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26 Commits
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bec594904d |
Fix/windows llama cpp serve and test upstream (#2669)
* fix: code runner base64, Windows serve paths, endpoint cache clear, copy-log guards, model-picker remove-recent * Revert model-picker 'remove from recent' feature and remove stray PR_DRAFT.md |
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e2f449f4ef |
Cookbook scheduler + serve: schedule via Tasks, Stop verifies kill, Ollama auto port-pick
- Schedule cookbook serves through the existing ScheduledTask system: the serve preset gets a ^ button next to Launch that opens a daily/hourly/ weekly form mirroring the admin-switch style; the schedule action runs action_cookbook_serve, which delegates to /api/model/serve and stamps the resulting task with _scheduledStopAtMs. A background cookbook_serve_lifecycle loop ticks every 60s and kills any serve whose window has ended, also dropping the auto-registered endpoint so the model picker doesn't keep pointing at a dead server. - Stop and remove on a Running serve now awaits the SSH/tmux kill, re-checks tmux has-session, and surfaces an error toast (leaving the row) when the kill failed. Previously fire-and-forget, so a failed SSH/tmux call silently left the live serve running while the row vanished from the UI. - Cookbook tasks/status orphan-adoption sweep no longer requires the serve-/cookbook- session-id prefix; any tmux session whose pane is running a known model-server process gets auto-pulled into Running. Without this loosening, a cookbook-launched serve whose tmux id fell back to a bare number was invisible — you couldn't see it, let alone stop it. - Ollama serve always launches a fresh process under cookbook's tmux (no more monitor-mode reattach to a systemd/Docker ollama Stop can't reach). The handler pre-picks a free port by probing the target host over SSH and mutates req.cmd's OLLAMA_HOST so the runner script AND the auto-registered endpoint agree on the same bind port. - Auto-register uses host.docker.internal (when running inside Docker) instead of localhost, matching the URL /setup adds for Ollama by hand. Local cookbook serves now produce a chat-reachable endpoint on first launch. - Cascade-delete: removing a scheduled cookbook task also deletes any linked calendar event (cookbook_task_id marker in the description). - Tasks list groups cookbook_serve under a "Cookbook" category that sorts above the rest, so scheduler-launched serves are easy to find. |
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a260e0abd4 |
Revert calendar-based cookbook scheduler
Reverts |
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b98ee04e2f |
Cookbook scheduler: reuse the standard calendar event card + auto-create Cookbook calendar
Drop the custom Schedule modal in favor of opening the calendar's existing event-creation form pre-filled with the model's name + cookbook YAML in the description. The user lands in the same event editor they already know from regular calendar use, just pointed at the auto-created "Cookbook" calendar. Backend: - POST /api/cookbook/schedule/ensure-calendar — idempotent: creates a calendar named "Cookbook" if one doesn't exist for the current user, saves its href into cookbook_schedule_calendar_href, flips cookbook_scheduler_enabled on. Verifies the saved href against /api/calendar/calendars on every call so a manually-deleted calendar self-heals. Frontend: - calendar.js: expose window.cookbookOpenScheduleForm(draft) which opens the calendar modal (if not open), calls _showEventForm, then pre-fills summary / description / rrule / calendar dropdown. Force-expands the "Add details" section so the user can see which calendar it's heading into. - cookbookSchedule.js: Schedule-button click now calls ensure-calendar, builds the cookbook: YAML block, and routes to window.cookbookOpenScheduleForm instead of openModal(). The legacy custom modal stays as a fallback for the case where calendar.js hasn't loaded. UX tweak: - cookbookServe.js: replace the standalone "Schedule…" text button with a small icon-only button (clock SVG) glued to the right edge of Launch. The pair forms one visual unit — Launch on the left, schedule-now on the right — sharing a thin divider. CSS handles the rounded corners + divider. |
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a19b6d2d4d |
Cookbook scheduler: calendar events drive model serve windows (experimental, feature-flagged)
Add a calendar-driven scheduler so a user can pick a model in Cookbook, click "Schedule…" instead of "Launch", choose time windows + days of the week + (optional) end date, and have Odysseus auto-launch the serve when the window starts and hard-kill it when the window ends. The calendar IS the source of truth — events on a designated calendar are interpreted as serve schedules, so editing the event in the calendar UI immediately changes the schedule.
