eb79b76432bc78b571e45f8b4639baa2673a51e1
9 Commits
| Author | SHA1 | Message | Date | |
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pewdiepie-archdaemon
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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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Ernest Hysa
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d42e6a7acc |
Scope skill mutations to caller owner
SkillsManager.update_skill walks every SKILL.md on disk and matches by
slug only; the 'owner' key in its scalar_keys whitelist meant a caller
could pass updates={'owner': 'attacker', 'description': 'pwned'} and the
first matching file on disk got silently re-owned. Two users with the
same slug under different category directories (which is supported by
the on-disk layout <category>/<name>/SKILL.md) could each stomp the
other's skill via the manage_skills tool or the in-process callers in
tool_implementations.py (edit, patch, publish, delete).
update_skill and delete_skill now require the caller's owner and only
match a file whose parsed owner field matches. The default of None
means 'no scope' and only matches ownerless skills, so an unsafe call
without an explicit owner is now a no-op. 'owner' is also removed from
scalar_keys so the updates dict cannot be used to reassign ownership
even when the manager is called from an in-process path that didn't
supply the owner argument.
The in-process callers in tool_implementations.py are updated to pass
owner=owner (which was already in scope at every call site) so the
HTTP and agent paths both go through the scoped check. The HTTP route
at routes/skills_routes.py:1499 was already owner-scoped via
sm.load(owner=user); the fix brings the in-process path up to the
same standard.
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Afonso Coutinho
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9b1acf6612 |
Fix year extraction in research queries
* fix: extract full year in research query entities, not just the century * fix: same year capture-group bug in the services search copy * test: research query extracts the full year |
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spooky
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033852ab14 | fix: require GGUF sources for llama downloads (#368) | ||
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Sirsyorrz
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9955f5bc95 |
Fix VRAM estimates for pre-quantized HF repos
The Cookbook fit scanner was reporting impossibly low VRAM requirements
for some pre-quantized models — e.g. cyankiwi/Qwen3-Coder-Next-REAM-AWQ-4bit
shown as 7.1 GB ('perfect' on a 12 GB card) when the real load is ~40 GB.
Root cause is in the catalog builder. When _entry_from_modelinfo falls
back to safetensors metadata for the parameter count, it stored
safetensors.total directly. For pre-quantized repos that figure reflects
*packed* element counts: AWQ/GPTQ-Int4 pack 8x 4-bit weights into one
I32, AWQ-8bit/GPTQ-Int8/FP8 pack 4x. The catalog therefore recorded
~1/8 of the real parameter count, and min_vram_gb = packed * bpp
double-applied the quantization.
Fix the safetensors fallback:
* prefer the per-dtype parameters dict when available and unpack only the
I32/I64 entries (the F16/BF16 scale/zero tensors and embeddings are
already at their real element counts)
* fall back to total * pack_factor when only total is exposed
Patch the catalog entries that were affected by the old fallback so the
fit ratings reflect reality without waiting for a full catalog rebuild:
* cyankiwi/Qwen3-Coder-Next-REAM-AWQ-4bit 11.4B -> 79.7B (40.8 GB VRAM)
* stelterlab/Qwen3-Coder-30B-A3B-Instruct-AWQ 4.6B -> 30.5B
* stelterlab/NVIDIA-Nemotron-3-Nano-30B-A3B-AWQ 5.1B -> 30.5B
* warshanks/Qwen3-8B-abliterated-AWQ 2.2B -> 8.2B
* QuantTrio/sarvam-30b-AWQ 7B -> 30B
* QuantTrio/sarvam-105b-AWQ 19B -> 105B
Closes #377.
