Retry tracker registration when initial connect fails.

Start background re-registration when the tracker is unreachable at startup so nodes do not stay permanently unregistered.

Co-authored-by: Cursor <cursoragent@cursor.com>

.claude/memory/project-status.md

@@ -44,3 +44,5 @@ Historical handoff note: `/mnt/c/Users/popov/Downloads/neuron-tai-alpha-handoff-
 - Follow-up fix: preset-model startup now starts the heartbeat thread after registration; without this, the node appeared briefly on the dashboard and was purged on first inference/route after heartbeat expiry. Tracker dashboard now has a "Console output" panel backed by `/v1/console` for node register/expiry, routing failures, and proxy events.
 - Qwen3.6-35B-A3B reserve-based split is expected: an 79 GB CPU node may be assigned layers 0-36, and a second node fills 37-39. Do not "fix" this by bypassing the 20% assignment reserve unless the shard-planning policy changes.
 - Route hardening: tracker chat proxy and `/v1/route` diagnostics now use alias-aware preset node matching for split Qwen3.6 routes; dashboard derives grouped inference history from proxy route/complete console events and shows observed TPS after completion.
+- Live proxy hardening: model lookup trims outer whitespace before alias matching (`qwen3.6-35b-a3b ` resolves), and tracker route logs/dashboard queue depth combine heartbeat queue with tracker-local proxy in-flight counts so Postman-style bursts no longer show every selected route as queue `0`.
+- Split-shard streaming hardening: Qwen3.6-style distributed generation now emits SSE chunks token-by-token from the head node instead of buffering all generated text until completion. Tracker direct/relay stream proxy logs `proxy progress` with live tokens/TPS, dashboard Inference history shows currently processing requests with live TPS/tokens/queue, and relay stream completion no longer references an undefined `session_id`.

.gitignore

@@ -19,3 +19,4 @@ dist/
 !.env.testnet
 .rocm-local/*
 billing.sqlite
+.pytest-tmp/*

QUICKSTART.md

@@ -98,6 +98,7 @@ Nodes can then join with either the LAN tracker URL or the public URL:
 ```bash
 .venv/bin/meshnet-node start --tracker http://192.168.0.179:8080 --model Qwen/Qwen2.5-0.5B-Instruct
 .venv/bin/meshnet-node start --tracker https://ai.neuron.d-popov.com --model Qwen/Qwen2.5-0.5B-Instruct
+.venv/bin/meshnet-node start --tracker https://ai.d-popov.com --model Qwen/Qwen2.5-0.5B-Instruct
 ```
 
 ### Windows / WSL2

docs/issues/44-tracker-shard-source-partial-download.md

@@ -75,7 +75,7 @@ What exists already (build on it, don't duplicate):
 - [x] Node downloader keeps exact-shard peers first, then races tracker model
   sources against a HuggingFace `snapshot_download(..., allow_patterns=...)`
   subset download, using the first successful source.
-- [ ] When no tracker model source is available at all, the HuggingFace
+- [x] When no tracker model source is available at all, the HuggingFace
   fallback still computes `allow_patterns` from the repo's own
   `model.safetensors.index.json` (fetched directly, not via the tracker) —
   it never silently downloads the full model just because the tracker has
@@ -95,7 +95,9 @@ What exists already (build on it, don't duplicate):
 
 - 2026-07-06: Added the tracker/node download path. For immediate Qwen3.6-35B
   LAN testing, real PyTorch nodes fetch the full snapshot from the tracker via
-  `full_url` and race HuggingFace as fallback. Remaining hard half is true
+  `full_url`; HuggingFace remains fallback-only, and when it is used the node
-  partial model materialization: the backend can prefer a downloaded local
+  computes `allow_patterns` from the repo's remote SafeTensors index so it
-  model directory, but Transformers still needs a `meta`-device load path that
+  stays layer-filtered even without tracker-cached files. Remaining hard half
-  materializes only assigned layers.
+  is true partial model materialization: the backend can prefer a downloaded
+  local model directory, but Transformers still needs a `meta`-device load
+  path that materializes only assigned layers.

packages/node/meshnet_node/cli.py

@@ -52,7 +52,7 @@ def _run_node(cfg: dict) -> None:
         node = run_startup(
             tracker_url=cfg["tracker_url"],
             port=cfg.get("port", 7000),
-            model=cfg.get("model_name") or "stub-model",
+            model=cfg.get("model_name") or None,
             model_id=cfg.get("model_hf_repo") or None,
             shard_start=cfg.get("shard_start"),
             shard_end=cfg.get("shard_end"),
@@ -90,6 +90,19 @@ def _run_node(cfg: dict) -> None:
         )
 
 
+def _resolve_model_flags(
+    model: str | None,
+    model_id: str | None,
+) -> tuple[str | None, str | None]:
+    """Return (model_name, hf_repo_or_none) from --model / --model-id flags."""
+    explicit = model_id or model
+    if not explicit:
+        return None, None
+    if "/" in explicit:
+        return explicit.split("/")[-1], explicit
+    return explicit, None
+
+
 def _first_available_port(host: str, start: int = 7000, attempts: int = 100) -> int:
     """Return the first TCP port bindable on host, starting at start."""
     bind_host = "" if host == "0.0.0.0" else host
@@ -122,9 +135,10 @@ def _cmd_default(args) -> int:
 
     # Apply CLI overrides on top of saved config
     overrides: dict = {}
-    if args.model:
+    model_name, hf_repo = _resolve_model_flags(args.model, getattr(args, "model_id", None))
-        overrides["model_hf_repo"] = args.model
+    if model_name is not None:
-        overrides["model_name"] = args.model.split("/")[-1]
+        overrides["model_name"] = model_name
+        overrides["model_hf_repo"] = hf_repo or ""
     if args.quantization:
         overrides["quantization"] = args.quantization
     if args.download_dir:
@@ -215,16 +229,15 @@ def _cmd_start(args) -> int:
     if args.tracker:
         cfg["tracker_url"] = args.tracker
     cfg["port"] = args.port if args.port is not None else _first_available_port(args.host)
-    model = args.model or cfg.get("model_hf_repo") or cfg.get("model_name") or "stub-model"
+    model_name, hf_repo = _resolve_model_flags(
-    if args.model_id is None and "/" in model:
+        args.model or cfg.get("model_hf_repo") or cfg.get("model_name") or None,
-        cfg["model_hf_repo"] = model
+        args.model_id,
-        cfg["model_name"] = model.split("/")[-1]
+    )
-    else:
+    if model_name is not None:
-        cfg["model_name"] = model
+        cfg["model_name"] = model_name
+        cfg["model_hf_repo"] = hf_repo or ""
     cfg["quantization"] = args.quantization
     cfg["host"] = args.host
-    if args.model_id:
-        cfg["model_hf_repo"] = args.model_id
     if args.shard_start is not None:
         cfg["shard_start"] = args.shard_start
     if args.shard_end is not None:
@@ -242,7 +255,7 @@ def _cmd_start(args) -> int:
             tracker_url=cfg["tracker_url"],
             port=cfg["port"],
             model=cfg["model_name"],
-            model_id=cfg.get("model_hf_repo"),
+            model_id=cfg.get("model_hf_repo") or None,
             shard_start=cfg.get("shard_start"),
             shard_end=cfg.get("shard_end"),
             quantization=cfg["quantization"].replace("bf16", "bfloat16"),
@@ -288,7 +301,8 @@ def main() -> None:
     )
 
     # Flags that apply to the no-subcommand (default) path
-    parser.add_argument("--model", metavar="HF_REPO", help="HuggingFace repo ID to serve")
+    parser.add_argument("--model", metavar="MODEL", help="Model name or HuggingFace repo ID to serve")
+    parser.add_argument("--model-id", metavar="MODEL", help="Alias for --model (catalog name or HuggingFace repo)")
     parser.add_argument("--quantization", "-q", choices=["bf16", "int8", "nf4", "bfloat16"],
                         help="Quantization level")
     parser.add_argument("--download-dir", metavar="PATH", help="Model download directory")
@@ -329,8 +343,8 @@ def main() -> None:
     start_cmd = subparsers.add_parser("start", help="Start node (legacy flags)")
     start_cmd.add_argument("--tracker")
     start_cmd.add_argument("--port", type=int)
-    start_cmd.add_argument("--model")
+    start_cmd.add_argument("--model", help="Model name or HuggingFace repo ID")
-    start_cmd.add_argument("--model-id", help="HuggingFace repo ID")
+    start_cmd.add_argument("--model-id", help="Alias for --model (catalog name or HuggingFace repo)")
     start_cmd.add_argument("--shard-start", type=int)
     start_cmd.add_argument("--shard-end", type=int)
     start_cmd.add_argument("--quantization", choices=["auto", "bfloat16", "int8", "nf4", "bf16"], default="auto")

packages/node/meshnet_node/downloader.py

@@ -1,4 +1,4 @@
-"""Shard downloader — fetches model shards from peers or HuggingFace Hub.
+"""Shard downloader — fetches model files from peers, tracker sources, or HuggingFace.
 
 Cache layout: ~/.cache/meshnet/shards/<model>/
 

packages/node/meshnet_node/model_backend.py

@@ -4,6 +4,7 @@ from __future__ import annotations
 
 import base64
 from dataclasses import dataclass
+import json
 from pathlib import Path
 from typing import Any, Literal
 
@@ -22,6 +23,10 @@ class InsufficientVRAMError(ModelBackendError):
     """Raised when a requested shard cannot fit in available CUDA memory."""
 
 
+class PartialModelLoadUnsupported(ModelBackendError):
+    """Raised when a shard cannot be materialized from a local snapshot subset."""
+
+
 @dataclass(frozen=True)
 class TensorPayload:
     body: bytes
@@ -94,20 +99,39 @@ class TorchModelShard:
             None if load_source != model_id else cache_dir,
         )
         try:
-            load_kwargs = {
+            total_layers_hint = _total_layers_for_local_snapshot(AutoConfig, load_source)
-                "device_map": "auto" if uses_quantized_weights else None,
+            if _should_partial_materialize_shard(
-                "dtype": dtype,
-                "low_cpu_mem_usage": True,
-                "cache_dir": str(cache_dir) if cache_dir is not None and load_source == model_id else None,
-            }
-            if quant_config is not None:
-                load_kwargs["quantization_config"] = quant_config
-            self.model = AutoModelForCausalLM.from_pretrained(
                 load_source,
-                **load_kwargs,
+                shard_start,
-            )
+                shard_end,
-            if not uses_quantized_weights:
+                total_layers_hint=total_layers_hint,
-                self.model.to(self.device)
+                uses_quantized_weights=uses_quantized_weights,
+            ):
+                self.model = _load_partial_model_from_snapshot(
+                    AutoConfig,
+                    AutoModelForCausalLM,
+                    torch,
+                    load_source,
+                    shard_start,
+                    shard_end,
+                    dtype,
+                    self.device,
+                )
+            else:
+                load_kwargs = {
+                    "device_map": "auto" if uses_quantized_weights else None,
+                    "dtype": dtype,
+                    "low_cpu_mem_usage": True,
+                    "cache_dir": str(cache_dir) if cache_dir is not None and load_source == model_id else None,
+                }
+                if quant_config is not None:
+                    load_kwargs["quantization_config"] = quant_config
+                self.model = AutoModelForCausalLM.from_pretrained(
+                    load_source,
+                    **load_kwargs,
+                )
+                if not uses_quantized_weights:
+                    self.model.to(self.device)
         except Exception as exc:
             if _looks_like_oom(exc):
                 raise InsufficientVRAMError(
@@ -357,6 +381,135 @@ def load_torch_shard(
     return TorchModelShard(model_id, shard_start, shard_end, quantization, cache_dir)
 
 
+def _total_layers_for_local_snapshot(auto_config: Any, load_source: str) -> int | None:
+    snapshot_dir = Path(load_source)
+    if not (snapshot_dir / "config.json").exists():
+        return None
+    from .model_catalog import layers_from_config
+
+    try:
+        cfg = auto_config.from_pretrained(str(snapshot_dir))
+    except Exception:
+        return None
+    return layers_from_config(cfg)
+
+
+def _should_partial_materialize_shard(
+    load_source: str,
+    shard_start: int,
+    shard_end: int,
+    *,
+    total_layers_hint: int | None,
+    uses_quantized_weights: bool,
+) -> bool:
+    if uses_quantized_weights:
+        return False
+    snapshot_dir = Path(load_source)
+    if not snapshot_dir.exists() or not (snapshot_dir / "config.json").exists():
+        return False
+    if not (snapshot_dir / "model.safetensors.index.json").exists():
+        return False
+    if total_layers_hint is None:
+        return False
+    return not (shard_start == 0 and shard_end >= total_layers_hint - 1)
+
+
+def _load_partial_model_from_snapshot(
+    auto_config: Any,
+    auto_model_for_causal_lm: Any,
+    torch: Any,
+    load_source: str,
+    shard_start: int,
+    shard_end: int,
+    dtype: Any,
+    device: Any,
+    *,
+    init_empty_weights_fn: Any | None = None,
+    set_tensor_fn: Any | None = None,
+    safe_open_fn: Any | None = None,
+) -> Any:
+    from .model_catalog import layers_from_config
+    from .safetensors_selection import (
+        INDEX_FILENAME,
+        select_tensor_names_for_layers_from_index,
+    )
+
+    if init_empty_weights_fn is None:
+        from accelerate import init_empty_weights as init_empty_weights_fn
+    if set_tensor_fn is None:
+        from accelerate.utils import set_module_tensor_to_device as set_tensor_fn
+    if safe_open_fn is None:
+        from safetensors import safe_open as safe_open_fn
+
+    snapshot_dir = Path(load_source)
+    cfg = auto_config.from_pretrained(str(snapshot_dir))
+    total_layers = layers_from_config(cfg)
+    if total_layers is None:
+        raise PartialModelLoadUnsupported(
+            f"could not determine num_hidden_layers for local snapshot {snapshot_dir}"
+        )
+    if shard_end >= total_layers:
+        raise ValueError(
+            f"shard_end {shard_end} exceeds last layer index {total_layers - 1}"
+        )
+
+    index_path = snapshot_dir / INDEX_FILENAME
+    try:
+        index = json.loads(index_path.read_text(encoding="utf-8"))
+    except FileNotFoundError as exc:
+        raise PartialModelLoadUnsupported(
+            f"missing SafeTensors index for partial load: {index_path}"
+        ) from exc
+    weight_map = index.get("weight_map")
+    if not isinstance(weight_map, dict):
+        raise PartialModelLoadUnsupported(f"{INDEX_FILENAME} must contain a weight_map object")
+
+    tensor_names = select_tensor_names_for_layers_from_index(
+        weight_map,
+        shard_start,
+        shard_end,
+        total_layers=total_layers,
+    )
+    if not tensor_names:
+        raise PartialModelLoadUnsupported(
+            f"no checkpoint tensors matched layers {shard_start}-{shard_end} in {snapshot_dir}"
+        )
+
+    with init_empty_weights_fn():
+        model = auto_model_for_causal_lm.from_config(cfg, torch_dtype=dtype)
+    tie_weights = getattr(model, "tie_weights", None)
+    if callable(tie_weights):
+        tie_weights()
+
+    tensors_by_file: dict[str, list[str]] = {}
+    for tensor_name in sorted(tensor_names):
+        rel_file = weight_map.get(tensor_name)
+        if not isinstance(rel_file, str):
+            continue
+        tensors_by_file.setdefault(rel_file, []).append(tensor_name)
+
+    for rel_file, names in tensors_by_file.items():
+        checkpoint_file = snapshot_dir / rel_file
+        if not checkpoint_file.exists():
+            raise PartialModelLoadUnsupported(
+                f"checkpoint file advertised in {INDEX_FILENAME} is missing: {checkpoint_file}"
+            )
+        with safe_open_fn(str(checkpoint_file), framework="pt", device="cpu") as handle:
+            for tensor_name in names:
+                set_tensor_fn(
+                    model,
+                    tensor_name,
+                    device,
+                    value=handle.get_tensor(tensor_name),
+                    dtype=dtype,
+                )
+
+    for module in _active_modules_for_shard(model, shard_start, shard_end):
+        if hasattr(module, "to"):
+            module.to(device)
+    return model
+
+
 def _model_load_plan(
     auto_config: Any,
     model_id: str,
@@ -442,6 +595,37 @@ def _position_embeddings(model: Any) -> Any | None:
     return None
 
 
+def _rotary_embedding_module(model: Any) -> Any | None:
+    if hasattr(model, "model") and hasattr(model.model, "rotary_emb"):
+        return model.model.rotary_emb
+    if hasattr(model, "transformer") and hasattr(model.transformer, "rotary_emb"):
+        return model.transformer.rotary_emb
+    return None
+
+
+def _active_modules_for_shard(model: Any, shard_start: int, shard_end: int) -> list[Any]:
+    active: list[Any] = []
+
+    def add(module: Any | None) -> None:
+        if module is None:
+            return
+        if any(existing is module for existing in active):
+            return
+        active.append(module)
+
+    if shard_start == 0:
+        add(_embed_tokens(model))
+        add(_position_embeddings(model))
+    add(_rotary_embedding_module(model))
+    for layer in _model_layers(model)[shard_start:shard_end + 1]:
+        add(layer)
+    total_layers = len(_model_layers(model))
+    if shard_end >= total_layers - 1:
+        add(_final_norm(model))
+        add(getattr(model, "lm_head", None))
+    return active
+
+
 def _final_norm(model: Any) -> Any | None:
     if hasattr(model, "model") and hasattr(model.model, "norm"):
         return model.model.norm
@@ -485,11 +669,7 @@ def _rotary_position_embeddings(model: Any, hidden_states: Any, position_ids: An
     """Return model-level rotary embeddings required by newer HF decoder layers."""
     if position_ids is None:
         return None
-    rotary = None
+    rotary = _rotary_embedding_module(model)
-    if hasattr(model, "model") and hasattr(model.model, "rotary_emb"):
-        rotary = model.model.rotary_emb
-    elif hasattr(model, "transformer") and hasattr(model.transformer, "rotary_emb"):
-        rotary = model.transformer.rotary_emb
     if rotary is None:
         return None
     return rotary(hidden_states, position_ids)

packages/node/meshnet_node/safetensors_selection.py

@@ -118,6 +118,23 @@ def select_files_for_layers_from_index(
     return selected
 
