runner failling should imply the runner is dead

this simplifies some restart logic that caused the runners to loop.
we only create runners if we failed or the instance has no failed
runners (the runners were revived successfully)

.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
@@ -243,6 +243,14 @@ jobs:
       # Build the bundle
       # ============================================================
 
+      - name: Add pinned macmon to PATH
+        run: |
+          MACMON_DIR=$(nix develop --command sh -c 'dirname $(which macmon)')
+          echo "Using macmon from: $MACMON_DIR"
+          echo "$MACMON_DIR" >> $GITHUB_PATH
+          # Remove any Homebrew macmon so PyInstaller can't accidentally pick it up
+          brew uninstall macmon 2>/dev/null || true
+
       - name: Build PyInstaller bundle
         run: uv run pyinstaller packaging/pyinstaller/exo.spec
 

.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: ...

README.md

@@ -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

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:
@@ -279,6 +367,17 @@ 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).",
+    )
     args = ap.parse_args()
 
     pp_list = parse_int_list(args.pp)
@@ -364,7 +463,9 @@ 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"]
@@ -390,6 +491,16 @@ 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(
@@ -408,15 +519,18 @@ 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
                                 )
+                                inference_windows.append((inf_t0, time.monotonic()))
                             except Exception as e:
                                 logger.error(e)
                                 continue
@@ -457,6 +571,7 @@ def main() -> int:
                                     c, full_model_id, _pp, _tg, prompt_sizer
                                 )
 
+                            inf_t0 = time.monotonic()
                             with ThreadPoolExecutor(max_workers=concurrency) as pool:
                                 futures = {
                                     pool.submit(_run_concurrent, i): i
@@ -468,6 +583,7 @@ def main() -> int:
                                     except Exception as e:
                                         logger.error(f"Concurrent request failed: {e}")
                                         batch_errors += 1
+                            inference_windows.append((inf_t0, time.monotonic()))
 
                             for idx, (row, actual_pp_tokens) in enumerate(
                                 batch_results
@@ -522,13 +638,30 @@ 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 +672,17 @@ 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/FamilySidebar.svelte

@@ -42,31 +42,20 @@
 </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 +79,7 @@
           : "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 +104,7 @@
           : "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 +128,7 @@
         : "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 +154,7 @@
           : "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 +1,52 @@
+<script lang="ts">
+  interface Props {
+    title: string;
+    subtitle: string;
+    config: string;
+    description?: string;
+    language?: "json" | "bash";
+  }
+
+  let {
+    title,
+    subtitle,
+    config,
+    description = "",
+    language = "json",
+  }: Props = $props();
+
+  let copied = $state(false);
+
+  async function copyToClipboard() {
+    await navigator.clipboard.writeText(config);
+    copied = true;
+    setTimeout(() => (copied = false), 2000);
+  }
+</script>
+
+<div
+  class="border border-exo-light-gray/20 rounded-lg bg-exo-medium-gray/20 overflow-hidden"
+>
+  <div class="flex items-center justify-between px-5 py-4">
+    <div>
+      <h3 class="text-white text-sm font-semibold tracking-wide">{title}</h3>
+      <p class="text-exo-light-gray/60 text-xs mt-0.5 font-mono">{subtitle}</p>
+    </div>
+    <button
+      onclick={copyToClipboard}
+      class="px-3 py-1.5 text-xs rounded border transition-all duration-200 cursor-pointer
+        {copied
+        ? 'border-green-500/50 text-green-400 bg-green-500/10'
+        : 'border-exo-light-gray/30 text-exo-light-gray hover:border-exo-yellow/50 hover:text-exo-yellow'}"
+    >
+      {copied ? "Copied!" : "Copy"}
+    </button>
+  </div>
+  {#if description}
+    <p class="text-exo-light-gray/70 text-xs px-5 pb-3">{description}</p>
+  {/if}
+  <div class="bg-black/30 border-t border-exo-light-gray/10">
+    <pre
+      class="text-xs text-exo-light-gray/90 font-mono p-4 overflow-x-auto whitespace-pre">{config}</pre>
+  </div>
+</div>