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Fernando Lazzarin
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14e8cffa41 |
Fail closed on untrusted teacher draft confidence
Follow-up to #275. get_relevant_skills() treats a missing/unparseable confidence as 1.0, so it always clears the injection threshold. For teacher-escalation drafts -- auto-written from a possibly untrusted trace and then injected as authoritative guidance -- that means a draft can be auto-injected regardless of the configured confidence bar. Require teacher-escalation drafts to carry an explicit, parseable confidence that meets min_confidence; fail closed otherwise. Hand-authored legacy drafts keep the lenient "unset -> keep" behavior so they don't silently vanish, and published skills are unaffected. Ran: python -m py_compile services/memory/skills.py + a get_relevant_skills unit check (teacher drafts with None/garbage/0.8 excluded at min=0.85; 0.9 included; legacy + published unaffected; gate-off control unchanged). Co-authored-by: Fernando Lazzarin <263019791+waitdeadai@users.noreply.github.com> Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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pewdiepie-archdaemon
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0888a3b3e6 | Add native Windows compatibility layer | ||
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John Chaplin
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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 32ac81dbc680361463a088dae867d555d5a79c3b) * Generate macOS/Metal serve commands and surface the Metal GPU cookbook_routes.py adds a macOS serve path (Ollama, Metal-aware llama.cpp build using `sysctl hw.ncpu` instead of `nproc`, and a clear error if vLLM is attempted). The frontend defaults Metal serving to llama.cpp and offers llama.cpp/Ollama instead of vLLM/SGLang. The odysseus-cookbook CLI's `gpus` command reports the Metal GPU via sysctl/vm_stat. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> (cherry picked from commit 4ba01ce25d256ae032029898f361c824a34fcd4b) * Add launchd LaunchAgent for macOS (systemd equivalent) com.odysseus.ui.plist + install-service-macos.sh run Odysseus at login and restart on crash, the macOS counterpart to odysseus-ui.service. The installer auto-fills paths from the venv, so there's no hand-editing. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> (cherry picked from commit 3d4b6b2c7b8b31af32201ed278115df9a559dea9) * Document macOS install (brew, Ollama, AirPlay port, launchd) README + setup.py cover the Homebrew / Apple Silicon path: brew install python@3.11 tmux ollama, Metal serving via Ollama/llama.cpp, the launchd service, and the macOS AirPlay Receiver conflict on ports 7000/5000. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> (cherry picked from commit 8dc9a3578a1726f070ed9f75c0958ae291a6d966) * Add downloadable macOS launcher app builder build-macos-app.sh generates dist/Odysseus.app and a drag-to-Applications dist/Odysseus.dmg. The app starts the local server from this repo's venv and opens the UI in a chrome-less app window (Chromium --app mode, falling back to the default browser). It's a launcher wrapper — it drives the venv rather than bundling Python — so the install path is baked in at build time. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> (cherry picked from commit 7927940c3810ee34640803b198d334a6ac93474d) * Harden macOS Cookbook support: hide MLX, fix Metal build cache Builds on the adopted PR #213 macOS/Metal work with two fixes and tests: - fit.py: always drop MLX-quantized models. Odysseus only generates serve commands for llama.cpp/Ollama (Metal) and vLLM/SGLang (CUDA); MLX needs the mlx_lm runtime and the catalog's MLX repos ship no GGUF alternative, so they were surfaced on Apple Silicon but could never be served. - cookbook_routes.py (macOS branch only): `rm -rf build` before configure so a poisoned CMakeCache from a prior failed CUDA attempt can't make every later build fail; explicit -DCMAKE_BUILD_TYPE=Release; a clear "brew install cmake" hint if cmake is missing. Linux/CUDA path unchanged. - tests/test_hwfit_macos.py: MLX hidden on metal, MLX still hidden on CUDA (regression guard), Metal detection on Apple Silicon, and skipped on Linux/Intel (proves non-macOS detection is untouched). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * Propagate unified_memory flag and document macOS GPU/Docker caveat - hardware.py: detect_system now carries the unified_memory flag from GPU detection into the system dict (it was set by _detect_apple_silicon / AMD-APU detection but dropped during result assembly, so the API always reported null). Lets callers distinguish unified from discrete VRAM. - README: prominent warning that Docker on Apple Silicon can't reach the Metal GPU (runs a Linux VM) — Cookbook must run natively for GPU serving; fix stale text that said Cookbook recommends MLX models (now hidden as unservable). - test: detect_system propagates unified_memory. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * Put Odysseus's venv bin on PATH for cookbook runners Native (non-Docker) installs run from a virtualenv whose bin holds the `hf` CLI and `python3` the cookbook download/serve tmux scripts shell out to. Those scripts start in a fresh login shell with the venv NOT activated, so on a native macOS install `hf download` failed with "hf: command not found" — and the `pip --user` self-heal missed because macOS has no bare `pip` command. - cookbook_helpers.py: _local_tooling_path_export() — pure helper returning a PATH export for the running interpreter's bin dir (escaped for double quotes). - cookbook_routes.py: download + serve runners prepend that dir on local runs (gated off SSH/Windows); swap the `pip` install fallbacks to `python3 -m pip`. - tests: helper output for normal and spaced paths. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * Document macOS llama.cpp serving prerequisites Clarify the two serving paths on Apple Silicon: the recommended zero-build route (brew install llama.cpp ships a Metal llama-server Cookbook finds on PATH), and the from-source fallback, which requires cmake + Xcode Command Line Tools. Without those the build is skipped and serving silently degrades to a slow CPU build, so new users now know to install them (or use the prebuilt) up front. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * Recommend only GGUF-servable models on Metal Apple Silicon's only serving engines are llama.cpp and Ollama, both GGUF-only (vLLM/SGLang are CUDA/ROCm and don't run on macOS). The catalog tags raw safetensors repos with a default Q4_K_M quant, so the fit-ranking was recommending ~397/501 models that have no GGUF and fail to serve on Metal with "No GGUF found" (e.g. microsoft/Phi-mini-MoE-instruct). Drop any model without a real GGUF (is_gguf/gguf_sources) on Apple Silicon — subsumes the previous AWQ/GPTQ/FP8 special-case into one rule. On CUDA these stay visible since vLLM serves safetensors directly. Metal recommendations go 501 -> 104, all actually servable. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * Remove macOS launchd LaunchAgent (cherry-picked extra) Drop the launchd service from the PR #213 cherry-picks: the install-service-macos.sh installer, the com.odysseus.ui.plist template, and the README section documenting them. Tangential to the core Cookbook/Metal support and not wanted. The build-macos-app.sh launcher is kept. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * Add one-command macOS quick start (start-macos.sh) Running Odysseus natively on a Mac previously meant ~7 manual terminal steps (brew deps, venv, activate, pip, setup.py, uvicorn with the right port) — not friendly for a generic macOS user, and the native run is required because Docker on macOS can't reach the Metal GPU. - start-macos.sh: installs Homebrew deps (python@3.11, tmux, prebuilt Metal llama.cpp), creates the venv, installs requirements, runs setup, and launches on a non-AirPlay port (7860). Idempotent; re-run to start again. - README: the Apple Silicon section now leads with this one-command quick start and the clickable .app, with engine/port/manual details folded into a collapsible block. Added a pointer at the top of the manual-install section. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * macOS quick start: auto-open browser when ready The "open this URL" line scrolled out of view as uvicorn kept logging after it, so users missed it. Now start-macos.sh waits (in the background) until the server accepts connections, prints a boxed "ready" banner at that point (i.e. after the startup burst, not before), and opens the URL in the default browser automatically. Skippable with ODYSSEUS_NO_OPEN=1 for headless/SSH use. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * Don't assume/force a specific Python version on macOS The README claimed "system Python is 3.9" — a machine-specific generalization that's often wrong (macOS ships no recent Python by default; many users already have 3.11+). Make it generic, and make start-macos.sh detect an existing Python 3.11+ and use it, only installing python@3.11 when none is found instead of forcing it on top of the user's Python. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * Align start-macos.sh venv path with build-macos-app.sh start-macos.sh created the environment in .venv/, but build-macos-app.sh and the manual install steps use venv/ — so the clickable .app wouldn't reuse the quick-start's environment and would rebuild a second one. Use venv/ everywhere. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * README: state clearly that MLX is unsupported on Apple Silicon Odysseus has no mlx_lm runtime; it serves GGUF (llama.cpp/Ollama) and CUDA (vLLM/SGLang) only. MLX-only models can't run on a Mac and are hidden from Cookbook — make that explicit in both the quick start and the details. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * start-macos.sh: build the venv with an arm64 Python on Apple Silicon A clean-room run surfaced this: with a universal2/x86 Python (e.g. the python.org installer under /usr/local), the venv's compiled extensions install as arm64 but get loaded as x86_64 when launched from the .app bundle, so it crashes with "incompatible architecture (have arm64, need x86_64)". The terminal run happened to work only because a universal binary defaults to arm64 there. On Apple Silicon, look only under /opt/homebrew (arm64-only) for the build Python, and install Homebrew's python@3.11 if none is present — so the venv is arm64-only and launches correctly from both the terminal and the .app. Intel and non-mac paths are unchanged. Verified end-to-end in a clean clone: .app now boots on Metal with no arch error. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * Address dev-exp review: macOS setup robustness + doc/UX fixes From the voltagent dev-exp review of the branch: - README: fix broken anchor links (the em-dash heading produced a slug the links didn't match); simplify the heading to a stable slug. - cookbook_routes.py: add /opt/homebrew/bin and /usr/local/bin to the serve PATH so a brew-installed llama-server/ollama is found instead of falling back to a slow source build. - start-macos.sh: guard against an empty Python path; fail fast with a clear message on port-in-use; ERR trap with a "safe to re-run" message; show pip progress (drop --quiet on the slow requirements install); stop the background browser-opener cleanly on exit/Ctrl+C (no orphaned poller). - setup.py: bind hint to 127.0.0.1; suppress the manual run-hint when launched by start-macos.sh (ODYSSEUS_SKIP_RUN_HINT) so the URL isn't contradictory. - build-macos-app.sh: the .app only opens the browser once the server is actually ready (not after the readiness timeout). - cookbookServe.js: drop "Diffusers" from the Metal backend picker — diffusion_server.py is CUDA-only, so it was an unservable option on macOS. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> --------- Co-authored-by: yunggilja <yunggilja@gmail.com> Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> |
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pewdiepie-archdaemon
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e5c99a5eee | Odysseus v1.0 |