Files
noema/internal/cognition/handlers.go
T
Andy Dixon 0071658c93 feat(evidence): record provenance and stop derived evidence counting as corroboration
Every evidence row now records its derivation (direct, assertion, operator,
external, prediction, consolidation, inference, reflection, dream,
retrieval), its independent-source family (an actor, an integration, an
operator, a prediction) and its root event or memory ids. Confidence
groups evidence by family: the strongest primary item counts in full, each
further primary item adds a quarter, capped at 1.5x, and derived items
count only when the family has no primary member. Three derived
re-expressions of one utterance therefore weigh exactly what the utterance
weighs, while three independent families still add up.

Producers (conversation, association, consolidation, predictions,
metacognition, dreaming, operator and seed input, contradictions) supply
their ancestry. Existing rows are marked legacy_unknown with family =
source; nothing is invented. The belief page shows per-family
contributions and the replay test checks that provenance is reconstructed
identically in the sandbox. Migration 0017 is additive.
2026-07-31 21:14:52 +01:00

202 lines
9.1 KiB
Go

package cognition
import (
"context"
"encoding/json"
"errors"
"fmt"
"strings"
"time"
"github.com/andydixon/noema/internal/beliefs"
"github.com/andydixon/noema/internal/brain"
"github.com/andydixon/noema/internal/conversation"
"github.com/andydixon/noema/internal/graph"
"github.com/andydixon/noema/internal/memory"
"github.com/andydixon/noema/internal/predictions"
"github.com/andydixon/noema/internal/storage"
"github.com/andydixon/noema/internal/workspace"
"github.com/andydixon/noema/pkg/concepts"
"github.com/andydixon/noema/pkg/events"
"github.com/andydixon/noema/pkg/ids"
)
// Handlers are the executive actions for admitted thought kinds.
type Handlers struct {
Memory *memory.Store
Beliefs *beliefs.Store
Conversations *conversation.Store
Graph *graph.Store
}
// Register installs the handlers on a registry.
func (h Handlers) Register(r *brain.Registry) {
r.Handle("attend", h.attend)
r.Handle("retrieve", h.retrieve)
r.Handle("hypothesis", h.hypothesis)
r.Handle("perceive", h.perceive)
r.Handle("goal", h.goal)
r.Handle("question", h.question)
r.Handle("metacognition", h.metacognition)
r.Handle("action", h.action)
}
// emitter adapts the cycle to the beliefs store's Emitter.
func emitter(c *brain.Cycle) beliefs.Emitter {
return func(ctx context.Context, _ storage.Querier, n events.New) (events.Event, error) {
return c.EmitNow(ctx, n)
}
}
// hypothesis turns an admitted hypothesis candidate into a belief whose
// confidence is computed from the cited observations. Temporal co-occurrence
// is weak evidence, so weights are small and the result stays a hypothesis
// until independent support arrives.
func (h Handlers) hypothesis(ctx context.Context, c *brain.Cycle, t workspace.Thought) error {
if h.Beliefs == nil {
return nil
}
prop, _ := t.Content["proposition"].(string)
if prop == "" {
prop = strings.TrimPrefix(t.Summary, "hypothesis: ")
}
var ev []beliefs.EvidenceInput
for _, ref := range t.Evidence {
if ref.Kind != "event" {
continue
}
cred := 0.6
family := "event:" + ref.ID
if e, err := c.Runtime.Events().Get(ctx, ids.ID(ref.ID)); err == nil {
var p events.ObservationPayload
if json.Unmarshal(e.Payload, &p) == nil && p.Trust.Valid() {
cred = p.Trust.Credibility()
}
if f := beliefs.FamilyFromEvent(e); f != "" {
family = f
}
}
// The two observations are the roots; the causal reading is an inference over them.
