model_backend.py was using Python-style exclusive end (layers[start:end])
while all callers (CLI, tests, QUICKSTART) use inclusive 0-based indexing.
Result: 24-layer model with shard_end=23 ran only 23 layers and never
set is_tail=True, so decode_tail() was never called and responses were empty.
- is_tail: == total_layers → >= total_layers - 1
- _run_layers: layers[start:end] → layers[start:end+1]
- Validation: > total_layers → >= total_layers (was also wrong)
Inference confirmed: Qwen2.5-0.5B-Instruct now returns real LLM output.
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>
