semantica/CHANGELOG.md

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

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[Unreleased]

Added

• Embedded Oxigraph backend for TripletStore (#838, closes #834) by @Linxiushen

  • Added OxigraphStore (semantica/triplet_store/oxigraph_store.py), an in-process SPARQL 1.1 store via the optional pyoxigraph dependency — no external server (Blazegraph/Jena/RDF4J/Anzo) required, fixing the confusing plain connection-error failure TripletStore previously produced with no server running (no local Docker daemon, no Java, CI, or a fresh laptop)
  • Runs fully in memory by default, or persists to a local directory via TripletStore(backend="oxigraph", path=...); reopening the same directory resumes existing data
  • Full CRUD, native batch loading (Store.extend), named-graph scoping (graph= on add/query), and SPARQL SELECT/ASK/CONSTRUCT/DESCRIBE result mapping matching the existing backend contract; reuses sparql_escaping.py for datatype-IRI resolution instead of reimplementing it, and preserves RDF literal datatype/language metadata across writes, reads, and query results
  • New optional semantica[tripletstore-oxigraph] extra (pyoxigraph>=0.5.0), included in the all extra; the import is lazy, so TripletStore and the rest of Semantica keep working without pyoxigraph installed
  • Wired into TripletStore (backend="oxigraph", added to SUPPORTED_BACKENDS and NAMED_GRAPH_CAPABLE_BACKENDS) and exported from semantica.triplet_store; README, module reference, glossary, and usage guide updated with install/configuration examples
  • Fixed along the way: a missing pyoxigraph install surfaced as a generic wrapped ProcessingError instead of the underlying ImportError and its install hint, because TripletStore._initialize_store_backend()'s broad except Exception caught and rewrapped it; ImportError is now re-raised as-is so the pip install "semantica[tripletstore-oxigraph]" hint reaches the caller
  • New integration tests in tests/triplet_store/test_oxigraph_store.py covering persistence/reopen, named-graph isolation, SELECT/ASK/CONSTRUCT result shapes, and the missing-dependency error message; skipped automatically when pyoxigraph isn't installed, and not yet exercised in CI since it doesn't install the optional extra or run the Python test suite

• PROV-O trust blockers and general spec completeness for ProvenanceManager (#825) by @KaifAhmad1

  • Invalidation instead of hard delete: new ProvenanceManager.invalidate(entity_id, agent_id, reason=None) tombstones an entry — archives its pre-invalidation state under a stable versioned key, then appends the invalidated entry (invalidated, invalidated_at_time, invalidated_by, invalidation_reason) — instead of mutating or deleting it, so an audit can prove a fact existed, was reviewed, and was retracted. ProvenanceManager.clear() remains the bulk dev/test store-reset utility it always was; it was not repurposed
  • Hash-chained integrity: every entry now carries sequence_id/previous_checksum, chaining it to the entry immediately before it in insertion order. New ProvenanceManager.verify_chain() walks the chain and reports any break, including a row hard-deleted directly from the underlying table — something a lone per-row SHA-256 checksum can never detect on its own. compute_checksum() now also covers agent_id/agent_type, the lineage-link fields, and the invalidation fields, closing several fields that previously weren't tamper-evident
  • Typed Agent/Activity: agent_id was a dead field — no track_* method read it from kwargs, so it was always the "semantica" default regardless of what callers passed; fixed, and paired with new AgentRecord(id, agent_type, is_automated) / ActivityRecord(id, activity_type, started_at_time, ended_at_time) dataclasses (pass via agent=/activity= kwargs) so a human reviewer, an LLM call, and an automated pipeline stage are now distinguishable, and activities carry real start/end timing. Wired through all 18 *_provenance.py wrapper modules and track_entity/track_relationship/track_chunk/track_property_source
  • Versioning vs. derivation split: new previous_version_id ("this corrects a prior version of the same fact") and derived_from_id ("this was derived from a different source entity") fields, additive alongside the legacy combined parent_entity_id so existing readers are unaffected
  • Downstream lineage traversal: new get_descendants()/trace_descendants() (reverse BFS in both InMemoryStorage and SQLiteStorage), closing the gap flagged in semantica/explorer/routes/provenance.py where direction="downstream" was dead code with no reverse lookup to feed it; the Explorer's /api/provenance lineage response now merges both directions
  • W3C PROV-O qualified relations: export_prov() now emits prov:qualifiedAssociation/hadRole (distinguishing "approved by" from "generated by" for sign-off workflows), qualifiedGeneration/Generation, qualifiedUsage/Usage, qualifiedDerivation/Derivation, qualifiedInvalidation/Invalidation, wasAssociatedWith (Activity→Agent), actedOnBehalfOf (Agent→Agent delegation), and wasInformedBy (Activity→Activity, via a new informed_by=[...] kwarg), alongside the existing plain triples
  • Bitemporal + Bundle support: revision_type/supersedes/valid_from/valid_until fields (plain caller-supplied passthrough, matching the deprecated kg.ProvenanceTracker's actual contract) plus new revision_history() and query_recorded_between() methods, closing the two "no direct equivalent yet" rows in docs/migration/kg-provenance-tracker.md; bundle_id emits prov:Bundle/hadMember membership triples to partition provenance by source/dataset/ingestion-run
  • Configurable, interlinked namespace: export_prov(base_uri=...) / --base-uri CLI flag, defaulting to a new ProvenanceManager.DEFAULT_BASE_URI (https://semantica.dev/ns#) that RDFExporter's NamespaceManager and OWLExporter's default ontology_uri now both reuse, so KG-exported, OWL-exported, and PROV-exported URIs for the same entity_id co-resolve instead of three independently-hardcoded placeholder domains
  • New CLI commands: semantica provenance invalidate|verify-chain|descendants
  • Fixed along the way: track_entities_batch() silently absorbed batch-level typed kwargs (agent_id, entity_type, activity_id) into the opaque metadata JSON blob instead of forwarding them, so the documented banking example in docs/guides/provenance.md never actually worked as written
  • Fixed along the way: compute_checksum() had to exclude entity_id itself from the hash — track_entity()'s versioning archives a prior value by copying it to a new key ("X" → "X:v:<timestamp>"), and hashing entity_id meant that legitimate relabel permanently orphaned any other entry that had already chained its previous_checksum from the pre-relabel value, surfacing as a false-positive "broken chain." Archival and invalidation are now always a pure relabel (unchanged checksum/sequence position) followed by a fresh chained append, never an in-place mutation of an already-chained entry
  • Fixed along the way: InMemoryStorage.get_chain_head() ignored the already-committed chain head whenever the current transaction had staged any entries, understating the head and corrupting the next append's chain link
  • Fixed along the way: several new ProvenanceEntry fields were initially wired into the dataclass and export_prov() but not into SQLiteStorage's DDL/INSERT/row-mapping — InMemoryStorage stores the dataclass directly so it masked the gap. Added a permanent regression test (test_all_fields_round_trip_through_sqlite) asserting every field survives a SQLite round trip, to catch this class of bug for any future field additions
  • Flagged, not fixed (separate, pre-existing issues independent of #825): semantica/pipeline/pipeline_provenance.py imports a nonexistent module and wraps a Pipeline dataclass with no run() method, so PipelineWithProvenance has never worked; most of the 18 wrapper modules' backing classes are themselves missing or incomplete (e.g. context.context_manager, deduplication.deduplicator, normalize.normalizer don't exist; EmbeddingGenerator exists but has no .embed()); kg_provenance.py passes entity_type inside its metadata={} dict instead of as a top-level track_entity() kwarg across most of its ~30 call sites, so it never actually populates the real field
  • Extensive new test coverage across tests/provenance/test_manager.py, test_schemas.py, and test_storage.py (invalidation, hash-chain verification including a simulated hard-delete-detection case and an interleaved-chaining stress test, agent/activity typing, versioning/derivation split, downstream lineage, qualified export triples, bitemporal methods, Bundle export, and namespace interlinking)

• Altair Anzo triplet store backend (#813) by @KaifAhmad1

  • Added AnzoStore (semantica/triplet_store/anzo_store.py), a fourth peer to BlazegraphStore/RDF4JStore/JenaStore speaking plain SPARQL 1.1 over HTTP — no new dependency, since Anzo has no official Python SDK but needs none
  • The one structural difference from the existing backends: Anzo addresses data by a dataset/graphmart URI (dataset_uri, required) rather than a short namespace/repository name, so the endpoint path (<endpoint>/sparql/<store_type>/<url-encoded_dataset_uri>) percent-encodes it; store_type defaults to "graphmart" and can be set to "dataset"
  • Reuses the shared sparql_escaping.py literal-escaping, datatype-IRI resolution, and CONSTRUCT-detection helpers rather than reimplementing them, matching BlazegraphStore's CONSTRUCT/bindings execute_sparql contract exactly
  • Wired into TripletStore (backend="anzo", added to SUPPORTED_BACKENDS and NAMED_GRAPH_CAPABLE_BACKENDS) and config.py (TRIPLET_STORE_ANZO_ENDPOINT env var / anzo_endpoint config key), and exported from semantica.triplet_store
  • 32 new tests in tests/triplet_store/test_anzo_store.py (mocked HTTP, no live Anzo instance needed), including dataset-URI percent-encoding cases that don't apply to the other backends
  • Bulk loading uses SPARQL INSERT DATA (the same approach BlazegraphStore uses) rather than Anzo's separate HTTP Client Interface, keeping the bulk_load() contract identical across backends

• Comprehensive unit and security test suite for the /api/sparql Explorer route (#773) by @Sameer6305

  • Added tests/explorer/test_sparql_route.py (34 tests) covering the SPARQL Explorer route (semantica/explorer/routes/sparql.py), which executes arbitrary SPARQL queries against an in-memory rdflib projection of the live graph and previously had zero test coverage
  • Verified read-only allowlist enforcement against write and mutation queries (INSERT DATA, DELETE DATA, DELETE WHERE, DROP ALL, CLEAR ALL, LOAD, CREATE GRAPH, MODIFY, comments, and multi-statement injections like SELECT ... ; DROP ALL), confirming rejected queries short-circuit before any graph is built or queried
  • Verified resource-limiting behavior, confirming row capping (_SPARQL_MAX_ROWS) truncates results and sets truncated: true, query timeout (_SPARQL_TIMEOUT_S) returns a clean error message without crashing, and concurrency semaphore (_SPARQL_MAX_CONCURRENT) prevents thread starvation under load
  • Verified RDF projection fidelity for node properties and edge relationships, and error formatting for malformed SPARQL syntax with line and column extraction
  • Follow-up review fixes (#805): extracted the duplicated row-cap-and-truncate loop (previously copy-pasted between the CONSTRUCT/DESCRIBE and SELECT branches) into a shared _cap_rows() helper so the _SPARQL_MAX_ROWS cap is enforced identically by both; added test_row_cap_truncates_construct_results, since the truncation path for CONSTRUCT/DESCRIBE results had no direct test coverage even though SELECT truncation did

• Global default persistent storage for ProvenanceManager, plus a working provenance CLI (#795, #802) by @Sameer6305 and @KaifAhmad1

  • Every ingestion/processing module (kg_provenance.py, pipeline_provenance.py, and 20+ other call sites) instantiated its own ProvenanceManager() with no storage_path, so all of them silently fell back to InMemoryStorage and the SQLite audit trail was never actually written. ProvenanceManager.set_default_storage_path(path) now sets a class-level default that every no-arg instantiation picks up, and Semantica.__init__ wires config.provenance.storage_path into it automatically during orchestrator init
  • Added the thread-safe default_storage_path(path) context manager (semantica.provenance.default_storage_path) for test isolation — it stacks nested overrides and guarantees restoration of the previous default on exit, even on exception, so tests can't leak global state into each other
  • Fixed ProvenanceManager.__init__ raising TypeError on the CLI's config= kwarg, and implemented the four methods the CLI already called but that didn't exist on the class: lineage(), audit_log(), export_prov() (W3C PROV-O turtle/ntriples/jsonld via rdflib), and check() — unblocking semantica provenance lineage|audit|export|check end-to-end
  • Follow-up review fixes: track_entity no longer aliases a caller-supplied used_entities list (it copied the reference and later mutated it in place via .append(), which could corrupt a list the caller still held); removed dead fallback branches in orchestrator.py/manager.py left over from not realizing Config.get() already resolves dotted paths; added a --dry-run option to provenance audit to match provenance export (previously only the global --dry-run flag worked, not a local one); and provenance check --strict no longer prints a green "✓" success line immediately before failing — a failing check now renders as a warning before the ClickException is raised

• Markdown round-trip export/import for AgentMemory (#765, #786) by @SaurabhScripts and @Sameer6305

  • AgentMemory.export(format="markdown") and import_data(format="markdown") add a human-editable, diff-friendly alternative to the existing JSON/dict serialization: one Markdown file per memory item, with id, created_at, updated_at, and type/kind in required YAML frontmatter and the memory content as the Markdown body
  • Exporting without a destination returns a single memory as a Markdown string; exporting a set requires a destination directory and writes one stable, content-hashed filename per memory ID, so re-exporting an unchanged set is byte-for-byte idempotent
  • Importing upserts by ID: unknown IDs create new memories, known IDs replace them atomically (local state and vector store are only mutated after the whole batch validates cleanly), and unchanged re-imports are a deterministic no-op
  • Malformed frontmatter, duplicate IDs within an import batch, and duplicate YAML keys are all rejected before any memory is mutated, with actionable error messages
  • Export refuses to overwrite symbolic links and replaces files atomically; import safely compares timezone-aware and timezone-naive timestamps so retention, recency sorting, and date filters stay correct across both
  • Entities and relationships round-trip as memory-local provenance only — Markdown import intentionally does not write into ContextGraph, matching the MVP scope agreed on in #765
  • Documented the file contract and workflow in docs/reference/context.md; 43 new tests in tests/context/test_agent_memory_markdown.py cover round-trip losslessness, idempotency, validation errors, rollback on failure, and vector-store sync ordering

Fixed

• VectorStore.search_vectors() returned inconsistent result shapes across backend implementations (#853, closes #845) by @Sameer6305, reviewed by @KaifAhmad1

  • Every built-in backend (FAISS, Milvus, pgvector, Pinecone, Qdrant, SQLite-vec, Weaviate, in-memory) now returns the same canonical SearchResult shape (id, score, metadata, vector, distance), instead of some backends omitting vector/metadata/distance or, for Weaviate, returning a backend-specific properties key instead of metadata
  • Added a SearchResult TypedDict (semantica/vector_store/vector_store.py, exported from semantica.vector_store) documenting the contract; metadata now always defaults to {} rather than being absent, and id accepts Union[str, int] to accommodate Milvus/Qdrant's native integer IDs without casting
  • Review fix: the score-normalization formula added for Pinecone and Qdrant (1.0 / (1.0 + max(0.0, 1.0 - score))) clamped every raw score >= 1.0 to an identical 1.0, silently collapsing result ranking whenever the raw score could exceed 1 — which happens routinely for dot-product-metric indexes (unbounded), as opposed to cosine (bounded to [-1, 1]). Replaced with (score / (1 + |score|) + 1) / 2, which is strictly monotonic and bounded in (0, 1) for any real input, so ranking order is preserved regardless of metric or vector normalization
  • Added test_qdrant_unbounded_dot_product_scores_preserve_ranking and test_pinecone_unbounded_dotproduct_scores_preserve_ranking (tests/vector_store/test_search_result_schema.py) asserting normalized scores stay strictly ordered and bounded for raw scores well above 1.0, the case the original formula silently collapsed and the existing tests (which only used scores < 1) never exercised
  • Left out of scope, per the original PR: Weaviate's similarity_search() still isn't wired into VectorStore.search_vectors()'s backend dispatch; Milvus's collection schema still has no metadata column so its results always return metadata: {}; and include_vectors support (populating the vector field) is not yet implemented for any backend

• DecisionEmbeddingPipeline.find_similar_decisions() crashed with AttributeError for any VectorStore backend other than inmemory (#842, closes #839) by @Sameer6305

  • _get_candidate_embeddings() iterated VectorStore.vectors/VectorStore.metadata directly, internal dicts only populated for backend="inmemory"; every persistent backend (FAISS, Pinecone, Qdrant, Milvus, ...) raised AttributeError. It now fetches candidates via the backend-agnostic VectorStore.search_vectors(), reading metadata via a res.get("metadata") or res.get("payload") fallback for backends that key it differently
  • Backends such as FAISS don't return the raw vector for each hit; find_similar_decisions() and _find_semantic_similar() now fall back to the search-provided score (normalized from distance when present) as the semantic similarity for those candidates instead of computing cosine similarity against a zero placeholder vector
  • get_decision_statistics() had the identical bug iterating store.metadata.values(); it now returns a limited stats payload with an explanatory warning field for backends that don't expose a full in-memory metadata dict, instead of crashing
  • Fixed along the way: _get_candidate_embeddings()'s expand-and-retry loop (which widens the search pool when post-filtering leaves too few matches) discarded every candidate it had found once the pool hit its cap (limit * 10) without ever collecting limit matches or getting a short page back from the backend — the loop fell through without executing the branch that assigns results, silently returning [] even when matching candidates existed. It now falls back to the last batch collected instead of dropping it
  • Added end-to-end regression tests against real inmemory and faiss backends (no mocks) plus a targeted unit test for the expand-and-retry loop's fallback behavior

• QdrantStore.search_vectors() returned results keyed by "payload" instead of "metadata" (#841, closes #840) by @divyankshah

  • QdrantCollection.search_points() built its result dicts as {"id", "score", "payload"}, while PineconeStore.search_vectors() and every other backend consumed by HybridSearch use "metadata". This silently dropped Qdrant metadata from results and made HybridSearch.filter_by_metadata() reject every candidate whenever a filter was applied, since it looks up result["metadata"] and got nothing back
  • Normalized search_points() to return "metadata" instead of "payload", matching the existing convention; no other module reads the old key, so the rename is a straight fix rather than a partial one
  • Extended tests/vector_store/test_vector_store_deepdive.py::test_qdrant_store to assert the returned key is "metadata" (not "payload") and that HybridSearch.filter_by_metadata() correctly matches against Qdrant results end-to-end

• Explorer Temporal panel never rendered after clicking the toolbar button (#830, #836) by @Sameer6305

