use 169.254, a little hacky

.github/workflows/pipeline.yml

@@ -142,6 +142,4 @@ jobs:
           # Run pytest outside sandbox (needs GPU access for MLX)
           export HOME="$RUNNER_TEMP"
           export EXO_TESTS=1
-          export EXO_DASHBOARD_DIR="$PWD/dashboard/" 
-          export EXO_RESOURCES_DIR="$PWD/resources" 
           $TEST_ENV/bin/python -m pytest src -m "not slow" --import-mode=importlib

.gitignore

@@ -28,7 +28,3 @@ target/
 dashboard/build/
 dashboard/node_modules/
 dashboard/.svelte-kit/
-
-# host config snapshots
-hosts_*.json
-.swp

.mlx_typings/mlx_lm/tokenizer_utils.pyi

@@ -108,7 +108,6 @@ class TokenizerWrapper:
     _tokenizer: PreTrainedTokenizerFast
     eos_token_id: int | None
     eos_token: str | None
-    eos_token_ids: list[int] | set[int] | None
     bos_token_id: int | None
     bos_token: str | None
     vocab_size: int
@@ -118,7 +117,7 @@ class TokenizerWrapper:
         self,
         tokenizer: Any,
         detokenizer_class: Any = ...,
-        eos_token_ids: list[int] | set[int] | None = ...,
+        eos_token_ids: list[int] | None = ...,
         chat_template: Any = ...,
         tool_parser: Any = ...,
         tool_call_start: str | None = ...,

app/EXO/EXO/Models/ClusterState.swift

@@ -293,7 +293,7 @@ struct ClusterTask {
     let modelName: String?
     let promptPreview: String?
     let errorMessage: String?
-    let parameters: TextGenerationTaskParameters?
+    let parameters: ChatCompletionTaskParameters?
 
     var sortPriority: Int {
         switch status {
@@ -330,12 +330,12 @@ struct ClusterTaskPayload: Decodable {
     let taskStatus: TaskStatus?
     let instanceId: String?
     let commandId: String?
-    let taskParams: TextGenerationTaskParameters?
+    let taskParams: ChatCompletionTaskParameters?
     let errorType: String?
     let errorMessage: String?
 }
 
-struct TextGenerationTaskParameters: Decodable, Equatable {
+struct ChatCompletionTaskParameters: Decodable, Equatable {
     let model: String?
     let messages: [ChatCompletionMessage]?
     let maxTokens: Int?
@@ -374,7 +374,7 @@ extension ClusterTask {
         guard let id = payload.taskId else { return nil }
         let status = payload.taskStatus ?? .unknown
         switch kindKey {
-        case "TextGeneration":
+        case "ChatCompletion":
             self.init(
                 id: id,
                 status: status,

app/EXO/EXO/ViewModels/InstanceViewModel.swift

@@ -216,7 +216,7 @@ struct InstanceTaskViewModel: Identifiable, Equatable {
     let promptPreview: String?
     let errorMessage: String?
     let subtitle: String?
-    let parameters: TextGenerationTaskParameters?
+    let parameters: ChatCompletionTaskParameters?
 
     var title: String {
         switch kind {

bench/exo_bench.py

@@ -5,13 +5,10 @@ from __future__ import annotations
 import argparse
 import contextlib
 import http.client
-import itertools
 import json
 import os
-import sys
 import time
 from collections.abc import Callable
-from pathlib import Path
 from statistics import mean
 from typing import Any
 from urllib.parse import urlencode
@@ -19,84 +16,6 @@ from urllib.parse import urlencode
 from loguru import logger
 from transformers import AutoTokenizer
 
-# Monkey-patch for transformers 5.x compatibility
-# Kimi's tokenization_kimi.py imports bytes_to_unicode from the old location
-# which was moved in transformers 5.0.0rc2
-try:
-    import transformers.models.gpt2.tokenization_gpt2 as gpt2_tokenization
-    from transformers.convert_slow_tokenizer import bytes_to_unicode
-
-    if not hasattr(gpt2_tokenization, "bytes_to_unicode"):
-        gpt2_tokenization.bytes_to_unicode = bytes_to_unicode  # type: ignore[attr-defined]
-except ImportError:
-    pass  # transformers < 5.0 or bytes_to_unicode not available
-
-
-def load_tokenizer_for_bench(model_id: str) -> Any:
-    """
-    Load tokenizer for benchmarking, with special handling for Kimi models.
-
-    Kimi uses a custom TikTokenTokenizer that transformers 5.x can't load via AutoTokenizer.
-    This function replicates the logic from utils_mlx.py for bench compatibility.
-    """
-    model_id_lower = model_id.lower()
-
-    if "kimi-k2" in model_id_lower:
-        import importlib.util
-        import types
-
-        from huggingface_hub import snapshot_download
-
-        # Download/get the model path
-        model_path = Path(
-            snapshot_download(
-                model_id,
-                allow_patterns=["*.json", "*.py", "*.tiktoken"],
-            )
-        )
-
-        sys.path.insert(0, str(model_path))
-
-        # Load tool_declaration_ts first (tokenization_kimi imports it with relative import)
-        tool_decl_path = model_path / "tool_declaration_ts.py"
-        if tool_decl_path.exists():
-            spec = importlib.util.spec_from_file_location(
-                "tool_declaration_ts", tool_decl_path
-            )
-            if spec and spec.loader:
-                tool_decl_module = importlib.util.module_from_spec(spec)
-                sys.modules["tool_declaration_ts"] = tool_decl_module
-                spec.loader.exec_module(tool_decl_module)
-
-        # Load tokenization_kimi with patched source (convert relative to absolute import)
-        tok_path = model_path / "tokenization_kimi.py"
-        source = tok_path.read_text()
-        source = source.replace("from .tool_declaration_ts", "from tool_declaration_ts")
-        spec = importlib.util.spec_from_file_location("tokenization_kimi", tok_path)
-        if spec:
-            tok_module = types.ModuleType("tokenization_kimi")
-            tok_module.__file__ = str(tok_path)
-            sys.modules["tokenization_kimi"] = tok_module
-            exec(compile(source, tok_path, "exec"), tok_module.__dict__)  # noqa: S102
-            TikTokenTokenizer = tok_module.TikTokenTokenizer  # noqa: N806
-        else:
-            from tokenization_kimi import TikTokenTokenizer  # type: ignore[import-not-found]  # noqa: I001
-
-        hf_tokenizer: Any = TikTokenTokenizer.from_pretrained(model_path)
-
-        # Patch encode to use internal tiktoken model directly
-        # transformers 5.x has a bug in the encode->pad path for slow tokenizers
-        def _patched_encode(text: str, **kwargs: object) -> list[int]:
-            # Pass allowed_special="all" to handle special tokens like <|im_user|>
-            return list(hf_tokenizer.model.encode(text, allowed_special="all"))
-
-        hf_tokenizer.encode = _patched_encode
-
-        return hf_tokenizer
-
-    # Default: use AutoTokenizer
-    return AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
-
 
 class ExoHttpError(RuntimeError):
     def __init__(self, status: int, reason: str, body_preview: str):
@@ -105,7 +24,7 @@ class ExoHttpError(RuntimeError):
 
 
 class ExoClient:
-    def __init__(self, host: str, port: int, timeout_s: float = 7200.0):
+    def __init__(self, host: str, port: int, timeout_s: float = 600.0):
         self.host = host
         self.port = port
         self.timeout_s = timeout_s
@@ -261,7 +180,14 @@ def parse_int_list(values: list[str]) -> list[int]:
             part = part.strip()
             if part:
                 items.append(int(part))
-    return items
+
+    seen: set[int] = set()
+    out: list[int] = []
+    for x in items:
+        if x not in seen:
+            out.append(x)
+            seen.add(x)
+    return out
 
 
 def resolve_model_short_id(client: ExoClient, model_arg: str) -> tuple[str, str]:
@@ -314,11 +240,7 @@ def run_one_completion(
 
     stats = out.get("generation_stats")
 
-    # Extract preview, handling None content (common for thinking models)
-    choices = out.get("choices") or [{}]
-    message = choices[0].get("message", {}) if choices else {}
-    content = message.get("content") or ""
-    preview = content[:200] if content else ""
+    preview = (out.get("choices") or [{}])[0]["message"]["content"][:200]
 
     return {
         "elapsed_s": elapsed,
@@ -355,29 +277,12 @@ class PromptSizer:
                 f"Target ({target}) is smaller than template overhead ({self.base_tokens})."
             )
 
-        # Estimate tokens per atom using a sample
-        sample_count = 100
-        sample_content = self.atom * sample_count
-        sample_tokens = self.count_fn(sample_content) - self.base_tokens
-        tokens_per_atom = sample_tokens / sample_count
-
-        # Estimate starting point
-        needed_tokens = target - self.base_tokens
-        estimated_atoms = int(needed_tokens / tokens_per_atom)
-
-        # Binary search to find exact atom count
-        low, high = 0, estimated_atoms * 2 + 100
-        while low < high:
-            mid = (low + high) // 2
-            tok = self.count_fn(self.atom * mid)
-            if tok < target:
-                low = mid + 1
-            else:
-                high = mid
-
-        content = self.atom * low
+        content = ""
         tok = self.count_fn(content)
-        logger.info(f"{tok=}")
+
+        while tok < target:
+            content += self.atom
+            tok = self.count_fn(content)
 
         if tok != target:
             raise RuntimeError(
@@ -443,7 +348,7 @@ def main() -> int:
         help="Warmup runs per placement (uses first pp/tg).",
     )
     ap.add_argument(
-        "--timeout", type=float, default=7200.0, help="HTTP timeout (seconds)."
+        "--timeout", type=float, default=600.0, help="HTTP timeout (seconds)."
     )
     ap.add_argument(
         "--json-out",
@@ -453,11 +358,6 @@ def main() -> int:
     ap.add_argument(
         "--dry-run", action="store_true", help="List selected placements and exit."
     )
-    ap.add_argument(
-        "--all-combinations",
-        action="store_true",
-        help="Force all pp×tg combinations (cartesian product) even when lists have equal length.",
-    )
     args = ap.parse_args()
 
     pp_list = parse_int_list(args.pp)
@@ -469,15 +369,6 @@ def main() -> int:
         logger.error("--repeat must be >= 1")
         return 2
 
-    # Log pairing mode
-    use_combinations = args.all_combinations or len(pp_list) != len(tg_list)
-    if use_combinations:
-        logger.info(
-            f"pp/tg mode: combinations (product) - {len(pp_list) * len(tg_list)} pairs"
-        )
-    else:
-        logger.info(f"pp/tg mode: tandem (zip) - {len(pp_list)} pairs")
-
     client = ExoClient(args.host, args.port, timeout_s=args.timeout)
     short_id, full_model_id = resolve_model_short_id(client, args.model)
 
@@ -486,7 +377,10 @@ def main() -> int:
     )
     previews = previews_resp.get("previews") or []
 
-    tokenizer = load_tokenizer_for_bench(full_model_id)
+    tokenizer = AutoTokenizer.from_pretrained(
+        full_model_id,
+        trust_remote_code=True,
+    )
     if tokenizer is None:
         raise RuntimeError("[exo-bench] tokenizer load failed")
 
@@ -592,55 +486,60 @@ def main() -> int:
                 )
                 logger.debug(f"  warmup {i + 1}/{args.warmup} done")
 
-            # If pp and tg lists have same length, run in tandem (zip)
-            # Otherwise (or if --all-combinations), run all combinations (cartesian product)
-            if use_combinations:
-                pp_tg_pairs = list(itertools.product(pp_list, tg_list))
-            else:
-                pp_tg_pairs = list(zip(pp_list, tg_list, strict=True))
-
-            for pp, tg in pp_tg_pairs:
-                runs: list[dict[str, Any]] = []
-                for r in range(args.repeat):
-                    time.sleep(3)
-                    try:
-                        row, actual_pp_tokens = run_one_completion(
-                            client, full_model_id, pp, tg, prompt_sizer
+            for pp in pp_list:
+                # if (
+                #     pp * n_nodes > 2048
+                #     and "ring" in instance_meta.lower()
+                #     and "tensor" in sharding.lower()
+                # ):
+                #     model_card = MODEL_CARDS[short_id]
+                #     if model_card.metadata.storage_size > Memory.from_gb(10):
+                #         logger.info(
+                #             f"Skipping tensor ring as this is too slow for model of size {model_card.metadata.storage_size} on {n_nodes=}"
+                #         )
+                #         continue
+                for tg in tg_list:
+                    runs: list[dict[str, Any]] = []
+                    for r in range(args.repeat):
+                        time.sleep(3)
+                        try:
+                            row, actual_pp_tokens = run_one_completion(
+                                client, full_model_id, pp, tg, prompt_sizer
+                            )
+                        except Exception as e:
+                            logger.error(e)
+                            continue
+                        row.update(
+                            {
+                                "model_short_id": short_id,
+                                "model_id": full_model_id,
+                                "placement_sharding": sharding,
+                                "placement_instance_meta": instance_meta,
+                                "placement_nodes": n_nodes,
+                                "instance_id": instance_id,
+                                "pp_tokens": actual_pp_tokens,
+                                "tg": tg,
+                                "repeat_index": r,
+                            }
                         )
-                    except Exception as e:
-                        logger.error(e)
-                        continue
-                    row.update(
-                        {
-                            "model_short_id": short_id,
-                            "model_id": full_model_id,
-                            "placement_sharding": sharding,
-                            "placement_instance_meta": instance_meta,
-                            "placement_nodes": n_nodes,
-                            "instance_id": instance_id,
-                            "pp_tokens": actual_pp_tokens,
-                            "tg": tg,
-                            "repeat_index": r,
-                        }
-                    )
-                    runs.append(row)
-                    all_rows.append(row)
+                        runs.append(row)
+                        all_rows.append(row)
 
-                if runs:
-                    prompt_tps = mean(x["stats"]["prompt_tps"] for x in runs)
-                    gen_tps = mean(x["stats"]["generation_tps"] for x in runs)
-                    ptok = mean(x["stats"]["prompt_tokens"] for x in runs)
-                    gtok = mean(x["stats"]["generation_tokens"] for x in runs)
-                    peak = mean(
-                        x["stats"]["peak_memory_usage"]["inBytes"] for x in runs
-                    )
+                    if runs:
+                        prompt_tps = mean(x["stats"]["prompt_tps"] for x in runs)
+                        gen_tps = mean(x["stats"]["generation_tps"] for x in runs)
+                        ptok = mean(x["stats"]["prompt_tokens"] for x in runs)
+                        gtok = mean(x["stats"]["generation_tokens"] for x in runs)
+                        peak = mean(
+                            x["stats"]["peak_memory_usage"]["inBytes"] for x in runs
+                        )
 
-                    logger.info(
-                        f"prompt_tps={prompt_tps:.2f} gen_tps={gen_tps:.2f}    "
-                        f"prompt_tokens={ptok} gen_tokens={gtok}    "
-                        f"peak_memory={format_peak_memory(peak)}\n"
-                    )
-                time.sleep(2)
+                        logger.info(
+                            f"prompt_tps={prompt_tps:.2f} gen_tps={gen_tps:.2f}    "
+                            f"prompt_tokens={ptok} gen_tokens={gtok}    "
+                            f"peak_memory={format_peak_memory(peak)}\n"
+                        )
+                    time.sleep(2)
         finally:
             try:
                 client.request_json("DELETE", f"/instance/{instance_id}")

dashboard/src/lib/components/FamilyLogos.svelte

@@ -1,73 +0,0 @@
-<script lang="ts">
-  type FamilyLogoProps = {
-    family: string;
-    class?: string;
-  };
-
-  let { family, class: className = "" }: FamilyLogoProps = $props();
-</script>
-
-{#if family === "favorites"}
-  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
-    <path
-      d="M12 2l3.09 6.26L22 9.27l-5 4.87 1.18 6.88L12 17.77l-6.18 3.25L7 14.14 2 9.27l6.91-1.01L12 2z"
-    />
-  </svg>
-{:else if family === "llama" || family === "meta"}
-  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
-    <path
-      d="M6.915 4.03c-1.968 0-3.683 1.28-4.871 3.113C.704 9.208 0 11.883 0 14.449c0 .706.07 1.369.21 1.973a6.624 6.624 0 0 0 .265.86 5.297 5.297 0 0 0 .371.761c.696 1.159 1.818 1.927 3.593 1.927 1.497 0 2.633-.671 3.965-2.444.76-1.012 1.144-1.626 2.663-4.32l.756-1.339.186-.325c.061.1.121.196.183.3l2.152 3.595c.724 1.21 1.665 2.556 2.47 3.314 1.046.987 1.992 1.22 3.06 1.22 1.075 0 1.876-.355 2.455-.843a3.743 3.743 0 0 0 .81-.973c.542-.939.861-2.127.861-3.745 0-2.72-.681-5.357-2.084-7.45-1.282-1.912-2.957-2.93-4.716-2.93-1.047 0-2.088.467-3.053 1.308-.652.57-1.257 1.29-1.82 2.05-.69-.875-1.335-1.547-1.958-2.056-1.182-.966-2.315-1.303-3.454-1.303zm10.16 2.053c1.147 0 2.188.758 2.992 1.999 1.132 1.748 1.647 4.195 1.647 6.4 0 1.548-.368 2.9-1.839 2.9-.58 0-1.027-.23-1.664-1.004-.496-.601-1.343-1.878-2.832-4.358l-.617-1.028a44.908 44.908 0 0 0-1.255-1.98c.07-.109.141-.224.211-.327 1.12-1.667 2.118-2.602 3.358-2.602zm-10.201.553c1.265 0 2.058.791 2.675 1.446.307.327.737.871 1.234 1.579l-1.02 1.566c-.757 1.163-1.882 3.017-2.837 4.338-1.191 1.649-1.81 1.817-2.486 1.817-.524 0-1.038-.237-1.383-.794-.263-.426-.464-1.13-.464-2.046 0-2.221.63-4.535 1.66-6.088.454-.687.964-1.226 1.533-1.533a2.264 2.264 0 0 1 1.088-.285z"
-    />
-  </svg>
-{:else if family === "qwen"}
-  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
-    <path
-      d="M12.604 1.34c.393.69.784 1.382 1.174 2.075a.18.18 0 00.157.091h5.552c.174 0 .322.11.446.327l1.454 2.57c.19.337.24.478.024.837-.26.43-.513.864-.76 1.3l-.367.658c-.106.196-.223.28-.04.512l2.652 4.637c.172.301.111.494-.043.77-.437.785-.882 1.564-1.335 2.34-.159.272-.352.375-.68.37-.777-.016-1.552-.01-2.327.016a.099.099 0 00-.081.05 575.097 575.097 0 01-2.705 4.74c-.169.293-.38.363-.725.364-.997.003-2.002.004-3.017.002a.537.537 0 01-.465-.271l-1.335-2.323a.09.09 0 00-.083-.049H4.982c-.285.03-.553-.001-.805-.092l-1.603-2.77a.543.543 0 01-.002-.54l1.207-2.12a.198.198 0 000-.197 550.951 550.951 0 01-1.875-3.272l-.79-1.395c-.16-.31-.173-.496.095-.965.465-.813.927-1.625 1.387-2.436.132-.234.304-.334.584-.335a338.3 338.3 0 012.589-.001.124.124 0 00.107-.063l2.806-4.895a.488.488 0 01.422-.246c.524-.001 1.053 0 1.583-.006L11.704 1c.341-.003.724.032.9.34zm-3.432.403a.06.06 0 00-.052.03L6.254 6.788a.157.157 0 01-.135.078H3.253c-.056 0-.07.025-.041.074l5.81 10.156c.025.042.013.062-.034.063l-2.795.015a.218.218 0 00-.2.116l-1.32 2.31c-.044.078-.021.118.068.118l5.716.008c.046 0 .08.02.104.061l1.403 2.454c.046.081.092.082.139 0l5.006-8.76.783-1.382a.055.055 0 01.096 0l1.424 2.53a.122.122 0 00.107.062l2.763-.02a.04.04 0 00.035-.02.041.041 0 000-.04l-2.9-5.086a.108.108 0 010-.113l.293-.507 1.12-1.977c.024-.041.012-.062-.035-.062H9.2c-.059 0-.073-.026-.043-.077l1.434-2.505a.107.107 0 000-.114L9.225 1.774a.06.06 0 00-.053-.031zm6.29 8.02c.046 0 .058.02.034.06l-.832 1.465-2.613 4.585a.056.056 0 01-.05.029.058.058 0 01-.05-.029L8.498 9.841c-.02-.034-.01-.052.028-.054l.216-.012 6.722-.012z"
-    />
-  </svg>
-{:else if family === "deepseek"}
-  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
-    <path
-      d="M23.748 4.482c-.254-.124-.364.113-.512.234-.051.039-.094.09-.137.136-.372.397-.806.657-1.373.626-.829-.046-1.537.214-2.163.848-.133-.782-.575-1.248-1.247-1.548-.352-.156-.708-.311-.955-.65-.172-.241-.219-.51-.305-.774-.055-.16-.11-.323-.293-.35-.2-.031-.278.136-.356.276-.313.572-.434 1.202-.422 1.84.027 1.436.633 2.58 1.838 3.393.137.093.172.187.129.323-.082.28-.18.552-.266.833-.055.179-.137.217-.329.14a5.526 5.526 0 01-1.736-1.18c-.857-.828-1.631-1.742-2.597-2.458a11.365 11.365 0 00-.689-.471c-.985-.957.13-1.743.388-1.836.27-.098.093-.432-.779-.428-.872.004-1.67.295-2.687.684a3.055 3.055 0 01-.465.137 9.597 9.597 0 00-2.883-.102c-1.885.21-3.39 1.102-4.497 2.623C.082 8.606-.231 10.684.152 12.85c.403 2.284 1.569 4.175 3.36 5.653 1.858 1.533 3.997 2.284 6.438 2.14 1.482-.085 3.133-.284 4.994-1.86.47.234.962.327 1.78.397.63.059 1.236-.03 1.705-.128.735-.156.684-.837.419-.961-2.155-1.004-1.682-.595-2.113-.926 1.096-1.296 2.746-2.642 3.392-7.003.05-.347.007-.565 0-.845-.004-.17.035-.237.23-.256a4.173 4.173 0 001.545-.475c1.396-.763 1.96-2.015 2.093-3.517.02-.23-.004-.467-.247-.588zM11.581 18c-2.089-1.642-3.102-2.183-3.52-2.16-.392.024-.321.471-.235.763.09.288.207.486.371.739.114.167.192.416-.113.603-.673.416-1.842-.14-1.897-.167-1.361-.802-2.5-1.86-3.301-3.307-.774-1.393-1.224-2.887-1.298-4.482-.02-.386.093-.522.477-.592a4.696 4.696 0 011.529-.039c2.132.312 3.946 1.265 5.468 2.774.868.86 1.525 1.887 2.202 2.891.72 1.066 1.494 2.082 2.48 2.914.348.292.625.514.891.677-.802.09-2.14.11-3.054-.614zm1-6.44a.306.306 0 01.415-.287.302.302 0 01.2.288.306.306 0 01-.31.307.303.303 0 01-.304-.308zm3.11 1.596c-.2.081-.399.151-.59.16a1.245 1.245 0 01-.798-.254c-.274-.23-.47-.358-.552-.758a1.73 1.73 0 01.016-.588c.07-.327-.008-.537-.239-.727-.187-.156-.426-.199-.688-.199a.559.559 0 01-.254-.078c-.11-.054-.2-.19-.114-.358.028-.054.16-.186.192-.21.356-.202.767-.136 1.146.016.352.144.618.408 1.001.782.391.451.462.576.685.914.176.265.336.537.445.848.067.195-.019.354-.25.452z"
-    />
-  </svg>
-{:else if family === "openai" || family === "gpt-oss"}
-  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
-    <path
-      d="M22.2819 9.8211a5.9847 5.9847 0 0 0-.5157-4.9108 6.0462 6.0462 0 0 0-6.5098-2.9A6.0651 6.0651 0 0 0 4.9807 4.1818a5.9847 5.9847 0 0 0-3.9977 2.9 6.0462 6.0462 0 0 0 .7427 7.0966 5.98 5.98 0 0 0 .511 4.9107 6.051 6.051 0 0 0 6.5146 2.9001A5.9847 5.9847 0 0 0 13.2599 24a6.0557 6.0557 0 0 0 5.7718-4.2058 5.9894 5.9894 0 0 0 3.9977-2.9001 6.0557 6.0557 0 0 0-.7475-7.0729zm-9.022 12.6081a4.4755 4.4755 0 0 1-2.8764-1.0408l.1419-.0804 4.7783-2.7582a.7948.7948 0 0 0 .3927-.6813v-6.7369l2.02 1.1686a.071.071 0 0 1 .038.052v5.5826a4.504 4.504 0 0 1-4.4945 4.4944zm-9.6607-4.1254a4.4708 4.4708 0 0 1-.5346-3.0137l.142.0852 4.783 2.7582a.7712.7712 0 0 0 .7806 0l5.8428-3.3685v2.3324a.0804.0804 0 0 1-.0332.0615L9.74 19.9502a4.4992 4.4992 0 0 1-6.1408-1.6464zM2.3408 7.8956a4.485 4.485 0 0 1 2.3655-1.9728V11.6a.7664.7664 0 0 0 .3879.6765l5.8144 3.3543-2.0201 1.1685a.0757.0757 0 0 1-.071 0l-4.8303-2.7865A4.504 4.504 0 0 1 2.3408 7.872zm16.5963 3.8558L13.1038 8.364 15.1192 7.2a.0757.0757 0 0 1 .071 0l4.8303 2.7913a4.4944 4.4944 0 0 1-.6765 8.1042v-5.6772a.79.79 0 0 0-.407-.667zm2.0107-3.0231l-.142-.0852-4.7735-2.7818a.7759.7759 0 0 0-.7854 0L9.409 9.2297V6.8974a.0662.0662 0 0 1 .0284-.0615l4.8303-2.7866a4.4992 4.4992 0 0 1 6.6802 4.66zM8.3065 12.863l-2.02-1.1638a.0804.0804 0 0 1-.038-.0567V6.0742a4.4992 4.4992 0 0 1 7.3757-3.4537l-.142.0805L8.704 5.459a.7948.7948 0 0 0-.3927.6813zm1.0976-2.3654l2.602-1.4998 2.6069 1.4998v2.9994l-2.5974 1.4997-2.6067-1.4997Z"
-    />
-  </svg>
-{:else if family === "glm"}
-  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
-    <path
-      d="M11.991 23.503a.24.24 0 00-.244.248.24.24 0 00.244.249.24.24 0 00.245-.249.24.24 0 00-.22-.247l-.025-.001zM9.671 5.365a1.697 1.697 0 011.099 2.132l-.071.172-.016.04-.018.054c-.07.16-.104.32-.104.498-.035.71.47 1.279 1.186 1.314h.366c1.309.053 2.338 1.173 2.286 2.523-.052 1.332-1.152 2.38-2.478 2.327h-.174c-.715.018-1.274.64-1.239 1.368 0 .124.018.23.053.337.209.373.54.658.96.8.75.23 1.517-.125 1.9-.782l.018-.035c.402-.64 1.17-.96 1.92-.711.854.284 1.378 1.226 1.099 2.167a1.661 1.661 0 01-2.077 1.102 1.711 1.711 0 01-.907-.711l-.017-.035c-.2-.323-.463-.58-.851-.711l-.056-.018a1.646 1.646 0 00-1.954.746 1.66 1.66 0 01-1.065.764 1.677 1.677 0 01-1.989-1.279c-.209-.906.332-1.83 1.257-2.043a1.51 1.51 0 01.296-.035h.018c.68-.071 1.151-.622 1.116-1.333a1.307 1.307 0 00-.227-.693 2.515 2.515 0 01-.366-1.403 2.39 2.39 0 01.366-1.208c.14-.195.21-.444.227-.693.018-.71-.506-1.261-1.186-1.332l-.07-.018a1.43 1.43 0 01-.299-.07l-.05-.019a1.7 1.7 0 01-1.047-2.114 1.68 1.68 0 012.094-1.101zm-5.575 10.11c.26-.264.639-.367.994-.27.355.096.633.379.728.74.095.362-.007.748-.267 1.013-.402.41-1.053.41-1.455 0a1.062 1.062 0 010-1.482zm14.845-.294c.359-.09.738.024.992.297.254.274.344.665.237 1.025-.107.36-.396.634-.756.718-.551.128-1.1-.22-1.23-.781a1.05 1.05 0 01.757-1.26zm-.064-4.39c.314.32.49.753.49 1.206 0 .452-.176.886-.49 1.206-.315.32-.74.5-1.185.5-.444 0-.87-.18-1.184-.5a1.727 1.727 0 010-2.412 1.654 1.654 0 012.369 0zm-11.243.163c.364.484.447 1.128.218 1.691a1.665 1.665 0 01-2.188.923c-.855-.36-1.26-1.358-.907-2.228a1.68 1.68 0 011.33-1.038c.593-.08 1.183.169 1.547.652zm11.545-4.221c.368 0 .708.2.892.524.184.324.184.724 0 1.048a1.026 1.026 0 01-.892.524c-.568 0-1.03-.47-1.03-1.048 0-.579.462-1.048 1.03-1.048zm-14.358 0c.368 0 .707.2.891.524.184.324.184.724 0 1.048a1.026 1.026 0 01-.891.524c-.569 0-1.03-.47-1.03-1.048 0-.579.461-1.048 1.03-1.048zm10.031-1.475c.925 0 1.675.764 1.675 1.706s-.75 1.705-1.675 1.705-1.674-.763-1.674-1.705c0-.942.75-1.706 1.674-1.706zm-2.626-.684c.362-.082.653-.356.761-.718a1.062 1.062 0 00-.238-1.028 1.017 1.017 0 00-.996-.294c-.547.14-.881.7-.752 1.257.13.558.675.907 1.225.783zm0 16.876c.359-.087.644-.36.75-.72a1.062 1.062 0 00-.237-1.019 1.018 1.018 0 00-.985-.301 1.037 1.037 0 00-.762.717c-.108.361-.017.754.239 1.028.245.263.606.377.953.305l.043-.01zM17.19 3.5a.631.631 0 00.628-.64c0-.355-.279-.64-.628-.64a.631.631 0 00-.628.64c0 .355.28.64.628.64zm-10.38 0a.631.631 0 00.628-.64c0-.355-.28-.64-.628-.64a.631.631 0 00-.628.64c0 .355.279.64.628.64zm-5.182 7.852a.631.631 0 00-.628.64c0 .354.28.639.628.639a.63.63 0 00.627-.606l.001-.034a.62.62 0 00-.628-.64zm5.182 9.13a.631.631 0 00-.628.64c0 .355.279.64.628.64a.631.631 0 00.628-.64c0-.355-.28-.64-.628-.64zm10.38.018a.631.631 0 00-.628.64c0 .355.28.64.628.64a.631.631 0 00.628-.64c0-.355-.279-.64-.628-.64zm5.182-9.148a.631.631 0 00-.628.64c0 .354.279.639.628.639a.631.631 0 00.628-.64c0-.355-.28-.64-.628-.64zm-.384-4.992a.24.24 0 00.244-.249.24.24 0 00-.244-.249.24.24 0 00-.244.249c0 .142.122.249.244.249zM11.991.497a.24.24 0 00.245-.248A.24.24 0 0011.99 0a.24.24 0 00-.244.249c0 .133.108.236.223.247l.021.001zM2.011 6.36a.24.24 0 00.245-.249.24.24 0 00-.244-.249.24.24 0 00-.244.249.24.24 0 00.244.249zm0 11.263a.24.24 0 00-.243.248.24.24 0 00.244.249.24.24 0 00.244-.249.252.252 0 00-.244-.248zm19.995-.018a.24.24 0 00-.245.248.24.24 0 00.245.25.24.24 0 00.244-.25.252.252 0 00-.244-.248z"
-    />
-  </svg>
-{:else if family === "minimax"}
-  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
-    <path
-      d="M16.278 2c1.156 0 2.093.927 2.093 2.07v12.501a.74.74 0 00.744.709.74.74 0 00.743-.709V9.099a2.06 2.06 0 012.071-2.049A2.06 2.06 0 0124 9.1v6.561a.649.649 0 01-.652.645.649.649 0 01-.653-.645V9.1a.762.762 0 00-.766-.758.762.762 0 00-.766.758v7.472a2.037 2.037 0 01-2.048 2.026 2.037 2.037 0 01-2.048-2.026v-12.5a.785.785 0 00-.788-.753.785.785 0 00-.789.752l-.001 15.904A2.037 2.037 0 0113.441 22a2.037 2.037 0 01-2.048-2.026V18.04c0-.356.292-.645.652-.645.36 0 .652.289.652.645v1.934c0 .263.142.506.372.638.23.131.514.131.744 0a.734.734 0 00.372-.638V4.07c0-1.143.937-2.07 2.093-2.07zm-5.674 0c1.156 0 2.093.927 2.093 2.07v11.523a.648.648 0 01-.652.645.648.648 0 01-.652-.645V4.07a.785.785 0 00-.789-.78.785.785 0 00-.789.78v14.013a2.06 2.06 0 01-2.07 2.048 2.06 2.06 0 01-2.071-2.048V9.1a.762.762 0 00-.766-.758.762.762 0 00-.766.758v3.8a2.06 2.06 0 01-2.071 2.049A2.06 2.06 0 010 12.9v-1.378c0-.357.292-.646.652-.646.36 0 .653.29.653.646V12.9c0 .418.343.757.766.757s.766-.339.766-.757V9.099a2.06 2.06 0 012.07-2.048 2.06 2.06 0 012.071 2.048v8.984c0 .419.343.758.767.758.423 0 .766-.339.766-.758V4.07c0-1.143.937-2.07 2.093-2.07z"
-    />
-  </svg>
-{:else if family === "kimi"}
-  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
-    <path
-      d="M19.738 5.776c.163-.209.306-.4.457-.585.07-.087.064-.153-.004-.244-.655-.861-.717-1.817-.34-2.787.283-.73.909-1.072 1.674-1.145.477-.045.945.004 1.379.236.57.305.902.77 1.01 1.412.086.512.07 1.012-.075 1.508-.257.878-.888 1.333-1.753 1.448-.718.096-1.446.108-2.17.157-.056.004-.113 0-.178 0z"
-    />
-    <path
-      d="M17.962 1.844h-4.326l-3.425 7.81H5.369V1.878H1.5V22h3.87v-8.477h6.824a3.025 3.025 0 002.743-1.75V22h3.87v-8.477a3.87 3.87 0 00-3.588-3.86v-.01h-2.125a3.94 3.94 0 002.323-2.12l2.545-5.689z"
-    />
-  </svg>
-{:else if family === "huggingface"}
-  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
-    <path
-      d="M12.025 1.13c-5.77 0-10.449 4.647-10.449 10.378 0 1.112.178 2.181.503 3.185.064-.222.203-.444.416-.577a.96.96 0 0 1 .524-.15c.293 0 .584.124.84.284.278.173.48.408.71.694.226.282.458.611.684.951v-.014c.017-.324.106-.622.264-.874s.403-.487.762-.543c.3-.047.596.06.787.203s.31.313.4.467c.15.257.212.468.233.542.01.026.653 1.552 1.657 2.54.616.605 1.01 1.223 1.082 1.912.055.537-.096 1.059-.38 1.572.637.121 1.294.187 1.967.187.657 0 1.298-.063 1.921-.178-.287-.517-.44-1.041-.384-1.581.07-.69.465-1.307 1.081-1.913 1.004-.987 1.647-2.513 1.657-2.539.021-.074.083-.285.233-.542.09-.154.208-.323.4-.467a1.08 1.08 0 0 1 .787-.203c.359.056.604.29.762.543s.247.55.265.874v.015c.225-.34.457-.67.683-.952.23-.286.432-.52.71-.694.257-.16.547-.284.84-.285a.97.97 0 0 1 .524.151c.228.143.373.388.43.625l.006.04a10.3 10.3 0 0 0 .534-3.273c0-5.731-4.678-10.378-10.449-10.378M8.327 6.583a1.5 1.5 0 0 1 .713.174 1.487 1.487 0 0 1 .617 2.013c-.183.343-.762-.214-1.102-.094-.38.134-.532.914-.917.71a1.487 1.487 0 0 1 .69-2.803m7.486 0a1.487 1.487 0 0 1 .689 2.803c-.385.204-.536-.576-.916-.71-.34-.12-.92.437-1.103.094a1.487 1.487 0 0 1 .617-2.013 1.5 1.5 0 0 1 .713-.174m-10.68 1.55a.96.96 0 1 1 0 1.921.96.96 0 0 1 0-1.92m13.838 0a.96.96 0 1 1 0 1.92.96.96 0 0 1 0-1.92M8.489 11.458c.588.01 1.965 1.157 3.572 1.164 1.607-.007 2.984-1.155 3.572-1.164.196-.003.305.12.305.454 0 .886-.424 2.328-1.563 3.202-.22-.756-1.396-1.366-1.63-1.32q-.011.001-.02.006l-.044.026-.01.008-.03.024q-.018.017-.035.036l-.032.04a1 1 0 0 0-.058.09l-.014.025q-.049.088-.11.19a1 1 0 0 1-.083.116 1.2 1.2 0 0 1-.173.18q-.035.029-.075.058a1.3 1.3 0 0 1-.251-.243 1 1 0 0 1-.076-.107c-.124-.193-.177-.363-.337-.444-.034-.016-.104-.008-.2.022q-.094.03-.216.087-.06.028-.125.063l-.13.074q-.067.04-.136.086a3 3 0 0 0-.135.096 3 3 0 0 0-.26.219 2 2 0 0 0-.12.121 2 2 0 0 0-.106.128l-.002.002a2 2 0 0 0-.09.132l-.001.001a1.2 1.2 0 0 0-.105.212q-.013.036-.024.073c-1.139-.875-1.563-2.317-1.563-3.203 0-.334.109-.457.305-.454m.836 10.354c.824-1.19.766-2.082-.365-3.194-1.13-1.112-1.789-2.738-1.789-2.738s-.246-.945-.806-.858-.97 1.499.202 2.362c1.173.864-.233 1.45-.685.64-.45-.812-1.683-2.896-2.322-3.295s-1.089-.175-.938.647 2.822 2.813 2.562 3.244-1.176-.506-1.176-.506-2.866-2.567-3.49-1.898.473 1.23 2.037 2.16c1.564.932 1.686 1.178 1.464 1.53s-3.675-2.511-4-1.297c-.323 1.214 3.524 1.567 3.287 2.405-.238.839-2.71-1.587-3.216-.642-.506.946 3.49 2.056 3.522 2.064 1.29.33 4.568 1.028 5.713-.624m5.349 0c-.824-1.19-.766-2.082.365-3.194 1.13-1.112 1.789-2.738 1.789-2.738s.246-.945.806-.858.97 1.499-.202 2.362c-1.173.864.233 1.45.685.64.451-.812 1.683-2.896 2.322-3.295s1.089-.175.938.647-2.822 2.813-2.562 3.244 1.176-.506 1.176-.506 2.866-2.567 3.49-1.898-.473 1.23-2.037 2.16c-1.564.932-1.686 1.178-1.464 1.53s3.675-2.511 4-1.297c.323 1.214-3.524 1.567-3.287 2.405.238.839 2.71-1.587 3.216-.642.506.946-3.49 2.056-3.522 2.064-1.29.33-4.568 1.028-5.713-.624"
-    />
-  </svg>
-{:else}
-  <svg class="w-6 h-6 {className}" viewBox="0 0 24 24" fill="currentColor">
-    <path
-      d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm-2 15l-5-5 1.41-1.41L10 14.17l7.59-7.59L19 8l-9 9z"
-    />
-  </svg>
-{/if}

