wah

## Motivation

Fixes #1918. Downloaded model status reverts from "completed" to
"pending" during each download scan. Reproduced with `zai-org/GLM-5.1`.

## Changes

- `coordinator.py`: In the periodic rescan, don't downgrade
already-completed models; fall back to `resolve_existing_model()`
(safetensors weight check) when per-file size check reports incomplete
- New `test_download_status_not_lost.py`: 3 regression tests

## Why It Works

The rescan compares local file sizes against HF's `main` revision. When
HF updates text files (README, jinja, etc.), remote sizes change but
local files still match the old revision — causing a false "incomplete".
The fix uses the safetensors weight check as ground truth instead.

Long-term: pin the downloaded revision SHA rather than always checking
against `main`.

## Test Plan

### Manual Testing

- Mac Studio M3 Ultra with GLM-5.1 downloaded (natural reproduction of
the issue)
- Confirmed GLM-5.1 stays `DownloadCompleted` through multiple rescan
cycles

### Automated Testing

- 3 new tests: completed-not-downgraded, fallback-to-resolve,
genuinely-incomplete-stays-pending

.envrc

@@ -1 +1,8 @@
 use flake
+
+# creates .venv if doesn't exist and loads its environment
+export VIRTUAL_ENV=".venv"
+if ! [ -d "./$VIRTUAL_ENV" ]; then
+  uv venv
+fi
+layout python

.github/workflows/build-app.yml

@@ -159,7 +159,7 @@ jobs:
           fi
 
       - name: Install Homebrew packages
-        run: brew install just awscli macmon
+        run: brew install just awscli
 
       - name: Install UV
         uses: astral-sh/setup-uv@v6
@@ -239,10 +239,92 @@ jobs:
           # Export keychain path for other steps
           echo "BUILD_KEYCHAIN_PATH=$KEYCHAIN_PATH" >> $GITHUB_ENV
 
+      # ============================================================
+      # Pre-flight credential / profile validation
+      # Runs BEFORE the ~16 min build so auth/expiry failures surface in <1 min.
+      # ============================================================
+
+      - name: Validate Apple notarization credentials
+        env:
+          APPLE_NOTARIZATION_USERNAME: ${{ secrets.APPLE_NOTARIZATION_USERNAME }}
+          APPLE_NOTARIZATION_PASSWORD: ${{ secrets.APPLE_NOTARIZATION_PASSWORD }}
+          APPLE_NOTARIZATION_TEAM: ${{ secrets.APPLE_NOTARIZATION_TEAM }}
+        run: |
+          # All-or-nothing: either all three creds are set, or none are.
+          CRED_COUNT=0
+          for v in "$APPLE_NOTARIZATION_USERNAME" "$APPLE_NOTARIZATION_PASSWORD" "$APPLE_NOTARIZATION_TEAM"; do
+            [[ -n "$v" ]] && CRED_COUNT=$((CRED_COUNT + 1))
+          done
+          if [[ "$CRED_COUNT" -eq 0 ]]; then
+            echo "No notarization credentials configured — skipping notarization for this build."
+            exit 0
+          fi
+          if [[ "$CRED_COUNT" -ne 3 ]]; then
+            echo "ERROR: partial notarization credentials set ($CRED_COUNT/3). Aborting before build."
+            exit 1
+          fi
+          # Cheap, ~5s, auth-only call. Fails instantly with a clear message if
+          # the app-specific password is stale, wrong team-id, etc.
+          echo "Verifying Apple notarization credentials via notarytool history..."
+          if ! xcrun notarytool history \
+            --apple-id "$APPLE_NOTARIZATION_USERNAME" \
+            --password "$APPLE_NOTARIZATION_PASSWORD" \
+            --team-id "$APPLE_NOTARIZATION_TEAM" >/dev/null; then
+            echo "ERROR: notarytool rejected the provided credentials. Fix before rerunning."
+            echo "Common causes: app-specific password expired/revoked, wrong team-id,"
+            echo "Apple ID not on the team, or 2FA not configured for this Apple ID."
+            exit 1
+          fi
+          echo "Apple notarization credentials OK."
+
+      - name: Validate provisioning profile expiry
+        run: |
+          PROFILE="$HOME/Library/Developer/Xcode/UserData/Provisioning Profiles/EXO.provisionprofile"
+          if [[ ! -f "$PROFILE" ]]; then
+            echo "ERROR: provisioning profile not found at $PROFILE"
+            exit 1
+          fi
+          EXPIRY=$(security cms -D -i "$PROFILE" | plutil -extract ExpirationDate raw -o - - 2>/dev/null || true)
+          if [[ -z "$EXPIRY" ]]; then
+            echo "WARNING: could not read ExpirationDate from provisioning profile; skipping expiry check."
+            exit 0
+          fi
+          # Try a couple of known plutil date formats. If none parse, skip the check rather
+          # than risk a false-positive "expired" block on a format we didn't anticipate.
+          EXPIRY_EPOCH=""
+          for fmt in "%Y-%m-%dT%H:%M:%SZ" "%Y-%m-%d %H:%M:%S %z" "%Y-%m-%d %H:%M:%S +0000"; do
+            if parsed=$(date -j -f "$fmt" "$EXPIRY" +%s 2>/dev/null); then
+              EXPIRY_EPOCH="$parsed"
+              break
+            fi
+          done
+          if [[ -z "$EXPIRY_EPOCH" ]]; then
+            echo "WARNING: could not parse ExpirationDate '$EXPIRY'; skipping expiry check."
+            exit 0
+          fi
+          NOW_EPOCH=$(date +%s)
+          if [[ "$EXPIRY_EPOCH" -le "$NOW_EPOCH" ]]; then
+            echo "ERROR: provisioning profile expired on $EXPIRY. Regenerate it before rerunning."
+            exit 1
+          fi
+          DAYS_LEFT=$(( (EXPIRY_EPOCH - NOW_EPOCH) / 86400 ))
+          echo "Provisioning profile valid until $EXPIRY ($DAYS_LEFT days remaining)."
+          if [[ "$DAYS_LEFT" -lt 14 ]]; then
+            echo "WARNING: profile expires in under 14 days — regenerate soon."
+          fi
+
       # ============================================================
       # 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
 
@@ -298,11 +380,41 @@ jobs:
           APPLE_NOTARIZATION_PASSWORD: ${{ secrets.APPLE_NOTARIZATION_PASSWORD }}
           APPLE_NOTARIZATION_TEAM: ${{ secrets.APPLE_NOTARIZATION_TEAM }}
         run: |
+          set -o pipefail
           cd output
           security unlock-keychain -p "$MACOS_CERTIFICATE_PASSWORD" "$BUILD_KEYCHAIN_PATH"
           SIGNING_IDENTITY=$(security find-identity -v -p codesigning "$BUILD_KEYCHAIN_PATH" | awk -F '"' '{print $2}')
+
+          # Fail fast if notarization creds are partial. All-or-nothing.
+          CRED_COUNT=0
+          for v in "$APPLE_NOTARIZATION_USERNAME" "$APPLE_NOTARIZATION_PASSWORD" "$APPLE_NOTARIZATION_TEAM"; do
+            [[ -n "$v" ]] && CRED_COUNT=$((CRED_COUNT + 1))
+          done
+          if [[ "$CRED_COUNT" -ne 0 && "$CRED_COUNT" -ne 3 ]]; then
+            echo "ERROR: partial Apple notarization credentials set ($CRED_COUNT/3). Aborting."
+            exit 1
+          fi
+
           /usr/bin/codesign --deep --force --timestamp --options runtime \
             --sign "$SIGNING_IDENTITY" EXO.app
+
+          # Pre-flight: verify the signed app BEFORE building DMG and submitting to Apple.
+          # If this fails, notarization will fail too — cheap way to fail in seconds, not 15 minutes.
+          echo "===== codesign --verify EXO.app ====="
+          if ! /usr/bin/codesign --verify --deep --strict --verbose=2 EXO.app; then
+            echo "ERROR: EXO.app failed codesign verification. Dumping signing status of every executable:"
+            find EXO.app -type f \( -perm -111 -o -name "*.dylib" -o -name "*.so" -o -name "*.framework" \) -print0 |
+              while IFS= read -r -d '' f; do
+                printf -- '--- %s\n' "$f"
+                /usr/bin/codesign -dv --verbose=2 "$f" 2>&1 | sed 's/^/    /' || true
+              done
+            exit 1
+          fi
+
+          # Gatekeeper assessment. A failure here strongly predicts notarization rejection.
+          echo "===== spctl assessment (predicts notarization outcome) ====="
+          /usr/bin/spctl -a -vvv -t install EXO.app || echo "WARNING: spctl assessment failed — notarization is likely to fail too."
+
           mkdir -p dmg-root
           cp -R EXO.app dmg-root/
           ln -s /Applications dmg-root/Applications
@@ -310,12 +422,22 @@ jobs:
           hdiutil create -volname "EXO" -srcfolder dmg-root -ov -format UDZO "$DMG_NAME"
           /usr/bin/codesign --force --timestamp --options runtime \
             --sign "$SIGNING_IDENTITY" "$DMG_NAME"
+
+          echo "===== codesign --verify DMG ====="
+          if ! /usr/bin/codesign --verify --verbose=2 "$DMG_NAME"; then
+            echo "ERROR: DMG failed codesign verification."
+            exit 1
+          fi
+
           if [[ -n "$APPLE_NOTARIZATION_USERNAME" ]]; then
+            echo "===== notarytool submit ====="
+            # `|| true` so set -e doesn't abort before we can echo output / fetch the log.
+            # We rely on the parsed STATUS below to decide pass/fail.
             SUBMISSION_OUTPUT=$(xcrun notarytool submit "$DMG_NAME" \
               --apple-id "$APPLE_NOTARIZATION_USERNAME" \
               --password "$APPLE_NOTARIZATION_PASSWORD" \
               --team-id "$APPLE_NOTARIZATION_TEAM" \
-              --wait --timeout 15m 2>&1)
+              --wait --timeout 15m 2>&1) || true
             echo "$SUBMISSION_OUTPUT"
 
             SUBMISSION_ID=$(echo "$SUBMISSION_OUTPUT" | awk 'tolower($1)=="id:" && $2 ~ /^[0-9a-fA-F-]+$/ {print $2; exit}')

.github/workflows/pipeline.yml

@@ -91,9 +91,6 @@ jobs:
             nix build .#metal-toolchain
           fi
 
-          # Build mlx (depends on metal-toolchain)
-          nix build .#mlx
-
       - name: Build all Nix outputs
         run: |
           nix flake show --json | jq -r '

.gitignore

@@ -38,3 +38,5 @@ bench/**/*.json
 
 # tmp
 tmp/models
+/build/exo
+/.claude/skills

.idea/exo-v2.iml

@@ -1,31 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="EMPTY_MODULE" version="4">
-  <component name="FacetManager">
-    <facet type="Python" name="Python facet">
-      <configuration sdkName="Python 3.13 virtualenv at ~/Desktop/exo/.venv" />
-    </facet>
-  </component>
-  <component name="Go" enabled="true" />
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$">
-      <sourceFolder url="file://$MODULE_DIR$/scripts/src" isTestSource="false" />
-      <sourceFolder url="file://$MODULE_DIR$/src" isTestSource="false" />
-      <sourceFolder url="file://$MODULE_DIR$/rust/exo_pyo3_bindings/src" isTestSource="false" />
-      <sourceFolder url="file://$MODULE_DIR$/rust/exo_pyo3_bindings/tests" isTestSource="true" />
-      <sourceFolder url="file://$MODULE_DIR$/rust/util/src" isTestSource="false" />
-      <sourceFolder url="file://$MODULE_DIR$/rust/networking/examples" isTestSource="false" />
-      <sourceFolder url="file://$MODULE_DIR$/rust/networking/src" isTestSource="false" />
-      <sourceFolder url="file://$MODULE_DIR$/rust/networking/tests" isTestSource="true" />
-      <sourceFolder url="file://$MODULE_DIR$/rust/system_custodian/src" isTestSource="false" />
-      <excludeFolder url="file://$MODULE_DIR$/.venv" />
-      <excludeFolder url="file://$MODULE_DIR$/.direnv" />
-      <excludeFolder url="file://$MODULE_DIR$/build" />
-      <excludeFolder url="file://$MODULE_DIR$/dist" />
-      <excludeFolder url="file://$MODULE_DIR$/.go_cache" />
-      <excludeFolder url="file://$MODULE_DIR$/rust/target" />
-    </content>
-    <orderEntry type="jdk" jdkName="Python 3.13 (exo)" jdkType="Python SDK" />
-    <orderEntry type="sourceFolder" forTests="false" />
-    <orderEntry type="library" name="Python 3.13 virtualenv at ~/Desktop/exo/.venv interpreter library" level="application" />
-  </component>
-</module>

.idea/externalDependencies.xml

@@ -1,6 +1,6 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
   <component name="ExternalDependencies">
-    <plugin id="systems.fehn.intellijdirenv" />
+    <plugin id="al.aoli.intellijdirenv" />
   </component>
 </project>

.idea/inspectionProfiles/Project_Default.xml

@@ -1,14 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <profile version="1.0">
-    <option name="myName" value="Project Default" />
-    <inspection_tool class="PyCompatibilityInspection" enabled="true" level="WARNING" enabled_by_default="true">
-      <option name="ourVersions">
-        <value>
-          <list size="1">
-            <item index="0" class="java.lang.String" itemvalue="3.14" />
-          </list>
-        </value>
-      </option>
-    </inspection_tool>
-  </profile>
-</component>

.idea/misc.xml

@@ -4,7 +4,4 @@
     <option name="sdkName" value="Python 3.13 (exo)" />
   </component>
   <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.13 (exo)" project-jdk-type="Python SDK" />
-  <component name="PythonCompatibilityInspectionAdvertiser">
-    <option name="version" value="3" />
-  </component>
 </project>

.mlx_typings/mlx/nn/layers/quantized.pyi

@@ -2,7 +2,7 @@
 This type stub file was generated by pyright.
 """
 
-from typing import Callable, Optional, Union
+from typing import Any, Callable, Optional, Union
 
 import mlx.core as mx
 from base import Module
@@ -13,8 +13,10 @@ def quantize(
     bits: int = ...,
     *,
     mode: str = ...,
-    class_predicate: Optional[Callable[[str, Module], Union[bool, dict]]] = ...,
-):  # -> None:
+    class_predicate: Optional[
+        Callable[[str, Module], Union[bool, dict[str, Any]]]
+    ] = ...,
+) -> None:
     """Quantize the sub-modules of a module according to a predicate.
 
     By default all layers that define a ``to_quantized(group_size, bits)``

.mlx_typings/mlx_lm/_version.pyi

@@ -0,0 +1,5 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+__version__ = ...

.mlx_typings/mlx_lm/generate.pyi

@@ -3,13 +3,12 @@ This type stub file was generated by pyright.
 """
 
 import contextlib
-from dataclasses import dataclass
-from typing import Any, Callable, Generator, List, Optional, Tuple, Union
-
 import mlx.core as mx
 import mlx.nn as nn
+from dataclasses import dataclass
+from collections import deque
+from typing import Any, Callable, Generator, List, Optional, Sequence, Tuple, Union
 from transformers import PreTrainedTokenizer
-
 from .tokenizer_utils import TokenizerWrapper
 
 DEFAULT_PROMPT = ...
@@ -29,6 +28,7 @@ def str2bool(string):  # -> bool:
     ...
 def setup_arg_parser():  # -> ArgumentParser:
     """Set up and return the argument parser."""
+    ...
 
 generation_stream: mx.Stream
 
@@ -43,6 +43,7 @@ def wired_limit(
     async eval could be running pass in the streams to synchronize with prior
     to exiting the context manager.
     """
+    ...
 @dataclass
 class GenerationResponse:
     """
@@ -91,7 +92,7 @@ def generate_step(
     kv_bits: Optional[int] = ...,
     kv_group_size: int = ...,
     quantized_kv_start: int = ...,
-    prompt_progress_callback: Optional[Callable[[int], int]] = ...,
+    prompt_progress_callback: Optional[Callable[[int, int], None]] = ...,
     input_embeddings: Optional[mx.array] = ...,
 ) -> Generator[Tuple[mx.array, mx.array], None, None]:
     """
@@ -117,7 +118,7 @@ def generate_step(
         kv_group_size (int): Group size for KV cache quantization. Default: ``64``.
         quantized_kv_start (int): Step to begin using a quantized KV cache.
            when ``kv_bits`` is non-None. Default: ``0``.
-        prompt_progress_callback (Callable[[int], int]): A call-back which takes the
+        prompt_progress_callback (Callable[[int, int], None]): A call-back which takes the
            prompt tokens processed so far and the total number of prompt tokens.
         input_embeddings (mx.array, optional): Input embeddings to use instead of or in
           conjunction with prompt tokens. Default: ``None``.
@@ -125,6 +126,7 @@ def generate_step(
     Yields:
         Tuple[mx.array, mx.array]: One token and a vector of log probabilities.
     """
+    ...
 
 def speculative_generate_step(
     prompt: mx.array,
@@ -170,6 +172,7 @@ def speculative_generate_step(
         Tuple[mx.array, mx.array, bool]: One token, a vector of log probabilities,
           and a bool indicating if the token was generated by the draft model
     """
+    ...
 
 def stream_generate(
     model: nn.Module,
@@ -177,7 +180,7 @@ def stream_generate(
     prompt: Union[str, mx.array, List[int]],
     max_tokens: int = ...,
     draft_model: Optional[nn.Module] = ...,
-    **kwargs: object,
+    **kwargs: Any,
 ) -> Generator[GenerationResponse, None, None]:
     """
     A generator producing text based on the given prompt from the model.
@@ -199,6 +202,7 @@ def stream_generate(
         GenerationResponse: An instance containing the generated text segment and
             associated metadata. See :class:`GenerationResponse` for details.
     """
+    ...
 
 def generate(
     model: nn.Module,
@@ -219,6 +223,9 @@ def generate(
        kwargs: The remaining options get passed to :func:`stream_generate`.
           See :func:`stream_generate` for more details.
     """
+    ...
+
+def _merge_caches(caches: List[List[Any]]) -> List[Any]: ...
 @dataclass
 class BatchStats:
     """
@@ -242,10 +249,262 @@ class BatchStats:
     generation_time: float = ...
     peak_memory: float = ...
 