  • The panel stayed permanently stuck on "Loading temporal…" in npm run dev, with repeating "Maximum update depth exceeded" errors in the browser console. Two independent render loops were responsible:
  • Diagnostics state churn: handleDiagnosticsChange unconditionally called setGraphDiagnosticsState on every invocation. buildEffectAvailability (inside GraphCanvas's diagnostics useEffect) always returns a new object, so each call scheduled a re-render that immediately retriggered the effect. Fixed by comparing the incoming snapshot field-by-field against the last accepted value via lastDiagnosticsRef before calling setState
  • scrubberTime churn: React 18 concurrent mode re-ran TimelinePanel's useEffect with a structurally-new Date object for the same timestamp when speculative renders discarded useMemo caches, causing repeated setScrubberTime calls that propagated into temporalState churn and retriggered the diagnostics effect. Fixed by deduplicating by millisecond value via onTimeChange/lastScrubberMsRef
  • Bonus: temporal-overlay's shouldLoad predicate was changed to gate strictly on panelState["temporal-panel"], removing the || temporalState?.currentTime branch that caused eager loading on every scrubber update and continuously cancelled in-flight load() completions
  • Bonus: temporalState removed from the plugin-loading useEffect dependency array; predicates extracted into pluginRegistryPredicates.ts and wired through GraphWorkspace.tsx so regression tests exercise the production code rather than a local copy
  • The scrubberTime-churn fix was also applied to the equivalent (but currently unused/unmounted) GraphWorkspaceShell.tsx, which shares the same TimelinePanel integration pattern but does not have the diagnostics-churn code path
  • Follow-up review fix: the diagnostics dedup's structureLayer comparison now also covers disabledReason, curveCount, bridgeCurveCount, and backboneCurveCount (previously only cacheKey/lastDrawAt/enabled were compared, so a pure disabledReason transition could leave the dev-only diagnostics panel stale)
  • Follow-up review fix: test:graph-store, test:graph-workspace, and the new test:plugin-registry regression test are now run in CI (.github/workflows/ci.yml) — previously none of the Explorer frontend's node --test suites executed anywhere in CI, only npm run build, so this fix's own regression coverage (and all prior frontend test coverage) provided no protection against silent regressions

• HybridSearch.search() crashed with AttributeError for any VectorStore backend other than inmemory (#833, #837) by @KaifAhmad1

  • HybridSearch.search() read self.vector_store.vectors directly, an internal dict VectorStore only populates for backend="inmemory"; every other backend (faiss, weaviate, qdrant, milvus, pinecone, pgvector, sqlite) raised AttributeError, making HybridSearch unusable against any real store. It now delegates to VectorStore.search_vectors() (the backend-agnostic public API) for non-inmemory backends, applies metadata_filter as a post-filter over the returned candidates, and normalizes results to a consistent {id, score, distance, metadata} shape
  • Fixed along the way: vector_ids could stay None when callers passed explicit vectors/metadata without vector_ids, crashing downstream list indexing — now defaulted to generated positional IDs
  • Fixed along the way: a query_vector passed as a plain list crashed backend stores (e.g. FAISSStore.search_similar) that call .ndim on it — now normalized to a numpy array up front
  • Fixed along the way: VectorStore.store_vectors() silently dropped metadata for FAISS (and any add_vectors-only backend) because it called add_vectors(vectors, **options) without forwarding metadata, even though FAISSStore.add_vectors() accepts it — this blocked HybridSearch's metadata filtering from ever matching anything on FAISS
  • Follow-up review fixes: the legacy top_k kwarg was read but left in options, then forwarded via **options into VectorStore.search_vectors(), colliding with backends (sqlite, pgvector) that pass an explicit top_k=k to their own search() and raising TypeError: got multiple values for keyword argument 'top_k' — now popped instead of just read; VectorStore.search_vectors()'s dispatch only recognized backend methods named search/search_similar, so delegation still hit NotImplementedError for qdrant/milvus/pinecone, which name their method search_vectors() with a differently-named count parameter (limit vs k) — added a third dispatch branch that binds the count positionally so it works regardless of the backend's parameter name; a missing distance in backend-delegated results defaulted to the raw score, silently reusing the local path's cosine-similarity convention (distance = 1 - score) even for backends using unrelated metrics (L2, inner product) — now left as None instead of a fabricated, metric-inconsistent value
  • Verified across all 7 supported backends: inmemory/faiss/sqlite work live end-to-end; pgvector's dispatch reaches PgVectorStore.add()/.search() (blocked only by no Postgres server in the verification sandbox); qdrant/milvus/pinecone now reach their real search_vectors() method instead of crashing, though their storage side (store_vectors()) still doesn't recognize insert_vectors/upsert_vectors, and weaviate remains entirely unwired (add_objects/query_vectors) on both sides — both are separate, pre-existing gaps independent of this fix, left for a follow-up

• VectorStore.store_vectors() silently dropped metadata for FAISS (and any add_vectors-only) backend (#832, #835) by @KaifAhmad1

  • store_vectors() fell into a branch that called self._backend_store.add_vectors(vectors, **options) without metadata whenever the backend exposed add_vectors() but neither add() nor store_vectors() — true for FAISSStore, the backend most real usage configures for genuine ANN search. Every caller that stores vectors with metadata (e.g. AgentMemory._store_memory_vector(), used internally by AgentContext.store()) lost that metadata once it reached FAISS, with no error or warning
  • Downstream, ContextRetriever._retrieve_from_vector() recovers a result's text via metadata.get("content", ""), which was always "" for any vector stored this way; _rank_and_merge() then embedded that empty string, tripping TextEmbedder.embed_text()'s empty-text rejection and masking the real bug as a spurious TextEmbedder failure recorded by the progress tracker
  • store_vectors() now forwards metadata to add_vectors(), but only when the backend's add_vectors() signature actually accepts it (checked via inspect.signature, accepting either an explicit metadata parameter or a **kwargs catch-all), so a future/custom backend with a stricter signature raises no TypeError
  • Follow-up review fix: the inspect.signature() probe is wrapped in try/except (ValueError, TypeError), consistent with the identical pattern already used in ProvenanceManager.trace_lineage(), so signature introspection failing on an unusual callable can no longer abort store_vectors() before it even attempts to call the backend

• AgnoDecisionKit.check_policy silently treated unevaluable policy rules as compliant (#778, #822) by @Sameer6305

  • _eval_rule() previously returned True when a rule referenced a field missing from the decision payload, or when the rule string didn't match the expected <field> <op> <value> format — the docstring's claim that exceptions never silently return compliant=True didn't cover this, since neither path raised
  • Both cases now raise ValueError instead, which routes through check_policy's existing exception handler and records a warnings entry (e.g. "Could not evaluate rule 'minimum_score >= 0.9': rule references undefined field 'minimum_score'") instead of disappearing with no signal
  • violations/compliant are unaffected — an unevaluable rule is not counted as a violation, since it's genuinely unknown whether it would have passed; this matches the existing compliant/violations/warnings shape already used by ContextGraph.enforce_decision_policy
  • This is additive: warnings was already part of the return contract and populated for other exception cases, so no caller that only checks compliant is affected, and no existing test asserts warnings == [] for a payload that hits either of these paths
  • Follow-up review fix: check_policy decoded policy_rules with json.loads and iterated the result without checking it was actually a list; a JSON-encoded bare string (e.g. policy_rules='"confidence >= 0.7"') decodes to a str, so iterating it evaluated one "rule" per character — combined with the fix above, an 18-character rule string produced 17 warnings instead of being treated as the single rule it was meant to be. A decoded string is now wrapped as a single-element rule list; any other non-list shape (number, object, etc.) or non-string list element now produces exactly one warnings entry instead of silently misbehaving or being iterated character-by-character
  • Follow-up review fix: _eval_rule used data.get(field) is None to detect a missing field, which can't distinguish a genuinely absent key from a key explicitly present with a JSON null value — both produced the same "undefined field" warning, misdiagnosing nullable fields. Field presence is now checked with field not in data first; a present-but-null value now raises a distinct "field {field!r} is null — cannot evaluate rule" message instead of the misleading "undefined field" one
  • Follow-up review fix: check_policy only checked that decision_data was valid JSON, not that it decoded to an object. When it decoded to a list, field not in data silently became list-membership testing instead of a key check (e.g. "confidence" not in ["confidence", 0.95] is False), so a matching rule fell through to data["confidence"], which raised a raw, confusing TypeError: list indices must be integers or slices, not str instead of any meaningful diagnostic; numbers/strings/bools produced similarly opaque TypeErrors. check_policy now rejects any decision_data that doesn't decode to a JSON object upfront with a single clear violations entry, the same way it already rejects malformed JSON
  • Added 15 tests to tests/integrations/agno/test_decision_kit.py covering the missing-field case (the issue's traced example), the malformed-rule-string case, the bare-JSON-string policy_rules amplification case, non-list/non-string policy_rules shapes, the missing-key-vs-null-value distinction, non-object decision_data shapes (list/number/string/bool/null), and regression checks confirming normal rule evaluation on present fields is unchanged

• No cycle detection for SKOS concepts at write time (#774, #819) by @mikemikimike, reviewed by @Sameer6305 and @KaifAhmad1

  • Added cycle detection (validate_skos_hierarchy) for skos:broader and skos:narrower relationships in ContextGraph.add_edge() and ContextGraph.add_edges(), preventing direct 2-node cycles, self-loops, and multi-hop hierarchy cycles
  • Added GraphSession.add_nodes_and_edges() to validate SKOS hierarchy edges upfront under lock before node insertion, preventing partial-write leaks where nodes remain after a cyclic edge is rejected
  • Updated vocabulary, ontology (/api/ontology/load, /api/ontology/create), and JSON/CSV import routes to use add_nodes_and_edges() and return HTTP 422 with actionable error messages when a cycle is detected
  • Follow-up fix by @KaifAhmad1: validate_skos_hierarchy() previously re-walked every SKOS hierarchy edge already in the graph on each write, so one pre-existing cycle anywhere (e.g. legacy data) blocked all unrelated future writes; it now only traverses concepts touched by the edges being written, while still checking against existing edges for cycles that span old and new data
  • Follow-up fix by @KaifAhmad1: in /api/ontology/load, except HTTPException: raise was unreachable because a broader except Exception clause above it already matched HTTPException, so a 422 raised after a successful OntologyIngestor parse was silently swallowed and reprocessed via the fallback RDF parser; reordered the clauses so the deliberate 422 always propagates
  • Follow-up fix (#775): /api/ontology/{uri}/refresh was missed by the original sweep and still called session.add_nodes() then session.add_edges() as two independent operations, so a cyclic SKOS edge rejected by add_edges() left the nodes from the preceding add_nodes() call committed to the graph; switched to session.add_nodes_and_edges() with the same except ValueError → HTTP 422 handling already used by /api/ontology/load and /api/ontology/create. Audited every other add_nodes()/add_edges() pairing in the repo (GraphStore, graph_builder.py, agent_memory.py, context_graph.py.load(), enrich.py) — none share GraphSession's SKOS-cycle-validation write path, so none were changed

• Agno _AgentScopedStore.upsert_memory silently swallowed decision recording failures (#779)

  • upsert_memory() now logs logger.warning("[%s] record_decision failed: %s", self._role, exc, exc_info=True) when record_decision() fails, matching the error-logging convention used for store() in the same method with traceback context preserved
  • Preserves graceful fallback behavior: record_decision() remains optional and upsert_memory() continues without propagating the exception
  • Added regression coverage in tests/integrations/agno/test_shared_context.py for both store() and record_decision() warning paths

• AgnoDecisionKit/AgnoKGToolkit silently swallowed Agno tool registration failures (#780, #818) by @Sameer6305 and @KaifAhmad1

  • Removed the try/except: pass wrapped around self.register(fn) in both toolkits' __init__; when Agno is installed, a registration failure now propagates immediately instead of leaving the toolkit half-registered with no signal to the caller
  • Graceful degradation when Agno isn't installed (AGNO_AVAILABLE=False) is unchanged — _tools is still populated so callers can introspect available tools without the package
  • Fixed a related duplicate-entry bug: self._tools was appended to unconditionally before register() ran, which could double-count a tool when Agno's own Toolkit.register() also tracks it in self._tools
  • This is a behavior change for callers that construct these toolkits expecting instantiation to always succeed — audited: no in-repo call site relies on the old silent-failure behavior
  • Expanded tests/integrations/agno/test_decision_kit.py and test_kg_toolkit.py with coverage for registration invocation counts, failure propagation, graceful degradation, and no-duplicate-_tools assertions

• ProvenanceManager tracking methods silently swallowed failures without logging and returned fabricated entries (#783)

  • track_relationship(), track_chunk(), and track_property_source() now return Optional[ProvenanceEntry] (None on storage failure, consistent with #782's track_entity fix) instead of a fabricated populated object
  • _save_entry() now always logs on any storage failure, including previously-silent per-item batch failures
  • track_entities_batch() and track_chunks_batch()'s rare block-level transaction failures are now logged too
  • source_tracker.py's track_sources_batch() no longer counts failed tracking calls in its stats

• MCP handle_get_causal_chain returned an empty-but-valid-looking response when both CausalChainAnalyzer and the graph fallback were unavailable (#781, #817) by @Sameer6305 and @KaifAhmad1

  • Returns an explicit {"error": "Causal chain analysis is not supported on this graph backend", "chain": []} instead of {"chain": [], "count": 0, "direction": ...}, letting clients distinguish "unsupported" from a legitimately empty chain
  • The fallback path now introspects graph.get_causal_chain's signature to forward direction/max_depth (or a depth kwarg, or nothing, depending on what the backend accepts) instead of always calling with just decision_id, matching the primary analyzer path's behavior
  • Hardened input handling: non-dict args, non-string decision_id (previously a latent AttributeError on .strip()), and max_depth clamped to (0, 100] with a safe default on invalid input
  • Added tests/test_mcp_decisions_causal_chain.py (11 tests) covering the unsupported-backend, fallback-forwarding, and validation/exception paths across multiple backend signature shapes
  • Follow-up review fix: the signature-detection try/except previously caught the actual call's exceptions in the same block used for introspection failures, so a genuine bug inside a backend's get_causal_chain (raising an unrelated TypeError) was misread as a signature mismatch and the backend was invoked a second time with identical arguments before the real error surfaced. Signature introspection and the resulting call are now split into separate try/excepts so a successfully-introspected call is made exactly once; added test_internal_typeerror_calls_backend_only_once to lock this in

• ProvenanceManager.track_entity persisted partial history and returned fabricated entries on storage failure (#782, #816) by @Sameer6305 and @KaifAhmad1

  • track_entity()'s two-step write (history archive + primary update) is now atomic — if either write fails, the whole operation rolls back via the existing #807 transaction() mechanism, instead of silently persisting a partial state
  • track_entity()'s return type is now Optional[ProvenanceEntry]: on failure it returns a safe deep copy of the pre-failure existing entry (if one existed) or None (if this was a brand-new, never-successfully-tracked entity) — never a fabricated object claiming values that were never actually persisted
  • This is a behavior change for callers that inspect the return value without checking for None first — audited: 0 of 47 production call sites in the repo currently dereference the return value, so this is safe today, but any NEW caller must handle None
  • InMemoryStorage gained real transactional rollback (staging-buffer based) to match this guarantee — previously transaction() was a no-op

• ProvenanceManager duplicated the same checksum/persist/exception-swallow block across 4 tracking methods (#784, #815) by @Sameer6305 and @KaifAhmad1

  • Consolidated the repeated entry.checksum = compute_checksum(entry) / try: self.storage.store(entry) except Exception: pass block used by track_entity, track_relationship, track_chunk, and track_property_source into a single ProvenanceManager._save_entry() helper, preserving the existing graceful-failure behavior and the batch _conn/re-raise semantics from #807
  • Added 4 regression tests (tests/provenance/test_manager.py) covering storage-failure swallowing for each of the four tracking methods, none of which had coverage for this path before
  • Follow-up review fix: the initial refactor of track_entity's exception fallback (the branch that runs when a failure happens before the entry is built, e.g. a retrieve error inside the atomic transaction) routed through _save_entry(), which made a new self.storage.store(entry) call outside the already-failed transaction — a real behavioral change from the original code (which only computed a checksum on that path) that could have reintroduced the exact race #807's BEGIN IMMEDIATE transaction serialization was meant to prevent. Reverted that branch to only compute the checksum, and added test_track_entity_pre_build_failure_fallback_skips_store asserting storage.store is never called on that path

• SQLiteStorage and ProvenanceManager connection churn, non-atomic writes, and batch tracking overhead (#807) by @Sameer6305

  • Scoped a single SQLite connection to the full duration of each public storage method call (track_entity(), store(), retrieve_all(), clear()) instead of opening independent connections per internal SQL statement, reducing connection churn by ~67% while closing the handle before the public method returns to preserve Windows filesystem unlink safety
  • Implemented the SQLiteStorage.transaction() context manager with Write-Ahead Logging (PRAGMA journal_mode=WAL), busy_timeout=5000, synchronous=NORMAL, and immediate write transactions (BEGIN IMMEDIATE), ensuring concurrent read-modify-write sequences (including history version ID generation) are serialized without lock contention or data loss
  • Added block-level transaction sharing to track_entities_batch() and track_chunks_batch(), reducing SQLite commit overhead by ~99.9% for large batches and deferring tracked_count increments until successful commit so rolled-back items are never reported as successes
  • Preserved 100% backward compatibility for custom storage backends overriding trace_lineage(self, entity_id) by inspecting signatures dynamically before passing max_depth, and optimized BFS lineage queries with batched IN-clause lookups per frontier level
  • Follow-up fix: retrieve() and trace_lineage() were initially routed through transaction() too, so plain reads took the same BEGIN IMMEDIATE writer lock as read-modify-write calls, serializing every read behind every other read/write and defeating the WAL concurrency this PR was meant to add. They now use a dedicated _read_connection() (configured, no explicit BEGIN) so reads no longer contend for the writer lock
  • Follow-up fix: track_entity()/track_chunk() caught all internal storage exceptions unconditionally, so when called from track_entities_batch()/track_chunks_batch()'s shared per-block transaction, a single item's storage failure (e.g. non-JSON-serializable metadata) was swallowed inside the call and never surfaced to the batch loop's per-item except, inflating tracked_count for entries that were never persisted. Both methods now re-raise when invoked with a shared _conn (batch context) while still degrading gracefully on standalone calls, so batch counts match what's actually committed
  • Added 8 dedicated regression tests in tests/provenance/test_sqlite_storage_performance_807.py covering PRAGMA configuration, Windows unlink safety, batch transaction sharing, BFS max_depth, rollback count accuracy, custom storage backward compatibility, concurrent read-modify-write serialization, and connection cleanup guards on configuration error

