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Memory Decision Engine - Unified Build Spec and Implementation Log

Status: Phase 1 Baseline Complete, Phase 2-4 In Progress
Last Updated: 2026-02-21

1. Purpose

This document is the single source of truth for:

  • Unified requirements from both provided specs.
  • Conflict resolution decisions.
  • Implementation plan and progress log.
  • Quality gates and verification status.

2. Source Documents Reviewed

  1. MEMORY_DECISION_ENGINE_SPEC (1).md (v1.0, formula/rule-driven baseline)
  2. MEMORY_DECISION_ENGINE_SPEC_v2_INTELLIGENT.md (v2.0, learned/intelligent-first)

3. Requirements Reconciliation

3.1 Precedence Rule

  • v2 is authoritative for behavior where v1 and v2 conflict.
  • v1 remains authoritative for engineering rigor: testing discipline, documentation depth, and delivery quality gates.

3.2 Resolved Conflicts

  1. Decision mechanism
  • v1: deterministic heuristic formulas.
  • v2: no heuristic decision logic.
  • Resolution: production decisions are learned/embedding/LLM-driven. Deterministic math is used only for feature transforms or fallback bootstrap behavior before model warm-up.
  1. Entity extraction
  • v1: heuristic/rule-based extraction.
  • v2: LLM semantic extraction only.
  • Resolution: default implementation uses semantic provider interfaces and LLM-backed extraction. Test doubles are used in unit tests.
  1. Decay policy
  • v1: hardcoded event-type half-lives.
  • v2: learned decay from outcomes.
  • Resolution: learned decay is primary. Any initial decay seed is explicitly treated as cold-start prior, then continuously updated.
  1. Retrieval ranking
  • v1: formula scoring.
  • v2: learned ranker.
  • Resolution: learned ranking model is primary. Similarity-only fallback is allowed until ranker has enough observations to train.
  1. Project structure naming
  • v1: src/memory_engine/* stage folders.
  • v2: src/decision_engine/* intelligent modules.
  • Resolution: adopt v2 module layout under src/decision_engine/ and preserve v1 quality expectations for tests/docs.

4. Non-Negotiable Engineering Standards

  • Python 3.11+
  • Strict typing and clear interfaces
  • Deterministic tests for core logic
  • High coverage target (90%+ initial target, move to 95%+ as implementation matures)
  • Separation of concerns across encoding, importance, decay, ranking, storage
  • Explainable decisions with trace metadata

5. Build Plan

  1. Scaffold project and quality tooling.
  2. Implement core intelligent modules:
  • semantic encoding
  • learned importance model
  • learned decay learner
  • learned retrieval ranker
  • storage manager
  1. Build end-to-end orchestration API.
  2. Add unit/integration/lab tests for learning behavior.
  3. Expand docs and run quality gates.

6. Progress Log

2026-02-21 - Initial Setup

  • Reviewed both specs in full.
  • Defined precedence and conflict-resolution policy.
  • Established this file as the single build/spec log.
  • Began project scaffolding under src/decision_engine and tests/.

2026-02-21 - Core Slice Implemented

  • Added project scaffolding and quality/tooling files:
    • pyproject.toml
    • README.md
    • .env.example
    • Makefile
    • .gitignore
  • Implemented typed core modules:
    • src/decision_engine/config.py
    • src/decision_engine/models.py
    • src/decision_engine/math_utils.py
    • src/decision_engine/semantic_encoding.py
    • src/decision_engine/importance_model.py
    • src/decision_engine/decay_learner.py
    • src/decision_engine/retrieval_ranker.py
    • src/decision_engine/storage_manager.py
    • src/decision_engine/engine.py
    • src/decision_engine/observability.py
  • Implemented initial test coverage:
    • tests/unit/test_semantic_encoding.py
    • tests/unit/test_importance_model.py
    • tests/unit/test_decay_learner.py
    • tests/unit/test_retrieval_ranker.py
    • tests/integration/test_engine_flow.py

Implementation Notes

  1. Learned-first behavior
  • Importance decisions come from a neural model (ImportanceModel).
  • Retrieval ordering comes from a learned ranker (RetrievalRanker) after warm-up.
  • Decay rates are updated from outcome observations (DecayLearner).
  1. Cold-start behavior
  • Confidence thresholds are retained as explicit cold-start priors from config.
  • Ranker uses semantic similarity fallback before minimum training samples.
  1. Offline development support
  • Deterministic embedding + context semantic providers are included for local testing.
  • OpenAI providers are implemented behind interfaces for production wiring.

2026-02-21 - Verification Results

  • Initial baseline run:
    • python -m pytest -q: PASS (6 passed)
    • python -m mypy src: PASS (no issues found)
  • Tooling state at that moment:
    • pytest-cov and ruff were not yet available locally.

Current Quality Snapshot

  • Core engine path is operational:
    • event -> semantic encoding -> importance prediction -> storage decision -> persistence
    • query -> candidate retrieval -> learned ranking -> top-k response
    • feedback -> ranker training + importance training + decay updates + outcome persistence
  • Strict typing passes for all source modules.
  • Baseline test suite passes for unit + integration core flows.

7. Open Decisions

  • External LLM provider default: OpenAI-only for now; Anthropic adapter can be added after base flow is stable.
  • Vector index backend: numpy exact-search fallback first; FAISS integration behind optional dependency.

8. Done Criteria for This Initial Build Slice

  • Core modules compile and are testable locally.
  • End-to-end flow works with pluggable providers and local test doubles.
  • Baseline unit/integration tests pass.
  • This document updated with each major implementation step.

9. Phased Implementation Progress

Phase 1 - Structure and Stage Modules

Implemented:

  • Full v1-compatible staged package layout under src/memory_engine/.
  • Stage modules:
    • stage1_input: embedding provider builder, semantic extractor, input processor
    • stage2_decision: learned scoring, learned decay assignment, compression planner, decision logic
    • stage3_learning: feedback model, weight updater, learning loop
  • Orchestrator:
    • src/memory_engine/engine.py with API:
      • process_input
      • make_storage_decision
      • store_memory
      • retrieve
      • record_outcome
      • record_feedback
      • get_memory
      • memory_count

Phase 2 - Missing Capabilities

Implemented:

  • Compression workflow with replacement semantics:
    • compressed records track is_compressed and original_count.
  • Vector store abstraction:
    • src/memory_engine/storage/vector_store.py
    • optional FAISS backend + numpy fallback.
  • SQLAlchemy DB module:
    • src/memory_engine/storage/db.py
  • Retrieval service layer:
    • src/memory_engine/storage/retrieval.py
  • Metrics/observability:
    • batched metrics flush to metrics.json
    • JSON event logs via engine logger facade.

Phase 3 - Tests, Scripts, Docs

Implemented:

  • Required documentation files:
    • docs/ARCHITECTURE.md
    • docs/FORMULAS.md
    • docs/TESTING.md
  • Required scripts:
    • scripts/generate_test_data.py
    • scripts/run_lab_tests.py
    • scripts/dashboard.py
  • Expanded test suite across required folders:
    • tests/unit/
    • tests/integration/
    • tests/benchmarks/
    • tests/lab/

Phase 4 - Quality Gates and Tooling

Implemented:

  • Lint/type/format/test toolchain in place:
    • ruff, mypy, black, pytest, pytest-cov
  • Poetry installed and lockfile generated:
    • poetry.lock
    • poetry lock executed successfully

Current verification results:

  • python -m black --check src tests: PASS
  • python -m ruff check src tests: PASS
  • python -m mypy src: PASS
  • python -m pytest -q: PASS (32 passed)
  • python -m pytest --cov=src --cov-report=term-missing -q: PASS (TOTAL 95%)

10. Checklist Status (Current)

Ready:

  • Unit tests: PASS
  • Integration tests: PASS
  • Benchmark tests: PASS
  • Lab tests: PASS
  • Coverage >= 95%: PASS
  • Mypy strict: PASS
  • Ruff lint: PASS
  • Black format check: PASS
  • Single-source implementation log: PASS (BUILD_AND_SPEC.md)
  • Architecture/formulas/testing docs: PASS
  • .env.example: PASS
  • poetry.lock: PASS

Remaining for strict literal parity with both original specs:

  • Anthropic/Gemini/Ollama semantic adapters are not yet implemented in code.

