Vapora/CHANGELOG.md

# Changelog

All notable changes to VAPORA will be documented in this file.

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [Unreleased]

### Added

- **Comprehensive Examples System**: 26+ executable examples demonstrating all VAPORA capabilities
  - **Basic Examples (6)**: Foundation for each core crate
    - `crates/vapora-agents/examples/01-simple-agent.rs` - Agent registry & metadata
    - `crates/vapora-llm-router/examples/01-provider-selection.rs` - Multi-provider routing
    - `crates/vapora-swarm/examples/01-agent-registration.rs` - Swarm coordination basics
    - `crates/vapora-knowledge-graph/examples/01-execution-tracking.rs` - Temporal KG persistence
    - `crates/vapora-backend/examples/01-health-check.rs` - Backend verification
    - `crates/vapora-shared/examples/01-error-handling.rs` - Error type patterns
  - **Intermediate Examples (9)**: System integration scenarios
    - Learning profiles with recency bias weighting
    - Budget enforcement with 3-tier fallback strategy
    - Cost tracking and ROI analysis per provider/task type
    - Swarm load distribution and capability-based filtering
    - Knowledge graph learning curves and similarity search
    - Full-stack agent + routing integration
    - Multi-agent swarm with expertise-based assignment
  - **Advanced Examples (2)**: Complete end-to-end workflows
    - Full system integration (API → Swarm → Agents → Router → KG)
    - REST API integration with real-time WebSocket updates
  - **Real-World Use Cases (3)**: Production scenarios with business value
    - Code review workflow: 3-stage pipeline with cost optimization ($488/month savings)
    - Documentation generation: Automated sync with quality checks ($989/month savings)
    - Issue triage: Intelligent classification with selective escalation ($997/month savings)
  - **Interactive Notebooks (4)**: Marimo-based exploration
    - Agent basics with role configuration
    - Budget playground with cost projections
    - Learning curves visualization with confidence intervals
    - Cost analysis with provider comparison charts

- **Examples Documentation**: 600+ line comprehensive guide
  - `docs/examples-guide.md` - Master reference for all examples
  - Example-by-example breakdown with learning objectives and run instructions
  - Three learning paths: Quick Overview (30min), System Integration (90min), Production Ready (2-3hrs)
  - Common tasks mapped to relevant examples
  - Business value analysis for real-world scenarios
  - Troubleshooting section and quick reference commands

- **Examples Organization**:
  - Per-crate examples following `crates/*/examples/` Cargo convention
  - Root-level examples in `examples/full-stack/` and `examples/real-world/`
  - Master README catalog at `examples/README.md` with navigation
  - Python requirements for Marimo notebooks: `examples/notebooks/requirements.txt`

- **Web Assets Optimization**: Restructured landing page with minification pipeline
  - Separated source (`assets/web/src/index.html`) from minified production version
  - Automated minification script (`assets/web/minify.sh`) for version synchronization
  - 32% compression achieved (26KB → 18KB)
  - Bilingual content (English/Spanish) preserved with localStorage persistence
  - Complete documentation in `assets/web/README.md`

- **Infrastructure & Build System**
  - Just recipes for CI/CD automation (50+ recipes organized by category)
  - Parametrized help system for command discovery
  - Integration with development workflows

### Changed

- **Code Quality Improvements**
  - Removed unused imports from API and workflow modules (5+ files)
  - Fixed 6 unnecessary `mut` keyword warnings in provider analytics
  - Improved code patterns: converted verbose match to `matches!` macro (workflow/state.rs)
  - Applied automatic clippy fixes for idiomatic Rust

- **Documentation & Linting**
  - Fixed markdown linting compliance in `assets/web/README.md`
  - Proper code fence language specifications (MD040)
  - Blank lines around code blocks (MD031)
  - Table formatting with compact style (MD060)

### Fixed

- **Compilation & Testing**
  - Eliminated all unused import warnings in vapora-backend
  - Suppressed architectural dead code with appropriate attributes
  - All 55 tests passing in vapora-backend
  - 0 compilation errors, clean build output

### Technical Details

- **Architecture**: Refactored unused imports from workflow and API modules
  - Tests moved to test-only scope for AgentConfig/RegistryConfig types
  - Intentional suppression for components not yet integrated
  - Future-proof markers for architectural patterns

