The Metadata dataclass dropped its `metadata: list[Triple]` field
and EntityEmbeddings/ChunkEmbeddings settled on a singular
`vector: list[float]` field, but several call sites kept passing
`Metadata(metadata=...)` and `EntityEmbeddings(vectors=...)`. The
bugs were latent until a websocket client first hit
`/api/v1/flow/default/import/entity-contexts`, at which point the
dispatcher TypeError'd on construction.
Production fixes (5 call sites on the same migration tail):
* trustgraph-flow gateway dispatchers entity_contexts_import.py
and graph_embeddings_import.py — drop the stale
Metadata(metadata=...) kwarg; switch graph_embeddings_import
to the singular `vector` wire key.
* trustgraph-base messaging translators knowledge.py and
document_loading.py — fix decode side to read the singular
`"vector"` key, matching what their own encode sides have
always written.
* trustgraph-flow tables/knowledge.py — fix Cassandra row
deserialiser to construct EntityEmbeddings(vector=...)
instead of vectors=.
* trustgraph-flow gateway core_import/core_export — switch the
kg-core msgpack wire format to the singular `"v"`/`"vector"`
key and drop the dead `m["m"]` envelope field that referenced
the removed Metadata.metadata triples list (it was a
guaranteed KeyError on the export side).
Defense-in-depth regression coverage (32 new tests across 7 files):
* tests/contract/test_schema_field_contracts.py — pin the field
set of Metadata, EntityEmbeddings, ChunkEmbeddings,
EntityContext so any future schema rename fails CI loudly
with a clear diff.
* tests/unit/test_translators/test_knowledge_translator_roundtrip.py
and test_document_embeddings_translator_roundtrip.py -
encode→decode round-trip the affected translators end to end,
locking in the singular `"vector"` wire key.
* tests/unit/test_gateway/test_entity_contexts_import_dispatcher.py
and test_graph_embeddings_import_dispatcher.py — exercise the
websocket dispatchers' receive() path with realistic
payloads, the direct regression test for the original
production crash.
* tests/unit/test_gateway/test_core_import_export_roundtrip.py
— pack/unpack the kg-core msgpack format through the real
dispatcher classes (with KnowledgeRequestor mocked),
including a full export→import round-trip.
* tests/unit/test_tables/test_knowledge_table_store.py —
exercise the Cassandra row → schema conversion via __new__ to
bypass the live cluster connection.
Also fixes an unrelated leaked-coroutine RuntimeWarning in
test_gateway/test_service.py::test_run_method_calls_web_run_app: the
mocked aiohttp.web.run_app now closes the coroutine that Api.run() hands
it, mirroring what the real run_app would do, instead of leaving it for
the GC to complain about.
The id field in pipeline Metadata was being overwritten at each processing
stage (document → page → chunk), causing knowledge storage to create
separate cores per chunk instead of grouping by document.
Add a root field that:
- Is set by librarian to the original document ID
- Is copied unchanged through PDF decoder, chunkers, and extractors
- Is used by knowledge storage for document_id grouping (with fallback to id)
Changes:
- Add root field to Metadata schema with empty string default
- Set root=document.id in librarian when initiating document processing
- Copy root through PDF decoder, recursive chunker, and all extractors
- Update knowledge storage to use root (or id as fallback) for grouping
- Add root handling to translators and gateway serialization
- Update test mock Metadata class to include root parameter
The metadata field (list of triples) in the pipeline Metadata class
was redundant. Document metadata triples already flow directly from
librarian to triple-store via emit_document_provenance() - they don't
need to pass through the extraction pipeline.
Additionally, chunker and PDF decoder were overwriting metadata to []
anyway, so any metadata passed through the pipeline was being
discarded.
Changes:
- Remove metadata field from Metadata dataclass
(schema/core/metadata.py)
- Update all Metadata instantiations to remove metadata=[]
parameter
- Remove metadata handling from translators (document_loading,
knowledge)
- Remove metadata consumption from extractors (ontology, agent)
- Update gateway serializers and import handlers
- Update all unit, integration, and contract tests
Terminology Rename, and named-graphs for explainability data
Changed terminology:
- session -> question
- retrieval -> exploration
- selection -> focus
- answer -> synthesis
- uris.py: Renamed query_session_uri → question_uri,
retrieval_uri → exploration_uri, selection_uri → focus_uri,
answer_uri → synthesis_uri
- triples.py: Renamed corresponding triple generation functions with
updated labels ("GraphRAG question", "Exploration", "Focus",
"Synthesis")
- namespaces.py: Added named graph constants GRAPH_DEFAULT,
GRAPH_SOURCE, GRAPH_RETRIEVAL
- init.py: Updated exports
- graph_rag.py: Updated to use new terminology
- invoke_graph_rag.py: Updated CLI to display new stage names
(Question, Exploration, Focus, Synthesis)
Query-Time Explainability → Named Graph
- triples.py: Added set_graph() helper function to set named graph
on triples
- graph_rag.py: All explainability triples now use GRAPH_RETRIEVAL
named graph
- rag.py: Explainability triples stored in user's collection (not
separate collection) with named graph
Extraction Provenance → Named Graph
- relationships/extract.py: Provenance triples use GRAPH_SOURCE
named graph
- definitions/extract.py: Provenance triples use GRAPH_SOURCE
named graph
- chunker.py: Provenance triples use GRAPH_SOURCE named graph
- pdf_decoder.py: Provenance triples use GRAPH_SOURCE named graph
CLI Updates
- show_graph.py: Added -g/--graph option to filter by named graph and
--show-graph to display graph column
Also:
- Fix knowledge core schemas
Knowledge core fixed:
- trustgraph-flow/trustgraph/tables/knowledge.py - v.vector, v.chunk_id
- trustgraph-base/trustgraph/messaging/translators/document_loading.py -
chunk.vector
- trustgraph-base/trustgraph/messaging/translators/knowledge.py -
entity.vector
- trustgraph-flow/trustgraph/gateway/dispatch/serialize.py - entity.vector,
chunk.vector
Test fixtures fixed:
- tests/unit/test_storage/conftest.py - All mock entities/chunks use vector
- tests/unit/test_query/conftest.py - All mock requests use vector
- tests/unit/test_query/test_doc_embeddings_pinecone_query.py - All mock
messages use vector
These changes align with commit f2ae0e86 which changed the schema from
vectors: list[list[float]] to vector: list[float].
* Don't emit graph embeddings if there aren't any.
* Don't store graph embeddings in a knowledge store if there's an empty list.
* Translate between Cassandra's 'null' representing an empty list and an
empty list which is what the surrounding code wants (and stored in the
first place).
* Avoid emitting empty embedding lists
* Avoid output empty triple lists
* Fix tests
* Changed schema for Value -> Term, majorly breaking change
* Following the schema change, Value -> Term into all processing
* Updated Cassandra for g, p, s, o index patterns (7 indexes)
* Reviewed and updated all tests
* Neo4j, Memgraph and FalkorDB remain broken, will look at once settled down
