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Author SHA1 Message Date
Evan 523eff541e aaa 2026-02-18 16:57:07 +00:00
329 changed files with 6835 additions and 33201 deletions
+1 -9
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@@ -159,7 +159,7 @@ jobs:
fi
- name: Install Homebrew packages
run: brew install just awscli
run: brew install just awscli macmon
- name: Install UV
uses: astral-sh/setup-uv@v6
@@ -243,14 +243,6 @@ jobs:
# Build the bundle
# ============================================================
- name: Add pinned macmon to PATH
run: |
MACMON_DIR=$(nix develop --command sh -c 'dirname $(which macmon)')
echo "Using macmon from: $MACMON_DIR"
echo "$MACMON_DIR" >> $GITHUB_PATH
# Remove any Homebrew macmon so PyInstaller can't accidentally pick it up
brew uninstall macmon 2>/dev/null || true
- name: Build PyInstaller bundle
run: uv run pyinstaller packaging/pyinstaller/exo.spec
+1 -17
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@@ -215,22 +215,6 @@ class StreamContext:
traceback: object | None = ...,
) -> None: ...
def device_info() -> dict[str, str | int]:
"""
Get information about the GPU device and system settings.
Currently returns:
* ``architecture``
* ``max_buffer_size``
* ``max_recommended_working_set_size``
* ``memory_size``
* ``resource_limit``
Returns:
dict: A dictionary with string keys and string or integer values.
"""
def abs(a: array, /, *, stream: Stream | Device | None = ...) -> array:
"""
Element-wise absolute value.
@@ -2396,7 +2380,7 @@ def degrees(a: array, /, *, stream: Stream | Device | None = ...) -> array:
array: The angles in degrees.
"""
def depends[T](inputs: T, dependencies: array | Sequence[array]) -> T:
def depends(inputs: array | Sequence[array], dependencies: array | Sequence[array]):
"""
Insert dependencies between arrays in the graph. The outputs are
identical to ``inputs`` but with dependencies on ``dependencies``.
+6 -2
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@@ -1,5 +1,9 @@
from .layers import *
from .utils import *
"""
This type stub file was generated by pyright.
"""
from layers import *
from utils import *
from . import init as init
from . import losses as losses
+20 -16
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@@ -1,16 +1,20 @@
from .activations import *
from .base import *
from .containers import *
from .convolution import *
from .convolution_transpose import *
from .distributed import *
from .dropout import *
from .embedding import *
from .linear import *
from .normalization import *
from .pooling import *
from .positional_encoding import *
from .quantized import *
from .recurrent import *
from .transformer import *
from .upsample import *
"""
This type stub file was generated by pyright.
"""
from activations import *
from base import *
from containers import *
from convolution import *
from convolution_transpose import *
from distributed import *
from dropout import *
from embedding import *
from linear import *
from normalization import *
from pooling import *
from positional_encoding import *
from quantized import *
from recurrent import *
from transformer import *
from upsample import *
+2 -2
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@@ -53,7 +53,7 @@ class Module(dict):
mx.eval(model.parameters())
"""
def __call__(self, *args: Any, **kwargs: Any) -> mx.array: ...
__call__: Callable
def __init__(self) -> None:
"""Should be called by the subclasses of ``Module``."""
@@ -200,7 +200,7 @@ class Module(dict):
) -> mx.MX_ARRAY_TREE: # -> dict[Any, Any | dict[Any, Any | dict[Any, Any] | list[Any]] | dict[Any, Any] | list[Any]]:
"""Return the submodules that do not contain other modules."""
def update(self, parameters: dict[str, Any], strict: bool = ...) -> Module:
def update(self, parameters: dict, strict: bool = ...) -> Module:
"""Replace the parameters of this Module with the provided ones in the
dict of dicts and lists.
@@ -32,7 +32,6 @@ class Conv1d(Module):
"""
weight: mx.array
bias: mx.array | None
groups: int
def __init__(
self,
-4
View File
@@ -40,10 +40,6 @@ class Linear(Module):
bias (bool, optional): If set to ``False`` then the layer will
not use a bias. Default is ``True``.
"""
weight: mx.array
bias: mx.array | None
def __init__(self, input_dims: int, output_dims: int, bias: bool = ...) -> None: ...
def __call__(self, x: mx.array) -> mx.array: ...
def to_quantized(
@@ -88,9 +88,6 @@ class RMSNorm(Module):
dims (int): The feature dimension of the input to normalize over
eps (float): A small additive constant for numerical stability
"""
weight: mx.array
def __init__(self, dims: int, eps: float = ...) -> None: ...
def __call__(self, x) -> mx.array: ...
+8 -11
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@@ -7,10 +7,7 @@ from typing import Any, Callable, Dict, List, Optional, Tuple, Union
from mlx.core import MX_ARRAY_TREE
def tree_map(
fn: Callable[..., Any],
tree: Any,
*rest: Any,
is_leaf: Callable[..., bool] | None = ...,
fn: Callable, tree: Any, *rest: Any, is_leaf: Optional[Callable] = ...
) -> Any:
"""Applies ``fn`` to the leaves of the Python tree ``tree`` and
returns a new collection with the results.
@@ -47,11 +44,11 @@ def tree_map(
"""
def tree_map_with_path(
fn: Callable[..., Any],
fn: Callable,
tree: Any,
*rest: Any,
is_leaf: Callable[..., bool] | None = ...,
path: str | None = ...,
is_leaf: Optional[Callable] = ...,
path: Optional[Any] = ...,
) -> Any:
"""Applies ``fn`` to the path and leaves of the Python tree ``tree`` and
returns a new collection with the results.
@@ -83,9 +80,9 @@ def tree_map_with_path(
def tree_flatten(
tree: Any,
prefix: str = ...,
is_leaf: Callable[..., bool] | None = ...,
destination: list[tuple[str, Any]] | dict[str, Any] | None = ...,
) -> list[tuple[str, Any]] | dict[str, Any]:
is_leaf: Optional[Callable] = ...,
destination: Optional[Union[List[Tuple[str, Any]], Dict[str, Any]]] = ...,
) -> Union[List[Tuple[str, Any]], Dict[str, Any]]:
"""Flattens a Python tree to a list of key, value tuples.
The keys are using the dot notation to define trees of arbitrary depth and
@@ -121,7 +118,7 @@ def tree_flatten(
the Python tree.
"""
def tree_unflatten(tree: list[tuple[str, Any]] | dict[str, Any]) -> Any:
def tree_unflatten(tree: Union[List[Tuple[str, Any]], Dict[str, Any]]) -> Any:
"""Recreate a Python tree from its flat representation.
.. code-block:: python
+20 -66
View File
@@ -30,7 +30,7 @@ def str2bool(string): # -> bool:
def setup_arg_parser(): # -> ArgumentParser:
"""Set up and return the argument parser."""
generation_stream: mx.Stream
generation_stream = ...
@contextlib.contextmanager
def wired_limit(
@@ -73,11 +73,9 @@ class GenerationResponse:
finish_reason: Optional[str] = ...
def maybe_quantize_kv_cache(
prompt_cache: Any,
quantized_kv_start: int | None,
kv_group_size: int | None,
kv_bits: int | None,
) -> None: ...
prompt_cache, quantized_kv_start, kv_group_size, kv_bits
): # -> None:
...
def generate_step(
prompt: mx.array,
model: nn.Module,
@@ -254,92 +252,48 @@ class BatchResponse:
texts: List[str]
stats: BatchStats
caches: Optional[List[List[Any]]]
def _left_pad_prompts(prompts: Any, max_length: Optional[int] = ...) -> mx.array: ...
def _right_pad_prompts(prompts: Any, max_length: Optional[int] = ...) -> mx.array: ...
def _make_cache(
model: Any, left_padding: Any, max_kv_size: Optional[int]
) -> List[Any]: ...
def _merge_caches(caches: Any) -> List[Any]: ...
@dataclass
class Batch:
uids: List[int]
y: mx.array
logprobs: List[mx.array] | mx.array
logprobs: mx.array
max_tokens: List[int]
num_tokens: List[int]
cache: List[Any]
samplers: List[Callable[[mx.array], mx.array] | None]
logits_processors: List[List[Callable[[mx.array, mx.array], mx.array]]]
tokens: List[mx.array]
def __len__(self) -> int: ...
def filter(self, keep_idx: List[int]) -> None: ...
def extend(self, other: "Batch") -> None: ...
def extract_cache(self, idx: int) -> List[Any]: ...
def __len__(self): # -> int:
...
def filter(self, keep_idx: List[int]): # -> None:
...
def extend(self, other): # -> None:
...
class BatchGenerator:
model: nn.Module
sampler: Callable[[mx.array], mx.array]
stop_tokens: set[int]
max_kv_size: Optional[int]
prefill_step_size: int
completion_batch_size: int
prefill_batch_size: int
unprocessed_prompts: List[Any]
active_batch: Optional[Batch]
prompt_progress_callback: Callable[[List[Tuple[int, int, int]]], None]
_stats: BatchStats
_next_count: int
@dataclass
class Response:
uid: int
token: int
logprobs: mx.array
finish_reason: Optional[str]
prompt_cache: Any
def __init__(
self,
model: Any,
model,
max_tokens: int = ...,
stop_tokens: Optional[set[int]] = ...,
stop_tokens: Optional[set] = ...,
sampler: Optional[Callable[[mx.array], mx.array]] = ...,
logits_processors: Optional[
List[Callable[[mx.array, mx.array], mx.array]]
] = ...,
completion_batch_size: int = ...,
prefill_batch_size: int = ...,
prefill_step_size: int = ...,
prompt_progress_callback: Optional[
Callable[[List[Tuple[int, int, int]]], None]
] = ...,
max_kv_size: Optional[int] = ...,
) -> None: ...
def close(self) -> None: ...
def insert(
self,
prompts: Any,
max_tokens: Union[List[int], int, None] = ...,
caches: Any = ...,
samplers: Optional[List[Any]] = ...,
logits_processors: Optional[List[Any]] = ...,
) -> List[int]: ...
def remove(
self, uids: List[int], return_prompt_caches: bool = ...
) -> Optional[dict[int, List[Any]]]: ...
def stats(self) -> BatchStats: ...
def next(self) -> List[Response]: ...
def _process_prompts(self, prompts: List[Any]) -> Batch: ...
def _step(
self,
input_tokens: mx.array,
prompt_cache: List[Any],
samplers: Optional[List[Any]],
logits_processors: Optional[List[Any]],
tokens: List[mx.array],
) -> Tuple[mx.array, List[mx.array]]: ...
self, prompts, max_tokens: Union[List[int], int, None] = ...
): # -> list[Any]:
...
def stats(self): # -> BatchStats:
...
def next(self): # -> list[Any]:
...
def batch_generate(
model,
+61 -52
View File
@@ -16,7 +16,7 @@ class Cache(Protocol):
self, keys: mx.array, values: mx.array
) -> tuple[mx.array, mx.array]: ...
@property
def state(self) -> tuple[mx.array | None, mx.array | None]: ...
def state(self) -> tuple[mx.array, mx.array]: ...
@state.setter
def state(self, v) -> None: ...
@@ -88,18 +88,17 @@ def create_attention_mask(
) -> array | Literal["causal"] | None: ...
class _BaseCache(Cache):
keys: mx.array | None
values: mx.array | None
keys: mx.array
values: mx.array
offset: int
@property
def state(self) -> tuple[mx.array | None, mx.array | None]: ...
def state(self) -> tuple[mx.array, mx.array]: ...
@state.setter
def state(self, v) -> None: ...
@property
def meta_state(self) -> Literal[""]: ...
@meta_state.setter
def meta_state(self, v) -> None: ...
def trim(self, n: int) -> int: ...
def is_trimmable(self) -> Literal[False]: ...
@classmethod
def from_state(cls, state, meta_state) -> Self: ...
@@ -115,13 +114,15 @@ class ConcatenateKVCache(_BaseCache):
def update_and_fetch(self, keys, values): # -> tuple[Any | array, Any | array]:
...
@property
def state(self) -> tuple[mx.array | None, mx.array | None]: ...
def state(self): # -> tuple[Any | array | None, Any | array | None]:
...
@state.setter
def state(self, v): # -> None:
...
def is_trimmable(self): # -> Literal[True]:
...
def trim(self, n: int) -> int: ...
def trim(self, n): # -> int:
...
def make_mask(self, *args, **kwargs): # -> array | Literal['causal'] | None:
...
@@ -131,7 +132,10 @@ class QuantizedKVCache(_BaseCache):
def update_and_fetch(self, keys, values): # -> Any:
...
@property
def state(self) -> tuple[mx.array | None, mx.array | None]: ...
def state(
self,
): # -> tuple[Any | tuple[array, array, array] | None, Any | tuple[array, array, array] | None] | Any:
...
@state.setter
def state(self, v): # -> None:
...
@@ -143,7 +147,8 @@ class QuantizedKVCache(_BaseCache):
...
def is_trimmable(self): # -> Literal[True]:
...
def trim(self, n: int) -> int: ...
def trim(self, n): # -> int:
...
def make_mask(self, *args, **kwargs): # -> array | Literal['causal'] | None:
...
@@ -155,30 +160,22 @@ class KVCache(_BaseCache):
@property
def state(
self,
) -> tuple[mx.array | None, mx.array | None]: ...
) -> tuple[array, array]: ...
@state.setter
def state(self, v) -> None: ...
def is_trimmable(self): # -> Literal[True]:
...
def trim(self, n: int) -> int: ...
def trim(self, n): # -> int:
...
def to_quantized(
self, group_size: int = ..., bits: int = ...
) -> QuantizedKVCache: ...
def make_mask(
self, *args: Any, **kwargs: Any
) -> mx.array | Literal["causal"] | None: ...
def make_mask(self, *args, **kwargs): # -> array | Literal['causal'] | None:
...
class RotatingKVCache(_BaseCache):
step = ...
keys: mx.array | None
values: mx.array | None
keep: int
max_size: int
_idx: int
def __init__(self, max_size, keep=...) -> None: ...
def _trim(
self, trim_size: int, v: mx.array, append: mx.array | None = ...
) -> mx.array: ...
def update_and_fetch(
self, keys, values
): # -> tuple[array | Any, array | Any] | tuple[array | Any, array | Any | None]:
@@ -186,7 +183,8 @@ class RotatingKVCache(_BaseCache):
@property
def state(
self,
) -> tuple[mx.array | None, mx.array | None]: ...
): # -> tuple[Any | array, Any | array] | tuple[Any | array | None, Any | array | None]:
...
@state.setter
def state(self, v): # -> None:
...
@@ -198,7 +196,8 @@ class RotatingKVCache(_BaseCache):
...
def is_trimmable(self): # -> bool:
...
def trim(self, n: int) -> int: ...
def trim(self, n): # -> int:
...
def to_quantized(
self, group_size: int = ..., bits: int = ...
) -> QuantizedKVCache: ...
@@ -213,7 +212,8 @@ class ArraysCache(_BaseCache):
...
def __getitem__(self, idx): ...
@property
def state(self) -> tuple[mx.array | None, mx.array | None]: ...
def state(self): # -> list[Any | array] | list[array]:
...
@state.setter
def state(self, v): # -> None:
...
@@ -227,7 +227,8 @@ class ArraysCache(_BaseCache):
In-place extend this cache with the other cache.
"""
def make_mask(self, N: int) -> mx.array | None: ...
def make_mask(self, N: int): # -> array | None:
...
class MambaCache(ArraysCache):
def __init__(self, left_padding: Optional[List[int]] = ...) -> None: ...
@@ -238,7 +239,8 @@ class ChunkedKVCache(KVCache):
...
def update_and_fetch(self, keys, values): # -> tuple[array, array]:
...
def trim(self, n: int) -> int: ...
def trim(self, n): # -> int:
...
@property
def meta_state(self): # -> tuple[str, ...]:
...
@@ -251,9 +253,10 @@ class CacheList(_BaseCache):
def __getitem__(self, idx): ...
def is_trimmable(self): # -> bool:
...
def trim(self, n: int) -> int: ...
def trim(self, n): ...
@property
def state(self) -> list[tuple[mx.array | None, mx.array | None]]: ...
def state(self): # -> list[Any]:
...
@state.setter
def state(self, v): # -> None:
...
@@ -268,14 +271,29 @@ class CacheList(_BaseCache):
"""
class BatchKVCache(_BaseCache):
step: int
keys: array | None
values: array | None
offset: array
left_padding: array
_idx: int
def __init__(self, left_padding: List[int]) -> None: ...
def update_and_fetch(self, keys: array, values: array) -> tuple[array, array]: ...
step = ...
def __init__(self, left_padding: List[int]) -> None:
"""
The BatchKV cache expects inputs to be left-padded.
E.g. the following prompts:
[1, 3, 5]
[7]
[2, 6, 8, 9]
Should be padded like so:
[0, 1, 3, 5]
[0, 0, 0, 7]
[2, 6, 8, 9]
And ``left_padding`` specifies the amount of padding for each.
In this case, ``left_padding = [1, 3, 0]``.
"""
def update_and_fetch(self, keys, values): # -> tuple[array | Any, array | Any]:
...
@property
def state(
self,
@@ -301,21 +319,12 @@ class BatchKVCache(_BaseCache):
"""
class BatchRotatingKVCache(_BaseCache):
step: int
keys: array | None
values: array | None
offset: array
left_padding: array
max_size: int
_idx: int
_offset: int
rotated: bool
_lengths: array | None
def __init__(self, max_size: int, left_padding: List[int]) -> None: ...
def _trim(self, trim_size: int, v: array, append: array | None = ...) -> array: ...
def _update_in_place(self, keys: array, values: array) -> tuple[array, array]: ...
def _update_concat(self, keys: array, values: array) -> tuple[array, array]: ...
def update_and_fetch(self, keys: array, values: array) -> tuple[array, array]: ...
step = ...
def __init__(self, max_size, left_padding: List[int]) -> None: ...
def update_and_fetch(
self, keys, values
): # -> tuple[array | Any, array | Any] | tuple[array | Any, array | Any | None]:
...
@property
def state(
self,
@@ -1,35 +0,0 @@
from typing import Optional
import mlx.core as mx
def compute_g(A_log: mx.array, a: mx.array, dt_bias: mx.array) -> mx.array: ...
def gated_delta_update(
q: mx.array,
k: mx.array,
v: mx.array,
a: mx.array,
b: mx.array,
A_log: mx.array,
dt_bias: mx.array,
state: Optional[mx.array] = ...,
mask: Optional[mx.array] = ...,
use_kernel: bool = ...,
) -> tuple[mx.array, mx.array]: ...
def gated_delta_ops(
q: mx.array,
k: mx.array,
v: mx.array,
g: mx.array,
beta: mx.array,
state: Optional[mx.array] = ...,
mask: Optional[mx.array] = ...,
) -> tuple[mx.array, mx.array]: ...
def gated_delta_kernel(
q: mx.array,
k: mx.array,
v: mx.array,
g: mx.array,
beta: mx.array,
state: mx.array,
mask: Optional[mx.array] = ...,
) -> tuple[mx.array, mx.array]: ...
-154
View File
@@ -1,154 +0,0 @@
from dataclasses import dataclass
from typing import Any, List, Optional, Tuple
import mlx.core as mx
import mlx.nn as nn
from .cache import ArraysCache, KVCache
from .switch_layers import SwitchMLP
@dataclass
class ModelArgs:
model_type: str
vocab_size: int
hidden_size: int
intermediate_size: int
num_hidden_layers: int
max_position_embeddings: int
num_attention_heads: int
num_key_value_heads: int
attention_bias: bool
mamba_num_heads: int
mamba_head_dim: int
mamba_proj_bias: bool
ssm_state_size: int
conv_kernel: int
n_groups: int
mlp_bias: bool
layer_norm_epsilon: float
use_bias: bool
use_conv_bias: bool
hybrid_override_pattern: List[str]
head_dim: Optional[int]
moe_intermediate_size: Optional[int]
moe_shared_expert_intermediate_size: Optional[int]
n_group: Optional[int]
n_routed_experts: Optional[int]
n_shared_experts: Optional[int]
topk_group: Optional[int]
num_experts_per_tok: Optional[int]
norm_topk_prob: Optional[bool]
routed_scaling_factor: Optional[float]
time_step_limit: Optional[Tuple[float, float]]
time_step_min: Optional[float]
time_step_max: Optional[float]
@classmethod
def from_dict(cls, params: dict[str, Any]) -> ModelArgs: ...
def __post_init__(self) -> None: ...
class NemotronHMamba2Mixer(nn.Module):
num_heads: int
hidden_size: int
ssm_state_size: int
conv_kernel_size: int
intermediate_size: int
n_groups: int
head_dim: int
conv_dim: int
conv1d: nn.Conv1d
in_proj: nn.Linear
dt_bias: mx.array
A_log: mx.array
D: mx.array
norm: nn.RMSNorm
heads_per_group: int
out_proj: nn.Linear
def __init__(self, args: ModelArgs) -> None: ...
def __call__(
self,
hidden_states: mx.array,
mask: Optional[mx.array],
cache: Optional[ArraysCache] = None,
) -> mx.array: ...
class NemotronHAttention(nn.Module):
hidden_size: int
num_heads: int
head_dim: int
num_key_value_heads: int
scale: float
q_proj: nn.Linear
k_proj: nn.Linear
v_proj: nn.Linear
o_proj: nn.Linear
def __init__(self, args: ModelArgs) -> None: ...
def __call__(
self,
x: mx.array,
mask: Optional[mx.array] = None,
cache: Optional[KVCache] = None,
) -> mx.array: ...
class NemotronHMLP(nn.Module):
up_proj: nn.Linear
down_proj: nn.Linear
def __init__(
self, args: ModelArgs, intermediate_size: Optional[int] = None
) -> None: ...
def __call__(self, x: mx.array) -> mx.array: ...
class NemotronHMoE(nn.Module):
num_experts_per_tok: int
switch_mlp: SwitchMLP
shared_experts: NemotronHMLP
def __init__(self, config: ModelArgs) -> None: ...
def __call__(self, x: mx.array) -> mx.array: ...
class NemotronHBlock(nn.Module):
block_type: str
norm: nn.RMSNorm
mixer: NemotronHMamba2Mixer | NemotronHAttention | NemotronHMLP | NemotronHMoE
def __init__(self, args: ModelArgs, block_type: str) -> None: ...
def __call__(
self,
x: mx.array,
mask: Optional[mx.array] = None,
cache: Optional[Any] = None,
) -> mx.array: ...
class NemotronHModel(nn.Module):
embeddings: nn.Embedding
layers: list[NemotronHBlock]
norm_f: nn.RMSNorm
fa_idx: int
ssm_idx: int
def __init__(self, args: ModelArgs) -> None: ...
def __call__(
self,
inputs: mx.array,
cache: Optional[Any] = None,
) -> mx.array: ...
class Model(nn.Module):
args: ModelArgs
backbone: NemotronHModel
lm_head: nn.Linear
model_type: str
def __init__(self, args: ModelArgs) -> None: ...
def __call__(
self,
inputs: mx.array,
cache: Optional[Any] = None,
) -> mx.array: ...
@property
def layers(self) -> list[NemotronHBlock]: ...
def make_cache(self) -> list[ArraysCache | KVCache]: ...
def sanitize(self, weights: dict[str, Any]) -> dict[str, Any]: ...
-153
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@@ -1,153 +0,0 @@
from dataclasses import dataclass
from typing import Any, Optional
import mlx.core as mx
import mlx.nn as nn
from .cache import ArraysCache, KVCache
from .qwen3_next import (
Qwen3NextAttention as Attention,
Qwen3NextMLP as MLP,
Qwen3NextRMSNormGated as RMSNormGated,
Qwen3NextSparseMoeBlock,
)
SparseMoeBlock = Qwen3NextSparseMoeBlock
from .switch_layers import SwitchGLU
@dataclass
class TextModelArgs:
model_type: str
hidden_size: int
intermediate_size: int
num_hidden_layers: int
num_attention_heads: int
rms_norm_eps: float
vocab_size: int
num_key_value_heads: int
max_position_embeddings: int
linear_num_value_heads: int
linear_num_key_heads: int
linear_key_head_dim: int
linear_value_head_dim: int
linear_conv_kernel_dim: int
tie_word_embeddings: bool
attention_bias: bool
head_dim: Optional[int]
full_attention_interval: int
num_experts: int
num_experts_per_tok: int
decoder_sparse_step: int
shared_expert_intermediate_size: int
moe_intermediate_size: int
norm_topk_prob: bool
rope_parameters: Optional[dict[str, Any]]
partial_rotary_factor: float
rope_theta: float
rope_scaling: Optional[dict[str, Any]]
@classmethod
def from_dict(cls, params: dict[str, Any]) -> TextModelArgs: ...
def __post_init__(self) -> None: ...
class GatedDeltaNet(nn.Module):
hidden_size: int
num_v_heads: int
num_k_heads: int
head_k_dim: int
head_v_dim: int
key_dim: int
value_dim: int
conv_kernel_size: int
conv_dim: int
conv1d: nn.Conv1d
in_proj_qkv: nn.Linear
in_proj_z: nn.Linear
in_proj_b: nn.Linear
in_proj_a: nn.Linear
dt_bias: mx.array
A_log: mx.array
norm: RMSNormGated
out_proj: nn.Linear
def __init__(self, config: TextModelArgs) -> None: ...
def __call__(
self,
inputs: mx.array,
mask: Optional[mx.array] = None,
cache: Optional[Any] = None,
) -> mx.array: ...
class DecoderLayer(nn.Module):
is_linear: bool
linear_attn: GatedDeltaNet
self_attn: Attention
input_layernorm: nn.RMSNorm
post_attention_layernorm: nn.RMSNorm
mlp: MLP | SparseMoeBlock
def __init__(self, args: TextModelArgs, layer_idx: int) -> None: ...
def __call__(
self,
x: mx.array,
mask: Optional[mx.array] = None,
cache: Optional[Any] = None,
) -> mx.array: ...
class Qwen3_5TextModel(nn.Module):
embed_tokens: nn.Embedding
layers: list[DecoderLayer]
norm: nn.RMSNorm
ssm_idx: int
fa_idx: int
def __init__(self, args: TextModelArgs) -> None: ...
def __call__(
self,
inputs: mx.array,
cache: Optional[Any] = None,
input_embeddings: Optional[mx.array] = None,
) -> mx.array: ...
class TextModel(nn.Module):
args: TextModelArgs
model_type: str
model: Qwen3_5TextModel
lm_head: nn.Linear
def __init__(self, args: TextModelArgs) -> None: ...
def __call__(
self,
inputs: mx.array,
cache: Optional[Any] = None,
input_embeddings: Optional[mx.array] = None,
) -> mx.array: ...
@property
def layers(self) -> list[DecoderLayer]: ...
def make_cache(self) -> list[ArraysCache | KVCache]: ...
def sanitize(self, weights: dict[str, Any]) -> dict[str, Any]: ...
@dataclass
class ModelArgs:
model_type: str
text_config: dict[str, Any]
@classmethod
def from_dict(cls, params: dict[str, Any]) -> ModelArgs: ...
class Model(nn.Module):
args: ModelArgs
model_type: str
language_model: TextModel
def __init__(self, args: ModelArgs) -> None: ...
def __call__(
self,
inputs: mx.array,
cache: Optional[Any] = None,
input_embeddings: Optional[mx.array] = None,
) -> mx.array: ...
def sanitize(self, weights: dict[str, Any]) -> dict[str, Any]: ...
@property
def layers(self) -> list[DecoderLayer]: ...
def make_cache(self) -> list[ArraysCache | KVCache]: ...
@@ -1,19 +0,0 @@
from dataclasses import dataclass
from typing import Any, Optional
import mlx.core as mx
import mlx.nn as nn
from .cache import ArraysCache, KVCache
from .qwen3_5 import DecoderLayer, Model as Qwen3_5Model, TextModel
@dataclass
class ModelArgs:
model_type: str
text_config: dict[str, Any]
@classmethod
def from_dict(cls, params: dict[str, Any]) -> ModelArgs: ...
class Model(Qwen3_5Model):
def sanitize(self, weights: dict[str, Any]) -> dict[str, Any]: ...
-13
View File
@@ -5,18 +5,8 @@ from typing import Any, Optional
import mlx.core as mx
import mlx.nn as nn
from .cache import ArraysCache, KVCache
from .switch_layers import SwitchGLU
class Qwen3NextRMSNormGated(nn.Module):
eps: float
weight: mx.array
def __init__(self, hidden_size: int, eps: float = ...) -> None: ...
def __call__(
self, hidden_states: mx.array, gate: mx.array | None = None
) -> mx.array: ...
class Qwen3NextMLP(nn.Module):
gate_proj: nn.Linear
down_proj: nn.Linear
@@ -100,8 +90,6 @@ class Qwen3NextModel(nn.Module):
embed_tokens: nn.Embedding
layers: list[Qwen3NextDecoderLayer]
norm: nn.RMSNorm
ssm_idx: int
fa_idx: int
def __init__(self, args: Any) -> None: ...
def __call__(
@@ -124,4 +112,3 @@ class Model(nn.Module):
def sanitize(self, weights: dict[str, Any]) -> dict[str, Any]: ...
@property
def layers(self) -> list[Qwen3NextDecoderLayer]: ...
def make_cache(self) -> list[ArraysCache | KVCache]: ...
-51
View File
@@ -1,51 +0,0 @@
from typing import Any, Optional
import mlx.nn as nn
class YarnRoPE(nn.Module):
def __init__(
self,
dims: int,
traditional: bool = ...,
max_position_embeddings: int = ...,
base: float = ...,
scaling_factor: float = ...,
original_max_position_embeddings: int = ...,
beta_fast: float = ...,
beta_slow: float = ...,
mscale: float = ...,
mscale_all_dim: float = ...,
) -> None: ...
class Llama3RoPE(nn.Module):
def __init__(
self,
dims: int,
traditional: bool = ...,
max_position_embeddings: int = ...,
base: float = ...,
scaling_factor: float = ...,
original_max_position_embeddings: int = ...,
low_freq_factor: float = ...,
high_freq_factor: float = ...,
) -> None: ...
class SuScaledRoPE(nn.Module):
def __init__(
self,
dims: int,
traditional: bool = ...,
max_position_embeddings: int = ...,
base: float = ...,
short_factor: Any = ...,
long_factor: Any = ...,
original_max_position_embeddings: int = ...,
) -> None: ...
def initialize_rope(
dims: int,
base: float = ...,
traditional: bool = ...,
scaling_config: Optional[dict[str, Any]] = ...,
max_position_embeddings: Optional[int] = ...,
) -> nn.Module: ...
@@ -73,9 +73,6 @@ class SwitchGLU(nn.Module):
def __call__(self, x, indices) -> mx.array: ...
class SwitchMLP(nn.Module):
fc1: SwitchLinear
fc2: SwitchLinear
def __init__(
self,
input_dims: int,
+1 -1
View File
@@ -48,7 +48,7 @@ def make_logits_processors(
logit_bias: Optional[Dict[int, float]] = ...,
repetition_penalty: Optional[float] = ...,
repetition_context_size: Optional[int] = ...,
) -> list[Callable[[mx.array, mx.array], mx.array]]:
): # -> list[Any]:
"""
Make logits processors for use with ``generate_step``.
+4 -4
View File
@@ -39,11 +39,11 @@ class StreamingDetokenizer:
"""
__slots__ = ...
def reset(self) -> None: ...
def add_token(self, token: int) -> None: ...
def finalize(self) -> None: ...
def reset(self): ...
def add_token(self, token): ...
def finalize(self): ...
@property
def last_segment(self) -> str:
def last_segment(self):
"""Return the last segment of readable text since last time this property was accessed."""
class NaiveStreamingDetokenizer(StreamingDetokenizer):
View File
-12
View File
@@ -1,12 +0,0 @@
from typing import Any
def get_message_json(
model_name: str,
prompt: str,
role: str = "user",
skip_image_token: bool = False,
skip_audio_token: bool = False,
num_images: int = 0,
num_audios: int = 0,
**kwargs: Any,
) -> dict[str, Any]: ...
-15
View File
@@ -1,15 +0,0 @@
from pathlib import Path
from typing import Any
class ImageProcessor:
def preprocess(
self, images: list[dict[str, Any]], **kwargs: Any
) -> dict[str, Any]: ...
def __call__(self, **kwargs: Any) -> dict[str, Any]: ...
def load_image_processor(
model_path: str | Path, **kwargs: Any
) -> ImageProcessor | None: ...
def load_processor(
model_path: str | Path, add_detokenizer: bool = ..., **kwargs: Any
) -> ImageProcessor: ...
-8
View File
@@ -1,8 +0,0 @@
from typing import Any, Self
class safe_open:
def __init__(self, filename: str, framework: str = "pt") -> None: ...
def __enter__(self) -> Self: ...
def __exit__(self, *args: Any) -> None: ...
def keys(self) -> list[str]: ...
def get_tensor(self, name: str) -> Any: ...
+1 -123
View File
@@ -11,18 +11,9 @@ To run EXO from source:
```bash
brew install uv
```
- [rust](https://github.com/rust-lang/rustup) (to build Rust bindings, nightly for now)
```bash
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
rustup toolchain install nightly
```
- [macmon](https://github.com/vladkens/macmon) (for hardware monitoring on Apple Silicon)
Use the pinned fork revision used by this repo instead of Homebrew `macmon`.
```bash
cargo install --git https://github.com/swiftraccoon/macmon \
--rev 9154d234f763fbeffdcb4135d0bbbaf80609699b \
macmon \
--force
brew install macmon
```
```bash
@@ -48,119 +39,6 @@ Write pure functions where possible. When adding new code, prefer Rust unless th
Run `nix fmt` to auto-format your code before submitting.
## Model Cards
EXO uses TOML-based model cards to define model metadata and capabilities. Model cards are stored in:
- `resources/inference_model_cards/` for text generation models
- `resources/image_model_cards/` for image generation models
- `~/.exo/custom_model_cards/` for user-added custom models
### Adding a Model Card
To add a new model, create a TOML file with the following structure:
```toml
model_id = "mlx-community/Llama-3.2-1B-Instruct-4bit"
n_layers = 16
hidden_size = 2048
supports_tensor = true
tasks = ["TextGeneration"]
family = "llama"
quantization = "4bit"
base_model = "Llama 3.2 1B"
capabilities = ["text"]
[storage_size]
in_bytes = 729808896
```
### Required Fields
- `model_id`: Hugging Face model identifier
- `n_layers`: Number of transformer layers
- `hidden_size`: Hidden dimension size
- `supports_tensor`: Whether the model supports tensor parallelism
- `tasks`: List of supported tasks (`TextGeneration`, `TextToImage`, `ImageToImage`)
- `family`: Model family (e.g., "llama", "deepseek", "qwen")
- `quantization`: Quantization level (e.g., "4bit", "8bit", "bf16")
- `base_model`: Human-readable base model name
- `capabilities`: List of capabilities (e.g., `["text"]`, `["text", "thinking"]`)
### Optional Fields
- `components`: For multi-component models (like image models with separate text encoders and transformers)
- `uses_cfg`: Whether the model uses classifier-free guidance (for image models)
- `trust_remote_code`: Whether to allow remote code execution (defaults to `false` for security)
### Capabilities
The `capabilities` field defines what the model can do:
- `text`: Standard text generation
- `thinking`: Model supports chain-of-thought reasoning
- `thinking_toggle`: Thinking can be enabled/disabled via `enable_thinking` parameter
- `image_edit`: Model supports image-to-image editing (FLUX.1-Kontext)
### Security Note
By default, `trust_remote_code` is set to `false` for security. Only enable it if the model explicitly requires remote code execution from the Hugging Face hub.
## API Adapters
EXO supports multiple API formats through an adapter pattern. Adapters convert API-specific request formats to the internal `TextGenerationTaskParams` format and convert internal token chunks back to API-specific responses.
### Adapter Architecture
All adapters live in `src/exo/master/adapters/` and follow the same pattern:
1. Convert API-specific requests to `TextGenerationTaskParams`
2. Handle both streaming and non-streaming response generation
3. Convert internal `TokenChunk` objects to API-specific formats
4. Manage error handling and edge cases
### Existing Adapters
- `chat_completions.py`: OpenAI Chat Completions API
- `claude.py`: Anthropic Claude Messages API
- `responses.py`: OpenAI Responses API
- `ollama.py`: Ollama API (for OpenWebUI compatibility)
### Adding a New API Adapter
To add support for a new API format:
1. Create a new adapter file in `src/exo/master/adapters/`
2. Implement a request conversion function:
```python
def your_api_request_to_text_generation(
request: YourAPIRequest,
) -> TextGenerationTaskParams:
# Convert API request to internal format
pass
```
3. Implement streaming response generation:
```python
async def generate_your_api_stream(
command_id: CommandId,
chunk_stream: AsyncGenerator[TokenChunk | ErrorChunk | ToolCallChunk, None],
) -> AsyncGenerator[str, None]:
# Convert internal chunks to API-specific streaming format
pass
```
4. Implement non-streaming response collection:
```python
async def collect_your_api_response(
command_id: CommandId,
chunk_stream: AsyncGenerator[TokenChunk | ErrorChunk | ToolCallChunk, None],
) -> AsyncGenerator[str]:
# Collect all chunks and return single response
pass
```
5. Register the adapter endpoints in `src/exo/master/api.py`
The adapter pattern keeps API-specific logic isolated from core inference systems. Internal systems (worker, runner, event sourcing) only see `TextGenerationTaskParams` and `TokenChunk` objects - no API-specific types cross the adapter boundary.
For detailed API documentation, see [docs/api.md](docs/api.md).
## Testing
EXO relies heavily on manual testing at this point in the project, but this is evolving. Before submitting a change, test both before and after to demonstrate how your change improves behavior. Do the best you can with the hardware you have available - if you need help testing, ask and we'll do our best to assist. Add automated tests where possible - we're actively working to substantially improve our automated testing story.
Generated
+2 -35
View File
@@ -216,28 +216,6 @@ dependencies = [
"windows-sys 0.61.2",
]
[[package]]
name = "async-stream"
version = "0.3.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0b5a71a6f37880a80d1d7f19efd781e4b5de42c88f0722cc13bcb6cc2cfe8476"
dependencies = [
"async-stream-impl",
"futures-core",
"pin-project-lite",
]
[[package]]
name = "async-stream-impl"
version = "0.3.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "c7c24de15d275a1ecfd47a380fb4d5ec9bfe0933f309ed5e705b775596a3574d"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.111",
]
[[package]]
name = "async-trait"
version = "0.1.89"
@@ -912,7 +890,7 @@ dependencies = [
"delegate",
"env_logger",
"extend",
"futures-lite",
"futures",
"libp2p",
"log",
"networking",
@@ -936,12 +914,6 @@ dependencies = [
"syn 2.0.111",
]
[[package]]
name = "fastrand"
version = "2.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "37909eebbb50d72f9059c3b6d82c0463f2ff062c9e95845c43a6c9c0355411be"
[[package]]
name = "ff"
version = "0.13.1"
@@ -1050,10 +1022,7 @@ version = "2.6.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "f78e10609fe0e0b3f4157ffab1876319b5b0db102a2c60dc4626306dc46b44ad"
dependencies = [
"fastrand",
"futures-core",
"futures-io",
"parking",
"pin-project-lite",
]
@@ -2781,16 +2750,14 @@ dependencies = [
name = "networking"
version = "0.0.1"
dependencies = [
"async-stream",
"delegate",
"either",
"extend",
"futures-lite",
"futures",
"futures-timer",
"keccak-const",
"libp2p",
"log",
"pin-project",
"tokio",
"tracing-subscriber",
"util",
+7 -3
View File
@@ -1,6 +1,10 @@
[workspace]
resolver = "3"
members = ["rust/networking", "rust/exo_pyo3_bindings", "rust/util"]
members = [
"rust/networking",
"rust/exo_pyo3_bindings",
"rust/util",
]
[workspace.package]
version = "0.0.1"
@@ -25,14 +29,14 @@ util = { path = "rust/util" }
# Macro dependecies
extend = "1.2"
delegate = "0.13"
pin-project = "1"
# Utility dependencies
keccak-const = "0.2"
# Async dependencies
async-stream = "0.3"
tokio = "1.46"
futures-lite = "2.6.1"
futures = "0.3"
futures-timer = "3.0"
# Data structures
+5 -140
View File
@@ -26,8 +26,6 @@ exo connects all your devices into an AI cluster. Not only does exo enable runni
- **Topology-Aware Auto Parallel**: exo figures out the best way to split your model across all available devices based on a realtime view of your device topology. It takes into account device resources and network latency/bandwidth between each link.
- **Tensor Parallelism**: exo supports sharding models, for up to 1.8x speedup on 2 devices and 3.2x speedup on 4 devices.
- **MLX Support**: exo uses [MLX](https://github.com/ml-explore/mlx) as an inference backend and [MLX distributed](https://ml-explore.github.io/mlx/build/html/usage/distributed.html) for distributed communication.
- **Multiple API Compatibility**: Compatible with OpenAI Chat Completions API, Claude Messages API, OpenAI Responses API, and Ollama API - use your existing tools and clients.
- **Custom Model Support**: Load custom models from HuggingFace hub to expand the range of available models.
## Dashboard
@@ -74,19 +72,12 @@ There are two ways to run exo:
### Run from Source (macOS)
If you have [Nix](https://nixos.org/) installed, you can skip most of the steps below and run exo directly:
If you have [Nix](https://nixos.org/) installed, you can skip most of the steps below and run exo directly (after accepting the Cachix cache):
```bash
nix run .#exo
```
**Note:** To accept the Cachix binary cache (and avoid the Xcode Metal ToolChain), add to `/etc/nix/nix.conf`:
```
trusted-users = root (or your username)
experimental-features = nix-command flakes
```
Then restart the Nix daemon: `sudo launchctl kickstart -k system/org.nixos.nix-daemon`
**Prerequisites:**
- [Xcode](https://developer.apple.com/xcode/) (provides the Metal ToolChain required for MLX compilation)
- [brew](https://github.com/Homebrew/brew) (for simple package management on macOS)
@@ -95,10 +86,11 @@ Then restart the Nix daemon: `sudo launchctl kickstart -k system/org.nixos.nix-d
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
```
- [uv](https://github.com/astral-sh/uv) (for Python dependency management)
- [macmon](https://github.com/vladkens/macmon) (for hardware monitoring on Apple Silicon)
- [node](https://github.com/nodejs/node) (for building the dashboard)
```bash
brew install uv node
brew install uv macmon node
```
- [rust](https://github.com/rust-lang/rustup) (to build Rust bindings, nightly for now)
@@ -106,17 +98,6 @@ Then restart the Nix daemon: `sudo launchctl kickstart -k system/org.nixos.nix-d
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
rustup toolchain install nightly
```
- [macmon](https://github.com/vladkens/macmon) (for hardware monitoring on Apple Silicon)
Install the pinned fork revision used by this repo instead of Homebrew `macmon`.
Homebrew `macmon 0.6.1` still crashes on Apple M5.
```bash
cargo install --git https://github.com/swiftraccoon/macmon \
--rev 9154d234f763fbeffdcb4135d0bbbaf80609699b \
macmon \
--force
```
Clone the repo, build the dashboard, and run exo:
@@ -208,8 +189,6 @@ exo follows the [XDG Base Directory Specification](https://specifications.freede
- **Configuration files**: `~/.config/exo/` (or `$XDG_CONFIG_HOME/exo/`)
- **Data files**: `~/.local/share/exo/` (or `$XDG_DATA_HOME/exo/`)
- **Cache files**: `~/.cache/exo/` (or `$XDG_CACHE_HOME/exo/`)
- **Log files**: `~/.cache/exo/exo_log/` (with automatic log rotation)
- **Custom model cards**: `~/.local/share/exo/custom_model_cards/`
You can override these locations by setting the corresponding XDG environment variables.
@@ -289,51 +268,8 @@ After that, RDMA will be enabled in macOS and exo will take care of the rest.
---
## Environment Variables
exo supports several environment variables for configuration:
| Variable | Description | Default |
|----------|-------------|---------|
| `EXO_DEFAULT_MODELS_DIR` | Default directory for model downloads and caches. Always first in the writable dirs list. | `~/.local/share/exo/models` (Linux) or `~/.exo/models` (macOS) |
| `EXO_MODELS_DIRS` | Colon-separated additional writable directories for model downloads. Checked in order after the default; first with enough free space is used. | None |
| `EXO_MODELS_READ_ONLY_DIRS` | Colon-separated read-only directories to search for pre-downloaded models (e.g., NFS mounts, shared storage). Models here cannot be deleted. | None |
| `EXO_OFFLINE` | Run without internet connection (uses only local models) | `false` |
| `EXO_ENABLE_IMAGE_MODELS` | Enable image model support | `false` |
| `EXO_LIBP2P_NAMESPACE` | Custom namespace for cluster isolation | None |
| `EXO_FAST_SYNCH` | Control MLX_METAL_FAST_SYNCH behavior (for JACCL backend) | Auto |
| `EXO_TRACING_ENABLED` | Enable distributed tracing for performance analysis | `false` |
**Example usage:**
```bash
# Use pre-downloaded models from NFS mount (read-only)
EXO_MODELS_READ_ONLY_DIRS=/mnt/nfs/models:/opt/ai-models uv run exo
# Download models to an external SSD (falls back to default dir if full)
EXO_MODELS_DIRS=/Volumes/ExternalSSD/exo-models uv run exo
# Run in offline mode
EXO_OFFLINE=true uv run exo
# Enable image models
EXO_ENABLE_IMAGE_MODELS=true uv run exo
# Use custom namespace for cluster isolation
EXO_LIBP2P_NAMESPACE=my-dev-cluster uv run exo
```
---
### Using the API
exo provides multiple API-compatible interfaces for maximum compatibility with existing tools:
- **OpenAI Chat Completions API** - Compatible with OpenAI clients
- **Claude Messages API** - Compatible with Anthropic's Claude format
- **OpenAI Responses API** - Compatible with OpenAI's Responses format
- **Ollama API** - Compatible with Ollama and tools like OpenWebUI
If you prefer to interact with exo via the API, here is an example creating an instance of a small model (`mlx-community/Llama-3.2-1B-Instruct-4bit`), sending a chat completions request and deleting the instance.
---
@@ -423,85 +359,14 @@ When you're done, delete the instance by its ID (find it via `/state` or `/insta
curl -X DELETE http://localhost:52415/instance/YOUR_INSTANCE_ID
```
### Claude Messages API Compatibility
Use the Claude Messages API format with the `/v1/messages` endpoint:
```bash
curl -N -X POST http://localhost:52415/v1/messages \
-H 'Content-Type: application/json' \
-d '{
"model": "mlx-community/Llama-3.2-1B-Instruct-4bit",
"messages": [
{"role": "user", "content": "Hello"}
],
"max_tokens": 1024,
"stream": true
}'
```
### OpenAI Responses API Compatibility
Use the OpenAI Responses API format with the `/v1/responses` endpoint:
```bash
curl -N -X POST http://localhost:52415/v1/responses \
-H 'Content-Type: application/json' \
-d '{
"model": "mlx-community/Llama-3.2-1B-Instruct-4bit",
"messages": [
{"role": "user", "content": "Hello"}
],
"stream": true
}'
```
### Ollama API Compatibility
exo supports Ollama API endpoints for compatibility with tools like OpenWebUI:
```bash
# Ollama chat
curl -X POST http://localhost:52415/ollama/api/chat \
-H 'Content-Type: application/json' \
-d '{
"model": "mlx-community/Llama-3.2-1B-Instruct-4bit",
"messages": [
{"role": "user", "content": "Hello"}
],
"stream": false
}'
# List models (Ollama format)
curl http://localhost:52415/ollama/api/tags
```
### Custom Model Loading from HuggingFace
You can add custom models from the HuggingFace hub:
```bash
curl -X POST http://localhost:52415/models/add \
-H 'Content-Type: application/json' \
-d '{
"model_id": "mlx-community/my-custom-model"
}'
```
**Security Note:**
Custom models requiring `trust_remote_code` in their configuration must be explicitly enabled (default is false) for security. Only enable this if you trust the model's remote code execution. Models are fetched from HuggingFace and stored locally as custom model cards.