+class SequenceStateMachine:
+    """A state machine that uses one Aho-Corasick trie per state to efficiently
+    track state across a generated sequence.
+
+    The transitions are provided as state -> [(sequence, new_state)].
+
+    Example:
+
+        sm = SequenceStateMachine(
+            transitions={
+                "normal": [
+                    (think_start_tokens, "reasoning"),
+                    (tool_start_tokens, "tool"),
+                    (eos, None),
+                ],
+                "reasoning": [
+                    (think_end_tokens, "normal"),
+                    (eos, None),
+                ],
+                "tool": [
+                    (tool_end_tokens, None),
+                    (eos, None)
+                ],
+            },
+            initial="normal"
+        )
+    """
+    def __init__(self, transitions=..., initial=...) -> None: ...
+    def __deepcopy__(self, memo):  # -> SequenceStateMachine:
+        ...
+    def make_state(self):  # -> tuple[str, Any, dict[Any, Any]]:
+        ...
+    @staticmethod
+    def match(state, x):  # -> tuple[tuple[Any, Any | None, Any], Any | None, Any]:
+        ...
+
+class PromptProcessingBatch:
+    """
+    A batch processor for prompt tokens with support for incremental processing.
+
+    This class handles batched prompt processing, managing KV caches and preparing
+    tokens for generation. It supports extending, filtering, and splitting batches.
+    """
+    @dataclass
+    class Response:
+        uid: int
+        progress: tuple
+        end_of_segment: bool
+        end_of_prompt: bool
+        ...
+
+    def __init__(
+        self,
+        model: nn.Module,
+        uids: List[int],
+        caches: List[List[Any]],
+        tokens: Optional[List[List[int]]] = ...,
+        prefill_step_size: int = ...,
+        samplers: Optional[List[Callable[[mx.array], mx.array]]] = ...,
+        fallback_sampler: Optional[Callable[[mx.array], mx.array]] = ...,
+        logits_processors: Optional[
+            List[List[Callable[[mx.array, mx.array], mx.array]]]
+        ] = ...,
+        state_machines: Optional[List[SequenceStateMachine]] = ...,
+        max_tokens: Optional[List[int]] = ...,
+    ) -> None: ...
+    def __len__(self):  # -> int:
+        ...
+    def extract_cache(self, idx: int) -> List[Any]: ...
+    def extend(self, batch):  # -> None:
+        ...
+    def split(self, indices: List[int]):  # -> Self:
+        ...
+    def filter(self, keep: List[int]):  # -> None:
+        ...
+    def prompt(self, tokens: List[List[int]]):  # -> None:
+        """
+        Process prompt tokens through the model.
+
+        Args:
+            tokens: List of token sequences to process.
+        """
+        ...
+
+    def generate(self, tokens: List[List[int]]):  # -> GenerationBatch:
+        """
+        Transition from prompt processing to generation.
+
+        Args:
+            tokens: Final tokens for each sequence to start generation.
+
+        Returns:
+            A GenerationBatch ready for token generation.
+        """
+        ...
+
+    @classmethod
+    def empty(
+        cls,
+        model: nn.Module,
+        fallback_sampler: Callable[[mx.array], mx.array],
+        prefill_step_size: int = ...,
+    ):  # -> Self:
+        ...
+
+class GenerationBatch:
+    """
+    A batched token generator that manages multiple sequences in parallel.
+
+    This class handles the generation phase after prompt processing, managing
+    KV caches, sampling, and stop sequence detection for multiple sequences.
+    """
+    @dataclass
+    class Response:
+        uid: int
+        token: int
+        logprobs: mx.array
+        finish_reason: Optional[str]
+        current_state: Optional[str]
+        match_sequence: Optional[List[int]]
+        prompt_cache: Optional[List[Any]]
+        all_tokens: Optional[List[int]]
+        ...
+
+    model: nn.Module
+    uids: List[int]
+    prompt_cache: List[Any]
+    tokens: List[List[int]]
+    samplers: Optional[List[Callable[[mx.array], mx.array]]]
+    fallback_sampler: Callable[[mx.array], mx.array]
+    logits_processors: Optional[List[List[Callable[[mx.array, mx.array], mx.array]]]]
+    state_machines: List[SequenceStateMachine]
+    max_tokens: List[int]
+    _current_tokens: Optional[mx.array]
+    _current_logprobs: List[mx.array]
+    _next_tokens: mx.array
+    _next_logprobs: List[mx.array]
+    _token_context: List[mx.array]
+    _num_tokens: List[int]
+
+    def __init__(
+        self,
+        model: nn.Module,
+        uids: List[int],
+        inputs: mx.array,
+        prompt_cache: List[Any],
+        tokens: List[List[int]],
+        samplers: Optional[List[Callable[[mx.array], mx.array]]],
+        fallback_sampler: Callable[[mx.array], mx.array],
+        logits_processors: Optional[
+            List[List[Callable[[mx.array, mx.array], mx.array]]]
+        ],
+        state_machines: List[SequenceStateMachine],
+        max_tokens: List[int],
+    ) -> None: ...
+    def __len__(self) -> int: ...
+    def extend(self, batch: GenerationBatch) -> None: ...
+    def extract_cache(self, idx: int) -> List[Any]: ...
+    def filter(self, keep: List[int]) -> None: ...
+    def _step(self) -> Tuple[List[int], List[mx.array]]: ...
+    def next(self) -> List[Response]:
+        """
+        Generate the next batch of tokens.
+
+        Returns:
+            List of Response objects for each sequence in the batch.
+        """
+        ...
+
+    @classmethod
+    def empty(
+        cls, model: nn.Module, fallback_sampler: Callable[[mx.array], mx.array]
+    ):  # -> Self:
+        ...
+
+class BatchGenerator:
+    """
+    A batch generator implements continuous batching.
+
+    This class provides automatic management of prompt processing and generation
+    batches, handling the transition between the two.
+
+    It also allows for segmented prompt processing which guarantees that the
+    generator will stop at these boundaries when processing an input.
+    """
+    def __init__(
+        self,
+        model: nn.Module,
+        max_tokens: int = ...,
+        stop_tokens: Optional[Sequence[Sequence[int]]] = ...,
+        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 = ...,
+    ) -> None: ...
+    def close(self) -> None: ...
+    def __del__(self):  # -> None:
+        ...
+    @contextlib.contextmanager
+    def stats(self, stats=...):  # -> Generator[Any | BatchStats, Any, None]:
+        ...
+    _unprocessed_sequences: deque[tuple[Any, ...]]
+    _prompt_batch: PromptProcessingBatch
+    _generation_batch: GenerationBatch
+    _currently_processing: list[Any]
+    _gen_tokens_counter: int
+    _steps_counter: int
+    def _next(
+        self,
+    ) -> tuple[
+        List[PromptProcessingBatch.Response], List[GenerationBatch.Response]
+    ]: ...
+    def insert(
+        self,
+        prompts: List[List[int]],
+        max_tokens: Optional[List[int]] = ...,
+        caches: Optional[List[List[Any]]] = ...,
+        all_tokens: Optional[List[List[int]]] = ...,
+        samplers: Optional[List[Callable[[mx.array], mx.array]]] = ...,
+        logits_processors: Optional[
+            List[List[Callable[[mx.array, mx.array], mx.array]]]
+        ] = ...,
+        state_machines: Optional[List[SequenceStateMachine]] = ...,
+    ) -> List[int]: ...
+    def insert_segments(
+        self,
+        segments: List[List[List[int]]],
+        max_tokens: Optional[List[int]] = ...,
+        caches: Optional[List[List[Any]]] = ...,
+        all_tokens: Optional[List[List[int]]] = ...,
+        samplers: Optional[List[Callable[[mx.array], mx.array]]] = ...,
+        logits_processors: Optional[
+            List[List[Callable[[mx.array, mx.array], mx.array]]]
+        ] = ...,
+        state_machines: Optional[List[SequenceStateMachine]] = ...,
+    ) -> List[int]: ...
+    def extract_cache(self, uids: List[int]) -> dict[int, Any]: ...
+    def remove(
+        self, uids: List[int], return_prompt_caches: bool = ...
+    ) -> dict[int, Any]: ...
+    @property
+    def prompt_cache_nbytes(self) -> int: ...
+    def next(
+        self,
+    ) -> tuple[
+        List[PromptProcessingBatch.Response], List[GenerationBatch.Response]
+    ]: ...
+    def next_generated(self) -> List[GenerationBatch.Response]: ...
+
 @dataclass
 class BatchResponse:
     """
-    An data object to hold a batch generation response.
+    A data object to hold a batch generation response.
 
     Args:
         texts: (List[str]): The generated text for each prompt.
@@ -255,98 +514,17 @@ 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
-    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]: ...
-
-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,
-        max_tokens: int = ...,
-        stop_tokens: Optional[set[int]] = ...,
-        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]]: ...
+    ...
 
 def batch_generate(
     model,
     tokenizer,
-    prompts: List[int],
+    prompts: List[List[int]],
+    prompt_caches: Optional[List[List[Any]]] = ...,
     max_tokens: Union[int, List[int]] = ...,
     verbose: bool = ...,
+    return_prompt_caches: bool = ...,
+    logits_processors: Optional[List[Callable[[mx.array, mx.array], mx.array]]] = ...,
     **kwargs,
 ) -> BatchResponse:
     """
@@ -355,14 +533,22 @@ def batch_generate(
     Args:
        model (nn.Module): The language model.
        tokenizer (PreTrainedTokenizer): The tokenizer.
-       prompt (List[List[int]]): The input prompts.
+       prompts (List[List[int]]): The input prompts.
+       prompt_caches (List[List[Any]], optional): Pre-computed prompt-caches
+          for each input prompt. Note, unlike ``generate_step``, the caches
+          won't be updated in-place.
        verbose (bool): If ``True``, print tokens and timing information.
           Default: ``False``.
        max_tokens (Union[int, List[int]): Maximum number of output tokens. This
           can be per prompt if a list is provided.
+       return_prompt_caches (bool): Return the prompt caches in the batch
+          responses. Default: ``False``.
+       logits_processors (List[Callable[[mx.array, mx.array], mx.array]], optional):
+          A list of functions that take tokens and logits and return the processed logits. Default: ``None``.
        kwargs: The remaining options get passed to :obj:`BatchGenerator`.
           See :obj:`BatchGenerator` for more details.
     """
+    ...
 
 def main():  # -> None:
     ...

.mlx_typings/mlx_lm/models/activations.pyi

@@ -0,0 +1,19 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.core as mx
+import mlx.nn as nn
+from functools import partial
+
+@partial(mx.compile, shapeless=True)
+def swiglu(gate, x): ...
+@partial(mx.compile, shapeless=True)
+def xielu(x, alpha_p, alpha_n, beta, eps):  # -> array:
+    ...
+
+class XieLU(nn.Module):
+    def __init__(
+        self, alpha_p_init=..., alpha_n_init=..., beta=..., eps=...
+    ) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...

.mlx_typings/mlx_lm/models/gemma4.pyi

@@ -0,0 +1,31 @@
+from dataclasses import dataclass
+from typing import Any, Optional
+
+import mlx.core as mx
+import mlx.nn as nn
+
+from . import gemma4_text
+from .base import BaseModelArgs
+from .cache import KVCache, RotatingKVCache
+
+@dataclass
+class ModelArgs(BaseModelArgs):
+    model_type: str
+    text_config: Optional[dict[str, Any]]
+    vocab_size: int
+
+    def __post_init__(self) -> None: ...
+
+class Model(nn.Module):
+    args: ModelArgs
+    model_type: str
+    language_model: gemma4_text.Model
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(self, *args: Any, **kwargs: Any) -> mx.array: ...
+    def sanitize(self, weights: dict[str, Any]) -> dict[str, Any]: ...
+    @property
+    def layers(self) -> list[gemma4_text.DecoderLayer]: ...
+    @property
+    def quant_predicate(self) -> Any: ...
+    def make_cache(self) -> list[KVCache | RotatingKVCache]: ...

.mlx_typings/mlx_lm/models/gemma4_text.pyi

@@ -0,0 +1,179 @@
+from dataclasses import dataclass
+from typing import Any, Dict, List, Optional
+
+import mlx.core as mx
+import mlx.nn as nn
+
+from .base import BaseModelArgs
+from .cache import KVCache, RotatingKVCache
+from .switch_layers import SwitchGLU
+
+@dataclass
+class ModelArgs(BaseModelArgs):
+    model_type: str
+    hidden_size: int
+    num_hidden_layers: int
+    intermediate_size: int
+    num_attention_heads: int
+    head_dim: int
+    global_head_dim: int
+    global_partial_rotary_factor: float
+    rms_norm_eps: float
+    vocab_size: int
+    vocab_size_per_layer_input: int
+    num_key_value_heads: int
+    num_global_key_value_heads: Optional[int]
+    num_kv_shared_layers: int
+    pad_token_id: int
+    hidden_size_per_layer_input: int
+    rope_traditional: bool
+    partial_rotary_factor: float
+    rope_parameters: Optional[Dict[str, Any]]
+    sliding_window: int
+    sliding_window_pattern: int
+    max_position_embeddings: int
+    attention_k_eq_v: bool
+    final_logit_softcapping: float
+    use_double_wide_mlp: bool
+    enable_moe_block: bool
+    num_experts: Optional[int]
+    top_k_experts: Optional[int]
+    moe_intermediate_size: Optional[int]
+    layer_types: Optional[List[str]]
+    tie_word_embeddings: bool
+
+    def __post_init__(self) -> None: ...
+
+class MLP(nn.Module):
+    gate_proj: nn.Linear
+    down_proj: nn.Linear
+    up_proj: nn.Linear
+
+    def __init__(self, config: ModelArgs, layer_idx: int = 0) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...
+
+class Router(nn.Module):
+    proj: nn.Linear
+    scale: mx.array
+    per_expert_scale: mx.array
+
+    def __init__(self, config: ModelArgs) -> None: ...
+    def __call__(self, x: mx.array) -> tuple[mx.array, mx.array]: ...
+
+class Experts(nn.Module):
+    switch_glu: SwitchGLU
+
+    def __init__(self, config: ModelArgs) -> None: ...
+    def __call__(
+        self, x: mx.array, top_k_indices: mx.array, top_k_weights: mx.array
+    ) -> mx.array: ...
+
+class Attention(nn.Module):
+    layer_idx: int
+    layer_type: str
+    is_sliding: bool
+    head_dim: int
+    n_heads: int
+    n_kv_heads: int
+    use_k_eq_v: bool
+    scale: float
+    q_proj: nn.Linear
+    k_proj: nn.Linear
+    v_proj: nn.Linear
+    o_proj: nn.Linear
+    q_norm: nn.Module
+    k_norm: nn.Module
+    v_norm: nn.Module
+    rope: nn.Module
+
+    def __init__(self, config: ModelArgs, layer_idx: int) -> None: ...
+    def __call__(self, *args: Any, **kwargs: Any) -> Any: ...
+
+class DecoderLayer(nn.Module):
+    layer_idx: int
+    layer_type: str
+    self_attn: Attention
+    mlp: MLP
+    enable_moe: bool
+    router: Router
+    experts: Experts
+    input_layernorm: nn.Module
+    post_attention_layernorm: nn.Module
+    pre_feedforward_layernorm: nn.Module
+    post_feedforward_layernorm: nn.Module
+    post_feedforward_layernorm_1: nn.Module
+    post_feedforward_layernorm_2: nn.Module
+    pre_feedforward_layernorm_2: nn.Module
+    hidden_size_per_layer_input: int
+    per_layer_input_gate: Optional[nn.Linear]
+    per_layer_projection: Optional[nn.Linear]
+    post_per_layer_input_norm: Optional[nn.Module]
+    layer_scalar: mx.array
+
+    def __init__(self, config: ModelArgs, layer_idx: int) -> None: ...
+    def __call__(
+        self,
+        x: mx.array,
+        mask: Optional[mx.array] = ...,
+        cache: Optional[Any] = ...,
+        per_layer_input: Optional[mx.array] = ...,
+        shared_kv: Optional[tuple[mx.array, mx.array]] = ...,
+        offset: Optional[mx.array] = ...,
+    ) -> tuple[mx.array, tuple[mx.array, mx.array], mx.array]: ...
+
+class Gemma4TextModel(nn.Module):
+    config: ModelArgs
+    vocab_size: int
+    window_size: int
+    sliding_window_pattern: int
+    num_hidden_layers: int
+    embed_tokens: nn.Embedding
+    embed_scale: float
+    layers: list[DecoderLayer]
+    norm: nn.Module
+    hidden_size_per_layer_input: int
+    embed_tokens_per_layer: Optional[nn.Embedding]
+    per_layer_model_projection: Optional[nn.Linear]
+    per_layer_projection_norm: Optional[nn.Module]
+    previous_kvs: list[int]
+
+    def __init__(self, config: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        inputs: Optional[mx.array] = ...,
+        cache: Optional[list[Any]] = ...,
+        input_embeddings: Optional[mx.array] = ...,
+        per_layer_inputs: Optional[mx.array] = ...,
+    ) -> mx.array: ...
+    def _get_per_layer_inputs(
+        self,
+        input_ids: Optional[mx.array],
+        input_embeddings: Optional[mx.array] = ...,
+    ) -> mx.array: ...
+    def _project_per_layer_inputs(
+        self,
+        input_embeddings: mx.array,
+        per_layer_inputs: Optional[mx.array] = ...,
+    ) -> mx.array: ...
+    def _make_masks(self, h: mx.array, cache: list[Any]) -> list[Any]: ...
+
+class Model(nn.Module):
+    args: ModelArgs
+    model_type: str
+    model: Gemma4TextModel
+    final_logit_softcapping: float
+    tie_word_embeddings: bool
+    lm_head: nn.Linear
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(self, *args: Any, **kwargs: Any) -> mx.array: ...
+    def sanitize(self, weights: dict[str, Any]) -> dict[str, Any]: ...
+    @property
+    def layers(self) -> list[DecoderLayer]: ...
+    @property
+    def head_dim(self) -> int: ...
+    @property
+    def n_kv_heads(self) -> int: ...
+    @property
+    def quant_predicate(self) -> Any: ...
+    def make_cache(self) -> list[KVCache | RotatingKVCache]: ...

.mlx_typings/mlx_lm/sample_utils.pyi

@@ -48,6 +48,10 @@ def make_logits_processors(
     logit_bias: Optional[Dict[int, float]] = ...,
     repetition_penalty: Optional[float] = ...,
     repetition_context_size: Optional[int] = ...,
+    presence_penalty: Optional[float] = ...,
+    presence_context_size: Optional[int] = ...,
+    frequency_penalty: Optional[float] = ...,
+    frequency_context_size: Optional[int] = ...,
 ) -> list[Callable[[mx.array, mx.array], mx.array]]:
     """
     Make logits processors for use with ``generate_step``.

.mlx_typings/mlx_lm/tokenizer_utils.pyi

@@ -117,6 +117,8 @@ class TokenizerWrapper:
     think_end: str | None
     think_start_id: int | None
     think_end_id: int | None
+    think_start_tokens: list[int] | None
+    think_end_tokens: list[int] | None
 
     def __init__(
         self,

.mlx_typings/mlx_lm/tuner/dora.pyi

@@ -0,0 +1,50 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.nn as nn
+
+class DoRALinear(nn.Module):
+    @staticmethod
+    def from_base(
+        linear: nn.Linear, r: int = ..., dropout: float = ..., scale: float = ...
+    ):  # -> DoRALinear:
+        ...
+    def fuse(self, dequantize: bool = ...):  # -> QuantizedLinear | Linear:
+        ...
+    def __init__(
+        self,
+        input_dims: int,
+        output_dims: int,
+        r: int = ...,
+        dropout: float = ...,
+        scale: float = ...,
+        bias: bool = ...,
+    ) -> None: ...
+    def set_linear(self, linear):  # -> None:
+        """
+        Set the self.linear layer and recompute self.m.
+        """
+        ...
+
+    def __call__(self, x): ...
+
+class DoRAEmbedding(nn.Module):
+    def from_base(
+        embedding: nn.Embedding, r: int = ..., dropout: float = ..., scale: float = ...
+    ):  # -> DoRAEmbedding:
+        ...
+    def fuse(self, dequantize: bool = ...):  # -> Embedding:
+        ...
+    def __init__(
+        self,
+        num_embeddings: int,
+        dims: int,
+        r: int = ...,
+        dropout: float = ...,
+        scale: float = ...,
+    ) -> None: ...
+    def set_embedding(self, embedding: nn.Module):  # -> None:
+        ...
+    def __call__(self, x): ...
+    def as_linear(self, x): ...

.mlx_typings/mlx_lm/tuner/lora.pyi

@@ -0,0 +1,66 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.nn as nn
+
+class LoRALinear(nn.Module):
+    @staticmethod
+    def from_base(
+        linear: nn.Linear, r: int = ..., dropout: float = ..., scale: float = ...
+    ):  # -> LoRALinear:
+        ...
+    def fuse(self, dequantize: bool = ...):  # -> QuantizedLinear | Linear:
+        ...
+    def __init__(
+        self,
+        input_dims: int,
+        output_dims: int,
+        r: int = ...,
+        dropout: float = ...,
+        scale: float = ...,
+        bias: bool = ...,
+    ) -> None: ...
+    def __call__(self, x):  # -> array:
+        ...
+
+class LoRASwitchLinear(nn.Module):
+    @staticmethod
+    def from_base(
+        linear: nn.Module, r: int = ..., dropout: float = ..., scale: float = ...
+    ):  # -> LoRASwitchLinear:
+        ...
+    def fuse(self, dequantize: bool = ...):  # -> QuantizedSwitchLinear | SwitchLinear:
+        ...
+    def __init__(
+        self,
+        input_dims: int,
+        output_dims: int,
+        num_experts: int,
+        r: int = ...,
+        dropout: float = ...,
+        scale: float = ...,
+        bias: bool = ...,
+    ) -> None: ...
+    def __call__(self, x, indices, sorted_indices=...): ...
+
+class LoRAEmbedding(nn.Module):
+    @staticmethod
+    def from_base(
+        embedding: nn.Embedding, r: int = ..., dropout: float = ..., scale: float = ...
+    ):  # -> LoRAEmbedding:
+        ...
+    def fuse(self, dequantize: bool = ...):  # -> QuantizedEmbedding | Embedding:
+        ...
+    def __init__(
+        self,
+        num_embeddings: int,
+        dims: int,
+        r: int = ...,
+        dropout: float = ...,
+        scale: float = ...,
+    ) -> None: ...
+    def __call__(self, x):  # -> array:
+        ...
+    def as_linear(self, x):  # -> array:
+        ...

.mlx_typings/mlx_lm/tuner/utils.pyi

@@ -0,0 +1,57 @@
+"""
+This type stub file was generated by pyright.
+"""
+
+import mlx.nn as nn
+from typing import Dict
+
+def build_schedule(schedule_config: Dict):  # -> Any:
+    """
+    Build a learning rate schedule from the given config.
+    """
+    ...
+
+def linear_to_lora_layers(
+    model: nn.Module, num_layers: int, config: Dict, use_dora: bool = ...
+):  # -> None:
+    """
+    Convert some of the models linear layers to lora layers.
+
+    Args:
+        model (nn.Module): The neural network model.
+        num_layers (int): The number of blocks to convert to lora layers
+        starting from the last layer.
+        config (dict): More configuration parameters for LoRA, including the
+          rank, scale, and optional layer keys.
+        use_dora (bool): If True, uses DoRA instead of LoRA.
+          Default: ``False``
+    """
+    ...
+
+def load_adapters(model: nn.Module, adapter_path: str) -> nn.Module:
+    """
+    Load any fine-tuned adapters / layers.
+
+    Args:
+        model (nn.Module): The neural network model.
+        adapter_path (str): Path to the adapter configuration file.
+
+    Returns:
+        nn.Module: The updated model with LoRA layers applied.
+    """
+    ...
+
+def remove_lora_layers(model: nn.Module) -> nn.Module:
+    """
+    Remove the LoRA layers from the model.
+
+    Args:
+        model (nn.Module): The model with LoRA layers.
+
+    Returns:
+        nn.Module: The model without LoRA layers.
+    """
+    ...
+
+def print_trainable_parameters(model):  # -> None:
+    ...

