Add human-led conversation learning loop

src/services/conversation-learning-types.ts

@@ -0,0 +1,129 @@
+import { z } from 'zod';
+import type { AttributionConfidence, ConversationEventKind } from '../database/conversation-event-repository.js';
+import type { ConversationPolicyMode } from './conversation-state.js';
+
+export const LearningStageSchema = z.enum([
+  'rapport',
+  'answer',
+  'flirt',
+  'disclosure',
+  'media-invitation',
+  'handoff',
+  'unknown',
+]);
+export type LearningStage = z.infer<typeof LearningStageSchema>;
+
+export const LearningTurnSchema = z.strictObject({
+  eventId: z.string(),
+  timestamp: z.number(),
+  role: z.enum(['recipient', 'operator']),
+  actor: z.enum(['recipient', 'ai', 'human']),
+  kind: z.enum([
+    'inbound-text',
+    'opener',
+    'automation-reply',
+    'manual-text',
+    'library-reciprocal',
+  ]),
+  text: z.string(),
+});
+export type LearningTurn = z.infer<typeof LearningTurnSchema>;
+
+export const LearningCreditClasses = [
+  'human-created-success',
+  'human-improved-success',
+  'human-completed-ai-trajectory',
+  'autonomous-success',
+  'recipient-initiated-media',
+  'uncertain',
+] as const;
+export type LearningCreditClass = (typeof LearningCreditClasses)[number];
+
+export type LearningTrajectoryStatus = 'provisional' | 'eligible' | 'excluded' | 'invalidated' | 'needs-review';
+export type LearningDecisionStatus = 'eligible' | 'excluded' | 'invalidated' | 'needs-review';
+
+export interface LearningTrajectoryRecord {
+  id: string;
+  accountId: string;
+  conversationId: string;
+  sentMessageId: number | null;
+  subreddit: string | null;
+  sourceType: 'image' | 'chat' | null;
+  policyMode: ConversationPolicyMode | null;
+  firstHumanEventId: string | null;
+  outcomeEventId: string;
+  outcomeType: 'image-received' | 'reciprocal-engagement';
+  creditClass: LearningCreditClass;
+  attributionConfidence: AttributionConfidence;
+  status: LearningTrajectoryStatus;
+  maturityAt: number;
+  invalidatedAt: number | null;
+  invalidationReason: string | null;
+  reviewedAt: number | null;
+  createdAt: number;
+  updatedAt: number;
+}
+
+export interface LearningDecisionRecord {
+  id: string;
+  trajectoryId: string;
+  accountId: string;
+  decisionEventId: string;
+  stage: LearningStage;
+  context: LearningTurn[];
+  chosenResponse: string;
+  turnsUntilOutcome: number;
+  isDirectMediaInvitation: boolean;
+  qualityStatus: LearningDecisionStatus;
+  createdAt: number;
+  updatedAt: number;
+}
+
+export interface LearningTrajectoryDetail extends LearningTrajectoryRecord {
+  decisions: LearningDecisionRecord[];
+}
+
+export interface RetrievedLearningExample {
+  decisionId: string;
+  trajectoryId: string;
+  creditClass: LearningCreditClass;
+  stage: LearningStage;
+  context: LearningTurn[];
+  chosenResponse: string;
+  turnsUntilOutcome: number;
+  subreddit: string | null;
+  policyMode: ConversationPolicyMode | null;
+}
+
+export interface ConversationLearningQuery {
+  accountId: string;
+  conversationId: string;
+  subreddit: string | null;
+  policyMode: ConversationPolicyMode;
+  stage: LearningStage;
+  purpose: 'reply' | 'media-ask';
+  incomingEventId: string;
+}
+
+export interface ConversationLearningProvider {
+  getExamples(query: ConversationLearningQuery): readonly RetrievedLearningExample[];
+  recordGeneration(input: {
+    query: ConversationLearningQuery;
+    mode: 'shadow' | 'injected';
+    policyVersion: string;
+    exampleIds: readonly string[];
+    promptSha256?: string | null;
+    generatedAt?: number;
+  }): void;
+}
+
+export interface AttributedConversationMessage {
+  eventId: string;
+  timestamp: number;
+  isSelf: boolean;
+  text: string;
+  mediaCount: number;
+  actor: 'recipient' | 'ai' | 'human' | 'unknown';
+  kind: ConversationEventKind;
+  confidence: AttributionConfidence;
+}