* feat(ai): job-shaped AI service with OpenAI-compatible backend, extraction-first; stop extracting every inbox document twice Sovereign plan WS1 PR1 (#1406 Tier 2, extraction-first, aligned with the AI surface audit). lib/ai grows a job-shaped service (generateText / generateStructured / extractFromDocument; no streaming members yet, see plan rule R3): - services/anthropic-family delegates to the existing createAiClient() and sends the exact request literals the inbox extractor sent before (request-shape tests deep-equal them), so hosted Bedrock stays byte-identical. - services/openai-compatible talks to any chat-completions endpoint (BYO Swedish provider) via Vercel AI SDK 6.x, exact-pinned and guarded: images as parts, PDFs rasterized with poppler (AI_PDF_MODE) or sent natively, AI_VISION / AI_STRICT_JSON declared, honest skips (ai_no_vision, pdf_rasterizer_missing) instead of fake failures. - config.ts: AI_PROVIDER/AI_BASE_URL/AI_API_KEY/AI_MODEL and per-tier AI_*_MODEL with the legacy BEDROCK_* names kept as the same overrides; getAiStatus() is the single source of truth for "is AI wired up". - provider.ts: openai-compatible in the auto-detect chain (after Bedrock and the direct API); createAiClient() refuses it loudly. Document extraction moves onto the service and gets the audit's fixes: - Inbox documents were extracted TWICE (pipeline A ran inside uploadDocument() before the inbox row existed, so its dedupe branch never fired; 3 707 + 1 666 calls / 30 d). The inbox now declares extractionOwner on the upload, the extension yields, and the inbox mirrors its single outcome onto document_attachments from every writer (sync, deferred, attach, retry, MCP). - Every "no extraction will ever happen" outcome is stamped (skipped:no_ai_entitlement / ai_unconfigured / system_generated / ...); the status route maps the quiet ones to 'disabled' on the first poll instead of a 30 s client timeout. Prod showed 309 of the 327 never-extracted uploads were the paywall working silently. - Self-generated documents (our own invoice PDFs, payout files) are no longer OCR'd. - Agent invoke answers 503 ai_unconfigured when the deployment has no assistant backend, distinct from the paywall. Guard: new direct-ai-client antipattern check (shrink-only allowlist of the pre-abstraction SDK callers) plus exact pins for @anthropic-ai/sdk, ai and @ai-sdk/openai-compatible. Verified: 15 958 unit tests green, guards, lint ratchet, typecheck, and a live smoke against hosted Bedrock through the new service (ping, streamed tool turn, thinking+cache, PDF extraction). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * feat(ai): make AI_API_KEY optional for OpenAI-compatible endpoints (keyless local model servers) A local model server (llama.cpp's server, Ollama /v1, LM Studio, vLLM) usually has no auth. Before, the OpenAI-compatible backend required both AI_BASE_URL and AI_API_KEY to count as configured, so running Accounted on a local model meant setting a meaningless placeholder key. - resolveAiProvider / hasAiCredentials: a base URL alone is now enough. - services/openai-compatible: only send Authorization: Bearer when AI_API_KEY is set, so a keyless server is never handed an empty bearer; a hosted provider that needs a key still sets it. - Docs (SELF-HOSTING Option 3: local-model example, key marked optional), DECISIONS. Verified: with no AI_API_KEY, just AI_BASE_URL + AI_MODEL, getAiStatus() reports configured=true / provider=openai-compatible (live). lib/ai suite 71 green; tsc, guards, lint clean. Bedrock/Anthropic logic unchanged. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> --------- Co-authored-by: Jakob Wennberg <311770904+jakobwennberg-oss@users.noreply.github.com> Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
67 lines
2.0 KiB
TypeScript
67 lines
2.0 KiB
TypeScript
import { getAiStatus, readAiConfig, type ResolvedAiConfig } from './config'
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import { createAnthropicFamilyService } from './services/anthropic-family'
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import { createOpenAICompatibleService } from './services/openai-compatible'
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import type { AiService } from './types'
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export type {
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AiCapabilities,
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AiDocumentInput,
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AiImageMediaType,
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AiPdfMode,
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AiProviderKind,
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AiService,
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AiStatus,
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AiTier,
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AiUsage,
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ExtractFromDocumentRequest,
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ExtractFromDocumentResult,
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ExtractionSkipReason,
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GenerateStructuredRequest,
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GenerateStructuredResult,
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GenerateTextRequest,
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GenerateTextResult,
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} from './types'
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export { getAiStatus, readAiConfig, resolveTierModel } from './config'
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export { extractJsonObject } from './json'
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// One service per resolved configuration. Keyed on the non-secret parts of
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// the config plus credential presence, so a changed environment (tests, the
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// smoke script) gets a fresh service while a long-lived process reuses one.
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let cached: { key: string; service: AiService } | null = null
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function cacheKey(cfg: ResolvedAiConfig): string {
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return JSON.stringify({
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provider: cfg.provider,
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configured: cfg.configured,
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baseUrl: cfg.baseUrl,
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hasKey: !!cfg.apiKey,
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models: cfg.models,
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vision: cfg.vision,
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strictJson: cfg.strictJson,
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pdfMode: cfg.pdfMode,
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pdfMaxPages: cfg.pdfMaxPages,
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})
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}
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/**
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* The AI service for this deployment. Never throws on construction: an
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* unconfigured deployment still gets a service whose extractFromDocument
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* answers `skipped: ai_unconfigured`, so upload paths degrade quietly.
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*/
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export function getAiService(): AiService {
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const cfg = readAiConfig()
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const key = cacheKey(cfg)
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if (cached && cached.key === key) return cached.service
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const service =
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cfg.provider === 'openai-compatible'
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? createOpenAICompatibleService(cfg)
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: createAnthropicFamilyService(cfg)
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cached = { key, service }
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return service
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}
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/** Tests only: drop the cached service so the next call re-reads the environment. */
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export function resetAiServiceForTests(): void {
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cached = null
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}
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