.mlx_typings/mlx_vlm/prompt_utils.pyi

@@ -0,0 +1,12 @@
+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]: ...

.mlx_typings/mlx_vlm/utils.pyi

@@ -0,0 +1,15 @@
+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: ...

.mlx_typings/safetensors/__init__.pyi

@@ -0,0 +1,8 @@
+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: ...

.vscode/extensions.json

@@ -1,7 +1,8 @@
 {
     "recommendations": [
         "detachhead.basedpyright",
-        "ms-python.python"
+        "ms-python.python",
+        "jnoortheen.nix-ide"
     ],
     "unwantedRecommendations": [
         "ms-python.vscode-pylance",

.vscode/settings.json

@@ -1,3 +1,32 @@
 {
-    "basedpyright.importStrategy": "fromEnvironment"
+    "files.associations": {
+        "*.nix": "nix",
+    },
+    "nix.enableLanguageServer": true,
+    "nix.serverPath": "nixd",
+    "nix.serverSettings": {
+        "nixd": {
+        "formatting": {
+            "command": ["nixpkgs-fmt"]
+        },
+        "nixpkgs": {
+            "expr": "(builtins.getFlake \"path:${workspaceFolder}\").currentSystem.config._module.args.pkgs"
+        },
+        "options": {
+            "flake-parts": {
+                "expr": "(builtins.getFlake \"path:${workspaceFolder}\").debug.options"
+            },
+            "flake-parts-perSystem": {
+                "expr": "(builtins.getFlake \"path:${workspaceFolder}\").currentSystem.options"
+            }
+        }
+      }
+    },
+    "[nix]": {
+        "editor.defaultFormatter": "jnoortheen.nix-ide"
+    },
+    
+    "python.defaultInterpreterPath": "${workspaceFolder}/.venv/bin/python",
+    "basedpyright.analysis.configFilePath": "${workspaceFolder}/pyproject.toml",
+    "basedpyright.importStrategy": "fromEnvironment",
 }

CONTRIBUTING.md

@@ -19,8 +19,8 @@ To run EXO from source:
 - [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 \
+  cargo install --git https://github.com/vladkens/macmon \
+    --rev a1cd06b6cc0d5e61db24fd8832e74cd992097a7d \
     macmon \
     --force
   ```

README.md

@@ -112,8 +112,8 @@ Then restart the Nix daemon: `sudo launchctl kickstart -k system/org.nixos.nix-d
   Homebrew `macmon 0.6.1` still crashes on Apple M5.
 
   ```bash
-  cargo install --git https://github.com/swiftraccoon/macmon \
-    --rev 9154d234f763fbeffdcb4135d0bbbaf80609699b \
+  cargo install --git https://github.com/vladkens/macmon \
+    --rev a1cd06b6cc0d5e61db24fd8832e74cd992097a7d \
     macmon \
     --force
   ```
@@ -295,8 +295,9 @@ exo supports several environment variables for configuration:
 
 | Variable | Description | Default |
 |----------|-------------|---------|
-| `EXO_MODELS_PATH` | Colon-separated paths to search for pre-downloaded models (e.g., on NFS mounts or shared storage) | None |
-| `EXO_MODELS_DIR` | Directory where exo downloads and stores models | `~/.local/share/exo/models` (Linux) or `~/.exo/models` (macOS) |
+| `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 |
@@ -306,8 +307,11 @@ exo supports several environment variables for configuration:
 **Example usage:**
 
 ```bash
-# Use pre-downloaded models from NFS mount
-EXO_MODELS_PATH=/mnt/nfs/models:/opt/ai-models uv run exo
+# 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

app/EXO/EXO/ExoProcessController.swift

@@ -7,7 +7,27 @@ private let hfTokenKey = "EXOHFToken"
 private let hfEndpointKey = "EXOHFEndpoint"
 private let enableImageModelsKey = "EXOEnableImageModels"
 private let offlineModeKey = "EXOOfflineMode"
+private let fastSynchEnabledKey = "EXOFastSynchEnabled"
 private let onboardingCompletedKey = "EXOOnboardingCompleted"
+private let defaultModelsDirKey = "EXODefaultModelsDir"
+private let additionalModelsDirsKey = "EXOAdditionalModelsDirs"
+private let readOnlyModelsDirsKey = "EXOReadOnlyModelsDirs"
+private let customEnvironmentVariablesKey = "EXOCustomEnvironmentVariables"
+
+/// A user-defined environment variable that is injected into the exo child
+/// process at launch. Used as an escape hatch for env vars that don't have
+/// first-class typed UI in Settings.
+struct CustomEnvironmentVariable: Codable, Identifiable, Equatable {
+    var id: UUID
+    var key: String
+    var value: String
+
+    init(id: UUID = UUID(), key: String = "", value: String = "") {
+        self.id = id
+        self.key = key
+        self.value = value
+    }
+}
 
 @MainActor
 final class ExoProcessController: ObservableObject {
@@ -78,6 +98,60 @@ final class ExoProcessController: ObservableObject {
             UserDefaults.standard.set(offlineMode, forKey: offlineModeKey)
         }
     }
+    @Published var fastSynchEnabled: Bool = {
+        if UserDefaults.standard.object(forKey: fastSynchEnabledKey) == nil {
+            return true
+        }
+        return UserDefaults.standard.bool(forKey: fastSynchEnabledKey)
+    }()
+    {
+        didSet {
+            UserDefaults.standard.set(fastSynchEnabled, forKey: fastSynchEnabledKey)
+        }
+    }
+    @Published var defaultModelsDir: String = {
+        return UserDefaults.standard.string(forKey: defaultModelsDirKey) ?? ""
+    }()
+    {
+        didSet {
+            UserDefaults.standard.set(defaultModelsDir, forKey: defaultModelsDirKey)
+        }
+    }
+    @Published var additionalModelsDirs: String = {
+        return UserDefaults.standard.string(forKey: additionalModelsDirsKey) ?? ""
+    }()
+    {
+        didSet {
+            UserDefaults.standard.set(additionalModelsDirs, forKey: additionalModelsDirsKey)
+        }
+    }
+    @Published var readOnlyModelsDirs: String = {
+        return UserDefaults.standard.string(forKey: readOnlyModelsDirsKey) ?? ""
+    }()
+    {
+        didSet {
+            UserDefaults.standard.set(readOnlyModelsDirs, forKey: readOnlyModelsDirsKey)
+        }
+    }
+    @Published var customEnvironmentVariables: [CustomEnvironmentVariable] = {
+        guard
+            let data = UserDefaults.standard.data(forKey: customEnvironmentVariablesKey),
+            let decoded = try? JSONDecoder().decode(
+                [CustomEnvironmentVariable].self, from: data
+            )
+        else {
+            return []
+        }
+        return decoded
+    }()
+    {
+        didSet {
+            guard let data = try? JSONEncoder().encode(customEnvironmentVariables) else {
+                return
+            }
+            UserDefaults.standard.set(data, forKey: customEnvironmentVariablesKey)
+        }
+    }
 
     /// Fires once when EXO transitions to `.running` for the very first time (fresh install).
     @Published private(set) var isFirstLaunchReady = false
@@ -291,6 +365,7 @@ final class ExoProcessController: ObservableObject {
         if offlineMode {
             environment["EXO_OFFLINE"] = "true"
         }
+        environment["EXO_FAST_SYNCH"] = fastSynchEnabled ? "true" : "false"
 
         var paths: [String] = []
         if let existing = environment["PATH"], !existing.isEmpty {
@@ -315,6 +390,29 @@ final class ExoProcessController: ObservableObject {
         }
 
         environment["PATH"] = paths.joined(separator: ":")
+
+        let trimmedDefaultModelsDir = defaultModelsDir.trimmingCharacters(in: .whitespaces)
+        if !trimmedDefaultModelsDir.isEmpty {
+            environment["EXO_DEFAULT_MODELS_DIR"] = trimmedDefaultModelsDir
+        }
+        let trimmedAdditionalModelsDirs = additionalModelsDirs.trimmingCharacters(in: .whitespaces)
+        if !trimmedAdditionalModelsDirs.isEmpty {
+            environment["EXO_MODELS_DIRS"] = trimmedAdditionalModelsDirs
+        }
+        let trimmedReadOnlyModelsDirs = readOnlyModelsDirs.trimmingCharacters(in: .whitespaces)
+        if !trimmedReadOnlyModelsDirs.isEmpty {
+            environment["EXO_MODELS_READ_ONLY_DIRS"] = trimmedReadOnlyModelsDirs
+        }
+
+        // Apply user-defined arbitrary environment variables last so that
+        // power users can override any of the typed fields above when
+        // necessary. Empty keys are ignored.
+        for variable in customEnvironmentVariables {
+            let trimmedKey = variable.key.trimmingCharacters(in: .whitespaces)
+            guard !trimmedKey.isEmpty else { continue }
+            environment[trimmedKey] = variable.value
+        }
+
         return environment
     }
 

app/EXO/EXO/Views/SettingsView.swift

@@ -15,6 +15,11 @@ struct SettingsView: View {
     @State private var pendingHFEndpoint: String = ""
     @State private var pendingEnableImageModels = false
     @State private var pendingOfflineMode = false
+    @State private var pendingFastSynchEnabled = false
+    @State private var pendingDefaultModelsDir: String = ""
+    @State private var pendingAdditionalModelsDirs: String = ""
+    @State private var pendingReadOnlyModelsDirs: String = ""
+    @State private var pendingCustomEnvironmentVariables: [CustomEnvironmentVariable] = []
     @State private var needsRestart = false
     @State private var bugReportInFlight = false
     @State private var bugReportMessage: String?
@@ -34,18 +39,27 @@ struct SettingsView: View {
                 .tabItem {
                     Label("Advanced", systemImage: "wrench.and.screwdriver")
                 }
+            environmentTab
+                .tabItem {
+                    Label("Environment", systemImage: "terminal")
+                }
             aboutTab
                 .tabItem {
                     Label("About", systemImage: "info.circle")
                 }
         }
-        .frame(width: 450, height: 400)
+        .frame(width: 640, height: 560)
         .onAppear {
             pendingNamespace = controller.customNamespace
             pendingHFToken = controller.hfToken
             pendingHFEndpoint = controller.hfEndpoint
             pendingEnableImageModels = controller.enableImageModels
             pendingOfflineMode = controller.offlineMode
+            pendingFastSynchEnabled = controller.fastSynchEnabled
+            pendingDefaultModelsDir = controller.defaultModelsDir
+            pendingAdditionalModelsDirs = controller.additionalModelsDirs
+            pendingReadOnlyModelsDirs = controller.readOnlyModelsDirs
+            pendingCustomEnvironmentVariables = controller.customEnvironmentVariables
             needsRestart = false
         }
     }
@@ -56,9 +70,9 @@ struct SettingsView: View {
         Form {
             Section {
                 LabeledContent("Cluster Namespace") {
-                    TextField("default", text: $pendingNamespace)
+                    TextField("", text: $pendingNamespace, prompt: Text("default"))
                         .textFieldStyle(.roundedBorder)
-                        .frame(width: 200)
+                        .frame(width: 260)
                 }
                 Text("Nodes with the same namespace form a cluster. Leave empty for default.")
                     .font(.caption)
@@ -67,9 +81,9 @@ struct SettingsView: View {
 
             Section {
                 LabeledContent("HuggingFace Token") {
-                    SecureField("optional", text: $pendingHFToken)
+                    SecureField("", text: $pendingHFToken, prompt: Text("optional"))
                         .textFieldStyle(.roundedBorder)
-                        .frame(width: 200)
+                        .frame(width: 260)
                 }
                 Text("Required for gated models. Get yours at huggingface.co/settings/tokens")
                     .font(.caption)
@@ -78,9 +92,9 @@ struct SettingsView: View {
 
             Section {
                 LabeledContent("HuggingFace Endpoint") {
-                    TextField("default", text: $pendingHFEndpoint)
+                    TextField("", text: $pendingHFEndpoint, prompt: Text("default"))
                         .textFieldStyle(.roundedBorder)
-                        .frame(width: 200)
+                        .frame(width: 260)
                 }
                 Text("Defaults to huggingface.co. Use a mirror (e.g. hf-mirror.com) for China.")
                     .font(.caption)
@@ -137,6 +151,23 @@ struct SettingsView: View {
 
     private var advancedTab: some View {
         Form {
+            Section("Performance") {
+                Toggle("Fast Synch Enabled", isOn: $pendingFastSynchEnabled)
+                Text(
+                    "Experimental: enables fast CPU to GPU synchronization. Can sometimes cause a \"GPU lock\" where inference hangs for ~10 seconds before starting. Necessary for low latency with RDMA and Tensor Parallelism."
+                )
+                .font(.caption)
+                .foregroundColor(.secondary)
+
+                HStack {
+                    Spacer()
+                    Button("Save & Restart") {
+                        applyAdvancedSettings()
+                    }
+                    .disabled(!hasAdvancedChanges)
+                }
+            }
+
             Section("Onboarding") {
                 HStack {
                     VStack(alignment: .leading) {
@@ -193,6 +224,128 @@ struct SettingsView: View {
         .padding()
     }
 
+    // MARK: - Environment Tab
+
+    private var environmentTab: some View {
+        Form {
+            Section("Models Directories") {
+                LabeledContent("Default Models Directory") {
+                    TextField(
+                        "",
+                        text: $pendingDefaultModelsDir,
+                        prompt: Text("~/.exo/models")
+                    )
+                    .textFieldStyle(.roundedBorder)
+                    .font(.system(.body, design: .monospaced))
+                    .frame(width: 260)
+                }
+                Text("Sets EXO_DEFAULT_MODELS_DIR. Where models are downloaded.")
+                    .font(.caption)
+                    .foregroundColor(.secondary)
+
+                LabeledContent("Additional Directories") {
+                    TextField(
+                        "",
+                        text: $pendingAdditionalModelsDirs,
+                        prompt: Text("optional, colon-separated")
+                    )
+                    .textFieldStyle(.roundedBorder)
+                    .font(.system(.body, design: .monospaced))
+                    .frame(width: 260)
+                }
+                Text("Sets EXO_MODELS_DIRS. Extra writable model directories.")
+                    .font(.caption)
+                    .foregroundColor(.secondary)
+
+                LabeledContent("Read-Only Directories") {
+                    TextField(
+                        "",
+                        text: $pendingReadOnlyModelsDirs,
+                        prompt: Text("optional, colon-separated")
+                    )
+                    .textFieldStyle(.roundedBorder)
+                    .font(.system(.body, design: .monospaced))
+                    .frame(width: 260)
+                }
+                Text("Sets EXO_MODELS_READ_ONLY_DIRS. Never written to.")
+                    .font(.caption)
+                    .foregroundColor(.secondary)
+            }
+
+            Section("Custom Environment Variables") {
+                Text(
+                    "Escape hatch for env vars that don't have typed fields above. "
+                        + "Values here override the typed fields on conflict."
+                )
+                .font(.caption)
+                .foregroundColor(.secondary)
+
+                if pendingCustomEnvironmentVariables.isEmpty {
+                    Text("No custom variables.")
+                        .font(.caption)
+                        .foregroundColor(.secondary)
+                } else {
+                    ForEach($pendingCustomEnvironmentVariables) { $variable in
+                        HStack(alignment: .center, spacing: 8) {
+                            VStack(spacing: 4) {
+                                TextField("key", text: $variable.key)
+                                    .labelsHidden()
+                                    .textFieldStyle(.roundedBorder)
+                                    .font(.system(.body, design: .monospaced))
+                                TextField("value", text: $variable.value)
+                                    .labelsHidden()
+                                    .textFieldStyle(.roundedBorder)
+                                    .font(.system(.body, design: .monospaced))
+                            }
+                            VStack(spacing: 4) {
+                                Button {
+                                    pendingCustomEnvironmentVariables.removeAll {
+                                        $0.id == variable.id
+                                    }
+                                } label: {
+                                    Image(systemName: "minus.circle")
+                                }
+                                .buttonStyle(.borderless)
+                                .help("Remove variable")
+                                if !isValidEnvironmentVariableName(variable.key) {
+                                    Image(systemName: "exclamationmark.triangle.fill")
+                                        .foregroundColor(.orange)
+                                        .help(
+                                            "Invalid environment variable name. "
+                                                + "Must match [A-Za-z_][A-Za-z0-9_]*."
+                                        )
+                                }
+                            }
+                        }
+                    }
+                }
+
+                HStack {
+                    Button {
+                        pendingCustomEnvironmentVariables.append(
+                            CustomEnvironmentVariable()
+                        )
+                    } label: {
+                        Label("Add Variable", systemImage: "plus")
+                    }
+                    Spacer()
+                }
+            }
+
+            Section {
+                HStack {
+                    Spacer()
+                    Button("Save & Restart") {
+                        applyEnvironmentSettings()
+                    }
+                    .disabled(!hasEnvironmentChanges)
+                }
+            }
+        }
+        .formStyle(.grouped)
+        .padding()
+    }
+
     // MARK: - About Tab
 
     private var aboutTab: some View {
@@ -475,6 +628,17 @@ struct SettingsView: View {
         pendingEnableImageModels != controller.enableImageModels
     }
 
+    private var hasAdvancedChanges: Bool {
+        pendingFastSynchEnabled != controller.fastSynchEnabled
+    }
+
+    private var hasEnvironmentChanges: Bool {
+        pendingDefaultModelsDir != controller.defaultModelsDir
+            || pendingAdditionalModelsDirs != controller.additionalModelsDirs
+            || pendingReadOnlyModelsDirs != controller.readOnlyModelsDirs
+            || pendingCustomEnvironmentVariables != controller.customEnvironmentVariables
+    }
+
     private func applyGeneralSettings() {
         controller.customNamespace = pendingNamespace
         controller.hfToken = pendingHFToken
@@ -488,6 +652,75 @@ struct SettingsView: View {
         restartIfRunning()
     }
 