• Closed remaining ProvenanceManager storage-failure test-coverage gaps identified by a #785 audit (#785)

  • An audit of tests/provenance/ (filed against a claim that zero tests exercised storage.store() failures) found #782/#783/#784/#807 had already closed most of the gap, but two residual surfaces had no test: track_relationship(), track_chunk(), and track_property_source()'s storage-failure-swallowing contract (returns None, logs, persists nothing) was only verified against InMemoryStorage, never SQLiteStorage; and track_chunks_batch() had no test for per-item _save_entry failure logging or for the block-level transaction-failure log message, even though track_entities_batch() had both
  • No production code changed — #782/#783/#784/#807 already implemented the correct behavior; this closes the coverage gap proving it holds on both backends
  • Added test_track_relationship_storage_error_swallowed_sqlite, test_track_chunk_storage_error_swallowed_sqlite, test_track_property_source_storage_error_swallowed_sqlite, test_chunks_batch_logs_per_item_failure_memory, and test_track_chunks_batch_block_level_transaction_failure_logs to tests/provenance/test_manager.py
  • Read-path failure coverage (get_lineage()/trace_lineage()/get_provenance()/clear() propagating a raised storage exception) remains untested and is a candidate for a follow-up issue, since none of those methods currently wrap the underlying storage call in a try/except

• Explorer's Provenance UI used a naive 2-hop graph traversal instead of the audit-grade ProvenanceManager backend (#792, #809) by @Sameer6305

  • semantica/explorer/routes/provenance.py never imported or called ProvenanceManager (semantica/provenance/manager.py); /api/provenance and /api/provenance/report built their lineage response entirely from a naive 2-hop networkx traversal over the live graph instead of querying the SQLite-backed, checksummed audit log. Both endpoints now query session.provenance_manager.get_lineage(node_id) first, and a new _transform_audit_lineage() maps the W3C PROV-O entries into the exact {"nodes": [...], "edges": [...]} shape LineageDiagram.tsx already expects — no frontend changes required
  • Falls back to the original 2-hop traversal, never a 500: no audit records for a node, a ProvenanceManager storage failure (corrupted DB, permissions), or a failed SHA-256 integrity check on any entry in the lineage chain all degrade cleanly to the naive path. A new source: "audit" | "graph_traversal" field on the response discloses which path actually served the data
  • ProvenanceManager.get_lineage() now returns integrity_verified, computed by re-verifying every entry's checksum before it's trusted; a single tampered or corrupted entry anywhere in the lineage chain now falls the entire response back to graph traversal rather than serving partially-verified audit data
  • Replaced an initial classmethod-based ProvenanceManager.set_default_storage_path() approach (caught in review before merge — it would have let any two sessions/apps in the same process silently share and overwrite each other's storage path, including across unrelated test runs) with provenance_storage_path threaded through GraphSession.__init__ and create_app(...), so each session's ProvenanceManager is independently scoped
  • Disclosed limitation: ProvenanceManager.trace_lineage()/get_lineage() only walk parent_entity_id/used_entities backward, so the audit path currently surfaces upstream lineage only — the naive fallback remains the only source for downstream/descendant relationships until ProvenanceManager gains a reverse lookup
  • New tests/explorer/test_provenance_manager_wiring.py (8 tests): the audit path via a real multi-hop track_entity() chain, empty-record fallback, simulated storage-failure degradation (asserts 200, not 500), checksum-tamper fallback, evidence-field preservation, create_app() storage-path wiring, and cross-session storage isolation, confirmed order-invariant across tests/explorer/ and tests/provenance/ in both execution orders

• POST /shacl/validate and the /health SHACL dimension never ran live SHACL validation (#772, #804) by @Sameer6305 and @KaifAhmad1

  • /shacl/validate had no data graph to validate submitted shapes against — only a Turtle syntax check. Added _data_graph_turtle_for_uri(), which serializes the loaded ontology's nodes/edges into an RDF/Turtle instance graph (CURIE resolution across owl/rdfs/skos/dct/dc, arbitrary node-property projection, typed individuals) and wires both /shacl/validate and the /health SHACL dimension to OntologyEngine.validate_graph() via pySHACL, returning real conforms/violations instead of a hardcoded status="unavailable" stub
  • Fixed a cross-ontology namespace leak in _node_belongs_to_ontology: its prefix fallback (_extract_namespace()) split only on the last /, so sibling ontologies sharing a domain (e.g. .../onto-a and .../onto-b) could match entities across ontologies that shouldn't be related; fixed by comparing against the full URI stem via the new _ontology_namespace() helper
  • Added resource guardrails to /shacl/validate to close a DoS risk flagged in review: a submitted-Turtle byte cap (SEMANTICA_MAX_SHACL_TURTLE_BYTES, default 256 KB), a parsed-triple cap (SEMANTICA_MAX_SHACL_TRIPLES, default 1,000), a validation timeout (SEMANTICA_MAX_SHACL_TIMEOUT, default 15s), and a global concurrency semaphore (SEMANTICA_MAX_SHACL_CONCURRENCY, default 4)
  • Fixed HealthDimension.status being set to "error" on a real (non-ImportError) validation exception, which isn't a valid value on that model — Pydantic construction raised and turned the whole /health endpoint into a 422 on any real bug; now reports status="critical" (already a valid value) with a regression test forcing this exact path
  • Follow-up review fixes: reverted an unrelated regression that had crept into this PR — POST /api/ontology/create had gone back to silently swallowing OntologyEngine.from_data/from_text failures into a near-empty "minimal" ontology instead of raising HTTPException(500), undoing the earlier #770/#787 fix for the same endpoint (and breaking TestOntologyCreateFailures, which wasn't run before this PR's initial merge request); sh:Warning/sh:Info-severity pySHACL results were silently dropped from the /shacl/validate response — a shape using non-Violation severities could report conforms=False with an empty violations list and no explanation, so warnings/infos are now folded into the response's violations array; and /health was independently re-fetching and re-truncation-checking the same ontology's nodes/edges once for the generated SHACL shapes and once for the data graph — both now share a single fetch via _fetch_analysis_graph()
  • New regression tests: TestOntologyCreateFailures (pre-existing, now passing again), test_shacl_validate_surfaces_warning_severity_results, test_health_dedupes_node_edge_fetch, plus the existing 26-test tests/explorer/test_ontology_subissue3.py suite (28/28 passing) and the pre-existing tests/ontology/ suite (83/83 passing)

• Neptune cookbook CloudFormation stack exposed the database port to the entire internet and had no network audit trail (code scanning alert #28, #26, #27, AC_AWS_0276/AC_AWS_0369/AC_AWS_0148) by @KaifAhmad1

  • cookbook/introduction/neptune-setup.yaml's security group let anyone on 0.0.0.0/0 reach the Neptune Bolt/OpenCypher port (8182); it now requires a ClientCidr parameter (CIDR-validated, no default) so the stack can't be created without the deployer explicitly scoping access to their own IP or VPN/office range
  • Added AWS::EC2::FlowLog plus a dedicated CloudWatch Logs group and IAM role so all traffic in the stack's VPC is now logged
  • Left the account-wide IAM password policy check (AC_AWS_0148) unimplemented as a stack resource on purpose: AWS::IAM::AccountPasswordPolicy is an account singleton, and wiring it into a disposable per-learner tutorial stack would mean creating or deleting this stack also mutates or removes the account's real password policy — suppressed with a documented ts:skip=AC_AWS_0148 explaining why, rather than "fixed"
  • Updated 21_Amazon_Neptune_Store.ipynb's aws cloudformation create-stack instructions, prerequisites, and cost table to match the new required ClientCidr parameter and flow-log line item

• Follow-up to the knowledge-explorer Helm chart default-namespace/seccomp scanner findings reopening (code scanning alert #846, #847, #848, #68, #63, CKV_K8S_21/AC_K8S_0086/AC_K8S_0080) by @KaifAhmad1

  • The checkov.io/skip1 metadata annotation added previously (see the CKV_K8S_21 entry below) evidently isn't being honored by the Microsoft Defender for DevOps scan — the same finding reopened under new alert numbers on the current main. Added the more standard # checkov:skip=CKV_K8S_21 and # ts:skip=AC_K8S_0086 inline comments at the top of templates/deployment.yaml, templates/service.yaml, and templates/configmap.yaml as a second suppression path (matching the convention already used in deploy/gcp/cloudrun-service.yaml), plus # ts:skip=AC_K8S_0080 on templates/deployment.yaml for the seccomp finding, which trips for the same root cause: terrascan's static template scan never resolves {{ toYaml .Values.podSecurityContext }}, even though values.yaml sets seccompProfile.type: RuntimeDefault correctly
  • Confirmed the deploy/kubernetes/* (non-Helm) manifests already had TLS and seccomp configured correctly, so no code change was needed there for the corresponding alerts (#61 and the non-Helm seccomp finding) — expected to close on the next scan
  • Documented both suppression mechanisms and the reasoning in .checkov.yaml
  • Residual risk: this environment could not run checkov/terrascan locally to confirm the inline comments are actually honored during a Helm-rendered scan; if the alerts are still open after the next scan, the reliable fallback is splitting the CI checkov/terrascan invocation so deploy/helm/ is scanned with these specific checks excluded via --skip-check instead of relying on in-file suppression

• react-hooks/set-state-in-effect cascading renders across 12 Explorer workspace files (#769, #796) by @Sameer6305 and @KaifAhmad1

  • Replaced synchronous setState calls inside useEffect bodies with React's recommended "adjust state during render" pattern (if (x !== prevX) { setPrevX(x); ...setState... }) across OntologyWorkspace, ManageWorkspace, LineageWorkspace, and GraphWorkspace, and inlined async data-fetching effects with ignore flags to prevent race conditions and stale writes after unmount
  • Fixed a regression the inlining itself introduced: AlignmentsTab.tsx, KGOverviewTab.tsx, OntologyManager.tsx, and VersionsTab.tsx each duplicated their existing fetch callback (reload / fetchOverview / fetchRegistry / loadVersions+loadProposals) into a second, inline copy for the mount effect, and the copy silently dropped the setError/flashMsg calls the original had — re-introducing, on the very first page load, the exact error-swallowing behavior that #767/#790 had already fixed for these same files. The inline copies now mirror the original's error handling (including 207 partial-success messages) exactly
  • Fixed LineageDiagram.tsx only clearing the previously-rendered nodes/edges when the new activeId was falsy instead of on every id change, so switching directly between two lineage views briefly kept showing the previous view's stale diagram instead of clearing before the new fetch resolved
  • GraphWorkspace.tsx and GraphLoadingOverlay.tsx still have unrelated react-hooks/set-state-in-effect violations outside this PR's 12-file scope (confirmed via npx eslint .); left as follow-up work rather than expanding this PR further

• Checkov flagged the knowledge-explorer Helm chart for using the default Kubernetes namespace (code scanning alert #779, #778, #777, CKV_K8S_21) by @KaifAhmad1

  • templates/service.yaml, templates/deployment.yaml, and templates/configmap.yaml all already set metadata.namespace to {{ .Release.Namespace }}, which is only bound at helm install/helm template time; Checkov's helm framework renders the chart without a namespace override, so it always resolves to default and trips CKV_K8S_21 even though the chart is namespace-agnostic by design
  • Added a checkov.io/skip1: CKV_K8S_21 metadata annotation to each of the three files to suppress the scanner artifact false-positive properly in Helm templates, and documented the reasoning in .checkov.yaml

• No React error boundaries around lazy-loaded Explorer workspaces — a single render error crashed the whole app (#768, #794) by @Sameer6305

  • Added an ErrorBoundary class component (explorer/src/ErrorBoundary.tsx) and wrapped each lazy-loaded workspace's <Suspense> block in App.tsx with it, keyed on the active sub-view so navigating away from and back to a crashed tab remounts it cleanly
  • Failed retries are capped at 3 before the fallback UI switches from "Try Again" to a "Reload Application" dead-end, preventing infinite retry loops on deterministic crashes; raw error/stack details are logged via console.error only and never rendered into the fallback UI
  • Fixed the retry counter so it resets after a retry actually succeeds and stays error-free for a few seconds, instead of never resetting (which could permanently exhaust the retry budget on unrelated, individually-recoverable transient errors) or resetting on the very next commit (which could fire prematurely while Suspense was still showing its fallback)

• Explorer frontend workspaces silently swallowed network/server errors (#767, #790) by @Sameer6305

  • ShaclStudio.tsx, VersionsTab.tsx, SKOSVocabularyManager.tsx, EntityResolutionTab.tsx, LineageDiagram.tsx, DecisionWorkspace.tsx, KGOverviewTab.tsx, OntologyManager.tsx, OntologySearch.tsx, ReasoningWorkspace.tsx, and SparqlWorkspace.tsx now render a visible error banner instead of only console.error()-ing failed fetches
  • Added explicit response.status === 207 (Multi-Status) handling across these workspaces so partial backend failures surface a warning instead of reading as a full success (response.ok is true for all 2xx codes, including 207)
  • Added defensive JSON parsing so an unexpected non-JSON (e.g. HTML 500) response body no longer crashes the app with SyntaxError: Unexpected token < in JSON
  • Fixed KGOverviewTab.tsx dropping the /api/graph/nodes partial-success warning whenever /api/graph/stats also returned 207 — both warnings are now shown (appended) instead of one being silently discarded
  • Fixed HealthTab.tsx's registry load still using a bare .catch(() => {}) that swallowed errors identically to the pattern fixed elsewhere in this same folder; failures now populate the existing error banner
  • Fixed AlignmentsTab.tsx's reload() using Promise.allSettled but never handling the "rejected" branches for the registry/alignments fetches, so both failures previously vanished with no error surfaced and no logging

• tests/explorer/test_explorer_api.py failed with TypeError: Client.__init__() got an unexpected keyword argument 'app' on current httpx (#788, #789) by @Sameer6305

  • httpx>=0.28.0 removed the app= kwarg that Starlette's TestClient relies on to wrap a FastAPI app for testing; httpx wasn't pinned anywhere in pyproject.toml, so different environments could independently resolve an incompatible transitive version and hit the same break
  • Added an explicit httpx<0.28.0 constraint to the main [project.dependencies] array (not just a dev extra), so it applies globally across production, dev, and CI installs
  • Without the pin, the full test suite fails to even complete collection (fails immediately on tests/explorer/test_vocabulary.py with the same TestClient error); with it, tests/explorer/test_explorer_api.py goes from 7 failed/12 passed/58 errors to 77 passed, 0 errors

• Explorer backend routes returned HTTP 200 with error/empty bodies on failure, defeating frontend error handling (#770, #787) by @Sameer6305 and @KaifAhmad1

  • GET /api/temporal/patterns now raises HTTPException(500) on a genuine computation failure instead of silently returning an empty-but-valid TemporalPatternResponse; the ImportError fallback (optional kg extra not installed) is unchanged and still degrades gracefully to an empty list
  • POST /api/ontology/create now raises HTTPException(500) when ontology generation fails in either the sample_data or schema_text mode, instead of silently falling back to a partial/minimal ontology with a misleading nodes_added count
  • GET /api/analytics sets response.status_code = 207 (Multi-Status) when some, but not all, of the requested metrics fail, and raises HTTPException(500) when every requested metric fails — a plain 2xx (including 207) reads as success to callers that only check response.ok, so an all-failed request now surfaces as a hard error rather than a body full of {"error": ...}
  • Added regression tests covering all three failure paths (test_patterns_failure_returns_500, test_analytics_partial_failure_returns_207, test_analytics_total_failure_returns_500, and two TestOntologyCreateFailures cases)

Security

• Cypher injection via unvalidated node labels, relationship types, and property keys (#910, GHSA-482h-hw99-h62p) by @KaifAhmad1

  • Node labels and property keys passed to create_node/create_relationship were interpolated directly into Cypher strings in the Neptune, Neo4j, and FalkorDB graph stores. Property values are parameterized, but labels and keys can't be bound as query parameters, and nothing validated them — so a document-derived entity type or property name (the normal ingest path) could close the current Cypher token early and append arbitrary statements (e.g. DETACH DELETE), running with the application's database credentials
  • New shared semantica/graph_store/query_sanitize.py: sanitize_identifier() generalizes age_store.py's existing _sanitize_label/_sanitize_rel_type (the only backend that already validated this) into a helper the other backends import without an import cycle with graph_store.py/methods.py
  • Applied at every label/relationship-type/property-key interpolation site in amazon_neptune.py, neo4j_store.py, falkordb_store.py, graph_store.py (degree_centrality's own query builder), and methods.py (update_relationship's own query builder) — covers create_node, create_nodes, create_relationship, get_nodes, get_relationships, get_neighbors, shortest_path, update_node, create_index, and all relationship-type filters across the three backends
  • Fixed along the way (caught in review, by @Sameer6305): depth/max_depth path-length parameters are meant to be integers, but Neo4jStore.get_neighbors()/shortest_path() interpolated them into the Cypher variable-length-path syntax (*1..{depth}) without coercion — unlike the Neptune/FalkorDB equivalents, which already cast to int(). A string depth (e.g. "1]->(x) DETACH DELETE x //") reached the query verbatim. Added the same int() coercion Neptune/FalkorDB already had, plus GraphStore.get_neighbors()'s hops/depth alias resolution
  • New tests/graph_store/test_cypher_injection.py (unit tests on sanitize_identifier plus the labels/keys/rel-types injection payload run against Neptune/Neo4j/FalkorDB create_node/create_relationship, asserting the malicious query is never built or sent) and the depth-coercion regression above; plus additions to tests/test_graph_store.py (degree_centrality) and tests/test_graph_store_methods.py (update_relationship). Full graph_store suite: 224+ tests passing

• 4 critical/high vulnerabilities in the Explorer API and vector store: RCE, SSRF, XXE, and DoS, plus Cypher/SPARQL injection hardening found along the way (#898) by @Sunil56224972

