv6);
return {
name: iface.name,
addresses: Array.from(new Set(addresses)),
};
},
);
const networkInterfaces = (network ?? []).map((iface) => ({
name: iface.name,
addresses: [iface.ipAddress],
}));
const ipToInterface: Record<string, string> = {};
for (const iface of networkInterfaces) {
for (const addr of iface.addresses || []) {
ipToInterface[addr] = iface.name ?? "";
for (const addr of iface.addresses) {
ipToInterface[addr] = iface.name;
}
}
nodes[node.nodeId] = {
system_info: {
model_id: profile?.modelId ?? "Unknown",
chip: profile?.chipId,
model_id: identity?.modelId ?? "Unknown",
chip: identity?.chipId,
memory: ramTotal,
},
network_interfaces: networkInterfaces,
@@ -278,17 +256,15 @@ function transformTopology(
ram_total: ramTotal,
},
temp:
profile?.system?.temp !== undefined
? { gpu_temp_avg: profile.system.temp }
system?.temp !== undefined
? { gpu_temp_avg: system.temp }
: undefined,
gpu_usage:
profile?.system?.gpuUsage !== undefined
? [0, profile.system.gpuUsage]
: undefined,
sys_power: profile?.system?.sysPower,
system?.gpuUsage !== undefined ? [0, system.gpuUsage] : undefined,
sys_power: system?.sysPower,
},
last_macmon_update: Date.now() / 1000,
friendly_name: profile?.friendlyName,
friendly_name: identity?.friendlyName,
};
}
@@ -868,7 +844,13 @@ class AppStore {
const data: RawStateResponse = await response.json();
if (data.topology) {
this.topologyData = transformTopology(data.topology, data.nodeProfiles);
this.topologyData = transformTopology(
data.topology,
data.nodeIdentities,
data.nodeMemories,
data.nodeSystems,
data.nodeNetworks,
);
}
if (data.instances) {
this.instances = data.instances;

View File

@@ -205,6 +205,14 @@ def main():
logger.info("Starting EXO")
logger.info(f"EXO_LIBP2P_NAMESPACE: {os.getenv('EXO_LIBP2P_NAMESPACE')}")
# Set FAST_SYNCH override env var for runner subprocesses
if args.fast_synch is True:
os.environ["EXO_FAST_SYNCH"] = "on"
logger.info("FAST_SYNCH forced ON")
elif args.fast_synch is False:
os.environ["EXO_FAST_SYNCH"] = "off"
logger.info("FAST_SYNCH forced OFF")
node = anyio.run(Node.create, args)
anyio.run(node.run)
logger.info("EXO Shutdown complete")
@@ -218,6 +226,7 @@ class Args(CamelCaseModel):
api_port: PositiveInt = 52415
tb_only: bool = False
no_worker: bool = False
fast_synch: bool | None = None # None = auto, True = force on, False = force off
@classmethod
def parse(cls) -> Self:
@@ -259,6 +268,20 @@ class Args(CamelCaseModel):
"--no-worker",
action="store_true",
)
fast_synch_group = parser.add_mutually_exclusive_group()
fast_synch_group.add_argument(
"--fast-synch",
action="store_true",
dest="fast_synch",
default=None,
help="Force MLX FAST_SYNCH on (for JACCL backend)",
)
fast_synch_group.add_argument(
"--no-fast-synch",
action="store_false",
dest="fast_synch",
help="Force MLX FAST_SYNCH off",
)
args = parser.parse_args()
return cls(**vars(args)) # pyright: ignore[reportAny] - We are intentionally validating here, we can't do it statically

View File

@@ -1,13 +1,14 @@
import time
from collections.abc import AsyncGenerator
from http import HTTPStatus
from typing import cast
import anyio
from anyio import create_task_group
from anyio import BrokenResourceError, create_task_group
from anyio.abc import TaskGroup
from fastapi import FastAPI, HTTPException
from fastapi import FastAPI, HTTPException, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import StreamingResponse
from fastapi.responses import JSONResponse, StreamingResponse
from fastapi.staticfiles import StaticFiles
from hypercorn.asyncio import serve # pyright: ignore[reportUnknownVariableType]
from hypercorn.config import Config
@@ -29,6 +30,8 @@ from exo.shared.types.api import (
CreateInstanceParams,
CreateInstanceResponse,
DeleteInstanceResponse,
ErrorInfo,
ErrorResponse,
FinishReason,
GenerationStats,
ModelList,
@@ -49,7 +52,12 @@ from exo.shared.types.commands import (
TaskFinished,
)
from exo.shared.types.common import CommandId, NodeId, SessionId
from exo.shared.types.events import ChunkGenerated, Event, ForwarderEvent, IndexedEvent
from exo.shared.types.events import (
ChunkGenerated,
Event,
ForwarderEvent,
IndexedEvent,
)
from exo.shared.types.memory import Memory
from exo.shared.types.models import ModelId, ModelMetadata
from exo.shared.types.state import State
@@ -115,6 +123,7 @@ class API:
self.paused_ev: anyio.Event = anyio.Event()
self.app = FastAPI()
self._setup_exception_handlers()
self._setup_cors()
self._setup_routes()
@@ -145,6 +154,20 @@ class API:
self.paused_ev.set()
self.paused_ev = anyio.Event()
def _setup_exception_handlers(self) -> None:
@self.app.exception_handler(HTTPException)
async def http_exception_handler( # pyright: ignore[reportUnusedFunction]
_: Request, exc: HTTPException
) -> JSONResponse:
err = ErrorResponse(
error=ErrorInfo(
message=exc.detail,
type=HTTPStatus(exc.status_code).phrase,
code=exc.status_code,
)
)
return JSONResponse(err.model_dump(), status_code=exc.status_code)
def _setup_cors(self) -> None:
self.app.add_middleware(
CORSMiddleware,
@@ -406,6 +429,18 @@ class API:
"""Generate chat completion stream as JSON strings."""
async for chunk in self._chat_chunk_stream(command_id):
if chunk.finish_reason == "error":
error_response = ErrorResponse(
error=ErrorInfo(
message=chunk.error_message or "Internal server error",
type="InternalServerError",
code=500,
)
)
yield f"data: {error_response.model_dump_json()}\n\n"
yield "data: [DONE]\n\n"
return
chunk_response: ChatCompletionResponse = chunk_to_response(
chunk, command_id
)
@@ -426,6 +461,12 @@ class API:
finish_reason: FinishReason | None = None
async for chunk in self._chat_chunk_stream(command_id):
if chunk.finish_reason == "error":
raise HTTPException(
status_code=500,
detail=chunk.error_message or "Internal server error",
)
if model is None:
model = chunk.model
@@ -463,6 +504,12 @@ class API:
stats: GenerationStats | None = None
async for chunk in self._chat_chunk_stream(command_id):
if chunk.finish_reason == "error":
raise HTTPException(
status_code=500,
detail=chunk.error_message or "Internal server error",
)
if model is None:
model = chunk.model
@@ -552,9 +599,8 @@ class API:
"""Calculate total available memory across all nodes in bytes."""
total_available = Memory()
for node in self.state.topology.list_nodes():
if node.node_profile is not None:
total_available += node.node_profile.memory.ram_available
for memory in self.state.node_memories.values():
total_available += memory.ram_available
return total_available
@@ -607,14 +653,14 @@ class API:
for idx, event in self.event_buffer.drain_indexed():
self._event_log.append(event)
self.state = apply(self.state, IndexedEvent(event=event, idx=idx))
if (
isinstance(event, ChunkGenerated)
and event.command_id in self._chat_completion_queues
):
if isinstance(event, ChunkGenerated):
assert isinstance(event.chunk, TokenChunk)
await self._chat_completion_queues[event.command_id].send(
event.chunk
)
queue = self._chat_completion_queues.get(event.command_id)
if queue is not None:
try:
await queue.send(event.chunk)
except BrokenResourceError:
self._chat_completion_queues.pop(event.command_id, None)
async def _pause_on_new_election(self):
with self.election_receiver as ems:

View File

@@ -113,6 +113,7 @@ def place_instance(
node.node_profile.memory.ram_available
for node in cycle
if node.node_profile is not None
and node.node_profile.memory is not None
),
start=Memory(),
),

View File

@@ -25,7 +25,10 @@ class NodeWithProfile(BaseModel):
def narrow_all_nodes(nodes: list[NodeInfo]) -> TypeGuard[list[NodeWithProfile]]:
return all(node.node_profile is not None for node in nodes)
return all(
node.node_profile is not None and node.node_profile.memory is not None
for node in nodes
)
def filter_cycles_by_memory(
@@ -36,8 +39,14 @@ def filter_cycles_by_memory(
if not narrow_all_nodes(cycle):
continue
# narrow_all_nodes guarantees memory is not None
total_mem = sum(
(node.node_profile.memory.ram_available for node in cycle), start=Memory()
(
node.node_profile.memory.ram_available
for node in cycle
if node.node_profile.memory is not None
),
start=Memory(),
)
if total_mem >= required_memory:
filtered_cycles.append(cast(list[NodeInfo], cycle))
@@ -53,8 +62,13 @@ def get_shard_assignments_for_pipeline_parallel(
model_meta: ModelMetadata,
selected_cycle: list[NodeWithProfile],
):
# NodeWithProfile guarantees memory is not None
cycle_memory = sum(
(node.node_profile.memory.ram_available for node in selected_cycle),
(
node.node_profile.memory.ram_available
for node in selected_cycle
if node.node_profile.memory is not None
),
start=Memory(),
)
total_layers = model_meta.n_layers
@@ -67,6 +81,8 @@ def get_shard_assignments_for_pipeline_parallel(
if i == len(selected_cycle) - 1:
node_layers = total_layers - layers_assigned
else:
# NodeWithProfile guarantees memory is not None
assert node.node_profile.memory is not None
node_layers = round(
total_layers
* (

View File

@@ -0,0 +1,107 @@
# pyright: reportUnusedFunction=false, reportAny=false
from typing import Any, get_args
from fastapi import FastAPI, HTTPException
from fastapi.testclient import TestClient
from exo.shared.types.api import ErrorInfo, ErrorResponse, FinishReason
from exo.shared.types.chunks import TokenChunk
from exo.worker.tests.constants import MODEL_A_ID
def test_http_exception_handler_formats_openai_style() -> None:
"""Test that HTTPException is converted to OpenAI-style error format."""
from exo.master.api import API
app = FastAPI()
# Setup exception handler
api = object.__new__(API)
api.app = app
api._setup_exception_handlers() # pyright: ignore[reportPrivateUsage]
# Add test routes that raise HTTPException
@app.get("/test-error")
async def _test_error() -> None:
raise HTTPException(status_code=500, detail="Test error message")
@app.get("/test-not-found")
async def _test_not_found() -> None:
raise HTTPException(status_code=404, detail="Resource not found")
client = TestClient(app)
# Test 500 error
response = client.get("/test-error")
assert response.status_code == 500
data: dict[str, Any] = response.json()
assert "error" in data
assert data["error"]["message"] == "Test error message"
assert data["error"]["type"] == "Internal Server Error"
assert data["error"]["code"] == 500
# Test 404 error
response = client.get("/test-not-found")
assert response.status_code == 404
data = response.json()
assert "error" in data
assert data["error"]["message"] == "Resource not found"
assert data["error"]["type"] == "Not Found"
assert data["error"]["code"] == 404
def test_finish_reason_includes_error() -> None:
valid_reasons = get_args(FinishReason)
assert "error" in valid_reasons
def test_token_chunk_with_error_fields() -> None:
chunk = TokenChunk(
idx=0,
model=MODEL_A_ID,
text="",
token_id=0,
finish_reason="error",
error_message="Something went wrong",
)
assert chunk.finish_reason == "error"
assert chunk.error_message == "Something went wrong"
def test_token_chunk_without_error() -> None:
chunk = TokenChunk(
idx=1,
model=MODEL_A_ID,
text="Hello",
token_id=42,
finish_reason=None,
)
assert chunk.finish_reason is None
assert chunk.error_message is None
def test_error_response_construction() -> None:
error_response = ErrorResponse(
error=ErrorInfo(
message="Generation failed",
type="InternalServerError",
code=500,
)
)
assert error_response.error.message == "Generation failed"
assert error_response.error.code == 500
def test_normal_finish_reasons_still_work() -> None:
for reason in ["stop", "length", "tool_calls", "content_filter", "function_call"]:
chunk = TokenChunk(
idx=0,
model=MODEL_A_ID,
text="done",
token_id=100,
finish_reason=reason, # type: ignore[arg-type]
)
assert chunk.finish_reason == reason