dashboard/src/lib/components/FamilySidebar.svelte

@@ -1,142 +0,0 @@
-<script lang="ts">
-  import FamilyLogos from "./FamilyLogos.svelte";
-
-  type FamilySidebarProps = {
-    families: string[];
-    selectedFamily: string | null;
-    hasFavorites: boolean;
-    onSelect: (family: string | null) => void;
-  };
-
-  let { families, selectedFamily, hasFavorites, onSelect }: FamilySidebarProps =
-    $props();
-
-  // Family display names
-  const familyNames: Record<string, string> = {
-    favorites: "Favorites",
-    huggingface: "Hub",
-    llama: "Meta",
-    qwen: "Qwen",
-    deepseek: "DeepSeek",
-    "gpt-oss": "OpenAI",
-    glm: "GLM",
-    minimax: "MiniMax",
-    kimi: "Kimi",
-  };
-
-  function getFamilyName(family: string): string {
-    return (
-      familyNames[family] || family.charAt(0).toUpperCase() + family.slice(1)
-    );
-  }
-</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-[64px]"
->
-  <!-- All models (no filter) -->
-  <button
-    type="button"
-    onclick={() => onSelect(null)}
-    class="group flex flex-col items-center justify-center p-2 rounded transition-all duration-200 cursor-pointer {selectedFamily ===
-    null
-      ? 'bg-exo-yellow/20 border-l-2 border-exo-yellow'
-      : 'hover:bg-white/5 border-l-2 border-transparent'}"
-    title="All models"
-  >
-    <svg
-      class="w-5 h-5 {selectedFamily === null
-        ? 'text-exo-yellow'
-        : 'text-white/50 group-hover:text-white/70'}"
-      viewBox="0 0 24 24"
-      fill="currentColor"
-    >
-      <path
-        d="M4 8h4V4H4v4zm6 12h4v-4h-4v4zm-6 0h4v-4H4v4zm0-6h4v-4H4v4zm6 0h4v-4h-4v4zm6-10v4h4V4h-4zm-6 4h4V4h-4v4zm6 6h4v-4h-4v4zm0 6h4v-4h-4v4z"
-      />
-    </svg>
-    <span
-      class="text-[9px] font-mono mt-0.5 {selectedFamily === null
-        ? 'text-exo-yellow'
-        : 'text-white/40 group-hover:text-white/60'}">All</span
-    >
-  </button>
-
-  <!-- Favorites (only show if has favorites) -->
-  {#if hasFavorites}
-    <button
-      type="button"
-      onclick={() => onSelect("favorites")}
-      class="group flex flex-col items-center justify-center p-2 rounded transition-all duration-200 cursor-pointer {selectedFamily ===
-      'favorites'
-        ? 'bg-exo-yellow/20 border-l-2 border-exo-yellow'
-        : 'hover:bg-white/5 border-l-2 border-transparent'}"
-      title="Show favorited models"
-    >
-      <FamilyLogos
-        family="favorites"
-        class={selectedFamily === "favorites"
-          ? "text-amber-400"
-          : "text-white/50 group-hover:text-amber-400/70"}
-      />
-      <span
-        class="text-[9px] font-mono mt-0.5 {selectedFamily === 'favorites'
-          ? 'text-amber-400'
-          : 'text-white/40 group-hover:text-white/60'}">Faves</span
-      >
-    </button>
-  {/if}
-
-  <!-- HuggingFace Hub -->
-  <button
-    type="button"
-    onclick={() => onSelect("huggingface")}
-    class="group flex flex-col items-center justify-center p-2 rounded transition-all duration-200 cursor-pointer {selectedFamily ===
-    'huggingface'
-      ? 'bg-orange-500/20 border-l-2 border-orange-400'
-      : 'hover:bg-white/5 border-l-2 border-transparent'}"
-    title="Browse and add models from Hugging Face"
-  >
-    <FamilyLogos
-      family="huggingface"
-      class={selectedFamily === "huggingface"
-        ? "text-orange-400"
-        : "text-white/50 group-hover:text-orange-400/70"}
-    />
-    <span
-      class="text-[9px] font-mono mt-0.5 {selectedFamily === 'huggingface'
-        ? 'text-orange-400'
-        : 'text-white/40 group-hover:text-white/60'}">Hub</span
-    >
-  </button>
-
-  <div class="h-px bg-exo-yellow/10 my-1"></div>
-
-  <!-- Model families -->
-  {#each families as family}
-    <button
-      type="button"
-      onclick={() => onSelect(family)}
-      class="group flex flex-col items-center justify-center p-2 rounded transition-all duration-200 cursor-pointer {selectedFamily ===
-      family
-        ? 'bg-exo-yellow/20 border-l-2 border-exo-yellow'
-        : 'hover:bg-white/5 border-l-2 border-transparent'}"
-      title={getFamilyName(family)}
-    >
-      <FamilyLogos
-        {family}
-        class={selectedFamily === family
-          ? "text-exo-yellow"
-          : "text-white/50 group-hover:text-white/70"}
-      />
-      <span
-        class="text-[9px] font-mono mt-0.5 truncate max-w-full {selectedFamily ===
-        family
-          ? 'text-exo-yellow'
-          : 'text-white/40 group-hover:text-white/60'}"
-      >
-        {getFamilyName(family)}
-      </span>
-    </button>
-  {/each}
-</div>

dashboard/src/lib/components/HuggingFaceResultItem.svelte

@@ -1,127 +0,0 @@
-<script lang="ts">
-  interface HuggingFaceModel {
-    id: string;
-    author: string;
-    downloads: number;
-    likes: number;
-    last_modified: string;
-    tags: string[];
-  }
-
-  type HuggingFaceResultItemProps = {
-    model: HuggingFaceModel;
-    isAdded: boolean;
-    isAdding: boolean;
-    onAdd: () => void;
-    onSelect: () => void;
-  };
-
-  let {
-    model,
-    isAdded,
-    isAdding,
-    onAdd,
-    onSelect,
-  }: HuggingFaceResultItemProps = $props();
-
-  function formatNumber(num: number): string {
-    if (num >= 1000000) {
-      return `${(num / 1000000).toFixed(1)}M`;
-    } else if (num >= 1000) {
-      return `${(num / 1000).toFixed(1)}k`;
-    }
-    return num.toString();
-  }
-
-  // Extract model name from full ID (e.g., "mlx-community/Llama-3.2-1B" -> "Llama-3.2-1B")
-  const modelName = $derived(model.id.split("/").pop() || model.id);
-</script>
-
-<div
-  class="flex items-center justify-between gap-3 px-3 py-2.5 hover:bg-white/5 transition-colors border-b border-white/5 last:border-b-0"
->
-  <div class="flex-1 min-w-0">
-    <div class="flex items-center gap-2">
-      <span class="text-sm font-mono text-white truncate" title={model.id}
-        >{modelName}</span
-      >
-      {#if isAdded}
-        <span
-          class="px-1.5 py-0.5 text-[10px] font-mono bg-green-500/20 text-green-400 rounded"
-          >Added</span
-        >
-      {/if}
-    </div>
-    <div class="flex items-center gap-3 mt-0.5 text-xs text-white/40">
-      <span class="truncate">{model.author}</span>
-      <span
-        class="flex items-center gap-1 shrink-0"
-        title="Downloads in the last 30 days"
-      >
-        <svg
-          class="w-3 h-3"
-          fill="none"
-          stroke="currentColor"
-          viewBox="0 0 24 24"
-        >
-          <path
-            stroke-linecap="round"
-            stroke-linejoin="round"
-            stroke-width="2"
-            d="M4 16v1a3 3 0 003 3h10a3 3 0 003-3v-1m-4-4l-4 4m0 0l-4-4m4 4V4"
-          />
-        </svg>
-        {formatNumber(model.downloads)}
-      </span>
-      <span
-        class="flex items-center gap-1 shrink-0"
-        title="Community likes on Hugging Face"
-      >
-        <svg
-          class="w-3 h-3"
-          fill="none"
-          stroke="currentColor"
-          viewBox="0 0 24 24"
-        >
-          <path
-            stroke-linecap="round"
-            stroke-linejoin="round"
-            stroke-width="2"
-            d="M4.318 6.318a4.5 4.5 0 000 6.364L12 20.364l7.682-7.682a4.5 4.5 0 00-6.364-6.364L12 7.636l-1.318-1.318a4.5 4.5 0 00-6.364 0z"
-          />
-        </svg>
-        {formatNumber(model.likes)}
-      </span>
-    </div>
-  </div>
-
-  <div class="flex items-center gap-2 shrink-0">
-    {#if isAdded}
-      <button
-        type="button"
-        onclick={onSelect}
-        class="px-3 py-1.5 text-xs font-mono tracking-wider uppercase bg-exo-yellow/10 text-exo-yellow border border-exo-yellow/30 hover:bg-exo-yellow/20 transition-colors rounded cursor-pointer"
-      >
-        Select
-      </button>
-    {:else}
-      <button
-        type="button"
-        onclick={onAdd}
-        disabled={isAdding}
-        class="px-3 py-1.5 text-xs font-mono tracking-wider uppercase bg-orange-500/10 text-orange-400 border border-orange-400/30 hover:bg-orange-500/20 transition-colors rounded cursor-pointer disabled:opacity-50 disabled:cursor-not-allowed"
-      >
-        {#if isAdding}
-          <span class="flex items-center gap-1.5">
-            <span
-              class="w-3 h-3 border-2 border-orange-400 border-t-transparent rounded-full animate-spin"
-            ></span>
-            Adding...
-          </span>
-        {:else}
-          + Add
-        {/if}
-      </button>
-    {/if}
-  </div>
-</div>

dashboard/src/lib/components/ModelFilterPopover.svelte

@@ -1,182 +0,0 @@
-<script lang="ts">
-  import { fly } from "svelte/transition";
-  import { cubicOut } from "svelte/easing";
-
-  interface FilterState {
-    capabilities: string[];
-    sizeRange: { min: number; max: number } | null;
-  }
-
-  type ModelFilterPopoverProps = {
-    filters: FilterState;
-    onChange: (filters: FilterState) => void;
-    onClear: () => void;
-    onClose: () => void;
-  };
-
-  let { filters, onChange, onClear, onClose }: ModelFilterPopoverProps =
-    $props();
-
-  // Available capabilities
-  const availableCapabilities = [
-    { id: "text", label: "Text" },
-    { id: "thinking", label: "Thinking" },
-    { id: "code", label: "Code" },
-    { id: "vision", label: "Vision" },
-  ];
-
-  // Size ranges
-  const sizeRanges = [
-    { label: "< 10GB", min: 0, max: 10 },
-    { label: "10-50GB", min: 10, max: 50 },
-    { label: "50-200GB", min: 50, max: 200 },
-    { label: "> 200GB", min: 200, max: 10000 },
-  ];
-
-  function toggleCapability(cap: string) {
-    const next = filters.capabilities.includes(cap)
-      ? filters.capabilities.filter((c) => c !== cap)
-      : [...filters.capabilities, cap];
-    onChange({ ...filters, capabilities: next });
-  }
-
-  function selectSizeRange(range: { min: number; max: number } | null) {
-    // Toggle off if same range is clicked
-    if (
-      filters.sizeRange &&
-      range &&
-      filters.sizeRange.min === range.min &&
-      filters.sizeRange.max === range.max
-    ) {
-      onChange({ ...filters, sizeRange: null });
-    } else {
-      onChange({ ...filters, sizeRange: range });
-    }
-  }
-
-  function handleClickOutside(e: MouseEvent) {
-    const target = e.target as HTMLElement;
-    if (
-      !target.closest(".filter-popover") &&
-      !target.closest(".filter-toggle")
-    ) {
-      onClose();
-    }
-  }
-</script>
-
-<svelte:window onclick={handleClickOutside} />
-
-<!-- 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"
-  transition:fly={{ y: -10, duration: 200, easing: cubicOut }}
-  onclick={(e) => e.stopPropagation()}
-  role="dialog"
-  aria-label="Filter options"
->
-  <div class="p-3 space-y-4">
-    <!-- Capabilities -->
-    <div>
-      <h4 class="text-xs font-mono text-white/50 mb-2">Capabilities</h4>
-      <div class="flex flex-wrap gap-1.5">
-        {#each availableCapabilities as cap}
-          {@const isSelected = filters.capabilities.includes(cap.id)}
-          <button
-            type="button"
-            class="px-2 py-1 text-xs font-mono rounded transition-colors {isSelected
-              ? 'bg-exo-yellow/20 text-exo-yellow border border-exo-yellow/30'
-              : 'bg-white/5 text-white/60 hover:bg-white/10 border border-transparent'}"
-            onclick={() => toggleCapability(cap.id)}
-          >
-            {#if cap.id === "text"}
-              <svg
-                class="w-3.5 h-3.5 inline-block"
-                viewBox="0 0 24 24"
-                fill="none"
-                stroke="currentColor"
-                stroke-width="1.5"
-                ><path
-                  d="M21 15a2 2 0 0 1-2 2H7l-4 4V5a2 2 0 0 1 2-2h14a2 2 0 0 1 2 2z"
-                  stroke-linecap="round"
-                  stroke-linejoin="round"
-                /></svg
-              >
-            {:else if cap.id === "thinking"}
-              <svg
-                class="w-3.5 h-3.5 inline-block"
-                viewBox="0 0 24 24"
-                fill="none"
-                stroke="currentColor"
-                stroke-width="1.5"
-                ><path
-                  d="M12 2a7 7 0 0 0-7 7c0 2.38 1.19 4.47 3 5.74V17a1 1 0 0 0 1 1h6a1 1 0 0 0 1-1v-2.26c1.81-1.27 3-3.36 3-5.74a7 7 0 0 0-7-7zM9 20h6M10 22h4"
-                  stroke-linecap="round"
-                  stroke-linejoin="round"
-                /></svg
-              >
-            {:else if cap.id === "code"}
-              <svg
-                class="w-3.5 h-3.5 inline-block"
-                viewBox="0 0 24 24"
-                fill="none"
-                stroke="currentColor"
-                stroke-width="1.5"
-                ><path
-                  d="M16 18l6-6-6-6M8 6l-6 6 6 6"
-                  stroke-linecap="round"
-                  stroke-linejoin="round"
-                /></svg
-              >
-            {:else if cap.id === "vision"}
-              <svg
-                class="w-3.5 h-3.5 inline-block"
-                viewBox="0 0 24 24"
-                fill="none"
-                stroke="currentColor"
-                stroke-width="1.5"
-                ><path
-                  d="M1 12s4-8 11-8 11 8 11 8-4 8-11 8-11-8-11-8z"
-                  stroke-linecap="round"
-                  stroke-linejoin="round"
-                /><circle cx="12" cy="12" r="3" /></svg
-              >
-            {/if}
-            <span class="ml-1">{cap.label}</span>
-          </button>
-        {/each}
-      </div>
-    </div>
-
-    <!-- Size range -->
-    <div>
-      <h4 class="text-xs font-mono text-white/50 mb-2">Model Size</h4>
-      <div class="flex flex-wrap gap-1.5">
-        {#each sizeRanges as range}
-          {@const isSelected =
-            filters.sizeRange &&
-            filters.sizeRange.min === range.min &&
-            filters.sizeRange.max === range.max}
-          <button
-            type="button"
-            class="px-2 py-1 text-xs font-mono rounded transition-colors {isSelected
-              ? 'bg-exo-yellow/20 text-exo-yellow border border-exo-yellow/30'
-              : 'bg-white/5 text-white/60 hover:bg-white/10 border border-transparent'}"
-            onclick={() => selectSizeRange(range)}
-          >
-            {range.label}
-          </button>
-        {/each}
-      </div>
-    </div>
-
-    <!-- Clear button -->
-    <button
-      type="button"
-      class="w-full py-1.5 text-xs font-mono text-white/50 hover:text-white/70 hover:bg-white/5 rounded transition-colors"
-      onclick={onClear}
-    >
-      Clear all filters
-    </button>
-  </div>
-</div>

dashboard/src/lib/components/ModelPickerGroup.svelte

@@ -1,324 +0,0 @@
-<script lang="ts">
-  interface ModelInfo {
-    id: string;
-    name?: string;
-    storage_size_megabytes?: number;
-    base_model?: string;
-    quantization?: string;
-    supports_tensor?: boolean;
-    capabilities?: string[];
-    family?: string;
-    is_custom?: boolean;
-  }
-
-  interface ModelGroup {
-    id: string;
-    name: string;
-    capabilities: string[];
-    family: string;
-    variants: ModelInfo[];
-    smallestVariant: ModelInfo;
-    hasMultipleVariants: boolean;
-  }
-
-  type ModelPickerGroupProps = {
-    group: ModelGroup;
-    isExpanded: boolean;
-    isFavorite: boolean;
-    selectedModelId: string | null;
-    canModelFit: (id: string) => boolean;
-    onToggleExpand: () => void;
-    onSelectModel: (modelId: string) => void;
-    onToggleFavorite: (baseModelId: string) => void;
-    onShowInfo: (group: ModelGroup) => void;
-  };
-
-  let {
-    group,
-    isExpanded,
-    isFavorite,
-    selectedModelId,
-    canModelFit,
-    onToggleExpand,
-    onSelectModel,
-    onToggleFavorite,
-    onShowInfo,
-  }: ModelPickerGroupProps = $props();
-
-  // Format storage size
-  function formatSize(mb: number | undefined): string {
-    if (!mb) return "";
-    if (mb >= 1024) {
-      return `${(mb / 1024).toFixed(0)}GB`;
-    }
-    return `${mb}MB`;
-  }
-
-  // Check if any variant can fit
-  const anyVariantFits = $derived(
-    group.variants.some((v) => canModelFit(v.id)),
-  );
-
-  // Check if this group's model is currently selected (for single-variant groups)
-  const isMainSelected = $derived(
-    !group.hasMultipleVariants &&
-      group.variants.some((v) => v.id === selectedModelId),
-  );
-</script>
-
-<div
-  class="border-b border-white/5 last:border-b-0 {!anyVariantFits
-    ? 'opacity-50'
-    : ''}"
->
-  <!-- Main row -->
-  <div
-    class="flex items-center gap-2 px-3 py-2.5 transition-colors {anyVariantFits
-      ? 'hover:bg-white/5 cursor-pointer'
-      : 'cursor-not-allowed'} {isMainSelected
-      ? 'bg-exo-yellow/10 border-l-2 border-exo-yellow'
-      : 'border-l-2 border-transparent'}"
-    onclick={() => {
-      if (group.hasMultipleVariants) {
-        onToggleExpand();
-      } else {
-        const modelId = group.variants[0]?.id;
-        if (modelId && canModelFit(modelId)) {
-          onSelectModel(modelId);
-        }
-      }
-    }}
-    role="button"
-    tabindex="0"
-    onkeydown={(e) => {
-      if (e.key === "Enter" || e.key === " ") {
-        e.preventDefault();
-        if (group.hasMultipleVariants) {
-          onToggleExpand();
-        } else {
-          const modelId = group.variants[0]?.id;
-          if (modelId && canModelFit(modelId)) {
-            onSelectModel(modelId);
-          }
-        }
-      }
-    }}
-  >
-    <!-- Expand/collapse chevron (for groups with variants) -->
-    {#if group.hasMultipleVariants}
-      <svg
-        class="w-4 h-4 text-white/40 transition-transform duration-200 flex-shrink-0 {isExpanded
-          ? 'rotate-90'
-          : ''}"
-        viewBox="0 0 24 24"
-        fill="currentColor"
-      >
-        <path d="M8.59 16.59L13.17 12 8.59 7.41 10 6l6 6-6 6-1.41-1.41z" />
-      </svg>
-    {:else}
-      <div class="w-4 flex-shrink-0"></div>
-    {/if}
-
-    <!-- Model name -->
-    <div class="flex-1 min-w-0">
-      <div class="flex items-center gap-2">
-        <span class="font-mono text-sm text-white truncate">
-          {group.name}
-        </span>
-        <!-- Capability icons -->
-        {#each group.capabilities.filter((c) => c !== "text") as cap}
-          {#if cap === "thinking"}
-            <svg
-              class="w-3.5 h-3.5 text-white/40 flex-shrink-0"
-              viewBox="0 0 24 24"
-              fill="none"
-              stroke="currentColor"
-              stroke-width="1.5"
-              title="Supports Thinking"
-            >
-              <path
-                d="M12 2a7 7 0 0 0-7 7c0 2.38 1.19 4.47 3 5.74V17a1 1 0 0 0 1 1h6a1 1 0 0 0 1-1v-2.26c1.81-1.27 3-3.36 3-5.74a7 7 0 0 0-7-7zM9 20h6M10 22h4"
-                stroke-linecap="round"
-                stroke-linejoin="round"
-              />
-            </svg>
-          {:else if cap === "code"}
-            <svg
-              class="w-3.5 h-3.5 text-white/40 flex-shrink-0"
-              viewBox="0 0 24 24"
-              fill="none"
-              stroke="currentColor"
-              stroke-width="1.5"
-              title="Supports code generation"
-            >
-              <path
-                d="M16 18l6-6-6-6M8 6l-6 6 6 6"
-                stroke-linecap="round"
-                stroke-linejoin="round"
-              />
-            </svg>
-          {:else if cap === "vision"}
-            <svg
-              class="w-3.5 h-3.5 text-white/40 flex-shrink-0"
-              viewBox="0 0 24 24"
-              fill="none"
-              stroke="currentColor"
-              stroke-width="1.5"
-              title="Supports image input"
-            >
-              <path
-                d="M1 12s4-8 11-8 11 8 11 8-4 8-11 8-11-8-11-8z"
-                stroke-linecap="round"
-                stroke-linejoin="round"
-              />
-              <circle cx="12" cy="12" r="3" />
-            </svg>
-          {:else if cap === "image_gen"}
-            <svg
-              class="w-3.5 h-3.5 text-white/40 flex-shrink-0"
-              viewBox="0 0 24 24"
-              fill="none"
-              stroke="currentColor"
-              stroke-width="1.5"
-              title="Supports image generation"
-            >
-              <rect x="3" y="3" width="18" height="18" rx="2" ry="2" />
-              <circle cx="8.5" cy="8.5" r="1.5" />
-              <path d="M21 15l-5-5L5 21" />
-            </svg>
-          {/if}
-        {/each}
-      </div>
-    </div>
-
-    <!-- Size indicator (smallest variant) -->
-    {#if !group.hasMultipleVariants && group.smallestVariant?.storage_size_megabytes}
-      <span class="text-xs font-mono text-white/30 flex-shrink-0">
-        {formatSize(group.smallestVariant.storage_size_megabytes)}
-      </span>
-    {/if}
-
-    <!-- Variant count -->
-    {#if group.hasMultipleVariants}
-      <span class="text-xs font-mono text-white/30 flex-shrink-0">
-        {group.variants.length} variants
-      </span>
-    {/if}
-
-    <!-- Check mark if selected (single-variant) -->
-    {#if isMainSelected}
-      <svg
-        class="w-4 h-4 text-exo-yellow flex-shrink-0"
-        viewBox="0 0 24 24"
-        fill="currentColor"
-      >
-        <path d="M9 16.17L4.83 12l-1.42 1.41L9 19 21 7l-1.41-1.41L9 16.17z" />
-      </svg>
-    {/if}
-
-    <!-- Favorite star -->
-    <button
-      type="button"
-      class="p-1 rounded hover:bg-white/10 transition-colors flex-shrink-0"
-      onclick={(e) => {
-        e.stopPropagation();
-        onToggleFavorite(group.id);
-      }}
-      title={isFavorite ? "Remove from favorites" : "Add to favorites"}
-    >
-      {#if isFavorite}
-        <svg
-          class="w-4 h-4 text-amber-400"
-          viewBox="0 0 24 24"
-          fill="currentColor"
-        >
-          <path
-            d="M12 2l3.09 6.26L22 9.27l-5 4.87 1.18 6.88L12 17.77l-6.18 3.25L7 14.14 2 9.27l6.91-1.01L12 2z"
-          />
-        </svg>
-      {:else}
-        <svg
-          class="w-4 h-4 text-white/30 hover:text-white/50"
-          viewBox="0 0 24 24"
-          fill="none"
-          stroke="currentColor"
-          stroke-width="2"
-        >
-          <path
-            d="M12 2l3.09 6.26L22 9.27l-5 4.87 1.18 6.88L12 17.77l-6.18 3.25L7 14.14 2 9.27l6.91-1.01L12 2z"
-          />
-        </svg>
-      {/if}
-    </button>
-
-    <!-- Info button -->
-    <button
-      type="button"
-      class="p-1 rounded hover:bg-white/10 transition-colors flex-shrink-0"
-      onclick={(e) => {
-        e.stopPropagation();
-        onShowInfo(group);
-      }}
-      title="View model details"
-    >
-      <svg
-        class="w-4 h-4 text-white/30 hover:text-white/50"
-        viewBox="0 0 24 24"
-        fill="currentColor"
-      >
-        <path
-          d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm1 15h-2v-6h2v6zm0-8h-2V7h2v2z"
-        />
-      </svg>
-    </button>
-  </div>
-
-  <!-- Expanded variants -->
-  {#if isExpanded && group.hasMultipleVariants}
-    <div class="bg-black/20 border-t border-white/5">
-      {#each group.variants as variant}
-        {@const modelCanFit = canModelFit(variant.id)}
-        {@const isSelected = selectedModelId === variant.id}
-        <button
-          type="button"
-          class="w-full flex items-center gap-3 px-3 py-2 pl-10 hover:bg-white/5 transition-colors text-left {!modelCanFit
-            ? 'opacity-50 cursor-not-allowed'
-            : 'cursor-pointer'} {isSelected
-            ? 'bg-exo-yellow/10 border-l-2 border-exo-yellow'
-            : 'border-l-2 border-transparent'}"
-          disabled={!modelCanFit}
-          onclick={() => {
-            if (modelCanFit) {
-              onSelectModel(variant.id);
-            }
-          }}
-        >
-          <!-- Quantization badge -->
-          <span
-            class="text-xs font-mono px-1.5 py-0.5 rounded bg-white/10 text-white/70 flex-shrink-0"
-          >
-            {variant.quantization || "default"}
-          </span>
-
-          <!-- Size -->
-          <span class="text-xs font-mono text-white/40 flex-1">
-            {formatSize(variant.storage_size_megabytes)}
-          </span>
-
-          <!-- Check mark if selected -->
-          {#if isSelected}
-            <svg
-              class="w-4 h-4 text-exo-yellow"
-              viewBox="0 0 24 24"
-              fill="currentColor"
-            >
-              <path
-                d="M9 16.17L4.83 12l-1.42 1.41L9 19 21 7l-1.41-1.41L9 16.17z"
-              />
-            </svg>
-          {/if}
-        </button>
-      {/each}
-    </div>
-  {/if}
-</div>