  • [CWE-502] Arbitrary code execution via pickle.load(): VectorStore.save()/load() used pickle for the on-disk store_data.pkl; a crafted .pkl file placed in the store directory (file upload, shared filesystem, or supply-chain compromise) could execute arbitrary code on deserialization. Replaced with JSON — vectors and metadata are fully JSON-serializable, so nothing is lost — and load() now refuses any legacy .pkl file it finds with a migration error rather than deserializing it
  • [CWE-918] SSRF via redirect bypass in ontology.py's URL fetcher: _validate_fetch_url() correctly blocked private/loopback/reserved addresses on the caller-supplied URL, but _fetch_url_sync() fetched with allow_redirects=True, so a validated public first hop could 302 to http://169.254.169.254/... (cloud instance metadata) or an internal service, and requests followed it with no re-check. Redirects are now followed manually, capped at 5 hops, with _validate_fetch_url() re-run against every hop's target — including relative Location headers, resolved via urljoin() before validation — and every response (redirect or final) is explicitly closed to avoid leaking connections back to the pool
  • [CWE-611] XXE injection in the RDF/XML parser: _safe_parse_rdf() depended on defusedxml for XXE protection, but defusedxml wasn't declared in pyproject.toml's explorer extra, so it was silently absent in normal installs and the code fell back to a bare warning plus unsafe parsing — a crafted RDF/XML ontology with an external entity could read arbitrary server files. Added defusedxml>=0.7.1 to the extra, and _safe_parse_rdf() now fails closed: it raises rather than parsing untrusted RDF/XML if defusedxml isn't importable, replacing an earlier regex-based DOCTYPE-stripping fallback that was reviewed and rejected as bypassable
  • [CWE-770] DoS via unbounded SPARQL graph materialization: _build_rdflib_graph() loaded up to 999,999 nodes and 999,999 edges into memory per query, and with up to 4 concurrent SPARQL requests permitted, an attacker could exhaust server memory. Added a 50,000 node/edge cap (_SPARQL_MAX_GRAPH_NODES); oversized graphs now return a clean error instead of attempting materialization
  • Cypher injection via Apache AGE's graph_name and $$-delimiter breakout: graph_name was interpolated unvalidated into cypher('{graph_name}', $$ ... $$), and raw Cypher query text containing $$ could close AGE's dollar-quoted string delimiter early and append arbitrary SQL. graph_name is now validated against the same identifier allowlist age_store.py already used for labels/relationship types, and any query containing $$ is rejected outright
  • SPARQL Explorer route (/api/sparql) hardened against comment/PREFIX-hiding bypass: _is_read_only_query() now strips comments and PREFIX/BASE declarations before checking the leading keyword, and additionally scans the full query body for SPARQL Update keywords (INSERT/DELETE/DROP/LOAD/CLEAR/CREATE/COPY/MOVE/ADD) — so SELECT ... ; DROP ALL is now rejected by the keyword scan itself rather than relying solely on rdflib's parser
  • Fixed along the way (maintainer follow-up, addressing automated review findings and a regression introduced across several rounds of iteration on the original fix):
    • VectorStore.save()'s numpy handling used list(v) for the JSON fallback path, which produces numpy.float32 elements that json.dump() can't serialize — changed to v.tolist()
    • the SPARQL graph-size ValueError was raised outside execute_sparql()'s exception handling and surfaced as an unhandled 500 instead of a clean API error — moved inside
    • every streamed requests response in the ontology redirect loop, including the one actually read and returned, is now closed in a finally block — a connection-pool leak that a rework of the redirect logic had briefly reintroduced after an earlier fix
    • a later commit meant to add opt-in API-key auth (explorer/auth.py, gated on EXPLORER_API_KEY) instead replaced and silently disabled the Depends(require_auth) enforcement already merged into main for GHSA-j4mq-hprp-987v (Critical — unauthenticated Explorer API), removed the /ws/graph-updates handshake check, and — unlike require_auth — failed open (allowed all requests) whenever its key was unset. Merging that version would have silently reverted an already-fixed Critical CVE the moment this branch landed. Removed explorer/auth.py; restored the per-router Depends(require_auth) wiring and the WebSocket auth check; kept the one genuine improvement in that commit (adding X-API-Key to the CORS allow_headers list) by folding it into the existing CORS config
    • the new SPARQL keyword-scan's comment-stripping regex (#[^\n]*) also matched the # inside standard RDF namespace IRIs (e.g. .../1999/02/22-rdf-syntax-ns#), corrupting any query with a normal rdf:/rdfs:-style PREFIX declaration — caught because the hardening's own bundled tests failed against two of its own cases. Fixed by only treating # as a comment-start at line-start or after whitespace; the companion PREFIX/BASE regex was also fixed to accept bare BASE <...> declarations, which have no prefix-name token between the keyword and the IRI
  • New/updated regression tests: tests/explorer/test_ontology_ssrf.py (redirect re-validation, relative-redirect resolution, response closing, redirect-cap enforcement), tests/test_security_regression.py (Cypher/SPARQL injection, XXE, numpy serialization, SSRF redirect handling), plus additions to tests/explorer/test_sparql_route.py, tests/vector_store/test_vector_store.py, and tests/explorer/test_explorer_auth.py
  • Note: the Cypher-injection hardening here is scoped to age_store.py's graph_name/$$ breakout, found while reviewing this PR. The broader label/property-key/relationship-type injection across the Neptune, Neo4j, and FalkorDB backends (GHSA-482h-hw99-h62p, #910) and the triplet-store SPARQL injection across Blazegraph/RDF4J/Jena (GHSA-8vgg-8mr4-r236, #911) are covered by separate, still-open PRs, as is the unauthenticated-Explorer-API fix referenced above (GHSA-j4mq-hprp-987v, #909, already merged)

• CI/CD supply-chain hardening against mutable-tag Action compromise (LiteLLM/Trivy-class attack) (#824) by @KaifAhmad1

  • Every third-party GitHub Action across all 8 workflows is now pinned to a full commit SHA instead of a mutable tag (@v7 → @3d3c42e... # v7), closing the exact vector used against LiteLLM in March 2026 (a compromised Trivy Action tag stole a long-lived publishing token)
  • Added verify-action-pins.yml + .github/scripts/verify-action-pins.sh: a CI check that fails closed on any uses: reference that isn't a full SHA (catching a newly introduced mutable tag, not just auditing existing pins) and re-verifies every pin against the GitHub API on each workflow change, on push to main, and weekly; an unresolvable API lookup is treated as a failure rather than a silent skip
  • release.yml: scoped permissions to the job level (workflow default is now contents: read), added a concurrency group so simultaneous tag pushes can't race the publish job, and added SLSA build provenance attestation (actions/attest-build-provenance) for every released wheel
  • Created a protected pypi GitHub Environment (required reviewer, restricted to v* tag deployments) and enabled branch protection on main (required PR review with stale-approval dismissal, required status checks, no force-push/deletion, required conversation resolution) — PyPI publishing already used Trusted Publishing (OIDC) with no long-lived token
  • Grouped Dependabot's github-actions updates into a single PR

• security-scan.yml's Safety dependency-vulnerability check was silently non-functional (#824) by @KaifAhmad1

  • safety check --json --output safety-report.json is invalid in Safety 3.x (--output now selects a console format, not a file path); the command errored on every run, swallowed by || true, so no report was ever produced and the job always fell back to a generic "scan completed" message with the vulnerability count hardcoded to 0
  • Switched to --save-json, the correct flag for writing a JSON report to disk; also fixed vuln.package → vuln.package_name and Semgrep's issue.rule_id → issue.check_id (both produced undefined in the PR comment)
  • The job never installed Semantica's own dependencies before scanning, so Safety was auditing the scanner tools' own transitive deps, not the project's; added pip install -e ".[llm-litellm]" so the actual dependency tree — including the LiteLLM extra — is what gets scanned
  • Rewrote the PR-comment builder: every line previously used \\n inside JS template literals, which renders as the literal text \n rather than a newline, producing an unreadable wall of text; now builds real line arrays and collapses long finding lists into a <details> block
  • Added the pull-requests: write permission the comment-posting step was missing (silently failing via its own try/catch on every prior run)

• pypdf2==3.0.1 removed (CVE-2023-36464) (#824) by @KaifAhmad1

  • Surfaced by the Safety fix above: PyPDF2 is a discontinued project (merged into pypdf) permanently frozen at the vulnerable 3.0.1 with no patched release possible. grep -rn "import PyPDF2" found zero real usages anywhere in the codebase — it was only referenced in docstrings describing a PyPDF2.PdfReader() fallback for PDF parsing that was never actually implemented (pdfplumber does the real work). Removed the dependency and corrected the stale docstrings in parse/__init__.py, parse/methods.py, parse/pdf_parser.py, and ingest/email_ingestor.py

• 10 Bandit B324 false positives suppressed (non-cryptographic MD5 use) (#824) by @KaifAhmad1

  • Surfaced by the same Safety fix restoring a working CI gate: Bandit's HIGH-severity check was blocking on 10 pre-existing hashlib.md5() calls, all generating short deterministic cache keys, entity IDs, or IRI suffixes from non-secret input — none used for passwords, tokens, or verifying untrusted data
  • Bandit's own message suggests usedforsecurity=False, but that keyword argument needs Python 3.9+ and pyproject.toml declares requires-python = ">=3.8"; used a targeted # nosec B324 with a one-line justification instead, which suppresses only this check with no runtime behavior change on any supported Python version

[0.6.0] - 2026-07-21

Added

• Named-graph support for JenaStore via Dataset migration (#756, #757) by @Sameer6305 and @KaifAhmad1

  • JenaStore now backs onto rdflib.Dataset(default_union=False) instead of rdflib.Graph, closing #756 and fully closing out the #754/#756 cross-backend named-graph parity effort across Blazegraph, RDF4J, and Jena
  • default_union=False is explicitly set so existing execute_sparql()/get_triplets() calls that don't pass graph= keep seeing only the default graph, not a union across all named graphs
  • add_triplets() accepts a graph= option: when supplied, triples are written to that named graph (4-tuple add via Dataset.graph(uri)); when omitted, behavior is unchanged (3-tuple add routes to the default graph)
  • Fixed a pre-existing bug where the remote-endpoint path instantiated the read-only rdflib SPARQLStore instead of SPARQLUpdateStore, so every add_triplets() call against a remote Fuseki endpoint silently failed (TypeError swallowed, success=True/added=0 returned); also fixed a constructor bug where self.endpoint was always None regardless of how JenaStore was called, making the remote path unreachable in practice
  • serialize() now logs a warning instead of silently dropping named-graph content when the requested format (turtle, xml, n3, …) can only serialize the default graph; use format="trig" or format="nquads" to include all graphs
  • create_model()'s triplet_count now documented as counting across all graphs (default + named), not just the default graph, matching the Dataset-wide semantics
  • delete_triplet() remains scoped to the default graph only (named-graph parity for delete is an explicit follow-up, matching the maintainer's scoping of this migration to add_triplets); the removal is passed self.graph.default_graph explicitly as its context, since Dataset.remove() on a bare 3-tuple resolves to a wildcard context internally and would otherwise delete matching triples out of every named graph too — a follow-up fix to the initial PR #757 for a bug that had no test coverage
  • 9 new tests covering Dataset construction, default_union=False confirmation, named-graph write isolation, serialize() warning behavior, and delete_triplet()'s default-graph scoping

• SPARQL CONSTRUCT query templates (#752, #322, #755, #754) by @Sameer6305

  • Added parameterized, injection-safe CONSTRUCT templates (ConstructTemplate, ParameterDescriptor, ConstructTemplateRegistry)
  • Extended CONSTRUCT execution support from Blazegraph-only to the RDF4J and Jena backends (#755), closing #754
    • RDF4JStore.execute_sparql gains a CONSTRUCT-aware path (Accept: text/turtle, rdflib Turtle parsing, the same (s, p, o, metadata) 4-tuple contract) and named-graph writes via RDF4J's REST context parameter
    • JenaStore.execute_sparql gains the equivalent CONSTRUCT-aware path over its in-process rdflib.Graph
    • _CONSTRUCT_QUERY_RE moved to sparql_escaping.py as a shared, backend-agnostic constant used by all three backends
  • Added pipeline integration via the construct_template step type

• Databricks Connector (Unity Catalog + Delta Lake ingestion) (#747) by @KaifAhmad1

  • Added DatabricksIngestor (semantica/ingest/databricks_ingestor.py), mirroring SnowflakeIngestor's structure and public API shape: a DatabricksConnector connection handler, a DatabricksData dataclass, and an optional-import guard for databricks-sdk/databricks-sql-connector
  • Supports personal access token and OAuth M2M (service principal client_id/client_secret) authentication, configurable via constructor args or DATABRICKS_* environment variables
  • ingest_table()/ingest_query() run against a SQL warehouse or cluster via databricks-sql-connector, with where/order_by/limit/offset support and the same identifier-escaping and unsafe-ORDER BY rejection as SnowflakeIngestor; each call closes the SQL connection it opened unless one is already open (e.g. via the with DatabricksIngestor(...) context manager), which reuses and closes it exactly once instead of leaking a second connection per call
  • get_table_schema(), list_catalogs(), list_schemas(), and list_tables() introspect Unity Catalog via databricks-sdk's WorkspaceClient, validating both catalog and schema are resolved before calling the SDK; get_table_lineage() calls Unity Catalog's table-lineage REST API for upstream/downstream Table --DEPENDS_ON--> Table dependencies, plus an opt-in include_column_lineage=True that resolves per-column lineage via the column-lineage API
  • export_as_documents() converts ingested rows into Semantica document dicts for KG construction, matching SnowflakeIngestor.export_as_documents()'s shape
  • Registered as a lazy export in semantica.ingest (DatabricksIngestor, DatabricksData, DatabricksConnector) and as the db-databricks optional extra (pip install "semantica[db-databricks]") in pyproject.toml, included in db-all
  • New docs/integrations/databricks.md page modeled on docs/integrations/snowflake.md, plus a DatabricksIngestor section and table row in docs/reference/ingest.md and cross-links between the two integration pages
  • 35 unit tests in tests/test_databricks_ingestor.py covering both auth methods, table/query ingestion, connection lifecycle (including reuse under the context manager), pagination, unsafe ORDER BY rejection, catalog/schema validation, schema/catalog/table listing, table and column lineage, document export, and the missing-dependency error path, closing #747

• SQLite Vector Store Backend (sqlite-vec) (#726) by @Luffy2208 and @KaifAhmad1

  • Added SQLiteVecStore (semantica/vector_store/sqlite_vec_store.py), a disk-backed local vector store using the sqlite-vec extension's vec0 virtual tables, closing #240
  • Supports Cosine and L2 distance metrics, dynamic JSON metadata filtering, read-only mode, and an in-memory (:memory:) mode
  • Registered as the "sqlite" backend in VectorStore.SUPPORTED_BACKENDS, with db_path/sqlite_path config and a VECTOR_STORE_SQLITE_PATH environment variable
  • Batched add/delete/get and executemany-based update to avoid per-row round trips; optional use_wal=True enables journal_mode=WAL + synchronous=NORMAL for improved write concurrency
  • Lazy-imports sqlite-vec so the dependency stays fully optional (pip install semantica[vectorstore-sqlite]); table names and metadata filter keys are validated against a strict identifier pattern before SQL interpolation
  • Fixes VectorStore.update_vectors/delete_vectors to delegate to the active backend store instead of only mutating in-memory state, correcting existing behavior for all non-inmemory backends
  • 25 unit and integration tests in tests/vector_store/test_sqlite_vec_store.py covering init, add, search, get, update, delete, read-only mode, and stats

Fixed

• kg.ProvenanceTracker compatibility wrapper out of sync with ProvenanceManager, causing 9 pre-existing test failures (#744, #751) by @Sameer6305 and @KaifAhmad1

  • kg.ProvenanceTracker was a standalone in-memory implementation that never delegated to the unified ProvenanceManager backend; its own test suite asserted the existence of get_lineage, track_relationship, track_entities_batch, get_provenance, and _use_unified, none of which were ever implemented, plus a stale get_all_sources() assertion expecting "timestamp" instead of the actual "recorded_at" key
  • Rather than completing the abandoned compatibility layer, kg.ProvenanceTracker and its remaining supported methods (track_entity, get_all_sources, query_recorded_between, revision_history, export_audit_log) now emit DeprecationWarnings pointing callers to semantica.provenance.ProvenanceManager
  • Removed/rewrote the 9 tests that only exercised the never-implemented compatibility methods to instead verify the observable behavior of the still-supported API, and corrected the stale get_all_sources() assertion
  • Added the previously-missing docs/migration/kg-provenance-tracker.md migration guide referenced by every new deprecation warning, with a method-mapping table to ProvenanceManager and a before/after example, closing #744

• ProvenanceManager.track_entity silently overrides an explicit parent_entity_id/derived_from on re-track (#742) by @Sameer6305

  • track_entity() resolved parent_id via a documented precedence chain (parent_entity_id kwarg > metadata["derived_from"] > source-as-known-entity-id fallback), but the history-preservation block that runs afterward unconditionally overwrote that resolved value with an auto-generated f"{entity_id}:v:{existing.last_updated}" history pointer whenever the entity was being re-tracked, discarding whatever parent the caller had just explicitly supplied with no warning
  • track_entity() now records whether the precedence chain already resolved an explicit parent (parent_entity_id kwarg, metadata["derived_from"], or the source-as-known-entity-id fallback) before the history block runs, and only falls back to the auto-generated history pointer when the caller supplied no explicit parent on that call
  • The archived history entry for the previous version is still kept reachable in get_lineage() via used_entities (BFS-traversed by InMemoryStorage.trace_lineage()) even when an explicit parent is supplied, so re-tracking with a new parent no longer orphans the prior version from the lineage chain; when no explicit parent is supplied, used_entities is left alone since parent_entity_id already points at the same history id, avoiding a duplicate self-reference
  • Added test_retrack_with_explicit_parent_overrides_history_link, test_retrack_without_explicit_parent_still_uses_history_link, test_retrack_with_derived_from_overrides_history_link, and test_retrack_history_reachable_via_used_entities regression tests, closing #742

• ProvenanceManager.get_lineage does not link entities that share a source URL (#735) by @KaifAhmad1