**Other useful API endpoints*:**
- List all models: `curl http://localhost:52415/models`
- List downloaded models only: `curl http://localhost:52415/models?status=downloaded`
- Search HuggingFace: `curl "http://localhost:52415/models/search?query=llama&limit=10"`
- Inspect instance IDs and deployment state: `curl http://localhost:52415/state`
For further details, see:
- API documentation in [docs/api.md](docs/api.md).
- 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).
---
@@ -560,4 +425,4 @@ On macOS, exo uses the GPU. On Linux, exo currently runs on CPU. We are working
## Contributing
See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines on how to contribute to exo.
See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines on how to contribute to exo.
+145 -212
View File
@@ -15,23 +15,14 @@ struct ContentView: View {
@EnvironmentObject private var localNetworkChecker: LocalNetworkChecker
@EnvironmentObject private var updater: SparkleUpdater
@EnvironmentObject private var thunderboltBridgeService: ThunderboltBridgeService
@EnvironmentObject private var settingsWindowController: SettingsWindowController
@State private var focusedNode: NodeViewModel?
@State private var deletingInstanceIDs: Set<String> = []
@State private var showAllNodes = false
@State private var showAllInstances = false
@State private var baseURLCopied = false
@State private var showAdvanced = false
@State private var showDebugInfo = false
private enum BugReportPhase: Equatable {
case idle
case prompting
case sending(String)
case success(String)
case failure(String)
}
@State private var bugReportPhase: BugReportPhase = .idle
@State private var bugReportUserDescription: String = ""
@State private var bugReportInFlight = false
@State private var bugReportMessage: String?
@State private var uninstallInProgress = false
@State private var pendingNamespace: String = ""
@State private var pendingHFToken: String = ""
@@ -267,79 +258,139 @@ struct ContentView: View {
VStack(alignment: .leading, spacing: 0) {
if controller.status != .stopped {
dashboardButton
baseURLRow
Divider()
.padding(.vertical, 8)
} else {
Divider()
.padding(.vertical, 4)
}
HoverButton(
title: "Settings",
tint: .primary,
trailingSystemImage: "gear"
) {
settingsWindowController.open(
controller: controller,
updater: updater,
networkStatusService: networkStatusService,
thunderboltBridgeService: thunderboltBridgeService,
stateService: stateService
)
}
HoverButton(
title: "Check for Updates",
tint: .primary,
trailingSystemImage: "arrow.triangle.2.circlepath"
) {
updater.checkForUpdates()
}
.padding(.bottom, 8)
HoverButton(title: "Quit", tint: .secondary) {
advancedSection
.padding(.bottom, 8)
controlButton(title: "Quit", tint: .secondary) {
controller.stop()
NSApplication.shared.terminate(nil)
}
}
}
private var dashboardButton: some View {
HoverButton(
title: "Web Dashboard",
tint: .primary,
trailingSystemImage: "arrow.up.right"
) {
guard let url = URL(string: "http://localhost:52415/") else { return }
NSWorkspace.shared.open(url)
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)
}
}
VStack(alignment: .leading, spacing: 4) {
Text("HuggingFace Token")
.font(.caption2)
.foregroundColor(.secondary)
HStack {
SecureField("optional", text: $pendingHFToken)
.textFieldStyle(.roundedBorder)
.font(.caption2)
.onAppear {
pendingHFToken = controller.hfToken
}
Button("Save & Restart") {
controller.hfToken = pendingHFToken
if controller.status == .running || controller.status == .starting {
controller.restart()
}
}
.font(.caption2)
.disabled(pendingHFToken == controller.hfToken)
}
}
Divider()
HStack {
Toggle(
"Enable Image Models (experimental)", isOn: $pendingEnableImageModels
)
.toggleStyle(.switch)
.font(.caption2)
.onAppear {
pendingEnableImageModels = controller.enableImageModels
}
Spacer()
Button("Save & Restart") {
controller.enableImageModels = pendingEnableImageModels
if controller.status == .running || controller.status == .starting {
controller.restart()
}
}
.font(.caption2)
.disabled(pendingEnableImageModels == controller.enableImageModels)
}
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 var baseURLRow: some View {
HStack(spacing: 6) {
Image(systemName: "link")
.imageScale(.small)
.foregroundColor(.secondary)
Text("localhost:52415/v1")
.font(.system(.caption, design: .monospaced))
.foregroundColor(.primary)
Spacer()
Button {
NSPasteboard.general.clearContents()
NSPasteboard.general.setString("http://localhost:52415/v1", forType: .string)
baseURLCopied = true
DispatchQueue.main.asyncAfter(deadline: .now() + 2) {
baseURLCopied = false
}
} label: {
Image(systemName: baseURLCopied ? "checkmark" : "doc.on.doc")
private func controlButton(title: String, tint: Color = .primary, action: @escaping () -> Void)
-> some View
{
HoverButton(title: title, tint: tint, trailingSystemImage: nil, action: action)
}
private var dashboardButton: some View {
Button {
guard let url = URL(string: "http://localhost:52415/") else { return }
NSWorkspace.shared.open(url)
} label: {
HStack {
Image(systemName: "arrow.up.right.square")
.imageScale(.small)
.foregroundColor(baseURLCopied ? .green : .secondary)
.contentTransition(.symbolEffect(.replace))
Text("Dashboard")
.fontWeight(.medium)
Spacer()
}
.buttonStyle(.plain)
.help("Copy API base URL")
.padding(.vertical, 8)
.padding(.horizontal, 10)
.background(
RoundedRectangle(cornerRadius: 8, style: .continuous)
.fill(Color(red: 1.0, green: 0.87, blue: 0.0).opacity(0.2))
)
}
.padding(.vertical, 4)
.padding(.horizontal, 8)
.buttonStyle(.plain)
.padding(.bottom, 4)
}
private func collapseButton(isExpanded: Binding<Bool>) -> some View {
@@ -560,115 +611,39 @@ struct ContentView: View {
}
private var sendBugReportButton: some View {
VStack(alignment: .leading, spacing: 6) {
switch bugReportPhase {
case .idle:
Button {
bugReportPhase = .prompting
bugReportUserDescription = ""
} label: {
HStack {
Text("Send Bug Report")
.font(.caption)
.fontWeight(.semibold)
Spacer()
}
.padding(.vertical, 6)
.padding(.horizontal, 8)
.background(
RoundedRectangle(cornerRadius: 6)
.fill(Color.accentColor.opacity(0.12))
)
VStack(alignment: .leading, spacing: 4) {
Button {
Task {
await sendBugReport()
}
.buttonStyle(.plain)
case .prompting:
VStack(alignment: .leading, spacing: 6) {
Text("What's the issue? (optional)")
.font(.caption2)
.foregroundColor(.secondary)
TextEditor(text: $bugReportUserDescription)
.font(.caption2)
.frame(height: 60)
.overlay(
RoundedRectangle(cornerRadius: 4)
.stroke(Color.secondary.opacity(0.3), lineWidth: 1)
)
HStack(spacing: 8) {
Button("Send") {
Task {
await sendBugReport()
}
}
.font(.caption2)
.buttonStyle(.borderedProminent)
.controlSize(.small)
Button("Cancel") {
bugReportPhase = .idle
}
.font(.caption2)
.buttonStyle(.bordered)
.controlSize(.small)
} label: {
HStack {
if bugReportInFlight {
ProgressView()
.scaleEffect(0.6)
}
Text("Send Bug Report")
.font(.caption)
.fontWeight(.semibold)
Spacer()
}
.padding(8)
.padding(.vertical, 6)
.padding(.horizontal, 8)
.background(
RoundedRectangle(cornerRadius: 6)
.fill(Color.accentColor.opacity(0.06))
.fill(Color.accentColor.opacity(0.12))
)
}
.buttonStyle(.plain)
.disabled(bugReportInFlight)
case .sending(let message):
HStack(spacing: 6) {
ProgressView()
.scaleEffect(0.6)
Text(message)
.font(.caption2)
.foregroundColor(.secondary)
}
case .success(let message):
VStack(alignment: .leading, spacing: 6) {
Text(message)
.font(.caption2)
.foregroundColor(.secondary)
.fixedSize(horizontal: false, vertical: true)
Button {
openGitHubIssue()
} label: {
HStack(spacing: 4) {
Image(systemName: "arrow.up.right.square")
.imageScale(.small)
Text("Create GitHub Issue")
.font(.caption2)
}
}
.buttonStyle(.bordered)
.controlSize(.small)
Button("Done") {
bugReportPhase = .idle
bugReportUserDescription = ""
}
if let message = bugReportMessage {
Text(message)
.font(.caption2)
.buttonStyle(.plain)
.foregroundColor(.secondary)
}
case .failure(let message):
VStack(alignment: .leading, spacing: 4) {
Text(message)
.font(.caption2)
.foregroundColor(.red)
.fixedSize(horizontal: false, vertical: true)
Button("Dismiss") {
bugReportPhase = .idle
}
.font(.caption2)
.buttonStyle(.plain)
.foregroundColor(.secondary)
}
.fixedSize(horizontal: false, vertical: true)
}
}
.animation(.easeInOut(duration: 0.2), value: bugReportPhase)
}
private var processToggleBinding: Binding<Bool> {
@@ -712,58 +687,16 @@ struct ContentView: View {
}
private func sendBugReport() async {
bugReportPhase = .sending("Collecting logs...")
bugReportInFlight = true
bugReportMessage = "Collecting logs..."
let service = BugReportService()
let description = bugReportUserDescription.trimmingCharacters(in: .whitespacesAndNewlines)
do {
let outcome = try await service.sendReport(
isManual: true,
userDescription: description.isEmpty ? nil : description
)
if outcome.success {
bugReportPhase = .success(outcome.message)
} else {
bugReportPhase = .failure(outcome.message)
}
let outcome = try await service.sendReport(isManual: true)
bugReportMessage = outcome.message
} catch {
bugReportPhase = .failure(error.localizedDescription)
}
}
private func openGitHubIssue() {
let description = bugReportUserDescription.trimmingCharacters(in: .whitespacesAndNewlines)
var bodyParts: [String] = []
bodyParts.append("## Describe the bug")
bodyParts.append("")
if !description.isEmpty {
bodyParts.append(description)
} else {
bodyParts.append("A clear and concise description of what the bug is.")
}
bodyParts.append("")
bodyParts.append("## Environment")
bodyParts.append("")
bodyParts.append("- macOS Version: \(ProcessInfo.processInfo.operatingSystemVersionString)")
bodyParts.append("- EXO Version: \(buildTag) (\(buildCommit))")
bodyParts.append("")
bodyParts.append("## Additional context")
bodyParts.append("")
bodyParts.append("A bug report with diagnostic logs was submitted via the app.")
let body = bodyParts.joined(separator: "\n")
var components = URLComponents(string: "https://github.com/exo-explore/exo/issues/new")!
components.queryItems = [
URLQueryItem(name: "template", value: "bug_report.md"),
URLQueryItem(name: "title", value: "[BUG] "),
URLQueryItem(name: "body", value: body),
URLQueryItem(name: "labels", value: "bug"),
]
if let url = components.url {
NSWorkspace.shared.open(url)
bugReportMessage = error.localizedDescription
}
bugReportInFlight = false
}
private func showUninstallConfirmationAlert() {
+1 -15
View File
@@ -21,9 +21,7 @@ struct EXOApp: App {
@StateObject private var localNetworkChecker: LocalNetworkChecker
@StateObject private var updater: SparkleUpdater
@StateObject private var thunderboltBridgeService: ThunderboltBridgeService
@StateObject private var settingsWindowController: SettingsWindowController
private let terminationObserver: TerminationObserver
private let firstLaunchPopout = FirstLaunchPopout()
private let ciContext = CIContext(options: nil)
init() {
@@ -45,13 +43,12 @@ struct EXOApp: App {
_updater = StateObject(wrappedValue: updater)
let thunderboltBridge = ThunderboltBridgeService(clusterStateService: service)
_thunderboltBridgeService = StateObject(wrappedValue: thunderboltBridge)
_settingsWindowController = StateObject(wrappedValue: SettingsWindowController())
enableLaunchAtLoginIfNeeded()
// Install LaunchDaemon to disable Thunderbolt Bridge on startup (prevents network loops)
NetworkSetupHelper.promptAndInstallIfNeeded()
// Check local network access periodically (warning disappears when user grants permission)
localNetwork.startPeriodicChecking(interval: 10)
controller.scheduleLaunch(after: 5)
controller.scheduleLaunch(after: 15)
service.startPolling()
networkStatus.startPolling()
}
@@ -65,19 +62,8 @@ struct EXOApp: App {
.environmentObject(localNetworkChecker)
.environmentObject(updater)
.environmentObject(thunderboltBridgeService)
.environmentObject(settingsWindowController)
} label: {
menuBarIcon
.onReceive(controller.$isFirstLaunchReady) { ready in
if ready {
DispatchQueue.main.asyncAfter(deadline: .now() + 3.0) {
self.firstLaunchPopout.onComplete = { [weak controller] in
controller?.markOnboardingCompleted()
}
self.firstLaunchPopout.show()
}
}
}
}
.menuBarExtraStyle(.window)
}
-42
View File
@@ -4,10 +4,7 @@ import Foundation
private let customNamespaceKey = "EXOCustomNamespace"
private let hfTokenKey = "EXOHFToken"
private let hfEndpointKey = "EXOHFEndpoint"
private let enableImageModelsKey = "EXOEnableImageModels"
private let offlineModeKey = "EXOOfflineMode"
private let onboardingCompletedKey = "EXOOnboardingCompleted"
@MainActor
final class ExoProcessController: ObservableObject {
@@ -54,14 +51,6 @@ final class ExoProcessController: ObservableObject {
UserDefaults.standard.set(hfToken, forKey: hfTokenKey)
}
}
@Published var hfEndpoint: String = {
return UserDefaults.standard.string(forKey: hfEndpointKey) ?? ""
}()
{
didSet {
UserDefaults.standard.set(hfEndpoint, forKey: hfEndpointKey)
}
}
@Published var enableImageModels: Bool = {
return UserDefaults.standard.bool(forKey: enableImageModelsKey)
}()
@@ -70,17 +59,6 @@ final class ExoProcessController: ObservableObject {
UserDefaults.standard.set(enableImageModels, forKey: enableImageModelsKey)
}
}
@Published var offlineMode: Bool = {
return UserDefaults.standard.bool(forKey: offlineModeKey)
}()
{
didSet {
UserDefaults.standard.set(offlineMode, forKey: offlineModeKey)
}
}
/// Fires once when EXO transitions to `.running` for the very first time (fresh install).
@Published private(set) var isFirstLaunchReady = false
private var process: Process?
private var runtimeDirectoryURL: URL?
@@ -135,9 +113,6 @@ final class ExoProcessController: ObservableObject {
try child.run()
process = child
status = .running
// Show welcome popout on every launch
isFirstLaunchReady = true
} catch {
process = nil
status = .failed(message: "Launch error")
@@ -189,17 +164,6 @@ final class ExoProcessController: ObservableObject {
launch()
}
/// Mark onboarding as completed (user interacted with the welcome popout).
func markOnboardingCompleted() {
UserDefaults.standard.set(true, forKey: onboardingCompletedKey)
}
/// Reset onboarding so the welcome popout appears on next launch.
func resetOnboarding() {
UserDefaults.standard.removeObject(forKey: onboardingCompletedKey)
isFirstLaunchReady = false
}
func scheduleLaunch(after seconds: TimeInterval) {
cancelPendingLaunch()
let start = max(1, Int(ceil(seconds)))
@@ -282,15 +246,9 @@ final class ExoProcessController: ObservableObject {
if !hfToken.isEmpty {
environment["HF_TOKEN"] = hfToken
}
if !hfEndpoint.isEmpty {
environment["HF_ENDPOINT"] = hfEndpoint
}
if enableImageModels {
environment["EXO_ENABLE_IMAGE_MODELS"] = "true"
}
if offlineMode {
environment["EXO_OFFLINE"] = "true"
}
var paths: [String] = []
if let existing = environment["PATH"], !existing.isEmpty {
+3 -9
View File
@@ -38,8 +38,7 @@ struct BugReportService {
func sendReport(
baseURL: URL = URL(string: "http://127.0.0.1:52415")!,
now: Date = Date(),
isManual: Bool = false,
userDescription: String? = nil
isManual: Bool = false
) async throws -> BugReportOutcome {
let timestamp = Self.runTimestampString(now)
let dayPrefix = Self.dayPrefixString(now)
@@ -61,8 +60,7 @@ struct BugReportService {
ifconfig: ifconfigText,
debugInfo: debugInfo,
isManual: isManual,
clusterTbBridgeStatus: clusterTbBridgeStatus,
userDescription: userDescription
clusterTbBridgeStatus: clusterTbBridgeStatus
)
let eventLogFiles = readAllEventLogs()
@@ -308,8 +306,7 @@ struct BugReportService {
ifconfig: String,
debugInfo: DebugInfo,
isManual: Bool,
clusterTbBridgeStatus: [[String: Any]]?,
userDescription: String? = nil
clusterTbBridgeStatus: [[String: Any]]?
) -> Data? {
let system = readSystemMetadata()
let exo = readExoMetadata()
@@ -326,9 +323,6 @@ struct BugReportService {
if let tbStatus = clusterTbBridgeStatus {
payload["cluster_thunderbolt_bridge"] = tbStatus
}
if let desc = userDescription, !desc.isEmpty {
payload["user_description"] = desc
}
return try? JSONSerialization.data(withJSONObject: payload, options: [.prettyPrinted])
}
-200
View File
@@ -1,200 +0,0 @@
import AppKit
import SwiftUI
/// A popover callout anchored to the menu bar icon on every launch,
/// pointing the user to the web dashboard with an arrow connecting to the icon.
@MainActor
final class FirstLaunchPopout {
private var popover: NSPopover?
private var countdownTask: Task<Void, Never>?
private static let dashboardURL = "http://localhost:52415/"
/// Called when the user completes onboarding (clicks Open Dashboard or dismisses).
var onComplete: (() -> Void)?
func show() {
guard popover == nil else { return }
// The status bar button may not exist yet on first launch; retry generously.
showWithRetry(attemptsRemaining: 15)
}
private func showWithRetry(attemptsRemaining: Int) {
guard attemptsRemaining > 0 else {
// Exhausted retries fall back to just opening the dashboard directly.
openDashboard()
onComplete?()
return
}
guard let button = Self.findStatusItemButton() else {
DispatchQueue.main.asyncAfter(deadline: .now() + 1.0) { [weak self] in
self?.showWithRetry(attemptsRemaining: attemptsRemaining - 1)
}
return
}
let pop = NSPopover()
pop.behavior = .applicationDefined
pop.animates = true
pop.contentSize = NSSize(width: 280, height: 120)
pop.contentViewController = NSHostingController(
rootView: WelcomeCalloutView(
countdownDuration: 10,
onDismiss: { [weak self] in
self?.onComplete?()
self?.dismiss()
},
onOpen: { [weak self] in
self?.openDashboard()
self?.onComplete?()
self?.dismiss()
}
)
)
self.popover = pop
pop.show(relativeTo: button.bounds, of: button, preferredEdge: .minY)
// Auto-open dashboard after 10s then dismiss
countdownTask = Task {
try? await Task.sleep(nanoseconds: 10_000_000_000)
if !Task.isCancelled {
openDashboard()
onComplete?()
dismiss()
}
}
}
func dismiss() {
countdownTask?.cancel()
countdownTask = nil
guard let pop = popover else { return }
popover = nil
pop.performClose(nil)
}
private func openDashboard() {
guard let url = URL(string: Self.dashboardURL) else { return }
NSWorkspace.shared.open(url)
}
/// Finds the NSStatusBarButton created by SwiftUI's MenuBarExtra.
/// Walks the view hierarchy to find the actual button rather than the content view.
private static func findStatusItemButton() -> NSView? {
for window in NSApp.windows {
let className = NSStringFromClass(type(of: window))
// Match NSStatusBarWindow or any internal SwiftUI status bar window
guard className.contains("StatusBar") || className.contains("MenuBarExtra") else {
continue
}
if let content = window.contentView {
if let button = findButton(in: content) {
return button
}
// Fall back to the content view itself if it has a non-zero frame
if content.frame.width > 0 {
return content
}
}
}
return nil
}
/// Recursively searches the view hierarchy for an NSStatusBarButton.
private static func findButton(in view: NSView) -> NSView? {
let className = NSStringFromClass(type(of: view))
if className.contains("StatusBarButton") || className.contains("StatusItem") {
return view
}
for subview in view.subviews {
if let found = findButton(in: subview) {
return found
}
}
return nil
}
}
/// Minimal welcome callout friendly pointer, not a wall of text.
/// Rendered inside the NSPopover which provides its own chrome and arrow.
private struct WelcomeCalloutView: View {
let countdownDuration: Int
let onDismiss: () -> Void
let onOpen: () -> Void
@State private var countdown: Int
@State private var timerTask: Task<Void, Never>?
init(countdownDuration: Int, onDismiss: @escaping () -> Void, onOpen: @escaping () -> Void) {
self.countdownDuration = countdownDuration
self.onDismiss = onDismiss
self.onOpen = onOpen
self._countdown = State(initialValue: countdownDuration)
}
var body: some View {
VStack(alignment: .leading, spacing: 10) {
HStack(alignment: .top) {
Text("EXO is running")
.font(.system(.headline, design: .rounded))
.fontWeight(.semibold)
.foregroundColor(.primary)
Spacer()
Button {
onDismiss()
} label: {
Image(systemName: "xmark.circle.fill")
.font(.system(size: 14))
.foregroundStyle(.tertiary)
}
.buttonStyle(.plain)
}
Text("Run your first model here:")
.font(.system(.subheadline, design: .default))
.foregroundColor(.secondary)
HStack {
Button {
onOpen()
} label: {
Label("Open Dashboard", systemImage: "arrow.up.right.square")
.font(.system(.caption, design: .default))
.fontWeight(.medium)
}
.buttonStyle(.borderedProminent)
.tint(.accentColor)
.controlSize(.small)
Spacer()
if countdown > 0 {
Text("Launching in \(countdown) secs...")
.font(.system(.caption2, design: .default))
.foregroundColor(.secondary.opacity(0.6))
.monospacedDigit()
}
}
}
.padding(14)
.onAppear {
startCountdown()
}
.onDisappear {
timerTask?.cancel()
timerTask = nil
}
}
private func startCountdown() {
timerTask = Task {
while countdown > 0 {
try? await Task.sleep(nanoseconds: 1_000_000_000)
if !Task.isCancelled {
countdown -= 1
}
}
}
}
}
-504
View File
@@ -1,504 +0,0 @@
import AppKit
import SwiftUI
/// Native macOS Settings window following Apple HIG.
/// Organized into General, Model, Advanced, and About sections.
struct SettingsView: View {
@EnvironmentObject private var controller: ExoProcessController
@EnvironmentObject private var updater: SparkleUpdater
@EnvironmentObject private var networkStatusService: NetworkStatusService
@EnvironmentObject private var thunderboltBridgeService: ThunderboltBridgeService
@EnvironmentObject private var stateService: ClusterStateService
@State private var pendingNamespace: String = ""
@State private var pendingHFToken: String = ""
@State private var pendingHFEndpoint: String = ""
@State private var pendingEnableImageModels = false
@State private var pendingOfflineMode = false
@State private var needsRestart = false
@State private var bugReportInFlight = false
@State private var bugReportMessage: String?
@State private var uninstallInProgress = false
var body: some View {
TabView {
generalTab
.tabItem {
Label("General", systemImage: "gear")
}
modelTab
.tabItem {
Label("Model", systemImage: "cube")
}
advancedTab
.tabItem {
Label("Advanced", systemImage: "wrench.and.screwdriver")
}
aboutTab
.tabItem {
Label("About", systemImage: "info.circle")
}
}
.frame(width: 450, height: 400)
.onAppear {
pendingNamespace = controller.customNamespace
pendingHFToken = controller.hfToken
pendingHFEndpoint = controller.hfEndpoint
pendingEnableImageModels = controller.enableImageModels
pendingOfflineMode = controller.offlineMode
needsRestart = false
}
}
// MARK: - General Tab
private var generalTab: some View {
Form {
Section {
LabeledContent("Cluster Namespace") {
TextField("default", text: $pendingNamespace)
.textFieldStyle(.roundedBorder)
.frame(width: 200)
}
Text("Nodes with the same namespace form a cluster. Leave empty for default.")
.font(.caption)
.foregroundColor(.secondary)
}
Section {
LabeledContent("HuggingFace Token") {
SecureField("optional", text: $pendingHFToken)
.textFieldStyle(.roundedBorder)
.frame(width: 200)
}
Text("Required for gated models. Get yours at huggingface.co/settings/tokens")
.font(.caption)
.foregroundColor(.secondary)
}
Section {
LabeledContent("HuggingFace Endpoint") {
TextField("default", text: $pendingHFEndpoint)
.textFieldStyle(.roundedBorder)
.frame(width: 200)
}
Text("Defaults to huggingface.co. Use a mirror (e.g. hf-mirror.com) for China.")
.font(.caption)
.foregroundColor(.secondary)
}
Section {
Toggle("Offline Mode", isOn: $pendingOfflineMode)
Text("Skip internet checks and use only locally available models.")
.font(.caption)
.foregroundColor(.secondary)
}
Section {
HStack {
Spacer()
Button("Save & Restart") {
applyGeneralSettings()
}
.disabled(!hasGeneralChanges)
}
}
}
.formStyle(.grouped)
.padding()
}
// MARK: - Model Tab
private var modelTab: some View {
Form {
Section {
Toggle("Enable Image Models (experimental)", isOn: $pendingEnableImageModels)
Text("Allow text-to-image and image-to-image models in the model picker.")
.font(.caption)
.foregroundColor(.secondary)
}
Section {
HStack {
Spacer()
Button("Save & Restart") {
applyModelSettings()
}
.disabled(!hasModelChanges)
}
}
}
.formStyle(.grouped)
.padding()
}
// MARK: - Advanced Tab
private var advancedTab: some View {
Form {
Section("Onboarding") {
HStack {
VStack(alignment: .leading) {
Text("Reset Onboarding")
Text("Opens the dashboard and resets the onboarding wizard.")
.font(.caption)
.foregroundColor(.secondary)
}
Spacer()
Button("Reset") {
guard let url = URL(string: "http://localhost:52415/?reset-onboarding")
else { return }
NSWorkspace.shared.open(url)
}
}
}
Section("Debug Info") {
LabeledContent("Thunderbolt Bridge") {
Text(thunderboltStatusText)
.foregroundColor(thunderboltStatusColor)
}
VStack(alignment: .leading, spacing: 2) {
clusterThunderboltBridgeView
}
VStack(alignment: .leading, spacing: 2) {
interfaceIpList
}
VStack(alignment: .leading, spacing: 2) {
rdmaStatusView
}
sendBugReportButton
}
Section("Danger Zone") {
Button(role: .destructive) {
showUninstallConfirmationAlert()
} label: {
HStack {
Text("Uninstall EXO")
Spacer()
Image(systemName: "trash")
.imageScale(.small)
}
}
.disabled(uninstallInProgress)
}
}
.formStyle(.grouped)
.padding()
}
// MARK: - About Tab
private var aboutTab: some View {
Form {
Section {
LabeledContent("Version") {
Text(buildTag)
.textSelection(.enabled)
}
LabeledContent("Commit") {
Text(buildCommit)
.font(.system(.body, design: .monospaced))
.textSelection(.enabled)
}
}
Section {
Button("Check for Updates") {
updater.checkForUpdates()
}
}
}
.formStyle(.grouped)
.padding()
}
// MARK: - Debug Info Views (moved from ContentView)
private var thunderboltStatusText: String {
switch networkStatusService.status.thunderboltBridgeState {
case .some(.disabled):
return "Disabled"
case .some(.deleted):
return "Deleted"
case .some(.enabled):
return "Enabled"
case nil:
return "Unknown"
}
}
private var thunderboltStatusColor: Color {
switch networkStatusService.status.thunderboltBridgeState {
case .some(.disabled), .some(.deleted):
return .green
case .some(.enabled):
return .red
case nil:
return .secondary
}
}
private var clusterThunderboltBridgeView: some View {
let bridgeStatuses = stateService.latestSnapshot?.nodeThunderboltBridge ?? [:]
let localNodeId = stateService.localNodeId
let nodeProfiles = stateService.latestSnapshot?.nodeProfiles ?? [:]
return VStack(alignment: .leading, spacing: 1) {
if bridgeStatuses.isEmpty {
Text("Cluster TB Bridge: No data")
.font(.caption2)
.foregroundColor(.secondary)
} else {
Text("Cluster TB Bridge Status:")
.font(.caption2)
.foregroundColor(.secondary)
ForEach(Array(bridgeStatuses.keys.sorted()), id: \.self) { nodeId in
if let status = bridgeStatuses[nodeId] {
let nodeName =
nodeProfiles[nodeId]?.friendlyName ?? String(nodeId.prefix(8))
let isLocal = nodeId == localNodeId
let prefix = isLocal ? " \(nodeName) (local):" : " \(nodeName):"
let statusText =
!status.exists
? "N/A"
: (status.enabled ? "Enabled" : "Disabled")
let color: Color =
!status.exists
? .secondary
: (status.enabled ? .red : .green)
Text("\(prefix) \(statusText)")
.font(.caption2)
.foregroundColor(color)
}
}
}
}
}
private var interfaceIpList: some View {
let statuses = networkStatusService.status.interfaceStatuses
return VStack(alignment: .leading, spacing: 1) {
Text("Interfaces (en0en7):")
.font(.caption2)
.foregroundColor(.secondary)
if statuses.isEmpty {
Text(" Unknown")
.font(.caption2)
.foregroundColor(.secondary)
} else {
ForEach(statuses, id: \.interfaceName) { status in
let ipText = status.ipAddress ?? "No IP"
Text(" \(status.interfaceName): \(ipText)")
.font(.caption2)
.foregroundColor(status.ipAddress == nil ? .red : .green)
}
}
}
}
private var rdmaStatusView: some View {
let rdmaStatuses = stateService.latestSnapshot?.nodeRdmaCtl ?? [:]
let localNodeId = stateService.localNodeId
let nodeProfiles = stateService.latestSnapshot?.nodeProfiles ?? [:]
let localDevices = networkStatusService.status.localRdmaDevices
let localPorts = networkStatusService.status.localRdmaActivePorts
return VStack(alignment: .leading, spacing: 1) {
if rdmaStatuses.isEmpty {
Text("Cluster RDMA: No data")
.font(.caption2)
.foregroundColor(.secondary)
} else {
Text("Cluster RDMA Status:")
.font(.caption2)
.foregroundColor(.secondary)
ForEach(Array(rdmaStatuses.keys.sorted()), id: \.self) { nodeId in
if let status = rdmaStatuses[nodeId] {
let nodeName =
nodeProfiles[nodeId]?.friendlyName ?? String(nodeId.prefix(8))
let isLocal = nodeId == localNodeId
let prefix = isLocal ? " \(nodeName) (local):" : " \(nodeName):"
let statusText = status.enabled ? "Enabled" : "Disabled"
let color: Color = status.enabled ? .green : .orange
Text("\(prefix) \(statusText)")
.font(.caption2)
.foregroundColor(color)
}
}
}
if !localDevices.isEmpty {
Text(" Local Devices: \(localDevices.joined(separator: ", "))")
.font(.caption2)
.foregroundColor(.secondary)
}
if !localPorts.isEmpty {
Text(" Local Active Ports:")
.font(.caption2)
.foregroundColor(.secondary)
ForEach(localPorts, id: \.device) { port in
Text(" \(port.device) port \(port.port): \(port.state)")
.font(.caption2)
.foregroundColor(.green)
}
}
}
}
private var sendBugReportButton: some View {
VStack(alignment: .leading, spacing: 4) {
Button {
Task {
await sendBugReport()
}
} label: {
HStack {
if bugReportInFlight {
ProgressView()
.scaleEffect(0.6)
}
Text("Send Bug Report")
.font(.caption)
.fontWeight(.semibold)
Spacer()
}
}
.disabled(bugReportInFlight)
if let message = bugReportMessage {
Text(message)
.font(.caption2)
.foregroundColor(.secondary)
.fixedSize(horizontal: false, vertical: true)
}
}
}
// MARK: - Actions
private func sendBugReport() async {
bugReportInFlight = true
bugReportMessage = "Collecting logs..."
let service = BugReportService()
do {
let outcome = try await service.sendReport(isManual: true)
bugReportMessage = outcome.message
} catch {
bugReportMessage = error.localizedDescription
}
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")
if let uninstallButton = alert.buttons.first {
uninstallButton.hasDestructiveAction = true
}
let response = alert.runModal()
if response == .alertFirstButtonReturn {
performUninstall()
}
}
private func performUninstall() {
uninstallInProgress = true
controller.cancelPendingLaunch()
controller.stop()
stateService.stopPolling()
DispatchQueue.global(qos: .utility).async {
do {
try NetworkSetupHelper.uninstall()
DispatchQueue.main.async {
LaunchAtLoginHelper.disable()
self.moveAppToTrash()
DispatchQueue.main.asyncAfter(deadline: .now() + 0.5) {
NSApplication.shared.terminate(nil)
}
}
} catch {
DispatchQueue.main.async {
let errorAlert = NSAlert()
errorAlert.messageText = "Uninstall Failed"
errorAlert.informativeText = error.localizedDescription
errorAlert.alertStyle = .critical
errorAlert.addButton(withTitle: "OK")
errorAlert.runModal()
self.uninstallInProgress = false
}
}
}
}
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
}
}
// MARK: - Helpers
private var hasGeneralChanges: Bool {
pendingNamespace != controller.customNamespace || pendingHFToken != controller.hfToken
|| pendingHFEndpoint != controller.hfEndpoint
|| pendingOfflineMode != controller.offlineMode
}
private var hasModelChanges: Bool {
pendingEnableImageModels != controller.enableImageModels
}
private func applyGeneralSettings() {
controller.customNamespace = pendingNamespace
controller.hfToken = pendingHFToken
controller.hfEndpoint = pendingHFEndpoint
controller.offlineMode = pendingOfflineMode
restartIfRunning()
}
private func applyModelSettings() {
controller.enableImageModels = pendingEnableImageModels
restartIfRunning()
}
private func restartIfRunning() {
if controller.status == .running || controller.status == .starting {
controller.restart()
}
}
private var buildTag: String {
Bundle.main.infoDictionary?["EXOBuildTag"] as? String ?? "unknown"
}
private var buildCommit: String {
Bundle.main.infoDictionary?["EXOBuildCommit"] as? String ?? "unknown"
}
}
@@ -1,47 +0,0 @@
import AppKit
import SwiftUI
/// Manages a standalone native macOS Settings window.
/// Ensures only one instance exists and brings it to front on repeated opens.
@MainActor
final class SettingsWindowController: ObservableObject {
private var window: NSWindow?
func open(
controller: ExoProcessController,
updater: SparkleUpdater,
networkStatusService: NetworkStatusService,
thunderboltBridgeService: ThunderboltBridgeService,
stateService: ClusterStateService
) {
if let existing = window, existing.isVisible {
existing.makeKeyAndOrderFront(nil)
NSApp.activate(ignoringOtherApps: true)
return
}
let settingsView = SettingsView()
.environmentObject(controller)
.environmentObject(updater)
.environmentObject(networkStatusService)
.environmentObject(thunderboltBridgeService)
.environmentObject(stateService)
let hostingView = NSHostingView(rootView: settingsView)
let newWindow = NSWindow(
contentRect: NSRect(x: 0, y: 0, width: 450, height: 400),
styleMask: [.titled, .closable],
backing: .buffered,
defer: false
)
newWindow.title = "EXO Settings"
newWindow.contentView = hostingView
newWindow.center()
newWindow.isReleasedWhenClosed = false
newWindow.makeKeyAndOrderFront(nil)
NSApp.activate(ignoringOtherApps: true)
window = newWindow
}
}
+3 -1
View File
@@ -2,4 +2,6 @@
#
# Lists the suite files to include. Each file defines benchmarks
# with shared constraints, topology, and default args.
include = ["single-m3-ultra.toml"]
include = [
"single-m3-ultra.toml",
]
-292
View File
@@ -1,292 +0,0 @@
# Model evaluation configurations for exo_eval.
#
# Each [[model]] entry uses `patterns` — a list of substrings matched
# against the model_id. First matching entry wins.
#
# Required fields:
# name, patterns, reasoning
#
# Optional per-model overrides (CLI flags take priority over these):
# temperature, top_p, max_tokens, reasoning_effort
#
# Fallback defaults (when no per-model config):
# reasoning: temperature=1.0, max_tokens=131072, reasoning_effort="high"
# non-reasoning: temperature=0.0, max_tokens=16384
#
# All per-model values below are sourced from official model cards,
# generation_config.json files, and vendor documentation.
# ─── Qwen3.5 (Feb 2026) ─────────────────────────────────────────────
# Source: HuggingFace model cards (Qwen/Qwen3.5-*)
# 35B-A3B thinking general: temp=1.0, top_p=0.95, top_k=20
# 397B thinking: temp=0.6, top_p=0.95, top_k=20
# Non-thinking: temp=0.7, top_p=0.8, top_k=20
# max_tokens: 32768 general, 81920 for complex math/code
[[model]]
name = "Qwen3.5 2B"
patterns = ["Qwen3.5-2B"]
reasoning = true
temperature = 0.6
top_p = 0.95
max_tokens = 81920
[[model]]
name = "Qwen3.5 9B"
patterns = ["Qwen3.5-9B"]
reasoning = true
temperature = 0.6
top_p = 0.95
max_tokens = 81920
[[model]]
name = "Qwen3.5 27B"
patterns = ["Qwen3.5-27B"]
reasoning = true
temperature = 0.6
top_p = 0.95
max_tokens = 81920
[[model]]
name = "Qwen3.5 35B A3B"
patterns = ["Qwen3.5-35B-A3B"]
reasoning = true
temperature = 1.0
top_p = 0.95
max_tokens = 81920
[[model]]
name = "Qwen3.5 122B A10B"
patterns = ["Qwen3.5-122B-A10B"]
reasoning = true
temperature = 0.6
top_p = 0.95
max_tokens = 81920
[[model]]
name = "Qwen3.5 397B A17B"
patterns = ["Qwen3.5-397B-A17B"]
reasoning = true
temperature = 0.6
top_p = 0.95
max_tokens = 81920
# ─── Qwen3 (Apr 2025) ───────────────────────────────────────────────
# Source: HuggingFace model cards (Qwen/Qwen3-*)
# Thinking: temp=0.6, top_p=0.95, top_k=20
# Non-thinking: temp=0.7, top_p=0.8, top_k=20
# max_tokens: 32768 general, 38912 for complex math/code
[[model]]
name = "Qwen3 0.6B"
patterns = ["Qwen3-0.6B"]
reasoning = true
temperature = 0.6
top_p = 0.95
max_tokens = 38912
[[model]]
name = "Qwen3 30B A3B"
patterns = ["Qwen3-30B-A3B"]
reasoning = true
temperature = 0.6
top_p = 0.95
max_tokens = 38912
[[model]]
name = "Qwen3 235B A22B"
patterns = ["Qwen3-235B-A22B"]
reasoning = true
temperature = 0.6
top_p = 0.95
max_tokens = 38912
[[model]]
name = "Qwen3 Next 80B Thinking"
patterns = ["Qwen3-Next-80B-A3B-Thinking"]
reasoning = true
temperature = 0.6
top_p = 0.95
max_tokens = 38912
[[model]]
name = "Qwen3 Next 80B Instruct"
patterns = ["Qwen3-Next-80B-A3B-Instruct"]
reasoning = false
temperature = 0.7
top_p = 0.8
max_tokens = 16384
[[model]]
name = "Qwen3 Coder 480B"
patterns = ["Qwen3-Coder-480B"]
reasoning = false
temperature = 0.7
top_p = 0.8
max_tokens = 16384
[[model]]
name = "Qwen3 Coder Next"
patterns = ["Qwen3-Coder-Next"]
reasoning = false
temperature = 0.7
top_p = 0.8
max_tokens = 16384
# ─── GPT-OSS (OpenAI) ───────────────────────────────────────────────
# Source: OpenAI GitHub README + HuggingFace discussion #21
# temp=1.0, top_p=1.0, NO top_k, NO repetition_penalty
# reasoning_effort supported: low/medium/high
[[model]]
name = "GPT-OSS 20B"
patterns = ["gpt-oss-20b"]
reasoning = true
temperature = 1.0
top_p = 1.0
[[model]]
name = "GPT-OSS 120B"
patterns = ["gpt-oss-120b"]
reasoning = true
temperature = 1.0
top_p = 1.0
# ─── DeepSeek ────────────────────────────────────────────────────────
# Source: https://api-docs.deepseek.com/quick_start/parameter_settings
# Coding/Math: temp=0.0, General: temp=1.3, Creative: temp=1.5
# NOTE: DeepSeek API applies nonlinear temp mapping. These are API values.
# When running model directly: API temp 1.0 = model temp 0.3
# We use temp=0.0 for eval (coding/math focus).
[[model]]
name = "DeepSeek V3.1"
patterns = ["DeepSeek-V3.1"]
reasoning = true
temperature = 0.0
# ─── GLM (ZhipuAI / THUDM) ──────────────────────────────────────────
# Source: HuggingFace model cards + generation_config.json + docs.z.ai
# GLM 4.5+: temp=1.0, top_p=0.95
# Reasoning tasks: 131072 max_tokens; coding/SWE tasks: temp=0.7
[[model]]
name = "GLM-5"
patterns = ["GLM-5"]
reasoning = true
temperature = 1.0
top_p = 0.95
max_tokens = 131072
[[model]]
name = "GLM 4.5 Air"
patterns = ["GLM-4.5-Air"]
reasoning = true
temperature = 1.0
top_p = 0.95
[[model]]
name = "GLM 4.7"
patterns = ["GLM-4.7-"]
reasoning = true
temperature = 1.0
top_p = 0.95
max_tokens = 131072
# Note: matches both GLM-4.7 and GLM-4.7-Flash
# ─── Kimi (Moonshot AI) ─────────────────────────────────────────────
# Source: HuggingFace model cards (moonshotai/Kimi-K2-*)
# K2-Instruct: temp=0.6
# K2-Thinking: temp=1.0, max_length=262144
# K2.5: thinking temp=1.0, top_p=0.95; instant temp=0.6, top_p=0.95
[[model]]
name = "Kimi K2 Thinking"
patterns = ["Kimi-K2-Thinking"]
reasoning = true
temperature = 1.0
max_tokens = 131072
[[model]]
name = "Kimi K2.5"
patterns = ["Kimi-K2.5"]
reasoning = true
temperature = 1.0
top_p = 0.95
max_tokens = 131072
[[model]]
name = "Kimi K2 Instruct"
patterns = ["Kimi-K2-Instruct"]
reasoning = false
temperature = 0.6
# ─── MiniMax ─────────────────────────────────────────────────────────
# Source: HuggingFace model cards + generation_config.json
# All models: temp=1.0, top_p=0.95, top_k=40
[[model]]
name = "MiniMax M2.5"
patterns = ["MiniMax-M2.5"]
reasoning = true
temperature = 1.0
top_p = 0.95
[[model]]
name = "MiniMax M2.1"
patterns = ["MiniMax-M2.1"]
reasoning = true
temperature = 1.0
top_p = 0.95
# ─── Step (StepFun) ─────────────────────────────────────────────────
# Source: HuggingFace model card (stepfun-ai/Step-3.5-Flash)
# Reasoning: temp=1.0, top_p=0.95
# General chat: temp=0.6, top_p=0.95
# We use reasoning settings for eval.
[[model]]
name = "Step 3.5 Flash"
patterns = ["Step-3.5-Flash"]
reasoning = true
temperature = 1.0
top_p = 0.95
# ─── Llama (Meta) ───────────────────────────────────────────────────
# Source: generation_config.json + meta-llama/llama-models generation.py
# All variants: temp=0.6, top_p=0.9
[[model]]
name = "Llama 3.2 1B"
patterns = ["Llama-3.2-1B"]
reasoning = false
temperature = 0.6
top_p = 0.9
[[model]]
name = "Llama 3.2 3B"
patterns = ["Llama-3.2-3B"]
reasoning = false
temperature = 0.6
top_p = 0.9
[[model]]
name = "Llama 3.1 8B"
patterns = ["Llama-3.1-8B", "Meta-Llama-3.1-8B"]
reasoning = false
temperature = 0.6
top_p = 0.9
[[model]]
name = "Llama 3.1 70B"
patterns = ["Llama-3.1-70B", "Meta-Llama-3.1-70B"]
reasoning = false
temperature = 0.6
top_p = 0.9
[[model]]
name = "Llama 3.3 70B"
patterns = ["Llama-3.3-70B", "llama-3.3-70b"]
reasoning = false
temperature = 0.6
top_p = 0.9
File diff suppressed because it is too large Load Diff
+497 -312
View File
@@ -1,52 +1,29 @@
# type: ignore
#!/usr/bin/env python3
"""Tool-calling eval for exo's OpenAI-compatible API.
Tests whether models correctly:
- Trigger tool calls when appropriate
- Return valid JSON arguments matching function schemas
- Handle multi-turn tool use (call -> result -> final answer)
- Avoid calling tools when unnecessary
Start exo with a model first, then run:
uv run python tool_call_eval.py --model <model-id>
uv run python tool_call_eval.py --model <model-id> --host 10.0.0.5 --port 52415
uv run python tool_call_eval.py --model <model-id> --repeat 3
uv run python tool_call_eval.py --model <model-id> --scenarios weather_simple calculator_multi_turn
"""
# pyright: reportAny=false, reportUnknownMemberType=false, reportUnknownVariableType=false, reportUnknownArgumentType=false
from __future__ import annotations
import argparse
import contextlib
import http.client
import itertools
import json
import os
import sys
import threading
import time
from collections.abc import Callable
from concurrent.futures import ThreadPoolExecutor, as_completed
from pathlib import Path
from statistics import mean
from typing import Any
from urllib.parse import urlencode
from harness import (
ExoClient,
ExoHttpError,
add_common_instance_args,
capture_cluster_snapshot,
instance_id_from_instance,
node_ids_from_instance,
nodes_used_in_instance,
resolve_model_short_id,
run_planning_phase,
settle_and_fetch_placements,
wait_for_instance_gone,
wait_for_instance_ready,
)
from loguru import logger
from transformers import AutoTokenizer
# Backoff constants for cluster settling retry
_SETTLE_INITIAL_BACKOFF_S = 1.0
_SETTLE_MAX_BACKOFF_S = 60.0
_SETTLE_BACKOFF_MULTIPLIER = 2.0
# 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
@@ -79,7 +56,7 @@ def load_tokenizer_for_bench(model_id: str) -> Any:
model_path = Path(
snapshot_download(
model_id,
allow_patterns=["*.json", "*.py", "*.tiktoken", "*.model"],
allow_patterns=["*.json", "*.py", "*.tiktoken"],
)
)
@@ -126,6 +103,154 @@ def load_tokenizer_for_bench(model_id: str) -> Any:
return AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
class ExoHttpError(RuntimeError):
def __init__(self, status: int, reason: str, body_preview: str):
super().__init__(f"HTTP {status} {reason}: {body_preview}")
self.status = status
class ExoClient:
def __init__(self, host: str, port: int, timeout_s: float = 7200.0):
self.host = host
self.port = port
self.timeout_s = timeout_s
def request_json(
self,
method: str,
path: str,
params: dict[str, Any] | None = None,
body: dict[str, Any] | None = None,
headers: dict[str, str] | None = None,
) -> Any:
if not path.startswith("/"):
path = "/" + path
if params:
path = path + "?" + urlencode(params)
conn = http.client.HTTPConnection(self.host, self.port, timeout=self.timeout_s)
try:
payload: bytes | None = None
hdrs: dict[str, str] = {"Accept": "application/json"}
if body is not None:
payload = json.dumps(body).encode("utf-8")
hdrs["Content-Type"] = "application/json"
if headers:
hdrs.update(headers)
conn.request(method.upper(), path, body=payload, headers=hdrs)
resp = conn.getresponse()
raw = resp.read()
text = raw.decode("utf-8", errors="replace") if raw else ""
if resp.status >= 400:
raise ExoHttpError(resp.status, resp.reason, text[:300])
if not text:
return None
return json.loads(text)
finally:
conn.close()
def post_bench_chat_completions(self, payload: dict[str, Any]) -> dict[str, Any]:
return self.request_json("POST", "/bench/chat/completions", body=payload)
def unwrap_instance(instance: dict[str, Any]) -> dict[str, Any]:
if len(instance) != 1:
raise KeyError(f"Expected 1 key, got keys={list(instance.keys())}")
tag = next(iter(instance))
inner = instance[tag]
if not isinstance(inner, dict):
raise TypeError(f"payload for {tag} must be dict, got {type(inner)}")
return inner
def instance_id_from_instance(instance: dict[str, Any]) -> str:
inner = unwrap_instance(instance)
return str(inner["instanceId"])
def nodes_used_in_instance(instance: dict[str, Any]) -> int:
inner = unwrap_instance(instance)
return len(inner["shardAssignments"]["nodeToRunner"])
def runner_ids_from_instance(instance: dict[str, Any]) -> list[str]:
inner = unwrap_instance(instance)
runner_to_shard = inner["shardAssignments"]["runnerToShard"]
return list(runner_to_shard.keys())
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
time.sleep(0.1)
raise TimeoutError(f"Instance {instance_id} did not become ready within {timeout=}")
def wait_for_instance_gone(
client: ExoClient, instance_id: str, timeout: float = 3.0
) -> None:
start_time = time.time()
while time.time() - start_time < timeout:
try:
client.request_json("GET", f"/instance/{instance_id}")
time.sleep(0.4)
except ExoHttpError as e:
if e.status == 404:
return
raise TimeoutError(f"Instance {instance_id} did not get deleted within {timeout=}")
def format_peak_memory(b: float) -> str:
for unit in ["B", "KB", "MB", "GB", "TB"]:
if b < 1024.0:
@@ -134,91 +259,6 @@ def format_peak_memory(b: float) -> str:
raise ValueError("You're using petabytes of memory. Something went wrong...")
