Files
support_backend/src/modules/ai-support/sessions/service/confidence-policy.service.ts
T
saqib mirandClaude Sonnet 5 82d02bcdcd feat: implement AI support agent (005) — diagnosis, tools, runbooks, verification
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>
2026-09-02 17:44:52 +05:30

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();