Promote the `mvp-system` workspace library crate to a standalone application at `apps/myelin`, rebranding the MVP system along with its binaries, node image, and spec.
- workspace `Cargo.toml`: swap member `crates/mvp-system` -> `apps/myelin` and drop `apps` from `exclude` so the app joins the workspace
- `apps/myelin/Cargo.toml`: declare package `myelin` with `autobins = false` and explicit `[[bin]]` targets `myelin-worker`, `myelin-orchestrator`, `myelin-chat`
- `apps/myelin/src`: move the whole `mvp-system` source tree and rebrand module surfaces (`chat/mod.rs`, `prompt/mod.rs`); add `bin/chat.rs` (`myelin::run_chat_from_args`) and delete the old `mvp_chat.rs`
- `apps/myelin/node-image`: relocate the worker image assets from `apps/mvp-node/` (Dockerfile, Dockerfile.base, tinygrad_worker.py, entrypoint, e2e script) and rename `MVP_SYSTEM_SPEC.md` -> `MYELIN_SPEC.md`
- `xtask`: rewrite build/reference paths for the rename (~1000-line churn); add `crates/dashboard/ACTOR_PANEL_SPEC.md`
Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
Speed up VastAI provisioning by creating instances directly from a cached offer pool, and replace best-effort SSH readiness with classified, post-grace bootstrap-failure detection plus a dedicated per-node provider-status monitor.
- vastai_provisioning: provision_one now iterates a cached candidate_pool of offers calling create_instance directly (with host blacklist and failed-host dedup) instead of re-running client.provision; plan_first_wave_offers caches planned_offer_pool/planned_offer_ids for reuse
- vastai_provisioning: add VastAiProviderMonitor (background thread + AtomicBool stop + Drop) spawned per node via the new spawn_provider_monitor trait method, polling instance_status and emitting VastAiProviderStatusObserved/PollRetry/StatusFailure and terminal-start failures
- vastai_provisioning: add classify_ssh_observation (auth_denied/refused/timeout) with spawn_classifying_stderr_reader; spawn_retrying_ssh_bootstrap aborts after POST_GRACE_BOOTSTRAP_FAILURE_LIMIT repeated classified failures past the grace window instead of retrying forever
- vastai_provisioning: ssh_endpoint delegates to client.wait_for_ssh_endpoint; VastAiNode carries run_id/node_id/label/sink and emits structured VastAiLeaseReady/SshEndpointDiscoveryStarted/SshEndpointReady/RuntimeReadyAccepted/ContractCleanup events; LifecyclePolicy is threaded into start_bootstrap
- tools/vastai: add fetch_instance_status and wait_for_ssh_endpoint_with_policy, refactor wait_for_running onto fetch_instance_status, and export both plus ProviderInstanceStatus from lib.rs
- tools/vastai/types: add ProviderInstanceStatus (actual/intended status, status_msg, public_ipaddr, ssh_port, disk_usage) with ssh_endpoint() and From<InstanceStatus>
Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
Distribute only each stage's GGUF layer slice over HTTP, add sampler and weight-load health telemetry, and harden node-image build, orchestrator provisioning, and the VastAI lease/search path.
- gguf_shard (new): StageShardPlan and plan_stage_shard parse the GGUF directory and compute coalesced per-stage tensor byte ranges; materialize_stage_shard_http fetches only those ranges (plus the header) to build a stage-local GGUF, with planned_fetch_bytes accounting.
- orchestrator_app: build a BTreeMap<u32, StageShardPlan> from the run plan for HuggingFace sources, thread stage_shard_plan through StageProvisionWire and weight-load, emit stage_shard_plan summaries, and add liveness phases (prefetching/fetching_stage_shard, cache_ready, stage_shard_ready).
- worker_node: add a stage-shard-fetcher subcommand and materialize_stage_shard_with_process that spawns the fetcher, streams its stdout/stderr as stage_shard_fetch events (StageShardCacheReady/StageShardReady), caches under MVP_MODEL_CACHE_DIR, and feeds the local shard path into load_weights.
- worker_node: add NODE_SAMPLER_CHANNEL and SamplerHealth telemetry (gpu/cpu/net samplers emit started/waiting/ready/failed) plus structured helper stdout/stderr streaming (wait_for_helper_event/drain_worker_stderr).
- node_image: expand node-image build/push handling for the deploy path.
- tools/vastai: extend lease, search, and types and drop unused pricing code.
Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
Complete an 8-stage pipeline-parallel run over VastAI by provisioning stages high-to-low, adding per-stage/per-step metrics, host anti-colocation, and provider state-timeout guardrails.
- orchestrator_app: select the next weight-load stage by max index (provision stages high-to-low for parallel spread), add a throttled "loaded N of M; waiting on stage X" stage_provision_wait headline, and surface min_compute_cap/state_timeout_secs in the config dump.
- orchestrator_app: enrich pipeline_token_in/out and tokenizer_decode events with token_count/token_ids/generated_index.
- worker_node: add timing metrics across the data path (helper_execute_ms, egress_ring_read_ms, send_ms, ingress_ring_write_ms, object_load_ms), refactor take_complete_ingress_record into IngressRecordBytes (object_id/sequence/extent/flags), and emit a new object_loaded event.
- vastai_provisioning: track leased host_ids and blacklist already-leased hosts in later ProvisionRequests so stages don't co-locate, and tag SSH-bootstrap retry logs with the attempt number.
- tools/vastai: add min_compute_cap (PP_MIN_COMPUTE_CAP) filter/search query and a LifecyclePolicy state_timeout (PP_STATE_TIMEOUT_SECS) that fails instances stuck in a non-running status instead of polling forever.
- xtask: raise the check timeout to 1800s/30s grace, drop --skip-rebuild for VastAI, aggregate per-stage StepExecuted metrics, add a vastai summary section, and write failure artifacts on abort.
Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
Land the first working two-stage pipeline-parallel run over VastAI, wiring a real inter-stage data path with observability, a max-price offer cap, and remote-image reuse.
- orchestrator_app: raise the VastAI pipeline-stage cap from 1 to 2 and let VastAI pipeline planning resolve the HuggingFace GGUF from the default local cached-model metadata path instead of requiring host mounts; add --vastai-max-dph-total (CLI/env/TOML) config.
- vastai_provisioning: make complete_bootstrap a no-op so the SSH bootstrap log tail stays alive past runtime-ready until node stop, preserving post-ready worker logs; add a test asserting the tail is only stopped on NodeStop.
- worker_node: emit data-path NodeEvents across the pipeline (iroh_edge_stream_arrived/bytes_read/bytes_sent, egress_ring_read, ingress_ring_write) with edge/byte metadata.
- tools/vastai: add max_dph_total (PP_MAX_DPH_TOTAL) to SelectionPolicy, the reachable-offer filter, and the search query, and improve the empty-pool error message.
- xtask: pass --skip-rebuild for the VastAI scenario and gate it on a new require_vastai_data_path_facts plus GPU facts (ring install, activation object load/step, interstage handoff, iroh edge read/sent).
- mvp_chat: add ChatModelConfig (model id/gguf/tokenizer/max-context) forwarded to the orchestrator; for VastAI + skip-rebuild, emit skip events and reuse the remote node image without a local build.
Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
Move iroh_driver and the relay binary out of distribution into a dedicated
crates/iroh-driver (lib re-exports IrohDriver; relay bin renamed). Remove the node crate
and the single-gpu-inference example; drop the docker/datastream demo. Slim
pipeline-parallel vastai.
Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