_SAMPLER_METRICS = ("gpuUsage", "temp", "sysPower", "pcpuUsage", "ecpuUsage")
class SystemMetricsSampler:
def __init__(self, client: ExoClient, node_ids: list[str], interval_s: float = 1.0):
self._client = client
self._node_ids = node_ids
self._interval_s = interval_s
self._samples: dict[str, list[tuple[float, dict[str, float]]]] = {
nid: [] for nid in node_ids
}
self._stop = threading.Event()
self._thread: threading.Thread | None = None
def start(self) -> None:
self._stop.clear()
self._thread = threading.Thread(target=self._poll_loop, daemon=True)
self._thread.start()
def stop(self) -> None:
self._stop.set()
if self._thread:
self._thread.join(timeout=5)
def _poll_loop(self) -> None:
while not self._stop.is_set():
t = time.monotonic()
for nid in self._node_ids:
try:
data = self._client.get_node_system(nid)
if data:
self._samples[nid].append(
(t, {k: data.get(k, 0.0) for k in _SAMPLER_METRICS})
)
except Exception:
pass
self._stop.wait(self._interval_s)
def energy_between(self, t0: float, t1: float) -> float:
total_joules = 0.0
for _nid, samples in self._samples.items():
window = [(t, s["sysPower"]) for t, s in samples if t0 <= t <= t1]
if len(window) >= 2:
for i in range(1, len(window)):
dt = window[i][0] - window[i - 1][0]
avg_power = (window[i][1] + window[i - 1][1]) / 2
total_joules += avg_power * dt
elif len(window) == 1:
total_joules += window[0][1] * (t1 - t0)
return total_joules
def summarize(self) -> dict[str, dict[str, dict[str, float]]]:
result: dict[str, dict[str, dict[str, float]]] = {}
for nid, samples in self._samples.items():
if not samples:
continue
metrics: dict[str, dict[str, float]] = {}
for key in _SAMPLER_METRICS:
values = [s[key] for t, s in samples]
metrics[key] = {
"min": round(min(values), 2),
"max": round(max(values), 2),
"mean": round(mean(values), 2),
"samples": len(values),
}
result[nid] = metrics
return result
def print_summary(self, placement_label: str) -> None:
summary = self.summarize()
if not summary:
return
logger.info(f"--- System Metrics ({placement_label}) ---")
for nid, metrics in summary.items():
gpu = metrics.get("gpuUsage", {})
temp = metrics.get("temp", {})
power = metrics.get("sysPower", {})
logger.info(
f" {nid}: "
f"GPU {gpu.get('mean', 0) * 100:.0f}% avg ({gpu.get('min', 0) * 100:.0f}{gpu.get('max', 0) * 100:.0f}%) | "
f"{temp.get('mean', 0):.1f}°C avg | "
f"{power.get('mean', 0):.1f}W avg"
)
def parse_int_list(values: list[str]) -> list[int]:
items: list[int] = []
for v in values:
@@ -229,6 +269,184 @@ def parse_int_list(values: list[str]) -> list[int]:
return items
def resolve_model_short_id(client: ExoClient, model_arg: str) -> tuple[str, str]:
models = client.request_json("GET", "/models") or {}
data = models.get("data") or []
for m in data:
if m.get("name").lower() == model_arg.lower():
short_id = str(m["name"])
full_id = str(m.get("hugging_face_id") or m["name"])
return short_id, full_id
for m in data:
if m.get("hugging_face_id") == model_arg:
short_id = str(m["name"])
full_id = str(m["hugging_face_id"])
return short_id, full_id
raise ValueError(f"Model not found in /models: {model_arg}")
def run_planning_phase(
client: ExoClient,
full_model_id: str,
preview: dict[str, Any],
danger_delete: bool,
timeout: float,
settle_deadline: float | None,
) -> None:
"""Check disk space and ensure model is downloaded before benchmarking."""
# Get model size from /models
models = client.request_json("GET", "/models") or {}
model_bytes = 0
for m in models.get("data", []):
if m.get("hugging_face_id") == full_model_id:
model_bytes = m.get("storage_size_megabytes", 0) * 1024 * 1024
break
if not model_bytes:
logger.warning(
f"Could not determine size for {full_model_id}, skipping disk check"
)
return
# Get nodes from preview
inner = unwrap_instance(preview["instance"])
node_ids = list(inner["shardAssignments"]["nodeToRunner"].keys())
runner_to_shard = inner["shardAssignments"]["runnerToShard"]
state = client.request_json("GET", "/state")
downloads = state.get("downloads", {})
node_disk = state.get("nodeDisk", {})
for node_id in node_ids:
node_downloads = downloads.get(node_id, [])
# Check if model already downloaded on this node
already_downloaded = any(
"DownloadCompleted" in p
and unwrap_instance(p["DownloadCompleted"]["shardMetadata"])["modelCard"][
"modelId"
]
== full_model_id
for p in node_downloads
)
if already_downloaded:
continue
# Wait for disk info if settle_deadline is set
disk_info = node_disk.get(node_id, {})
backoff = _SETTLE_INITIAL_BACKOFF_S
while not disk_info and settle_deadline and time.monotonic() < settle_deadline:
remaining = settle_deadline - time.monotonic()
logger.info(
f"Waiting for disk info on {node_id} ({remaining:.0f}s remaining)..."
)
time.sleep(min(backoff, remaining))
backoff = min(backoff * _SETTLE_BACKOFF_MULTIPLIER, _SETTLE_MAX_BACKOFF_S)
state = client.request_json("GET", "/state")
node_disk = state.get("nodeDisk", {})
disk_info = node_disk.get(node_id, {})
if not disk_info:
logger.warning(f"No disk info for {node_id}, skipping space check")
continue
avail = disk_info.get("available", {}).get("inBytes", 0)
if avail >= model_bytes:
continue
if not danger_delete:
raise RuntimeError(
f"Insufficient disk on {node_id}: need {model_bytes // (1024**3)}GB, "
f"have {avail // (1024**3)}GB. Use --danger-delete-downloads to free space."
)
# Delete from smallest to largest
completed = [
(
unwrap_instance(p["DownloadCompleted"]["shardMetadata"])["modelCard"][
"modelId"
],
p["DownloadCompleted"]["totalBytes"]["inBytes"],
)
for p in node_downloads
if "DownloadCompleted" in p
]
for del_model, size in sorted(completed, key=lambda x: x[1]):
logger.info(f"Deleting {del_model} from {node_id} ({size // (1024**2)}MB)")
client.request_json("DELETE", f"/download/{node_id}/{del_model}")
avail += size
if avail >= model_bytes:
break
if avail < model_bytes:
raise RuntimeError(f"Could not free enough space on {node_id}")
# Start downloads (idempotent)
for node_id in node_ids:
runner_id = inner["shardAssignments"]["nodeToRunner"][node_id]
shard = runner_to_shard[runner_id]
client.request_json(
"POST",
"/download/start",
body={
"targetNodeId": node_id,
"shardMetadata": shard,
},
)
logger.info(f"Started download on {node_id}")
# Wait for downloads
start = time.time()
while time.time() - start < timeout:
state = client.request_json("GET", "/state")
downloads = state.get("downloads", {})
all_done = True
for node_id in node_ids:
done = any(
"DownloadCompleted" in p
and unwrap_instance(p["DownloadCompleted"]["shardMetadata"])[
"modelCard"
]["modelId"]
== full_model_id
for p in downloads.get(node_id, [])
)
failed = [
p["DownloadFailed"]["errorMessage"]
for p in downloads.get(node_id, [])
if "DownloadFailed" in p
and unwrap_instance(p["DownloadFailed"]["shardMetadata"])["modelCard"][
"modelId"
]
== full_model_id
]
if failed:
raise RuntimeError(f"Download failed on {node_id}: {failed[0]}")
if not done:
all_done = False
if all_done:
return
time.sleep(1)
raise TimeoutError("Downloads did not complete in time")
def placement_filter(instance_meta: str, wanted: str) -> bool:
s = (instance_meta or "").lower()
if wanted == "both":
return ("ring" in s) or ("jaccl" in s)
return wanted in s
def sharding_filter(sharding: str, wanted: str) -> bool:
s = (sharding or "").lower()
if wanted == "both":
return ("pipeline" in s) or ("tensor" in s)
return wanted in s
def run_one_completion(
client: ExoClient, model_id: str, pp_hint: int, tg: int, prompt_sizer: PromptSizer
) -> tuple[dict[str, Any], int]:
@@ -320,12 +538,76 @@ class PromptSizer:
return content, tok
def fetch_and_filter_placements(
client: ExoClient, full_model_id: str, args: argparse.Namespace
) -> list[dict[str, Any]]:
previews_resp = client.request_json(
"GET", "/instance/previews", params={"model_id": full_model_id}
)
previews = previews_resp.get("previews") or []
selected: list[dict[str, Any]] = []
for p in previews:
if p.get("error") is not None:
continue
if not placement_filter(str(p.get("instance_meta", "")), args.instance_meta):
continue
if not sharding_filter(str(p.get("sharding", "")), args.sharding):
continue
instance = p.get("instance")
if not isinstance(instance, dict):
continue
n = nodes_used_in_instance(instance)
# Skip tensor ring single node as it is pointless when pipeline ring
if n == 1 and (
(args.sharding == "both" and "tensor" in p.get("sharding", "").lower())
or (
args.instance_meta == "both"
and "jaccl" in p.get("instance_meta", "").lower()
)
):
continue
if (
args.skip_pipeline_jaccl
and (
args.instance_meta == "both"
and "jaccl" in p.get("instance_meta", "").lower()
)
and (
args.sharding == "both" and "pipeline" in p.get("sharding", "").lower()
)
):
continue
if (
args.skip_tensor_ring
and (
args.instance_meta == "both"
and "ring" in p.get("instance_meta", "").lower()
)
and (args.sharding == "both" and "tensor" in p.get("sharding", "").lower())
):
continue
if args.min_nodes <= n <= args.max_nodes:
selected.append(p)
return selected
def main() -> int:
ap = argparse.ArgumentParser(
prog="exo-bench",
description="Benchmark exo model throughput across placement previews.",
)
add_common_instance_args(ap)
ap.add_argument("--host", default=os.environ.get("EXO_HOST", "localhost"))
ap.add_argument(
"--port", type=int, default=int(os.environ.get("EXO_PORT", "52415"))
)
ap.add_argument("--model", required=True, help="Model short id or huggingface id")
ap.add_argument(
"--pp",
nargs="+",
@@ -339,13 +621,35 @@ def main() -> int:
help="Generation lengths (ints). Accepts commas.",
)
ap.add_argument(
"--repeat", type=int, default=1, help="Repetitions per (pp,tg) pair."
"--max-nodes",
type=int,
default=4,
help="Only consider placements using <= this many nodes.",
)
ap.add_argument(
"--concurrency",
nargs="+",
default=["1"],
help="Concurrency levels (ints). Accepts commas. E.g. --concurrency 1,2,4,8. Default 1.",
"--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"
)
ap.add_argument(
"--sharding", choices=["pipeline", "tensor", "both"], default="both"
)
ap.add_argument(
"--skip-pipeline-jaccl",
action="store_true",
help="Skip pipeline+jaccl placements, as it's often pointless.",
)
ap.add_argument(
"--skip-tensor-ring",
action="store_true",
help="Skip tensor+ring placements, as it's so slow.",
)
ap.add_argument(
"--repeat", type=int, default=1, help="Repetitions per (pp,tg) pair."
)
ap.add_argument(
"--warmup",
@@ -353,6 +657,9 @@ def main() -> int:
default=0,
help="Warmup runs per placement (uses first pp/tg).",
)
ap.add_argument(
"--timeout", type=float, default=7200.0, help="HTTP timeout (seconds)."
)
ap.add_argument(
"--json-out",
default="bench/results.json",
@@ -368,15 +675,15 @@ def main() -> int:
help="Force all pp×tg combinations (cartesian product) even when lists have equal length.",
)
ap.add_argument(
"--no-system-metrics",
action="store_true",
help="Disable GPU utilization, temperature, and power collection during inference.",
"--settle-timeout",
type=float,
default=0,
help="Max seconds to wait for the cluster to produce valid placements (0 = try once).",
)
ap.add_argument(
"--metrics-interval",
type=float,
default=1.0,
help="System metrics polling interval in seconds (default: 1.0).",
"--danger-delete-downloads",
action="store_true",
help="Delete existing models from smallest to largest to make room for benchmark model.",
)
args = ap.parse_args()
@@ -388,10 +695,6 @@ def main() -> int:
if args.repeat <= 0:
logger.error("--repeat must be >= 1")
return 2
concurrency_list = parse_int_list(args.concurrency)
if not concurrency_list or any(c <= 0 for c in concurrency_list):
logger.error("--concurrency values must be >= 1")
return 2
# Log pairing mode
use_combinations = args.all_combinations or len(pp_list) != len(tg_list)
@@ -403,9 +706,7 @@ def main() -> int:
logger.info(f"pp/tg mode: tandem (zip) - {len(pp_list)} pairs")
client = ExoClient(args.host, args.port, timeout_s=args.timeout)
short_id, full_model_id = resolve_model_short_id(
client, args.model, force_download=args.force_download
)
short_id, full_model_id = resolve_model_short_id(client, args.model)
tokenizer = load_tokenizer_for_bench(full_model_id)
if tokenizer is None:
@@ -418,10 +719,24 @@ def main() -> int:
logger.error("[exo-bench] tokenizer usable but prompt sizing failed")
raise
selected = settle_and_fetch_placements(
client, full_model_id, args, settle_timeout=args.settle_timeout
settle_deadline = (
time.monotonic() + args.settle_timeout if args.settle_timeout > 0 else None
)
selected = fetch_and_filter_placements(client, full_model_id, args)
if not selected and settle_deadline:
backoff = _SETTLE_INITIAL_BACKOFF_S
while not selected and time.monotonic() < settle_deadline:
remaining = settle_deadline - time.monotonic()
logger.warning(
f"No valid placements yet (cluster may still be settling). "
f"Retrying in {backoff:.1f}s ({remaining:.0f}s remaining)..."
)
time.sleep(min(backoff, remaining))
backoff = min(backoff * _SETTLE_BACKOFF_MULTIPLIER, _SETTLE_MAX_BACKOFF_S)
selected = fetch_and_filter_placements(client, full_model_id, args)
if not selected:
logger.error("No valid placements matched your filters.")
return 1
@@ -445,12 +760,8 @@ def main() -> int:
if args.dry_run:
return 0
settle_deadline = (
time.monotonic() + args.settle_timeout if args.settle_timeout > 0 else None
)
logger.info("Planning phase: checking downloads...")
download_duration_s = run_planning_phase(
run_planning_phase(
client,
full_model_id,
selected[0],
@@ -458,14 +769,8 @@ def main() -> int:
args.timeout,
settle_deadline,
)
if download_duration_s is not None:
logger.info(f"Download: {download_duration_s:.1f}s (freshly downloaded)")
else:
logger.info("Download: model already cached")
cluster_snapshot = capture_cluster_snapshot(client)
all_rows: list[dict[str, Any]] = []
all_system_metrics: dict[str, dict[str, dict[str, float]]] = {}
for preview in selected:
instance = preview["instance"]
@@ -491,16 +796,6 @@ def main() -> int:
time.sleep(1)
sampler: SystemMetricsSampler | None = None
if not args.no_system_metrics:
nids = node_ids_from_instance(instance)
sampler = SystemMetricsSampler(
ExoClient(args.host, args.port, timeout_s=30),
nids,
interval_s=args.metrics_interval,
)
sampler.start()
try:
for i in range(args.warmup):
run_one_completion(
@@ -516,152 +811,48 @@ def main() -> int:
pp_tg_pairs = list(zip(pp_list, tg_list, strict=True))
for pp, tg in pp_tg_pairs:
for concurrency in concurrency_list:
logger.info(f"--- pp={pp} tg={tg} concurrency={concurrency} ---")
runs: list[dict[str, Any]] = []
inference_windows: list[tuple[float, float]] = []
for r in range(args.repeat):
time.sleep(3)
if concurrency <= 1:
# Sequential: single request
try:
inf_t0 = time.monotonic()
row, actual_pp_tokens = run_one_completion(
client, full_model_id, pp, tg, prompt_sizer
)
inference_windows.append((inf_t0, time.monotonic()))
except Exception as e:
logger.error(e)
continue
row.update(
{
"model_short_id": short_id,
"model_id": full_model_id,
"placement_sharding": sharding,
"placement_instance_meta": instance_meta,
"placement_nodes": n_nodes,
"instance_id": instance_id,
"pp_tokens": actual_pp_tokens,
"tg": tg,
"repeat_index": r,
"concurrency": 1,
**(
{"download_duration_s": download_duration_s}
if download_duration_s is not None
else {}
),
}
)
runs.append(row)
all_rows.append(row)
else:
# Concurrent: fire N requests in parallel
# Each thread gets its own ExoClient (separate HTTP connection)
batch_results: list[tuple[dict[str, Any], int]] = []
batch_errors = 0
def _run_concurrent(
idx: int, *, _pp: int = pp, _tg: int = tg
) -> tuple[dict[str, Any], int]:
c = ExoClient(
args.host, args.port, timeout_s=args.timeout
)
return run_one_completion(
c, full_model_id, _pp, _tg, prompt_sizer
)
inf_t0 = time.monotonic()
with ThreadPoolExecutor(max_workers=concurrency) as pool:
futures = {
pool.submit(_run_concurrent, i): i
for i in range(concurrency)
}
for fut in as_completed(futures):
try:
batch_results.append(fut.result())
except Exception as e:
logger.error(f"Concurrent request failed: {e}")
batch_errors += 1
inference_windows.append((inf_t0, time.monotonic()))
for idx, (row, actual_pp_tokens) in enumerate(
batch_results
):
row.update(
{
"model_short_id": short_id,
"model_id": full_model_id,
"placement_sharding": sharding,
"placement_instance_meta": instance_meta,
"placement_nodes": n_nodes,
"instance_id": instance_id,
"pp_tokens": actual_pp_tokens,
"tg": tg,
"repeat_index": r,
"concurrency": concurrency,
"concurrent_index": idx,
**(
{"download_duration_s": download_duration_s}
if download_duration_s is not None
else {}
),
}
)
runs.append(row)
all_rows.append(row)
if batch_results:
valid_gen_tps = [
x["stats"]["generation_tps"]
for x, _ in batch_results
if x["stats"]["generation_tps"] > 0
]
per_req_tps = (
mean(valid_gen_tps) if valid_gen_tps else 0.0
)
agg_gen_tps = per_req_tps * concurrency
logger.info(
f"[concurrent {concurrency}x] "
f"agg_gen_tps={agg_gen_tps:.2f} "
f"per_req_tps={per_req_tps:.2f} "
f"errors={batch_errors}"
)
if runs:
prompt_tps = mean(x["stats"]["prompt_tps"] for x in runs)
per_req_tps = mean(x["stats"]["generation_tps"] for x in runs)
gen_tps = per_req_tps * concurrency
ptok = mean(x["stats"]["prompt_tokens"] for x in runs)
gtok = mean(x["stats"]["generation_tokens"] for x in runs)
peak = mean(
x["stats"]["peak_memory_usage"]["inBytes"] for x in runs
runs: list[dict[str, Any]] = []
for r in range(args.repeat):
time.sleep(3)
try:
row, actual_pp_tokens = run_one_completion(
client, full_model_id, pp, tg, prompt_sizer
)
except Exception as e:
logger.error(e)
continue
row.update(
{
"model_short_id": short_id,
"model_id": full_model_id,
"placement_sharding": sharding,
"placement_instance_meta": instance_meta,
"placement_nodes": n_nodes,
"instance_id": instance_id,
"pp_tokens": actual_pp_tokens,
"tg": tg,
"repeat_index": r,
}
)
runs.append(row)
all_rows.append(row)
summary = (
f"prompt_tps={prompt_tps:.2f} gen_tps={gen_tps:.2f} "
f"prompt_tokens={ptok} gen_tokens={gtok} "
f"peak_memory={format_peak_memory(peak)}"
)
if sampler and inference_windows:
joules = sum(
sampler.energy_between(t0, t1)
for t0, t1 in inference_windows
)
inf_seconds = sum(t1 - t0 for t0, t1 in inference_windows)
avg_watts = joules / inf_seconds if inf_seconds > 0 else 0
summary += f" energy={joules:.1f}J ({avg_watts:.1f}W avg over {inf_seconds:.1f}s inference)"
logger.info(f"{summary}\n")
time.sleep(2)
if runs:
prompt_tps = mean(x["stats"]["prompt_tps"] for x in runs)
gen_tps = mean(x["stats"]["generation_tps"] for x in runs)
ptok = mean(x["stats"]["prompt_tokens"] for x in runs)
gtok = mean(x["stats"]["generation_tokens"] for x in runs)
peak = mean(
x["stats"]["peak_memory_usage"]["inBytes"] for x in runs
)
logger.info(
f"prompt_tps={prompt_tps:.2f} gen_tps={gen_tps:.2f} "
f"prompt_tokens={ptok} gen_tokens={gtok} "
f"peak_memory={format_peak_memory(peak)}\n"
)
time.sleep(2)
finally:
if sampler:
sampler.stop()
placement_label = f"{sharding}/{instance_meta}/{n_nodes} nodes"
sampler.print_summary(placement_label)
placement_metrics = sampler.summarize()
if placement_metrics:
all_system_metrics.update(placement_metrics)
try:
client.request_json("DELETE", f"/instance/{instance_id}")
except ExoHttpError as e:
@@ -672,17 +863,11 @@ def main() -> int:
time.sleep(5)
output: dict[str, Any] = {"runs": all_rows}
if cluster_snapshot:
output["cluster"] = cluster_snapshot
if all_system_metrics:
output["system_metrics"] = all_system_metrics
if args.stdout:
json.dump(output, sys.stdout, indent=2, ensure_ascii=False)
json.dump(all_rows, sys.stdout, indent=2, ensure_ascii=False)
elif args.json_out:
with open(args.json_out, "w", encoding="utf-8") as f:
json.dump(output, f, indent=2, ensure_ascii=False)
json.dump(all_rows, f, indent=2, ensure_ascii=False)
logger.debug(f"\nWrote results JSON: {args.json_out}")
return 0
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-574
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@@ -1,574 +0,0 @@
# type: ignore
from __future__ import annotations
import argparse
import http.client
import json
import os
import time
from typing import Any
from urllib.parse import urlencode
from loguru import logger
_SETTLE_INITIAL_BACKOFF_S = 1.0
_SETTLE_MAX_BACKOFF_S = 60.0
_SETTLE_BACKOFF_MULTIPLIER = 2.0
class ExoHttpError(RuntimeError):
def __init__(self, status: int, reason: str, body_preview: str):
super().__init__(f"HTTP {status} {reason}: {body_preview}")
self.status = status
class ExoClient:
def __init__(self, host: str, port: int, timeout_s: float = 7200.0):
self.host = host
self.port = port
self.timeout_s = timeout_s
def request_json(
self,
method: str,
path: str,
params: dict[str, Any] | None = None,
body: dict[str, Any] | None = None,
headers: dict[str, str] | None = None,
) -> Any:
if not path.startswith("/"):
path = "/" + path
if params:
path = path + "?" + urlencode(params)
conn = http.client.HTTPConnection(self.host, self.port, timeout=self.timeout_s)
try:
payload: bytes | None = None
hdrs: dict[str, str] = {"Accept": "application/json"}
if body is not None:
payload = json.dumps(body).encode("utf-8")
hdrs["Content-Type"] = "application/json"
if headers:
hdrs.update(headers)
conn.request(method.upper(), path, body=payload, headers=hdrs)
resp = conn.getresponse()
raw = resp.read()
text = raw.decode("utf-8", errors="replace") if raw else ""
if resp.status >= 400:
raise ExoHttpError(resp.status, resp.reason, text[:300])
if not text:
return None
return json.loads(text)
finally:
conn.close()
def post_bench_chat_completions(self, payload: dict[str, Any]) -> dict[str, Any]:
return self.request_json("POST", "/bench/chat/completions", body=payload)
def get_state_path(self, path: str) -> Any:
try:
return self.request_json("GET", f"/state/{path}")
except ExoHttpError as e:
if e.status == 404:
return None
raise
def get_instance(self, instance_id: str) -> dict[str, Any] | None:
return self.get_state_path(f"instances/{instance_id}")
def get_runner(self, runner_id: str) -> dict[str, Any] | None:
return self.get_state_path(f"runners/{runner_id}")
def get_node_downloads(self, node_id: str) -> list[dict[str, Any]] | None:
return self.get_state_path(f"downloads/{node_id}")
def get_node_disk(self, node_id: str) -> dict[str, Any] | None:
return self.get_state_path(f"nodeDisk/{node_id}")
def get_node_system(self, node_id: str) -> dict[str, Any] | None:
return self.get_state_path(f"nodeSystem/{node_id}")
def get_node_identities(self) -> dict[str, Any] | None:
return self.get_state_path("nodeIdentities")
def get_topology(self) -> dict[str, Any] | None:
return self.get_state_path("topology")
def unwrap_instance(instance: dict[str, Any]) -> dict[str, Any]:
if len(instance) != 1:
raise KeyError(f"Expected 1 key, got keys={list(instance.keys())}")
tag = next(iter(instance))
inner = instance[tag]
if not isinstance(inner, dict):
raise TypeError(f"payload for {tag} must be dict, got {type(inner)}")
return inner
def instance_id_from_instance(instance: dict[str, Any]) -> str:
inner = unwrap_instance(instance)
return str(inner["instanceId"])
def nodes_used_in_instance(instance: dict[str, Any]) -> int:
inner = unwrap_instance(instance)
return len(inner["shardAssignments"]["nodeToRunner"])
def runner_ids_from_instance(instance: dict[str, Any]) -> list[str]:
inner = unwrap_instance(instance)
runner_to_shard = inner["shardAssignments"]["runnerToShard"]
return list(runner_to_shard.keys())
def node_ids_from_instance(instance: dict[str, Any]) -> list[str]:
inner = unwrap_instance(instance)
return list(inner["shardAssignments"]["nodeToRunner"].keys())
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
last_loaded: dict[str, int] = {}
while time.time() - start_time < timeout:
instance = client.get_instance(instance_id)
if instance is None:
if instance_existed:
raise RuntimeError(
f"Instance {instance_id} was deleted (runner may have failed)"
)
time.sleep(0.1)
continue
instance_existed = True
rids = runner_ids_from_instance(instance)
all_ready = True
for rid in rids:
runner = client.get_runner(rid) or {}
if runner_failed(runner):
error_msg = get_runner_failed_message(runner) or "Unknown error"
raise RuntimeError(f"Runner {rid} failed: {error_msg}")
if "RunnerLoading" in runner:
loading = runner["RunnerLoading"]
loaded = loading.get("layersLoaded", 0)
total = loading.get("totalLayers", 0)
if total > 0 and last_loaded.get(rid) != loaded:
last_loaded[rid] = loaded
logger.debug(f"Runner {rid}: loading layers {loaded}/{total}")
if not runner_ready(runner):
all_ready = False
if all_ready:
return
time.sleep(0.1)
raise TimeoutError(f"Instance {instance_id} did not become ready within {timeout=}")
def wait_for_instance_gone(
client: ExoClient, instance_id: str, timeout: float = 3.0
) -> None:
start_time = time.time()
while time.time() - start_time < timeout:
try:
client.request_json("GET", f"/instance/{instance_id}")
time.sleep(0.4)
except ExoHttpError as e:
if e.status == 404:
return
raise
raise TimeoutError(f"Instance {instance_id} did not get deleted within {timeout=}")
def capture_cluster_snapshot(client: ExoClient) -> dict[str, Any]:
snapshot: dict[str, Any] = {}
identities = client.get_node_identities()
if identities:
snapshot["nodeIdentities"] = identities
topology = client.get_topology()
if topology:
snapshot["topology"] = topology
node_memory = client.get_state_path("nodeMemory")
if node_memory:
snapshot["nodeMemory"] = node_memory
node_system = client.get_state_path("nodeSystem")
if node_system:
snapshot["nodeSystem"] = node_system
return snapshot
def resolve_model_short_id(
client: ExoClient, model_arg: str, *, force_download: bool = False
) -> tuple[str, str]:
models = client.request_json("GET", "/models") or {}
data = models.get("data") or []
for m in data:
if (m.get("name") or "").lower() == model_arg.lower():
short_id = str(m["name"])
full_id = str(m.get("hugging_face_id") or m["name"])
return short_id, full_id
for m in data:
if m.get("hugging_face_id") == model_arg:
short_id = str(m["name"])
full_id = str(m["hugging_face_id"])
return short_id, full_id
if force_download and "/" in model_arg:
logger.info(f"Model not in /models, adding from HuggingFace: {model_arg}")
result = client.request_json(
"POST", "/models/add", body={"model_id": model_arg}
)
if result:
short_id = str(result.get("name") or model_arg.rsplit("/", 1)[-1])
full_id = str(result.get("hugging_face_id") or model_arg)
return short_id, full_id
raise ValueError(f"Model not found in /models: {model_arg}")
def placement_filter(instance_meta: str, wanted: str) -> bool:
s = (instance_meta or "").lower()
if wanted == "both":
return ("ring" in s) or ("jaccl" in s)
return wanted in s
def sharding_filter(sharding: str, wanted: str) -> bool:
s = (sharding or "").lower()
if wanted == "both":
return ("pipeline" in s) or ("tensor" in s)
return wanted in s
def fetch_and_filter_placements(
client: ExoClient, full_model_id: str, args: argparse.Namespace
) -> list[dict[str, Any]]:
previews_resp = client.request_json(
"GET", "/instance/previews", params={"model_id": full_model_id}
)
previews = previews_resp.get("previews") or []
selected: list[dict[str, Any]] = []
for p in previews:
if p.get("error") is not None:
continue
if not placement_filter(str(p.get("instance_meta", "")), args.instance_meta):
continue
if not sharding_filter(str(p.get("sharding", "")), args.sharding):
continue
instance = p.get("instance")
if not isinstance(instance, dict):
continue
n = nodes_used_in_instance(instance)
# Skip tensor ring single node as it is pointless when pipeline ring
if n == 1 and (
(args.sharding == "both" and "tensor" in p.get("sharding", "").lower())
or (
args.instance_meta == "both"
and "jaccl" in p.get("instance_meta", "").lower()
)
):
continue
if (
args.skip_pipeline_jaccl
and (
args.instance_meta == "both"
and "jaccl" in p.get("instance_meta", "").lower()
)
and (
args.sharding == "both" and "pipeline" in p.get("sharding", "").lower()
)
):
continue
if (
args.skip_tensor_ring
and (
args.instance_meta == "both"
and "ring" in p.get("instance_meta", "").lower()
)
and (args.sharding == "both" and "tensor" in p.get("sharding", "").lower())
):
continue
if args.min_nodes <= n <= args.max_nodes:
selected.append(p)
return selected
def settle_and_fetch_placements(
client: ExoClient,
full_model_id: str,
args: argparse.Namespace,
settle_timeout: float = 0,
) -> list[dict[str, Any]]:
selected = fetch_and_filter_placements(client, full_model_id, args)
if not selected and settle_timeout > 0:
backoff = _SETTLE_INITIAL_BACKOFF_S
deadline = time.monotonic() + settle_timeout
while not selected and time.monotonic() < deadline:
remaining = deadline - time.monotonic()
logger.warning(
f"No valid placements yet (cluster may still be settling). "
f"Retrying in {backoff:.1f}s ({remaining:.0f}s remaining)..."
)
time.sleep(min(backoff, remaining))
backoff = min(backoff * _SETTLE_BACKOFF_MULTIPLIER, _SETTLE_MAX_BACKOFF_S)
selected = fetch_and_filter_placements(client, full_model_id, args)
return selected
def run_planning_phase(
client: ExoClient,
full_model_id: str,
preview: dict[str, Any],
danger_delete: bool,
timeout: float,
settle_deadline: float | None,
) -> float | None:
"""Check disk space and ensure model is downloaded before benchmarking.
Returns the wall-clock download duration in seconds if a fresh download
was needed, or None if the model was already cached on all nodes.
"""
# Get model size from /models
models = client.request_json("GET", "/models") or {}
model_bytes = 0
for m in models.get("data", []):
if m.get("hugging_face_id") == full_model_id:
model_bytes = m.get("storage_size_megabytes", 0) * 1024 * 1024
break
if not model_bytes:
logger.warning(
f"Could not determine size for {full_model_id}, skipping disk check"
)
return None
# Get nodes from preview
inner = unwrap_instance(preview["instance"])
node_ids = list(inner["shardAssignments"]["nodeToRunner"].keys())
runner_to_shard = inner["shardAssignments"]["runnerToShard"]
needs_download = False
for node_id in node_ids:
node_downloads = client.get_node_downloads(node_id) or []
already_downloaded = any(
"DownloadCompleted" in p
and unwrap_instance(p["DownloadCompleted"]["shardMetadata"])["modelCard"][
"modelId"
]
== full_model_id
for p in node_downloads
)
if already_downloaded:
continue
needs_download = True
disk_info = client.get_node_disk(node_id) or {}
backoff = _SETTLE_INITIAL_BACKOFF_S
while not disk_info and settle_deadline and time.monotonic() < settle_deadline:
remaining = settle_deadline - time.monotonic()
logger.info(
f"Waiting for disk info on {node_id} ({remaining:.0f}s remaining)..."
)
time.sleep(min(backoff, remaining))
backoff = min(backoff * _SETTLE_BACKOFF_MULTIPLIER, _SETTLE_MAX_BACKOFF_S)
disk_info = client.get_node_disk(node_id) or {}
if not disk_info:
logger.warning(f"No disk info for {node_id}, skipping space check")
continue
avail = disk_info.get("available", {}).get("inBytes", 0)
if avail >= model_bytes:
continue
if not danger_delete:
raise RuntimeError(
f"Insufficient disk on {node_id}: need {model_bytes // (1024**3)}GB, "
f"have {avail // (1024**3)}GB. Use --danger-delete-downloads to free space."
)
completed = [
(
unwrap_instance(p["DownloadCompleted"]["shardMetadata"])["modelCard"][
"modelId"
],
p["DownloadCompleted"]["total"]["inBytes"],
)
for p in node_downloads
if "DownloadCompleted" in p
and not p["DownloadCompleted"].get("readOnly", False)
]
for del_model, size in sorted(completed, key=lambda x: x[1]):
logger.info(f"Deleting {del_model} from {node_id} ({size // (1024**2)}MB)")
client.request_json("DELETE", f"/download/{node_id}/{del_model}")
avail += size
if avail >= model_bytes:
break
if avail < model_bytes:
raise RuntimeError(f"Could not free enough space on {node_id}")
# Start downloads (idempotent)
download_t0 = time.perf_counter() if needs_download else None
for node_id in node_ids:
runner_id = inner["shardAssignments"]["nodeToRunner"][node_id]
shard = runner_to_shard[runner_id]
client.request_json(
"POST",
"/download/start",
body={
"targetNodeId": node_id,
"shardMetadata": shard,
},
)
logger.info(f"Started download on {node_id}")
# Wait for downloads
start = time.time()
while time.time() - start < timeout:
all_done = True
for node_id in node_ids:
node_downloads = client.get_node_downloads(node_id) or []
done = any(
"DownloadCompleted" in p
and unwrap_instance(p["DownloadCompleted"]["shardMetadata"])[
"modelCard"
]["modelId"]
== full_model_id
for p in node_downloads
)
failed = [
p["DownloadFailed"]["errorMessage"]
for p in node_downloads
if "DownloadFailed" in p
and unwrap_instance(p["DownloadFailed"]["shardMetadata"])["modelCard"][
"modelId"
]
== full_model_id
]
if failed:
raise RuntimeError(f"Download failed on {node_id}: {failed[0]}")
if not done:
all_done = False
ongoing = [
p
for p in node_downloads
if "DownloadOngoing" in p
and unwrap_instance(p["DownloadOngoing"]["shardMetadata"])[
"modelCard"
]["modelId"]
== full_model_id
]
if ongoing:
prog = ongoing[0]["DownloadOngoing"]["downloadProgress"]
speed_mb = prog.get("speed", 0) / (1024 * 1024)
eta_s = prog.get("etaMs", 0) / 1000
dl_bytes = prog.get("downloaded", {}).get("inBytes", 0)
total_bytes = prog.get("total", {}).get("inBytes", 0)
pct = (dl_bytes / total_bytes * 100) if total_bytes else 0
logger.info(
f"Downloading on {node_id}: {pct:.1f}% @ {speed_mb:.1f} MB/s, "
f"ETA {eta_s:.0f}s "
f"({prog.get('completedFiles', 0)}/{prog.get('totalFiles', 0)} files)"
)
if all_done:
if download_t0 is not None:
return time.perf_counter() - download_t0
return None
time.sleep(1)
raise TimeoutError("Downloads did not complete in time")
def add_common_instance_args(ap: argparse.ArgumentParser) -> None:
ap.add_argument("--host", default=os.environ.get("EXO_HOST", "localhost"))
ap.add_argument(
"--port", type=int, default=int(os.environ.get("EXO_PORT", "52415"))
)
ap.add_argument("--model", required=True, help="Model short id or huggingface id")
ap.add_argument(
"--force-download",
action="store_true",
help="If model not in /models, add it from HuggingFace via exo and download.",
)
ap.add_argument(
"--max-nodes",
type=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"
)
ap.add_argument(
"--sharding", choices=["pipeline", "tensor", "both"], default="both"
)
ap.add_argument(
"--skip-pipeline-jaccl",
action="store_true",
help="Skip pipeline+jaccl placements, as it's often pointless.",
)
ap.add_argument(
"--skip-tensor-ring",
action="store_true",
help="Skip tensor+ring placements, as it's so slow.",
)
ap.add_argument(
"--timeout", type=float, default=7200.0, help="HTTP timeout (seconds)."
)
ap.add_argument(
"--settle-timeout",
type=float,
default=0,
help="Max seconds to wait for the cluster to produce valid placements (0 = try once).",
)
ap.add_argument(
"--danger-delete-downloads",
action="store_true",
help="Delete existing models from smallest to largest to make room for benchmark model.",
)
-255
View File
@@ -1,255 +0,0 @@
# type: ignore
import argparse
import asyncio
import sys
import termios
import time
import tty
import aiohttp
NUM_REQUESTS = 10
BASE_URL = ""
QUESTIONS = [
"What is the capital of Australia?",
"How many bones are in the human body?",
"What year did World War II end?",
"What is the speed of light in meters per second?",
"Who wrote Romeo and Juliet?",
"What is the chemical formula for water?",
"How many planets are in our solar system?",
"What is the largest ocean on Earth?",
"Who painted the Mona Lisa?",
"What is the boiling point of water in Celsius?",
]
def write(s: str) -> None:
sys.stdout.write(s)
# ---------------------------------------------------------------------------
# Model picker (same style as exo_eval)
# ---------------------------------------------------------------------------
def fetch_models() -> list[str]:
import json
import urllib.request
with urllib.request.urlopen(f"{BASE_URL}/state") as resp:
data = json.loads(resp.read())
model_ids: set[str] = set()
for instance in data.get("instances", {}).values():
for variant in instance.values():
sa = variant.get("shardAssignments", {})
model_id = sa.get("modelId")
if model_id:
model_ids.add(model_id)
return sorted(model_ids)
def pick_model() -> str | None:
models = fetch_models()
if not models:
print("No models found.")
return None
cursor = 0
total_lines = len(models) + 4
def render(first: bool = False) -> None:
if not first:
write(f"\033[{total_lines}A")
write("\033[J")
write("\033[1mSelect model\033[0m (up/down, enter confirm, q quit)\r\n\r\n")
for i, model in enumerate(models):
line = f" {'>' if i == cursor else ' '} {model}"
write(f"\033[7m{line}\033[0m\r\n" if i == cursor else f"{line}\r\n")
write("\r\n")
sys.stdout.flush()
fd = sys.stdin.fileno()
old = termios.tcgetattr(fd)
try:
tty.setraw(fd)
write("\033[?25l")
render(first=True)
while True:
ch = sys.stdin.read(1)
if ch in ("q", "\x03"):
write("\033[?25h\033[0m\r\n")
return None
elif ch in ("\r", "\n"):
break
elif ch == "\x1b":
seq = sys.stdin.read(2)
if seq == "[A":
cursor = (cursor - 1) % len(models)
elif seq == "[B":
cursor = (cursor + 1) % len(models)
render()
finally:
termios.tcsetattr(fd, termios.TCSADRAIN, old)
write(f"\033[{total_lines}A\033[J") # clear picker UI
write("\033[?25h\033[0m")
sys.stdout.flush()
return models[cursor]
# ---------------------------------------------------------------------------
# Parallel requests
# ---------------------------------------------------------------------------
statuses: list[str] = []
times: list[str] = []
previews: list[str] = []
tokens: list[str] = []
full_responses: list[dict | None] = []
total_lines = 0
start_time: float = 0
selected_model: str = ""
def render_progress(first: bool = False) -> None:
if not first:
write(f"\033[{total_lines}A")
write("\033[J")
elapsed = time.monotonic() - start_time if start_time else 0
done = sum(1 for s in statuses if s == "done")
write(
f"\033[1m{selected_model}\033[0m [{done}/{NUM_REQUESTS}] {elapsed:.1f}s\r\n\r\n"
)
for i in range(NUM_REQUESTS):
q = QUESTIONS[i % len(QUESTIONS)]
status = statuses[i]
if status == "pending":
color = "\033[33m" # yellow
elif status == "running":
color = "\033[36m" # cyan
elif status == "done":
color = "\033[32m" # green
else:
color = "\033[31m" # red
write(
f" {i:>2} {color}{status:<8}\033[0m {times[i]:>6} {tokens[i]:>5}tok {q[:40]:<40} {previews[i][:50]}\r\n"
)
write("\r\n")
sys.stdout.flush()
async def send_request(
session: aiohttp.ClientSession, i: int, lock: asyncio.Lock
) -> None:
payload = {
"model": selected_model,
"messages": [{"role": "user", "content": QUESTIONS[i % len(QUESTIONS)]}],
"max_tokens": 1024,
}
statuses[i] = "running"
async with lock:
render_progress()
t0 = time.monotonic()
try:
async with session.post(
f"{BASE_URL}/v1/chat/completions", json=payload
) as resp:
data = await resp.json()
elapsed = time.monotonic() - t0
full_responses[i] = data
times[i] = f"{elapsed:.1f}s"
if resp.status == 200:
choice = data["choices"][0]
msg = choice["message"]
content = msg.get("content", "")
previews[i] = content[:50].replace("\n", " ") or "(empty)"
if "usage" in data:
tokens[i] = str(data["usage"].get("total_tokens", ""))
statuses[i] = "done"
else:
statuses[i] = f"err:{resp.status}"
previews[i] = str(data.get("error", {}).get("message", ""))[:50]
except Exception as e:
elapsed = time.monotonic() - t0
times[i] = f"{elapsed:.1f}s"
statuses[i] = "error"
previews[i] = str(e)[:50]
async with lock:
render_progress()
async def run_requests(print_stdout: bool = False) -> None:
global start_time, total_lines, statuses, times, previews, tokens, full_responses
statuses = ["pending"] * NUM_REQUESTS
times = ["-"] * NUM_REQUESTS
previews = ["-"] * NUM_REQUESTS
tokens = ["-"] * NUM_REQUESTS
full_responses = [None] * NUM_REQUESTS
total_lines = NUM_REQUESTS + 4
write("\033[?25l") # hide cursor
start_time = time.monotonic()
render_progress(first=True)
lock = asyncio.Lock()
try:
async with aiohttp.ClientSession() as session:
tasks = [send_request(session, i, lock) for i in range(NUM_REQUESTS)]
await asyncio.gather(*tasks)
total = time.monotonic() - start_time
write(
f"\033[1m=== All {NUM_REQUESTS} requests done in {total:.1f}s ===\033[0m\r\n\r\n"
)
if print_stdout:
for i in range(NUM_REQUESTS):
data = full_responses[i]
if not data or "choices" not in data:
continue
choice = data["choices"][0]
msg = choice["message"]
q = QUESTIONS[i % len(QUESTIONS)]
write(f"\033[1m--- #{i}: {q} ---\033[0m\r\n")
if msg.get("reasoning_content"):
write(f"\033[2m[Thinking]: {msg['reasoning_content']}\033[0m\r\n")
write(f"{msg.get('content', '')}\r\n")
if "usage" in data:
u = data["usage"]
write(
f"\033[2m[Usage: prompt={u.get('prompt_tokens')}, "
f"completion={u.get('completion_tokens')}, "
f"total={u.get('total_tokens')}]\033[0m\r\n"
)
write("\r\n")
finally:
write("\033[?25h") # show cursor
sys.stdout.flush()
def main() -> None:
global selected_model, BASE_URL
parser = argparse.ArgumentParser(
description="Send parallel requests to an exo cluster"
)
parser.add_argument(
"--host", required=True, help="Hostname of the exo node (e.g. s1)"
)
parser.add_argument("--port", type=int, default=52415, help="Port (default: 52415)")
parser.add_argument(
"--stdout", action="store_true", help="Print full responses after completion"
)
args = parser.parse_args()
BASE_URL = f"http://{args.host}:{args.port}"
model = pick_model()
if not model:
return
selected_model = model
asyncio.run(run_requests(print_stdout=args.stdout))
if __name__ == "__main__":
main()
+5 -12
View File
@@ -4,18 +4,11 @@ version = "0.1.0"
description = "Benchmarking tool for exo distributed inference"
requires-python = ">=3.13"
dependencies = [
"httpx>=0.27.0",
"loguru>=0.7.3",
"transformers>=5.0.0",
"huggingface-hub>=0.33.4",
"tiktoken>=0.12.0",
"jinja2>=3.1.0",
"protobuf>=5.29.0",
"datasets>=2.0.0",
"math-verify>=0.7.0",
"lm-eval[api,math]>=0.4.0",
"human-eval>=1.0.3",
"numpy>=1.24.0",
"loguru>=0.7.3",
"transformers>=5.0.0",
"huggingface-hub>=0.33.4",
"tiktoken>=0.12.0",
"jinja2>=3.1.0",
]
[build-system]
-306
View File
@@ -1,306 +0,0 @@
# Tool definitions — each becomes an OpenAI function tool.
# All scenarios get all tools unless they specify a `tools` list.
[tools.get_current_weather]
description = "Get the current weather in a given location"
required = ["location"]
[tools.get_current_weather.properties.location]
type = "string"
description = "City and state, e.g. San Francisco, CA"
[tools.get_current_weather.properties.unit]
type = "string"
enum = ["celsius", "fahrenheit"]
description = "Temperature unit"
[tools.calculate]
description = "Evaluate a mathematical expression and return the numeric result"
required = ["expression"]
[tools.calculate.properties.expression]
type = "string"
description = "The math expression to evaluate, e.g. '2 + 3 * 4'"
[tools.search_products]
description = "Search for products in a catalog by query, category, and price"
required = ["query"]
[tools.search_products.properties.query]
type = "string"
description = "Search query string"
[tools.search_products.properties.category]
type = "string"
enum = ["electronics", "clothing", "food", "books"]
description = "Product category to filter by"
[tools.search_products.properties.max_price]
type = "number"
description = "Maximum price in USD"
[tools.create_todos]
description = "Create a structured todo list"
required = ["todos"]
[tools.create_todos.properties.todos]
type = "array"
description = "List of todo items"
[tools.create_todos.properties.todos.items]
type = "object"
required = ["content", "status", "priority"]
[tools.create_todos.properties.todos.items.properties.content]
type = "string"
description = "The todo item text"
[tools.create_todos.properties.todos.items.properties.status]
type = "string"
description = "Status: pending, in_progress, or completed"
[tools.create_todos.properties.todos.items.properties.priority]
type = "string"
description = "Priority: low, normal, or high"
# -- Should call a tool --
[[scenarios]]
name = "weather_simple"
description = "Basic weather query -> get_current_weather"
expect_tool_call = true
expected_function = "get_current_weather"
required_arg_keys = ["location"]
[[scenarios.messages]]
role = "user"
content = "What's the weather like in Tokyo right now?"
