* Fix Metadata/EntityEmbeddings schema migration tail and add regression tests (#776)
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.
* Fix RabbitMQ request/response race and chunker Flow API drift
Two unrelated regressions surfaced after the v2.2 queue class
refactor. Bundled here because both are small and both block
production.
1. Request/response race against ephemeral RabbitMQ response
queues
Commit feeb92b3 switched response/notify queues to per-subscriber
auto-delete exclusive queues. That fixed orphaned-queue
accumulation but introduced a setup race: Subscriber.start()
created the run() task and returned immediately, while the
underlying RabbitMQ consumer only declared and bound its queue
lazily on the first receive() call. RequestResponse.request()
therefore published the request before any queue was bound to the
matching routing key, and the broker dropped the reply. Symptoms:
"Failed to fetch config on notify" / "Request timeout exception"
repeating roughly every 10s in api-gateway, document-embeddings
and any other service exercising the config notify path.
Fix:
* Add ensure_connected() to the BackendConsumer protocol;
implement it on RabbitMQBackendConsumer (calls _connect
synchronously, declaring and binding the queue) and as a
no-op on PulsarBackendConsumer (Pulsar's client.subscribe is
already synchronous at construction).
* Convert Subscriber's readiness signal from a non-existent
Event to an asyncio.Future created in start(). run() calls
consumer.ensure_connected() immediately after
create_consumer() and sets _ready.set_result(None) on first
successful bind. start() awaits the future via asyncio.wait
so it returns only once the consumer is fully bound. Any
reply published after start() returns is therefore guaranteed
to land in a bound queue.
* First-attempt connection failures call
_ready.set_exception(e) and exit run() so start() unblocks
with the error rather than hanging forever — the existing
higher-level retry pattern in fetch_and_apply_config takes
over from there. Runtime failures after a successful start
still go through the existing retry-with-backoff path.
* Update the two existing graceful-shutdown tests that
monkey-patch Subscriber.run with a custom coroutine to honor
the new contract by signalling _ready themselves.
* Add tests/unit/test_base/test_subscriber_readiness.py with
five regression tests pinning the readiness contract:
ensure_connected must be called before start() returns;
start() must block while ensure_connected runs
(race-condition guard with a threading.Event gate);
first-attempt create_consumer and ensure_connected failures
must propagate to start() instead of hanging;
ensure_connected must run before any receive() call.
2. Chunker Flow parameter lookup using the wrong attribute
trustgraph-base/trustgraph/base/chunking_service.py was reading
flow.parameters.get("chunk-size") and chunk-overlap, but the Flow
class has no `parameters` attribute — parameter lookup is exposed
through Flow.__call__ (flow("chunk-size") returns the resolved
value or None). The exception was caught and logged as a
WARNING, so chunking continued with the default sizes and any
configured chunk-size / chunk-overlap was silently ignored:
chunker - WARNING - Could not parse chunk-size parameter:
'Flow' object has no attribute 'parameters'
The chunker tests didn't catch this because they constructed
mock_flow = MagicMock() and configured
mock_flow.parameters.get.side_effect = ..., which is the same
phantom attribute MagicMock auto-creates on demand. Tests and
production agreed on the wrong API.
Fix: switch chunking_service.py to flow("chunk-size") /
flow("chunk-overlap"). Update both chunker test files to mock the
__call__ side_effect instead of the phantom parameters.get,
merging parameter values into the existing flow() lookup the
on_message tests already used for producer resolution.
Adds a RabbitMQ backend as an alternative to Pulsar, selectable via
PUBSUB_BACKEND=rabbitmq. Both backends implement the same PubSubBackend
protocol — no application code changes needed to switch.
RabbitMQ topology:
- Single topic exchange per topicspace (e.g. 'tg')
- Routing key derived from queue class and topic name
- Shared consumers: named queue bound to exchange (competing, round-robin)
- Exclusive consumers: anonymous auto-delete queue (broadcast, each gets
every message). Used by Subscriber and config push consumer.
- Thread-local producer connections (pika is not thread-safe)
- Push-based consumption via basic_consume with process_data_events
for heartbeat processing
Consumer model changes:
- Consumer class creates one backend consumer per concurrent task
(required for pika thread safety, harmless for Pulsar)
- Consumer class accepts consumer_type parameter
- Subscriber passes consumer_type='exclusive' for broadcast semantics
- Config push consumer uses consumer_type='exclusive' so every
processor instance receives config updates
- handle_one_from_queue receives consumer as parameter for correct
per-connection ack/nack
LibrarianClient:
- New shared client class replacing duplicated librarian request-response
code across 6+ services (chunking, decoders, RAG, etc.)
- Uses stream-document instead of get-document-content for fetching
document content in 1MB chunks (avoids broker message size limits)
- Standalone object (self.librarian = LibrarianClient(...)) not a mixin
- get-document-content marked deprecated in schema and OpenAPI spec
Serialisation:
- Extracted dataclass_to_dict/dict_to_dataclass to shared
serialization.py (used by both Pulsar and RabbitMQ backends)
Librarian queues:
- Changed from flow class (persistent) back to request/response class
now that stream-document eliminates large single messages
- API upload chunk size reduced from 5MB to 3MB to stay under broker
limits after base64 encoding
Factory and CLI:
- get_pubsub() handles 'rabbitmq' backend with RabbitMQ connection params
- add_pubsub_args() includes RabbitMQ options (host, port, credentials)
- add_pubsub_args(standalone=True) defaults to localhost for CLI tools
- init_trustgraph skips Pulsar admin setup for non-Pulsar backends
- tg-dump-queues and tg-monitor-prompts use backend abstraction
- BaseClient and ConfigClient accept generic pubsub config
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
Tech spec
BlobStore (trustgraph-flow/trustgraph/librarian/blob_store.py):
- get_stream() - yields document content in chunks for streaming retrieval
- create_multipart_upload() - initializes S3 multipart upload, returns
upload_id
- upload_part() - uploads a single part, returns etag
- complete_multipart_upload() - finalizes upload with part etags
- abort_multipart_upload() - cancels and cleans up
Cassandra schema (trustgraph-flow/trustgraph/tables/library.py):
- New upload_session table with 24-hour TTL
- Index on user for listing sessions
- Prepared statements for all operations
- Methods: create_upload_session(), get_upload_session(),
update_upload_session_chunk(), delete_upload_session(),
list_upload_sessions()
- Schema extended with UploadSession, UploadProgress, and new
request/response fields
- Librarian methods: begin_upload, upload_chunk, complete_upload,
abort_upload, get_upload_status, list_uploads
- Service routing for all new operations
- Python SDK with transparent chunked upload:
- add_document() auto-switches to chunked for files > 10MB
- Progress callback support (on_progress)
- get_pending_uploads(), get_upload_status(), abort_upload(),
resume_upload()
- Document table: Added parent_id and document_type columns with index
- Document schema (knowledge/document.py): Added document_id field for
streaming retrieval
- Librarian operations:
- add-child-document for extracted PDF pages
- list-children to get child documents
- stream-document for chunked content retrieval
- Cascade delete removes children when parent is deleted
- list-documents filters children by default
- PDF decoder (decoding/pdf/pdf_decoder.py): Updated to stream large
documents from librarian API to temp file
- Librarian service (librarian/service.py): Sends document_id instead of
content for large PDFs (>2MB)
- Deprecated tools (load_pdf.py, load_text.py): Added deprecation
warnings directing users to tg-add-library-document +
tg-start-library-processing
Remove load_pdf and load_text utils
Move chunker/librarian comms to base class
Updating tests