dashboard/src/lib/components/ModelPickerModal.svelte

@@ -1,748 +0,0 @@
-<script lang="ts">
-  import { fade, fly } from "svelte/transition";
-  import { cubicOut } from "svelte/easing";
-  import FamilySidebar from "./FamilySidebar.svelte";
-  import ModelPickerGroup from "./ModelPickerGroup.svelte";
-  import ModelFilterPopover from "./ModelFilterPopover.svelte";
-  import HuggingFaceResultItem from "./HuggingFaceResultItem.svelte";
-
-  interface ModelInfo {
-    id: string;
-    name?: string;
-    storage_size_megabytes?: number;
-    base_model?: string;
-    quantization?: string;
-    supports_tensor?: boolean;
-    capabilities?: string[];
-    family?: string;
-    is_custom?: boolean;
-    tasks?: string[];
-    hugging_face_id?: string;
-  }
-
-  interface ModelGroup {
-    id: string;
-    name: string;
-    capabilities: string[];
-    family: string;
-    variants: ModelInfo[];
-    smallestVariant: ModelInfo;
-    hasMultipleVariants: boolean;
-  }
-
-  interface FilterState {
-    capabilities: string[];
-    sizeRange: { min: number; max: number } | null;
-  }
-
-  interface HuggingFaceModel {
-    id: string;
-    author: string;
-    downloads: number;
-    likes: number;
-    last_modified: string;
-    tags: string[];
-  }
-
-  type ModelPickerModalProps = {
-    isOpen: boolean;
-    models: ModelInfo[];
-    selectedModelId: string | null;
-    favorites: Set<string>;
-    existingModelIds: Set<string>;
-    canModelFit: (modelId: string) => boolean;
-    onSelect: (modelId: string) => void;
-    onClose: () => void;
-    onToggleFavorite: (baseModelId: string) => void;
-    onAddModel: (modelId: string) => Promise<void>;
-    onDeleteModel: (modelId: string) => Promise<void>;
-    totalMemoryGB: number;
-    usedMemoryGB: number;
-  };
-
-  let {
-    isOpen,
-    models,
-    selectedModelId,
-    favorites,
-    existingModelIds,
-    canModelFit,
-    onSelect,
-    onClose,
-    onToggleFavorite,
-    onAddModel,
-    onDeleteModel,
-    totalMemoryGB,
-    usedMemoryGB,
-  }: ModelPickerModalProps = $props();
-
-  // Local state
-  let searchQuery = $state("");
-  let selectedFamily = $state<string | null>(null);
-  let expandedGroups = $state<Set<string>>(new Set());
-  let showFilters = $state(false);
-  let filters = $state<FilterState>({ capabilities: [], sizeRange: null });
-  let infoGroup = $state<ModelGroup | null>(null);
-
-  // HuggingFace Hub state
-  let hfSearchQuery = $state("");
-  let hfSearchResults = $state<HuggingFaceModel[]>([]);
-  let hfTrendingModels = $state<HuggingFaceModel[]>([]);
-  let hfIsSearching = $state(false);
-  let hfIsLoadingTrending = $state(false);
-  let addingModelId = $state<string | null>(null);
-  let hfSearchDebounceTimer: ReturnType<typeof setTimeout> | null = null;
-  let manualModelId = $state("");
-  let addModelError = $state<string | null>(null);
-
-  // Reset state when modal opens
-  $effect(() => {
-    if (isOpen) {
-      searchQuery = "";
-      selectedFamily = null;
-      expandedGroups = new Set();
-      showFilters = false;
-      hfSearchQuery = "";
-      hfSearchResults = [];
-      manualModelId = "";
-      addModelError = null;
-    }
-  });
-
-  // Fetch trending models when HuggingFace is selected
-  $effect(() => {
-    if (
-      selectedFamily === "huggingface" &&
-      hfTrendingModels.length === 0 &&
-      !hfIsLoadingTrending
-    ) {
-      fetchTrendingModels();
-    }
-  });
-
-  async function fetchTrendingModels() {
-    hfIsLoadingTrending = true;
-    try {
-      const response = await fetch("/models/search?query=&limit=20");
-      if (response.ok) {
-        hfTrendingModels = await response.json();
-      }
-    } catch (error) {
-      console.error("Failed to fetch trending models:", error);
-    } finally {
-      hfIsLoadingTrending = false;
-    }
-  }
-
-  async function searchHuggingFace(query: string) {
-    if (query.length < 2) {
-      hfSearchResults = [];
-      return;
-    }
-
-    hfIsSearching = true;
-    try {
-      const response = await fetch(
-        `/models/search?query=${encodeURIComponent(query)}&limit=20`,
-      );
-      if (response.ok) {
-        hfSearchResults = await response.json();
-      } else {
-        hfSearchResults = [];
-      }
-    } catch (error) {
-      console.error("Failed to search models:", error);
-      hfSearchResults = [];
-    } finally {
-      hfIsSearching = false;
-    }
-  }
-
-  function handleHfSearchInput(query: string) {
-    hfSearchQuery = query;
-    addModelError = null;
-
-    if (hfSearchDebounceTimer) {
-      clearTimeout(hfSearchDebounceTimer);
-    }
-
-    if (query.length >= 2) {
-      hfSearchDebounceTimer = setTimeout(() => {
-        searchHuggingFace(query);
-      }, 300);
-    } else {
-      hfSearchResults = [];
-    }
-  }
-
-  async function handleAddModel(modelId: string) {
-    addingModelId = modelId;
-    addModelError = null;
-    try {
-      await onAddModel(modelId);
-    } catch (error) {
-      addModelError =
-        error instanceof Error ? error.message : "Failed to add model";
-    } finally {
-      addingModelId = null;
-    }
-  }
-
-  async function handleAddManualModel() {
-    if (!manualModelId.trim()) return;
-    await handleAddModel(manualModelId.trim());
-    if (!addModelError) {
-      manualModelId = "";
-    }
-  }
-
-  function handleSelectHfModel(modelId: string) {
-    onSelect(modelId);
-    onClose();
-  }
-
-  // Models to display in HuggingFace view
-  const hfDisplayModels = $derived.by((): HuggingFaceModel[] => {
-    if (hfSearchQuery.length >= 2) {
-      return hfSearchResults;
-    }
-    return hfTrendingModels;
-  });
-
-  // Group models by base_model
-  const groupedModels = $derived.by((): ModelGroup[] => {
-    const groups = new Map<string, ModelGroup>();
-
-    for (const model of models) {
-      const groupId = model.base_model || model.id;
-      const groupName = model.base_model || model.name || model.id;
-
-      if (!groups.has(groupId)) {
-        groups.set(groupId, {
-          id: groupId,
-          name: groupName,
-          capabilities: model.capabilities || ["text"],
-          family: model.family || "",
-          variants: [],
-          smallestVariant: model,
-          hasMultipleVariants: false,
-        });
-      }
-
-      const group = groups.get(groupId)!;
-      group.variants.push(model);
-
-      // Track smallest variant
-      if (
-        (model.storage_size_megabytes || 0) <
-        (group.smallestVariant.storage_size_megabytes || Infinity)
-      ) {
-        group.smallestVariant = model;
-      }
-
-      // Update capabilities if not set
-      if (
-        group.capabilities.length <= 1 &&
-        model.capabilities &&
-        model.capabilities.length > 1
-      ) {
-        group.capabilities = model.capabilities;
-      }
-      if (!group.family && model.family) {
-        group.family = model.family;
-      }
-    }
-
-    // Sort variants within each group by size
-    for (const group of groups.values()) {
-      group.variants.sort(
-        (a, b) =>
-          (a.storage_size_megabytes || 0) - (b.storage_size_megabytes || 0),
-      );
-      group.hasMultipleVariants = group.variants.length > 1;
-    }
-
-    // Convert to array and sort by smallest variant size (biggest first)
-    return Array.from(groups.values()).sort((a, b) => {
-      return (
-        (b.smallestVariant.storage_size_megabytes || 0) -
-        (a.smallestVariant.storage_size_megabytes || 0)
-      );
-    });
-  });
-
-  // Get unique families
-  const uniqueFamilies = $derived.by((): string[] => {
-    const families = new Set<string>();
-    for (const group of groupedModels) {
-      if (group.family) {
-        families.add(group.family);
-      }
-    }
-    const familyOrder = [
-      "kimi",
-      "qwen",
-      "glm",
-      "minimax",
-      "deepseek",
-      "gpt-oss",
-      "llama",
-    ];
-    return Array.from(families).sort((a, b) => {
-      const aIdx = familyOrder.indexOf(a);
-      const bIdx = familyOrder.indexOf(b);
-      if (aIdx === -1 && bIdx === -1) return a.localeCompare(b);
-      if (aIdx === -1) return 1;
-      if (bIdx === -1) return -1;
-      return aIdx - bIdx;
-    });
-  });
-
-  // Filter models based on search, family, and filters
-  const filteredGroups = $derived.by((): ModelGroup[] => {
-    let result: ModelGroup[] = [...groupedModels];
-
-    // Filter by family
-    if (selectedFamily === "favorites") {
-      result = result.filter((g) => favorites.has(g.id));
-    } else if (selectedFamily && selectedFamily !== "huggingface") {
-      result = result.filter((g) => g.family === selectedFamily);
-    }
-
-    // Filter by search query
-    if (searchQuery.trim()) {
-      const query = searchQuery.toLowerCase().trim();
-      result = result.filter(
-        (g) =>
-          g.name.toLowerCase().includes(query) ||
-          g.variants.some(
-            (v) =>
-              v.id.toLowerCase().includes(query) ||
-              (v.name || "").toLowerCase().includes(query),
-          ),
-      );
-    }
-
-    // Filter by capabilities
-    if (filters.capabilities.length > 0) {
-      result = result.filter((g) =>
-        filters.capabilities.every((cap) => g.capabilities.includes(cap)),
-      );
-    }
-
-    // Filter by size range
-    if (filters.sizeRange) {
-      const { min, max } = filters.sizeRange;
-      result = result.filter((g) => {
-        const sizeGB = (g.smallestVariant.storage_size_megabytes || 0) / 1024;
-        return sizeGB >= min && sizeGB <= max;
-      });
-    }
-
-    // Sort: models that fit first, then by size (largest first)
-    result.sort((a, b) => {
-      const aFits = a.variants.some((v) => canModelFit(v.id));
-      const bFits = b.variants.some((v) => canModelFit(v.id));
-
-      if (aFits && !bFits) return -1;
-      if (!aFits && bFits) return 1;
-
-      return (
-        (b.smallestVariant.storage_size_megabytes || 0) -
-        (a.smallestVariant.storage_size_megabytes || 0)
-      );
-    });
-
-    return result;
-  });
-
-  // Check if any favorites exist
-  const hasFavorites = $derived(favorites.size > 0);
-
-  function toggleGroupExpanded(groupId: string) {
-    const next = new Set(expandedGroups);
-    if (next.has(groupId)) {
-      next.delete(groupId);
-    } else {
-      next.add(groupId);
-    }
-    expandedGroups = next;
-  }
-
-  function handleSelect(modelId: string) {
-    onSelect(modelId);
-    onClose();
-  }
-
-  function handleKeydown(e: KeyboardEvent) {
-    if (e.key === "Escape") {
-      onClose();
-    }
-  }
-
-  function handleFiltersChange(newFilters: FilterState) {
-    filters = newFilters;
-  }
-
-  function clearFilters() {
-    filters = { capabilities: [], sizeRange: null };
-  }
-
-  const hasActiveFilters = $derived(
-    filters.capabilities.length > 0 || filters.sizeRange !== null,
-  );
-</script>
-
-<svelte:window onkeydown={handleKeydown} />
-
-{#if isOpen}
-  <!-- Backdrop -->
-  <div
-    class="fixed inset-0 z-50 bg-black/80 backdrop-blur-sm"
-    transition:fade={{ duration: 200 }}
-    onclick={onClose}
-    role="presentation"
-  ></div>
-
-  <!-- Modal -->
-  <div
-    class="fixed z-50 top-1/2 left-1/2 -translate-x-1/2 -translate-y-1/2 w-[min(90vw,600px)] h-[min(80vh,700px)] bg-exo-dark-gray border border-exo-yellow/10 rounded-lg shadow-2xl overflow-hidden flex flex-col"
-    transition:fly={{ y: 20, duration: 300, easing: cubicOut }}
-    role="dialog"
-    aria-modal="true"
-    aria-label="Select a model"
-  >
-    <!-- Header with search -->
-    <div
-      class="flex items-center gap-2 p-3 border-b border-exo-yellow/10 bg-exo-medium-gray/30"
-    >
-      {#if selectedFamily === "huggingface"}
-        <!-- HuggingFace search -->
-        <svg
-          class="w-5 h-5 text-orange-400/60 flex-shrink-0"
-          viewBox="0 0 24 24"
-          fill="none"
-          stroke="currentColor"
-          stroke-width="2"
-        >
-          <circle cx="11" cy="11" r="8" />
-          <path d="M21 21l-4.35-4.35" />
-        </svg>
-        <input
-          type="search"
-          class="flex-1 bg-transparent border-none outline-none text-sm font-mono text-white placeholder-white/40"
-          placeholder="Search mlx-community models..."
-          value={hfSearchQuery}
-          oninput={(e) => handleHfSearchInput(e.currentTarget.value)}
-        />
-        {#if hfIsSearching}
-          <div class="flex-shrink-0">
-            <span
-              class="w-4 h-4 border-2 border-orange-400 border-t-transparent rounded-full animate-spin block"
-            ></span>
-          </div>
-        {/if}
-      {:else}
-        <!-- Normal model search -->
-        <svg
-          class="w-5 h-5 text-white/40 flex-shrink-0"
-          viewBox="0 0 24 24"
-          fill="none"
-          stroke="currentColor"
-          stroke-width="2"
-        >
-          <circle cx="11" cy="11" r="8" />
-          <path d="M21 21l-4.35-4.35" />
-        </svg>
-        <input
-          type="search"
-          class="flex-1 bg-transparent border-none outline-none text-sm font-mono text-white placeholder-white/40"
-          placeholder="Search models..."
-          bind:value={searchQuery}
-        />
-        <!-- Cluster memory -->
-        <span
-          class="text-xs font-mono flex-shrink-0"
-          title="Cluster memory usage"
-          ><span class="text-exo-yellow">{Math.round(usedMemoryGB)}GB</span
-          ><span class="text-white/40">/{Math.round(totalMemoryGB)}GB</span
-          ></span
-        >
-        <!-- Filter button -->
-        <div class="relative filter-toggle">
-          <button
-            type="button"
-            class="p-1.5 rounded hover:bg-white/10 transition-colors {hasActiveFilters
-              ? 'text-exo-yellow'
-              : 'text-white/50'}"
-            onclick={() => (showFilters = !showFilters)}
-            title="Filter by capability or size"
-          >
-            <svg class="w-5 h-5" viewBox="0 0 24 24" fill="currentColor">
-              <path d="M10 18h4v-2h-4v2zM3 6v2h18V6H3zm3 7h12v-2H6v2z" />
-            </svg>
-          </button>
-          {#if showFilters}
-            <ModelFilterPopover
-              {filters}
-              onChange={handleFiltersChange}
-              onClear={clearFilters}
-              onClose={() => (showFilters = false)}
-            />
-          {/if}
-        </div>
-      {/if}
-      <!-- Close button -->
-      <button
-        type="button"
-        class="p-1.5 rounded hover:bg-white/10 transition-colors text-white/50 hover:text-white/70"
-        onclick={onClose}
-        title="Close model picker"
-      >
-        <svg class="w-5 h-5" viewBox="0 0 24 24" fill="currentColor">
-          <path
-            d="M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41z"
-          />
-        </svg>
-      </button>
-    </div>
-
-    <!-- Body -->
-    <div class="flex flex-1 overflow-hidden">
-      <!-- Family sidebar -->
-      <FamilySidebar
-        families={uniqueFamilies}
-        {selectedFamily}
-        {hasFavorites}
-        onSelect={(family) => (selectedFamily = family)}
-      />
-
-      <!-- Model list -->
-      <div class="flex-1 overflow-y-auto flex flex-col">
-        {#if selectedFamily === "huggingface"}
-          <!-- HuggingFace Hub view -->
-          <div class="flex-1 flex flex-col min-h-0">
-            <!-- Section header -->
-            <div
-              class="sticky top-0 z-10 px-3 py-2 bg-exo-dark-gray/95 border-b border-exo-yellow/10"
-            >
-              <span class="text-xs font-mono text-white/40">
-                {#if hfSearchQuery.length >= 2}
-                  Search results for "{hfSearchQuery}"
-                {:else}
-                  Trending on mlx-community
-                {/if}
-              </span>
-            </div>
-
-            <!-- Results list -->
-            <div class="flex-1 overflow-y-auto">
-              {#if hfIsLoadingTrending && hfTrendingModels.length === 0}
-                <div
-                  class="flex items-center justify-center py-12 text-white/40"
-                >
-                  <span
-                    class="w-5 h-5 border-2 border-orange-400 border-t-transparent rounded-full animate-spin mr-2"
-                  ></span>
-                  <span class="font-mono text-sm"
-                    >Loading trending models...</span
-                  >
-                </div>
-              {:else if hfDisplayModels.length === 0}
-                <div
-                  class="flex flex-col items-center justify-center py-12 text-white/40"
-                >
-                  <svg
-                    class="w-10 h-10 mb-2"
-                    viewBox="0 0 24 24"
-                    fill="currentColor"
-                  >
-                    <path
-                      d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm-2 13.5c-.83 0-1.5-.67-1.5-1.5s.67-1.5 1.5-1.5 1.5.67 1.5 1.5-.67 1.5-1.5 1.5zm4 0c-.83 0-1.5-.67-1.5-1.5s.67-1.5 1.5-1.5 1.5.67 1.5 1.5-.67 1.5-1.5 1.5zm2-4.5H8c0-2.21 1.79-4 4-4s4 1.79 4 4z"
-                    />
-                  </svg>
-                  <p class="font-mono text-sm">No models found</p>
-                  {#if hfSearchQuery}
-                    <p class="font-mono text-xs mt-1">
-                      Try a different search term
-                    </p>
-                  {/if}
-                </div>
-              {:else}
-                {#each hfDisplayModels as model}
-                  <HuggingFaceResultItem
-                    {model}
-                    isAdded={existingModelIds.has(model.id)}
-                    isAdding={addingModelId === model.id}
-                    onAdd={() => handleAddModel(model.id)}
-                    onSelect={() => handleSelectHfModel(model.id)}
-                  />
-                {/each}
-              {/if}
-            </div>
-
-            <!-- Manual input footer -->
-            <div
-              class="sticky bottom-0 border-t border-exo-yellow/10 bg-exo-dark-gray p-3"
-            >
-              {#if addModelError}
-                <div
-                  class="bg-red-500/10 border border-red-500/30 rounded px-3 py-2 mb-2"
-                >
-                  <p class="text-red-400 text-xs font-mono break-words">
-                    {addModelError}
-                  </p>
-                </div>
-              {/if}
-              <div class="flex gap-2">
-                <input
-                  type="text"
-                  class="flex-1 bg-exo-black/60 border border-exo-yellow/30 rounded px-3 py-1.5 text-xs font-mono text-white placeholder-white/30 focus:outline-none focus:border-exo-yellow/50"
-                  placeholder="Or paste model ID directly..."
-                  bind:value={manualModelId}
-                  onkeydown={(e) => {
-                    if (e.key === "Enter") handleAddManualModel();
-                  }}
-                />
-                <button
-                  type="button"
-                  onclick={handleAddManualModel}
-                  disabled={!manualModelId.trim() || addingModelId !== null}
-                  class="px-3 py-1.5 text-xs font-mono tracking-wider uppercase bg-orange-500/10 text-orange-400 border border-orange-400/30 hover:bg-orange-500/20 transition-colors rounded disabled:opacity-50 disabled:cursor-not-allowed"
-                >
-                  Add
-                </button>
-              </div>
-            </div>
-          </div>
-        {:else if filteredGroups.length === 0}
-          <div
-            class="flex flex-col items-center justify-center h-full text-white/40 p-8"
-          >
-            <svg class="w-12 h-12 mb-3" viewBox="0 0 24 24" fill="currentColor">
-              <path
-                d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm-2 15l-5-5 1.41-1.41L10 14.17l7.59-7.59L19 8l-9 9z"
-              />
-            </svg>
-            <p class="font-mono text-sm">No models found</p>
-            {#if hasActiveFilters || searchQuery}
-              <button
-                type="button"
-                class="mt-2 text-xs text-exo-yellow hover:underline"
-                onclick={() => {
-                  searchQuery = "";
-                  clearFilters();
-                }}
-              >
-                Clear filters
-              </button>
-            {/if}
-          </div>
-        {:else}
-          {#each filteredGroups as group}
-            <ModelPickerGroup
-              {group}
-              isExpanded={expandedGroups.has(group.id)}
-              isFavorite={favorites.has(group.id)}
-              {selectedModelId}
-              {canModelFit}
-              onToggleExpand={() => toggleGroupExpanded(group.id)}
-              onSelectModel={handleSelect}
-              {onToggleFavorite}
-              onShowInfo={(g) => (infoGroup = g)}
-            />
-          {/each}
-        {/if}
-      </div>
-    </div>
-
-    <!-- Footer with active filters indicator -->
-    {#if hasActiveFilters}
-      <div
-        class="flex items-center gap-2 px-3 py-2 border-t border-exo-yellow/10 bg-exo-medium-gray/20 text-xs font-mono text-white/50"
-      >
-        <span>Filters:</span>
-        {#each filters.capabilities as cap}
-          <span class="px-1.5 py-0.5 bg-exo-yellow/20 text-exo-yellow rounded"
-            >{cap}</span
-          >
-        {/each}
-        {#if filters.sizeRange}
-          <span class="px-1.5 py-0.5 bg-exo-yellow/20 text-exo-yellow rounded">
-            {filters.sizeRange.min}GB - {filters.sizeRange.max}GB
-          </span>
-        {/if}
-        <button
-          type="button"
-          class="ml-auto text-white/40 hover:text-white/60"
-          onclick={clearFilters}
-        >
-          Clear all
-        </button>
-      </div>
-    {/if}
-  </div>
-
-  <!-- Info modal -->
-  {#if infoGroup}
-    <div
-      class="fixed inset-0 z-[60] bg-black/60"
-      transition:fade={{ duration: 150 }}
-      onclick={() => (infoGroup = null)}
-      role="presentation"
-    ></div>
-    <div
-      class="fixed z-[60] top-1/2 left-1/2 -translate-x-1/2 -translate-y-1/2 w-[min(80vw,400px)] bg-exo-dark-gray border border-exo-yellow/10 rounded-lg shadow-2xl p-4"
-      transition:fly={{ y: 10, duration: 200, easing: cubicOut }}
-      role="dialog"
-      aria-modal="true"
-    >
-      <div class="flex items-start justify-between mb-3">
-        <h3 class="font-mono text-lg text-white">{infoGroup.name}</h3>
-        <button
-          type="button"
-          class="p-1 rounded hover:bg-white/10 transition-colors text-white/50"
-          onclick={() => (infoGroup = null)}
-          title="Close model details"
-          aria-label="Close info dialog"
-        >
-          <svg class="w-4 h-4" viewBox="0 0 24 24" fill="currentColor">
-            <path
-              d="M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41z"
-            />
-          </svg>
-        </button>
-      </div>
-      <div class="space-y-2 text-xs font-mono">
-        <div class="flex items-center gap-2">
-          <span class="text-white/40">Family:</span>
-          <span class="text-white/70">{infoGroup.family || "Unknown"}</span>
-        </div>
-        <div class="flex items-center gap-2">
-          <span class="text-white/40">Capabilities:</span>
-          <span class="text-white/70">{infoGroup.capabilities.join(", ")}</span>
-        </div>
-        <div class="flex items-center gap-2">
-          <span class="text-white/40">Variants:</span>
-          <span class="text-white/70">{infoGroup.variants.length}</span>
-        </div>
-        {#if infoGroup.variants.length > 0}
-          <div class="mt-3 pt-3 border-t border-exo-yellow/10">
-            <span class="text-white/40">Available quantizations:</span>
-            <div class="flex flex-wrap gap-1 mt-1">
-              {#each infoGroup.variants as variant}
-                <span
-                  class="px-1.5 py-0.5 bg-white/10 text-white/60 rounded text-[10px]"
-                >
-                  {variant.quantization || "default"} ({Math.round(
-                    (variant.storage_size_megabytes || 0) / 1024,
-                  )}GB)
-                </span>
-              {/each}
-            </div>
-          </div>
-        {/if}
-      </div>
-    </div>
-  {/if}
-{/if}

dashboard/src/lib/components/index.ts

@@ -6,9 +6,3 @@ export { default as ChatSidebar } from "./ChatSidebar.svelte";
 export { default as ModelCard } from "./ModelCard.svelte";
 export { default as MarkdownContent } from "./MarkdownContent.svelte";
 export { default as ImageParamsPanel } from "./ImageParamsPanel.svelte";
-export { default as FamilyLogos } from "./FamilyLogos.svelte";
-export { default as FamilySidebar } from "./FamilySidebar.svelte";
-export { default as HuggingFaceResultItem } from "./HuggingFaceResultItem.svelte";
-export { default as ModelFilterPopover } from "./ModelFilterPopover.svelte";
-export { default as ModelPickerGroup } from "./ModelPickerGroup.svelte";
-export { default as ModelPickerModal } from "./ModelPickerModal.svelte";

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

@@ -178,36 +178,6 @@ interface ImageApiResponse {
   data: Array<{ b64_json?: string; url?: string }>;
 }
 
-// Trace API response types
-export interface TraceCategoryStats {
-  totalUs: number;
-  count: number;
-  minUs: number;
-  maxUs: number;
-  avgUs: number;
-}
-
-export interface TraceRankStats {
-  byCategory: Record<string, TraceCategoryStats>;
-}
-
-export interface TraceStatsResponse {
-  taskId: string;
-  totalWallTimeUs: number;
-  byCategory: Record<string, TraceCategoryStats>;
-  byRank: Record<number, TraceRankStats>;
-}
-
-export interface TraceListItem {
-  taskId: string;
-  createdAt: string;
-  fileSize: number;
-}
-
-export interface TraceListResponse {
-  traces: TraceListItem[];
-}
-
 interface RawStateResponse {
   topology?: RawTopology;
   instances?: Record<
@@ -2585,49 +2555,6 @@ class AppStore {
       throw error;
     }
   }
-
-  /**
-   * List all available traces
-   */
-  async listTraces(): Promise<TraceListResponse> {
-    const response = await fetch("/v1/traces");
-    if (!response.ok) {
-      throw new Error(`Failed to list traces: ${response.status}`);
-    }
-    return (await response.json()) as TraceListResponse;
-  }
-
-  /**
-   * Check if a trace exists for a given task ID
-   */
-  async checkTraceExists(taskId: string): Promise<boolean> {
-    try {
-      const response = await fetch(`/v1/traces/${encodeURIComponent(taskId)}`);
-      return response.ok;
-    } catch {
-      return false;
-    }
-  }
-
-  /**
-   * Get computed statistics for a task's trace
-   */
-  async fetchTraceStats(taskId: string): Promise<TraceStatsResponse> {
-    const response = await fetch(
-      `/v1/traces/${encodeURIComponent(taskId)}/stats`,
-    );
-    if (!response.ok) {
-      throw new Error(`Failed to fetch trace stats: ${response.status}`);
-    }
-    return (await response.json()) as TraceStatsResponse;
-  }
-
-  /**
-   * Get the URL for the raw trace file (for Perfetto)
-   */
-  getTraceRawUrl(taskId: string): string {
-    return `/v1/traces/${encodeURIComponent(taskId)}/raw`;
-  }
 }
 
 export const appStore = new AppStore();
@@ -2739,12 +2666,3 @@ export const startDownload = (nodeId: string, shardMetadata: object) =>
   appStore.startDownload(nodeId, shardMetadata);
 export const deleteDownload = (nodeId: string, modelId: string) =>
   appStore.deleteDownload(nodeId, modelId);
-
-// Trace actions
-export const listTraces = () => appStore.listTraces();
-export const checkTraceExists = (taskId: string) =>
-  appStore.checkTraceExists(taskId);
-export const fetchTraceStats = (taskId: string) =>
-  appStore.fetchTraceStats(taskId);
-export const getTraceRawUrl = (taskId: string) =>
-  appStore.getTraceRawUrl(taskId);

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

@@ -1,97 +0,0 @@
-/**
- * FavoritesStore - Manages favorite models with localStorage persistence
- */
-
-import { browser } from "$app/environment";
-
-const FAVORITES_KEY = "exo-favorite-models";
-
-class FavoritesStore {
-  favorites = $state<Set<string>>(new Set());
-
-  constructor() {
-    if (browser) {
-      this.loadFromStorage();
-    }
-  }
-
-  private loadFromStorage() {
-    try {
-      const stored = localStorage.getItem(FAVORITES_KEY);
-      if (stored) {
-        const parsed = JSON.parse(stored) as string[];
-        this.favorites = new Set(parsed);
-      }
-    } catch (error) {
-      console.error("Failed to load favorites:", error);
-    }
-  }
-
-  private saveToStorage() {
-    try {
-      const array = Array.from(this.favorites);
-      localStorage.setItem(FAVORITES_KEY, JSON.stringify(array));
-    } catch (error) {
-      console.error("Failed to save favorites:", error);
-    }
-  }
-
-  add(baseModelId: string) {
-    const next = new Set(this.favorites);
-    next.add(baseModelId);
-    this.favorites = next;
-    this.saveToStorage();
-  }
-
-  remove(baseModelId: string) {
-    const next = new Set(this.favorites);
-    next.delete(baseModelId);
-    this.favorites = next;
-    this.saveToStorage();
-  }
-
-  toggle(baseModelId: string) {
-    if (this.favorites.has(baseModelId)) {
-      this.remove(baseModelId);
-    } else {
-      this.add(baseModelId);
-    }
-  }
-
-  isFavorite(baseModelId: string): boolean {
-    return this.favorites.has(baseModelId);
-  }
-
-  getAll(): string[] {
-    return Array.from(this.favorites);
-  }
-
-  getSet(): Set<string> {
-    return new Set(this.favorites);
-  }
-
-  hasAny(): boolean {
-    return this.favorites.size > 0;
-  }
-
-  clearAll() {
-    this.favorites = new Set();
-    this.saveToStorage();
-  }
-}
-
-export const favoritesStore = new FavoritesStore();
-
-export const favorites = () => favoritesStore.favorites;
-export const hasFavorites = () => favoritesStore.hasAny();
-export const isFavorite = (baseModelId: string) =>
-  favoritesStore.isFavorite(baseModelId);
-export const toggleFavorite = (baseModelId: string) =>
-  favoritesStore.toggle(baseModelId);
-export const addFavorite = (baseModelId: string) =>
-  favoritesStore.add(baseModelId);
-export const removeFavorite = (baseModelId: string) =>
-  favoritesStore.remove(baseModelId);
-export const getFavorites = () => favoritesStore.getAll();
-export const getFavoritesSet = () => favoritesStore.getSet();
-export const clearFavorites = () => favoritesStore.clearAll();

dashboard/src/routes/+page.svelte

@@ -5,13 +5,7 @@
     ChatMessages,
     ChatSidebar,
     ModelCard,
-    ModelPickerModal,
   } from "$lib/components";
-  import {
-    favorites,
-    toggleFavorite,
-    getFavoritesSet,
-  } from "$lib/stores/favorites.svelte";
   import {
     hasStartedChat,
     isTopologyMinimized,
@@ -106,11 +100,6 @@
       storage_size_megabytes?: number;
       tasks?: string[];
       hugging_face_id?: string;
-      is_custom?: boolean;
-      family?: string;
-      quantization?: string;
-      base_model?: string;
-      capabilities?: string[];
     }>
   >([]);
 
@@ -222,11 +211,9 @@
   let launchingModelId = $state<string | null>(null);
   let instanceDownloadExpandedNodes = $state<Set<string>>(new Set());
 
-  // Model picker modal state
-  let isModelPickerOpen = $state(false);
-
-  // Favorites state (reactive)
-  const favoritesSet = $derived(getFavoritesSet());
+  // Custom dropdown state
+  let isModelDropdownOpen = $state(false);
+  let modelDropdownSearch = $state("");
 
   // Slider dragging state
   let isDraggingSlider = $state(false);
@@ -543,47 +530,6 @@
     }
   }
 
-  async function addModelFromPicker(modelId: string) {
-    const response = await fetch("/models/add", {
-      method: "POST",
-      headers: { "Content-Type": "application/json" },
-      body: JSON.stringify({ model_id: modelId }),
-    });
-
-    if (!response.ok) {
-      let message = `Failed to add model (${response.status}: ${response.statusText})`;
-      try {
-        const err = await response.json();
-        if (err.detail) message = err.detail;
-      } catch {
-        // use default message
-      }
-      throw new Error(message);
-    }
-
-    await fetchModels();
-  }
-
-  async function deleteCustomModel(modelId: string) {
-    try {
-      const response = await fetch(
-        `/models/custom/${encodeURIComponent(modelId)}`,
-        { method: "DELETE" },
-      );
-      if (response.ok) {
-        await fetchModels();
-      }
-    } catch {
-      console.error("Failed to delete custom model");
-    }
-  }
-
-  function handleModelPickerSelect(modelId: string) {
-    selectPreviewModel(modelId);
-    saveLaunchDefaults();
-    isModelPickerOpen = false;
-  }
-
   async function launchInstance(
     modelId: string,
     specificPreview?: PlacementPreview | null,
@@ -2414,12 +2360,14 @@
               >
             </div>
 
-            <!-- Model Picker Button -->
-            <div class="flex-shrink-0 mb-3">
+            <!-- Model Dropdown (Custom) -->
+            <div class="flex-shrink-0 mb-3 relative">
               <button
                 type="button"
-                onclick={() => (isModelPickerOpen = true)}
-                class="w-full bg-exo-medium-gray/50 border border-exo-yellow/30 rounded pl-3 pr-8 py-2.5 text-sm font-mono text-left tracking-wide cursor-pointer transition-all duration-200 hover:border-exo-yellow/50 focus:outline-none focus:border-exo-yellow/70 relative"
+                onclick={() => (isModelDropdownOpen = !isModelDropdownOpen)}
+                class="w-full bg-exo-medium-gray/50 border border-exo-yellow/30 rounded pl-3 pr-8 py-2.5 text-sm font-mono text-left tracking-wide cursor-pointer transition-all duration-200 hover:border-exo-yellow/50 focus:outline-none focus:border-exo-yellow/70 {isModelDropdownOpen
+                  ? 'border-exo-yellow/70'
+                  : ''}"
               >
                 {#if selectedModelId}
                   {@const foundModel = models.find(
@@ -2427,12 +2375,54 @@
                   )}
                   {#if foundModel}
                     {@const sizeGB = getModelSizeGB(foundModel)}
+                    {@const isImageModel = modelSupportsImageGeneration(
+                      foundModel.id,
+                    )}
+                    {@const isImageEditModel = modelSupportsImageEditing(
+                      foundModel.id,
+                    )}
                     <span
                       class="flex items-center justify-between gap-2 w-full pr-4"
                     >
                       <span
                         class="flex items-center gap-2 text-exo-light-gray truncate"
                       >
+                        {#if isImageModel}
+                          <svg
+                            class="w-4 h-4 flex-shrink-0 text-exo-yellow"
+                            fill="none"
+                            viewBox="0 0 24 24"
+                            stroke="currentColor"
+                            stroke-width="2"
+                          >
+                            <rect
+                              x="3"
+                              y="3"
+                              width="18"
+                              height="18"
+                              rx="2"
+                              ry="2"
+                            />
+                            <circle cx="8.5" cy="8.5" r="1.5" />
+                            <polyline points="21 15 16 10 5 21" />
+                          </svg>
+                        {/if}
+                        {#if isImageEditModel}
+                          <svg
+                            class="w-4 h-4 flex-shrink-0 text-exo-yellow"
+                            fill="none"
+                            viewBox="0 0 24 24"
+                            stroke="currentColor"
+                            stroke-width="2"
+                          >
+                            <path
+                              d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"
+                            />
+                            <path
+                              d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"
+                            />
+                          </svg>
+                        {/if}
                         <span class="truncate"
                           >{foundModel.name || foundModel.id}</span
                         >
@@ -2449,24 +2439,142 @@
                 {:else}
                   <span class="text-white/50">— SELECT MODEL —</span>
                 {/if}
-                <div
-                  class="absolute right-3 top-1/2 -translate-y-1/2 pointer-events-none"
-                >
-                  <svg
-                    class="w-4 h-4 text-exo-yellow/60"
-                    fill="none"
-                    viewBox="0 0 24 24"
-                    stroke="currentColor"
-                  >
-                    <path
-                      stroke-linecap="round"
-                      stroke-linejoin="round"
-                      stroke-width="2"
-                      d="M19 9l-7 7-7-7"
-                    />
-                  </svg>
-                </div>
               </button>
+              <div
+                class="absolute right-3 top-1/2 -translate-y-1/2 pointer-events-none transition-transform duration-200 {isModelDropdownOpen
+                  ? 'rotate-180'
+                  : ''}"
+              >
+                <svg
+                  class="w-4 h-4 text-exo-yellow/60"
+                  fill="none"
+                  viewBox="0 0 24 24"
+                  stroke="currentColor"
+                >
+                  <path
+                    stroke-linecap="round"
+                    stroke-linejoin="round"
+                    stroke-width="2"
+                    d="M19 9l-7 7-7-7"
+                  />
+                </svg>
+              </div>
+
+              {#if isModelDropdownOpen}
+                <!-- Backdrop to close dropdown -->
+                <button
+                  type="button"
+                  class="fixed inset-0 z-40 cursor-default"
+                  onclick={() => (isModelDropdownOpen = false)}
+                  aria-label="Close dropdown"
+                ></button>
+
+                <!-- Dropdown Panel -->
+                <div
+                  class="absolute top-full left-0 right-0 mt-1 bg-exo-dark-gray border border-exo-yellow/30 rounded shadow-lg shadow-black/50 z-50 max-h-64 overflow-y-auto"
+                >
+                  <!-- Search within dropdown -->
+                  <div
+                    class="sticky top-0 bg-exo-dark-gray border-b border-exo-medium-gray/30 p-2"
+                  >
+                    <input
+                      type="text"
+                      placeholder="Search models..."
+                      bind:value={modelDropdownSearch}
+                      class="w-full bg-exo-dark-gray/60 border border-exo-medium-gray/30 rounded px-2 py-1.5 text-xs font-mono text-white/80 placeholder:text-white/40 focus:outline-none focus:border-exo-yellow/50"
+                    />
+                  </div>
+
+                  <!-- Options -->
+                  <div class="py-1">
+                    {#each sortedModels().filter((m) => !modelDropdownSearch || (m.name || m.id)
+                          .toLowerCase()
+                          .includes(modelDropdownSearch.toLowerCase())) as model}
+                      {@const sizeGB = getModelSizeGB(model)}
+                      {@const modelCanFit = hasEnoughMemory(model)}
+                      {@const isImageModel = modelSupportsImageGeneration(
+                        model.id,
+                      )}
+                      {@const isImageEditModel = modelSupportsImageEditing(
+                        model.id,
+                      )}
+                      <button
+                        type="button"
+                        onclick={() => {
+                          if (modelCanFit) {
+                            selectPreviewModel(model.id);
+                            saveLaunchDefaults();
+                            isModelDropdownOpen = false;
+                            modelDropdownSearch = "";
+                          }
+                        }}
+                        disabled={!modelCanFit}
+                        class="w-full px-3 py-2 text-left text-sm font-mono tracking-wide transition-colors duration-100 flex items-center justify-between gap-2 {selectedModelId ===
+                        model.id
+                          ? 'bg-transparent text-exo-yellow cursor-pointer'
+                          : modelCanFit
+                            ? 'text-white/80 hover:text-exo-yellow cursor-pointer'
+                            : 'text-white/30 cursor-default'}"
+                      >
+                        <span class="flex items-center gap-2 truncate flex-1">
+                          {#if isImageModel}
+                            <svg
+                              class="w-4 h-4 flex-shrink-0 text-exo-yellow"
+                              fill="none"
+                              viewBox="0 0 24 24"
+                              stroke="currentColor"
+                              stroke-width="2"
+                              aria-label="Image generation model"
+                            >
+                              <rect
+                                x="3"
+                                y="3"
+                                width="18"
+                                height="18"
+                                rx="2"
+                                ry="2"
+                              />
+                              <circle cx="8.5" cy="8.5" r="1.5" />
+                              <polyline points="21 15 16 10 5 21" />
+                            </svg>
+                          {/if}
+                          {#if isImageEditModel}
+                            <svg
+                              class="w-4 h-4 flex-shrink-0 text-exo-yellow"
+                              fill="none"
+                              viewBox="0 0 24 24"
+                              stroke="currentColor"
+                              stroke-width="2"
+                              aria-label="Image editing model"
+                            >
+                              <path
+                                d="M11 4H4a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7"
+                              />
+                              <path
+                                d="M18.5 2.5a2.121 2.121 0 0 1 3 3L12 15l-4 1 1-4 9.5-9.5z"
+                              />
+                            </svg>
+                          {/if}
+                          <span class="truncate">{model.name || model.id}</span>
+                        </span>
+                        <span
+                          class="flex-shrink-0 text-xs {modelCanFit
+                            ? 'text-white/50'
+                            : 'text-red-400/60'}"
+                        >
+                          {sizeGB >= 1
+                            ? sizeGB.toFixed(0)
+                            : sizeGB.toFixed(1)}GB
+                        </span>
+                      </button>
+                    {:else}
+                      <div class="px-3 py-2 text-xs text-white/50 font-mono">
+                        No models found
+                      </div>
+                    {/each}
+                  </div>
+                </div>
+              {/if}
             </div>
 