[[scenarios]]
name = "calculator_simple"
description = "Math question -> calculate"
expect_tool_call = true
expected_function = "calculate"
required_arg_keys = ["expression"]
[[scenarios.messages]]
role = "user"
content = "Use the calculator to compute 3847 * 926 + 17293"
[[scenarios]]
name = "search_with_filters"
description = "Product search with category and price filter"
expect_tool_call = true
expected_function = "search_products"
required_arg_keys = ["query"]
[[scenarios.messages]]
role = "user"
content = "Find me electronics under $50"
# -- Multi-turn: tool call then follow-up --
[[scenarios]]
name = "weather_multi_turn"
description = "Weather query -> tool result -> natural language summary"
expect_tool_call = true
expected_function = "get_current_weather"
required_arg_keys = ["location"]
[scenarios.tool_result]
temperature = "18C"
condition = "partly cloudy"
humidity = "65%"
wind = "12 km/h NW"
[[scenarios.messages]]
role = "user"
content = "What's the weather in Paris?"
[[scenarios]]
name = "calculator_multi_turn"
description = "Math query -> tool result -> model reports the answer"
expect_tool_call = true
expected_function = "calculate"
required_arg_keys = ["expression"]
[scenarios.tool_result]
result = 491682
[[scenarios.messages]]
role = "user"
content = "Use the calculator to compute 1847 * 263 + 5921"
[[scenarios]]
name = "search_multi_turn"
description = "Search query -> tool result -> model summarizes products"
expect_tool_call = true
expected_function = "search_products"
required_arg_keys = ["query"]
[[scenarios.tool_result.results]]
name = "Hands-On Machine Learning"
price = 45.99
rating = 4.8
[[scenarios.tool_result.results]]
name = "Deep Learning with Python"
price = 39.99
rating = 4.6
[[scenarios.messages]]
role = "user"
content = "Search for books about machine learning"
# -- Sequential tool calls --
[[scenarios]]
name = "chained_tool_calls_same"
description = "Thinking + weather(Tokyo) -> result -> model must call weather(London)"
expect_tool_call = true
expected_function = "get_current_weather"
required_arg_keys = ["location"]
[[scenarios.messages]]
role = "user"
content = "Compare the weather in Tokyo and London."
[[scenarios.messages]]
role = "assistant"
content = "I'll check both cities. Let me start with Tokyo."
[[scenarios.messages.tool_calls]]
id = "call_1"
name = "get_current_weather"
arguments = { location = "Tokyo" }
[[scenarios.messages]]
role = "tool"
tool_call_id = "call_1"
content = '{"temperature": "25C", "condition": "sunny"}'
[[scenarios]]
name = "chained_tool_calls_different"
description = "Thinking + weather(Berlin) -> result -> model must call calculator"
expect_tool_call = true
expected_function = "calculate"
required_arg_keys = ["expression"]
[[scenarios.messages]]
role = "user"
content = "What's the weather in Berlin, and also use the calculator to compute 4819 * 37 + 291."
[[scenarios.messages]]
role = "assistant"
content = "I'll handle both. Let me check Berlin's weather first."
[[scenarios.messages.tool_calls]]
id = "call_2"
name = "get_current_weather"
arguments = { location = "Berlin" }
[[scenarios.messages]]
role = "tool"
tool_call_id = "call_2"
content = '{"temperature": "12C", "condition": "rainy"}'
[[scenarios]]
name = "chained_tool_calls_three"
description = "Two prior thinking+tool calls -> results -> model must make a third"
expect_tool_call = true
expected_function = "get_current_weather"
required_arg_keys = ["location"]
[[scenarios.messages]]
role = "user"
content = "Compare weather in Tokyo, Paris, and London."
[[scenarios.messages]]
role = "assistant"
content = "I'll check all three cities. Starting with Tokyo."
[[scenarios.messages.tool_calls]]
id = "call_3"
name = "get_current_weather"
arguments = { location = "Tokyo" }
[[scenarios.messages]]
role = "tool"
tool_call_id = "call_3"
content = '{"temperature": "25C", "condition": "sunny"}'
[[scenarios.messages]]
role = "assistant"
content = "Got Tokyo. Now checking Paris."
[[scenarios.messages.tool_calls]]
id = "call_4"
name = "get_current_weather"
arguments = { location = "Paris" }
[[scenarios.messages]]
role = "tool"
tool_call_id = "call_4"
content = '{"temperature": "18C", "condition": "cloudy"}'
# -- Nested object schema (regression for lossy chat template rendering) --
[[scenarios]]
name = "nested_schema_tool_call"
description = "Tool call with nested object array schema -> create_todos"
expect_tool_call = true
expected_function = "create_todos"
required_arg_keys = ["todos"]
nested_array_key = "todos"
required_item_keys = ["content", "status", "priority"]
tools = ["create_todos"]
[[scenarios.messages]]
role = "user"
content = "Create a todo list with 3 items to learn Python"
# -- Tool name integrity (regression for harmony token leaking into name) --
[tools.glob]
description = "Search for files matching a glob pattern in the codebase"
required = ["pattern"]
[tools.glob.properties.pattern]
type = "string"
description = "The glob pattern to match files against, e.g. '**/*.py'"
[tools.glob.properties.path]
type = "string"
description = "The directory to search in"
[[scenarios]]
name = "tool_name_integrity"
description = "Tool name must not contain harmony tokens like <|channel|>"
expect_tool_call = true
expected_function = "glob"
required_arg_keys = ["pattern"]
tools = ["glob"]
[[scenarios.messages]]
role = "user"
content = "Find all Python files in the src directory"
# -- Should NOT call a tool --
[[scenarios]]
name = "no_tool_joke"
description = "Joke request should NOT trigger any tool"
expect_tool_call = false
[[scenarios.messages]]
role = "user"
content = "Tell me a funny joke about cats."
[[scenarios]]
name = "no_tool_factual"
description = "Factual question answerable from training data"
expect_tool_call = false
[[scenarios.messages]]
role = "user"
content = "What is the capital of Japan?"
+4 -4
View File
@@ -2,10 +2,10 @@
#
# Shared constraints applied to ALL benchmarks in this file.
constraints = [
"All(MacOsBuild(=25D125))",
"Hosts(=1)",
"All(Chip(m3_ultra))",
"All(GpuCores(=80))",
"All(MacOsBuild(=25D125))",
"Hosts(=1)",
"All(Chip(m3_ultra))",
"All(GpuCores(=80))",
]
[topology]
View File
-593
View File
@@ -1,593 +0,0 @@
# type: ignore
# Vendored from LiveCodeBench (https://github.com/LiveCodeBench/LiveCodeBench)
# File: lcb_runner/evaluation/testing_util.py
# License: MIT
# Vendored 2026-03-07 — do not modify without updating from upstream.
import ast
import faulthandler
import json
import platform
# to run the solution files we're using a timing based approach
import signal
import sys
import time
# used for debugging to time steps
from datetime import datetime
from decimal import Decimal
from enum import Enum
from io import StringIO
# from pyext import RuntimeModule
from types import ModuleType
# used for testing the code that reads from input
from unittest.mock import mock_open, patch
import_string = "from string import *\nfrom re import *\nfrom datetime import *\nfrom collections import *\nfrom heapq import *\nfrom bisect import *\nfrom copy import *\nfrom math import *\nfrom random import *\nfrom statistics import *\nfrom itertools import *\nfrom functools import *\nfrom operator import *\nfrom io import *\nfrom sys import *\nfrom json import *\nfrom builtins import *\nfrom typing import *\nimport string\nimport re\nimport datetime\nimport collections\nimport heapq\nimport bisect\nimport copy\nimport math\nimport random\nimport statistics\nimport itertools\nimport functools\nimport operator\nimport io\nimport sys\nimport json\nsys.setrecursionlimit(50000)\n"
def truncatefn(s, length=300):
if isinstance(s, str):
pass
else:
s = str(s)
if len(s) <= length:
return s
return s[: length // 2] + "...(truncated) ..." + s[-length // 2 :]
class CODE_TYPE(Enum):
call_based = 0
standard_input = 1
# stuff for setting up signal timer
class TimeoutException(Exception):
pass
def timeout_handler(signum, frame):
print("timeout occured: alarm went off")
raise TimeoutException
# used to capture stdout as a list
# from https://stackoverflow.com/a/16571630/6416660
# alternative use redirect_stdout() from contextlib
class Capturing(list):
def __enter__(self):
self._stdout = sys.stdout
sys.stdout = self._stringio = StringIO()
# Make closing the StringIO a no-op
self._stringio.close = lambda x: 1
return self
def __exit__(self, *args):
self.append(self._stringio.getvalue())
del self._stringio # free up some memory
sys.stdout = self._stdout
# Custom mock for sys.stdin that supports buffer attribute
class MockStdinWithBuffer:
def __init__(self, inputs: str):
self.inputs = inputs
self._stringio = StringIO(inputs)
self.buffer = MockBuffer(inputs)
def read(self, *args):
return self.inputs
def readline(self, *args):
return self._stringio.readline(*args)
def readlines(self, *args):
return self.inputs.split("\n")
def __getattr__(self, name):
# Delegate other attributes to StringIO
return getattr(self._stringio, name)
class MockBuffer:
def __init__(self, inputs: str):
self.inputs = inputs.encode("utf-8") # Convert to bytes
def read(self, *args):
# Return as byte strings that can be split
return self.inputs
def readline(self, *args):
return self.inputs.split(b"\n")[0] + b"\n"
def clean_if_name(code: str) -> str:
try:
astree = ast.parse(code)
last_block = astree.body[-1]
if isinstance(last_block, ast.If):
condition = last_block.test
if ast.unparse(condition).strip() == "__name__ == '__main__'":
code = (
ast.unparse(astree.body[:-1]) + "\n" + ast.unparse(last_block.body) # type: ignore
)
except:
pass
return code
def make_function(code: str) -> str:
try:
import_stmts = []
all_other_stmts = []
astree = ast.parse(code)
for stmt in astree.body:
if isinstance(stmt, (ast.Import, ast.ImportFrom)):
import_stmts.append(stmt)
else:
all_other_stmts.append(stmt)
function_ast = ast.FunctionDef(
name="wrapped_function",
args=ast.arguments(
posonlyargs=[], args=[], kwonlyargs=[], kw_defaults=[], defaults=[]
),
body=all_other_stmts,
decorator_list=[],
lineno=-1,
)
main_code = (
import_string
+ "\n"
+ ast.unparse(import_stmts)
+ "\n"
+ ast.unparse(function_ast)
)
return main_code
except Exception:
return code
def call_method(method, inputs):
if isinstance(inputs, list):
inputs = "\n".join(inputs)
inputs_line_iterator = iter(inputs.split("\n"))
# Create custom stdin mock with buffer support
mock_stdin = MockStdinWithBuffer(inputs)
# sys.setrecursionlimit(10000)
# @patch('builtins.input', side_effect=inputs.split("\n"))
@patch("builtins.open", mock_open(read_data=inputs))
@patch("sys.stdin", mock_stdin) # Use our custom mock instead of StringIO
@patch("sys.stdin.readline", lambda *args: next(inputs_line_iterator))
@patch("sys.stdin.readlines", lambda *args: inputs.split("\n"))
@patch("sys.stdin.read", lambda *args: inputs)
# @patch('sys.stdout.write', print)
def _inner_call_method(_method):
try:
return _method()
except SystemExit:
pass
finally:
pass
return _inner_call_method(method)
def get_function(compiled_sol, fn_name: str): # type: ignore
try:
assert hasattr(compiled_sol, fn_name)
return getattr(compiled_sol, fn_name)
except Exception:
return
def compile_code(code: str, timeout: int):
signal.alarm(timeout)
try:
tmp_sol = ModuleType("tmp_sol", "")
exec(code, tmp_sol.__dict__)
if "class Solution" in code:
# leetcode wraps solutions in `Solution`
# this is a hack to check if it is leetcode solution or not
# currently livecodebench only supports LeetCode but
# else condition allows future extensibility to other platforms
compiled_sol = tmp_sol.Solution()
else:
# do nothing in the other case since function is accesible
compiled_sol = tmp_sol
assert compiled_sol is not None
finally:
signal.alarm(0)
return compiled_sol
def convert_line_to_decimals(line: str) -> tuple[bool, list[Decimal]]:
try:
decimal_line = [Decimal(elem) for elem in line.split()]
except:
return False, []
return True, decimal_line
def get_stripped_lines(val: str):
## you don't want empty lines to add empty list after splitlines!
val = val.strip()
return [val_line.strip() for val_line in val.split("\n")]
def grade_call_based(
code: str, all_inputs: list, all_outputs: list, fn_name: str, timeout: int
):
# call-based clean up logic
# need to wrap in try-catch logic after to catch the correct errors, but for now this is fine.
code = import_string + "\n\n" + code
compiled_sol = compile_code(code, timeout)
if compiled_sol is None:
return
method = get_function(compiled_sol, fn_name)
if method is None:
return
all_inputs = [
[json.loads(line) for line in inputs.split("\n")] for inputs in all_inputs
]
all_outputs = [json.loads(output) for output in all_outputs]
total_execution = 0
all_results = []
for idx, (gt_inp, gt_out) in enumerate(zip(all_inputs, all_outputs)):
signal.alarm(timeout)
faulthandler.enable()
try:
# can lock here so time is useful
start = time.time()
prediction = method(*gt_inp)
total_execution += time.time() - start
signal.alarm(0)
# don't penalize model if it produces tuples instead of lists
# ground truth sequences are not tuples
if isinstance(prediction, tuple):
prediction = list(prediction)
tmp_result = prediction == gt_out
# handle floating point comparisons
all_results.append(tmp_result)
if not tmp_result:
return all_results, {
"output": truncatefn(prediction),
"inputs": truncatefn(gt_inp),
"expected": truncatefn(gt_out),
"error_code": -2,
"error_message": "Wrong Answer",
}
except Exception as e:
signal.alarm(0)
if "timeoutexception" in repr(e).lower():
all_results.append(-3)
return all_results, {
"error": repr(e),
"error_code": -3,
"error_message": "Time Limit Exceeded",
"inputs": truncatefn(gt_inp),
"expected": truncatefn(gt_out),
}
else:
all_results.append(-4)
return all_results, {
"error": repr(e),
"error_code": -4,
"error_message": "Runtime Error",
"inputs": truncatefn(gt_inp),
"expected": truncatefn(gt_out),
}
finally:
signal.alarm(0)
faulthandler.disable()
return all_results, {"execution time": total_execution}
def grade_stdio(
code: str,
all_inputs: list,
all_outputs: list,
timeout: int,
):
## runtime doesn't interact well with __name__ == '__main__'
code = clean_if_name(code)
## we wrap the given code inside another function
code = make_function(code)
compiled_sol = compile_code(code, timeout)
if compiled_sol is None:
return
method = get_function(compiled_sol, "wrapped_function")
if method is None:
return
all_results = []
total_execution_time = 0
for idx, (gt_inp, gt_out) in enumerate(zip(all_inputs, all_outputs)):
signal.alarm(timeout)
faulthandler.enable()
signal.alarm(timeout)
with Capturing() as captured_output:
try:
start = time.time()
call_method(method, gt_inp)
total_execution_time += time.time() - start
# reset the alarm
signal.alarm(0)
except Exception as e:
signal.alarm(0)
if "timeoutexception" in repr(e).lower():
all_results.append(-3)
return all_results, {
"error": repr(e),
"error_code": -3,
"error_message": "Time Limit Exceeded",
"inputs": truncatefn(gt_inp),
"expected": truncatefn(gt_out),
}
else:
all_results.append(-4)
return all_results, {
"error": repr(e),
"error_code": -4,
"error_message": "Runtime Error",
"inputs": truncatefn(gt_inp),
"expected": truncatefn(gt_out),
}
finally:
signal.alarm(0)
faulthandler.disable()
prediction = captured_output[0]
stripped_prediction_lines = get_stripped_lines(prediction)
stripped_gt_out_lines = get_stripped_lines(gt_out)
## WA happens in multiple circumstances
## so cache the return to make it clean!
WA_send_args = {
"output": truncatefn(prediction),
"inputs": truncatefn(gt_inp),
"expected": truncatefn(gt_out),
"error_code": -2,
}
if len(stripped_prediction_lines) != len(stripped_gt_out_lines):
all_results.append(-2)
WA_send_args["error_message"] = "Wrong answer: mismatched output length"
return all_results, WA_send_args
for output_line_idx, (
stripped_prediction_line,
stripped_gt_out_line,
) in enumerate(zip(stripped_prediction_lines, stripped_gt_out_lines)):
WA_send_args["error_message"] = (
f"Wrong answer at {output_line_idx=}: {truncatefn(stripped_prediction_line)} != {truncatefn(stripped_gt_out_line)}"
)
## CASE 1: exact match
if stripped_prediction_line == stripped_gt_out_line:
continue
## CASE 2: element-wise comparision
## if there are floating elements
## use `decimal` library for good floating point comparision
## otherwise gotcha: np.isclose(50000000000000000, 50000000000000001) = True
## note that we should always be able to convert to decimals
success, decimal_prediction_line = convert_line_to_decimals(
stripped_prediction_line
)
if not success:
all_results.append(-2)
return all_results, WA_send_args
success, decimal_gtout_line = convert_line_to_decimals(stripped_gt_out_line)
if not success:
all_results.append(-2)
return all_results, WA_send_args
if decimal_prediction_line == decimal_gtout_line:
continue
all_results.append(-2)
return all_results, WA_send_args
all_results.append(True)
return all_results, {"execution time": total_execution_time}
def run_test(sample, test=None, debug=False, timeout=6):
"""
if test(generated_code) is not None it'll try to run the code.
otherwise it'll just return an input and output pair.
"""
signal.signal(signal.SIGALRM, timeout_handler)
# Disable functionalities that can make destructive changes to the test.
# max memory is set to 4GB
reliability_guard()
if debug:
print(f"start = {datetime.now().time()}")
try:
in_outs = json.loads(sample["input_output"])
except ValueError as e:
raise e
in_outs = None
if in_outs:
if in_outs.get("fn_name") is None:
which_type = CODE_TYPE.standard_input # Standard input
method_name = None
else:
which_type = CODE_TYPE.call_based # Call-based
method_name = in_outs["fn_name"]
if debug:
print(f"loaded input_output = {datetime.now().time()}")
if test is None:
assert False, "should not happen: test code is none"
return in_outs, {"error": "no test code provided"}
elif test is not None:
results = []
sol = import_string
if debug:
print(f"loading test code = {datetime.now().time()}")
if which_type == CODE_TYPE.call_based:
signal.alarm(timeout)
try:
results, metadata = grade_call_based(
code=test,
all_inputs=in_outs["inputs"],
all_outputs=in_outs["outputs"],
fn_name=method_name,
timeout=timeout,
)
return results, metadata
except Exception as e:
return [-4], {
"error_code": -4,
"error_message": f"Error during testing: {e}",
}
finally:
signal.alarm(0)
elif which_type == CODE_TYPE.standard_input:
# sol
# if code has if __name__ == "__main__": then remove it
signal.alarm(timeout)
try:
results, metadata = grade_stdio(
code=test,
all_inputs=in_outs["inputs"],
all_outputs=in_outs["outputs"],
timeout=timeout,
)
return results, metadata
except Exception as e:
return [-4], {
"error_code": -4,
"error_message": f"Error during testing: {e}",
}
finally:
signal.alarm(0)
def reliability_guard(maximum_memory_bytes=None):
"""
This disables various destructive functions and prevents the generated code
from interfering with the test (e.g. fork bomb, killing other processes,
removing filesystem files, etc.)
WARNING
This function is NOT a security sandbox. Untrusted code, including, model-
generated code, should not be blindly executed outside of one. See the
Codex paper for more information about OpenAI's code sandbox, and proceed
with caution.
"""
if maximum_memory_bytes is not None:
import resource
resource.setrlimit(
resource.RLIMIT_AS, (maximum_memory_bytes, maximum_memory_bytes)
)
resource.setrlimit(
resource.RLIMIT_DATA, (maximum_memory_bytes, maximum_memory_bytes)
)
if not platform.uname().system == "Darwin":
resource.setrlimit(
resource.RLIMIT_STACK, (maximum_memory_bytes, maximum_memory_bytes)
)
faulthandler.disable()
import builtins
# builtins.exit = None
builtins.quit = None
import os
os.environ["OMP_NUM_THREADS"] = "1"
os.kill = None
os.system = None
os.putenv = None
os.remove = None
os.removedirs = None
os.rmdir = None
os.fchdir = None
os.setuid = None
os.fork = None
os.forkpty = None
os.killpg = None
os.rename = None
os.renames = None
os.truncate = None
os.replace = None
os.unlink = None
os.fchmod = None
os.fchown = None
os.chmod = None
os.chown = None
os.chroot = None
os.fchdir = None
os.lchflags = None
os.lchmod = None
os.lchown = None
os.getcwd = None
os.chdir = None
import shutil
shutil.rmtree = None
shutil.move = None
shutil.chown = None
import subprocess
subprocess.Popen = None
__builtins__["help"] = None
import sys
sys.modules["ipdb"] = None
sys.modules["joblib"] = None
sys.modules["resource"] = None
sys.modules["psutil"] = None
sys.modules["tkinter"] = None
+1 -272
View File
@@ -11,8 +11,7 @@
"highlight.js": "^11.11.1",
"katex": "^0.16.27",
"marked": "^17.0.1",
"mode-watcher": "^1.1.0",
"pdfjs-dist": "^5.6.205"
"mode-watcher": "^1.1.0"
},
"devDependencies": {
"@sveltejs/adapter-static": "^3.0.10",
@@ -519,256 +518,6 @@
"@jridgewell/sourcemap-codec": "^1.4.14"
}
},
"node_modules/@napi-rs/canvas": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas/-/canvas-0.1.97.tgz",
"integrity": "sha512-8cFniXvrIEnVwuNSRCW9wirRZbHvrD3JVujdS2P5n5xiJZNZMOZcfOvJ1pb66c7jXMKHHglJEDVJGbm8XWFcXQ==",
"license": "MIT",
"optional": true,
"workspaces": [
"e2e/*"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
},
"optionalDependencies": {
"@napi-rs/canvas-android-arm64": "0.1.97",
"@napi-rs/canvas-darwin-arm64": "0.1.97",
"@napi-rs/canvas-darwin-x64": "0.1.97",
"@napi-rs/canvas-linux-arm-gnueabihf": "0.1.97",
"@napi-rs/canvas-linux-arm64-gnu": "0.1.97",
"@napi-rs/canvas-linux-arm64-musl": "0.1.97",
"@napi-rs/canvas-linux-riscv64-gnu": "0.1.97",
"@napi-rs/canvas-linux-x64-gnu": "0.1.97",
"@napi-rs/canvas-linux-x64-musl": "0.1.97",
"@napi-rs/canvas-win32-arm64-msvc": "0.1.97",
"@napi-rs/canvas-win32-x64-msvc": "0.1.97"
}
},
"node_modules/@napi-rs/canvas-android-arm64": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-android-arm64/-/canvas-android-arm64-0.1.97.tgz",
"integrity": "sha512-V1c/WVw+NzH8vk7ZK/O8/nyBSCQimU8sfMsB/9qeSvdkGKNU7+mxy/bIF0gTgeBFmHpj30S4E9WHMSrxXGQuVQ==",
"cpu": [
"arm64"
],
"license": "MIT",
"optional": true,
"os": [
"android"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@napi-rs/canvas-darwin-arm64": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-darwin-arm64/-/canvas-darwin-arm64-0.1.97.tgz",
"integrity": "sha512-ok+SCEF4YejcxuJ9Rm+WWunHHpf2HmiPxfz6z1a/NFQECGXtsY7A4B8XocK1LmT1D7P174MzwPF9Wy3AUAwEPw==",
"cpu": [
"arm64"
],
"license": "MIT",
"optional": true,
"os": [
"darwin"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@napi-rs/canvas-darwin-x64": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-darwin-x64/-/canvas-darwin-x64-0.1.97.tgz",
"integrity": "sha512-PUP6e6/UGlclUvAQNnuXCcnkpdUou6VYZfQOQxExLp86epOylmiwLkqXIvpFmjoTEDmPmXrI+coL/9EFU1gKPA==",
"cpu": [
"x64"
],
"license": "MIT",
"optional": true,
"os": [
"darwin"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@napi-rs/canvas-linux-arm-gnueabihf": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-arm-gnueabihf/-/canvas-linux-arm-gnueabihf-0.1.97.tgz",
"integrity": "sha512-XyXH2L/cic8eTNtbrXCcvqHtMX/nEOxN18+7rMrAM2XtLYC/EB5s0wnO1FsLMWmK+04ZSLN9FBGipo7kpIkcOw==",
"cpu": [
"arm"
],
"license": "MIT",
"optional": true,
"os": [
"linux"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@napi-rs/canvas-linux-arm64-gnu": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-arm64-gnu/-/canvas-linux-arm64-gnu-0.1.97.tgz",
"integrity": "sha512-Kuq/M3djq0K8ktgz6nPlK7Ne5d4uWeDxPpyKWOjWDK2RIOhHVtLtyLiJw2fuldw7Vn4mhw05EZXCEr4Q76rs9w==",
"cpu": [
"arm64"
],
"license": "MIT",
"optional": true,
"os": [
"linux"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@napi-rs/canvas-linux-arm64-musl": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-arm64-musl/-/canvas-linux-arm64-musl-0.1.97.tgz",
"integrity": "sha512-kKmSkQVnWeqg7qdsiXvYxKhAFuHz3tkBjW/zyQv5YKUPhotpaVhpBGv5LqCngzyuRV85SXoe+OFj+Tv0a0QXkQ==",
"cpu": [
"arm64"
],
"license": "MIT",
"optional": true,
"os": [
"linux"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@napi-rs/canvas-linux-riscv64-gnu": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-riscv64-gnu/-/canvas-linux-riscv64-gnu-0.1.97.tgz",
"integrity": "sha512-Jc7I3A51jnEOIAXeLsN/M/+Z28LUeakcsXs07FLq9prXc0eYOtVwsDEv913Gr+06IRo34gJJVgT0TXvmz+N2VA==",
"cpu": [
"riscv64"
],
"license": "MIT",
"optional": true,
"os": [
"linux"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@napi-rs/canvas-linux-x64-gnu": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-x64-gnu/-/canvas-linux-x64-gnu-0.1.97.tgz",
"integrity": "sha512-iDUBe7AilfuBSRbSa8/IGX38Mf+iCSBqoVKLSQ5XaY2JLOaqz1TVyPFEyIck7wT6mRQhQt5sN6ogfjIDfi74tg==",
"cpu": [
"x64"
],
"license": "MIT",
"optional": true,
"os": [
"linux"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@napi-rs/canvas-linux-x64-musl": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-x64-musl/-/canvas-linux-x64-musl-0.1.97.tgz",
"integrity": "sha512-AKLFd/v0Z5fvgqBDqhvqtAdx+fHMJ5t9JcUNKq4FIZ5WH+iegGm8HPdj00NFlCSnm83Fp3Ln8I2f7uq1aIiWaA==",
"cpu": [
"x64"
],
"license": "MIT",
"optional": true,
"os": [
"linux"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@napi-rs/canvas-win32-arm64-msvc": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-win32-arm64-msvc/-/canvas-win32-arm64-msvc-0.1.97.tgz",
"integrity": "sha512-u883Yr6A6fO7Vpsy9YE4FVCIxzzo5sO+7pIUjjoDLjS3vQaNMkVzx5bdIpEL+ob+gU88WDK4VcxYMZ6nmnoX9A==",
"cpu": [
"arm64"
],
"license": "MIT",
"optional": true,
"os": [
"win32"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@napi-rs/canvas-win32-x64-msvc": {
"version": "0.1.97",
"resolved": "https://registry.npmjs.org/@napi-rs/canvas-win32-x64-msvc/-/canvas-win32-x64-msvc-0.1.97.tgz",
"integrity": "sha512-sWtD2EE3fV0IzN+iiQUqr/Q1SwqWhs2O1FKItFlxtdDkikpEj5g7DKQpY3x55H/MAOnL8iomnlk3mcEeGiUMoQ==",
"cpu": [
"x64"
],
"license": "MIT",
"optional": true,
"os": [
"win32"
],
"engines": {
"node": ">= 10"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/Brooooooklyn"
}
},
"node_modules/@polka/url": {
"version": "1.0.0-next.29",
"resolved": "https://registry.npmjs.org/@polka/url/-/url-1.0.0-next.29.tgz",
@@ -2886,26 +2635,6 @@
"node": "^10 || ^12 || ^13.7 || ^14 || >=15.0.1"
}
},
"node_modules/node-readable-to-web-readable-stream": {
"version": "0.4.2",
"resolved": "https://registry.npmjs.org/node-readable-to-web-readable-stream/-/node-readable-to-web-readable-stream-0.4.2.tgz",
"integrity": "sha512-/cMZNI34v//jUTrI+UIo4ieHAB5EZRY/+7OmXZgBxaWBMcW2tGdceIw06RFxWxrKZ5Jp3sI2i5TsRo+CBhtVLQ==",
"license": "MIT",
"optional": true
},
"node_modules/pdfjs-dist": {
"version": "5.6.205",
"resolved": "https://registry.npmjs.org/pdfjs-dist/-/pdfjs-dist-5.6.205.tgz",
"integrity": "sha512-tlUj+2IDa7G1SbvBNN74UHRLJybZDWYom+k6p5KIZl7huBvsA4APi6mKL+zCxd3tLjN5hOOEE9Tv7VdzO88pfg==",
"license": "Apache-2.0",
"engines": {
"node": ">=20.19.0 || >=22.13.0 || >=24"
},
"optionalDependencies": {
"@napi-rs/canvas": "^0.1.96",
"node-readable-to-web-readable-stream": "^0.4.2"
}
},
"node_modules/picocolors": {
"version": "1.1.1",
"resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.1.1.tgz",
+1 -2
View File
@@ -31,7 +31,6 @@
"highlight.js": "^11.11.1",
"katex": "^0.16.27",
"marked": "^17.0.1",
"mode-watcher": "^1.1.0",
"pdfjs-dist": "^5.6.205"
"mode-watcher": "^1.1.0"
}
}
-65
View File
@@ -202,23 +202,6 @@
filter: drop-shadow(0 0 3px oklch(0.85 0.18 85 / 0.5));
}
/* Onboarding step 2: connection line between devices */
.onboarding-connection-line {
stroke: oklch(0.85 0.18 85 / 0.5);
stroke-width: 1.5px;
stroke-dasharray: 6, 6;
animation: flowAnimation 1s linear infinite;
filter: drop-shadow(0 0 4px oklch(0.85 0.18 85 / 0.4));
}
/* Onboarding step 4: red connection line for disconnect */
.onboarding-connection-line-red {
stroke: rgba(220, 38, 38, 0.7);
stroke-width: 1.5px;
stroke-dasharray: 6, 6;
filter: drop-shadow(0 0 2px rgba(220, 38, 38, 0.3));
}
.graph-link-active {
stroke: oklch(0.85 0.18 85 / 0.8);
stroke-width: 2px;
@@ -337,51 +320,3 @@ input:focus, textarea:focus {
transform: translate(400px, 400px);
}
}
/* Onboarding smooth fade-in */
@keyframes onb-fade-in {
from { opacity: 0; transform: translateY(8px); }
to { opacity: 1; transform: none; }
}
/* Opacity-only fade-in — no transform, safe for containers with fixed-position children */
@keyframes onb-fade-opacity {
from { opacity: 0; }
to { opacity: 1; }
}
/* Respect reduced motion preference */
@media (prefers-reduced-motion: reduce) {
.shooting-star,
.shooting-star::before {
animation: none !important;
opacity: 0 !important;
}
.graph-link {
animation: none;
}
.status-pulse {
animation: none;
}
.cursor-blink {
animation: none;
}
.onboarding-connection-line {
animation: none;
}
.onboarding-connection-line-red {
animation: none;
}
[style*="onb-fade-in"],
[style*="onb-fade-opacity"] {
animation: none !important;
opacity: 1 !important;
}
*,
*::before,
*::after {
transition-duration: 0.01ms !important;
animation-duration: 0.01ms !important;
animation-iteration-count: 1 !important;
}
}
+287 -121
View File
@@ -1,15 +1,19 @@
<script lang="ts">
import {
isLoading,
sendMessage,
generateImage,
editImage,
editingImage,
clearEditingImage,
selectedChatModel,
setSelectedChatModel,
instances,
ttftMs,
tps,
totalTokens,
thinkingEnabled as thinkingEnabledStore,
setConversationThinking,
stopGeneration,
} from "$lib/stores/app.svelte";
import ChatAttachments from "./ChatAttachments.svelte";
import ImageParamsPanel from "./ImageParamsPanel.svelte";
@@ -24,19 +28,6 @@
showModelSelector?: boolean;
modelTasks?: Record<string, string[]>;
modelCapabilities?: Record<string, string[]>;
onSend?: () => void;
onAutoSend: (
content: string,
files?: {
id: string;
name: string;
type: string;
textContent?: string;
preview?: string;
}[],
) => void;
onOpenModelPicker?: () => void;
modelDisplayOverride?: string;
}
let {
@@ -47,10 +38,6 @@
showModelSelector = false,
modelTasks = {},
modelCapabilities = {},
onSend,
onAutoSend,
onOpenModelPicker,
modelDisplayOverride,
}: Props = $props();
let message = $state("");
@@ -61,12 +48,27 @@
const thinkingEnabled = $derived(thinkingEnabledStore());
let loading = $derived(isLoading());
const currentModel = $derived(selectedChatModel());
const instanceData = $derived(instances());
const currentTtft = $derived(ttftMs());
const currentTps = $derived(tps());
const currentTokens = $derived(totalTokens());
const currentEditingImage = $derived(editingImage());
const isEditMode = $derived(currentEditingImage !== null);
// Custom dropdown state
let isModelDropdownOpen = $state(false);
let dropdownButtonRef: HTMLButtonElement | undefined = $state();
let dropdownPosition = $derived(() => {
if (!dropdownButtonRef || !isModelDropdownOpen)
return { top: 0, left: 0, width: 0 };
const rect = dropdownButtonRef.getBoundingClientRect();
return {
top: rect.top,
left: rect.left,
width: rect.width,
};
});
// Accept all supported file types
const acceptString = getAcceptString(["image", "text", "pdf"]);
@@ -101,7 +103,7 @@
const modelSupportsThinking = $derived(() => {
if (!currentModel) return false;
const caps = modelCapabilities[currentModel] || [];
return caps.includes("thinking_toggle") && caps.includes("text");
return caps.includes("thinking") && caps.includes("text");
});
const isEditOnlyWithoutImage = $derived(
@@ -119,14 +121,73 @@
uploadedFiles.length > 0),
);
// Short label for the currently selected model
const currentModelLabel = $derived(
currentModel
? currentModel.split("/").pop() || currentModel
: modelDisplayOverride
? modelDisplayOverride.split("/").pop() || modelDisplayOverride
: "",
);
// Extract available models from running instances
const availableModels = $derived(() => {
const models: Array<{ id: string; label: string; isImageModel: boolean }> =
[];
for (const [, instance] of Object.entries(instanceData)) {
const modelId = getInstanceModelId(instance);
if (
modelId &&
modelId !== "Unknown" &&
!models.some((m) => m.id === modelId)
) {
models.push({
id: modelId,
label: modelId.split("/").pop() || modelId,
isImageModel: modelSupportsImageGeneration(modelId),
});
}
}
return models;
});
// Track previous model IDs to detect newly added models (plain variable to avoid reactive loop)
let previousModelIds: Set<string> = new Set();
// Auto-select the first available model if none is selected, if current selection is stale, or if a new model is added
$effect(() => {
const models = availableModels();
const currentModelIds = new Set(models.map((m) => m.id));
if (models.length > 0) {
// Find newly added models (in current but not in previous)
const newModels = models.filter((m) => !previousModelIds.has(m.id));
// If no model selected, select the first available
if (!currentModel) {
setSelectedChatModel(models[0].id);
}
// If current model is stale (no longer has a running instance), reset to first available
else if (!models.some((m) => m.id === currentModel)) {
setSelectedChatModel(models[0].id);
}
// If a new model was just added, select it
else if (newModels.length > 0 && previousModelIds.size > 0) {
setSelectedChatModel(newModels[0].id);
}
} else {
// No instances running - clear the selected model
if (currentModel) {
setSelectedChatModel("");
}
}
// Update previous model IDs for next comparison
previousModelIds = currentModelIds;
});
function getInstanceModelId(instanceWrapped: unknown): string {
if (!instanceWrapped || typeof instanceWrapped !== "object") return "";
const keys = Object.keys(instanceWrapped as Record<string, unknown>);
if (keys.length === 1) {
const instance = (instanceWrapped as Record<string, unknown>)[
keys[0]
] as { shardAssignments?: { modelId?: string } };
return instance?.shardAssignments?.modelId || "";
}
return "";
}
async function handleFiles(files: File[]) {
if (files.length === 0) return;
@@ -213,10 +274,38 @@
uploadedFiles = [];
resetTextareaHeight();
// Parent controls all send logic (including image routing,
// launching non-running models before sending, etc.)
