* feat(crewai): add first-class CrewAI integration (#962)
Add native CrewAI support so Crew agents can share a ContextGraph and
AgentContext via BaseTool subclasses and a BaseKnowledgeSource, matching
the existing agno integration pattern.
- SemanticaKGTool: 5 KG actions (extract_entities, extract_relations,
add_to_graph, query_graph, find_related) with sync run()/async arun()
- SemanticaDecisionTool: 5 decision-intelligence actions
(record_decision, find_precedents, trace_causal_chain,
analyze_impact, check_policy) over AgentContext
- SemanticaKnowledgeSource: serializes a ContextGraph into crew
knowledge storage; bridges legacy load_content() and current
validate_content()/aadd() contracts for crewai>=0.80.0
- All classes degrade gracefully when crewai is absent
- New pip extra crewai=... included in the all bundle
- 70 new tests (stub-based present-case + subprocess degradation path)
- Docs: integrations/crewai.md, docs.json nav, README matrix updates
* fix(crewai): harden tools against real Semantica dataclass shapes (#962)
Bugs found during live testing with crewai 1.15.16:
- SemanticaKGTool.add_to_graph crashed on real Entity/Relation dataclasses
('str' object has no attribute 'end_char'): string names were passed to
extract_relations(entities=...), which requires Entity objects, and the
tool read .name/.source/.target instead of Entity's .text/.label and
Relation's .subject/.object. Add shape-agnostic field helpers.
- SemanticaDecisionTool() created an AgentContext without a knowledge_graph,
so _decision_backend was never set and record_decision raised 'Decision
tracking is not enabled'. Wire in a ContextGraph.
- record_decision hard-failed when the agent omitted optional fields; fall
back to category='general', reasoning='agent decision',
outcome='recorded'.
Add tests covering real Entity/Relation dataclass shapes and the live
auto-created AgentContext path (now 77 crewai tests, 212 total).
* fix(crewai): make find_related traverse edges undirected (#962)
ContextGraph.get_neighbors only follows outgoing edges, so a node whose
only edge is incoming (A -> B) reported no related concepts. Rebuild a
bidirectional adjacency from find_edges() in SemanticaKGTool._find_related
so 'related' honors both directions.
* fix(crewai): harden tools for checkpoint serialization and correct action semantics (#962)
- Exclude live graph/context/extractor state from JSON serialization
(model_dump(mode="json")) so CrewAI checkpointing no longer raises
PydanticSerializationError; model_post_init self-heals defaults on restore
- query_graph now searches node content via graph.query() plus id/type
- trace_causal_chain returns an explicit error when causal tracing is
unavailable instead of substituting similarity precedents; call
trace_decision_causality(..., max_depth=...) with the correct kwarg name
- find_precedents propagates max_precedents/limit to the backend instead of
being silently capped at 10
- Serialize add_to_graph batches under a module lock to prevent concurrent
double-counting; skip nameless entities instead of creating repr()-junk nodes
- aadd() runs CPU-bound serialization in a thread executor
- Mirror crewai args_schema serialize/restore in the conftest stub and add
serialization regression tests (crewai: 92 tests)
* fix(crewai): correct check_policy coercion, guard causal tracing, and harden concurrency (#962)
- _eval_rule now coerces rule values type-aware: bool("false") was truthy, so
'enabled == false' reported a violation for enabled=false, and string datums
like "0.90" were compared lexicographically instead of numerically
- _trace_causal_chain no longer raises AttributeError (which escaped _run) when
the decision context lacks knowledge_graph; returns honest error JSON
- SemanticaKnowledgeSource storage failures log an actionable ERROR; without a
configured crew embedder agents previously retrieved nothing silently
- add_to_graph uses a per-graph re-entrant lock (WeakKeyDictionary) instead of a
process-global one: independent graphs no longer serialize each other and
re-entrant extractor callbacks cannot deadlock
- entity/relation confidence=None normalizes to 1.0 instead of failing the
whole extraction with float(None)
- add subprocess integration test against real crewai covering Crew-level
serialization round-trip and checkpoint restore (stub tests cannot see it)
- docs: embedder requirement for SemanticaKnowledgeSource; resume contract note
* fix(crewai): surface knowledge-source save failures at ERROR when storage is wired (#962)
Re-verification against real crewai showed the embedder-missing failure raises
ValueError even though storage IS wired, so the old except-ValueError branch
mislabeled it as 'storage not wired' and logged DEBUG — hiding the failure.