             <!-- Configuration Options -->
@@ -3246,22 +3354,3 @@
     {/if}
   </main>
 </div>
-
-<ModelPickerModal
-  isOpen={isModelPickerOpen}
-  {models}
-  {selectedModelId}
-  favorites={favoritesSet}
-  existingModelIds={new Set(models.map((m) => m.id))}
-  canModelFit={(modelId) => {
-    const model = models.find((m) => m.id === modelId);
-    return model ? hasEnoughMemory(model) : false;
-  }}
-  onSelect={handleModelPickerSelect}
-  onClose={() => (isModelPickerOpen = false)}
-  onToggleFavorite={toggleFavorite}
-  onAddModel={addModelFromPicker}
-  onDeleteModel={deleteCustomModel}
-  totalMemoryGB={clusterMemory().total / (1024 * 1024 * 1024)}
-  usedMemoryGB={clusterMemory().used / (1024 * 1024 * 1024)}
-/>

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

@@ -1,190 +0,0 @@
-<script lang="ts">
-  import { onMount } from "svelte";
-  import {
-    listTraces,
-    getTraceRawUrl,
-    type TraceListItem,
-  } from "$lib/stores/app.svelte";
-  import HeaderNav from "$lib/components/HeaderNav.svelte";
-
-  let traces = $state<TraceListItem[]>([]);
-  let loading = $state(true);
-  let error = $state<string | null>(null);
-
-  function formatBytes(bytes: number): string {
-    if (!bytes || bytes <= 0) return "0B";
-    const units = ["B", "KB", "MB", "GB"];
-    const i = Math.min(
-      Math.floor(Math.log(bytes) / Math.log(1024)),
-      units.length - 1,
-    );
-    const val = bytes / Math.pow(1024, i);
-    return `${val.toFixed(val >= 10 ? 0 : 1)}${units[i]}`;
-  }
-
-  function formatDate(isoString: string): string {
-    const date = new Date(isoString);
-    return date.toLocaleString();
-  }
-
-  async function downloadTrace(taskId: string) {
-    const response = await fetch(getTraceRawUrl(taskId));
-    const blob = await response.blob();
-    const url = URL.createObjectURL(blob);
-    const a = document.createElement("a");
-    a.href = url;
-    a.download = `trace_${taskId}.json`;
-    a.click();
-    URL.revokeObjectURL(url);
-  }
-
-  async function openInPerfetto(taskId: string) {
-    // Fetch trace data from our local API
-    const response = await fetch(getTraceRawUrl(taskId));
-    const traceData = await response.arrayBuffer();
-
-    // Open Perfetto UI
-    const perfettoWindow = window.open("https://ui.perfetto.dev");
-    if (!perfettoWindow) {
-      alert("Failed to open Perfetto. Please allow popups.");
-      return;
-    }
-
-    // Wait for Perfetto to be ready, then send trace via postMessage
-    const onMessage = (e: MessageEvent) => {
-      if (e.data === "PONG") {
-        window.removeEventListener("message", onMessage);
-        perfettoWindow.postMessage(
-          {
-            perfetto: {
-              buffer: traceData,
-              title: `Trace ${taskId}`,
-            },
-          },
-          "https://ui.perfetto.dev",
-        );
-      }
-    };
-    window.addEventListener("message", onMessage);
-
-    // Ping Perfetto until it responds
-    const pingInterval = setInterval(() => {
-      perfettoWindow.postMessage("PING", "https://ui.perfetto.dev");
-    }, 50);
-
-    // Clean up after 10 seconds
-    setTimeout(() => {
-      clearInterval(pingInterval);
-      window.removeEventListener("message", onMessage);
-    }, 10000);
-  }
-
-  async function refresh() {
-    loading = true;
-    error = null;
-    try {
-      const response = await listTraces();
-      traces = response.traces;
-    } catch (e) {
-      error = e instanceof Error ? e.message : "Failed to load traces";
-    } finally {
-      loading = false;
-    }
-  }
-
-  onMount(() => {
-    refresh();
-  });
-</script>
-
-<div class="min-h-screen bg-exo-dark-gray text-white">
-  <HeaderNav showHome={true} />
-  <div class="max-w-7xl mx-auto px-4 lg:px-8 py-6 space-y-6">
-    <div class="flex items-center justify-between gap-4 flex-wrap">
-      <div>
-        <h1
-          class="text-2xl font-mono tracking-[0.2em] uppercase text-exo-yellow"
-        >
-          Traces
-        </h1>
-      </div>
-      <div class="flex items-center gap-3">
-        <button
-          type="button"
-          class="text-xs font-mono text-exo-light-gray hover:text-exo-yellow transition-colors uppercase border border-exo-medium-gray/40 px-2 py-1 rounded"
-          onclick={refresh}
-          disabled={loading}
-        >
-          Refresh
-        </button>
-      </div>
-    </div>
-
-    {#if loading}
-      <div
-        class="rounded border border-exo-medium-gray/30 bg-exo-black/30 p-6 text-center text-exo-light-gray"
-      >
-        <div class="text-sm">Loading traces...</div>
-      </div>
-    {:else if error}
-      <div
-        class="rounded border border-red-500/30 bg-red-500/10 p-6 text-center text-red-400"
-      >
-        <div class="text-sm">{error}</div>
-      </div>
-    {:else if traces.length === 0}
-      <div
-        class="rounded border border-exo-medium-gray/30 bg-exo-black/30 p-6 text-center text-exo-light-gray space-y-2"
-      >
-        <div class="text-sm">No traces found.</div>
-        <div class="text-xs text-exo-light-gray/70">
-          Run exo with EXO_TRACING_ENABLED=1 to collect traces.
-        </div>
-      </div>
-    {:else}
-      <div class="space-y-3">
-        {#each traces as trace}
-          <div
-            class="rounded border border-exo-medium-gray/30 bg-exo-black/30 p-4 flex items-center justify-between gap-4"
-          >
-            <div class="min-w-0 flex-1">
-              <a
-                href="#/traces/{trace.taskId}"
-                class="text-sm font-mono text-white hover:text-exo-yellow transition-colors truncate block"
-              >
-                {trace.taskId}
-              </a>
-              <div class="text-xs text-exo-light-gray font-mono mt-1">
-                {formatDate(trace.createdAt)} &bull; {formatBytes(
-                  trace.fileSize,
-                )}
-              </div>
-            </div>
-            <div class="flex items-center gap-2 shrink-0">
-              <a
-                href="#/traces/{trace.taskId}"
-                class="text-xs font-mono text-exo-light-gray hover:text-exo-yellow transition-colors uppercase border border-exo-medium-gray/40 px-2 py-1 rounded"
-              >
-                View Stats
-              </a>
-              <button
-                type="button"
-                class="text-xs font-mono text-exo-light-gray hover:text-exo-yellow transition-colors uppercase border border-exo-medium-gray/40 px-2 py-1 rounded"
-                onclick={() => downloadTrace(trace.taskId)}
-              >
-                Download
-              </button>
-              <button
-                type="button"
-                class="text-xs font-mono text-exo-dark-gray bg-exo-yellow hover:bg-exo-yellow/90 transition-colors uppercase px-2 py-1 rounded font-semibold"
-                onclick={() => openInPerfetto(trace.taskId)}
-              >
-                View Trace
-              </button>
-            </div>
-          </div>
-        {/each}
-      </div>
-    {/if}
-  </div>
-</div>

dashboard/src/routes/traces/[taskId]/+page.svelte

@@ -1,367 +0,0 @@
-<script lang="ts">
-  import { page } from "$app/stores";
-  import { onMount } from "svelte";
-  import {
-    fetchTraceStats,
-    getTraceRawUrl,
-    type TraceStatsResponse,
-    type TraceCategoryStats,
-  } from "$lib/stores/app.svelte";
-  import HeaderNav from "$lib/components/HeaderNav.svelte";
-
-  const taskId = $derived($page.params.taskId);
-
-  let stats = $state<TraceStatsResponse | null>(null);
-  let loading = $state(true);
-  let error = $state<string | null>(null);
-
-  function formatDuration(us: number): string {
-    if (us < 1000) return `${us.toFixed(0)}us`;
-    if (us < 1_000_000) return `${(us / 1000).toFixed(2)}ms`;
-    return `${(us / 1_000_000).toFixed(2)}s`;
-  }
-
-  function formatPercentage(part: number, total: number): string {
-    if (total === 0) return "0.0%";
-    return `${((part / total) * 100).toFixed(1)}%`;
-  }
-
-  // Parse hierarchical categories like "sync/compute" into phases
-  type PhaseData = {
-    name: string;
-    subcategories: { name: string; stats: TraceCategoryStats }[];
-    totalUs: number; // From outer span (e.g., "sync" category)
-    stepCount: number; // Count of outer span events
-  };
-
-  function parsePhases(
-    byCategory: Record<string, TraceCategoryStats>,
-  ): PhaseData[] {
-    const phases = new Map<
-      string,
-      {
-        subcats: Map<string, TraceCategoryStats>;
-        outerStats: TraceCategoryStats | null;
-      }
-    >();
-
-    for (const [category, catStats] of Object.entries(byCategory)) {
-      if (category.includes("/")) {
-        const [phase, subcat] = category.split("/", 2);
-        if (!phases.has(phase)) {
-          phases.set(phase, { subcats: new Map(), outerStats: null });
-        }
-        phases.get(phase)!.subcats.set(subcat, catStats);
-      } else {
-        // Outer span - this IS the phase total
-        if (!phases.has(category)) {
-          phases.set(category, { subcats: new Map(), outerStats: null });
-        }
-        phases.get(category)!.outerStats = catStats;
-      }
-    }
-
-    return Array.from(phases.entries())
-      .filter(([_, data]) => data.outerStats !== null) // Only phases with outer spans
-      .map(([name, data]) => ({
-        name,
-        subcategories: Array.from(data.subcats.entries())
-          .map(([subName, subStats]) => ({ name: subName, stats: subStats }))
-          .sort((a, b) => b.stats.totalUs - a.stats.totalUs),
-        totalUs: data.outerStats!.totalUs, // Outer span total
-        stepCount: data.outerStats!.count, // Number of steps
-      }))
-      .sort((a, b) => b.totalUs - a.totalUs);
-  }
-
-  async function downloadTrace() {
-    if (!taskId) return;
-    const response = await fetch(getTraceRawUrl(taskId));
-    const blob = await response.blob();
-    const url = URL.createObjectURL(blob);
-    const a = document.createElement("a");
-    a.href = url;
-    a.download = `trace_${taskId}.json`;
-    a.click();
-    URL.revokeObjectURL(url);
-  }
-
-  async function openInPerfetto() {
-    if (!taskId) return;
-
-    // Fetch trace data from our local API
-    const response = await fetch(getTraceRawUrl(taskId));
-    const traceData = await response.arrayBuffer();
-
-    // Open Perfetto UI
-    const perfettoWindow = window.open("https://ui.perfetto.dev");
-    if (!perfettoWindow) {
-      alert("Failed to open Perfetto. Please allow popups.");
-      return;
-    }
-
-    // Wait for Perfetto to be ready, then send trace via postMessage
-    const onMessage = (e: MessageEvent) => {
-      if (e.data === "PONG") {
-        window.removeEventListener("message", onMessage);
-        perfettoWindow.postMessage(
-          {
-            perfetto: {
-              buffer: traceData,
-              title: `Trace ${taskId}`,
-            },
-          },
-          "https://ui.perfetto.dev",
-        );
-      }
-    };
-    window.addEventListener("message", onMessage);
-
-    // Ping Perfetto until it responds
-    const pingInterval = setInterval(() => {
-      perfettoWindow.postMessage("PING", "https://ui.perfetto.dev");
-    }, 50);
-
-    // Clean up after 10 seconds
-    setTimeout(() => {
-      clearInterval(pingInterval);
-      window.removeEventListener("message", onMessage);
-    }, 10000);
-  }
-
-  onMount(async () => {
-    if (!taskId) {
-      error = "No task ID provided";
-      loading = false;
-      return;
-    }
-
-    try {
-      stats = await fetchTraceStats(taskId);
-    } catch (e) {
-      error = e instanceof Error ? e.message : "Failed to load trace";
-    } finally {
-      loading = false;
-    }
-  });
-
-  const phases = $derived(stats ? parsePhases(stats.byCategory) : []);
-  const sortedRanks = $derived(
-    stats
-      ? Object.keys(stats.byRank)
-          .map(Number)
-          .sort((a, b) => a - b)
-      : [],
-  );
-  const nodeCount = $derived(sortedRanks.length || 1);
-</script>
-
-<div class="min-h-screen bg-exo-dark-gray text-white">
-  <HeaderNav showHome={true} />
-  <div class="max-w-7xl mx-auto px-4 lg:px-8 py-6 space-y-6">
-    <div class="flex items-center justify-between gap-4 flex-wrap">
-      <div>
-        <h1
-          class="text-2xl font-mono tracking-[0.2em] uppercase text-exo-yellow"
-        >
-          Trace
-        </h1>
-        <p class="text-sm text-exo-light-gray font-mono truncate max-w-lg">
-          {taskId}
-        </p>
-      </div>
-      <div class="flex items-center gap-3">
-        <a
-          href="#/traces"
-          class="text-xs font-mono text-exo-light-gray hover:text-exo-yellow transition-colors uppercase border border-exo-medium-gray/40 px-3 py-1.5 rounded"
-        >
-          All Traces
-        </a>
-        <button
-          type="button"
-          class="text-xs font-mono text-exo-light-gray hover:text-exo-yellow transition-colors uppercase border border-exo-medium-gray/40 px-3 py-1.5 rounded"
-          onclick={downloadTrace}
-          disabled={loading || !!error}
-        >
-          Download
-        </button>
-        <button
-          type="button"
-          class="text-xs font-mono text-exo-dark-gray bg-exo-yellow hover:bg-exo-yellow/90 transition-colors uppercase px-3 py-1.5 rounded font-semibold"
-          onclick={openInPerfetto}
-          disabled={loading || !!error}
-        >
-          View Trace
-        </button>
-      </div>
-    </div>
-
-    {#if loading}
-      <div
-        class="rounded border border-exo-medium-gray/30 bg-exo-black/30 p-6 text-center text-exo-light-gray"
-      >
-        <div class="text-sm">Loading trace data...</div>
-      </div>
-    {:else if error}
-      <div
-        class="rounded border border-red-500/30 bg-red-500/10 p-6 text-center text-red-400"
-      >
-        <div class="text-sm">{error}</div>
-      </div>
-    {:else if stats}
-      <!-- Wall Time Summary -->
-      <div
-        class="rounded border border-exo-medium-gray/30 bg-exo-black/30 p-4 space-y-2"
-      >
-        <h2
-          class="text-sm font-mono uppercase tracking-wider text-exo-light-gray"
-        >
-          Summary
-        </h2>
-        <div class="text-3xl font-mono text-exo-yellow">
-          {formatDuration(stats.totalWallTimeUs)}
-        </div>
-        <div class="text-xs text-exo-light-gray">Total wall time</div>
-      </div>
-
-      <!-- By Phase -->
-      {#if phases.length > 0}
-        <div
-          class="rounded border border-exo-medium-gray/30 bg-exo-black/30 p-4 space-y-4"
-        >
-          <h2
-            class="text-sm font-mono uppercase tracking-wider text-exo-light-gray"
-          >
-            By Phase <span class="text-exo-light-gray/50">(avg per node)</span>
-          </h2>
-          <div class="space-y-4">
-            {#each phases as phase}
-              {@const normalizedTotal = phase.totalUs / nodeCount}
-              {@const normalizedStepCount = phase.stepCount / nodeCount}
-              <div class="space-y-2">
-                <div class="flex items-center justify-between">
-                  <span class="text-sm font-mono text-white">{phase.name}</span>
-                  <span class="text-sm font-mono">
-                    <span class="text-exo-yellow"
-                      >{formatDuration(normalizedTotal)}</span
-                    >
-                    <span class="text-exo-light-gray ml-2">
-                      ({normalizedStepCount} steps, {formatDuration(
-                        normalizedTotal / normalizedStepCount,
-                      )}/step)
-                    </span>
-                  </span>
-                </div>
-                {#if phase.subcategories.length > 0}
-                  <div class="pl-4 space-y-1.5">
-                    {#each phase.subcategories as subcat}
-                      {@const normalizedSubcat =
-                        subcat.stats.totalUs / nodeCount}
-                      {@const pct = formatPercentage(
-                        normalizedSubcat,
-                        normalizedTotal,
-                      )}
-                      {@const perStep = normalizedSubcat / normalizedStepCount}
-                      <div
-                        class="flex items-center justify-between text-xs font-mono"
-                      >
-                        <span class="text-exo-light-gray">{subcat.name}</span>
-                        <span class="text-white">
-                          {formatDuration(normalizedSubcat)}
-                          <span class="text-exo-light-gray ml-2">({pct})</span>
-                          <span class="text-exo-light-gray/60 ml-2"
-                            >{formatDuration(perStep)}/step</span
-                          >
-                        </span>
-                      </div>
-                      <!-- Progress bar -->
-                      <div
-                        class="relative h-1.5 bg-exo-black/60 rounded-sm overflow-hidden"
-                      >
-                        <div
-                          class="absolute inset-y-0 left-0 bg-gradient-to-r from-exo-yellow to-exo-yellow/70 transition-all duration-300"
-                          style="width: {pct}"
-                        ></div>
-                      </div>
-                    {/each}
-                  </div>
-                {/if}
-              </div>
-            {/each}
-          </div>
-        </div>
-      {/if}
-
-      <!-- By Rank -->
-      {#if sortedRanks.length > 0}
-        <div
-          class="rounded border border-exo-medium-gray/30 bg-exo-black/30 p-4 space-y-4"
-        >
-          <h2
-            class="text-sm font-mono uppercase tracking-wider text-exo-light-gray"
-          >
-            By Rank
-          </h2>
-          <div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-4">
-            {#each sortedRanks as rank}
-              {@const rankStats = stats.byRank[rank]}
-              {@const rankPhases = parsePhases(rankStats.byCategory)}
-              <div
-                class="rounded border border-exo-medium-gray/20 bg-exo-dark-gray/60 p-3 space-y-3"
-              >
-                <div class="text-sm font-mono text-exo-yellow">
-                  Rank {rank}
-                </div>
-                <div class="space-y-2">
-                  {#each rankPhases as phase}
-                    <div class="space-y-1">
-                      <div class="flex items-center justify-between text-xs">
-                        <span class="font-mono text-exo-light-gray"
-                          >{phase.name}</span
-                        >
-                        <span class="font-mono text-white">
-                          {formatDuration(phase.totalUs)}
-                          <span class="text-exo-light-gray/50 ml-1">
-                            ({phase.stepCount}x)
-                          </span>
-                        </span>
-                      </div>
-                      {#if phase.subcategories.length > 0}
-                        <div class="pl-2 space-y-0.5">
-                          {#each phase.subcategories as subcat}
-                            {@const pct = formatPercentage(
-                              subcat.stats.totalUs,
-                              phase.totalUs,
-                            )}
-                            {@const perStep =
-                              subcat.stats.totalUs / phase.stepCount}
-                            <div
-                              class="flex items-center justify-between text-[10px] font-mono"
-                            >
-                              <span class="text-exo-light-gray/70"
-                                >{subcat.name}</span
-                              >
-                              <span class="text-exo-light-gray">
-                                {formatDuration(subcat.stats.totalUs)}
-                                <span class="text-exo-light-gray/50"
-                                  >({pct})</span
-                                >
-                                <span class="text-exo-light-gray/30 ml-1"
-                                  >{formatDuration(perStep)}/step</span
-                                >
-                              </span>
-                            </div>
-                          {/each}
-                        </div>
-                      {/if}
-                    </div>
-                  {/each}
-                </div>
-              </div>
-            {/each}
-          </div>
-        </div>
-      {/if}
-    {/if}
-  </div>
-</div>

packaging/pyinstaller/exo.spec

@@ -10,7 +10,6 @@ PROJECT_ROOT = Path.cwd()
 SOURCE_ROOT = PROJECT_ROOT / "src"
 ENTRYPOINT = SOURCE_ROOT / "exo" / "__main__.py"
 DASHBOARD_DIR = PROJECT_ROOT / "dashboard" / "build"
-RESOURCES_DIR = PROJECT_ROOT / "resources"
 EXO_SHARED_MODELS_DIR = SOURCE_ROOT / "exo" / "shared" / "models"
 
 if not ENTRYPOINT.is_file():
@@ -19,9 +18,6 @@ if not ENTRYPOINT.is_file():
 if not DASHBOARD_DIR.is_dir():
     raise SystemExit(f"Dashboard assets are missing: {DASHBOARD_DIR}")
 
-if not RESOURCES_DIR.is_dir():
-    raise SystemExit(f"Resource assets are missing: {RESOURCES_DIR}")
-
 if not EXO_SHARED_MODELS_DIR.is_dir():
     raise SystemExit(f"Shared model assets are missing: {EXO_SHARED_MODELS_DIR}")
 
@@ -62,7 +58,6 @@ HIDDEN_IMPORTS = sorted(
 
 DATAS: list[tuple[str, str]] = [
     (str(DASHBOARD_DIR), "dashboard"),
-    (str(RESOURCES_DIR), "resources"),
     (str(MLX_LIB_DIR), "mlx/lib"),
     (str(EXO_SHARED_MODELS_DIR), "exo/shared/models"),
 ]

python/parts.nix

@@ -69,9 +69,7 @@
           # Create wrapper scripts
           for script in exo exo-master exo-worker; do
             makeWrapper ${exoVenv}/bin/$script $out/bin/$script \
-              --set EXO_DASHBOARD_DIR ${self'.packages.dashboard} \
-              --set EXO_RESOURCES_DIR ${inputs.self + "/resources"} \
-              ${lib.optionalString pkgs.stdenv.isDarwin "--prefix PATH : ${pkgs.macmon}/bin"}
+              --set DASHBOARD_DIR ${self'.packages.dashboard}
           done
         '';
     in

resources/image_model_cards/exolabs--FLUX.1-Krea-dev-4bit.toml

@@ -1,45 +0,0 @@
-model_id = "exolabs/FLUX.1-Krea-dev-4bit"
-n_layers = 57
-hidden_size = 1
-supports_tensor = false
-tasks = ["TextToImage"]
-
-[storage_size]
-in_bytes = 15475325472
-
-[[components]]
-component_name = "text_encoder"
-component_path = "text_encoder/"
-n_layers = 12
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0
-
-[[components]]
-component_name = "text_encoder_2"
-component_path = "text_encoder_2/"
-n_layers = 24
-can_shard = false
-safetensors_index_filename = "model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 9524621312
-
-[[components]]
-component_name = "transformer"
-component_path = "transformer/"
-n_layers = 57
-can_shard = true
-safetensors_index_filename = "diffusion_pytorch_model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 5950704160
-
-[[components]]
-component_name = "vae"
-component_path = "vae/"
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0

resources/image_model_cards/exolabs--FLUX.1-Krea-dev-8bit.toml

@@ -1,45 +0,0 @@
-model_id = "exolabs/FLUX.1-Krea-dev-8bit"
-n_layers = 57
-hidden_size = 1
-supports_tensor = false
-tasks = ["TextToImage"]
-
-[storage_size]
-in_bytes = 21426029632
-
-[[components]]
-component_name = "text_encoder"
-component_path = "text_encoder/"
-n_layers = 12
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0
-
-[[components]]
-component_name = "text_encoder_2"
-component_path = "text_encoder_2/"
-n_layers = 24
-can_shard = false
-safetensors_index_filename = "model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 9524621312
-
-[[components]]
-component_name = "transformer"
-component_path = "transformer/"
-n_layers = 57
-can_shard = true
-safetensors_index_filename = "diffusion_pytorch_model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 11901408320
-
-[[components]]
-component_name = "vae"
-component_path = "vae/"
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0

resources/image_model_cards/exolabs--FLUX.1-Krea-dev.toml

@@ -1,45 +0,0 @@
-model_id = "exolabs/FLUX.1-Krea-dev"
-n_layers = 57
-hidden_size = 1
-supports_tensor = false
-tasks = ["TextToImage"]
-
-[storage_size]
-in_bytes = 33327437952
-
-[[components]]
-component_name = "text_encoder"
-component_path = "text_encoder/"
-n_layers = 12
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0
-
-[[components]]
-component_name = "text_encoder_2"
-component_path = "text_encoder_2/"
-n_layers = 24
-can_shard = false
-safetensors_index_filename = "model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 9524621312
-
-[[components]]
-component_name = "transformer"
-component_path = "transformer/"
-n_layers = 57
-can_shard = true
-safetensors_index_filename = "diffusion_pytorch_model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 23802816640
-
-[[components]]
-component_name = "vae"
-component_path = "vae/"
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0

resources/image_model_cards/exolabs--FLUX.1-dev-4bit.toml

@@ -1,45 +0,0 @@
-model_id = "exolabs/FLUX.1-dev-4bit"
-n_layers = 57
-hidden_size = 1
-supports_tensor = false
-tasks = ["TextToImage"]
-
-[storage_size]
-in_bytes = 15475325472
-
-[[components]]
-component_name = "text_encoder"
-component_path = "text_encoder/"
-n_layers = 12
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0
-
-[[components]]
-component_name = "text_encoder_2"
-component_path = "text_encoder_2/"
-n_layers = 24
-can_shard = false
-safetensors_index_filename = "model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 9524621312
-
-[[components]]
-component_name = "transformer"
-component_path = "transformer/"
-n_layers = 57
-can_shard = true
-safetensors_index_filename = "diffusion_pytorch_model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 5950704160
-
-[[components]]
-component_name = "vae"
-component_path = "vae/"
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0

resources/image_model_cards/exolabs--FLUX.1-dev-8bit.toml

@@ -1,45 +0,0 @@
-model_id = "exolabs/FLUX.1-dev-8bit"
-n_layers = 57
-hidden_size = 1
-supports_tensor = false
-tasks = ["TextToImage"]
-
-[storage_size]
-in_bytes = 21426029632
-
-[[components]]
-component_name = "text_encoder"
-component_path = "text_encoder/"
-n_layers = 12
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0
-
-[[components]]
-component_name = "text_encoder_2"
-component_path = "text_encoder_2/"
-n_layers = 24
-can_shard = false
-safetensors_index_filename = "model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 9524621312
-
-[[components]]
-component_name = "transformer"
-component_path = "transformer/"
-n_layers = 57
-can_shard = true
-safetensors_index_filename = "diffusion_pytorch_model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 11901408320
-
-[[components]]
-component_name = "vae"
-component_path = "vae/"
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0

resources/image_model_cards/exolabs--FLUX.1-dev.toml

@@ -1,45 +0,0 @@
-model_id = "exolabs/FLUX.1-dev"
-n_layers = 57
-hidden_size = 1
-supports_tensor = false
-tasks = ["TextToImage"]
-
-[storage_size]
-in_bytes = 33327437952
-
-[[components]]
-component_name = "text_encoder"
-component_path = "text_encoder/"
-n_layers = 12
-can_shard = false
-
-[components.storage_size]
-in_bytes = 0
-
-[[components]]
-component_name = "text_encoder_2"
-component_path = "text_encoder_2/"
-n_layers = 24
-can_shard = false
-safetensors_index_filename = "model.safetensors.index.json"
-
-[components.storage_size]
-in_bytes = 9524621312
-
-[[components]]
-component_name = "transformer"
-component_path = "transformer/"
-n_layers = 57
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resources/image_model_cards/exolabs--FLUX.1-schnell-4bit.toml

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resources/image_model_cards/exolabs--FLUX.1-schnell-8bit.toml

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resources/image_model_cards/exolabs--FLUX.1-schnell.toml

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resources/image_model_cards/exolabs--Qwen-Image-4bit.toml

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resources/image_model_cards/exolabs--Qwen-Image-8bit.toml

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resources/image_model_cards/exolabs--Qwen-Image-Edit-2509-4bit.toml

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resources/image_model_cards/exolabs--Qwen-Image-Edit-2509-8bit.toml

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resources/image_model_cards/exolabs--Qwen-Image-Edit-2509.toml

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resources/image_model_cards/exolabs--Qwen-Image.toml

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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-n_layers = 28
-hidden_size = 1024
-supports_tensor = false
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "8bit"
-base_model = "Qwen3 0.6B"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 698351616

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

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Qwen3-235B-A22B-Instruct-2507-4bit"
-n_layers = 94
-hidden_size = 4096
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "4bit"
-base_model = "Qwen3 235B"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 141733920768

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

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Qwen3-235B-A22B-Instruct-2507-8bit"
-n_layers = 94
-hidden_size = 4096
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "8bit"
-base_model = "Qwen3 235B"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 268435456000

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

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Qwen3-30B-A3B-4bit"
-n_layers = 48
-hidden_size = 2048
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "4bit"
-base_model = "Qwen3 30B"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 17612931072

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

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Qwen3-30B-A3B-8bit"
-n_layers = 48
-hidden_size = 2048
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "8bit"
-base_model = "Qwen3 30B"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 33279705088

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

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Qwen3-Coder-480B-A35B-Instruct-4bit"
-n_layers = 62
-hidden_size = 6144
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "4bit"
-base_model = "Qwen3 Coder 480B"
-capabilities = ["text", "code"]
-
-[storage_size]
-in_bytes = 289910292480

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

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Qwen3-Coder-480B-A35B-Instruct-8bit"
-n_layers = 62
-hidden_size = 6144
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "8bit"
-base_model = "Qwen3 Coder 480B"
-capabilities = ["text", "code"]
-
-[storage_size]
-in_bytes = 579820584960

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

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Qwen3-Next-80B-A3B-Instruct-4bit"
-n_layers = 48
-hidden_size = 2048
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "4bit"
-base_model = "Qwen3 Next 80B"
-capabilities = ["text"]
-
-[storage_size]
-in_bytes = 46976204800

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

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Qwen3-Next-80B-A3B-Instruct-8bit"
-n_layers = 48
-hidden_size = 2048
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "8bit"
-base_model = "Qwen3 Next 80B"
-capabilities = ["text"]
-
-[storage_size]
-in_bytes = 88814387200

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

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Qwen3-Next-80B-A3B-Thinking-4bit"
-n_layers = 48
-hidden_size = 2048
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "4bit"
-base_model = "Qwen3 Next 80B"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 47080074240

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

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Qwen3-Next-80B-A3B-Thinking-8bit"
-n_layers = 48
-hidden_size = 2048
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "qwen"
-quantization = "8bit"
-base_model = "Qwen3 Next 80B"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 88814387200

resources/inference_model_cards/mlx-community--gpt-oss-120b-MXFP4-Q8.toml

@@ -1,12 +0,0 @@
-model_id = "mlx-community/gpt-oss-120b-MXFP4-Q8"
-n_layers = 36
-hidden_size = 2880
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "gpt-oss"
-quantization = "MXFP4-Q8"
-base_model = "GPT-OSS 120B"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 70652212224

resources/inference_model_cards/mlx-community--gpt-oss-20b-MXFP4-Q8.toml

@@ -1,12 +0,0 @@
-model_id = "mlx-community/gpt-oss-20b-MXFP4-Q8"
-n_layers = 24
-hidden_size = 2880
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "gpt-oss"
-quantization = "MXFP4-Q8"
-base_model = "GPT-OSS 20B"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 12025908224

resources/inference_model_cards/mlx-community--llama-3.3-70b-instruct-fp16.toml

@@ -1,12 +0,0 @@
-model_id = "mlx-community/llama-3.3-70b-instruct-fp16"
-n_layers = 80
-hidden_size = 8192
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "llama"
-quantization = "fp16"
-base_model = "Llama 3.3 70B"
-capabilities = ["text"]
-
-[storage_size]
-in_bytes = 144383672320

src/exo/download/coordinator.py

@@ -1,5 +1,4 @@
 import asyncio
-import socket
 from dataclasses import dataclass, field
 from typing import Iterator
 
@@ -53,44 +52,18 @@ class DownloadCoordinator:
     # Internal event channel for forwarding (initialized in __post_init__)
     event_sender: Sender[Event] = field(init=False)
     event_receiver: Receiver[Event] = field(init=False)
-    _tg: TaskGroup = field(init=False, default_factory=anyio.create_task_group)
+    _tg: TaskGroup = field(init=False)
 
     def __post_init__(self) -> None:
         self.event_sender, self.event_receiver = channel[Event]()
+        self._tg = anyio.create_task_group()
 
     async def run(self) -> None:
         logger.info("Starting DownloadCoordinator")
-        self._test_internet_connection()
         async with self._tg as tg:
             tg.start_soon(self._command_processor)
             tg.start_soon(self._forward_events)
             tg.start_soon(self._emit_existing_download_progress)
-            tg.start_soon(self._check_internet_connection)
-
-    def _test_internet_connection(self) -> None:
-        try:
-            socket.create_connection(("1.1.1.1", 443), timeout=3).close()
-            self.shard_downloader.set_internet_connection(True)
-        except OSError:
-            self.shard_downloader.set_internet_connection(False)
-        logger.debug(
-            f"Internet connectivity: {self.shard_downloader.internet_connection}"
-        )
-
-    async def _check_internet_connection(self) -> None:
-        first_connection = True
-        while True:
-            await asyncio.sleep(10)
-
-            # Assume that internet connection is set to False on 443 errors.
-            if self.shard_downloader.internet_connection:
-                continue
-
-            self._test_internet_connection()
-
-            if first_connection and self.shard_downloader.internet_connection:
-                first_connection = False
-                self._tg.start_soon(self._emit_existing_download_progress)
 
     def shutdown(self) -> None:
         self._tg.cancel_scope.cancel()
@@ -268,7 +241,7 @@ class DownloadCoordinator:
     async def _emit_existing_download_progress(self) -> None:
         try:
             while True:
-                logger.debug(
+                logger.info(
                     "DownloadCoordinator: Fetching and emitting existing download progress..."
                 )
                 async for (
@@ -301,10 +274,10 @@ class DownloadCoordinator:
                     await self.event_sender.send(
                         NodeDownloadProgress(download_progress=status)
                     )
-                logger.debug(
+                logger.info(
                     "DownloadCoordinator: Done emitting existing download progress."
                 )
-                await anyio.sleep(60)
+                await anyio.sleep(5 * 60)  # 5 minutes
         except Exception as e:
             logger.error(
                 f"DownloadCoordinator: Error emitting existing download progress: {e}"

src/exo/download/download_utils.py

@@ -49,10 +49,6 @@ class HuggingFaceAuthenticationError(Exception):
     """Raised when HuggingFace returns 401/403 for a model download."""
 