onAutoSend(content, files);
onSend?.();
// Use image editing if in edit mode
if (isEditMode && currentEditingImage && content) {
editImage(content, currentEditingImage.imageDataUrl);
}
// If user attached an image with an ImageToImage model, use edit endpoint
else if (
currentModel &&
modelSupportsImageEditing(currentModel) &&
files.length > 0 &&
content
) {
// Use the first attached image for editing
const imageFile = files[0];
if (imageFile.preview) {
editImage(content, imageFile.preview);
}
} else if (
currentModel &&
modelSupportsTextToImage(currentModel) &&
content
) {
// Use image generation for text-to-image models
generateImage(content);
} else {
sendMessage(
content,
files,
modelSupportsThinking() ? thinkingEnabled : null,
);
}
// Refocus the textarea after sending
setTimeout(() => textareaRef?.focus(), 10);
}
@@ -326,7 +415,7 @@
{/if}
<!-- Model selector (when enabled) -->
{#if showModelSelector}
{#if showModelSelector && availableModels().length > 0}
<div
class="flex items-center justify-between gap-2 px-3 py-2 border-b border-exo-medium-gray/30"
>
@@ -335,22 +424,33 @@
class="text-xs text-exo-light-gray uppercase tracking-wider flex-shrink-0"
>MODEL:</span
>
<!-- Model button — opens the full model picker -->
<!-- Custom dropdown -->
<div class="relative flex-1 max-w-xs">
<button
bind:this={dropdownButtonRef}
type="button"
onclick={() => onOpenModelPicker?.()}
class="w-full bg-exo-medium-gray/50 border border-exo-yellow/30 rounded pl-3 pr-8 py-1.5 text-xs font-mono text-left tracking-wide cursor-pointer transition-all duration-200 hover:border-exo-yellow/50 focus:outline-none focus:border-exo-yellow/70"
onclick={() => (isModelDropdownOpen = !isModelDropdownOpen)}
class="w-full bg-exo-medium-gray/50 border border-exo-yellow/30 rounded pl-3 pr-8 py-1.5 text-xs font-mono text-left tracking-wide cursor-pointer transition-all duration-200 hover:border-exo-yellow/50 focus:outline-none focus:border-exo-yellow/70 {isModelDropdownOpen
? 'border-exo-yellow/70'
: ''}"
>
{#if currentModelLabel}
<span class="text-exo-yellow truncate">{currentModelLabel}</span
{#if availableModels().find((m) => m.id === currentModel)}
<span class="text-exo-yellow truncate"
>{availableModels().find((m) => m.id === currentModel)
?.label}</span
>
{:else if availableModels().length > 0}
<span class="text-exo-yellow truncate"
>{availableModels()[0].label}</span
>
{:else}
<span class="text-exo-light-gray/50">— SELECT MODEL —</span>
{/if}
</button>
<div
class="absolute right-2 top-1/2 -translate-y-1/2 pointer-events-none"
class="absolute right-2 top-1/2 -translate-y-1/2 pointer-events-none transition-transform duration-200 {isModelDropdownOpen
? 'rotate-180'
: ''}"
>
<svg
class="w-3 h-3 text-exo-yellow/60"
@@ -367,6 +467,78 @@
</svg>
</div>
</div>
{#if isModelDropdownOpen}
<!-- Backdrop to close dropdown -->
<button
type="button"
class="fixed inset-0 z-[9998] cursor-default"
onclick={() => (isModelDropdownOpen = false)}
aria-label="Close dropdown"
></button>
<!-- Dropdown Panel - fixed positioning to escape overflow:hidden -->
<div
class="fixed bg-exo-dark-gray border border-exo-yellow/30 rounded shadow-lg shadow-black/50 z-[9999] max-h-48 overflow-y-auto"
style="bottom: calc(100vh - {dropdownPosition()
.top}px + 4px); left: {dropdownPosition()
.left}px; width: {dropdownPosition().width}px;"
>
<div class="py-1">
{#each availableModels() as model}
<button
type="button"
onclick={() => {
setSelectedChatModel(model.id);
isModelDropdownOpen = false;
}}
class="w-full px-3 py-2 text-left text-xs font-mono tracking-wide transition-colors duration-100 flex items-center gap-2 {currentModel ===
model.id
? 'bg-transparent text-exo-yellow'
: 'text-exo-light-gray hover:text-exo-yellow'}"
>
{#if currentModel === model.id}
<svg
class="w-3 h-3 flex-shrink-0"
fill="currentColor"
viewBox="0 0 20 20"
>
<path
fill-rule="evenodd"
d="M16.707 5.293a1 1 0 010 1.414l-8 8a1 1 0 01-1.414 0l-4-4a1 1 0 011.414-1.414L8 12.586l7.293-7.293a1 1 0 011.414 0z"
clip-rule="evenodd"
/>
</svg>
{:else}
<span class="w-3"></span>
{/if}
{#if model.isImageModel}
<svg
class="w-3.5 h-3.5 flex-shrink-0 text-exo-yellow"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
aria-label="Image generation model"
>
<rect
x="3"
y="3"
width="18"
height="18"
rx="2"
ry="2"
/>
<circle cx="8.5" cy="8.5" r="1.5" />
<polyline points="21 15 16 10 5 21" />
</svg>
{/if}
<span class="truncate flex-1">{model.label}</span>
</button>
{/each}
</div>
</div>
{/if}
</div>
<!-- Thinking toggle -->
{#if modelSupportsThinking()}
@@ -481,92 +653,86 @@
style="min-height: 28px; max-height: 150px;"
></textarea>
{#if loading}
<button
type="button"
onclick={() => stopGeneration()}
class="px-2.5 sm:px-4 py-1.5 sm:py-2 rounded text-xs sm:text-xs tracking-[0.1em] sm:tracking-[0.15em] font-medium transition-all duration-200 whitespace-nowrap bg-exo-medium-gray/70 text-exo-light-gray hover:bg-exo-medium-gray hover:text-white"
aria-label="Stop generation"
>
<button
type="submit"
disabled={!canSend || loading || isEditOnlyWithoutImage}
class="px-2.5 sm:px-4 py-1.5 sm:py-2 rounded text-xs sm:text-xs tracking-[0.1em] sm:tracking-[0.15em] uppercase font-medium transition-all duration-200 whitespace-nowrap
{!canSend || loading || isEditOnlyWithoutImage
? 'bg-exo-medium-gray/50 text-exo-light-gray cursor-not-allowed'
: 'bg-exo-yellow text-exo-black hover:bg-exo-yellow-darker hover:shadow-[0_0_20px_rgba(255,215,0,0.3)]'}"
aria-label={shouldShowEditMode
? "Edit image"
: isImageModel()
? "Generate image"
: "Send message"}
>
{#if loading}
<span class="inline-flex items-center gap-1 sm:gap-2">
<svg
class="w-3 h-3 sm:w-3.5 sm:h-3.5"
fill="currentColor"
viewBox="0 0 24 24"
<span
class="w-2.5 h-2.5 sm:w-3 sm:h-3 border-2 border-current border-t-transparent rounded-full animate-spin"
></span>
<span class="hidden sm:inline"
>{shouldShowEditMode
? "EDITING"
: isImageModel()
? "GENERATING"
: "PROCESSING"}</span
>
<rect x="6" y="6" width="12" height="12" rx="1" />
</svg>
<span class="hidden sm:inline">Cancel</span>
<span class="sm:hidden">...</span>
</span>
</button>
{:else}
<button
type="submit"
disabled={!canSend || isEditOnlyWithoutImage}
class="px-2.5 sm:px-4 py-1.5 sm:py-2 rounded text-xs sm:text-xs tracking-[0.1em] sm:tracking-[0.15em] uppercase font-medium transition-all duration-200 whitespace-nowrap
{!canSend || isEditOnlyWithoutImage
? 'bg-exo-medium-gray/50 text-exo-light-gray cursor-not-allowed'
: 'bg-exo-yellow text-exo-black hover:bg-exo-yellow-darker hover:shadow-[0_0_20px_rgba(255,215,0,0.3)]'}"
aria-label={shouldShowEditMode
? "Edit image"
: isImageModel()
? "Generate image"
: "Send message"}
>
{#if shouldShowEditMode}
<span class="inline-flex items-center gap-1.5">
<svg
class="w-3.5 h-3.5"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z"
/>
</svg>
<span>EDIT</span>
</span>
{:else if isEditOnlyWithoutImage}
<span class="inline-flex items-center gap-1.5">
<svg
class="w-3.5 h-3.5"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z"
/>
</svg>
<span>EDIT</span>
</span>
{:else if isImageModel()}
<span class="inline-flex items-center gap-1.5">
<svg
class="w-3.5 h-3.5"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
>
<rect x="3" y="3" width="18" height="18" rx="2" ry="2" />
<circle cx="8.5" cy="8.5" r="1.5" />
<polyline points="21 15 16 10 5 21" />
</svg>
<span>GENERATE</span>
</span>
{:else}
SEND
{/if}
</button>
{/if}
{:else if shouldShowEditMode}
<span class="inline-flex items-center gap-1.5">
<svg
class="w-3.5 h-3.5"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z"
/>
</svg>
<span>EDIT</span>
</span>
{:else if isEditOnlyWithoutImage}
<span class="inline-flex items-center gap-1.5">
<svg
class="w-3.5 h-3.5"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z"
/>
</svg>
<span>EDIT</span>
</span>
{:else if isImageModel()}
<span class="inline-flex items-center gap-1.5">
<svg
class="w-3.5 h-3.5"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
>
<rect x="3" y="3" width="18" height="18" rx="2" ry="2" />
<circle cx="8.5" cy="8.5" r="1.5" />
<polyline points="21 15 16 10 5 21" />
</svg>
<span>GENERATE</span>
</span>
{:else}
SEND
{/if}
</button>
</div>
<!-- Bottom accent line -->
@@ -3,17 +3,16 @@
messages,
currentResponse,
isLoading,
prefillProgress,
deleteMessage,
editAndRegenerate,
regenerateLastResponse,
regenerateFromToken,
setEditingImage,
} from "$lib/stores/app.svelte";
import type { Message } from "$lib/stores/app.svelte";
import type { MessageAttachment } from "$lib/stores/app.svelte";
import MarkdownContent from "./MarkdownContent.svelte";
import TokenHeatmap from "./TokenHeatmap.svelte";
import PrefillProgressBar from "./PrefillProgressBar.svelte";
import ImageLightbox from "./ImageLightbox.svelte";
interface Props {
@@ -26,7 +25,6 @@
const messageList = $derived(messages());
const response = $derived(currentResponse());
const loading = $derived(isLoading());
const prefill = $derived(prefillProgress());
// Scroll management - user controls scroll, show button when not at bottom
const SCROLL_THRESHOLD = 100;
@@ -139,8 +137,6 @@
return "🖼";
case "text":
return "📄";
case "pdf":
return "📑";
default:
return "📎";
}
@@ -432,9 +428,6 @@
{:else}
<!-- Assistant message styling -->
<div class="p-3 sm:p-4">
{#if loading && isLastAssistantMessage(message.id) && prefill && !message.content}
<PrefillProgressBar progress={prefill} class="mb-3" />
{/if}
{#if message.thinking && message.thinking.trim().length > 0}
<div
class="mb-3 rounded border border-exo-yellow/20 bg-exo-black/40"
@@ -809,8 +802,8 @@
>
AWAITING INPUT
</p>
<p class="text-xs text-white/30 tracking-wider mt-1.5 font-mono">
Type a message below &middot; Shift+Enter for newline
<p class="text-sm sm:text-xs text-exo-light-gray tracking-wider mt-1">
ENTER A QUERY TO BEGIN
</p>
</div>
{/if}
@@ -825,7 +818,6 @@
onclick={scrollToBottom}
class="sticky bottom-4 left-1/2 -translate-x-1/2 w-10 h-10 rounded-full bg-exo-dark-gray/90 border border-exo-medium-gray/50 flex items-center justify-center text-exo-light-gray hover:text-exo-yellow hover:border-exo-yellow/50 transition-all shadow-lg cursor-pointer z-10"
title="Scroll to bottom"
aria-label="Scroll to bottom of messages"
>
<svg
class="w-5 h-5"
@@ -1,401 +0,0 @@
<script lang="ts" module>
export interface ChatModelInfo {
id: string;
name: string;
base_model: string;
storage_size_megabytes: number;
capabilities: string[];
family: string;
quantization: string;
}
// Auto mode tier list (for when user just starts typing)
export const AUTO_TIERS: string[][] = [
// Tier 1 (frontier)
["DeepSeek V3.1", "GLM-5", "Kimi K2.5", "Qwen3 Coder Next"],
// Tier 2 (excellent)
[
"Kimi K2",
"Qwen3 235B",
"MiniMax M2.5",
"Step 3.5 Flash",
"Qwen3 Next 80B",
],
// Tier 3 (great)
[
"GLM 4.7",
"MiniMax M2.1",
"Qwen3 Coder 480B",
"GLM 4.5 Air",
"Llama 3.3 70B",
],
// Tier 4 (good)
["GPT-OSS 120B", "Qwen3 30B", "Llama 3.1 70B", "GLM 4.7 Flash"],
// Tier 5 (small/fast)
[
"Llama 3.1 8B",
"GPT-OSS 20B",
"Llama 3.2 3B",
"Qwen3 0.6B",
"Llama 3.2 1B",
],
];
/** Return the tier index (0 = best) for a base_model name. */
export function getAutoTierIndex(baseModel: string): number {
for (let i = 0; i < AUTO_TIERS.length; i++) {
if (AUTO_TIERS[i].includes(baseModel)) return i;
}
return AUTO_TIERS.length; // not in any tier → lowest priority
}
/** Auto mode: walk tiers top-down, pick biggest fitting variant from highest tier. */
export function pickAutoModel(
modelList: ChatModelInfo[],
memoryGB: number,
): ChatModelInfo | null {
for (const tier of AUTO_TIERS) {
const candidates: ChatModelInfo[] = [];
for (const baseModel of tier) {
const variants = modelList
.filter(
(m) =>
m.base_model === baseModel &&
(m.storage_size_megabytes || 0) / 1024 <= memoryGB &&
(m.storage_size_megabytes || 0) > 0,
)
.sort(
(a, b) =>
(b.storage_size_megabytes || 0) - (a.storage_size_megabytes || 0),
);
if (variants[0]) candidates.push(variants[0]);
}
if (candidates.length > 0) {
candidates.sort(
(a, b) =>
(b.storage_size_megabytes || 0) - (a.storage_size_megabytes || 0),
);
return candidates[0];
}
}
return null;
}
</script>
<script lang="ts">
interface CategoryRecommendation {
category: "coding" | "writing" | "agentic" | "biggest";
label: string;
model: ChatModelInfo | null;
tooltip: string;
}
interface Props {
models: ChatModelInfo[];
clusterLabel: string;
totalMemoryGB: number;
onSelect: (modelId: string, category: string) => void;
onAddModel: () => void;
class?: string;
}
let {
models,
clusterLabel,
totalMemoryGB,
onSelect,
onAddModel,
class: className = "",
}: Props = $props();
// --- Hardcoded Rankings ---
const CODING_RANKING = [
"Qwen3 Coder Next",
"Qwen3 Coder 480B",
"Qwen3 30B",
"GPT-OSS 20B",
"Llama 3.1 8B",
"Llama 3.2 3B",
"Qwen3 0.6B",
];
const WRITING_RANKING = [
"Kimi K2.5",
"Kimi K2",
"Qwen3 Next 80B",
"Llama 3.3 70B",
"MiniMax M2.5",
"GLM 4.5 Air",
"GLM 4.7 Flash",
"GPT-OSS 20B",
"Llama 3.1 8B",
"Llama 3.2 3B",
"Qwen3 0.6B",
];
const AGENTIC_RANKING = [
"DeepSeek V3.1",
"GLM-5",
"Qwen3 235B",
"Step 3.5 Flash",
"GLM 4.7",
"MiniMax M2.1",
"GPT-OSS 120B",
"Llama 3.3 70B",
"Llama 3.1 70B",
"GLM 4.7 Flash",
"GPT-OSS 20B",
"Qwen3 30B",
"Llama 3.1 8B",
"Llama 3.2 3B",
"Qwen3 0.6B",
];
function getModelSizeGB(m: ChatModelInfo): number {
return (m.storage_size_megabytes || 0) / 1024;
}
function fitsInMemory(m: ChatModelInfo): boolean {
return getModelSizeGB(m) <= totalMemoryGB && getModelSizeGB(m) > 0;
}
/** For a given base_model name, find the biggest quant variant that fits in memory. */
function pickBestVariant(baseModel: string): ChatModelInfo | null {
const variants = models
.filter((m) => m.base_model === baseModel && fitsInMemory(m))
.sort((a, b) => getModelSizeGB(b) - getModelSizeGB(a));
return variants[0] ?? null;
}
/** Walk a ranked list of base_model names, return the first that has a fitting variant. */
function pickFromRanking(ranking: string[]): ChatModelInfo | null {
for (const baseModel of ranking) {
const pick = pickBestVariant(baseModel);
if (pick) return pick;
}
return null;
}
/** Pick the single biggest model that fits. */
function pickBiggest(): ChatModelInfo | null {
const fitting = models
.filter((m) => fitsInMemory(m))
.sort((a, b) => getModelSizeGB(b) - getModelSizeGB(a));
return fitting[0] ?? null;
}
const recommendations = $derived.by((): CategoryRecommendation[] => {
return [
{
category: "coding",
label: "Best for Coding",
model: pickFromRanking(CODING_RANKING),
tooltip:
"Ranked by coding benchmark performance (LiveCodeBench, SWE-bench)",
},
{
category: "writing",
label: "Best for Writing",
model: pickFromRanking(WRITING_RANKING),
tooltip: "Ranked by creative writing quality and instruction following",
},
{
category: "agentic",
label: "Best Agentic",
model: pickFromRanking(AGENTIC_RANKING),
tooltip: "Ranked by reasoning, planning, and tool-use capability",
},
{
category: "biggest",
label: "Biggest",
model: pickBiggest(),
tooltip: "Largest model that fits in your available memory",
},
];
});
function formatSize(mb: number): string {
const gb = mb / 1024;
if (gb >= 100) return `${Math.round(gb)} GB`;
return `${gb.toFixed(1)} GB`;
}
// Category icons (SVG paths)
const categoryIcons: Record<string, string> = {
coding:
"M8 9l3 3-3 3m5 0h3M5 20h14a2 2 0 002-2V6a2 2 0 00-2-2H5a2 2 0 00-2 2v12a2 2 0 002 2z",
writing:
"M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z",
agentic:
"M9.663 17h4.673M12 3v1m6.364 1.636l-.707.707M21 12h-1M4 12H3m3.343-5.657l-.707-.707m2.828 9.9a5 5 0 117.072 0l-.548.547A3.374 3.374 0 0014 18.469V19a2 2 0 11-4 0v-.531c0-.895-.356-1.754-.988-2.386l-.548-.547z",
biggest:
"M19 11H5m14 0a2 2 0 012 2v6a2 2 0 01-2 2H5a2 2 0 01-2-2v-6a2 2 0 012-2m14 0V9a2 2 0 00-2-2M5 11V9a2 2 0 012-2m0 0V5a2 2 0 012-2h6a2 2 0 012 2v2M7 7h10",
};
let hoveredTooltip = $state<string | null>(null);
let tooltipAnchor = $state<{ x: number; y: number } | null>(null);
function showTooltip(category: string, e: MouseEvent | FocusEvent) {
hoveredTooltip = category;
const target = e.currentTarget as HTMLElement;
const rect = target.getBoundingClientRect();
tooltipAnchor = { x: rect.left + rect.width / 2, y: rect.top };
}
function hideTooltip() {
hoveredTooltip = null;
tooltipAnchor = null;
}
</script>
<div class="flex flex-col items-center justify-center gap-6 {className}">
<!-- Header -->
<div class="text-center">
<p class="text-xs text-exo-light-gray uppercase tracking-[0.2em] mb-1">
Recommended for your
</p>
<p class="text-sm text-white font-mono tracking-wide">{clusterLabel}</p>
</div>
<!-- Category Cards Grid -->
<div class="grid grid-cols-2 gap-3 w-full max-w-md">
{#each recommendations as rec}
{#if rec.model}
<button
type="button"
onclick={() => rec.model && onSelect(rec.model.id, rec.category)}
class="group relative flex flex-col items-start gap-2 p-4 rounded-lg border border-exo-medium-gray/50 bg-exo-dark-gray/50 hover:border-exo-yellow/40 hover:bg-exo-dark-gray transition-all duration-200 cursor-pointer text-left"
>
<!-- Category icon + label -->
<div class="flex items-center gap-2 w-full">
<svg
class="w-4 h-4 text-exo-yellow/70 group-hover:text-exo-yellow transition-colors flex-shrink-0"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="1.5"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
d={categoryIcons[rec.category]}
/>
</svg>
<span
class="text-xs font-mono uppercase tracking-wider text-exo-light-gray group-hover:text-white transition-colors"
>
{rec.label}
</span>
<!-- Info tooltip -->
<div class="ml-auto flex-shrink-0">
<span
role="button"
tabindex="-1"
class="text-exo-light-gray/40 hover:text-exo-light-gray transition-colors cursor-help inline-flex"
onmouseenter={(e: MouseEvent) => showTooltip(rec.category, e)}
onmouseleave={() => hideTooltip()}
onclick={(e: MouseEvent) => {
e.stopPropagation();
if (hoveredTooltip === rec.category) {
hideTooltip();
} else {
showTooltip(rec.category, e);
}
}}
>
<svg
class="w-3.5 h-3.5"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
>
<circle cx="12" cy="12" r="10" />
<path d="M12 16v-4m0-4h.01" />
</svg>
</span>
</div>
</div>
<!-- Model name + size -->
<div class="w-full">
<p class="text-sm text-white font-mono truncate">
{rec.model.base_model}
</p>
<p class="text-xs text-exo-light-gray/60 font-mono mt-0.5">
{formatSize(rec.model.storage_size_megabytes)}
{#if rec.model.quantization}
<span class="text-exo-light-gray/40"
>&middot; {rec.model.quantization}</span
>
{/if}
</p>
</div>
</button>
{:else}
<!-- No model fits for this category -->
<div
class="flex flex-col items-start gap-2 p-4 rounded-lg border border-exo-medium-gray/30 bg-exo-dark-gray/30 opacity-50"
>
<div class="flex items-center gap-2">
<svg
class="w-4 h-4 text-exo-light-gray/40 flex-shrink-0"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="1.5"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
d={categoryIcons[rec.category]}
/>
</svg>
<span
class="text-xs font-mono uppercase tracking-wider text-exo-light-gray/50"
>{rec.label}</span
>
</div>
<p class="text-xs text-exo-light-gray/40 font-mono">No model fits</p>
</div>
{/if}
{/each}
</div>
<!-- Add Model Button -->
<button
type="button"
onclick={onAddModel}
class="flex items-center gap-2 px-4 py-2 text-xs font-mono uppercase tracking-wider text-exo-light-gray hover:text-exo-yellow border border-exo-medium-gray/30 hover:border-exo-yellow/30 rounded-lg transition-all duration-200 cursor-pointer"
>
<svg
class="w-3.5 h-3.5"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
>
<path stroke-linecap="round" stroke-linejoin="round" d="M12 4v16m8-8H4" />
</svg>
Add Model
</button>
<!-- Auto hint -->
<p class="text-xs text-exo-light-gray/40 font-mono tracking-wide text-center">
Or just start typing &mdash; we'll pick the best model automatically
</p>
</div>
<!-- Fixed-position tooltip (escapes overflow-hidden ancestors) -->
{#if hoveredTooltip && tooltipAnchor}
{@const rec = recommendations.find((r) => r.category === hoveredTooltip)}
{#if rec}
<div
class="fixed z-[9999] px-3 py-2 bg-exo-black border border-exo-medium-gray/50 rounded text-xs text-exo-light-gray whitespace-nowrap shadow-lg pointer-events-none"
style="left: {tooltipAnchor.x}px; top: {tooltipAnchor.y -
8}px; transform: translate(-50%, -100%);"
>
{rec.tooltip}
</div>
{/if}
{/if}
+33 -67
View File
@@ -2,6 +2,7 @@
import {
conversations,
activeConversationId,
createConversation,
loadConversation,
deleteConversation,
deleteAllConversations,
@@ -16,21 +17,9 @@
interface Props {
class?: string;
onNewChat?: () => void;
onSelectConversation?: () => void;
isMobileDrawer?: boolean;
isOpen?: boolean;
onClose?: () => void;
}
let {
class: className = "",
onNewChat,
onSelectConversation,
isMobileDrawer = false,
isOpen = false,
onClose,
}: Props = $props();
let { class: className = "" }: Props = $props();
const conversationList = $derived(conversations());
const activeId = $derived(activeConversationId());
@@ -53,16 +42,11 @@
);
function handleNewChat() {
onNewChat?.();
createConversation();
}
function handleSelectConversation(id: string) {
onSelectConversation?.();
loadConversation(id);
// Close mobile drawer when selecting a conversation
if (isMobileDrawer && isOpen) {
onClose?.();
}
}
function handleStartEdit(id: string, name: string, event: MouseEvent) {
@@ -201,7 +185,11 @@
let instanceType: string | null = null;
if (instanceTag === "MlxRingInstance") instanceType = "MLX Ring";
else if (instanceTag === "MlxJacclInstance") instanceType = "MLX RDMA";
else if (
instanceTag === "MlxIbvInstance" ||
instanceTag === "MlxJacclInstance"
)
instanceType = "MLX RDMA";
let sharding: string | null = null;
const inst = instance as {
@@ -262,7 +250,9 @@
}
</script>
{#snippet sidebarContent()}
<aside
class="flex flex-col h-full bg-exo-dark-gray border-r border-exo-yellow/10 {className}"
>
<!-- Header -->
<div class="p-4">
<button
@@ -317,7 +307,7 @@
<div class="py-2">
<div class="px-4 py-2">
<span
class="text-xs text-exo-light-gray font-mono tracking-wider uppercase"
class="text-sm text-white/70 font-mono tracking-wider uppercase"
>
{searchQuery ? "SEARCH RESULTS" : "CONVERSATIONS"}
</span>
@@ -386,37 +376,39 @@
onkeydown={(e) =>
e.key === "Enter" &&
handleSelectConversation(conversation.id)}
class="group w-full flex items-center justify-between p-2.5 rounded-lg mb-1 transition-all text-left cursor-pointer
class="group w-full flex items-center justify-between p-2 rounded mb-1 transition-all text-left cursor-pointer
{activeId === conversation.id
? 'bg-exo-yellow/5 border border-exo-yellow/30'
: 'hover:bg-white/[0.03] hover:border-white/10 border border-transparent'}"
? 'bg-transparent border border-exo-yellow/30'
: 'hover:border-exo-yellow/20 border border-transparent'}"
>
<div class="flex-1 min-w-0 pr-2">
<div
class="text-sm font-medium truncate {activeId ===
conversation.id
class="text-sm truncate {activeId === conversation.id
? 'text-exo-yellow'
: 'text-white'}"
: 'text-white/90'}"
>
{conversation.name}
</div>
<div class="text-xs text-white/60 mt-0.5">
<div class="text-sm text-white/50 mt-0.5">
{formatDate(conversation.updatedAt)}
</div>
<div class="text-xs text-exo-light-gray truncate">
<div class="text-sm text-white/70 truncate">
{info.modelLabel}
</div>
<div class="text-xs text-white/60 font-mono">
Strategy: <span class="text-white/80"
>{info.strategyLabel}</span
>
</div>
{#if stats}
<div class="text-xs text-white/70 font-mono mt-1">
{#if stats.ttftMs}<span class="text-white/50">TTFT</span>
<span class="text-exo-yellow/80"
>{stats.ttftMs.toFixed(0)}ms</span
>{/if}{#if stats.ttftMs && stats.tps}<span
class="text-white/30 mx-1.5">·</span
>{/if}{#if stats.tps}<span class="text-exo-yellow/80"
>{stats.tps.toFixed(1)}</span
>
<span class="text-white/50">tok/s</span>{/if}
<div class="text-xs text-white/60 font-mono mt-1">
{#if stats.ttftMs}<span class="text-white/40">TTFT</span>
{stats.ttftMs.toFixed(
0,
)}ms{/if}{#if stats.ttftMs && stats.tps}<span
class="text-white/30 mx-1.5"></span
>{/if}{#if stats.tps}{stats.tps.toFixed(1)}
<span class="text-white/40">tok/s</span>{/if}
</div>
{/if}
</div>
@@ -599,30 +591,4 @@
</button>
</div>
</div>
{/snippet}
{#if isMobileDrawer}
<!-- Mobile drawer with overlay -->
{#if isOpen}
<!-- Overlay backdrop -->
<button
type="button"
class="fixed inset-0 bg-black/60 backdrop-blur-sm z-40 md:hidden"
onclick={() => onClose?.()}
aria-label="Close sidebar"
></button>
<!-- Drawer panel -->
<aside
class="fixed left-0 top-0 bottom-0 w-72 bg-exo-dark-gray border-r border-exo-yellow/10 z-50 flex flex-col md:hidden"
>
{@render sidebarContent()}
</aside>
{/if}
{:else}
<!-- Desktop sidebar -->
<aside
class="flex flex-col h-full bg-exo-dark-gray border-r border-exo-yellow/10 {className}"
>
{@render sidebarContent()}
</aside>
{/if}
</aside>
@@ -1,20 +0,0 @@
<script lang="ts">
import { isConnected } from "$lib/stores/app.svelte";
import { slide } from "svelte/transition";
const connected = $derived(isConnected());
</script>
{#if !connected}
<div
transition:slide={{ duration: 200 }}
class="relative z-50 flex items-center justify-center gap-2 px-4 py-2 bg-red-950/80 border-b border-red-500/30"
role="alert"
aria-live="assertive"
>
<div class="w-2 h-2 bg-red-500 rounded-full animate-pulse"></div>
<span class="text-xs font-mono text-red-300 tracking-wider uppercase">
Connection lost &mdash; Reconnecting to backend&hellip;
</span>
</div>
{/if}
@@ -1,277 +0,0 @@
<script lang="ts">
/**
* DeviceIcon — renders a device icon as an SVG <g> element.
* Uses the exact same proportional math as TopologyGraph.svelte
* so that devices look identical in both the topology view and
* the onboarding animation.
*
* Must be placed inside an <svg> element.
*/
interface Props {
/** "macbook pro" | "mac studio" | "mac mini" etc. */
deviceType: string;
/** Center X coordinate in SVG space */
cx: number;
/** Center Y coordinate in SVG space */
cy: number;
/** Base sizing factor (equivalent to TopologyGraph's nodeRadius) */
size?: number;
/** RAM usage 0100 */
ramPercent?: number;
/** Unique id suffix for clip-path ids */
uid?: string;
}
let {
deviceType,
cx,
cy,
size = 60,
ramPercent = 60,
uid = "dev",
}: Props = $props();
// Apple logo path — same constant used by TopologyGraph
const APPLE_LOGO_PATH =
"M788.1 340.9c-5.8 4.5-108.2 62.2-108.2 190.5 0 148.4 130.3 200.9 134.2 202.2-.6 3.2-20.7 71.9-68.7 141.9-42.8 61.6-87.5 123.1-155.5 123.1s-85.5-39.5-164-39.5c-76.5 0-103.7 40.8-165.9 40.8s-105.6-57-155.5-127C46.7 790.7 0 663 0 541.8c0-194.4 126.4-297.5 250.8-297.5 66.1 0 121.2 43.4 162.7 43.4 39.5 0 101.1-46 176.3-46 28.5 0 130.9 2.6 198.3 99.2zm-234-181.5c31.1-36.9 53.1-88.1 53.1-139.3 0-7.1-.6-14.3-1.9-20.1-50.6 1.9-110.8 33.7-147.1 75.8-28.5 32.4-55.1 83.6-55.1 135.5 0 7.8 1.3 15.6 1.9 18.1 3.2.6 8.4 1.3 13.6 1.3 45.4 0 102.5-30.4 135.5-71.3z";
const LOGO_NATIVE_WIDTH = 814;
const LOGO_NATIVE_HEIGHT = 1000;
const wireColor = "rgba(179,179,179,0.8)";
const strokeWidth = 1.5;
const modelLower = $derived(deviceType.toLowerCase());
// ── Mac Studio dimensions (same ratios as TopologyGraph) ──
const studioW = $derived(size * 1.25);
const studioH = $derived(size * 0.85);
const studioX = $derived(cx - studioW / 2);
const studioY = $derived(cy - studioH / 2);
const studioCorner = 4;
const studioTopH = $derived(studioH * 0.15);
// Studio front panel details
const studioSlotH = $derived(studioH * 0.14);
const studioVSlotW = $derived(studioW * 0.05);
const studioVSlotY = $derived(
studioY + studioTopH + (studioH - studioTopH) * 0.6,
);
const studioVSlot1X = $derived(studioX + studioW * 0.18);
const studioVSlot2X = $derived(studioX + studioW * 0.28);
const studioHSlotW = $derived(studioW * 0.2);
const studioHSlotX = $derived(studioX + studioW * 0.5 - studioHSlotW / 2);
// Studio memory fill
const studioMemTotalH = $derived(studioH - studioTopH);
const studioMemH = $derived((ramPercent / 100) * studioMemTotalH);
// ── MacBook dimensions (same ratios as TopologyGraph) ──
const mbW = $derived((size * 1.6 * 0.85) / 1.15);
const mbH = $derived(size * 0.85);
const mbX = $derived(cx - mbW / 2);
const mbY = $derived(cy - mbH / 2);
const mbScreenH = $derived(mbH * 0.7);
const mbBaseH = $derived(mbH * 0.3);
const mbScreenW = $derived(mbW * 0.85);
const mbScreenX = $derived(cx - mbScreenW / 2);
const mbBezel = 3;
// MacBook memory fill
const mbMemTotalH = $derived(mbScreenH - mbBezel * 2);
const mbMemH = $derived((ramPercent / 100) * mbMemTotalH);
// Apple logo sizing
const mbLogoTargetH = $derived(mbScreenH * 0.22);
const mbLogoScale = $derived(mbLogoTargetH / LOGO_NATIVE_HEIGHT);
const mbLogoX = $derived(cx - (LOGO_NATIVE_WIDTH * mbLogoScale) / 2);
const mbLogoY = $derived(
mbY + mbScreenH / 2 - (LOGO_NATIVE_HEIGHT * mbLogoScale) / 2,
);
// MacBook base (trapezoidal)
const mbBaseY = $derived(mbY + mbScreenH);
const mbBaseTopW = $derived(mbScreenW);
const mbBaseBottomW = $derived(mbW);
const mbBaseTopX = $derived(cx - mbBaseTopW / 2);
const mbBaseBottomX = $derived(cx - mbBaseBottomW / 2);
// Keyboard
const mbKbX = $derived(mbBaseTopX + 6);
const mbKbY = $derived(mbBaseY + 3);
const mbKbW = $derived(mbBaseTopW - 12);
const mbKbH = $derived(mbBaseH * 0.55);
// Trackpad
const mbTpW = $derived(mbBaseTopW * 0.4);
const mbTpX = $derived(cx - mbTpW / 2);
const mbTpY = $derived(mbBaseY + mbKbH + 5);
const mbTpH = $derived(mbBaseH * 0.3);
// Clip IDs
const screenClipId = $derived(`di-screen-${uid}`);
const studioClipId = $derived(`di-studio-${uid}`);
</script>
{#if modelLower === "mac studio" || modelLower === "mac mini"}
<!-- Mac Studio / Mac Mini -->
<defs>
<clipPath id={studioClipId}>
<rect
x={studioX}
y={studioY + studioTopH}
width={studioW}
height={studioH - studioTopH}
rx={studioCorner - 1}
/>
</clipPath>
</defs>
<!-- Main body -->
<rect
x={studioX}
y={studioY}
width={studioW}
height={studioH}
rx={studioCorner}
fill="#1a1a1a"
stroke={wireColor}
stroke-width={strokeWidth}
/>
<!-- Memory fill -->
{#if ramPercent > 0}
<rect
x={studioX}
y={studioY + studioTopH + (studioMemTotalH - studioMemH)}
width={studioW}
height={studioMemH}
fill="rgba(255,215,0,0.75)"
clip-path="url(#{studioClipId})"
/>
{/if}
<!-- Top surface divider -->
<line
x1={studioX}
y1={studioY + studioTopH}
x2={studioX + studioW}
y2={studioY + studioTopH}
stroke="rgba(179,179,179,0.3)"
stroke-width="0.5"
/>
<!-- Front panel: vertical slots -->
<rect
x={studioVSlot1X - studioVSlotW / 2}
y={studioVSlotY}
width={studioVSlotW}
height={studioSlotH}
fill="rgba(0,0,0,0.35)"
rx="1.5"
/>
<rect
x={studioVSlot2X - studioVSlotW / 2}
y={studioVSlotY}
width={studioVSlotW}
height={studioSlotH}
fill="rgba(0,0,0,0.35)"
rx="1.5"
/>
<!-- Horizontal slot (SD card) -->
<rect
x={studioHSlotX}
y={studioVSlotY}
width={studioHSlotW}
height={studioSlotH * 0.6}
fill="rgba(0,0,0,0.35)"
rx="1"
/>
{:else}
<!-- MacBook Pro -->
<defs>
<clipPath id={screenClipId}>
<rect
x={mbScreenX + mbBezel}
y={mbY + mbBezel}
width={mbScreenW - mbBezel * 2}
height={mbScreenH - mbBezel * 2}
rx="2"
/>
</clipPath>
</defs>
<!-- Screen outer frame -->
<rect
x={mbScreenX}
y={mbY}
width={mbScreenW}
height={mbScreenH}
rx="3"
fill="#1a1a1a"
stroke={wireColor}
stroke-width={strokeWidth}
/>
<!-- Screen inner (dark) -->
<rect
x={mbScreenX + mbBezel}
y={mbY + mbBezel}
width={mbScreenW - mbBezel * 2}
height={mbScreenH - mbBezel * 2}
rx="2"
fill="#0a0a12"
/>
<!-- Memory fill on screen -->
{#if ramPercent > 0}
<rect
x={mbScreenX + mbBezel}
y={mbY + mbBezel + (mbMemTotalH - mbMemH)}
width={mbScreenW - mbBezel * 2}
height={mbMemH}
fill="rgba(255,215,0,0.85)"
clip-path="url(#{screenClipId})"
/>
{/if}
<!-- Apple logo -->
<path
d={APPLE_LOGO_PATH}
transform="translate({mbLogoX}, {mbLogoY}) scale({mbLogoScale})"
fill="#FFFFFF"
opacity="0.9"
/>
<!-- Keyboard base (trapezoidal) -->
<path
d="M {mbBaseTopX} {mbBaseY} L {mbBaseTopX +
mbBaseTopW} {mbBaseY} L {mbBaseBottomX + mbBaseBottomW} {mbBaseY +
mbBaseH} L {mbBaseBottomX} {mbBaseY + mbBaseH} Z"
fill="#2c2c2c"
stroke={wireColor}
stroke-width="1"
/>
<!-- Keyboard area -->
<rect
x={mbKbX}
y={mbKbY}
width={mbKbW}
height={mbKbH}
fill="rgba(0,0,0,0.2)"
rx="2"
/>
<!-- Trackpad -->
<rect
x={mbTpX}
y={mbTpY}
width={mbTpW}
height={mbTpH}
fill="rgba(255,255,255,0.08)"
rx="2"
/>
{/if}
@@ -82,18 +82,6 @@
d="M12.025 1.13c-5.77 0-10.449 4.647-10.449 10.378 0 1.112.178 2.181.503 3.185.064-.222.203-.444.416-.577a.96.96 0 0 1 .524-.15c.293 0 .584.124.84.284.278.173.48.408.71.694.226.282.458.611.684.951v-.014c.017-.324.106-.622.264-.874s.403-.487.762-.543c.3-.047.596.06.787.203s.31.313.4.467c.15.257.212.468.233.542.01.026.653 1.552 1.657 2.54.616.605 1.01 1.223 1.082 1.912.055.537-.096 1.059-.38 1.572.637.121 1.294.187 1.967.187.657 0 1.298-.063 1.921-.178-.287-.517-.44-1.041-.384-1.581.07-.69.465-1.307 1.081-1.913 1.004-.987 1.647-2.513 1.657-2.539.021-.074.083-.285.233-.542.09-.154.208-.323.4-.467a1.08 1.08 0 0 1 .787-.203c.359.056.604.29.762.543s.247.55.265.874v.015c.225-.34.457-.67.683-.952.23-.286.432-.52.71-.694.257-.16.547-.284.84-.285a.97.97 0 0 1 .524.151c.228.143.373.388.43.625l.006.04a10.3 10.3 0 0 0 .534-3.273c0-5.731-4.678-10.378-10.449-10.378M8.327 6.583a1.5 1.5 0 0 1 .713.174 1.487 1.487 0 0 1 .617 2.013c-.183.343-.762-.214-1.102-.094-.38.134-.532.914-.917.71a1.487 1.487 0 0 1 .69-2.803m7.486 0a1.487 1.487 0 0 1 .689 2.803c-.385.204-.536-.576-.916-.71-.34-.12-.92.437-1.103.094a1.487 1.487 0 0 1 .617-2.013 1.5 1.5 0 0 1 .713-.174m-10.68 1.55a.96.96 0 1 1 0 1.921.96.96 0 0 1 0-1.92m13.838 0a.96.96 0 1 1 0 1.92.96.96 0 0 1 0-1.92M8.489 11.458c.588.01 1.965 1.157 3.572 1.164 1.607-.007 2.984-1.155 3.572-1.164.196-.003.305.12.305.454 0 .886-.424 2.328-1.563 3.202-.22-.756-1.396-1.366-1.63-1.32q-.011.001-.02.006l-.044.026-.01.008-.03.024q-.018.017-.035.036l-.032.04a1 1 0 0 0-.058.09l-.014.025q-.049.088-.11.19a1 1 0 0 1-.083.116 1.2 1.2 0 0 1-.173.18q-.035.029-.075.058a1.3 1.3 0 0 1-.251-.243 1 1 0 0 1-.076-.107c-.124-.193-.177-.363-.337-.444-.034-.016-.104-.008-.2.022q-.094.03-.216.087-.06.028-.125.063l-.13.074q-.067.04-.136.086a3 3 0 0 0-.135.096 3 3 0 0 0-.26.219 2 2 0 0 0-.12.121 2 2 0 0 0-.106.128l-.002.002a2 2 0 0 0-.09.132l-.001.001a1.2 1.2 0 0 0-.105.212q-.013.036-.024.073c-1.139-.875-1.563-2.317-1.563-3.203 0-.334.109-.457.305-.454m.836 10.354c.824-1.19.766-2.082-.365-3.194-1.13-1.112-1.789-2.738-1.789-2.738s-.246-.945-.806-.858-.97 1.499.202 2.362c1.173.864-.233 1.45-.685.64-.45-.812-1.683-2.896-2.322-3.295s-1.089-.175-.938.647 2.822 2.813 2.562 3.244-1.176-.506-1.176-.506-2.866-2.567-3.49-1.898.473 1.23 2.037 2.16c1.564.932 1.686 1.178 1.464 1.53s-3.675-2.511-4-1.297c-.323 1.214 3.524 1.567 3.287 2.405-.238.839-2.71-1.587-3.216-.642-.506.946 3.49 2.056 3.522 2.064 1.29.33 4.568 1.028 5.713-.624m5.349 0c-.824-1.19-.766-2.082.365-3.194 1.13-1.112 1.789-2.738 1.789-2.738s.246-.945.806-.858.97 1.499-.202 2.362c-1.173.864.233 1.45.685.64.451-.812 1.683-2.896 2.322-3.295s1.089-.175.938.647-2.822 2.813-2.562 3.244 1.176-.506 1.176-.506 2.866-2.567 3.49-1.898-.473 1.23-2.037 2.16c-1.564.932-1.686 1.178-1.464 1.53s3.675-2.511 4-1.297c.323 1.214-3.524 1.567-3.287 2.405.238.839 2.71-1.587 3.216-.642.506.946-3.49 2.056-3.522 2.064-1.29.33-4.568 1.028-5.713-.624"
/>
</svg>
{:else if family === "step"}
<svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
<path
d="M22.012 0h1.032v.927H24v.968h-.956V3.78h-1.032V1.896h-1.878v-.97h1.878V0zM2.6 12.371V1.87h.969v10.502h-.97zm10.423.66h10.95v.918h-6.208v9.579h-4.742V13.03zM5.629 3.333v12.356H0v4.51h10.386V8L20.859 8l-.003-4.668-15.227.001z"
/>
</svg>
{:else if family === "nemotron"}
<svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
<path
d="M8.948 8.798v-1.43a6.7 6.7 0 0 1 .424-.018c3.922-.124 6.493 3.374 6.493 3.374s-2.774 3.851-5.75 3.851c-.398 0-.787-.062-1.158-.185v-4.346c1.528.185 1.837.857 2.747 2.385l2.04-1.714s-1.492-1.952-4-1.952a6.016 6.016 0 0 0-.796.035m0-4.735v2.138l.424-.027c5.45-.185 9.01 4.47 9.01 4.47s-4.08 4.964-8.33 4.964c-.37 0-.733-.035-1.095-.097v1.325c.3.035.61.062.91.062 3.957 0 6.82-2.023 9.593-4.408.459.371 2.34 1.263 2.73 1.652-2.633 2.208-8.772 3.984-12.253 3.984-.335 0-.653-.018-.971-.053v1.864H24V4.063zm0 10.326v1.131c-3.657-.654-4.673-4.46-4.673-4.46s1.758-1.944 4.673-2.262v1.237H8.94c-1.528-.186-2.73 1.245-2.73 1.245s.68 2.412 2.739 3.11M2.456 10.9s2.164-3.197 6.5-3.533V6.201C4.153 6.59 0 10.653 0 10.653s2.35 6.802 8.948 7.42v-1.237c-4.84-.6-6.492-5.936-6.492-5.936z"
/>
</svg>
{:else}
<svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
<path
@@ -31,7 +31,6 @@
kimi: "Kimi",
flux: "FLUX",
"qwen-image": "Qwen Img",
nemotron: "NVIDIA",
};
function getFamilyName(family: string): string {
@@ -42,20 +41,31 @@
</script>
<div
class="flex flex-col gap-1 py-2 px-1 border-r border-exo-yellow/10 bg-exo-medium-gray/30 min-w-[80px] sm:min-w-[72px] overflow-y-auto scrollbar-hide"
class="flex flex-col gap-1 py-2 px-1 border-r border-exo-yellow/10 bg-exo-medium-gray/30 min-w-[64px] overflow-y-auto scrollbar-hide"
>
<!-- All models (no filter) -->
<button
type="button"
onclick={() => onSelect(null)}
class="group flex items-center justify-center px-3 py-2.5 rounded transition-all duration-200 cursor-pointer min-h-[44px] sm:min-h-0 {selectedFamily ===
class="group flex flex-col items-center justify-center p-2 rounded transition-all duration-200 cursor-pointer {selectedFamily ===
null
? 'bg-exo-yellow/20 border-l-2 border-exo-yellow'
: 'hover:bg-white/5 border-l-2 border-transparent'}"
title="All models"
>
<svg
class="w-5 h-5 {selectedFamily === null
? 'text-exo-yellow'
: 'text-white/50 group-hover:text-white/70'}"
viewBox="0 0 24 24"
fill="currentColor"
>
<path
d="M4 8h4V4H4v4zm6 12h4v-4h-4v4zm-6 0h4v-4H4v4zm0-6h4v-4H4v4zm6 0h4v-4h-4v4zm6-10v4h4V4h-4zm-6 4h4V4h-4v4zm6 6h4v-4h-4v4zm0 6h4v-4h-4v4z"
/>
</svg>
<span
class="text-[12px] font-mono font-medium {selectedFamily === null
class="text-[9px] font-mono mt-0.5 {selectedFamily === null
? 'text-exo-yellow'
: 'text-white/40 group-hover:text-white/60'}">All</span
>
@@ -79,7 +89,7 @@
: "text-white/50 group-hover:text-amber-400/70"}
/>
<span
class="text-[11px] font-mono mt-0.5 {selectedFamily === 'favorites'
class="text-[9px] font-mono mt-0.5 {selectedFamily === 'favorites'
? 'text-amber-400'
: 'text-white/40 group-hover:text-white/60'}">Faves</span
>
@@ -104,7 +114,7 @@
: "text-white/50 group-hover:text-white/70"}
/>
<span
class="text-[11px] font-mono mt-0.5 {selectedFamily === 'recents'
class="text-[9px] font-mono mt-0.5 {selectedFamily === 'recents'
? 'text-exo-yellow'
: 'text-white/40 group-hover:text-white/60'}">Recent</span
>
@@ -128,7 +138,7 @@
: "text-white/50 group-hover:text-orange-400/70"}
/>
<span
class="text-[11px] font-mono mt-0.5 {selectedFamily === 'huggingface'
class="text-[9px] font-mono mt-0.5 {selectedFamily === 'huggingface'
? 'text-orange-400'
: 'text-white/40 group-hover:text-white/60'}">Hub</span
>
@@ -154,7 +164,7 @@
: "text-white/50 group-hover:text-white/70"}
/>
<span
class="text-[11px] font-mono mt-0.5 truncate max-w-full {selectedFamily ===
class="text-[9px] font-mono mt-0.5 truncate max-w-full {selectedFamily ===
family
? 'text-exo-yellow'
: 'text-white/40 group-hover:text-white/60'}"
+51 -223
View File
@@ -1,38 +1,11 @@
<script lang="ts">
import { browser } from "$app/environment";
interface Props {
showHome?: boolean;
onHome?: (() => void) | null;
showSidebarToggle?: boolean;
sidebarVisible?: boolean;
onToggleSidebar?: (() => void) | null;
showMobileMenuToggle?: boolean;
mobileMenuOpen?: boolean;
onToggleMobileMenu?: (() => void) | null;
showMobileRightToggle?: boolean;
mobileRightOpen?: boolean;
onToggleMobileRight?: (() => void) | null;
downloadProgress?: {
count: number;
percentage: number;
} | null;
}
let {
showHome = true,
onHome = null,
showSidebarToggle = false,
sidebarVisible = true,
onToggleSidebar = null,
showMobileMenuToggle = false,
mobileMenuOpen = false,
onToggleMobileMenu = null,
showMobileRightToggle = false,
mobileRightOpen = false,
onToggleMobileRight = null,
downloadProgress = null,
}: Props = $props();
export let showHome = true;
export let onHome: (() => void) | null = null;
export let showSidebarToggle = false;
export let sidebarVisible = true;
export let onToggleSidebar: (() => void) | null = null;
function handleHome(): void {
if (onHome) {
@@ -50,96 +23,45 @@
onToggleSidebar();
}
}
function handleToggleMobileMenu(): void {
if (onToggleMobileMenu) {
onToggleMobileMenu();
}
}
function handleToggleMobileRight(): void {
if (onToggleMobileRight) {
onToggleMobileRight();
}
}
</script>
<header
class="relative z-20 flex items-center justify-center px-4 md:px-6 pt-4 md:pt-8 pb-3 md:pb-4 bg-exo-dark-gray"
class="relative z-20 flex items-center justify-center px-6 pt-8 pb-4 bg-exo-dark-gray"
>
<!-- Left: Sidebar Toggle (desktop) or Mobile Sidebar Toggle (mobile) -->
<div
class="absolute left-4 md:left-6 top-1/2 -translate-y-1/2 flex items-center gap-2"
>
<!-- Mobile sidebar toggle -->
<button
onclick={handleToggleMobileMenu}
class="p-2 rounded border border-exo-light-gray/30 hover:border-exo-yellow/50 hover:bg-exo-medium-gray/30 transition-colors cursor-pointer md:hidden"
title={mobileMenuOpen ? "Hide sidebar" : "Show sidebar"}
aria-label={mobileMenuOpen
? "Hide conversation sidebar"
: "Show conversation sidebar"}
aria-pressed={mobileMenuOpen}
>
<svg
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
class="w-5 h-5 {mobileMenuOpen
? 'text-exo-yellow'
: 'text-exo-light-gray'}"
<!-- Left: Sidebar Toggle -->
{#if showSidebarToggle}
<div class="absolute left-6 top-1/2 -translate-y-1/2">
<button
onclick={handleToggleSidebar}
class="p-2 rounded border border-exo-medium-gray/40 hover:border-exo-yellow/50 transition-colors cursor-pointer"
title={sidebarVisible ? "Hide sidebar" : "Show sidebar"}
>
{#if mobileMenuOpen}
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M11 19l-7-7 7-7m8 14l-7-7 7-7"
></path>
{:else}
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M13 5l7 7-7 7M5 5l7 7-7 7"
></path>
{/if}
</svg>
</button>
<!-- Desktop sidebar toggle -->
<button
onclick={handleToggleSidebar}
class="p-2 rounded border border-exo-light-gray/30 hover:border-exo-yellow/50 hover:bg-exo-medium-gray/30 transition-colors cursor-pointer hidden md:block"
title={sidebarVisible ? "Hide sidebar" : "Show sidebar"}
aria-label={sidebarVisible
? "Hide conversation sidebar"
: "Show conversation sidebar"}
aria-pressed={sidebarVisible}
>
<svg
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
class="w-5 h-5 {sidebarVisible
? 'text-exo-yellow'
: 'text-exo-light-gray'}"
>
{#if sidebarVisible}
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M11 19l-7-7 7-7m8 14l-7-7 7-7"
></path>
{:else}
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M13 5l7 7-7 7M5 5l7 7-7 7"
></path>
{/if}
</svg>
</button>
</div>
<svg
class="w-5 h-5 {sidebarVisible
? 'text-exo-yellow'
: 'text-exo-medium-gray'}"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
>
{#if sidebarVisible}
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M11 19l-7-7 7-7m8 14l-7-7 7-7"
/>
{:else}
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M13 5l7 7-7 7M5 5l7 7-7 7"
/>
{/if}
</svg>
</button>
</div>
{/if}
<!-- Center: Logo (clickable to go home) -->
<button
@@ -153,55 +75,18 @@
<img
src="/exo-logo.png"
alt="EXO"
class="h-12 md:h-18 drop-shadow-[0_0_4px_rgba(255,215,0,0.3)]"
class="h-18 drop-shadow-[0_0_20px_rgba(255,215,0,0.5)]"
/>
</button>
<!-- Right: Home + Downloads + Mobile Right Toggle -->
<nav
class="absolute right-4 md:right-6 top-1/2 -translate-y-1/2 flex items-center gap-2 md:gap-4"
aria-label="Main navigation"
<!-- Right: Home + Downloads -->
<div
class="absolute right-6 top-1/2 -translate-y-1/2 flex items-center gap-4"
>
<!-- Mobile right sidebar toggle (instances/models) - only show when not in chat mode -->
{#if showMobileRightToggle}
<button
onclick={handleToggleMobileRight}
class="p-2 rounded border border-exo-light-gray/30 hover:border-exo-yellow/50 hover:bg-exo-medium-gray/30 transition-colors cursor-pointer md:hidden"
title={mobileRightOpen ? "Hide instances" : "Show instances"}
aria-label={mobileRightOpen
? "Hide instances panel"
: "Show instances panel"}
aria-pressed={mobileRightOpen}
>
<svg
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
class="w-5 h-5 {mobileRightOpen
? 'text-exo-yellow'
: 'text-exo-light-gray'}"
>
{#if mobileRightOpen}
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M13 5l7 7-7 7M5 5l7 7-7 7"
></path>
{:else}
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M11 19l-7-7 7-7m8 14l-7-7 7-7"
></path>
{/if}
</svg>
</button>
{/if}
{#if showHome}
<button
onclick={handleHome}
class="flex text-sm text-white/70 hover:text-exo-yellow transition-colors tracking-wider uppercase items-center gap-2 cursor-pointer"
class="text-sm text-exo-light-gray hover:text-exo-yellow transition-colors tracking-wider uppercase flex items-center gap-2 cursor-pointer"
title="Back to topology view"
>
<svg
@@ -217,69 +102,13 @@
d="M3 12l2-2m0 0l7-7 7 7M5 10v10a1 1 0 001 1h3m10-11l2 2m-2-2v10a1 1 0 01-1 1h-3m-6 0a1 1 0 001-1v-4a1 1 0 011-1h2a1 1 0 011 1v4a1 1 0 001 1m-6 0h6"
/>
</svg>
<span class="hidden sm:inline">Home</span>
Home
</button>
{/if}
<a
href="/#/downloads"
class="text-xs md:text-sm text-white/70 hover:text-exo-yellow transition-colors tracking-wider uppercase flex items-center gap-1.5 md:gap-2 cursor-pointer"
class="text-sm text-exo-light-gray hover:text-exo-yellow transition-colors tracking-wider uppercase flex items-center gap-2 cursor-pointer"
title="View downloads overview"
>
{#if downloadProgress}
<!-- Compact download progress indicator -->
<div class="relative w-4 h-4 flex-shrink-0">
<svg class="w-4 h-4 -rotate-90" viewBox="0 0 20 20">
<circle
cx="10"
cy="10"
r="8"
fill="none"
stroke="currentColor"
stroke-width="2"
opacity="0.2"
/>
<circle
cx="10"
cy="10"
r="8"
fill="none"
stroke="currentColor"
stroke-width="2"
stroke-dasharray={2 * Math.PI * 8}
stroke-dashoffset={2 *
Math.PI *
8 *
(1 - downloadProgress.percentage / 100)}
class="text-blue-400 transition-all duration-300"
/>
</svg>
<div
class="absolute inset-0 flex items-center justify-center text-[6px] font-mono text-blue-400"
>
{downloadProgress.count}
</div>
</div>
{:else}
<svg
class="w-4 h-4"
viewBox="0 0 24 24"
fill="none"
stroke="currentColor"
stroke-width="2"
stroke-linecap="round"
stroke-linejoin="round"
>
<path d="M12 3v12" />
<path d="M7 12l5 5 5-5" />
<path d="M5 21h14" />
</svg>
{/if}
<span class="hidden sm:inline">Downloads</span>
</a>
<a
href="/#/integrations"
class="text-xs md:text-sm text-white/70 hover:text-exo-yellow transition-colors tracking-wider uppercase flex items-center gap-1.5 md:gap-2 cursor-pointer"
title="Integration configs for external tools"
>
<svg
class="w-4 h-4"
@@ -290,12 +119,11 @@
stroke-linecap="round"
stroke-linejoin="round"
>
<path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71" />
<path
d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71"
/>
<path d="M12 3v12" />
<path d="M7 12l5 5 5-5" />
<path d="M5 21h14" />
</svg>
<span class="hidden sm:inline">Integrations</span>
Downloads
</a>
</nav>
</div>
</header>
@@ -26,8 +26,7 @@
downloadedOnNodes = [],
}: HuggingFaceResultItemProps = $props();
function formatNumber(num: number | undefined): string {
if (num == null) return "0";
function formatNumber(num: number): string {
if (num >= 1000000) {
return `${(num / 1000000).toFixed(1)}M`;
} else if (num >= 1000) {
@@ -36,12 +35,8 @@
return num.toString();
}
// Show short name for mlx-community models, full ID for everything else
const modelName = $derived(
model.author === "mlx-community"
? model.id.split("/").pop() || model.id
: model.id,
);
// Extract model name from full ID (e.g., "mlx-community/Llama-3.2-1B" -> "Llama-3.2-1B")
const modelName = $derived(model.id.split("/").pop() || model.id);
</script>
<div
@@ -1,52 +0,0 @@
<script lang="ts">
interface Props {
title: string;
subtitle: string;
config: string;
description?: string;
language?: "json" | "bash";
}
let {
title,
subtitle,
config,
description = "",
language = "json",
}: Props = $props();
let copied = $state(false);
async function copyToClipboard() {
await navigator.clipboard.writeText(config);
copied = true;
setTimeout(() => (copied = false), 2000);
}
</script>
<div
class="border border-exo-light-gray/20 rounded-lg bg-exo-medium-gray/20 overflow-hidden"
>
<div class="flex items-center justify-between px-5 py-4">
<div>
<h3 class="text-white text-sm font-semibold tracking-wide">{title}</h3>
<p class="text-exo-light-gray/60 text-xs mt-0.5 font-mono">{subtitle}</p>
</div>
<button
onclick={copyToClipboard}
class="px-3 py-1.5 text-xs rounded border transition-all duration-200 cursor-pointer
{copied
? 'border-green-500/50 text-green-400 bg-green-500/10'
: 'border-exo-light-gray/30 text-exo-light-gray hover:border-exo-yellow/50 hover:text-exo-yellow'}"
>
{copied ? "Copied!" : "Copy"}
</button>
</div>
{#if description}
<p class="text-exo-light-gray/70 text-xs px-5 pb-3">{description}</p>
{/if}
<div class="bg-black/30 border-t border-exo-light-gray/10">
<pre
class="text-xs text-exo-light-gray/90 font-mono p-4 overflow-x-auto whitespace-pre">{config}</pre>
</div>
</div>
@@ -507,29 +507,9 @@
});
$effect(() => {
if (!containerRef || !browser) return;
function handleDelegatedClick(event: MouseEvent) {
const codeBtn = (event.target as HTMLElement).closest(
".copy-code-btn",
) as HTMLButtonElement | null;
if (codeBtn) {
handleCopyClick({ currentTarget: codeBtn } as unknown as Event);
return;
}
const mathBtn = (event.target as HTMLElement).closest(
".copy-math-btn",
) as HTMLButtonElement | null;
if (mathBtn) {
handleMathCopyClick({ currentTarget: mathBtn } as unknown as Event);
return;
}
if (containerRef && processedHtml) {
setupCopyButtons();
}
containerRef.addEventListener("click", handleDelegatedClick);
return () => {
containerRef?.removeEventListener("click", handleDelegatedClick);
};
});
</script>
+18 -66
View File
@@ -16,14 +16,12 @@
perNode?: Array<{
nodeId: string;
nodeName: string;
status: "completed" | "partial" | "pending" | "downloading";
percentage: number;
progress: DownloadProgress | null;
progress: DownloadProgress;
}>;
} | null;
nodes?: Record<string, NodeInfo>;
sharding?: "Pipeline" | "Tensor";
runtime?: "MlxRing" | "MlxJaccl";
runtime?: "MlxRing" | "MlxIbv" | "MlxJaccl";
onLaunch?: () => void;
tags?: string[];
apiPreview?: PlacementPreview | null;
@@ -147,7 +145,10 @@
return `${s}s`;
}
const perNode = $derived(downloadStatus?.perNode ?? []);
const isDownloading = $derived(downloadStatus?.isDownloading ?? false);
const progress = $derived(downloadStatus?.progress);
const percentage = $derived(progress?.percentage ?? 0);
let expandedNodes = $state<Set<string>>(new Set());
function toggleNodeDetails(nodeId: string): void {
const next = new Set(expandedNodes);
@@ -347,7 +348,7 @@
// Debug mode state
const isDebugMode = $derived(debugMode());
const topology = $derived(topologyData());
const isRdma = $derived(runtime === "MlxJaccl");
const isRdma = $derived(runtime === "MlxIbv" || runtime === "MlxJaccl");
// Get interface name for an IP from node data
function getInterfaceForIp(nodeId: string, ip?: string): string | null {
@@ -566,72 +567,20 @@
<div class="flex items-center gap-1.5 mb-2">
<span
class="px-1.5 py-0.5 text-xs font-mono tracking-wider uppercase bg-exo-medium-gray/30 text-exo-light-gray border border-exo-medium-gray/40"
title={sharding === "Pipeline"
? "Pipeline: splits model into sequential stages across devices. Lower network overhead."