+    private func applyAdvancedSettings() {
+        controller.fastSynchEnabled = pendingFastSynchEnabled
+        restartIfRunning()
+    }
+
+    private func applyEnvironmentSettings() {
+        controller.defaultModelsDir = pendingDefaultModelsDir.trimmingCharacters(
+            in: .whitespaces)
+        controller.additionalModelsDirs = pendingAdditionalModelsDirs.trimmingCharacters(
+            in: .whitespaces)
+        controller.readOnlyModelsDirs = pendingReadOnlyModelsDirs.trimmingCharacters(
+            in: .whitespaces)
+
+        pendingDefaultModelsDir = controller.defaultModelsDir
+        pendingAdditionalModelsDirs = controller.additionalModelsDirs
+        pendingReadOnlyModelsDirs = controller.readOnlyModelsDirs
+
+        // Trim whitespace from keys and drop empty ones so that the stored
+        // form matches what is actually injected into the child process and
+        // hasEnvironmentChanges doesn't show a stale diff after save.
+        let trimmed: [CustomEnvironmentVariable] =
+            pendingCustomEnvironmentVariables.compactMap { variable in
+                let key = variable.key.trimmingCharacters(in: .whitespaces)
+                guard !key.isEmpty else { return nil }
+                return CustomEnvironmentVariable(
+                    id: variable.id, key: key, value: variable.value
+                )
+            }
+
+        // De-duplicate keys, keeping the last occurrence. This matches the
+        // effective semantics of the dictionary assignment in
+        // ExoProcessController.makeEnvironment and avoids silently losing
+        // visible rows after save.
+        var seenKeys = Set<String>()
+        var deduplicatedReversed: [CustomEnvironmentVariable] = []
+        for variable in trimmed.reversed() {
+            if seenKeys.insert(variable.key).inserted {
+                deduplicatedReversed.append(variable)
+            }
+        }
+        let sanitized = Array(deduplicatedReversed.reversed())
+
+        pendingCustomEnvironmentVariables = sanitized
+        controller.customEnvironmentVariables = sanitized
+
+        restartIfRunning()
+    }
+
+    /// Validates a POSIX-style environment variable name:
+    /// `[A-Za-z_][A-Za-z0-9_]*`. Uses an ASCII-only charset so that
+    /// Unicode letters (e.g. `ñ`, Cyrillic) are rejected in line with what
+    /// the help tooltip advertises. Empty strings are treated as valid
+    /// here so that a freshly added blank row does not immediately look
+    /// broken; the save step filters empty keys out instead.
+    private func isValidEnvironmentVariableName(_ key: String) -> Bool {
+        if key.isEmpty { return true }
+        let headAllowed = CharacterSet(
+            charactersIn: "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz_"
+        )
+        let tailAllowed = headAllowed.union(CharacterSet(charactersIn: "0123456789"))
+        guard let first = key.unicodeScalars.first, headAllowed.contains(first) else {
+            return false
+        }
+        for scalar in key.unicodeScalars.dropFirst() {
+            if !tailAllowed.contains(scalar) { return false }
+        }
+        return true
+    }
+
     private func restartIfRunning() {
         if controller.status == .running || controller.status == .starting {
             controller.restart()

app/EXO/EXO/Views/SettingsWindowController.swift

@@ -30,7 +30,7 @@ final class SettingsWindowController: ObservableObject {
         let hostingView = NSHostingView(rootView: settingsView)
 
         let newWindow = NSWindow(
-            contentRect: NSRect(x: 0, y: 0, width: 450, height: 400),
+            contentRect: NSRect(x: 0, y: 0, width: 640, height: 560),
             styleMask: [.titled, .closable],
             backing: .buffered,
             defer: false

bench/METHODOLOGY.md

@@ -0,0 +1,160 @@
+# Exo-Bench — Methodology
+
+exo bench measures inference throughput and resource consumption of an exo cluster under controlled conditions. It sends prompts to the `/bench/chat/completions` endpoint, collects server-reported timing statistics, and records system-level metrics (power, GPU utilisation, temperature) throughout each run.
+
+The goal is to have accurate, transparent and reproducible numbers to compare speed and scaling across different models and different setups, and to be able to track these results as optimizations and features are added to EXO.
+
+Below is a technical summary of how Exo-Bench works. While the methodology and benchmark may change over time, this document will be kept up to date whenever this happens. If you find an issue with the methodology, or would like a  feature to be added, please open a GitHub issue!
+
+---
+
+## Prompt Construction
+
+Benchmarks need prompts of an exact token length. Unfortunately, we do not have direct access to the model but just the chat completion endpoint. To get around this fact, we create a request that will tokenise to a certain prompt length.
+
+This is achieved by:
+
+1. Tokenising a sample message through the model's `apply_chat_template()` to measure overhead (system tokens, special tokens, chat formatting).
+2. Binary-searching over a repeated atom string (default `"a "`) to find the content length that produces exactly the target number of tokens after template expansion.
+3. Returning both the content string and the verified token count.
+
+The actual token count is recorded in every result row as `pp_tokens`, so downstream analysis can confirm the prompt hit its target.
+
+Chat template formatting means that it may be impossible to attain very small pp benchmarks. e.g. pp=32 may not work. This tradeoff was made because the result of such a small prompt does not seem very interesting or useful for any real-world use cases.
+
+---
+
+## Bench Endpoint
+
+When a request reaches the server via the `/bench/chat/completions` endpoint, three things change compared to a normal chat completion:
+
+- **KV prefix cache is disabled by default**. Every request starts from a cold cache, ensuring prefill timing is not affected by prior requests. See [Prefix Cache Mode](#prefix-cache-mode) for the `--use-prefix-cache` option.
+- **EOS tokens are banned**. A logits processor suppresses all end-of-sequence tokens, forcing the model to generate exactly `max_tokens` tokens. This guarantees consistent generation length for fair TPS comparison — the model cannot short-circuit a run by stopping early.
+- **No model output parsing**. The bench collection path concatenates raw token text without any model-specific post-processing (thinking tag extraction, structured output handling, etc.). This is to avoid model outputs such as tool parsing or any structural mistakes from breaking the benchmark - we are testing for speed; see Exo-Eval for performance metrics.
+
+---
+
+## Timing
+
+### Prefill TPS
+
+Measured server-side per task.
+
+```
+prefill_tps = num_prompt_tokens / prefill_wall_seconds
+```
+
+### Generation TPS
+
+Measured server-side per task. Each task records wall-clock timestamps as tokens arrive:
+
+- First generated token: timestamp recorded
+- Every subsequent token: timestamp updated
+
+When generation completes:
+
+```
+gen_span = last_token_time - first_token_time
+generation_tps = (completion_tokens - 1) / gen_span
+```
+
+The first token is excluded from the numerator because the rate measures inter-token throughput — the time between the first and last token divided by the number of intervals.
+
+This does mean that tg=1 will not work.
+
+---
+
+## Concurrency
+
+### Single Request
+
+The client records wall-clock `elapsed_s` around the HTTP round-trip (network latency + server prefill + generation + response serialisation). This is a convenience metric for end-to-end latency. The authoritative TPS numbers come from the server-side per-task timing in the `generation_stats` response.
+
+### Concurrent Requests
+
+When `--concurrency N` is set with N > 1, all N requests must hit the server at the same instant. The mechanism:
+
+1. The prompt is built once and shared across all threads.
+2. Each thread gets its own HTTP connection.
+3. A thread barrier blocks all threads until every thread is ready.
+4. The first thread past the barrier records the batch start time and signals the others.
+5. All threads use the same start time as their reference, then fire their HTTP request.
+6. Each thread's `elapsed_s` is measured from the shared start time to its own response completion.
+
+**Batch wall time** is the maximum `elapsed_s` across all N requests — the time until the last request finishes.
+
+### Aggregate TPS
+
+```
+per_req_tps = max(generation_tps across N concurrent requests)
+agg_gen_tps = per_req_tps * concurrency
+```
+
+`max` is used instead of `mean` because all requests run in parallel against the same model. The fastest request's generation rate represents the system's per-stream throughput capacity; multiplying by concurrency gives aggregate throughput.
+
+---
+
+## Prefix Cache Mode
+
+When `--use-prefix-cache` is passed, the KV prefix cache remains active during benchmarking. This speeds up repeated runs by skipping redundant prefill work, which is useful when prompt processing is not the focus of the benchmark (e.g. when measuring generation throughput or power consumption across many configurations).
+
+Each response includes a `prefix_cache_hit` field (`"none"`, `"partial"`, or `"exact"`):
+
+- **none**: Cold prefill — no cached KV state was available. The reported `prompt_tps` is the real prefill throughput.
+- **partial**: A prefix of the prompt was found in cache. Only the remaining tokens were prefilled. The reported `prompt_tps` reflects the real throughput on the uncached portion. This occurs when multiple ascending `--pp` values share a common prefix (e.g. `--pp 1000,5000` — the 5000-token prompt reuses the 1000-token cache entry and prefills the remaining 4000 tokens).
+- **exact**: The entire prompt was found in cache (e.g. same `--pp` value on a `--repeat`). No prefill work was done. The reported `prompt_tps` is the TPS from when the cache entry was originally created, not a new measurement.
+
+**Prompt TPS is approximate in this mode.** Exact-hit runs report the stored TPS from the original cold/partial prefill rather than a freshly measured value. For accurate cold prefill numbers, run without `--use-prefix-cache`.
+
+Ascending `--pp` order (e.g. `--pp 1000,5000,10000`) gives the most useful data: each size gets a meaningful partial hit except the first which is cold. Descending order produces exact hits with approximate TPS from a longer prompt's original run.
+
+---
+
+## Warmup
+
+Before measurement begins, `--warmup N` (default: 0) discarded requests are sent using the first pp/tg pair. Warmup results are not included in the output.
+
+---
+
+## System Metrics
+
+A background thread polls each node at 1 Hz, collecting:
+
+- GPU utilisation (%)
+- Temperature (C)
+- System power draw (W)
+- CPU cluster usage (performance and efficiency cores)
+
+**Energy** is computed via trapezoidal integration of the power samples over each inference window (the wall-clock span of each benchmark request or concurrent batch). Average power is `total_joules / total_inference_seconds`.
+
+---
+
+## Output Format
+
+Results are written as JSON with three top-level keys:
+
+- **`runs`**: Array of per-request result objects, each containing:
+  - `elapsed_s`, `output_text_preview` (first 200 chars)
+  - `stats`: `{ prompt_tps, generation_tps, prompt_tokens, generation_tokens, peak_memory_usage }`
+  - Placement metadata: `model_id`, `placement_sharding`, `placement_instance_meta`, `placement_nodes`
+  - Run metadata: `pp_tokens`, `tg`, `repeat_index`, `concurrency`, `concurrent_index`
+  - `download_duration_s` (if model was freshly downloaded)
+- **`cluster`**: Cluster state snapshot at time of benchmarking.
+- **`system_metrics`**: Per-node time-series samples (GPU, power, temperature).
+
+---
+
+## Reproducing Results
+
+```bash
+cd bench && uv run python exo_bench.py \
+  --model "mlx-community/Qwen3.5-27B-4bit" \
+  --instance-meta jaccl \
+  --sharding tensor \
+  --min-nodes 2 --max-nodes 2 \
+  --pp 512 4096 --tg 128 \
+  --repeat 3 \
+  --warmup 1
+```
+
+Run --help for all the available flags.

bench/eval_tool_calls.py

@@ -17,6 +17,7 @@ from harness import (
     ExoClient,
     ExoHttpError,
     add_common_instance_args,
+    capture_cluster_snapshot,
     instance_id_from_instance,
     nodes_used_in_instance,
     resolve_model_short_id,
@@ -1006,6 +1007,7 @@ Examples:
         sys.exit(1)
 
     time.sleep(1)
+    cluster_snapshot = capture_cluster_snapshot(exo)
     all_results: list[ScenarioResult] = []
 
     try:
@@ -1084,16 +1086,19 @@ Examples:
                 print(f"  - {r.name} [{r.api}/{r.phase}]: {r.error}", file=log)
 
     json_results = [result_to_dict(r) for r in all_results]
+    output: dict[str, Any] = {"results": json_results}
+    if cluster_snapshot:
+        output["cluster"] = cluster_snapshot
 
     if args.stdout:
-        print(json.dumps(json_results, indent=2))
+        print(json.dumps(output, indent=2))
     else:
         json_path = args.json_out
         parent = os.path.dirname(json_path)
         if parent:
             os.makedirs(parent, exist_ok=True)
         with open(json_path, "w") as f:
-            json.dump(json_results, f, indent=2)
+            json.dump(output, f, indent=2)
             f.write("\n")
         print(f"\nJSON results written to {json_path}", file=log)
 

bench/exo_bench.py

@@ -22,6 +22,7 @@ import contextlib
 import itertools
 import json
 import sys
+import threading
 import time
 from collections.abc import Callable
 from concurrent.futures import ThreadPoolExecutor, as_completed
@@ -33,7 +34,9 @@ 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,
@@ -131,6 +134,91 @@ 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:
@@ -142,7 +230,13 @@ def parse_int_list(values: list[str]) -> list[int]:
 
 
 def run_one_completion(
-    client: ExoClient, model_id: str, pp_hint: int, tg: int, prompt_sizer: PromptSizer
+    client: ExoClient,
+    model_id: str,
+    pp_hint: int,
+    tg: int,
+    prompt_sizer: PromptSizer,
+    *,
+    use_prefix_cache: bool = False,
 ) -> tuple[dict[str, Any], int]:
     content, pp_tokens = prompt_sizer.build(pp_hint)
     payload: dict[str, Any] = {
@@ -150,6 +244,8 @@ def run_one_completion(
         "messages": [{"role": "user", "content": content}],
         "stream": False,
         "max_tokens": tg,
+        "logprobs": False,
+        "use_prefix_cache": use_prefix_cache,
     }
 
     t0 = time.perf_counter()
@@ -279,6 +375,22 @@ def main() -> int:
         action="store_true",
         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.",
+    )
+    ap.add_argument(
+        "--metrics-interval",
+        type=float,
+        default=1.0,
+        help="System metrics polling interval in seconds (default: 1.0).",
+    )
+    ap.add_argument(
+        "--use-prefix-cache",
+        action="store_true",
+        help="Enable KV prefix cache during bench (default: disabled for cold-cache measurements).",
+    )
     args = ap.parse_args()
 
     pp_list = parse_int_list(args.pp)
@@ -294,6 +406,15 @@ def main() -> int:
         logger.error("--concurrency values must be >= 1")
         return 2
 
+    if args.use_prefix_cache:
+        logger.warning(
+            "--use-prefix-cache: prompt TPS will be approximate. See METHODOLOGY.md for details."
+        )
+        if pp_list != sorted(pp_list):
+            logger.warning(
+                "--pp values are not in ascending order: prompt TPS will be less accurate. Use ascending --pp for best results."
+            )
+
     # Log pairing mode
     use_combinations = args.all_combinations or len(pp_list) != len(tg_list)
     if use_combinations:
@@ -364,7 +485,9 @@ def main() -> int:
     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"]
@@ -390,10 +513,25 @@ 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(
-                    client, full_model_id, pp_list[0], tg_list[0], prompt_sizer
+                    client,
+                    full_model_id,
+                    pp_list[0],
+                    tg_list[0],
+                    prompt_sizer,
+                    use_prefix_cache=args.use_prefix_cache,
                 )
                 logger.debug(f"  warmup {i + 1}/{args.warmup} done")
 
@@ -408,15 +546,23 @@ def main() -> int:
                 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
+                                    client,
+                                    full_model_id,
+                                    pp,
+                                    tg,
+                                    prompt_sizer,
+                                    use_prefix_cache=args.use_prefix_cache,
                                 )
+                                inference_windows.append((inf_t0, time.monotonic()))
                             except Exception as e:
                                 logger.error(e)
                                 continue
@@ -443,20 +589,54 @@ def main() -> int:
                             all_rows.append(row)
                         else:
                             # Concurrent: fire N requests in parallel
-                            # Each thread gets its own ExoClient (separate HTTP connection)
+                            # Pre-build prompt once, barrier ensures simultaneous dispatch
+                            content, actual_pp = prompt_sizer.build(pp)
+                            pre_built_payload: dict[str, Any] = {
+                                "model": full_model_id,
+                                "messages": [{"role": "user", "content": content}],
+                                "stream": False,
+                                "max_tokens": tg,
+                                "logprobs": False,
+                                "use_prefix_cache": args.use_prefix_cache,
+                            }
+                            barrier = threading.Barrier(concurrency)
+                            batch_start = threading.Event()
+                            batch_t0: float = 0.0
                             batch_results: list[tuple[dict[str, Any], int]] = []
                             batch_errors = 0
 
                             def _run_concurrent(
-                                idx: int, *, _pp: int = pp, _tg: int = tg
+                                idx: int,
+                                _barrier: threading.Barrier = barrier,
+                                _batch_start: threading.Event = batch_start,
+                                _payload: dict[str, Any] = pre_built_payload,
+                                _actual_pp: int = actual_pp,
                             ) -> tuple[dict[str, Any], int]:
+                                nonlocal batch_t0
                                 c = ExoClient(
                                     args.host, args.port, timeout_s=args.timeout
                                 )
-                                return run_one_completion(
-                                    c, full_model_id, _pp, _tg, prompt_sizer
+                                if _barrier.wait() == 0:
+                                    batch_t0 = time.perf_counter()
+                                    _batch_start.set()
+                                else:
+                                    _batch_start.wait()
+                                t0 = batch_t0
+                                out = c.post_bench_chat_completions(_payload)
+                                elapsed = time.perf_counter() - t0
+                                stats = out.get("generation_stats")
+                                choices = out.get("choices") or [{}]
+                                message = (
+                                    choices[0].get("message", {}) if choices else {}
                                 )
+                                text = message.get("content") or ""
+                                return {
+                                    "elapsed_s": elapsed,
+                                    "output_text_preview": text[:200],
+                                    "stats": stats,
+                                }, _actual_pp
 
+                            inf_t0 = time.monotonic()
                             with ThreadPoolExecutor(max_workers=concurrency) as pool:
                                 futures = {
                                     pool.submit(_run_concurrent, i): i
@@ -468,6 +648,12 @@ def main() -> int:
                                     except Exception as e:
                                         logger.error(f"Concurrent request failed: {e}")
                                         batch_errors += 1
+                            batch_wall_s = (
+                                max(x["elapsed_s"] for x, _ in batch_results)
+                                if batch_results
+                                else time.perf_counter() - batch_t0
+                            )
+                            inference_windows.append((inf_t0, time.monotonic()))
 
                             for idx, (row, actual_pp_tokens) in enumerate(
                                 batch_results
@@ -502,19 +688,25 @@ def main() -> int:
                                     if x["stats"]["generation_tps"] > 0
                                 ]
                                 per_req_tps = (
-                                    mean(valid_gen_tps) if valid_gen_tps else 0.0
+                                    max(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"wall_s={batch_wall_s:.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)
+                        valid_gen = [
+                            x["stats"]["generation_tps"]
+                            for x in runs
+                            if x["stats"]["generation_tps"] > 0
+                        ]
+                        per_req_tps = max(valid_gen) if valid_gen else 0.0
                         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)
@@ -522,13 +714,30 @@ def main() -> int:
                             x["stats"]["peak_memory_usage"]["inBytes"] for x in runs
                         )
 
-                        logger.info(
+                        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)}\n"
+                            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)
         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:
@@ -539,11 +748,17 @@ 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(all_rows, sys.stdout, indent=2, ensure_ascii=False)
+        json.dump(output, sys.stdout, indent=2, ensure_ascii=False)
     elif args.json_out:
         with open(args.json_out, "w", encoding="utf-8") as f:
-            json.dump(all_rows, f, indent=2, ensure_ascii=False)
+            json.dump(output, f, indent=2, ensure_ascii=False)
         logger.debug(f"\nWrote results JSON: {args.json_out}")
 
     return 0

bench/exo_eval.py

@@ -46,6 +46,7 @@ from harness import (
     ExoClient,
     ExoHttpError,
     add_common_instance_args,
+    capture_cluster_snapshot,
     instance_id_from_instance,
     nodes_used_in_instance,
     resolve_model_short_id,
@@ -1027,16 +1028,18 @@ def save_results(
     concurrency: int,
     results: list[QuestionResult],
     scores: dict[str, Any],
+    cluster: dict[str, Any] | None = None,
 ) -> Path:
     out_dir = Path(results_dir) / model.replace("/", "_") / benchmark_name
     out_dir.mkdir(parents=True, exist_ok=True)
     ts = time.strftime("%Y%m%d_%H%M%S")
     path = out_dir / f"c{concurrency}_{ts}.json"
 
-    data = {
+    data: dict[str, Any] = {
         "benchmark": benchmark_name,
         "model": model,
         "concurrency": concurrency,
+        **({"cluster": cluster} if cluster else {}),
         "scores": scores,
         "results": [
             {
@@ -1231,8 +1234,10 @@ def main() -> int:
                 client.request_json("DELETE", f"/instance/{instance_id}")
             return 1
         time.sleep(1)
+        cluster_snapshot = capture_cluster_snapshot(client)
     else:
         full_model_id = args.model
+        cluster_snapshot = None
 
     # Auto-detect reasoning from model config
     model_config = load_model_config(full_model_id)
@@ -1328,6 +1333,7 @@ def main() -> int:
                             c,
                             results,
                             scores,
+                            cluster=cluster_snapshot,
                         )
                         results_by_c[c] = results
                 if len(results_by_c) >= 2:
@@ -1358,6 +1364,7 @@ def main() -> int:
                         args.num_concurrent,
                         results,
                         scores,
+                        cluster=cluster_snapshot,
                     )
     finally:
         if instance_id is not None:

bench/harness.py

@@ -69,6 +69,35 @@ class ExoClient:
     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:
@@ -97,6 +126,11 @@ def runner_ids_from_instance(instance: dict[str, Any]) -> list[str]:
     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
 
@@ -116,13 +150,12 @@ def wait_for_instance_ready(
 ) -> None:
     start_time = time.time()
     instance_existed = False
+    last_loaded: dict[str, int] = {}
     while time.time() - start_time < timeout:
-        state = client.request_json("GET", "/state")
-        instances = state.get("instances", {})
+        instance = client.get_instance(instance_id)
 
-        if instance_id not in instances:
+        if instance is None:
             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)"
                 )
@@ -130,18 +163,25 @@ def wait_for_instance_ready(
             continue
 
         instance_existed = True
-        instance = instances[instance_id]
-        runner_ids = runner_ids_from_instance(instance)
-        runners = state.get("runners", {})
+        rids = runner_ids_from_instance(instance)
 
-        # Check for failed runners first
-        for rid in runner_ids:
-            runner = runners.get(rid, {})
+        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(runner_ready(runners.get(rid, {})) for rid in runner_ids):
+        if all_ready:
             return
 
         time.sleep(0.1)
@@ -165,6 +205,23 @@ def wait_for_instance_gone(
     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]:
@@ -326,16 +383,11 @@ def run_planning_phase(
     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", {})
-
     needs_download = False
 
     for node_id in node_ids:
-        node_downloads = downloads.get(node_id, [])
+        node_downloads = client.get_node_downloads(node_id) or []
 
-        # Check if model already downloaded on this node
         already_downloaded = any(
             "DownloadCompleted" in p
             and unwrap_instance(p["DownloadCompleted"]["shardMetadata"])["modelCard"][
@@ -349,8 +401,7 @@ def run_planning_phase(
 
         needs_download = True
 
-        # Wait for disk info if settle_deadline is set
-        disk_info = node_disk.get(node_id, {})
+        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()
@@ -359,9 +410,7 @@ def run_planning_phase(
             )
             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, {})
+            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")
@@ -377,7 +426,6 @@ def run_planning_phase(
                 f"have {avail // (1024**3)}GB. Use --danger-delete-downloads to free space."
             )
 
