Route lookup was using the client-provided model name ("qwen2.5-0.5b") but
the tracker registers nodes under their full hf_repo ("Qwen/Qwen2.5-0.5B-Instruct").
This caused a 404 on /v1/route and the non-tail node fell back to the
"no downstream route available" error message.
Fix: _get_remaining_route now uses server.backend.model_id (the actual hf_repo)
for the tracker query. Skips self by port matching rather than blind route[0] drop.
Also prints a warning when route lookup fails so the cause is visible.
Distributed generation was also only producing 1 token (single greedy argmax
in decode_tail). Replaced with an autoregressive loop: head node encodes the
growing sequence and forwards to the downstream shard each step, collecting
one token per iteration up to max_tokens or EOS.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Single-node mode now uses HF model.generate() instead of one-shot
decode_tail(), giving correct multi-token output with KV cache.
model_backend.py:
- generate_text(messages, max_new_tokens, temperature, top_p) — full
autoregressive generation via model.generate() with chat template
- generate_text_streaming() — yields token strings via TextIteratorStreamer
- _encode_messages() — applies chat template (tokenize=False then tokenize),
falls back to joining user messages; avoids BatchEncoding issues
torch_server.py:
- _handle_chat_completions: fast path when backend is head+tail — calls
generate_text() or generate_text_streaming() directly instead of the
single-token encode_prompt+decode_tail pipeline
- _stream_openai_response: new SSE streaming handler for token iterators
- Parses max_tokens, temperature, top_p from request body
- Distributed path (partial shards) unchanged
Verified: streaming and non-streaming both work with Qwen2.5-0.5B-Instruct.
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>