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/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();
     }
@@ -3271,6 +3378,7 @@ export const sendMessage = (
     type: string;
     textContent?: string;
     preview?: string;
+    pageImages?: string[];
   }[],
   enableThinking?: boolean | null,
 ) => appStore.sendMessage(content, files, enableThinking);

dashboard/src/lib/types/files.ts

@@ -2,6 +2,15 @@
  * File attachment types for the chat interface
  */
 
+import { getDocument, GlobalWorkerOptions, version } from "pdfjs-dist";
+import type { DocumentInitParameters } from "pdfjs-dist/types/src/display/api";
+
+GlobalWorkerOptions.workerSrc = `https://cdn.jsdelivr.net/npm/pdfjs-dist@${version}/build/pdf.worker.mjs`;
+
+const PDF_PAGE_SCALE = 2.0;
+const PDF_MAX_PAGES = 20;
+const PDF_MAX_TEXT_CHARS = 100_000;
+
 export interface ChatUploadedFile {
   id: string;
   name: string;
@@ -10,6 +19,7 @@ export interface ChatUploadedFile {
   file: File;
   preview?: string;
   textContent?: string;
+  pageImages?: string[];
 }
 
 export interface ChatAttachment {
@@ -194,6 +204,58 @@ 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 +285,12 @@ 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/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/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>

flake.lock

@@ -164,11 +164,11 @@
         ]
       },
       "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 +184,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1764134915,
-        "narHash": "sha256-xaKvtPx6YAnA3HQVp5LwyYG1MaN4LLehpQI8xEdBvBY=",
+        "lastModified": 1774498001,
+        "narHash": "sha256-wTfdyzzrmpuqt4TQQNqilF91v0m5Mh1stNy9h7a/WK4=",
         "owner": "pyproject-nix",
         "repo": "pyproject.nix",
-        "rev": "2c8df1383b32e5443c921f61224b198a2282a657",
+        "rev": "794afa6eb588b498344f2eaa36ab1ceb7e6b0b09",
         "type": "github"
       },
       "original": {
@@ -280,11 +280,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1767701098,
-        "narHash": "sha256-CJhKZnWb3gumR9oTRjFvCg/6lYTGbZRU7xtvcyWIRwU=",
+        "lastModified": 1774490495,
+        "narHash": "sha256-a9WmQWj8fF7BctZGCoyzpUjP6GJw8H+lxl+zxpGnETk=",
         "owner": "pyproject-nix",
         "repo": "uv2nix",
-        "rev": "9d357f0d2ce6f5f35ec7959d7e704452352eb4da",
+        "rev": "18ae62fc5e389e3069854a7c66455c22e31708fc",
         "type": "github"
       },
       "original": {

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "exo"
-version = "0.3.68"
+version = "0.3.69"
 description = "Exo"
 readme = "README.md"
 requires-python = ">=3.13"
@@ -12,7 +12,7 @@ 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
@@ -29,6 +29,8 @@ dependencies = [
   "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",
 ]
 
 [project.scripts]
@@ -61,7 +63,7 @@ members = ["rust/exo_pyo3_bindings", "bench"]
 [tool.uv.sources]
 exo_pyo3_bindings = { workspace = true }
 mlx = { git = "https://github.com/rltakashige/mlx-jaccl-fix-small-recv.git", branch = "address-rdma-gpu-locks", marker = "sys_platform == 'darwin'" }
-mlx-lm = { git = "https://github.com/rltakashige/mlx-lm", branch = "leo/fix-deepseek-v32-indexer" }
+mlx-lm = { git = "https://github.com/rltakashige/mlx-lm", branch = "leo/fix-arrayscache-leak" }
 # 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 }
@@ -114,6 +116,7 @@ root = "src"
 required-version = ">=0.8.6"
 prerelease = "allow"
 environments = ["sys_platform == 'darwin'", "sys_platform == 'linux'"]
+extra-build-dependencies = { "miniaudio" = ["setuptools", "cffi", "pycparser"] }
 
 ###
 # ruff configuration

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "DeepSeek V3.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 405874409472

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "DeepSeek V3.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 765577920512

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "DeepSeek V3.2"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 378086226621

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "DeepSeek V3.2"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 755957120916

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "GLM 4.5 Air"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 122406567936

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

@@ -9,5 +9,7 @@ quantization = "bf16"
 base_model = "GLM 4.5 Air"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 229780750336

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "GLM 4.7"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 198556925568

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

@@ -9,5 +9,7 @@ quantization = "6bit"
 base_model = "GLM 4.7"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 286737579648

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "GLM 4.7"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 396963397248

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 19327352832

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

@@ -9,5 +9,7 @@ quantization = "5bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 22548578304