Whole feature is gated by setting `cookbook_scheduler_enabled` (default False). Disabling the setting silences the reconciler and the API refuses requests; setting + three new files = entire surface, easy to revert.
New files:
- src/cookbook_scheduler.py — background reconciler: ticks every 60s, reads next ±90s of calendar events on the designated calendar, launches/kills serves to match. Honors "refuse if GPUs busy" (skips with reason, no retry). Adopts pre-existing manual serves matching the event's model so window-end cleanup still applies. Tags scheduler-owned tasks with `_scheduledBy: <event_uid>` so it never kills serves it doesn't own.
- routes/cookbook_schedule_routes.py — POST /api/cookbook/schedule/from-cookbook builds RRULE+ICS events from the modal's input (model, slots[], days[], until). GET /upcoming returns the next 24h with per-event status (scheduled / running / adopted / skipped / failed / ended) for the UI. POST /reconcile-now manually kicks the reconciler.
- static/js/cookbookSchedule.js — Schedule button click handler + modal. Daily/hourly time slot picker, multi-slot ("+ add another time slot"), weekday chips with Weekdays/Weekend/Every-day quicksets, optional Until date. Calls /from-cookbook on save. Whole module is a single IIFE; deleting the file plus its <script> tag removes the UI surface.
Existing files touched (minimal):
- app.py: register the new router + add the reconcile loop as a startup task (~10 lines, all in one block). Reconcile loop checks the feature flag on every tick, so leaving it running with the flag off costs ~one settings lookup per minute.
- static/index.html: one new <script> tag for cookbookSchedule.js.
- static/js/cookbookServe.js: add a "Schedule…" button next to the existing Launch button. Hidden by default; cookbookSchedule.js reveals it after confirming the feature flag is on.
- static/style.css: ~80 lines for the modal styles (mobile-aware via @media).
User choices baked in:
- Calendar events are the source of truth.
- Refuse to launch if GPUs busy (skip + log reason in scheduler.events[uid].reason).
- Hard kill at event end.
- No retry on a skipped event within the window.
- Multi-slot per day supported (one calendar event per slot, shared RRULE).
- Pre-existing manual serves get adopted at window start so they're killed at end.
Known follow-ups (not in this commit):
- Settings UI to pick the schedule calendar + toggle the feature flag.
- Calendar event color/badge for status (running/skipped/failed).
- "Lazy launch on first request" — currently launches at event start. Replacing _launch_serve with a proxy that defers vllm until the first chat request is a contained future change.
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9112861d8e |
cookbook agent debug loop: persistent log files, auto-adopt orphan tmux, Codex/Claude skill parity
Three converging fixes so the chat agent + external Codex/Claude skills can actually debug a crashed serve instead of staring at a post-crash neofetch banner:
* Serves now `tee` to /tmp/odysseus-tmux/SESSION.log on the host running them. Runner saves fds 3/4 before the tee and restores them right before `exec ${SHELL}`, so the post-crash interactive zsh banner does NOT pollute the log file.
* `tail_serve_output` (chat agent) and `/api/codex/cookbook/output/{sid}` (Codex+Claude skills) both prefer the persistent log file over the tmux pane. Pane is fallback for sessions predating the tee runner. Default tail bumped 150 -> 400.
* `list_served_models` "recent log" snippet seeks to the Traceback line instead of showing the last 6 lines (which was always the bash prompt).
Cookbook auto-adoption sweep on `/api/cookbook/tasks/status`: every 20s (rate-limited) the cookbook SSHes each configured server, finds `serve-*` / `cookbook-*` tmux sessions running an actual model process (vllm/python/llama-server/etc., filtered via `pane_current_command`), and writes them into state.tasks. So when the agent falls back to raw ssh+tmux, the session appears in the Cookbook UI on the next poll.
`serve_model` error path now reads `data["detail"]` in addition to `data["error"]` so the FastAPI HTTPException message ("Invalid characters in cmd") actually reaches the agent instead of being swallowed as a generic "Serve failed". Tool description updated to warn against `cd …`/`source …`/`&&` prefixes.