: "Tensor: splits each layer across devices. Best with high-bandwidth connections (Thunderbolt)."}
>
{sharding}
</span>
<span
class="px-1.5 py-0.5 text-xs font-mono tracking-wider uppercase bg-exo-medium-gray/30 text-exo-light-gray border border-exo-medium-gray/40"
title={runtime === "MlxRing"
? "Ring: standard networking. Works over any connection (Wi-Fi, Ethernet, Thunderbolt)."
: "RDMA: direct memory access over Thunderbolt. Significantly faster for multi-device inference."}
>
{runtime === "MlxRing"
? "MLX Ring"
: runtime === "MlxJaccl"
: runtime === "MlxIbv" || runtime === "MlxJaccl"
? "MLX RDMA"
: runtime}
</span>
</div>
<!-- Download Status (per-node) -->
{#if perNode.length > 0}
<div class="mb-2 space-y-1">
<div
class="text-[10px] font-mono text-white/20 tracking-widest uppercase"
>
Download progress
</div>
{#each perNode as node}
<div class="flex items-center gap-2 text-xs font-mono">
<span class="text-white/40 w-20 truncate" title={node.nodeId}
>{node.nodeName}</span
>
<div
class="flex-1 h-1 bg-exo-medium-gray/30 rounded overflow-hidden"
>
<div
class="h-full transition-all duration-300 {node.status ===
'downloading'
? 'bg-blue-500/70'
: node.status === 'completed'
? 'bg-exo-yellow/40'
: 'bg-white/20'}"
style="width: {node.percentage}%"
></div>
</div>
<span
class="text-right {node.status === 'completed'
? 'text-exo-yellow/60'
: node.status === 'downloading'
? 'text-blue-400/60'
: 'text-white/30'}"
>
{#if node.status === "downloading" && node.progress}
{Math.round(node.percentage)}% {formatSpeed(
node.progress.speed,
)}
{:else}
{node.percentage > 0 ? `${Math.round(node.percentage)}%` : "0%"}
{/if}
</span>
</div>
{/each}
</div>
{/if}
<!-- Mini Topology Preview -->
{#if placementPreview().nodes.length > 0}
{@const preview = placementPreview()}
@@ -687,7 +636,15 @@
{@const allConnections =
isDebugMode && usedNodes.length > 1
? (() => {
const conns: Array = [];
const conns: Array<{
ip: string;
iface: string | null;
from: string;
to: string;
midX: number;
midY: number;
arrow: string;
}> = [];
for (let i = 0; i < usedNodes.length; i++) {
for (let j = i + 1; j < usedNodes.length; j++) {
const n1 = usedNodes[i];
@@ -699,12 +656,7 @@
const toPos = nodePositions[c.to];
const arrow =
fromPos && toPos ? getArrow(fromPos, toPos) : "→";
conns.push({
...c,
midX,
midY,
arrow,
});
conns.push({ ...c, midX, midY, arrow });
}
}
}
@@ -6,7 +6,6 @@
capabilities: string[];
sizeRange: { min: number; max: number } | null;
downloadedOnly: boolean;
readyOnly: boolean;
}
type ModelFilterPopoverProps = {
@@ -73,7 +72,7 @@
<!-- svelte-ignore a11y_no_static_element_interactions -->
<div
class="filter-popover absolute right-0 top-full mt-2 w-64 bg-exo-dark-gray border border-exo-yellow/10 rounded-lg shadow-xl z-20"
class="filter-popover absolute right-0 top-full mt-2 w-64 bg-exo-dark-gray border border-exo-yellow/10 rounded-lg shadow-xl z-10"
transition:fly={{ y: -10, duration: 200, easing: cubicOut }}
onclick={(e) => e.stopPropagation()}
role="dialog"
@@ -191,58 +190,34 @@
</div>
</div>
<!-- Availability filters -->
<!-- Downloaded only -->
<div>
<h4 class="text-xs font-mono text-white/50 mb-2">Availability</h4>
<div class="flex flex-wrap gap-1.5">
<button
type="button"
class="px-2 py-1 text-xs font-mono rounded transition-colors {filters.downloadedOnly
? 'bg-green-500/20 text-green-400 border border-green-500/30'
: 'bg-white/5 text-white/60 hover:bg-white/10 border border-transparent'}"
onclick={() =>
onChange({ ...filters, downloadedOnly: !filters.downloadedOnly })}
<button
type="button"
class="px-2 py-1 text-xs font-mono rounded transition-colors {filters.downloadedOnly
? 'bg-green-500/20 text-green-400 border border-green-500/30'
: 'bg-white/5 text-white/60 hover:bg-white/10 border border-transparent'}"
onclick={() =>
onChange({ ...filters, downloadedOnly: !filters.downloadedOnly })}
>
<svg
class="w-3.5 h-3.5 inline-block"
viewBox="0 0 24 24"
fill="none"
stroke="currentColor"
stroke-width="2"
stroke-linecap="round"
stroke-linejoin="round"
>
<svg
class="w-3.5 h-3.5 inline-block"
viewBox="0 0 24 24"
fill="none"
stroke="currentColor"
stroke-width="2"
stroke-linecap="round"
stroke-linejoin="round"
>
<path
class="text-white/40"
d="M20 20a2 2 0 0 0 2-2V8a2 2 0 0 0-2-2h-7.9a2 2 0 0 1-1.69-.9L9.6 3.9A2 2 0 0 0 7.93 3H4a2 2 0 0 0-2 2v13a2 2 0 0 0 2 2Z"
/>
<path class="text-green-400" d="m9 13 2 2 4-4" />
</svg>
<span class="ml-1">Downloaded</span>
</button>
<button
type="button"
class="px-2 py-1 text-xs font-mono rounded transition-colors {filters.readyOnly
? 'bg-green-500/20 text-green-400 border border-green-500/30'
: 'bg-white/5 text-white/60 hover:bg-white/10 border border-transparent'}"
onclick={() =>
onChange({ ...filters, readyOnly: !filters.readyOnly })}
>
<svg
class="w-3.5 h-3.5 inline-block"
viewBox="0 0 24 24"
fill="none"
stroke="currentColor"
stroke-width="2"
stroke-linecap="round"
stroke-linejoin="round"
>
<circle cx="12" cy="12" r="10" />
<path d="m9 12 2 2 4-4" />
</svg>
<span class="ml-1">Ready</span>
</button>
</div>
<path
class="text-white/40"
d="M20 20a2 2 0 0 0 2-2V8a2 2 0 0 0-2-2h-7.9a2 2 0 0 1-1.69-.9L9.6 3.9A2 2 0 0 0 7.93 3H4a2 2 0 0 0-2 2v13a2 2 0 0 0 2 2Z"
/>
<path class="text-green-400" d="m9 13 2 2 4-4" />
</svg>
<span class="ml-1">Downloaded</span>
</button>
</div>
<!-- Size range -->
@@ -32,7 +32,6 @@
group: ModelGroup;
isExpanded: boolean;
isFavorite: boolean;
isHighlighted?: boolean;
selectedModelId: string | null;
canModelFit: (id: string) => boolean;
getModelFitStatus: (id: string) => ModelFitStatus;
@@ -42,14 +41,12 @@
onShowInfo: (group: ModelGroup) => void;
downloadStatusMap?: Map<string, DownloadAvailability>;
launchedAt?: number;
instanceStatuses?: Record<string, { status: string; statusClass: string }>;
};
let {
group,
isExpanded,
isFavorite,
isHighlighted = false,
selectedModelId,
canModelFit,
getModelFitStatus,
@@ -59,7 +56,6 @@
onShowInfo,
downloadStatusMap,
launchedAt,
instanceStatuses = {},
}: ModelPickerGroupProps = $props();
// Group-level download status: show if any variant is downloaded
@@ -96,12 +92,6 @@
const anyVariantFits = $derived(
group.variants.some((v) => canModelFit(v.id)),
);
// Check if any variant has an active instance (ready, loading, downloading)
const anyVariantHasInstance = $derived(
instanceStatuses
? group.variants.some((v) => instanceStatuses[v.id] != null)
: false,
);
const groupFitStatus = $derived.by((): ModelFitStatus => {
let hasClusterCapacityOnly = false;
for (const variant of group.variants) {
@@ -132,36 +122,16 @@
!group.hasMultipleVariants &&
group.variants.some((v) => v.id === selectedModelId),
);
// Group-level instance status: show the "best" status across all variants
const groupInstanceStatus = $derived.by(() => {
if (!instanceStatuses) return null;
const readyStatuses = ["READY", "LOADED", "RUNNING"];
const loadingStatuses = ["LOADING", "WARMING UP"];
let bestStatus: { status: string; statusClass: string } | null = null;
for (const variant of group.variants) {
const s = instanceStatuses[variant.id];
if (!s) continue;
if (readyStatuses.includes(s.status)) return s; // Ready is best
if (loadingStatuses.includes(s.status) || s.status === "DOWNLOADING") {
bestStatus = s;
}
}
return bestStatus;
});
</script>
<div
data-model-ids={group.variants.map((v) => v.id).join(" ")}
class="border-b border-white/5 last:border-b-0 {!anyVariantFits &&
!anyVariantHasInstance
class="border-b border-white/5 last:border-b-0 {!anyVariantFits
? 'opacity-50'
: ''} {isHighlighted ? 'model-just-added' : ''}"
: ''}"
>
<!-- Main row -->
<div
class="flex items-center gap-2 px-3 py-2.5 transition-colors {anyVariantFits ||
anyVariantHasInstance
class="flex items-center gap-2 px-3 py-2.5 transition-colors {anyVariantFits
? 'hover:bg-white/5 cursor-pointer'
: 'cursor-not-allowed'} {isMainSelected
? 'bg-exo-yellow/10 border-l-2 border-exo-yellow'
@@ -171,7 +141,7 @@
onToggleExpand();
} else {
const modelId = group.variants[0]?.id;
if (modelId && (canModelFit(modelId) || instanceStatuses[modelId])) {
if (modelId && canModelFit(modelId)) {
onSelectModel(modelId);
}
}
@@ -185,7 +155,7 @@
onToggleExpand();
} else {
const modelId = group.variants[0]?.id;
if (modelId && (canModelFit(modelId) || instanceStatuses[modelId])) {
if (modelId && canModelFit(modelId)) {
onSelectModel(modelId);
}
}
@@ -376,47 +346,6 @@
</span>
{/if}
<!-- Instance status badge -->
{#if groupInstanceStatus}
{#if groupInstanceStatus.status === "READY" || groupInstanceStatus.status === "LOADED" || groupInstanceStatus.status === "RUNNING"}
<span class="flex-shrink-0" title="Running">
<svg
class="w-3 h-3 text-green-400"
viewBox="0 0 12 12"
fill="currentColor"
>
<circle cx="6" cy="6" r="5" />
</svg>
</span>
{:else if groupInstanceStatus.status === "DOWNLOADING"}
<span class="flex-shrink-0 animate-pulse" title="Downloading">
<svg
class="w-3.5 h-3.5 text-blue-400"
viewBox="0 0 24 24"
fill="none"
stroke="currentColor"
stroke-width="2"
stroke-linecap="round"
stroke-linejoin="round"
>
<path d="M21 15v4a2 2 0 01-2 2H5a2 2 0 01-2-2v-4" />
<polyline points="7 10 12 15 17 10" />
<line x1="12" y1="15" x2="12" y2="3" />
</svg>
</span>
{:else if groupInstanceStatus.status === "LOADING" || groupInstanceStatus.status === "WARMING UP"}
<span class="flex-shrink-0 animate-pulse" title="Loading">
<svg
class="w-3 h-3 text-yellow-400"
viewBox="0 0 12 12"
fill="currentColor"
>
<circle cx="6" cy="6" r="5" />
</svg>
</span>
{/if}
{/if}
<!-- Check mark if selected (single-variant) -->
{#if isMainSelected}
<svg
@@ -491,30 +420,20 @@
{#each group.variants as variant}
{@const fitStatus = getModelFitStatus(variant.id)}
{@const modelCanFit = canModelFit(variant.id)}
{@const variantHasInstance = instanceStatuses[variant.id] != null}
{@const isSelected = selectedModelId === variant.id}
<div
class="w-full flex items-center gap-3 px-3 py-2 pl-10 hover:bg-white/5 transition-colors text-left {!modelCanFit &&
!variantHasInstance
<button
type="button"
class="w-full flex items-center gap-3 px-3 py-2 pl-10 hover:bg-white/5 transition-colors text-left {!modelCanFit
? 'opacity-50 cursor-not-allowed'
: 'cursor-pointer'} {isSelected
? 'bg-exo-yellow/10 border-l-2 border-exo-yellow'
: 'border-l-2 border-transparent'}"
role="button"
tabindex="0"
disabled={!modelCanFit}
onclick={() => {
if (modelCanFit || variantHasInstance) {
if (modelCanFit) {
onSelectModel(variant.id);
}
}}
onkeydown={(e) => {
if (e.key === "Enter" || e.key === " ") {
e.preventDefault();
if (modelCanFit) {
onSelectModel(variant.id);
}
}
}}
>
<!-- Quantization badge -->
<span
@@ -559,48 +478,6 @@
{/if}
{/if}
<!-- Instance status badge -->
{#if instanceStatuses[variant.id]}
{@const instStatus = instanceStatuses[variant.id]}
{#if instStatus.status === "READY" || instStatus.status === "LOADED" || instStatus.status === "RUNNING"}
<span class="flex-shrink-0" title="Running">
<svg
class="w-3 h-3 text-green-400"
viewBox="0 0 12 12"
fill="currentColor"
>
<circle cx="6" cy="6" r="5" />
</svg>
</span>
{:else if instStatus.status === "DOWNLOADING"}
<span class="flex-shrink-0 animate-pulse" title="Downloading">
<svg
class="w-3.5 h-3.5 text-blue-400"
viewBox="0 0 24 24"
fill="none"
stroke="currentColor"
stroke-width="2"
stroke-linecap="round"
stroke-linejoin="round"
>
<path d="M21 15v4a2 2 0 01-2 2H5a2 2 0 01-2-2v-4" />
<polyline points="7 10 12 15 17 10" />
<line x1="12" y1="15" x2="12" y2="3" />
</svg>
</span>
{:else if instStatus.status === "LOADING" || instStatus.status === "WARMING UP"}
<span class="flex-shrink-0 animate-pulse" title="Loading">
<svg
class="w-3 h-3 text-yellow-400"
viewBox="0 0 12 12"
fill="currentColor"
>
<circle cx="6" cy="6" r="5" />
</svg>
</span>
{/if}
{/if}
<!-- Check mark if selected -->
{#if isSelected}
<svg
@@ -613,55 +490,8 @@
/>
</svg>
{/if}
<!-- Info button -->
<button
type="button"
class="p-1 rounded hover:bg-white/10 transition-colors flex-shrink-0"
onclick={(e) => {
e.stopPropagation();
onShowInfo({
id: variant.id,
name: variant.name || variant.id,
capabilities: group.capabilities,
family: group.family,
variants: [variant],
smallestVariant: variant,
hasMultipleVariants: false,
});
}}
title="View variant details"
>
<svg
class="w-4 h-4 text-white/30 hover:text-white/50"
viewBox="0 0 24 24"
fill="currentColor"
>
<path
d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm1 15h-2v-6h2v6zm0-8h-2V7h2v2z"
/>
</svg>
</button>
</div>
</button>
{/each}
</div>
{/if}
</div>
<style>
.model-just-added {
animation: highlightFade 4s ease-out forwards;
}
@keyframes highlightFade {
0%,
40% {
background-color: rgba(20, 83, 45, 0.25);
box-shadow: inset 0 0 0 1px rgba(74, 222, 128, 0.4);
}
100% {
background-color: transparent;
box-shadow: none;
}
}
</style>
@@ -1,5 +1,4 @@
<script lang="ts">
import { tick } from "svelte";
import { fade, fly } from "svelte/transition";
import { cubicOut } from "svelte/easing";
import FamilySidebar from "./FamilySidebar.svelte";
@@ -8,7 +7,6 @@
import HuggingFaceResultItem from "./HuggingFaceResultItem.svelte";
import { getNodesWithModelDownloaded } from "$lib/utils/downloads";
import { getRecentEntries } from "$lib/stores/recents.svelte";
import { addToast } from "$lib/stores/toast.svelte";
interface ModelInfo {
id: string;
@@ -38,7 +36,6 @@
capabilities: string[];
sizeRange: { min: number; max: number } | null;
downloadedOnly: boolean;
readyOnly: boolean;
}
interface HuggingFaceModel {
@@ -52,11 +49,6 @@
type ModelFitStatus = "fits_now" | "fits_cluster_capacity" | "too_large";
export type InstanceStatus = {
status: string;
statusClass: string;
};
type ModelPickerModalProps = {
isOpen: boolean;
models: ModelInfo[];
@@ -83,7 +75,6 @@
macmon_info?: { memory?: { ram_total?: number } };
}
>;
instanceStatuses?: Record<string, InstanceStatus>;
};
let {
@@ -105,7 +96,6 @@
usedMemoryGB,
downloadsData,
topologyNodes,
instanceStatuses = {},
}: ModelPickerModalProps = $props();
// Local state
@@ -117,7 +107,6 @@
capabilities: [],
sizeRange: null,
downloadedOnly: false,
readyOnly: false,
});
let infoGroup = $state<ModelGroup | null>(null);
@@ -193,13 +182,6 @@
let hfSearchDebounceTimer: ReturnType<typeof setTimeout> | null = null;
let manualModelId = $state("");
let addModelError = $state<string | null>(null);
let justAddedModelId = $state<string | null>(null);
let justAddedTimer: ReturnType<typeof setTimeout> | null = null;
// Inline HuggingFace search in main search bar
let mainSearchHfResults = $state<HuggingFaceModel[]>([]);
let mainSearchHfLoading = $state(false);
let mainSearchDebounceTimer: ReturnType<typeof setTimeout> | null = null;
// Reset transient state when modal opens, but preserve tab selection
$effect(() => {
@@ -209,11 +191,6 @@
showFilters = false;
manualModelId = "";
addModelError = null;
justAddedModelId = null;
if (justAddedTimer) {
clearTimeout(justAddedTimer);
justAddedTimer = null;
}
}
});
@@ -228,50 +205,6 @@
}
});
// Inline HuggingFace search when local search returns no results
$effect(() => {
const query = searchQuery.trim();
const noLocalResults = filteredGroups.length === 0;
if (mainSearchDebounceTimer) {
clearTimeout(mainSearchDebounceTimer);
mainSearchDebounceTimer = null;
}
if (
selectedFamily === "huggingface" ||
selectedFamily === "recents" ||
selectedFamily === "favorites" ||
query.length < 2 ||
!noLocalResults
) {
mainSearchHfResults = [];
mainSearchHfLoading = false;
return;
}
mainSearchHfLoading = true;
mainSearchDebounceTimer = setTimeout(async () => {
try {
const response = await fetch(
`/models/search?query=${encodeURIComponent(query)}&limit=10`,
);
if (response.ok) {
const results: HuggingFaceModel[] = await response.json();
mainSearchHfResults = results.filter(
(r) => !existingModelIds.has(r.id),
);
} else {
mainSearchHfResults = [];
}
} catch {
mainSearchHfResults = [];
} finally {
mainSearchHfLoading = false;
}
}, 500);
});
async function fetchTrendingModels() {
hfIsLoadingTrending = true;
try {
@@ -332,24 +265,6 @@
addModelError = null;
try {
await onAddModel(modelId);
// Success: show toast, switch to All Models, highlight the model
const shortName = modelId.split("/").pop() || modelId;
addToast({ type: "success", message: `Added ${shortName}` });
justAddedModelId = modelId;
selectedFamily = null;
searchQuery = "";
// Scroll to the newly added model after DOM update
await tick();
const el = document.querySelector(
`[data-model-ids~="${CSS.escape(modelId)}"]`,
);
el?.scrollIntoView({ behavior: "smooth", block: "center" });
// Clear highlight after 4 seconds
if (justAddedTimer) clearTimeout(justAddedTimer);
justAddedTimer = setTimeout(() => {
justAddedModelId = null;
justAddedTimer = null;
}, 4000);
} catch (error) {
addModelError =
error instanceof Error ? error.message : "Failed to add model";
@@ -459,7 +374,6 @@
"llama",
"flux",
"qwen-image",
"nemotron",
];
return Array.from(families).sort((a, b) => {
const aIdx = familyOrder.indexOf(a);
@@ -526,16 +440,6 @@
);
}
// Filter to ready/running models only
if (filters.readyOnly) {
result = result.filter((g) =>
g.variants.some((v) => {
const s = instanceStatuses[v.id];
return s && s.statusClass === "ready";
}),
);
}
// Sort: fits-now first, then fits-cluster-capacity, then too-large
result.sort((a, b) => {
const getGroupFitRank = (group: ModelGroup): number => {
@@ -608,18 +512,6 @@
);
});
// Split filtered groups into recommended (fits_now) and others for visual separation
const recommendedGroups = $derived(
filteredGroups.filter((g) =>
g.variants.some((v) => getModelFitStatus(v.id) === "fits_now"),
),
);
const otherGroups = $derived(
filteredGroups.filter(
(g) => !g.variants.some((v) => getModelFitStatus(v.id) === "fits_now"),
),
);
function toggleGroupExpanded(groupId: string) {
const next = new Set(expandedGroups);
if (next.has(groupId)) {
@@ -646,19 +538,13 @@
}
function clearFilters() {
filters = {
capabilities: [],
sizeRange: null,
downloadedOnly: false,
readyOnly: false,
};
filters = { capabilities: [], sizeRange: null, downloadedOnly: false };
}
const hasActiveFilters = $derived(
filters.capabilities.length > 0 ||
filters.sizeRange !== null ||
filters.downloadedOnly ||
filters.readyOnly,
filters.downloadedOnly,
);
</script>
@@ -918,8 +804,6 @@
{group}
isExpanded={expandedGroups.has(group.id)}
isFavorite={favorites.has(group.id)}
isHighlighted={justAddedModelId !== null &&
group.variants.some((v) => v.id === justAddedModelId)}
{selectedModelId}
{canModelFit}
{getModelFitStatus}
@@ -929,7 +813,6 @@
onShowInfo={(g) => (infoGroup = g)}
downloadStatusMap={getVariantDownloadMap(group)}
launchedAt={recentTimestamps.get(group.variants[0]?.id ?? "")}
{instanceStatuses}
/>
{/each}
{/if}
@@ -957,40 +840,11 @@
{/if}
</div>
{:else}
<!-- Recommended for your cluster -->
{#if recommendedGroups.length > 0 && otherGroups.length > 0 && !searchQuery.trim()}
<div
class="sticky top-0 z-10 flex items-center gap-2 px-3 py-2 bg-green-950/60 border-b border-green-500/20 backdrop-blur-sm"
>
<svg
class="w-3.5 h-3.5 text-green-400 flex-shrink-0"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
stroke-width="2"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M9 12.75L11.25 15 15 9.75M21 12a9 9 0 11-18 0 9 9 0 0118 0z"
/>
</svg>
<span
class="text-xs font-mono text-green-400 tracking-wider uppercase"
>Recommended for your cluster</span
>
<span class="text-xs font-mono text-green-400/50"
>— fits in available memory</span
>
</div>
{/if}
{#each recommendedGroups as group}
{#each filteredGroups as group}
<ModelPickerGroup
{group}
isExpanded={expandedGroups.has(group.id)}
isFavorite={favorites.has(group.id)}
isHighlighted={justAddedModelId !== null &&
group.variants.some((v) => v.id === justAddedModelId)}
{selectedModelId}
{canModelFit}
{getModelFitStatus}
@@ -999,87 +853,8 @@
{onToggleFavorite}
onShowInfo={(g) => (infoGroup = g)}
downloadStatusMap={getVariantDownloadMap(group)}
{instanceStatuses}
/>
{/each}
<!-- Other models -->
{#if otherGroups.length > 0 && recommendedGroups.length > 0 && !searchQuery.trim()}
<div
class="sticky top-0 z-10 flex items-center gap-2 px-3 py-2 bg-exo-dark-gray/80 border-y border-exo-medium-gray/20 backdrop-blur-sm"
>
<span
class="text-xs font-mono text-white/40 tracking-wider uppercase"
>Other models</span
>
</div>
{/if}
{#each otherGroups as group}
<ModelPickerGroup
{group}
isExpanded={expandedGroups.has(group.id)}
isFavorite={favorites.has(group.id)}
isHighlighted={justAddedModelId !== null &&
group.variants.some((v) => v.id === justAddedModelId)}
{selectedModelId}
{canModelFit}
{getModelFitStatus}
onToggleExpand={() => toggleGroupExpanded(group.id)}
onSelectModel={handleSelect}
{onToggleFavorite}
onShowInfo={(g) => (infoGroup = g)}
downloadStatusMap={getVariantDownloadMap(group)}
{instanceStatuses}
/>
{/each}
<!-- Inline HuggingFace search results (shown when no local results match) -->
{#if filteredGroups.length === 0 && searchQuery.trim().length >= 2 && selectedFamily !== "huggingface" && selectedFamily !== "recents" && selectedFamily !== "favorites"}
{#if mainSearchHfLoading}
<div
class="flex items-center gap-2 px-3 py-2 border-t border-orange-400/20 bg-orange-950/20"
>
<span
class="w-4 h-4 border-2 border-orange-400 border-t-transparent rounded-full animate-spin"
></span>
<span class="text-xs font-mono text-orange-400/60"
>Searching HuggingFace...</span
>
</div>
{:else if mainSearchHfResults.length > 0}
<div
class="sticky top-0 z-10 flex items-center gap-2 px-3 py-2 bg-orange-950/30 border-y border-orange-400/20 backdrop-blur-sm"
>
<span
class="text-xs font-mono text-orange-400 tracking-wider uppercase"
>From HuggingFace</span
>
</div>
{#each mainSearchHfResults as model}
<HuggingFaceResultItem
{model}
isAdded={existingModelIds.has(model.id)}
isAdding={addingModelId === model.id}
onAdd={() => handleAddModel(model.id)}
onSelect={() => handleSelectHfModel(model.id)}
downloadedOnNodes={downloadsData
? getNodesWithModelDownloaded(downloadsData, model.id).map(
getNodeName,
)
: []}
/>
{/each}
<button
type="button"
class="w-full px-3 py-2 text-xs font-mono text-orange-400/60 hover:text-orange-400 hover:bg-orange-500/10 transition-colors text-center"
onclick={() => {
hfSearchQuery = searchQuery;
searchHuggingFace(searchQuery);
selectedFamily = "huggingface";
}}
>
See all results on Hub
</button>
{/if}
{/if}
{/if}
</div>
</div>
@@ -1100,11 +875,6 @@
>Downloaded</span
>
{/if}
{#if filters.readyOnly}
<span class="px-1.5 py-0.5 bg-green-500/20 text-green-400 rounded"
>Ready</span
>
{/if}
{#if filters.sizeRange}
<span class="px-1.5 py-0.5 bg-exo-yellow/20 text-exo-yellow rounded">
{filters.sizeRange.min}GB - {filters.sizeRange.max}GB
@@ -1,70 +0,0 @@
<script lang="ts">
import type { PrefillProgress } from "$lib/stores/app.svelte";
interface Props {
progress: PrefillProgress;
class?: string;
}
let { progress, class: className = "" }: Props = $props();
const percentage = $derived(
progress.total > 0
? Math.round((progress.processed / progress.total) * 100)
: 0,
);
const etaText = $derived.by(() => {
if (progress.processed <= 0 || progress.total <= 0) return null;
const elapsedMs = performance.now() - progress.startedAt;
if (elapsedMs < 200) return null; // need a minimum sample window
const tokensPerMs = progress.processed / elapsedMs;
const remainingTokens = progress.total - progress.processed;
const remainingMs = remainingTokens / tokensPerMs;
const remainingSec = Math.ceil(remainingMs / 1000);
if (remainingSec <= 0) return null;
if (remainingSec < 60) return `~${remainingSec}s remaining`;
const mins = Math.floor(remainingSec / 60);
const secs = remainingSec % 60;
return `~${mins}m ${secs}s remaining`;
});
function formatTokenCount(count: number | undefined): string {
if (count == null) return "0";
if (count >= 1000) {
return `${(count / 1000).toFixed(1)}k`;
}
return count.toString();
}
</script>
<div class="prefill-progress {className}">
<div
class="flex items-center justify-between text-xs text-exo-light-gray mb-1"
>
<span>Processing prompt</span>
<span class="font-mono">
{formatTokenCount(progress.processed)} / {formatTokenCount(
progress.total,
)} tokens
</span>
</div>
<div class="h-1.5 bg-exo-black/60 rounded-full overflow-hidden">
<div
class="h-full bg-exo-yellow rounded-full transition-all duration-150 ease-out"
style="width: {percentage}%"
></div>
</div>
<div
class="flex items-center justify-between text-xs text-exo-light-gray/70 mt-0.5 font-mono"
>
<span>{etaText ?? ""}</span>
<span>{percentage}%</span>
</div>
</div>
<style>
.prefill-progress {
width: 100%;
}
</style>
@@ -1,117 +0,0 @@
<script lang="ts">
import { toasts, dismissToast, type Toast } from "$lib/stores/toast.svelte";
import { fly, fade } from "svelte/transition";
import { flip } from "svelte/animate";
const items = $derived(toasts());
const typeStyles: Record<
Toast["type"],
{ border: string; icon: string; iconColor: string }
> = {
success: {
border: "border-l-green-500",
icon: "M9 12.75L11.25 15 15 9.75M21 12a9 9 0 11-18 0 9 9 0 0118 0z",
iconColor: "text-green-400",
},
error: {
border: "border-l-red-500",
icon: "M12 9v3.75m9-.75a9 9 0 11-18 0 9 9 0 0118 0zm-9 3.75h.008v.008H12v-.008z",
iconColor: "text-red-400",
},
warning: {
border: "border-l-yellow-500",
icon: "M12 9v3.75m-9.303 3.376c-.866 1.5.217 3.374 1.948 3.374h14.71c1.73 0 2.813-1.874 1.948-3.374L13.949 3.378c-.866-1.5-3.032-1.5-3.898 0L2.697 16.126z",
iconColor: "text-yellow-400",
},
info: {
border: "border-l-blue-500",
icon: "M11.25 11.25l.041-.02a.75.75 0 011.063.852l-.708 2.836a.75.75 0 001.063.853l.041-.021M21 12a9 9 0 11-18 0 9 9 0 0118 0zm-9-3.75h.008v.008H12V8.25z",
iconColor: "text-blue-400",
},
};
</script>
{#if items.length > 0}
<div
class="fixed bottom-6 right-6 z-[9999] flex flex-col gap-2 pointer-events-none"
role="log"
aria-live="polite"
aria-label="Notifications"
>
{#each items as toast (toast.id)}
{@const style = typeStyles[toast.type]}
<div
class="pointer-events-auto max-w-sm w-80 bg-exo-dark-gray/95 backdrop-blur-sm border border-exo-medium-gray/60 border-l-[3px] {style.border} rounded shadow-lg shadow-black/40"
in:fly={{ x: 80, duration: 250 }}
out:fade={{ duration: 150 }}
animate:flip={{ duration: 200 }}
role="alert"
>
<div class="flex items-start gap-3 px-4 py-3">
<!-- Icon -->
<svg
class="w-5 h-5 flex-shrink-0 mt-0.5 {style.iconColor}"
fill="none"
viewBox="0 0 24 24"
stroke-width="1.5"
stroke="currentColor"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
d={style.icon}
/>
</svg>
<!-- Message -->
<p class="flex-1 text-sm text-white/90 font-mono leading-snug">
{toast.message}
</p>
<!-- Dismiss button -->
<button
onclick={() => dismissToast(toast.id)}
class="flex-shrink-0 p-0.5 text-white/40 hover:text-white/80 transition-colors cursor-pointer"
aria-label="Dismiss notification"
>
<svg
class="w-4 h-4"
fill="none"
viewBox="0 0 24 24"
stroke-width="2"
stroke="currentColor"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
d="M6 18L18 6M6 6l12 12"
/>
</svg>
</button>
</div>
<!-- Auto-dismiss progress bar -->
{#if toast.duration > 0}
<div class="h-0.5 bg-white/5 rounded-b overflow-hidden">
<div
class="h-full {style.border.replace('border-l-', 'bg-')}/60"
style="animation: shrink {toast.duration}ms linear forwards"
></div>
</div>
{/if}
</div>
{/each}
</div>
{/if}
<style>
@keyframes shrink {
from {
width: 100%;
}
to {
width: 0%;
}
}
</style>
-2
View File
@@ -12,5 +12,3 @@ export { default as HuggingFaceResultItem } from "./HuggingFaceResultItem.svelte
export { default as ModelFilterPopover } from "./ModelFilterPopover.svelte";
export { default as ModelPickerGroup } from "./ModelPickerGroup.svelte";
export { default as ModelPickerModal } from "./ModelPickerModal.svelte";
export { default as ChatModelSelector } from "./ChatModelSelector.svelte";
export { default as IntegrationCard } from "./IntegrationCard.svelte";
+61 -388
View File
@@ -168,7 +168,7 @@ export interface ModelDownloadStatus {
export interface PlacementPreview {
model_id: string;
sharding: "Pipeline" | "Tensor";
instance_meta: "MlxRing" | "MlxJaccl";
instance_meta: "MlxRing" | "MlxIbv" | "MlxJaccl";
instance: unknown | null;
memory_delta_by_node: Record<string, number> | null;
error: string | null;
@@ -219,6 +219,7 @@ interface RawStateResponse {
string,
{
MlxRingInstance?: Instance;
MlxIbvInstance?: Instance;
MlxJacclInstance?: Instance;
}
>;
@@ -249,20 +250,14 @@ interface RawStateResponse {
>;
// Thunderbolt bridge cycles (nodes with bridge enabled forming loops)
thunderboltBridgeCycles?: string[][];
// Disk usage per node
nodeDisk?: Record<
string,
{ total: { inBytes: number }; available: { inBytes: number } }
>;
}
export interface MessageAttachment {
type: "image" | "text" | "file" | "generated-image" | "pdf";
type: "image" | "text" | "file" | "generated-image";
name: string;
content?: string;
preview?: string;
mimeType?: string;
pageImages?: string[];
}
export interface TopLogprob {
@@ -278,13 +273,6 @@ export interface TokenData {
topLogprobs: TopLogprob[];
}
export interface PrefillProgress {
processed: number;
total: number;
/** Timestamp (performance.now()) when prefill started. */
startedAt: number;
}
export interface Message {
id: string;
role: "user" | "assistant" | "system";
@@ -532,10 +520,6 @@ class AppStore {
ttftMs = $state<number | null>(null); // Time to first token in ms
tps = $state<number | null>(null); // Tokens per second
totalTokens = $state<number>(0); // Total tokens in current response
prefillProgress = $state<PrefillProgress | null>(null);
// Abort controller for stopping generation
private currentAbortController: AbortController | null = null;
// Topology state
topologyData = $state<TopologyData | null>(null);
@@ -581,8 +565,6 @@ class AppStore {
debugMode = $state(false);
topologyOnlyMode = $state(false);
chatSidebarVisible = $state(true); // Shown by default
mobileChatSidebarOpen = $state(false); // Mobile drawer state
mobileRightSidebarOpen = $state(false); // Mobile right drawer state
// Image generation params
imageGenerationParams = $state<ImageGenerationParams>({
@@ -592,12 +574,6 @@ class AppStore {
// Image editing state
editingImage = $state<EditingImage | null>(null);
/** True when the backend is reachable. */
isConnected = $state<boolean>(true);
/** Number of consecutive fetch failures. */
private consecutiveFailures = 0;
private static readonly CONNECTION_LOST_THRESHOLD = 3;
private fetchInterval: ReturnType<typeof setInterval> | null = null;
private previewsInterval: ReturnType<typeof setInterval> | null = null;
private lastConversationPersistTs = 0;
@@ -850,10 +826,6 @@ class AppStore {
this.thinkingEnabled = conversation.enableThinking ?? true;
this.refreshConversationModelFromInstances();
// Sync global selection to the loaded conversation's model so reactive
// effects in +page.svelte can determine the correct chat launch state.
this.selectedChatModel = conversation.modelId || "";
return true;
}
@@ -924,7 +896,11 @@ class AppStore {
let instanceType: string | null = null;
if (instanceTag === "MlxRingInstance") instanceType = "MLX Ring";
else if (instanceTag === "MlxJacclInstance") instanceType = "MLX RDMA";
else if (
instanceTag === "MlxIbvInstance" ||
instanceTag === "MlxJacclInstance"
)
instanceType = "MLX RDMA";
let sharding: string | null = null;
const inst = instance as {
@@ -1248,30 +1224,6 @@ class AppStore {
this.saveChatSidebarVisibleToStorage();
}
getMobileChatSidebarOpen(): boolean {
return this.mobileChatSidebarOpen;
}
setMobileChatSidebarOpen(open: boolean) {
this.mobileChatSidebarOpen = open;
}
toggleMobileChatSidebar() {
this.mobileChatSidebarOpen = !this.mobileChatSidebarOpen;
}
getMobileRightSidebarOpen(): boolean {
return this.mobileRightSidebarOpen;
}
setMobileRightSidebarOpen(open: boolean) {
this.mobileRightSidebarOpen = open;
}
toggleMobileRightSidebar() {
this.mobileRightSidebarOpen = !this.mobileRightSidebarOpen;
}
startPolling() {
this.fetchState();
this.fetchInterval = setInterval(() => this.fetchState(), 1000);
@@ -1327,19 +1279,7 @@ class AppStore {
// Thunderbolt bridge status per node
this.nodeThunderboltBridge = data.nodeThunderboltBridge ?? {};
this.lastUpdate = Date.now();
// Connection recovered
if (!this.isConnected) {
this.isConnected = true;
}
this.consecutiveFailures = 0;
} catch (error) {
this.consecutiveFailures++;
if (
this.consecutiveFailures >= AppStore.CONNECTION_LOST_THRESHOLD &&
this.isConnected
) {
this.isConnected = false;
}
console.error("Error fetching state:", error);
}
}
@@ -1578,7 +1518,6 @@ class AppStore {
// Remove messages after user message (including the user message for image requests
// since generateImage/editImage will re-add it)
this.messages = this.messages.slice(0, lastUserIndex);
this.updateActiveConversation();
switch (requestType) {
case "image-generation":
@@ -1704,12 +1643,11 @@ class AppStore {
if (!reader) throw new Error("No response body");
let fullContent = prefixText;
let streamedThinking = "";
const collectedTokens: TokenData[] = [...tokensToKeep];
interface ChatCompletionChunk {
choices?: Array<{
delta?: { content?: string; reasoning_content?: string };
delta?: { content?: string };
logprobs?: {
content?: Array<{
token: string;
@@ -1730,7 +1668,6 @@ class AppStore {
(parsed) => {
const choice = parsed.choices?.[0];
const delta = choice?.delta?.content;
const thinkingDelta = choice?.delta?.reasoning_content;
// Collect logprobs data
const logprobsContent = choice?.logprobs?.content;
@@ -1749,11 +1686,7 @@ class AppStore {
}
}
if (thinkingDelta) {
streamedThinking += thinkingDelta;
}
if (delta || thinkingDelta) {
if (delta) {
if (firstTokenTime === null) {
firstTokenTime = performance.now();
this.ttftMs = firstTokenTime - requestStartTime;
@@ -1767,14 +1700,9 @@ class AppStore {
this.tps = ((tokenCount - tokensToKeep.length) / elapsed) * 1000;
}
if (delta) {
fullContent += delta;
}
const { displayContent, thinkingContent: tagThinking } =
fullContent += delta;
const { displayContent, thinkingContent } =
this.stripThinkingTags(fullContent);
const combinedThinking = [streamedThinking, tagThinking]
.filter(Boolean)
.join("\n\n");
if (this.activeConversationId === targetConversationId) {
this.currentResponse = displayContent;
@@ -1786,7 +1714,7 @@ class AppStore {
messageId,
(m) => {
m.content = displayContent;
m.thinking = combinedThinking || undefined;
m.thinking = thinkingContent || undefined;
m.tokens = [...collectedTokens];
},
);
@@ -1794,26 +1722,15 @@ class AppStore {
this.persistConversation(targetConversationId);
}
},
{
generation_stats: (data) => {
const stats = data as { generation_tps: number };
if (stats.generation_tps > 0) {
this.tps = stats.generation_tps;
}
},
},
);
// Final update
if (this.conversationExists(targetConversationId)) {
const { displayContent, thinkingContent: tagThinking } =
const { displayContent, thinkingContent } =
this.stripThinkingTags(fullContent);
const finalThinking = [streamedThinking, tagThinking]
.filter(Boolean)
.join("\n\n");
this.updateConversationMessage(targetConversationId, messageId, (m) => {
m.content = displayContent;
m.thinking = finalThinking || undefined;
m.thinking = thinkingContent || undefined;
m.tokens = [...collectedTokens];
if (this.ttftMs !== null) m.ttftMs = this.ttftMs;
if (this.tps !== null) m.tps = this.tps;
@@ -1889,7 +1806,7 @@ class AppStore {
assistantMessage.id,
(msg) => {
msg.content =
"No model is loaded yet. Select a model from the sidebar to get started — it will download and load automatically.";
"Error: No model available. Please launch an instance first.";
},
);
this.syncActiveMessagesIfNeeded(targetConversationId);
@@ -1921,12 +1838,11 @@ class AppStore {
}
let streamedContent = "";
let streamedThinking = "";
const collectedTokens: TokenData[] = [];
interface ChatCompletionChunk {
choices?: Array<{
delta?: { content?: string; reasoning_content?: string };
delta?: { content?: string };
logprobs?: {
content?: Array<{
token: string;
@@ -1947,7 +1863,6 @@ class AppStore {
(parsed) => {
const choice = parsed.choices?.[0];
const delta = choice?.delta?.content;
const thinkingDelta = choice?.delta?.reasoning_content;
// Collect logprobs data
const logprobsContent = choice?.logprobs?.content;
@@ -1966,19 +1881,10 @@ class AppStore {
}
}
if (thinkingDelta) {
streamedThinking += thinkingDelta;
}
if (delta || thinkingDelta) {
if (delta) {
streamedContent += delta;
}
const { displayContent, thinkingContent: tagThinking } =
if (delta) {
streamedContent += delta;
const { displayContent, thinkingContent } =
this.stripThinkingTags(streamedContent);
const combinedThinking = [streamedThinking, tagThinking]
.filter(Boolean)
.join("\n\n");
// Only update currentResponse if target conversation is active
if (this.activeConversationId === targetConversationId) {
@@ -1991,7 +1897,7 @@ class AppStore {
assistantMessage.id,
(msg) => {
msg.content = displayContent;
msg.thinking = combinedThinking || undefined;
msg.thinking = thinkingContent || undefined;
msg.tokens = [...collectedTokens];
},
);
@@ -1999,29 +1905,18 @@ class AppStore {
this.persistConversation(targetConversationId);
}
},
{
generation_stats: (data) => {
const stats = data as { generation_tps: number };
if (stats.generation_tps > 0) {
this.tps = stats.generation_tps;
}
},
},
);
// Final cleanup of the message (if conversation still exists)
if (this.conversationExists(targetConversationId)) {
const { displayContent, thinkingContent: tagThinking } =
const { displayContent, thinkingContent } =
this.stripThinkingTags(streamedContent);
const finalThinking = [streamedThinking, tagThinking]
.filter(Boolean)
.join("\n\n");
this.updateConversationMessage(
targetConversationId,
assistantMessage.id,
(msg) => {
msg.content = displayContent;
msg.thinking = finalThinking || undefined;
msg.thinking = thinkingContent || undefined;
msg.tokens = [...collectedTokens];
},
);
@@ -2110,7 +2005,6 @@ class AppStore {
reader: ReadableStreamDefaultReader<Uint8Array>,
targetConversationId: string,
onChunk: (parsed: T) => void,
onEvent?: Record<string, (data: unknown) => void>,
): Promise<void> {
const decoder = new TextDecoder();
let buffer = "";
@@ -2131,24 +2025,6 @@ class AppStore {
const trimmed = line.trim();
if (!trimmed) continue;
// Handle SSE comments (": key json") for prefill progress etc.
