Replace remaining Hawksight-AI GitHub org links and the old
semantica-dev noreply email with the current semantica-agi org
and kaif@getsemantica.ai contact, so security/support contacts
match pyproject.toml.
Documents the 9 pre-existing test failures caused by never-implemented
kg.ProvenanceTracker compatibility methods, the deprecation fix, and
the follow-up migration guide addition in this PR.
Every deprecation warning added in this PR (and the class docstring)
points to docs/migration/kg-provenance-tracker.md, but the file was
never added, so the reference was dead. Adds the guide with a
method-mapping table to semantica.provenance.ProvenanceManager.
Add graph-apache-age extra (psycopg2-binary) which was previously
undeclared despite age_store.py depending on it, wire it into
graph-all, and document install commands for FalkorDB/AGE/Neptune
alongside Neo4j. Note that RDF triple stores need no extra since they
talk SPARQL over HTTP via the core `requests` dependency. Also align
README's "Triplet Stores" table label to "Triple Stores (RDF)" to
match the standard term used elsewhere in the docs, while keeping the
TripletStore interface name in backticks.
Semantica already ships both an RDF triplet-store stack (Blazegraph,
Apache Jena, Eclipse RDF4J via a unified TripletStore/SPARQL interface)
and an LPG graph-store stack (Neo4j, FalkorDB, Apache AGE, AWS Neptune
via Cypher), but the README only surfaced the LPG side. Add a hero
highlight line, a "What Semantica gives you" bullet, and split the
Features-at-a-Glance table row so both formats and all backends are
named explicitly.
- get_table_lineage() gains include_column_lineage=True, resolving
per-column upstream/downstream references via Unity Catalog's
column-lineage API (one request per column, opt-in)
- DatabricksConnector.connect() now reuses an already-open connection
instead of opening a second one; ingest_table()/ingest_query() only
close the connection they opened themselves, so using the ingestor
as a context manager no longer leaks the connection opened by
__enter__
- get_table_schema()/get_table_lineage()/list_tables() now validate
both catalog and schema are resolved before calling Unity Catalog,
matching list_tables()'s existing catalog check
- 8 new regression tests (35 total)
Adds DatabricksIngestor to semantica/ingest/, mirroring SnowflakeIngestor's
structure and public API shape: table/query ingestion via
databricks-sql-connector, Unity Catalog metadata and lineage via
databricks-sdk, and export-as-documents for KG construction.
Closes#747
Review follow-up: only append archived_history_id to used_entities when
explicit_parent_supplied is True. Previously it was appended unconditionally,
so the no-explicit-parent re-track path ended up with the same history id in
both parent_entity_id and used_entities, duplicating the reference in
get_lineage() output.
- get_lineage() aggregated metadata by iterating trace_lineage()'s BFS
order and calling dict.update() on each entry, so ancestor metadata
(now reachable via derived_from chains) could overwrite the queried
entity's own metadata on conflicting keys. Reverse the iteration so
the queried entity (always lineage_entries[0]) is applied last and
wins, matching the documented "most recent entry's metadata takes
precedence" intent.
- track_entity()'s derived_from guard only accepted a concrete dict,
silently ignoring other collections.abc.Mapping implementations
(e.g. types.MappingProxyType). Switch the isinstance check to
Mapping so any mapping-like metadata is honored.
Addresses Qodo review findings on PR #741.
track_entity() only auto-linked a parent by looking up `source` as an
existing entity_id, so two entities sharing a real source URL (e.g. a
document and a decision derived from it) never got connected, and
metadata["derived_from"] was stored but never consulted by any linking
or traversal code.
track_entity() now treats metadata["derived_from"] as an explicit
parent link (unless parent_entity_id was already passed directly), so
the existing BFS in trace_lineage() picks it up for free.
Closes#735
Rule is a mutable dataclass, so an already-registered rule's priority
could change after being added; the dedup early-return skipped the
priority re-sort, so re-adding a rule after mutating its priority
left self.rules stale relative to that change. The duplicate branch
now re-sorts before returning, matching the append path.
- add_rule()'s duplicate-skip path now logs at warning level instead
of debug, so a skipped duplicate is visible by default rather than
silent in typical logging configs
- The duplicate-rule log message now stringifies conditions via
map(str, ...) before joining, since Rule.conditions is List[Any]
and non-string entries would otherwise raise TypeError
add_rule() unconditionally appended to self.rules, so re-running the
same setup code on an existing Reasoner instance (e.g. re-executing a
Jupyter cell) duplicated every rule; forward_chain() would then match
the duplicated rules but silently return no new results since the
conclusions were already in self.facts, with no error or warning.
add_rule() now compares an incoming rule's rule_type, conditions, and
conclusion against existing rules and returns the existing Rule
instead of appending a duplicate, keeping repeated add_rule() calls
with the same definition idempotent.
* Add shacl extra to pyproject.toml (fixes#736)
* docs(changelog): add entry for shacl extra fix (#736)
by @Sameer6305
---------
Co-authored-by: KaifAhmad1 <kaifahmad087@gmail.com>
'By default, initializing ... with storage_path=...' read as if passing
storage_path were the default, contradicting the very next sentence
about the no-argument in-memory default. Rephrased so the in-memory
default isn't undercut by the first sentence.
* docs: improve SHACL validation guide onboarding and workflow guidance
* docs: fix SHACL validation implementation mismatches
* docs: fix stale violation URIs and drop unused imports in SHACL guide
Step 5's illustrative explain_violations() output still referenced the
old cti.example.org/data/... node URIs after Step 4's data_ttl was
rewritten to use example.org/... URIs. Also removes now-unused
export_rdf/tempfile/os imports left over from replacing dynamic RDF
export with inline Turtle strings in five of the code examples.
---------
Co-authored-by: KaifAhmad1 <kaifahmad087@gmail.com>
Step 5's illustrative explain_violations() output still referenced the
old cti.example.org/data/... node URIs after Step 4's data_ttl was
rewritten to use example.org/... URIs. Also removes now-unused
export_rdf/tempfile/os imports left over from replacing dynamic RDF
export with inline Turtle strings in five of the code examples.
Condense the CLI section to the essential install/usage snippet and
command groups, pointing to docs.getsemantica.ai for the full
reference instead of maintaining static terminal mockups in the README.
Consolidate the hero around a single category claim (Context and
Accountability Layer for AI agents), drop the named-competitor
comparison table (LangChain/LlamaIndex/Mem0/Zep/Palantir Foundry),
remove GitHub alert-box tips/notes, cut redundant module/changelog
sections, strip vanity feature counts, and trim em dashes for a
cleaner, more premium read.
KaifAhmad1