Intent-without-action supervisor in agent_loop: when the model writes "Let me tail the output" / "I'll check the logs" / "Let me investigate" and ends the turn without emitting a tool call, the loop injects a sharp system nudge ("You said you would X — DO IT NOW") and continues. Capped at 2 nudges per chat so a model that genuinely cannot use the tool does not pin the loop.
Codex/Claude skill parity: adds `/cookbook/cached`, `/cookbook/presets`, `/cookbook/preset/{name}`, `/cookbook/adopt` so external agents have the same surface as the chat agent. SKILL.md docs + odysseus_api.py wrapper updated for both bundles.
`adopt_served_model` promoted to the always-on tool set so the agent has a documented fallback when serve_model rejects a cmd.
Also various cookbook UI tweaks accumulated alongside the above (cookbook.js, cookbookRunning.js, cookbookServe.js, cookbook-diagnosis.js, settings.js, style.css).
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562bc4dedc |
Cookbook polish: auto-reconnect, ctx slider fixes, scoring, lots of UI
Backend (services/hwfit + routes):
- VRAM column sort now shows global highest first (was special-cased to
ascending then truncated top-N, which made "highest VRAM" mathematically
unreachable). Every column path uses reverse=True for the truncation.
- Hardware probe cache TTL 30min -> 24h so changing filters doesn't keep
re-probing the rig during a session; Rescan button still forces fresh.
- Multi-GPU rigs filter GGUF Q*/IQ quants (vLLM/SGLang can't serve them);
default non-prequantized to BF16 on 2+ GPUs.
- AWQ / AWQ-8bit / GPTQ-8bit get a -1.0 quality penalty so FP8 wins ties.
- Version-aware tiebreaker (parse Mn.n / Vn) — MiniMax-M2.7 ranks above M2.5.
- hf_models.json: zai-org/GLM-5.1 added; zai-org/GLM-5 quantization flipped
Q4_K_M -> BF16. DeepSeek-V4-Flash / -Pro + their -Base variants registered
with new FP4-MoE-Mixed / FP8-Mixed quant keys (calibrated BPP from the
actual 156 GB / 284 GB disk footprints).
- New FP4-MoE-Mixed + FP8-Mixed entries in QUANT_BPP / QUANT_SPEED_MULT /
QUANT_QUALITY_PENALTY / QUANT_BYTES_PER_PARAM / PREQUANTIZED_PREFIXES.
Frontend — Scan/Download:
- Engine + Quant swapped in the toolbar; Quant defaults to "All".
- Ctx (range slider) ported from origin/main: 8k/16k/32k/50k/128k/Max. Drag
re-sorts by vram ascending (smallest fitting first); back to Max → score.
- Ctx slider rail now visible — was background:transparent in a duplicate
later-cascade rule. Hardcoded grey + !important.
- Search input moved to the far right of the toolbar.
- Type/Standard default; "Context" not uppercased; Search placeholder dimmed.
- Engine "?" + Quant "?" inline help chips inside their dropdown boxes.
- Fit-column dot toggles fit-only filter; un-toggling re-sorts by VRAM desc.
- Quant column truncates to 9 chars + ellipsis ("FP4-MoE-M..."), full in
tooltip. Smart title-suffix strips the parts already in the repo name
(QuantTrio/MiniMax-M2-AWQ + quant AWQ-4bit -> just "(4bit)").
- Conditional warning for safetensors models on non-GPU rigs only.
- Dependency Install / Installed / Installed▾ / N/A all 75.85px wide.
- Rebuild llama.cpp moved into the llama_cpp dep row, styled as a tag.
- Foldable Download admin-card (h2 chevron); line under h2 only when folded.
- HF token save gets a green ✓ + "Saved" flash.
- Cached scan no longer counts stalled rows as downloaded.
- Footer: "Request it →" link with GitHub mark to the public discussion
(#1962) for model-add requests.