- **Build Status**: Clean compilation pipeline
  - `cargo build -p vapora-backend` ✅
  - `cargo clippy -p vapora-backend` ✅ (5 nesting suggestions only)
  - `cargo test -p vapora-backend` ✅ (55/55 passing)

## [1.2.0] - 2026-01-11

### Added - Phase 5.3: Multi-Agent Learning

- **Learning Profiles**: Per-task-type expertise tracking for each agent
  - `LearningProfile` struct with task-type expertise mapping
  - Success rate calculation with recency bias (7-day window weighted 3x)
  - Confidence scoring based on execution count (prevents small-sample overfitting)
  - Learning curve computation with exponential decay

- **Agent Scoring Service**: Unified agent selection combining swarm metrics + learning
  - Formula: `final_score = 0.3*base + 0.5*expertise + 0.2*confidence`
  - Base score from SwarmCoordinator (load balancing)
  - Expertise score from learning profiles (historical success)
  - Confidence weighting dampens low-execution-count agents

- **Knowledge Graph Integration**: Learning curve calculator
  - `calculate_learning_curve()` with time-series expertise evolution
  - `apply_recency_bias()` with exponential weighting formula
  - Aggregate by time windows (daily/weekly) for trend analysis

- **Coordinator Enhancement**: Learning-based agent selection
  - Extract task type from description/role
  - Query learning profiles for task-specific expertise
  - Replace simple load balancing with learning-aware scoring
  - Background profile synchronization (30s interval)

### Added - Phase 5.4: Cost Optimization

- **Budget Manager**: Per-role cost enforcement
  - `BudgetConfig` with TOML serialization/deserialization
  - Role-specific monthly and weekly limits (in cents)
  - Automatic fallback provider when budget exceeded
  - Alert thresholds (default 80% utilization)
  - Weekly/monthly automatic resets

- **Configuration Loading**: Graceful budget initialization
  - `BudgetConfig::load()` with strict validation
  - `BudgetConfig::load_or_default()` with fallback to empty config
  - Environment variable override: `BUDGET_CONFIG_PATH`
  - Validation: limits > 0, thresholds in [0.0, 1.0]

- **Cost-Aware Routing**: Provider selection with budget constraints
  - Three-tier enforcement:
    1. Budget exceeded → force fallback provider
    2. Near threshold (>80%) → prefer cost-efficient providers
    3. Normal → rule-based routing with cost as tiebreaker
  - Cost efficiency ranking: `(quality * 100) / (cost + 1)`
  - Fallback chain ordering by cost (Ollama → Gemini → OpenAI → Claude)

- **Prometheus Metrics**: Real-time cost and budget monitoring
  - `vapora_llm_budget_remaining_cents{role}` - Monthly budget remaining
  - `vapora_llm_budget_utilization{role}` - Budget usage fraction (0.0-1.0)
  - `vapora_llm_fallback_triggered_total{role,reason}` - Fallback event counter
  - `vapora_llm_cost_per_provider_cents{provider}` - Cumulative cost per provider
  - `vapora_llm_tokens_per_provider{provider,type}` - Token usage tracking

- **Grafana Dashboards**: Visual monitoring
  - Budget utilization gauge (color thresholds: 70%, 90%, 100%)
  - Cost distribution pie chart (percentage per provider)
  - Fallback trigger time series (rate of fallback activations)
  - Agent assignment latency histogram (P50, P95, P99)

- **Alert Rules**: Prometheus alerting
  - `BudgetThresholdExceeded`: Utilization > 80% for 5 minutes
  - `HighFallbackRate`: Rate > 0.1 for 10 minutes
  - `CostAnomaly`: Cost spike > 2x historical average
  - `LearningProfilesInactive`: No updates for 5 minutes

### Added - Integration & Testing

- **End-to-End Integration Tests**: Validate learning + budget interaction
  - `test_end_to_end_learning_with_budget_enforcement()` - Full system test
  - `test_learning_selection_with_budget_constraints()` - Budget pressure scenarios
  - `test_learning_profile_improvement_with_budget_tracking()` - Learning evolution

- **Agent Server Integration**: Budget initialization at startup
  - Load budget configuration from `config/agent-budgets.toml`
  - Initialize BudgetManager with Arc for thread-safe sharing
  - Attach to coordinator via `with_budget_manager()` builder pattern
  - Graceful fallback if no configuration exists