  • track_entity()'s only auto-linking logic looked up source as if it were an existing entity's entity_id, so passing the same real URL/DOI as source for two conceptually linked entities (e.g. a document and a decision derived from it) never produced a parent link, leaving get_lineage() returning a chain of length 1
  • metadata["derived_from"] was preserved and echoed back in the output JSON but was never consulted by any linking or traversal code, so the caller's explicit relationship was silently inert
  • track_entity() now treats metadata["derived_from"] as an explicit parent link (unless parent_entity_id was already passed directly), so InMemoryStorage.trace_lineage()'s existing BFS over parent_entity_id picks it up for free
  • metadata["derived_from"] is now recognized on any collections.abc.Mapping, not just a concrete dict, so e.g. types.MappingProxyType metadata still creates the parent link
  • get_lineage()'s metadata aggregation now applies the queried entity's own metadata last so it wins over ancestor metadata on conflicting keys, matching the documented "most recent entry's metadata takes precedence" behavior — previously trace_lineage()'s BFS order caused ancestor metadata (now reachable via derived_from chains) to silently overwrite the queried entity's own values
  • Added 9 regression/edge-case tests in tests/provenance/test_manager.py covering the happy path, explicit parent_entity_id precedence over derived_from, precedence over the source-as-known-entity-id fallback, a derived_from pointing at a never-tracked entity, non-string/empty-string derived_from values being ignored, a self-referencing derived_from not hanging traversal, multi-hop derived_from chains, metadata precedence between a queried entity and its ancestors, and non-dict Mapping metadata, closing #735

• Reasoner.add_rule had no deduplication, doubling rules and silently emptying forward_chain() on rerun (#732) by @KaifAhmad1

  • 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; since forward_chain() only records a conclusion if it isn't already in self.facts, the second run's duplicated rules matched but produced no new results, 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
  • Added test_add_rule_deduplicates_identical_rule, test_add_rule_deduplication_is_idempotent_across_forward_chain, and test_add_rule_does_not_dedupe_distinct_rules regression tests

• InferenceResult.premises always empty from forward_chain/backward_chain (#739) by @Sameer6305

  • _match_rule() discarded matched facts and returned only instantiated conclusions, so ExplanationGenerator always produced empty premises lists regardless of which facts actually satisfied a rule, closing #733
  • _match_rule() now returns (conclusion, matched_facts) tuples; forward_chain() threads those facts into InferenceResult(premises=...), merging premises when the same conclusion is derived more than once within a pass
  • _prove_goal()'s base cases (goal already a known fact; goal matched via pattern unification) now return premises=[goal]/premises=[fact] instead of []
  • Facts are matched against a sorted() snapshot instead of the raw set so rule matching and premise selection are deterministic
  • Added test_forward_chaining_premises regression test mirroring the existing backward-chaining premises test

• Missing shacl optional-dependency extra (#736) by @Sameer6305

  • pip install semantica[shacl] referenced no matching extra in pyproject.toml, so pyshacl was never installed despite being documented as the fix in ontology_validator.py's ImportError message, the Explorer API, the healthcare cookbook notebook, and the changelog
  • Added shacl = ["pyshacl>=0.25.0"] to [project.optional-dependencies] and folded shacl into the all extra

• NodeEmbedder AttributeError masked in ContextGraph.analyze_graph_with_kg (#734) by @Sameer6305

  • analyze_graph_with_kg() called a non-existent NodeEmbedder.generate_embeddings(), and the surrounding broad except Exception swallowed the resulting AttributeError, silently returning {"error": "Graph analysis failed due to an internal error"} from get_causal_chain()'s supporting analytics and get_decision_insights()
  • Rewired the call site to the real NodeEmbedder.compute_embeddings(graph_store, node_labels, relationship_types) API, deriving node_labels/relationship_types from self.node_type_index/self.edge_type_index
  • Added a dedicated except AttributeError branch that logs distinctly and re-raises, so a broken internal method call surfaces as a diagnosable error instead of being indistinguishable from a legitimately empty analysis result

---

[0.5.1] - 2026-06-29

Added

• Apache Arrow & Feather File Ingestion (#705) by @Luffy2208

  • Added ArrowIngestor (semantica/ingest/arrow_ingestor.py) for reading .arrow, .feather, and .ipc files via PyArrow
  • Supports Arrow IPC File format (random-access), Arrow IPC Stream format, Feather v1 and v2
  • Selective column reads, optional row limits, and batch-aware iteration that stops early without scanning the full file
  • extract_schema() and extract_metadata() convenience methods for schema/metadata inspection without reading row data
  • _ArrowReaderWrapper provides a unified interface across all three reader types, preventing stream exhaustion during schema inspection
  • ingest_arrow() convenience function and ingest(..., source_type="arrow") unified dispatch
  • Automatic Arrow format detection in ingest() by file extension (.arrow, .feather, .ipc) and by Arrow IPC magic bytes (ARROW1\x00\x00) in FileTypeDetector
  • Registry integration under the arrow task namespace with file, schema, and metadata methods
  • Lazy-import exports of ArrowIngestor, ArrowData, and ingest_arrow from semantica.ingest
  • Optional dependency group: pip install semantica[ingest-arrow]; included in pip install semantica[all]
  • 34 tests covering schema extraction, metadata inspection, row limits, column selection, multi-batch reading, IPC stream format, Feather ingestion, empty datasets, null values, magic-byte detection, and failure modes

• Knowledge Explorer Deployment Templates (#684) by @ZohaibHassan16 and @KaifAhmad1

  • Added deploy/ directory with ready-to-use templates for 7 platforms, closing #681
  • Docker — fixed Dockerfile path (was broken on clean checkout), added non-root user, HEALTHCHECK, .dockerignore; fixed docker-compose.yml to start Explorer alongside FalkorDB on a shared network; added docker-compose.dev.yml with source volume-mounts for hot-reload (docker compose up brings up the full stack in one command)
  • Railway — deploy/railway/railway.toml with Dockerfile builder, healthcheck path, restart policy, and env vars wired from the Railway Redis plugin
  • Render — deploy/render/render.yaml Blueprint provisioning the web service and a Redis instance together with cross-linked env vars
  • Fly.io — deploy/fly/fly.toml with region, 512 MB VM, auto-stop, HTTP healthcheck, and a short README with four flyctl commands to deploy from zero
  • GCP Cloud Run — deploy/gcp/cloudbuild.yaml (build → push → deploy pipeline) and deploy/gcp/cloudrun-service.yaml (scale-to-zero, Secret Manager env vars, liveness probe)
  • Azure Container Apps — deploy/azure/azure.yaml, main.bicep (Container App + managed environment, HTTP ingress, HPA min 0 / max 10, liveness probe), and main.parameters.json; deployable with azd up
  • Kubernetes + Helm — raw manifests (namespace, configmap, secret.example, deployment with 2 replicas + rolling update, service, ingress with cert-manager TLS, kustomization); Helm chart with Chart.yaml, values.yaml, values.prod.yaml, HPA template, and helm lint-passing templates; all templates carry namespace: {{ .Release.Namespace }}
  • Added /api/health endpoint returning {"status": "ok"} used by all platform healthchecks
  • Wired ALLOWED_ORIGINS, FALKORDB_HOST, and FALKORDB_PORT from environment variables in semantica/explorer/app.py
  • Security hardened: non-root containers, readOnlyRootFilesystem, NetworkPolicy with explicit ingress/egress selectors, seccompProfile: RuntimeDefault, capabilities dropped; secrets via secret.yaml.example templates only — no committed credentials

Fixed

• Arrow ingestion double full-scan on every data read (#705) by @KaifAhmad1

  • ingest_file previously called _file_metadata (a full batch scan) before _read_batches, meaning every read scanned the entire file twice; for a limit=1 read on a large file the metadata pass visited every batch while the data pass read only one; replaced with a single-pass _read_batches_with_info that collects batch metadata as a side effect of the data read; _file_metadata is now only invoked for include_data=False

• Dead num_record_batches property on _ArrowReaderWrapper materialised all table batches (#705) by @KaifAhmad1

  • The property was never called by production code but its is_table branch called to_batches() purely to take len(), materialising the entire table in memory just for a count; property removed

• Arrow _open_file chained the wrong exception (#705) by @KaifAhmad1

  • The fallback cascade (IPC file → IPC stream → Feather) raised from feather_err, surfacing the least diagnostic error in the Python traceback chain; changed to from file_err so the IPC file open error — the most informative signal for unrecognised formats — appears as __cause__

• Neo4j Bulk CSV Export (#665) by @Luffy2208

  • Added Neo4jCSVExporter for generating Neo4j bulk-import CSV files compatible with neo4j-admin database import
  • Produces deterministic nodes.csv and relationships.csv with stable node IDs — reuses existing graph IDs or derives reproducible SHA-256 content-based IDs when none are present
  • Multi-label support via Neo4j :LABEL convention with configurable label_separator (default ;)
  • Alphabetically sorted property columns and deterministic row ordering for reproducible output across permuted inputs
  • Relationship endpoint resolution: aliases (name, text, label) automatically mapped to stable node IDs
  • Nested property serialisation to canonical JSON; flat scalar values written directly
  • dry_run() method for pre-flight CSV validation without writing files
  • validate_export() for post-write integrity checks (unique :id, consistent column widths, valid endpoint references)
  • export_nodes() and export_relationships() for partial exports
  • strict=True mode raises ValidationError on unresolved relationship endpoints
  • export_neo4j_csv() convenience function and format="neo4j_csv" / format="neo4j-csv" dispatch in export_knowledge_graph()
  • Registry integration under the neo4j_csv task namespace
  • Documentation added to semantica/export/export_usage.md with usage examples, mapping assumptions, and neo4j-admin import command
  • 13 tests covering headers, node/relationship CSV structure, multi-label, missing properties, deterministic output, CSV quoting/escaping, Unicode, empty graphs, dry-run, duplicate ID detection, ambiguous alias handling, nested property serialisation, and KnowledgeGraph integration

Fixed

• Neo4j CSV exporter _write_csv crashed with TypeError on dialect kwargs (#665) by @KaifAhmad1

  • Passing delimiter=, encoding=, or any caller kwarg to export_neo4j_csv caused csv.writer to receive unknown or duplicate keyword arguments; _write_csv now whitelists only valid csv.writer dialect params (quotechar, doublequote, skipinitialspace, escapechar, strict)

• export_neo4j_csv double-passed kwargs to both the constructor and export() (#665) by @KaifAhmad1

  • Constructor-level settings (node_file_name, relationship_file_name, encoding, delimiter, label_separator, strict) were merged into config for the constructor then re-forwarded as **kwargs to export_knowledge_graph, causing dialect params to collide; kwargs are now split into init_kwargs and call_kwargs before forwarding

• Dead node_id_lookup dict removed from _prepare_export (#665) by @KaifAhmad1

  • The {original_index → stable_id} mapping was built on every export but never consumed; removed to avoid misleading future readers

• Dropped ambiguous format="neo4j" alias from export_knowledge_graph dispatch (#665) by @KaifAhmad1

  • "neo4j" is used throughout the codebase to identify the live Bolt/Cypher graph store backend; routing it silently to the offline bulk-CSV exporter would have confused callers; only "neo4j_csv" and "neo4j-csv" are accepted

• export_usage.md documented non-existent constructor and function parameters (#665) by @KaifAhmad1

  • Examples showed node_label_sep (correct: label_separator), strict_validation (correct: strict), and nodes_path/rels_path kwargs that do not exist; all three examples corrected to match the actual API

• Public API Ingestion Support (#602) by @Luffy2208

  • Added PublicAPIIngestor class built on top of RESTIngestor for credential-free REST endpoints
  • Added PublicAPIExample and PublicAPIExamples catalog with 6 pre-configured no-auth examples:
    • jsonplaceholder_posts, jsonplaceholder_users, jsonplaceholder_todos — fake REST resources for testing
    • rest_countries_all — country reference data
    • data_gov_datasets — Data.gov CKAN catalog search
    • open_meteo_forecast — weather forecast (Berlin sample)
  • Added PublicAPIDetection dataclass for endpoint-level public/no-auth detection
  • Endpoint-level public API detection via detect_public_api() (informational, never raises)
  • No-auth validation: rejects Authorization, X-Api-Key, and all common auth headers before sending the request
  • Auth credential detection in URL query strings (api_key=, token=, access_token=, etc.)
  • Polite rate limiting with per-request and per-ingestor rate_limit_delay controls
  • Response parsing for JSON, CSV, and XML with response_format="auto" content-type detection
  • HTML response guard — text/html responses are never misclassified as XML
  • Nested record_path dot-notation extraction (e.g. "result.results" for Data.gov envelope)
  • _to_records normalization with automatic envelope unwrapping for items, data, results, records keys
  • batch_public_apis() for multi-endpoint ingestion with optional fail_fast
  • ingest_examples() for bulk example ingestion
  • sample_response() fixtures on PublicAPIExamples for mocked unit tests without live network calls
  • ingest_public_api() convenience function and ingest(..., source_type="public_api") unified dispatch
  • source_type="api" alias supported in ingest()
  • Registry integration: public_api and api task namespaces with endpoint, example, detect, batch, examples methods
  • Lazy-import exports of RESTIngestor, APIData, PublicAPIIngestor, PublicAPIExample, PublicAPIExamples, PublicAPIDetection from semantica.ingest
  • Documentation: updated docs/reference/ingest.md, docs/modules.md, and semantica/ingest/ingest_usage.md with full usage examples
  • 18 mocked tests covering JSON/CSV/XML parsing, nested record extraction, auth rejection, detection, string boolean config, batch dispatch, and unified ingest() routing
  • 3 optional-import tests covering defusedxml fallback path and import isolation without web-scraping backends

Fixed

• Public API XML parsing hardened against malicious payloads (#602) by @Luffy2208

  • Replaced stdlib xml.etree.ElementTree with defusedxml.ElementTree (XXE/entity-expansion safe); falls back to a hardened lxml parser (resolve_entities=False, no_network=True, load_dtd=False, huge_tree=False) when defusedxml is not installed
  • Added regression test asserting XXE entity payloads raise ProcessingError

• validate_no_auth config value not honoured when passed as a string (#602) by @Luffy2208

  • bool("false") evaluated to True, making validate_no_auth=False impossible via config files or environment variables; replaced with explicit _coerce_bool() that maps "false", "0", "no", "off" → False and rejects unrecognised strings with ValidationError

• Auth credential detection extended to URL query strings (#602) by @Sameer6305

  • detect_public_api() and ingest_public_api() now scan the endpoint URL itself for auth parameters (api_key, token, access_token, etc.) via urllib.parse.parse_qs, not only request headers and explicit params= dicts
  • Added regression tests for URL auth rejection (3 parametrized cases)

• ingest_examples and batch_public_apis mutable options mutation (#602)

  • Shared **options dict was passed by reference across loop iterations; mutable values such as params dicts were silently mutated after the first call, causing subsequent calls to receive a different (partially modified) options set; fixed by deep-copying options on each iteration

• rate_limit_delay forwarded twice in ingest_public_api method dispatcher (#602)

  • rate_limit_delay was consumed by the PublicAPIIngestor constructor via config but also leaked into request_kwargs forwarded to the ingestor method; added to the config_only_key strip list so it is consumed once at construction time only

• XML File Ingestion Support (#560) by @Luffy2208

  • Added XMLIngestor class with lxml backend for parsing local XML files
  • Nested element hierarchy and flat element list extraction
  • Namespace and prefix extraction with collision handling
  • Attribute and element metadata extraction
  • Optional XSD schema validation with detailed error reporting
  • Optional DTD validation (internal and external)
  • Secure-by-default parser (resolve_entities=False, no_network=True) blocking XXE attacks
  • ingest_xml() convenience function and ingest_file(..., method="xml") support
  • Unified .xml auto-detection via ingest("file.xml")
  • Directory ingestion with recursive scanning and fail_fast support
  • ingest_string() for in-memory XML bytes/str ingestion
  • Comprehensive test coverage (8/8 tests passing)

Fixed

• NERExtractor LLM method returning pattern-based output on custom gateways (#554, PR #556) by @KaifAhmad1

  NERExtractor(method="llm") silently fell back to regex/pattern extraction when used with OpenAI-compatible enterprise or self-hosted gateways (Qwen, LLaMA proxies, internal routing layers). Returned entities carried extraction_method='pattern' even though the LLM itself was producing correct tool-call output. Three root causes fixed:

  • Silent exception swallowing — exc_info=True was missing from the method-failure WARNING in NERExtractor.extract_entities. The full gateway-rejection traceback was invisible in logs even with DEBUG level enabled, making the failure impossible to diagnose without reading source code.

  • response_format=json_object sent to incompatible gateways — OpenAIProvider.generate_structured unconditionally included response_format={"type": "json_object"} in every API call. Custom/enterprise gateways frequently reject this parameter, causing both the instructor path and the manual repair loop to fail with the same error on every retry, eventually triggering _extract_fallback (pattern extraction).

  • No fallback in the generate_typed manual repair loop — when generate_structured itself raised (due to gateway rejection), the repair loop retried the identical failing call up to max_retries times before giving up. There was no path to recover via plain generate() + JSON parsing.

  Additional fixes applied during PR review:

  • Mode.JSON retry in generate_typed now strips response_format from create_kwargs before forwarding to the retry client, preventing incompatible kwargs from being sent to a client configured for a different instructor mode.
  • exc_info=True added to the generate_structured fallback warning in the manual repair loop for consistent observability across all failure paths.
  • Removed dead duplicate is_available definition in GroqProvider — Python silently kept only the second definition; the first was unreachable.
  • OpenAIProvider._init_client now validates base_url scheme at construction time. Non-HTTP(S) schemes (file://, ftp://, javascript:, etc.) raise ValueError immediately, preventing SSRF if base_url originates from configuration rather than hardcoded values.

  17 regression tests added in tests/test_issue_554_fixes.py covering all bug paths, including harshalizode's exact gateway configuration.

Security

• GitHub Actions workflow permissions hardened — added explicit permissions: contents: read + security-events: write block to defender-for-devops.yml, resolving CodeQL alert actions/missing-workflow-permissions (CWE: principle of least privilege).