View File

@@ -19,16 +19,13 @@ from exo.shared.types.events import (
ForwarderEvent,
IndexedEvent,
InstanceCreated,
NodePerformanceMeasured,
NodeIdentityMeasured,
NodeMemoryMeasured,
TaskCreated,
)
from exo.shared.types.memory import Memory
from exo.shared.types.models import ModelId, ModelMetadata
from exo.shared.types.profiling import (
MemoryPerformanceProfile,
NodePerformanceProfile,
SystemPerformanceProfile,
)
from exo.shared.types.profiling import MemoryPerformanceProfile
from exo.shared.types.tasks import ChatCompletion as ChatCompletionTask
from exo.shared.types.tasks import TaskStatus
from exo.shared.types.worker.instances import (
@@ -75,29 +72,39 @@ async def test_master():
tg.start_soon(master.run)
sender_node_id = NodeId(f"{keypair.to_peer_id().to_base58()}_sender")
# inject a NodePerformanceProfile event
logger.info("inject a NodePerformanceProfile event")
# inject NodeIdentityMeasured and NodeMemoryMeasured events
logger.info("inject NodeIdentityMeasured event")
await local_event_sender.send(
ForwarderEvent(
origin_idx=0,
origin=sender_node_id,
session=session_id,
event=(
NodePerformanceMeasured(
NodeIdentityMeasured(
when=str(datetime.now(tz=timezone.utc)),
node_id=node_id,
node_profile=NodePerformanceProfile(
model_id="maccy",
chip_id="arm",
friendly_name="test",
memory=MemoryPerformanceProfile(
ram_total=Memory.from_bytes(678948 * 1024),
ram_available=Memory.from_bytes(678948 * 1024),
swap_total=Memory.from_bytes(0),
swap_available=Memory.from_bytes(0),
),
network_interfaces=[],
system=SystemPerformanceProfile(),
model_id="maccy",
chip_id="arm",
friendly_name="test",
)
),
)
)
logger.info("inject NodeMemoryMeasured event")
await local_event_sender.send(
ForwarderEvent(
origin_idx=1,
origin=sender_node_id,
session=session_id,
event=(
NodeMemoryMeasured(
when=str(datetime.now(tz=timezone.utc)),
node_id=node_id,
memory=MemoryPerformanceProfile(
ram_total=Memory.from_bytes(678948 * 1024),
ram_available=Memory.from_bytes(678948 * 1024),
swap_total=Memory.from_bytes(0),
swap_available=Memory.from_bytes(0),
),
)
),
@@ -108,7 +115,7 @@ async def test_master():
logger.info("wait for initial topology event")
while len(list(master.state.topology.list_nodes())) == 0:
await anyio.sleep(0.001)
while len(master.state.node_profiles) == 0:
while len(master.state.node_identities) == 0:
await anyio.sleep(0.001)
logger.info("inject a CreateInstance Command")
@@ -155,17 +162,19 @@ async def test_master():
),
)
)
while len(_get_events()) < 3:
while len(_get_events()) < 4:
await anyio.sleep(0.01)
events = _get_events()
assert len(events) == 3
assert len(events) == 4
assert events[0].idx == 0
assert events[1].idx == 1
assert events[2].idx == 2
assert isinstance(events[0].event, NodePerformanceMeasured)
assert isinstance(events[1].event, InstanceCreated)
created_instance = events[1].event.instance
assert events[3].idx == 3
assert isinstance(events[0].event, NodeIdentityMeasured)
assert isinstance(events[1].event, NodeMemoryMeasured)
assert isinstance(events[2].event, InstanceCreated)
created_instance = events[2].event.instance
assert isinstance(created_instance, MlxRingInstance)
runner_id = list(created_instance.shard_assignments.runner_to_shard.keys())[0]
# Validate the shard assignments
@@ -197,10 +206,10 @@ async def test_master():
assert len(created_instance.hosts_by_node[node_id]) == 1
assert created_instance.hosts_by_node[node_id][0].ip == "0.0.0.0"
assert created_instance.ephemeral_port > 0
assert isinstance(events[2].event, TaskCreated)
assert events[2].event.task.task_status == TaskStatus.Pending
assert isinstance(events[2].event.task, ChatCompletionTask)
assert events[2].event.task.task_params == ChatCompletionTaskParams(
assert isinstance(events[3].event, TaskCreated)
assert events[3].event.task.task_status == TaskStatus.Pending
assert isinstance(events[3].event.task, ChatCompletionTask)
assert events[3].event.task.task_params == ChatCompletionTaskParams(
model="llama-3.2-1b",
messages=[
ChatCompletionMessage(role="user", content="Hello, how are you?")