-        # Delete from smallest to largest (skip read-only models from EXO_MODELS_PATH)
         completed = [
             (
                 unwrap_instance(p["DownloadCompleted"]["shardMetadata"])["modelCard"][
@@ -417,21 +465,20 @@ def run_planning_phase(
     # 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:
+            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 downloads.get(node_id, [])
+                for p in node_downloads
             )
             failed = [
                 p["DownloadFailed"]["errorMessage"]
-                for p in downloads.get(node_id, [])
+                for p in node_downloads
                 if "DownloadFailed" in p
                 and unwrap_instance(p["DownloadFailed"]["shardMetadata"])["modelCard"][
                     "modelId"
@@ -442,6 +489,27 @@ def run_planning_phase(
                 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

dashboard/package-lock.json

@@ -11,7 +11,8 @@
 				"highlight.js": "^11.11.1",
 				"katex": "^0.16.27",
 				"marked": "^17.0.1",
-				"mode-watcher": "^1.1.0"
+				"mode-watcher": "^1.1.0",
+				"pdfjs-dist": "^5.6.205"
 			},
 			"devDependencies": {
 				"@sveltejs/adapter-static": "^3.0.10",
@@ -518,6 +519,256 @@
 				"@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",
@@ -2635,6 +2886,26 @@
 				"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",

dashboard/package.json

@@ -31,6 +31,7 @@
 		"highlight.js": "^11.11.1",
 		"katex": "^0.16.27",
 		"marked": "^17.0.1",
-		"mode-watcher": "^1.1.0"
+		"mode-watcher": "^1.1.0",
+		"pdfjs-dist": "^5.6.205"
 	}
 }

dashboard/src/lib/components/ChatMessages.svelte

@@ -139,6 +139,8 @@
         return "🖼";
       case "text":
         return "📄";
+      case "pdf":
+        return "📑";
       default:
         return "📎";
     }

dashboard/src/lib/components/FamilyLogos.svelte

@@ -94,6 +94,12 @@
       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 if family === "gemma"}
+  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
+    <path
+      d="M12.48 10.92v3.28h7.84c-.24 1.84-.853 3.187-1.787 4.133-1.147 1.147-2.933 2.4-6.053 2.4-4.827 0-8.6-3.893-8.6-8.72s3.773-8.72 8.6-8.72c2.6 0 4.507 1.027 5.907 2.347l2.307-2.307C18.747 1.44 16.133 0 12.48 0 5.867 0 .307 5.387.307 12s5.56 12 12.173 12c3.573 0 6.267-1.173 8.373-3.36 2.16-2.16 2.84-5.213 2.84-7.667 0-.76-.053-1.467-.173-2.053H12.48z"
+    />
+  </svg>
 {:else}
   <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
     <path

dashboard/src/lib/components/FamilySidebar.svelte

@@ -32,6 +32,7 @@
     flux: "FLUX",
     "qwen-image": "Qwen Img",
     nemotron: "NVIDIA",
+    gemma: "Google",
   };
 
   function getFamilyName(family: string): string {
@@ -42,31 +43,20 @@
 </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-[72px] sm:min-w-[64px] 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-[80px] sm:min-w-[72px] overflow-y-auto scrollbar-hide"
 >
   <!-- All models (no filter) -->
   <button
     type="button"
     onclick={() => onSelect(null)}
-    class="group flex flex-col items-center justify-center p-2 sm:p-2 rounded transition-all duration-200 cursor-pointer min-h-[44px] sm:min-h-0 {selectedFamily ===
+    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 ===
     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-[9px] font-mono mt-0.5 {selectedFamily === null
+      class="text-[12px] font-mono font-medium {selectedFamily === null
         ? 'text-exo-yellow'
         : 'text-white/40 group-hover:text-white/60'}">All</span
     >
@@ -90,7 +80,7 @@
           : "text-white/50 group-hover:text-amber-400/70"}
       />
       <span
-        class="text-[9px] font-mono mt-0.5 {selectedFamily === 'favorites'
+        class="text-[11px] font-mono mt-0.5 {selectedFamily === 'favorites'
           ? 'text-amber-400'
           : 'text-white/40 group-hover:text-white/60'}">Faves</span
       >
@@ -115,7 +105,7 @@
           : "text-white/50 group-hover:text-white/70"}
       />
       <span
-        class="text-[9px] font-mono mt-0.5 {selectedFamily === 'recents'
+        class="text-[11px] font-mono mt-0.5 {selectedFamily === 'recents'
           ? 'text-exo-yellow'
           : 'text-white/40 group-hover:text-white/60'}">Recent</span
       >
@@ -139,7 +129,7 @@
         : "text-white/50 group-hover:text-orange-400/70"}
     />
     <span
-      class="text-[9px] font-mono mt-0.5 {selectedFamily === 'huggingface'
+      class="text-[11px] font-mono mt-0.5 {selectedFamily === 'huggingface'
         ? 'text-orange-400'
         : 'text-white/40 group-hover:text-white/60'}">Hub</span
     >
@@ -165,7 +155,7 @@
           : "text-white/50 group-hover:text-white/70"}
       />
       <span
-        class="text-[9px] font-mono mt-0.5 truncate max-w-full {selectedFamily ===
+        class="text-[11px] font-mono mt-0.5 truncate max-w-full {selectedFamily ===
         family
           ? 'text-exo-yellow'
           : 'text-white/40 group-hover:text-white/60'}"

dashboard/src/lib/components/HeaderNav.svelte

@@ -1,21 +1,38 @@
 <script lang="ts">
   import { browser } from "$app/environment";
 
-  export let showHome = true;
-  export let onHome: (() => void) | null = null;
-  export let showSidebarToggle = false;
-  export let sidebarVisible = true;
-  export let onToggleSidebar: (() => void) | null = null;
-  export let showMobileMenuToggle = false;
-  export let mobileMenuOpen = false;
-  export let onToggleMobileMenu: (() => void) | null = null;
-  export let showMobileRightToggle = false;
-  export let mobileRightOpen = false;
-  export let onToggleMobileRight: (() => void) | null = null;
-  export let downloadProgress: {
-    count: number;
-    percentage: number;
-  } | null = null;
+  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();
 
   function handleHome(): void {
     if (onHome) {
@@ -259,5 +276,26 @@
       {/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"
+        viewBox="0 0 24 24"
+        fill="none"
+        stroke="currentColor"
+        stroke-width="2"
+        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"
+        />
+      </svg>
+      <span class="hidden sm:inline">Integrations</span>
+    </a>
   </nav>
 </header>

dashboard/src/lib/components/IntegrationCard.svelte

@@ -0,0 +1,62 @@
+<script lang="ts">
+  import { copyText } from "$lib/utils/clipboard";
+
+  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);
+  let failed = $state(false);
+
+  async function copyToClipboard() {
+    const ok = await copyText(config);
+    if (ok) {
+      copied = true;
+      setTimeout(() => (copied = false), 2000);
+    } else {
+      failed = true;
+      setTimeout(() => (failed = 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'
+        : failed
+          ? 'border-red-500/50 text-red-400 bg-red-500/10'
+          : 'border-exo-light-gray/30 text-exo-light-gray hover:border-exo-yellow/50 hover:text-exo-yellow'}"
+    >
+      {copied ? "Copied!" : failed ? "Copy failed" : "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>

dashboard/src/lib/components/ModelFilterPopover.svelte

@@ -73,7 +73,7 @@
 
 <!-- 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-10"
+  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"
   transition:fly={{ y: -10, duration: 200, easing: cubicOut }}
   onclick={(e) => e.stopPropagation()}
   role="dialog"

dashboard/src/lib/components/ModelPickerModal.svelte

@@ -457,6 +457,7 @@
       "deepseek",
       "gpt-oss",
       "llama",
+      "gemma",
       "flux",
       "qwen-image",
       "nemotron",

dashboard/src/lib/components/index.ts

@@ -13,3 +13,4 @@ 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";

dashboard/src/lib/stores/app.svelte.ts

@@ -257,11 +257,12 @@ interface RawStateResponse {
 }
 
 export interface MessageAttachment {
-  type: "image" | "text" | "file" | "generated-image";
+  type: "image" | "text" | "file" | "generated-image" | "pdf";
   name: string;
   content?: string;
   preview?: string;
   mimeType?: string;
+  pageImages?: string[];
 }
 
 export interface TopLogprob {
@@ -2242,6 +2243,7 @@ class AppStore {
       type: string;
       textContent?: string;
       preview?: string;
+      pageImages?: string[];
     }[],
     enableThinking?: boolean | null,
   ): Promise<void> {
@@ -2277,6 +2279,20 @@ 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",
@@ -2344,13 +2360,70 @@ class AppStore {
       const apiMessages = [
         systemPrompt,
         ...targetConversation.messages.slice(0, -1).map((m) => {
-          // Build content including any text file attachments
+          // 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)
           let msgContent = m.content;
 
-          // Add text attachments as context
+          // Add text/pdf attachments as context
           if (m.attachments) {
             for (const attachment of m.attachments) {
-              if (attachment.type === "text" && attachment.content) {
+              if (
+                (attachment.type === "text" || attachment.type === "pdf") &&
+                attachment.content
+              ) {
                 msgContent += `\n\n[File: ${attachment.name}]\n\`\`\`\n${attachment.content}\n\`\`\``;
               }
             }
@@ -2650,6 +2723,9 @@ 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);
@@ -2704,6 +2780,7 @@ class AppStore {
           "Content-Type": "application/json",
         },
         body: JSON.stringify(requestBody),
+        signal: abortController.signal,
       });
 
       if (!response.ok) {
@@ -2843,14 +2920,27 @@ class AppStore {
         );
       }
     } catch (error) {
-      console.error("Error generating image:", error);
-      this.handleStreamingError(
-        error,
-        targetConversationId,
-        assistantMessage.id,
-        "Failed to generate image",
-      );
+      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",
+        );
+      }
     } finally {
+      this.currentAbortController = null;
       this.isLoading = false;
       this.saveConversationsToStorage();
     }
@@ -2914,6 +3004,9 @@ 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);
@@ -2975,6 +3068,7 @@ class AppStore {
       const apiResponse = await fetch("/v1/images/edits", {
         method: "POST",
         body: formData,
+        signal: abortController.signal,
       });
 
       if (!apiResponse.ok) {
@@ -3075,14 +3169,27 @@ class AppStore {
         );
       }
     } catch (error) {
-      console.error("Error editing image:", error);
-      this.handleStreamingError(
-        error,
-        targetConversationId,
-        assistantMessage.id,
-        "Failed to edit image",
-      );
+      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",
+        );
+      }
     } finally {
+      this.currentAbortController = null;
       this.isLoading = false;
       this.saveConversationsToStorage();
     }
@@ -3149,6 +3256,31 @@ class AppStore {
     }
   }
 
+  /**
+   * Cancel/pause an active download on a specific node
+   */
+  async cancelDownload(nodeId: string, modelId: string): Promise<void> {
+    try {
+      const response = await fetch("/download/cancel", {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({
+          targetNodeId: nodeId,
+          modelId: modelId,
+        }),
+      });
+      if (!response.ok) {
+        const errorText = await response.text();
+        throw new Error(
+          `Failed to cancel download: ${response.status} - ${errorText}`,
+        );
+      }
+    } catch (error) {
+      console.error("Error cancelling download:", error);
+      throw error;
+    }
+  }
+
   /**
    * Delete a downloaded model from a specific node
    */
@@ -3271,6 +3403,7 @@ export const sendMessage = (
     type: string;
     textContent?: string;
     preview?: string;
+    pageImages?: string[];
   }[],
   enableThinking?: boolean | null,
 ) => appStore.sendMessage(content, files, enableThinking);
@@ -3369,6 +3502,8 @@ export const resetImageGenerationParams = () =>
 // Download actions
 export const startDownload = (nodeId: string, shardMetadata: object) =>
   appStore.startDownload(nodeId, shardMetadata);
+export const cancelDownload = (nodeId: string, modelId: string) =>
+  appStore.cancelDownload(nodeId, modelId);
 export const deleteDownload = (nodeId: string, modelId: string) =>
   appStore.deleteDownload(nodeId, modelId);
 

dashboard/src/lib/types/files.ts

@@ -2,6 +2,41 @@
  * File attachment types for the chat interface
  */
 
+import { getDocument, GlobalWorkerOptions, version } from "pdfjs-dist";
+import type { DocumentInitParameters } from "pdfjs-dist/types/src/display/api";
+
+// Safari (through at least 18/26) does not implement
+// ReadableStream.prototype[Symbol.asyncIterator], which pdfjs-dist uses
+// internally in getTextContent(). Without this polyfill, `for await (const n
+// of stream)` throws "undefined is not a function" and PDF processing fails.
+if (
+  typeof ReadableStream !== "undefined" &&
+  !(ReadableStream.prototype as unknown as Record<symbol, unknown>)[
+    Symbol.asyncIterator
+  ]
+) {
+  (ReadableStream.prototype as unknown as Record<symbol, unknown>)[
+    Symbol.asyncIterator
+  ] = async function* (this: ReadableStream<unknown>) {
+    const reader = this.getReader();
+    try {
+      while (true) {
+        const { done, value } = await reader.read();
+        if (done) return;
+        yield value;
+      }
+    } finally {
+      reader.releaseLock();
+    }
+  };
+}
+
+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;
@@ -10,6 +45,7 @@ export interface ChatUploadedFile {
   file: File;
   preview?: string;
   textContent?: string;
+  pageImages?: string[];
 }
 
 export interface ChatAttachment {
@@ -194,6 +230,58 @@ 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
  */
@@ -223,7 +311,12 @@ export async function processUploadedFiles(
         const textContent = await readFileAsText(file);
         results.push({ ...base, textContent });
       } else if (category === "pdf") {
-        results.push(base);
+        const { text, pageImages } = await extractPdfContent(file);
+        results.push({
+          ...base,
+          textContent: text || undefined,
+          pageImages: pageImages.length > 0 ? pageImages : undefined,
+        });
       } else if (category === "audio") {
         const preview = await readFileAsDataURL(file);
         results.push({ ...base, preview });

dashboard/src/lib/utils/clipboard.ts

@@ -0,0 +1,55 @@
+export async function copyText(text: string): Promise<boolean> {
+  if (
+    typeof window !== "undefined" &&
+    window.isSecureContext &&
+    navigator.clipboard?.writeText
+  ) {
+    try {
+      await navigator.clipboard.writeText(text);
+      return true;
+    } catch {
+      // fall through to execCommand fallback
+    }
+  }
+
+  if (typeof document === "undefined") {
+    return false;
+  }
+
+  const textarea = document.createElement("textarea");
+  textarea.value = text;
+  textarea.setAttribute("readonly", "");
+  textarea.style.position = "fixed";
+  textarea.style.top = "0";
+  textarea.style.left = "0";
+  textarea.style.width = "1px";
+  textarea.style.height = "1px";
+  textarea.style.padding = "0";
+  textarea.style.border = "none";
+  textarea.style.outline = "none";
+  textarea.style.boxShadow = "none";
+  textarea.style.background = "transparent";
+  textarea.style.opacity = "0";
+  document.body.appendChild(textarea);
+
+  const previousSelection = document.getSelection();
+  const previousRange =
+    previousSelection && previousSelection.rangeCount > 0
+      ? previousSelection.getRangeAt(0)
+      : null;
+
+  try {
+    textarea.focus();
+    textarea.select();
+    textarea.setSelectionRange(0, text.length);
+    return document.execCommand("copy");
+  } catch {
+    return false;
+  } finally {
+    document.body.removeChild(textarea);
+    if (previousRange && previousSelection) {
+      previousSelection.removeAllRanges();
+      previousSelection.addRange(previousRange);
+    }
+  }
+}

dashboard/src/routes/+page.svelte

@@ -265,6 +265,7 @@
 
   let mounted = $state(false);
   let localNodeId = $state<string | null>(null);
+  let pendingFirefoxQuery = $state<string | null>(null); // ?q= param deferred until state loads
 
   // ── Onboarding wizard state ──
   const ONBOARDING_COMPLETE_KEY = "exo-onboarding-complete";
@@ -1309,6 +1310,20 @@
       return;
     }
 
+    // Firefox AI sidebar integration: handle ?q= query parameter
+    // Firefox's built-in AI sidebar (about:config: browser.ml.chat.enabled) sends
+    // the user's prompt as ?q=<URL-encoded prompt> to the configured provider URL.
+    // See: https://support.mozilla.org/en-US/kb/ai-chatbot
+    const queryParam = params.get("q");
+    if (queryParam) {
+      // Clean up the URL to prevent re-submission on page refresh
+      window.history.replaceState({}, "", window.location.pathname);
+      // Defer the auto-send until cluster state is loaded (topologyData,
+      // instances, availableMemory) so that model auto-selection works
+      // correctly. The $effect below will pick this up once data is ready.
+      pendingFirefoxQuery = queryParam;
+    }
+
     // Check server-side onboarding state (persisted in ~/.exo)
     try {
       const res = await fetch("/onboarding");
@@ -1329,6 +1344,18 @@
     }
   });
 
+  // Deferred Firefox AI sidebar auto-send: wait for cluster state and model
+  // list before submitting. Both data (from /state polling) and models (from
+  // the async /models fetch in onMount) must be loaded for handleAutoSend to
+  // correctly auto-select a model.
+  $effect(() => {
+    if (pendingFirefoxQuery && data && models.length > 0) {
+      const query = pendingFirefoxQuery;
+      pendingFirefoxQuery = null;
+      handleChatSend(query);
+    }
+  });
+
   async function fetchModels() {
     try {
       const response = await fetch("/models");

dashboard/src/routes/downloads/+page.svelte

@@ -9,6 +9,7 @@
     refreshState,
     lastUpdate as lastUpdateStore,
     startDownload,
+    cancelDownload,
     deleteDownload,
   } from "$lib/stores/app.svelte";
   import {
@@ -349,6 +350,59 @@
   });
 </script>
 
+{#snippet trashIcon()}
+  <svg
+    class="w-5 h-5"
+    viewBox="0 0 20 20"
+    fill="none"
+    stroke="currentColor"
+    stroke-width="2"
+  >
+    <path
+      d="M4 6h12M8 6V4h4v2m1 0v10a1 1 0 01-1 1H8a1 1 0 01-1-1V6h6"
+      stroke-linecap="round"
+      stroke-linejoin="round"
+    ></path>
+  </svg>
+{/snippet}
+
+{#snippet downloadIcon(size?: string)}
+  <svg
+    class={size ?? "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>
+{/snippet}
+
+{#snippet pauseIcon()}
+  <svg class="w-5 h-5" viewBox="0 0 20 20" fill="currentColor">
+    <path
+      fill-rule="evenodd"
+      d="M6 4h2v12H6V4zm6 0h2v12h-2V4z"
+      clip-rule="evenodd"
+    ></path>
+  </svg>
+{/snippet}
+
+{#snippet deleteButton(nodeId: string, modelId: string)}
+  <button
+    type="button"
+    class="text-white/50 hover:text-red-400 transition-colors cursor-pointer"
+    onclick={() => deleteDownload(nodeId, modelId)}
+    title="Delete from this node"
+  >
+    {@render trashIcon()}
+  </button>
+{/snippet}
+
 <div class="min-h-screen bg-exo-dark-gray text-white">
   <HeaderNav showHome={true} />
   <div class="max-w-7xl mx-auto px-4 lg:px-8 py-6 space-y-6">
@@ -486,27 +540,7 @@
                         <span class="text-xs text-white/70"
                           >{formatBytes(cell.totalBytes)}</span
                         >
-                        <button
-                          type="button"
-                          class="text-white/50 hover:text-red-400 transition-colors mt-0.5 cursor-pointer"
-                          onclick={() =>
-                            deleteDownload(col.nodeId, row.modelId)}
-                          title="Delete from this node"
-                        >
-                          <svg
-                            class="w-5 h-5"
-                            viewBox="0 0 20 20"
-                            fill="none"
-                            stroke="currentColor"
-                            stroke-width="2"
-                          >
-                            <path
-                              d="M4 6h12M8 6V4h4v2m1 0v10a1 1 0 01-1 1H8a1 1 0 01-1-1V6h6"
-                              stroke-linecap="round"
-                              stroke-linejoin="round"
-                            ></path>
-                          </svg>
-                        </button>
+                        {@render deleteButton(col.nodeId, row.modelId)}
                       </div>
                     {:else if cell.kind === "downloading"}
                       <div
@@ -533,6 +567,18 @@
                         <span class="text-[10px] text-white/70"
                           >{formatSpeed(cell.speed)}</span
                         >
+                        <div class="flex gap-1 mt-0.5">
+                          <button
+                            type="button"
+                            class="text-white/50 hover:text-exo-yellow transition-colors cursor-pointer"
+                            onclick={() =>
+                              cancelDownload(col.nodeId, row.modelId)}
+                            title="Pause download"
+                          >
+                            {@render pauseIcon()}
+                          </button>
+                          {@render deleteButton(col.nodeId, row.modelId)}
+                        </div>
                       </div>
                     {:else if cell.kind === "pending"}
                       <div
@@ -558,32 +604,24 @@
                               ).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"
+                          <div class="flex gap-1">
+                            {#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"
                               >
-                                <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}
+                                {@render downloadIcon()}
+                              </button>
+                            {:else}
+                              <span class="text-white/50 text-[10px]"
+                                >paused</span
+                              >
+                            {/if}
+                            {@render deleteButton(col.nodeId, row.modelId)}
+                          </div>
                         {:else if row.shardMetadata}
                           <button
                             type="button"
@@ -592,19 +630,7 @@
                               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>
+                            {@render downloadIcon("w-6 h-6")}
                           </button>
                         {:else}
                           <span class="text-white/40 text-sm">...</span>
@@ -626,29 +652,20 @@
                             clip-rule="evenodd"
                           ></path>
                         </svg>
-                        {#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="Retry download on this node"
-                          >
-                            <svg
-                              class="w-5 h-5"
-                              viewBox="0 0 20 20"
-                              fill="none"
-                              stroke="currentColor"
-                              stroke-width="2"
+                        <div class="flex gap-1">
+                          {#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="Retry download on this node"
                             >
-                              <path
-                                d="M10 3v10m0 0l-3-3m3 3l3-3M3 17h14"
-                                stroke-linecap="round"
-                                stroke-linejoin="round"
-                              ></path>
-                            </svg>
-                          </button>
-                        {/if}
+                              {@render downloadIcon()}
+                            </button>
+                          {/if}
+                          {@render deleteButton(col.nodeId, row.modelId)}
+                        </div>
                       </div>
                     {:else}
                       <div
@@ -666,19 +683,7 @@
                               startDownload(col.nodeId, row.shardMetadata!)}
                             title="Download to 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>
+                            {@render downloadIcon()}
                           </button>
                         {/if}
                       </div>

dashboard/src/routes/integrations/+page.svelte

@@ -0,0 +1,577 @@
+<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>

docs/architecture.md

@@ -81,4 +81,4 @@ Whenever a device produces side effects, it captures those side effects in an `E
 
