- `meshnet-node` with no args runs interactive setup wizard on first run,
then starts directly on subsequent runs using saved config
- Wizard auto-detects all GPUs/VRAM, shows curated model list with per-quant
VRAM requirements, marks models that exceed available VRAM as incompatible,
offers HuggingFace Hub browse as escape hatch
- Persistent config saved to ~/.config/meshnet/config.json (0o600)
- Live rich dashboard (tokens/sec EMA, VRAM, requests, peers, uptime) with
automatic plain-text fallback when stdout is not a TTY (WSL2/SSH/CI)
- All wizard values overridable via CLI flags; --reset-config re-runs wizard
- `meshnet-node models` lists curated models; `--browse` fetches HF Hub top-20
- `meshnet-node config` prints saved config
- `meshnet-node start ...` preserved for backward compatibility
- 19 new tests; 97 passed, 1 skipped (no regressions)
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>