View File

@@ -13,8 +13,10 @@ from exo.shared.types.events import (
InstanceDeleted,
NodeCreated,
NodeDownloadProgress,
NodeIdentityMeasured,
NodeMemoryMeasured,
NodePerformanceMeasured,
NodeNetworkMeasured,
NodeSystemMeasured,
NodeTimedOut,
RunnerDeleted,
RunnerStatusUpdated,
@@ -27,7 +29,13 @@ from exo.shared.types.events import (
TopologyEdgeCreated,
TopologyEdgeDeleted,
)
from exo.shared.types.profiling import NodePerformanceProfile, SystemPerformanceProfile
from exo.shared.types.profiling import (
MemoryPerformanceProfile,
NetworkInterfaceInfo,
NodeIdentity,
NodePerformanceProfile,
SystemPerformanceProfile,
)
from exo.shared.types.state import State
from exo.shared.types.tasks import Task, TaskId, TaskStatus
from exo.shared.types.topology import NodeInfo
@@ -51,8 +59,12 @@ def event_apply(event: Event, state: State) -> State:
return apply_topology_node_created(event, state)
case NodeTimedOut():
return apply_node_timed_out(event, state)
case NodePerformanceMeasured():
return apply_node_performance_measured(event, state)
case NodeIdentityMeasured():
return apply_node_identity_measured(event, state)
case NodeSystemMeasured():
return apply_node_system_measured(event, state)
case NodeNetworkMeasured():
return apply_node_network_measured(event, state)
case NodeDownloadProgress():
return apply_node_download_progress(event, state)
case NodeMemoryMeasured():
@@ -190,8 +202,19 @@ def apply_runner_deleted(event: RunnerDeleted, state: State) -> State:
def apply_node_timed_out(event: NodeTimedOut, state: State) -> State:
topology = copy.copy(state.topology)
state.topology.remove_node(event.node_id)
node_profiles = {
key: value for key, value in state.node_profiles.items() if key != event.node_id
node_identities = {
key: value
for key, value in state.node_identities.items()
if key != event.node_id
}
node_memories = {
key: value for key, value in state.node_memories.items() if key != event.node_id
}
node_systems = {
key: value for key, value in state.node_systems.items() if key != event.node_id
}
node_networks = {
key: value for key, value in state.node_networks.items() if key != event.node_id
}
last_seen = {
key: value for key, value in state.last_seen.items() if key != event.node_id
@@ -199,32 +222,120 @@ def apply_node_timed_out(event: NodeTimedOut, state: State) -> State:
return state.model_copy(
update={
"topology": topology,
"node_profiles": node_profiles,
"node_identities": node_identities,
"node_memories": node_memories,
"node_systems": node_systems,
"node_networks": node_networks,
"last_seen": last_seen,
}
)
def apply_node_performance_measured(
event: NodePerformanceMeasured, state: State
) -> State:
new_profiles: Mapping[NodeId, NodePerformanceProfile] = {
**state.node_profiles,
event.node_id: event.node_profile,
def _reconstruct_profile(
node_id: NodeId,
state: State,
*,
identity: NodeIdentity | None = None,
memory: MemoryPerformanceProfile | None = None,
system: SystemPerformanceProfile | None = None,
network_interfaces: list[NetworkInterfaceInfo] | None = None,
) -> NodePerformanceProfile:
"""Reconstruct a NodePerformanceProfile from split state storage.
Uses provided overrides, falling back to state values.
"""
ident = identity or state.node_identities.get(node_id)
mem = memory or state.node_memories.get(node_id)
sys = system or state.node_systems.get(node_id)
nets = (
network_interfaces
if network_interfaces is not None
else state.node_networks.get(node_id, [])
)
return NodePerformanceProfile(
model_id=ident.model_id if ident else None,
chip_id=ident.chip_id if ident else None,
friendly_name=ident.friendly_name if ident else None,
memory=mem,
network_interfaces=nets,
system=sys,
)
def apply_node_identity_measured(event: NodeIdentityMeasured, state: State) -> State:
topology = copy.copy(state.topology)
identity = NodeIdentity(
model_id=event.model_id,
chip_id=event.chip_id,
friendly_name=event.friendly_name,
)
new_identities: Mapping[NodeId, NodeIdentity] = {
**state.node_identities,
event.node_id: identity,
}
last_seen: Mapping[NodeId, datetime] = {
**state.last_seen,
event.node_id: datetime.fromisoformat(event.when),
}
state = state.model_copy(update={"node_profiles": new_profiles})
topology = copy.copy(state.topology)
# TODO: NodeCreated
if not topology.contains_node(event.node_id):
topology.add_node(NodeInfo(node_id=event.node_id))
topology.update_node_profile(event.node_id, event.node_profile)
reconstructed = _reconstruct_profile(event.node_id, state, identity=identity)
topology.update_node_profile(event.node_id, reconstructed)
return state.model_copy(
update={
"node_profiles": new_profiles,
"node_identities": new_identities,
"topology": topology,
"last_seen": last_seen,
}
)
def apply_node_system_measured(event: NodeSystemMeasured, state: State) -> State:
topology = copy.copy(state.topology)
new_systems: Mapping[NodeId, SystemPerformanceProfile] = {
**state.node_systems,
event.node_id: event.system,
}
last_seen: Mapping[NodeId, datetime] = {
**state.last_seen,
event.node_id: datetime.fromisoformat(event.when),
}
if not topology.contains_node(event.node_id):
topology.add_node(NodeInfo(node_id=event.node_id))
reconstructed = _reconstruct_profile(event.node_id, state, system=event.system)
topology.update_node_profile(event.node_id, reconstructed)
return state.model_copy(
update={
"node_systems": new_systems,
"topology": topology,
"last_seen": last_seen,
}
)
def apply_node_network_measured(event: NodeNetworkMeasured, state: State) -> State:
topology = copy.copy(state.topology)
new_networks: Mapping[NodeId, list[NetworkInterfaceInfo]] = {
**state.node_networks,
event.node_id: event.network_interfaces,
}
last_seen: Mapping[NodeId, datetime] = {
**state.last_seen,
event.node_id: datetime.fromisoformat(event.when),
}
if not topology.contains_node(event.node_id):
topology.add_node(NodeInfo(node_id=event.node_id))
reconstructed = _reconstruct_profile(
event.node_id, state, network_interfaces=event.network_interfaces
)
topology.update_node_profile(event.node_id, reconstructed)
return state.model_copy(
update={
"node_networks": new_networks,
"topology": topology,
"last_seen": last_seen,
}
@@ -232,57 +343,26 @@ def apply_node_performance_measured(
def apply_node_memory_measured(event: NodeMemoryMeasured, state: State) -> State:
existing = state.node_profiles.get(event.node_id)
topology = copy.copy(state.topology)
if existing is None:
created = NodePerformanceProfile(
model_id="unknown",
chip_id="unknown",
friendly_name="Unknown",
memory=event.memory,
network_interfaces=[],
system=SystemPerformanceProfile(
# TODO: flops_fp16=0.0,
gpu_usage=0.0,
temp=0.0,
sys_power=0.0,
pcpu_usage=0.0,
ecpu_usage=0.0,
ane_power=0.0,
),
)
created_profiles: Mapping[NodeId, NodePerformanceProfile] = {
**state.node_profiles,
event.node_id: created,
}
last_seen: Mapping[NodeId, datetime] = {
**state.last_seen,
event.node_id: datetime.fromisoformat(event.when),
}
if not topology.contains_node(event.node_id):
topology.add_node(NodeInfo(node_id=event.node_id))
# TODO: NodeCreated
topology.update_node_profile(event.node_id, created)
return state.model_copy(
update={
"node_profiles": created_profiles,
"topology": topology,
"last_seen": last_seen,
}
)
updated = existing.model_copy(update={"memory": event.memory})
updated_profiles: Mapping[NodeId, NodePerformanceProfile] = {
**state.node_profiles,
event.node_id: updated,
new_memories: Mapping[NodeId, MemoryPerformanceProfile] = {
**state.node_memories,
event.node_id: event.memory,
}
last_seen: Mapping[NodeId, datetime] = {
**state.last_seen,
event.node_id: datetime.fromisoformat(event.when),
}
# TODO: NodeCreated
if not topology.contains_node(event.node_id):
topology.add_node(NodeInfo(node_id=event.node_id))
topology.update_node_profile(event.node_id, updated)
reconstructed = _reconstruct_profile(event.node_id, state, memory=event.memory)
topology.update_node_profile(event.node_id, reconstructed)
return state.model_copy(
update={"node_profiles": updated_profiles, "topology": topology}
update={
"node_memories": new_memories,
"topology": topology,
"last_seen": last_seen,
}
)