 
-class HuggingFaceRateLimitError(Exception):
-    """429 Huggingface code"""
-
-
 async def _build_auth_error_message(status_code: int, model_id: ModelId) -> str:
     token = await get_hf_token()
     if status_code == 401 and token is None:
@@ -158,76 +154,49 @@ async def seed_models(seed_dir: str | Path):
                     logger.error(traceback.format_exc())
 
 
-_fetched_file_lists_this_session: set[str] = set()
-
-
 async def fetch_file_list_with_cache(
-    model_id: ModelId,
-    revision: str = "main",
-    recursive: bool = False,
-    skip_internet: bool = False,
-    on_connection_lost: Callable[[], None] = lambda: None,
+    model_id: ModelId, revision: str = "main", recursive: bool = False
 ) -> list[FileListEntry]:
     target_dir = (await ensure_models_dir()) / "caches" / model_id.normalize()
     await aios.makedirs(target_dir, exist_ok=True)
     cache_file = target_dir / f"{model_id.normalize()}--{revision}--file_list.json"
-    cache_key = f"{model_id.normalize()}--{revision}"
-
-    if cache_key in _fetched_file_lists_this_session and await aios.path.exists(
-        cache_file
-    ):
-        async with aiofiles.open(cache_file, "r") as f:
-            return TypeAdapter(list[FileListEntry]).validate_json(await f.read())
-
-    if skip_internet:
-        if await aios.path.exists(cache_file):
-            async with aiofiles.open(cache_file, "r") as f:
-                return TypeAdapter(list[FileListEntry]).validate_json(await f.read())
-        raise FileNotFoundError(
-            f"No internet connection and no cached file list for {model_id}"
-        )
 
+    # Always try fresh first
     try:
         file_list = await fetch_file_list_with_retry(
-            model_id,
-            revision,
-            recursive=recursive,
-            on_connection_lost=on_connection_lost,
+            model_id, revision, recursive=recursive
         )
+        # Update cache with fresh data
         async with aiofiles.open(cache_file, "w") as f:
             await f.write(
                 TypeAdapter(list[FileListEntry]).dump_json(file_list).decode()
             )
-        _fetched_file_lists_this_session.add(cache_key)
         return file_list
     except Exception as e:
+        # Fetch failed - try cache fallback
         if await aios.path.exists(cache_file):
             logger.warning(
                 f"Failed to fetch file list for {model_id}, using cached data: {e}"
             )
             async with aiofiles.open(cache_file, "r") as f:
                 return TypeAdapter(list[FileListEntry]).validate_json(await f.read())
-        raise FileNotFoundError(f"Failed to fetch file list for {model_id}: {e}") from e
+        # No cache available, propagate the error
+        raise
 
 
 async def fetch_file_list_with_retry(
-    model_id: ModelId,
-    revision: str = "main",
-    path: str = "",
-    recursive: bool = False,
-    on_connection_lost: Callable[[], None] = lambda: None,
+    model_id: ModelId, revision: str = "main", path: str = "", recursive: bool = False
 ) -> list[FileListEntry]:
-    n_attempts = 3
+    n_attempts = 30
     for attempt in range(n_attempts):
         try:
             return await _fetch_file_list(model_id, revision, path, recursive)
         except HuggingFaceAuthenticationError:
             raise
         except Exception as e:
-            on_connection_lost()
             if attempt == n_attempts - 1:
                 raise e
-            await asyncio.sleep(2.0**attempt)
+            await asyncio.sleep(min(8, 0.1 * float(2.0 ** int(attempt))))
     raise Exception(
         f"Failed to fetch file list for {model_id=} {revision=} {path=} {recursive=}"
     )
@@ -247,11 +216,7 @@ async def _fetch_file_list(
         if response.status in [401, 403]:
             msg = await _build_auth_error_message(response.status, model_id)
             raise HuggingFaceAuthenticationError(msg)
-        elif response.status == 429:
-            raise HuggingFaceRateLimitError(
-                f"Couldn't download {model_id} because of HuggingFace rate limit."
-            )
-        elif response.status == 200:
+        if response.status == 200:
             data_json = await response.text()
             data = TypeAdapter(list[FileListEntry]).validate_json(data_json)
             files: list[FileListEntry] = []
@@ -284,7 +249,7 @@ def create_http_session(
     else:
         total_timeout = 1800
         connect_timeout = 60
-        sock_read_timeout = 60
+        sock_read_timeout = 1800
         sock_connect_timeout = 60
 
     ssl_context = ssl.create_default_context(
@@ -359,9 +324,8 @@ async def download_file_with_retry(
     path: str,
     target_dir: Path,
     on_progress: Callable[[int, int, bool], None] = lambda _, __, ___: None,
-    on_connection_lost: Callable[[], None] = lambda: None,
 ) -> Path:
-    n_attempts = 3
+    n_attempts = 30
     for attempt in range(n_attempts):
         try:
             return await _download_file(
@@ -369,19 +333,14 @@ async def download_file_with_retry(
             )
         except HuggingFaceAuthenticationError:
             raise
-        except HuggingFaceRateLimitError as e:
-            if attempt == n_attempts - 1:
+        except Exception as e:
+            if isinstance(e, FileNotFoundError) or attempt == n_attempts - 1:
                 raise e
             logger.error(
                 f"Download error on attempt {attempt}/{n_attempts} for {model_id=} {revision=} {path=} {target_dir=}"
             )
             logger.error(traceback.format_exc())
-            await asyncio.sleep(2.0**attempt)
-        except Exception as e:
-            on_connection_lost()
-            if attempt == n_attempts - 1:
-                raise e
-            break
+            await asyncio.sleep(min(8, 0.1 * (2.0**attempt)))
     raise Exception(
         f"Failed to download file {model_id=} {revision=} {path=} {target_dir=}"
     )
@@ -583,9 +542,7 @@ async def download_shard(
     on_progress: Callable[[ShardMetadata, RepoDownloadProgress], Awaitable[None]],
     max_parallel_downloads: int = 8,
     skip_download: bool = False,
-    skip_internet: bool = False,
     allow_patterns: list[str] | None = None,
-    on_connection_lost: Callable[[], None] = lambda: None,
 ) -> tuple[Path, RepoDownloadProgress]:
     if not skip_download:
         logger.debug(f"Downloading {shard.model_card.model_id=}")
@@ -605,11 +562,7 @@ async def download_shard(
 
     all_start_time = time.time()
     file_list = await fetch_file_list_with_cache(
-        shard.model_card.model_id,
-        revision,
-        recursive=True,
-        skip_internet=skip_internet,
-        on_connection_lost=on_connection_lost,
+        shard.model_card.model_id, revision, recursive=True
     )
     filtered_file_list = list(
         filter_repo_objects(
@@ -719,7 +672,6 @@ async def download_shard(
                 lambda curr_bytes, total_bytes, is_renamed: schedule_progress(
                     file, curr_bytes, total_bytes, is_renamed
                 ),
-                on_connection_lost=on_connection_lost,
             )
 
     if not skip_download:

src/exo/download/impl_shard_downloader.py

@@ -1,5 +1,4 @@
 import asyncio
-from asyncio import create_task
 from collections.abc import Awaitable
 from pathlib import Path
 from typing import AsyncIterator, Callable
@@ -8,7 +7,7 @@ from loguru import logger
 
 from exo.download.download_utils import RepoDownloadProgress, download_shard
 from exo.download.shard_downloader import ShardDownloader
-from exo.shared.models.model_cards import ModelCard, ModelId, get_model_cards
+from exo.shared.models.model_cards import MODEL_CARDS, ModelCard, ModelId
 from exo.shared.types.worker.shards import (
     PipelineShardMetadata,
     ShardMetadata,
@@ -22,7 +21,7 @@ def exo_shard_downloader(max_parallel_downloads: int = 8) -> ShardDownloader:
 
 
 async def build_base_shard(model_id: ModelId) -> ShardMetadata:
-    model_card = await ModelCard.load(model_id)
+    model_card = await ModelCard.from_hf(model_id)
     return PipelineShardMetadata(
         model_card=model_card,
         device_rank=0,
@@ -50,10 +49,6 @@ class SingletonShardDownloader(ShardDownloader):
         self.shard_downloader = shard_downloader
         self.active_downloads: dict[ShardMetadata, asyncio.Task[Path]] = {}
 
-    def set_internet_connection(self, value: bool) -> None:
-        self.internet_connection = value
-        self.shard_downloader.set_internet_connection(value)
-
     def on_progress(
         self,
         callback: Callable[[ShardMetadata, RepoDownloadProgress], Awaitable[None]],
@@ -90,10 +85,6 @@ class CachedShardDownloader(ShardDownloader):
         self.shard_downloader = shard_downloader
         self.cache: dict[tuple[str, ShardMetadata], Path] = {}
 
-    def set_internet_connection(self, value: bool) -> None:
-        self.internet_connection = value
-        self.shard_downloader.set_internet_connection(value)
-
     def on_progress(
         self,
         callback: Callable[[ShardMetadata, RepoDownloadProgress], Awaitable[None]],
@@ -151,8 +142,6 @@ class ResumableShardDownloader(ShardDownloader):
             self.on_progress_wrapper,
             max_parallel_downloads=self.max_parallel_downloads,
             allow_patterns=allow_patterns,
-            skip_internet=not self.internet_connection,
-            on_connection_lost=lambda: self.set_internet_connection(False),
         )
         return target_dir
 
@@ -165,31 +154,21 @@ class ResumableShardDownloader(ShardDownloader):
             """Helper coroutine that builds the shard for a model and gets its download status."""
             shard = await build_full_shard(model_id)
             return await download_shard(
-                shard,
-                self.on_progress_wrapper,
-                skip_download=True,
-                skip_internet=not self.internet_connection,
-                on_connection_lost=lambda: self.set_internet_connection(False),
+                shard, self.on_progress_wrapper, skip_download=True
             )
 
-        semaphore = asyncio.Semaphore(self.max_parallel_downloads)
-
-        async def download_with_semaphore(
-            model_card: ModelCard,
-        ) -> tuple[Path, RepoDownloadProgress]:
-            async with semaphore:
-                return await _status_for_model(model_card.model_id)
-
+        # Kick off download status coroutines concurrently
         tasks = [
-            create_task(download_with_semaphore(model_card))
-            for model_card in await get_model_cards()
+            asyncio.create_task(_status_for_model(model_card.model_id))
+            for model_card in MODEL_CARDS.values()
         ]
 
         for task in asyncio.as_completed(tasks):
             try:
                 yield await task
+            # TODO: except Exception
             except Exception as e:
-                logger.warning(f"Error downloading shard: {type(e).__name__}")
+                logger.error("Error downloading shard:", e)
 
     async def get_shard_download_status_for_shard(
         self, shard: ShardMetadata

src/exo/download/shard_downloader.py

@@ -16,11 +16,6 @@ from exo.shared.types.worker.shards import (
 
 # TODO: the PipelineShardMetadata getting reinstantiated is a bit messy. Should this be a classmethod?
 class ShardDownloader(ABC):
-    internet_connection: bool = False
-
-    def set_internet_connection(self, value: bool) -> None:
-        self.internet_connection = value
-
     @abstractmethod
     async def ensure_shard(
         self, shard: ShardMetadata, config_only: bool = False

src/exo/main.py

@@ -90,6 +90,7 @@ class Node:
             worker = Worker(
                 node_id,
                 session_id,
+                connection_message_receiver=router.receiver(topics.CONNECTION_MESSAGES),
                 global_event_receiver=router.receiver(topics.GLOBAL_EVENTS),
                 local_event_sender=router.sender(topics.LOCAL_EVENTS),
                 command_sender=router.sender(topics.COMMANDS),
@@ -135,22 +136,19 @@ class Node:
         )
 
     async def run(self):
-        with anyio.open_signal_receiver(signal.SIGINT, signal.SIGTERM) as signals:
-            async with self._tg as tg:
-                tg.start_soon(self.router.run)
-                tg.start_soon(self.election.run)
-                if self.download_coordinator:
-                    tg.start_soon(self.download_coordinator.run)
-                if self.worker:
-                    tg.start_soon(self.worker.run)
-                if self.master:
-                    tg.start_soon(self.master.run)
-                if self.api:
-                    tg.start_soon(self.api.run)
-                tg.start_soon(self._elect_loop)
-                async for sig in signals:
-                    self.shutdown()
-
+        async with self._tg as tg:
+            signal.signal(signal.SIGINT, lambda _, __: self.shutdown())
+            tg.start_soon(self.router.run)
+            tg.start_soon(self.election.run)
+            if self.download_coordinator:
+                tg.start_soon(self.download_coordinator.run)
+            if self.worker:
+                tg.start_soon(self.worker.run)
+            if self.master:
+                tg.start_soon(self.master.run)
+            if self.api:
+                tg.start_soon(self.api.run)
+            tg.start_soon(self._elect_loop)
 
     def shutdown(self):
         # if this is our second call to shutdown, just sys.exit
@@ -229,6 +227,9 @@ class Node:
                         self.worker = Worker(
                             self.node_id,
                             result.session_id,
+                            connection_message_receiver=self.router.receiver(
+                                topics.CONNECTION_MESSAGES
+                            ),
                             global_event_receiver=self.router.receiver(
                                 topics.GLOBAL_EVENTS
                             ),

src/exo/master/adapters/__init__.py

@@ -1 +0,0 @@
-"""API adapters for different API formats (Claude, OpenAI Responses, etc.)."""

src/exo/master/adapters/chat_completions.py

@@ -1,214 +0,0 @@
-"""OpenAI Chat Completions API adapter for converting requests/responses."""
-
-import time
-from collections.abc import AsyncGenerator
-from typing import Any
-from uuid import uuid4
-
-from exo.shared.types.api import (
-    ChatCompletionChoice,
-    ChatCompletionMessage,
-    ChatCompletionMessageText,
-    ChatCompletionRequest,
-    ChatCompletionResponse,
-    ErrorInfo,
-    ErrorResponse,
-    FinishReason,
-    StreamingChoiceResponse,
-    ToolCall,
-)
-from exo.shared.types.chunks import ErrorChunk, TokenChunk, ToolCallChunk
-from exo.shared.types.common import CommandId
-from exo.shared.types.text_generation import InputMessage, TextGenerationTaskParams
-
-
-def chat_request_to_text_generation(
-    request: ChatCompletionRequest,
-) -> TextGenerationTaskParams:
-    instructions: str | None = None
-    input_messages: list[InputMessage] = []
-    chat_template_messages: list[dict[str, Any]] = []
-
-    for msg in request.messages:
-        # Normalize content to string
-        content: str
-        if msg.content is None:
-            content = ""
-        elif isinstance(msg.content, str):
-            content = msg.content
-        elif isinstance(msg.content, ChatCompletionMessageText):
-            content = msg.content.text
-        else:
-            # List of ChatCompletionMessageText
-            content = "\n".join(item.text for item in msg.content)
-
-        # Extract system message as instructions
-        if msg.role == "system":
-            if instructions is None:
-                instructions = content
-            else:
-                # Append additional system messages
-                instructions = f"{instructions}\n{content}"
-            chat_template_messages.append({"role": "system", "content": content})
-        else:
-            # Skip messages with no meaningful content
-            if msg.content is None and msg.thinking is None and msg.tool_calls is None:
-                continue
-
-            if msg.role in ("user", "assistant", "developer"):
-                input_messages.append(InputMessage(role=msg.role, content=content))
-
-            # Build full message dict for chat template (preserves tool_calls etc.)
-            # Normalize content for model_dump
-            msg_copy = msg.model_copy(update={"content": content})
-            dumped: dict[str, Any] = msg_copy.model_dump(exclude_none=True)
-            chat_template_messages.append(dumped)
-
-    return TextGenerationTaskParams(
-        model=request.model,
-        input=input_messages
-        if input_messages
-        else [InputMessage(role="user", content="")],
-        instructions=instructions,
-        max_output_tokens=request.max_tokens,
-        temperature=request.temperature,
-        top_p=request.top_p,
-        top_k=request.top_k,
-        stop=request.stop,
-        seed=request.seed,
-        stream=request.stream,
-        tools=request.tools,
-        chat_template_messages=chat_template_messages
-        if chat_template_messages
-        else None,
-    )
-
-
-def chunk_to_response(
-    chunk: TokenChunk, command_id: CommandId
-) -> ChatCompletionResponse:
-    """Convert a TokenChunk to a streaming ChatCompletionResponse."""
-    return ChatCompletionResponse(
-        id=command_id,
-        created=int(time.time()),
-        model=chunk.model,
-        choices=[
-            StreamingChoiceResponse(
-                index=0,
-                delta=ChatCompletionMessage(role="assistant", content=chunk.text),
-                finish_reason=chunk.finish_reason,
-            )
-        ],
-    )
-
-
-async def generate_chat_stream(
-    command_id: CommandId,
-    chunk_stream: AsyncGenerator[ErrorChunk | ToolCallChunk | TokenChunk, None],
-) -> AsyncGenerator[str, None]:
-    """Generate Chat Completions API streaming events from chunks."""
-    async for chunk in chunk_stream:
-        if isinstance(chunk, ErrorChunk):
-            error_response = ErrorResponse(
-                error=ErrorInfo(
-                    message=chunk.error_message or "Internal server error",
-                    type="InternalServerError",
-                    code=500,
-                )
-            )
-            yield f"data: {error_response.model_dump_json()}\n\n"
-            yield "data: [DONE]\n\n"
-            return
-
-        if isinstance(chunk, ToolCallChunk):
-            tool_call_deltas = [
-                ToolCall(
-                    id=str(uuid4()),
-                    index=i,
-                    function=tool,
-                )
-                for i, tool in enumerate(chunk.tool_calls)
-            ]
-            tool_response = ChatCompletionResponse(
-                id=command_id,
-                created=int(time.time()),
-                model=chunk.model,
-                choices=[
-                    StreamingChoiceResponse(
-                        index=0,
-                        delta=ChatCompletionMessage(
-                            role="assistant",
-                            tool_calls=tool_call_deltas,
-                        ),
-                        finish_reason="tool_calls",
-                    )
-                ],
-            )
-            yield f"data: {tool_response.model_dump_json()}\n\n"
-            yield "data: [DONE]\n\n"
-            return
-
-        chunk_response = chunk_to_response(chunk, command_id)
-        yield f"data: {chunk_response.model_dump_json()}\n\n"
-
-        if chunk.finish_reason is not None:
-            yield "data: [DONE]\n\n"
-
-
-async def collect_chat_response(
-    command_id: CommandId,
-    chunk_stream: AsyncGenerator[ErrorChunk | ToolCallChunk | TokenChunk, None],
-) -> ChatCompletionResponse:
-    """Collect all token chunks and return a single ChatCompletionResponse."""
-    text_parts: list[str] = []
-    tool_calls: list[ToolCall] = []
-    model: str | None = None
-    finish_reason: FinishReason | None = None
-    error_message: str | None = None
-
-    async for chunk in chunk_stream:
-        if isinstance(chunk, ErrorChunk):
-            error_message = chunk.error_message or "Internal server error"
-            break
-
-        if model is None:
-            model = chunk.model
-
-        if isinstance(chunk, TokenChunk):
-            text_parts.append(chunk.text)
-
-        if isinstance(chunk, ToolCallChunk):
-            tool_calls.extend(
-                ToolCall(
-                    id=str(uuid4()),
-                    index=i,
-                    function=tool,
-                )
-                for i, tool in enumerate(chunk.tool_calls)
-            )
-
-        if chunk.finish_reason is not None:
-            finish_reason = chunk.finish_reason
-
-    if error_message is not None:
-        raise ValueError(error_message)
-
-    combined_text = "".join(text_parts)
-    assert model is not None
-
-    return ChatCompletionResponse(
-        id=command_id,
-        created=int(time.time()),
-        model=model,
-        choices=[
-            ChatCompletionChoice(
-                index=0,
-                message=ChatCompletionMessage(
-                    role="assistant",
-                    content=combined_text,
-                    tool_calls=tool_calls if tool_calls else None,
-                ),
-                finish_reason=finish_reason,
-            )
-        ],
-    )

src/exo/master/adapters/claude.py

@@ -1,323 +0,0 @@
-"""Claude Messages API adapter for converting requests/responses."""
-
-import json
-from collections.abc import AsyncGenerator
-from typing import Any
-from uuid import uuid4
-
-from exo.shared.types.api import FinishReason
-from exo.shared.types.chunks import ErrorChunk, TokenChunk, ToolCallChunk
-from exo.shared.types.claude_api import (
-    ClaudeContentBlock,
-    ClaudeContentBlockDeltaEvent,
-    ClaudeContentBlockStartEvent,
-    ClaudeContentBlockStopEvent,
-    ClaudeInputJsonDelta,
-    ClaudeMessageDelta,
-    ClaudeMessageDeltaEvent,
-    ClaudeMessageDeltaUsage,
-    ClaudeMessagesRequest,
-    ClaudeMessagesResponse,
-    ClaudeMessageStart,
-    ClaudeMessageStartEvent,
-    ClaudeMessageStopEvent,
-    ClaudeStopReason,
-    ClaudeTextBlock,
-    ClaudeTextDelta,
-    ClaudeToolResultBlock,
-    ClaudeToolUseBlock,
-    ClaudeUsage,
-)
-from exo.shared.types.common import CommandId
-from exo.shared.types.text_generation import InputMessage, TextGenerationTaskParams
-
-
-def finish_reason_to_claude_stop_reason(
-    finish_reason: FinishReason | None,
-) -> ClaudeStopReason | None:
-    """Map OpenAI finish_reason to Claude stop_reason."""
-    if finish_reason is None:
-        return None
-    mapping: dict[FinishReason, ClaudeStopReason] = {
-        "stop": "end_turn",
-        "length": "max_tokens",
-        "tool_calls": "tool_use",
-        "content_filter": "end_turn",
-        "function_call": "tool_use",
-    }
-    return mapping.get(finish_reason, "end_turn")
-
-
-def _extract_tool_result_text(block: ClaudeToolResultBlock) -> str:
-    """Extract plain text from a tool_result content field."""
-    if block.content is None:
-        return ""
-    if isinstance(block.content, str):
-        return block.content
-    return "".join(sub_block.text for sub_block in block.content)
-
-
-def claude_request_to_text_generation(
-    request: ClaudeMessagesRequest,
-) -> TextGenerationTaskParams:
-    # Handle system message
-    instructions: str | None = None
-    chat_template_messages: list[dict[str, Any]] = []
-
-    if request.system:
-        if isinstance(request.system, str):
-            instructions = request.system
-        else:
-            instructions = "".join(block.text for block in request.system)
-        chat_template_messages.append({"role": "system", "content": instructions})
-
-    # Convert messages to input
-    input_messages: list[InputMessage] = []
-    for msg in request.messages:
-        if isinstance(msg.content, str):
-            input_messages.append(InputMessage(role=msg.role, content=msg.content))
-            chat_template_messages.append({"role": msg.role, "content": msg.content})
-            continue
-
-        # Process structured content blocks
-        text_parts: list[str] = []
-        tool_calls: list[dict[str, Any]] = []
-        tool_results: list[ClaudeToolResultBlock] = []
-
-        for block in msg.content:
-            if isinstance(block, ClaudeTextBlock):
-                text_parts.append(block.text)
-            elif isinstance(block, ClaudeToolUseBlock):
-                tool_calls.append(
-                    {
-                        "id": block.id,
-                        "type": "function",
-                        "function": {
-                            "name": block.name,
-                            "arguments": json.dumps(block.input),
-                        },
-                    }
-                )
-            elif isinstance(block, ClaudeToolResultBlock):
-                tool_results.append(block)
-
-        content = "".join(text_parts)
-
-        # Build InputMessage from text content
-        if msg.role in ("user", "assistant"):
-            input_messages.append(InputMessage(role=msg.role, content=content))
-
-        # Build chat_template_messages preserving tool structure
-        if tool_calls:
-            chat_template_messages.append(
-                {"role": "assistant", "content": content, "tool_calls": tool_calls}
-            )
-        elif tool_results:
-            for tr in tool_results:
-                chat_template_messages.append(
-                    {
-                        "role": "tool",
-                        "tool_call_id": tr.tool_use_id,
-                        "content": _extract_tool_result_text(tr),
-                    }
-                )
-        else:
-            chat_template_messages.append({"role": msg.role, "content": content})
-
-    # Convert Claude tool definitions to OpenAI-style function tools
-    tools: list[dict[str, Any]] | None = None
-    if request.tools:
-        tools = [
-            {
-                "type": "function",
-                "function": {
-                    "name": tool.name,
-                    "description": tool.description or "",
-                    "parameters": tool.input_schema,
-                },
-            }
-            for tool in request.tools
-        ]
-
-    return TextGenerationTaskParams(
-        model=request.model,
-        input=input_messages
-        if input_messages
-        else [InputMessage(role="user", content="")],
-        instructions=instructions,
-        max_output_tokens=request.max_tokens,
-        temperature=request.temperature,
-        top_p=request.top_p,
-        top_k=request.top_k,
-        stop=request.stop_sequences,
-        stream=request.stream,
-        tools=tools,
-        chat_template_messages=chat_template_messages
-        if chat_template_messages
-        else None,
-    )
-
-
-async def collect_claude_response(
-    command_id: CommandId,
-    model: str,
-    chunk_stream: AsyncGenerator[ErrorChunk | ToolCallChunk | TokenChunk, None],
-) -> ClaudeMessagesResponse:
-    """Collect all token chunks and return a single ClaudeMessagesResponse."""
-    text_parts: list[str] = []
-    tool_use_blocks: list[ClaudeToolUseBlock] = []
-    stop_reason: ClaudeStopReason | None = None
-    last_stats = None
-    error_message: str | None = None
-
-    async for chunk in chunk_stream:
-        if isinstance(chunk, ErrorChunk):
-            error_message = chunk.error_message or "Internal server error"
-            break
-
-        if isinstance(chunk, ToolCallChunk):
-            for tool in chunk.tool_calls:
-                tool_use_blocks.append(
-                    ClaudeToolUseBlock(
-                        id=f"toolu_{uuid4().hex[:24]}",
-                        name=tool.name,
-                        input=json.loads(tool.arguments),  # pyright: ignore[reportAny]
-                    )
-                )
-            last_stats = chunk.stats or last_stats
-            stop_reason = "tool_use"
-            continue
-
-        text_parts.append(chunk.text)
-        last_stats = chunk.stats or last_stats
-
-        if chunk.finish_reason is not None:
-            stop_reason = finish_reason_to_claude_stop_reason(chunk.finish_reason)
-
-    if error_message is not None:
-        raise ValueError(error_message)
-
-    combined_text = "".join(text_parts)
-
-    # Build content blocks
-    content: list[ClaudeContentBlock] = []
-    if combined_text:
-        content.append(ClaudeTextBlock(text=combined_text))
-    content.extend(tool_use_blocks)
-
-    # If no content at all, include empty text block
-    if not content:
-        content.append(ClaudeTextBlock(text=""))
-
-    # Use actual usage data from stats if available
-    input_tokens = last_stats.prompt_tokens if last_stats else 0
-    output_tokens = last_stats.generation_tokens if last_stats else 0
-
-    return ClaudeMessagesResponse(
-        id=f"msg_{command_id}",
-        model=model,
-        content=content,
-        stop_reason=stop_reason,
-        usage=ClaudeUsage(
-            input_tokens=input_tokens,
-            output_tokens=output_tokens,
-        ),
-    )
-
-
-async def generate_claude_stream(
-    command_id: CommandId,
-    model: str,
-    chunk_stream: AsyncGenerator[ErrorChunk | ToolCallChunk | TokenChunk, None],
-) -> AsyncGenerator[str, None]:
-    """Generate Claude Messages API streaming events from TokenChunks."""
-    # Initial message_start event
-    initial_message = ClaudeMessageStart(
-        id=f"msg_{command_id}",
-        model=model,
-        content=[],
-        stop_reason=None,
-        usage=ClaudeUsage(input_tokens=0, output_tokens=0),
-    )
-    start_event = ClaudeMessageStartEvent(message=initial_message)
-    yield f"event: message_start\ndata: {start_event.model_dump_json()}\n\n"
-
-    # content_block_start for text block at index 0
-    block_start = ClaudeContentBlockStartEvent(
-        index=0, content_block=ClaudeTextBlock(text="")
-    )
-    yield f"event: content_block_start\ndata: {block_start.model_dump_json()}\n\n"
-
-    output_tokens = 0
-    stop_reason: ClaudeStopReason | None = None
-    last_stats = None
-    next_block_index = 1  # text block is 0, tool blocks start at 1
-
-    async for chunk in chunk_stream:
-        if isinstance(chunk, ErrorChunk):
-            # Close text block and bail
-            break
-
-        if isinstance(chunk, ToolCallChunk):
-            last_stats = chunk.stats or last_stats
-            stop_reason = "tool_use"
-
-            # Emit tool_use content blocks
-            for tool in chunk.tool_calls:
-                tool_id = f"toolu_{uuid4().hex[:24]}"
-                tool_input_json = tool.arguments
-
-                # content_block_start for tool_use
-                tool_block_start = ClaudeContentBlockStartEvent(
-                    index=next_block_index,
-                    content_block=ClaudeToolUseBlock(
-                        id=tool_id, name=tool.name, input={}
-                    ),
-                )
-                yield f"event: content_block_start\ndata: {tool_block_start.model_dump_json()}\n\n"
-
-                # content_block_delta with input_json_delta
-                tool_delta_event = ClaudeContentBlockDeltaEvent(
-                    index=next_block_index,
-                    delta=ClaudeInputJsonDelta(partial_json=tool_input_json),
-                )
-                yield f"event: content_block_delta\ndata: {tool_delta_event.model_dump_json()}\n\n"
-
-                # content_block_stop
-                tool_block_stop = ClaudeContentBlockStopEvent(index=next_block_index)
-                yield f"event: content_block_stop\ndata: {tool_block_stop.model_dump_json()}\n\n"
-
-                next_block_index += 1
-            continue
-
-        output_tokens += 1  # Count each chunk as one token
-        last_stats = chunk.stats or last_stats
-
-        # content_block_delta
-        delta_event = ClaudeContentBlockDeltaEvent(
-            index=0,
-            delta=ClaudeTextDelta(text=chunk.text),
-        )
-        yield f"event: content_block_delta\ndata: {delta_event.model_dump_json()}\n\n"
-
-        if chunk.finish_reason is not None:
-            stop_reason = finish_reason_to_claude_stop_reason(chunk.finish_reason)
-
-    # Use actual token count from stats if available
-    if last_stats is not None:
-        output_tokens = last_stats.generation_tokens
-
-    # content_block_stop for text block
-    block_stop = ClaudeContentBlockStopEvent(index=0)
-    yield f"event: content_block_stop\ndata: {block_stop.model_dump_json()}\n\n"
-
-    # message_delta
-    message_delta = ClaudeMessageDeltaEvent(
-        delta=ClaudeMessageDelta(stop_reason=stop_reason),
-        usage=ClaudeMessageDeltaUsage(output_tokens=output_tokens),
-    )
-    yield f"event: message_delta\ndata: {message_delta.model_dump_json()}\n\n"
-
-    # message_stop
-    message_stop = ClaudeMessageStopEvent()
-    yield f"event: message_stop\ndata: {message_stop.model_dump_json()}\n\n"

