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"River" in Quechua, Amazon's language
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查看完整 README ↗Documentation (English) · 한국어 문서 · Quickstart · Deployment profiles · Production readiness
inferplane — set the policy; let the data plane enforce it.
A governance plane for coding agents, with policy administration separated from
inference traffic. Configure model access, sensitive-data handling, budget limits
and approved routing choices. mayu applies them on requests and provider
attempts; inferplaned distributes policy and budget authority without carrying
prompts or response streams.
Enabled policies turn operating rules into request-time decisions: route detected PII to approved internal models, mask and reinspect content, select a model using configured context signals, or switch to a lower-cost target at a budget threshold. Hard caps and privacy restrictions still constrain the result and its fallbacks. Operators supply and validate the rules, model metadata and processing boundaries; PII detection has finite coverage. Why inferplane · 한국어.
Control-plane HTTP is not called for per-request admission. Shared admission still depends on Postgres; finite authority, readiness/staleness gates and credential renewal have their own failure contracts. See deployment profiles.
mayu is a component name, not a project name — it holds the same position in
inferplane that ztunnel/waypoint hold in Istio. It runs on localhost or on each
Kubernetes node, speaks your coding agent's native protocol (Anthropic Messages,
OpenAI Chat Completions/Responses, Bedrock InvokeModel), and enforces the rules the control
plane (inferplaned) hands it: per-user attribution, budget cutoffs, and model
routing.
These are goals, not blanket completion or no-SPOF guarantees. See Deployment profiles and Current limits.
Enterprise platform/SRE teams governing coding-assistant LLM traffic across
many developers and teams. The on-ramp stays bottom-up — a single team can
run mayu standalone in minutes with no control plane (see Quick
start) — but the intended growth path is a
platform team adopting inferplaned to govern that traffic fleet-wide once
more than one team is on it.
docs/roadmap.md).Basic JSON parsing is required. Additional inspection is conditional on the ingress and effective rules; Responses performs compatibility inspection even without policy; native Bedrock Converse also always checks structure. Structure-only paths skip finite PII detectors; applicable privacy and verified masking retain full detection, including beside context Shadow. Learned classification and legacy masking are separate opt-ins. See inspection conditions.
GovernancePolicy.sensitiveData selects approved internal destinations, complete
masking, or refusal before egress. Independent routing.context rules classify
weak/simple, optional normal, and strong/complex tasks. Context starts in Shadow;
explicit stability and Enforce support compatible multi-turn/tool workflows
and retain the actual successful model/provider between related requests.
Privacy always enforces, including during Shadow (ADR-043/044).
Strict budget tiers (enforceTargets: true) constrain every later selection and
retry after a switching threshold. A separate total hard cap remains binding.
The soft switching threshold does not become a smaller blocking admission cap.
Legacy optional tiers retain their behavior. Legacy ADR-043 two-class context
selection remains limited to eligible, completely inspectable single-user-turn
requests without history/tools/media/reasoning/structured output. ADR-044's
extended context/stability rules support compatible tool/history sessions; pins
are bounded and local to one gateway, not fleet-wide session state.
Responses ingress and native/stateless adapters have local protocol tests and installed Codex CLI tool-round-trip tests, including Bedrock Converse. The model-aware launcher supplies model selection and context limits. Backend tool availability and native-only features remain explicit; see Codex setup. ↩
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