- **Coordinator Builder Pattern**: Budget manager attachment
  - Added `budget_manager: Option<Arc<BudgetManager>>` field
  - `with_budget_manager()` method for fluent API
  - Updated all constructors (`new()`, `with_registry()`)
  - Backward compatible (works without budget configuration)

### Added - Documentation

- **Implementation Summary**: `.coder/2026-01-11-phase-5-completion.done.md`
  - Complete architecture overview (3-layer integration)
  - All files created/modified with line counts
  - Prometheus metrics reference
  - Quality metrics (120 tests passing)
  - Educational insights

- **Gradual Deployment Guide**: `guides/gradual-deployment-guide.md`
  - Week 1: Staging validation (24 hours)
  - Week 2-3: Canary deployment (incremental traffic shift)
  - Week 4+: Production rollout (100% traffic)
  - Automated rollback procedures (< 5 minutes)
  - Success criteria per phase
  - Emergency procedures and checklists

### Changed

- **LLMRouter**: Enhanced with budget awareness
  - `select_provider_with_budget()` method for budget-aware routing
  - Fixed incomplete fallback implementation (lines 227-246)
  - Cost-ordered fallback chain (cheapest first)

- **ProfileAdapter**: Learning integration
  - `update_from_kg_learning()` method for learning profile sync
  - Query KG for task-specific executions with recency filter
  - Calculate success rate with 7-day exponential decay

- **AgentCoordinator**: Learning-based assignment
  - Replaced min-load selection with `AgentScoringService`
  - Extract task type from task description
  - Combine swarm metrics + learning profiles for final score

### Fixed

- **Clippy Warnings**: All resolved (0 warnings)
  - `redundant_guards` in BudgetConfig
  - `needless_borrow` in registry defaults
  - `or_insert_with` → `or_default()` conversions
  - `map_clone` → `cloned()` conversions
  - `manual_div_ceil` → `div_ceil()` method

- **Test Warnings**: Unused variables marked with underscore prefix

### Technical Details

**New Files Created (13)**:

- `vapora-agents/src/learning_profile.rs` (250 lines)
- `vapora-agents/src/scoring.rs` (200 lines)
- `vapora-knowledge-graph/src/learning.rs` (150 lines)
- `vapora-llm-router/src/budget.rs` (300 lines)
- `vapora-llm-router/src/cost_ranker.rs` (180 lines)
- `vapora-llm-router/src/cost_metrics.rs` (120 lines)
- `config/agent-budgets.toml` (50 lines)
- `vapora-agents/tests/end_to_end_learning_budget_test.rs` (NEW)
- 4+ integration test files (700+ lines total)

**Modified Files (10)**:

- `vapora-agents/src/coordinator.rs` - Learning integration
- `vapora-agents/src/profile_adapter.rs` - KG sync
- `vapora-agents/src/bin/server.rs` - Budget initialization
- `vapora-llm-router/src/router.rs` - Cost-aware routing
- `vapora-llm-router/src/lib.rs` - Budget exports
- Plus 5 more lib.rs and config updates

**Test Suite**:

- Total: 120 tests passing
- Unit tests: 71 (vapora-agents: 41, vapora-llm-router: 30)
- Integration tests: 42 (learning: 7, coordinator: 9, budget: 11, cost: 12, end-to-end: 3)
- Quality checks: Zero warnings, clippy -D warnings passing

**Deployment Readiness**:

- Staging validation checklist complete
- Canary deployment Istio VirtualService configured
- Grafana dashboards deployed
- Alert rules created
- Rollback automation ready (< 5 minutes)

## [0.1.0] - 2026-01-10

### Added

- Initial release with core platform features
- Multi-agent orchestration with 12 specialized roles
- Multi-IA router (Claude, OpenAI, Gemini, Ollama)
- Kanban board UI with glassmorphism design
- SurrealDB multi-tenant data layer
- NATS JetStream agent coordination
- Kubernetes-native deployment
- Istio service mesh integration
- MCP plugin system
- RAG integration for semantic search
- Cedar policy engine RBAC
- Full-stack Rust implementation (Axum + Leptos)

[unreleased]: https://github.com/vapora-platform/vapora/compare/v1.2.0...HEAD
[1.2.0]: https://github.com/vapora-platform/vapora/compare/v0.1.0...v1.2.0
[0.1.0]: https://github.com/vapora-platform/vapora/releases/tag/v0.1.0