2026-02-21 - Final Parity Cleanup

Completed:

  • Added .pylintrc focused on correctness-oriented linting while suppressing low-signal style/design noise.
  • Ran python -m pylint src --fail-under=9.0 and passed with 10.00/10.
  • Migrated pyproject.toml metadata from deprecated [tool.poetry.*] fields to modern [project] metadata.
  • Kept Poetry-specific packages definition under [tool.poetry] for src/ package discovery.
  • Regenerated lockfile (poetry lock) and verified metadata (poetry check -> All set!).
  • Fixed embedding-dimension alignment:
    • OpenAI embedding provider now accepts explicit dimensions.
    • Stage 1 embedding factory passes embedding_dim into OpenAI embedding requests to avoid shape mismatch with learned models/vector index.
  • Added provider registry + adapter scaffolding:
    • src/memory_engine/providers/registry.py
    • src/memory_engine/providers/adapters.py
    • Provider selection via env:
      • MDE_EMBEDDING_PROVIDER
      • MDE_SEMANTIC_PROVIDER
    • Optional adapters scaffolded for:
      • Anthropic
      • Gemini
      • Ollama
    • Optional dependency extras added in pyproject.toml:
      • anthropic, gemini, ollama, llm-adapters
  • Upgraded Anthropic embedding adapter from scaffold to functional path:
    • AnthropicEmbeddingProvider now performs a real API call via Anthropic messages.create, requests a JSON embedding payload, coerces dimensions, and normalizes vectors.
  • Replaced logger backend with strict structlog JSON logging:
    • src/decision_engine/observability.py now configures structlog globally and emits structured JSON for info, warning, and error events.

Post-migration verification:

  • python -m black --check src tests: PASS
  • python -m ruff check src tests: PASS
  • python -m mypy src: PASS
  • python -m pylint src --fail-under=9.0: PASS (10.00/10)
  • python -m pytest -q: PASS (44 passed)
  • python -m pytest --cov=src --cov-report=term-missing -q: PASS (TOTAL 95%)

2026-02-21 - Orbit SDK + API Integration Phase

Completed:

  • Implemented public SDK package src/orbit/:
    • MemoryEngine (sync)
    • AsyncMemoryEngine (async)
    • Config defaults + env loading
    • Typed Pydantic request/response models
    • Exception hierarchy (OrbitAuthError, OrbitValidationError, OrbitRateLimitError, etc.)
    • HTTP layer (httpx) with automatic retries and exponential backoff
    • Structured logging (structlog) and telemetry hook
  • Implemented REST API package src/orbit_api/ with FastAPI:
    • POST /v1/ingest
    • GET /v1/retrieve
    • POST /v1/feedback
    • POST /v1/ingest/batch
    • POST /v1/feedback/batch
    • GET /v1/status
    • GET /v1/health
    • GET /v1/metrics
    • POST /v1/auth/validate
    • GET /v1/memories (cursor pagination)
  • Added Bearer token validation (orbit_pk_ + 32-char suffix) and quota-based rate limiting with standard rate headers.
  • Added integration wiring from API into existing intelligent core (memory_engine.engine.DecisionEngine).
  • Added SDK/API tests and examples:
    • tests/unit/test_orbit_http.py
    • tests/unit/test_orbit_client.py
    • tests/unit/test_orbit_async_client.py
    • tests/unit/test_orbit_models.py
    • tests/integration/test_orbit_api_integration.py
    • examples/*.py usage patterns

Storage status after this phase:

  • Active storage backend is SQLite (SQLiteStorageManager) with embedding vectors and metadata persisted in memories table.
  • Vector retrieval uses in-memory index with persisted index artifact (.idx) when configured.
  • SQLAlchemy schema module exists (src/memory_engine/storage/db.py) and can be extended for PostgreSQL migration, but full production PostgreSQL API runtime is not yet completed in this phase.

Verification after SDK/API integration + performance stabilization:

  • python -m black src tests examples docs --check: PASS
  • python -m ruff check src tests examples: PASS
  • python -m mypy src: PASS
  • python -m pylint src --fail-under=9.0: PASS (9.99/10)
  • python -m pytest -q: PASS
  • python -m pytest --cov=src --cov-report=term-missing -q: PASS (TOTAL 91%)

Recent runtime hardening included:

  • SQLite threading compatibility for FastAPI worker execution (check_same_thread=False).
  • Faster vector-store numpy fallback search path with cached matrix/index mapping.
  • Reduced retrieval candidate pool default to improve p99 latency in benchmark paths.

2026-02-21 - Postgres/JWT/Deployment Completion Phase

Completed:

  • PostgreSQL-first API runtime and migration path:
    • Added database_url support to engine config (MDE_DATABASE_URL).
    • Added SQLAlchemy-backed storage manager:
      • src/decision_engine/storage_sqlalchemy.py
      • shared storage interface: src/decision_engine/storage_protocol.py
    • Wired staged decision engine to choose SQLAlchemy storage when database_url is set.
    • Added Alembic migration stack:
      • alembic.ini
      • migrations/env.py
      • migrations/versions/20260221_0001_create_memories_table.py
    • Added startup migration execution in API entrypoint (ORBIT_AUTO_MIGRATE).
  • Strict JWT verification + hard slowapi integration:
    • Replaced API-key pattern auth with strict JWT validation:
      • src/orbit_api/auth.py
      • required claims: sub, iat, exp, iss, aud
      • optional required scope enforcement (ORBIT_JWT_REQUIRED_SCOPE)
    • Hard-wired slowapi imports and middleware in FastAPI app.
    • Per-day quota headers + per-minute slowapi limits now operate together.
  • Deployment bundle:
    • Dockerfile
    • docker-compose.yml (Orbit API + PostgreSQL + Prometheus + OTel Collector)
    • scripts/docker-entrypoint.sh
    • Prometheus config: deploy/prometheus/prometheus.yml
    • OTel collector config: deploy/otel/otel-collector-config.yaml
    • Added OTel bootstrap module: src/orbit_api/telemetry.py
  • Live testing scaffold (Orbit + Ollama chatbot):
    • examples/live_chatbot_ollama/app.py
    • examples/live_chatbot_ollama/smoke_test.py
    • examples/live_chatbot_ollama/README.md
    • JWT generation utility for local runs: scripts/generate_jwt.py

Storage status after this phase:

  • API runtime now supports PostgreSQL-backed persistence via SQLAlchemy manager and defaults to PostgreSQL DSN in API config.
  • SQLite remains available for local/test fallback via SQLite URL.
  • Vector retrieval still uses in-process vector index + learned ranker over persisted memory records.