Frontend — Running tab:
- Strict download-finish check (DOWNLOAD_OK or /snapshots/, not bare
"Download complete"). True overall % for multi-shard downloads:
((N-1)+frac)/total instead of hf_transfer's per-shard aggregate.
- ETA in the uptime ticker: "downloading: 12m 34s · ETA 1h 23m".
- Clear button kills the tmux session too; if the output still shows a
live shard line, the pill is hidden + relabels as "reconnect" + revives
on click.
- Self-heal: on cookbook open AND every bg-monitor cycle (10s, throttled
to 8s), scan persisted done/error/crashed downloads and probe their
tmux session — if alive, flip status back to running and reattach.
- Per-launch zombie probe: clicking Download on a model whose persisted
state is done but tmux is still alive revives the existing task and
refuses to start a duplicate.
- Pre-launch GPU probe: vllm / sglang / diffusers serve check
/api/cookbook/gpus first; warns + confirms if no GPU is visible.
- Server-side state guard: rejects "done" POSTs for downloads lacking
DOWNLOAD_OK / DOWNLOAD_FAILED / /snapshots/ when the last-mentioned
shard is N<total — stale tabs can't poison persisted state any more.
- Running count includes tasks whose output looks active even if persisted
status got stuck. Dir text on the running row, font matched to uptime.
Serve panel:
- Ctx text input always resets to model max on open (default 20000 when
metadata is missing).
- Max Seqs default 8 -> 4. KV Cache dtype select 32px tall.
- Lightning icon on Launch (same as Action toggle).
- Diagnosis card simplified (no fold/copy/dismiss), suggestion font
matches body; action buttons get icons on the left (Retry/Copy/Edit/
Install/Kill/Switch/etc.).
- Incomplete-download serve warning when model status is
downloading / stalled / has_incomplete.
- MTP "?" tooltip ("supported on a few model families … up to ~3× faster").
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3706d756f3 |
Merge remote-tracking branch 'origin/main' into visual-pr-playground
# Conflicts: # routes/cookbook_routes.py # routes/hwfit_routes.py # services/hwfit/fit.py # services/hwfit/models.py # static/js/cookbook-diagnosis.js # static/js/cookbook-hwfit.js # static/js/cookbook.js # static/js/cookbookRunning.js |
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eb79b76432 |
Cookbook: scoring fixes, UI polish, false-finished + stale-state bug fixes
Backend (services/hwfit + routes): - rank_models picks visible set by REQUESTED column, not always score — sorting by Param now shows highest-param models PERIOD (incl. too_tight). - New fit_only param. Multi-GPU rigs filter GGUF Q*/IQ quants (vLLM/SGLang cannot serve them); default non-prequantized to BF16 on 2+ GPUs. - AWQ / GPTQ-8bit get a -1.0 quality penalty (was 0.0, tied with FP8), so FP8 wins when both fit. - Version-aware tiebreaker (parse Mn.n / Vn) — MiniMax-M2.7 ranks above M2.5 on equal composite score; >=100B integers not misread as versions. - /api/cookbook/hf-latest no longer drops models without an "NB" pattern in the repo id (MiniMax-M2.7, DeepSeek-V4-Pro etc. were silently filtered). - Cached-model scan: atexit flushes models JSON even if the script is killed mid-walk; each scan_dir wrapped in try/except; timeout 60s -> 180s. - KB granularity for sub-MB sizes (was "0 MB" for 12 KB shells). New "stalled" status for shells <1 MB with no .incomplete files. - /api/cookbook/state POST guard: rejects "done" download tasks lacking DOWNLOAD_OK / DOWNLOAD_FAILED / /snapshots/ when the last-mentioned shard is N<total — stops stale tabs from poisoning persisted state. - hf_models.json: add zai-org/GLM-5.1; flip zai-org/GLM-5 quantization Q4_K_M -> BF16 (it is the native base, not a quant). Frontend (static/js): - Scan/Download toolbar: quant defaults to All; ctx slider (8k/16k/32k/ 50k/128k/Max) ported from origin/main with sort=fit on drag, sort=score on Max. GPU toggle commits _activeCount to maxGpu on initial render. Fit column header tagged with active budget (RAM / GPU / N GPU). - Foldable Download admin-card: the Download h2 is the chevron trigger; state persists in localStorage. - Download card surfaces destination dir (Dir: <path>). Same dir on running task row, font/color matched to uptime (9px Fira Code muted, opacity .4). - Serve panel ctx text input always resets to model max on open. Sub-MB cached