Add distance scale bar and user-placed location pins to the offline maps viewer.
- Scale bar (bottom-left) shows distance reference that updates with zoom level
- Click anywhere on map to place a named pin with color selection (6 colors)
- Collapsible "Saved Locations" panel lists all pins with fly-to navigation
- Full dark mode support for popups and panel via CSS overrides
- New `map_markers` table with future-proofed columns for routing (marker_type,
route_id, route_order, notes) to avoid a migration when routes are added later
- CRUD endpoints: GET/POST /api/maps/markers, PATCH/DELETE /api/maps/markers/:id
- VineJS validation on create/update
- MapMarker Lucid model
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(downloads): increase retry attempts and backoff for large file downloads
* fix download retry config and abort handling
* use abort reason to detect user-initiated cancels
New defaults:
OLLAMA_NO_CLOUD=1 - "Ollama can run in local only mode by disabling
Ollama’s cloud features. By turning off Ollama’s cloud features, you
will lose the ability to use Ollama’s cloud models and web search."
https://ollama.com/blog/web-searchhttps://docs.ollama.com/faq#how-do-i-disable-ollama%E2%80%99s-cloud-features
example output:
```
ollama run minimax-m2.7:cloud
Error: ollama cloud is disabled: remote model details are unavailable
```
This setting can be safely disabled as you have to click on a link to
login to ollama cloud and theres no real way to do that in nomad outside
of looking at the nomad_ollama logs.
This one can be disabled in settings in case theres a model out there
that doesn't play nice. but that doesnt seem necessary so far.
OLLAMA_FLASH_ATTENTION=1 - "Flash Attention is a feature of most modern
models that can significantly reduce memory usage as the context size
grows. "
Tested with llama3.2:
```
docker logs nomad_ollama --tail 1000 2>&1 |grep --color -i flash_attn
llama_context: flash_attn = enabled
```
And with second_constantine/deepseek-coder-v2 with is based on
https://huggingface.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF
which is a model that specifically calls out that you should disable
flash attention, but during testing it seems ollama can do this for you
automatically:
```
docker logs nomad_ollama --tail 1000 2>&1 |grep --color -i flash_attn
llama_context: flash_attn = disabled
```
Surfaces all installed AI models in a dedicated table between Settings
and Active Model Downloads, so users can quickly see what's installed
and delete models without hunting through the expandable model catalog.
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat(downloads): rich progress, friendly names, cancel, and live status
Redesign the Active Downloads UI with four improvements:
- Rich progress: BullMQ jobs now report downloadedBytes/totalBytes instead
of just a percentage, showing "2.3 GB / 5.1 GB" instead of "78% / 100%"
- Friendly names: dispatch title metadata from curated categories, Content
Explorer library, Wikipedia selector, and map collections
- Cancel button: Redis-based cross-process abort signal lets users cancel
active downloads with file cleanup. Confirmation step prevents accidents.
- Live status indicator: green pulsing dot with transfer speed for active
downloads, orange stall warning after 60s of no data, gray dot for queued
Backward compatible with in-flight jobs that have integer-only progress.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(downloads): fix cancel, dismiss, speed, and retry bugs
- Speed indicator: only set prevBytesRef on first observation to prevent
intermediate re-renders from inflating the calculated speed
- Cancel: throw UnrecoverableError on abort to prevent BullMQ retries
- Dismiss: remove stale BullMQ lock before job.remove() so cancelled
jobs can actually be dismissed
- Retry: add getActiveByUrl() helper that checks job state before
blocking re-download, auto-cleans terminal jobs
- Wikipedia: reset selection status to failed on cancel so the
"downloading" state doesn't persist
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat(downloads): improve cancellation logic and surface true BullMQ job states
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Jake Turner <jturner@cosmistack.com>
The assertNotPrivateUrl() function blocked standard loopback and link-local
addresses but could be bypassed using IPv4-mapped IPv6 representations:
- http://[::ffff:127.0.0.1]:8080/ → loopback bypass
- http://[::ffff:169.254.169.254]:8080/ → metadata endpoint bypass
- http://[::]:8080/ → all-interfaces bypass
Node.js normalises these to [::ffff:7f00:1], [::ffff:a9fe:a9fe], and [::]
respectively, none of which matched the existing regex patterns.
Add two patterns to close the gap:
- /^\[::ffff:/i catches all IPv4-mapped IPv6 addresses
- /^\[::\]$/ catches the IPv6 all-zeros address
Legitimate RFC1918 LAN URLs (192.168.x, 10.x, 172.16-31.x) remain allowed.
The App Installation Activity list on the Easy Setup complete page grew
unboundedly, pushing Active Downloads off-screen. Caps the list at ~8
visible items with overflow scrolling, auto-scrolling to keep the latest
activity visible.
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The NVIDIA container toolkit setup requires gpg to dearmor the GPG key,
but minimal Debian/Ubuntu installs may not have it present. Adds gpg to
the dependency check alongside curl so it gets installed automatically.
Closes#522
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Backend returned { error: message } on 400 but frontend expected { message }.
catchInternal swallowed Axios errors and returned undefined, causing a
generic 'An internal error occurred' message instead of the real reason
(already installed, already in progress, not found).
- Fix 400 response shape to { success: false, message } in controller
- Replace catchInternal with direct error handling in installService,
affectService, and forceReinstallService API methods
- Extract error.response.data.message from Axios errors so callers
see the actual server message
The log2 normalization formula `50 * (1 + log2(ratio))` produces negative
values (clamped to 0) whenever the measured value is less than half the
reference. For example, a CPU scoring 1993 events/sec against a 5000
reference gives ratio=0.4, log2(0.4)=-1.32, score=-16 -> 0%.
Fix by dividing log2 by 3 to widen the usable range. This preserves the
50% score at the reference value while allowing below-average hardware
to receive proportional non-zero scores (e.g., 28% for the CPU above).
Also adds debug logging for CPU sysbench output parsing to aid future
diagnosis of parsing issues.
Fixes#415
cosmistack-bot
chriscrosstalk
Jake Turner
Jake Turner
0xGlitch
Henry Estela
David Gross
Sebastion
Luís Miguel
Sam
arn6694
Salman Chishti
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Benjamin Sanders
Tom Boucher
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