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>
Add mvp-system/src/mvp_chat.rs with a run_from_args entrypoint wiring swactor runtime,
dashboard, chat datastream, and a PromptLoop. Add a mock integration test; refresh
mvp-chat and MVP_SYSTEM specs.
Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
Stand up an interactive end-to-end chat over a CUDA GPU, provisioning a Dockerized node that loads a GGUF model and serves prompts over TCP.
- prompt_rpc: add the newline-JSON prompt protocol (`SubmitPrompt` + `PromptEvent::{TextDelta,Done,Fault}`) carried over TCP
- mvp_chat: add an interactive REPL client connecting to the prompt RPC port (default 127.0.0.1:19777)
- mvp_orch_one_node / mvp_one_node_chat: add the single-node orchestrator that provisions a `LocalDockerPlugin` node, loads `bartowski/Llama-3.2-1B-Instruct-GGUF` (Q4_K_M), and exposes the prompt RPC listener with boot/route/weight timeouts
- mvp_node: add the GPU worker binary that spawns `tinygrad_worker.py` (default device CUDA) and ships runtime telemetry via a `ClusterFrameSink`
- vastai_provisioning / bootstrap_datastream: add the vast.ai provider adapter (`VastAiProvisioningConfig`, `VastAiLeaseClient`) wrapping `swactor_vastai`, plus a bridge that folds provision stdout onto a per-node datastream
- apps/mvp-node: add CUDA base/runtime Dockerfiles (nvidia/cuda 12.6.3, tinygrad 0.12.0, sshd), `mvp_entrypoint.sh` (sshd + mvp-node, held for postmortem), `local_docker_e2e.sh`, the GGUF tinygrad worker, and one-node-chat/bootstrap/vastai guarantee tests
Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
Fold the fragmented distribution swim/routing/gossip tests into swim_core, routing,
and swim_actor. Prune the dashboard tui and command surfaces. Add mvp-system actors
(node_agent, orchestrator, stage_controller), the local_e2e harness, and gpu worker
e2e.
Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
