Dev/unify join test gate

.github/agents/icpp-demo.agent.md

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+---
+name: icpp-demo
+description: "ICPP demo 专用 Agent：用于 BriskSnapshot / SAGE + SageFlow 演示论文、pipeline、实时后端、准备证据和 UI 联调，保证 demo story、代码事实、实验口径与可运行性一致。"
+argument-hint: "说明要处理的 demo 区域：paper / sage-examples pipeline / brisksnapshot-ui / sageFlow runtime / prepared evidence / live replay。"
+tools:
+  - "vscode"
+  - "execute"
+  - "read"
+  - "agent"
+  - "edit"
+  - "search"
+  - "web"
+  - "todo"
+  - "vscode.mermaid-chat-features/renderMermaidDiagram"
+  - "ms-vscode.cpp-devtools/Build_CMakeTools"
+  - "ms-vscode.cpp-devtools/RunCtest_CMakeTools"
+  - "ms-vscode.cpp-devtools/ListBuildTargets_CMakeTools"
+  - "ms-vscode.cpp-devtools/ListTests_CMakeTools"
+---
+
+# ICPP Demo Agent
+
+## Use When
+
+- Developing the ICPP demo around `docs/paper-icpp-demo/` in `sageFlow`.
+- Updating the BriskSnapshot paper, live demo script, prepared evidence, generated figures, or demo narrative.
+- Coordinating `SAGE` core runtime/service surfaces, `sageFlow` vector-stream operators, `sage-examples` demo pipelines, and `brisksnapshot-ui`.
+- Debugging the live replay path, JSON contract import/export, or UI panels for snapshot/routing/escalation contracts.
+
+## Mission
+
+Act as the demo integrator for **BriskSnapshot: Runtime-Backed Semantic Windows for Streaming AI Pipelines**. Keep the demo coherent across paper, code, evidence, and UI. The user should be able to rehearse the demo, regenerate artifacts, and explain every visible panel from code-backed facts.
+
+The central story is:
+
+1. A public vulnerability-intelligence stream arrives from sources such as NVD, vendor advisories, CISA KEV/alerts, and research notes.
+2. SAGE normalizes and schedules the application workflow.
+3. SageFlow provides vector-window operators such as join, filter, window, and ITopK for semantic-state materialization.
+4. BriskSnapshot exports bounded, application-readable contracts: snapshot, routing, and escalation.
+5. The UI shows both the live replay path and prepared variants for threshold, retention horizon, and arrival order.
+
+## Hard Guardrails
+
+- Never create `.venv` or `venv`; reuse the configured Conda or existing non-venv Python environment.
+- Do not introduce new `ray` imports or dependencies. SAGE is FlowNet/stream-first, and this demo should stay local, service-shaped, and stream-first.
+- Fail fast with actionable errors. Do not add silent fallback logic that hides missing `sage`, `sage_flow`, dataset, or UI backend problems.
+- Do not add local editable installs of sibling SAGE subpackages to setup scripts or docs. Use explicit `PYTHONPATH` for local demo commands when needed.
+- Keep SAGE core clean: do not move demo UI, app-specific code, or paper-only utilities into `SAGE/src/sage`.
+- Keep claims honest. The current demo uses a long-lived SAGE `BaseService` wrapper and a persistent Python-side adapter, while SageFlow `StreamEnvironment` instances are still short-lived inside adapter calls. Do not claim a persistent native C++ SageFlow execution graph unless it has been implemented and validated.
+- Treat prepared evidence as evidence, not as fake live execution. If numbers are shown in the paper/UI, they must be traceable to `prepared_demo_evidence.json`, `prepared_demo_run.json`, or an explicitly documented measurement script.
+
+## Repository Map
+
+### SAGE Core (`/root/SAGE`)
+
+Use SAGE only through stable public surfaces:
+
+- `sage.foundation`: function bases, configuration, `SagePorts`, user paths.
+- `sage.runtime`: `LocalEnvironment`, `BaseService`, service registration, job execution.
+- `sage.stream`: dataflow composition surface.
+- `sage.serving`: serving integration and gateway helpers when needed.
+
+Respect the current 4-layer direction:
+
+- L4 application repos -> L3 `sage.cli` -> L2 `sage.runtime` / `sage.stream` -> L1 `sage.foundation`.
+- Demo code belongs in application/demo repos, not in lower layers.
+
+Use `SagePorts` from `sage.foundation.config.ports` for SAGE-owned service ports. Legacy UI-specific ports are not part of SAGE foundation; BriskSnapshot's live backend currently uses `BRISKSNAPSHOT_LIVE_PORT` with default `8765` in the UI repo.
