Commit Graph

5 Commits

Author SHA1 Message Date
Keysat e87158c492 v0.20.0:0 - per-spark ssh-key copy + wireguard status badge 2026-06-15 09:53:40 -05:00
Grant a02f4db850 v0.5.0 - Wake-on-LAN + connectivity history
wol.py:
- build_magic_packet(): standard 6x0xFF + 16x MAC layout
- send_local_broadcast(): direct from container (ports 9 + 7 for safety)
- send_via_peer(): preferred path; SSHes to the OTHER Spark and runs a Python one-liner there so the packet originates on the target's LAN segment (most reliable)
- MAC validation + normalization

connectivity.py:
- /data/connectivity.json persistence (thread-safe, atomic rename)
- Stores per-Spark current state + last_change timestamp + rolling 200-event log
- Records up/down transitions; computes down_seconds / up_seconds durations
- MAC cache populated lazily during hardware probes

hardware.py:
- Probe now reads MAC via /sys/class/net/<default-route-iface>/address
- After each probe, record_state() emits a transition event if state changed
- record_mac() caches the address so WoL works when the Spark next goes down

Endpoints:
- GET /api/connectivity: macs, current state, last_change, events[]
- POST /api/spark/{name}/wake: tries via-peer first, falls back to direct broadcast

UI:
- Unreachable hardware card shows the cached MAC + 'Wake (WoL)' button (only if MAC known)
- New 'Connectivity log' button opens a modal with per-Spark transition history (last 25 each), including duration of each prior up/down period
- pollHardware also pulls /api/connectivity so WoL buttons appear without an extra fetch

Package: bump 0.5.0:0; main.ts sets CONNECTIVITY_LOG=/data/connectivity.json
2026-05-12 12:51:49 -05:00
Grant 1889ab45fb v0.4.0 - NIM installer + dashboard resilience
Hotfix (was v0.3.1):
- services.py: cache 'unreachable' per (host,user) for 25s so a dead Spark doesn't hang every /api/services call behind 6s ssh timeout
- ssh_run timeout reduced 10 -> 6s for docker_state probes
- hardware probe: shorter SSH timeout (6s), longer cache TTL for failures (25s)
- JS pollStatus retries loadModels() if state.models is empty (recovers from cold-start proxy timeout)
- Unreachable hardware card now includes troubleshooting steps (Spark Control cannot SSH into an unreachable Spark to restart it)

v0.4 NIM installer:
- nim.py module: curated SUGGESTED_NIMS list (Parakeet, Magpie, Riva) + NimManager that runs docker login nvcr.io + docker pull + docker run -d --gpus all -p PORT:PORT -v VOL:/opt/nim/.cache -e NGC_API_KEY -e ... --restart=unless-stopped + chown the volume to uid 1000 + restart. Streams all output via SSE; redacts the API key from log lines.
- custom_services.py: persists installed NIMs to /data/services-overrides.yaml so they appear in the services panel after install
- services.py: merges custom services into the panel
- /api/nim/catalog GET, /api/nim/install POST + GET/SSE
- /api/services/{name} DELETE for custom services
- UI: '+ Install NIM' button next to 'Always-on services'; modal lists curated images each with a 'Pick' button + a custom-image form; installation runs in a second dialog with phase + elapsed timer + collapsible log
- NGC API key field added to Configure Sparks (masked); injected as NGC_API_KEY env var into the container

Package: bump 0.4.0:0; main.ts adds SERVICES_OVERRIDES + NGC_API_KEY env vars
2026-05-12 12:32:29 -05:00
Grant e88fdcfde4 v0.3.0:1 - hotfix: parallel SSH probes + longer timeout
- Hardware probes for spark1 and spark2 now run via asyncio.gather (parallel) so the worst-case wall time is max(per-probe), not sum
- Bump per-probe SSH timeout from 8s to 12s to absorb first-call overhead (StrictHostKeyChecking=accept-new on first connect + nvidia-smi cold start)
- Unreachable Spark now shows up cleanly in the UI as a single 'unreachable' card with the error message
2026-05-12 12:14:36 -05:00
Grant 64ce0fca10 v0.3.0 - Hardware dashboard + knob context + Explain context + Open WebUI link
Hardware dashboard:
- New hardware.py module: SSH probes each Spark for hostname, uptime, load+cores, RAM, disk, GPU (name, util, temp, power) + per-process GPU memory sum
- DGX Spark uses unified memory (nvidia-smi memory.total returns N/A); fall back to per-process compute memory and compute fraction against system RAM. Marks with gpu_unified_memory=true.
- 4s TTL cache in HardwareProbe to avoid hammering
- /api/hardware returns per-Spark snapshot
- UI: 'Spark hardware' section at the top with per-Spark cards (CPU load, RAM, GPU mem (unified), GPU util + temp + power, disk) — bars with warn threshold styling
- Polls every 8s

Knob context (tied to live hardware):
- Each Advanced knob now shows plain-English help text
- 'GPU memory %' shows '~N GB allocated · ~M GB left for OS/buffers' computed from actual Spark RAM
- 'Max context' shows '~N pages of text'
- Toggles show tradeoff descriptions

Explain context:
- ' Explain context' button on the update banner
- /api/explain-updates POST: forwards pending commits to the loaded vLLM model and streams its response back as SSE
- Renders into an expandable 'Explained by the loaded LLM' section under Pending commits
- Reasoning tokens shown italicized when the model emits them

Open WebUI integration:
- New 'Open WebUI URL' optional field in Configure Sparks
- /api/config exposes it; UI shows 'Open chat ↗' button in the top bar if set

Downloads:
- Third radio option: Spark 1 only / Spark 2 only / Both Sparks
- Backend picks SSH target based on mode
- HF repo link icon next to the input
- Helper line about NVFP4 for Blackwell

Model cards:
- Repo name is now a clickable link to its Hugging Face page

Package: bump 0.3.0:0
2026-05-12 12:00:15 -05:00