models show with red "download stalled" badge. - Bulk-select Cancel + Delete reset the Select button label on exit. - Cookbook running: false-finished bug fixed — DOWNLOAD_OK or /snapshots/ required; bare "Download complete" no longer marks the task done after the first config file. Clear button now sends tmux kill-session too. True overall % for multi-shard downloads: ((N-1)+frac)/total instead of hf_transfer per-shard aggregate. - Diagnosis card simplified: removed fold toggle, copy button, dismiss X. Suggestion font matches message body (12px). - HF token field flashes green check + "Saved" on save. - Cached scan no longer counts stalled rows as downloaded in Scan/Download. CSS: - dep Install button width pinned to 76px to match Installed split. - task-sub row +1px; task-status badge gets margin-right 8px. - Ctx slider styled like gallery editor sliders (thin pill rail, red thumb). - Bulk-select cancel button top -3px -> -5px. |
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e392be0d65 |
fix: Cookbook local GGUF serving inside Docker (#1264)
* fix: Cookbook local GGUF serving inside Docker Cookbook’s in-container GGUF serve flow had multiple Docker-specific breakages that made local llama.cpp models fail or register against the wrong endpoint. Fixes included here: use the scanned model cache root when generating GGUF serve commands instead of hardcoding $HOME/.cache/huggingface/hub fix malformed llama.cpp preflight build lines that generated invalid bash in serve runner scripts preserve loopback model URLs inside Docker when the target port is already reachable from the Odysseus container, instead of rewriting them unconditionally to host.docker.internal Before this change, Docker local serves could fail in several ways: Cookbook pointed llama.cpp at the wrong GGUF path generated serve runner scripts crashed before launch with a shell syntax error successfully started in-container model servers were auto-registered as host.docker.internal: instead of localhost/127.0.0.1 This makes the Docker Cookbook path work as expected for: downloaded GGUF -> local llama.cpp serve -> endpoint registration * test: add test for docker-local endpoint rewrites |
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37f5635f8f | feat: show serve runtime readiness (#1209) | ||
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b89141679f | fix(cookbook): scroll serve panel into view when expanded (#1180) (#1191) | ||
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5b87e69221 | feat: add vllm kv cache dtype option (#1185) | ||
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0f3280ee05 | Expose advanced llama.cpp serve controls | ||
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6fca7e86b7 |
Cookbook serve profiles and engine filter
* Cookbook: Engine filter + intelligent hardware-computed serve profiles Two related Cookbook serving improvements for accurate, hardware-aware model serving (especially on consumer GPUs that can only run GGUF/llama.cpp). Engine filter - New "Engine" dropdown (All / llama.cpp / vLLM / SGLang) beside the quant picker. Pure client-side view filter over the fetched list via the same _detectBackend() the serve commands use, so what you filter to is exactly what would launch. Re-renders from cache (no refetch). Empty-state message + the instant-cache-paint path account for it too. Intelligent serve profiles (Quality / Balanced / Speed) - services/hwfit/profiles.py: compute_serve_profiles() turns detected VRAM + model size into concrete llama.cpp flags (n_gpu_layers, n_cpu_moe, cache-type, context). Encodes the by-hand tuning: a too-big MoE offloads experts to CPU instead of failing; a model that fits stays fully on GPU; quant tracks profile intent; vision models keep image-encoder headroom. Reuses models.py VRAM math so filtering and serving agree on what fits. Pure/deterministic (no t/s claims — partial-offload speed isn't reliably predictable; fit is what's computed). - /api/hwfit/profiles endpoint returns the profiles + the model's trained context limit, with loose name matching (strips org/ prefix, -GGUF suffix, quant tag) so a local GGUF folder name resolves to its catalog entry. - _buildServeCmd (llama.cpp) now emits --n-cpu-moe / --flash-attn / --cache-type-k/v when set, with llama-cpp-python fallback