AACP coordination layer for Pydantic AI multi-agent workflows
Project description
aacp-pydantic-ai
AACP coordination layer for Pydantic AI multi-agent workflows.
Pydantic AI already types the result layer -- agents return validated Pydantic models. AACP adds typing to the instruction layer: what the orchestrator says to agents is now also typed, deterministic, and schema-validated. Both layers become fully deterministic.
Without AACP: NL instruction → Agent → typed result
With AACP: AACP packet → Agent → typed result
↑ typed ↑ typed (already)
Install
pip install aacp-pydantic-ai
Quick start
from aacp_pydantic.orchestrator import AACPPydanticOrchestrator
orch = AACPPydanticOrchestrator(model="openai:gpt-4o-mini")
result = orch.run_workflow("payroll", period="2026-03")
Comparison demo
python3 examples/comparison.py --mock
Links
- Protocol: https://aacp.dev
- Python SDK: https://github.com/MackayAndrew/aacp
- IETF Draft: https://datatracker.ietf.org/doc/draft-mackay-aacp/
Licence
MIT
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