Distinguish by storage presence instead of exception type: storage is None ->
DEBUG keep-in-memory (legitimate standalone use); storage wired but save()
raises -> actionable ERROR. Add regression test mirroring real crewai's
ValueError-on-missing-embedder behavior.
* fix(crewai): expose run()/arun() entry points in degraded mode (#962)
The public crewai contract is run()/arun(); without crewai installed they were
missing (only the private _run existed), so the documented 'usable without
crewai' path raised AttributeError at the entry point. Define them in degraded
mode only, leaving crewai's BaseTool implementations untouched when present.
Extend the degradation subprocess test to exercise run() and arun().
* fix(crewai): standardize query shape, field-name rules, and restore-state flag
- _query_graph: id/type matches now return the same schema as content
matches (id/type/label/content/score) instead of a bare list
- _eval_rule: non-greedy field capture so hyphen/dot/space JSON keys
(e.g. "risk-score >= 0.9") are addressable in policy rules
- add had_live_state/reconstructed_state so checkpoint-restored tools
and knowledge sources signal that their live graph/context was lost
and an empty one reconstructed; knowledge source no longer hides the
loss by eagerly rebuilding its graph inside __init__ (pydantic calls
__init__ during model_validate)
* fix(crewai): address Qodo review — confidence errors, string trim, holistic availability
- record_decision: stop calling float() in _run, so malformed confidence
values surface as JSON errors (via _record_decision's handling) instead
of crashing the tool
- _coerce_value: return the stripped string for non-numeric literals so
whitespace-padded decision_data fields match policy rules
- centralize crewai availability in _availability.py so the exported
CREWAI_AVAILABLE flag is holistic across tools and knowledge source
(previously each module probed crewai independently and the package
flag came from decision_tool only)
* ci: regenerate requirements-ci.txt for the crewai extra
The crewai extra in pyproject.toml brings in crewai, crewai-tools and
transitive deps (chromadb, lancedb, ...). Recompile with
uv==0.12.1 per CONTRIBUTING.md so the CI staleness check passes.
* ci: keep crewai out of the locked CI dependency set
crewai (all versions) hard-requires chromadb~=1.1.0, which carries a
pre-authentication code-injection advisory (CVE-2026-45829 / GHSA-f4j7-r4q5-qw2c)
with NO fixed release — even the latest 1.5.9 is affected. Keeping crewai in
the 'all' extra failed pip-audit and the safety check on requirements-ci.txt.
- drop crewai from the 'all' aggregate (standalone semantica[crewai] extra is
unchanged and still installs crewai)
- stop listing crewai-tools in the extra: the integration only uses crewai core
(BaseTool, BaseKnowledgeSource) and crewai-tools pulled extra transitive deps
- regenerate requirements-ci.txt: OSV/pip-audit 0 vulnerabilities, safety 0
vulnerabilities, staleness check matches
* docs(crewai): document crewai extra scope and chromadb CVE-2026-45829
- CHANGELOG: extra is crewai>=0.80.0 only (no crewai-tools) and is not
part of the 'all' bundle, with the chromadb CVE-2026-45829 reason
- integrations/crewai/README.md: add a security warning that installing
the extra pulls chromadb~=1.1.0, which is affected by the unpatched
pre-auth code-injection CVE-2026-45829
---------
* fix(agno): surface unevaluable policy rules (#778)
* fix(agno): fixed qodo reviews
check_policy previously let unevaluable policy rules silently return
compliant=True with no signal (issue #778): a rule referencing a field
missing from decision_data, or a rule string not matching the expected
<field> <op> <value> format, both fell through _eval_rule's `return
True` and were treated as passed.
Both now raise ValueError, which routes through check_policy's existing
exception handler and surfaces as a `warnings` entry instead. compliant/
violations semantics are unchanged for every case that previously worked
correctly; an unevaluable rule is not counted as a violation since it's
genuinely unknown whether it would have passed.
Follow-up fixes from code review:
- policy_rules decoded via json.loads without checking it was a list;
a JSON-encoded bare string decoded to a Python str, so iterating it
evaluated one "rule" per character, amplifying a single input-shape
mistake into a wall of per-character warnings. A decoded string is
now treated as a single rule; any other non-list shape or non-string
list element produces exactly one warning instead.
- _eval_rule used `data.get(field) is None` to detect a missing field,
which can't distinguish an absent key from a key present with JSON
null - both produced the same "undefined field" warning. Field
presence is now checked with `field not in data` first, and a
present-but-null value gets its own distinct message.
