Surface a lot of accumulated cookbook + UI work as a single non-agent
commit so the agent rework lands cleanly.
Highlights:
- Ollama as a first-class backend in the Cookbook:
* Download input accepts ollama-style names (name:tag) → backend=ollama
* /api/cookbook/ollama/library (cached scrape of ollama.com + curated
fallback so classic models like qwen2.5 stay reachable)
* "Browse Ollama library" toggle below Download with size chips
* Engine=Ollama in hwfit toolbar merges the Ollama library into the
main scan list as per-tag rows with the same Fit/Param/Quant/VRAM
columns; click → fills Download input
- API Tokens form added to Integrations panel (matching wired
loadTokens()/initTokenForm() that had no HTML)
- Serve panel polish: Advanced fold tightening (-8px nudges on vLLM
checks, Extra args, Spec row), n_cpu_moe + Split Mode controls
pulled up 8px to align with the row's checkboxes, GGUF File dropdown
exposed for Ollama backend, GPU re-render on Edit serve restore,
_forceBackend flag so saved serveState wins over backend detection,
cookbook:servers-changed CustomEvent so panels don't need refresh
- Models page redesign: Add Models row (URL + hidden API key reveal +
Type select + Scan/Ollama/Key/Test/Add icon buttons), Probe All +
Clear-offline buttons in Added Models toolbar, offline-pill removed
(opacity already conveys state), Engine dropdown gains Ollama option
- _ping_endpoint probes /v1/models then base, accepts 4xx as
reachable (vLLM returns 404 on bare /v1, fully working endpoints
were showing offline)
- Diagnosis card: × dismiss + Copy bundle buttons restored on the
serve error feedback card
- Orphan tmux sweep re-enabled behind a 60s rate-limit + background
Thread (off the main event loop) so dead serves get discovered
- cookbook_routes auto-register watchdog: drops the endpoint if the
serve session exits non-zero within the first ~3min
- ollama-rocm sidecar awareness in download wrapper (`docker exec
ollama-rocm ollama pull` when host ollama isn't installed)
- Skill extractor sets initial_status="published" when
auto_approve_skills pref is on (audit demotes later)
- Skill list / model list / cookbook scan misc polish
* fix(skill-extractor): walk all brace candidates so stray braces in prose do not swallow valid JSON
The extractor sliced from the FIRST brace to the LAST brace to recover
JSON embedded in surrounding commentary. When the model emits stray
braces before the JSON object, the slice produces invalid JSON,
json.loads raises, and the exception is swallowed -- the skill is
silently lost.
Fix: walk each brace candidate left-to-right and attempt json.loads on
each slice. The first candidate that parses successfully wins. If none
parse, json.loads on the original text raises and the existing
JSONDecodeError handler logs and returns None as before.
Tested locally -- 8/8 tests passed:
tests/test_extract_skill_json_nonstring.py (2 passed)
tests/test_skill_extractor_rows.py (1 passed)
tests/test_search_content_extraction_parity.py (2 passed)
tests/test_deep_research_search_error.py (3 passed)
Closes#2199
* test(skill-extractor): add focused repro for stray-brace JSON recovery
* test(skill-extractor): add regression test for leading invalid-brace fragment
Addresses the remaining edge case from review: a response that *starts*
with a brace but the leading fragment isn't valid JSON (e.g.
'{not json}\n{"title": "Valid later", ...}') still needs to recover
the valid skill object that follows.
_extract_json_object (already on dev) handles this correctly — it tries
the whole de-fenced string first, then walks each '{' candidate left-to-
right regardless of whether the response begins with '{', so the leading
invalid fragment no longer short-circuits recovery of the real object.
Updates the comment at the call site to call this out explicitly and adds
a regression test covering exactly the scenario described in review.
maybe_extract_skill() sliced the LLM response from the first '{' to the
last '}'. When a model emits a stray brace in prose before the real
object (e.g. "uses {placeholder} then {...}"), the slice starts at the
prose brace, json.loads fails, and a valid skill is silently dropped.
Factor parsing into _extract_json_object(), which tries the whole
(de-fenced) string first and then each '{' start position, returning the
first candidate that parses to a JSON object.
Adds tests/test_skill_extractor_json.py.
pewdiepie-archdaemon