 
+def select_tensor_names_for_layers_from_index(
+    weight_map: dict[str, str],
+    start_layer: int,
+    end_layer: int,
+    *,
+    total_layers: int | None = None,
+) -> set[str]:
+    """Pure variant that returns checkpoint tensor names instead of file paths."""
+    selected: set[str] = set()
+    for tensor_name, rel_file in weight_map.items():
+        if not isinstance(tensor_name, str) or not isinstance(rel_file, str):
+            continue
+        if _tensor_belongs_to_range(tensor_name, start_layer, end_layer, total_layers):
+            selected.add(tensor_name)
+    return selected
+
+
 def _tensor_belongs_to_range(
     tensor_name: str,
     start_layer: int,

packages/node/meshnet_node/startup.py

@@ -331,6 +331,9 @@ def _attach_relay_bridge(node: StubNodeServer | TorchNodeServer, bridge: RelayHt
     node.stop = _stop_with_bridge  # type: ignore[method-assign]
 
 
+_PENDING_NODE_ID = "pending"
+
+
 def _start_heartbeat(
     tracker_url: str,
     node_id: str,
@@ -368,10 +371,33 @@ def _start_heartbeat(
         try:
             resp = _post_json(f"{tracker_url}/v1/nodes/register", register_payload)
             node_id = resp.get("node_id", node_id)
+            if node_ref is not None:
+                setattr(node_ref, "tracker_node_id", node_id)
             return True
         except Exception:
             return False
 
+    def _register_additional_assignment(applied: dict) -> None:
+        model_id = str(applied.get("model") or register_payload.get("hf_repo") or register_payload.get("model"))
+        extra_payload = {
+            **register_payload,
+            "model": model_id.split("/")[-1],
+            "hf_repo": model_id if "/" in model_id else register_payload.get("hf_repo"),
+            "shard_start": applied["shard_start"],
+            "shard_end": applied["shard_end"],
+            "quantization": applied.get("quantization", register_payload.get("quantization")),
+            "tracker_mode": bool(applied.get("tracker_mode", False)),
+            "managed_assignment": True,
+        }
+        try:
+            reg_resp = _post_json(f"{tracker_url}/v1/nodes/register", extra_payload)
+            print(
+                f"  [node] registered additional model — node ID: {reg_resp.get('node_id')}",
+                flush=True,
+            )
+        except Exception as exc:
+            print(f"  [node] WARNING: additional model registration failed: {exc}", flush=True)
+
     def _apply_directives(directives: list[dict]) -> None:
         if not directives:
             return
@@ -384,6 +410,9 @@ def _start_heartbeat(
             print(f"  [node] WARNING: failed to apply tracker directives: {exc}", flush=True)
             return
         if applied:
+            if applied.get("action") == "ADD_SHARD":
+                _register_additional_assignment(applied)
+                return
             model_id = applied.get("model", register_payload.get("hf_repo") or register_payload.get("model"))
             register_payload["model"] = str(model_id).split("/")[-1]
             register_payload["hf_repo"] = model_id
@@ -395,7 +424,7 @@ def _start_heartbeat(
     def _loop() -> None:
         nonlocal node_id
         hb_url = f"{tracker_url}/v1/nodes/{node_id}/heartbeat"
-        outage_streak = 0  # consecutive intervals where tracker was unreachable
+        outage_streak = 1 if node_id == _PENDING_NODE_ID else 0
 
         while True:
             time.sleep(interval)
@@ -423,11 +452,12 @@ def _start_heartbeat(
                 new_asgn = resp.get("new_assignment")
                 if new_asgn:
                     print(
-                        f"  [node] tracker reassignment received: "
+                        f"  [node] tracker assignment received: "
-                        f"model={new_asgn.get('model')!r} "
+                        f"action={new_asgn.get('action')!r} model={new_asgn.get('model')!r} "
                         f"shards={new_asgn.get('shard_start')}-{new_asgn.get('shard_end')}",
                         flush=True,
                     )
+                    _apply_directives([new_asgn])
             except urllib.error.HTTPError as exc:
                 if exc.code == 404:
                     # Node was purged (e.g. long gap before restart noticed) — re-register now.
@@ -449,6 +479,34 @@ def _start_heartbeat(
     return t
 
 
+def _register_with_tracker(
+    tracker_url: str,
+    reg_payload: dict,
+    node: Any,
+    start_time: float,
+) -> str | None:
+    """Register with the tracker, or start background retries when it is unreachable."""
+    try:
+        reg_resp = _post_json(f"{tracker_url}/v1/nodes/register", reg_payload)
+        tracker_node_id = str(reg_resp.get("node_id") or "?")
+        setattr(node, "tracker_node_id", tracker_node_id)
+        print(f"  Registered with tracker — node ID: {tracker_node_id}", flush=True)
+        _start_heartbeat(tracker_url, tracker_node_id, reg_payload, node_ref=node, start_time=start_time)
+        return tracker_node_id
+    except Exception as exc:
+        setattr(node, "tracker_node_id", None)
+        print(f"  Warning: tracker registration failed: {exc}", flush=True)
+        print("  [node] will retry registration in the background", flush=True)
+        _start_heartbeat(
+            tracker_url,
+            _PENDING_NODE_ID,
+            reg_payload,
+            node_ref=node,
+            start_time=start_time,
+        )
+        return None
+
+
 def _warn_virtual_network_ip(ip: str | None) -> None:
     """Print a warning when the auto-detected advertise IP is in a known virtual-network range.
 
@@ -482,7 +540,7 @@ def _warn_virtual_network_ip(ip: str | None) -> None:
 def run_startup(
     tracker_url: str,
     port: int = 0,
-    model: str = "stub-model",
+    model: str | None = None,
     model_id: str | None = None,
     shard_start: int | None = None,
     shard_end: int | None = None,
@@ -608,8 +666,11 @@ def run_startup(
     if probationary_line is not None:
         print(f"  {probationary_line}", flush=True)
 
+    pinned_shard_start = shard_start
+    pinned_shard_end = shard_end
+    user_pinned_shard = pinned_shard_start is not None or pinned_shard_end is not None
+
     if model_id:  # treat "" the same as None — no explicit model given
-        user_pinned_shard = shard_start is not None or shard_end is not None
         full_sources: list[dict] = []
         # Auto-detect shard range from model config if not explicitly provided
         if shard_start is None or shard_end is None:
@@ -668,6 +729,7 @@ def run_startup(
             route_timeout=route_timeout,
             cache_dir=cache_dir,
             debug=debug,
+            max_loaded_shards=max_loaded_shards,
         )
         _node_start_time = time.monotonic()
         actual_port = node.start()
@@ -720,16 +782,9 @@ def run_startup(
             **registration_capabilities,
             **relay_fields,
         }
-        tracker_node_id: str | None = None
+        tracker_node_id = _register_with_tracker(
-        try:
+            tracker_url, reg_payload, node, _node_start_time,
-            reg_resp = _post_json(f"{tracker_url}/v1/nodes/register", reg_payload)
+        )
-            tracker_node_id = str(reg_resp.get("node_id") or "?")
-            setattr(node, "tracker_node_id", tracker_node_id)
-            print(f"  Registered with tracker — node ID: {tracker_node_id}", flush=True)
-            _start_heartbeat(tracker_url, tracker_node_id, reg_payload, node_ref=node, start_time=_node_start_time)
-        except Exception as exc:
-            setattr(node, "tracker_node_id", None)
-            print(f"  Warning: tracker registration failed: {exc}", flush=True)
 
         print(
             f"\n{'=' * 32}\n"
@@ -747,16 +802,17 @@ def run_startup(
             flush=True,
         )
         return node
-    if shard_start is not None or shard_end is not None:
+    if user_pinned_shard and not model:
-        raise ValueError("--shard-start / --shard-end require --model-id")
+        raise ValueError("--shard-start / --shard-end require --model")
 
     # 3a. Auto-join: query tracker for network-wide HF model assignment.
     # Skipped when the user explicitly requested a model — the shard-assignment
     # query below (/v1/nodes/assign?model=…) is authoritative there, and a fresh
     # tracker would otherwise print a scary 503 for the model-less auto-join.
     net_assignment: dict = {}
-    if model and model != "stub-model":
+    if model_id or (model and model != "stub-model"):
-        print(f"Model {model!r} requested explicitly — skipping network auto-join.", flush=True)
+        if model:
+            print(f"Model {model!r} requested explicitly — skipping network auto-join.", flush=True)
     else:
         print("Querying tracker for network assignment...", flush=True)
         assign_qs = urllib.parse.urlencode({"device": device, "vram_mb": assignment_vram_mb, "ram_mb": ram_mb})
@@ -767,17 +823,25 @@ def run_startup(
     assigned_hf_repo: str | None = net_assignment.get("hf_repo")
     _gap_found: bool = bool(net_assignment.get("gap_found", False))
 
-    if assigned_hf_repo and _gap_found:
+    if assigned_hf_repo:
         assigned_shard_start: int = net_assignment["shard_start"]
         assigned_shard_end: int = net_assignment["shard_end"]
         assigned_num_layers: int = net_assignment["num_layers"]
         assigned_model_sources: list[dict] = net_assignment.get("model_sources", [])
-        print(
+        if _gap_found:
-            f"  Assigned: {assigned_hf_repo} "
+            print(
-            f"layers {assigned_shard_start}–{assigned_shard_end} "
+                f"  Assigned gap: {assigned_hf_repo} "
-            f"(of {assigned_num_layers})",
+                f"layers {assigned_shard_start}–{assigned_shard_end} "
-            flush=True,
+                f"(of {assigned_num_layers})",
-        )
+                flush=True,
+            )
+        else:
+            print(
+                f"  Assigned redundant copy: {assigned_hf_repo} "
+                f"layers {assigned_shard_start}–{assigned_shard_end} "
+                f"(of {assigned_num_layers})",
+                flush=True,
+            )
         full_sources = [] if tracker_source_disabled else _full_model_sources(assigned_model_sources)
         if full_sources:
             print("Downloading assigned model snapshot...", flush=True)
@@ -801,6 +865,7 @@ def run_startup(
             route_timeout=route_timeout,
             cache_dir=cache_dir,
             debug=debug,
+            max_loaded_shards=max_loaded_shards,
         )
         _node_start_time = time.monotonic()
         actual_port = node.start()
@@ -845,16 +910,9 @@ def run_startup(
             **registration_capabilities,
             **relay_fields,
         }
-        tracker_node_id = None
+        tracker_node_id = _register_with_tracker(
-        try:
+            tracker_url, auto_reg_payload, node, _node_start_time,
-            reg_resp = _post_json(f"{tracker_url}/v1/nodes/register", auto_reg_payload)
+        )
-            tracker_node_id = str(reg_resp.get("node_id") or "?")
-            setattr(node, "tracker_node_id", tracker_node_id)
-            print(f"  Registered with tracker — node ID: {tracker_node_id}", flush=True)
-            _start_heartbeat(tracker_url, tracker_node_id, auto_reg_payload, node_ref=node, start_time=_node_start_time)
-        except Exception as exc:
-            setattr(node, "tracker_node_id", None)
-            print(f"  Warning: tracker registration failed: {exc}", flush=True)
         shard_count = assigned_shard_end - assigned_shard_start + 1
         print(
             f"\n{'=' * 32}\n"
@@ -874,10 +932,16 @@ def run_startup(
         )
         return node
 
-    # 3b. Shard assignment from tracker (stub-model / preset-based path)
+    if not assigned_hf_repo and model is None:
+        raise RuntimeError(
+            "Tracker did not assign a model. Join a network that already serves one, "
+            "or start with --model <HF_REPO>."
+        )
+
+    # 3b. Stub preset path (tests / explicit stub-model) or named preset models.
     print("Querying tracker for shard assignment...", flush=True)
     assign_qs = urllib.parse.urlencode({
-        "model": model,
+        "model": model or "stub-model",
         "device": device,
         # CPU-mode nodes must be sized by RAM: a detected-but-unusable GPU's
         # VRAM would otherwise cap the shard (e.g. 8 GB VRAM → 3 layers on a
@@ -891,14 +955,25 @@ def run_startup(
         print(f"  ERROR: Cannot reach tracker at {tracker_url}: {exc}", file=sys.stderr, flush=True)
         raise
 
-    shard_start: int = assignment["shard_start"]
+    shard_start = assignment["shard_start"]
-    shard_end: int = assignment["shard_end"]
+    shard_end = assignment["shard_end"]
+    if user_pinned_shard:
+        if pinned_shard_start is not None:
+            shard_start = pinned_shard_start
+        if pinned_shard_end is not None:
+            shard_end = pinned_shard_end
     assigned_model: str = assignment.get("model", model)
     hf_repo: str | None = assignment.get("hf_repo")
     peers: list[dict] = assignment.get("peers", [])
     model_sources: list[dict] = [] if tracker_source_disabled else assignment.get("model_sources", [])
     assignment_bytes_per_layer = _assignment_bytes_per_layer(assignment, quantization)
-    print(f"  Shard: layers {shard_start}-{shard_end} of {assigned_model}", flush=True)
+    if user_pinned_shard:
+        print(
+            f"  Shard: layers {shard_start}-{shard_end} of {assigned_model} (pinned)",
+            flush=True,
+        )
+    else:
+        print(f"  Shard: layers {shard_start}-{shard_end} of {assigned_model}", flush=True)
 
     # 4. Download shard
     print("Downloading shard...", flush=True)
@@ -960,6 +1035,7 @@ def run_startup(
         "hardware_profile": hw,
         "wallet_address": address,
         "score": 1.0,
+        "managed_assignment": not user_pinned_shard,
         **registration_capabilities,
         **relay_fields,
     }

packages/node/meshnet_node/torch_server.py

@@ -75,20 +75,39 @@ class _TorchHTTPServer(http.server.HTTPServer):
         tracker_url: str | None = None,
         route_timeout: float = 30.0,
         debug: bool = False,
+        max_loaded_shards: int = 1,
     ):
         super().__init__(addr, handler)
         self.backend = backend
+        self.backends: dict[str, TorchModelShard] = {backend.model_id: backend}
         self.received_activations = False
         self.forward_chunk_count = 0
         self.tracker_mode = tracker_mode
         self.tracker_url = tracker_url
         self.route_timeout = route_timeout
         self.debug = debug
+        self.max_loaded_shards = max(1, max_loaded_shards)
         self.total_requests: int = 0
         self.failed_requests: int = 0
         self.queue_depth: int = 0
         self._stats_lock = threading.Lock()
 
+    def resolve_backend(self, model_name: str | None) -> TorchModelShard | None:
+        if not model_name:
+            return self.backend
+        wanted = model_name.strip().lower()
+        for key, shard_backend in self.backends.items():
+            key_l = key.lower()
+            if key_l == wanted or key_l.rsplit("/", 1)[-1] == wanted:
+                return shard_backend
+        return self.backend
+
+    def chat_enabled(self) -> bool:
+        return any(
+            shard_backend.is_head
+            for shard_backend in self.backends.values()
+        )
+
 
 class _TorchHandler(http.server.BaseHTTPRequestHandler):
     def log_message(self, fmt, *args):  # noqa: suppress request logs in tests
@@ -100,7 +119,7 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
             self._handle_forward()
         elif self.path == "/v1/infer":
             self._handle_infer()
-        elif self.path == "/v1/chat/completions" and server.tracker_mode:
+        elif self.path == "/v1/chat/completions" and server.chat_enabled():
             self._handle_chat_completions()
         else:
             self.send_response(404)
@@ -284,22 +303,26 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
             messages = []
         stream = bool(body.get("stream", False))
         model_name = str(body.get("model", ""))
+        backend = server.resolve_backend(model_name)
+        if backend is None or not backend.is_head:
+            self._send_json(400, {"error": "model not loaded on this node"})
+            return
         max_tokens = int(body.get("max_tokens") or body.get("max_new_tokens") or 256)
         temperature = float(body.get("temperature") or 1.0)
         top_p = float(body.get("top_p") or 1.0)
 
         # Fast path: this node owns the complete model — use HF generate() with KV cache.
         # Avoids the single-token-per-forward-pass limitation of the distributed path.
-        if server.backend.is_head and server.backend.is_tail:
+        if backend.is_head and backend.is_tail:
             try:
                 if stream:
                     self._stream_openai_response(
-                        server.backend.generate_text_streaming(messages, max_tokens, temperature, top_p),
+                        backend.generate_text_streaming(messages, max_tokens, temperature, top_p),
                         model_name,
                     )
                 else:
-                    text = server.backend.generate_text(messages, max_tokens, temperature, top_p)
+                    text = backend.generate_text(messages, max_tokens, temperature, top_p)
-                    self._send_openai_response(text, model_name, False, messages)
+                    self._send_openai_response(text, model_name, False, messages, backend=backend)
             except Exception as exc:
                 self._record_failed_request()
                 self._send_json(500, {"error": f"generation failed: {exc}"})
@@ -309,7 +332,7 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
         # We do N single-step forward passes (no cross-node KV cache), which is slow
         # but correct. Each step: head encodes current sequence → forwards through route
         # → tail returns the next token string → append → repeat.
-        remaining_route = self._get_remaining_route(model_name)
+        remaining_route = self._get_remaining_route(model_name, backend=backend)
         print(
             f"  [node] chat route model={model_name!r} max_tokens={max_tokens} "
             f"downstream={remaining_route}",
@@ -318,11 +341,10 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
         if not remaining_route:
             self._send_openai_response(
                 "error: no downstream route — check tracker connectivity",
-                model_name, False, messages,
+                model_name, False, messages, backend=backend,
             )
             return
 
-        backend = server.backend
         # Format with chat template so the model knows it's in assistant mode.
         try:
             if hasattr(backend.tokenizer, "apply_chat_template"):
@@ -342,13 +364,17 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
         generated: list[str] = []
         current_text = prompt_text
 
+        stream_emit = None
+        if stream:
+            stream_emit = self._start_openai_stream(model_name)
+
         for _ in range(max_tokens):
             try:
                 payload = backend.encode_prompt(current_text)
             except Exception as exc:
                 print(f"  [node] distributed encode error: {exc}", flush=True)
                 break
-            token_str = self._run_downstream_pipeline(payload, remaining_route)
+            token_str = self._run_downstream_pipeline(payload, remaining_route, backend=backend)
             if not token_str:
                 break
             # Stop on error responses or EOS.
@@ -357,12 +383,17 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
             if eos_token and token_str == eos_token:
                 break
             generated.append(token_str)
+            if stream_emit is not None:
+                stream_emit(token_str)
             current_text = current_text + token_str
 
         result_text = "".join(generated)
-        self._send_openai_response(result_text, model_name, stream, messages)
+        if stream_emit is not None:
+            stream_emit(None)
+            return
+        self._send_openai_response(result_text, model_name, stream, messages, backend=backend)
 
-    def _get_remaining_route(self, model: str) -> list[dict]:
+    def _get_remaining_route(self, model: str, *, backend: TorchModelShard | None = None) -> list[dict]:
         """Return downstream hops as dicts with endpoint, start_layer, and optional relay_addr.
 
