Observed since 21 Oct, 11:06 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
aiking-core
AI King engine — guards, runtime, ZIQ, FieldRead, PSYCHE, Cerno (AGPL-3.0-or-later or commercial)
The substantive engine of the AI King distribution. Wires together the governance stack (Concinno guards + Sancio runtime), ZIQ retrieval, FieldRead memory, PSYCHE chat-completion gateway, and the Cerno 7-step mother-agent cycle.
pip install aiking-core # base engine
pip install "aiking-core[body]" # adds persona-api adapters (see caveat)
You normally do not install aiking-core directly — pip install aiking
pulls it transitively and exposes the curated public surface.
aiking.core_engine)ziq = aiking_core.ziq:get_engine
fieldread = aiking_core.fieldread:get_engine
cerno = aiking_core.cerno:get_engine
The aiking shell discovers these via importlib.metadata rather than
direct imports, preserving the Apache-2.0 / AGPL boundary.
Dual-licensed:
LICENSE.COMMERCIAL_LICENSE.md.If you are not sure which applies, the AGPL terms govern by default.
aiking_core.ziq.retrieval imports concinno.core.state_store.StateStore,
and several governance / hooks submodules import from concinno.* and
persona.* during the Phase 2 migration. The relevant concinno>=5.3.0
dep is declared automatically; persona-api>=2.1.0 is opt-in via the
[body] extra because persona-api 2.1.0 has an upstream
from .engine import PersonaEngine self-import bug. Wait for 2.1.1 if
you need the body-engine path.
Download counts and popularity will appear here as the collector receives them.
| Package / target | Requirement | Relationship |
|---|---|---|
anthropicEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.10",
"evaluation": "NOT_EVALUATED"
} | anthropic>=0.40 | runtime |
concinnoEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.10",
"evaluation": "NOT_EVALUATED"
} | concinno>=5.3.0 | runtime |
httpxEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.10",
"evaluation": "NOT_EVALUATED"
} | httpx>=0.27 | runtime |
openaiEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.10",
"evaluation": "NOT_EVALUATED"
} | openai>=1.50 | runtime |
pydanticEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.10",
"evaluation": "NOT_EVALUATED"
} | pydantic>=2.0 | runtime |
starletteEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.10",
"evaluation": "NOT_EVALUATED"
} | starlette>=0.40.0 | runtime |
uvicornEnvironment{
"extras": "",
"marker": null,
"requires_python": ">=3.10",
"evaluation": "NOT_EVALUATED"
} | uvicorn>=0.30.0 | runtime |
persona-apiEnvironment{
"extras": "",
"marker": "extra == \"body\"",
"requires_python": ">=3.10",
"evaluation": "NOT_EVALUATED"
} | persona-api>=2.1.0; extra == "body" | runtime |
bdist_wheel · 309.05 KB · Python py3
sdist · 289.89 KB · Python source
Observed since 21 Oct, 11:06 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package_version:61ba687ef95b3f27ff50e584f624c699314f9f1eb5418e6272056dd88e926bca