View File

@@ -11,10 +11,21 @@ from exo.shared.types.worker.instances import Instance, InstanceId, InstanceMeta
from exo.shared.types.worker.shards import Sharding
FinishReason = Literal[
"stop", "length", "tool_calls", "content_filter", "function_call"
"stop", "length", "tool_calls", "content_filter", "function_call", "error"
]
class ErrorInfo(BaseModel):
message: str
type: str
param: str | None = None
code: int
class ErrorResponse(BaseModel):
error: ErrorInfo
class ModelListModel(BaseModel):
id: str
object: str = "model"

View File

@@ -22,6 +22,7 @@ class TokenChunk(BaseChunk):
token_id: int
finish_reason: FinishReason | None = None
stats: GenerationStats | None = None
error_message: str | None = None
class ImageChunk(BaseChunk):

View File

@@ -2,10 +2,14 @@ from datetime import datetime
from pydantic import Field
from exo.shared.topology import Connection, NodePerformanceProfile
from exo.shared.topology import Connection
from exo.shared.types.chunks import GenerationChunk
from exo.shared.types.common import CommandId, Id, NodeId, SessionId
from exo.shared.types.profiling import MemoryPerformanceProfile
from exo.shared.types.profiling import (
MemoryPerformanceProfile,
NetworkInterfaceInfo,
SystemPerformanceProfile,
)
from exo.shared.types.tasks import Task, TaskId, TaskStatus
from exo.shared.types.worker.downloads import DownloadProgress
from exo.shared.types.worker.instances import Instance, InstanceId
@@ -85,13 +89,35 @@ class NodeTimedOut(BaseEvent):
node_id: NodeId
class NodePerformanceMeasured(BaseEvent):
class NodeIdentityMeasured(BaseEvent):
"""Static identity info - emitted once at startup."""
node_id: NodeId
when: str # this is a manually cast datetime overrode by the master when the event is indexed, rather than the local time on the device
node_profile: NodePerformanceProfile
model_id: str
chip_id: str
friendly_name: str
class NodeSystemMeasured(BaseEvent):
"""Dynamic system metrics (GPU, temp, power) - emitted at 1s intervals."""
node_id: NodeId
when: str # this is a manually cast datetime overrode by the master when the event is indexed, rather than the local time on the device
system: SystemPerformanceProfile
class NodeNetworkMeasured(BaseEvent):
"""Semi-static network interface info - emitted at 30s intervals."""
node_id: NodeId
when: str # this is a manually cast datetime overrode by the master when the event is indexed, rather than the local time on the device
network_interfaces: list[NetworkInterfaceInfo]
class NodeMemoryMeasured(BaseEvent):
"""Dynamic memory metrics - emitted at 0.5s intervals."""
node_id: NodeId
when: str # this is a manually cast datetime overrode by the master when the event is indexed, rather than the local time on the device
memory: MemoryPerformanceProfile
@@ -127,7 +153,9 @@ Event = (
| RunnerDeleted
| NodeCreated
| NodeTimedOut
| NodePerformanceMeasured
| NodeIdentityMeasured
| NodeSystemMeasured
| NodeNetworkMeasured
| NodeMemoryMeasured
| NodeDownloadProgress
| ChunkGenerated

View File

@@ -52,13 +52,21 @@ class NetworkInterfaceInfo(CamelCaseModel):
ip_address: str
class NodePerformanceProfile(CamelCaseModel):
class NodeIdentity(CamelCaseModel):
"""Static identity info for a node."""
model_id: str
chip_id: str
friendly_name: str
memory: MemoryPerformanceProfile
class NodePerformanceProfile(CamelCaseModel):
model_id: str | None = None
chip_id: str | None = None
friendly_name: str | None = None
memory: MemoryPerformanceProfile | None = None
network_interfaces: list[NetworkInterfaceInfo] = []
system: SystemPerformanceProfile
system: SystemPerformanceProfile | None = None
class ConnectionProfile(CamelCaseModel):

View File

@@ -7,7 +7,12 @@ from pydantic.alias_generators import to_camel
from exo.shared.topology import Topology, TopologySnapshot
from exo.shared.types.common import NodeId
from exo.shared.types.profiling import NodePerformanceProfile
from exo.shared.types.profiling import (
MemoryPerformanceProfile,
NetworkInterfaceInfo,
NodeIdentity,
SystemPerformanceProfile,
)
from exo.shared.types.tasks import Task, TaskId
from exo.shared.types.worker.downloads import DownloadProgress
from exo.shared.types.worker.instances import Instance, InstanceId
@@ -35,7 +40,10 @@ class State(CamelCaseModel):
runners: Mapping[RunnerId, RunnerStatus] = {}
downloads: Mapping[NodeId, Sequence[DownloadProgress]] = {}
tasks: Mapping[TaskId, Task] = {}
node_profiles: Mapping[NodeId, NodePerformanceProfile] = {}
node_identities: Mapping[NodeId, NodeIdentity] = {}
node_memories: Mapping[NodeId, MemoryPerformanceProfile] = {}
node_systems: Mapping[NodeId, SystemPerformanceProfile] = {}
node_networks: Mapping[NodeId, list[NetworkInterfaceInfo]] = {}
last_seen: Mapping[NodeId, datetime] = {}
topology: Topology = Field(default_factory=Topology)
last_event_applied_idx: int = Field(default=-1, ge=-1)