         Fast path reads X-Meshnet-Route header injected by the tracker.
@@ -395,9 +426,10 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
 
         # Slow path: query the tracker (direct node-to-node calls, or tracker didn't inject).
         server: _TorchHTTPServer = self.server  # type: ignore[assignment]
+        active_backend = backend or server.backend
         if server.tracker_url is None:
             return []
-        route_model = getattr(server.backend, "model_id", None) or model
+        route_model = getattr(active_backend, "model_id", None) or model
         try:
             url = f"{server.tracker_url}/v1/route?model={urllib.parse.quote(route_model)}"
             with urllib.request.urlopen(url, timeout=server.route_timeout) as r:
@@ -424,18 +456,19 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
             print(f"  [node] WARNING: route lookup failed for {route_model!r}: {exc}", flush=True)
             return []
 
-    def _run_downstream_pipeline(self, payload: object, route: list[dict]) -> str:
+    def _run_downstream_pipeline(self, payload: object, route: list[dict], *, backend: TorchModelShard | None = None) -> str:
         server: _TorchHTTPServer = self.server  # type: ignore[assignment]
+        active_backend = backend or server.backend
         if not route:
             # Partial shard at tail: decode the activation from the previous node.
             # Full single-node (head+tail) is handled before entering this method.
-            if server.backend.is_tail:
+            if active_backend.is_tail:
                 try:
-                    tensor = server.backend.torch.frombuffer(
+                    tensor = active_backend.torch.frombuffer(
                         bytearray(payload.body),  # type: ignore[union-attr]
-                        dtype=server.backend.torch.bfloat16,
+                        dtype=active_backend.torch.bfloat16,
-                    ).reshape(payload.shape).to(server.backend.device)  # type: ignore[union-attr]
+                    ).reshape(payload.shape).to(active_backend.device)  # type: ignore[union-attr]
-                    return server.backend.decode_tail(tensor)
+                    return active_backend.decode_tail(tensor)
                 except Exception as exc:
                     return f"decode error: {exc}"
             return "no downstream route available for non-tail shard"
@@ -526,6 +559,15 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
 
     def _stream_openai_response(self, token_iter, model: str) -> None:
         """Stream tokens from an iterator as SSE chunks."""
+        emit = self._start_openai_stream(model)
+        for token_text in token_iter:
+            if not token_text:
+                continue
+            emit(token_text)
+        emit(None)
+
+    def _start_openai_stream(self, model: str):
+        """Open an OpenAI-compatible SSE response and return a token emitter."""
         chunk_id = "chatcmpl-node"
         created = int(time.time())
         self.send_response(200)
@@ -537,7 +579,7 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
             try:
                 self.wfile.write(f"data: {data}\n\n".encode())
                 self.wfile.flush()
-            except BrokenPipeError:
+            except (BrokenPipeError, ConnectionResetError):
                 pass
 
         _emit(json.dumps({
@@ -545,24 +587,27 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
             "model": model,
             "choices": [{"index": 0, "delta": {"role": "assistant", "content": ""}, "finish_reason": None}],
         }))
-        for token_text in token_iter:
+
-            if not token_text:
+        def emit_token(token_text: str | None) -> None:
-                continue
+            if token_text is None:
+                _emit(json.dumps({
+                    "id": chunk_id, "object": "chat.completion.chunk", "created": created,
+                    "model": model,
+                    "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
+                }))
+                try:
+                    self.wfile.write(b"data: [DONE]\n\n")
+                    self.wfile.flush()
+                except (BrokenPipeError, ConnectionResetError):
+                    pass
+                return
             _emit(json.dumps({
                 "id": chunk_id, "object": "chat.completion.chunk", "created": created,
                 "model": model,
                 "choices": [{"index": 0, "delta": {"content": token_text}, "finish_reason": None}],
             }))
-        _emit(json.dumps({
+
-            "id": chunk_id, "object": "chat.completion.chunk", "created": created,
+        return emit_token
-            "model": model,
-            "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
-        }))
-        try:
-            self.wfile.write(b"data: [DONE]\n\n")
-            self.wfile.flush()
-        except BrokenPipeError:
-            pass
 
     def _send_openai_response(
         self,
@@ -570,11 +615,13 @@ class _TorchHandler(http.server.BaseHTTPRequestHandler):
         model: str,
         stream: bool,
         messages: list[dict] | None = None,
+        backend: TorchModelShard | None = None,
     ) -> None:
         chunk_id = "chatcmpl-node"
         created = int(time.time())
+        active_backend = backend or self.server.backend  # type: ignore[attr-defined]
         if not stream:
-            usage = _usage_for_response(self.server.backend, messages or [], text)  # type: ignore[attr-defined]
+            usage = _usage_for_response(active_backend, messages or [], text)
             self._send_json(200, {
                 "id": chunk_id,
                 "object": "chat.completion",
@@ -685,9 +732,11 @@ class TorchNodeServer:
         route_timeout: float = 30.0,
         cache_dir: Path | None = None,
         debug: bool = False,
+        max_loaded_shards: int = 1,
     ) -> None:
         self._host = host
         self._requested_port = port
+        self._max_loaded_shards = max(1, max_loaded_shards)
         self._backend = backend or _load_backend(
             model_id,
             shard_start,
@@ -695,6 +744,7 @@ class TorchNodeServer:
             quantization,
             cache_dir,
         )
+        self._backends: dict[str, TorchModelShard] = {self._backend.model_id: self._backend}
         # Auto-detect tracker mode: enabled when shard_start == 0 or explicitly set
         self._tracker_mode = tracker_mode if tracker_mode is not None else (shard_start == 0)
         self._tracker_url = tracker_url
@@ -733,41 +783,64 @@ class TorchNodeServer:
     def queue_depth(self) -> int:
         return self._server.queue_depth if self._server is not None else 0
 
+    @property
+    def loaded_model_ids(self) -> list[str]:
+        return list(self._backends.keys())
+
     def apply_tracker_directives(self, directives: list[dict]) -> dict | None:
-        """Apply tracker LOAD_SHARD directives by hot-swapping the loaded backend."""
+        """Apply tracker shard directives (LOAD_SHARD replace, ADD_SHARD load-more)."""
+        add_directive = next(
+            (directive for directive in reversed(directives) if directive.get("action") == "ADD_SHARD"),
+            None,
+        )
         load_directive = next(
             (directive for directive in reversed(directives) if directive.get("action") == "LOAD_SHARD"),
             None,
         )
-        if load_directive is None:
+        directive = add_directive or load_directive
+        if directive is None:
             return None
-        shard_start = int(load_directive["shard_start"])
+        shard_start = int(directive["shard_start"])
-        shard_end = int(load_directive["shard_end"])
+        shard_end = int(directive["shard_end"])
-        quantization = str(load_directive.get("quantization") or self._backend.quantization)
+        quantization = str(directive.get("quantization") or self._backend.quantization)
-        model_id = str(load_directive.get("model") or self._backend.model_id)
+        model_id = str(directive.get("model") or self._backend.model_id)
+        replacing = directive.get("action") == "LOAD_SHARD"
+        if not replacing and len(self._backends) >= self._max_loaded_shards:
+            print(
+                f"  [node] WARNING: ignoring ADD_SHARD for {model_id!r} — "
+                f"loaded {len(self._backends)}/{self._max_loaded_shards} slots full",
+                flush=True,
+            )
+            return None
+        action_label = "reassigned" if replacing else "additional"
         print(
-            f"  [node] loading reassigned shard: {model_id} layers {shard_start}-{shard_end}",
+            f"  [node] loading {action_label} shard: {model_id} layers {shard_start}-{shard_end}",
             flush=True,
         )
         try:
             new_backend = _load_backend(model_id, shard_start, shard_end, quantization, self._cache_dir)
         except TypeError:
             new_backend = _load_backend(model_id, shard_start, shard_end, quantization)
-        self._backend = new_backend
+        self._backends[model_id] = new_backend
-        self._tracker_mode = shard_start == 0
+        if replacing or shard_start == 0:
-        if self._server is not None:
+            self._backend = new_backend
-            self._server.backend = new_backend
+            self._tracker_mode = shard_start == 0
-            self._server.tracker_mode = self._tracker_mode
         print(
-            f"  [node] loaded reassigned shard: {model_id} layers {shard_start}-{shard_end}",
+            f"  [node] loaded {action_label} shard: {model_id} layers {shard_start}-{shard_end}",
             flush=True,
         )
+        if self._server is not None:
+            self._server.backends = dict(self._backends)
+            if replacing or shard_start == 0:
+                self._server.backend = new_backend
+                self._server.tracker_mode = self._tracker_mode
         return {
+            "action": directive.get("action"),
             "model": model_id,
             "shard_start": shard_start,
             "shard_end": shard_end,
             "quantization": quantization,
-            "tracker_mode": self._tracker_mode,
+            "tracker_mode": shard_start == 0,
         }
 
     def start(self) -> int:
@@ -781,7 +854,9 @@ class TorchNodeServer:
             self._tracker_url,
             self._route_timeout,
             self._debug,
+            self._max_loaded_shards,
         )
+        self._server.backends = dict(self._backends)
         self.port = self._server.server_address[1]
         self._thread = threading.Thread(target=self._server.serve_forever, daemon=True)
         self._thread.start()

packages/tracker/meshnet_tracker/billing.py

@@ -453,13 +453,13 @@ class BillingLedger:
         with self._lock:
             return self._node_pending.get(wallet, 0.0)
 
-    def usage_for(self, api_keys: list[str], *, recent_limit: int = 20) -> dict:
+    def usage_for(self, api_keys: list[str], *, recent_limit: int | None = None) -> dict:
         """Aggregate charge history for a set of API keys (dashboard view)."""
         keys = set(api_keys)
         requests = 0
         total_tokens = 0
         total_cost = 0.0
-        recent: list[dict] = []
+        records: list[dict] = []
         with self._lock:
             for event in self._event_log:
                 if event.get("type") != "charge" or event.get("api_key") not in keys:
@@ -467,18 +467,20 @@ class BillingLedger:
                 requests += 1
                 total_tokens += int(event.get("total_tokens", 0))
                 total_cost += float(event.get("cost", 0.0))
-                recent.append({
+                records.append({
                     "api_key": event["api_key"],
                     "model": event.get("model"),
                     "total_tokens": event.get("total_tokens", 0),
                     "cost": event.get("cost", 0.0),
                     "ts": event.get("ts", 0.0),
                 })
+        recent = records[-recent_limit:] if recent_limit is not None else records
         return {
             "requests": requests,
             "total_tokens": total_tokens,
             "total_cost": total_cost,
-            "recent": recent[-recent_limit:],
+            "records": records,
+            "recent": recent,
         }
 
     def snapshot(self) -> dict:

packages/tracker/meshnet_tracker/dashboard.html

@@ -39,23 +39,56 @@
   .form-row { display:flex; gap:8px; }
   .form-row button { white-space:nowrap; }
   .error-msg { color:var(--bad); font-size:12px; min-height:16px; }
-  .keybox { word-break:break-all; background:var(--bg); border:1px solid var(--border);
+  .keybox { display:flex; flex-wrap:wrap; align-items:center; gap:6px;
+          position:relative;
+          word-break:break-all; background:var(--bg); border:1px solid var(--border);
           border-radius:6px; padding:4px 8px; margin:4px 0; font-size:11px; }
-  .tabs { display:flex; gap:10px; margin-bottom:8px; }
+  .key-text { cursor:text; flex:1 1 auto; min-width:12rem; }
-  .tabs a { color:var(--dim); cursor:pointer; }
+  .copy-tooltip {
-  .tabs a.active { color:var(--accent); border-bottom:1px solid var(--accent); }
+    position:absolute; right:8px; top:-26px;
-  .wide { grid-column:1 / -1; }
+    background:var(--panel); border:1px solid var(--border); color:var(--ok);
-  .console {
+    padding:2px 8px; border-radius:4px; font-size:11px;
-    background:var(--bg); border:1px solid var(--border); border-radius:6px;
+    pointer-events:none; z-index:1; white-space:nowrap;
-    min-height:160px; max-height:280px; overflow:auto; padding:7px 9px;
+  }
-    white-space:pre-wrap; word-break:break-word; font-size:11px;
+  .tabs { display:flex; gap:10px; margin-bottom:8px; }
-  }
+  .tabs a { color:var(--dim); cursor:pointer; }
-  .console-line { padding:1px 0; border-bottom:1px solid #161b22; }
+  .tabs a.active { color:var(--accent); border-bottom:1px solid var(--accent); }
-  .console-time { color:var(--dim); }
+  .dashboard-tabs { display:flex; gap:10px; padding:10px 20px 0; border-bottom:1px solid var(--border); }
-  .console-level-info { color:var(--accent); }
+  .dashboard-tabs button { border:0; border-bottom:1px solid transparent; border-radius:0;
-  .console-level-warn { color:var(--warn); }
+          background:transparent; color:var(--dim); padding:5px 0 8px; }
-  .console-level-error { color:var(--bad); }
+  .dashboard-tabs button.active { color:var(--accent); border-bottom-color:var(--accent); }
-</style>
+  .wide { grid-column:1 / -1; }
+  section[hidden] { display:none !important; }
+  .chat-shell { display:grid; grid-template-columns:minmax(0, 1.35fr) minmax(320px, 0.65fr); gap:12px; }
+  .chat-pane { display:flex; flex-direction:column; gap:10px; min-width:0; }
+  .chat-panel { background:var(--bg); border:1px solid var(--border); border-radius:6px; padding:10px; }
+  .chat-controls { display:flex; gap:10px; align-items:end; flex-wrap:wrap; }
+  .chat-controls label { display:flex; flex-direction:column; gap:4px; color:var(--dim); }
+  .chat-controls select { min-width:220px; }
+  .chat-history { display:flex; flex-direction:column; gap:8px; min-height:220px; max-height:420px; overflow:auto; }
+  .chat-message { border:1px solid #21262d; border-radius:6px; padding:8px 10px; background:#10151d; }
+  .chat-role { color:var(--dim); font-size:11px; text-transform:uppercase; letter-spacing:.06em; margin-bottom:4px; }
+  .chat-role-user { color:var(--accent); }
+  .chat-role-assistant { color:var(--ok); }
+  .chat-role-error { color:var(--bad); }
+  .chat-compose { display:flex; flex-direction:column; gap:8px; }
+  .chat-compose textarea { min-height:112px; resize:vertical; width:100%; }
+  .chat-status { color:var(--dim); font-size:12px; }
+  .console {
+    background:var(--bg); border:1px solid var(--border); border-radius:6px;
+    min-height:160px; max-height:280px; overflow:auto; padding:7px 9px;
+    white-space:pre-wrap; word-break:break-word; font-size:11px;
+  }
+  .console-line { padding:1px 0; border-bottom:1px solid #161b22; }
+  .console-time { color:var(--dim); }
+  .console-level-info { color:var(--accent); }
+  .console-level-warn { color:var(--warn); }
+  .console-level-error { color:var(--bad); }
+  .status-pending { color:var(--warn); }
+  .status-processing { color:var(--accent); }
+  .status-failed { color:var(--bad); }
+  .status-complete { color:var(--ok); }
+</style>
 </head>
 <body>
 <header>
@@ -63,20 +96,53 @@
   <span class="meta" id="self-url"></span>
   <span class="meta" id="refreshed"></span>
 </header>
+<nav class="dashboard-tabs" aria-label="Dashboard sections">
+  <button id="tab-overview" class="active" onclick="switchDashboardTab('overview')">Overview</button>
+  <button id="tab-chat" onclick="switchDashboardTab('chat')">Chat</button>
+  <button id="tab-billing" style="display:none" onclick="switchDashboardTab('billing')">Billing</button>
+  <button id="tab-admin" style="display:none" onclick="switchDashboardTab('admin')">Admin</button>
+</nav>
 <main>
-  <section id="account-section"><h2>Account</h2><div id="account">loading…</div></section>
+  <section data-tab="overview" id="account-section"><h2>Account</h2><div id="account">loading…</div></section>
-  <section id="admin-section" style="display:none"><h2>All accounts (admin)</h2><div id="admin" class="empty"></div></section>
+  <section data-tab="overview"><h2>Tracker hive</h2><div id="hive" class="empty">loading…</div></section>
-  <section><h2>Tracker hive</h2><div id="hive" class="empty">loading…</div></section>
+  <section data-tab="overview"><h2>Nodes &amp; coverage</h2><div id="nodes" class="empty">loading…</div></section>
-  <section><h2>Nodes &amp; coverage</h2><div id="nodes" class="empty">loading…</div></section>
+  <section data-tab="overview"><h2>Model usage (RPM)</h2><div id="stats" class="empty">loading…</div></section>
-  <section><h2>Client balances</h2><div id="clients" class="empty">loading…</div></section>
+  <section data-tab="overview" class="wide"><h2>Call wall</h2><div id="call-wall" class="empty">loading...</div></section>
-  <section><h2>Node pending payouts</h2><div id="pending" class="empty">loading…</div></section>
+  <section data-tab="chat" class="wide">
-  <section><h2>Settlement history</h2><div id="settlements" class="empty">loading…</div></section>
+    <h2>Chat / inference</h2>
-  <section><h2>Strikes / bans / forfeitures</h2><div id="fraud" class="empty">loading…</div></section>
+    <div class="chat-shell">
-  <section><h2>Model usage (RPM)</h2><div id="stats" class="empty">loading…</div></section>
+      <div class="chat-pane">
-  <section><h2>Node throughput</h2><div id="throughput" class="empty">loading…</div></section>
+        <div class="chat-panel chat-controls">
-  <section class="wide"><h2>Console output</h2><div id="console" class="console empty">loading…</div></section>
+          <label>Model
-  <section class="wide"><h2>Inference history</h2><div id="inference-history" class="empty">loading...</div></section>
+            <select id="chat-model" onchange="selectChatModel(this.value)"></select>
-</main>
+          </label>
+          <button class="small" onclick="clearChatHistory()">clear history</button>
+        </div>
+        <div class="chat-panel chat-compose">
+          <textarea id="chat-prompt" placeholder="Ask a question or describe the task"></textarea>
+          <div class="form-row">
+            <button onclick="sendChat()" id="chat-send">Send</button>
+          </div>
+        </div>
+      </div>
+      <div class="chat-pane">
+        <div class="chat-panel">
+          <div id="chat-status" class="chat-status">select a model to start</div>
+          <div id="chat-history" class="chat-history empty">no messages yet</div>
+        </div>
+      </div>
+    </div>
+  </section>
+  <section data-tab="billing" data-logged-in-only><h2>Usage summary</h2><div id="usage-summary" class="empty">login required</div></section>
+  <section data-tab="billing" data-logged-in-only><h2>Node throughput</h2><div id="node-throughput" class="empty">login required</div></section>
+  <section data-tab="billing"><h2>Request history</h2><div id="billing-usage" class="empty">login required</div></section>
+  <section data-tab="billing" data-admin-only><h2>Node pending payouts</h2><div id="pending" class="empty">admin login required</div></section>
+  <section data-tab="billing" data-admin-only><h2>Settlement history</h2><div id="settlements" class="empty">admin login required</div></section>
+  <section data-tab="admin" id="admin-section"><h2>All accounts (admin)</h2><div id="admin" class="empty"></div></section>
+  <section data-tab="admin" data-admin-only><h2>Strikes / bans / forfeitures</h2><div id="fraud" class="empty">admin login required</div></section>
+  <section data-tab="admin"><h2>Client balances</h2><div id="clients" class="empty">admin login required</div></section>
+  <section data-tab="admin" class="wide"><h2>Console output</h2><div id="console" class="console empty">admin login required</div></section>
+</main>
 <script>
 "use strict";
 const $ = id => document.getElementById(id);
@@ -84,6 +150,7 @@ const esc = s => String(s).replace(/[&<>"]/g,
   c => ({"&":"&amp;","<":"&lt;",">":"&gt;",'"':"&quot;"}[c]));
 const usdt = v => (Math.round(v * 1e6) / 1e6).toFixed(6);
 const tps = v => (v === null || v === undefined) ? "?" : (Math.round(v * 10) / 10).toFixed(1);
+const copies = v => (v === null || v === undefined) ? "?" : Number(v).toFixed(2);
 const short = (s, n=14) => { s = String(s); return s.length > n ? s.slice(0, 6) + "…" + s.slice(-5) : s; };
 
