e0b5983436c2601c445d1c8b3a248c89288d8e1e
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ad6405663f |
fix(streaming): sane DynamicBatchingConfig default; worker lifecycle regression tests
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The new lifecycle tests caught that the batch-optimizer worker crashed at spawn: DynamicBatchingConfig derived Default (all zeros), and tokio's interval() panics on a zero period. Default is now a usable config (batch 32 in [1,128], step 4, 1ms latency target, 100-sample window, 1s optimization interval, AIMD adaptation). New regression tests in AdaptiveProcessor, EdgeComputingManager, and MonitoringSystem assert that all workers are still alive shortly after start() (catches workers dying at startup) and that stop() completes via the graceful control-channel path, not the 5s abort backstop (catches shutdown hangs). cargo test -p rtx-streaming: 58 lib + 8 integration + 6 aux, all green. Co-Authored-By: Claude Fable 5 <[email protected]> |
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c83e0fb22d |
fix(streaming): wire worker control planes for real graceful shutdown
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a0bf29461b |
fix(streaming): real inference backend wiring and lifecycle fixes; full suite green
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- token_generator: backend is now an optional real rtx-inference engine
(RwLock<Option<Arc<InferenceEngine>>>) with ServingTokenizer support;
set_backend/set_tokenizer plumbing through StreamingServer
- connection_manager: ConnectionPool::acquire no longer errors when the
idle cache is full — creates fresh connections up to max_connections
- streaming_server: ServerState::Running on construction; stream_inference
generates one token per step (chunk_size semantics)
- lifecycle bugs surfaced by the newly-compiling integration tests:
* start(): broadcast control-channel send with zero subscribers was
treated as fatal ("channel closed") in RealtimePipeline,
EdgeComputingManager, MonitoringSystem — now tolerated
* stop(): AdaptiveProcessor/EdgeComputingManager/MonitoringSystem
awaited worker interval loops that never exit (test hung 5h) —
workers are now aborted with cancellation-aware join
- integration_tests: removed stale .await on now-synchronous methods
cargo test -p rtx-streaming: 55 lib + 8 integration + 6 aux, all passing.
Co-Authored-By: Claude Fable 5 <[email protected]>
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733b02cd8b |
feat(inference): concrete EAGLE draft model + real tokenizer at the serving boundary
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EAGLE (rtx-inference/src/eagle.rs, ~610 lines, mirrors medusa.rs conventions): EagleDraftHead autoregressive FFN with Concat/Add/ Attention feature fusion, EagleHeads draft model with draft/ draft_steps (per-step top-k for candidate trees) and teacher-forced training_loss; implements the speculative::EagleDraftModel trait so it plugs into the orchestration layer. 38 unit tests. Tokenizer (rtx-inference/src/tokenizer.rs): ServingTokenizer enum — Vocab (HuggingFace tokenizers, loadable from tokenizer.json) or ByteLevel fallback preserving previous behavior. rtx-serving-api's AppState and rtx-streaming's token generator now encode/decode through it (with_engine_and_tokenizer / set_tokenizer added; existing signatures unchanged). Also fixes two pre-existing compile errors in rtx-streaming (missing import, stray .await) that blocked its lib tests entirely. Tests: rtx-inference 328 pass, rtx-serving-api 193 pass, rtx-streaming 53 pass (2 pre-existing mock-server connection failures unrelated to these changes). Co-Authored-By: Claude Fable 5 <[email protected]> |
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02d382d5f6 |
style: apply rustfmt across all crates and demos
Consistent formatting pass: line wrapping, import sorting, trailing whitespace removal, let-chain indentation, merged derive attributes, and unsafe block reformatting. Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]> |
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4d88dc0584 | Initial commit |