 ## Purity
 
-A significant goal of the current design is to make data flow explicit. Classes should either represent simple data (`CamelCaseModel`s typically, and `TaggedModel`s for unions) or active `System`s (Erlang `Actor`s), with all transformations of that data being "referentially transparent" - destructure and construct new data, don't mutate in place. We have had varying degrees of success with this, and are still exploring where purity makes sense.
+A significant goal of the current design is to make data flow explicit. Classes should either represent simple data (`FrozenModel`s typically, and `TaggedModel`s for unions) or active `System`s (Erlang `Actor`s), with all transformations of that data being "referentially transparent" - destructure and construct new data, don't mutate in place. We have had varying degrees of success with this, and are still exploring where purity makes sense.

flake.lock

@@ -2,11 +2,11 @@
   "nodes": {
     "crane": {
       "locked": {
-        "lastModified": 1767744144,
-        "narHash": "sha256-9/9ntI0D+HbN4G0TrK3KmHbTvwgswz7p8IEJsWyef8Q=",
+        "lastModified": 1775790182,
+        "narHash": "sha256-pG2RWVQY0Pe+rmmXJx+Jpyi+JcgjWzS18m7fcD1B64Q=",
         "owner": "ipetkov",
         "repo": "crane",
-        "rev": "2fb033290bf6b23f226d4c8b32f7f7a16b043d7e",
+        "rev": "534982f1c41834b101e381b07b1121a4f065a374",
         "type": "github"
       },
       "original": {
@@ -47,11 +47,11 @@
         "rust-analyzer-src": "rust-analyzer-src"
       },
       "locked": {
-        "lastModified": 1768287139,
-        "narHash": "sha256-nsXFt0OzUi6K7dUzzJD5/v9e0Ic+fvclfIW936/43ZM=",
+        "lastModified": 1775807984,
+        "narHash": "sha256-Redoe3D9zGN5I9QPHWL9vfMVQBehY1fKsMiRXQ83X3w=",
         "owner": "nix-community",
         "repo": "fenix",
-        "rev": "a4a3aa956931f90f35453cb519e4545e9ad7f773",
+        "rev": "fcf90c0c4d368b2ca917a7afa6d08e98a397e5fd",
         "type": "github"
       },
       "original": {
@@ -83,11 +83,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1768135262,
-        "narHash": "sha256-PVvu7OqHBGWN16zSi6tEmPwwHQ4rLPU9Plvs8/1TUBY=",
+        "lastModified": 1775087534,
+        "narHash": "sha256-91qqW8lhL7TLwgQWijoGBbiD4t7/q75KTi8NxjVmSmA=",
         "owner": "hercules-ci",
         "repo": "flake-parts",
-        "rev": "80daad04eddbbf5a4d883996a73f3f542fa437ac",
+        "rev": "3107b77cd68437b9a76194f0f7f9c55f2329ca5b",
         "type": "github"
       },
       "original": {
@@ -96,38 +96,42 @@
         "type": "github"
       }
     },
+    "nixglhost": {
+      "inputs": {
+        "nixpkgs": [
+          "nixpkgs"
+        ]
+      },
+      "locked": {
+        "lastModified": 1732211616,
+        "narHash": "sha256-QZCKJoypcwgS3tDNSWMjlxEBZtOYPW3eXV24rMzKsac=",
+        "owner": "numtide",
+        "repo": "nix-gl-host",
+        "rev": "5269b233f83880a0b433eafe026f0bc0d8f1a4a9",
+        "type": "github"
+      },
+      "original": {
+        "owner": "numtide",
+        "repo": "nix-gl-host",
+        "type": "github"
+      }
+    },
     "nixpkgs": {
       "locked": {
-        "lastModified": 1768127708,
-        "narHash": "sha256-1Sm77VfZh3mU0F5OqKABNLWxOuDeHIlcFjsXeeiPazs=",
+        "lastModified": 1775595990,
+        "narHash": "sha256-OEf7YqhF9IjJFYZJyuhAypgU+VsRB5lD4DuiMws5Ltc=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "ffbc9f8cbaacfb331b6017d5a5abb21a492c9a38",
+        "rev": "4e92bbcdb030f3b4782be4751dc08e6b6cb6ccf2",
         "type": "github"
       },
       "original": {
         "owner": "NixOS",
-        "ref": "nixos-unstable",
+        "ref": "nixos-25.11",
         "repo": "nixpkgs",
         "type": "github"
       }
     },
-    "nixpkgs-swift": {
-      "locked": {
-        "lastModified": 1761672384,
-        "narHash": "sha256-o9KF3DJL7g7iYMZq9SWgfS1BFlNbsm6xplRjVlOCkXI=",
-        "owner": "NixOS",
-        "repo": "nixpkgs",
-        "rev": "08dacfca559e1d7da38f3cf05f1f45ee9bfd213c",
-        "type": "github"
-      },
-      "original": {
-        "owner": "NixOS",
-        "repo": "nixpkgs",
-        "rev": "08dacfca559e1d7da38f3cf05f1f45ee9bfd213c",
-        "type": "github"
-      }
-    },
     "purescript-overlay": {
       "inputs": {
         "flake-compat": "flake-compat",
@@ -164,11 +168,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1763662255,
-        "narHash": "sha256-4bocaOyLa3AfiS8KrWjZQYu+IAta05u3gYZzZ6zXbT0=",
+        "lastModified": 1773870109,
+        "narHash": "sha256-ZoTdqZP03DcdoyxvpFHCAek4bkPUTUPUF3oCCgc3dP4=",
         "owner": "pyproject-nix",
         "repo": "build-system-pkgs",
-        "rev": "042904167604c681a090c07eb6967b4dd4dae88c",
+        "rev": "b6e74f433b02fa4b8a7965ee24680f4867e2926f",
         "type": "github"
       },
       "original": {
@@ -184,11 +188,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1764134915,
-        "narHash": "sha256-xaKvtPx6YAnA3HQVp5LwyYG1MaN4LLehpQI8xEdBvBY=",
+        "lastModified": 1775439158,
+        "narHash": "sha256-NHY9SJNU019n+8NCabBDtmuzRFeE2gZlYKHowp9bV24=",
         "owner": "pyproject-nix",
         "repo": "pyproject.nix",
-        "rev": "2c8df1383b32e5443c921f61224b198a2282a657",
+        "rev": "fb6b728260f3f32761367e9fd1e1a25b4245bcd0",
         "type": "github"
       },
       "original": {
@@ -203,8 +207,8 @@
         "dream2nix": "dream2nix",
         "fenix": "fenix",
         "flake-parts": "flake-parts",
+        "nixglhost": "nixglhost",
         "nixpkgs": "nixpkgs",
-        "nixpkgs-swift": "nixpkgs-swift",
         "pyproject-build-systems": "pyproject-build-systems",
         "pyproject-nix": "pyproject-nix",
         "treefmt-nix": "treefmt-nix",
@@ -214,11 +218,11 @@
     "rust-analyzer-src": {
       "flake": false,
       "locked": {
-        "lastModified": 1768224240,
-        "narHash": "sha256-Pp1dDrXKPBUJReZnnDElFyHYn67XTd48zRhToheLjtk=",
+        "lastModified": 1775745684,
+        "narHash": "sha256-8MbfLwd60FNa8dRFkjE+G3TT/x21G3Rsplm1bMBQUtU=",
         "owner": "rust-lang",
         "repo": "rust-analyzer",
-        "rev": "725349602e525df37f377701e001fe8aab807878",
+        "rev": "64ddb549bc9a70d011328746fa46a8883f937b6b",
         "type": "github"
       },
       "original": {
@@ -257,11 +261,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1768158989,
-        "narHash": "sha256-67vyT1+xClLldnumAzCTBvU0jLZ1YBcf4vANRWP3+Ak=",
+        "lastModified": 1775636079,
+        "narHash": "sha256-pc20NRoMdiar8oPQceQT47UUZMBTiMdUuWrYu2obUP0=",
         "owner": "numtide",
         "repo": "treefmt-nix",
-        "rev": "e96d59dff5c0d7fddb9d113ba108f03c3ef99eca",
+        "rev": "790751ff7fd3801feeaf96d7dc416a8d581265ba",
         "type": "github"
       },
       "original": {
@@ -280,11 +284,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1767701098,
-        "narHash": "sha256-CJhKZnWb3gumR9oTRjFvCg/6lYTGbZRU7xtvcyWIRwU=",
+        "lastModified": 1775706324,
+        "narHash": "sha256-BTb4sydzX2B5/oNbvCdQFeSbk97xEnbb8bk84CiKCOs=",
         "owner": "pyproject-nix",
         "repo": "uv2nix",
-        "rev": "9d357f0d2ce6f5f35ec7959d7e704452352eb4da",
+        "rev": "5707df99097375896a3dda811d492a2fabe63500",
         "type": "github"
       },
       "original": {

flake.nix

@@ -2,7 +2,7 @@
   description = "The development environment for Exo";
 
   inputs = {
-    nixpkgs.url = "github:NixOS/nixpkgs/nixos-unstable";
+    nixpkgs.url = "github:NixOS/nixpkgs/nixos-25.11";
 
     flake-parts = {
       url = "github:hercules-ci/flake-parts";
@@ -46,17 +46,18 @@
       inputs.nixpkgs.follows = "nixpkgs";
     };
 
-    # Pinned nixpkgs for swift-format (swift is broken on x86_64-linux in newer nixpkgs)
-    nixpkgs-swift.url = "github:NixOS/nixpkgs/08dacfca559e1d7da38f3cf05f1f45ee9bfd213c";
+    nixglhost = {
+      url = "github:numtide/nix-gl-host";
+      inputs.nixpkgs.follows = "nixpkgs";
+    };
   };
 
   nixConfig = {
-    extra-trusted-public-keys = "exo.cachix.org-1:okq7hl624TBeAR3kV+g39dUFSiaZgLRkLsFBCuJ2NZI=";
-    extra-substituters = "https://exo.cachix.org";
+    extra-trusted-public-keys = "exo.cachix.org-1:okq7hl624TBeAR3kV+g39dUFSiaZgLRkLsFBCuJ2NZI= cache.nixos-cuda.org:74DUi4Ye579gUqzH4ziL9IyiJBlDpMRn9MBN8oNan9M=";
+    extra-substituters = "https://exo.cachix.org https://cache.nixos-cuda.org";
   };
 
-  outputs =
-    inputs:
+  outputs = inputs:
     inputs.flake-parts.lib.mkFlake { inherit inputs; } {
       systems = [
         "x86_64-linux"
@@ -71,32 +72,38 @@
         ./python/parts.nix
       ];
 
-      perSystem =
-        { config, self', pkgs, lib, system, ... }:
+      debug = true; # Enable options autocompletion
+
+      perSystem = { config, self', pkgs, lib, system, ... }:
         let
-          # Use pinned nixpkgs for swift-format (swift is broken on x86_64-linux in newer nixpkgs)
-          pkgsSwift = import inputs.nixpkgs-swift { inherit system; };
-        in
-        {
-          # Allow unfree for metal-toolchain (needed for Darwin Metal packages)
-          _module.args.pkgs = import inputs.nixpkgs {
+          pkgsArgs = {
             inherit system;
             config.allowUnfreePredicate = pkg: (pkg.pname or "") == "metal-toolchain";
             overlays = [
+              inputs.nixglhost.overlays.default
               (import ./nix/apple-sdk-overlay.nix)
-              (final: prev: {
-                macmon = prev.macmon.overrideAttrs (_: {
+              (final: _: {
+                macmon = final.rustPlatform.buildRustPackage {
+                  pname = "macmon";
                   version = "git";
                   src = final.fetchFromGitHub {
-                    owner = "swiftraccoon";
+                    owner = "vladkens";
                     repo = "macmon";
-                    rev = "9154d234f763fbeffdcb4135d0bbbaf80609699b";
-                    hash = "sha256-CwhilKNbs5XL9/tF5DMwyPBlE/hpmjGNTuxQ36sM50M=";
+                    rev = "a1cd06b6cc0d5e61db24fd8832e74cd992097a7d";
+                    hash = "sha256-wcq4PUXK44XfUKOZKl32u8LpOxXpSbUUfItQGwS2Zso=";
                   };
-                });
+                  cargoHash = "sha256-Epj3L+db1flGNK5y6yfSig8piEiXTz15lPo/FNkqlkA=";
+                };
               })
             ];
           };
+        in
+        {
+          # Allow unfree for metal-toolchain (needed for Darwin Metal packages)
+          _module.args = {
+            pkgs = import inputs.nixpkgs pkgsArgs;
+            unfreePkgs = import inputs.nixpkgs (pkgsArgs // { config.allowUnfree = true; });
+          };
           treefmt = {
             projectRootFile = "flake.nix";
             programs = {
@@ -116,29 +123,19 @@
               };
               swift-format = {
                 enable = true;
-                package = pkgsSwift.swiftPackages.swift-format;
+                package = pkgs.swiftPackages.swift-format;
               };
               shfmt.enable = true;
               taplo.enable = true;
             };
           };
 
-          packages = lib.optionalAttrs pkgs.stdenv.hostPlatform.isDarwin (
-            let
-              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;
-              };
-              default = self'.packages.exo;
-            }
-          );
+          packages = {
+            default = self'.packages.exo;
+          } //
+          lib.optionalAttrs pkgs.stdenv.hostPlatform.isDarwin {
+            metal-toolchain = pkgs.callPackage ./nix/metal-toolchain.nix { };
+          };
 
           devShells.default = with pkgs; pkgs.mkShell {
             inputsFrom = [ self'.checks.cargo-build ];
@@ -149,16 +146,15 @@
                 config.treefmt.build.wrapper
 
                 # PYTHON
-                python313
+                self'.packages.editableVenv
                 uv
-                ruff
-                basedpyright
 
                 # RUST
                 config.rust.toolchain
                 maturin
 
                 # NIX
+                nixd
                 nixpkgs-fmt
 
                 # SVELTE
@@ -168,9 +164,6 @@
                 just
                 jq
               ]
-              ++ lib.optionals stdenv.isLinux [
-                unixtools.ifconfig
-              ]
               ++ lib.optionals stdenv.isDarwin [
                 macmon
               ];

justfile

@@ -22,19 +22,21 @@ sync-clean:
     uv sync --all-packages --force-reinstall --no-cache
 
 rust-rebuild:
-    cargo run --bin stub_gen
+    PYO3_PYTHON="$(uv run python -c 'import sys; print(sys.executable)')" cargo run --bin stub_gen
     uv sync --reinstall-package exo_pyo3_bindings
 
 build-dashboard:
     #!/usr/bin/env bash
-    cd dashboard
+    pushd dashboard
     npm install
     npm run build
+    popd
 
-package:
+package: build-dashboard
     uv run pyinstaller packaging/pyinstaller/exo.spec
+    rm -rf build
 
-build-app: package
+build-app: rust-rebuild sync-clean 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"
 

nix/darwin-build-fixes.patch

@@ -59,7 +59,7 @@ index 262b0495..5c7446ad 100644
 
  add_custom_command(
    OUTPUT ${MLX_METAL_PATH}/mlx.metallib
--  COMMAND xcrun -sdk macosx metallib ${KERNEL_AIR} -o
+-  COMMAND xcrun -sdk macosx metal ${KERNEL_AIR} -o
 +  COMMAND metallib ${KERNEL_AIR} -o
            ${MLX_METAL_PATH}/mlx.metallib
    DEPENDS ${KERNEL_AIR}

nix/mlx.nix

@@ -1,158 +0,0 @@
-{ stdenv
-, lib
-, fetchFromGitHub
-, replaceVars
-, fetchzip
-, cmake
-, nlohmann_json
-, apple-sdk_26
-, metal-toolchain
-, runCommand
-, fmt
-, python313Packages
-, uvLockMlxVersion
-, uvLockMlxRev
-}:
-
-assert stdenv.isDarwin;
-
-let
-  python = python313Packages.python;
-
-  # Static dependencies included directly during compilation
-  gguf-tools = fetchFromGitHub {
-    owner = "antirez";
-    repo = "gguf-tools";
-    rev = "8fa6eb65236618e28fd7710a0fba565f7faa1848";
-    hash = "sha256-15FvyPOFqTOr5vdWQoPnZz+mYH919++EtghjozDlnSA=";
-  };
-
-  metal_cpp = fetchzip {
-    url = "https://developer.apple.com/metal/cpp/files/metal-cpp_26.zip";
-    hash = "sha256-7n2eI2lw/S+Us6l7YPAATKwcIbRRpaQ8VmES7S8ZjY8=";
-  };
-
-  nanobind = fetchFromGitHub {
-    owner = "wjakob";
-    repo = "nanobind";
-    rev = "v2.10.2";
-    hash = "sha256-io44YhN+VpfHFWyvvLWSanRgbzA0whK8WlDNRi3hahU=";
-    fetchSubmodules = true;
-  };
-
-  mlx = stdenv.mkDerivation rec {
-    pname = "mlx";
-    version = uvLockMlxVersion;
-    pyproject = true;
-
-    src = fetchFromGitHub {
-      owner = "rltakashige";
-      repo = "mlx-jaccl-fix-small-recv";
-      rev = uvLockMlxRev;
-      hash = "sha256-GosFIWxIB48Egb1MqJrR3xhsUsQeWdRk5rV93USY6wQ=";
-    };
-
-    patches = [
-      (replaceVars ./darwin-build-fixes.patch {
-        sdkVersion = apple-sdk_26.version;
-        metalVersion = metal-toolchain.metalVersion;
-      })
-    ];
-
-    postPatch = ''
-      substituteInPlace mlx/backend/cpu/jit_compiler.cpp \
-        --replace-fail "g++" "$CXX"
-    '';
-
-    dontUseCmakeConfigure = true;
-
-    enableParallelBuilding = true;
-
-    # Allows multiple cores to be used in Python builds.
-    postUnpack = ''
-      export MAKEFLAGS+="''${enableParallelBuilding:+-j$NIX_BUILD_CORES}"
-    '';
-
-    # Updates the wrong fetcher rev attribute
-    passthru.skipBulkUpdate = true;
-
-    env = {
-      DEV_RELEASE = 1;
-      CMAKE_ARGS = toString [
-        (lib.cmakeBool "USE_SYSTEM_FMT" true)
-        (lib.cmakeOptionType "filepath" "FETCHCONTENT_SOURCE_DIR_GGUFLIB" "${gguf-tools}")
-        (lib.cmakeOptionType "filepath" "FETCHCONTENT_SOURCE_DIR_JSON" "${nlohmann_json.src}")
-        (lib.cmakeOptionType "filepath" "FETCHCONTENT_SOURCE_DIR_NANOBIND" "${nanobind}")
-        (lib.cmakeBool "FETCHCONTENT_FULLY_DISCONNECTED" true)
-        (lib.cmakeBool "MLX_BUILD_CPU" true)
-        (lib.cmakeBool "MLX_BUILD_METAL" true)
-        (lib.cmakeOptionType "filepath" "FETCHCONTENT_SOURCE_DIR_METAL_CPP" "${metal_cpp}")
-        (lib.cmakeOptionType "string" "CMAKE_OSX_DEPLOYMENT_TARGET" "${apple-sdk_26.version}")
-        (lib.cmakeOptionType "filepath" "CMAKE_OSX_SYSROOT" "${apple-sdk_26.passthru.sdkroot}")
-      ];
-      SDKROOT = apple-sdk_26.passthru.sdkroot;
-      MACOSX_DEPLOYMENT_TARGET = apple-sdk_26.version;
-    };
-
-    build-system = [
-      python313Packages.setuptools
-    ];
-
-    nativeBuildInputs = [
-      cmake
-      metal-toolchain
-      python313Packages.pypaBuildHook
-      python313Packages.pypaInstallHook
-      python313Packages.setuptools
-      python313Packages.typing-extensions
-      python313Packages.wheel
-      python313Packages.cmake
-      python313Packages.ninja
-    ];
-
-    buildInputs = [
-      fmt
-      gguf-tools
-      python313Packages.nanobind
-      python313Packages.pybind11
-      apple-sdk_26
-    ];
-
-    # Tests require Metal GPU access which isn't available in the Nix sandbox.
-    # To run tests, build with: nix build --option sandbox false .#mlx.passthru.tests.mlxTest
-    doCheck = false;
-
-    pythonImportsCheck = [ "mlx" ];
-
-    passthru.tests = {
-      # Runs example scripts to verify MLX works. Requires --option sandbox false
-      # since Metal GPU access is needed.
-      mlxTest =
-        runCommand "run-mlx-examples"
-          {
-            buildInputs = [ mlx ];
-            nativeBuildInputs = [ python ];
-          }
-          ''
-            cp ${src}/examples/python/logistic_regression.py .
-            ${python.interpreter} logistic_regression.py
-            rm logistic_regression.py
-
-            cp ${src}/examples/python/linear_regression.py .
-            ${python.interpreter} linear_regression.py
-            rm linear_regression.py
-
-            touch $out
-          '';
-    };
-
-    meta = {
-      homepage = "https://github.com/ml-explore/mlx";
-      description = "Array framework for Apple silicon";
-      changelog = "https://github.com/ml-explore/mlx/releases/tag/${src.tag}";
-      license = lib.licenses.mit;
-      platforms = [ "aarch64-darwin" ];
-    };
-  };
-in
-mlx

packaging/pyinstaller/exo.spec

@@ -1,5 +1,6 @@
 # -*- mode: python ; coding: utf-8 -*-
 
+import sys
 import importlib.util
 import shutil
 from pathlib import Path
@@ -56,6 +57,7 @@ HIDDEN_IMPORTS = sorted(
     set(
         collect_submodules("mlx")
         + _safe_collect("mlx_lm")
+        + _safe_collect("mlx_vlm")
         + _safe_collect("transformers")
     )
 )
@@ -67,18 +69,19 @@ DATAS: list[tuple[str, str]] = [
     (str(EXO_SHARED_MODELS_DIR), "exo/shared/models"),
 ]
 