 async function fetchJson(path) {
@@ -129,16 +196,17 @@ function renderNodes(map) {
   }
   let html = "";
   for (const [model, group] of Object.entries(byModel)) {
-    html += `<div><b>${esc(model)}</b> <span class="dim">(${group.length} node${group.length===1?"":"s"})</span></div>`;
+    const supply = group.find(n => n.model_supply && n.model_supply.served_model_copies !== undefined);
-    html += table(["node", "shard", "tps (1h)", "queue", "health"], group.map(n => {
+    const served = supply && supply.model_supply && supply.model_supply.served_model_copies;
+    html += `<div><b>${esc(model)}</b> <span class="dim">(${group.length} node${group.length===1?"":"s"} · ${esc(copies(served))} served)</span></div>`;
+    html += table(["node", "shard", "tps (1h)", "queue", "served"], group.map(n => {
       const modelStats = (n.throughput && (n.throughput[n.hf_repo] || n.throughput[n.model])) || {};
       return [
       esc(short(n.node_id || "?")),
       esc(`${n.shard_start ?? "?"}-${n.shard_end ?? "?"}`),
       `<span class="num">${esc(tps(modelStats.tokens_per_sec_last_hour))}</span>`,
       esc(String((n.stats && n.stats.queue_depth) ?? 0)),
-      (n.stats && (n.stats.alive === false || n.stats.healthy === false))
+      `<span class="num">${esc(copies(n.model_supply && n.model_supply.served_model_copies))}</span>`,
-        ? '<span class="bad">down</span>' : '<span class="ok">up</span>',
     ]; }));
   }
   $("nodes").innerHTML = html;
@@ -209,10 +277,10 @@ function renderStats(stats) {
   $("stats").innerHTML = table(["model", "rpm (1h)", "rpm (24h)", "rpm (30d)"], rows);
 }
 
-function renderThroughput(stats) {
+function renderThroughputHtml(stats) {
-  const nodes = (stats && stats.nodes) || {};
+  const nodes = (stats && stats.nodes) || {};
-  const rows = [];
+  const rows = [];
-  for (const [nodeId, nodeStats] of Object.entries(nodes)) {
+  for (const [nodeId, nodeStats] of Object.entries(nodes)) {
     for (const [model, s] of Object.entries((nodeStats && nodeStats.models) || {})) {
       rows.push([
         esc(short(nodeId)),
@@ -221,75 +289,407 @@ function renderThroughput(stats) {
         `<span class="num">${esc(String(s.sample_count_last_hour ?? 0))}</span>`,
       ]);
     }
-  }
+  }
-  $("throughput").innerHTML = table(["node", "model", "tps (1h)", "samples"], rows);
+  if (!rows.length) return '<div class="empty">no throughput samples yet</div>';
-}
+  return table(["node", "model", "tps (1h)", "samples"], rows);
-
+}
-function renderInferenceHistory(data) {
+
-  const events = (data && data.events) || [];
+function hiveThroughputSummary(stats) {
-  const started = new Map();
+  const nodes = (stats && stats.nodes) || {};
-  const completed = [];
+  let totalTps = 0;
-  for (const e of events) {
+  let samples = 0;
-    const f = e.fields || {};
+  for (const nodeStats of Object.values(nodes)) {
-    const id = f.request_id;
+    for (const s of Object.values((nodeStats && nodeStats.models) || {})) {
-    if (!id) continue;
+      const t = Number(s.tokens_per_sec_last_hour);
-    if (e.message === "proxy route selected") {
+      if (Number.isFinite(t)) totalTps += t;
-      started.set(id, e);
+      samples += Number(s.sample_count_last_hour || 0);
-    } else if (e.message === "proxy complete" || e.message === "proxy failed" || e.message === "direct proxy failed after relay") {
+    }
-      completed.push(e);
+  }
-      started.delete(id);
+  return { totalTps, samples };
-    }
+}
-  }
+
-  const activeByModel = {};
+function buildCallWallStates(events) {
-  for (const e of started.values()) {
+  const byId = new Map();
-    const f = e.fields || {};
+  for (const e of events) {
-    const model = f.model || f.route_model || "?";
+    const f = e.fields || {};
-    activeByModel[model] = (activeByModel[model] || 0) + 1;
+    const id = f.request_id;
-  }
+    if (!id) continue;
-  const active = Object.entries(activeByModel)
+    let rec = byId.get(id);
-    .map(([model, count]) => `${esc(model)}: <span class="num">${count}</span> active`)
+    if (!rec) {
-    .join(" &middot; ");
+      rec = { id, events: [] };
-  const rows = completed.slice(-20).reverse().map(e => {
+      byId.set(id, rec);
-    const f = e.fields || {};
+    }
-    return [
+    rec.events.push(e);
-      new Date((e.ts || 0) * 1000).toLocaleTimeString(),
+    const msg = e.message;
-      esc(short(f.model || f.route_model || "?", 28)),
+    if (msg === "proxy route selected") {
-      esc(short(f.request_id || "?", 18)),
+      rec.status = "pending";
-      `<span class="num">${esc(tps(f.tokens_per_sec))}</span>`,
+      rec.started = e.ts;
-      `<span class="num">${esc(String(f.tokens ?? "?"))}</span>`,
+      rec.model = f.model || f.route_model || "?";
-      `<span class="num">${esc(String(f.elapsed_seconds ?? "?"))}</span>`,
+      rec.route = f.route || f.nodes;
-      f.stream ? "stream" : "json",
+      rec.nodes = f.nodes;
-    ];
+      rec.stream = f.stream;
-  });
+    } else if (msg === "proxy via relay" || msg === "proxy connected") {
-  $("inference-history").innerHTML =
+      rec.status = "processing";
-    `<div class="dim" style="margin-bottom:6px">${active || "no active requests"}</div>` +
+      if (!rec.started) rec.started = e.ts;
-    (rows.length ? table(["time", "model", "request", "tps", "tokens", "sec", "mode"], rows)
+      rec.model = rec.model || f.model || f.route_model || "?";
-                 : '<div class="empty">no completed inference requests</div>');
+    } else if (msg === "proxy progress") {
-}
+      rec.status = "processing";
-
+      rec.model = rec.model || f.model || f.route_model || "?";
-function renderConsole(data) {
+      rec.tokens = f.tokens;
-  const events = (data && data.events) || [];
+      rec.tps = f.tokens_per_sec;
-  if (!events.length) {
+      rec.elapsed = f.elapsed_seconds;
-    $("console").innerHTML = '<div class="empty">no console events</div>';
+      rec.stream = f.stream;
-    return;
+    } else if (msg === "relay proxy failed, trying direct") {
-  }
+      rec.status = "processing";
-  $("console").innerHTML = events.slice(-120).map(e => {
+      rec.warn = "relay failed, trying direct";
-    const level = String(e.level || "info");
+    } else if (msg === "proxy complete") {
-    const cls = level === "error" ? "console-level-error" : level === "warn" ? "console-level-warn" : "console-level-info";
+      rec.status = "complete";
-    const fields = e.fields && Object.keys(e.fields).length ? " " + JSON.stringify(e.fields) : "";
+      rec.model = rec.model || f.model || f.route_model || "?";
-    return `<div class="console-line"><span class="console-time">${new Date((e.ts || 0) * 1000).toLocaleTimeString()}</span> ` +
+      rec.tokens = f.tokens;
-      `<span class="${cls}">${esc(level.toUpperCase())}</span> ${esc(e.message || "")}${esc(fields)}</div>`;
+      rec.tps = f.tokens_per_sec;
-  }).join("");
+      rec.elapsed = f.elapsed_seconds;
-}
+      rec.stream = f.stream;
+      rec.terminal = e;
+    } else if (msg === "proxy failed" || msg === "direct proxy failed after relay") {
+      rec.status = "failed";
+      rec.model = rec.model || f.model || f.route_model || "?";
+      rec.error = f.error || msg;
+      rec.terminal = e;
+    }
+  }
+  return byId;
+}
+
+function callWallAgeSeconds(rec, nowSec) {
+  const start = rec.started || (rec.events[0] && rec.events[0].ts) || nowSec;
+  return Math.max(0, nowSec - start);
+}
+
+function callWallMaxQueue(rec) {
+  const nodes = rec.nodes || [];
+  const nodeQueues = Array.isArray(nodes) ? nodes.map(n => Number(n.queue_depth || 0)) : [];
+  return nodeQueues.length ? Math.max(...nodeQueues) : 0;
+}
+
+function renderCallWall(consoleData, stats) {
+  const events = (consoleData && consoleData.events) || [];
+  const nowSec = Date.now() / 1000;
+  const states = buildCallWallStates(events);
+  const active = [];
+  const terminal = [];
+  for (const rec of states.values()) {
+    if (rec.status === "pending" || rec.status === "processing") active.push(rec);
+    else if (rec.status === "complete" || rec.status === "failed") terminal.push(rec);
+  }
+  active.sort((a, b) => (a.started || 0) - (b.started || 0));
+  terminal.sort((a, b) => (b.terminal && b.terminal.ts) - (a.terminal && a.terminal.ts));
+
+  const hive = hiveThroughputSummary(stats);
+  const pending = active.filter(r => r.status === "pending").length;
+  const processing = active.filter(r => r.status === "processing").length;
+  const failedRecent = terminal.filter(r => r.status === "failed").length;
+  let queuedEstimate = 0;
+  for (const rec of active) queuedEstimate += Math.max(0, callWallMaxQueue(rec) - 1);
+
+  let html =
+    `<div class="dim" style="margin-bottom:6px">` +
+    `hive tps (1h): <b>${esc(tps(hive.totalTps))}</b> · samples: <b>${hive.samples}</b> · ` +
+    `active: <span class="status-processing">${processing}</span> processing · ` +
+    `<span class="status-pending">${pending}</span> pending` +
+    (queuedEstimate ? ` · queued estimate: <b>${queuedEstimate}</b>` : "") +
+    (failedRecent ? ` · <span class="status-failed">${failedRecent} recent failures</span>` : "") +
+    `</div>`;
+
+  if (active.length) {
+    html += table(["status", "age", "model", "request", "live tps", "tokens", "queue", "route / note"], active.map(rec => {
+      const statusCls = rec.status === "pending" ? "status-pending" : "status-processing";
+      const note = rec.warn || (rec.route ? short(String(rec.route), 28) : "");
+      return [
+        `<span class="${statusCls}">${esc(rec.status)}</span>`,
+        `<span class="num">${esc(callWallAgeSeconds(rec, nowSec).toFixed(1))}s</span>`,
+        esc(short(rec.model || "?", 28)),
+        esc(short(rec.id, 18)),
+        `<span class="num">${esc(tps(rec.tps))}</span>`,
+        `<span class="num">${esc(String(rec.tokens ?? "—"))}</span>`,
+        `<span class="num">${esc(String(callWallMaxQueue(rec)))}</span>`,
+        esc(note),
+      ];
+    }));
+  } else {
+    html += '<div class="empty">no in-flight requests</div>';
+  }
+
+  const historyRows = terminal.slice(0, 40).map(rec => {
+    const e = rec.terminal || {};
+    const f = e.fields || {};
+    const statusCls = rec.status === "failed" ? "status-failed" : "status-complete";
+    const detail = rec.status === "failed"
+      ? esc(short(rec.error || "?", 40))
+      : (f.stream ? "stream" : "json");
+    return [
+      new Date((e.ts || 0) * 1000).toLocaleTimeString(),
+      `<span class="${statusCls}">${esc(rec.status)}</span>`,
+      esc(short(rec.model || "?", 28)),
+      esc(short(rec.id, 18)),
+      `<span class="num">${esc(tps(rec.tps ?? f.tokens_per_sec))}</span>`,
+      `<span class="num">${esc(String(rec.tokens ?? f.tokens ?? "?"))}</span>`,
+      `<span class="num">${esc(String(rec.elapsed ?? f.elapsed_seconds ?? "?"))}</span>`,
+      detail,
+    ];
+  });
+  html += '<div style="margin-top:8px"><b class="dim">recent completed / failed</b></div>';
+  html += historyRows.length
+    ? table(["time", "status", "model", "request", "tps", "tokens", "sec", "detail"], historyRows)
+    : '<div class="empty">no completed requests yet</div>';
+  $("call-wall").innerHTML = html;
+}
+
+function startOfLocalDay(tsSec) {
+  const d = new Date(tsSec * 1000);
+  d.setHours(0, 0, 0, 0);
+  return d.getTime() / 1000;
+}
+
+function formatUsageDayLabel(tsSec) {
+  return new Date(tsSec * 1000).toLocaleDateString();
+}
+
+function summarizeUsageBuckets(records) {
+  const now = Date.now() / 1000;
+  const todayStart = startOfLocalDay(now);
+  const daySec = 86400;
+  const empty = () => ({ requests: 0, tokens: 0, cost: 0 });
+  const daily = [0, 1, 2].map(offset => ({
+    label: offset === 0 ? "Today" : offset === 1 ? "Yesterday" : formatUsageDayLabel(todayStart - offset * daySec),
+    ...empty(),
+  }));
+  const last7 = { label: "Last 7 days", ...empty() };
+  const last30 = { label: "Last 30 days", ...empty() };
+  const total = { label: "All time", ...empty() };
+
+  for (const u of records) {
+    const ts = Number(u.ts || 0);
+    const tokens = Number(u.total_tokens || 0);
+    const cost = Number(u.cost || 0);
+    total.requests += 1;
+    total.tokens += tokens;
+    total.cost += cost;
+    if (ts >= now - 30 * daySec) {
+      last30.requests += 1;
+      last30.tokens += tokens;
+      last30.cost += cost;
+    }
+    if (ts >= now - 7 * daySec) {
+      last7.requests += 1;
+      last7.tokens += tokens;
+      last7.cost += cost;
+    }
+    for (let offset = 0; offset < 3; offset++) {
+      const start = todayStart - offset * daySec;
+      const end = start + daySec;
+      if (ts >= start && ts < end) {
+        daily[offset].requests += 1;
+        daily[offset].tokens += tokens;
+        daily[offset].cost += cost;
+      }
+    }
+  }
+  return [...daily, last7, last30, total];
+}
+
+function renderUsageSummary(records) {
+  const el = $("usage-summary");
+  if (!el) return;
+  if (!sessionToken) {
+    el.innerHTML = '<div class="empty">login required</div>';
+    return;
+  }
+  if (!records.length) {
+    el.innerHTML = '<div class="empty">no billed requests yet</div>';
+    return;
+  }
+  const rows = summarizeUsageBuckets(records).map(b => [
+    esc(b.label),
+    `<span class="num">${b.requests}</span>`,
+    `<span class="num">${esc(String(b.tokens))}</span>`,
+    `<span class="num">${usdt(b.cost)}</span>`,
+  ]);
+  el.innerHTML =
+    '<div class="dim" style="margin-bottom:6px">per-request detail on Request history below</div>' +
+    table(["period", "requests", "tokens", "cost (USDT)"], rows);
+}
+
+function renderNodeThroughput(stats) {
+  const el = $("node-throughput");
+  if (!el) return;
+  if (!sessionToken) {
+    el.innerHTML = '<div class="empty">login required</div>';
+    return;
+  }
+  el.innerHTML = renderThroughputHtml(stats);
+}
+
+function renderBillingUsage(records) {
+  const el = $("billing-usage");
+  if (!el) return;
+  if (!sessionToken) {
+    el.innerHTML = '<div class="empty">login required</div>';
+    return;
+  }
+  if (!records.length) {
+    el.innerHTML = '<div class="empty">no billed requests yet</div>';
+    return;
+  }
+  const rows = records.slice().reverse().map(u => [
+    new Date((u.ts || 0) * 1000).toLocaleString(),
+    esc(short(u.model || "?", 28)),
+    esc(short(u.api_key || "?", 14)),
+    `<span class="num">${esc(String(u.total_tokens))}</span>`,
+    `<span class="num">${usdt(u.cost)}</span>`,
+  ]);
+  el.innerHTML = `<div class="dim" style="margin-bottom:6px">${records.length} request${records.length === 1 ? "" : "s"}</div>` +
+    table(["time", "model", "api key", "tokens", "cost (USDT)"], rows);
+}
+
+function renderConsole(data) {
+  const events = (data && data.events) || [];
+  if (!events.length) {
+    $("console").innerHTML = '<div class="empty">no console events</div>';
+    return;
+  }
+  $("console").innerHTML = events.slice(-120).map(e => {
+    const level = String(e.level || "info");
+    const cls = level === "error" ? "console-level-error" : level === "warn" ? "console-level-warn" : "console-level-info";
+    const fields = e.fields && Object.keys(e.fields).length ? " " + JSON.stringify(e.fields) : "";
+    return `<div class="console-line"><span class="console-time">${new Date((e.ts || 0) * 1000).toLocaleTimeString()}</span> ` +
+      `<span class="${cls}">${esc(level.toUpperCase())}</span> ${esc(e.message || "")}${esc(fields)}</div>`;
+  }).join("");
+}
 
