Phase 10. Metacognition is a cognitive process with deterministic self-checks (insufficient evidence, single-source reliance, model output without evidence, repeated failed hypotheses, stale contradictions, calibration overconfidence); its warnings compete for attention and, when admitted, add counter-evidence or open an investigation goal. Reflection reviews the period since the last run (prediction errors, rejected beliefs, corrections, status changes, completed goals, contradictions, calibration), turns repeated failures into procedural lessons written once, and records a reflection event; a model may only word the prose within the mind's budget. Consolidation clusters unconsolidated episodes by shared stemmed terms, creates a belief whose confidence is computed from the episodes as evidence and a semantic memory linked to each episode by derived_from, and records jobs with inputs and outputs. Wording may come from the consolidate prompt within a per-run model budget; the job says which. Operators can run, pause and reject; originals are never touched. The narrative hook keeps a five-part first-person narrative built from state and stored with narrative_updated events. The notification hook applies explicit thresholded rules, aggregates repeats within a cooldown and records suppressions with reasons. A scheduled job runs consolidation and reflection per mind, switching the runtime mode while it works. API, Background tab, notifications page with unread badge, overview narrative and warnings, CLI commands, docs/cognition.md.
274 lines
11 KiB
Go
274 lines
11 KiB
Go
// Package reflection reviews a mind's recent history on a schedule: mistakes,
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// abandoned hypotheses, belief changes, completed goals, unresolved
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// contradictions, prediction errors and operator corrections. It produces an
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// explicit reflection event and, where a pattern repeats, a procedural memory
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// (spec §18). Findings are computed; a model may only write the prose.
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package reflection
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import (
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"context"
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"encoding/json"
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"fmt"
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"log/slog"
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"strings"
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"time"
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"github.com/jackc/pgx/v5/pgxpool"
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"github.com/andydixon/noema/internal/beliefs"
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evstore "github.com/andydixon/noema/internal/events"
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"github.com/andydixon/noema/internal/goals"
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"github.com/andydixon/noema/internal/llm"
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"github.com/andydixon/noema/internal/llm/prompts"
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"github.com/andydixon/noema/internal/llm/router"
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"github.com/andydixon/noema/internal/memory"
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"github.com/andydixon/noema/internal/minds"
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"github.com/andydixon/noema/internal/predictions"
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"github.com/andydixon/noema/pkg/concepts"
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"github.com/andydixon/noema/pkg/events"
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"github.com/andydixon/noema/pkg/ids"
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)
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// Findings is the structured review.
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type Findings struct {
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PeriodStart time.Time `json:"period_start"`
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PeriodEnd time.Time `json:"period_end"`
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PredictionErrors []string `json:"prediction_errors"`
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Corrections []string `json:"corrections"`
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RejectedBeliefs []string `json:"rejected_beliefs"`
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ChangedBeliefs []string `json:"changed_beliefs"`
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CompletedGoals []string `json:"completed_goals"`
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Contradictions []string `json:"contradictions"`
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Calibration predictions.Calibration `json:"calibration"`
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Patterns []string `json:"patterns"` // repeated failure subjects
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Lessons []string `json:"lessons"` // procedural memories written
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Counts map[string]int `json:"counts"`
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}
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// Reflection is a stored review.
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type Reflection struct {
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ID ids.ID `json:"id"`
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MindID ids.ID `json:"mind_id"`
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PeriodStart time.Time `json:"period_start"`
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PeriodEnd time.Time `json:"period_end"`
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Findings Findings `json:"findings"`
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Prose string `json:"prose"`
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EventID ids.ID `json:"event_id,omitempty"`
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LLMCallID ids.ID `json:"llm_call_id,omitempty"`
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CreatedAt time.Time `json:"created_at"`
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}
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// Service runs reflections.
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type Service struct {
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DB *pgxpool.Pool
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Events *evstore.Store
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Beliefs *beliefs.Store
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Goals *goals.Store
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Memory *memory.Store
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Predictions *predictions.Store
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LLM *router.Router
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Prompts *prompts.Store
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Log *slog.Logger
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}
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// Run reviews the period since the last reflection (or the interval) and
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// records the outcome.