View File

@@ -2,7 +2,9 @@ import json
import os
import resource
import sys
import threading
import time
from collections.abc import Callable
from pathlib import Path
from typing import Any, cast
@@ -82,6 +84,45 @@ def get_weights_size(model_shard_meta: ShardMetadata) -> Memory:
)
class ModelLoadingTimeoutError(Exception):
pass
TimeoutCallback = Callable[[], None]
def eval_with_timeout(
mlx_item: Any, # pyright: ignore[reportAny]
timeout_seconds: float = 60.0,
on_timeout: TimeoutCallback | None = None,
) -> None:
"""Evaluate MLX item with a hard timeout.
If on_timeout callback is provided, it will be called before terminating
the process. This allows the runner to send a failure event before exit.
"""
completed = threading.Event()
def watchdog() -> None:
if not completed.wait(timeout=timeout_seconds):
logger.error(
f"mlx_item evaluation timed out after {timeout_seconds:.0f}s. "
"This may indicate an issue with FAST_SYNCH and tensor parallel sharding. "
"Terminating process."
)
if on_timeout is not None:
on_timeout()
os._exit(1)
watchdog_thread = threading.Thread(target=watchdog, daemon=True)
watchdog_thread.start()
try:
mx.eval(mlx_item) # pyright: ignore[reportAny]
finally:
completed.set()
def mx_barrier(group: Group | None = None):
mx.eval(
mx.distributed.all_sum(
@@ -188,7 +229,9 @@ def initialize_mlx(
def load_mlx_items(
bound_instance: BoundInstance, group: Group | None
bound_instance: BoundInstance,
group: Group | None,
on_timeout: TimeoutCallback | None = None,
) -> tuple[Model, TokenizerWrapper]:
if group is None:
logger.info(f"Single device used for {bound_instance.instance}")
@@ -202,7 +245,9 @@ def load_mlx_items(
else:
logger.info("Starting distributed init")
start_time = time.perf_counter()
model, tokenizer = shard_and_load(bound_instance.bound_shard, group=group)
model, tokenizer = shard_and_load(
bound_instance.bound_shard, group=group, on_timeout=on_timeout
)
end_time = time.perf_counter()
logger.info(
f"Time taken to shard and load model: {(end_time - start_time):.2f}s"
@@ -216,6 +261,7 @@ def load_mlx_items(
def shard_and_load(
shard_metadata: ShardMetadata,
group: Group,
on_timeout: TimeoutCallback | None = None,
) -> tuple[nn.Module, TokenizerWrapper]:
model_path = build_model_path(shard_metadata.model_meta.model_id)
@@ -252,7 +298,15 @@ def shard_and_load(
logger.info(f"loading model from {model_path} with pipeline parallelism")
model = pipeline_auto_parallel(model, group, shard_metadata)
mx.eval(model.parameters())
# Estimate timeout based on model size
base_timeout = float(os.environ.get("EXO_MODEL_LOAD_TIMEOUT", "60"))
model_size_gb = get_weights_size(shard_metadata).in_bytes / (1024**3)
timeout_seconds = base_timeout + model_size_gb / 5
logger.info(
f"Evaluating model parameters with timeout of {timeout_seconds:.0f}s "
f"(model size: {model_size_gb:.1f}GB)"
)
eval_with_timeout(model.parameters(), timeout_seconds, on_timeout)
# TODO: Do we need this?
mx.eval(model)

View File

@@ -16,8 +16,10 @@ from exo.shared.types.events import (
ForwarderEvent,
IndexedEvent,
NodeDownloadProgress,
NodeIdentityMeasured,
NodeMemoryMeasured,
NodePerformanceMeasured,
NodeNetworkMeasured,
NodeSystemMeasured,
TaskCreated,
TaskStatusUpdated,
TopologyEdgeCreated,
@@ -25,7 +27,11 @@ from exo.shared.types.events import (
)
from exo.shared.types.models import ModelId
from exo.shared.types.multiaddr import Multiaddr
from exo.shared.types.profiling import MemoryPerformanceProfile, NodePerformanceProfile
from exo.shared.types.profiling import (
MemoryPerformanceProfile,
NetworkInterfaceInfo,
SystemPerformanceProfile,
)
from exo.shared.types.state import State
from exo.shared.types.tasks import (
CreateRunner,
@@ -51,7 +57,13 @@ from exo.worker.download.download_utils import (
from exo.worker.download.shard_downloader import RepoDownloadProgress, ShardDownloader
from exo.worker.plan import plan
from exo.worker.runner.runner_supervisor import RunnerSupervisor
from exo.worker.utils import start_polling_memory_metrics, start_polling_node_metrics
from exo.worker.utils import (
IdentityMetrics,
start_polling_identity_metrics,
start_polling_memory_metrics,
start_polling_network_metrics,
start_polling_system_metrics,
)
from exo.worker.utils.net_profile import check_reachable
@@ -98,37 +110,51 @@ class Worker:
async def run(self):
logger.info("Starting Worker")
# TODO: CLEANUP HEADER
async def resource_monitor_callback(
node_performance_profile: NodePerformanceProfile,
) -> None:
async def identity_callback(identity: IdentityMetrics) -> None:
await self.event_sender.send(
NodePerformanceMeasured(
NodeIdentityMeasured(
node_id=self.node_id,
node_profile=node_performance_profile,
model_id=identity.model_id,
chip_id=identity.chip_id,
friendly_name=identity.friendly_name,
when=str(datetime.now(tz=timezone.utc)),
),
)
async def memory_monitor_callback(
memory_profile: MemoryPerformanceProfile,
) -> None:
async def system_callback(system: SystemPerformanceProfile) -> None:
await self.event_sender.send(
NodeSystemMeasured(
node_id=self.node_id,
system=system,
when=str(datetime.now(tz=timezone.utc)),
),
)
async def network_callback(interfaces: list[NetworkInterfaceInfo]) -> None:
await self.event_sender.send(
NodeNetworkMeasured(
node_id=self.node_id,
network_interfaces=interfaces,
when=str(datetime.now(tz=timezone.utc)),
),
)
async def memory_callback(memory: MemoryPerformanceProfile) -> None:
await self.event_sender.send(
NodeMemoryMeasured(
node_id=self.node_id,
memory=memory_profile,
memory=memory,
when=str(datetime.now(tz=timezone.utc)),
)
)
# END CLEANUP
async with create_task_group() as tg:
self._tg = tg
tg.start_soon(self.plan_step)
tg.start_soon(start_polling_node_metrics, resource_monitor_callback)
tg.start_soon(start_polling_memory_metrics, memory_monitor_callback)
tg.start_soon(start_polling_identity_metrics, identity_callback)
tg.start_soon(start_polling_system_metrics, system_callback)
tg.start_soon(start_polling_network_metrics, network_callback)
tg.start_soon(start_polling_memory_metrics, memory_callback)
tg.start_soon(self._emit_existing_download_progress)
tg.start_soon(self._connection_message_event_writer)
tg.start_soon(self._resend_out_for_delivery)

