Agent framework integrations for Sigmodx — audit infrastructure for AI agents making consequential decisions.
pip install sigmodx-integrationsRegister one callback. Every agent tool call is automatically logged to Sigmodx with cryptographic attestation.
from sigmodx import SigmodxClient
from sigmodx_integrations import SigmodxCallbackHandler, ANOMALY_DETECTION_CONFIG
client = SigmodxClient(
api_key="your-api-key",
agent_id="your-agent-uuid",
)
handler = SigmodxCallbackHandler(
client=client,
config=ANOMALY_DETECTION_CONFIG,
)
result = agent_executor.invoke(
{"input": "Check transaction TXN-2026-4421"},
config={"callbacks": [handler]},
)The handler:
- Hashes tool inputs client-side (your data never leaves your environment)
- Extracts decision type, rationale, and metadata from tool output
- Submits the decision to Sigmodx's append-only audit trail
- Never blocks agent execution — errors are logged, not raised
from sigmodx_integrations import SigmodxCallbackHandler, ScenarioConfig
config = ScenarioConfig(
scenario="invoice_approval",
filter_tools=["approve_invoice", "reject_invoice"],
decision_type_extractor=lambda output: output.get("decision"),
rationale_extractor=lambda output: output.get("reason"),
metadata_extractor=lambda output: {
"invoice_amount": output.get("amount"),
"vendor_id": output.get("vendor_id"),
},
)
handler = SigmodxCallbackHandler(client=client, config=config)from sigmodx_integrations import SigmodxAdapter
adapter = SigmodxAdapter(client=client, scenario="anomaly_detection")
adapter.log(
inputs={"txn_ref": "TXN-001", "amount": 5000},
decision_type="flag",
rationale="Amount 3x historical average.",
anomaly_subtype="unusual_amount",
severity="high",
transaction_amount=5000,
)| Framework | Status |
|---|---|
| LangChain | Live |
| Universal adapter | Live |
| AutoGen | Coming soon |
| CrewAI | Coming soon |
| OpenAI Agents SDK | Coming soon |
| Semantic Kernel | Coming soon |
Request framework prioritization: github.com/Sigmodx/integrations-python/issues