Welcome to TeaQL
Start using TeaQL as a model-aware business API platform across seven language runtimes.
How the TeaQL Harness Works
How TeaQL places an evaluated domain model, generated business APIs, model-aware Assist, runtime governance, and executable evidence around an AI coding agent.
Architecture Overview
Understand TeaQL as a generated business API layer, runtime boundary, and provider-based execution model.
Runtime Overview
Understand TeaQL runtime execution, UserContext, repositories, data services, and provider boundaries.
Seven-Runtime Contract
The shared TeaQL application lifecycle across Java, Rust, TypeScript, Swift, Python, .NET, and Go.
Query, Mutation, Analytics, and Facets
One entry point for TeaQL reads, writes, aggregates, relation statistics, and facet navigation across seven languages.
Cross-language Query Contract
Shared TeaQL predicates, deep relation loading, analytics, facets, and pagination across all seven native runtimes.
Cross-language Mutation Lifecycle
Shared TeaQL create, update, deletion, Checker/Fix, Mutation Ledger, audit, and save semantics.
Debugging, Audit, and Observability
Diagnose TeaQL queries, facets, aggregates, deep relations, mutations, audit delivery, telemetry, and tenant policy across seven runtimes.
Cache, Lock, and Cloud Runtime Infrastructure
Use TeaQL local and Redis-backed cache, local and remote locks, Nacos/Consul integration, health endpoints, metrics, and graceful shutdown at their verified capability level.
Assist and Generated Workspaces
How model-aware Assist and generated workspace targets align across TeaQL's seven runtimes.
TeaQL Federal Protocol Boundary
Governed cross-runtime query and mutation roles, evidence, and security boundaries for TFP v1.
Java/Rust Parity & Generator
How one TeaQL model generates Java and Rust targets, which concepts are shared, and where each stack intentionally differs.
Internationalization Design Baseline
The cross-runtime design baseline for TeaQL internationalization. This feature is under development and is not available for application use yet.
Authorization Governance (Design)
Proposed model-driven authorization, policy distribution, local enforcement, and centralized governance across all TeaQL runtimes.
Protected Field Encryption (Design)
Proposed encrypted-field metadata, reveal workflows, short-lived grants, key boundaries, and client handling responsibilities.
Service Behind the Scenes
TeaQL looks simple from the application code side because a lot of work is handled by the runtime and the generated library behind the scenes.