Added regression tests for all of the above in
tests/integrations/agno/test_decision_kit.py (38 tests in the file,
128 passing across tests/integrations/agno/).
* fix(agno): reject non-object decision_data in check_policy
check_policy only validated that decision_data was well-formed JSON,
not that it decoded to an object. When it decoded to a list, `field
not in data` in _eval_rule silently became list-membership testing
of values instead of a dict key check - e.g. "confidence" not in
["confidence", 0.95] evaluates to False - so a matching rule fell
through to data["confidence"], raising a raw internal TypeError
("list indices must be integers or slices, not str") instead of any
meaningful diagnostic. Numbers, strings, and bools produced similarly
opaque TypeErrors deep inside _eval_rule.
check_policy now checks isinstance(data, dict) right after decoding
and rejects any other shape with a single clear violations entry,
the same way it already rejects malformed JSON.
Added 5 regression tests in tests/integrations/agno/test_decision_kit.py
covering list/number/string/bool/null decision_data shapes (43 tests
in the file, 133 passing across tests/integrations/agno/).
Addresses Copilot PR review comment on the #778 fix branch.
* docs(changelog): reference PR #822 in the check_policy changelog entry
---------
Co-authored-by: KaifAhmad1 <kaifahmad087@gmail.com>
- Added exc_info=True to both store failed and record_decision failed warning logs in _AgentScopedStore.upsert_memory() to preserve full traceback context for debugging
- Updated CHANGELOG.md entry to document traceback preservation
- Add integrations/openclaw/ with OpenClawKGTool (REST) and
OpenClawMCPConfig (mcporter.json generator)
- Add plugins/.openclaw-plugin/ bundle (plugin.json, marketplace.json,
README) with MCP + native tool support
- Add OpenClaw badge to README header
- Reorganize "Works With Every AI Tool" table into labeled groups:
Native Plugin Bundle, MCP Server + Plugin, MCP Server, REST API
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Package & distribution
- pyproject.toml: add integrations* to packages.find include so pip
install semantica[agno] ships the integration
context_store.py
- upsert_memory(): run NERExtractor after store() to index entities
into the ContextGraph
- delete_memory() / drop_table() / clear(): call AgentContext.forget()
to propagate deletions to vector/graph storage
- find_precedents(): pass limit parameter to find_precedents_advanced()
- retrieve(): pass limit as max_results to AgentContext.retrieve()
- add get_context_for_prompt() for automatic system-prompt injection
knowledge_graph.py
- __init__: wire graph_builder.graph_store = self._graph so build()
persists into the ContextGraph
- add internal AgentContext for vector retrieval (shared ContextGraph)
- search(): use AgentContext.retrieve() for vector similarity; keyword
scoring as fallback
- _ingest_text(): add paragraph-level chunking before NER/relation
extraction (parse → split → NER → relation extract → graph build)
- get_graph_context(): return structured subgraph with edge types via
ContextGraph.get_neighbors()
- load_urls(): validate scheme (http/https only) to prevent SSRF
decision_kit.py
- check_policy(): replace broken PolicyEngine.check_compliance() call
with inline _eval_rule() that evaluates simple field-op-value rules;
return compliant=False (not True) on failure — closes security bug
kg_toolkit.py
- add_to_graph(): fix add_node(node_id=, node_type=) and
add_edge(source_id=, target_id=, edge_type=) to match real API
- query_graph(): use find_nodes() (no label param) + keyword filter
- find_related(): use get_neighbors(node_id=) returning List[Dict]
- infer_facts() / export_subgraph(): use find_nodes() public API
instead of private _nodes dict
shared_context.py
- _AgentScopedStore: store shared context as self._context (not
self._ctx) so all inherited AgnoContextStore methods work correctly
tests/integrations/agno/test_kg_toolkit.py
- _FakeGraph: rewrite to match real ContextGraph signatures —
find_nodes(node_type=), add_node(node_id, node_type, **),
add_edge(source_id, target_id, edge_type, **),
get_neighbors(node_id, hops=1, ...) returning List[Dict]
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Created integrations/ folder at repository root for optional framework integrations
- Moved integrations folder from semantica/integrations/ to root-level integrations/
- Added __init__.py with documentation for future integrations (Google ADK, Claude Agent SDK, Agno)
- Keeps core semantica package lean while enabling ecosystem integrations
- Each integration will be self-contained and installable via extras_require