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func (s *Service) Run(ctx context.Context, m minds.Mind, trigger, by string) (Reflection, error) {
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end := time.Now()
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start := end.Add(-m.Config.ReflectionInterval.D())
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if last, err := s.Latest(ctx, m.ID); err == nil && last.PeriodEnd.After(start) {
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start = last.PeriodEnd
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}
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f := Findings{PeriodStart: start, PeriodEnd: end, Counts: map[string]int{}}
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evs, err := s.Events.Query(ctx, evstore.Filter{MindID: m.ID, Since: start, Until: end, Types: []events.Type{events.PredictionError, events.BeliefRetracted, events.OperatorAction, events.GoalCompleted, events.ContradictionDetected, events.GoalAbandoned}, Ascending: true, Limit: 1000})
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if err != nil {
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return Reflection{}, err
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}
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subjectFailures := map[string]int{}
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for _, ev := range evs {
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f.Counts[string(ev.Type)]++
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switch ev.Type {
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case events.PredictionError:
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f.PredictionErrors = append(f.PredictionErrors, ev.Summary)
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subjectFailures[subjectOf(ev.Summary)]++
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case events.BeliefRetracted:
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f.RejectedBeliefs = append(f.RejectedBeliefs, ev.Summary)
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subjectFailures[subjectOf(ev.Summary)]++
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case events.OperatorAction:
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if strings.HasPrefix(fmt.Sprint(ev.Metadata["action"]), "memory.") || strings.HasPrefix(fmt.Sprint(ev.Metadata["action"]), "correction") || strings.HasPrefix(fmt.Sprint(ev.Metadata["action"]), "belief") {
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f.Corrections = append(f.Corrections, ev.Summary)
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}
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case events.GoalCompleted:
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f.CompletedGoals = append(f.CompletedGoals, ev.Summary)
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case events.ContradictionDetected:
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f.Contradictions = append(f.Contradictions, ev.Summary)
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}
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}
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if ch, err := s.Beliefs.RecentChanges(ctx, m.ID, start, 20); err == nil {
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for _, c := range ch {
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f.ChangedBeliefs = append(f.ChangedBeliefs, fmt.Sprintf("%s: %s → %s (%s)", c.Belief.Proposition, c.FromStatus, c.Belief.Status, c.Reason))
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}
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}
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if contested, err := s.Beliefs.Contested(ctx, m.ID, 20); err == nil {
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for _, b := range contested {
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f.Contradictions = append(f.Contradictions, "still contested: "+b.Proposition)
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}
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}
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f.Calibration, _ = s.Predictions.Calibrate(ctx, m.ID, end.Add(-90*24*time.Hour))
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for subj, n := range subjectFailures {
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if n >= 2 && subj != "" {
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f.Patterns = append(f.Patterns, fmt.Sprintf("%d failures concerning %q", n, subj))
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}
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}
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if f.Calibration.Overconfident {
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f.Patterns = append(f.Patterns, "stated confidence runs ahead of outcomes")
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}
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// Lessons become procedural memories, once per pattern.
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for _, p := range f.Patterns {
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lesson := "Lesson: " + p + ". Seek an independent source before raising confidence on this subject."
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if existing, _ := s.Memory.List(ctx, m.ID, memory.Filter{Kinds: []concepts.MemoryKind{concepts.Procedural}, Search: strings.Trim(p, "\""), Limit: 1}); len(existing) > 0 {
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continue
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}
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if _, err := s.Memory.Create(ctx, s.DB, memory.New{MindID: m.ID, Kind: concepts.Procedural, Epistemic: concepts.Inference, Content: lesson, Source: "reflection", Trust: events.TrustSystem, Confidence: 0.6, Importance: 0.7, Salience: 0.4}); err == nil {
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f.Lessons = append(f.Lessons, lesson)
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}
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}
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prose := Render(f)
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var callID ids.ID
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if s.LLM != nil && s.Prompts != nil && m.Config.ReflectionLLMCalls > 0 && s.LLM.Available(ctx, llm.RoleNarrate) {
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if pr, err := s.Prompts.Get(ctx, "reflect"); err == nil {
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if req, err := pr.Render(map[string]any{"Findings": prose, "Brief": m.Personality.Brief()}); err == nil {
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req.MindID, req.Purpose = m.ID, "reflection prose"
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if resp, err := s.LLM.Complete(ctx, req); err == nil && strings.TrimSpace(resp.Text) != "" {
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prose, callID = strings.TrimSpace(resp.Text), resp.CallID
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}
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}
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}
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}
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total := len(f.PredictionErrors) + len(f.RejectedBeliefs) + len(f.ChangedBeliefs) + len(f.CompletedGoals) + len(f.Contradictions) + len(f.Corrections)
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refs := []events.EvidenceRef{}
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if !callID.IsZero() {
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refs = append(refs, events.EvidenceRef{Kind: "llm_call", ID: string(callID), Note: "prose"})
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}
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evsOut, err := s.Events.Append(ctx, events.New{MindID: m.ID, Type: events.Reflection, Source: "reflection", Summary: fmt.Sprintf("reflected on %s: %d notable items, %d patterns, %d lessons", humanSpan(end.Sub(start)), total, len(f.Patterns), len(f.Lessons)),
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Salience: 0.3 + 0.1*float64(min(len(f.Patterns), 5)), Confidence: 0.8, Evidence: refs, Metadata: map[string]any{"trigger": trigger, "items": total, "patterns": len(f.Patterns)}, Payload: map[string]any{"findings": f, "prose": prose}})
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if err != nil {
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return Reflection{}, err
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}
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r := Reflection{ID: ids.New(), MindID: m.ID, PeriodStart: start, PeriodEnd: end, Findings: f, Prose: prose, EventID: evsOut[0].ID, LLMCallID: callID, CreatedAt: end}
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fj, _ := json.Marshal(f)
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var call *string
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if !callID.IsZero() {
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c := string(callID)
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call = &c
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}
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_, err = s.DB.Exec(ctx, `INSERT INTO reflections (id, mind_id, period_start, period_end, findings, prose, event_id, llm_call_id) VALUES ($1,$2,$3,$4,$5,$6,$7,$8)`, r.ID, r.MindID, r.PeriodStart, r.PeriodEnd, fj, r.Prose, string(r.EventID), call)
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return r, err
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}
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// Render writes the findings as plain prose without a model.
