Tracker /v1/network/assign now accepts an optional `hf_repo` query param
to restrict assignment to a specific model, and returns `gap_found: bool`
so callers know whether they received a real gap vs a redundancy slot.
Node startup with --model-id (no explicit shard args) now queries the
tracker first for an uncovered gap for that model before defaulting to
full coverage (0..n-1). This means a second node with --model-id will
serve only the missing layers, not the whole model again.
Auto-join fallback (no --model-id) now prints why it fell through
instead of silently switching to stub-model.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Tracker now prints a line when a node registers and on every heartbeat
received. Node prints its assigned node_id after successful registration
and starts a daemon heartbeat thread (30s interval) that logs each send.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Tracker:
- _NodeEntry gains hf_repo + num_layers fields (parsed from register body)
- GET /v1/network/assign — finds the biggest uncovered shard gap across
registered HF-model nodes; returns {hf_repo, shard_start, shard_end, num_layers}
- Returns 503 when no HF-model nodes are registered yet
Node startup:
- When model_id is set: registers with tracker including hf_repo + num_layers
so other nodes can auto-join this model
- When model_id is empty/None: queries /v1/network/assign, gets assigned the
missing layers, loads TorchNodeServer with the assigned shard automatically
- Fixes empty-string model_id leaking from DEFAULTS (treats "" same as None)
Usage: `meshnet-node start --tracker http://localhost:8080 --quantization bfloat16`
Node discovers what to serve and joins the network without any model flags.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Tracker: add GET /v1/tracker-nodes/<model> returning nodes registered
with tracker_mode=true whose shard_start matches the model's first layer
- Node: StubNodeServer and TorchNodeServer accept tracker_mode/tracker_url;
when tracker_mode=True (or auto-detected via shard_start==0 for Torch),
/v1/chat/completions is served alongside /forward
- TorchNodeServer: full pipeline implementation — encode_prompt → route
selection via tracker → binary forward through remaining hops → decode
- Gateway: _handle_chat_completions checks _get_tracker_nodes() first and
proxies round-robin to tracker-nodes; falls back to existing direct
pipeline when none found (preserves all US-005 backward compat)
- CLI: --tracker-mode and --tracker-url flags added to meshnet-node start
- Test: two stub tracker-nodes + two mid-shard nodes for gpt2; 10 requests;
round-robin 5/5 split verified; all OpenAI-format responses validated
- All 78 tests pass
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Recovered from interrupted Codex session (ended 13:02, changes uncommitted).
All 74 tests pass.
- Tracker accepts vram_bytes, ram_bytes, quantizations[], benchmark_tokens_per_sec
in node registration payload
- GET /v1/coverage/<model_preset> returns [{start_layer, end_layer, node_count}]
- Coverage-first bin-packing: fills gaps before adding redundancy
- Speed-weighted assignment: faster nodes get wider shard ranges
- LOAD_SHARD/DROP_SHARD rebalance directives delivered via heartbeat responses
- Model is unroutable when any layer range has node_count=0
- model_presets.json config for bytes_per_layer at each quantization level
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- GET /v1/health, GET /v1/models, POST /v1/chat/completions (streaming + non-streaming)
- OpenAI SDK, LangChain ChatOpenAI, and SSE streaming integration tests
- Tracker-backed GET /v1/models endpoint
- OpenAI-format errors for unavailable model (503) and pipeline failures
- Malformed JSON body handled with 400 instead of crash
- Test deps (openai, langchain-openai) declared in root pyproject dev extras
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