src/exo/master/adapters/responses.py

@@ -1,373 +0,0 @@
-"""OpenAI Responses API adapter for converting requests/responses."""
-
-from collections.abc import AsyncGenerator
-from itertools import count
-from typing import Any
-from uuid import uuid4
-
-from exo.shared.types.chunks import ErrorChunk, TokenChunk, ToolCallChunk
-from exo.shared.types.common import CommandId
-from exo.shared.types.openai_responses import (
-    FunctionCallInputItem,
-    ResponseCompletedEvent,
-    ResponseContentPart,
-    ResponseContentPartAddedEvent,
-    ResponseContentPartDoneEvent,
-    ResponseCreatedEvent,
-    ResponseFunctionCallArgumentsDeltaEvent,
-    ResponseFunctionCallArgumentsDoneEvent,
-    ResponseFunctionCallItem,
-    ResponseInProgressEvent,
-    ResponseInputMessage,
-    ResponseItem,
-    ResponseMessageItem,
-    ResponseOutputItemAddedEvent,
-    ResponseOutputItemDoneEvent,
-    ResponseOutputText,
-    ResponsesRequest,
-    ResponsesResponse,
-    ResponseTextDeltaEvent,
-    ResponseTextDoneEvent,
-    ResponseUsage,
-)
-from exo.shared.types.text_generation import InputMessage, TextGenerationTaskParams
-
-
-def _extract_content(content: str | list[ResponseContentPart]) -> str:
-    """Extract plain text from a content field that may be a string or list of parts."""
-    if isinstance(content, str):
-        return content
-    return "".join(part.text for part in content)
-
-
-def responses_request_to_text_generation(
-    request: ResponsesRequest,
-) -> TextGenerationTaskParams:
-    input_value: list[InputMessage]
-    built_chat_template: list[dict[str, Any]] | None = None
-    if isinstance(request.input, str):
-        input_value = [InputMessage(role="user", content=request.input)]
-    else:
-        input_messages: list[InputMessage] = []
-        chat_template_messages: list[dict[str, Any]] = []
-
-        if request.instructions is not None:
-            chat_template_messages.append(
-                {"role": "system", "content": request.instructions}
-            )
-
-        for item in request.input:
-            if isinstance(item, ResponseInputMessage):
-                content = _extract_content(item.content)
-                if item.role in ("user", "assistant", "developer"):
-                    input_messages.append(InputMessage(role=item.role, content=content))
-                if item.role == "system":
-                    chat_template_messages.append(
-                        {"role": "system", "content": content}
-                    )
-                else:
-                    chat_template_messages.append(
-                        {"role": item.role, "content": content}
-                    )
-            elif isinstance(item, FunctionCallInputItem):
-                chat_template_messages.append(
-                    {
-                        "role": "assistant",
-                        "content": "",
-                        "tool_calls": [
-                            {
-                                "id": item.call_id,
-                                "type": "function",
-                                "function": {
-                                    "name": item.name,
-                                    "arguments": item.arguments,
-                                },
-                            }
-                        ],
-                    }
-                )
-            else:
-                chat_template_messages.append(
-                    {
-                        "role": "tool",
-                        "tool_call_id": item.call_id,
-                        "content": item.output,
-                    }
-                )
-
-        input_value = (
-            input_messages
-            if input_messages
-            else [InputMessage(role="user", content="")]
-        )
-        built_chat_template = chat_template_messages if chat_template_messages else None
-
-    return TextGenerationTaskParams(
-        model=request.model,
-        input=input_value,
-        instructions=request.instructions,
-        max_output_tokens=request.max_output_tokens,
-        temperature=request.temperature,
-        top_p=request.top_p,
-        stream=request.stream,
-        tools=request.tools,
-        top_k=request.top_k,
-        stop=request.stop,
-        seed=request.seed,
-        chat_template_messages=built_chat_template or request.chat_template_messages,
-    )
-
-
-async def collect_responses_response(
-    command_id: CommandId,
-    model: str,
-    chunk_stream: AsyncGenerator[ErrorChunk | ToolCallChunk | TokenChunk, None],
-) -> ResponsesResponse:
-    """Collect all token chunks and return a single ResponsesResponse."""
-    response_id = f"resp_{command_id}"
-    item_id = f"item_{command_id}"
-    accumulated_text = ""
-    function_call_items: list[ResponseFunctionCallItem] = []
-    last_stats = None
-    error_message: str | None = None
-
-    async for chunk in chunk_stream:
-        if isinstance(chunk, ErrorChunk):
-            error_message = chunk.error_message or "Internal server error"
-            break
-
-        if isinstance(chunk, ToolCallChunk):
-            for tool in chunk.tool_calls:
-                function_call_items.append(
-                    ResponseFunctionCallItem(
-                        id=f"fc_{uuid4().hex[:24]}",
-                        call_id=f"call_{uuid4().hex[:24]}",
-                        name=tool.name,
-                        arguments=tool.arguments,
-                    )
-                )
-            last_stats = chunk.stats or last_stats
-            continue
-
-        accumulated_text += chunk.text
-        last_stats = chunk.stats or last_stats
-
-    if error_message is not None:
-        raise ValueError(error_message)
-
-    # Create usage from stats if available
-    usage = None
-    if last_stats is not None:
-        usage = ResponseUsage(
-            input_tokens=last_stats.prompt_tokens,
-            output_tokens=last_stats.generation_tokens,
-            total_tokens=last_stats.prompt_tokens + last_stats.generation_tokens,
-        )
-
-    output: list[ResponseItem] = [
-        ResponseMessageItem(
-            id=item_id,
-            content=[ResponseOutputText(text=accumulated_text)],
-            status="completed",
-        )
-    ]
-    output.extend(function_call_items)
-
-    return ResponsesResponse(
-        id=response_id,
-        model=model,
-        status="completed",
-        output=output,
-        output_text=accumulated_text,
-        usage=usage,
-    )
-
-
-async def generate_responses_stream(
-    command_id: CommandId,
-    model: str,
-    chunk_stream: AsyncGenerator[ErrorChunk | ToolCallChunk | TokenChunk, None],
-) -> AsyncGenerator[str, None]:
-    """Generate OpenAI Responses API streaming events from TokenChunks."""
-    response_id = f"resp_{command_id}"
-    item_id = f"item_{command_id}"
-    seq = count(1)
-
-    # response.created
-    initial_response = ResponsesResponse(
-        id=response_id,
-        model=model,
-        status="in_progress",
-        output=[],
-        output_text="",
-    )
-    created_event = ResponseCreatedEvent(
-        sequence_number=next(seq), response=initial_response
-    )
-    yield f"event: response.created\ndata: {created_event.model_dump_json()}\n\n"
-
-    # response.in_progress
-    in_progress_event = ResponseInProgressEvent(
-        sequence_number=next(seq), response=initial_response
-    )
-    yield f"event: response.in_progress\ndata: {in_progress_event.model_dump_json()}\n\n"
-
-    # response.output_item.added
-    initial_item = ResponseMessageItem(
-        id=item_id,
-        content=[ResponseOutputText(text="")],
-        status="in_progress",
-    )
-    item_added = ResponseOutputItemAddedEvent(
-        sequence_number=next(seq), output_index=0, item=initial_item
-    )
-    yield f"event: response.output_item.added\ndata: {item_added.model_dump_json()}\n\n"
-
-    # response.content_part.added
-    initial_part = ResponseOutputText(text="")
-    part_added = ResponseContentPartAddedEvent(
-        sequence_number=next(seq),
-        item_id=item_id,
-        output_index=0,
-        content_index=0,
-        part=initial_part,
-    )
-    yield f"event: response.content_part.added\ndata: {part_added.model_dump_json()}\n\n"
-
-    accumulated_text = ""
-    function_call_items: list[ResponseFunctionCallItem] = []
-    last_stats = None
-    next_output_index = 1  # message item is at 0
-
-    async for chunk in chunk_stream:
-        if isinstance(chunk, ErrorChunk):
-            break
-
-        if isinstance(chunk, ToolCallChunk):
-            last_stats = chunk.stats or last_stats
-            for tool in chunk.tool_calls:
-                fc_id = f"fc_{uuid4().hex[:24]}"
-                call_id = f"call_{uuid4().hex[:24]}"
-
-                # response.output_item.added for function_call
-                fc_item = ResponseFunctionCallItem(
-                    id=fc_id,
-                    call_id=call_id,
-                    name=tool.name,
-                    arguments="",
-                    status="in_progress",
-                )
-                fc_added = ResponseOutputItemAddedEvent(
-                    sequence_number=next(seq),
-                    output_index=next_output_index,
-                    item=fc_item,
-                )
-                yield f"event: response.output_item.added\ndata: {fc_added.model_dump_json()}\n\n"
-
-                # response.function_call_arguments.delta
-                args_delta = ResponseFunctionCallArgumentsDeltaEvent(
-                    sequence_number=next(seq),
-                    item_id=fc_id,
-                    output_index=next_output_index,
-                    delta=tool.arguments,
-                )
-                yield f"event: response.function_call_arguments.delta\ndata: {args_delta.model_dump_json()}\n\n"
-
-                # response.function_call_arguments.done
-                args_done = ResponseFunctionCallArgumentsDoneEvent(
-                    sequence_number=next(seq),
-                    item_id=fc_id,
-                    output_index=next_output_index,
-                    name=tool.name,
-                    arguments=tool.arguments,
-                )
-                yield f"event: response.function_call_arguments.done\ndata: {args_done.model_dump_json()}\n\n"
-
-                # response.output_item.done
-                fc_done_item = ResponseFunctionCallItem(
-                    id=fc_id,
-                    call_id=call_id,
-                    name=tool.name,
-                    arguments=tool.arguments,
-                    status="completed",
-                )
-                fc_item_done = ResponseOutputItemDoneEvent(
-                    sequence_number=next(seq),
-                    output_index=next_output_index,
-                    item=fc_done_item,
-                )
-                yield f"event: response.output_item.done\ndata: {fc_item_done.model_dump_json()}\n\n"
-
-                function_call_items.append(fc_done_item)
-                next_output_index += 1
-            continue
-
-        accumulated_text += chunk.text
-        last_stats = chunk.stats or last_stats
-
-        # response.output_text.delta
-        delta_event = ResponseTextDeltaEvent(
-            sequence_number=next(seq),
-            item_id=item_id,
-            output_index=0,
-            content_index=0,
-            delta=chunk.text,
-        )
-        yield f"event: response.output_text.delta\ndata: {delta_event.model_dump_json()}\n\n"
-
-    # response.output_text.done
-    text_done = ResponseTextDoneEvent(
-        sequence_number=next(seq),
-        item_id=item_id,
-        output_index=0,
-        content_index=0,
-        text=accumulated_text,
-    )
-    yield f"event: response.output_text.done\ndata: {text_done.model_dump_json()}\n\n"
-
-    # response.content_part.done
-    final_part = ResponseOutputText(text=accumulated_text)
-    part_done = ResponseContentPartDoneEvent(
-        sequence_number=next(seq),
-        item_id=item_id,
-        output_index=0,
-        content_index=0,
-        part=final_part,
-    )
-    yield f"event: response.content_part.done\ndata: {part_done.model_dump_json()}\n\n"
-
-    # response.output_item.done
-    final_message_item = ResponseMessageItem(
-        id=item_id,
-        content=[ResponseOutputText(text=accumulated_text)],
-        status="completed",
-    )
-    item_done = ResponseOutputItemDoneEvent(
-        sequence_number=next(seq), output_index=0, item=final_message_item
-    )
-    yield f"event: response.output_item.done\ndata: {item_done.model_dump_json()}\n\n"
-
-    # Create usage from stats if available
-    usage = None
-    if last_stats is not None:
-        usage = ResponseUsage(
-            input_tokens=last_stats.prompt_tokens,
-            output_tokens=last_stats.generation_tokens,
-            total_tokens=last_stats.prompt_tokens + last_stats.generation_tokens,
-        )
-
-    # response.completed
-    output: list[ResponseItem] = [final_message_item]
-    output.extend(function_call_items)
-    final_response = ResponsesResponse(
-        id=response_id,
-        model=model,
-        status="completed",
-        output=output,
-        output_text=accumulated_text,
-        usage=usage,
-    )
-    completed_event = ResponseCompletedEvent(
-        sequence_number=next(seq), response=final_response
-    )
-    yield f"event: response.completed\ndata: {completed_event.model_dump_json()}\n\n"

src/exo/master/main.py

@@ -11,8 +11,8 @@ from exo.master.placement import (
     place_instance,
 )
 from exo.shared.apply import apply
-from exo.shared.constants import EXO_TRACING_ENABLED
 from exo.shared.types.commands import (
+    ChatCompletion,
     CreateInstance,
     DeleteInstance,
     ForwarderCommand,
@@ -23,7 +23,6 @@ from exo.shared.types.commands import (
     SendInputChunk,
     TaskFinished,
     TestCommand,
-    TextGeneration,
 )
 from exo.shared.types.common import CommandId, NodeId, SessionId
 from exo.shared.types.events import (
@@ -36,11 +35,11 @@ from exo.shared.types.events import (
     NodeTimedOut,
     TaskCreated,
     TaskDeleted,
-    TraceEventData,
-    TracesCollected,
-    TracesMerged,
 )
 from exo.shared.types.state import State
+from exo.shared.types.tasks import (
+    ChatCompletion as ChatCompletionTask,
+)
 from exo.shared.types.tasks import (
     ImageEdits as ImageEditsTask,
 )
@@ -51,9 +50,6 @@ from exo.shared.types.tasks import (
     TaskId,
     TaskStatus,
 )
-from exo.shared.types.tasks import (
-    TextGeneration as TextGenerationTask,
-)
 from exo.shared.types.worker.instances import InstanceId
 from exo.utils.channels import Receiver, Sender, channel
 from exo.utils.event_buffer import MultiSourceBuffer
@@ -90,24 +86,20 @@ class Master:
         self._multi_buffer = MultiSourceBuffer[NodeId, Event]()
         # TODO: not have this
         self._event_log: list[Event] = []
-        self._pending_traces: dict[TaskId, dict[int, list[TraceEventData]]] = {}
-        self._expected_ranks: dict[TaskId, set[int]] = {}
 
     async def run(self):
         logger.info("Starting Master")
 
-        try:
-            async with self._tg as tg:
-                tg.start_soon(self._event_processor)
-                tg.start_soon(self._command_processor)
-                tg.start_soon(self._loopback_processor)
-                tg.start_soon(self._plan)
-        finally:
-            self.global_event_sender.close()
-            self.local_event_receiver.close()
-            self.command_receiver.close()
-            self._loopback_event_sender.close()
-            self._loopback_event_receiver.close()
+        async with self._tg as tg:
+            tg.start_soon(self._event_processor)
+            tg.start_soon(self._command_processor)
+            tg.start_soon(self._loopback_processor)
+            tg.start_soon(self._plan)
+        self.global_event_sender.close()
+        self.local_event_receiver.close()
+        self.command_receiver.close()
+        self._loopback_event_sender.close()
+        self._loopback_event_receiver.close()
 
     async def shutdown(self):
         logger.info("Stopping Master")
@@ -125,11 +117,11 @@ class Master:
                     match command:
                         case TestCommand():
                             pass
-                        case TextGeneration():
+                        case ChatCompletion():
                             for instance in self.state.instances.values():
                                 if (
                                     instance.shard_assignments.model_id
-                                    == command.task_params.model
+                                    == command.request_params.model
                                 ):
                                     task_count = sum(
                                         1
@@ -142,7 +134,7 @@ class Master:
 
                             if not instance_task_counts:
                                 raise ValueError(
-                                    f"No instance found for model {command.task_params.model}"
+                                    f"No instance found for model {command.request_params.model}"
                                 )
 
                             available_instance_ids = sorted(
@@ -156,12 +148,12 @@ class Master:
                             generated_events.append(
                                 TaskCreated(
                                     task_id=task_id,
-                                    task=TextGenerationTask(
+                                    task=ChatCompletionTask(
                                         task_id=task_id,
                                         command_id=command.command_id,
                                         instance_id=available_instance_ids[0],
                                         task_status=TaskStatus.Pending,
-                                        task_params=command.task_params,
+                                        task_params=command.request_params,
                                     ),
                                 )
                             )
@@ -171,7 +163,7 @@ class Master:
                             for instance in self.state.instances.values():
                                 if (
                                     instance.shard_assignments.model_id
-                                    == command.task_params.model
+                                    == command.request_params.model
                                 ):
                                     task_count = sum(
                                         1
@@ -184,7 +176,7 @@ class Master:
 
                             if not instance_task_counts:
                                 raise ValueError(
-                                    f"No instance found for model {command.task_params.model}"
+                                    f"No instance found for model {command.request_params.model}"
                                 )
 
                             available_instance_ids = sorted(
@@ -195,37 +187,25 @@ class Master:
                             )
 
                             task_id = TaskId()
-                            selected_instance_id = available_instance_ids[0]
                             generated_events.append(
                                 TaskCreated(
                                     task_id=task_id,
                                     task=ImageGenerationTask(
                                         task_id=task_id,
                                         command_id=command.command_id,
-                                        instance_id=selected_instance_id,
+                                        instance_id=available_instance_ids[0],
                                         task_status=TaskStatus.Pending,
-                                        task_params=command.task_params,
+                                        task_params=command.request_params,
                                     ),
                                 )
                             )
 
                             self.command_task_mapping[command.command_id] = task_id
-
-                            if EXO_TRACING_ENABLED:
-                                selected_instance = self.state.instances.get(
-                                    selected_instance_id
-                                )
-                                if selected_instance:
-                                    ranks = set(
-                                        shard.device_rank
-                                        for shard in selected_instance.shard_assignments.runner_to_shard.values()
-                                    )
-                                    self._expected_ranks[task_id] = ranks
                         case ImageEdits():
                             for instance in self.state.instances.values():
                                 if (
                                     instance.shard_assignments.model_id
-                                    == command.task_params.model
+                                    == command.request_params.model
                                 ):
                                     task_count = sum(
                                         1
@@ -238,7 +218,7 @@ class Master:
 
                             if not instance_task_counts:
                                 raise ValueError(
-                                    f"No instance found for model {command.task_params.model}"
+                                    f"No instance found for model {command.request_params.model}"
                                 )
 
                             available_instance_ids = sorted(
@@ -249,32 +229,20 @@ class Master:
                             )
 
                             task_id = TaskId()
-                            selected_instance_id = available_instance_ids[0]
                             generated_events.append(
                                 TaskCreated(
                                     task_id=task_id,
                                     task=ImageEditsTask(
                                         task_id=task_id,
                                         command_id=command.command_id,
-                                        instance_id=selected_instance_id,
+                                        instance_id=available_instance_ids[0],
                                         task_status=TaskStatus.Pending,
-                                        task_params=command.task_params,
+                                        task_params=command.request_params,
                                     ),
                                 )
                             )
 
                             self.command_task_mapping[command.command_id] = task_id
-
-                            if EXO_TRACING_ENABLED:
-                                selected_instance = self.state.instances.get(
-                                    selected_instance_id
-                                )
-                                if selected_instance:
-                                    ranks = set(
-                                        shard.device_rank
-                                        for shard in selected_instance.shard_assignments.runner_to_shard.values()
-                                    )
-                                    self._expected_ranks[task_id] = ranks
                         case DeleteInstance():
                             placement = delete_instance(command, self.state.instances)
                             transition_events = get_transition_events(
@@ -367,10 +335,6 @@ class Master:
                     local_event.origin,
                 )
                 for event in self._multi_buffer.drain():
-                    if isinstance(event, TracesCollected):
-                        await self._handle_traces_collected(event)
-                        continue
-
                     logger.debug(f"Master indexing event: {str(event)[:100]}")
                     indexed = IndexedEvent(event=event, idx=len(self._event_log))
                     self.state = apply(self.state, indexed)
@@ -409,29 +373,3 @@ class Master:
                 event=event.event,
             )
         )
-
-    async def _handle_traces_collected(self, event: TracesCollected) -> None:
-        task_id = event.task_id
-        if task_id not in self._pending_traces:
-            self._pending_traces[task_id] = {}
-        self._pending_traces[task_id][event.rank] = event.traces
-
-        if (
-            task_id in self._expected_ranks
-            and set(self._pending_traces[task_id].keys())
-            >= self._expected_ranks[task_id]
-        ):
-            await self._merge_and_save_traces(task_id)
-
-    async def _merge_and_save_traces(self, task_id: TaskId) -> None:
-        all_trace_data: list[TraceEventData] = []
-        for trace_data in self._pending_traces[task_id].values():
-            all_trace_data.extend(trace_data)
-
-        await self.event_sender.send(
-            TracesMerged(task_id=task_id, traces=all_trace_data)
-        )
-
-        del self._pending_traces[task_id]
-        if task_id in self._expected_ranks:
-            del self._expected_ranks[task_id]

src/exo/master/placement_utils.py

@@ -10,7 +10,6 @@ from exo.shared.types.profiling import MemoryUsage, NodeNetworkInfo
 from exo.shared.types.topology import Cycle, RDMAConnection, SocketConnection
 from exo.shared.types.worker.runners import RunnerId, ShardAssignments
 from exo.shared.types.worker.shards import (
-    CfgShardMetadata,
     PipelineShardMetadata,
     Sharding,
     ShardMetadata,
@@ -75,43 +74,40 @@ def allocate_layers_proportionally(
     return result
 
 
-def _validate_cycle(cycle: Cycle) -> None:
+def get_shard_assignments_for_pipeline_parallel(
+    model_card: ModelCard,
+    cycle: Cycle,
+    node_memory: Mapping[NodeId, MemoryUsage],
+):
     if not cycle.node_ids:
         raise ValueError("Cannot create shard assignments for empty node cycle")
 
-
-def _compute_total_memory(
-    node_ids: list[NodeId],
-    node_memory: Mapping[NodeId, MemoryUsage],
-) -> Memory:
-    total_memory = sum(
-        (node_memory[node_id].ram_available for node_id in node_ids),
+    cycle_memory = sum(
+        (node_memory[node_id].ram_available for node_id in cycle.node_ids),
         start=Memory(),
     )
-    if total_memory.in_bytes == 0:
+    if cycle_memory.in_bytes == 0:
         raise ValueError("Cannot create shard assignments: total available memory is 0")
-    return total_memory
 
+    total_layers = model_card.n_layers
+    world_size = len(cycle)
+    runner_to_shard: dict[RunnerId, ShardMetadata] = {}
+    node_to_runner: dict[NodeId, RunnerId] = {}
 
-def _allocate_and_validate_layers(
-    node_ids: list[NodeId],
-    node_memory: Mapping[NodeId, MemoryUsage],
-    total_memory: Memory,
-    model_card: ModelCard,
-) -> list[int]:
     layer_allocations = allocate_layers_proportionally(
-        total_layers=model_card.n_layers,
+        total_layers=total_layers,
         memory_fractions=[
-            node_memory[node_id].ram_available.in_bytes / total_memory.in_bytes
-            for node_id in node_ids
+            node_memory[node_id].ram_available.in_bytes / cycle_memory.in_bytes
+            for node_id in cycle.node_ids
         ],
     )
 
-    total_storage_bytes = model_card.storage_size.in_bytes
-    total_layers = model_card.n_layers
-    for i, node_id in enumerate(node_ids):
-        node_layers = layer_allocations[i]
-        required_memory = (total_storage_bytes * node_layers) // total_layers
+    # Validate each node has sufficient memory for its assigned layers
+    memory_per_layer = model_card.storage_size.in_bytes / total_layers
+    for i, (node_id, node_layers) in enumerate(
+        zip(cycle.node_ids, layer_allocations, strict=True)
+    ):
+        required_memory = node_layers * memory_per_layer
         available_memory = node_memory[node_id].ram_available.in_bytes
         if required_memory > available_memory:
             raise ValueError(
@@ -120,126 +116,33 @@ def _allocate_and_validate_layers(
                 f"but only has {available_memory / (1024**3):.2f} GB available"
             )
 
-    return layer_allocations
-
-
-def get_shard_assignments_for_pipeline_parallel(
-    model_card: ModelCard,
-    cycle: Cycle,
-    node_memory: Mapping[NodeId, MemoryUsage],
-) -> ShardAssignments:
-    """Create shard assignments for pipeline parallel execution."""
-    world_size = len(cycle)
-    use_cfg_parallel = model_card.uses_cfg and world_size >= 2 and world_size % 2 == 0
-
-    if use_cfg_parallel:
-        return _get_shard_assignments_for_cfg_parallel(model_card, cycle, node_memory)
-    else:
-        return _get_shard_assignments_for_pure_pipeline(model_card, cycle, node_memory)
-
-
-def _get_shard_assignments_for_cfg_parallel(
-    model_card: ModelCard,
-    cycle: Cycle,
-    node_memory: Mapping[NodeId, MemoryUsage],
-) -> ShardAssignments:
-    """Create shard assignments for CFG parallel execution.
-
-    CFG parallel runs two independent pipelines. Group 0 processes the positive
-    prompt, group 1 processes the negative prompt. The ring topology places
-    group 1's ranks in reverse order so both "last stages" are neighbors for
-    efficient CFG exchange.
-    """
-    _validate_cycle(cycle)
-
-    world_size = len(cycle)
-    cfg_world_size = 2
-    pipeline_world_size = world_size // cfg_world_size
-
-    # Allocate layers for one pipeline group (both groups run the same layers)
-    pipeline_node_ids = cycle.node_ids[:pipeline_world_size]
-    pipeline_memory = _compute_total_memory(pipeline_node_ids, node_memory)
-    layer_allocations = _allocate_and_validate_layers(
-        pipeline_node_ids, node_memory, pipeline_memory, model_card
-    )
-
-    # Ring topology: group 0 ascending [0,1,2,...], group 1 descending [...,2,1,0]
-    # This places both last stages as neighbors for CFG exchange.
-    position_to_cfg_pipeline = [(0, r) for r in range(pipeline_world_size)] + [
-        (1, r) for r in reversed(range(pipeline_world_size))
-    ]
-
-    runner_to_shard: dict[RunnerId, ShardMetadata] = {}
-    node_to_runner: dict[NodeId, RunnerId] = {}
-
-    for device_rank, node_id in enumerate(cycle.node_ids):
-        cfg_rank, pipeline_rank = position_to_cfg_pipeline[device_rank]
-        layers_before = sum(layer_allocations[:pipeline_rank])
-        node_layers = layer_allocations[pipeline_rank]
-
-        shard = CfgShardMetadata(
-            model_card=model_card,
-            device_rank=device_rank,
-            world_size=world_size,
-            start_layer=layers_before,
-            end_layer=layers_before + node_layers,
-            n_layers=model_card.n_layers,
-            cfg_rank=cfg_rank,
-            cfg_world_size=cfg_world_size,
-            pipeline_rank=pipeline_rank,
-            pipeline_world_size=pipeline_world_size,
-        )
-
+    layers_assigned = 0
+    for i, (node_id, node_layers) in enumerate(
+        zip(cycle.node_ids, layer_allocations, strict=True)
+    ):
         runner_id = RunnerId()
-        runner_to_shard[runner_id] = shard
-        node_to_runner[node_id] = runner_id
-
-    return ShardAssignments(
-        model_id=model_card.model_id,
-        runner_to_shard=runner_to_shard,
-        node_to_runner=node_to_runner,
-    )
-
-
-def _get_shard_assignments_for_pure_pipeline(
-    model_card: ModelCard,
-    cycle: Cycle,
-    node_memory: Mapping[NodeId, MemoryUsage],
-) -> ShardAssignments:
-    """Create shard assignments for pure pipeline execution."""
-    _validate_cycle(cycle)
-    total_memory = _compute_total_memory(cycle.node_ids, node_memory)
-
-    layer_allocations = _allocate_and_validate_layers(
-        cycle.node_ids, node_memory, total_memory, model_card
-    )
-
-    runner_to_shard: dict[RunnerId, ShardMetadata] = {}
-    node_to_runner: dict[NodeId, RunnerId] = {}
-
-    for pipeline_rank, node_id in enumerate(cycle.node_ids):
-        layers_before = sum(layer_allocations[:pipeline_rank])
-        node_layers = layer_allocations[pipeline_rank]
 
         shard = PipelineShardMetadata(
             model_card=model_card,
-            device_rank=pipeline_rank,
-            world_size=len(cycle),
-            start_layer=layers_before,
-            end_layer=layers_before + node_layers,
-            n_layers=model_card.n_layers,
+            device_rank=i,
+            world_size=world_size,
+            start_layer=layers_assigned,
+            end_layer=layers_assigned + node_layers,
+            n_layers=total_layers,
         )
 
-        runner_id = RunnerId()
         runner_to_shard[runner_id] = shard
         node_to_runner[node_id] = runner_id
+        layers_assigned += node_layers
 
-    return ShardAssignments(
+    shard_assignments = ShardAssignments(
         model_id=model_card.model_id,
         runner_to_shard=runner_to_shard,
         node_to_runner=node_to_runner,
     )
 
+    return shard_assignments
+
 
 def get_shard_assignments_for_tensor_parallel(
     model_card: ModelCard,
@@ -342,10 +245,13 @@ def _find_ip_prioritised(
     other_node_id: NodeId,
     cycle_digraph: Topology,
     node_network: Mapping[NodeId, NodeNetworkInfo],
+    *,
+    prefer_thunderbolt: bool = False,
 ) -> str | None:
     """Find an IP address between nodes with prioritization.
 
-    Priority: ethernet > wifi > unknown > thunderbolt
+    Default priority: ethernet > wifi > unknown > maybe_ethernet > thunderbolt
+    With prefer_thunderbolt: thunderbolt/link-local > ethernet > wifi > unknown > maybe_ethernet
     """
     ips = list(_find_connection_ip(node_id, other_node_id, cycle_digraph))
     if not ips:
@@ -354,14 +260,33 @@ def _find_ip_prioritised(
     ip_to_type = {
         iface.ip_address: iface.interface_type for iface in other_network.interfaces
     }
-    priority = {
-        "ethernet": 0,
-        "wifi": 1,
-        "unknown": 2,
-        "maybe_ethernet": 3,
-        "thunderbolt": 4,
-    }
-    return min(ips, key=lambda ip: priority.get(ip_to_type.get(ip, "unknown"), 2))
+
+    def get_priority(ip: str) -> int:
+        interface_type = ip_to_type.get(ip, "unknown")
+        if prefer_thunderbolt:
+            # Link-local IPs (169.254.x.x) on maybe_ethernet are likely Thunderbolt
+            # TODO: This is a hack - fix this.
+            if interface_type == "maybe_ethernet" and ip.startswith("169.254."):
+                return 0
+            priority = {
+                "thunderbolt": 0,
+                "ethernet": 1,
+                "wifi": 2,
+                "unknown": 3,
+                "maybe_ethernet": 4,
+            }
+            return priority.get(interface_type, 3)
+        else:
+            priority = {
+                "ethernet": 0,
+                "wifi": 1,
+                "unknown": 2,
+                "maybe_ethernet": 3,
+                "thunderbolt": 4,
+            }
+            return priority.get(interface_type, 2)
+
+    return min(ips, key=get_priority)
 
 
 def get_mlx_ring_hosts_by_node(
@@ -400,7 +325,8 @@ def get_mlx_ring_hosts_by_node(
                 continue
 
             connection_ip = _find_ip_prioritised(
-                node_id, other_node_id, cycle_digraph, node_network
+                node_id, other_node_id, cycle_digraph, node_network,
+                prefer_thunderbolt=True,
             )
             if connection_ip is None:
                 raise ValueError(

src/exo/master/tests/test_claude_api.py

@@ -1,182 +0,0 @@
-"""Tests for Claude Messages API conversion functions and types."""
-
-import pydantic
-import pytest
-
-from exo.master.adapters.claude import (
-    claude_request_to_text_generation,
-    finish_reason_to_claude_stop_reason,
-)
-from exo.shared.types.claude_api import (
-    ClaudeMessage,
-    ClaudeMessagesRequest,
-    ClaudeTextBlock,
-)
-from exo.shared.types.common import ModelId
-
-
-class TestFinishReasonToClaudeStopReason:
-    """Tests for finish_reason to Claude stop_reason mapping."""
-
-    def test_stop_maps_to_end_turn(self):
-        assert finish_reason_to_claude_stop_reason("stop") == "end_turn"
-
-    def test_length_maps_to_max_tokens(self):
-        assert finish_reason_to_claude_stop_reason("length") == "max_tokens"
-
-    def test_tool_calls_maps_to_tool_use(self):
-        assert finish_reason_to_claude_stop_reason("tool_calls") == "tool_use"
-
-    def test_function_call_maps_to_tool_use(self):
-        assert finish_reason_to_claude_stop_reason("function_call") == "tool_use"
-
-    def test_content_filter_maps_to_end_turn(self):
-        assert finish_reason_to_claude_stop_reason("content_filter") == "end_turn"
-
-    def test_none_returns_none(self):
-        assert finish_reason_to_claude_stop_reason(None) is None
-
-
-class TestClaudeRequestToInternal:
-    """Tests for converting Claude Messages API requests to TextGenerationTaskParams."""
-
-    def test_basic_request_conversion(self):
-        request = ClaudeMessagesRequest(
-            model=ModelId("claude-3-opus"),
-            max_tokens=100,
-            messages=[
-                ClaudeMessage(role="user", content="Hello"),
-            ],
-        )
-        params = claude_request_to_text_generation(request)
-
-        assert params.model == "claude-3-opus"
-        assert params.max_output_tokens == 100
-        assert isinstance(params.input, list)
-        assert len(params.input) == 1
-        assert params.input[0].role == "user"
-        assert params.input[0].content == "Hello"
-        assert params.instructions is None
-
-    def test_request_with_system_string(self):
-        request = ClaudeMessagesRequest(
-            model=ModelId("claude-3-opus"),
-            max_tokens=100,
-            system="You are a helpful assistant.",
-            messages=[
-                ClaudeMessage(role="user", content="Hello"),
-            ],
-        )
-        params = claude_request_to_text_generation(request)
-
-        assert params.instructions == "You are a helpful assistant."
-        assert isinstance(params.input, list)
-        assert len(params.input) == 1
-        assert params.input[0].role == "user"
-        assert params.input[0].content == "Hello"
-
-    def test_request_with_system_text_blocks(self):
-        request = ClaudeMessagesRequest(
-            model=ModelId("claude-3-opus"),
-            max_tokens=100,
-            system=[
-                ClaudeTextBlock(text="You are helpful. "),
-                ClaudeTextBlock(text="Be concise."),
-            ],
-            messages=[
-                ClaudeMessage(role="user", content="Hello"),
-            ],
-        )
-        params = claude_request_to_text_generation(request)
-
-        assert params.instructions == "You are helpful. Be concise."
-        assert isinstance(params.input, list)
-        assert len(params.input) == 1
-
-    def test_request_with_content_blocks(self):
-        request = ClaudeMessagesRequest(
-            model=ModelId("claude-3-opus"),
-            max_tokens=100,
-            messages=[
-                ClaudeMessage(
-                    role="user",
-                    content=[
-                        ClaudeTextBlock(text="First part. "),
-                        ClaudeTextBlock(text="Second part."),
-                    ],
-                ),
-            ],
-        )
-        params = claude_request_to_text_generation(request)
-
-        assert isinstance(params.input, list)
-        assert len(params.input) == 1
-        assert params.input[0].content == "First part. Second part."
-
-    def test_request_with_multi_turn_conversation(self):
-        request = ClaudeMessagesRequest(
-            model=ModelId("claude-3-opus"),
-            max_tokens=100,
-            messages=[
-                ClaudeMessage(role="user", content="Hello"),
-                ClaudeMessage(role="assistant", content="Hi there!"),
-                ClaudeMessage(role="user", content="How are you?"),
-            ],
-        )
-        params = claude_request_to_text_generation(request)
-
-        assert isinstance(params.input, list)
-        assert len(params.input) == 3
-        assert params.input[0].role == "user"
-        assert params.input[1].role == "assistant"
-        assert params.input[2].role == "user"
-
-    def test_request_with_optional_parameters(self):
-        request = ClaudeMessagesRequest(
-            model=ModelId("claude-3-opus"),
-            max_tokens=100,
-            messages=[ClaudeMessage(role="user", content="Hello")],
-            temperature=0.7,
-            top_p=0.9,
-            top_k=40,
-            stop_sequences=["STOP", "END"],
-            stream=True,
-        )
-        params = claude_request_to_text_generation(request)
-
-        assert params.temperature == 0.7
-        assert params.top_p == 0.9
-        assert params.top_k == 40
-        assert params.stop == ["STOP", "END"]
-        assert params.stream is True
-
-
-class TestClaudeMessagesRequestValidation:
-    """Tests for Claude Messages API request validation."""
-
-    def test_request_requires_model(self):
-        with pytest.raises(pydantic.ValidationError):
-            ClaudeMessagesRequest.model_validate(
-                {
-                    "max_tokens": 100,
-                    "messages": [{"role": "user", "content": "Hello"}],
-                }
-            )
-
-    def test_request_requires_max_tokens(self):
-        with pytest.raises(pydantic.ValidationError):
-            ClaudeMessagesRequest.model_validate(
-                {
-                    "model": "claude-3-opus",
-                    "messages": [{"role": "user", "content": "Hello"}],
-                }
-            )
-
-    def test_request_requires_messages(self):
-        with pytest.raises(pydantic.ValidationError):
-            ClaudeMessagesRequest.model_validate(
-                {
-                    "model": "claude-3-opus",
-                    "max_tokens": 100,
-                }
-            )