View File

@@ -17,15 +17,23 @@ def entrypoint(
task_receiver: MpReceiver[Task],
_logger: "loguru.Logger",
) -> None:
if (
isinstance(bound_instance.instance, MlxJacclInstance)
and len(bound_instance.instance.ibv_devices) >= 2
fast_synch_override = os.environ.get("EXO_FAST_SYNCH")
if fast_synch_override == "on" or (
fast_synch_override != "off"
and (
isinstance(bound_instance.instance, MlxJacclInstance)
and len(bound_instance.instance.ibv_devices) >= 2
)
):
os.environ["MLX_METAL_FAST_SYNCH"] = "1"
else:
os.environ["MLX_METAL_FAST_SYNCH"] = "0"
global logger
logger = _logger
logger.info(f"Fast synch flag: {os.environ['MLX_METAL_FAST_SYNCH']}")
# Import main after setting global logger - this lets us just import logger from this module
try:
from exo.worker.runner.runner import main

View File

@@ -1,6 +1,8 @@
import time
from collections.abc import Generator
from contextlib import contextmanager
from functools import cache
from typing import cast
import mlx.core as mx
from mlx_lm.models.gpt_oss import Model as GptOssModel
@@ -13,6 +15,7 @@ from openai_harmony import ( # pyright: ignore[reportMissingTypeStubs]
from exo.shared.types.api import ChatCompletionMessageText
from exo.shared.types.chunks import TokenChunk
from exo.shared.types.common import CommandId
from exo.shared.types.events import (
ChunkGenerated,
Event,
@@ -20,6 +23,7 @@ from exo.shared.types.events import (
TaskAcknowledged,
TaskStatusUpdated,
)
from exo.shared.types.models import ModelId
from exo.shared.types.tasks import (
ChatCompletion,
ConnectToGroup,
@@ -48,6 +52,7 @@ from exo.shared.types.worker.runners import (
RunnerWarmingUp,
)
from exo.utils.channels import MpReceiver, MpSender
from exo.worker.engines.mlx import Model
from exo.worker.engines.mlx.generator.generate import mlx_generate, warmup_inference
from exo.worker.engines.mlx.utils_mlx import (
initialize_mlx,
@@ -57,6 +62,33 @@ from exo.worker.engines.mlx.utils_mlx import (
from exo.worker.runner.bootstrap import logger
@contextmanager
def send_error_chunk_on_exception(
event_sender: MpSender[Event],
command_id: CommandId,
model_id: ModelId,
device_rank: int,
):
try:
yield
except Exception as e:
logger.error(e)
if device_rank == 0:
event_sender.send(
ChunkGenerated(
command_id=command_id,
chunk=TokenChunk(
idx=0,
model=model_id,
text="",
token_id=0,
finish_reason="error",
error_message=str(e),
),
)
)
def main(
bound_instance: BoundInstance,
event_sender: MpSender[Event],
@@ -118,7 +150,20 @@ def main(
)
)
model, tokenizer = load_mlx_items(bound_instance, group)
def on_model_load_timeout() -> None:
event_sender.send(
RunnerStatusUpdated(
runner_id=runner_id,
runner_status=RunnerFailed(
error_message="Model loading timed out"
),
)
)
time.sleep(0.5)
model, tokenizer = load_mlx_items(
bound_instance, group, on_timeout=on_model_load_timeout
)
current_status = RunnerLoaded()
logger.info("runner loaded")
@@ -135,7 +180,7 @@ def main(
logger.info(f"warming up inference for instance: {instance}")
toks = warmup_inference(
model=model,
model=cast(Model, model),
tokenizer=tokenizer,
# kv_prefix_cache=kv_prefix_cache, # supply for warmup-time prefix caching
)
@@ -148,8 +193,6 @@ def main(
case ChatCompletion(task_params=task_params, command_id=command_id) if (
isinstance(current_status, RunnerReady)
):
assert model
assert tokenizer
logger.info(f"received chat request: {str(task)[:500]}")
current_status = RunnerRunning()
logger.info("runner running")
@@ -158,41 +201,47 @@ def main(
runner_id=runner_id, runner_status=current_status
)
)
assert task_params.messages[0].content is not None
_check_for_debug_prompts(task_params.messages[0].content)
with send_error_chunk_on_exception(
event_sender,
command_id,
shard_metadata.model_meta.model_id,
shard_metadata.device_rank,
):
assert model
assert tokenizer
assert task_params.messages[0].content is not None
_check_for_debug_prompts(task_params.messages[0].content)
# Generate responses using the actual MLX generation
mlx_generator = mlx_generate(
model=model,
tokenizer=tokenizer,
task=task_params,
)
# Generate responses using the actual MLX generation
mlx_generator = mlx_generate(
model=cast(Model, model),
tokenizer=tokenizer,
task=task_params,
)
# GPT-OSS specific parsing to match other model formats.
if isinstance(model, GptOssModel):
mlx_generator = parse_gpt_oss(mlx_generator)
# GPT-OSS specific parsing to match other model formats.
if isinstance(model, GptOssModel):
mlx_generator = parse_gpt_oss(mlx_generator)
# TODO: Add tool call parser here
# TODO: Add tool call parser here
for response in mlx_generator:
match response:
case GenerationResponse():
if shard_metadata.device_rank == 0:
event_sender.send(
ChunkGenerated(
command_id=command_id,
chunk=TokenChunk(
idx=response.token,
model=shard_metadata.model_meta.model_id,
text=response.text,
token_id=response.token,
finish_reason=response.finish_reason,
stats=response.stats,
),
for response in mlx_generator:
match response:
case GenerationResponse():
if shard_metadata.device_rank == 0:
event_sender.send(
ChunkGenerated(
command_id=command_id,
chunk=TokenChunk(
idx=response.token,
model=shard_metadata.model_meta.model_id,
text=response.text,
token_id=response.token,
finish_reason=response.finish_reason,
stats=response.stats,
),
)
)
)
# case TokenizedResponse():
# TODO: something here ig
current_status = RunnerReady()
logger.info("runner ready")