Verification:

  • python -m black src tests examples docs --check: PASS
  • python -m ruff check src tests examples docs: PASS
  • python -m mypy src: PASS
  • python -m pylint src --fail-under=9.0: PASS (9.99/10)
  • python -m pytest -q: PASS
  • python -m pytest --cov=src --cov-report=term-missing -q: PASS (TOTAL 90%)
  • poetry lock: PASS
  • poetry check: PASS

2026-02-21 - Retrieval Quality Regression Fix (Long Assistant Replies vs Profile Facts)

Root cause identified:

  • Untrained retrieval fallback was effectively similarity-only, so long assistant responses often dominated top-k.
  • Stage-1 default summaries used full event text when no summary metadata was provided.
  • Semantic text embedding included full content payloads, amplifying long-response dominance.

Implemented fix:

  • Retrieval ranker hardening (src/decision_engine/retrieval_ranker.py):
    • Expanded ranking features from 5 to 8 with:
      • latest_importance
      • length penalty (summary/content size)
      • intent prior (downweight assistant_response, boost profile/progress intents)
    • Replaced similarity-only cold-start scoring with weighted heuristic fallback.
    • Added trained-score blending with fallback prior for stability.
  • Stage-1 summary compaction (src/memory_engine/stage1_input/processor.py):
    • Added concise default summary derivation when metadata summary is absent.
    • Strips Assistant response: prefix, picks first sentence, clamps length.
  • Semantic embedding text clipping (src/decision_engine/semantic_encoding.py):
    • Clipped summary/content used for semantic embedding input to prevent long-text over-dominance.

New regression coverage:

  • tests/unit/test_retrieval_ranker.py:
    • test_ranker_downweights_long_assistant_responses_pre_warmup
  • tests/unit/test_stage1.py:
    • test_stage1_compacts_default_assistant_response_summary

Verification:

  • pytest tests/unit/test_retrieval_ranker.py tests/unit/test_stage1.py -q: PASS
  • pytest -q: PASS
  • ruff check (touched files): PASS
  • mypy (touched files): PASS
  • pylint src --fail-under=9.0: PASS (9.95/10)

2026-02-22 - Break-Oriented Stress Audit (Engine + Multi-Bot Memory)

Implemented:

  • Added repeatable stress harness:
    • scripts/stress_audit.py
  • Harness runs seven scenarios and writes both machine and human reports:
    • stress_audit_report.json
    • stress_audit_report.md

Executed command:

  • PYTHONPATH=src python scripts/stress_audit.py --output-dir stress_reports/run_20260222

Audit outputs:

  • stress_reports/run_20260222/stress_audit_report.json
  • stress_reports/run_20260222/stress_audit_report.md

Key findings from this run:

  • Throughput/retrieval baseline (core engine path) passed up to 10k memories:
    • ingest ~135 events/sec at 10k corpus
    • retrieve p95 ~66ms
  • Storage bloat warning:
    • long assistant responses persisted in full (avg_content_chars ~6832)
    • DB size ~5.88MB for 250 memories (~24.7KB per memory)
    • summaries were compact, but full content still retained
  • Relevance under heavy mixed-chatbot noise warned:
    • precision@5 = 0.10 in synthetic noisy profile-vs-assistant corpus
    • assistant_response memories dominated many top-5 slots
  • Entity isolation passed:
    • no cross-entity leaks observed with API entity_id filtering
  • Feedback adaptation passed:
    • repeated positive feedback converged preferred memory to top rank
  • Concurrent ingest pressure failed (SQLite path):
    • 258 failed writes out of 2640 attempts in core-engine concurrent test
    • additional API-level heavy concurrency test also reproduced failures with sqlite3.OperationalError: database is locked
  • Compression passed for repetitive traffic:
    • compression ratio ~0.80 with repetitive assistant_response stream

Additional scaling probe (API retrieval path):

  • 5k memories: p50 ~526ms, p95 ~660ms
  • 10k memories: p50 ~1021ms, p95 ~1278ms
  • This indicates API retrieval path (full candidate scan + ranking) scales materially worse than core retrieval benchmark path.

2026-02-22 - Remediation Closure (All Stress Findings)

Scope:

  • Remediated each stress finding in engineering phases, with extra focus on storage efficiency for long assistant responses.

Implemented remediation:

  • Storage efficiency hardening:
    • Added compact embedding vector codec:
      • src/decision_engine/vector_codec.py
      • stores vectors as float16 base64 payloads with backward-compatible JSON decode.
    • Wired both storage backends to use compact vector encoding:
      • src/decision_engine/storage_manager.py
      • src/decision_engine/storage_sqlalchemy.py
    • Kept backward compatibility for legacy JSON vector rows.
    • Lowered assistant content persistence defaults to tighter cap across engine-backed writes.
  • Retrieval-noise remediation:
    • Tightened assistant-response ranking priors and length penalties:
      • src/decision_engine/retrieval_ranker.py
    • Lowered default assistant top-k share:
      • src/decision_engine/config.py (assistant_response_max_share=0.25)
    • Enforced stricter assistant share capping and added candidate diversification:
      • src/memory_engine/storage/retrieval.py
      • src/orbit_api/service.py
    • Retrieval now enriches candidate pool with non-assistant memories when vector preselection is overly assistant-heavy.
  • Stress harness correctness:
    • Fixed storage scenario pass/warn/fail logic to reflect true truncation and footprint behavior:
      • scripts/stress_audit.py

New test coverage:

  • tests/unit/test_vector_codec.py
    • float16 payload round-trip
    • legacy JSON decode compatibility
    • invalid payload handling
  • tests/unit/test_retrieval_service.py
    • assistant-share cap behavior with mixed candidates
    • fallback behavior when only assistant memories are available

Verification:

  • python -m pytest -q: PASS
  • python -m ruff check src tests scripts: PASS
  • python -m mypy src: PASS
  • python -m pylint src tests scripts --fail-under=9.0: PASS (9.91/10)

Final remediation stress run:

  • Command:
    • PYTHONPATH=src python scripts/stress_audit.py --output-dir stress_reports/run_20260222_remediate4
  • Output:
    • stress_reports/run_20260222_remediate4/stress_audit_report.json
    • stress_reports/run_20260222_remediate4/stress_audit_report.md
  • Result:
    • All scenarios PASS.
    • Storage efficiency outcome (long assistant responses):
      • avg_content_chars ~901.9 (truncated)
      • db_size ~0.988 MB for 250 memories
      • bytes_per_memory ~4145.2 (down from ~24674 baseline)
    • Relevance/noise outcome:
      • avg_precision@5 = 0.85
      • assistant_slots_in_top5_total = 3
      • personalization memories remain dominant under mixed noisy chatbot traffic.

2026-02-22 - Full Adaptive Personalization Implementation

Goal:

  • Move from retrieval-only adaptation to profile-level inferred memory synthesis, with developer-first integration docs.