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

@@ -9,5 +9,7 @@ quantization = "6bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 26843545600

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 34359738368

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "GLM-5"
 capabilities = ["text", "thinking"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 790517400864

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

@@ -9,5 +9,7 @@ quantization = "MXFP4-Q8"
 base_model = "GLM-5"
 capabilities = ["text", "thinking"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 405478939008

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

@@ -9,5 +9,7 @@ quantization = "bf16"
 base_model = "GLM-5"
 capabilities = ["text", "thinking"]
 
+context_length = 202752
+
 [storage_size]
 in_bytes = 1487822475264

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Kimi K2"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 620622774272

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

@@ -9,5 +9,7 @@ quantization = ""
 base_model = "Kimi K2"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 706522120192

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

@@ -7,7 +7,15 @@ 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"

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

@@ -8,5 +8,7 @@ quantization = "4bit"
 base_model = "NVIDIA Llama-3.1-Nemotron-70B-Instruct"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 39688355840

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

@@ -8,5 +8,7 @@ quantization = "8bit"
 base_model = "NVIDIA Llama-3.1-Nemotron-70B-Instruct"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 74964549632

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

@@ -8,5 +8,7 @@ quantization = "bf16"
 base_model = "NVIDIA Llama-3.1-Nemotron-70B-Instruct"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 141107412992

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

@@ -8,5 +8,7 @@ quantization = "4bit"
 base_model = "NVIDIA Llama-3.1-Nemotron-Nano-4B-v1.1"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 2538706944

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

@@ -8,5 +8,7 @@ quantization = "8bit"
 base_model = "NVIDIA Llama-3.1-Nemotron-Nano-4B-v1.1"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 4794980352

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

@@ -8,5 +8,7 @@ quantization = "bf16"
 base_model = "NVIDIA Llama-3.1-Nemotron-Nano-4B-v1.1"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 9025492992

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Llama 3.2 1B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 729808896

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Llama 3.2 3B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 1863319552

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "Llama 3.2 3B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 3501195264

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Llama 3.3 70B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 40652242944

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "Llama 3.3 70B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 76799803392

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Llama 3.1 70B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 40652242944

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Llama 3.1 8B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 4637851648

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "Llama 3.1 8B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 8954839040

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

@@ -9,5 +9,7 @@ quantization = "bf16"
 base_model = "Llama 3.1 8B"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 16882073600

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

@@ -9,5 +9,7 @@ quantization = "3bit"
 base_model = "MiniMax M2.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 196608
+
 [storage_size]
 in_bytes = 100086644736

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "MiniMax M2.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 196608
+
 [storage_size]
 in_bytes = 242986745856

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

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "MiniMax M2.5"
 capabilities = ["text", "thinking"]
 
+context_length = 196608
+
 [storage_size]
 in_bytes = 128666664960

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

@@ -9,5 +9,7 @@ quantization = "6bit"
 base_model = "MiniMax M2.5"
 capabilities = ["text", "thinking"]
 
+context_length = 196608
+
 [storage_size]
 in_bytes = 185826705408

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

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "MiniMax M2.5"
 capabilities = ["text", "thinking"]
 
+context_length = 196608
+
 [storage_size]
 in_bytes = 242986745856

resources/inference_model_cards/mlx-community--NVIDIA-Nemotron-3-Nano-30B-A3B-MLX-4Bit.toml

@@ -8,5 +8,7 @@ quantization = "4bit"
 base_model = "NVIDIA Nemotron-3-Nano-30B-A3B"
 capabilities = ["text"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 17775342336

resources/inference_model_cards/mlx-community--NVIDIA-Nemotron-3-Nano-30B-A3B-MLX-5Bit.toml

@@ -8,5 +8,7 @@ quantization = "5bit"
 base_model = "NVIDIA Nemotron-3-Nano-30B-A3B"
 capabilities = ["text"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 21721476864

resources/inference_model_cards/mlx-community--NVIDIA-Nemotron-3-Nano-30B-A3B-MLX-6Bit.toml

@@ -8,5 +8,7 @@ quantization = "6bit"
 base_model = "NVIDIA Nemotron-3-Nano-30B-A3B"
 capabilities = ["text"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 25667611392

resources/inference_model_cards/mlx-community--NVIDIA-Nemotron-3-Nano-30B-A3B-MLX-8Bit.toml

