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* fix(sources): fall back to auto when a selected engine's runtime is absent The content-processing engine choice is persisted in the database; the runtime that serves it (Docling, local Crawl4AI) is installed on demand from environment flags evaluated at boot. The two therefore drift: a redeploy that drops OPEN_NOTEBOOK_ENABLE_CRAWL4AI/_DOCLING, a volume moved to a new deployment, or a failed on-demand install all leave a stored selection pointing at a runtime that is not there. The source graph passed that selection straight to content-core, so every affected extraction failed with "Could not extract any text content from this source" - no mention of the engine, the runtime, or the flag that would fix it. For a URL engine set to crawl4ai this breaks URL ingestion entirely. The graph now checks runtime availability before honoring the stored engine and degrades to content-core's "auto" chain, logging a WARNING that names the engine and the env var that would enable it. Engines with no opt-in runtime (auto/simple/firecrawl/jina) are passed through untouched. The availability probes moved from api/routers/capabilities.py to open_notebook/utils/runtime_capabilities.py so the graph can use them without importing from the API layer; the capabilities endpoint keeps identical behavior and its tests follow the probes to their new home. Found by the smoke-e2e agent during v1.14.0 release testing, on a dev environment that was in exactly this state. Pre-existing since v1.13.0 (#1122 made the runtimes opt-in, #432 made the stored selection take effect), not a v1.14.0 regression. * docs(changelog): record the unavailable-engine fallback fix |
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| ask.py | ||
| chat.py | ||
| prompt.py | ||
| source.py | ||
| source_chat.py | ||
| tools.py | ||
| transformation.py | ||