• DOMPurify upgraded to 3.4.0+ via npm overrides — monaco-editor pinned dompurify at 3.2.7; added overrides in explorer/package.json to force ^3.4.0 (resolved to 3.4.10). Fixes 6 Dependabot alerts:

  • Prototype pollution → XSS bypass via CUSTOM_ELEMENT_HANDLING fallback (CVE-2026-41238 / GHSA-v9jr-rg53-9pgp)
  • Mutation-XSS via re-contextualization into raw-text wrappers (GHSA-h8r8-wccr-v5f2)
  • SAFE_FOR_TEMPLATES bypass in RETURN_DOM mode (CVE-2026-41239 / GHSA-crv5-9vww-q3g8)
  • ADD_TAGS function-predicate bypasses FORBID_TAGS (GHSA-39q2-94rc-95cp / GHSA-h7mw-gpvr-xq4m)
  • ADD_ATTR predicate skips URI validation, allowing javascript: URLs (GHSA-cjmm-f4jc-qw8r)
  • USE_PROFILES prototype pollution allows event handlers (GHSA-cj63-jhhr-wcxv)

• uuid upgraded to 13.0.1+ via npm overrides — bumped from 13.0.0 to 13.0.2, fixing missing buffer bounds check in v3/v5/v6 APIs that allowed silent partial writes into caller-provided buffers (CVE-2026-41907 / GHSA-w5hq-g745-h8pq).

• Vite upgraded from 5.x to 6.4.3 — resolves path traversal in optimised-deps .map handling (CVE-2026-39365 / GHSA-4w7w-66w2-5vf9) and the esbuild dev-server CORS issue (GHSA-4w7w-66w2-5vf9). Bundled esbuild updated from 0.21.5 → 0.25.12.

• esbuild forced to 0.28.1+ via npm override — vite 6.4.3 bundles esbuild 0.25.12 which is vulnerable to missing binary integrity verification in the Deno distribution module (GHSA-gv7w-rqvm-qjhr); added "esbuild": "^0.28.1" to overrides in explorer/package.json. npm audit now reports 0 vulnerabilities (Dependabot #15).

• Leaked Groq API keys removed from cookbook notebooks — 6 hardcoded GROQ_API_KEY values (gsk_...) stripped from configuration cells in supply_chain/01, intelligence/01, cybersecurity/01, cybersecurity/02, finance/01, and blockchain/02; fallback replaced with empty string (secret scanning alerts #1–#6). Keys were already publicly exposed — rotate them in the Groq console.

• Leaked Groq API keys removed from additional cookbook notebooks — 6 distinct hardcoded GROQ_API_KEY values stripped from 4 additional notebooks: advanced_rag/01_GraphRAG_Complete, advanced_rag/02_RAG_vs_GraphRAG_Comparison, blockchain/01_DeFi_Protocol_Intelligence, and biomedical/01_Drug_Discovery_Pipeline (secret scanning alerts #1–#6). Affected keys: gsk_SLLE0..., gsk_S4dBVJ..., gsk_SLOv6..., gsk_lR6Qcj..., gsk_ToJis6..., gsk_LmbQBr...; all publicly exposed since Dec 2025 — revoke in the Groq console and close the GitHub secret scanning alerts as "Revoked" in the Security tab.

---

[0.5.0] - 2026-05-11

Added

• Distance Intelligence Embedding Cache Optimization by @KaifAhmad1
  • Implemented per-session graph revision-based embedding cache to avoid re-scanning all nodes on every request
  • Added get_cached_embeddings() method to GraphSession with thread-safe caching and automatic invalidation
  • Updated distance matrix and semantic neighborhood endpoints to use cached embeddings for significant performance improvement
  • Added graph revision tracking using hash-based identifiers for cache invalidation
  • Implemented force refresh capability and automatic cache invalidation on graph modifications (add_nodes/add_edges)
  • Resolved TODO in graph.py for embedding caching optimization
• Parquet File Ingestion Support (#548) by @Luffy2208
  • Added ParquetIngestor class with PyArrow backend
  • Single file and partitioned directory ingestion
  • Schema and metadata extraction capabilities
  • Selective column reading with memory efficiency
  • Hive-style partition discovery support
  • Unified dispatch integration
  • Optional dependency management (ingest-parquet extra)
  • Comprehensive test coverage (32/32 tests passing)

Ontology Hub (part of #517)

• Alignments tab (PR #524, @KaifAhmad1 @ZohaibHassan16) — cross-ontology alignment authoring UI:

  • Create/edit/delete alignments with source URI, target URI, relation selector (owl:equivalentClass, all five skos:*Match variants), confidence slider, provenance, and reviewer fields.
  • Pairwise alignment matrix: scrollable table for all loaded ontology pairs; clicking a badge pre-fills the form.
  • Alignment suggestions via POST /api/ontology/suggest-alignments — blended score (0.4×label + 0.6×TF-IDF char-ngram cosine); one-click accept.
  • Ephemeral-storage banner; all handlers wrapped in useCallback.

• Health Dashboard (PR #524) — per-ontology quality scoring across 5 dimensions:

  • Completeness, Consistency, SHACL (stub), Alignment, Documentation.
  • Total score computed as mean of scoreable dimensions only (SHACL excluded when unavailable).
  • Issue list with severity badges (error/warning/info), entity URI chip, "Fix in Editor" deep-link.
  • Downloadable JSON health report; GET /api/ontology/health with _MAX_ANALYSIS_NODES = 5 000 OOM cap.

• SHACL Studio (PR #524) — interactive SHACL shape authoring:

  • Shape generation via POST /api/ontology/shacl/generate (permissive/standard/strict tiers).
  • Shape library panel with per-shape Turtle extraction; "View all" restores full document.
  • Monaco editor with custom Monarch tokenizer for Turtle syntax.
  • Validation stub via POST /api/ontology/shacl/validate; rejects empty/invalid Turtle with HTTP 422.

• Visual Ontology Editor (PR #519, @KaifAhmad1) — @xyflow/react canvas for authoring classes/properties/individuals without hand-writing OWL/Turtle:

  • Context menus on nodes (rename, add super/subclass, restrictions, SKOS metadata, deprecation, delete with impact count) and edges (toggle functional/symmetric/transitive/inverse-functional, add inverse).
  • All edits debounced and staged as pending diffs via PATCH /api/ontology/draft; nothing commits until proposal publish.

• Versions & Proposals tab (PR #519) — version timeline, proposal review (approve/reject/publish), SHACL pre-validation, side-by-side diff via VersionManager.diff_ontologies().

• Ontology Registry (PR #518, @KaifAhmad1) — full CRUD with status/format badges, per-ontology stats, live search, filter pills (All/OWL/SKOS/Internal/External), action feedback auto-hide.

• Ontology Loader (PR #518) — three-mode modal: URL import (fetch preview + load), file upload (.ttl/.rdf/.owl/.nt/.jsonld/.n3), create new (scratch/from-data/from-text).

• Entity Search panel (PR #518) — debounced 320 ms search across all loaded ontologies; type filter pills; result detail panel with super/subclasses, domain/range, instance count.

• SKOS Vocabulary Manager (PR #518) — hierarchical concept browser with recursive ConceptTreeNode, client-side filterConcepts(), full SKOS annotation detail (definition, scopeNote, broader/narrower/related/exactMatch).

• 16 backend endpoints under /api/ontology — registry, preview, load, create, search, entity, skos/schemes, skos/concept, draft, proposals CRUD, versions, alignments, health, shacl/generate, shacl/shapes, shacl/validate (PRs #518, #519, #524).

• Explorer landing page redesign (PR #516, @ZohaibHassan16) — hero section, animated SVG graph preview, live /api/graph/stats metrics, workspace launcher; Space Grotesk / IBM Plex Sans fonts; prefers-reduced-motion support.

• Distance Intelligence (PR #502, @KaifAhmad1):

  • ContextGraph.get_neighbors(include_distance_metadata) — adds distance_band, confidence_decay, path_to_anchor per result.
  • AgentContext.retrieve() / find_precedents() blend graph proximity with semantic score (combined_score = (1−w)×semantic + w×proximity).
  • 5 new API endpoints: POST /api/graph/distance-matrix (N×N, upper-triangle mirrored), GET /api/graph/node/{id}/semantic-neighborhood, GET /api/decisions/causal-distance, GET /api/temporal/distance-history, POST /api/export/distance-enriched (CSV/JSONL, capped at 200 nodes).
  • Explorer UI: Ego Mode (BFS depth-of-field fading, depth slider 1–8), Structural overlay, Semantic overlay, Heatmap (green→red by hop); Path inspector with distance band chip, metric cards, bottleneck node highlight.
  • 57 new tests in tests/context/test_distance_intelligence.py.

• Graph Explorer visual refresh (PR #503, @ZohaibHassan16) — structured ui.* design-token namespace; per-shape biomolecule/condition/compound config; decomposed toolbar memos; typed sub-components (SearchCommandBar, ToolbarCluster, etc.); deterministic LOD edge classification via GraphFullEdgeClass.

• Graph Workspace declutter (PR #483, @ZohaibHassan16) — calmer default presentation for dense graphs, display-edge aggregation with raw-edge bundle retention, grouped community view, neighborhood collapse/expand.

• Bidirectional path finding (closes #469, @KaifAhmad1) — directed=false query param on BFS and Dijkstra; undirected view built via graph.to_undirected() for traversal only; empty-path 404 guard; PathResponse.directed field.

• Node distance semantics in path responses (closes #472) — PathResponse gains hop_count and distance_band ("direct"/"near"/"mid-range"/"distant"); classify_path_distance() in semantica/utils/helpers.py; KGVisualizer.visualize_network(highlight_path) with band-scaled edge rendering.

• Native KnowledgeGraph type support in KGVisualizer (closes #471) — formal KnowledgeGraph dataclass (entities, relationships, metadata); _normalize_graph() duck-types input; raises clear ProcessingError on unknown types. 21 tests added.

• Indexed search for large graphs (PR #481, @ZohaibHassan16) — purpose-built inverted index with exact/token/prefix lookup tiers; LRU cache (128 slots); O(log n) mutation sync via bisect.insort; warm-query time 24 ms → 0.004 ms on 118 k-node graph.

• Provenance traversal multi-hop fix (PR #480, @Sameer6305) — undirected ego-graph expansion so upstream ancestors at depth ≥ 2 are no longer silently excluded; ProvenanceEdge.direction field (upstream/downstream/lateral); grouped markdown report under ## Upstream/Downstream/Lateral sections.

• TripletStore ontology namespace (PR #447, @KaifAhmad1) — _resolve_iri() applies base_uri before urn: fallback; W3C prefix expansion table (owl/xsd/rdf/rdfs/skos) expands to canonical IRIs regardless of base_uri.

• Blazegraph literal serialization (PR #448, @KaifAhmad1) — _format_object_for_sparql() selects IRI/typed-literal/language-tagged-literal/plain-literal token; _resolve_datatype_iri() with prefix expansion; RFC 5646 language-tag validation; _escape_literal() for string escaping.

• DeepSeek provider via OpenAI SDK (PR #482, @liling) — _init_client rewritten using openai.OpenAI(base_url=self.base_url) instead of defunct deepseek package; verbose_mode assignment fix; pyproject.toml updated to openai>=1.0.0.

• DuplicateDetector result limiting and ranking (issue #534, by @KaifAhmad1):

  • max_results — hard global cap on returned candidates; applied after sorting. None means no limit.
  • top_k_per_entity — keep at most k candidates per entity (by the sort field) so no single entity floods the output. None means no per-entity limit.
  • min_similarity — extra similarity floor on top of similarity_threshold; candidates below it are dropped before ranking. None means no extra floor.
  • sort_by — ranking field before limits are applied; accepts "confidence" (default) or "similarity_score". Invalid values raise ValueError at construction time.
  • All four options are applied by the new _apply_result_limits helper and are respected by both detect_duplicates() and incremental_detect().
  • 15 new tests in TestResultLimiting covering each option in isolation and in combination.
  • Follow-up Qodo review fixes (by @KaifAhmad1):
    • top_k_per_entity now uses OR semantics — a candidate is kept if either entity is still under quota, preventing high-quality pairs from being silently dropped when a popular counterpart saturates its limit.
    • max_results and top_k_per_entity now validated at construction time; negative or non-integer values raise ValueError.
    • min_similarity now validated in [0.0, 1.0] at construction; out-of-range values raise ValueError.
    • Added _normalize_entity_id helper (always returns str) used consistently in both _apply_result_limits and _build_duplicate_groups, eliminating int vs str ID key mismatches.
    • Updated detect_duplicates and incremental_detect docstrings to reflect the configurable sort_by field.

Fixed

• Fix: ConflictDetector.detect_conflicts() raises AttributeError when called with method= or property_name= kwargs (issue #533, PR conflicts, by @KaifAhmad1):

  • detect_conflicts was defined twice in conflict_detector.py; Python silently overwrote the first (dispatcher) definition with the second (comprehensive), which accepted no method or property_name parameters — causing AttributeError or TypeError for any caller using those kwargs.
  • Removed the first (dead) definition and merged its dispatcher logic into the surviving method. New signature: detect_conflicts(entities, method="all", property_name=None, entity_type=None, **kwargs).
  • Supported method values: "all" (default, comprehensive), "value", "property", "type", "relationship", "temporal", "logical", "entity". Unknown values raise ValueError.
  • Fixed method="relationship" silently defaulting relationships to the entities list, which caused entity dicts to be iterated as relationship dicts producing silent wrong results (None_None_None keys). Now defaults to [] with dict normalization.
  • Removed unreachable dead code (for field_name in fields_to_check loop after try/except raise) in detect_entity_conflicts.
  • Follow-up Qodo review fix — hardened method="relationship" normalization: when relationships kwarg is a dict whose "relationships" value is itself a non-list (or the key is absent), the value is now always wrapped in a list before being passed to detect_relationship_conflicts, guaranteeing List[Dict] input in all cases.

• Fix: semantica[all] installation fails on Windows due to faiss-gpu dependency (issue #532, PR #utlis, by @KaifAhmad1):

  • [all] bundled the [gpu] extra (faiss-gpu>=1.7.0, cupy>=10.0.0), which has no Windows builds, causing pip install "semantica[all]" to fail with No matching distribution found for faiss-gpu>=1.7.0.
  • Removed gpu from both [all] lines in pyproject.toml — [all] now installs only cross-platform dependencies. Users on Linux who need GPU acceleration can install semantica[gpu] explicitly.

• Fix: Progress tracker crashes with UnicodeEncodeError on Windows cp1252 consoles (issue #531, PR #utlis, by @KaifAhmad1):

  • ConsoleProgressDisplay.update() had 5 direct sys.stdout.write() calls that bypassed the existing _safe_write() guard, causing UnicodeEncodeError when emoji characters (🧠, 📊) were written to cp1252-encoded consoles during any progress-tracked operation.
  • All 5 calls replaced with self._safe_write(), which catches UnicodeEncodeError and re-encodes output with errors="replace" so progress output never crashes the process.
  • Added TestProgressTrackerEncoding regression class (3 tests) covering _safe_write safety, pipeline header write, and auto emoji-disable on cp1252 stdout.

• Fix: Break circular import in semantic_extract; address Qodo review bug (issue #528, PR #536, by @ZohaibHassan16, review fixes by @KaifAhmad1):

  • Root cause — ner_extractor.py imported get_entity_method from methods.py, while methods.py imported Entity from ner_extractor.py, creating a circular import that raised ImportError: cannot import name 'Entity' from partially initialized module on any import of semantica.semantic_extract.
  • semantica/semantic_extract/types.py (new) — shared Entity, Relation, and Triplet dataclasses extracted into a dedicated module that neither side of the old cycle imports, so both ner_extractor, relation_extractor, triplet_extractor, and methods can import from it freely.
  • semantica/semantic_extract/__init__.py — lazy-loads package-level exports so core extractor imports do not pull in optional modules (e.g. the YAML-backed semantic network extractor); added TripleExtractor as a compatibility alias for TripletExtractor; legacy re-exports from the individual extractor modules preserved for backward compatibility.
  • semantica/semantic_extract/methods.py — updated to import shared types from types.py; extractor-specific imports moved to function scope where needed to prevent re-introducing the cycle.
  • Added regression tests (tests/semantic_extract/test_imports.py) covering import order independence (methods-before-extractors and extractors-before-methods), legacy type import compatibility, TripleExtractor alias, and that core imports do not require yaml.
  • Review fix (Qodo — Py3.8 test import crash): test_imports.py annotated _run_python as -> subprocess.CompletedProcess[str], which is not subscriptable at runtime on Python 3.8 (generic subscript on built-in types requires 3.9+). Added from __future__ import annotations (PEP 563) so all annotations are lazy strings never evaluated at import time, restoring compatibility with the declared requires-python = ">=3.8" without any behaviour change on 3.9+.

• Fix: Lazy-load optional ingest backends; address Qodo review bugs (issue #527, PR #535, by @ZohaibHassan16, review fixes by @KaifAhmad1):

  • semantica/ingest/__init__.py — core exports (FileIngestor, ingest_file, config, registry) remain eagerly imported; all optional backends (WebIngestor, FeedIngestor, RepoIngestor, EmailIngestor, StreamIngestor, DBIngestor, MCPIngestor, OntologyIngestor, SnowflakeIngestor) are now deferred behind a module-level __getattr__, so from semantica.ingest import FileIngestor no longer fails when GitPython or BeautifulSoup4 are absent.
  • semantica/ingest/methods.py — backend imports relocated into their respective ingestion functions (ingest_web, ingest_feed, ingest_repository, ingest_email) with helper _missing_optional_dependency() / _is_missing_dependency() for consistent, actionable error messages.
  • Review fix (Bug 1 — overbroad missing-dep detection): replaced except ImportError with except ModuleNotFoundError in all four function-level import guards and in __getattr__. ImportError catches failures thrown by code inside a successfully found module, masking real bugs with a misleading "package not installed" message; ModuleNotFoundError (its subclass) is specific to absent modules. Simplified _is_missing_dependency to rely solely on exc.name now that ModuleNotFoundError always sets it.
  • Review fix (Bug 2 — expected errors logged as failures): added except ConfigurationError: raise before the blanket except Exception handlers in ingest_web, ingest_feed, ingest_repository, and ingest_email. Missing optional dependencies are expected user-configuration issues and must not produce error-level log entries.
  • Review fix (Bug 3 — test blocker not setting exc.name): OptionalDependencyBlocker.find_spec now sets err.name = root_name on the manually constructed ModuleNotFoundError, matching what Python's import machinery does, so _is_missing_dependency correctly identifies the missing package in tests.
  • Added regression tests (tests/ingest/test_optional_imports.py) that block the git and bs4 modules via a custom meta path finder and assert core imports succeed and backends raise ConfigurationError with an actionable message.

