c7a75d069d
* 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>
56 lines
2.0 KiB
TypeScript
56 lines
2.0 KiB
TypeScript
// Bounds for the candidate scan below. Real model output is already capped by
|
|
// the caller's max_tokens (roughly 33 KB of text at 8192 tokens), so genuine
|
|
// responses never come near these; they exist so pathological or adversarially
|
|
// brace-laden text cannot make the scan quadratic (compliance review A.8.28).
|
|
// Oversized or exhausted inputs fall through to the raw text and land in the
|
|
// caller's existing parse-failure path.
|
|
const MAX_SCAN_INPUT_LENGTH = 256 * 1024
|
|
const MAX_CANDIDATE_ATTEMPTS = 50
|
|
|
|
/**
|
|
* Models intermittently wrap a JSON answer in markdown fences (```json ... ```)
|
|
* or add prose around it despite a JSON-only instruction. Scan for balanced
|
|
* top-level '{'..'}' candidates (string- and escape-aware, so braces inside
|
|
* JSON string values don't end a candidate early) and return the first one
|
|
* JSON.parse accepts; prose braces around the object form unparseable
|
|
* candidates and are skipped. Returns the input unchanged when no candidate
|
|
* parses, so the caller's parse-failure path handles prose-only refusals.
|
|
* Schema validation downstream still rejects well-formed-but-wrong JSON.
|
|
*/
|
|
export function extractJsonObject(raw: string): string {
|
|
if (raw.length > MAX_SCAN_INPUT_LENGTH) return raw
|
|
let attempts = 0
|
|
let start = raw.indexOf('{')
|
|
while (start !== -1 && attempts < MAX_CANDIDATE_ATTEMPTS) {
|
|
attempts++
|
|
let depth = 0
|
|
let inString = false
|
|
let escaped = false
|
|
for (let i = start; i < raw.length; i++) {
|
|
const ch = raw[i]
|
|
if (inString) {
|
|
if (escaped) escaped = false
|
|
else if (ch === '\\') escaped = true
|
|
else if (ch === '"') inString = false
|
|
} else if (ch === '"') {
|
|
inString = true
|
|
} else if (ch === '{') {
|
|
depth++
|
|
} else if (ch === '}') {
|
|
depth--
|
|
if (depth === 0) {
|
|
const candidate = raw.slice(start, i + 1)
|
|
try {
|
|
JSON.parse(candidate)
|
|
return candidate
|
|
} catch {
|
|
break
|
|
}
|
|
}
|
|
}
|
|
}
|
|
start = raw.indexOf('{', start + 1)
|
|
}
|
|
return raw
|
|
}
|