ev = append(ev, beliefs.EvidenceInput{Direction: "for", Kind: "event", RefID: ref.ID, Source: "co-occurrence:" + ref.ID, Weight: 0.15, Credibility: cred, Note: "temporal co-occurrence (" + ref.Note + ")",
Derivation: beliefs.DerivationInference, Family: family, RootIDs: []string{ref.ID}})
}
res, err := h.Beliefs.Create(ctx, c.Tx, emitter(c), beliefs.New{MindID: c.State.Mind.ID, Proposition: prop, Epistemic: concepts.Hypothesis, Source: "brain.associate",
Evidence: ev, Alternatives: []string{"coincidence: the two events are unrelated", "a third factor caused both"}, OriginEvent: t.EventID, Causation: t.EventID, Correlation: c.State.CycleID,
Detail: map[string]any{"cause_event": t.Content["cause_event"], "effect_event": t.Content["effect_event"], "gap_seconds": t.Content["gap_seconds"]}})
if err != nil {
if errors.Is(err, beliefs.ErrBlocked) {
c.Emit(events.New{Type: events.Metacognition, Source: "brain.executive", Summary: "hypothesis blocked by operator correction: " + prop, Salience: 0.3, Confidence: 1, Metadata: map[string]any{"check": "do_not_infer"}})
return nil
}
return err
}
c.Runtime.Hold(workspace.Item{Key: "belief:" + string(res.Belief.ID), Content: "hypothesis (" + fmt.Sprintf("%.2f", res.Belief.Confidence) + "): " + prop, Kind: "thought", Ref: string(res.Belief.ID), SourceEvent: t.EventID})
// A causal hypothesis implies a checkable expectation: the effect recurs
// after the cause. Its confidence is the belief's, so a miss will lower it.
if c.State.Services.Predictions != nil {
effect, _ := t.Content["effect_event"].(string)
if ev, err := c.Runtime.Events().Get(ctx, ids.ID(effect)); err == nil {
terms := distinctiveTerms(ev.Summary, 3)
if len(terms) > 0 {
p, err := c.State.Services.Predictions.Create(ctx, c.Tx, predictions.New{MindID: c.State.Mind.ID, Statement: "something like \"" + truncate(ev.Summary, 80) + "\" will recur within 24 hours if the cause is real",
Subject: subjectKey(ev.Summary), Confidence: res.Belief.Confidence, WindowEnd: c.State.Now.Add(24 * time.Hour),
Criteria: predictions.Criteria{Kind: "event_match", Expect: "occurs", Terms: terms, MinTerms: min(2, len(terms))}, Source: "brain.associate", OriginEvent: res.Events[0].ID, BeliefID: res.Belief.ID})
if err == nil {
c.Emit(events.New{Type: events.PredictionCreated, Source: "brain.associate", Summary: fmt.Sprintf("predicted (%.2f): %s", p.Confidence, p.Statement), Salience: 0.3, Confidence: p.Confidence, CausationID: res.Events[0].ID,
Evidence: []events.EvidenceRef{{Kind: "prediction", ID: string(p.ID)}, {Kind: "belief", ID: string(res.Belief.ID)}}, Metadata: map[string]any{"prediction_id": string(p.ID), "belief_id": string(res.Belief.ID), "window_end": p.WindowEnd}, Payload: p})
}
}
}
}
return nil
}
// distinctiveTerms picks the longest tokens of a summary as match terms.
func distinctiveTerms(text string, n int) []string {
toks := tokeniseWS(text)
var out []string
for _, t := range toks {
if len(t) >= 5 {
out = append(out, t)
}
if len(out) == n {
break
}
}
return out
}
// attend encodes the attended event as a memory and holds it in working
// memory. Only attended events become episodes: attention gates encoding.