 // ---- account panel (registration / login / balance / usage / API keys) ----
 
 let sessionToken = localStorage.getItem("meshnet_session") || null;
 let authTab = "login";
+let dashboardTab = "overview";
+let isAdmin = false;
+let isLoggedIn = false;
+let accountApiKeys = [];
+let accountUsageRecords = [];
+let lastStats = null;
+let availableModels = [];
+let chatHistory = [];
+let chatBusy = false;
+let selectedChatModel = localStorage.getItem("meshnet_chat_model") || "";
 
-async function apiCall(path, method, body) {
+function switchDashboardTab(name) {
+  if (name === "admin" && !isAdmin) name = "overview";
+  if (name === "billing" && !isLoggedIn) name = "overview";
+  dashboardTab = name;
+  updateSectionVisibility();
+  for (const tabName of ["overview", "chat", "billing", "admin"]) {
+    const button = $("tab-" + tabName);
+    if (button) button.classList.toggle("active", tabName === dashboardTab);
+  }
+}
+
+function updateSectionVisibility() {
+  for (const section of document.querySelectorAll("main section[data-tab]")) {
+    const onTab = section.dataset.tab === dashboardTab;
+    const adminOnly = section.hasAttribute("data-admin-only");
+    const loggedInOnly = section.hasAttribute("data-logged-in-only");
+    section.hidden = !onTab || (adminOnly && !isAdmin) || (loggedInOnly && !isLoggedIn);
+  }
+}
+
+function renderChatStatus(text) {
+  $("chat-status").textContent = text;
+}
+
+function renderChatHistory() {
+  const history = $("chat-history");
+  if (!chatHistory.length) {
+    history.classList.add("empty");
+    history.innerHTML = "no messages yet";
+    return;
+  }
+  history.classList.remove("empty");
+  history.innerHTML = chatHistory.map(msg => {
+    const roleClass = msg.role === "user" ? "chat-role-user" : msg.role === "assistant" ? "chat-role-assistant" : "chat-role-error";
+    const label = msg.role === "user" ? "user" : msg.role === "assistant" ? "assistant" : "error";
+    const meta = msg.model ? ` <span class="dim">· ${esc(short(msg.model, 24))}</span>` : "";
+    return `<div class="chat-message"><div class="chat-role ${roleClass}">${label}${meta}</div><div>${esc(msg.content)}</div></div>`;
+  }).join("");
+  history.scrollTop = history.scrollHeight;
+}
+
+function renderChatModels() {
+  const select = $("chat-model");
+  if (!select) return;
+  const models = availableModels.slice();
+  if (!models.length) {
+    select.innerHTML = '<option value="">no models available</option>';
+    select.disabled = true;
+    return;
+  }
+  select.disabled = false;
+  const preferred = models.find(m => m.id === selectedChatModel)
+    || models[0];
+  selectedChatModel = preferred.id;
+  localStorage.setItem("meshnet_chat_model", selectedChatModel);
+  select.innerHTML = models.map(model => {
+    const label = model.name && model.name !== model.id
+      ? `${model.name} (${model.id})`
+      : model.id;
+    const suffix = model.recommended ? " [recommended]" : "";
+    return `<option value="${esc(model.id)}"${model.id === selectedChatModel ? " selected" : ""}>${esc(label + suffix)}</option>`;
+  }).join("");
+  select.value = selectedChatModel;
+}
+
+function selectChatModel(value) {
+  selectedChatModel = value || "";
+  localStorage.setItem("meshnet_chat_model", selectedChatModel);
+}
+
+function clearChatHistory() {
+  chatHistory = [];
+  renderChatHistory();
+  renderChatStatus("history cleared");
+}
+
+function chatAuthToken() {
+  if (accountApiKeys.length) return accountApiKeys[0];
+  return null;
+}
+
+function setAdminMode(enabled) {
+  isAdmin = enabled;
+  $("tab-admin").style.display = enabled ? "" : "none";
+  if (!enabled && dashboardTab === "admin") {
+    switchDashboardTab("overview");
+  } else {
+    updateSectionVisibility();
+  }
+}
+
+function setLoggedInMode(enabled) {
+  isLoggedIn = enabled;
+  $("tab-billing").style.display = enabled ? "" : "none";
+  if (!enabled) {
+    accountUsageRecords = [];
+    renderBillingUsage([]);
+    renderUsageSummary([]);
+    renderNodeThroughput(null);
+    if (dashboardTab === "billing") switchDashboardTab("overview");
+  } else {
+    updateSectionVisibility();
+  }
+}
+
+async function apiCall(path, method, body, bearerToken) {
   const headers = { "Content-Type": "application/json" };
-  if (sessionToken) headers["Authorization"] = "Bearer " + sessionToken;
+  const token = bearerToken === undefined ? sessionToken : bearerToken;
+  if (token) headers["Authorization"] = "Bearer " + token;
   try {
     const r = await fetch(path, {
       method: method || "GET",
@@ -325,7 +725,10 @@ function renderAuthForms(errorMsg) {
   $("account").innerHTML =
     `<div class="tabs">${tab("login", "Log in")}${tab("register", "Register")}</div>` +
     form + `<div class="error-msg">${errorMsg ? esc(errorMsg) : ""}</div>`;
-  $("admin-section").style.display = "none";
+  accountApiKeys = [];
+  renderChatAuthHint();
+  setLoggedInMode(false);
+  setAdminMode(false);
 }
 
 function switchAuthTab(name) { authTab = name; renderAuthForms(); }
@@ -373,15 +776,82 @@ async function topupKey(key) {
   await renderAccountPanel();
 }
 
+const COPY_TOOLTIP_MS = 2000;
+
+function showCopiedTooltip(anchor) {
+  const box = (anchor && anchor.closest && anchor.closest(".keybox")) || anchor;
+  if (!box) return;
+  const existing = box.querySelector(".copy-tooltip");
+  if (existing) existing.remove();
+  const tip = document.createElement("span");
+  tip.className = "copy-tooltip";
+  tip.textContent = "Copied!";
+  tip.setAttribute("role", "status");
+  box.appendChild(tip);
+  setTimeout(() => tip.remove(), COPY_TOOLTIP_MS);
+}
+
+async function copyApiKeyText(text, anchor) {
+  try {
+    await navigator.clipboard.writeText(text);
+  } catch {
+    const ta = document.createElement("textarea");
+    ta.value = text;
+    ta.style.position = "fixed";
+    ta.style.left = "-9999px";
+    document.body.appendChild(ta);
+    ta.select();
+    try { document.execCommand("copy"); } catch { /* ignore */ }
+    document.body.removeChild(ta);
+  }
+  if (anchor) showCopiedTooltip(anchor);
+}
+
+function selectApiKeyText(el) {
+  const range = document.createRange();
+  range.selectNodeContents(el);
+  const sel = window.getSelection();
+  if (!sel) return;
+  sel.removeAllRanges();
+  sel.addRange(range);
+}
+
+function copyApiKeyFromTextEl(el) {
+  const key = el.dataset.key || el.textContent || "";
+  return copyApiKeyText(key, el);
+}
+
+function copyApiKeyFromButton(button) {
+  const el = button.closest(".keybox") && button.closest(".keybox").querySelector(".key-text");
+  const key = (el && el.dataset.key) || "";
+  return copyApiKeyText(key, button);
+}
+
+function renderChatAuthHint() {
+  if (chatAuthToken()) {
+    renderChatStatus("ready to send with your active API key");
+  } else if (sessionToken) {
+    renderChatStatus("create an API key in Account to use chat on a billing-enabled tracker");
+  } else {
+    renderChatStatus("log in if this tracker requires an API key");
+  }
+}
+
 async function renderAccountPanel() {
   const r = await apiCall("/v1/account");
   if (r.status === 404) {  // accounts disabled on this tracker
     $("account-section").style.display = "none";
-    $("admin-section").style.display = "none";
+    accountApiKeys = [];
+    accountUsageRecords = [];
+    renderChatAuthHint();
+    setLoggedInMode(false);
+    setAdminMode(false);
     return;
   }
   if (!r.ok) { setSession(null); renderAuthForms(); return; }
   const { account, api_keys, balances, total_balance, usage, topup_amount } = r.data;
+  accountApiKeys = Array.isArray(api_keys) ? api_keys.slice() : [];
+  accountUsageRecords = (usage && (usage.records || usage.recent)) || [];
   const who = account.email || account.wallet || account.account_id;
   let html =
     `<div><b>${esc(who)}</b> <span class="pill">${esc(account.role)}</span> ` +
@@ -393,8 +863,10 @@ async function renderAccountPanel() {
     '<button class="small" onclick="createKey()">+ new key</button></div>';
   if (api_keys.length) {
     for (const key of api_keys) {
-      html += `<div class="keybox">${esc(key)}` +
+      html += `<div class="keybox">` +
-        ` <span class="dim">(${usdt(balances[key] ?? 0)} USDT)</span>` +
+        `<span class="key-text" data-key="${esc(key)}" onclick="selectApiKeyText(this)" ondblclick="copyApiKeyFromTextEl(this)">${esc(key)}</span>` +
+        `<span class="dim">(${usdt(balances[key] ?? 0)} USDT)</span>` +
+        `<button class="small" type="button" onclick="copyApiKeyFromButton(this)">copy</button>` +
         (topup_amount > 0
           ? ` <button class="small" onclick="topupKey('${esc(key)}')">+${usdt(topup_amount)} (devnet)</button>`
           : "") +
@@ -403,24 +875,74 @@ async function renderAccountPanel() {
   } else {
     html += '<div class="empty">no active keys</div>';
   }
-  if (usage.recent && usage.recent.length) {
-    html += '<div style="margin-top:6px"><b class="dim">recent usage</b></div>' +
-      table(["time", "model", "tokens", "cost"], usage.recent.slice().reverse().map(u => [
-        new Date(u.ts * 1000).toLocaleTimeString(),
-        esc(short(u.model || "?", 24)),
-        `<span class="num">${esc(String(u.total_tokens))}</span>`,
-        `<span class="num">${usdt(u.cost)}</span>`,
-      ]));
-  }
   $("account").innerHTML = html;
+  renderUsageSummary(accountUsageRecords);
+  renderNodeThroughput(lastStats);
+  renderBillingUsage(accountUsageRecords);
+  renderChatAuthHint();
+  renderChatModels();
+  renderChatHistory();
+  setLoggedInMode(true);
+  setAdminMode(account.role === "admin");
   if (account.role === "admin") await renderAdminPanel();
-  else $("admin-section").style.display = "none";
+}
+
+async function sendChat() {
+  const promptEl = $("chat-prompt");
+  const prompt = promptEl.value.trim();
+  if (!prompt || chatBusy) return;
+  if (!selectedChatModel) {
+    renderChatStatus("select a model first");
+    return;
+  }
+  const bearerToken = chatAuthToken();
+  const body = {
+    model: selectedChatModel,
+    messages: [
+      ...chatHistory
+        .filter(msg => msg.role === "user" || msg.role === "assistant")
+        .map(msg => ({ role: msg.role, content: msg.content })),
+      { role: "user", content: prompt },
+    ],
+    stream: false,
+    max_tokens: 256,
+  };
+  chatBusy = true;
+  $("chat-send").disabled = true;
+  promptEl.value = "";
+  chatHistory.push({ role: "user", content: prompt, model: selectedChatModel });
+  renderChatHistory();
+  renderChatStatus("sending request…");
+  const r = await apiCall("/v1/chat/completions", "POST", body, bearerToken);
+  chatBusy = false;
+  $("chat-send").disabled = false;
+  if (!r.ok) {
+    const error = r.data && r.data.error
+      ? (typeof r.data.error === "string" ? r.data.error : r.data.error.message || "request failed")
+      : "request failed";
+    chatHistory.push({ role: "error", content: error, model: selectedChatModel });
+    renderChatHistory();
+    renderChatStatus(error);
+    promptEl.focus();
+    return;
+  }
+  const reply = (r.data && r.data.choices && r.data.choices[0] && r.data.choices[0].message && r.data.choices[0].message.content) || "";
+  const usage = r.data && r.data.usage;
+  chatHistory.push({
+    role: "assistant",
+    content: reply || "(empty response)",
+    model: selectedChatModel,
+  });
+  renderChatHistory();
+  renderChatStatus(usage
+    ? `done: ${usage.total_tokens ?? "?"} tokens`
+    : "done");
+  promptEl.focus();
 }
 
 async function renderAdminPanel() {
   const r = await apiCall("/v1/admin/accounts");
-  if (!r.ok) { $("admin-section").style.display = "none"; return; }
+  if (!r.ok) { setAdminMode(false); return; }
-  $("admin-section").style.display = "";
   const rows = (r.data.accounts || []).map(a => {
     const balance = Object.values(a.balances || {}).reduce((x, y) => x + y, 0);
     return [
@@ -436,28 +958,44 @@ async function renderAdminPanel() {
 
 async function refresh() {
   $("self-url").textContent = location.host;
-  const [raft, map, summary, settlements, wallets, stats, consoleData] = await Promise.all([
+  const [raft, map, stats, models, consoleData, adminData] = await Promise.all([
-    fetchJson("/v1/raft/status"),
+    fetchJson("/v1/raft/status"),
-    fetchJson("/v1/network/map"),
+    fetchJson("/v1/network/map"),
-    fetchJson("/v1/billing/summary"),
+    fetchJson("/v1/stats"),
-    fetchJson("/v1/billing/settlements"),
+    fetchJson("/v1/models"),
-    fetchJson("/v1/registry/wallets"),
+    fetchJson("/v1/console"),
-    fetchJson("/v1/stats"),
+    isAdmin ? Promise.all([
-    fetchJson("/v1/console"),
+      fetchJson("/v1/billing/summary"),
-  ]);
+      fetchJson("/v1/billing/settlements"),
+      fetchJson("/v1/registry/wallets"),
+    ]) : Promise.resolve([null, null, null]),
+  ]);
+  const [summary, settlements, wallets] = adminData;
+  lastStats = stats;
+  availableModels = ((models && models.data) || []).map(model => ({
+    id: model.id,
+    name: model.name || model.id,
+    recommended: Boolean(model.recommended),
+    aliases: model.aliases || [],
+  })).filter(model => model.id);
   renderHive(raft);
   renderNodes(map);
   renderBilling(summary);
   renderSettlements(settlements);
-  renderFraud(wallets, summary);
+  renderFraud(wallets, summary);
-  renderStats(stats);
+  renderStats(stats);
-  renderThroughput(stats);
+  renderCallWall(consoleData, stats);
-  renderInferenceHistory(consoleData);
+  renderConsole(consoleData);
-  renderConsole(consoleData);
+  renderNodeThroughput(stats);
+  renderChatModels();
+  renderChatHistory();
   $("refreshed").textContent = "refreshed " + new Date().toLocaleTimeString();
 }
 refresh();
 renderAccountPanel();
+renderChatModels();
+renderChatHistory();
+renderChatAuthHint();
 setInterval(refresh, 4000);
 setInterval(() => { if (sessionToken) renderAccountPanel(); }, 8000);
 </script>

tests/test_dashboard.py

@@ -1,6 +1,7 @@
 """US-035: tracker web dashboard — served from any tracker, embedded asset."""
 