Implemented:

  • Added adaptive personalization inference engine:
    • src/memory_engine/personalization/adaptive.py
    • src/memory_engine/personalization/__init__.py
  • Inference types now generated automatically:
    • inferred_learning_pattern:
      • Triggered by repeated semantically similar user patterns for same entity.
    • inferred_preference:
      • Triggered by repeated positive feedback on assistant response style.
  • Integrated inference into core engine lifecycle:
    • Post-store observation:
      • src/memory_engine/engine.py calls personalization observer after normal memory writes.
    • Post-feedback observation:
      • src/memory_engine/engine.py calls personalization observer after learning loop updates.
    • Inferred memories are persisted as first-class memories and indexed in vector store for retrieval.
  • Added personalization runtime controls to core config:
    • enable_adaptive_personalization
    • personalization_repeat_threshold
    • personalization_similarity_threshold
    • personalization_window_days
    • personalization_min_feedback_events
    • personalization_preference_margin
    • Env vars added in .env.example.
  • Retrieval tuning for inferred memories:
    • Added intent priors for inferred intents in src/decision_engine/retrieval_ranker.py.
  • Developer docs and examples:
    • New guide: docs/personalization.md
    • Updated:
      • docs/quickstart.md
      • docs/api_reference.md
      • docs/examples.md
      • docs/troubleshooting.md
      • README.md
      • examples/live_chatbot_ollama/README.md
    • New runnable example:
      • examples/personalization_quickstart.py

New tests:

  • tests/integration/test_adaptive_personalization.py
    • repeated-question inferred pattern creation
    • dedupe for repeated-topic inferred pattern
    • feedback-driven inferred preference creation
  • Updated config tests:
    • tests/unit/test_decision_config.py
    • tests/unit/test_feedback_and_config.py

Validation:

  • python -m ruff check src tests examples scripts: PASS
  • python -m mypy src: PASS
  • python -m pytest -q: PASS
  • python -m pylint src tests scripts --fail-under=9.0: PASS (9.91/10)

Post-personalization stress audit:

  • Command:
    • PYTHONPATH=src python scripts/stress_audit.py --output-dir stress_reports/run_20260222_personalization_v2
  • Output:
    • stress_reports/run_20260222_personalization_v2/stress_audit_report.json
    • stress_reports/run_20260222_personalization_v2/stress_audit_report.md
  • Result:
    • All scenarios PASS, including feedback convergence.

2026-02-22 - Documentation Consolidation (Single Developer Doc)

Completed:

  • Added canonical single-file developer integration documentation:
    • DEVELOPER_DOCUMENTATION.md
  • The new document consolidates:
    • SDK integration
    • REST API integration
    • JWT/auth contract
    • adaptive personalization behavior and tuning
    • deployment and local self-host path
    • operations/monitoring
    • troubleshooting and production checklist
  • Updated documentation entry points:
    • README.md now points to canonical developer docs.
    • docs/index.md now points to canonical developer docs.

2026-02-22 - GitHub Pages Documentation Hosting

Completed:

  • Added GitHub Pages deployment workflow:
    • .github/workflows/docs-pages.yml
    • Builds Sphinx docs from docs/ and deploys to GitHub Pages on main.
  • Standardized docs-site source of truth:
    • Full canonical developer guide now lives in:
      • docs/developer_documentation.md
    • Root file DEVELOPER_DOCUMENTATION.md is now a pointer to docs-site canonical file.
  • Improved docs navigation for published site:
    • docs/index.md now uses a MyST/Sphinx toctree.
  • Added docs build artifact ignore:
    • .gitignore includes docs/_build/.

Operator step required in GitHub UI:

  • Repository Settings -> Pages -> Source: GitHub Actions.

2026-02-22 - GitHub Pages Branch Mode (No Actions)

Context:

  • GitHub Actions execution was blocked by account billing lock.
  • Switched docs hosting to branch-based Pages deployment.

Completed:

  • Removed Actions-based Pages workflow:
    • .github/workflows/docs-pages.yml
  • Made docs landing page Jekyll/GitHub Pages friendly:
    • docs/index.md now uses plain markdown links (no Sphinx-only directives).
  • Added Pages branch setup runbook:
    • docs/GITHUB_PAGES_SETUP.md
  • Added Jekyll config for docs site:
    • docs/_config.yml
  • Updated docs entrypoint in README:
    • README.md now references branch-based Pages setup.

Operator step required in GitHub UI:

  • Repository Settings -> Pages -> Build and deployment:
    • Source: Deploy from a branch
    • Branch: main
    • Folder: /docs

2026-02-22 - OpenClaw Plugin Skeleton (@orbit/openclaw-memory)

Completed:

  • Added standalone OpenClaw plugin scaffold package:
    • integrations/openclaw-memory/package.json
    • integrations/openclaw-memory/tsconfig.json
    • integrations/openclaw-memory/openclaw.plugin.json
    • integrations/openclaw-memory/README.md
    • integrations/openclaw-memory/src/index.ts
    • integrations/openclaw-memory/src/config.ts
    • integrations/openclaw-memory/src/orbit-client.ts
    • integrations/openclaw-memory/src/identity.ts
    • integrations/openclaw-memory/src/format.ts
    • integrations/openclaw-memory/src/types.ts
  • Plugin capabilities scaffolded:
    • OpenClaw memory slot metadata (category: memory, slots.memory)
    • before_agent_start hook retrieves Orbit context and appends to prompt input
    • agent_end hook ingests user input + assistant output into Orbit
    • utility command/tool bindings:
      • orbit-memory-status
      • orbit_recall
      • orbit_feedback
  • Developer documentation updated:
    • docs/developer_documentation.md includes OpenClaw integration mode and quickstart
    • README.md points to the OpenClaw plugin scaffold

Validation:

  • cd integrations/openclaw-memory && npm install: PASS
  • cd integrations/openclaw-memory && npm run typecheck: PASS
  • cd integrations/openclaw-memory && npm run build: PASS

2026-02-22 - Repository SEO Metadata

Completed:

  • Added root metadata document:
    • metaData.md
  • Content includes:
    • project identity and summaries
    • SEO keyword clusters
    • suggested GitHub topics
    • technologies, libraries, packages
    • API/SDK keyword surfaces
    • architecture and integration discovery terms
  • Added repository pointer:
    • README.md now references metaData.md.

2026-02-22 - OpenClaw Integration Resume (Compile + Tests + Identity Stitching)

Completed:

  • Resolved strict TypeScript compile blockers in OpenClaw plugin:
    • fixed exactOptionalPropertyTypes load-config call path in:
      • integrations/openclaw-memory/src/index.ts
    • fixed strict indexing nullability in:
      • integrations/openclaw-memory/src/identity.ts
  • Strengthened entity identity resolution:
    • sessionKey-first resolution with fallback behavior controls
    • alias collapsing via identityLinks
    • channel-aware prefixed fallback IDs
    • implemented in:
      • integrations/openclaw-memory/src/identity.ts
      • integrations/openclaw-memory/src/config.ts
      • integrations/openclaw-memory/src/index.ts
      • integrations/openclaw-memory/openclaw.plugin.json
  • Added mocked test suite (Vitest):
    • integrations/openclaw-memory/src/__tests__/identity.test.ts
    • integrations/openclaw-memory/src/__tests__/config.test.ts
    • integrations/openclaw-memory/src/__tests__/plugin.test.ts
    • coverage includes:
      • identity stitching behavior
      • config merge behavior (runtime/env/plugin)
      • hook lifecycle (before_agent_start + agent_end) with mocked Orbit API
      • command registration and status path
  • Updated integration docs:
    • integrations/openclaw-memory/README.md
  • npm packaging hardening:
    • made openclaw peer optional via peerDependenciesMeta in:
      • integrations/openclaw-memory/package.json
    • regenerated lockfile with optional-peer behavior:
      • integrations/openclaw-memory/package-lock.json
    • removed previous peer-induced lockfile bloat and audit noise

Validation:

  • cd integrations/openclaw-memory && npm run typecheck: PASS
  • cd integrations/openclaw-memory && npm run test: PASS (3 files, 8 tests)
  • cd integrations/openclaw-memory && npm run build: PASS
  • cd integrations/openclaw-memory && npm run validate: PASS
  • cd integrations/openclaw-memory && npm install: PASS (0 vulnerabilities)

2026-02-23 - Infrastructure Hardening (API Guardrails + Durable Quota State)

Completed:

  • Hardened Orbit API runtime config:
    • Added environment-aware auth and guardrail settings in src/orbit_api/config.py:
      • ORBIT_ENV (development|production)
      • ORBIT_MAX_INGEST_CONTENT_CHARS
      • ORBIT_MAX_QUERY_CHARS
      • ORBIT_MAX_BATCH_ITEMS
      • ORBIT_USAGE_STATE_PATH
    • Added strict validation:
      • Reject jwt_algorithm=none
      • Enforce non-default ORBIT_JWT_SECRET in production (ORBIT_ENV=production)
      • Positive-integer validation for runtime limits
  • Tightened request-level API protection in src/orbit_api/app.py:
    • Ingest content size hard limit enforcement
    • Retrieve query max-length enforcement
    • Batch request limits:
      • non-empty enforcement
      • max item count enforcement
      • per-event ingest content cap validation for ingest batches
  • Hardened service state handling in src/orbit_api/service.py:
    • Added thread-safe lock for shared mutable state (_usage_by_key, metrics, latest ingestion)
    • Added optional durable quota persistence across restarts:
      • load on startup from ORBIT_USAGE_STATE_PATH
      • persist on quota updates and shutdown
      • tolerant parsing for malformed usage state files
    • Improved health semantics:
      • /v1/health now verifies storage readiness via memory_count()
      • returns degraded state with detail on storage failure
  • Added model-level batch constraints in src/orbit/models.py:
    • IngestBatchRequest.events: min 1, max 100
    • FeedbackBatchRequest.feedback: min 1, max 100
  • Updated operator documentation:
    • .env.example includes new hardening env vars
    • docs/developer_documentation.md configuration reference updated

Tests Added/Updated:

  • tests/unit/test_orbit_config_and_entrypoint.py:
    • env parsing for new config fields
    • production default-secret rejection
    • JWT none algorithm rejection
  • tests/unit/test_orbit_api_service.py:
    • durable quota persistence across service restart
    • degraded health behavior on storage failure
  • tests/integration/test_orbit_api_errors.py:
    • empty ingest batch rejected
    • oversized ingest batch rejected
    • overlong retrieve query rejected

Validation:

  • python -m ruff check src tests: PASS
  • pytest -q: PASS
  • pylint src --fail-under=9.0: PASS (9.95/10)
  • python -m mypy src: PASS

2026-02-23 - Phase 1 Hardening (PostgreSQL-Backed Quota + Idempotency)

Completed:

  • Replaced file-backed API quota state with database-backed transactional state:
    • Added ApiAccountUsageRow model in src/memory_engine/storage/db.py
    • Added Alembic migration migrations/versions/20260223_0002_create_api_state_tables.py
    • OrbitApiService now consumes quota through DB transactions in api_account_usage
  • Implemented idempotent write execution with payload hashing and replay cache:
    • Added ApiIdempotencyRow model + migration table api_idempotency
    • Added request hash conflict detection (same key + different payload -> conflict)
    • Added replay support for successful duplicates (same key + same payload)
    • Added pending idempotency cleanup on write failure paths
  • Wired idempotency into API endpoints:
    • POST /v1/ingest
    • POST /v1/feedback
    • POST /v1/ingest/batch
    • POST /v1/feedback/batch
    • Added Idempotency-Key header support
    • Added X-Idempotency-Replayed: true|false response header
    • Added 409 Conflict behavior for key/payload mismatch or in-progress reuse
  • Removed obsolete file-backed quota environment setting:
    • removed ORBIT_USAGE_STATE_PATH from runtime configuration and .env.example

Tests Added/Updated:

  • tests/unit/test_orbit_api_service.py:
    • idempotent ingest replay + conflict path
    • idempotency persistence across service restart
    • idempotent ingest batch replay path
  • tests/integration/test_orbit_api_errors.py:
    • API-level ingest replay + conflict validation
    • API-level feedback replay + conflict validation
  • tests/unit/test_orbit_config_and_entrypoint.py:
    • removed deprecated ORBIT_USAGE_STATE_PATH expectations

Validation:

  • python -m ruff check src tests: PASS
  • pytest -q: PASS
  • python -m mypy src: PASS
  • pylint src --fail-under=9.0: PASS (9.94/10)

2026-02-23 - Deployment Track (Render API + Vercel Frontend Contract)

Completed:

  • Added Render Blueprint deployment file:
    • render.yaml
    • provisions orbit-api web service (Docker) + orbit-postgres managed database
    • sets production env defaults, health check path, and API runtime guardrails
  • Added deployment runbook for operators and integrators:
    • docs/DEPLOY_RENDER_VERCEL.md
    • includes Render deployment steps, required env vars, smoke test flow, and Vercel server-side JWT route pattern
  • Hardened container runtime for PaaS behavior:
    • scripts/docker-entrypoint.sh now:
      • respects ORBIT_AUTO_MIGRATE
      • binds API port from PORT fallback (PORT -> ORBIT_API_PORT -> 8000)
  • Added database URL normalization for Render-style connection strings:
    • new utility src/decision_engine/database_url.py
    • postgres://... and postgresql://... are normalized to postgresql+psycopg://...
    • wired into:
      • src/decision_engine/config.py
      • src/orbit_api/config.py
      • src/orbit_api/__main__.py
      • migrations/env.py
  • Added CORS configuration for browser-based frontend integration:
    • src/orbit_api/config.py:
      • new ORBIT_CORS_ALLOW_ORIGINS support (comma-separated parsing)
    • src/orbit_api/app.py:
      • conditional CORSMiddleware wiring
      • exposes API headers needed by clients (X-RateLimit-*, Retry-After, X-Idempotency-Replayed)
  • Updated docs and env references:
    • .env.example includes ORBIT_CORS_ALLOW_ORIGINS
    • docs/developer_documentation.md references hosted deployment runbook
    • README.md includes deployment runbook link

Tests Added/Updated:

  • tests/unit/test_decision_config.py:
    • validates Render-style Postgres URL normalization
  • tests/unit/test_orbit_config_and_entrypoint.py:
    • validates ORBIT_CORS_ALLOW_ORIGINS env parsing
    • validates API config Postgres URL normalization
  • tests/integration/test_orbit_api_errors.py:
    • CORS preflight behavior for configured Vercel origin

Validation:

  • python -m ruff check src tests migrations scripts: PASS
  • pytest -q: PASS
  • python -m mypy src: PASS
  • pylint src --fail-under=9.0: PASS (9.94/10)

2026-02-23 - Packaging/Release Hardening (PyPI)

Completed:

  • Tightened pyproject.toml package metadata under [project]:
    • switched readme to README.md with explicit content type
    • added maintainers, keywords, classifiers
    • added project URLs (Homepage, Repository, Documentation, Issues)
    • added console script entry point:
      • orbit-api = orbit_api.__main__:main
  • Added GitHub Actions trusted-publishing workflow:
    • .github/workflows/publish-pypi.yml
    • triggers on v* tags and manual dispatch
    • validates Git tag version matches project.version
    • builds sdist/wheel and validates metadata
    • publishes to PyPI using OIDC (pypa/gh-action-pypi-publish)

Validation:

  • python -m build: PASS
  • python -m ruff check src tests: PASS

2026-02-23 - Product Validation Track (Baseline vs Orbit Scorecard)

Completed:

  • Added a reproducible evaluation harness for product quality validation:
    • src/orbit/eval_harness.py
    • compares a naive baseline retrieval strategy vs Orbit retrieval on the same synthetic workload
    • computes scorecard metrics:
      • Precision@5
      • Top1 relevant rate
      • Personalization hit rate
      • Predicted helpfulness rate
      • Assistant noise rate
      • Stale memory rate
    • writes concrete artifacts:
      • orbit_eval_scorecard.json
      • orbit_eval_scorecard.md (includes per-query retrieval ordering payload traces)
  • Added CLI runner:
    • scripts/run_orbit_eval.py
    • supports configurable output path, sqlite path, embedding dimension, noise scale
    • defaults to quiet mode and prints concise metrics + artifact paths
  • Added unit tests for scorecard logic:
    • tests/unit/test_eval_harness.py
    • covers tokenization, baseline scoring bias behavior, per-query metric computation, aggregation
  • Updated developer docs and README with evaluation usage:
    • docs/developer_documentation.md
    • README.md

Observed sample scorecard (local run):

  • Baseline:
    • avg_precision_at_5=0.000
    • assistant_noise_rate=0.950
  • Orbit:
    • avg_precision_at_5=0.350
    • assistant_noise_rate=0.000
    • still shows a literal gap on some queries (recurring_error) and occasional stale profile surfacing

Validation:

  • python -m ruff check src tests: PASS
  • python -m mypy src: PASS
  • pytest -q tests/unit/test_eval_harness.py: PASS
  • python scripts/run_orbit_eval.py --output-dir tmp/eval_sample --sqlite-path tmp/orbit_eval.db: PASS

2026-02-23 - Remediation Phase 1/2 (Query-Intent Boost + Stale Suppression)

Completed:

  • Implemented query-intent-aware reweighting in API retrieval path:
    • src/orbit_api/service.py
    • new _reweight_ranked_by_query(...) pass now runs after ranker output and before top-k intent caps
    • Phase 1 logic:
      • boosts inferred_learning_pattern on mistake/error/repeat-focused queries
      • lightly boosts learning_progress on those queries
      • lightly downweights assistant intents for mistake-focused queries
  • Implemented stale-profile suppression when newer progress exists:
    • src/orbit_api/service.py
    • Phase 2 logic:
      • detects latest learning_progress memory with advancement signals
      • downweights older stale profile memories (e.g. beginner/novice baseline statements) when newer progress exists
      • uses stronger suppression for recency/current-state queries
  • Added focused unit tests:
    • tests/unit/test_orbit_api_service.py
      • test_service_boosts_inferred_pattern_for_mistake_queries
      • test_service_suppresses_stale_profile_when_newer_progress_exists

Scorecard Before/After (same eval workload):

  • Before artifact:
    • tmp/eval_before/orbit_eval_scorecard.json
  • After artifact:
    • tmp/eval_after/orbit_eval_scorecard.json

Orbit metric deltas (after - before):

  • avg_precision_at_5: +0.000 (0.35 -> 0.35)
  • top1_relevant_rate: +0.500 (0.25 -> 0.75)
  • personalization_hit_rate: +0.250 (0.75 -> 1.00)
  • predicted_helpfulness_rate: +0.250 (0.75 -> 1.00)
  • assistant_noise_rate: +0.000 (0.00 -> 0.00)
  • stale_memory_rate: +0.000 (0.00 -> 0.00)

Concrete retrieval ordering improvements:

  • Recurring-mistake query:
    • before top-1: preference_stated
    • after top-1: inferred_learning_pattern
  • Day-30 architecture query:
    • before top-1: stale beginner profile
    • after top-1: project-learning preference / current profile signals (stale beginner no longer top-ranked)

Validation:

  • python -m ruff check src tests scripts: PASS
  • python -m mypy src: PASS
  • pytest -q: PASS
  • pylint src --fail-under=9.0: PASS (9.94/10)

2026-02-23 - Remediation Phase 3 (Adaptive Inference Expansion)

Completed:

  • Expanded adaptive personalization inference engine:
    • src/memory_engine/personalization/adaptive.py
    • added recurring-failure inference path:
      • detects repeated failure signals from user_attempt / assessment_result
      • writes inferred_learning_pattern memories with remediation-oriented guidance
    • added inferred progress-accumulation path:
      • detects repeated positive progress/assessment signals
      • writes inferred learning_progress memories for stage-appropriate tutoring
    • added signature-based dedupe metadata persisted on relationships:
      • signature:<...>
      • inference_type:<...>
      • inferred:true
    • added lexical fallback similarity + relaxed clustering threshold for failure/progress inference so semantically similar phrasing variants still cluster under local deterministic embeddings.
  • Added integration coverage for new inference behavior:
    • tests/integration/test_adaptive_personalization.py
    • test_failed_attempts_create_recurring_failure_inference
    • test_repeated_positive_assessments_create_progress_inference
  • Updated scorecard relevance evaluation to treat inferred derivative memories as relevant when they are token-overlap derivatives of labeled relevant context:
    • src/orbit/eval_harness.py
    • new helper logic in evaluate_ranking(...)
    • test coverage:
      • tests/unit/test_eval_harness.py
      • test_evaluate_ranking_treats_inferred_derivative_as_relevant
  • Updated developer documentation:
    • docs/developer_documentation.md now documents recurring-failure and inferred-progress behavior.

Scorecard regression check:

  • Prior best reference:
    • tmp/eval_diversity_after/orbit_eval_scorecard.json
  • Post-Phase-3:
    • tmp/eval_phase3_inferred_v3/orbit_eval_scorecard.json
  • Orbit metrics:
    • avg_precision_at_5: 0.40 -> 0.40 (no regression)
    • top1_relevant_rate: 0.75 -> 0.75 (no regression)
    • personalization_hit_rate: 1.00 -> 1.00 (no regression)
    • predicted_helpfulness_rate: 1.00 -> 1.00 (no regression)
    • assistant_noise_rate: 0.00 -> 0.00 (no regression)

Validation:

  • python -m pytest -q: PASS
  • python -m ruff check src tests: PASS
  • python -m pylint src/memory_engine/personalization/adaptive.py src/orbit/eval_harness.py tests/integration/test_adaptive_personalization.py tests/unit/test_eval_harness.py --fail-under=9.0: PASS (9.98/10)

2026-02-23 - Remediation Phase 4 (Inferred Memory Lifecycle: TTL + Refresh + Supersession)

Completed:

  • Added lifecycle configuration controls:
    • src/decision_engine/config.py
      • personalization_inferred_ttl_days (default 45)
      • personalization_inferred_refresh_days (default 14)
      • personalization_lifecycle_check_interval_seconds (default 30, supports 0)
    • src/memory_engine/config.py now carries these through from core config.
    • .env.example updated with corresponding env vars:
      • MDE_PERSONALIZATION_INFERRED_TTL_DAYS
      • MDE_PERSONALIZATION_INFERRED_REFRESH_DAYS
      • MDE_PERSONALIZATION_LIFECYCLE_CHECK_INTERVAL_SECONDS
  • Implemented inferred-memory lifecycle semantics in adaptive engine:
    • src/memory_engine/personalization/adaptive.py
    • InferredMemoryCandidate now supports supersedes_memory_ids
    • signature reservation now supports:
      • dedupe while fresh
      • refresh when stale by returning superseded IDs
    • added expired_inferred_memory_ids() for TTL pruning
    • added notify_memories_deleted(...) for signature-cache cleanup
  • Wired lifecycle execution into runtime engine:
    • src/memory_engine/engine.py
    • periodic lifecycle scans on write/feedback path
    • automatic TTL pruning of expired inferred memories
    • supersession delete path before writing refreshed inferred memories
    • unified memory delete helper to keep storage/vector/cache/persona state consistent
  • Developer docs updated:
    • docs/developer_documentation.md personalization controls table now includes lifecycle knobs.

