Bring the LLM-driven "automatic" metadata filtering mode from the legacy
Knowledge Retrieval node to the KnowledgeFS retrieval node
(knowledge-retrieval-v2).
Backend:
- Accept `automatic` in `metadata_filtering_mode` and add
`metadata_model_config` to the node entity.
- Add `automatic_metadata_filter.py`, which reuses the legacy metadata
filter prompt templates, invokes the configured model, parses the JSON
answer and normalises operators/values against the KnowledgeFS
metadata catalog before building custom metadata conditions.
- Resolve the shared metadata catalog across the selected spaces through
the new `list_metadata_fields` app execution capability (paginated),
fail closed on missing/unavailable models and catalog admission errors,
fail open on extraction errors, and expose the outcome via
`metrics.metadata_filtering` and `llm_usage`.
- Inject the default extractor from the node factory.
- Fix an unescaped brace in the legacy completion prompt template that
broke `.format()`.
Frontend:
- Offer disabled/automatic/manual modes, normalise unknown persisted
modes to disabled, store the automatic model and completion params,
render the model selector through the shared MetadataFilter, and
require a model when saving in automatic mode.
Co-Authored-By: Claude Code <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnUM1CdV5LpcxZEQ2vu9Xc
