- qa-tester: add validation v2 testing checklist - speckit.plan: add component reuse scan for frontend - molecular-cot-logging: add Svelte logger + CLI reader - semantics-svelte: add RSM model-first protocol, frontend stack - templates: update plan/tasks/ux-reference templates - ADR-0004: add llm_dashboard_validation plugin registration - ADR-0008: add assistant tool registry for v2 validation - Specs: update 017 tasks from 51 to 99
4.6 KiB
4.6 KiB
[DEF:ADR-0004:ADR]
@STATUS ACTIVE
@PURPOSE Define the plugin architecture for ss-tools — the loading mechanism, lifecycle contract, isolation guarantees, and the boundary between core services and pluggable extensions.
@RELATION DEPENDS_ON -> [ADR-0001:ADR]
@RELATION DEPENDS_ON -> [ADR-0003:ADR]
@RELATION CALLS -> [ADR-0005:ADR]
@RATIONALE Extensibility is a core architectural value: the system must support LLM‑driven analysis, custom data transformations, and environment‑specific logic without modifying core code. A plugin system prevents the monolith from accumulating every domain‑specific feature and enables third‑party (or future‑self) contributions without forking.
@RATIONALE Process isolation was chosen over in‑process imports because: (a) plugins may use incompatible library versions, (b) a crashing plugin must not take down the orchestrator, (c) security boundary — plugins should not access the orchestrator's database connection directly.
@REJECTED In‑process Python importlib plugin loading — rejected because a misbehaving plugin can corrupt global state, exhaust memory, or crash the server. Process isolation provides a hard boundary.
@REJECTED Docker‑container per plugin — rejected because it adds excessive orchestration complexity and startup latency for plugins that are mostly lightweight LLM prompt chains. Subprocess isolation is sufficient.
@REJECTED WebAssembly (WASI) sandbox — rejected because the Python AI/LLM ecosystem (langchain, transformers) does not yet reliably compile to WASM. Premature optimization.
Decision
Plugin Architecture
ss-tools Core
├── core/plugin_loader.py # Plugin discovery, loading, lifecycle
├── core/plugin_executor.py # Subprocess execution, timeout, error boundary
├── core/plugin_registry.py # Registered plugins, metadata, health
└── plugins/ # Plugin packages (each = one directory)
├── llm_analysis/ # LLM‑driven Superset data analysis; v2 adds dual-path execution (Path A: Playwright screenshot + multimodal LLM; Path B: text-only API + dataset health checking)
├── dataset_orchestration/ # LLM dataset operations
└── git_integration/ # Git‑based version control for dashboards
Plugin Contract
v2 update: Task-based validation was introduced via
ValidationTaskService, creating persistent validation policies withValidationRunaggregates for grouping per-dashboard results. Each run is tracked as aValidationRunrecord with aggregate pass/fail/warn counts, replacing the previous single-shot task result pattern. SeeValidationTaskServiceinservices/validation_service.py.
Every plugin MUST provide:
-
plugin.toml— metadata manifest at the plugin root[plugin] id = "llm_analysis" name = "LLM Data Analysis" version = "1.0.0" entrypoint = "plugin.py" timeout_sec = 300 max_memory_mb = 512 requires = ["superset-api>=1.0", "openai>=1.0"] -
plugin.py— entrypoint with two required functions:def register(registry: PluginRegistry) -> PluginInfo— declare capabilitiesdef execute(task: TaskContext) -> TaskResult— run the plugin
-
Task context contract (Pydantic
TaskContext):task_id: str,plugin_id: str,action: str,params: dict,superset_env: SupersetConnection,auth_token: str(scoped, short‑lived)
-
Result envelope (Pydantic
TaskResult):status: Literal["success", "warning", "error"],data: dict | None,error_message: str | None,execution_time_ms: int,artifacts: list[str](file paths to saved artifacts)
Plugin Lifecycle
Discover → Validate → Register → [Execute] → Report
│ │ │ │
│ Check TOML Store in Spawn subprocess
│ schema, registry with timeout +
│ dependencies in DB memory limit
Isolation Guarantees
- Subprocess:
subprocess.run(..., timeout=timeout_sec), killed on timeout. - Memory:
resource.setrlimit(RLIMIT_AS, max_memory_mb * 1024 * 1024)before exec. - No DB access: Plugins receive only a scoped REST API token, never a database connection.
- No filesystem writes outside allowed dirs: Configurable artifact directory per plugin.
RBAC Integration
Plugin access is governed by ADR-0005 (RBAC):
- Each plugin declares
required_roles: ["admin", "analyst"]inplugin.toml. - Plugin executor checks the user's role set before allowing execution.
- Forbidden access returns
403with audit log entry.