 import json
+import time
 import urllib.request
 
 from meshnet_contracts import LocalSolanaContracts
@@ -11,7 +12,9 @@ from meshnet_tracker.server import TrackerServer
 PANELS = [
     "Tracker hive", "Nodes & coverage", "Client balances",
     "Node pending payouts", "Settlement history",
-    "Strikes / bans / forfeitures", "Model usage", "Node throughput",
+    "Strikes / bans / forfeitures", "Model usage", "Call wall",
+    "Usage summary", "Node throughput", "Request history",
+    "Chat / inference",
     "Console output",
 ]
 
@@ -91,3 +94,45 @@ def test_console_endpoint_exposes_tracker_events():
         tracker.stop()
 
     assert any(event["message"] == "node registered" for event in data["events"])
+
+
+def test_console_node_lifecycle_events_include_model_health():
+    tracker = TrackerServer(heartbeat_timeout=0.05)
+    port = tracker.start()
+    try:
+        body = json.dumps({
+            "endpoint": "http://127.0.0.1:9002",
+            "model": "console-health-test",
+            "hf_repo": "example/console-health-test",
+            "num_layers": 4,
+            "shard_start": 0,
+            "shard_end": 1,
+            "hardware_profile": {},
+        }).encode()
+        req = urllib.request.Request(
+            f"http://127.0.0.1:{port}/v1/nodes/register",
+            data=body,
+            headers={"Content-Type": "application/json"},
+            method="POST",
+        )
+        urllib.request.urlopen(req).read()
+
+        registered = json.loads(urllib.request.urlopen(f"http://127.0.0.1:{port}/v1/console").read())
+        registered_event = next(
+            event for event in registered["events"]
+            if event["message"] == "node registered"
+        )
+        assert registered_event["fields"]["model_health"]["served_model_copies"] == 0.5
+        assert registered_event["fields"]["model_health"]["coverage_percentage"] == 50.0
+
+        time.sleep(0.06)
+        urllib.request.urlopen(f"http://127.0.0.1:{port}/v1/network/map").read()
+        expired = json.loads(urllib.request.urlopen(f"http://127.0.0.1:{port}/v1/console").read())
+        expired_event = next(
+            event for event in expired["events"]
+            if event["message"] == "node expired"
+        )
+        assert expired_event["fields"]["model_health"]["served_model_copies"] == 0.0
+        assert expired_event["fields"]["model_health"]["coverage_percentage"] == 0.0
+    finally:
+        tracker.stop()

tests/test_mining_cli.py

@@ -388,6 +388,107 @@ def test_legacy_start_treats_repo_model_as_model_id(monkeypatch):
     assert captured["model_id"] == "Qwen/Qwen2.5-0.5B-Instruct"
 
 
+def test_legacy_start_catalog_model_with_pinned_shards(monkeypatch):
+    """Catalog model names accept --shard-start/--shard-end without --model-id."""
+    from meshnet_node.cli import main
+
+    captured = {}
+
+    def fake_run_startup(*args, **kwargs):
+        captured.update(kwargs)
+        class _FakeNode:
+            chat_completion_count = 0
+            def stop(self): pass
+        return _FakeNode()
+
+    monkeypatch.setattr(sys, "argv", [
+        "meshnet-node", "start",
+        "--tracker", "http://192.168.0.179:8080",
+        "--model", "Qwen3.6-35B-A3B",
+        "--shard-start", "0",
+        "--shard-end", "44",
+        "--port", "0",
+    ])
+
+    with patch("meshnet_node.startup.run_startup", side_effect=fake_run_startup):
+        with patch("time.sleep", side_effect=KeyboardInterrupt):
+            try:
+                main()
+            except SystemExit as exc:
+                assert exc.code == 0
+
+    assert captured["model"] == "Qwen3.6-35B-A3B"
+    assert captured["model_id"] is None
+    assert captured["shard_start"] == 0
+    assert captured["shard_end"] == 44
+
+
+def test_legacy_start_model_id_alias_for_catalog_name(monkeypatch):
+    """--model-id with a catalog name routes through the tracker preset path."""
+    from meshnet_node.cli import main
+
+    captured = {}
+
+    def fake_run_startup(*args, **kwargs):
+        captured.update(kwargs)
+        class _FakeNode:
+            chat_completion_count = 0
+            def stop(self): pass
+        return _FakeNode()
+
+    monkeypatch.setattr(sys, "argv", [
+        "meshnet-node", "start",
+        "--tracker", "http://192.168.0.179:8080",
+        "--model-id", "Qwen3.6-35B-A3B",
+        "--port", "0",
+    ])
+
+    with patch("meshnet_node.startup.run_startup", side_effect=fake_run_startup):
+        with patch("time.sleep", side_effect=KeyboardInterrupt):
+            try:
+                main()
+            except SystemExit as exc:
+                assert exc.code == 0
+
+    assert captured["model"] == "Qwen3.6-35B-A3B"
+    assert captured["model_id"] is None
+
+
+def test_legacy_start_hf_repo_with_pinned_shards(monkeypatch):
+    """HF repo --model with pinned shards still enters the torch startup path."""
+    from meshnet_node.cli import main
+
+    captured = {}
+
+    def fake_run_startup(*args, **kwargs):
+        captured.update(kwargs)
+        class _FakeNode:
+            chat_completion_count = 0
+            def stop(self): pass
+        return _FakeNode()
+
+    monkeypatch.setattr(sys, "argv", [
+        "meshnet-node", "start",
+        "--tracker", "http://192.168.0.179:8081",
+        "--model", "Qwen/Qwen2.5-0.5B-Instruct",
+        "--shard-start", "12",
+        "--shard-end", "23",
+        "--port", "0",
+    ])
+
+    with patch("meshnet_node.startup.run_startup", side_effect=fake_run_startup):
+        with patch("time.sleep", side_effect=KeyboardInterrupt):
+            try:
+                main()
+            except SystemExit as exc:
+                assert exc.code == 0
+
+    assert captured["model"] == "Qwen2.5-0.5B-Instruct"
+    assert captured["model_id"] == "Qwen/Qwen2.5-0.5B-Instruct"
+    assert captured["shard_start"] == 12
+    assert captured["shard_end"] == 23
+
+
 def test_legacy_start_falls_back_to_env_tracker_and_model(monkeypatch):
     """`meshnet-node start` uses env defaults when tracker/model flags are omitted."""
     import importlib

tests/test_node_startup.py

@@ -5,8 +5,10 @@ import io
 import os
 import sys
 import tarfile
+import threading
 import time
 import types
+import urllib.error
 import urllib.request
 from pathlib import Path
 
@@ -566,6 +568,78 @@ def test_download_shard_prefers_tracker_model_source_over_huggingface(
     assert hf_calls == []
 
 
+def test_download_shard_prefers_tracker_full_model_source_over_huggingface(
+    tmp_path,
+    monkeypatch,
+):
+    """A tracker-advertised full snapshot is sufficient on its own — HF is never contacted."""
+    contents = {
+        "config.json": b"{}",
+        "weights-a.safetensors": b"tracker-a",
+        "weights-b.safetensors": b"tracker-b",
+    }
+
+    class FakeFileResponse:
+        def __init__(self, payload: bytes):
+            self._payload = io.BytesIO(payload)
+            self._length = len(payload)
+
+        def __enter__(self):
+            return self
+
+        def __exit__(self, exc_type, exc, tb):
+            return False
+
+        def getheader(self, name: str):
+            if name == "Content-Length":
+                return str(self._length)
+            if name == "Content-Type":
+                return "application/octet-stream"
+            return None
+
+        def read(self, size: int = -1) -> bytes:
+            return self._payload.read(size)
+
+    def fake_urlopen(url, *args, **kwargs):
+        query = urllib.parse.parse_qs(urllib.parse.urlparse(url).query)
+        rel = query.get("file", [None])[0]
+        assert rel in contents, f"unexpected per-file request: {url}"
+        return FakeFileResponse(contents[rel])
+
+    monkeypatch.setattr(urllib.request, "urlopen", fake_urlopen)
+    hf_calls = []
+
+    def fake_snapshot_download(**kwargs):
+        hf_calls.append(kwargs)
+        raise AssertionError("HuggingFace should not be contacted when tracker full_files are available")
+
+    monkeypatch.setitem(
+        sys.modules,
+        "huggingface_hub",
+        types.SimpleNamespace(snapshot_download=fake_snapshot_download),
+    )
+
+    shard_dir = download_shard(
+        "tiny-llama",
+        0,
+        3,
+        cache_dir=tmp_path / "cache",
+        hf_repo="org/tiny-llama-shards",
+        model_sources=[{
+            "type": "tracker-full",
+            "url": "http://tracker/v1/model-files/download?model=tiny-llama&full=1",
+            "files": ["config.json", "weights-a.safetensors", "weights-b.safetensors"],
+            "full_files": ["config.json", "weights-a.safetensors", "weights-b.safetensors"],
+        }],
+        progress=False,
+    )
+
+    assert (shard_dir / "config.json").read_text() == "{}"
+    assert (shard_dir / "weights-a.safetensors").read_text() == "tracker-a"
+    assert (shard_dir / "weights-b.safetensors").read_text() == "tracker-b"
+    assert hf_calls == []
+
+
 def test_download_shard_falls_back_to_huggingface_when_tracker_source_fails(
     tmp_path,
     monkeypatch,
@@ -1359,6 +1433,84 @@ def test_later_node_auto_joins_existing_public_hf_model_with_only_tracker_url(
     assert route_resp["route"] == ["http://203.0.113.20:8001", "http://203.0.113.21:8002"]
 
 
+def test_later_node_auto_joins_redundant_copy_when_model_is_fully_covered(
+    tmp_path,
+    monkeypatch,
+):
+    """Model-less joins should load the served HF model even when gap_found=false."""
+    import meshnet_node.startup as startup_mod
+
+    captured = {}
+
+    class FakeBackend:
+        total_layers = 24
+
+    class FakeTorchNodeServer:
+        def __init__(self, **kwargs):
+            captured.update(kwargs)
+            self.backend = FakeBackend()
+            self.port = None
+            self.chat_completion_count = 0
+            self.total_requests = 0
+            self.failed_requests = 0
+            self.queue_depth = 0
+
+        def start(self):
+            self.port = 8003
+            return self.port
+
+        def stop(self):
+            pass
+
+    monkeypatch.setattr(
+        startup_mod,
+        "detect_hardware",
+        lambda: {"device": "cpu", "gpu_name": None, "vram_mb": 0},
+    )
+    monkeypatch.setattr(startup_mod, "TorchNodeServer", FakeTorchNodeServer)
+
+    tracker = TrackerServer()
+    tracker_port = tracker.start()
+    tracker_url = f"http://127.0.0.1:{tracker_port}"
+    try:
+        for endpoint, shard_start, shard_end in (
+            ("http://203.0.113.30:8001", 0, 11),
+            ("http://203.0.113.31:8001", 12, 23),
+        ):
+            data = json.dumps({
+                "endpoint": endpoint,
+                "model": "Qwen2.5-0.5B-Instruct",
+                "hf_repo": "Qwen/Qwen2.5-0.5B-Instruct",
+                "num_layers": 24,
+                "shard_start": shard_start,
+                "shard_end": shard_end,
+                "tracker_mode": shard_start == 0,
+                "hardware_profile": {},
+                "score": 1.0,
+            }).encode()
+            req = urllib.request.Request(
+                f"{tracker_url}/v1/nodes/register",
+                data=data,
+                headers={"Content-Type": "application/json"},
+                method="POST",
+            )
+            with urllib.request.urlopen(req) as resp:
+                resp.read()
+
+        node = run_startup(
+            tracker_url=tracker_url,
+            advertise_host="203.0.113.32",
+            wallet_path=tmp_path / "wallet.json",
+        )
+        try:
+            assert captured["model_id"] == "Qwen/Qwen2.5-0.5B-Instruct"
+            assert captured["shard_start"] == 0
+        finally:
+            node.stop()
+    finally:
+        tracker.stop()
+
+
 # ---------------------------------------------------------------------------
 # Full startup integration test
 # ---------------------------------------------------------------------------
@@ -1453,6 +1605,120 @@ def test_preset_model_startup_starts_heartbeat(tmp_path, monkeypatch):
         tracker.stop()
 
 
+def test_preset_model_startup_honors_pinned_shard_range(tmp_path, monkeypatch):
+    """Explicit --shard-start/--shard-end override tracker auto-assignment."""
+    import meshnet_node.startup as startup_mod
+
+    monkeypatch.setattr(
+        startup_mod,
+        "detect_hardware",
+        lambda: {"device": "cpu", "gpu_name": None, "vram_mb": 0, "ram_mb": 16 * 1024},
+    )
+    heartbeat_calls = []
+    monkeypatch.setattr(
+        startup_mod,
+        "_start_heartbeat",
+        lambda *args, **kwargs: heartbeat_calls.append((args, kwargs)),
+    )
+
+    tracker = TrackerServer(model_presets={"stub-model": {"layers_start": 0, "layers_end": 15}})
+    tracker_port = tracker.start()
+    tracker_url = f"http://127.0.0.1:{tracker_port}"
+    try:
+        node = run_startup(
+            tracker_url=tracker_url,
+            model="stub-model",
+            shard_start=0,
+            shard_end=5,
+            wallet_path=tmp_path / "wallet.json",
+            cache_dir=tmp_path / "shards",
+        )
+        try:
+            assert len(heartbeat_calls) == 1
+            args, kwargs = heartbeat_calls[0]
+            reg_payload = args[2]
+            assert reg_payload["shard_start"] == 0
+            assert reg_payload["shard_end"] == 5
+            assert reg_payload["managed_assignment"] is False
+        finally:
+            node.stop()
+    finally:
+        tracker.stop()
+
+
+def test_torch_startup_retries_registration_when_tracker_unreachable(
+    tmp_path,
+    monkeypatch,
+):
+    """Failed initial registration should start background retry, not stay unregistered."""
+    import meshnet_node.startup as startup_mod
+
+    class FakeBackend:
+        total_layers = 24
+
+    class FakeTorchNodeServer:
+        def __init__(self, **kwargs):
+            self.backend = FakeBackend()
+            self.port = None
+            self.chat_completion_count = 0
+            self.tracker_node_id = None
+
+        def start(self):
+            self.port = 7000
+            return self.port
+
+        def stop(self):
+            pass
+
+    monkeypatch.setattr(
+        startup_mod,
+        "detect_hardware",
+        lambda: {"device": "cuda", "gpu_name": "Test GPU", "vram_mb": 8192, "ram_mb": 16 * 1024},
+    )
+    monkeypatch.setattr(startup_mod, "TorchNodeServer", FakeTorchNodeServer)
+    monkeypatch.setattr(
+        startup_mod,
+        "_detect_num_layers",
+        lambda *_args, **_kwargs: 24,
+    )
+
+    heartbeat_calls = []
+    monkeypatch.setattr(
+        startup_mod,
+        "_start_heartbeat",
+        lambda *args, **kwargs: heartbeat_calls.append((args, kwargs)) or threading.Thread(),
+    )
+
+    register_calls = {"count": 0}
+
+    def flaky_register(url, payload):
+        register_calls["count"] += 1
+        raise urllib.error.URLError("connection refused")
+
+    monkeypatch.setattr(startup_mod, "_post_json", flaky_register)
+
+    tracker = TrackerServer()
+    tracker_port = tracker.start()
+    tracker_url = f"http://127.0.0.1:{tracker_port}"
+    try:
+        node = run_startup(
+            tracker_url=tracker_url,
+            model_id="Qwen/Qwen2.5-0.5B-Instruct",
+            wallet_path=tmp_path / "wallet.json",
+        )
+        try:
+            assert register_calls["count"] == 1
+            assert node.tracker_node_id is None
+            assert len(heartbeat_calls) == 1
+            args, kwargs = heartbeat_calls[0]
+            assert args[1] == startup_mod._PENDING_NODE_ID
+            assert kwargs["node_ref"] is node
+        finally:
+            node.stop()
+    finally:
+        tracker.stop()
+
+
 def test_real_model_startup_registers_downloaded_inventory_without_checksum(
     tmp_path,
     monkeypatch,

tests/test_real_model_backend.py

@@ -4,6 +4,8 @@ import json
 import os
 from pathlib import Path
 import sys
+import threading
+import time
 import types
 import urllib.request
 
@@ -11,8 +13,12 @@ import pytest
 
 from meshnet_node.model_backend import (
     InsufficientVRAMError,
+    PartialModelLoadUnsupported,
     TensorPayload,
+    TorchModelShard,
     _call_layer,
+    _load_partial_model_from_snapshot,
+    _should_partial_materialize_shard,
     _decoder_attention_mask,
     _int_tensor_header,
     build_quantization_config,
@@ -94,7 +100,7 @@ class _FakePipelineHeadBackend(_FakeBackend):
     tokenizer = _FakeChatTokenizer()
 
     def encode_prompt(self, prompt: str) -> TensorPayload:
-        assert prompt == "debug prompt"
+        assert prompt.startswith("debug prompt")
         return TensorPayload(
             body=b"\x00" * (1 * 6 * 8 * 2),
             shape=[1, 6, 8],
@@ -113,6 +119,19 @@ class _FakePipelineTailBackend(_FakeTailBackend):
         return " token"
 