• Fix: Ontology Hub post-review bug fixes and security hardening (follow-up to #518, closes security advisory #23, by @KaifAhmad1):

  • Broken registry filters — fetchRegistry was sending toolbar filter values (owl, skos, internal, external) to the backend as the status query param, which only accepts published|draft|external, causing those filters to return empty lists. Removed the spurious status param; all format/kind filtering is now applied client-side via filteredEntries, which already had the correct logic.
  • Toggle/refresh URI corruption — toggle_ontology and refresh_ontology applied .removesuffix("/toggle") / .removesuffix("/refresh") to the captured path parameter, which would silently corrupt any ontology URI that legitimately ends with those strings. Starlette's route regex (/{uri:path}/toggle) already strips the literal suffix via backtracking, so the removesuffix calls were removed and the raw ontology_uri parameter is used directly.
  • SSRF in URL fetch — _fetch_url_sync() accepted arbitrary user-supplied URLs and called requests.get() with no validation, enabling server-side request forgery against internal services. Added _validate_fetch_url() which rejects non-http/https schemes and resolves the hostname via socket.getaddrinfo, blocking loopback, private, link-local, reserved, and multicast addresses.
  • File upload format misdetected — the file picker accepted .xml and .json but fmtMap had no entries for those extensions, causing them to default to turtle. Added xml: "xml" and json: "json-ld" mappings. Changed the unknown-extension fallback from || "turtle" to ?? "" (empty string), and omit the format key from the request body when empty so the backend _detect_format() runs instead of receiving a forced incorrect value. Also added .n3 to the accepted extension list and dropzone hint.
  • Inconsistent XML hardening — _parse_rdf_sync() called rdflib.Graph().parse() directly, bypassing the defusedxml-based XXE protection already present in semantica/explorer/utils/rdf_parser.py. Now routes through _safe_parse_rdf() from that module, applying consistent protection for all RDF/XML parse paths.
  • Search scans whole graph (GET /api/ontology/search) — the endpoint fetched up to 999 999 nodes and performed a linear Python substring scan on every request. Replaced with session.search(q, limit * 6) which uses the GraphSearchIndex; results are then post-filtered by _SEARCHABLE_TYPES and entity_type before being returned up to the requested limit.
  • ReDoS in format detector (security advisory #23, CodeQL py/polynomial-redos, CWE-1333/730/400) — _detect_format() used re.match(r"_:\w+|<[^>]+>\s+<[^>]+>", ...) to detect N-Triples content. The <[^>]+>\s+<[^>]+> alternative was flagged as a polynomial regular expression on uncontrolled data. The URI-subject branch was already unreachable (strings starting with < return "xml" two lines above), so the entire regex was replaced with two O(1) string operations: stripped.startswith("_:") and " <" in stripped. import re removed as now unused.

• OWLExporter Turtle syntax (closes #478) — invalid multi-block output fixed via _ttl_block(); data properties no longer silently dropped; _escape_ttl_str() applied to all label/comment/version sites. 43 tests added.

• OWLGenerator schema compatibility (Issue #446) — label-first IRI fallback, list-typed datatype ranges, per-call namespace consistency, subClassOf/subclassOf parity.

• TripletStore IRI regressions (PR #447 follow-up) — non-string IDs coerced to str(); W3C prefix expansion now correct regardless of base_uri.

• KGVisualizer accepts KnowledgeGraph objects (closes #458) — _normalize_graph() duck-types input; raises clear ProcessingError on unknown types. 21 tests added.

• Semantic Distance UI slash-safe routes (PR #515, @ZohaibHassan16) — query-param routes /api/graph/semantic-neighborhood?node_id= and /api/graph/path?source=&target= bypass FastAPI's %2F pre-decode; legacy path-segment routes kept as deprecated aliases.

• Explorer Distance Intelligence rendering (PR #513, @ZohaibHassan16) — distance state flows through Sigma reducer/theme pipeline instead of mutating raw graph attributes; restoreNodeColors() race eliminated by merging ego/heatmap useEffect hooks.

• Distance Intelligence code review regressions (PR #502 follow-up, @KaifAhmad1) — top_k param name fix; include_distance_metadata gated behind False default; weakest_link key standardized; temporal sampling uses timedelta not timetuple; O(E×L) decay replaced with O(E) index; AgentContext._apply_proximity_metadata stores graph_node_id separately; sweep animation sweepGeneration counter fix; HTTP 413 for >200 node subsets; upper-triangle distance matrix.

• Knowledge Explorer blockers (PR #420, @ZohaibHassan16):

  • Dockerfile: renamed DockerFile → Dockerfile; fixed CMD module path; added app = create_app() at module level.
  • CORS: default origins narrowed from "*" to localhost:5173 only.
  • get_ws_manager() now raises HTTP 503 instead of unhandled AttributeError.
  • SPARQL: read-only enforcement — INSERT/DELETE/UPDATE/LOAD/DROP rejected.
  • Vocabulary: 10 MB upload cap; JSON-LD format auto-detection for .jsonld/.json-ld/.json.
  • Annotation O(1) lookup via GraphSession.get_annotation(id).
  • Self-loop guard in batchMergeEdges prevents Graphology crash.
  • Static build artifacts removed from git; semantica/static/ added to .gitignore.

• Ontology Hub post-review hardening (PR #518 follow-up, @KaifAhmad1):

  • Registry filter: status param removed from fetchRegistry; filtering applied client-side.
  • Toggle/refresh URI: removed .removesuffix() calls that corrupted URIs ending with those strings.
  • Format detector: _detect_format() ReDoS eliminated — re.match replaced with two O(1) string ops.
  • Broken fmtMap entries: added xml/json mappings; unknown-extension fallback changed from || "turtle" to ?? "".
  • XML hardening: _parse_rdf_sync() now routes through _safe_parse_rdf() for consistent defusedxml XXE protection.
  • Search: replaced O(999 999) linear scan with GraphSearchIndex-backed session.search().

Security

• 12 vulnerability fixes (PR security-enhancement, @KaifAhmad1):
  • [CRITICAL — CWE-95] Eval injection in media_parser.py: replaced eval(ffprobe_output) with fractions.Fraction.
  • [CRITICAL — CWE-502] Pickle deserialization in agent_memory.py: replaced with JSON; legacy .pkl files detected and refused with migration message.
  • [HIGH — CWE-89] SQL injection in snowflake_ingestor.py: LIMIT/OFFSET parameterized; ORDER BY regex-validated; WHERE clauses containing semicolons rejected.
  • [HIGH — CWE-611] XXE in rdf_parser.py: defusedxml.defuse_stdlib() before all RDF/XML parsing.
  • [HIGH — CWE-346/200] Missing security headers in server.py: CORSMiddleware, X-Content-Type-Options, X-Frame-Options, HSTS, generic 500 handler.
  • [HIGH — CWE-346/400] Overpermissive CORS in explorer/app.py: methods/headers narrowed; 64 KB WebSocket frame cap.
  • [MEDIUM — CWE-20] Algorithm param unconstrained in graph.py: enum-validated bfs|dijkstra only.
  • [MEDIUM — CWE-434] RDF upload without extension check in vocabulary.py: .ttl/.rdf/.owl/.xml/.jsonld allowlist enforced.
  • [MEDIUM — CWE-1336] Prompt injection in llm_extraction.py: user-supplied content wrapped in json.dumps().
  • [MEDIUM — CWE-95] Dynamic __import__() in pipeline_validator.py: replaced with proper module-level import.
  • [MEDIUM — CWE-1333] ReDoS in enrich.py: whitespace-normalize then split on literal " AND ".
  • [LOW — CWE-22] Path traversal in server.py SPA route: Path.resolve().relative_to() guard; 400 on escape.
  • [LOW — CWE-400] Unbounded SPARQL in sparql.py: 5 000-row cap, 30 s asyncio.wait_for timeout, Semaphore(4) concurrency cap; SparqlResponse.truncated field added.
  • [LOW — CWE-434] Import upload in export_import.py: 50 MB cap; {.json,.csv} allowlist.
  • CodeQL paths-ignore for cookbook/**/*.html to suppress false-positive JS alerts #15–18.
• SSRF in Ontology Hub (PR #518 follow-up): _validate_fetch_url() rejects non-http/https schemes and resolves hostname via socket.getaddrinfo, blocking loopback/private/link-local/multicast addresses.

---

[0.4.0] - 2026-04-08

Added

Temporal Intelligence (@KaifAhmad1, PRs #396–#402)

• Core Temporal Data Model (PR #396) — semantica.kg.temporal_model with shared parsing/normalization/serialization helpers; TemporalBound and BiTemporalFact exported from semantica.kg; valid-time and transaction-time filtering; TemporalValidationError on invalid inputs; history-preserving revisions in TemporalVersionManager.apply_revision() with supersession semantics.
• Point-in-Time Query Engine (PR #397) — TemporalGraphQuery.reconstruct_at_time(graph, at_time) builds consistent point-in-time subgraphs without mutating source; TemporalConsistencyReport detects inverted intervals, relationships outside entity lifetimes, overlapping same-type relationships, and temporal gaps; sequence/cycle pattern detection; calendar-aligned evolution bucketing via temporal_granularity; causal ordering controls on find_temporal_paths() (strict/overlap/loose).
• Deterministic Temporal Reasoning Engine (PR #398) — semantica.kg.temporal_reasoning; full Allen interval algebra via IntervalRelation (all 13 relations); TemporalReasoningEngine with interval merging, gap analysis, coverage calculation, timelines, retroactive coverage; zero LLM calls; circular import risk between semantica.reasoning and semantica.kg eliminated.
• Temporal Awareness in ContextGraph (PR #399) — Decision dataclass gains valid_from/valid_until; superseded decisions remain in graph (immutable history); find_precedents_by_scenario(include_superseded, as_of); ContextGraph.state_at(timestamp) serializable snapshot; CausalChainAnalyzer.trace_at_time(event_id, at_time); AgentContext.checkpoint(label), diff_checkpoints(), flush_checkpoint().
• Temporal Metadata Extraction from Text (PR #400):
  • extract_relations_llm(extract_temporal_bounds=True) — each Relation gains valid_from, valid_until, temporal_confidence (0.0–1.0), temporal_source_text; default False is 100% backward-compatible.
  • Calibrated confidence anchors: 1.00 = full ISO date → 0.00 = no temporal signal.
  • TemporalNormalizer (zero LLM calls, pure regex + dateutil): normalize(value) → UTC datetime tuple or None; normalize_phrase(phrase) → metadata dict or None; 13-domain default phrase map; TemporalAmbiguityWarning for ambiguous DD/MM/YYYY inputs (never silently guesses locale).
• Temporal Provenance & OWL-Time Export (PR #401):
  • ProvenanceTracker.track_entity() auto-stamps recorded_at on every new record.
  • query_recorded_between(start, end), revision_history(fact_id), export_audit_log(fact_ids, format) (JSON/CSV).
  • RDFExporter.export_to_rdf(include_temporal=True, time_axis="valid|transaction|both") — emits OWL-Time triples for all temporally-annotated relationships.
  • create_snapshot() stamps "format_version": "1.0"; validate_snapshot() and migrate_snapshot() for stable snapshot lifecycle.
• Temporal GraphRAG Integration (PR #402) — TemporalGraphRetriever filters retrieved context to a point in time; ContextRetriever.query_with_reasoning(at_time, header_template) prepends structured temporal header; TemporalQueryRewriter extracts temporal intent (before/after/at/during/between) from natural language; regex-only by default, optional LLM-assisted mode.

Ontology (@KaifAhmad1 @ZohaibHassan16)

• SHACL Shape Generation & Validation (PR #318) — SHACLGenerator derives SHACL node/property shapes from any ontology dict; three quality tiers (basic/standard/strict); Turtle/JSON-LD/N-Triples output; iterative multi-level inheritance propagation, cycle-safe; OntologyEngine.to_shacl(), export_shacl(), validate_graph(explain=True); SHACLValidationReport with plain-English explanations for all 7 constraint types. pip install semantica[shacl].
• SKOS Vocabulary Module (PR #319) — TripletStore.add_skos_concept() / get_skos_concepts(scheme_uri); OntologyEngine.list_vocabularies(), list_concepts(), search_concepts(); NamespaceManager.get_skos_uri() / build_concept_scheme_uri(); SPARQL injection hardened.
• Ontology Alignment API (PR #361) — OntologyEngine.create_alignment(), get_alignments(), list_alignments(); OWL/SKOS standard predicates (owl:equivalentClass, all five skos:*Match); ReuseManager.suggest_alignments(); QueryEngine.expand_entity_uri(use_alignments=True) with SPARQL VALUES clause injection; SPARQL injection hardened.
• Ontology Diff & Migration (PR #367) — VersionManager.diff_ontologies() covering classes/properties/individuals/axioms; ChangeLogAnalyzer.analyze() classifying CRITICAL/HIGH/MEDIUM/INFO impact; ImpactReport, generate_change_report(); OntologyEngine.compare_versions() end-to-end orchestrator with optional validation and graph-instance checks.

Knowledge Explorer API (@ZohaibHassan16 @KaifAhmad1)

• Full FastAPI backend (PR #384) — semantica.explorer package with graph, analytics, decisions, temporal, enrichment, export/import, annotations routes; 12 export formats; WebSocket progress for import; 99 integration tests. pip install semantica[explorer]; CLI: semantica-explorer --graph my_graph.json.
• Thread safety (PR #385) — ContextGraph and GraphSession protected with threading.RLock; 8 analytics components lazily initialized under lock.
• In-memory fallbacks (PR #386) — All 7 DecisionQuery and 4 DecisionRecorder methods have ContextGraph fallback paths for in-memory usage without a graph DB.
• Snapshot schema compatibility (PR #393) — accepts both nodes/edges and entities/relationships snapshot schemas transparently; metadata counts always accurate.
• Audit trail & rollback protection (PR #394) — mutation-level audit tracking, named version tags, restore_snapshot() requires explicit confirmation, get_node_history(), diff() Git-like alias.
• SKOS Vocabulary REST API (PR #426) — GET /api/vocabulary/schemes, GET /api/vocabulary/hierarchy?scheme=<uri> with cycle detection, POST /api/vocabulary/import (.ttl/.rdf/.owl; HTTP 422 on invalid).
• O(N) → O(limit) Pagination (PR #431) — find_nodes/find_edges use itertools.islice on generators; ghost-node fix (accepts source_id/target_id and source/target key names); deterministic page boundaries via sorted(); stats() applies same validity filters as pagination.
• Named graph support (PR #432, @Sameer6305) — enable_named_graphs flag forwarded correctly through TripletStore.execute_query(); duplicate FROM/FROM NAMED clauses prevented; graph URIs percent-encoded in DROP statements.

Integrations

• Agno Agentic Framework (Issue #249, @KaifAhmad1) — 5 components, all degrading gracefully when agno is not installed:
  • AgnoContextStore — graph-backed agent memory implementing agno.memory.db.base.MemoryDb.
  • AgnoKnowledgeGraph — multi-hop GraphRAG knowledge base implementing agno.knowledge.base.AgentKnowledge.
  • AgnoDecisionKit — 6 decision-intelligence tools (record_decision, find_precedents, trace_causal_chain, analyze_impact, check_policy, get_decision_summary).
  • AgnoKGToolkit — 7 KG pipeline tools (extract_entities, extract_relations, add_to_graph, query_graph, find_related, infer_facts, export_subgraph).
  • AgnoSharedContext — team coordinator with single shared ContextGraph; bind_agent(role) returns role-scoped view; thread-safe via RLock.
  • 110 integration tests; 3 cookbook notebooks. pip install semantica[agno].
• Novita AI Provider (PR #374, @Alex-wuhu) — OpenAI-compatible; default model deepseek/deepseek-v3.2; NOVITA_API_KEY; create_provider("novita").

Reasoning

• Native Datalog Reasoning Engine (PR #371, @ZohaibHassan16) — pure-Python bottom-up semi-naive fixpoint with guaranteed termination; recursive Horn clause rules (e.g. ancestor(X,Y) :- parent(X,Z), ancestor(Z,Y).); O(1) delta-index lookup; load_from_graph(ContextGraph); query("pred(?X, ?Y)") with optional bindings=; DatalogReasoner, DatalogFact, DatalogRule exported from semantica.reasoning.

Fixed

• Pattern Matcher restored (PR #387, @ZohaibHassan16) — dead code silently overwrote _match_pattern regex (pre-bound variable embedding, repeated-variable backreferences) with re.escape, breaking transitivity/symmetry/self-join rules; removed. re.error now surfaced instead of swallowed.
• OllamaProvider base_url ignored (PR #408, @AlexeyMyslin) — ollama.Client(host=self.base_url) instead of raw module assignment; remote Ollama servers now reachable.
• spaCy runtime fallback — NERExtractor now catches runtime initialization failures, not just missing-model errors.
• CentralityCalculator crash — _build_adjacency() handles both ContextGraph dataclass edges (source_id/target_id) and plain dicts.
• find_path always used BFS (PR #384) — algorithm query param now correctly dispatched to dijkstra_shortest_path or bfs_shortest_path.
• Event loop blocked in /api/enrich/links (PR #385) — score_link scoring loop wrapped in asyncio.to_thread.
• Temp file leak in export_graph (PR #384) — try/finally cleanup for all error paths.
• ChangeCategory enum typo (PR #367) — "potenitally_breaking" → "potentially_breaking".
• DecisionQuery/DecisionRecorder fallbacks (PR #386) — type() guard instead of isinstance() for Mock safety; flat property storage in _store_decision_node; spurious properties={} kwarg removed; tz-aware/naive datetime mismatch resolved; find_edges() hoisted out of BFS loop (O(nodes×edges) → O(1) per call).
• Snapshot schema (PR #393) — silent restore failures when nodes/edges schema didn't match legacy entities/relationships expectations.
• Context explainability (@KaifAhmad1) — decision nodes now store full scenario/reasoning text; causal/precedent reconstruction returns enriched Decision objects; PolicyEngine.get_affected_decisions() consistent across Cypher and fallback branches.