@@ -8,5 +8,7 @@ quantization = "8bit"
 base_model = "NVIDIA Nemotron-3-Nano-30B-A3B"
 capabilities = ["text"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 33559880448

resources/inference_model_cards/mlx-community--NVIDIA-Nemotron-3-Nano-30B-A3B-MLX-BF16.toml

@@ -8,5 +8,7 @@ quantization = "bf16"
 base_model = "NVIDIA Nemotron-3-Nano-30B-A3B"
 capabilities = ["text"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 63155889408

resources/inference_model_cards/mlx-community--NVIDIA-Nemotron-3-Nano-30B-A3B-MLX-MXFP4.toml

@@ -8,5 +8,7 @@ quantization = "4bit"
 base_model = "NVIDIA Nemotron-3-Nano-30B-A3B"
 capabilities = ["text"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 16788808704

resources/inference_model_cards/mlx-community--NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4.toml

@@ -8,5 +8,7 @@ quantization = "4bit"
 base_model = "NVIDIA Nemotron-3-Nano-30B-A3B"
 capabilities = ["text"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 19323906944

resources/inference_model_cards/mlx-community--NVIDIA-Nemotron-Nano-9B-v2-4bits.toml

@@ -8,5 +8,7 @@ quantization = "4bit"
 base_model = "NVIDIA Nemotron-Nano-9B-v2"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 5002791936

resources/inference_model_cards/mlx-community--NVIDIA-Nemotron-Nano-9B-v2-6bit.toml

@@ -8,5 +8,7 @@ quantization = "6bit"
 base_model = "NVIDIA Nemotron-Nano-9B-v2"
 capabilities = ["text"]
 
+context_length = 131072
+
 [storage_size]
 in_bytes = 7224298496

resources/inference_model_cards/mlx-community--Qwen3-0.6B-4bit.toml

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Qwen3 0.6B"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 32768
+
 [storage_size]
 in_bytes = 342884352

resources/inference_model_cards/mlx-community--Qwen3-0.6B-8bit.toml

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "Qwen3 0.6B"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 32768
+
 [storage_size]
 in_bytes = 698351616

resources/inference_model_cards/mlx-community--Qwen3-235B-A22B-Instruct-2507-4bit.toml

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Qwen3 235B"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 141733920768

resources/inference_model_cards/mlx-community--Qwen3-235B-A22B-Instruct-2507-8bit.toml

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "Qwen3 235B"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 268435456000

resources/inference_model_cards/mlx-community--Qwen3-30B-A3B-4bit.toml

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Qwen3 30B"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 32768
+
 [storage_size]
 in_bytes = 17612931072

resources/inference_model_cards/mlx-community--Qwen3-30B-A3B-8bit.toml

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "Qwen3 30B"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 32768
+
 [storage_size]
 in_bytes = 33279705088

resources/inference_model_cards/mlx-community--Qwen3-Coder-480B-A35B-Instruct-4bit.toml

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Qwen3 Coder 480B"
 capabilities = ["text", "code"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 289910292480

resources/inference_model_cards/mlx-community--Qwen3-Coder-480B-A35B-Instruct-8bit.toml

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "Qwen3 Coder 480B"
 capabilities = ["text", "code"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 579820584960

resources/inference_model_cards/mlx-community--Qwen3-Coder-Next-4bit.toml

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Qwen3 Coder Next"
 capabilities = ["text", "code"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 45644286500

resources/inference_model_cards/mlx-community--Qwen3-Coder-Next-5bit.toml

@@ -9,5 +9,7 @@ quantization = "5bit"
 base_model = "Qwen3 Coder Next"
 capabilities = ["text", "code"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 57657697020

resources/inference_model_cards/mlx-community--Qwen3-Coder-Next-6bit.toml

@@ -9,5 +9,7 @@ quantization = "6bit"
 base_model = "Qwen3 Coder Next"
 capabilities = ["text", "code"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 68899327465

resources/inference_model_cards/mlx-community--Qwen3-Coder-Next-8bit.toml

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "Qwen3 Coder Next"
 capabilities = ["text", "code"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 89357758772

resources/inference_model_cards/mlx-community--Qwen3-Coder-Next-bf16.toml

@@ -9,5 +9,7 @@ quantization = "bf16"
 base_model = "Qwen3 Coder Next"
 capabilities = ["text", "code"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 157548627945

resources/inference_model_cards/mlx-community--Qwen3-Next-80B-A3B-Instruct-4bit.toml