src/exo/master/tests/test_claude_tool_use.py

@@ -1,265 +0,0 @@
-"""Tests for Claude Messages API tool_use support in the adapter."""
-
-import json
-from collections.abc import AsyncGenerator
-from typing import Any, cast
-
-from exo.master.adapters.claude import collect_claude_response, generate_claude_stream
-from exo.shared.types.api import ToolCallItem
-from exo.shared.types.chunks import ErrorChunk, TokenChunk, ToolCallChunk
-from exo.shared.types.common import CommandId, ModelId
-
-
-async def _chunks_to_stream(
-    chunks: list[ErrorChunk | ToolCallChunk | TokenChunk],
-) -> AsyncGenerator[ErrorChunk | ToolCallChunk | TokenChunk, None]:
-    for chunk in chunks:
-        yield chunk
-
-
-MODEL = ModelId("test-model")
-COMMAND_ID = CommandId("cmd_test123")
-
-
-def _parse_sse_events(events: list[str]) -> list[dict[str, Any]]:
-    """Parse SSE event strings into JSON dicts."""
-    parsed: list[dict[str, Any]] = []
-    for event_str in events:
-        for line in event_str.strip().split("\n"):
-            if line.startswith("data: "):
-                parsed.append(cast(dict[str, Any], json.loads(line[6:])))
-    return parsed
-
-
-class TestCollectClaudeResponseToolUse:
-    """Tests for non-streaming tool_use response collection."""
-
-    async def test_tool_call_chunk_produces_tool_use_blocks(self):
-        chunks: list[ErrorChunk | ToolCallChunk | TokenChunk] = [
-            ToolCallChunk(
-                model=MODEL,
-                usage=None,
-                tool_calls=[
-                    ToolCallItem(
-                        name="get_weather",
-                        arguments='{"location": "San Francisco"}',
-                    )
-                ],
-            ),
-        ]
-        response = await collect_claude_response(
-            COMMAND_ID, "test-model", _chunks_to_stream(chunks)
-        )
-
-        assert response.stop_reason == "tool_use"
-        tool_blocks = [b for b in response.content if b.type == "tool_use"]
-        assert len(tool_blocks) == 1
-        block = tool_blocks[0]
-        assert block.type == "tool_use"
-        assert block.name == "get_weather"
-        assert block.input == {"location": "San Francisco"}
-        assert block.id.startswith("toolu_")
-
-    async def test_multiple_tool_calls(self):
-        chunks: list[ErrorChunk | ToolCallChunk | TokenChunk] = [
-            ToolCallChunk(
-                model=MODEL,
-                usage=None,
-                tool_calls=[
-                    ToolCallItem(
-                        name="get_weather",
-                        arguments='{"location": "SF"}',
-                    ),
-                    ToolCallItem(
-                        name="get_time",
-                        arguments='{"timezone": "PST"}',
-                    ),
-                ],
-            ),
-        ]
-        response = await collect_claude_response(
-            COMMAND_ID, "test-model", _chunks_to_stream(chunks)
-        )
-
-        assert response.stop_reason == "tool_use"
-        tool_blocks = [b for b in response.content if b.type == "tool_use"]
-        assert len(tool_blocks) == 2
-        assert tool_blocks[0].name == "get_weather"
-        assert tool_blocks[1].name == "get_time"
-
-    async def test_mixed_text_and_tool_use(self):
-        chunks: list[ErrorChunk | ToolCallChunk | TokenChunk] = [
-            TokenChunk(model=MODEL, text="Let me check ", token_id=1, usage=None),
-            TokenChunk(model=MODEL, text="the weather.", token_id=2, usage=None),
-            ToolCallChunk(
-                model=MODEL,
-                usage=None,
-                tool_calls=[
-                    ToolCallItem(
-                        name="get_weather",
-                        arguments='{"location": "NYC"}',
-                    )
-                ],
-            ),
-        ]
-        response = await collect_claude_response(
-            COMMAND_ID, "test-model", _chunks_to_stream(chunks)
-        )
-
-        assert response.stop_reason == "tool_use"
-        text_blocks = [b for b in response.content if b.type == "text"]
-        tool_blocks = [b for b in response.content if b.type == "tool_use"]
-        assert len(text_blocks) == 1
-        assert text_blocks[0].text == "Let me check the weather."
-        assert len(tool_blocks) == 1
-        assert tool_blocks[0].name == "get_weather"
-
-    async def test_no_content_produces_empty_text_block(self):
-        chunks: list[ErrorChunk | ToolCallChunk | TokenChunk] = []
-        response = await collect_claude_response(
-            COMMAND_ID, "test-model", _chunks_to_stream(chunks)
-        )
-        assert len(response.content) == 1
-        assert response.content[0].type == "text"
-
-
-class TestGenerateClaudeStreamToolUse:
-    """Tests for streaming tool_use event generation."""
-
-    async def test_tool_call_emits_tool_use_events(self):
-        chunks: list[ErrorChunk | ToolCallChunk | TokenChunk] = [
-            ToolCallChunk(
-                model=MODEL,
-                usage=None,
-                tool_calls=[
-                    ToolCallItem(
-                        name="get_weather",
-                        arguments='{"location": "SF"}',
-                    )
-                ],
-            ),
-        ]
-        events: list[str] = []
-        async for event in generate_claude_stream(
-            COMMAND_ID, "test-model", _chunks_to_stream(chunks)
-        ):
-            events.append(event)
-
-        parsed = _parse_sse_events(events)
-
-        # Find tool_use content_block_start
-        tool_starts = [
-            e
-            for e in parsed
-            if e.get("type") == "content_block_start"
-            and cast(dict[str, Any], e.get("content_block", {})).get("type")
-            == "tool_use"
-        ]
-        assert len(tool_starts) == 1
-        content_block = cast(dict[str, Any], tool_starts[0]["content_block"])
-        assert content_block["name"] == "get_weather"
-        assert content_block["input"] == {}
-        assert cast(str, content_block["id"]).startswith("toolu_")
-
-        # Find input_json_delta
-        json_deltas = [
-            e
-            for e in parsed
-            if e.get("type") == "content_block_delta"
-            and cast(dict[str, Any], e.get("delta", {})).get("type")
-            == "input_json_delta"
-        ]
-        assert len(json_deltas) == 1
-        delta = cast(dict[str, Any], json_deltas[0]["delta"])
-        assert json.loads(cast(str, delta["partial_json"])) == {"location": "SF"}
-
-        # Find message_delta with tool_use stop reason
-        msg_deltas = [e for e in parsed if e.get("type") == "message_delta"]
-        assert len(msg_deltas) == 1
-        assert cast(dict[str, Any], msg_deltas[0]["delta"])["stop_reason"] == "tool_use"
-
-    async def test_streaming_mixed_text_and_tool_use(self):
-        chunks: list[ErrorChunk | ToolCallChunk | TokenChunk] = [
-            TokenChunk(model=MODEL, text="Hello ", token_id=1, usage=None),
-            ToolCallChunk(
-                model=MODEL,
-                usage=None,
-                tool_calls=[
-                    ToolCallItem(
-                        name="search",
-                        arguments='{"query": "test"}',
-                    )
-                ],
-            ),
-        ]
-        events: list[str] = []
-        async for event in generate_claude_stream(
-            COMMAND_ID, "test-model", _chunks_to_stream(chunks)
-        ):
-            events.append(event)
-
-        parsed = _parse_sse_events(events)
-
-        # Should have text delta at index 0
-        text_deltas = [
-            e
-            for e in parsed
-            if e.get("type") == "content_block_delta"
-            and cast(dict[str, Any], e.get("delta", {})).get("type") == "text_delta"
-        ]
-        assert len(text_deltas) == 1
-        assert text_deltas[0]["index"] == 0
-        assert cast(dict[str, Any], text_deltas[0]["delta"])["text"] == "Hello "
-
-        # Tool block at index 1
-        tool_starts = [
-            e
-            for e in parsed
-            if e.get("type") == "content_block_start"
-            and cast(dict[str, Any], e.get("content_block", {})).get("type")
-            == "tool_use"
-        ]
-        assert len(tool_starts) == 1
-        assert tool_starts[0]["index"] == 1
-
-        # Stop reason should be tool_use
-        msg_deltas = [e for e in parsed if e.get("type") == "message_delta"]
-        assert cast(dict[str, Any], msg_deltas[0]["delta"])["stop_reason"] == "tool_use"
-
-    async def test_streaming_tool_block_stop_events(self):
-        chunks: list[ErrorChunk | ToolCallChunk | TokenChunk] = [
-            ToolCallChunk(
-                model=MODEL,
-                usage=None,
-                tool_calls=[
-                    ToolCallItem(name="fn1", arguments="{}"),
-                    ToolCallItem(name="fn2", arguments='{"a": 1}'),
-                ],
-            ),
-        ]
-        events: list[str] = []
-        async for event in generate_claude_stream(
-            COMMAND_ID, "test-model", _chunks_to_stream(chunks)
-        ):
-            events.append(event)
-
-        parsed = _parse_sse_events(events)
-
-        # Two tool block starts (at indices 1 and 2)
-        tool_starts = [
-            e
-            for e in parsed
-            if e.get("type") == "content_block_start"
-            and cast(dict[str, Any], e.get("content_block", {})).get("type")
-            == "tool_use"
-        ]
-        assert len(tool_starts) == 2
-        assert tool_starts[0]["index"] == 1
-        assert tool_starts[1]["index"] == 2
-
-        # Two tool block stops (at indices 1 and 2), plus text block stop at 0
-        block_stops = [e for e in parsed if e.get("type") == "content_block_stop"]
-        stop_indices = [e["index"] for e in block_stops]
-        assert 0 in stop_indices
-        assert 1 in stop_indices
-        assert 2 in stop_indices

src/exo/master/tests/test_master.py

@@ -7,14 +7,15 @@ from loguru import logger
 
 from exo.master.main import Master
 from exo.routing.router import get_node_id_keypair
-from exo.shared.models.model_cards import ModelCard, ModelTask
+from exo.shared.models.model_cards import ModelCard, ModelId, ModelTask
+from exo.shared.types.api import ChatCompletionMessage, ChatCompletionTaskParams
 from exo.shared.types.commands import (
+    ChatCompletion,
     CommandId,
     ForwarderCommand,
     PlaceInstance,
-    TextGeneration,
 )
-from exo.shared.types.common import ModelId, NodeId, SessionId
+from exo.shared.types.common import NodeId, SessionId
 from exo.shared.types.events import (
     ForwarderEvent,
     IndexedEvent,
@@ -26,9 +27,8 @@ from exo.shared.types.memory import Memory
 from exo.shared.types.profiling import (
     MemoryUsage,
 )
+from exo.shared.types.tasks import ChatCompletion as ChatCompletionTask
 from exo.shared.types.tasks import TaskStatus
-from exo.shared.types.tasks import TextGeneration as TextGenerationTask
-from exo.shared.types.text_generation import InputMessage, TextGenerationTaskParams
 from exo.shared.types.worker.instances import (
     InstanceMeta,
     MlxRingInstance,
@@ -127,17 +127,19 @@ async def test_master():
         logger.info("wait for an instance")
         while len(master.state.instances.keys()) == 0:
             await anyio.sleep(0.001)
-        logger.info("inject a TextGeneration Command")
+        logger.info("inject a ChatCompletion Command")
         await command_sender.send(
             ForwarderCommand(
                 origin=node_id,
                 command=(
-                    TextGeneration(
+                    ChatCompletion(
                         command_id=CommandId(),
-                        task_params=TextGenerationTaskParams(
-                            model=ModelId("llama-3.2-1b"),
-                            input=[
-                                InputMessage(role="user", content="Hello, how are you?")
+                        request_params=ChatCompletionTaskParams(
+                            model="llama-3.2-1b",
+                            messages=[
+                                ChatCompletionMessage(
+                                    role="user", content="Hello, how are you?"
+                                )
                             ],
                         ),
                     )
@@ -188,10 +190,12 @@ async def test_master():
         assert created_instance.ephemeral_port > 0
         assert isinstance(events[2].event, TaskCreated)
         assert events[2].event.task.task_status == TaskStatus.Pending
-        assert isinstance(events[2].event.task, TextGenerationTask)
-        assert events[2].event.task.task_params == TextGenerationTaskParams(
-            model=ModelId("llama-3.2-1b"),
-            input=[InputMessage(role="user", content="Hello, how are you?")],
+        assert isinstance(events[2].event.task, ChatCompletionTask)
+        assert events[2].event.task.task_params == ChatCompletionTaskParams(
+            model="llama-3.2-1b",
+            messages=[
+                ChatCompletionMessage(role="user", content="Hello, how are you?")
+            ],
         )
 
         await master.shutdown()

src/exo/master/tests/test_openai_responses_api.py

@@ -1,48 +0,0 @@
-"""Tests for OpenAI Responses API wire types.
-
-ResponsesRequest is the API wire type for the Responses endpoint.
-The responses adapter converts it to TextGenerationTaskParams for the pipeline.
-"""
-
-import pydantic
-import pytest
-
-from exo.shared.types.common import ModelId
-from exo.shared.types.openai_responses import (
-    ResponseInputMessage,
-    ResponsesRequest,
-)
-
-
-class TestResponsesRequestValidation:
-    """Tests for OpenAI Responses API request validation."""
-
-    def test_request_requires_model(self):
-        with pytest.raises(pydantic.ValidationError):
-            ResponsesRequest.model_validate(
-                {
-                    "input": "Hello",
-                }
-            )
-
-    def test_request_requires_input(self):
-        with pytest.raises(pydantic.ValidationError):
-            ResponsesRequest.model_validate(
-                {
-                    "model": "gpt-4o",
-                }
-            )
-
-    def test_request_accepts_string_input(self):
-        request = ResponsesRequest(
-            model=ModelId("gpt-4o"),
-            input="Hello",
-        )
-        assert request.input == "Hello"
-
-    def test_request_accepts_message_array_input(self):
-        request = ResponsesRequest(
-            model=ModelId("gpt-4o"),
-            input=[ResponseInputMessage(role="user", content="Hello")],
-        )
-        assert len(request.input) == 1

src/exo/master/tests/test_placement_utils.py

@@ -5,7 +5,6 @@ from exo.master.placement_utils import (
     filter_cycles_by_memory,
     get_mlx_jaccl_coordinators,
     get_shard_assignments,
-    get_shard_assignments_for_pipeline_parallel,
     get_smallest_cycles,
 )
 from exo.master.tests.conftest import (
@@ -21,11 +20,7 @@ from exo.shared.types.profiling import (
     NodeNetworkInfo,
 )
 from exo.shared.types.topology import Connection, SocketConnection
-from exo.shared.types.worker.shards import (
-    CfgShardMetadata,
-    PipelineShardMetadata,
-    Sharding,
-)
+from exo.shared.types.worker.shards import Sharding
 
 
 def test_filter_cycles_by_memory():
@@ -492,193 +487,3 @@ def test_get_shard_assignments_insufficient_memory_raises():
         get_shard_assignments(
             model_card, selected_cycle, Sharding.Pipeline, node_memory
         )
-
-
-class TestCfgParallelPlacement:
-    def _create_ring_topology(self, node_ids: list[NodeId]) -> Topology:
-        topology = Topology()
-        for node_id in node_ids:
-            topology.add_node(node_id)
-
-        for i, node_id in enumerate(node_ids):
-            next_node = node_ids[(i + 1) % len(node_ids)]
-            conn = Connection(
-                source=node_id,
-                sink=next_node,
-                edge=create_socket_connection(i + 1),
-            )
-            topology.add_connection(conn)
-
-        return topology
-
-    def test_two_nodes_cfg_model_uses_cfg_parallel(self):
-        """Two nodes with CFG model should use CFG parallel (no pipeline)."""
-        node_a = NodeId()
-        node_b = NodeId()
-
-        topology = self._create_ring_topology([node_a, node_b])
-        cycles = [c for c in topology.get_cycles() if len(c) == 2]
-        cycle = cycles[0]
-
-        node_memory = {
-            node_a: create_node_memory(1000 * 1024),
-            node_b: create_node_memory(1000 * 1024),
-        }
-
-        model_card = ModelCard(
-            model_id=ModelId("qwen-image-test"),
-            n_layers=60,
-            storage_size=Memory.from_kb(1000),
-            hidden_size=1,
-            supports_tensor=False,
-            uses_cfg=True,
-            tasks=[ModelTask.TextToImage],
-        )
-
-        assignments = get_shard_assignments_for_pipeline_parallel(
-            model_card, cycle, node_memory
-        )
-
-        shards = list(assignments.runner_to_shard.values())
-        assert len(shards) == 2
-
-        # CFG models should get CfgShardMetadata
-        for shard in shards:
-            assert isinstance(shard, CfgShardMetadata)
-            # Both nodes should have all layers (no pipeline split)
-            assert shard.start_layer == 0
-            assert shard.end_layer == 60
-            assert shard.cfg_world_size == 2
-            # Each node is the only stage in its pipeline group
-            assert shard.pipeline_world_size == 1
-            assert shard.pipeline_rank == 0
-
-        cfg_ranks = sorted(
-            s.cfg_rank for s in shards if isinstance(s, CfgShardMetadata)
-        )
-        assert cfg_ranks == [0, 1]
-
-    def test_four_nodes_cfg_model_uses_hybrid(self):
-        """Four nodes with CFG model should use 2 CFG groups x 2 pipeline stages."""
-        nodes = [NodeId() for _ in range(4)]
-
-        topology = self._create_ring_topology(nodes)
-        cycles = [c for c in topology.get_cycles() if len(c) == 4]
-        cycle = cycles[0]
-
-        node_memory = {n: create_node_memory(1000 * 1024) for n in nodes}
-
-        model_card = ModelCard(
-            model_id=ModelId("qwen-image-test"),
-            n_layers=60,
-            storage_size=Memory.from_kb(1000),
-            hidden_size=1,
-            supports_tensor=False,
-            uses_cfg=True,
-            tasks=[ModelTask.TextToImage],
-        )
-
-        assignments = get_shard_assignments_for_pipeline_parallel(
-            model_card, cycle, node_memory
-        )
-
-        shards = list(assignments.runner_to_shard.values())
-        assert len(shards) == 4
-
-        # CFG models should get CfgShardMetadata
-        for shard in shards:
-            assert isinstance(shard, CfgShardMetadata)
-            assert shard.cfg_world_size == 2
-            assert shard.pipeline_world_size == 2
-            assert shard.pipeline_rank in [0, 1]
-
-        # Check we have 2 nodes in each CFG group
-        cfg_0_shards = [
-            s for s in shards if isinstance(s, CfgShardMetadata) and s.cfg_rank == 0
-        ]
-        cfg_1_shards = [
-            s for s in shards if isinstance(s, CfgShardMetadata) and s.cfg_rank == 1
-        ]
-        assert len(cfg_0_shards) == 2
-        assert len(cfg_1_shards) == 2
-
-        # Both CFG groups should have the same layer assignments
-        cfg_0_layers = [(s.start_layer, s.end_layer) for s in cfg_0_shards]
-        cfg_1_layers = [(s.start_layer, s.end_layer) for s in cfg_1_shards]
-        assert sorted(cfg_0_layers) == sorted(cfg_1_layers)
-
-    def test_three_nodes_cfg_model_uses_sequential_cfg(self):
-        """Three nodes (odd) with CFG model should use sequential CFG (PipelineShardMetadata)."""
-        nodes = [NodeId() for _ in range(3)]
-
-        topology = self._create_ring_topology(nodes)
-        cycles = [c for c in topology.get_cycles() if len(c) == 3]
-        cycle = cycles[0]
-
-        node_memory = {n: create_node_memory(1000 * 1024) for n in nodes}
-
-        model_card = ModelCard(
-            model_id=ModelId("qwen-image-test"),
-            n_layers=60,
-            storage_size=Memory.from_kb(1000),
-            hidden_size=1,
-            supports_tensor=False,
-            uses_cfg=True,
-            tasks=[ModelTask.TextToImage],
-        )
-
-        assignments = get_shard_assignments_for_pipeline_parallel(
-            model_card, cycle, node_memory
-        )
-
-        shards = list(assignments.runner_to_shard.values())
-        assert len(shards) == 3
-
-        # Odd node count with CFG model falls back to PipelineShardMetadata (sequential CFG)
-        for shard in shards:
-            assert isinstance(shard, PipelineShardMetadata)
-
-    def test_two_nodes_non_cfg_model_uses_pipeline(self):
-        """Two nodes with non-CFG model should use pure pipeline (PipelineShardMetadata)."""
-        node_a = NodeId()
-        node_b = NodeId()
-
-        topology = self._create_ring_topology([node_a, node_b])
-        cycles = [c for c in topology.get_cycles() if len(c) == 2]
-        cycle = cycles[0]
-
-        node_memory = {
-            node_a: create_node_memory(1000 * 1024),
-            node_b: create_node_memory(1000 * 1024),
-        }
-
-        model_card = ModelCard(
-            model_id=ModelId("flux-test"),
-            n_layers=57,
-            storage_size=Memory.from_kb(1000),
-            hidden_size=1,
-            supports_tensor=False,
-            uses_cfg=False,  # Non-CFG model
-            tasks=[ModelTask.TextToImage],
-        )
-
-        assignments = get_shard_assignments_for_pipeline_parallel(
-            model_card, cycle, node_memory
-        )
-
-        shards = list(assignments.runner_to_shard.values())
-        assert len(shards) == 2
-
-        # Non-CFG models should get PipelineShardMetadata
-        for shard in shards:
-            assert isinstance(shard, PipelineShardMetadata)
-
-        # Should have actual layer sharding (pipeline)
-        layer_ranges = sorted(
-            (s.start_layer, s.end_layer)
-            for s in shards
-            if isinstance(s, PipelineShardMetadata)
-        )
-        # First shard starts at 0, last shard ends at 57
-        assert layer_ranges[0][0] == 0
-        assert layer_ranges[-1][1] == 57

src/exo/routing/router.py

@@ -10,7 +10,6 @@ from anyio import (
     ClosedResourceError,
     create_task_group,
     sleep_forever,
-    move_on_after
 )
 from anyio.abc import TaskGroup
 from exo_pyo3_bindings import (
@@ -147,21 +146,18 @@ class Router:
 
     async def run(self):
         logger.debug("Starting Router")
-        try:
-            async with create_task_group() as tg:
-                self._tg = tg
-                for topic in self.topic_routers:
-                    router = self.topic_routers[topic]
-                    tg.start_soon(router.run)
-                tg.start_soon(self._networking_recv)
-                tg.start_soon(self._networking_recv_connection_messages)
-                tg.start_soon(self._networking_publish)
-                # Router only shuts down if you cancel it.
-                await sleep_forever()
-        finally:
-            with move_on_after(1, shield=True):
-                for topic in self.topic_routers:
-                    await self._networking_unsubscribe(str(topic))
+        async with create_task_group() as tg:
+            self._tg = tg
+            for topic in self.topic_routers:
+                router = self.topic_routers[topic]
+                tg.start_soon(router.run)
+            tg.start_soon(self._networking_recv)
+            tg.start_soon(self._networking_recv_connection_messages)
+            tg.start_soon(self._networking_publish)
+            # Router only shuts down if you cancel it.
+            await sleep_forever()
+        for topic in self.topic_routers:
+            await self._networking_unsubscribe(str(topic))
 
     async def shutdown(self):
         logger.debug("Shutting down Router")
@@ -170,12 +166,12 @@ class Router:
         self._tg.cancel_scope.cancel()
 
     async def _networking_subscribe(self, topic: str):
+        logger.info(f"Subscribing to {topic}")
         await self._net.gossipsub_subscribe(topic)
-        logger.info(f"Subscribed to {topic}")
 
     async def _networking_unsubscribe(self, topic: str):
+        logger.info(f"Unsubscribing from {topic}")
         await self._net.gossipsub_unsubscribe(topic)
-        logger.info(f"Unsubscribed from {topic}")
 
     async def _networking_recv(self):
         while True:
@@ -220,8 +216,6 @@ def get_node_id_keypair(
     Obtains the :class:`Keypair` associated with this node-ID.
     Obtain the :class:`PeerId` by from it.
     """
-    # TODO(evan): bring back node id persistence once we figure out how to deal with duplicates
-    return Keypair.generate_ed25519()
 
     def lock_path(path: str | bytes | PathLike[str] | PathLike[bytes]) -> Path:
         return Path(str(path) + ".lock")

src/exo/shared/apply.py

@@ -25,8 +25,6 @@ from exo.shared.types.events import (
     TestEvent,
     TopologyEdgeCreated,
     TopologyEdgeDeleted,
-    TracesCollected,
-    TracesMerged,
 )
 from exo.shared.types.profiling import (
     NodeIdentity,
@@ -57,12 +55,7 @@ def event_apply(event: Event, state: State) -> State:
     """Apply an event to state."""
     match event:
         case (
-            TestEvent()
-            | ChunkGenerated()
-            | TaskAcknowledged()
-            | InputChunkReceived()
-            | TracesCollected()
-            | TracesMerged()
+            TestEvent() | ChunkGenerated() | TaskAcknowledged() | InputChunkReceived()
         ):  # Pass-through events that don't modify state
             return state
         case InstanceCreated():

src/exo/shared/constants.py

@@ -2,8 +2,6 @@ import os
 import sys
 from pathlib import Path
 
-from exo.utils.dashboard_path import find_dashboard, find_resources
-
 _EXO_HOME_ENV = os.environ.get("EXO_HOME", None)
 
 
@@ -33,14 +31,6 @@ EXO_MODELS_DIR = (
     if _EXO_MODELS_DIR_ENV is None
     else Path.home() / _EXO_MODELS_DIR_ENV
 )
-_RESOURCES_DIR_ENV = os.environ.get("EXO_RESOURCES_DIR", None)
-RESOURCES_DIR = (
-    find_resources() if _RESOURCES_DIR_ENV is None else Path.home() / _RESOURCES_DIR_ENV
-)
-_DASHBOARD_DIR_ENV = os.environ.get("EXO_DASHBOARD_DIR", None)
-DASHBOARD_DIR = (
-    find_dashboard() if _DASHBOARD_DIR_ENV is None else Path.home() / _DASHBOARD_DIR_ENV
-)
 
 # Log files (data/logs or cache)
 EXO_LOG = EXO_CACHE_HOME / "exo.log"
@@ -58,13 +48,8 @@ LIBP2P_COMMANDS_TOPIC = "commands"
 
 EXO_MAX_CHUNK_SIZE = 512 * 1024
 
-EXO_CUSTOM_MODEL_CARDS_DIR = EXO_DATA_HOME / "custom_model_cards"
-
 EXO_IMAGE_CACHE_DIR = EXO_CACHE_HOME / "images"
-EXO_TRACING_CACHE_DIR = EXO_CACHE_HOME / "traces"
 
 EXO_ENABLE_IMAGE_MODELS = (
     os.getenv("EXO_ENABLE_IMAGE_MODELS", "false").lower() == "true"
 )
-
-EXO_TRACING_ENABLED = os.getenv("EXO_TRACING_ENABLED", "false").lower() == "true"

src/exo/shared/election.py

@@ -86,29 +86,28 @@ class Election:
 
     async def run(self):
         logger.info("Starting Election")
-        try:
-            async with create_task_group() as tg:
-                self._tg = tg
-                tg.start_soon(self._election_receiver)
-                tg.start_soon(self._connection_receiver)
-                tg.start_soon(self._command_counter)
+        async with create_task_group() as tg:
+            self._tg = tg
+            tg.start_soon(self._election_receiver)
+            tg.start_soon(self._connection_receiver)
+            tg.start_soon(self._command_counter)
 
-                # And start an election immediately, that instantly resolves
-                candidates: list[ElectionMessage] = []
-                logger.debug("Starting initial campaign")
-                self._candidates = candidates
-                await self._campaign(candidates, campaign_timeout=0.0)
-                logger.debug("Initial campaign finished")
-        finally:
-            # Cancel and wait for the last election to end
-            if self._campaign_cancel_scope is not None:
-                logger.debug("Cancelling campaign")
-                self._campaign_cancel_scope.cancel()
-            if self._campaign_done is not None:
-                logger.debug("Waiting for campaign to finish")
-                await self._campaign_done.wait()
-            logger.debug("Campaign cancelled and finished")
-            logger.info("Election shutdown")
+            # And start an election immediately, that instantly resolves
+            candidates: list[ElectionMessage] = []
+            logger.debug("Starting initial campaign")
+            self._candidates = candidates
+            await self._campaign(candidates, campaign_timeout=0.0)
+            logger.debug("Initial campaign finished")
+
+        # Cancel and wait for the last election to end
+        if self._campaign_cancel_scope is not None:
+            logger.debug("Cancelling campaign")
+            self._campaign_cancel_scope.cancel()
+        if self._campaign_done is not None:
+            logger.debug("Waiting for campaign to finish")
+            await self._campaign_done.wait()
+        logger.debug("Campaign cancelled and finished")
+        logger.info("Election finished")
 
     async def elect(self, em: ElectionMessage) -> None:
         logger.debug(f"Electing: {em}")

src/exo/shared/models/model_cards.py

@@ -12,47 +12,16 @@ from pydantic import (
     BaseModel,
     Field,
     PositiveInt,
-    ValidationError,
     field_validator,
     model_validator,
 )
-from tomlkit.exceptions import TOMLKitError
 
-from exo.shared.constants import (
-    EXO_CUSTOM_MODEL_CARDS_DIR,
-    EXO_ENABLE_IMAGE_MODELS,
-    RESOURCES_DIR,
-)
+from exo.shared.constants import EXO_ENABLE_IMAGE_MODELS
 from exo.shared.types.common import ModelId
 from exo.shared.types.memory import Memory
 from exo.utils.pydantic_ext import CamelCaseModel
 
-# kinda ugly...
-# TODO: load search path from config.toml
-_custom_cards_dir = Path(str(EXO_CUSTOM_MODEL_CARDS_DIR))
-_csp = [Path(RESOURCES_DIR) / "inference_model_cards", _custom_cards_dir]
-if EXO_ENABLE_IMAGE_MODELS:
-    _csp.append(Path(RESOURCES_DIR) / "image_model_cards")
-
-CARD_SEARCH_PATH = _csp
-
-_card_cache: dict[ModelId, "ModelCard"] = {}
-
-
-async def _refresh_card_cache():
-    for path in CARD_SEARCH_PATH:
-        async for toml_file in path.rglob("*.toml"):
-            try:
-                card = await ModelCard.load_from_path(toml_file)
-                _card_cache[card.model_id] = card
-            except (ValidationError, TOMLKitError):
-                pass
-
-
-async def get_model_cards() -> list["ModelCard"]:
-    if len(_card_cache) == 0:
-        await _refresh_card_cache()
-    return list(_card_cache.values())
+_card_cache: dict[str, "ModelCard"] = {}
 
 
 class ModelTask(str, Enum):
@@ -65,9 +34,9 @@ class ComponentInfo(CamelCaseModel):
     component_name: str
     component_path: str
     storage_size: Memory
-    n_layers: PositiveInt | None = None
+    n_layers: PositiveInt | None
     can_shard: bool
-    safetensors_index_filename: str | None = None
+    safetensors_index_filename: str | None
 
 
 class ModelCard(CamelCaseModel):
@@ -78,11 +47,6 @@ class ModelCard(CamelCaseModel):
     supports_tensor: bool
     tasks: list[ModelTask]
     components: list[ComponentInfo] | None = None
-    family: str = ""
-    quantization: str = ""
-    base_model: str = ""
-    capabilities: list[str] = []
-    uses_cfg: bool = False
 
     @field_validator("tasks", mode="before")
     @classmethod
@@ -91,37 +55,31 @@ class ModelCard(CamelCaseModel):
 
     async def save(self, path: Path) -> None:
         async with await open_file(path, "w") as f:
-            py = self.model_dump(exclude_none=True)
+            py = self.model_dump()
             data = tomlkit.dumps(py)  # pyright: ignore[reportUnknownMemberType]
             await f.write(data)
 
-    async def save_to_custom_dir(self) -> None:
-        await aios.makedirs(str(_custom_cards_dir), exist_ok=True)
-        await self.save(_custom_cards_dir / (self.model_id.normalize() + ".toml"))
-
     @staticmethod
     async def load_from_path(path: Path) -> "ModelCard":
         async with await open_file(path, "r") as f:
             py = tomlkit.loads(await f.read())
             return ModelCard.model_validate(py)
 
-    # Is it okay that model card.load defaults to network access if the card doesn't exist? do we want to be more explicit here?
     @staticmethod
     async def load(model_id: ModelId) -> "ModelCard":
-        if model_id not in _card_cache:
-            await _refresh_card_cache()
-        if (mc := _card_cache.get(model_id)) is not None:
-            return mc
-
-        return await ModelCard.fetch_from_hf(model_id)
+        for card in MODEL_CARDS.values():
+            if card.model_id == model_id:
+                return card
+        return await ModelCard.from_hf(model_id)
 