if (trimmed.startsWith(": ") && onEvent) {
const comment = trimmed.slice(2);
const spaceIdx = comment.indexOf(" ");
if (spaceIdx > 0) {
const key = comment.slice(0, spaceIdx);
if (onEvent[key]) {
try {
const parsed = JSON.parse(comment.slice(spaceIdx + 1));
onEvent[key](parsed);
} catch {
// Skip malformed JSON in comment
}
}
}
continue;
}
if (trimmed.startsWith("data: ")) {
const data = trimmed.slice(6);
if (data === "[DONE]") continue;
@@ -2243,7 +2119,6 @@ class AppStore {
type: string;
textContent?: string;
preview?: string;
pageImages?: string[];
}[],
enableThinking?: boolean | null,
): Promise<void> {
@@ -2279,20 +2154,6 @@ class AppStore {
preview: file.preview,
mimeType: file.type,
});
} else if (
file.pageImages ||
(file.textContent && file.type === "application/pdf")
) {
attachments.push({
type: "pdf",
name: file.name,
content: file.textContent,
pageImages: file.pageImages,
mimeType: file.type,
});
if (file.textContent) {
fileContext += `\n\n[File: ${file.name}]\n\`\`\`\n${file.textContent}\n\`\`\``;
}
} else if (file.textContent) {
attachments.push({
type: "text",
@@ -2360,70 +2221,13 @@ class AppStore {
const apiMessages = [
systemPrompt,
...targetConversation.messages.slice(0, -1).map((m) => {
// Check if this message has image or PDF attachments
const visualAttachments = m.attachments?.filter(
(a) =>
(a.type === "image" && a.preview) ||
(a.type === "pdf" && a.pageImages?.length),
);
if (visualAttachments && visualAttachments.length > 0) {
// Build multimodal content array (OpenAI vision format)
const contentParts: Array<
| { type: "text"; text: string }
| { type: "image_url"; image_url: { url: string } }
> = [];
// Add image parts first
for (const att of visualAttachments) {
if (att.type === "image" && att.preview) {
contentParts.push({
type: "image_url",
image_url: { url: att.preview },
});
} else if (att.type === "pdf" && att.pageImages) {
for (const pageImg of att.pageImages) {
contentParts.push({
type: "image_url",
image_url: { url: pageImg },
});
}
}
}
// Build text content including any text/pdf file attachments
let textContent = m.content;
if (m.attachments) {
for (const attachment of m.attachments) {
if (
(attachment.type === "text" || attachment.type === "pdf") &&
attachment.content
) {
textContent += `\n\n[File: ${attachment.name}]\n\`\`\`\n${attachment.content}\n\`\`\``;
}
}
}
if (textContent) {
contentParts.push({ type: "text", text: textContent });
}
return {
role: m.role,
content: contentParts,
};
}
// Text-only message (original path)
// Build content including any text file attachments
let msgContent = m.content;
// Add text/pdf attachments as context
// Add text attachments as context
if (m.attachments) {
for (const attachment of m.attachments) {
if (
(attachment.type === "text" || attachment.type === "pdf") &&
attachment.content
) {
if (attachment.type === "text" && attachment.content) {
msgContent += `\n\n[File: ${attachment.name}]\n\`\`\`\n${attachment.content}\n\`\`\``;
}
}
@@ -2440,7 +2244,7 @@ class AppStore {
const modelToUse = this.getModelForRequest();
if (!modelToUse) {
throw new Error(
"No model is loaded yet. Select a model from the sidebar to get started — it will download and load automatically.",
"No model selected and no running instances available. Please launch an instance first.",
);
}
@@ -2452,9 +2256,6 @@ class AppStore {
let firstTokenTime: number | null = null;
let tokenCount = 0;
const abortController = new AbortController();
this.currentAbortController = abortController;
const response = await fetch("/v1/chat/completions", {
method: "POST",
headers: {
@@ -2471,7 +2272,6 @@ class AppStore {
enable_thinking: enableThinking,
}),
}),
signal: abortController.signal,
});
if (!response.ok) {
@@ -2485,11 +2285,10 @@ class AppStore {
}
let streamedContent = "";
let streamedThinking = "";
let serverTpsReceived = false;
interface ChatCompletionChunk {
choices?: Array<{
delta?: { content?: string; reasoning_content?: string };
delta?: { content?: string };
logprobs?: {
content?: Array<{
token: string;
@@ -2510,14 +2309,8 @@ class AppStore {
reader,
targetConversationId,
(parsed) => {
// Clear prefill progress when first token data arrives
if (this.prefillProgress) {
this.prefillProgress = null;
}
const choice = parsed.choices?.[0];
const tokenContent = choice?.delta?.content;
const thinkingContent = choice?.delta?.reasoning_content;
// Collect logprobs data
const logprobsContent = choice?.logprobs?.content;
@@ -2536,11 +2329,7 @@ class AppStore {
}
}
if (thinkingContent) {
streamedThinking += thinkingContent;
}
if (tokenContent || thinkingContent) {
if (tokenContent) {
// Track first token for TTFT
if (firstTokenTime === null) {
firstTokenTime = performance.now();
@@ -2551,21 +2340,17 @@ class AppStore {
tokenCount += 1;
this.totalTokens = tokenCount;
// Update real-time TPS during streaming
if (firstTokenTime !== null && tokenCount > 1) {
const elapsed = performance.now() - firstTokenTime;
this.tps = (tokenCount / elapsed) * 1000;
}
if (tokenContent) {
streamedContent += tokenContent;
}
streamedContent += tokenContent;
// Use stripThinkingTags as fallback for any <think> tags still in content
const { displayContent, thinkingContent: tagThinking } =
// Strip thinking tags for display and extract thinking content
const { displayContent, thinkingContent } =
this.stripThinkingTags(streamedContent);
const combinedThinking = [streamedThinking, tagThinking]
.filter(Boolean)
.join("\n\n");
// Only update currentResponse if target conversation is active
if (this.activeConversationId === targetConversationId) {
@@ -2578,7 +2363,7 @@ class AppStore {
assistantMessage.id,
(msg) => {
msg.content = displayContent;
msg.thinking = combinedThinking || undefined;
msg.thinking = thinkingContent || undefined;
msg.tokens = [...collectedTokens];
},
);
@@ -2586,54 +2371,24 @@ class AppStore {
this.persistConversation(targetConversationId);
}
},
{
prefill_progress: (data) => {
// TaggedModel wraps as {"PrefillProgressChunk": {...}}
// model_dump_json() uses snake_case (by_alias defaults to False)
const raw = data as Record<string, unknown>;
const inner = (raw["PrefillProgressChunk"] ?? raw) as {
processed_tokens: number;
total_tokens: number;
};
this.prefillProgress = {
processed: inner.processed_tokens,
total: inner.total_tokens,
startedAt: this.prefillProgress?.startedAt ?? performance.now(),
};
},
generation_stats: (data) => {
const stats = data as { generation_tps: number };
if (stats.generation_tps > 0) {
this.tps = stats.generation_tps;
serverTpsReceived = true;
}
},
},
);
// Clear prefill progress after stream ends
this.prefillProgress = null;
// Use server-side TPS if available, otherwise fall back to client-side
if (!serverTpsReceived && firstTokenTime !== null && tokenCount > 1) {
// Calculate final TPS
if (firstTokenTime !== null && tokenCount > 1) {
const totalGenerationTime = performance.now() - firstTokenTime;
this.tps = (tokenCount / totalGenerationTime) * 1000;
this.tps = (tokenCount / totalGenerationTime) * 1000; // tokens per second
}
// Final cleanup of the message (if conversation still exists)
if (this.conversationExists(targetConversationId)) {
const { displayContent, thinkingContent: tagThinking } =
const { displayContent, thinkingContent } =
this.stripThinkingTags(streamedContent);
const finalThinking = [streamedThinking, tagThinking]
.filter(Boolean)
.join("\n\n");
this.updateConversationMessage(
targetConversationId,
assistantMessage.id,
(msg) => {
msg.content = displayContent;
msg.thinking = finalThinking || undefined;
msg.thinking = thinkingContent || undefined;
msg.tokens = [...collectedTokens];
// Store performance metrics on the message
if (this.ttftMs !== null) {
@@ -2648,31 +2403,20 @@ class AppStore {
this.persistConversation(targetConversationId);
}
} catch (error) {
if (error instanceof DOMException && error.name === "AbortError") {
// User stopped generation — not an error
} else {
console.error("Error sending message:", error);
this.handleStreamingError(
error,
targetConversationId,
assistantMessage.id,
"Failed to get response",
);
}
console.error("Error sending message:", error);
this.handleStreamingError(
error,
targetConversationId,
assistantMessage.id,
"Failed to get response",
);
} finally {
this.currentAbortController = null;
this.prefillProgress = null;
this.isLoading = false;
this.currentResponse = "";
this.saveConversationsToStorage();
}
}
stopGeneration(): void {
this.currentAbortController?.abort();
this.currentAbortController = null;
}
/**
* Generate an image using the image generation API
*/
@@ -2723,9 +2467,6 @@ class AppStore {
this.syncActiveMessagesIfNeeded(targetConversationId);
this.saveConversationsToStorage();
const abortController = new AbortController();
this.currentAbortController = abortController;
try {
// Determine the model to use
const model = this.getModelForRequest(modelId);
@@ -2780,7 +2521,6 @@ class AppStore {
"Content-Type": "application/json",
},
body: JSON.stringify(requestBody),
signal: abortController.signal,
});
if (!response.ok) {
@@ -2920,27 +2660,14 @@ class AppStore {
);
}
} catch (error) {
if (abortController.signal.aborted) {
this.updateConversationMessage(
targetConversationId,
assistantMessage.id,
(msg) => {
msg.content = "Cancelled";
msg.attachments = [];
},
);
this.syncActiveMessagesIfNeeded(targetConversationId);
} else {
console.error("Error generating image:", error);
this.handleStreamingError(
error,
targetConversationId,
assistantMessage.id,
"Failed to generate image",
);
}
console.error("Error generating image:", error);
this.handleStreamingError(
error,
targetConversationId,
assistantMessage.id,
"Failed to generate image",
);
} finally {
this.currentAbortController = null;
this.isLoading = false;
this.saveConversationsToStorage();
}
@@ -3004,9 +2731,6 @@ class AppStore {
// Clear editing state
this.editingImage = null;
const abortController = new AbortController();
this.currentAbortController = abortController;
try {
// Determine the model to use
const model = this.getModelForRequest(modelId);
@@ -3068,7 +2792,6 @@ class AppStore {
const apiResponse = await fetch("/v1/images/edits", {
method: "POST",
body: formData,
signal: abortController.signal,
});
if (!apiResponse.ok) {
@@ -3169,27 +2892,14 @@ class AppStore {
);
}
} catch (error) {
if (abortController.signal.aborted) {
this.updateConversationMessage(
targetConversationId,
assistantMessage.id,
(msg) => {
msg.content = "Cancelled";
msg.attachments = [];
},
);
this.syncActiveMessagesIfNeeded(targetConversationId);
} else {
console.error("Error editing image:", error);
this.handleStreamingError(
error,
targetConversationId,
assistantMessage.id,
"Failed to edit image",
);
}
console.error("Error editing image:", error);
this.handleStreamingError(
error,
targetConversationId,
assistantMessage.id,
"Failed to edit image",
);
} finally {
this.currentAbortController = null;
this.isLoading = false;
this.saveConversationsToStorage();
}
@@ -3315,23 +3025,6 @@ class AppStore {
return (await response.json()) as TraceStatsResponse;
}
/**
* Delete traces by task IDs
*/
async deleteTraces(
taskIds: string[],
): Promise<{ deleted: string[]; notFound: string[] }> {
const response = await fetch("/v1/traces/delete", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ taskIds }),
});
if (!response.ok) {
throw new Error(`Failed to delete traces: ${response.status}`);
}
return await response.json();
}
/**
* Get the URL for the raw trace file (for Perfetto)
*/
@@ -3350,7 +3043,6 @@ export const isLoading = () => appStore.isLoading;
export const ttftMs = () => appStore.ttftMs;
export const tps = () => appStore.tps;
export const totalTokens = () => appStore.totalTokens;
export const prefillProgress = () => appStore.prefillProgress;
export const topologyData = () => appStore.topologyData;
export const instances = () => appStore.instances;
export const runners = () => appStore.runners;
@@ -3368,7 +3060,6 @@ export const topologyOnlyMode = () => appStore.getTopologyOnlyMode();
export const chatSidebarVisible = () => appStore.getChatSidebarVisible();
// Actions
export const stopGeneration = () => appStore.stopGeneration();
export const startChat = () => appStore.startChat();
export const sendMessage = (
content: string,
@@ -3378,7 +3069,6 @@ export const sendMessage = (
type: string;
textContent?: string;
preview?: string;
pageImages?: string[];
}[],
enableThinking?: boolean | null,
) => appStore.sendMessage(content, files, enableThinking);
@@ -3440,23 +3130,8 @@ export const toggleChatSidebarVisible = () =>
appStore.toggleChatSidebarVisible();
export const setChatSidebarVisible = (visible: boolean) =>
appStore.setChatSidebarVisible(visible);
// Mobile sidebar state
export const mobileChatSidebarOpen = () => appStore.mobileChatSidebarOpen;
export const toggleMobileChatSidebar = () => appStore.toggleMobileChatSidebar();
export const setMobileChatSidebarOpen = (open: boolean) =>
appStore.setMobileChatSidebarOpen(open);
export const mobileRightSidebarOpen = () => appStore.mobileRightSidebarOpen;
export const toggleMobileRightSidebar = () =>
appStore.toggleMobileRightSidebar();
export const setMobileRightSidebarOpen = (open: boolean) =>
appStore.setMobileRightSidebarOpen(open);
export const refreshState = () => appStore.fetchState();
// Connection status
export const isConnected = () => appStore.isConnected;
// Node identities (for OS version mismatch detection)
export const nodeIdentities = () => appStore.nodeIdentities;
@@ -3488,5 +3163,3 @@ export const fetchTraceStats = (taskId: string) =>
appStore.fetchTraceStats(taskId);
export const getTraceRawUrl = (taskId: string) =>
appStore.getTraceRawUrl(taskId);
export const deleteTraces = (taskIds: string[]) =>
appStore.deleteTraces(taskIds);
-87
View File
@@ -1,87 +0,0 @@
/**
* Toast notification store - Global notification system for the EXO dashboard.
*
* Usage:
* import { addToast, dismissToast, toasts } from "$lib/stores/toast.svelte";
* addToast({ type: "success", message: "Model launched" });
* addToast({ type: "error", message: "Connection lost", persistent: true });
*/
type ToastType = "success" | "error" | "warning" | "info";
export interface Toast {
id: string;
type: ToastType;
message: string;
/** Auto-dismiss after this many ms. 0 = persistent (must be dismissed manually). */
duration: number;
createdAt: number;
}
interface ToastInput {
type: ToastType;
message: string;
/** If true, toast stays until manually dismissed. Default: false. */
persistent?: boolean;
/** Auto-dismiss duration in ms. Default: 4000 for success/info, 6000 for error/warning. */
duration?: number;
}
const DEFAULT_DURATIONS: Record<ToastType, number> = {
success: 4000,
info: 4000,
warning: 6000,
error: 6000,
};
let toastList = $state<Toast[]>([]);
const timers = new Map<string, ReturnType<typeof setTimeout>>();
function generateId(): string {
return `toast-${Date.now()}-${Math.random().toString(36).slice(2, 8)}`;
}
export function addToast(input: ToastInput): string {
const id = generateId();
const duration = input.persistent
? 0
: (input.duration ?? DEFAULT_DURATIONS[input.type]);
const toast: Toast = {
id,
type: input.type,
message: input.message,
duration,
createdAt: Date.now(),
};
toastList = [...toastList, toast];
if (duration > 0) {
const timer = setTimeout(() => dismissToast(id), duration);
timers.set(id, timer);
}
return id;
}
export function dismissToast(id: string): void {
const timer = timers.get(id);
if (timer) {
clearTimeout(timer);
timers.delete(id);
}
toastList = toastList.filter((t) => t.id !== id);
}
/** Dismiss all toasts matching a message (useful for dedup). */
export function dismissByMessage(message: string): void {
const matching = toastList.filter((t) => t.message === message);
for (const t of matching) {
dismissToast(t.id);
}
}
export function toasts(): Toast[] {
return toastList;
}
+1 -68
View File
@@ -2,15 +2,6 @@
* File attachment types for the chat interface
*/
import { getDocument, GlobalWorkerOptions, version } from "pdfjs-dist";
import type { DocumentInitParameters } from "pdfjs-dist/types/src/display/api";
GlobalWorkerOptions.workerSrc = `https://cdn.jsdelivr.net/npm/pdfjs-dist@${version}/build/pdf.worker.mjs`;
const PDF_PAGE_SCALE = 2.0;
const PDF_MAX_PAGES = 20;
const PDF_MAX_TEXT_CHARS = 100_000;
export interface ChatUploadedFile {
id: string;
name: string;
@@ -19,7 +10,6 @@ export interface ChatUploadedFile {
file: File;
preview?: string;
textContent?: string;
pageImages?: string[];
}
export interface ChatAttachment {
@@ -204,58 +194,6 @@ export function readFileAsText(file: File): Promise<string> {
});
}
async function extractPdfContent(
file: File,
): Promise<{ text: string; pageImages: string[] }> {
const arrayBuffer = await file.arrayBuffer();
const pdf = await getDocument({
data: new Uint8Array(arrayBuffer),
useSystemFonts: true,
} as DocumentInitParameters).promise;
const numPages = Math.min(pdf.numPages, PDF_MAX_PAGES);
const pageTexts: string[] = [];
const pageImages: string[] = [];
for (let i = 1; i <= numPages; i++) {
const page = await pdf.getPage(i);
const content = await page.getTextContent();
const strings = content.items
.filter((item: any) => "str" in item)
.map((item: any) => item.str as string);
pageTexts.push(strings.join(" "));
const viewport = page.getViewport({ scale: PDF_PAGE_SCALE });
const canvas = new OffscreenCanvas(viewport.width, viewport.height);
const ctx = canvas.getContext("2d");
if (ctx) {
await page.render({ canvasContext: ctx as any, viewport }).promise;
const blob = await canvas.convertToBlob({
type: "image/jpeg",
quality: 0.8,
});
const reader = new FileReader();
const dataUrl = await new Promise<string>((resolve, reject) => {
reader.onload = () => resolve(reader.result as string);
reader.onerror = () => reject(reader.error);
reader.readAsDataURL(blob);
});
pageImages.push(dataUrl);
}
}
let text = pageTexts.join("\n\n").trim();
if (text.length > PDF_MAX_TEXT_CHARS) {
text = text.slice(0, PDF_MAX_TEXT_CHARS) + "\n\n[truncated]";
}
if (pdf.numPages > PDF_MAX_PAGES) {
text += `\n\n[showing ${PDF_MAX_PAGES} of ${pdf.numPages} pages]`;
}
return { text, pageImages };
}
/**
* Process uploaded files into ChatUploadedFile format
*/
@@ -285,12 +223,7 @@ export async function processUploadedFiles(
const textContent = await readFileAsText(file);
results.push({ ...base, textContent });
} else if (category === "pdf") {
const { text, pageImages } = await extractPdfContent(file);
results.push({
...base,
textContent: text || undefined,
pageImages: pageImages.length > 0 ? pageImages : undefined,
});
results.push(base);
} else if (category === "audio") {
const preview = await readFileAsDataURL(file);
results.push({ ...base, preview });
-4
View File
@@ -1,7 +1,5 @@
<script lang="ts">
import "../app.css";
import ToastContainer from "$lib/components/ToastContainer.svelte";
import ConnectionBanner from "$lib/components/ConnectionBanner.svelte";
let { children } = $props();
</script>
@@ -12,7 +10,5 @@
</svelte:head>
<div class="min-h-screen bg-background text-foreground">
<ConnectionBanner />
{@render children?.()}
<ToastContainer />
</div>
File diff suppressed because it is too large Load Diff
+42 -156
View File
@@ -29,12 +29,7 @@
etaMs: number;
modelDirectory?: string;
}
| {
kind: "pending";
downloaded: number;
total: number;
modelDirectory?: string;
}
| { kind: "pending"; modelDirectory?: string }
| { kind: "failed"; modelDirectory?: string }
| { kind: "not_present" };
@@ -79,6 +74,7 @@
if (typeof value === "number") return value;
if (value && typeof value === "object") {
const v = value as Record<string, unknown>;
if (typeof v.in_bytes === "number") return v.in_bytes;
if (typeof v.inBytes === "number") return v.inBytes;
}
return 0;
@@ -235,14 +231,23 @@
undefined;
let cell: CellStatus;
if (tag === "DownloadCompleted") {
const totalBytes = getBytes(payload.total);
const totalBytes = getBytes(
payload.total_bytes ?? payload.totalBytes,
);
cell = { kind: "completed", totalBytes, modelDirectory };
} else if (tag === "DownloadOngoing") {
const rawProgress =
payload.download_progress ?? payload.downloadProgress ?? {};
const prog = rawProgress as Record<string, unknown>;
const totalBytes = getBytes(prog.total ?? payload.total);
const downloadedBytes = getBytes(prog.downloaded);
const totalBytes = getBytes(
prog.total_bytes ??
prog.totalBytes ??
payload.total_bytes ??
payload.totalBytes,
);
const downloadedBytes = getBytes(
prog.downloaded_bytes ?? prog.downloadedBytes,
);
const speed = (prog.speed as number) ?? 0;
const etaMs =
(prog.eta_ms as number) ?? (prog.etaMs as number) ?? 0;
@@ -260,20 +265,7 @@
} else if (tag === "DownloadFailed") {
cell = { kind: "failed", modelDirectory };
} else {
const downloaded = getBytes(
payload.downloaded ??
payload.downloaded_bytes ??
payload.downloadedBytes,
);
const total = getBytes(
payload.total ?? payload.total_bytes ?? payload.totalBytes,
);
cell = {
kind: "pending",
downloaded,
total,
modelDirectory,
};
cell = { kind: "pending", modelDirectory };
}
const existing = row.cells[nodeId];
@@ -283,51 +275,14 @@
}
}
function rowSortKey(row: ModelRow): number {
// in progress (4) -> completed (3) -> paused (2) -> not started (1) -> not present (0)
let best = 0;
for (const cell of Object.values(row.cells)) {
let score = 0;
if (cell.kind === "downloading") score = 4;
else if (cell.kind === "completed") score = 3;
else if (cell.kind === "pending" && cell.downloaded > 0)
score = 2; // paused
else if (cell.kind === "pending" || cell.kind === "failed") score = 1; // not started
if (score > best) best = score;
}
return best;
}
function totalCompletedBytes(row: ModelRow): number {
let total = 0;
for (const cell of Object.values(row.cells)) {
if (cell.kind === "completed") total += cell.totalBytes;
}
return total;
}
const rows = Array.from(rowMap.values()).sort((a, b) => {
const aPriority = rowSortKey(a);
const bPriority = rowSortKey(b);
if (aPriority !== bPriority) return bPriority - aPriority;
// Within completed or paused, sort by biggest size first
if (aPriority === 3 && bPriority === 3) {
const sizeDiff = totalCompletedBytes(b) - totalCompletedBytes(a);
if (sizeDiff !== 0) return sizeDiff;
}
if (aPriority === 2 && bPriority === 2) {
const aSize = Math.max(
...Object.values(a.cells).map((c) =>
c.kind === "pending" ? c.total : 0,
),
);
const bSize = Math.max(
...Object.values(b.cells).map((c) =>
c.kind === "pending" ? c.total : 0,
),
);
if (aSize !== bSize) return bSize - aSize;
}
const aCompleted = Object.values(a.cells).filter(
(c) => c.kind === "completed",
).length;
const bCompleted = Object.values(b.cells).filter(
(c) => c.kind === "completed",
).length;
if (aCompleted !== bCompleted) return bCompleted - aCompleted;
return a.modelId.localeCompare(b.modelId);
});
@@ -412,7 +367,7 @@
<div>{col.label}</div>
{#if col.diskAvailable != null}
<div
class="text-[9px] text-white/70 normal-case tracking-normal mt-0.5"
class="text-[9px] text-exo-light-gray/60 normal-case tracking-normal mt-0.5"
>
{formatBytes(col.diskAvailable)} free
</div>
@@ -436,7 +391,7 @@
</div>
{#if row.prettyName}
<div
class="text-[10px] text-white/60"
class="text-[10px] text-exo-light-gray/60"
title={row.modelId}
>
{row.modelId}
@@ -450,7 +405,7 @@
title="View model details"
>
<svg
class="w-4 h-4 text-white/60 hover:text-white/80"
class="w-4 h-4 text-white/30 hover:text-white/60"
viewBox="0 0 24 24"
fill="currentColor"
>
@@ -469,11 +424,11 @@
<td class="px-4 py-3 text-center align-middle">
{#if cell.kind === "completed"}
<div
class="flex flex-col items-center gap-1"
class="flex flex-col items-center gap-0.5"
title="Completed ({formatBytes(cell.totalBytes)})"
>
<svg
class="w-7 h-7 text-green-400"
class="w-5 h-5 text-green-400"
viewBox="0 0 20 20"
fill="currentColor"
>
@@ -483,18 +438,18 @@
clip-rule="evenodd"
></path>
</svg>
<span class="text-xs text-white/70"
<span class="text-[10px] text-exo-light-gray/70"
>{formatBytes(cell.totalBytes)}</span
>
<button
type="button"
class="text-white/50 hover:text-red-400 transition-colors mt-0.5 cursor-pointer"
class="text-exo-light-gray/40 hover:text-red-400 transition-colors mt-0.5"
onclick={() =>
deleteDownload(col.nodeId, row.modelId)}
title="Delete from this node"
>
<svg
class="w-5 h-5"
class="w-3.5 h-3.5"
viewBox="0 0 20 20"
fill="none"
stroke="currentColor"
@@ -517,11 +472,11 @@
cell.speed,
)} - ETA {formatEta(cell.etaMs)}"
>
<span class="text-exo-yellow text-sm font-medium"
<span class="text-exo-yellow text-xs font-medium"
>{clampPercent(cell.percentage).toFixed(1)}%</span
>
<div
class="w-16 h-2 bg-exo-black/60 rounded-sm overflow-hidden"
class="w-14 h-1.5 bg-exo-black/60 rounded-sm overflow-hidden"
>
<div
class="h-full bg-gradient-to-r from-exo-yellow to-exo-yellow/70 transition-all duration-300"
@@ -530,93 +485,24 @@
).toFixed(1)}%"
></div>
</div>
<span class="text-[10px] text-white/70"
<span class="text-[9px] text-exo-light-gray/60"
>{formatSpeed(cell.speed)}</span
>
</div>
{:else if cell.kind === "pending"}
<div
class="flex flex-col items-center gap-1"
title={cell.downloaded > 0
? `${formatBytes(cell.downloaded)} / ${formatBytes(cell.total)} downloaded (paused)`
: "Download pending"}
class="flex flex-col items-center gap-0.5"
title="Download pending"
>
{#if cell.downloaded > 0 && cell.total > 0}
<span class="text-white/70 text-xs"
>{formatBytes(cell.downloaded)} / {formatBytes(
cell.total,
)}</span
>
<div
class="w-full h-1.5 bg-white/10 rounded-full overflow-hidden"
>
<div
class="h-full bg-exo-light-gray/40 rounded-full"
style="width: {(
(cell.downloaded / cell.total) *
100
).toFixed(1)}%"
></div>
</div>
{#if row.shardMetadata}
<button
type="button"
class="text-white/50 hover:text-exo-yellow transition-colors cursor-pointer"
onclick={() =>
startDownload(col.nodeId, row.shardMetadata!)}
title="Resume download on this node"
>
<svg
class="w-5 h-5"
viewBox="0 0 20 20"
fill="none"
stroke="currentColor"
stroke-width="2"
>
<path
d="M10 3v10m0 0l-3-3m3 3l3-3M3 17h14"
stroke-linecap="round"
stroke-linejoin="round"
></path>
</svg>
</button>
{:else}
<span class="text-white/50 text-[10px]">paused</span
>
{/if}
{:else if row.shardMetadata}
<button
type="button"
class="text-white/50 hover:text-exo-yellow transition-colors cursor-pointer"
onclick={() =>
startDownload(col.nodeId, row.shardMetadata!)}
title="Start download on this node"
>
<svg
class="w-6 h-6"
viewBox="0 0 20 20"
fill="none"
stroke="currentColor"
stroke-width="2"
>
<path
d="M10 3v10m0 0l-3-3m3 3l3-3M3 17h14"
stroke-linecap="round"
stroke-linejoin="round"
></path>
</svg>
</button>
{:else}
<span class="text-white/40 text-sm">...</span>
{/if}
<span class="text-exo-light-gray/50 text-sm">...</span>
</div>
{:else if cell.kind === "failed"}
<div
class="flex flex-col items-center gap-1"
class="flex flex-col items-center gap-0.5"
title="Download failed"
>
<svg
class="w-7 h-7 text-red-400"
class="w-5 h-5 text-red-400"
viewBox="0 0 20 20"
fill="currentColor"
>
@@ -629,13 +515,13 @@
{#if row.shardMetadata}
<button
type="button"
class="text-white/50 hover:text-exo-yellow transition-colors cursor-pointer"
class="text-exo-light-gray/40 hover:text-exo-yellow transition-colors"
onclick={() =>
startDownload(col.nodeId, row.shardMetadata!)}
title="Retry download on this node"
>
<svg
class="w-5 h-5"
class="w-3.5 h-3.5"
viewBox="0 0 20 20"
fill="none"
stroke="currentColor"
@@ -661,13 +547,13 @@
{#if row.shardMetadata}
<button
type="button"
class="text-white/50 hover:text-exo-yellow transition-colors mt-0.5 opacity-0 group-hover:opacity-100 cursor-pointer"
class="text-exo-light-gray/30 hover:text-exo-yellow transition-colors mt-0.5 opacity-0 group-hover:opacity-100"
onclick={() =>
startDownload(col.nodeId, row.shardMetadata!)}
title="Download to this node"
>
<svg
class="w-5 h-5"
class="w-3.5 h-3.5"
viewBox="0 0 20 20"
fill="none"
stroke="currentColor"
@@ -1,577 +0,0 @@
<script lang="ts">
import { browser } from "$app/environment";
import { fade } from "svelte/transition";
import HeaderNav from "$lib/components/HeaderNav.svelte";
import IntegrationCard from "$lib/components/IntegrationCard.svelte";
import { instances, refreshState } from "$lib/stores/app.svelte";
import { onMount } from "svelte";
const apiUrl = browser
? window.location.origin.replace("localhost", "127.0.0.1")
: "http://127.0.0.1:52415";
const instancesData = $derived(instances());
let modelCapabilities = $state<Record<string, string[]>>({});
let modelContextLengths = $state<Record<string, number>>({});
const runningModels = $derived.by(() => {
const models: string[] = [];
for (const [, wrapper] of Object.entries(instancesData)) {
if (wrapper && typeof wrapper === "object") {
const values = Object.values(wrapper as Record<string, unknown>);
if (values.length > 0) {
const instance = values[0];
if (instance && typeof instance === "object") {
const inst = instance as {
shardAssignments?: { modelId?: string };
};
const modelId = inst.shardAssignments?.modelId;
if (modelId && !models.includes(modelId)) {
models.push(modelId);
}
}
}
}
}
return models;
});
function estimateParamSize(modelId: string): number {
const match = modelId.match(/(\d+(?:\.\d+)?)[Bb]/);
return match ? parseFloat(match[1]) : 0;
}
const modelsBySize = $derived(
[...runningModels].sort(
(a, b) => estimateParamSize(b) - estimateParamSize(a),
),
);
const defaultTiers = $derived.by(() => {
const n = modelsBySize.length;
if (n === 0)
return {
opus: "your-model-id",
sonnet: "your-model-id",
haiku: "your-model-id",
};
if (n === 1)
return {
opus: modelsBySize[0],
sonnet: modelsBySize[0],
haiku: modelsBySize[0],
};
if (n === 2)
return {
opus: modelsBySize[0],
sonnet: modelsBySize[1],
haiku: modelsBySize[1],
};
return {
opus: modelsBySize[0],
sonnet: modelsBySize[Math.floor(n / 2)],
haiku: modelsBySize[n - 1],
};
});
let opusModel = $state("");
let sonnetModel = $state("");
let haikuModel = $state("");
$effect(() => {
opusModel = defaultTiers.opus;
sonnetModel = defaultTiers.sonnet;
haikuModel = defaultTiers.haiku;
});
let codexModel = $state("");
let codexMcpPath = $state("/Users/username");
let openClawModel = $state("");
$effect(() => {
const def = modelsBySize.length > 0 ? modelsBySize[0] : "your-model-id";
codexModel = def;
openClawModel = def;
});
const claudeShellCommand = $derived(
[
`ANTHROPIC_BASE_URL=${apiUrl} \\`,
`ANTHROPIC_API_KEY=x \\`,
`ANTHROPIC_DEFAULT_OPUS_MODEL=${opusModel} \\`,
`ANTHROPIC_DEFAULT_SONNET_MODEL=${sonnetModel} \\`,
`ANTHROPIC_DEFAULT_HAIKU_MODEL=${haikuModel} \\`,
`API_TIMEOUT_MS=3000000 \\`,
`CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1 \\`,
`claude`,
].join("\n"),
);
const claudeSettingsJson = $derived(
JSON.stringify(
{
env: {
ANTHROPIC_BASE_URL: apiUrl,
ANTHROPIC_API_KEY: "x",
ANTHROPIC_DEFAULT_OPUS_MODEL: opusModel,
ANTHROPIC_DEFAULT_SONNET_MODEL: sonnetModel,
ANTHROPIC_DEFAULT_HAIKU_MODEL: haikuModel,
API_TIMEOUT_MS: "3000000",
CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC: "1",
},
},
null,
2,
),
);
const openCodeConfig = $derived.by(() => {
const models: Record<string, Record<string, unknown>> = {};
for (const modelId of runningModels) {
const caps = modelCapabilities[modelId] || [];
const ctxLen = modelContextLengths[modelId] || 0;
const entry: Record<string, unknown> = { name: modelId };
if (ctxLen > 0) {
entry.limit = { context: ctxLen, output: Math.min(ctxLen, 16384) };
}
if (caps.includes("vision")) {
entry.modalities = { input: ["text", "image"], output: ["text"] };
}
models[modelId] = entry;
}
if (Object.keys(models).length === 0) {
models["your-model-id"] = { name: "your-model-name" };
}
const firstModel =
runningModels.length > 0 ? runningModels[0] : "your-model-id";
return JSON.stringify(
{
$schema: "https://opencode.ai/config.json",
provider: {
exo: {
npm: "@ai-sdk/openai-compatible",
name: "exo",
options: {
baseURL: `${apiUrl}/v1`,
apiKey: "x",
},
models,
},
},
model: `exo/${firstModel}`,
},
null,
2,
);
});
const codexShellCommand = $derived(`EXO_API_KEY=x npx @openai/codex`);
const codexConfig = $derived(
[
`model = "${codexModel}"`,
`model_provider = "exo"`,
``,
`[model_providers.exo]`,
`name = "exo"`,
`base_url = "${apiUrl}/v1"`,
`env_key = "EXO_API_KEY"`,
``,
`[mcp_servers.filesystem]`,
`command = "npx"`,
`args = ["-y", "@modelcontextprotocol/server-filesystem", "${codexMcpPath}"]`,
].join("\n"),
);
const openClawConfig = $derived(
JSON.stringify(
{
gateway: { mode: "local" },
models: {
providers: {
exo: {
baseUrl: `${apiUrl}/v1`,
apiKey: "x",
api: "openai-completions",
models: [
{
id: openClawModel,
name: "exo local",
input: (modelCapabilities[openClawModel] || []).includes(
"vision",
)
? ["text", "image"]
: ["text"],
},
],
},
},
},
agents: {
defaults: {
model: `exo/${openClawModel}`,
},
},
},
null,
2,
),
);
const ollamaCommand = $derived(
`OLLAMA_HOST=${apiUrl}/ollama ollama run ${modelsBySize.length > 0 ? modelsBySize[0] : "your-model-id"}`,
);
const openWebUiCommand = $derived(
[
`docker run -d -p 3000:8080 \\`,
` -e OLLAMA_BASE_URL=${apiUrl.replace("localhost", "host.docker.internal")}/ollama \\`,
` -v open-webui:/app/backend/data \\`,
` --name open-webui \\`,
` ghcr.io/open-webui/open-webui:main`,
].join("\n"),
);
const n8nDockerCommand = $derived(
[
`docker run -d -p 5678:5678 \\`,
` -v n8n_data:/home/node/.n8n \\`,
` --name n8n \\`,
` docker.n8n.io/n8nio/n8n`,
].join("\n"),
);
const n8nCredentialSteps = $derived(
[
`1. Go to Credentials → Add Credential → search "OpenAI API"`,
`2. Set API Key to: x`,
`3. Set Base URL to: ${apiUrl.replace("127.0.0.1", "host.docker.internal").replace("localhost", "host.docker.internal")}/v1`,
`4. Save the credential`,
].join("\n"),
);
const n8nWorkflowSteps = $derived(
[
`1. Create a new workflow → "Start from Scratch"`,
`2. Add an "AI Agent" or "Basic LLM Chain" node`,
`3. Inside it, add an "OpenAI Chat Model" sub-node`,
`4. Select the OpenAI credential you just created`,
`5. Set Model to "From list" and pick your model (e.g. ${modelsBySize.length > 0 ? modelsBySize[0] : "your-model-id"})`,
`6. Optionally toggle "Use Responses API", add Built-in Tools, or click "Add Option" for sampling settings`,
`7. Connect a "Chat Trigger" node for interactive chat`,
`8. On the Chat Trigger, enable "Allow File Uploads" for vision`,
].join("\n"),
);
const firefoxConfig = $derived(
[
`1. Open about:config in Firefox`,
`2. Set browser.ml.chat.enabled to true`,
`3. Set browser.ml.chat.hideLocalhost to false`,
`4. Set browser.ml.chat.provider to: ${apiUrl}/`,
].join("\n"),
);
const tabs = [
"Claude Code",
"OpenCode",
"Codex",
"OpenClaw",
"Open WebUI",
"n8n",
"Firefox",
] as const;
type Tab = (typeof tabs)[number];
const stored = browser ? localStorage.getItem("exo-integrations-tab") : null;
let activeTab = $state<Tab>(
stored && tabs.includes(stored as Tab) ? (stored as Tab) : "Claude Code",
);
$effect(() => {
if (browser) localStorage.setItem("exo-integrations-tab", activeTab);
});
const selectClass =
"bg-black/30 border border-exo-light-gray/20 rounded px-2 py-1.5 text-white font-mono text-xs focus:border-exo-yellow/50 focus:outline-none appearance-none cursor-pointer";
onMount(async () => {
refreshState();
try {
const resp = await fetch("/v1/models");
const data = (await resp.json()) as {
data: { id: string; capabilities: string[]; context_length: number }[];
};
const caps: Record<string, string[]> = {};
const ctxs: Record<string, number> = {};
for (const model of data.data) {
caps[model.id] = model.capabilities || [];
if (model.context_length > 0) ctxs[model.id] = model.context_length;
}
modelCapabilities = caps;
modelContextLengths = ctxs;
} catch {
/* ignore */
}
});
</script>
<div class="min-h-screen bg-exo-dark-gray flex flex-col">
<HeaderNav showHome={true} />
<main
class="flex-1 max-w-3xl mx-auto w-full px-4 md:px-6 py-8"
in:fade={{ duration: 200 }}
>
<div class="mb-8">
<h1
class="text-white text-xl md:text-2xl font-semibold tracking-wide mb-2"
>
Integrations
</h1>
<p class="text-exo-light-gray/60 text-sm">
Connect external tools to your exo cluster.