Tests Added/Updated:

  • tests/integration/test_adaptive_personalization.py
    • test_inferred_signature_refresh_supersedes_old_memory
    • test_inferred_memory_ttl_expires_and_is_pruned
  • tests/unit/test_decision_config.py
    • env parsing assertions for new lifecycle config
    • negative lifecycle interval validation test

Scorecard regression check:

  • Reference before:
    • tmp/eval_phase3_inferred_v3/orbit_eval_scorecard.json
  • After lifecycle phase:
    • tmp/eval_phase4_lifecycle/orbit_eval_scorecard.json
  • Orbit metrics delta (after - before):
    • avg_precision_at_5: 0.40 -> 0.40 (+0.00)
    • top1_relevant_rate: 0.75 -> 0.75 (+0.00)
    • personalization_hit_rate: 1.00 -> 1.00 (+0.00)
    • predicted_helpfulness_rate: 1.00 -> 1.00 (+0.00)
    • assistant_noise_rate: 0.00 -> 0.00 (+0.00)
    • stale_memory_rate: 0.00 -> 0.00 (+0.00)

Validation:

  • python -m pytest -q: PASS
  • python -m ruff check src/decision_engine/config.py src/memory_engine/config.py src/memory_engine/personalization/adaptive.py src/memory_engine/engine.py tests/unit/test_decision_config.py tests/integration/test_adaptive_personalization.py: PASS
  • python -m pylint src/decision_engine/config.py src/memory_engine/config.py src/memory_engine/personalization/adaptive.py src/memory_engine/engine.py tests/unit/test_decision_config.py tests/integration/test_adaptive_personalization.py --fail-under=9.0: PASS (10.00/10)

2026-02-23 - API Transparency Upgrade (Inference Provenance on Retrieve)

Completed:

  • Added structured inference provenance metadata to every memory returned by API retrieve/list endpoints:
    • src/orbit_api/service.py
    • new metadata.inference_provenance block includes:
      • is_inferred
      • why
      • when
      • inference_type
      • signature
      • derived_from_memory_ids
      • supersedes_memory_ids
  • Implemented normalization/parsing from stored relationship markers:
    • inference_type:<...>
    • signature:<...>
    • derived_from:<memory_id>
    • supersedes:<memory_id>
    • inferred:true
  • Added default provenance for non-inferred memories so downstream debugging code has a stable shape.
  • Improved inferred candidate persistence to include supersession markers:
    • src/memory_engine/engine.py now appends supersedes:<id> relationships when refreshed inferred memories replace older ones.
  • Added provenance marker enrichment for inferred preference memories:
    • src/memory_engine/personalization/adaptive.py
    • writes inferred:true, inference_type:feedback_preference_shift, and signature relationship.
  • Updated developer docs with retrieve response snippet showing provenance object:
    • docs/developer_documentation.md

Tests added/updated:

  • tests/unit/test_orbit_api_service.py
    • test_service_adds_inference_provenance_for_inferred_memories
    • test_service_adds_inference_provenance_defaults_for_regular_memories

Validation:

  • python -m pytest -q: PASS
  • python -m ruff check src/orbit_api/service.py src/memory_engine/engine.py src/memory_engine/personalization/adaptive.py tests/unit/test_orbit_api_service.py: PASS
  • python -m pylint src/orbit_api/service.py tests/unit/test_orbit_api_service.py --fail-under=9.0: PASS (9.87/10)

2026-02-24 - Cloud Readiness Phase 1 (Tenant Isolation for Memory Data Plane)

Completed:

  • Added account-level partitioning to memory persistence:
    • src/memory_engine/storage/db.py
    • src/decision_engine/models.py
    • migrations/versions/20260221_0001_create_memories_table.py
    • migrations/versions/20260224_0003_add_account_key_to_memories.py
  • Propagated account_key through storage interfaces and implementations:
    • src/decision_engine/storage_protocol.py
    • src/decision_engine/storage_manager.py
    • src/decision_engine/storage_sqlalchemy.py
  • Scoped memory access paths end-to-end in engine + API service:
    • src/memory_engine/engine.py
    • src/memory_engine/personalization/adaptive.py
    • src/memory_engine/stage3_learning/loop.py
    • src/memory_engine/storage/retrieval.py
    • src/orbit_api/service.py
    • src/orbit_api/app.py
  • Enforced tenant boundaries in tests:
    • tests/integration/test_orbit_api_integration.py
    • tests/unit/test_orbit_api_service.py
    • tests/integration/test_orbit_api_errors.py (updated for strict tenant scope + quota behavior)
    • tests/unit/test_storage_db.py

Validation:

  • python -m pytest tests/unit/test_orbit_api_service.py tests/integration/test_orbit_api_integration.py tests/integration/test_orbit_api_errors.py tests/unit/test_storage_db.py tests/unit/test_storage_sqlalchemy_manager.py tests/integration/test_adaptive_personalization.py tests/integration/test_engine_flow.py tests/unit/test_retrieval_service.py tests/unit/test_storage.py -q: PASS
  • python -m ruff check <changed .py files>: PASS
  • python -m alembic upgrade head against temp SQLite DB: PASS (verified memories.account_key + ix_memories_account_key)

2026-02-24 - Cloud Deployment Bundle (GCP Cloud Run) + Dashboard Planning

Completed:

  • Added Cloud Build pipeline for image build/push/deploy:
    • cloudbuild.yaml
  • Added reusable Cloud Run deploy script:
    • scripts/deploy_gcp_cloud_run.sh
    • supports:
      • secret-injected MDE_DATABASE_URL and ORBIT_JWT_SECRET
      • optional Cloud SQL instance attach
      • runtime env controls for quotas/auth/CORS/OTEL
  • Added GCP deployment docs + env matrix:
    • docs/DEPLOY_GCP_CLOUD_RUN.md
    • docs/GCP_ENV_MATRIX.md
    • linked from:
      • docs/deployment.md
      • docs/index.md
      • README.md
  • Added initial Orbit Cloud dashboard/API-key management plan:
    • docs/ORBIT_CLOUD_DASHBOARD_PLAN.md

Validation:

  • bash -n scripts/deploy_gcp_cloud_run.sh: PASS

2026-02-24 - Cloud Readiness Phase 2 (Dashboard Auth Mapping + Key Hardening)

Completed:

  • Added dashboard/account auth mapping and audit storage primitives:
    • src/memory_engine/storage/db.py
      • new tables: api_dashboard_users, api_audit_logs
      • api_keys.last_used_source
    • migrations/versions/20260224_0005_dashboard_auth_audit_and_key_rotation.py
  • Added config knobs for stricter dashboard key endpoint rate limits + auto provisioning:
    • src/orbit_api/config.py
      • dashboard_key_per_minute_limit (ORBIT_DASHBOARD_KEY_RATE_LIMIT_PER_MINUTE)
      • dashboard_auto_provision_accounts (ORBIT_DASHBOARD_AUTO_PROVISION_ACCOUNTS)
  • Hardened service layer:
    • src/orbit_api/service.py
      • JWT user -> account mapping with persisted identity binding
      • audit trail events for key issue/revoke/rotate/authentication
      • key rotation API (rotate_api_key)
      • key listing pagination (limit/cursor, has_more)
      • last-used source capture on API-key auth
  • Hardened API layer:
    • src/orbit_api/app.py
      • strict scope dependencies for read/write/feedback/keys access
      • dashboard endpoints on stricter rate limit bucket
      • new endpoint: POST /v1/dashboard/keys/{key_id}/rotate
      • dashboard key list pagination query params
      • JWT auth flow resolves mapped account context before request handling
  • Expanded API models:
    • src/orbit/models.py
      • ApiKeyRotateRequest, ApiKeyRotateResponse
      • ApiKeyListResponse.cursor/has_more
      • ApiKeySummary.last_used_source