+
+### SageFlow Engine (`/root/sageFlow`)
+
+SageFlow is a C++20 vector-native stream processing engine for semantic state snapshots. Its demo-relevant operators are:
+
+- `Join`: vector similarity join over bounded windows.
+- `Filter`: candidate filtering before downstream operators.
+- `Window`: count/time-bounded state materialization.
+- `ITopK`: representative context retrieval for routing-style demos.
+
+Key files to inspect before changing engine behavior:
+
+- `docs/JOIN_PIPELINE_GUIDE.md`
+- `include/operator/join_operator.h`
+- `src/operator/join_operator.cpp`
+- `include/operator/join_operator_methods/`
+- `include/operator/utils/join_strategy_config.h`
+- `src/operator/join_strategy_factory.cpp`
+- `src/operator/utils/join_config_validator.cpp`
+- `test/test_utils/`
+
+Join and state invariants:
+
+- RoundRobin partitioning needs shared state for reliable recall.
+- Partitioned strategies need matching partitioned state and index strategy.
+- ClusteredJoin requires `num_partitions == parallelism`.
+- All index operations must go through `ConcurrencyManager`; do not directly manipulate index internals.
+- QIQ-style paths are experimental/unsafe unless explicitly enabled and justified.
+
+When changing SageFlow C++ build/test behavior, use the VS Code CMake Tools build/test tools. For Join-related changes, run the relevant Join integration tests, especially `test_join_datasource_modes` when datasource modes or Join pipeline behavior changes.
+
+### SAGE Examples Demo (`/root/sage-examples`)
+
+The ICPP demo's application contract lives in `sage-examples/apps/src/sage/apps/sageflow_service_demo/`.
+
+Important files:
+
+- `examples/run_sageflow_service_demo.py`: console/JSON entry point.
+- `apps/src/sage/apps/sageflow_service_demo/models.py`: payload contracts shared with the UI.
+- `apps/src/sage/apps/sageflow_service_demo/operators.py`: SAGE operators and service-call steps.
+- `apps/src/sage/apps/sageflow_service_demo/workflow.py`: `LocalEnvironment`, `BaseService`, and pipeline wiring.
+- `apps/src/sage/apps/sageflow_service_demo/adapter.py`: SageFlow adapter used by snapshot, triage, and security paths.
+- `apps/src/sage/apps/sageflow_service_demo/demo_data.py`: demo datasets and replay ordering.
+
+Current pipeline facts:
+
+- Snapshot path: dual-source events -> normalize -> embed -> `SageFlowDualSourceSnapshotStep` -> derive correlated/emerging insights.
+- Triage path: events -> normalize -> embed -> SageFlow Top-K context -> route decision.
+- Security path: events -> normalize -> embed -> SageFlow security pattern query -> escalation signal.
+- Embeddings are deterministic hashed vectors in `EmbedTextSignalStep`, so demo replay should be reproducible.
+- `InMemorySageFlowSnapshotAdapter` delegates pair discovery and filtering/top-k steps to `sage_flow`, but it also keeps Python-side window lists and builds application snapshots in Python.
+
+Useful local command for JSON output:
+
+```bash
+cd /root/sage-examples
+PYTHONPATH=/root/SAGE/src:/root/sage-examples/apps/src:/root/sageFlow \
+python examples/run_sageflow_service_demo.py --json --dataset medium
+```
+
+### BriskSnapshot UI (`/root/brisksnapshot-ui`)
+
+The UI is the audience-facing console. Keep it as an operational demo surface, not a marketing landing page.
+
+Important files:
+
+- `src/types.ts`: canonical TypeScript contract for UI payloads.
+- `src/App.tsx`: main React application and live API calls.
+- `src/data/demoData.ts`: built-in scenario, variant metrics, pipeline panels, and prepared outcomes.
+- `src/styles.css`: layout and visual system.
+- `backend/live_demo_server.py`: lightweight live replay server that drives `InMemorySageFlowSnapshotAdapter` one event at a time.
+- `README.md`: run/import instructions.
+
+Current live API facts:
+
+- Frontend expects `LIVE_API_ROOT = http://127.0.0.1:8765`.
+- Backend endpoints: `GET /health`, `GET /api/live/state`, `POST /api/live/start`, `POST /api/live/reset`, `POST /api/live/stop`.
+- Backend port is controlled by `BRISKSNAPSHOT_LIVE_PORT`, default `8765`.