-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"
-    )
+if sys.platform == "darwin":
+    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/vladkens/macmon "
+            "--rev a1cd06b6cc0d5e61db24fd8832e74cd992097a7d macmon --force"
+        )
 
 BINARIES: list[tuple[str, str]] = [
     (MACMON_PATH, "."),
-]
+] if sys.platform == "darwin" else []
 
 a = Analysis(
     [str(ENTRYPOINT)],

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "exo"
-version = "0.3.68"
+version = "0.3.70"
 description = "Exo"
 readme = "README.md"
 requires-python = ">=3.13"
@@ -12,23 +12,25 @@ dependencies = [
   "fastapi>=0.116.1",
   "filelock>=3.18.0",
   "rustworkx>=0.17.1",
-  "huggingface-hub>=0.33.4",
+  "huggingface-hub>=1.8.0",
   "psutil>=7.0.0",
   "loguru>=0.7.3",
-  "exo_pyo3_bindings",                         # rust bindings
+  "exo-pyo3-bindings",                       # rust bindings
   "anyio==4.11.0",
-  "mlx; sys_platform == 'darwin'",
-  "mlx[cpu]==0.30.6; sys_platform == 'linux'",
+  "mlx==0.31.1; sys_platform == 'darwin'",
   "mlx-lm",
-  "tiktoken>=0.12.0",                          # required for kimi k2 tokenizer
+  "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",
+  "mflux==0.17.2; sys_platform == 'darwin'",
   "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",
+  "pydantic-settings>=2.13.1",
 ]
 
 [project.scripts]
@@ -45,11 +47,20 @@ dev = [
   "ruff>=0.11.13",
 ]
 
-# mlx[cuda] requires a newer version of mlx. the ideal on linux is: default to mlx[cpu] unless[cuda] specified.
 [project.optional-dependencies]
-# cuda = [
-#     "mlx[cuda]==0.26.3",
-# ]
+build = ["nanobind"]
+cpu = [
+  "mlx-cpu==0.31.1; sys_platform == 'linux'",
+  "torch>=2.10.0; sys_platform == 'linux'",
+]
+cuda12 = [
+  "mlx-cuda-12==0.31.1; sys_platform == 'linux'",
+  "torch>=2.10.0; sys_platform == 'linux'",
+]
+cuda13 = [
+  "mlx-cuda-13==0.31.1; sys_platform == 'linux'",
+  "torch>=2.10.0; sys_platform == 'linux'",
+]
 
 ###
 # workspace configuration
@@ -59,12 +70,30 @@ dev = [
 members = ["rust/exo_pyo3_bindings", "bench"]
 
 [tool.uv.sources]
-exo_pyo3_bindings = { workspace = true }
+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-deepseek-v32-indexer" }
-# 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 }
+mlx-lm = { git = "https://github.com/rltakashige/mlx-lm", branch = "leo/fix-arrayscache-leak" }
+torch = [
+  { index = "pytorch-cu130", marker = "sys_platform == 'linux' and extra == 'cuda13' and extra != 'cpu' and extra != 'cuda12'" },
+  { index = "pytorch-cu120", marker = "sys_platform == 'linux' and extra == 'cuda12' and extra != 'cpu' and extra != 'cuda13'" },
+  { index = "pytorch-cpu", marker = "sys_platform == 'linux' and extra == 'cpu' and extra != 'cuda12' and extra != 'cuda13'" },
+]
+vllm = { git = "https://github.com/hmellor/vllm.git", branch = "transformers-v5" }
+
+[[tool.uv.index]]
+name = "pytorch-cu130"
+url = "https://download.pytorch.org/whl/cu130"
+explicit = true
+
+[[tool.uv.index]]
+name = "pytorch-cu120"
+url = "https://download.pytorch.org/whl/cu120"
+explicit = true
+
+[[tool.uv.index]]
+name = "pytorch-cpu"
+url = "https://download.pytorch.org/whl/cpu"
+explicit = true
 
 [build-system]
 requires = ["uv_build>=0.8.9,<0.9.0"]
@@ -75,7 +104,7 @@ build-backend = "uv_build"
 ###
 
 [tool.basedpyright]
-include = [".venv/lib/mlx", ".venv/lib/mlx_lm", "src", "bench"]
+include = ["src", "bench"]
 typeCheckingMode = "strict"
 failOnWarnings = true
 
@@ -102,9 +131,14 @@ exclude = [
 ]
 stubPath = ".mlx_typings"
 
+[[tool.basedpyright.executionEnvironments]]
+root = "src/exo/worker/engines/image"
+reportMissingModuleSource = false
+
 [[tool.basedpyright.executionEnvironments]]
 root = "src"
 
+
 ###
 # uv configuration
 ###
@@ -114,6 +148,46 @@ root = "src"
 required-version = ">=0.8.6"
 prerelease = "allow"
 environments = ["sys_platform == 'darwin'", "sys_platform == 'linux'"]
+conflicts = [[{ extra = "cuda12" }, { extra = "cuda13" }, { extra = "cpu" }]]
+constraint-dependencies = ["transformers>=5.0.0,<5.4.0"]
+
+[tool.uv.extra-build-dependencies]
+miniaudio = ["setuptools", "cffi", "pycparser"]
+mlx = [
+  "setuptools",
+  "typing-extensions",
+  "nanobind",
+  "pybind11",
+  "wheel",
+  "cmake",
+  "ninja",
+]
+mlx-lm = ["setuptools"]
+xgrammar = [
+  "nanobind",
+  "setuptools",
+  "scikit-build-core",
+  "packaging",
+  "pathspec",
+]
+rouge-score = ["setuptools"]
+sacrebleu = ["setuptools"]
+sqlitedict = ["setuptools"]
+word2number = ["setuptools"]
+vllm = [
+  "setuptools",
+  "setuptools-scm",
+  "scikit-build-core",
+  "jinja2",
+  "wheel",
+  "markupsafe",
+  "typing-extensions",
+  "torch",
+]
+fastsafetensors = ["setuptools", "pybind11"]
+torch = ["typing-extensions"]
+torchvision = ["torch"]
+torchaudio = ["torch"]
 
 ###
 # ruff configuration
@@ -121,7 +195,6 @@ environments = ["sys_platform == 'darwin'", "sys_platform == 'linux'"]
 
 [tool.ruff]
 extend-exclude = [
-  "shared/protobufs/**",
   "*mlx_typings/**",
   "rust/exo_pyo3_bindings/**",
   "bench/vendor/**",

python/parts.nix

@@ -1,18 +1,37 @@
 { inputs, ... }:
-{
-  perSystem =
-    { config, self', pkgs, lib, system, ... }:
+let
+  # Load workspace from uv.lock
+  workspace = inputs.uv2nix.lib.workspace.loadWorkspace {
+    workspaceRoot = ../.;
+  };
+
+  mkPythonSet = { pkgs, lib, self' }:
     let
-      # Load workspace from uv.lock
-      workspace = inputs.uv2nix.lib.workspace.loadWorkspace {
-        workspaceRoot = inputs.self;
-      };
-
-      # Create overlay from workspace
-      # Use wheels from PyPI for most packages; we override mlx with our pure Nix Metal build
-      overlay = workspace.mkPyprojectOverlay { sourcePreference = "wheel"; };
-
-      # Override overlay to inject Nix-built components
+      inherit (pkgs.stdenv.hostPlatform) isLinux isDarwin isx86_64;
+      inherit (pkgs.config) cudaSupport;
+      inherit (pkgs) cudaPackages;
+      cuda13Support = cudaSupport && cudaPackages.cudaMajorVersion == "13";
+      libmlx_source = if cuda13Support then "mlx-cuda-13" else if cudaSupport then "mlx-cuda-12" else "mlx-cpu";
+      uv_extra = if cuda13Support then "cuda13" else if cudaSupport then "cuda12" else "cpu";
+      python = pkgs.python313;
+      cudaLibs = with cudaPackages; [
+        cuda_cudart
+        cuda_cccl
+        cuda_cupti
+        cuda_nvrtc
+        cuda_nvtx
+        cudnn
+        libcufile
+        libcublas
+        libcufft
+        libcurand
+        libcusolver
+        libcusparse
+        libcusparse_lt
+        libnvjitlink
+        libnvshmem
+        nccl
+      ];
       exoOverlay = final: prev: {
         # Replace workspace exo_pyo3_bindings with Nix-built wheel.
         # Preserve passthru so mkVirtualEnv can resolve dependency groups.
@@ -32,126 +51,157 @@
           '';
         };
       };
+      buildSystemsOverlay = final: prev: { } //
+        lib.optionalAttrs isDarwin
+          {
+            mlx = prev.mlx.overrideAttrs (old:
+              let
+                # Static dependencies included directly during compilation
+                gguf-tools = pkgs.fetchFromGitHub {
+                  owner = "antirez";
+                  repo = "gguf-tools";
+                  rev = "8fa6eb65236618e28fd7710a0fba565f7faa1848";
+                  hash = "sha256-15FvyPOFqTOr5vdWQoPnZz+mYH919++EtghjozDlnSA=";
+                };
 
-      python = pkgs.python313;
+                metal_cpp = pkgs.fetchzip {
+                  url = "https://developer.apple.com/metal/cpp/files/metal-cpp_26.zip";
+                  hash = "sha256-7n2eI2lw/S+Us6l7YPAATKwcIbRRpaQ8VmES7S8ZjY8=";
+                };
 
-      # Overlay to provide build systems and custom packages
-      buildSystemsOverlay = final: prev: {
-        # mlx-lm is a git dependency that needs setuptools
-        mlx-lm = prev.mlx-lm.overrideAttrs (old: {
-          nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [
-            final.setuptools
-          ];
+                nanobind = pkgs.fetchFromGitHub {
+                  owner = "wjakob";
+                  repo = "nanobind";
+                  rev = "v2.10.2";
+                  hash = "sha256-io44YhN+VpfHFWyvvLWSanRgbzA0whK8WlDNRi3hahU=";
+                  fetchSubmodules = true;
+                };
+              in
+              {
+                nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [ pkgs.cmake self'.packages.metal-toolchain ];
+                # TODO: non-sdk_26 support
+                buildInputs = (old.buildInputs or [ ])
+                  ++ [ gguf-tools pkgs.fmt pkgs.nlohmann_json pkgs.apple-sdk_26 ];
+                patches = [
+                  (pkgs.replaceVars ../nix/darwin-build-fixes.patch {
+                    sdkVersion = pkgs.apple-sdk_26.version;
+                    inherit (self'.packages.metal-toolchain) metalVersion;
+                  })
+                ];
+                postPatch = ''
+                  substituteInPlace mlx/backend/cpu/jit_compiler.cpp \
+                    --replace-fail "g++" "${lib.getExe' pkgs.stdenv.cc "c++"}"
+                '';
+
+                DEV_RELEASE = 1;
+                CMAKE_ARGS = toString ([
+                  (lib.cmakeBool "USE_SYSTEM_FMT" true)
+                  (lib.cmakeOptionType "filepath" "FETCHCONTENT_SOURCE_DIR_GGUFLIB" "${gguf-tools}")
+                  (lib.cmakeOptionType "filepath" "FETCHCONTENT_SOURCE_DIR_JSON" "${pkgs.nlohmann_json.src}")
+                  (lib.cmakeOptionType "filepath" "FETCHCONTENT_SOURCE_DIR_NANOBIND" "${nanobind}")
+                  (lib.cmakeBool "FETCHCONTENT_FULLY_DISCONNECTED" true)
+                  (lib.cmakeBool "MLX_BUILD_CPU" true)
+                  (lib.cmakeBool "MLX_BUILD_METAL" true)
+                  (lib.cmakeOptionType "string" "CMAKE_INSTALL_LIBDIR" "lib")
+                  (lib.cmakeOptionType "filepath" "FETCHCONTENT_SOURCE_DIR_METAL_CPP" "${metal_cpp}")
+                  (lib.cmakeOptionType "string" "CMAKE_OSX_DEPLOYMENT_TARGET" "${pkgs.apple-sdk_26.version}")
+                  (lib.cmakeOptionType "filepath" "CMAKE_OSX_SYSROOT" "${pkgs.apple-sdk_26.passthru.sdkroot}")
+                ] ++ lib.optionals (isDarwin && isx86_64) [
+                  (lib.cmakeBool "MLX_ENABLE_X64_MAC" true)
+                ]);
+                SDKROOT = pkgs.apple-sdk_26.passthru.sdkroot;
+                MACOSX_DEPLOYMENT_TARGET = pkgs.apple-sdk_26.version;
+              });
+          } // lib.optionalAttrs isLinux {
+        mlx = prev.mlx.overrideAttrs (old: {
+          buildInputs = old.buildInputs ++ lib.optionals cudaSupport cudaLibs;
+          autoPatchelfIgnoreMissingDeps = lib.optionals cudaSupport [ "libcuda.so.1" ];
+          postInstall = (old.postInstall or "") + ''
+            cp -r "${final.${libmlx_source}}/${final.python.sitePackages}/mlx" "$out/${final.python.sitePackages}/mlx/"
+          '';
         });
-        # 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
-          ];
+      } // lib.optionalAttrs cudaSupport {
+        "${libmlx_source}" = prev."${libmlx_source}".overrideAttrs (old: {
+          buildInputs = old.buildInputs ++ cudaLibs;
+          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
         });
-        sacrebleu = prev.sacrebleu.overrideAttrs (old: {
-          nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [
-            final.setuptools
-          ];
+        nvidia-cufile = prev.nvidia-cufile.overrideAttrs (old: {
+          buildInputs = old.buildInputs ++ [ pkgs.rdma-core ];
+          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
         });
-        sqlitedict = prev.sqlitedict.overrideAttrs (old: {
-          nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [
-            final.setuptools
-          ];
+        nvidia-cusolver = prev.nvidia-cusolver.overrideAttrs (old: {
+          buildInputs = old.buildInputs ++ cudaLibs;
+          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
         });
-        word2number = prev.word2number.overrideAttrs (old: {
-          nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [
-            final.setuptools
-          ];
+        nvidia-nvshmem-cu13 = prev.nvidia-nvshmem-cu13.overrideAttrs (old: {
+          buildInputs = old.buildInputs ++ [ pkgs.rdma-core pkgs.pmix pkgs.libfabric pkgs.ucx pkgs.openmpi ];
+          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+        });
+        nvidia-cusparse = prev.nvidia-cusparse.overrideAttrs (old: {
+          buildInputs = old.buildInputs ++ [ cudaLibs ];
+          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+        });
+        torch = prev.torch.overrideAttrs (old: {
+          buildInputs = old.buildInputs ++ cudaLibs;
+          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
         });
-      } // lib.optionalAttrs pkgs.stdenv.hostPlatform.isDarwin {
-        # Use our pure Nix-built MLX with Metal support (macOS only)
-        mlx = self'.packages.mlx;
       };
-
-      # Additional overlay for Linux-specific fixes (type checking env).
-      # Native wheels have shared lib dependencies we don't need at type-check time.
-      linuxOverlay = final: prev:
-        let
-          ignoreMissing = drv: drv.overrideAttrs { autoPatchelfIgnoreMissingDeps = [ "*" ]; };
-          nvidiaPackages = lib.filterAttrs (name: _: lib.hasPrefix "nvidia-" name) prev;
-        in
-        lib.optionalAttrs pkgs.stdenv.hostPlatform.isLinux (
-          (lib.mapAttrs (_: ignoreMissing) nvidiaPackages) // {
-            mlx = ignoreMissing prev.mlx;
-            mlx-cuda-13 = prev.mlx-cuda-13.overrideAttrs (old: {
-              buildInputs = (old.buildInputs or [ ]) ++ [
-                final.nvidia-cublas
-                final.nvidia-cuda-nvrtc
-                final.nvidia-cudnn-cu13
-                final.nvidia-nccl-cu13
-              ];
-              preFixup = ''
-                addAutoPatchelfSearchPath ${final.nvidia-cublas}
-                addAutoPatchelfSearchPath ${final.nvidia-cuda-nvrtc}
-                addAutoPatchelfSearchPath ${final.nvidia-cudnn-cu13}
-                addAutoPatchelfSearchPath ${final.nvidia-nccl-cu13}
-              '';
-              autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-            });
-            torch = ignoreMissing prev.torch;
-            triton = ignoreMissing prev.triton;
-          }
-        );
-
+      pyprojectOverlay = workspace.mkPyprojectOverlay {
+        sourcePreference = "wheel";
+        dependencies = { exo = [ uv_extra ]; exo-bench = [ ]; };
+      };
+      editableOverlay = workspace.mkEditablePyprojectOverlay {
+        # Use environment variable pointing to editable root directory
+        root = "$REPO_ROOT";
+        members = [ "exo" "exo-bench" ];
+      };
       pythonSet = (pkgs.callPackage inputs.pyproject-nix.build.packages {
         inherit python;
       }).overrideScope (
         lib.composeManyExtensions [
           inputs.pyproject-build-systems.overlays.default
-          overlay
+          pyprojectOverlay
           exoOverlay
           buildSystemsOverlay
-          linuxOverlay
         ]
       );
-      # mlx-cpu and mlx-cuda-13 both ship mlx/ site-packages files; keep first.
-      # mlx-cpu/mlx-cuda-13 and nvidia-cudnn-cu12/cu13 ship overlapping files.
-      venvCollisionPaths = lib.optionals pkgs.stdenv.hostPlatform.isLinux [
-        "lib/python3.13/site-packages/mlx*"
-        "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 {
-        venvIgnoreCollisions = venvCollisionPaths;
-      };
-
-      # Virtual environment with dev dependencies for testing
-      testVenv = (pythonSet.mkVirtualEnv "exo-test-env" (
-        exoDeps // {
-          exo = [ "dev" ]; # Include pytest, pytest-asyncio, pytest-env
-        }
-      )).overrideAttrs {
-        venvIgnoreCollisions = venvCollisionPaths;
-      };
-
-      mkPythonScript = name: path: pkgs.writeShellApplication {
+      mkApp = cmd: name: members: pkgs.writeShellApplication {
         inherit name;
-        runtimeInputs = [ exoVenv ];
         runtimeEnv = {
           EXO_DASHBOARD_DIR = self'.packages.dashboard;
           EXO_RESOURCES_DIR = inputs.self + /resources;
         };
-        text = ''exec python ${path} "$@"'';
+        runtimeInputs = [
+          # mlx and mlx-cuda ship clashing cmake files - we dont need them at runtime anyway
+          ((pythonSet.mkVirtualEnv "${name}-env" members).overrideAttrs (_: { venvSkip = [ "lib/python${python.pythonVersion}/site-packages/mlx/share/cmake/*" ]; }))
+        ]
+        ++ lib.optionals isDarwin [ pkgs.macmon ];
+        text = "exec " + lib.optionalString cudaSupport "${lib.getExe pkgs.nix-gl-host} " + cmd;
+      };
+    in
+    {
+      inherit pythonSet;
+      editablePythonSet = pythonSet.overrideScope editableOverlay;
+      mkPythonScript = members: name: path: mkApp ''python ${path} "$@"'' name members;
+      mkExo = name: members: mkApp ''exo "$@"'' name members;
+    };
+in
+{
+  perSystem =
+    { self', pkgs, unfreePkgs, lib, ... }:
+    let
+      inherit (pkgs.stdenv.hostPlatform) isLinux;
+      inherit (mkPythonSet { inherit self' pkgs lib; }) pythonSet editablePythonSet mkPythonScript mkExo;
+
+      exoVenv = pythonSet.mkVirtualEnv "exo-env" { exo = lib.optionals isLinux [ "cpu" ]; };
+
+      # Virtual environment with dev dependencies for testing
+      testVenv = pythonSet.mkVirtualEnv "exo-test-env" {
+        exo = [ "dev" ] ++ lib.optionals isLinux [ "cpu" ]; # Include pytest, pytest-asyncio, pytest-env
       };
 
