jesus/Vapora
1
0
Fork 0
Code Issues Pull Requests Actions 3 Packages Projects Releases Wiki Activity
30 Commits 1 Branch 0 Tags
Commit Graph

15 Commits

Author SHA1 Message Date
Jesús Pérez
6e0a706cdb
chore: add cd/ci ops provisioning
Some checks failed
Rust CI / Security Audit (push) Has been cancelled
Details
Rust CI / Check + Test + Lint (nightly) (push) Has been cancelled
Details
Rust CI / Check + Test + Lint (stable) (push) Has been cancelled
Details
2026-01-12 03:37:18 +00:00
Jesús Pérez
4cbbf3f864
chore: add setup md files
Some checks failed
Rust CI / Security Audit (push) Has been cancelled
Details
Rust CI / Check + Test + Lint (nightly) (push) Has been cancelled
Details
Rust CI / Check + Test + Lint (stable) (push) Has been cancelled
Details
2026-01-12 03:17:04 +00:00
Jesús Pérez
ff98adba88
chore: fix README.md
Some checks failed
Rust CI / Security Audit (push) Has been cancelled
Details
Rust CI / Check + Test + Lint (nightly) (push) Has been cancelled
Details
Rust CI / Check + Test + Lint (stable) (push) Has been cancelled
Details
Nickel Type Check / Nickel Type Checking (push) Has been cancelled
Details
2026-01-11 21:53:30 +00:00
Jesús Pérez
8f6a884f6e docs: Update README and CHANGELOG with web assets optimization 
- Document web assets restructuring with minification pipeline
  * 32% compression (26KB → 18KB)
  * Bilingual support (EN/ES) preserved
  * Automated minify.sh script for version sync
  * Complete README.md guide with examples

- Add web assets structure to project directory layout in README
  - New assets/web/ section with source and production versions
  - Reference to minification script and documentation

- Include Just recipes documentation for local development
  - Show `just help` commands for discovering available recipes
  - Document 50+ recipes for build, test, and CI operations

- Update CHANGELOG with infrastructure improvements
  - Web assets optimization (32% compression)
  - Just recipes CI/CD system (50+ commands)
  - Code quality improvements and bug fixes
  - Markdown linting compliance achieved
  - All tests passing (55/55 in vapora-backend)

- Add build and test results to unreleased changes section
  - Clean compilation with 0 warnings in vapora-backend
  - 55 tests passing
  - Clippy compliance achieved
 2026-01-11 20:12:56 +00:00
Jesús Pérez
d14150da75 feat: Phase 5.3 - Multi-Agent Learning Infrastructure 
Implement intelligent agent learning from Knowledge Graph execution history
with per-task-type expertise tracking, recency bias, and learning curves.

## Phase 5.3 Implementation

### Learning Infrastructure (✅ Complete)
- LearningProfileService with per-task-type expertise metrics
- TaskTypeExpertise model tracking success_rate, confidence, learning curves
- Recency bias weighting: recent 7 days weighted 3x higher (exponential decay)
- Confidence scoring prevents overfitting: min(1.0, executions / 20)
- Learning curves computed from daily execution windows

### Agent Scoring Service (✅ Complete)
- Unified AgentScore combining SwarmCoordinator + learning profiles
- Scoring formula: 0.3*base + 0.5*expertise + 0.2*confidence
- Rank agents by combined score for intelligent assignment
- Support for recency-biased scoring (recent_success_rate)
- Methods: rank_agents, select_best, rank_agents_with_recency

### KG Integration (✅ Complete)
- KGPersistence::get_executions_for_task_type() - query by agent + task type
- KGPersistence::get_agent_executions() - all executions for agent
- Coordinator::load_learning_profile_from_kg() - core KG→Learning integration
- Coordinator::load_all_learning_profiles() - batch load for multiple agents
- Convert PersistedExecution → ExecutionData for learning calculations

### Agent Assignment Integration (✅ Complete)
- AgentCoordinator uses learning profiles for task assignment
- extract_task_type() infers task type from title/description
- assign_task() scores candidates using AgentScoringService
- Fallback to load-based selection if no learning data available
- Learning profiles stored in coordinator.learning_profiles RwLock

### Profile Adapter Enhancements (✅ Complete)
- create_learning_profile() - initialize empty profiles
- add_task_type_expertise() - set task-type expertise
- update_profile_with_learning() - update swarm profiles from learning

## Files Modified

### vapora-knowledge-graph/src/persistence.rs (+30 lines)
- get_executions_for_task_type(agent_id, task_type, limit)
- get_agent_executions(agent_id, limit)

### vapora-agents/src/coordinator.rs (+100 lines)
- load_learning_profile_from_kg() - core KG integration method
- load_all_learning_profiles() - batch loading for agents
- assign_task() already uses learning-based scoring via AgentScoringService

### Existing Complete Implementation
- vapora-knowledge-graph/src/learning.rs - calculation functions
- vapora-agents/src/learning_profile.rs - data structures and expertise
- vapora-agents/src/scoring.rs - unified scoring service
- vapora-agents/src/profile_adapter.rs - adapter methods

## Tests Passing
- learning_profile: 7 tests ✅
- scoring: 5 tests ✅
- profile_adapter: 6 tests ✅
- coordinator: learning-specific tests ✅

## Data Flow
1. Task arrives → AgentCoordinator::assign_task()
2. Extract task_type from description
3. Query KG for task-type executions (load_learning_profile_from_kg)
4. Calculate expertise with recency bias
5. Score candidates (SwarmCoordinator + learning)
6. Assign to top-scored agent
7. Execution result → KG → Update learning profiles

## Key Design Decisions
✅ Recency bias: 7-day half-life with 3x weight for recent performance
✅ Confidence scoring: min(1.0, total_executions / 20) prevents overfitting
✅ Hierarchical scoring: 30% base load, 50% expertise, 20% confidence
✅ KG query limit: 100 recent executions per task-type for performance
✅ Async loading: load_learning_profile_from_kg supports concurrent loads

## Next: Phase 5.4 - Cost Optimization
Ready to implement budget enforcement and cost-aware provider selection.
 2026-01-11 13:03:53 +00:00
Jesús Pérez
ca3fa91d5d chore: fix graphs 2025-11-10 12:24:13 +00:00
Jesús Pérez
748606325a chore: fix graphs 2025-11-10 12:23:35 +00:00
Jesús Pérez
e7264f069d chore: fix graphs 2025-11-10 12:21:03 +00:00
Jesús Pérez
d095e520f3 chore: fix graphs 2025-11-10 12:20:33 +00:00
Jesús Pérez
5fde6a87da chore: fix graphs 2025-11-10 12:19:39 +00:00
Jesús Pérez
c97f712573 chore: fix graphs 2025-11-10 12:18:34 +00:00
Jesús Pérez
2669e2822f chore: fix version 2025-11-10 12:13:05 +00:00
Jesús Pérez
cd8bc02944 chore: fix content 2025-11-10 11:45:23 +00:00
Jesús Pérez
d89a2bc26f chore: fix content 2025-11-10 11:41:29 +00:00
Jesús Pérez
f9dbd54ca6 init project 2025-11-09 12:27:37 +00:00