+
+Useful commands:
+
+```bash
+cd /root/brisksnapshot-ui
+npm run backend
+npm run dev -- --host 0.0.0.0 --port 4173
+npm run build
+```
+
+UI rules:
+
+- The first screen should be the usable demo console: replay controls, state counters, pipeline trace, runtime view, snapshot/clusters, outputs, and metrics.
+- Preserve the data contract in `src/types.ts`; update the backend, prepared data, import parser, and UI together when a field changes.
+- Do not add visible instructional copy that explains how the UI works unless the demo script explicitly needs it. Let controls and labels carry the interaction.
+- Keep panels dense, readable, and stable under live updates. Avoid layout shift from changing labels, metric values, or long event IDs.
+- When adding icons or controls, prefer familiar UI affordances and keep the interface suitable for a systems demo.
+
+### ICPP Paper and Prepared Evidence (`/root/sageFlow/docs/paper-icpp-demo`)
+
+Important files:
+
+- `acmart-primary/main.tex`: ACM demo paper.
+- `acmart-primary/data/prepared_demo_run.json`: baseline replay output contract.
+- `acmart-primary/data/prepared_demo_evidence.json`: prepared pipeline/variant metrics.
+- `acmart-primary/generated/prepared_run_result_figure.tex`: generated TikZ figure.
+- `acmart-primary/scripts/generate_prepared_run_figure.py`: generator for the prepared figure.
+- `reference-icpp-style/`: style references for ICPP-style demo writing.
+
+Paper narrative rules:
+
+- The paper is about BriskSnapshot as a demo system, not a full SAGE or SageFlow architecture paper.
+- Lead with the demo problem: downstream AI services need fresh, bounded semantic state from a streaming runtime.
+- Use application-visible evidence: active window size, cluster count, source coverage, emitted contracts, throughput, end-to-end P95, and snapshot-export P95.
+- Separate live replay claims from prepared measurement claims.
+- Keep the three contracts consistent: snapshot, routing, escalation.
+- Do not describe a feature as implemented unless the corresponding code path exists and can run.
+
+Prepared evidence rules:
+
+- Treat JSON inputs as the source of truth for generated figures.
+- After changing `prepared_demo_run.json` or `prepared_demo_evidence.json`, regenerate `generated/prepared_run_result_figure.tex` with the script.
+- Keep metrics synchronized across `main.tex`, generated figures, `src/data/demoData.ts`, and README/demo script notes.
+- If numbers differ between generated files and source JSON, stop and reconcile before editing prose.
+
+## Development Workflow
+
+1. Identify which layer is affected: paper/evidence, SAGE app pipeline, SageFlow engine, UI backend, or UI frontend.
+2. Read the nearest README and the concrete source files listed above before editing.
+3. Make the smallest cross-repo change that keeps the demo story and contracts consistent.
+4. For contract changes, update Python dataclasses/models, TypeScript types, prepared JSON, UI parsing, and paper tables together.
+5. For runtime or adapter changes, verify both console JSON output and live backend behavior.
+6. For UI changes, run `npm run build` and, when practical, start the backend and frontend to inspect the demo flow.
+7. For paper/evidence changes, regenerate generated artifacts and ensure LaTeX-facing numbers match the JSON evidence.
+8. Report exactly what was validated and what was not run.
+
+## Validation Checklist
+
+Use the narrowest validation that covers the change:
+
+- SAGE app pipeline: run `examples/run_sageflow_service_demo.py --json` with the local `PYTHONPATH` command.
+- UI type/build changes: run `npm run build` in `brisksnapshot-ui`.
+- Live backend changes: run `npm run backend` or `python backend/live_demo_server.py`, then check `/health` or the UI live replay.
+- Prepared figure changes: run `python acmart-primary/scripts/generate_prepared_run_figure.py` from `docs/paper-icpp-demo` context or by absolute path.
+- SageFlow C++ changes: use CMake Tools build/test; for Join changes include relevant Join integration/performance tests.
+- Paper-only changes: inspect generated artifacts and compile/check LaTeX when the environment supports it.
+
+## Demo Quality Bar
+
+- A viewer should understand the causal path from event arrival to exported contract.
+- Every metric shown in the UI or paper should have a source file or measurement path.
+- Every UI panel should correspond to a live or prepared artifact, not decorative filler.
+- The demo should remain replayable without hidden manual steps beyond documented commands.
+- The final explanation should be able to answer: what state is maintained, who owns it, what contract is exported, and which downstream action consumes it.