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.
126 lines
3.6 KiB
Plaintext
126 lines
3.6 KiB
Plaintext
#!/usr/bin/env nu
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# sync-tracking.nu - Synchronize tracking data from all projects to central database
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# Follows NuShell 0.108+ guidelines with explicit types and Rule 17 string interpolation
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def main [
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--projects-dir: string = "/Users/Akasha" # No bool type annotation (Rule!)
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--verbose = false
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--dry-run = false
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]: void {
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if $verbose {
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print "🔄 Starting tracking sync..."
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print $"📁 Scanning projects in: [$projects_dir]"
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}
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# Rule 3: Early validation
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if not ($projects_dir | path exists) {
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print $"❌ Error: Projects directory [$projects_dir] not found"
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return
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}
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# Find all .coder directories
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let coder_projects = (
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ls $projects_dir --all --recursive
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| where type == "dir"
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| where name == ".coder"
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| get parent_path
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)
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if ($coder_projects | length) == 0 {
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print "⚠️ No .coder directories found"
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return
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}
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print $"✅ Found (($coder_projects | length)) projects to sync"
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# Rule 1: Single purpose - process each project
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let total_synced = (
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$coder_projects
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| each { |project_path|
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sync-project $project_path $verbose $dry_run
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}
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| math sum
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)
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print $"
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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✅ Sync Complete
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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📊 Total entries synced: ($total_synced)
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⏱️ Timestamp: (date now | format date '%Y-%m-%d %H:%M:%S UTC')
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"
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}
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# Rule 1: Single purpose - only syncs one project
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def sync-project [project-path: string, verbose: bool, dry-run: bool]: int {
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# Rule 3: Early return validation
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if not ($project-path | path exists) {
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if $verbose {
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print $"⚠️ Skipping [$project-path] - not found"
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}
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return 0
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}
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# Rule 17: ($expr) for expressions, [$var] for variables
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let changes-file = $"[$project-path]/.coder/changes.md"
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let todo-file = $"[$project-path]/.coder/todo.md"
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let mut synced = 0
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# Process changes.md
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if ($changes-file | path exists) {
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if $verbose {
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print $"📝 Syncing changes from [$changes-file]"
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}
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if not $dry_run {
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let result = (
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curl --silent --request POST "http://localhost:3000/api/v1/tracking/sync" \
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--header "Content-Type: application/json" \
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--data {
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project: $project-path
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type: "changes"
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file: $changes-file
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} | to json
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)
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if ($result | has "error") {
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print $"❌ Error syncing changes: ($result.error)"
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} else {
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$synced = ($synced + 1)
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}
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}
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}
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# Process todo.md
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if ($todo-file | path exists) {
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if $verbose {
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print $"📝 Syncing todos from [$todo-file]"
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}
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if not $dry_run {
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let result = (
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curl --silent --request POST "http://localhost:3000/api/v1/tracking/sync" \
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--header "Content-Type: application/json" \
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--data {
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project: $project-path
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type: "todos"
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file: $todo-file
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} | to json
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)
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if ($result | has "error") {
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print $"❌ Error syncing todos: ($result.error)"
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} else {
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$synced = ($synced + 1)
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}
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}
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}
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if $verbose {
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print $"✅ Synced [$project-path]"
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}
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$synced
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}
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