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
1 maintainer
Metadata
1 maintainer
Release files for aacp-pydantic-ai 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| aacp_pydantic_ai-0.1.0.tar.gz | 10.9 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| aacp_pydantic_ai-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 24.5 kB
Release files / aacp_pydantic_ai-0.1.0.tar.gz
| Download URL | aacp_pydantic_ai-0.1.0.tar.gz |
|---|---|
| Size | 10.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
60d8f0ccd7ff0a8e8b43694923761ecfa52f47a1b963ba7322527b57e5aebdd3
|
|
BLAKE2b-256 checksum How to use checksums |
d2d8912b3a8d57c263cb8ce7ad20a27111e8351f96284ebae18960ac02023040
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.5
|
Release files / aacp_pydantic_ai-0.1.0-py3-none-any.whl
| Download URL | aacp_pydantic_ai-0.1.0-py3-none-any.whl |
|---|---|
| Size | 13.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
bf8e0c8dfccac93dc142a4e16a4d690afc4c0b1d5867ac697bf018c26e579d2a
|
|
BLAKE2b-256 checksum How to use checksums |
d11a0beab2329c78a3e365bb7ee84781bb1c62696849bf218890f9e795642df6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.14.5
|
Security for aacp-pydantic-ai 0.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
