Phase 8, completing milestone M1. A user message is stored and appended as an observation event carrying trust, actor, channel and reference. The perceive process analyses it deterministically (intent, introspection kind, entities, claims, urgency) and, within the per-cycle model allowance, enriches it through the perceive prompt. Its handler writes a perception event, an episodic memory with participants, turns claims into beliefs whose evidence is the message, and builds a response intent from state: beliefs and memories for the topic, evidence rows for why-questions, the uncertain band, contested beliefs and their links, recent learning, status changes, and honest declines for subsystems that do not exist yet or for requests with no capabilities. The respond prompt phrases the intent when a model is assigned; otherwise the reply is a direct rendering of the intent. response_generated cites the message, the perception, every belief and memory used, the episode and the model call. API: conversations, messages with optional wait, one-shot ask; chat UI with live refresh and a per-reply intent view. Sample mind Dani as a strictly decoded seed document with an import endpoint and noemactl mind import. tests/m1 drives all fourteen milestone steps including restart.
154 lines
6.7 KiB
Go
154 lines
6.7 KiB
Go
package cognition
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import (
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"context"
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"encoding/json"
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"errors"
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"fmt"
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"strings"
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"github.com/andydixon/noema/internal/beliefs"
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"github.com/andydixon/noema/internal/brain"
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"github.com/andydixon/noema/internal/conversation"
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"github.com/andydixon/noema/internal/memory"
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"github.com/andydixon/noema/internal/storage"
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"github.com/andydixon/noema/internal/workspace"
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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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// Handlers are the executive actions for admitted thought kinds.
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type Handlers struct {
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Memory *memory.Store
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Beliefs *beliefs.Store
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Conversations *conversation.Store
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}
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// Register installs the handlers on a registry.
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func (h Handlers) Register(r *brain.Registry) {
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r.Handle("attend", h.attend)
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r.Handle("retrieve", h.retrieve)
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r.Handle("hypothesis", h.hypothesis)
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r.Handle("perceive", h.perceive)
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}
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// emitter adapts the cycle to the beliefs store's Emitter.
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func emitter(c *brain.Cycle) beliefs.Emitter {
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return func(ctx context.Context, _ storage.Querier, n events.New) (events.Event, error) {
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return c.EmitNow(ctx, n)
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}
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}
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// hypothesis turns an admitted hypothesis candidate into a belief whose
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// confidence is computed from the cited observations. Temporal co-occurrence
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// is weak evidence, so weights are small and the result stays a hypothesis
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// until independent support arrives.
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func (h Handlers) hypothesis(ctx context.Context, c *brain.Cycle, t workspace.Thought) error {
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if h.Beliefs == nil {
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return nil
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}
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prop, _ := t.Content["proposition"].(string)
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if prop == "" {
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prop = strings.TrimPrefix(t.Summary, "hypothesis: ")
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}
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var ev []beliefs.EvidenceInput
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for _, ref := range t.Evidence {
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if ref.Kind != "event" {
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continue
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}
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cred := 0.6
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if e, err := c.Runtime.Events().Get(ctx, ids.ID(ref.ID)); err == nil {
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var p events.ObservationPayload
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if json.Unmarshal(e.Payload, &p) == nil && p.Trust.Valid() {
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cred = p.Trust.Credibility()
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}
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}
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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 + ")"})
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}
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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",
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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,
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Detail: map[string]any{"cause_event": t.Content["cause_event"], "effect_event": t.Content["effect_event"], "gap_seconds": t.Content["gap_seconds"]}})
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if err != nil {
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if errors.Is(err, beliefs.ErrBlocked) {
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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"}})
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return nil
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}
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return err
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}
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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})
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return nil
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}
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// attend encodes the attended event as a memory and holds it in working
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// memory. Only attended events become episodes: attention gates encoding.
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func (h Handlers) attend(ctx context.Context, c *brain.Cycle, t workspace.Thought) error {
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evID, _ := t.Content["source_event"].(string)
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var mem memory.Memory
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if h.Memory != nil && evID != "" {
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ev, err := c.Runtime.Events().Get(ctx, ids.ID(evID))
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if err == nil && ev.Metadata["conversation_id"] != nil {
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err = errSkipEncode // the perceive handler encodes conversational episodes
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}
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if err == nil {
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n := memory.New{MindID: c.State.Mind.ID, Kind: concepts.Episodic, Epistemic: concepts.Observation, Content: ev.Summary, Source: ev.Source,
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Trust: events.TrustLow, Confidence: ev.Confidence, Importance: t.Score, Salience: ev.Salience, Valence: ev.Valence, Arousal: ev.Arousal, OccurredAt: ev.OccurredAt, OriginEvent: ev.ID,
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Detail: map[string]any{"event_type": ev.Type, "participants": []string{}}}
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switch ev.Type {
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case events.Observation:
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var p events.ObservationPayload
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if json.Unmarshal(ev.Payload, &p) == nil {
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if p.Text != "" {
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n.Content = p.Text
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}
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n.Trust = p.Trust
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n.Detail["channel"], n.Detail["reference"], n.Detail["method"] = p.Channel, p.Reference, p.Method
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if p.Actor != "" {
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n.Detail["participants"] = []string{p.Actor}
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}
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}
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case events.OperatorAction:
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n.Kind, n.Trust, n.Importance = concepts.Autobiographical, events.TrustOperator, max(t.Score, 0.6)
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n.Content = "An operator changed me: " + ev.Summary
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default:
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n.Trust = events.TrustSystem
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}
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mem, err = h.Memory.Create(ctx, c.Tx, n)
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if err != nil {
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return fmt.Errorf("encode memory: %w", err)
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}
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c.Emit(events.New{Type: events.MemoryCreated, Source: "brain.memory", Summary: fmt.Sprintf("encoded %s memory: %s", mem.Kind, truncate(mem.Content, 120)),
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Salience: 0.3, Confidence: mem.Confidence, CausationID: t.EventID, ParentIDs: []ids.ID{t.EventID, ev.ID},
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Evidence: []events.EvidenceRef{{Kind: "memory", ID: string(mem.ID)}, {Kind: "event", ID: string(ev.ID), Note: "source"}},
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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}})
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}
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}
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item := workspace.Item{Key: "attend:" + t.Subject, Content: t.Summary, Kind: "observation", SourceEvent: ids.ID(evID)}
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if !mem.ID.IsZero() {
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item.Ref = string(mem.ID)
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}
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c.Runtime.Hold(item)
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return nil
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}
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// retrieve reinforces a recalled memory, records the retrieval with its
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// scoring components, and holds it in working memory.
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func (h Handlers) retrieve(ctx context.Context, c *brain.Cycle, t workspace.Thought) error {
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ref, _ := t.Content["ref"].(string)
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if h.Memory == nil || ref == "" {
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return nil
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}
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mid := ids.ID(ref)
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if err := h.Memory.Reinforce(ctx, c.Tx, c.State.Mind.ID, mid); err != nil {
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return err
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}
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src, _ := t.Content["source_event"].(string)
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c.Emit(events.New{Type: events.MemoryRetrieved, Source: "brain.memory", Summary: t.Summary, Salience: t.Score, Confidence: t.Confidence,
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CausationID: t.EventID, ParentIDs: []ids.ID{t.EventID}, Evidence: t.Evidence,
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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"]}})
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c.Runtime.Hold(workspace.Item{Key: "memory:" + ref, Content: t.Summary, Kind: "retrieval", Ref: ref, SourceEvent: ids.ID(src)})
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return nil
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}
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var errSkipEncode = errors.New("skip")
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