Security

• CWE-312/359/532 — Removed api_key debug print blocks from relation_extractor.py and triplet_extractor.py.
• CWE-20 — URL sanitization: "url" in urls replaced with any(url == "url" for url in urls), eliminating substring match.
• CI overpermissions — permissions: contents: read added to benchmark.yml and security.yml.
• SHACL path traversal (PR #318) — replaced len < 500 and "\n" not in s heuristic with os.path.exists().
• SHACL inheritance mutation (PR #318) — _propagate_inheritance uses dataclasses.replace() instead of appending parent PropertyShape objects by reference.
• SPARQL injection (PR #361) — search_concepts, list_alignments, build_values_clause fully hardened.

---

[0.3.0] - 2026-03-10

Added

• Context Graph Feature Completeness (@KaifAhmad1):
  • ContextNode / ContextEdge gain valid_from / valid_until with is_active(at_time) -> bool.
  • ContextGraph.find_active_nodes(node_type, at_time) — temporal node filtering.
  • get_neighbors(min_weight) — confidence-filtered BFS (default 0.0 passes all edges).
  • link_graph() / navigate_to() / resolve_links(registry) — cross-graph navigation with full save/load round-trip.
  • graph_id UUID field persisted to JSON.

Fixed

• is_active() tz-aware/naive datetime normalization.
• valid_from/valid_until serialization in add_nodes(), add_edges(), to_dict(), from_dict().
• Cross-graph link phantom-node prevention in link_graph().
• pipeline_builder.add_step() return type annotation.
• test_hybrid_search_performance timing computation; threshold raised to < 5.0 s.
• ProvenanceTracker added to semantica/kg/__init__.py exports.
• Duplicate relation creation in _parse_relation_result — orphaned legacy block removed.
• extraction_method parameter added; typed path now correctly sets "llm_typed".
• Cross-test cache pollution in test_retry_logic.py — _result_cache.clear() added to setUp().
• 14 tests in tests/context/test_cross_graph_navigation.py; 85 real-world tests in tests/test_030_realworld_comprehensive.py.

---

[0.3.0-beta] - 2026-03-07

Added

• Multi-Founder LLM Extraction (PR #354, @KaifAhmad1):
  • _parse_relation_result: unmatched subjects/objects produce a synthetic UNKNOWN entity instead of being silently dropped.
  • _match_pattern rewritten: splits on ?var placeholders, pre-bound variable resolution, repeated-variable backreferences.
• TTL Export Aliases (PR #355, @KaifAhmad1) — format="ttl"/"nt"/"xml"/"rdf"/"json-ld" resolve correctly before format validation; 8 tests in tests/export/test_rdf_exporter.py.
• Incremental/Delta Processing (PR #349, @ZohaibHassan16) — native delta computation between graph snapshots via SPARQL, delta-aware pipeline execution (delta_mode), snapshot retention with prune_versions(), significant performance improvements for near real-time pipelines.
• Deduplication v2:
  • Candidate Generation v2 (PR #338, @ZohaibHassan16) — multi-key blocking, phonetic (Soundex) blocking, deterministic candidate budgeting; 63.6% faster (0.259 s → 0.094 s for 100 entities).
  • Two-Stage Scoring Prefilter (PR #339, @ZohaibHassan16) — type mismatch, length ratio, token overlap gates; 18–25% faster batch processing.
  • Semantic Relationship Deduplication v2 (PR #340, @ZohaibHassan16) — predicate synonym mapping (works_for → employed_by), O(1) hash matching, weighted scoring (60% predicate + 40% object); 6.98x speedup (~83 ms vs ~579 ms).
  • Migration Guide (PR #344, @ZohaibHassan16) — comprehensive MIGRATION_V2.md; critical infinite recursion bug in dedup_triplets() fixed.
• ArangoDB AQL Export (PR #342, @tibisabau) — AQL INSERT generation, configurable collections, batch processing (default 1 000), .aql auto-detection, 17 tests.
• Apache Parquet Export (PR #343, @tibisabau) — columnar storage, configurable compression (snappy/gzip/brotli/zstd/lz4/none), explicit Arrow schemas, .parquet auto-detection, 25 tests.

Fixed

• Test Suite Fixes (@KaifAhmad1):
  • Context: entity extraction gated on use_hybrid_search=True; _extract_entities_from_query uses word[0].isupper(); added expand_context BFS method; hybrid_retrieval and multi_hop_context_assembly corrected; vector result fallback to metadata["content"].
  • KG: calculate_pagerank aliases; community_detector._to_networkx no longer silently loses edges; _build_adjacency handles both "edges" and "relationships" keys; 9 tracking methods added to AlgorithmTrackerWithProvenance.
  • Pipeline: retry loop honours max_retries; FailureHandler.handle_failure() added; add_step return type fixed; validate alias added; error message standardized.
  • Tests: emoji replaced with ASCII for Windows cp1252 compatibility.
• NameError: missing Type import in utils/helpers.py.

---

[0.3.0-alpha] - 2026-02-19

Added

• Decision Tracking System — complete lifecycle management (record → analyze → query → precedent → influence) with audit trails and provenance tracking.
• Advanced KG Algorithms — Node2Vec embeddings, centrality analysis, community detection for decision insights.
• Enhanced Context Module — unified AgentContext with granular feature flags for decision tracking, KG algorithms, and vector store features.
• Vector Store Features — hybrid search combining semantic, structural, and category similarity.
• Policy Management — versioning, compliance checking, and exception handling.
• Context Engineering Enhancement (PR #307, @KaifAhmad1) — full decision tracking, hybrid search, PolicyException model, GraphStore validation, explainable AI features, 9 critical bug fixes, 100% test coverage (9/9).
• PgVector Store Support (PR #303, @Sameer6305 @KaifAhmad1) — HNSW/IVFFlat indexing, JSONB metadata filtering, psycopg3/psycopg2 fallback, SQL injection protection via psycopg_sql.SQL(), 36+ tests.
• Apache AGE Backend (PR #311, @Sameer6305) — AgeStore with GraphStore API compatibility, SQL injection protection.
• Improved Vector Store for Decision Tracking (PR #293, @KaifAhmad1) — DecisionEmbeddingPipeline, HybridSimilarityCalculator (0.7 semantic + 0.3 structural), DecisionContext, ContextRetriever with multi-hop reasoning; 34+ tests.
• Improved Graph Algorithms (PR #292, @KaifAhmad1) — 30+ algorithms across 7 categories (Node2Vec, Dijkstra, A*, PageRank, Louvain, Leiden, etc.), unified provenance tracking with GraphBuilderWithProvenance / AlgorithmTrackerWithProvenance.
• ResourceScheduler Deadlock Fix (PRs #299 #301, @d4ndr4d3 @KaifAhmad1) — threading.Lock → threading.RLock; allocation validation; leak prevention on failure; 6 regression tests.
• Dependabot & Security Automation — bi-weekly security updates, automated Bandit/Safety/Semgrep scans, security-critical package grouping.

Fixed

• Context Graphs decision tracking bugs (PR #315, @KaifAhmad1): empty/None decision ID, None metadata, causal chain depth logic, nonexistent node handling, to_dict/from_dict round-trip.
• PolicyEngine latest version selection; AgentContext fallback robustness and secure logging.
• Import issues in test suite (ProvenanceTracker location); causal analyzer max_depth bounds.

---

[0.2.7] - 2026-02-09

Added

• Snowflake Connector (PR #276, @Sameer6305) — multi-auth (password/OAuth/key-pair/SSO), table and query ingestion, SQL injection prevention, progress tracking, 24 tests. pip install semantica[db-snowflake].
• Apache Arrow Export (PR #273, @Sameer6305) — explicit Arrow schemas, entity/relationship export, Pandas/DuckDB compatible, 20 tests.
• Benchmark Suite (PR #289, @ZohaibHassan16 @KaifAhmad1) — 137+ benchmarks across all 10 modules, Z-score statistical regression detection, GitHub Actions workflow. CLI: python benchmarks/benchmark_runner.py.

---

[0.2.6] - 2026-02-03

Added

• W3C PROV-O Provenance Tracking (Issues #254 #246, @KaifAhmad1):
  • Comprehensive provenance across all 17 Semantica modules; InMemory/SQLite backends; SHA-256 integrity.
  • FDA 21 CFR Part 11, SOX, HIPAA, TNFD compliance infrastructure.
  • 237 tests; opt-in (provenance=False by default).
• Enhanced Change Management (Issues #248 #243, @KaifAhmad1):
  • TemporalVersionManager and OntologyVersionManager with SQLite/in-memory backends; SHA-256 checksums; detailed diffs.
  • 104 tests; 17.6 ms for 10 k entities; 510+ ops/sec concurrent.
• CSV Ingestion Enhancements (PR #244, @saloni0318) — auto-detect encoding (chardet) and delimiter (csv.Sniffer); tolerant decoding; optional chunked reading.
• Ingest Unit Tests (Issues #239 #232, @Mohammed2372) — file, web, and feed ingestors; 998 lines of tests; 80–86% coverage.
• TextNormalizer comprehensive unit tests (PR #242, @ZohaibHassan16).

Fixed

• Temperature Compatibility (Issues #256 #252, @F0rt1s @IGES-Institut) — temperature=None now omits parameter so APIs use model defaults; _add_if_set helper applied to all 5 providers; 10 tests.
• JenaStore Empty Graph (Issues #257 #258, @ZohaibHassan16) — if self.graph is None: replaces implicit falsy check in 5 methods.

---

[0.2.5] - 2026-01-27

Added

• Pinecone Vector Store (closes #219 #220) — serverless and pod-based indexes, namespace support, metadata filtering, unified VectorStore integration.
• Configurable LLM Retry Logic — max_retries parameter (default 3) in NERExtractor, RelationExtractor, TripletExtractor, and all extract_*_llm methods.
• Bring Your Own Model (BYOM) — custom HuggingFace models in all extractors; custom tokenizer support; runtime model= overrides config defaults.
• Enhanced NER — configurable aggregation strategies (simple/first/average/max); IOB/BILOU parsing for raw model outputs; confidence scoring.
• Relation Extraction — entity marker technique (<subj>/<obj> tags) for sequence classification models; structured output parsing.
• Triplet Extraction — Seq2Seq model support (REBEL) for direct structured triplet generation from text.

Fixed

• LLM extraction: strict max_retries enforcement prevents infinite retry loops.
• Model parameter precedence: runtime arguments now correctly override config defaults in HuggingFace extractors.
• Circular imports in test suites.

---

[0.2.4] - 2026-01-22

Added

• Ontology Ingestion Module — OntologyIngestor for Turtle/RDF-XML/JSON-LD/N3 files; ingest_ontology() convenience function; recursive directory scanning; OntologyData dataclass; integrated into ingest(source_type="ontology").

---

[0.2.3] - 2026-01-20

Added

• Amazon Neptune dev environment — CloudFormation template; cfn-lint in pre-commit.
• Vector Store high-performance ingestion — VectorStore.add_documents() with batching and parallel processing (max_workers=6); VectorStore.embed_batch() helper.
• LLM relation extraction tests (mocked and Groq integration).

Changed

• Simplified relation extraction parameter interface; improved error handling and verbose logging.
• Standardized VectorStore concurrency defaults; implicit max_workers=6 in examples.

Fixed

• LLM Relation Extraction Parsing — normalized typed responses to consistent dict format before parsing; structured JSON fallback; extra kwargs removed from internals.
• Pipeline Circular Import (Issues #192 #193) — lazy-loaded PipelineValidator inside PipelineBuilder.__init__; TYPE_CHECKING guard.
• JupyterLab Progress (Issue #181) — SEMANTICA_DISABLE_JUPYTER_PROGRESS env var suppresses rich progress tables.

---

[0.2.2] - 2026-01-15

Added

• Parallel Extraction Engine — concurrent.futures.ThreadPoolExecutor across all extractors (NERExtractor, RelationExtractor, TripletExtractor, EventDetector, SemanticNetworkExtractor); max_workers parameter; thread-safe ProgressTracker.
• Semantic extract regression suite; real-use-case benchmark script.

Changed

• Gemini SDK Migration — google-genai SDK with google.generativeai fallback.
• Pinned opentelemetry-api/-sdk to 1.37.0; updated protobuf/grpcio constraints.
• Entity filtering applied only to LLM prompt construction, not non-LLM flows.
• Raised global optimization.max_workers default to 8.

Security

• Credential sanitization — hardcoded API keys removed from 8 notebooks; ExtractionCache excludes api_key/token/password from cache keys; cache key hashing upgraded MD5 → SHA-256.

Performance

• ~1.89× speedup via parallel extraction (Groq llama-3.3-70b-versatile, standard datasets).
• Optimized entity matching: exact/substring/word-boundary fast paths before embedding similarity.

---

[0.2.1] - 2026-01-12

Fixed

• LLM Output Stability (Bug #176) — correct max_tokens propagation; automatic chunk-halving and retry on context/output limit errors.
• Removed hardcoded max_length constraints from Entity, Relation, Triplet.
• Orchestrator lazy property initialization and configuration normalization.
• AssertionError in orchestrator tests (mock alignment).
• Pinned protobuf>=5.29.1,<7.0, grpcio>=1.71.2; added GitPython and chardet to pyproject.toml.

Changed

• Increased default max_text_length to 64 000 characters for all major providers.
• Standardized Groq defaults: llama-3.3-70b-versatile, 64 k context, native max_tokens/max_completion_tokens.

---

[0.2.0] - 2026-01-10

Added

• Amazon Neptune Support — AmazonNeptuneStore via Bolt/OpenCypher; NeptuneAuthTokenManager with AWS IAM SigV4 signing; retry/backoff. pip install semantica[graph-amazon-neptune].
• Docling Integration — DoclingParser for PDF/DOCX/PPTX/XLSX/HTML/image parsing; OCR support; Markdown/HTML/JSON export.
• Robust Extraction Fallbacks — ML/LLM → Pattern → Last Resort chains across all extractors.
• Provenance & Tracking — batch_index and document_id metadata on all extracted items.
• Semantic Extract — auto-chunking for long text; silent_fail parameter; JSON parsing with 3-attempt exponential backoff.
• End-to-end KG pipeline integration tests; TextEmbedder model switching tests.

Changed

• Removed internal dedup logic from extractors (deferred to semantica/conflicts).
• Standardized batch processing across all extractors using unified extract/analyze/resolve pattern.
• Clarified weighted confidence scoring (50% Method Confidence + 50% Type Similarity).

Fixed

• NameError in extraction_validator.py (missing Union import).
• Extractors returning empty lists for valid input when primary methods fail.
• Model switching bug in TextEmbedder (state not cleared on model switch). (Issue #160)
• TypeError: unhashable type: 'Entity' in GraphAnalyzer. (Issue #159)
• Pinned protobuf==4.25.3, grpcio==1.67.1.
• TripletExtractor.validate_triplets shadowed by internal attribute.
• Incorrect TextSplitter import path.

---

[0.1.1] - 2026-01-05

Added

• Exported DoclingParser and DoclingMetadata from semantica.parse.
• Windows-specific troubleshooting note for PyTorch DLL issues.

Fixed

• DoclingParser import/export across platforms (Windows, Linux, Google Colab).
• Error messaging when optional docling dependency is missing.
• Versioning inconsistencies across the framework.

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[0.1.0] - 2025-12-31

Added

• Command-line interface (semantica CLI) with knowledge base building and info commands.
• FastAPI-based REST API server for remote access.
• Background worker component for scalable task processing.
• Framework-level versioning configuration for PyPI distribution.
• Automated release workflow with Trusted Publishing support.

Changed

• Updated versioning across the framework to 0.1.0.
• Refined entry point configurations in pyproject.toml.
• Improved lazy module loading for core components.

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[0.0.5] - 2025-11-26

Changed

• Configured Trusted Publishing for secure automated PyPI deployments.

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[0.0.4] - 2025-11-26

Changed

• Fixed PyPI deployment issues from v0.0.3.

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[0.0.3] - 2025-11-25

Added

• Comprehensive issue templates (Bug, Feature, Documentation, Support, Grant/Partnership).
• Updated pull request template with clear guidelines.
• Community support documentation (SUPPORT.md).
• Funding and sponsorship configuration (FUNDING.yml).
• 10+ domain-specific cookbook examples (Finance, Healthcare, Cybersecurity, etc.).

Changed

• Simplified CI/CD workflows — removed failing tests and strict linting.
• Combined release and PyPI publishing into single workflow.
• Simplified security scanning to weekly pip-audit only.

Removed

• Redundant scripts folder (8 shell/PowerShell scripts).
• Unnecessary automation workflows (label-issues, mark-answered).
• Excessive issue templates.

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[0.0.2] - 2025-11-25

Changed

• Updated README with streamlined content and better examples.
• Added more notebooks to cookbook.
• Improved documentation structure.

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[0.0.1] - 2024-01-XX

Added

• Core framework architecture.
• Universal data ingestion (multiple file formats).
• Semantic intelligence engine (NER, relation extraction, event detection).
• Knowledge graph construction with entity resolution.
• 6-stage ontology generation pipeline.
• GraphRAG engine for hybrid retrieval.
• Multi-agent system infrastructure.
• Production-ready quality assurance modules.
• Comprehensive documentation with MkDocs.
• Cookbook with interactive tutorials.
• Multiple vector store backends (Weaviate, Qdrant, FAISS).
• Multiple graph database backends (Neo4j, NetworkX, RDFLib).
• Temporal knowledge graph support.
• Conflict detection and resolution; deduplication and entity merging.
• Schema template enforcement; seed data management.
• Multi-format export (RDF, JSON-LD, CSV, GraphML).
• Visualization tools; pipeline orchestration.
• Streaming support (Kafka, RabbitMQ, Kinesis).
• Context engineering for AI agents; reasoning and inference engine.

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Types of Changes

Label	Meaning
Added	New features
Changed	Changes in existing functionality
Deprecated	Soon-to-be removed features
Removed	Removed features
Fixed	Bug fixes
Security	Vulnerability fixes
Performance	Performance improvements

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For detailed release notes, see GitHub Releases.