equivalents. It previously only set -ngl/-c, which is why it OOM'd or ran slow. - Serve panel: profile chips that fill the fields on click, plus CPU-MoE / KV Cache / Flash Attn fields. Context is clamped to the model's trained limit (and an absolute 1M sanity ceiling) on type/blur/profile-load and at launch — fixes a crash where a stale 256k/16M preset + quantized KV cache caused an amdgpu ErrorDeviceLost. Tests: tests/test_serve_profiles.py (7) — offload vs full-GPU fit, never exceed VRAM, context cap, launchable flags, vision headroom, no-GPU empty. Checks: py_compile + node --check pass; pytest test_serve_profiles + test_hwfit_amd green; verified live on an RDNA4 box (gfx1200) — Balanced lands ~ncm18 q4 128k, matching hand-tuning. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Cookbook: make column-header sorting discoverable (incl. Newest) Sorting in Cookbook is via clickable column headers (pewds' design), but the headers had no visual cue that they're interactive — so sorting in general, and the Newest sort on the Model header specifically, was undiscoverable. - Style sortable headers as interactive: pointer cursor, hover underline, and the active sort column bolded/highlighted. There was no CSS for .hwfit-sortable / .hwfit-sort-active at all; this helps every existing sort, not just Newest. - The Model column header sorts by release_date (newest first), reusing the existing header-click sort wiring and the "newest" SORT_KEY. No new sort control — uses the existing column-header paradigm. Checks: node --check passes. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Cookbook serve profiles: keep the on-disk file's quant fixed (don't propose Q6/Q2) In the Serve tab the model is a specific GGUF file already on disk, so its quant can't change — but the profiles were suggesting "Quality · Q6_K" / "Speed · Q2_K" as if you could re-quantize it. That's meaningless when serving a fixed file. - compute_serve_profiles gains serve_weights_gb / serve_quant. When set (SERVE mode), the quant is locked to the file's and profiles differ only in the real serving knobs — n_cpu_moe, KV-cache type, context. _weights_gb / _cpu_moe_for_budget use the file's actual size instead of a quant-derived estimate. DOWNLOAD mode (no override) still varies the quant to show download options. - /api/hwfit/profiles accepts serve_weights_gb & serve_quant. - The Serve panel parses the file's size (from m.size "20.6 GB") and quant (from the repo/file name) and passes them, so profiles match what's actually served. Result for a 20.6 GB Q4_K_M file: all three profiles stay Q4_K_M and differ by KV/ctx/offload (Quality q8 KV 128k ncm21, Balanced q4 128k ncm17, Speed q4 32k ncm15) — no nonsensical quant changes. Tests: test_serve_mode_keeps_fixed_quant. Full serve-profile suite green (9). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Cookbook serve: Vision toggle (auto-find mmproj) + live VRAM/RAM-spillover monitor Two serve-panel additions: 1. **Vision toggle.** A "Vision" checkbox that serves the model with its multimodal projector so it can read images. The mmproj path is resolved at runtime (find mmproj-*.gguf next to the model), so dropping an mmproj file in the model folder makes the toggle just work; `--mmproj … --image-max-tokens 1024` (native) / `--clip_model_path` (llama-cpp-python) only when on + found. 2. **Live GPU-memory monitor.** A readout that polls /api/cookbook/gpus every 4s while the panel is open and shows VRAM used/total/%, free, and — crucially on a discrete card — **RAM spillover** (AMD gtt_used_mb), with a plain-language health hint: green/healthy, amber/tight, red/"spilled to RAM — slow (raise CPU MoE or lower context)". Surfaces gtt_used_mb from the gpus endpoint (previously read for total only and discarded for 'used'). Lets you see at a glance whether a config fits VRAM (fast) or is paging to system RAM over PCIe (slow) instead of guessing. Checks: node --check + py_compile pass. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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8b3c0d8ad4 | feat: select cached gguf artifacts for serve (#891) | ||
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517aa593e0 |
Cookbook: clearer tooltips on saved-config badge and GPU chip (#850)
Two small polish items in the Cookbook Serve panel.