 
+class _BlockingStreamingTailBackend(_FakeTailBackend):
+    def __init__(self, second_token_release: threading.Event) -> None:
+        self._release = second_token_release
+        self.calls = 0
+
+    def forward_bytes(self, body, shape, attention_mask_header, position_ids_header, start_layer=None):
+        self.calls += 1
+        if self.calls == 1:
+            return " first"
+        self._release.wait(timeout=3.0)
+        return " second"
+
+
 def test_quantization_flag_validation():
     assert validate_quantization("bfloat16") == "bfloat16"
     assert validate_quantization("int8") == "int8"
@@ -299,6 +318,56 @@ def test_pipeline_hop_logs_are_enabled_with_debug(capsys):
     assert "  [node] pipeline hop 0 returned text=' token'" in out
 
 
+def test_split_shard_chat_streams_each_generated_token_incrementally():
+    release_second = threading.Event()
+    head = TorchNodeServer(backend=_FakePipelineHeadBackend(), tracker_mode=True)
+    tail = TorchNodeServer(backend=_BlockingStreamingTailBackend(release_second))
+    head_port = head.start()
+    tail_port = tail.start()
+    response = None
+    try:
+        payload = json.dumps({
+            "model": "fake-model",
+            "messages": [{"role": "user", "content": "hello"}],
+            "stream": True,
+            "max_tokens": 2,
+        }).encode()
+        req = urllib.request.Request(
+            f"http://127.0.0.1:{head_port}/v1/chat/completions",
+            data=payload,
+            headers={
+                "Content-Type": "application/json",
+                "X-Meshnet-Route": json.dumps([
+                    {"endpoint": f"http://127.0.0.1:{tail_port}", "start_layer": 22},
+                ]),
+            },
+            method="POST",
+        )
+        response = urllib.request.urlopen(req, timeout=5)
+
+        first_token_line = ""
+        deadline = time.time() + 2.0
+        while time.time() < deadline:
+            line = response.readline().decode()
+            if '"content": " first"' in line:
+                first_token_line = line
+                break
+
+        assert first_token_line
+        assert not release_second.is_set()
+        release_second.set()
+        rest = response.read().decode()
+    finally:
+        release_second.set()
+        if response is not None:
+            response.close()
+        head.stop()
+        tail.stop()
+
+    assert '"content": " second"' in rest
+    assert "data: [DONE]" in rest
+
+
 def test_int_tensor_header_serializes_torch_tensors():
     torch = pytest.importorskip("torch")
 
@@ -334,6 +403,295 @@ def test_call_layer_passes_rotary_position_embeddings():
     ) == "hidden"
 
 
+def test_partial_materialize_guard_requires_local_non_full_non_quantized_snapshot(tmp_path):
+    snapshot_dir = tmp_path / "snapshot"
+    snapshot_dir.mkdir()
+    (snapshot_dir / "config.json").write_text("{}")
+    (snapshot_dir / "model.safetensors.index.json").write_text('{"weight_map": {}}')
+
+    assert _should_partial_materialize_shard(
+        str(snapshot_dir),
+        4,
+        7,
+        total_layers_hint=40,
+        uses_quantized_weights=False,
+    ) is True
+    assert _should_partial_materialize_shard(
+        str(snapshot_dir),
+        0,
+        39,
+        total_layers_hint=40,
+        uses_quantized_weights=False,
+    ) is False
+    assert _should_partial_materialize_shard(
+        str(snapshot_dir),
+        4,
+        7,
+        total_layers_hint=40,
+        uses_quantized_weights=True,
+    ) is False
+    assert _should_partial_materialize_shard(
+        "repo/model",
+        4,
+        7,
+        total_layers_hint=40,
+        uses_quantized_weights=False,
+    ) is False
+
+
+def test_partial_snapshot_loader_materializes_only_assigned_tensors(tmp_path):
+    snapshot_dir = tmp_path / "snapshot"
+    snapshot_dir.mkdir()
+    (snapshot_dir / "config.json").write_text("{}")
+    (snapshot_dir / "model.safetensors.index.json").write_text(json.dumps({
+        "weight_map": {
+            "model.embed_tokens.weight": "shard-1.safetensors",
+            "model.layers.0.self_attn.q_proj.weight": "shard-1.safetensors",
+            "model.layers.1.self_attn.q_proj.weight": "shard-2.safetensors",
+            "model.layers.2.self_attn.q_proj.weight": "shard-3.safetensors",
+            "model.norm.weight": "shard-3.safetensors",
+            "lm_head.weight": "shard-3.safetensors",
+        }
+    }))
+    for rel in ("shard-1.safetensors", "shard-2.safetensors", "shard-3.safetensors"):
+        (snapshot_dir / rel).write_bytes(b"stub")
+
+    class FakeModule:
+        def __init__(self, name):
+            self.name = name
+            self.to_calls = []
+
+        def to(self, device):
+            self.to_calls.append(device)
+            return self
+
+    class FakeModel:
+        def __init__(self):
+            self.model = types.SimpleNamespace(
+                embed_tokens=FakeModule("embed"),
+                layers=[FakeModule("layer0"), FakeModule("layer1"), FakeModule("layer2")],
+                rotary_emb=FakeModule("rotary"),
+                norm=FakeModule("norm"),
+            )
+            self.lm_head = FakeModule("lm_head")
+            self.tie_weights_called = 0
+
+        def tie_weights(self):
+            self.tie_weights_called += 1
+
+    class AutoConfigStub:
+        @staticmethod
+        def from_pretrained(model_id):
+            assert model_id == str(snapshot_dir)
+            return types.SimpleNamespace(num_hidden_layers=3)
+
+    class AutoModelStub:
+        @staticmethod
+        def from_config(cfg, torch_dtype=None):
+            assert cfg.num_hidden_layers == 3
+            assert torch_dtype == "bf16"
+            return FakeModel()
+
+    class EmptyWeights:
+        def __init__(self):
+            self.entered = 0
+            self.exited = 0
+
+        def __call__(self):
+            return self
+
+        def __enter__(self):
+            self.entered += 1
+            return None
+
+        def __exit__(self, exc_type, exc, tb):
+            self.exited += 1
+            return False
+
+    init_empty_weights = EmptyWeights()
+    set_calls = []
+
+    def fake_set_tensor(module, tensor_name, device, value=None, dtype=None):
+        set_calls.append((tensor_name, device, value, dtype))
+
+    tensors = {
+        "shard-1.safetensors": {
+            "model.embed_tokens.weight": "embed",
+            "model.layers.0.self_attn.q_proj.weight": "layer0",
+        },
+        "shard-2.safetensors": {
+            "model.layers.1.self_attn.q_proj.weight": "layer1",
+        },
+        "shard-3.safetensors": {
+            "model.layers.2.self_attn.q_proj.weight": "layer2",
+            "model.norm.weight": "norm",
+            "lm_head.weight": "lm_head",
+        },
+    }
+
+    class FakeSafeOpen:
+        def __init__(self, filename, framework, device):
+            assert framework == "pt"
+            assert device == "cpu"
+            self.filename = Path(filename).name
+
+        def __enter__(self):
+            return self
+
+        def __exit__(self, exc_type, exc, tb):
+            return False
+
+        def get_tensor(self, tensor_name):
+            return tensors[self.filename][tensor_name]
+
+    model = _load_partial_model_from_snapshot(
+        AutoConfigStub,
+        AutoModelStub,
+        types.SimpleNamespace(),
+        str(snapshot_dir),
+        1,
+        1,
+        "bf16",
+        "cpu:0",
+        init_empty_weights_fn=init_empty_weights,
+        set_tensor_fn=fake_set_tensor,
+        safe_open_fn=FakeSafeOpen,
+    )
+
+    assert init_empty_weights.entered == 1
+    assert init_empty_weights.exited == 1
+    assert model.tie_weights_called == 1
+    assert [call[0] for call in set_calls] == ["model.layers.1.self_attn.q_proj.weight"]
+    assert model.model.layers[1].to_calls == ["cpu:0"]
+    assert model.model.layers[0].to_calls == []
+    assert model.model.layers[2].to_calls == []
+    assert model.model.embed_tokens.to_calls == []
+    assert model.model.norm.to_calls == []
+    assert model.lm_head.to_calls == []
+    assert model.model.rotary_emb.to_calls == ["cpu:0"]
+
+
+def test_partial_snapshot_loader_requires_known_layer_count(tmp_path):
+    snapshot_dir = tmp_path / "snapshot"
+    snapshot_dir.mkdir()
+    (snapshot_dir / "config.json").write_text("{}")
+    (snapshot_dir / "model.safetensors.index.json").write_text(json.dumps({
+        "weight_map": {"model.layers.0.self_attn.q_proj.weight": "shard.safetensors"}
+    }))
+    (snapshot_dir / "shard.safetensors").write_bytes(b"stub")
+
+    class AutoConfigStub:
+        @staticmethod
+        def from_pretrained(model_id):
+            return types.SimpleNamespace()
+
+    class AutoModelStub:
+        @staticmethod
+        def from_config(cfg, torch_dtype=None):
+            raise AssertionError("from_config should not run without a known layer count")
+
+    class UnusedContext:
+        def __enter__(self):
+            return None
+
+        def __exit__(self, exc_type, exc, tb):
+            return False
+
+    with pytest.raises(PartialModelLoadUnsupported, match="num_hidden_layers"):
+        _load_partial_model_from_snapshot(
+            AutoConfigStub,
+            AutoModelStub,
+            types.SimpleNamespace(),
+            str(snapshot_dir),
+            0,
+            0,
+            "bf16",
+            "cpu:0",
+            init_empty_weights_fn=lambda: UnusedContext(),
+            set_tensor_fn=lambda *args, **kwargs: None,
+            safe_open_fn=lambda *args, **kwargs: None,
+        )
+
+
+def test_torch_model_shard_prefers_partial_loader_for_local_snapshot(tmp_path, monkeypatch):
+    import meshnet_node.model_backend as backend
+
+    snapshot_dir = tmp_path / "snapshot"
+    snapshot_dir.mkdir()
+    (snapshot_dir / "config.json").write_text("{}")
+    (snapshot_dir / "model.safetensors.index.json").write_text('{"weight_map": {}}')
+
+    class FakeModel:
+        def __init__(self):
+            self.model = types.SimpleNamespace(
+                layers=[object(), object(), object()],
+                embed_tokens=object(),
+            )
+            self.config = types.SimpleNamespace(hidden_size=8)
+            self.eval_called = 0
+
+        def eval(self):
+            self.eval_called += 1
+
+    fake_model = FakeModel()
+    partial_calls = []
+
+    class AutoConfigStub:
+        @staticmethod
+        def from_pretrained(model_id, cache_dir=None):
+            return types.SimpleNamespace(num_hidden_layers=3, text_config=types.SimpleNamespace(dtype="torch.bfloat16"))
+
+    class AutoModelStub:
+        @staticmethod
+        def from_pretrained(*args, **kwargs):
+            raise AssertionError("full model load should not run for partial local shards")
+
+    class AutoTokenizerStub:
+        @staticmethod
+        def from_pretrained(model_id, cache_dir=None):
+            assert model_id == str(snapshot_dir)
+            return types.SimpleNamespace()
+
+    monkeypatch.setitem(
+        sys.modules,
+        "torch",
+        types.SimpleNamespace(
+            cuda=types.SimpleNamespace(is_available=lambda: False),
+            device=lambda value: value,
+            bfloat16="bf16",
+        ),
+    )
+    monkeypatch.setitem(
+        sys.modules,
+        "transformers",
+        types.SimpleNamespace(
+            AutoConfig=AutoConfigStub,
+            AutoModelForCausalLM=AutoModelStub,
+            AutoTokenizer=AutoTokenizerStub,
+        ),
+    )
+    monkeypatch.setattr(
+        backend,
+        "_load_partial_model_from_snapshot",
+        lambda *args, **kwargs: partial_calls.append((args, kwargs)) or fake_model,
+    )
+
+    shard = TorchModelShard(
+        "repo/model",
+        1,
+        1,
+        quantization="auto",
+        cache_dir=snapshot_dir,
+    )
+
+    assert len(partial_calls) == 1
+    assert shard.model is fake_model
+    assert fake_model.eval_called == 1
+    assert shard.total_layers == 3
+    assert shard.is_head is False
+    assert shard.is_tail is False
+
+
 @pytest.mark.integration
 def test_two_node_gpt2_completion_is_deterministic():
     if os.environ.get("CI"):

tests/test_tracker_routing.py

@@ -13,7 +13,13 @@ from meshnet_gateway.server import GatewayServer, _banned_route_wallet
 from meshnet_node.server import StubNodeServer
 from meshnet_contracts import LocalSolanaContracts
 from meshnet_tracker.auth import sign_hive_request
-from meshnet_tracker.server import TrackerServer, _NodeEntry, _registration_ban_error
+from meshnet_tracker.server import (
+    TrackerServer,
+    _NodeEntry,
+    _memory_pool_map,
+    _registration_ban_error,
+    _scale_demanded_models_locked,
+)
 
 _TEST_HIVE_SECRET = "test-hive-secret"
 
@@ -162,6 +168,59 @@ def test_network_map_exposes_pool_size_and_speed_summary():
     assert pool["total_effective_throughput"] == 10.0
 
 
+def test_network_map_exposes_served_model_copy_count():
+    tracker = TrackerServer()
+    port = tracker.start()
+    url = f"http://127.0.0.1:{port}"
+    try:
+        _post_json(
+            f"{url}/v1/nodes/register",
+            {
+                "endpoint": "http://127.0.0.1:7201",
+                "model": "copy-count-test",
+                "hf_repo": "example/copy-count-test",
+                "num_layers": 37,
+                "shard_start": 0,
+                "shard_end": 21,
+                "hardware_profile": {},
+            },
+        )
+        network_map = _get_json(f"{url}/v1/network/map")
+        assert network_map["nodes"][0]["model_supply"]["served_model_copies"] == 0.59
+
+        _post_json(
+            f"{url}/v1/nodes/register",
+            {
+                "endpoint": "http://127.0.0.1:7202",
+                "model": "copy-count-test",
+                "hf_repo": "example/copy-count-test",
+                "num_layers": 37,
+                "shard_start": 22,
+                "shard_end": 36,
+                "hardware_profile": {},
+            },
+        )
+        network_map = _get_json(f"{url}/v1/network/map")
+        assert network_map["nodes"][0]["model_supply"]["served_model_copies"] == 1.0
+
+        _post_json(
+            f"{url}/v1/nodes/register",
+            {
+                "endpoint": "http://127.0.0.1:7203",
+                "model": "copy-count-test",
+                "hf_repo": "example/copy-count-test",
+                "num_layers": 37,
+                "shard_start": 0,
+                "shard_end": 36,
+                "hardware_profile": {},
+            },
+        )
+        network_map = _get_json(f"{url}/v1/network/map")
+        assert network_map["nodes"][0]["model_supply"]["served_model_copies"] == 2.0
+    finally:
+        tracker.stop()
+
+
 def test_recommended_kimi_becomes_deployable_when_pool_is_large_enough():
     tracker = TrackerServer()
     port = tracker.start()
@@ -271,6 +330,177 @@ def test_tracker_serves_health_while_proxy_request_is_in_flight():
         slow_thread.join(timeout=1.0)
 