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Qwen3 Next 80B"
 capabilities = ["text"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 46976204800

resources/inference_model_cards/mlx-community--Qwen3-Next-80B-A3B-Instruct-8bit.toml

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "Qwen3 Next 80B"
 capabilities = ["text"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 88814387200

resources/inference_model_cards/mlx-community--Qwen3-Next-80B-A3B-Thinking-4bit.toml

@@ -9,5 +9,7 @@ quantization = "4bit"
 base_model = "Qwen3 Next 80B"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 47080074240

resources/inference_model_cards/mlx-community--Qwen3-Next-80B-A3B-Thinking-8bit.toml

@@ -9,5 +9,7 @@ quantization = "8bit"
 base_model = "Qwen3 Next 80B"
 capabilities = ["text", "thinking", "thinking_toggle"]
 
+context_length = 262144
+
 [storage_size]
 in_bytes = 88814387200

resources/inference_model_cards/mlx-community--Qwen3-VL-4B-Instruct-4bit.toml

@@ -0,0 +1,14 @@
+model_id = "mlx-community/Qwen3-VL-4B-Instruct-4bit"
+n_layers = 36
+hidden_size = 2560
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "qwen"
+quantization = "4bit"
+base_model = "Qwen3-VL 4B"
+capabilities = ["text", "thinking", "vision"]
+
+context_length = 262144
+
+[storage_size]
+in_bytes = 3340000000

resources/inference_model_cards/mlx-community--Qwen3.5-122B-A10B-4bit.toml

@@ -7,7 +7,9 @@ tasks = ["TextGeneration"]
 family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3.5 122B A10B"
-capabilities = ["text", "thinking", "thinking_toggle"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 69593314272

resources/inference_model_cards/mlx-community--Qwen3.5-122B-A10B-6bit.toml

@@ -7,7 +7,9 @@ tasks = ["TextGeneration"]
 family = "qwen"
 quantization = "6bit"
 base_model = "Qwen3.5 122B A10B"
-capabilities = ["text", "thinking", "thinking_toggle"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 100120675296

resources/inference_model_cards/mlx-community--Qwen3.5-122B-A10B-8bit.toml

@@ -7,7 +7,9 @@ tasks = ["TextGeneration"]
 family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.5 122B A10B"
-capabilities = ["text", "thinking", "thinking_toggle"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 130648036320

resources/inference_model_cards/mlx-community--Qwen3.5-122B-A10B-bf16.toml

@@ -7,7 +7,9 @@ tasks = ["TextGeneration"]
 family = "qwen"
 quantization = "bf16"
 base_model = "Qwen3.5 122B A10B"
-capabilities = ["text", "thinking", "thinking_toggle"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 245125640160

resources/inference_model_cards/mlx-community--Qwen3.5-27B-4bit.toml

@@ -7,7 +7,9 @@ tasks = ["TextGeneration"]
 family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3.5 27B"
-capabilities = ["text", "thinking"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 16054266848

resources/inference_model_cards/mlx-community--Qwen3.5-27B-8bit.toml

@@ -7,7 +7,9 @@ tasks = ["TextGeneration"]
 family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.5 27B"
-capabilities = ["text", "thinking"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 29500943328

resources/inference_model_cards/mlx-community--Qwen3.5-2B-MLX-8bit.toml

@@ -7,7 +7,9 @@ tasks = ["TextGeneration"]
 family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.5 2B"
-capabilities = ["text", "thinking"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 2662787264

resources/inference_model_cards/mlx-community--Qwen3.5-35B-A3B-4bit.toml

@@ -7,7 +7,9 @@ tasks = ["TextGeneration"]
 family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3.5 35B A3B"
-capabilities = ["text", "thinking", "thinking_toggle"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 20391405152

resources/inference_model_cards/mlx-community--Qwen3.5-35B-A3B-8bit.toml

@@ -7,7 +7,9 @@ tasks = ["TextGeneration"]
 family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.5 35B A3B"
-capabilities = ["text", "thinking", "thinking_toggle"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 37721130592

resources/inference_model_cards/mlx-community--Qwen3.5-397B-A17B-4bit.toml

@@ -7,7 +7,9 @@ tasks = ["TextGeneration"]
 family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3.5 397B A17B"
-capabilities = ["text", "thinking", "thinking_toggle"]
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
 
 [storage_size]
 in_bytes = 223860768352