Saved-config badge
The little count badge next to the Save button ("3 ▾" etc.) had a
generic "Saved launch configs" tooltip, so the number reads like a
notification dot. Make it spell out what it is and what clicking does:
"3 saved launch configs for <model> — click ▾ to load or delete"
(and "No saved launch configs for <model> yet — click Save to add
one" when empty). Tooltip stays in sync via _updateSavedToggleLabel
so save/delete updates both the count and the hint.
GPU chip on mixed-GPU boxes (#711)
The chip label was `${gpuCount}x ${gpu_name}`, where gpu_name is
just gpus[0].name — so a 4090 + 3060 reads as "2x RTX 4090". The
backend already emits gpu_groups (identical cards grouped, used by
the serve flow to pin CUDA_VISIBLE_DEVICES) and a per-card gpus[]
array, so use them:
- Label renders each homogeneous pool: "1× RTX 4090 + 1× RTX 3060".
Homogeneous setups keep the existing "2× RTX 4090" form.
- Tooltip lists each GPU with its index + VRAM, useful for picking
the right device when launching.
Refs #711.
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966b53df77 | Improve Cookbook serve diagnostics and recommendations | ||
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35ba56fa0c | fix: remove ollama backend filter conflict (#613) | ||
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96618b01c0 | Polish task UI slash commands and Ollama serving | ||
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ab0a480f30 | Show Ollama models in Cookbook Serve | ||
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6873b60721 | Merge branch 'pr-594' into visual-pr-playground | ||
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471ee494f0 |
fix: make transient dropdown/popup menus close on Escape
The global Escape arbiter in ui.js only sees `.modal` elements, so the many ad-hoc dropdowns and context popups that are built on the fly and appended to <body> ignored Escape entirely: document-library card/chat menus, chat context/stats/overflow popups, cookbook serve & running menus, calendar event menus, and compare pane menus. Add a small DOM-free dismissal registry (static/js/escMenuStack.js). Menus register a dismiss callback while open, and the arbiter closes the most-recently-opened one first, so a menu opened over a modal closes before the modal. bindMenuDismiss() wires the ubiquitous "append-to-body, close on outside click" idiom to both the outside-click listener and the Escape stack in one call, and dismissOrRemove() lets the pre-existing bulk removers (scroll/swipe/ modal-dismiss cleanup, reopen sweeps) tear a menu down through its real teardown instead of orphaning its stack entry. Covers ~14 menus across documentLibrary, chatRenderer, cookbookServe, cookbookRunning, calendar, and compare/panes. Every teardown path — item click, outside click, swipe, toggle, rebuild, bulk cleanup — routes through the registry so no entry is ever stranded. tests/test_esc_menu_stack_js.py pins the registry's LIFO and exactly-one-per-press guarantees (node-driven; skips when node is absent). |
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853576273a |
Cookbook: make the GPU process popup actually visible
Two bugs hid the popup that opens on double-click (or right-click) of a GPU button in the Serve panel: 1. z-index 240 vs the cookbook modal at 260 — popup rendered behind the modal it was spawned from. 2. Horizontal position was just `button.left`, with no clamp against the viewport. GPU buttons sit near the right edge of the modal, so the popup got anchored at a left that pushed most of its body past the viewport's right edge. Switch the popup to position:fixed (escapes scrolling / transform stacking contexts on any ancestor), bump z-index to 10010 (above the themed-confirm / overlay layer that sits around 9000-10000), and clamp left/top after measuring the rendered size — including flipping above the button if there isn't room below. The popup is now fully visible regardless of which GPU button it's anchored to or how narrow the viewport is. |
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f1817fd560 |
Add macOS Apple Silicon Cookbook support
* Add Apple Silicon (Metal) GPU detection and unified-memory fit tuning hardware.py detects Apple Silicon locally and over SSH, reporting backend=metal, the chip name, and a RAM-scaled fraction of unified memory as the usable GPU budget. fit.py gains an M1-M4 memory-bandwidth table for realistic tok/s and drops vLLM-only formats (AWQ/GPTQ/FP8) that can't be served on Metal. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> (cherry picked from commit |
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e5c99a5eee | Odysseus v1.0 |