Real Anthropic Claude integration per explicit product decision: a ticket's AI session diagnoses the problem via a structured-output call, applies a DB-configurable confidence-band policy (FR-005), and on "proceed" reasons and acts through a small permission/risk-gated tool system (FR-011/FR-012), optionally walking a matching runbook step by step with the application — never the model — owning the step index (FR-015/FR-016). Resolution requires real tool evidence, never customer claims alone (FR-018) — verifyProductResolution is a documented fail-closed placeholder mirroring the existing malware-scanner precedent, since no real per-product operational signal exists yet. AISupportSession.status mirrors onto Ticket.status through 003-ticketing's existing AI_ANALYZING/AI_TROUBLESHOOTING/AI_VERIFYING/AI_RESOLVED/ HUMAN_ESCALATION state machine, discovered during planning to have been built anticipating this exact feature. Two circular module dependencies (escalation<->sessions, tools<->sessions) were designed around rather than found as bugs: escalation is a pure summary formatter with no state dependencies of its own, and tools stays a clean leaf module with zero dependency on ai-support/sessions. Ticket creation enqueues the first diagnosis turn via the existing queue infrastructure (off the hot path of the inbound SaaS integration endpoint); a human actor changing ticket status ends the AI session via the event-bus scaffold that existed in this codebase but had never been wired to anything. A real Prisma limitation was found and fixed before it reached tests: compound-unique upsert rejects null for a nullable key column, so AIConfidencePolicy uses find-then-update/create instead, same fix class 004 already used for the same underlying limitation. Adds 9 unit tests (confidence-band, tool-policy-gate, runbook-step- advance) and 6 integration test files, including the two constitution- required standing E2E scenarios. AI-independent tests were run against real Postgres/Redis/MinIO (88 passed, 0 failed across the full suite, including every pre-existing 002/003/004 test). The AI-dependent tests compile and skip cleanly via describe.skipIf but were not run against a live model — no ANTHROPIC_API_KEY was available in this session; a real key must be supplied before this feature can actually run. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
55 lines
1.9 KiB
TypeScript
55 lines
1.9 KiB
TypeScript
import { AIConfidencePolicy } from '@prisma/client';
|
|
import { ValidationError } from '@/common/errors';
|
|
import { aiConfig } from '@/config';
|
|
import {
|
|
confidencePolicyRepository,
|
|
ConfidencePolicyRepository,
|
|
UpsertConfidencePolicyData,
|
|
} from '../repository/confidence-policy.repository';
|
|
import { ConfidenceBandPolicy } from './confidence-band';
|
|
|
|
export interface ResolvedConfidencePolicy extends ConfidenceBandPolicy {
|
|
maxClarifyingQuestions: number;
|
|
}
|
|
|
|
export class ConfidencePolicyService {
|
|
constructor(private readonly repo: ConfidencePolicyRepository = confidencePolicyRepository) {}
|
|
|
|
/**
|
|
* FR-005: most-specific-match-with-fallback — a DB row for this exact (product, category),
|
|
* else the product-wide row, else the env-configured system defaults. Never throws for a
|
|
* product with no configuration at all — that's the expected, common case (research.md).
|
|
*/
|
|
async resolve(
|
|
productId: string,
|
|
categoryId?: string | undefined,
|
|
): Promise<ResolvedConfidencePolicy> {
|
|
const row = await this.repo.findApplicable(productId, categoryId);
|
|
if (row) {
|
|
return {
|
|
highThreshold: row.highThreshold,
|
|
lowThreshold: row.lowThreshold,
|
|
maxClarifyingQuestions: row.maxClarifyingQuestions,
|
|
};
|
|
}
|
|
return {
|
|
highThreshold: aiConfig.defaultHighConfidence,
|
|
lowThreshold: aiConfig.defaultLowConfidence,
|
|
maxClarifyingQuestions: aiConfig.defaultMaxClarifyingQuestions,
|
|
};
|
|
}
|
|
|
|
async listForProduct(productId: string): Promise<AIConfidencePolicy[]> {
|
|
return this.repo.listForProduct(productId);
|
|
}
|
|
|
|
async upsert(data: UpsertConfidencePolicyData): Promise<AIConfidencePolicy> {
|
|
if (data.highThreshold <= data.lowThreshold) {
|
|
throw new ValidationError('highThreshold must be greater than lowThreshold.');
|
|
}
|
|
return this.repo.upsert(data);
|
|
}
|
|
}
|
|
|
|
export const confidencePolicyService = new ConfidencePolicyService();
|