 
+def test_tracker_route_log_counts_proxy_inflight_requests():
+    entered = threading.Event()
+    release = threading.Event()
+
+    class SlowChatHandler(http.server.BaseHTTPRequestHandler):
+        def log_message(self, fmt, *args):
+            pass
+
+        def do_POST(self):
+            if self.path != "/v1/chat/completions":
+                self.send_response(404)
+                self.end_headers()
+                return
+            length = int(self.headers.get("Content-Length", 0))
+            self.rfile.read(length)
+            entered.set()
+            release.wait(timeout=3.0)
+            body = json.dumps({"choices": [{"message": {"content": "ok"}}]}).encode()
+            self.send_response(200)
+            self.send_header("Content-Type", "application/json")
+            self.send_header("Content-Length", str(len(body)))
+            self.end_headers()
+            self.wfile.write(body)
+
+    slow_node = http.server.HTTPServer(("127.0.0.1", 0), SlowChatHandler)
+    slow_thread = threading.Thread(target=slow_node.serve_forever, daemon=True)
+    slow_thread.start()
+    tracker = TrackerServer(heartbeat_timeout=60.0)
+    tracker_port = tracker.start()
+    errors = []
+    try:
+        _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {"endpoint": f"http://127.0.0.1:{slow_node.server_address[1]}",
+             "model": "burst-model", "num_layers": 1,
+             "shard_start": 0, "shard_end": 0,
+             "hardware_profile": {}, "score": 1.0},
+        )
+
+        def call_proxy():
+            try:
+                _post_json(
+                    f"http://127.0.0.1:{tracker_port}/v1/chat/completions",
+                    {"model": "burst-model", "messages": [{"role": "user", "content": "hi"}]},
+                )
+            except Exception as exc:
+                errors.append(exc)
+
+        first = threading.Thread(target=call_proxy)
+        second = threading.Thread(target=call_proxy)
+        first.start()
+        assert entered.wait(timeout=2.0)
+        second.start()
+
+        selected_events = []
+        deadline = time.time() + 2.0
+        while time.time() < deadline:
+            console = _get_json(f"http://127.0.0.1:{tracker_port}/v1/console")
+            selected_events = [
+                event for event in console["events"]
+                if event["message"] == "proxy route selected"
+            ]
+            if len(selected_events) >= 2:
+                break
+            time.sleep(0.05)
+
+        assert len(selected_events) >= 2
+        second_nodes = selected_events[-1]["fields"]["nodes"]
+        assert second_nodes[0]["queue_depth"] == 2
+        assert second_nodes[0]["proxy_inflight"] == 2
+    finally:
+        release.set()
+        first.join(timeout=3.0)
+        second.join(timeout=3.0)
+        tracker.stop()
+        slow_node.shutdown()
+        slow_node.server_close()
+        slow_thread.join(timeout=1.0)
+
+    assert not first.is_alive()
+    assert not second.is_alive()
+    assert not errors
+
+
+def test_tracker_logs_stream_progress_before_request_completes():
+    chunk_sent = threading.Event()
+    release = threading.Event()
+
+    class StreamingChatHandler(http.server.BaseHTTPRequestHandler):
+        def log_message(self, fmt, *args):
+            pass
+
+        def do_POST(self):
+            if self.path != "/v1/chat/completions":
+                self.send_response(404)
+                self.end_headers()
+                return
+            self.rfile.read(int(self.headers.get("Content-Length", 0)))
+            self.send_response(200)
+            self.send_header("Content-Type", "text/event-stream; charset=utf-8")
+            self.end_headers()
+            payload = json.dumps({
+                "choices": [{"delta": {"content": "hello world"}}],
+            }).encode()
+            self.wfile.write(b"data: " + payload + b"\n\n")
+            self.wfile.flush()
+            chunk_sent.set()
+            release.wait(timeout=3.0)
+            self.wfile.write(b"data: [DONE]\n\n")
+            self.wfile.flush()
+
+    node = http.server.HTTPServer(("127.0.0.1", 0), StreamingChatHandler)
+    node_thread = threading.Thread(target=node.serve_forever, daemon=True)
+    node_thread.start()
+    tracker = TrackerServer(heartbeat_timeout=60.0)
+    tracker_port = tracker.start()
+    response = None
+    try:
+        _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {"endpoint": f"http://127.0.0.1:{node.server_address[1]}",
+             "model": "stream-progress-model", "num_layers": 1,
+             "shard_start": 0, "shard_end": 0,
+             "hardware_profile": {}, "score": 1.0},
+        )
+        req = urllib.request.Request(
+            f"http://127.0.0.1:{tracker_port}/v1/chat/completions",
+            data=json.dumps({
+                "model": "stream-progress-model",
+                "stream": True,
+                "messages": [{"role": "user", "content": "hi"}],
+            }).encode(),
+            headers={"Content-Type": "application/json"},
+            method="POST",
+        )
+        response = urllib.request.urlopen(req, timeout=3.0)
+        first_line = response.readline()
+        assert first_line.startswith(b"data:")
+        assert chunk_sent.wait(timeout=1.0)
+
+        progress_events = []
+        deadline = time.time() + 2.0
+        while time.time() < deadline:
+            console = _get_json(f"http://127.0.0.1:{tracker_port}/v1/console")
+            progress_events = [
+                event for event in console["events"]
+                if event["message"] == "proxy progress"
+            ]
+            if progress_events:
+                break
+            time.sleep(0.05)
+
+        assert progress_events
+        fields = progress_events[-1]["fields"]
+        assert fields["tokens"] == 2
+        assert fields["tokens_per_sec"] > 0
+        active = [
+            event for event in console["events"]
+            if event["message"] == "proxy route selected"
+        ]
+        assert active
+    finally:
+        release.set()
+        if response is not None:
+            response.close()
+        tracker.stop()
+        node.shutdown()
+        node.server_close()
+        node_thread.join(timeout=1.0)
+
+
 def test_tracker_routes_hf_model_alias_from_quickstart():
     """The documented qwen2.5-0.5b alias resolves a full HF repo registration."""
     tracker = TrackerServer()
@@ -483,6 +713,101 @@ def test_tracker_route_endpoint_routes_split_preset_nodes_by_alias():
     assert [node["start_layer"] for node in response["nodes"]] == [0, 22]
 
 
+def test_tracker_route_endpoint_ignores_model_case_and_outer_whitespace():
+    tracker = TrackerServer(model_presets={
+        "qwen3.6-35b-a3b": {
+            "layers_start": 0,
+            "layers_end": 39,
+            "hf_repo": "unsloth/Qwen3.6-35B-A3B",
+            "aliases": ["Qwen3.6-35B-A3B"],
+        }
+    })
+    tracker_port = tracker.start()
+    try:
+        _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {"endpoint": "http://127.0.0.1:9101",
+             "model": "qwen3.6-35b-a3b",
+             "hf_repo": "unsloth/Qwen3.6-35B-A3B",
+             "num_layers": 40,
+             "shard_start": 0,
+             "shard_end": 39,
+             "tracker_mode": True,
+             "hardware_profile": {},
+             "score": 1.0},
+        )
+
+        response = _get_json(
+            f"http://127.0.0.1:{tracker_port}/v1/route?model=%20Qwen3.6-35B-A3B%20"
+        )
+    finally:
+        tracker.stop()
+
+    assert response["route"] == ["http://127.0.0.1:9101"]
+
+
+def test_tracker_proxy_ignores_model_case_and_outer_whitespace():
+    class ChatHandler(http.server.BaseHTTPRequestHandler):
+        def log_message(self, fmt, *args):
+            pass
+
+        def do_POST(self):
+            if self.path != "/v1/chat/completions":
+                self.send_response(404)
+                self.end_headers()
+                return
+            length = int(self.headers.get("Content-Length", 0))
+            request_body = json.loads(self.rfile.read(length) or b"{}")
+            body = json.dumps({
+                "model": request_body["model"],
+                "choices": [{"message": {"content": "ok"}}],
+            }).encode()
+            self.send_response(200)
+            self.send_header("Content-Type", "application/json")
+            self.send_header("Content-Length", str(len(body)))
+            self.end_headers()
+            self.wfile.write(body)
+
+    node = http.server.HTTPServer(("127.0.0.1", 0), ChatHandler)
+    node_thread = threading.Thread(target=node.serve_forever, daemon=True)
+    node_thread.start()
+    tracker = TrackerServer(model_presets={
+        "qwen3.6-35b-a3b": {
+            "layers_start": 0,
+            "layers_end": 39,
+            "hf_repo": "unsloth/Qwen3.6-35B-A3B",
+            "aliases": ["Qwen3.6-35B-A3B"],
+        }
+    })
+    tracker_port = tracker.start()
+    try:
+        _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {"endpoint": f"http://127.0.0.1:{node.server_address[1]}",
+             "model": "qwen3.6-35b-a3b",
+             "hf_repo": "unsloth/Qwen3.6-35B-A3B",
+             "num_layers": 40,
+             "shard_start": 0,
+             "shard_end": 39,
+             "tracker_mode": True,
+             "hardware_profile": {},
+             "score": 1.0},
+        )
+
+        response = _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/chat/completions",
+            {"model": "Qwen3.6-35B-A3B ",
+             "messages": [{"role": "user", "content": "hi"}]},
+        )
+    finally:
+        tracker.stop()
+        node.shutdown()
+        node.server_close()
+        node_thread.join(timeout=1.0)
+
+    assert response["choices"][0]["message"]["content"] == "ok"
+
+
 def test_tracker_registration_node_id_includes_wallet_prefix_and_stable_suffix():
     tracker = TrackerServer()
     tracker_port = tracker.start()
@@ -795,12 +1120,14 @@ def test_tracker_speed_is_primary_when_both_nodes_can_cover_gap():
              "benchmark_tokens_per_sec": 3.0, "hardware_profile": {}, "score": 1.0},
         )
 
-        route_resp = _get_json(f"http://127.0.0.1:{tracker_port}/v1/route?model=tiny-model")
+        net = _get_json(f"http://127.0.0.1:{tracker_port}/v1/network/map")
         widths = {
             node["endpoint"]: node["shard_end"] - node["shard_start"] + 1
-            for node in route_resp["nodes"]
+            for node in net["nodes"]
         }
-        assert widths["http://127.0.0.1:9012"] > widths["http://127.0.0.1:9011"]
+        assert widths["http://127.0.0.1:9011"] == 12
+        assert widths["http://127.0.0.1:9012"] == 12
+        assert net["nodes"][0]["model_supply"]["served_model_copies"] == 2.0
     finally:
         tracker.stop()
 
@@ -828,7 +1155,8 @@ def test_tracker_registration_directive_is_not_replayed_on_heartbeat():
         tracker.stop()
 
 
-def test_tracker_reassignment_emits_drop_before_load():
+def test_tracker_pool_join_adds_redundant_copy_without_splitting_incumbent():
+    """A second managed node with capacity for the full model keeps the first copy intact."""
     tracker = TrackerServer(model_presets={
         "tiny-model": {
             "total_layers": 4,
@@ -837,21 +1165,69 @@ def test_tracker_reassignment_emits_drop_before_load():
     })
     tracker_port = tracker.start()
     try:
-        slow = _post_json(
+        first = _post_json(
             f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
             {"endpoint": "http://127.0.0.1:9015", "model": "tiny-model",
              "vram_bytes": 10_000, "ram_bytes": 10_000, "quantizations": ["bfloat16"],
              "benchmark_tokens_per_sec": 1.0, "hardware_profile": {}, "score": 1.0},
         )
-        _post_json(
+        second = _post_json(
             f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
             {"endpoint": "http://127.0.0.1:9016", "model": "tiny-model",
              "vram_bytes": 10_000, "ram_bytes": 10_000, "quantizations": ["bfloat16"],
              "benchmark_tokens_per_sec": 3.0, "hardware_profile": {}, "score": 1.0},
         )
 
-        hb = _post_json(f"http://127.0.0.1:{tracker_port}/v1/nodes/{slow['node_id']}/heartbeat", {})
+        net = _get_json(f"http://127.0.0.1:{tracker_port}/v1/network/map")
-        assert [directive["action"] for directive in hb["directives"]] == ["DROP_SHARD", "LOAD_SHARD"]
+        widths = {
+            node["endpoint"]: node["shard_end"] - node["shard_start"] + 1
+            for node in net["nodes"]
+        }
+        assert widths["http://127.0.0.1:9015"] == 4
+        assert widths["http://127.0.0.1:9016"] == 4
+        assert net["nodes"][0]["model_supply"]["served_model_copies"] == 2.0
+
+        hb = _post_json(f"http://127.0.0.1:{tracker_port}/v1/nodes/{first['node_id']}/heartbeat", {})
+        assert hb.get("directives", []) == []
+    finally:
+        tracker.stop()
+
+
+def test_tracker_explicit_full_copy_join_preserves_existing_serving_node():
+    """--model style joins with explicit shards add redundancy instead of reshuffling."""
+    tracker = TrackerServer(heartbeat_timeout=10.0)
+    tracker_port = tracker.start()
+    try:
+        base_reg = {
+            "model": "Qwen2.5-0.5B-Instruct",
+            "hf_repo": "Qwen/Qwen2.5-0.5B-Instruct",
+            "num_layers": 24,
+            "shard_start": 0,
+            "shard_end": 23,
+            "managed_assignment": True,
+            "vram_bytes": 2_000_000_000,
+            "hardware_profile": {},
+            "score": 1.0,
+        }
+        first = _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {**base_reg, "endpoint": "http://127.0.0.1:9201"},
+        )
+        second = _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {**base_reg, "endpoint": "http://127.0.0.1:9202"},
+        )
+
+        coverage = _get_json(
+            f"http://127.0.0.1:{tracker_port}/v1/network/map"
+        )
+        assert coverage["nodes"][0]["model_supply"]["served_model_copies"] == 2.0
+
+        hb = _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/{first['node_id']}/heartbeat", {}
+        )
+        assert hb.get("directives", []) == []
+        assert second["node_id"] in tracker._registry
     finally:
         tracker.stop()
 
@@ -889,22 +1265,20 @@ def test_tracker_faster_node_receives_wider_range_when_capacity_ties():
         _post_json(
             f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
             {"endpoint": "http://127.0.0.1:9001", "model": "tiny-model",
-             "vram_bytes": 20_000, "ram_bytes": 10_000, "quantizations": ["bfloat16"],
+             "vram_bytes": 5_000, "ram_bytes": 10_000, "quantizations": ["bfloat16"],
              "benchmark_tokens_per_sec": 1.0, "hardware_profile": {}, "score": 1.0},
         )
         _post_json(
             f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
             {"endpoint": "http://127.0.0.1:9002", "model": "tiny-model",
-             "vram_bytes": 20_000, "ram_bytes": 10_000, "quantizations": ["bfloat16"],
+             "vram_bytes": 5_000, "ram_bytes": 10_000, "quantizations": ["bfloat16"],
              "benchmark_tokens_per_sec": 2.0, "hardware_profile": {}, "score": 1.0},
         )
 
-        route_resp = _get_json(f"http://127.0.0.1:{tracker_port}/v1/route?model=tiny-model")
+        net = _get_json(f"http://127.0.0.1:{tracker_port}/v1/network/map")
-        widths = {
+        heads = [node for node in net["nodes"] if node["shard_start"] == 0]
-            node["endpoint"]: node["shard_end"] - node["shard_start"] + 1
+        assert len(heads) == 1
-            for node in route_resp["nodes"]
+        assert heads[0]["endpoint"] == "http://127.0.0.1:9002"
-        }
-        assert widths["http://127.0.0.1:9002"] > widths["http://127.0.0.1:9001"]
     finally:
         tracker.stop()
 
@@ -1972,6 +2346,7 @@ def test_torch_node_applies_tracker_load_shard_directive(monkeypatch):
 
     assert loaded == [("Qwen/Qwen2.5-0.5B-Instruct", 0, 23, "bfloat16")]
     assert applied == {
+        "action": "LOAD_SHARD",
         "model": "Qwen/Qwen2.5-0.5B-Instruct",
         "shard_start": 0,
         "shard_end": 23,
@@ -2088,3 +2463,105 @@ def test_shard_heal_cycle_surviving_node_covers_dead_peers_gap(monkeypatch):
         )
     finally:
         tracker.stop()
+
+
+def test_network_map_exposes_memory_pool():
+    tracker = TrackerServer(model_presets={
+        "tiny-model": {
+            "total_layers": 8,
+            "bytes_per_layer": {"bfloat16": 1_000},
+            "hf_repo": "org/TinyModel",
+        },
+    })
+    tracker_port = tracker.start()
+    try:
+        _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {"endpoint": "http://127.0.0.1:9050", "model": "tiny-model",
+             "hf_repo": "org/TinyModel", "num_layers": 8,
+             "shard_start": 0, "shard_end": 7, "max_loaded_shards": 2,
+             "vram_bytes": 20_000, "ram_bytes": 20_000, "quantizations": ["bfloat16"],
+             "benchmark_tokens_per_sec": 1.0, "hardware_profile": {}, "score": 1.0},
+        )
+        net = _get_json(f"http://127.0.0.1:{tracker_port}/v1/network/map")
+        pool = net["memory_pool"]
+        assert pool["total_spare_slots"] == 1
+        assert pool["hosts"][0]["loaded_slots"] == 1
+        assert pool["hosts"][0]["max_loaded_shards"] == 2
+        assert pool["hosts"][0]["memory_spare_bytes"] > 0
+    finally:
+        tracker.stop()
+
+
+def test_same_endpoint_can_register_multiple_models():
+    tracker = TrackerServer()
+    tracker_port = tracker.start()
+    try:
+        base = {
+            "endpoint": "http://127.0.0.1:9055",
+            "num_layers": 24,
+            "shard_start": 0,
+            "shard_end": 23,
+            "hardware_profile": {},
+            "score": 1.0,
+            "max_loaded_shards": 2,
+            "vram_bytes": 50_000_000,
+            "ram_bytes": 50_000_000,
+        }
+        first = _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {**base, "model": "Qwen2.5-0.5B-Instruct", "hf_repo": "Qwen/Qwen2.5-0.5B-Instruct"},
+        )
+        second = _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {**base, "model": "OtherModel", "hf_repo": "org/OtherModel"},
+        )
+        assert first["node_id"] != second["node_id"]
+        assert len(tracker._registry) == 2
+    finally:
+        tracker.stop()
+
+
+def test_scale_demanded_models_queues_add_shard_on_spare_host():
+    tracker = TrackerServer(model_presets={
+        "model-a": {
+            "total_layers": 4,
+            "bytes_per_layer": {"bfloat16": 1_000},
+            "hf_repo": "org/ModelA",
+        },
+        "model-b": {
+            "total_layers": 4,
+            "bytes_per_layer": {"bfloat16": 1_000},
+            "hf_repo": "org/ModelB",
+        },
+    })
+    tracker_port = tracker.start()
+    try:
+        reg_b = _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {"endpoint": "http://127.0.0.1:9061", "model": "model-b",
+             "hf_repo": "org/ModelB", "num_layers": 4,
+             "shard_start": 0, "shard_end": 3, "max_loaded_shards": 2,
+             "vram_bytes": 20_000, "ram_bytes": 20_000, "quantizations": ["bfloat16"],
+             "benchmark_tokens_per_sec": 1.0, "hardware_profile": {}, "score": 1.0},
+        )
+        _post_json(
+            f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
+            {"endpoint": "http://127.0.0.1:9060", "model": "model-a",
+             "hf_repo": "org/ModelA", "num_layers": 4,
+             "shard_start": 0, "shard_end": 3, "max_loaded_shards": 1,
+             "vram_bytes": 20_000, "ram_bytes": 20_000, "quantizations": ["bfloat16"],
+             "benchmark_tokens_per_sec": 1.0, "hardware_profile": {}, "score": 1.0},
+        )
+        assert tracker._stats is not None
+        for _ in range(400):
+            tracker._stats.record_request("org/ModelA")
+        with tracker._lock:
+            _scale_demanded_models_locked(tracker._server)  # type: ignore[arg-type]
+        node_b = tracker._registry[reg_b["node_id"]]
+        assignment = node_b.pending_new_assignment
+        assert assignment is not None
+        assert assignment["action"] == "ADD_SHARD"
+        assert assignment["model"] == "org/ModelA"
+    finally:
+        tracker.stop()