- Split arena/ring/object-record into a new data-plane crate and node/plugin contracts
into a provisioning crate.
- Reorganize mvp-system into orchestration, staging, node, chat, and worker modules;
extract binaries into chat/runtime and node/worker_node_runtime.
- Add MVP_SYSTEM_MODULE_BOUNDARY_SPEC.
Signed-off-by: Zachery Aaron Shores-Chmielewski <zacheryasc@gmail.com>
Add end-to-end timing instrumentation and an xtask benchmark report for mvp-chat runs.
- benchmark_observability: add a shared stamping module — stamp(component) emitting schema/pid/monotonic+wall ms from a process-global start and sequence counter, plus unix_ms_now() — stamped onto every mvp-chat/orchestrator/worker-node event and frame-archive record
- mvp-chat: thread a run_id (new --run-id, defaults to 1) through config and the orchestrator CLI, add per-phase started/ready/failed emits for ensure_orch_binary/ensure_worker_binary/prepare_node_image, and a prompt_complete record carrying tokens_generated/elapsed_ms/final_text bytes
- orchestrator/worker-node: stamp bootstrap and prompt events, add arrival_unix_ms to archived frames, propagate MVP_RUN_ID/MVP_LOGICAL_NODE_ID/MVP_STAGE_INDEX into the tinygrad worker, default the device to CPU for the process provider, emit a prompt_rpc started span, and drop the MVP_TINYGRAD_TEST_MODE passthrough
- tinygrad_worker.py: stamp every control() event and tag it with run/node/stage env, add a CPU:X86 fallback when clang is absent, and remove the test_mode() short-circuits
- xtask: replace the flat dump-log fact assertions with a benchmark report builder (build_benchmark_report) that requires named spans (prepare_runtime, ensure_*_binary, weights_loaded, prompt_rpc) and emits per-prompt first-token/decode/tokens-per-second latency; wrap the cargo run in XtaskBenchmark synthetic frames and pass a unix-ms --run-id
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>
Introduce pool/planner/launcher/runtime_stack/model/roles primitives for topology
construction and cluster launch. Drop the core guarantees module entirely; rework
worker bootstrap.
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>