View File

@@ -0,0 +1,50 @@
# pyright: reportAny=false
from unittest.mock import MagicMock
from exo.shared.types.chunks import TokenChunk
from exo.shared.types.common import CommandId
from exo.shared.types.events import ChunkGenerated
from exo.worker.runner.runner import send_error_chunk_on_exception
from exo.worker.tests.constants import MODEL_A_ID
def test_send_error_chunk_on_exception_no_error() -> None:
event_sender = MagicMock()
command_id = CommandId()
with send_error_chunk_on_exception(
event_sender, command_id, MODEL_A_ID, device_rank=0
):
_ = 1 + 1
event_sender.send.assert_not_called()
def test_send_error_chunk_on_exception_catches_error() -> None:
event_sender = MagicMock()
command_id = CommandId()
with send_error_chunk_on_exception(
event_sender, command_id, MODEL_A_ID, device_rank=0
):
raise ValueError("test error")
event_sender.send.assert_called_once()
call_args = event_sender.send.call_args[0][0]
assert isinstance(call_args, ChunkGenerated)
assert call_args.command_id == command_id
assert isinstance(call_args.chunk, TokenChunk)
assert call_args.chunk.finish_reason == "error"
assert call_args.chunk.error_message == "test error"
def test_send_error_chunk_on_exception_skips_non_rank_zero() -> None:
event_sender = MagicMock()
command_id = CommandId()
with send_error_chunk_on_exception(
event_sender, command_id, MODEL_A_ID, device_rank=1
):
raise ValueError("test error")
event_sender.send.assert_not_called()

View File

@@ -1,6 +1,15 @@
from .profile import start_polling_memory_metrics, start_polling_node_metrics
from .profile import (
IdentityMetrics,
start_polling_identity_metrics,
start_polling_memory_metrics,
start_polling_network_metrics,
start_polling_system_metrics,
)
__all__ = [
"start_polling_node_metrics",
"IdentityMetrics",
"start_polling_identity_metrics",
"start_polling_memory_metrics",
"start_polling_network_metrics",
"start_polling_system_metrics",
]

View File

@@ -1,6 +1,7 @@
import asyncio
import os
import platform
from dataclasses import dataclass
from typing import Any, Callable, Coroutine
import anyio
@@ -9,7 +10,7 @@ from loguru import logger
from exo.shared.types.memory import Memory
from exo.shared.types.profiling import (
MemoryPerformanceProfile,
NodePerformanceProfile,
NetworkInterfaceInfo,
SystemPerformanceProfile,
)
@@ -27,6 +28,13 @@ from .system_info import (
)
@dataclass(frozen=True)
class IdentityMetrics:
model_id: str
chip_id: str
friendly_name: str
async def get_metrics_async() -> Metrics | None:
"""Return detailed Metrics on macOS or a minimal fallback elsewhere."""
@@ -67,48 +75,73 @@ async def start_polling_memory_metrics(
await anyio.sleep(poll_interval_s)
async def start_polling_node_metrics(
callback: Callable[[NodePerformanceProfile], Coroutine[Any, Any, None]],
):
poll_interval_s = 1.0
async def start_polling_identity_metrics(
callback: Callable[[IdentityMetrics], Coroutine[Any, Any, None]],
*,
poll_interval_s: float = 30.0,
) -> None:
"""Continuously poll and emit identity metrics at 30s intervals."""
while True:
try:
model_id, chip_id = await get_model_and_chip()
friendly_name = await get_friendly_name()
await callback(
IdentityMetrics(
model_id=model_id,
chip_id=chip_id,
friendly_name=friendly_name,
)
)
except Exception as e:
logger.opt(exception=e).error("Failed to emit identity metrics")
finally:
await anyio.sleep(poll_interval_s)
async def start_polling_system_metrics(
callback: Callable[[SystemPerformanceProfile], Coroutine[Any, Any, None]],
*,
poll_interval_s: float = 1.0,
) -> None:
"""Continuously poll and emit system metrics (GPU, temp, power) at 1s intervals."""
while True:
try:
metrics = await get_metrics_async()
if metrics is None:
return
network_interfaces = get_network_interfaces()
# these awaits could be joined but realistically they should be cached
model_id, chip_id = await get_model_and_chip()
friendly_name = await get_friendly_name()
# do the memory profile last to get a fresh reading to not conflict with the other memory profiling loop
memory_profile = get_memory_profile()
await callback(
NodePerformanceProfile(
model_id=model_id,
chip_id=chip_id,
friendly_name=friendly_name,
network_interfaces=network_interfaces,
memory=memory_profile,
system=SystemPerformanceProfile(
gpu_usage=metrics.gpu_usage[1],
temp=metrics.temp.gpu_temp_avg,
sys_power=metrics.sys_power,
pcpu_usage=metrics.pcpu_usage[1],
ecpu_usage=metrics.ecpu_usage[1],
ane_power=metrics.ane_power,
),
SystemPerformanceProfile(
gpu_usage=metrics.gpu_usage[1],
temp=metrics.temp.gpu_temp_avg,
sys_power=metrics.sys_power,
pcpu_usage=metrics.pcpu_usage[1],
ecpu_usage=metrics.ecpu_usage[1],
ane_power=metrics.ane_power,
)
)
except asyncio.TimeoutError:
logger.warning(
"[resource_monitor] Operation timed out after 30s, skipping this cycle."
"[system_monitor] Operation timed out after 30s, skipping this cycle."
)
except MacMonError as e:
logger.opt(exception=e).error("Resource Monitor encountered error")
logger.opt(exception=e).error("System Monitor encountered error")
return
finally:
await anyio.sleep(poll_interval_s)
async def start_polling_network_metrics(
callback: Callable[[list[NetworkInterfaceInfo]], Coroutine[Any, Any, None]],
*,
poll_interval_s: float = 30.0,
) -> None:
"""Continuously poll and emit network interface info at 30s intervals."""
while True:
try:
network_interfaces = get_network_interfaces()
await callback(network_interfaces)
except Exception as e:
logger.opt(exception=e).error("Network Monitor encountered error")
finally:
await anyio.sleep(poll_interval_s)