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* feat: streaming N-Quads serializer for wire-format triples Groundwork for Phase 2 of #877 (knowledge export). Hand-rolled N-Triples term encoding: rdflib's term.n3() emits Turtle-style forms (numeric shorthand, unescaped newlines) that are invalid in line-oriented N-Quads, so literals are escaped per the ECHAR grammar and IRIs validated for representability. Round-trip tests parse the output back with rdflib's nquads parser and compare term-for-term. * feat: export/import workspace knowledge in .tgx bundles (#877) Phase 2 of the workspace bundle commands: tg-export-workspace now includes the workspace's knowledge by default — per-collection knowledge-graph triples as N-Quads (the collection names the graph, streamed through a tempfile so memory stays flat regardless of knowledge-base size) and the document library (metadata plus content, fetched one document at a time). --config-only skips knowledge on both sides; --triples-limit bounds very large graphs; -f/--flow-id selects the flow the triples services run through. tg-import-workspace streams triples back through the bulk import per collection and recreates library documents (children after parents). Knowledge import is additive, unlike config's skip-existing semantics. Embedding vectors are not carried in bundles: --process re-runs imported documents through the flow, which regenerates extraction output and embeddings; --process-collection targets it. Round-trip covered by unit tests over real archives: export with a mocked Api, re-import, and assert the bulk triples stream and library add calls reproduce the original values (including datatyped literals via the N-Quads path). |
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| .. | ||
| __init__.py | ||
| conftest.py | ||
| test_config_commands.py | ||
| test_error_handling_edge_cases.py | ||
| test_load_knowledge.py | ||
| test_load_structured_data.py | ||
| test_nquads.py | ||
| test_schema_descriptor_generation.py | ||
| test_tool_commands.py | ||
| test_workspace_bundle_commands.py | ||
| test_xml_xpath_parsing.py | ||