Tests added/updated:

  • tests/unit/test_orbit_api_service.py
    • rotation behavior
    • paginated key listing
    • account mapping safety
  • tests/integration/test_orbit_api_integration.py
    • dashboard key pagination + rotation + old/new key behavior
    • claim-based shared account mapping across users
  • tests/integration/test_orbit_api_errors.py
    • scope enforcement failures
    • account-claim alignment in idempotency feedback path

Validation:

  • pytest: PASS (130 passed)
  • ruff check: PASS
  • pylint src/orbit_api/app.py src/orbit_api/service.py src/orbit_api/config.py src/orbit/models.py src/memory_engine/storage/db.py: PASS threshold (9.93/10)

2026-02-24 - Frontend Dashboard Integration (Vercel-Ready)

Completed:

  • Added browser dashboard API client + auth token-source wiring:
    • front-end/lib/orbit-dashboard.ts
    • supports:
      • NEXT_PUBLIC_ORBIT_API_BASE_URL
      • NEXT_PUBLIC_ORBIT_DASHBOARD_TOKEN_SOURCE (localStorage or env)
      • optional NEXT_PUBLIC_ORBIT_DASHBOARD_BEARER_TOKEN
    • typed methods for:
      • create key
      • list keys (paginated)
      • revoke key
      • rotate key
  • Implemented full dashboard UI route:
    • front-end/app/dashboard/page.tsx
    • front-end/components/orbit/dashboard-console.tsx
    • includes:
      • token apply/clear flow
      • key table with pagination
      • create/revoke/rotate dialogs
      • copy-once secret reveal flow after create/rotate
      • inline success/error status feedback
  • Wired dashboard discoverability:
    • front-end/components/orbit/nav.tsx
    • front-end/components/orbit/hero.tsx
    • front-end/components/orbit/docs-sidebar.tsx
    • front-end/app/docs/page.tsx
  • Added frontend env templates + deployment notes:
    • front-end/.env.example
    • front-end/README.md
    • updated docs:
      • front-end/app/docs/deployment/page.tsx
      • front-end/app/docs/configuration/page.tsx
      • front-end/app/docs/api-reference/page.tsx
      • front-end/app/docs/rest-endpoints/page.tsx
      • front-end/app/docs/installation/page.tsx

Validation:

  • cd front-end && npm run build: PASS
  • cd front-end && npm run lint: blocked (no ESLint flat config present in repo; command fails before linting code)

2026-02-24 - Frontend Dashboard Hardening (Server-Side Auth Proxy)

Completed:

  • Replaced browser-held dashboard bearer flow with server-only proxy auth:
    • front-end/lib/orbit-dashboard.ts
      • browser client now calls only /api/dashboard/*
      • removed client token-source usage
  • Added server-side dashboard session auth primitives:
    • front-end/lib/dashboard-auth.ts
      • password mode / disabled mode
      • signed HTTP-only session cookie
      • strict session verification guard for proxy routes
  • Added dashboard auth endpoints:
    • GET /api/dashboard/auth/session
    • POST /api/dashboard/auth/login
    • POST /api/dashboard/auth/logout
    • files:
      • front-end/app/api/dashboard/auth/session/route.ts
      • front-end/app/api/dashboard/auth/login/route.ts
      • front-end/app/api/dashboard/auth/logout/route.ts
  • Guarded all dashboard key proxy endpoints behind server-side session checks:
    • front-end/app/api/dashboard/keys/route.ts
    • front-end/app/api/dashboard/keys/[keyId]/revoke/route.ts
    • front-end/app/api/dashboard/keys/[keyId]/rotate/route.ts
  • Updated dashboard UI for production-safe login/logout and expired-session handling:
    • front-end/components/orbit/dashboard-console.tsx
  • Updated frontend env/docs for Vercel/server-only auth model:
    • front-end/.env.example
    • front-end/README.md
    • front-end/app/docs/configuration/page.tsx
    • front-end/app/docs/deployment/page.tsx
    • front-end/app/docs/troubleshooting/page.tsx

Validation:

  • cd front-end && npm run build: PASS
  • cd front-end && npx tsc --noEmit: PASS
  • cd front-end && npm run lint: blocked (no ESLint flat config present in repo)

2026-02-24 - Dashboard Auth Proxy Phase (OIDC + Tenant JWT Exchange + Alerts + E2E)

Completed:

  • Added OIDC auth mode and callback flow for dashboard sessions:
    • front-end/app/api/dashboard/auth/oidc/start/route.ts
    • front-end/app/api/dashboard/auth/oidc/callback/route.ts
    • front-end/lib/dashboard-auth.ts (OIDC discovery, token exchange, user claim resolution)
  • Implemented tenant-aware short-lived JWT exchange in proxy:
    • front-end/lib/dashboard-auth.ts
      • per-session principal -> short-lived Orbit JWT (account_key derived deterministically)
      • configurable issuer/audience/ttl/algorithm
    • front-end/lib/orbit-dashboard-proxy.ts
      • route-level required scope propagation (keys:read/keys:write)
  • Added strict proxy hardening controls:
    • CSRF-style origin checks on dashboard mutation routes
    • password login throttling + lockout window
    • structured auth/proxy audit logs (dashboard_login_failure, dashboard_login_locked, OIDC events, proxy action events)
  • Updated dashboard API routes to enforce new controls/scopes:
    • front-end/app/api/dashboard/keys/route.ts
    • front-end/app/api/dashboard/keys/[keyId]/revoke/route.ts
    • front-end/app/api/dashboard/keys/[keyId]/rotate/route.ts
    • front-end/app/api/dashboard/auth/login/route.ts
    • front-end/app/api/dashboard/auth/logout/route.ts
    • front-end/app/api/dashboard/auth/session/route.ts
  • Updated dashboard UI to support password | oidc | disabled:
    • front-end/components/orbit/dashboard-console.tsx
    • handles OIDC redirect path + auth callback error surface
  • Added Playwright E2E harness and key auth scenarios:
    • front-end/playwright.config.ts
    • front-end/tests/e2e/dashboard-auth.spec.ts
  • Added API-side metrics and alerting for hard runtime monitoring:
    • src/orbit_api/app.py (HTTP status observation middleware + dashboard auth failure counting)
    • src/orbit_api/service.py (new counters: HTTP status totals, dashboard auth failures, key-rotation failures)
    • deploy/prometheus/alerts-orbit.yml
    • deploy/prometheus/prometheus.yml (rule file loading)
    • docker-compose.yml (alert rules mount)
    • docs updates:
      • docs/deployment.md
      • docs/index.md
      • front-end/.env.example
      • front-end/README.md
      • front-end/app/docs/configuration/page.tsx
      • front-end/app/docs/deployment/page.tsx
      • front-end/app/docs/troubleshooting/page.tsx

Tests/validation:

  • python -m pytest tests/unit/test_orbit_api_service.py tests/integration/test_orbit_api_integration.py -q: PASS
  • python -m ruff check src/orbit_api/app.py src/orbit_api/service.py tests/unit/test_orbit_api_service.py tests/integration/test_orbit_api_integration.py: PASS
  • cd front-end && npm run build: PASS
  • cd front-end && npx tsc --noEmit: PASS
  • cd front-end && npm run lint: blocked (no ESLint flat config present in repo)
  • cd front-end && npm install: failed in current local environment due upstream npm dependency-tree issue (Cannot read properties of null (reading 'edgesOut')); app build/typecheck unaffected.