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func Render(f Findings) string {
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var b strings.Builder
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fmt.Fprintf(&b, "Reviewing the last %s.\n", humanSpan(f.PeriodEnd.Sub(f.PeriodStart)))
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section := func(title string, items []string) {
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if len(items) == 0 {
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return
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}
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b.WriteString(title + ":\n")
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for i, it := range items {
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if i >= 6 {
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fmt.Fprintf(&b, " … and %d more\n", len(items)-6)
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break
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}
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b.WriteString(" - " + it + "\n")
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}
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}
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section("Predictions that failed", f.PredictionErrors)
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section("Beliefs I had to reject", f.RejectedBeliefs)
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section("Operator corrections", f.Corrections)
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section("Beliefs that changed status", f.ChangedBeliefs)
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section("Goals completed", f.CompletedGoals)
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section("Unresolved contradictions", f.Contradictions)
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section("Patterns", f.Patterns)
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section("Lessons recorded", f.Lessons)
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if f.Calibration.Total > 0 {
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fmt.Fprintf(&b, "Calibration over 90 days: accuracy %.0f%%, Brier %.2f.\n", f.Calibration.Accuracy*100, f.Calibration.Brier)
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}
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if b.Len() < 60 {
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b.WriteString("Nothing notable happened.\n")
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}
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return strings.TrimSpace(b.String())
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}
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func humanSpan(d time.Duration) string {
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switch {
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case d < 2*time.Hour:
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return fmt.Sprintf("%d minutes", int(d.Minutes()))
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case d < 48*time.Hour:
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return fmt.Sprintf("%d hours", int(d.Hours()))
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default:
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return fmt.Sprintf("%d days", int(d.Hours()/24))
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}
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}
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// subjectOf extracts a crude subject (first hostname-like or long token) from a summary.
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func subjectOf(s string) string {
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for _, w := range strings.Fields(strings.ToLower(s)) {
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w = strings.Trim(w, ".,:;()\"'")
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if strings.ContainsAny(w, "-.") && len(w) >= 5 {
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return w
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}
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}
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return ""
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}
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// Latest returns the most recent reflection.
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func (s *Service) Latest(ctx context.Context, mind ids.ID) (Reflection, error) {
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var r Reflection
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var fj []byte
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var ev, call *string
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err := s.DB.QueryRow(ctx, `SELECT id, mind_id, period_start, period_end, findings, prose, event_id, llm_call_id, created_at FROM reflections WHERE mind_id=$1 ORDER BY created_at DESC LIMIT 1`, mind).
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Scan(&r.ID, &r.MindID, &r.PeriodStart, &r.PeriodEnd, &fj, &r.Prose, &ev, &call, &r.CreatedAt)
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if err != nil {
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return r, err
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}
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json.Unmarshal(fj, &r.Findings) //nolint:errcheck
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if ev != nil {
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r.EventID = ids.ID(*ev)
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}
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if call != nil {
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r.LLMCallID = ids.ID(*call)
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}
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return r, nil
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}
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// List returns recent reflections.
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func (s *Service) List(ctx context.Context, mind ids.ID, limit int) ([]Reflection, error) {
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if limit <= 0 || limit > 100 {
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limit = 20
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}
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rows, err := s.DB.Query(ctx, `SELECT id, mind_id, period_start, period_end, findings, prose, event_id, llm_call_id, created_at FROM reflections WHERE mind_id=$1 ORDER BY created_at DESC LIMIT $2`, mind, limit)
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if err != nil {
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return nil, err
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}
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defer rows.Close()
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var out []Reflection
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for rows.Next() {
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var r Reflection
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var fj []byte
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var ev, call *string
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if err := rows.Scan(&r.ID, &r.MindID, &r.PeriodStart, &r.PeriodEnd, &fj, &r.Prose, &ev, &call, &r.CreatedAt); err != nil {
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return nil, err
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}
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json.Unmarshal(fj, &r.Findings) //nolint:errcheck
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if ev != nil {
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r.EventID = ids.ID(*ev)
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}
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if call != nil {
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r.LLMCallID = ids.ID(*call)
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}
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out = append(out, r)
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}
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return out, rows.Err()
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}
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