</p>
</div>
<!-- Status -->
<div class="mb-8">
<span class="text-exo-light-gray/70 text-xs uppercase tracking-wider"
>API Endpoint</span
>
<span class="text-white font-mono text-sm ml-2">{apiUrl}</span>
{#if runningModels.length > 0}
<div class="text-exo-light-gray/50 text-xs mt-2">
Running model{runningModels.length > 1 ? "s" : ""}:
<ul class="mt-1 space-y-0.5 list-none">
{#each runningModels as model}
<li class="text-exo-yellow font-mono">{model}</li>
{/each}
</ul>
</div>
{:else}
<p class="text-exo-light-gray/40 text-xs mt-2 italic">
No models currently running
</p>
{/if}
</div>
<!-- API Endpoints -->
<div class="mb-8">
<div
class="flex flex-col sm:flex-row gap-3 text-xs font-mono text-exo-light-gray/70"
>
<div
class="flex-1 bg-black/20 border border-exo-light-gray/10 rounded px-3 py-2"
>
<span class="text-exo-light-gray/40 text-[10px] uppercase block mb-1"
>OpenAI-compatible</span
>
<span class="text-white/80">{apiUrl}/v1</span>
</div>
<div
class="flex-1 bg-black/20 border border-exo-light-gray/10 rounded px-3 py-2"
>
<span class="text-exo-light-gray/40 text-[10px] uppercase block mb-1"
>Claude-compatible</span
>
<span class="text-white/80">{apiUrl}</span>
</div>
<div
class="flex-1 bg-black/20 border border-exo-light-gray/10 rounded px-3 py-2"
>
<span class="text-exo-light-gray/40 text-[10px] uppercase block mb-1"
>Ollama-compatible</span
>
<span class="text-white/80">{apiUrl}/ollama</span>
</div>
</div>
</div>
<!-- Tabs -->
<div
class="flex flex-wrap gap-2 mb-6 border-b border-exo-light-gray/10 pb-3"
>
{#each tabs as tab}
<button
onclick={() => (activeTab = tab)}
class="px-3 py-1.5 text-xs rounded-md transition-all cursor-pointer
{activeTab === tab
? 'bg-exo-yellow/15 text-exo-yellow border border-exo-yellow/30'
: 'text-exo-light-gray/60 hover:text-white/80 border border-transparent hover:border-exo-light-gray/20'}"
>
{tab}
</button>
{/each}
</div>
<!-- Tab Content -->
<div class="space-y-4">
{#if activeTab === "Claude Code"}
{#if runningModels.length > 1}
<div class="grid grid-cols-3 gap-3 text-xs">
{#each [{ label: "Opus", bind: () => opusModel, set: (v: string) => (opusModel = v) }, { label: "Sonnet", bind: () => sonnetModel, set: (v: string) => (sonnetModel = v) }, { label: "Haiku", bind: () => haikuModel, set: (v: string) => (haikuModel = v) }] as tier}
<div>
<span
class="text-exo-light-gray/50 text-[10px] uppercase tracking-wider block mb-1"
>{tier.label}</span
>
<select
value={tier.bind()}
onchange={(e) =>
tier.set((e.target as HTMLSelectElement).value)}
class="w-full {selectClass}"
>
{#each runningModels as model}
<option value={model}>{model.split("/").pop()}</option>
{/each}
</select>
</div>
{/each}
</div>
{/if}
<IntegrationCard
title="Shell Command"
subtitle="Run in terminal"
description="Launch Claude Code with exo as the backend. Paste this into your terminal."
config={claudeShellCommand}
language="bash"
/>
<IntegrationCard
title="Settings File"
subtitle="~/.claude/settings.json"
description="Or add this to your Claude Code settings for persistent configuration."
config={claudeSettingsJson}
/>
{:else if activeTab === "OpenCode"}
<IntegrationCard
title="Config File"
subtitle="opencode.json"
description="Add this to your project root or ~/.config/opencode/opencode.json for global config. Vision models automatically get image input modality."
config={openCodeConfig}
/>
{:else if activeTab === "Codex"}
<div class="flex gap-3 text-xs">
{#if runningModels.length > 1}
<div>
<span
class="text-exo-light-gray/50 text-[10px] uppercase tracking-wider block mb-1"
>Model</span
>
<select bind:value={codexModel} class={selectClass}>
{#each runningModels as model}
<option value={model}>{model.split("/").pop()}</option>
{/each}
</select>
</div>
{/if}
<div class="flex-1">
<span
class="text-exo-light-gray/50 text-[10px] uppercase tracking-wider block mb-1"
>MCP Filesystem Path</span
>
<input
type="text"
bind:value={codexMcpPath}
class="w-full bg-black/30 border border-exo-light-gray/20 rounded px-2 py-1.5 text-white font-mono text-xs focus:border-exo-yellow/50 focus:outline-none"
/>
</div>
</div>
<IntegrationCard
title="Config File"
subtitle="~/.codex/config.toml"
description="Add this to your Codex CLI config so the model and provider persist."
config={codexConfig}
/>
<IntegrationCard
title="Shell Command"
subtitle="Run in terminal"
description="Launch Codex with exo as the backend."
config={codexShellCommand}
language="bash"
/>
{:else if activeTab === "OpenClaw"}
{#if runningModels.length > 1}
<div class="text-xs">
<span
class="text-exo-light-gray/50 text-[10px] uppercase tracking-wider block mb-1"
>Model</span
>
<select bind:value={openClawModel} class={selectClass}>
{#each runningModels as model}
<option value={model}>{model.split("/").pop()}</option>
{/each}
</select>
</div>
{/if}
<IntegrationCard
title="Config File"
subtitle="~/.openclaw/openclaw.json"
description="Add this to your OpenClaw config. If you haven't installed OpenClaw yet, run: npm install -g openclaw@latest"
config={openClawConfig}
/>
<IntegrationCard
title="Setup Commands"
subtitle="Run in terminal"
description="After saving the config, run these commands to fix metadata and start the gateway."
config={`openclaw doctor --fix${(modelCapabilities[openClawModel] || []).includes("vision") ? `\nopenclaw models set-image exo/${openClawModel}` : ""}\nopenclaw gateway &\nopenclaw dashboard`}
language="bash"
/>
{:else if activeTab === "Open WebUI"}
<IntegrationCard
title="1. Start Open WebUI"
subtitle="Run in terminal"
description="Run this to start Open WebUI."
config={openWebUiCommand}
language="bash"
/>
<IntegrationCard
title="2. Open & Select Model"
subtitle="http://localhost:3000"
description={`Open http://localhost:3000 in your browser. Select the running model from the dropdown at the top: ${runningModels.length > 0 ? runningModels.join(", ") : "no models running"}`}
config={"open http://localhost:3000"}
language="bash"
/>
<IntegrationCard
title="Ollama CLI"
subtitle="Run in terminal"
description="Or use the Ollama CLI directly."
config={ollamaCommand}
language="bash"
/>
{:else if activeTab === "n8n"}
<IntegrationCard
title="1. Start n8n"
subtitle="Run in terminal"
description="Start n8n with Docker. If you already have n8n running, skip this step."
config={n8nDockerCommand}
language="bash"
/>
<IntegrationCard
title="2. Open n8n"
subtitle="http://localhost:5678"
description="Open n8n in your browser. If this is your first time, complete the setup and select 'Start from Scratch' when prompted."
config={"open http://localhost:5678"}
language="bash"
/>
<IntegrationCard
title="3. Add OpenAI Credential"
subtitle="n8n UI → Credentials"
description="Create an OpenAI credential pointing at your exo cluster."
config={n8nCredentialSteps}
/>
<IntegrationCard
title="4. Build a Workflow"
subtitle="n8n UI → Workflows"
description="Create a workflow that uses your exo-powered model."
config={n8nWorkflowSteps}
/>
{:else if activeTab === "Firefox"}
<IntegrationCard
title="Firefox AI Chatbot"
subtitle="about:config"
description="Use the exo dashboard as Firefox's built-in AI chatbot. Requires Firefox 130+."
config={firefoxConfig}
/>
{/if}
</div>
</main>
</div>
+3 -90
View File
@@ -3,7 +3,6 @@
import {
listTraces,
getTraceRawUrl,
deleteTraces,
type TraceListItem,
} from "$lib/stores/app.svelte";
import HeaderNav from "$lib/components/HeaderNav.svelte";
@@ -11,51 +10,6 @@
let traces = $state<TraceListItem[]>([]);
let loading = $state(true);
let error = $state<string | null>(null);
let selectedIds = $state<Set<string>>(new Set());
let deleting = $state(false);
let allSelected = $derived(
traces.length > 0 && selectedIds.size === traces.length,
);
function toggleSelect(taskId: string) {
const next = new Set(selectedIds);
if (next.has(taskId)) {
next.delete(taskId);
} else {
next.add(taskId);
}
selectedIds = next;
}
function toggleSelectAll() {
if (allSelected) {
selectedIds = new Set();
} else {
selectedIds = new Set(traces.map((t) => t.taskId));
}
}
async function handleDelete() {
if (selectedIds.size === 0) return;
const count = selectedIds.size;
if (
!confirm(
`Delete ${count} trace${count === 1 ? "" : "s"}? This cannot be undone.`,
)
)
return;
deleting = true;
try {
await deleteTraces([...selectedIds]);
selectedIds = new Set();
await refresh();
} catch (e) {
error = e instanceof Error ? e.message : "Failed to delete traces";
} finally {
deleting = false;
}
}
function formatBytes(bytes: number): string {
if (!bytes || bytes <= 0) return "0B";
@@ -155,16 +109,6 @@
</h1>
</div>
<div class="flex items-center gap-3">
{#if selectedIds.size > 0}
<button
type="button"
class="text-xs font-mono text-red-400 hover:text-red-300 transition-colors uppercase border border-red-500/40 px-2 py-1 rounded"
onclick={handleDelete}
disabled={deleting}
>
{deleting ? "Deleting..." : `Delete (${selectedIds.size})`}
</button>
{/if}
<button
type="button"
class="text-xs font-mono text-exo-light-gray hover:text-exo-yellow transition-colors uppercase border border-exo-medium-gray/40 px-2 py-1 rounded"
@@ -199,41 +143,14 @@
</div>
{:else}
<div class="space-y-3">
<div class="flex items-center gap-2 px-1">
<button
type="button"
class="text-xs font-mono uppercase transition-colors {allSelected
? 'text-exo-yellow'
: 'text-exo-light-gray hover:text-exo-yellow'}"
onclick={toggleSelectAll}
>
{allSelected ? "Deselect all" : "Select all"}
</button>
</div>
{#each traces as trace}
{@const isSelected = selectedIds.has(trace.taskId)}
<!-- svelte-ignore a11y_no_static_element_interactions -->
<div
role="button"
tabindex="0"
class="w-full text-left rounded border-l-2 border-r border-t border-b transition-all p-4 flex items-center justify-between gap-4 cursor-pointer {isSelected
? 'bg-exo-yellow/10 border-l-exo-yellow border-r-exo-medium-gray/30 border-t-exo-medium-gray/30 border-b-exo-medium-gray/30'
: 'bg-exo-black/30 border-l-transparent border-r-exo-medium-gray/30 border-t-exo-medium-gray/30 border-b-exo-medium-gray/30 hover:bg-white/[0.03]'}"
onclick={() => toggleSelect(trace.taskId)}
onkeydown={(e) => {
if (e.key === "Enter" || e.key === " ") {
e.preventDefault();
toggleSelect(trace.taskId);
}
}}
class="rounded border border-exo-medium-gray/30 bg-exo-black/30 p-4 flex items-center justify-between gap-4"
>
<div class="min-w-0 flex-1">
<a
href="#/traces/{trace.taskId}"
class="text-sm font-mono transition-colors truncate block {isSelected
? 'text-exo-yellow'
: 'text-white hover:text-exo-yellow'}"
onclick={(e) => e.stopPropagation()}
class="text-sm font-mono text-white hover:text-exo-yellow transition-colors truncate block"
>
{trace.taskId}
</a>
@@ -243,11 +160,7 @@
)}
</div>
</div>
<!-- svelte-ignore a11y_click_events_have_key_events -->
<div
class="flex items-center gap-2 shrink-0"
onclick={(e) => e.stopPropagation()}
>
<div class="flex items-center gap-2 shrink-0">
<a
href="#/traces/{trace.taskId}"
class="text-xs font-mono text-exo-light-gray hover:text-exo-yellow transition-colors uppercase border border-exo-medium-gray/40 px-2 py-1 rounded"
+23 -475
View File
@@ -4,7 +4,7 @@ This document describes the REST API exposed by the **EXO** service, as implemen
`src/exo/master/api.py`
The API is used to manage model instances in the cluster, inspect cluster state, and perform inference using multiple API-compatible interfaces.
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:
@@ -144,59 +144,8 @@ Placement result.
Returns the list of available models and their metadata.
**Query parameters:**
* `status`: string (optional) - Filter by `downloaded` to show only downloaded models
**Response:**
Array of model descriptors including `is_custom` field for custom HuggingFace models.
### Add Custom Model
**POST** `/models/add`
Add a custom model from HuggingFace hub.
**Request body (example):**
```json
{
"model_id": "mlx-community/my-custom-model"
}
```
**Response:**
Model descriptor for the added model.
**Security note:**
Models with `trust_remote_code` enabled in their configuration require explicit opt-in (default is false) for security.
### Delete Custom Model
**DELETE** `/models/custom/{model_id}`
Delete a user-added custom model card.
**Path parameters:**
* `model_id`: string, ID of the custom model to delete
**Response:**
Confirmation JSON with deleted model ID.
### Search Models
**GET** `/models/search`
Search HuggingFace Hub for mlx-community models.
**Query parameters:**
* `query`: string (optional) - Search query
* `limit`: integer (default: 20) - Maximum number of results
**Response:**
Array of HuggingFace model search results.
Array of model descriptors.
## 4. Inference / Chat Completions
@@ -219,123 +168,9 @@ Executes a chat completion request using an OpenAI-compatible schema. Supports s
}
```
**Request parameters:**
* `model`: string, required - Model ID to use
* `messages`: array, required - Conversation messages
* `stream`: boolean (default: false) - Enable streaming responses
* `max_tokens`: integer (optional) - Maximum tokens to generate
* `temperature`: float (optional) - Sampling temperature
* `top_p`: float (optional) - Nucleus sampling parameter
* `top_k`: integer (optional) - Top-k sampling parameter
* `stop`: string or array (optional) - Stop sequences
* `seed`: integer (optional) - Random seed for reproducibility
* `enable_thinking`: boolean (optional) - Enable thinking mode for capable models (DeepSeek V3.1, Qwen3, GLM-4.7)
* `tools`: array (optional) - Tool definitions for function calling
* `logprobs`: boolean (optional) - Return log probabilities
* `top_logprobs`: integer (optional) - Number of top log probabilities to return
**Response:**
OpenAI-compatible chat completion response.
**Streaming response format:**
When `stream=true`, returns Server-Sent Events (SSE) with format:
```
data: {"id":"...","object":"chat.completion","created":...,"model":"...","choices":[...]}
data: [DONE]
```
**Non-streaming response includes usage statistics:**
```json
{
"id": "...",
"object": "chat.completion",
"created": 1234567890,
"model": "llama-3.2-1b",
"choices": [{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! How can I help you?"
},
"finish_reason": "stop"
}],
"usage": {
"prompt_tokens": 15,
"completion_tokens": 8,
"total_tokens": 23
}
}
```
**Cancellation:**
You can cancel an active generation by closing the HTTP connection. The server detects the disconnection and stops processing.
### Claude Messages API
**POST** `/v1/messages`
Executes a chat completion request using the Claude Messages API format. Supports streaming and non-streaming modes.
**Request body (example):**
```json
{
"model": "llama-3.2-1b",
"messages": [
{ "role": "user", "content": "Hello" }
],
"max_tokens": 1024,
"stream": false
}
```
**Streaming response format:**
When `stream=true`, returns Server-Sent Events with Claude-specific event types:
* `message_start` - Message generation started
* `content_block_start` - Content block started
* `content_block_delta` - Incremental content chunk
* `content_block_stop` - Content block completed
* `message_delta` - Message metadata updates
* `message_stop` - Message generation completed
**Response:**
Claude-compatible messages response.
### OpenAI Responses API
**POST** `/v1/responses`
Executes a chat completion request using the OpenAI Responses API format. Supports streaming and non-streaming modes.
**Request body (example):**
```json
{
"model": "llama-3.2-1b",
"messages": [
{ "role": "user", "content": "Hello" }
],
"stream": false
}
```
**Streaming response format:**
When `stream=true`, returns Server-Sent Events with response-specific event types:
* `response.created` - Response generation started
* `response.in_progress` - Response is being generated
* `response.output_item.added` - New output item added
* `response.output_item.done` - Output item completed
* `response.done` - Response generation completed
**Response:**
OpenAI Responses API-compatible response.
### Benchmarked Chat Completions
**POST** `/bench/chat/completions`
@@ -346,177 +181,26 @@ Same as `/v1/chat/completions`, but also returns performance and generation stat
Same schema as `/v1/chat/completions`.
**Response:**
Chat completion plus benchmarking metrics including:
Chat completion plus benchmarking metrics.
* `prompt_tps` - Tokens per second during prompt processing
* `generation_tps` - Tokens per second during generation
* `prompt_tokens` - Number of prompt tokens
* `generation_tokens` - Number of generated tokens
* `peak_memory_usage` - Peak memory used during generation
### Cancel Command
**POST** `/v1/cancel/{command_id}`
Cancels an active generation command (text or image). Notifies workers and closes the stream.
**Path parameters:**
* `command_id`: string, ID of the command to cancel
**Response (example):**
```json
{
"message": "Command cancelled.",
"command_id": "cmd-abc-123"
}
```
Returns 404 if the command is not found or already completed.
## 5. Ollama API Compatibility
EXO provides Ollama API compatibility for tools like OpenWebUI.
### Ollama Chat
**POST** `/ollama/api/chat`
**POST** `/ollama/api/api/chat` (alias)
**POST** `/ollama/api/v1/chat` (alias)
Execute a chat request using Ollama API format.
**Request body (example):**
```json
{
"model": "llama-3.2-1b",
"messages": [
{ "role": "user", "content": "Hello" }
],
"stream": false
}
```
**Response:**
Ollama-compatible chat response.
### Ollama Generate
**POST** `/ollama/api/generate`
Execute a text generation request using Ollama API format.
**Request body (example):**
```json
{
"model": "llama-3.2-1b",
"prompt": "Hello",
"stream": false
}
```
**Response:**
Ollama-compatible generation response.
### Ollama Tags
**GET** `/ollama/api/tags`
**GET** `/ollama/api/api/tags` (alias)
**GET** `/ollama/api/v1/tags` (alias)
Returns list of downloaded models in Ollama tags format.
**Response:**
Array of model tags with metadata.
### Ollama Show
**POST** `/ollama/api/show`
Returns model information in Ollama show format.
**Request body:**
```json
{
"name": "llama-3.2-1b"
}
```
**Response:**
Model details including modelfile and family.
### Ollama PS
**GET** `/ollama/api/ps`
Returns list of running models (active instances).
**Response:**
Array of active model instances.
### Ollama Version
**GET** `/ollama/api/version`
**HEAD** `/ollama/` (alias)
**HEAD** `/ollama/api/version` (alias)
Returns version information for Ollama API compatibility.
**Response:**
```json
{
"version": "exo v1.0"
}
```
## 6. Image Generation & Editing
## 5. Image Generation & Editing
### Image Generation
**POST** `/v1/images/generations`
Executes an image generation request using an OpenAI-compatible schema with additional advanced_params. Supports both streaming and non-streaming modes.
Executes an image generation request using an OpenAI-compatible schema with additional advanced_params.
**Request body (example):**
```json
{
"prompt": "a robot playing chess",
"model": "exolabs/FLUX.1-dev",
"n": 1,
"size": "1024x1024",
"model": "flux-dev",
"stream": false,
"response_format": "b64_json"
}
```
**Request parameters:**
* `prompt`: string, required - Text description of the image
* `model`: string, required - Image model ID
* `n`: integer (default: 1) - Number of images to generate
* `size`: string (default: "auto") - Image dimensions. Supported sizes:
- `512x512`
- `768x768`
- `1024x768`
- `768x1024`
- `1024x1024`
- `1024x1536`
- `1536x1024`
- `1024x1365`
- `1365x1024`
* `stream`: boolean (default: false) - Enable streaming for partial images
* `partial_images`: integer (default: 0) - Number of partial images to stream during generation
* `response_format`: string (default: "b64_json") - Either `url` or `b64_json`
* `quality`: string (default: "medium") - Either `high`, `medium`, or `low`
* `output_format`: string (default: "png") - Either `png`, `jpeg`, or `webp`
* `advanced_params`: object (optional) - Advanced generation parameters
**Advanced Parameters (`advanced_params`):**
| Parameter | Type | Constraints | Description |
@@ -526,54 +210,8 @@ Executes an image generation request using an OpenAI-compatible schema with addi
| `guidance` | float | 1.0-20.0 | Classifier-free guidance scale |
| `negative_prompt` | string | - | Text describing what to avoid in the image |
**Non-streaming response:**
```json
{
"created": 1234567890,
"data": [
{
"b64_json": "iVBORw0KGgoAAAANSUhEUgAA...",
"url": null
}
]
}
```
**Streaming response format:**
When `stream=true` and `partial_images > 0`, returns Server-Sent Events:
```
data: {"type":"partial","image_index":0,"partial_index":1,"total_partials":5,"format":"png","data":{"b64_json":"..."}}
data: {"type":"final","image_index":0,"format":"png","data":{"b64_json":"..."}}
data: [DONE]
```
### Image Editing
**POST** `/v1/images/edits`
Executes an image editing request (img2img) using FLUX.1-Kontext-dev or similar models.
**Request (multipart/form-data):**
* `image`: file, required - Input image to edit
* `prompt`: string, required - Text description of desired changes
* `model`: string, required - Image editing model ID (e.g., `exolabs/FLUX.1-Kontext-dev`)
* `n`: integer (default: 1) - Number of edited images to generate
* `size`: string (optional) - Output image dimensions
* `response_format`: string (default: "b64_json") - Either `url` or `b64_json`
* `input_fidelity`: string (default: "low") - Either `low` or `high` - Controls how closely the output follows the input image
* `stream`: string (default: "false") - Enable streaming
* `partial_images`: string (default: "0") - Number of partial images to stream
* `quality`: string (default: "medium") - Either `high`, `medium`, or `low`
* `output_format`: string (default: "png") - Either `png`, `jpeg`, or `webp`
* `advanced_params`: string (optional) - JSON-encoded advanced parameters
**Response:**
Same format as `/v1/images/generations`.
OpenAI-compatible image generation response.
### Benchmarked Image Generation
@@ -585,15 +223,16 @@ Same as `/v1/images/generations`, but also returns generation statistics.
Same schema as `/v1/images/generations`.
**Response:**
Image generation plus benchmarking metrics including:
Image generation plus benchmarking metrics.
* `seconds_per_step` - Average time per denoising step
* `total_generation_time` - Total generation time
* `num_inference_steps` - Number of inference steps used
* `num_images` - Number of images generated
* `image_width` - Output image width
* `image_height` - Output image height
* `peak_memory_usage` - Peak memory used during generation
### Image Editing
**POST** `/v1/images/edits`
Executes an image editing request using an OpenAI-compatible schema with additional advanced_params (same as `/v1/images/generations`).
**Response:**
Same format as `/v1/images/generations`.
### Benchmarked Image Editing
@@ -607,127 +246,36 @@ Same schema as `/v1/images/edits`.
**Response:**
Same format as `/bench/images/generations`, including `generation_stats`.
### List Images
**GET** `/images`
List all stored images.
**Response:**
Array of image metadata including URLs and expiration times.
### Get Image
**GET** `/images/{image_id}`
Retrieve a stored image by ID.
**Path parameters:**
* `image_id`: string, ID of the image
**Response:**
Image file with appropriate content type.
## 7. Complete Endpoint Summary
## 6. Complete Endpoint Summary
```
# General
GET /node_id
GET /state
GET /events
# Instance Management
POST /instance
GET /instance/{instance_id}
DELETE /instance/{instance_id}
GET /instance/previews
GET /instance/placement
POST /place_instance
# Models
GET /models
GET /v1/models
POST /models/add
DELETE /models/custom/{model_id}
GET /models/search
# Text Generation (OpenAI Chat Completions)
POST /v1/chat/completions
POST /bench/chat/completions
# Text Generation (Claude Messages API)
POST /v1/messages
# Text Generation (OpenAI Responses API)
POST /v1/responses
# Text Generation (Ollama API)
POST /ollama/api/chat
POST /ollama/api/api/chat
POST /ollama/api/v1/chat
POST /ollama/api/generate
GET /ollama/api/tags
GET /ollama/api/api/tags
GET /ollama/api/v1/tags
POST /ollama/api/show
GET /ollama/api/ps
GET /ollama/api/version
HEAD /ollama/
HEAD /ollama/api/version
# Command Control
POST /v1/cancel/{command_id}
# Image Generation
POST /v1/images/generations
POST /bench/images/generations
POST /v1/images/edits
POST /bench/images/edits
GET /images
GET /images/{image_id}
```
## 8. Notes
## 7. Notes
### API Compatibility
EXO provides multiple API-compatible interfaces:
* **OpenAI Chat Completions API** - Compatible with OpenAI clients and tools
* **Claude Messages API** - Compatible with Anthropic's Claude API format
* **OpenAI Responses API** - Compatible with OpenAI's Responses API format
* **Ollama API** - Compatible with Ollama and tools like OpenWebUI
Existing OpenAI, Claude, or Ollama clients can be pointed to EXO by changing the base URL.
### Custom Models
You can add custom models from HuggingFace using the `/models/add` endpoint. Custom models are identified by the `is_custom` field in model list responses.
**Security:** Models requiring `trust_remote_code` must be explicitly enabled (default is false) for security. Only enable this if you trust the model's remote code.
### Usage Statistics
Chat completion responses include usage statistics with:
* `prompt_tokens` - Number of tokens in the prompt
* `completion_tokens` - Number of tokens generated
* `total_tokens` - Sum of prompt and completion tokens
### Request Cancellation
You can cancel active requests by:
1. Closing the HTTP connection (for streaming requests)
2. Calling `/v1/cancel/{command_id}` (for any request)
The server detects cancellation and stops processing immediately.
### Instance Placement
The instance placement endpoints allow you to plan and preview cluster allocations before creating instances. This helps optimize resource usage across nodes.
### Observability
The `/events` and `/state` endpoints are primarily intended for operational visibility and debugging.
* The `/v1/chat/completions` endpoint is compatible with the OpenAI Chat API format, so existing OpenAI clients can be pointed to EXO by changing the base URL.
* The `/v1/images/generations` and `/v1/images/edits` endpoints are compatible with the OpenAI Images API format.
* 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.
-20
View File
@@ -28,26 +28,6 @@ There are currently 5 major systems:
Implements a distributed algorithm for master election in unstable networking conditions
## API Layer
The API system uses multiple adapters to support multiple API formats, converting them to a single request / response type.
### Adapter Pattern
Adapters convert between external API formats and EXO's internal types:
```
Chat Completions → [adapter] → TextGenerationTaskParams → Application
Claude Messages → [adapter] → TextGenerationTaskParams → Application
Responses API → [adapter] → TextGenerationTaskParams → Application
Ollama API → [adapter] → TextGenerationTaskParams → Application
```
Each adapter implements two key functions:
1. **Request conversion**: Converts API-specific requests to `TextGenerationTaskParams`
2. **Response generation**: Converts internal `TokenChunk` streams back to API-specific formats (streaming and non-streaming)
## Topics
There are currently 5 topics:
Generated
+9 -9
View File
@@ -164,11 +164,11 @@
]
},
"locked": {
"lastModified": 1773870109,
"narHash": "sha256-ZoTdqZP03DcdoyxvpFHCAek4bkPUTUPUF3oCCgc3dP4=",
"lastModified": 1763662255,
"narHash": "sha256-4bocaOyLa3AfiS8KrWjZQYu+IAta05u3gYZzZ6zXbT0=",
"owner": "pyproject-nix",
"repo": "build-system-pkgs",
"rev": "b6e74f433b02fa4b8a7965ee24680f4867e2926f",
"rev": "042904167604c681a090c07eb6967b4dd4dae88c",
"type": "github"
},
"original": {
@@ -184,11 +184,11 @@
]
},
"locked": {
"lastModified": 1774498001,
"narHash": "sha256-wTfdyzzrmpuqt4TQQNqilF91v0m5Mh1stNy9h7a/WK4=",
"lastModified": 1764134915,
"narHash": "sha256-xaKvtPx6YAnA3HQVp5LwyYG1MaN4LLehpQI8xEdBvBY=",
"owner": "pyproject-nix",
"repo": "pyproject.nix",
"rev": "794afa6eb588b498344f2eaa36ab1ceb7e6b0b09",
"rev": "2c8df1383b32e5443c921f61224b198a2282a657",
"type": "github"
},
"original": {
@@ -280,11 +280,11 @@
]
},
"locked": {
"lastModified": 1774490495,
"narHash": "sha256-a9WmQWj8fF7BctZGCoyzpUjP6GJw8H+lxl+zxpGnETk=",
"lastModified": 1767701098,
"narHash": "sha256-CJhKZnWb3gumR9oTRjFvCg/6lYTGbZRU7xtvcyWIRwU=",
"owner": "pyproject-nix",
"repo": "uv2nix",
"rev": "18ae62fc5e389e3069854a7c66455c22e31708fc",
"rev": "9d357f0d2ce6f5f35ec7959d7e704452352eb4da",
"type": "github"
},
"original": {
+3 -15
View File
@@ -72,8 +72,9 @@
];
perSystem =
{ config, self', pkgs, lib, system, ... }:
{ config, self', inputs', pkgs, lib, system, ... }:
let
fenixToolchain = inputs'.fenix.packages.complete;
# Use pinned nixpkgs for swift-format (swift is broken on x86_64-linux in newer nixpkgs)
pkgsSwift = import inputs.nixpkgs-swift { inherit system; };
in
@@ -84,17 +85,6 @@
config.allowUnfreePredicate = pkg: (pkg.pname or "") == "metal-toolchain";
overlays = [
(import ./nix/apple-sdk-overlay.nix)
(final: prev: {
macmon = prev.macmon.overrideAttrs (_: {
version = "git";
src = final.fetchFromGitHub {
owner = "swiftraccoon";
repo = "macmon";
rev = "9154d234f763fbeffdcb4135d0bbbaf80609699b";
hash = "sha256-CwhilKNbs5XL9/tF5DMwyPBlE/hpmjGNTuxQ36sM50M=";
};
});
})
];
};
treefmt = {
@@ -119,7 +109,6 @@
package = pkgsSwift.swiftPackages.swift-format;
};
shfmt.enable = true;
taplo.enable = true;
};
};
@@ -128,13 +117,12 @@
uvLock = builtins.fromTOML (builtins.readFile ./uv.lock);
mlxPackage = builtins.head (builtins.filter (p: p.name == "mlx" && p.source ? git) uvLock.package);
uvLockMlxVersion = mlxPackage.version;
uvLockMlxRev = builtins.elemAt (builtins.split "#" mlxPackage.source.git) 2;
in
{
metal-toolchain = pkgs.callPackage ./nix/metal-toolchain.nix { };
mlx = pkgs.callPackage ./nix/mlx.nix {
inherit (self'.packages) metal-toolchain;
inherit uvLockMlxVersion uvLockMlxRev;
inherit uvLockMlxVersion;
};
default = self'.packages.exo;
}
-7
View File
@@ -1,8 +1,5 @@
export NIX_CONFIG := "extra-experimental-features = nix-command flakes"
default: lint fmt
all: lint fmt check
fmt:
treefmt || nix fmt
@@ -34,10 +31,6 @@ build-dashboard:
package:
uv run pyinstaller packaging/pyinstaller/exo.spec
build-app: package
xcodebuild build -project app/EXO/EXO.xcodeproj -scheme EXO -configuration Debug -derivedDataPath app/EXO/build
@echo "\nBuild complete. Run with:\n open {{justfile_directory()}}/app/EXO/build/Build/Products/Debug/EXO.app"
clean:
rm -rf **/__pycache__
rm -rf target/
+5 -4
View File
@@ -11,7 +11,6 @@
, fmt
, python313Packages
, uvLockMlxVersion
, uvLockMlxRev
}:
assert stdenv.isDarwin;
@@ -42,14 +41,16 @@ let
mlx = stdenv.mkDerivation rec {
pname = "mlx";
version = uvLockMlxVersion;
version = let v = "0.30.7.dev20260218+14841977"; in
assert v == uvLockMlxVersion || throw "MLX version mismatch: nix/mlx.nix has ${v} but uv.lock has ${uvLockMlxVersion}. Update both the version and hash in nix/mlx.nix.";
v;
pyproject = true;
src = fetchFromGitHub {
owner = "rltakashige";
repo = "mlx-jaccl-fix-small-recv";
rev = uvLockMlxRev;
hash = "sha256-GosFIWxIB48Egb1MqJrR3xhsUsQeWdRk5rV93USY6wQ=";
rev = "1484197707f35186ad3bd614357c7c47fdf86ebc";
hash = "sha256-FupCMoK/SF/ldfKuvMSAKECcOP8c+ANgkQlPZttDsLk=";
};
patches = [
Binary file not shown.

Before

Width:  |  Height:  |  Size: 6.8 KiB

-112
View File
@@ -1,112 +0,0 @@
#!/usr/bin/env bash
# create-dmg.sh — Build a polished macOS DMG installer for EXO
#
# Usage:
# ./packaging/dmg/create-dmg.sh <app-path> <output-dmg> [volume-name]
#
# Example:
# ./packaging/dmg/create-dmg.sh output/EXO.app EXO-1.0.0.dmg "EXO"
#
# Creates a DMG with:
# - Custom background image with drag-to-Applications arrow
# - App icon on left, Applications alias on right
# - Proper window size and icon positioning
set -euo pipefail
APP_PATH="${1:?Usage: create-dmg.sh <app-path> <output-dmg> [volume-name]}"
OUTPUT_DMG="${2:?Usage: create-dmg.sh <app-path> <output-dmg> [volume-name]}"
VOLUME_NAME="${3:-EXO}"
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
BACKGROUND_SCRIPT="${SCRIPT_DIR}/generate-background.py"
TEMP_DIR="$(mktemp -d)"
DMG_STAGING="${TEMP_DIR}/dmg-root"
TEMP_DMG="${TEMP_DIR}/temp.dmg"
BACKGROUND_PNG="${TEMP_DIR}/background.png"
cleanup() { rm -rf "$TEMP_DIR"; }
trap cleanup EXIT
echo "==> Creating DMG installer for ${VOLUME_NAME}"
# ── Step 1: Generate background image ────────────────────────────────────────
if command -v python3 &>/dev/null; then
python3 "$BACKGROUND_SCRIPT" "$BACKGROUND_PNG"
echo " Background image generated"
else
echo " Warning: python3 not found, skipping custom background"
BACKGROUND_PNG=""
fi
# ── Step 2: Prepare staging directory ─────────────────────────────────────────
mkdir -p "$DMG_STAGING"
cp -R "$APP_PATH" "$DMG_STAGING/"
ln -s /Applications "$DMG_STAGING/Applications"
# ── Step 3: Create writable DMG ──────────────────────────────────────────────
# Calculate required size (app size + 20MB headroom)
APP_SIZE_KB=$(du -sk "$APP_PATH" | cut -f1)
DMG_SIZE_KB=$((APP_SIZE_KB + 20480))
hdiutil create \
-volname "$VOLUME_NAME" \
-size "${DMG_SIZE_KB}k" \
-fs HFS+ \
-layout SPUD \
"$TEMP_DMG"
# ── Step 4: Mount and configure ──────────────────────────────────────────────
MOUNT_DIR=$(hdiutil attach "$TEMP_DMG" -readwrite -noverify | awk -F'\t' '/Apple_HFS/ {gsub(/^[[:space:]]+|[[:space:]]+$/, "", $NF); print $NF}')
echo " Mounted at: $MOUNT_DIR"
# Copy contents
cp -R "$DMG_STAGING/"* "$MOUNT_DIR/"
# Add background image
if [[ -n $BACKGROUND_PNG && -f $BACKGROUND_PNG ]]; then
mkdir -p "$MOUNT_DIR/.background"
cp "$BACKGROUND_PNG" "$MOUNT_DIR/.background/background.png"
fi
# ── Step 5: Configure window appearance via AppleScript ──────────────────────
# Window: 800×400, app icon on left, Applications on right (matches Ollama layout)
# Background image is 1600×740 (2× retina for 800×400 logical window).
APP_NAME="$(basename "$APP_PATH")"
osascript <<APPLESCRIPT
tell application "Finder"
tell disk "$VOLUME_NAME"
open
set current view of container window to icon view
set toolbar visible of container window to false
set statusbar visible of container window to false
set bounds of container window to {200, 120, 1000, 520}
set opts to icon view options of container window
set icon size of opts to 128
set text size of opts to 12
set arrangement of opts to not arranged
if exists file ".background:background.png" then
set background picture of opts to file ".background:background.png"
end if
set position of item "$APP_NAME" of container window to {200, 190}
set position of item "Applications" of container window to {600, 190}
close
open
update without registering applications
delay 1
close
end tell
end tell
APPLESCRIPT
echo " Window layout configured"
# Ensure Finder updates are flushed
sync
# ── Step 6: Finalise ─────────────────────────────────────────────────────────
hdiutil detach "$MOUNT_DIR" -quiet
hdiutil convert "$TEMP_DMG" -format UDZO -imagekey zlib-level=9 -o "$OUTPUT_DMG"
echo "==> DMG created: $OUTPUT_DMG"
echo " Size: $(du -h "$OUTPUT_DMG" | cut -f1)"
-91
View File
@@ -1,91 +0,0 @@
#!/usr/bin/env python3
"""Generate the DMG background image with a centered drag-to-Applications arrow.
The output is a 1600×740 retina PNG (2× for 800×400 logical window).
Icons are positioned at (200, 190) and (600, 190) in logical coordinates;
the arrow is drawn centered between them.
Usage:
python3 generate-background.py [output.png]
If no output path is given, overwrites the bundled background.png in-place.
"""
from __future__ import annotations
import math
import sys
from pathlib import Path
from PIL import Image, ImageDraw
# Retina dimensions (2× logical 800×400)
WIDTH = 1600
HEIGHT = 740
# Icon positions in logical coords → retina coords
# App icon at (200, 190), Applications at (600, 190)
APP_X = 200 * 2 # 400
APPS_X = 600 * 2 # 1200
ICON_Y = 190 * 2 # 380
# Arrow drawn between icons, slightly above icon center
ARROW_START_X = APP_X + 160 # past the icon
ARROW_END_X = APPS_X - 160 # before the Applications icon
ARROW_Y = ICON_Y # same height as icons
ARROW_RISE = 120 # upward arc height
def draw_arrow(draw: ImageDraw.ImageDraw) -> None:
"""Draw a hand-drawn-style curved arrow from app icon toward Applications."""
color = (30, 30, 30)
line_width = 8
# Compute bezier curve points for a gentle upward arc
points: list[tuple[float, float]] = []
steps = 80
for i in range(steps + 1):
t = i / steps
# Quadratic bezier: start → control → end
cx = (ARROW_START_X + ARROW_END_X) / 2
cy = ARROW_Y - ARROW_RISE
x = (1 - t) ** 2 * ARROW_START_X + 2 * (1 - t) * t * cx + t**2 * ARROW_END_X
y = (1 - t) ** 2 * ARROW_Y + 2 * (1 - t) * t * cy + t**2 * ARROW_Y
points.append((x, y))
# Draw the curve as connected line segments
for i in range(len(points) - 1):
draw.line([points[i], points[i + 1]], fill=color, width=line_width)
# Arrowhead at the end
end_x, end_y = points[-1]
# Direction from second-to-last to last point
prev_x, prev_y = points[-3]
angle = math.atan2(end_y - prev_y, end_x - prev_x)
head_len = 36
head_angle = math.radians(25)
left_x = end_x - head_len * math.cos(angle - head_angle)
left_y = end_y - head_len * math.sin(angle - head_angle)
right_x = end_x - head_len * math.cos(angle + head_angle)
right_y = end_y - head_len * math.sin(angle + head_angle)
draw.polygon(
[(end_x, end_y), (left_x, left_y), (right_x, right_y)],
fill=color,
)
def generate_background(output_path: str) -> None:
"""Generate a white DMG background with a centered arrow."""
img = Image.new("RGBA", (WIDTH, HEIGHT), (255, 255, 255, 255))
draw = ImageDraw.Draw(img)
draw_arrow(draw)
img.save(output_path, "PNG")
if __name__ == "__main__":
default_output = str(Path(__file__).parent / "background.png")
out = sys.argv[1] if len(sys.argv) >= 2 else default_output
generate_background(out)
print(f"Background image written to {out}")
+2 -3
View File
@@ -71,9 +71,7 @@ MACMON_PATH = shutil.which("macmon")
if MACMON_PATH is None:
raise SystemExit(
"macmon binary not found in PATH. "
"Install the pinned fork used by exo via: "
"cargo install --git https://github.com/swiftraccoon/macmon "
"--rev 9154d234f763fbeffdcb4135d0bbbaf80609699b macmon --force"
"Install it via: brew install macmon"
)
BINARIES: list[tuple[str, str]] = [
@@ -122,3 +120,4 @@ coll = COLLECT(
upx_exclude=[],
name="exo",
)
+50 -55
View File
@@ -1,36 +1,33 @@
[project]
name = "exo"
version = "0.3.69"
version = "0.3.0"
description = "Exo"
readme = "README.md"
requires-python = ">=3.13"
dependencies = [
"aiofiles>=24.1.0",
"aiohttp>=3.12.14",
"types-aiofiles>=24.1.0.20250708",
"pydantic>=2.11.7",
"fastapi>=0.116.1",
"filelock>=3.18.0",
"rustworkx>=0.17.1",
"huggingface-hub>=1.8.0",
"psutil>=7.0.0",
"loguru>=0.7.3",
"exo_pyo3_bindings", # rust bindings
"anyio==4.11.0",
"mlx; sys_platform == 'darwin'",
"mlx[cpu]==0.30.6; sys_platform == 'linux'",
"mlx-lm",
"tiktoken>=0.12.0", # required for kimi k2 tokenizer
"hypercorn>=0.18.0",
"openai-harmony>=0.0.8",
"httpx>=0.28.1",
"tomlkit>=0.14.0",
"mflux==0.17.2",
"python-multipart>=0.0.21",
"msgspec>=0.19.0",
"zstandard>=0.23.0",
"mlx-vlm>=0.3.11",
"transformers>=5.0.0,<5.4.0",
"aiofiles>=24.1.0",
"pydantic>=2.11.7",
"fastapi>=0.116.1",
"filelock>=3.18.0",
"rustworkx>=0.17.1",
"huggingface-hub>=0.33.4",
"psutil>=7.0.0",
"loguru>=0.7.3",
"exo_pyo3_bindings", # rust bindings
"anyio==4.11.0",
"mlx; sys_platform == 'darwin'",
"mlx[cpu]==0.30.6; sys_platform == 'linux'",
"mlx-lm==0.30.7",
"tiktoken>=0.12.0", # required for kimi k2 tokenizer
"hypercorn>=0.18.0",
"openai-harmony>=0.0.8",
"httpx>=0.28.1",
"tomlkit>=0.14.0",
"pillow>=11.0,<12.0", # compatibility with mflux
"mflux==0.15.5",
"python-multipart>=0.0.21",
"msgspec>=0.19.0",
"zstandard>=0.23.0",
]
[project.scripts]
@@ -39,12 +36,12 @@ 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",
"pytest-env",
"ruff>=0.11.13",
"basedpyright>=1.29.0",
"pyinstaller>=6.17.0",
"pytest>=8.4.0",
"pytest-asyncio>=1.0.0",
"pytest-env",
"ruff>=0.11.13",
]
# mlx[cuda] requires a newer version of mlx. the ideal on linux is: default to mlx[cpu] unless[cuda] specified.
@@ -58,12 +55,15 @@ dev = [
###
[tool.uv.workspace]
members = ["rust/exo_pyo3_bindings", "bench"]
members = [
"rust/exo_pyo3_bindings",
"bench",
]
[tool.uv.sources]
exo_pyo3_bindings = { workspace = true }
mlx = { git = "https://github.com/rltakashige/mlx-jaccl-fix-small-recv.git", branch = "address-rdma-gpu-locks", marker = "sys_platform == 'darwin'" }
mlx-lm = { git = "https://github.com/rltakashige/mlx-lm", branch = "leo/fix-arrayscache-leak" }
#mlx-lm = { git = "https://github.com/davidmcc73/mlx-lm", branch = "stable" }
# Uncomment to use local mlx/mlx-lm development versions:
# mlx = { path = "/Users/Shared/mlx", editable=true }
# mlx-lm = { path = "/Users/Shared/mlx-lm", editable=true }
@@ -93,15 +93,7 @@ reportUnnecessaryTypeIgnoreComment = "error"
pythonVersion = "3.13"
pythonPlatform = "Darwin"
exclude = [
"**/.venv",
"**/venv",
"**/__pycache__",
"**/exo_scripts",
"**/.direnv",
"**/rust",
"**/.github",
]
exclude = ["**/.venv", "**/venv", "**/__pycache__", "**/exo_scripts", "**/.direnv", "**/rust", "**/.github"]
stubPath = ".mlx_typings"
[[tool.basedpyright.executionEnvironments]]
@@ -115,20 +107,17 @@ root = "src"
[tool.uv]
required-version = ">=0.8.6"
prerelease = "allow"
environments = ["sys_platform == 'darwin'", "sys_platform == 'linux'"]
extra-build-dependencies = { "miniaudio" = ["setuptools", "cffi", "pycparser"] }
environments = [
"sys_platform == 'darwin'",
"sys_platform == 'linux'",
]
###
# ruff configuration
###
[tool.ruff]
extend-exclude = [
"shared/protobufs/**",
"*mlx_typings/**",
"rust/exo_pyo3_bindings/**",
"bench/vendor/**",
]
extend-exclude = ["shared/protobufs/**", "*mlx_typings/**", "rust/exo_pyo3_bindings/**"]
[tool.ruff.lint]
extend-select = ["I", "N", "B", "A", "PIE", "SIM"]
@@ -136,7 +125,13 @@ extend-select = ["I", "N", "B", "A", "PIE", "SIM"]
[tool.pytest.ini_options]
pythonpath = "."
asyncio_mode = "auto"
markers = ["slow: marks tests as slow (deselected by default)"]
env = ["EXO_TESTS=1"]
markers = [
"slow: marks tests as slow (deselected by default)"
]
env = [
"EXO_TESTS=1"
]
addopts = "-m 'not slow' --ignore=tests/start_distributed_test.py"
filterwarnings = ["ignore:builtin type Swig:DeprecationWarning"]
filterwarnings = [
"ignore:builtin type Swig:DeprecationWarning",
]
+2 -28
View File
@@ -43,27 +43,6 @@
final.setuptools
];
});
# rouge-score and sacrebleu don't declare setuptools as a build dependency
rouge-score = prev.rouge-score.overrideAttrs (old: {
nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [
final.setuptools
];
});
sacrebleu = prev.sacrebleu.overrideAttrs (old: {
nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [
final.setuptools
];
});
sqlitedict = prev.sqlitedict.overrideAttrs (old: {
nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [
final.setuptools
];
});
word2number = prev.word2number.overrideAttrs (old: {
nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [
final.setuptools
];
});
} // lib.optionalAttrs pkgs.stdenv.hostPlatform.isDarwin {
# Use our pure Nix-built MLX with Metal support (macOS only)
mlx = self'.packages.mlx;
@@ -117,16 +96,13 @@
"lib/python3.13/site-packages/nvidia*"
];
# Exclude bench deps from main env (bench has its own benchVenv)
exoDeps = removeAttrs workspace.deps.default [ "exo-bench" ];
exoVenv = (pythonSet.mkVirtualEnv "exo-env" exoDeps).overrideAttrs {
exoVenv = (pythonSet.mkVirtualEnv "exo-env" workspace.deps.default).overrideAttrs {
venvIgnoreCollisions = venvCollisionPaths;
};
# Virtual environment with dev dependencies for testing
testVenv = (pythonSet.mkVirtualEnv "exo-test-env" (
exoDeps // {
workspace.deps.default // {
exo = [ "dev" ]; # Include pytest, pytest-asyncio, pytest-env
}
)).overrideAttrs {
@@ -182,8 +158,6 @@
exo-test-env = testVenv;
} // {
exo-bench = mkBenchScript "exo-bench" (inputs.self + /bench/exo_bench.py);
exo-eval = mkBenchScript "exo-eval" (inputs.self + /bench/exo_eval.py);
exo-eval-tool-calls = mkBenchScript "exo-eval-tool-calls" (inputs.self + /bench/eval_tool_calls.py);
exo-get-all-models-on-cluster = mkSimplePythonScript "exo-get-all-models-on-cluster" (inputs.self + /tests/get_all_models_on_cluster.py);
};
@@ -1,15 +1,12 @@
model_id = "mlx-community/DeepSeek-V3.1-4bit"
n_layers = 61
hidden_size = 7168
num_key_value_heads = 128
supports_tensor = true
tasks = ["TextGeneration"]
family = "deepseek"
quantization = "4bit"
base_model = "DeepSeek V3.1"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 131072
capabilities = ["text", "thinking"]
[storage_size]
in_bytes = 405874409472
@@ -1,15 +1,12 @@
model_id = "mlx-community/DeepSeek-V3.1-8bit"
n_layers = 61
hidden_size = 7168
num_key_value_heads = 128
supports_tensor = true
tasks = ["TextGeneration"]
family = "deepseek"
quantization = "8bit"
base_model = "DeepSeek V3.1"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 131072
capabilities = ["text", "thinking"]
[storage_size]
in_bytes = 765577920512
@@ -1,15 +0,0 @@
model_id = "mlx-community/DeepSeek-V3.2-4bit"
n_layers = 61
hidden_size = 7168
num_key_value_heads = 128
supports_tensor = true
tasks = ["TextGeneration"]
family = "deepseek"
quantization = "4bit"
base_model = "DeepSeek V3.2"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 131072
[storage_size]
in_bytes = 378086226621
@@ -1,15 +0,0 @@
model_id = "mlx-community/DeepSeek-V3.2-8bit"
n_layers = 61
hidden_size = 7168
num_key_value_heads = 128
supports_tensor = true
tasks = ["TextGeneration"]
family = "deepseek"
quantization = "8bit"
base_model = "DeepSeek V3.2"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 131072
[storage_size]
in_bytes = 755957120916
@@ -1,15 +1,12 @@
model_id = "mlx-community/GLM-4.5-Air-8bit"
n_layers = 46
hidden_size = 4096
num_key_value_heads = 8
supports_tensor = false
tasks = ["TextGeneration"]
family = "glm"
quantization = "8bit"
base_model = "GLM 4.5 Air"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 131072
capabilities = ["text", "thinking"]
[storage_size]
in_bytes = 122406567936
@@ -1,15 +1,12 @@
model_id = "mlx-community/GLM-4.5-Air-bf16"
n_layers = 46
hidden_size = 4096
num_key_value_heads = 8
supports_tensor = true
tasks = ["TextGeneration"]
family = "glm"
quantization = "bf16"
base_model = "GLM 4.5 Air"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 131072
capabilities = ["text", "thinking"]
[storage_size]
in_bytes = 229780750336
@@ -1,15 +1,12 @@
model_id = "mlx-community/GLM-4.7-4bit"
n_layers = 91
hidden_size = 5120
num_key_value_heads = 8
supports_tensor = true
tasks = ["TextGeneration"]
family = "glm"
quantization = "4bit"
base_model = "GLM 4.7"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 202752
capabilities = ["text", "thinking"]
[storage_size]
in_bytes = 198556925568
@@ -1,15 +1,12 @@
model_id = "mlx-community/GLM-4.7-6bit"
n_layers = 91
hidden_size = 5120
num_key_value_heads = 8
supports_tensor = true
tasks = ["TextGeneration"]
family = "glm"
quantization = "6bit"
base_model = "GLM 4.7"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 202752
capabilities = ["text", "thinking"]
[storage_size]
in_bytes = 286737579648
@@ -1,15 +1,12 @@
model_id = "mlx-community/GLM-4.7-8bit-gs32"
n_layers = 91
hidden_size = 5120
num_key_value_heads = 8
supports_tensor = true
tasks = ["TextGeneration"]
family = "glm"
quantization = "8bit"
base_model = "GLM 4.7"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 202752
capabilities = ["text", "thinking"]
[storage_size]
in_bytes = 396963397248
@@ -1,15 +1,12 @@
model_id = "mlx-community/GLM-4.7-Flash-4bit"
n_layers = 47
hidden_size = 2048
num_key_value_heads = 20
supports_tensor = true
tasks = ["TextGeneration"]
family = "glm"
quantization = "4bit"
base_model = "GLM 4.7 Flash"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 202752
capabilities = ["text", "thinking"]
[storage_size]
in_bytes = 19327352832
@@ -1,15 +1,12 @@
model_id = "mlx-community/GLM-4.7-Flash-5bit"
n_layers = 47
hidden_size = 2048
num_key_value_heads = 20
supports_tensor = true
tasks = ["TextGeneration"]
family = "glm"
quantization = "5bit"
base_model = "GLM 4.7 Flash"
capabilities = ["text", "thinking", "thinking_toggle"]
context_length = 202752
capabilities = ["text", "thinking"]
[storage_size]
in_bytes = 22548578304

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