-      benchVenv = pythonSet.mkVirtualEnv "exo-bench-env" {
-        exo-bench = [ ];
-      };
-
-      mkBenchScript = name: path: pkgs.writeShellApplication {
-        inherit name;
-        runtimeInputs = [ benchVenv ];
-        text = ''exec python ${path} "$@"'';
-      };
+      mkBenchScript = mkPythonScript { exo-bench = [ ]; };
 
       mkSimplePythonScript = name: path: pkgs.writeShellApplication {
         inherit name;
@@ -159,43 +209,32 @@
         text = ''exec python ${path} "$@"'';
       };
 
-      exoPackage = pkgs.runCommand "exo"
-        {
-          nativeBuildInputs = [ pkgs.makeWrapper ];
-        }
-        ''
-          mkdir -p $out/bin
-
-          # Create wrapper script
-          makeWrapper ${exoVenv}/bin/exo $out/bin/exo \
-            --set EXO_DASHBOARD_DIR ${self'.packages.dashboard} \
-            --set EXO_RESOURCES_DIR ${inputs.self + /resources} \
-            ${lib.optionalString pkgs.stdenv.hostPlatform.isDarwin "--prefix PATH : ${pkgs.macmon}/bin"}
-        '';
     in
     {
-      # Python package only available on macOS (requires MLX/Metal)
-      packages = lib.optionalAttrs pkgs.stdenv.hostPlatform.isDarwin
-        {
-          exo = exoPackage;
-          # Test environment for running pytest outside of Nix sandbox (needs GPU access)
-          exo-test-env = testVenv;
-        } // {
+      packages = {
+        exo = mkExo "exo" { exo = lib.optionals isLinux [ "cpu" ]; };
+        # for devShell
+        exo-venv = exoVenv;
+        editableVenv = editablePythonSet.mkVirtualEnv "exo-dev-env" { exo = [ "dev" ]; };
+        # for running tests in ci
+        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);
+        # used by ./tests/run_exo_on.sh
         exo-get-all-models-on-cluster = mkSimplePythonScript "exo-get-all-models-on-cluster" (inputs.self + /tests/get_all_models_on_cluster.py);
+      } // lib.optionalAttrs isLinux {
+        exo-cuda-12 = (mkPythonSet { inherit self' lib; inherit (unfreePkgs.pkgsCuda.cudaPackages_12) pkgs; }).mkExo "exo-cuda-12" { exo = [ "cuda12" ]; };
+        exo-cuda-13 = (mkPythonSet { inherit self' lib; inherit (unfreePkgs.pkgsCuda.cudaPackages_13) pkgs; }).mkExo "exo-cuda-13" { exo = [ "cuda13" ]; };
       };
 
       checks = {
-        # Ruff linting (works on all platforms)
         lint = pkgs.runCommand "ruff-lint" { } ''
           export RUFF_CACHE_DIR="$TMPDIR/ruff-cache"
           ${pkgs.ruff}/bin/ruff check ${inputs.self}
           touch $out
         '';
 
-        # Hermetic basedpyright type checking
         typecheck = pkgs.runCommand "typecheck"
           {
             nativeBuildInputs = [
@@ -206,7 +245,7 @@
           ''
             cd ${inputs.self}
             export HOME=$TMPDIR
-            basedpyright --pythonpath ${testVenv}/bin/python
+            basedpyright --pythonpath ${testVenv}/bin/python --project ${inputs.self}/pyproject.toml
             touch $out
           '';
       };

resources/inference_model_cards/mlx-community--DeepSeek-V3.1-4bit.toml

@@ -9,5 +9,13 @@ quantization = "4bit"
 base_model = "DeepSeek V3.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 405874409472
+
+# Source: https://huggingface.co/deepseek-ai/DeepSeek-V3.1/blob/main/generation_config.json
+# Source: https://huggingface.co/deepseek-ai/DeepSeek-V3.1/discussions/19
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.95

resources/inference_model_cards/mlx-community--DeepSeek-V3.1-8bit.toml

@@ -9,5 +9,13 @@ quantization = "8bit"
 base_model = "DeepSeek V3.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 765577920512
+
+# Source: https://huggingface.co/deepseek-ai/DeepSeek-V3.1/blob/main/generation_config.json
+# Source: https://huggingface.co/deepseek-ai/DeepSeek-V3.1/discussions/19
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.95

resources/inference_model_cards/mlx-community--DeepSeek-V3.2-4bit.toml

@@ -9,5 +9,13 @@ quantization = "4bit"
 base_model = "DeepSeek V3.2"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 378086226621
+
+# Source: https://huggingface.co/deepseek-ai/DeepSeek-V3.2/blob/main/generation_config.json
+# Source: https://docs.vllm.ai/projects/recipes/en/latest/DeepSeek/DeepSeek-V3_2.html
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--DeepSeek-V3.2-8bit.toml

@@ -9,5 +9,13 @@ quantization = "8bit"
 base_model = "DeepSeek V3.2"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 755957120916
+
+# Source: https://huggingface.co/deepseek-ai/DeepSeek-V3.2/blob/main/generation_config.json
+# Source: https://docs.vllm.ai/projects/recipes/en/latest/DeepSeek/DeepSeek-V3_2.html
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-4.5-Air-8bit.toml

@@ -9,5 +9,12 @@ quantization = "8bit"
 base_model = "GLM 4.5 Air"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 122406567936
+
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-4.5-Air-bf16.toml

@@ -9,5 +9,12 @@ quantization = "bf16"
 base_model = "GLM 4.5 Air"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 229780750336
+
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-4.7-4bit.toml

@@ -9,5 +9,14 @@ quantization = "4bit"
 base_model = "GLM 4.7"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 198556925568
+
+# Source: https://huggingface.co/zai-org/GLM-4.7
+# Source: https://unsloth.ai/docs/models/glm-4.7-flash
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-4.7-6bit.toml

@@ -9,5 +9,14 @@ quantization = "6bit"
 base_model = "GLM 4.7"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 286737579648
+
+# Source: https://huggingface.co/zai-org/GLM-4.7
+# Source: https://unsloth.ai/docs/models/glm-4.7-flash
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-4.7-8bit-gs32.toml

@@ -9,5 +9,14 @@ quantization = "8bit"
 base_model = "GLM 4.7"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 396963397248
+
+# Source: https://huggingface.co/zai-org/GLM-4.7
+# Source: https://unsloth.ai/docs/models/glm-4.7-flash
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-4.7-Flash-4bit.toml

@@ -9,5 +9,14 @@ quantization = "4bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 19327352832
+
+# Source: https://huggingface.co/zai-org/GLM-4.7-Flash
+# Source: https://unsloth.ai/docs/models/glm-4.7-flash
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-4.7-Flash-5bit.toml

@@ -9,5 +9,14 @@ quantization = "5bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 22548578304
+
+# Source: https://huggingface.co/zai-org/GLM-4.7-Flash
+# Source: https://unsloth.ai/docs/models/glm-4.7-flash
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-4.7-Flash-6bit.toml

@@ -9,5 +9,14 @@ quantization = "6bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 26843545600
+
+# Source: https://huggingface.co/zai-org/GLM-4.7-Flash
+# Source: https://unsloth.ai/docs/models/glm-4.7-flash
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-4.7-Flash-8bit.toml

@@ -9,5 +9,14 @@ quantization = "8bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 34359738368
+
+# Source: https://huggingface.co/zai-org/GLM-4.7-Flash
+# Source: https://unsloth.ai/docs/models/glm-4.7-flash
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-5-8bit.toml

@@ -9,5 +9,13 @@ quantization = "8bit"
 base_model = "GLM-5"
 capabilities = ["text", "thinking"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 790517400864
+
+# Source: https://huggingface.co/zai-org/GLM-5
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-5-MXFP4-Q8.toml

@@ -9,5 +9,13 @@ quantization = "MXFP4-Q8"
 base_model = "GLM-5"
 capabilities = ["text", "thinking"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 405478939008
+
+# Source: https://huggingface.co/zai-org/GLM-5
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-5-bf16.toml

@@ -9,5 +9,13 @@ quantization = "bf16"
 base_model = "GLM-5"
 capabilities = ["text", "thinking"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 1487822475264
+
+# Source: https://huggingface.co/zai-org/GLM-5
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--Kimi-K2-Instruct-4bit.toml

@@ -9,5 +9,12 @@ quantization = "4bit"
 base_model = "Kimi K2"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 620622774272
+
+# Source: https://huggingface.co/moonshotai/Kimi-K2-Instruct
+# Source: https://platform.kimi.ai/docs/guide/kimi-k2-quickstart
+[sampling_defaults]
+temperature = 0.6

resources/inference_model_cards/mlx-community--Kimi-K2-Thinking.toml

@@ -9,5 +9,12 @@ quantization = ""
 base_model = "Kimi K2"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 706522120192
+
+# Source: https://huggingface.co/moonshotai/Kimi-K2-Thinking
+# Source: https://platform.kimi.ai/docs/guide/use-kimi-k2-thinking-model
+[sampling_defaults]
+temperature = 1.0

resources/inference_model_cards/mlx-community--Kimi-K2.5.toml

@@ -7,7 +7,29 @@ tasks = ["TextGeneration"]
 family = "kimi"
 quantization = ""
 base_model = "Kimi K2.5"
-capabilities = ["text", "thinking", "thinking_toggle"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 662498705408
+
+[vision]
+image_token_id = 163605
+model_type = "kimi_vl"
+weights_repo = "davehind/Kimi-K2.5-vision"
+processor_repo = "moonshotai/Kimi-K2.5"
+
+# Source: https://deepwiki.com/MoonshotAI/Kimi-K2.5/3.7-recommended-parameters
+# Source: https://unsloth.ai/docs/models/kimi-k2.5
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+min_p = 0.01
+
+# Source: https://deepwiki.com/MoonshotAI/Kimi-K2.5/3.7-recommended-parameters
+# Source: https://unsloth.ai/docs/models/kimi-k2.5
+[sampling_defaults.non_thinking]
+temperature = 0.6
+top_p = 0.95
+min_p = 0.01

resources/inference_model_cards/mlx-community--Llama-3.1-Nemotron-70B-Instruct-HF-4bit.toml

@@ -8,5 +8,13 @@ quantization = "4bit"
 base_model = "NVIDIA Llama-3.1-Nemotron-70B-Instruct"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 39688355840
+
+# Source: https://huggingface.co/RedHatAI/Llama-3.1-Nemotron-70B-Instruct-HF-FP8-dynamic
+# Source: https://deepinfra.com/nvidia/Llama-3.1-Nemotron-70B-Instruct/api
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Llama-3.1-Nemotron-70B-Instruct-HF-8bit.toml

@@ -8,5 +8,13 @@ quantization = "8bit"
 base_model = "NVIDIA Llama-3.1-Nemotron-70B-Instruct"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 74964549632
+
+# Source: https://huggingface.co/RedHatAI/Llama-3.1-Nemotron-70B-Instruct-HF-FP8-dynamic
+# Source: https://deepinfra.com/nvidia/Llama-3.1-Nemotron-70B-Instruct/api
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Llama-3.1-Nemotron-70B-Instruct-HF-bf16.toml

@@ -8,5 +8,13 @@ quantization = "bf16"
 base_model = "NVIDIA Llama-3.1-Nemotron-70B-Instruct"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 141107412992
+
+# Source: https://huggingface.co/RedHatAI/Llama-3.1-Nemotron-70B-Instruct-HF-FP8-dynamic
+# Source: https://deepinfra.com/nvidia/Llama-3.1-Nemotron-70B-Instruct/api
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Llama-3.1-Nemotron-Nano-4B-v1.1-4bit.toml

@@ -8,5 +8,16 @@ quantization = "4bit"
 base_model = "NVIDIA Llama-3.1-Nemotron-Nano-4B-v1.1"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 2538706944
+
+# Source: https://huggingface.co/nvidia/Llama-3.1-Nemotron-Nano-4B-v1.1
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.95
+
+# Source: https://huggingface.co/nvidia/Llama-3.1-Nemotron-Nano-4B-v1.1
+[sampling_defaults.non_thinking]
+temperature = 0.0

resources/inference_model_cards/mlx-community--Llama-3.1-Nemotron-Nano-4B-v1.1-8bit.toml

@@ -8,5 +8,16 @@ quantization = "8bit"
 base_model = "NVIDIA Llama-3.1-Nemotron-Nano-4B-v1.1"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 4794980352
+
+# Source: https://huggingface.co/nvidia/Llama-3.1-Nemotron-Nano-4B-v1.1
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.95
+
+# Source: https://huggingface.co/nvidia/Llama-3.1-Nemotron-Nano-4B-v1.1
+[sampling_defaults.non_thinking]
+temperature = 0.0

resources/inference_model_cards/mlx-community--Llama-3.1-Nemotron-Nano-4B-v1.1-bf16.toml

@@ -8,5 +8,16 @@ quantization = "bf16"
 base_model = "NVIDIA Llama-3.1-Nemotron-Nano-4B-v1.1"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 9025492992
+
+# Source: https://huggingface.co/nvidia/Llama-3.1-Nemotron-Nano-4B-v1.1
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.95
+
+# Source: https://huggingface.co/nvidia/Llama-3.1-Nemotron-Nano-4B-v1.1
+[sampling_defaults.non_thinking]
+temperature = 0.0

resources/inference_model_cards/mlx-community--Llama-3.2-1B-Instruct-4bit.toml

@@ -9,5 +9,13 @@ quantization = "4bit"
 base_model = "Llama 3.2 1B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 729808896
+
+# Source: https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct/blob/main/generation_config.json
+# Source: https://huggingface.co/unsloth/Llama-3.2-1B-Instruct/blob/main/generation_config.json
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Llama-3.2-3B-Instruct-4bit.toml

@@ -9,5 +9,13 @@ quantization = "4bit"
 base_model = "Llama 3.2 3B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 1863319552
+
+# Source: https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct/blob/main/generation_config.json
+# Source: https://huggingface.co/unsloth/Llama-3.2-3B-Instruct/blob/main/generation_config.json
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Llama-3.2-3B-Instruct-8bit.toml

@@ -9,5 +9,13 @@ quantization = "8bit"
 base_model = "Llama 3.2 3B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 3501195264
+
+# Source: https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct/blob/main/generation_config.json
+# Source: https://huggingface.co/unsloth/Llama-3.2-3B-Instruct/blob/main/generation_config.json
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Llama-3.3-70B-Instruct-4bit.toml

@@ -9,5 +9,13 @@ quantization = "4bit"
 base_model = "Llama 3.3 70B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 40652242944
+
+# Source: https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct/blob/main/generation_config.json
+# Source: https://huggingface.co/unsloth/Llama-3.3-70B-Instruct/blob/main/generation_config.json
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Llama-3.3-70B-Instruct-8bit.toml

@@ -9,5 +9,13 @@ quantization = "8bit"
 base_model = "Llama 3.3 70B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 76799803392
+
+# Source: https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct/blob/main/generation_config.json
+# Source: https://huggingface.co/unsloth/Llama-3.3-70B-Instruct/blob/main/generation_config.json
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Meta-Llama-3.1-70B-Instruct-4bit.toml

@@ -9,5 +9,13 @@ quantization = "4bit"
 base_model = "Llama 3.1 70B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 40652242944
+
+# Source: https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct/blob/main/generation_config.json
+# Source: https://huggingface.co/unsloth/Meta-Llama-3.1-70B-Instruct/blob/main/generation_config.json
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Meta-Llama-3.1-8B-Instruct-4bit.toml

@@ -9,5 +9,13 @@ quantization = "4bit"
 base_model = "Llama 3.1 8B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 4637851648
+
+# Source: https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct/blob/main/generation_config.json
+# Source: https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct/blob/main/generation_config.json
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Meta-Llama-3.1-8B-Instruct-8bit.toml

@@ -9,5 +9,13 @@ quantization = "8bit"
 base_model = "Llama 3.1 8B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 8954839040
+
+# Source: https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct/blob/main/generation_config.json
+# Source: https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct/blob/main/generation_config.json
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--Meta-Llama-3.1-8B-Instruct-bf16.toml

@@ -9,5 +9,13 @@ quantization = "bf16"
 base_model = "Llama 3.1 8B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 16882073600
+
+# Source: https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct/blob/main/generation_config.json
+# Source: https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct/blob/main/generation_config.json
+[sampling_defaults]
+temperature = 0.6
+top_p = 0.9

resources/inference_model_cards/mlx-community--MiniMax-M2.1-3bit.toml

@@ -9,5 +9,14 @@ quantization = "3bit"
 base_model = "MiniMax M2.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 196608
+
 [storage_size]
 in_bytes = 100086644736
+
+# Source: https://huggingface.co/MiniMaxAI/MiniMax-M2.1
+# Source: https://github.com/MiniMax-AI/MiniMax-M2.1
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+top_k = 40

resources/inference_model_cards/mlx-community--MiniMax-M2.1-8bit.toml

@@ -9,5 +9,14 @@ quantization = "8bit"
 base_model = "MiniMax M2.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 196608
+
 [storage_size]
 in_bytes = 242986745856
+
+# Source: https://huggingface.co/MiniMaxAI/MiniMax-M2.1
+# Source: https://github.com/MiniMax-AI/MiniMax-M2.1
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+top_k = 40

resources/inference_model_cards/mlx-community--MiniMax-M2.5-4bit.toml

@@ -9,5 +9,14 @@ quantization = "4bit"
 base_model = "MiniMax M2.5"
 capabilities = ["text", "thinking"]
 
+context_length = 196608
+
 [storage_size]
 in_bytes = 128666664960
+
+# Source: https://huggingface.co/MiniMaxAI/MiniMax-M2.5
+# Source: https://github.com/MiniMax-AI/MiniMax-M2.5
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+top_k = 40

resources/inference_model_cards/mlx-community--MiniMax-M2.5-6bit.toml

@@ -9,5 +9,14 @@ quantization = "6bit"
 base_model = "MiniMax M2.5"
 capabilities = ["text", "thinking"]
 
+context_length = 196608
+
 [storage_size]
 in_bytes = 185826705408
+
+# Source: https://huggingface.co/MiniMaxAI/MiniMax-M2.5
+# Source: https://github.com/MiniMax-AI/MiniMax-M2.5
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+top_k = 40

resources/inference_model_cards/mlx-community--MiniMax-M2.5-8bit.toml

@@ -9,5 +9,14 @@ quantization = "8bit"
 base_model = "MiniMax M2.5"
 capabilities = ["text", "thinking"]
 
+context_length = 196608
+
 [storage_size]
 in_bytes = 242986745856
+
+# Source: https://huggingface.co/MiniMaxAI/MiniMax-M2.5
+# Source: https://github.com/MiniMax-AI/MiniMax-M2.5
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+top_k = 40

resources/inference_model_cards/mlx-community--MiniMax-M2.7-4bit-mxfp4.toml

@@ -0,0 +1,23 @@
+model_id = "mlx-community/MiniMax-M2.7-4bit-mxfp4"
+n_layers = 62
+hidden_size = 3072
+num_key_value_heads = 8
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "minimax"
+quantization = "4bit-mxfp4"
+base_model = "MiniMax M2.7"
+capabilities = ["text", "thinking"]
+
+context_length = 196608
+
+[storage_size]
+in_bytes = 121537496794
+
+# Source: https://huggingface.co/MiniMaxAI/MiniMax-M2.7
+# Source: https://github.com/MiniMax-AI/MiniMax-M2.7
+# Source: https://unsloth.ai/docs/models/minimax-m27
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+top_k = 40