     @staticmethod
-    async def fetch_from_hf(model_id: ModelId) -> "ModelCard":
+    async def from_hf(model_id: ModelId) -> "ModelCard":
         """Fetches storage size and number of layers for a Hugging Face model, returns Pydantic ModelMeta."""
-        # TODO: failure if files do not exist
-        config_data = await fetch_config_data(model_id)
+        if (mc := _card_cache.get(model_id)) is not None:
+            return mc
+        config_data = await get_config_data(model_id)
         num_layers = config_data.layer_count
-        mem_size_bytes = await fetch_safetensors_size(model_id)
+        mem_size_bytes = await get_safetensors_size(model_id)
 
         mc = ModelCard(
             model_id=ModelId(model_id),
@@ -131,29 +89,630 @@ class ModelCard(CamelCaseModel):
             supports_tensor=config_data.supports_tensor,
             tasks=[ModelTask.TextGeneration],
         )
-        await mc.save_to_custom_dir()
         _card_cache[model_id] = mc
         return mc
 
 
-async def delete_custom_card(model_id: ModelId) -> bool:
-    """Delete a user-added custom model card. Returns True if deleted."""
-    card_path = _custom_cards_dir / (ModelId(model_id).normalize() + ".toml")
-    if await card_path.exists():
-        await card_path.unlink()
-        _card_cache.pop(model_id, None)
-        return True
-    return False
+MODEL_CARDS: dict[str, ModelCard] = {
+    # deepseek v3
+    "deepseek-v3.1-4bit": ModelCard(
+        model_id=ModelId("mlx-community/DeepSeek-V3.1-4bit"),
+        storage_size=Memory.from_gb(378),
+        n_layers=61,
+        hidden_size=7168,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "deepseek-v3.1-8bit": ModelCard(
+        model_id=ModelId("mlx-community/DeepSeek-V3.1-8bit"),
+        storage_size=Memory.from_gb(713),
+        n_layers=61,
+        hidden_size=7168,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    # kimi k2
+    "kimi-k2-instruct-4bit": ModelCard(
+        model_id=ModelId("mlx-community/Kimi-K2-Instruct-4bit"),
+        storage_size=Memory.from_gb(578),
+        n_layers=61,
+        hidden_size=7168,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "kimi-k2-thinking": ModelCard(
+        model_id=ModelId("mlx-community/Kimi-K2-Thinking"),
+        storage_size=Memory.from_gb(658),
+        n_layers=61,
+        hidden_size=7168,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "kimi-k2.5": ModelCard(
+        model_id=ModelId("mlx-community/Kimi-K2.5"),
+        storage_size=Memory.from_gb(617),
+        n_layers=61,
+        hidden_size=7168,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    # llama-3.1
+    "llama-3.1-8b": ModelCard(
+        model_id=ModelId("mlx-community/Meta-Llama-3.1-8B-Instruct-4bit"),
+        storage_size=Memory.from_mb(4423),
+        n_layers=32,
+        hidden_size=4096,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "llama-3.1-8b-8bit": ModelCard(
+        model_id=ModelId("mlx-community/Meta-Llama-3.1-8B-Instruct-8bit"),
+        storage_size=Memory.from_mb(8540),
+        n_layers=32,
+        hidden_size=4096,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "llama-3.1-8b-bf16": ModelCard(
+        model_id=ModelId("mlx-community/Meta-Llama-3.1-8B-Instruct-bf16"),
+        storage_size=Memory.from_mb(16100),
+        n_layers=32,
+        hidden_size=4096,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "llama-3.1-70b": ModelCard(
+        model_id=ModelId("mlx-community/Meta-Llama-3.1-70B-Instruct-4bit"),
+        storage_size=Memory.from_mb(38769),
+        n_layers=80,
+        hidden_size=8192,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    # llama-3.2
+    "llama-3.2-1b": ModelCard(
+        model_id=ModelId("mlx-community/Llama-3.2-1B-Instruct-4bit"),
+        storage_size=Memory.from_mb(696),
+        n_layers=16,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "llama-3.2-3b": ModelCard(
+        model_id=ModelId("mlx-community/Llama-3.2-3B-Instruct-4bit"),
+        storage_size=Memory.from_mb(1777),
+        n_layers=28,
+        hidden_size=3072,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "llama-3.2-3b-8bit": ModelCard(
+        model_id=ModelId("mlx-community/Llama-3.2-3B-Instruct-8bit"),
+        storage_size=Memory.from_mb(3339),
+        n_layers=28,
+        hidden_size=3072,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    # llama-3.3
+    "llama-3.3-70b": ModelCard(
+        model_id=ModelId("mlx-community/Llama-3.3-70B-Instruct-4bit"),
+        storage_size=Memory.from_mb(38769),
+        n_layers=80,
+        hidden_size=8192,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "llama-3.3-70b-8bit": ModelCard(
+        model_id=ModelId("mlx-community/Llama-3.3-70B-Instruct-8bit"),
+        storage_size=Memory.from_mb(73242),
+        n_layers=80,
+        hidden_size=8192,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "llama-3.3-70b-fp16": ModelCard(
+        model_id=ModelId("mlx-community/llama-3.3-70b-instruct-fp16"),
+        storage_size=Memory.from_mb(137695),
+        n_layers=80,
+        hidden_size=8192,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    # qwen3
+    "qwen3-0.6b": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-0.6B-4bit"),
+        storage_size=Memory.from_mb(327),
+        n_layers=28,
+        hidden_size=1024,
+        supports_tensor=False,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-0.6b-8bit": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-0.6B-8bit"),
+        storage_size=Memory.from_mb(666),
+        n_layers=28,
+        hidden_size=1024,
+        supports_tensor=False,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-30b": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-30B-A3B-4bit"),
+        storage_size=Memory.from_mb(16797),
+        n_layers=48,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-30b-8bit": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-30B-A3B-8bit"),
+        storage_size=Memory.from_mb(31738),
+        n_layers=48,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-80b-a3B-4bit": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-Next-80B-A3B-Instruct-4bit"),
+        storage_size=Memory.from_mb(44800),
+        n_layers=48,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-80b-a3B-8bit": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-Next-80B-A3B-Instruct-8bit"),
+        storage_size=Memory.from_mb(84700),
+        n_layers=48,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-80b-a3B-thinking-4bit": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-Next-80B-A3B-Thinking-4bit"),
+        storage_size=Memory.from_mb(84700),
+        n_layers=48,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-80b-a3B-thinking-8bit": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-Next-80B-A3B-Thinking-8bit"),
+        storage_size=Memory.from_mb(84700),
+        n_layers=48,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-235b-a22b-4bit": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-235B-A22B-Instruct-2507-4bit"),
+        storage_size=Memory.from_gb(132),
+        n_layers=94,
+        hidden_size=4096,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-235b-a22b-8bit": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-235B-A22B-Instruct-2507-8bit"),
+        storage_size=Memory.from_gb(250),
+        n_layers=94,
+        hidden_size=4096,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-coder-480b-a35b-4bit": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-Coder-480B-A35B-Instruct-4bit"),
+        storage_size=Memory.from_gb(270),
+        n_layers=62,
+        hidden_size=6144,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "qwen3-coder-480b-a35b-8bit": ModelCard(
+        model_id=ModelId("mlx-community/Qwen3-Coder-480B-A35B-Instruct-8bit"),
+        storage_size=Memory.from_gb(540),
+        n_layers=62,
+        hidden_size=6144,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    # gpt-oss
+    "gpt-oss-120b-MXFP4-Q8": ModelCard(
+        model_id=ModelId("mlx-community/gpt-oss-120b-MXFP4-Q8"),
+        storage_size=Memory.from_kb(68_996_301),
+        n_layers=36,
+        hidden_size=2880,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "gpt-oss-20b-MXFP4-Q8": ModelCard(
+        model_id=ModelId("mlx-community/gpt-oss-20b-MXFP4-Q8"),
+        storage_size=Memory.from_kb(11_744_051),
+        n_layers=24,
+        hidden_size=2880,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    # glm 4.5
+    "glm-4.5-air-8bit": ModelCard(
+        # Needs to be quantized g32 or g16 to work with tensor parallel
+        model_id=ModelId("mlx-community/GLM-4.5-Air-8bit"),
+        storage_size=Memory.from_gb(114),
+        n_layers=46,
+        hidden_size=4096,
+        supports_tensor=False,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "glm-4.5-air-bf16": ModelCard(
+        model_id=ModelId("mlx-community/GLM-4.5-Air-bf16"),
+        storage_size=Memory.from_gb(214),
+        n_layers=46,
+        hidden_size=4096,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    # glm 4.7
+    "glm-4.7-4bit": ModelCard(
+        model_id=ModelId("mlx-community/GLM-4.7-4bit"),
+        storage_size=Memory.from_bytes(198556925568),
+        n_layers=91,
+        hidden_size=5120,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "glm-4.7-6bit": ModelCard(
+        model_id=ModelId("mlx-community/GLM-4.7-6bit"),
+        storage_size=Memory.from_bytes(286737579648),
+        n_layers=91,
+        hidden_size=5120,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "glm-4.7-8bit-gs32": ModelCard(
+        model_id=ModelId("mlx-community/GLM-4.7-8bit-gs32"),
+        storage_size=Memory.from_bytes(396963397248),
+        n_layers=91,
+        hidden_size=5120,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    # glm 4.7 flash
+    "glm-4.7-flash-4bit": ModelCard(
+        model_id=ModelId("mlx-community/GLM-4.7-Flash-4bit"),
+        storage_size=Memory.from_gb(18),
+        n_layers=47,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "glm-4.7-flash-5bit": ModelCard(
+        model_id=ModelId("mlx-community/GLM-4.7-Flash-5bit"),
+        storage_size=Memory.from_gb(21),
+        n_layers=47,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "glm-4.7-flash-6bit": ModelCard(
+        model_id=ModelId("mlx-community/GLM-4.7-Flash-6bit"),
+        storage_size=Memory.from_gb(25),
+        n_layers=47,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "glm-4.7-flash-8bit": ModelCard(
+        model_id=ModelId("mlx-community/GLM-4.7-Flash-8bit"),
+        storage_size=Memory.from_gb(32),
+        n_layers=47,
+        hidden_size=2048,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    # minimax-m2
+    "minimax-m2.1-8bit": ModelCard(
+        model_id=ModelId("mlx-community/MiniMax-M2.1-8bit"),
+        storage_size=Memory.from_bytes(242986745856),
+        n_layers=61,
+        hidden_size=3072,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+    "minimax-m2.1-3bit": ModelCard(
+        model_id=ModelId("mlx-community/MiniMax-M2.1-3bit"),
+        storage_size=Memory.from_bytes(100086644736),
+        n_layers=61,
+        hidden_size=3072,
+        supports_tensor=True,
+        tasks=[ModelTask.TextGeneration],
+    ),
+}
+
+_IMAGE_BASE_MODEL_CARDS: dict[str, ModelCard] = {
+    "flux1-schnell": ModelCard(
+        model_id=ModelId("exolabs/FLUX.1-schnell"),
+        storage_size=Memory.from_bytes(23782357120 + 9524621312),
+        n_layers=57,
+        hidden_size=1,
+        supports_tensor=False,
+        tasks=[ModelTask.TextToImage],
+        components=[
+            ComponentInfo(
+                component_name="text_encoder",
+                component_path="text_encoder/",
+                storage_size=Memory.from_kb(0),
+                n_layers=12,
+                can_shard=False,
+                safetensors_index_filename=None,
+            ),
+            ComponentInfo(
+                component_name="text_encoder_2",
+                component_path="text_encoder_2/",
+                storage_size=Memory.from_bytes(9524621312),
+                n_layers=24,
+                can_shard=False,
+                safetensors_index_filename="model.safetensors.index.json",
+            ),
+            ComponentInfo(
+                component_name="transformer",
+                component_path="transformer/",
+                storage_size=Memory.from_bytes(23782357120),
+                n_layers=57,
+                can_shard=True,
+                safetensors_index_filename="diffusion_pytorch_model.safetensors.index.json",
+            ),
+            ComponentInfo(
+                component_name="vae",
+                component_path="vae/",
+                storage_size=Memory.from_kb(0),
+                n_layers=None,
+                can_shard=False,
+                safetensors_index_filename=None,
+            ),
+        ],
+    ),
+    "flux1-dev": ModelCard(
+        model_id=ModelId("exolabs/FLUX.1-dev"),
+        storage_size=Memory.from_bytes(23782357120 + 9524621312),
+        n_layers=57,
+        hidden_size=1,
+        supports_tensor=False,
+        tasks=[ModelTask.TextToImage],
+        components=[
+            ComponentInfo(
+                component_name="text_encoder",
+                component_path="text_encoder/",
+                storage_size=Memory.from_kb(0),
+                n_layers=12,
+                can_shard=False,
+                safetensors_index_filename=None,
+            ),
+            ComponentInfo(
+                component_name="text_encoder_2",
+                component_path="text_encoder_2/",
+                storage_size=Memory.from_bytes(9524621312),
+                n_layers=24,
+                can_shard=False,
+                safetensors_index_filename="model.safetensors.index.json",
+            ),
+            ComponentInfo(
+                component_name="transformer",
+                component_path="transformer/",
+                storage_size=Memory.from_bytes(23802816640),
+                n_layers=57,
+                can_shard=True,
+                safetensors_index_filename="diffusion_pytorch_model.safetensors.index.json",
+            ),
+            ComponentInfo(
+                component_name="vae",
+                component_path="vae/",
+                storage_size=Memory.from_kb(0),
+                n_layers=None,
+                can_shard=False,
+                safetensors_index_filename=None,
+            ),
+        ],
+    ),
+    "flux1-krea-dev": ModelCard(
+        model_id=ModelId("exolabs/FLUX.1-Krea-dev"),
+        storage_size=Memory.from_bytes(23802816640 + 9524621312),  # Same as dev
+        n_layers=57,
+        hidden_size=1,
+        supports_tensor=False,
+        tasks=[ModelTask.TextToImage],
+        components=[
+            ComponentInfo(
+                component_name="text_encoder",
+                component_path="text_encoder/",
+                storage_size=Memory.from_kb(0),
+                n_layers=12,
+                can_shard=False,
+                safetensors_index_filename=None,
+            ),
+            ComponentInfo(
+                component_name="text_encoder_2",
+                component_path="text_encoder_2/",
+                storage_size=Memory.from_bytes(9524621312),
+                n_layers=24,
+                can_shard=False,
+                safetensors_index_filename="model.safetensors.index.json",
+            ),
+            ComponentInfo(
+                component_name="transformer",
+                component_path="transformer/",
+                storage_size=Memory.from_bytes(23802816640),
+                n_layers=57,
+                can_shard=True,
+                safetensors_index_filename="diffusion_pytorch_model.safetensors.index.json",
+            ),
+            ComponentInfo(
+                component_name="vae",
+                component_path="vae/",
+                storage_size=Memory.from_kb(0),
+                n_layers=None,
+                can_shard=False,
+                safetensors_index_filename=None,
+            ),
+        ],
+    ),
+    "qwen-image": ModelCard(
+        model_id=ModelId("exolabs/Qwen-Image"),
+        storage_size=Memory.from_bytes(16584333312 + 40860802176),
+        n_layers=60,
+        hidden_size=1,
+        supports_tensor=False,
+        tasks=[ModelTask.TextToImage],
+        components=[
+            ComponentInfo(
+                component_name="text_encoder",
+                component_path="text_encoder/",
+                storage_size=Memory.from_bytes(16584333312),
+                n_layers=12,
+                can_shard=False,
+                safetensors_index_filename=None,
+            ),
+            ComponentInfo(
+                component_name="transformer",
+                component_path="transformer/",
+                storage_size=Memory.from_bytes(40860802176),
+                n_layers=60,
+                can_shard=True,
+                safetensors_index_filename="diffusion_pytorch_model.safetensors.index.json",
+            ),
+            ComponentInfo(
+                component_name="vae",
+                component_path="vae/",
+                storage_size=Memory.from_kb(0),
+                n_layers=None,
+                can_shard=False,
+                safetensors_index_filename=None,
+            ),
+        ],
+    ),
+    "qwen-image-edit-2509": ModelCard(
+        model_id=ModelId("exolabs/Qwen-Image-Edit-2509"),
+        storage_size=Memory.from_bytes(16584333312 + 40860802176),
+        n_layers=60,
+        hidden_size=1,
+        supports_tensor=False,
+        tasks=[ModelTask.ImageToImage],
+        components=[
+            ComponentInfo(
+                component_name="text_encoder",
+                component_path="text_encoder/",
+                storage_size=Memory.from_bytes(16584333312),
+                n_layers=12,
+                can_shard=False,
+                safetensors_index_filename=None,
+            ),
+            ComponentInfo(
+                component_name="transformer",
+                component_path="transformer/",
+                storage_size=Memory.from_bytes(40860802176),
+                n_layers=60,
+                can_shard=True,
+                safetensors_index_filename="diffusion_pytorch_model.safetensors.index.json",
+            ),
+            ComponentInfo(
+                component_name="vae",
+                component_path="vae/",
+                storage_size=Memory.from_kb(0),
+                n_layers=None,
+                can_shard=False,
+                safetensors_index_filename=None,
+            ),
+        ],
+    ),
+}
 
 
-def is_custom_card(model_id: ModelId) -> bool:
-    """Check if a model card exists in the custom cards directory."""
-    import os
+def _generate_image_model_quant_variants(
+    base_name: str,
+    base_card: ModelCard,
+) -> dict[str, ModelCard]:
+    """Create quantized variants of an image model card.
 
-    card_path = Path(str(EXO_CUSTOM_MODEL_CARDS_DIR)) / (
-        ModelId(model_id).normalize() + ".toml"
+    Only the transformer component is quantized; text encoders stay at bf16.
+    Sizes are calculated exactly from the base card's component sizes.
+    """
+    if base_card.components is None:
+        raise ValueError(f"Image model {base_name} must have components defined")
+
+    # quantizations = [8, 6, 5, 4, 3]
+    quantizations = [8, 4]
+
+    num_transformer_bytes = next(
+        c.storage_size.in_bytes
+        for c in base_card.components
+        if c.component_name == "transformer"
     )
-    return os.path.isfile(str(card_path))
+
+    transformer_bytes = Memory.from_bytes(num_transformer_bytes)
+
+    remaining_bytes = Memory.from_bytes(
+        sum(
+            c.storage_size.in_bytes
+            for c in base_card.components
+            if c.component_name != "transformer"
+        )
+    )
+
+    def with_transformer_size(new_size: Memory) -> list[ComponentInfo]:
+        assert base_card.components is not None
+        return [
+            ComponentInfo(
+                component_name=c.component_name,
+                component_path=c.component_path,
+                storage_size=new_size
+                if c.component_name == "transformer"
+                else c.storage_size,
+                n_layers=c.n_layers,
+                can_shard=c.can_shard,
+                safetensors_index_filename=c.safetensors_index_filename,
+            )
+            for c in base_card.components
+        ]
+
+    variants = {
+        base_name: ModelCard(
+            model_id=base_card.model_id,
+            storage_size=transformer_bytes + remaining_bytes,
+            n_layers=base_card.n_layers,
+            hidden_size=base_card.hidden_size,
+            supports_tensor=base_card.supports_tensor,
+            tasks=base_card.tasks,
+            components=with_transformer_size(transformer_bytes),
+        )
+    }
+
+    for quant in quantizations:
+        quant_transformer_bytes = Memory.from_bytes(
+            (num_transformer_bytes * quant) // 16
+        )
+        total_bytes = remaining_bytes + quant_transformer_bytes
+
+        model_id = ModelId(base_card.model_id + f"-{quant}bit")
+
+        variants[f"{base_name}-{quant}bit"] = ModelCard(
+            model_id=model_id,
+            storage_size=total_bytes,
+            n_layers=base_card.n_layers,
+            hidden_size=base_card.hidden_size,
+            supports_tensor=base_card.supports_tensor,
+            tasks=base_card.tasks,
+            components=with_transformer_size(quant_transformer_bytes),
+        )
+
+    return variants
+
+
+_image_model_cards: dict[str, ModelCard] = {}
+for _base_name, _base_card in _IMAGE_BASE_MODEL_CARDS.items():
+    _image_model_cards |= _generate_image_model_quant_variants(_base_name, _base_card)
+_IMAGE_MODEL_CARDS = _image_model_cards
+
+if EXO_ENABLE_IMAGE_MODELS:
+    MODEL_CARDS.update(_IMAGE_MODEL_CARDS)
 
 
 class ConfigData(BaseModel):
@@ -208,7 +767,7 @@ class ConfigData(BaseModel):
         return data
 
 
-async def fetch_config_data(model_id: ModelId) -> ConfigData:
+async def get_config_data(model_id: ModelId) -> ConfigData:
     """Downloads and parses config.json for a model."""
     from exo.download.download_utils import (
         download_file_with_retry,
@@ -230,7 +789,7 @@ async def fetch_config_data(model_id: ModelId) -> ConfigData:
         return ConfigData.model_validate_json(await f.read())
 
 
-async def fetch_safetensors_size(model_id: ModelId) -> Memory:
+async def get_safetensors_size(model_id: ModelId) -> Memory:
     """Gets model size from safetensors index or falls back to HF API."""
     from exo.download.download_utils import (
         download_file_with_retry,

src/exo/shared/tests/test_node_id_persistence.py

@@ -8,7 +8,7 @@ from multiprocessing.synchronize import Event as EventT
 from multiprocessing.synchronize import Semaphore as SemaphoreT
 
 from loguru import logger
-from pytest import LogCaptureFixture, mark
+from pytest import LogCaptureFixture
 
 from exo.routing.router import get_node_id_keypair
 from exo.shared.constants import EXO_NODE_ID_KEYPAIR
@@ -74,7 +74,6 @@ def _delete_if_exists(p: str | bytes | os.PathLike[str] | os.PathLike[bytes]):
         os.remove(p)
 
 
-@mark.skip(reason="this functionality is currently disabled but may return in future")
 def test_node_id_fetching(caplog: LogCaptureFixture):
     reps = 10
 

src/exo/shared/tracing.py

@@ -1,238 +0,0 @@
-from __future__ import annotations
-
-import json
-import time
-from collections import defaultdict
-from collections.abc import Generator
-from contextlib import contextmanager
-from contextvars import ContextVar
-from dataclasses import dataclass, field
-from pathlib import Path
-from typing import cast, final
-
-from exo.shared.constants import EXO_TRACING_ENABLED
-from exo.worker.runner.bootstrap import logger
-
-# Context variable to track the current trace category for hierarchical nesting
-_current_category: ContextVar[str | None] = ContextVar("current_category", default=None)
-
-
-@final
-@dataclass(frozen=True)
-class TraceEvent:
-    name: str
-    start_us: int
-    duration_us: int
-    rank: int
-    category: str
-
-
-@final
-@dataclass
-class CategoryStats:
-    total_us: int = 0
-    count: int = 0
-    min_us: int = 0
-    max_us: int = 0
-
-    def add(self, duration_us: int) -> None:
-        if self.count == 0:
-            self.min_us = duration_us
-            self.max_us = duration_us
-        else:
-            self.min_us = min(self.min_us, duration_us)
-            self.max_us = max(self.max_us, duration_us)
-        self.total_us += duration_us
-        self.count += 1
-
-    @property
-    def avg_us(self) -> float:
-        return self.total_us / self.count if self.count > 0 else 0.0
-
-
-@final
-@dataclass
-class TraceStats:
-    total_wall_time_us: int = 0
-    by_category: dict[str, CategoryStats] = field(default_factory=dict)
-    by_rank: dict[int, dict[str, CategoryStats]] = field(default_factory=dict)
-
-
-# Global trace buffer - each rank accumulates traces here
-_trace_buffer: list[TraceEvent] = []
-
-
-def _record_span(
-    name: str, start_us: int, duration_us: int, rank: int, category: str
-) -> None:
-    _trace_buffer.append(
-        TraceEvent(
-            name=name,
-            start_us=start_us,
-            duration_us=duration_us,
-            rank=rank,
-            category=category,
-        )
-    )
-
-
-@contextmanager
-def trace(
-    name: str,
-    rank: int,
-    category: str = "compute",
-) -> Generator[None, None, None]:
-    """Context manager to trace any operation.
-
-    Nested traces automatically inherit the parent category, creating hierarchical
-    categories like "sync/compute" or "async/comms".
-
-    Args:
-        name: Name of the operation (e.g., "recv 0", "send 1", "joint_blocks")
-        rank: This rank's ID
-        category: Category for grouping in trace viewer ("comm", "compute", "step")
-
-    Example:
-        with trace(f"sync {t}", rank, "sync"):
-            with trace("joint_blocks", rank, "compute"):
-                # Recorded with category "sync/compute"
-                hidden_states = some_computation(...)
-    """
-    if not EXO_TRACING_ENABLED:
-        yield
-        return
-
-    # Combine with parent category if nested
-    parent = _current_category.get()
-    full_category = f"{parent}/{category}" if parent else category
-
-    # Set as current for nested traces
-    token = _current_category.set(full_category)
-
-    try:
-        start_us = int(time.time() * 1_000_000)
-        start_perf = time.perf_counter()
-        yield
-        duration_us = int((time.perf_counter() - start_perf) * 1_000_000)
-        _record_span(name, start_us, duration_us, rank, full_category)
-    finally:
-        _current_category.reset(token)
-
-
-def get_trace_buffer() -> list[TraceEvent]:
-    return list(_trace_buffer)
-
-
-def clear_trace_buffer() -> None:
-    _trace_buffer.clear()
-
-
-def export_trace(traces: list[TraceEvent], output_path: Path) -> None:
-    trace_events: list[dict[str, object]] = []
-
-    for event in traces:
-        # Chrome trace format uses "X" for complete events (with duration)
-        chrome_event: dict[str, object] = {
-            "name": event.name,
-            "cat": event.category,
-            "ph": "X",
-            "ts": event.start_us,
-            "dur": event.duration_us,
-            "pid": 0,
-            "tid": event.rank,
-            "args": {"rank": event.rank},
-        }
-        trace_events.append(chrome_event)
-
-    ranks_seen = set(t.rank for t in traces)
-    for rank in ranks_seen:
-        trace_events.append(
-            {
-                "name": "thread_name",
-                "ph": "M",  # Metadata event
-                "pid": 0,
-                "tid": rank,
-                "args": {"name": f"Rank {rank}"},
-            }
-        )
-
-    chrome_trace = {"traceEvents": trace_events}
-
-    try:
-        output_path.parent.mkdir(parents=True, exist_ok=True)
-        with open(output_path, "w") as f:
-            json.dump(chrome_trace, f, indent=2)
-    except OSError as e:
-        logger.warning("Failed to export trace to %s: %s", output_path, e)
-
-
-def load_trace_file(path: Path) -> list[TraceEvent]:
-    with open(path) as f:
-        data = cast(dict[str, list[dict[str, object]]], json.load(f))
-
-    events = data.get("traceEvents", [])
-    traces: list[TraceEvent] = []
-
-    for event in events:
-        # Skip metadata events
-        if event.get("ph") == "M":
-            continue
-
-        name = str(event.get("name", ""))
-        category = str(event.get("cat", ""))
-        ts_value = event.get("ts", 0)
-        dur_value = event.get("dur", 0)
-        tid_value = event.get("tid", 0)
-        start_us = int(ts_value) if isinstance(ts_value, (int, float, str)) else 0
-        duration_us = int(dur_value) if isinstance(dur_value, (int, float, str)) else 0
-
-        # Get rank from tid or args
-        rank = int(tid_value) if isinstance(tid_value, (int, float, str)) else 0
-        args = event.get("args")
-        if isinstance(args, dict):
-            args_dict = cast(dict[str, object], args)
-            rank_from_args = args_dict.get("rank")
-            if isinstance(rank_from_args, (int, float, str)):
-                rank = int(rank_from_args)
-
-        traces.append(
-            TraceEvent(
-                name=name,
-                start_us=start_us,
-                duration_us=duration_us,
-                rank=rank,
-                category=category,
-            )
-        )
-
-    return traces
-
-
-def compute_stats(traces: list[TraceEvent]) -> TraceStats:
-    stats = TraceStats()
-
-    if not traces:
-        return stats
-
-    # Calculate wall time from earliest start to latest end
-    min_start = min(t.start_us for t in traces)
-    max_end = max(t.start_us + t.duration_us for t in traces)
-    stats.total_wall_time_us = max_end - min_start
-
-    # Initialize nested dicts
-    by_category: dict[str, CategoryStats] = defaultdict(CategoryStats)
-    by_rank: dict[int, dict[str, CategoryStats]] = defaultdict(
-        lambda: defaultdict(CategoryStats)
-    )
-
-    for event in traces:
-        # By category
-        by_category[event.category].add(event.duration_us)
-
-        # By rank and category
-        by_rank[event.rank][event.category].add(event.duration_us)
-
-    stats.by_category = dict(by_category)
-    stats.by_rank = {k: dict(v) for k, v in by_rank.items()}
-
-    return stats

src/exo/shared/types/api.py

@@ -2,7 +2,8 @@ import time
 from collections.abc import Generator
 from typing import Annotated, Any, Literal
 
-from pydantic import BaseModel, Field, field_validator
+from fastapi import UploadFile
+from pydantic import BaseModel, ConfigDict, Field, field_validator
 from pydantic_core import PydanticUseDefault
 
 from exo.shared.models.model_cards import ModelCard, ModelId
@@ -10,7 +11,7 @@ from exo.shared.types.common import CommandId, NodeId
 from exo.shared.types.memory import Memory
 from exo.shared.types.worker.instances import Instance, InstanceId, InstanceMeta
 from exo.shared.types.worker.shards import Sharding, ShardMetadata
-from exo.utils.pydantic_ext import CamelCaseModel
+from exo.utils.pydantic_ext import CamelCaseModel, TaggedModel
 
 FinishReason = Literal[
     "stop", "length", "tool_calls", "content_filter", "function_call", "error"
@@ -42,11 +43,6 @@ class ModelListModel(BaseModel):
     storage_size_megabytes: int = Field(default=0)
     supports_tensor: bool = Field(default=False)
     tasks: list[str] = Field(default=[])
-    is_custom: bool = Field(default=False)
-    family: str = Field(default="")
-    quantization: str = Field(default="")
-    base_model: str = Field(default="")
-    capabilities: list[str] = Field(default_factory=list)
 
 
 class ModelList(BaseModel):
@@ -120,8 +116,8 @@ class Usage(BaseModel):
     prompt_tokens: int
     completion_tokens: int
     total_tokens: int
-    prompt_tokens_details: PromptTokensDetails
-    completion_tokens_details: CompletionTokensDetails
+    prompt_tokens_details: PromptTokensDetails | None = None
+    completion_tokens_details: CompletionTokensDetails | None = None
 
 
 class StreamingChoiceResponse(BaseModel):
@@ -174,12 +170,10 @@ class BenchChatCompletionResponse(ChatCompletionResponse):
     generation_stats: GenerationStats | None = None
 
 
-class StreamOptions(BaseModel):
-    include_usage: bool = False
+class ChatCompletionTaskParams(TaggedModel):
+    model_config = ConfigDict(extra="ignore")
 
-
-class ChatCompletionRequest(BaseModel):
-    model: ModelId
+    model: str
     frequency_penalty: float | None = None
     messages: list[ChatCompletionMessage]
     logit_bias: dict[str, int] | None = None
@@ -192,33 +186,18 @@ class ChatCompletionRequest(BaseModel):
     seed: int | None = None
     stop: str | list[str] | None = None
     stream: bool = False
-    stream_options: StreamOptions | None = None
     temperature: float | None = None
     top_p: float | None = None
-    top_k: int | None = None
     tools: list[dict[str, Any]] | None = None
     tool_choice: str | dict[str, Any] | None = None
     parallel_tool_calls: bool | None = None
     user: str | None = None
 
 
-class BenchChatCompletionRequest(ChatCompletionRequest):
+class BenchChatCompletionTaskParams(ChatCompletionTaskParams):
     pass
 
 
-class AddCustomModelParams(BaseModel):
-    model_id: ModelId
-
-
-class HuggingFaceSearchResult(BaseModel):
-    id: str
-    author: str = ""
-    downloads: int = 0
-    likes: int = 0
-    last_modified: str = ""
-    tags: list[str] = Field(default_factory=list)
-
-
 class PlaceInstanceParams(BaseModel):
     model_id: ModelId
     sharding: Sharding = Sharding.Pipeline
@@ -299,7 +278,28 @@ class BenchImageGenerationTaskParams(ImageGenerationTaskParams):
 
 
 class ImageEditsTaskParams(BaseModel):
-    """Internal task params for image-editing requests."""
+    image: UploadFile
+    prompt: str
+    background: str | None = None
+    input_fidelity: float | None = None
+    mask: UploadFile | None = None
+    model: str
+    n: int | None = 1
+    output_compression: int | None = None
+    output_format: Literal["png", "jpeg", "webp"] = "png"
+    partial_images: int | None = 0
+    quality: Literal["high", "medium", "low"] | None = "medium"
+    response_format: Literal["url", "b64_json"] | None = "b64_json"
+    size: str | None = "1024x1024"
+    stream: bool | None = False
+    user: str | None = None
+    advanced_params: AdvancedImageParams | None = None
+    # Internal flag for benchmark mode - set by API, preserved through serialization
+    bench: bool = False
+
+
+class ImageEditsInternalParams(BaseModel):
+    """Serializable version of ImageEditsTaskParams for distributed task execution."""
 
     image_data: str = ""  # Base64-encoded image (empty when using chunked transfer)
     total_input_chunks: int = 0
@@ -368,45 +368,3 @@ class StartDownloadResponse(CamelCaseModel):
 
 class DeleteDownloadResponse(CamelCaseModel):
     command_id: CommandId
-
-
-class TraceEventResponse(CamelCaseModel):
-    name: str
-    start_us: int
-    duration_us: int
-    rank: int
-    category: str
-
-
-class TraceResponse(CamelCaseModel):
-    task_id: str
-    traces: list[TraceEventResponse]
-
-
-class TraceCategoryStats(CamelCaseModel):
-    total_us: int
-    count: int
-    min_us: int
-    max_us: int
-    avg_us: float
-
-
-class TraceRankStats(CamelCaseModel):
-    by_category: dict[str, TraceCategoryStats]
-
-
-class TraceStatsResponse(CamelCaseModel):
-    task_id: str
-    total_wall_time_us: int
-    by_category: dict[str, TraceCategoryStats]
-    by_rank: dict[int, TraceRankStats]
-
-
-class TraceListItem(CamelCaseModel):
-    task_id: str
-    created_at: str
-    file_size: int
-
-
-class TraceListResponse(CamelCaseModel):
-    traces: list[TraceListItem]