func (h Handlers) attend(ctx context.Context, c *brain.Cycle, t workspace.Thought) error {
evID, _ := t.Content["source_event"].(string)
var mem memory.Memory
if h.Memory != nil && evID != "" {
ev, err := c.Runtime.Events().Get(ctx, ids.ID(evID))
if err == nil && ev.Metadata["conversation_id"] != nil {
err = errSkipEncode // the perceive handler encodes conversational episodes
}
if err == nil {
n := memory.New{MindID: c.State.Mind.ID, Kind: concepts.Episodic, Epistemic: concepts.Observation, Content: ev.Summary, Source: ev.Source,
Trust: events.TrustLow, Confidence: ev.Confidence, Importance: t.Score, Salience: ev.Salience, Valence: ev.Valence, Arousal: ev.Arousal, OccurredAt: ev.OccurredAt, OriginEvent: ev.ID,
Detail: map[string]any{"event_type": ev.Type, "participants": []string{}}}
switch ev.Type {
case events.Observation:
var p events.ObservationPayload
if json.Unmarshal(ev.Payload, &p) == nil {
if p.Text != "" {
n.Content = p.Text
}
n.Trust = p.Trust
n.Detail["channel"], n.Detail["reference"], n.Detail["method"] = p.Channel, p.Reference, p.Method
if p.Actor != "" {
n.Detail["participants"] = []string{p.Actor}
}
}
case events.OperatorAction:
n.Kind, n.Trust, n.Importance = concepts.Autobiographical, events.TrustOperator, max(t.Score, 0.6)
n.Content = "An operator changed me: " + ev.Summary
default:
n.Trust = events.TrustSystem
}
mem, err = h.Memory.Create(ctx, c.Tx, n)
if err != nil {
return fmt.Errorf("encode memory: %w", err)
}
c.Emit(events.New{Type: events.MemoryCreated, Source: "brain.memory", Summary: fmt.Sprintf("encoded %s memory: %s", mem.Kind, truncate(mem.Content, 120)),
Salience: 0.3, Confidence: mem.Confidence, CausationID: t.EventID, ParentIDs: []ids.ID{t.EventID, ev.ID},
Evidence: []events.EvidenceRef{{Kind: "memory", ID: string(mem.ID)}, {Kind: "event", ID: string(ev.ID), Note: "source"}},
Metadata: map[string]any{"memory_id": mem.ID, "kind": mem.Kind}, Payload: map[string]any{"memory_id": mem.ID, "kind": mem.Kind, "importance": mem.Importance, "trust": mem.Trust}})
}
}
item := workspace.Item{Key: "attend:" + t.Subject, Content: t.Summary, Kind: "observation", SourceEvent: ids.ID(evID)}
if !mem.ID.IsZero() {
item.Ref = string(mem.ID)
text, _ := t.Content["text"].(string)
h.linkEntities(ctx, c, entitiesFromText(text), "", ids.ID(evID), map[string]ids.ID{"memory": mem.ID})
}
c.Runtime.Hold(item)
return nil
}
// retrieve reinforces a recalled memory, records the retrieval with its
// scoring components, and holds it in working memory.
func (h Handlers) retrieve(ctx context.Context, c *brain.Cycle, t workspace.Thought) error {
ref, _ := t.Content["ref"].(string)
if h.Memory == nil || ref == "" {
return nil
}
mid := ids.ID(ref)
if err := h.Memory.Reinforce(ctx, c.Tx, c.State.Mind.ID, mid); err != nil {
return err
}
src, _ := t.Content["source_event"].(string)
c.Emit(events.New{Type: events.MemoryRetrieved, Source: "brain.memory", Summary: t.Summary, Salience: t.Score, Confidence: t.Confidence,
CausationID: t.EventID, ParentIDs: []ids.ID{t.EventID}, Evidence: t.Evidence,
Metadata: map[string]any{"memory_id": mid, "score": t.Content["score"]}, Payload: map[string]any{"memory_id": mid, "score": t.Content["score"], "components": t.Content["components"], "query": t.Content["query"]}})
c.Runtime.Hold(workspace.Item{Key: "memory:" + ref, Content: t.Summary, Kind: "retrieval", Ref: ref, SourceEvent: ids.ID(src)})
return nil
}
var errSkipEncode = errors.New("skip")