mirror of
https://github.com/hanzoai/dataroom.git
synced 2026-10-30 18:41:07 +00:00
zeekay
a15864b16b
hanzo-build-linux-amd64 is the only ARC runner pool installed on hanzo-k8s today (arm64 pool is paused until DigitalOcean ships arm64 droplets, per ~/work/hanzo/.github/RUNNERS.md). The arm64 job was waiting on spark-hanzoai-arm64 — not provisioned in this cluster — so every build sat in queue forever and the amd64 leg got cancelled. Set platforms: linux/amd64 on the reusable build call to skip arm64 entirely. Re-add arm64 if/when DO ships arm64 droplets and the spark runner pool comes back online.
64 lines
1.6 KiB
TypeScript
64 lines
1.6 KiB
TypeScript
import prisma from "@/lib/prisma";
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interface DocumentMetadata {
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documentId: string;
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documentName: string;
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versionId: string;
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dataroomId?: string;
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folderId?: string;
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teamId: string;
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}
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/**
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* Extract metadata from a document for vector store tagging
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* @param documentId - The document ID
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* @param versionId - The document version ID
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* @returns Document metadata
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*/
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export async function extractDocumentMetadata(
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documentId: string,
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versionId: string,
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): Promise<DocumentMetadata> {
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try {
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const documentVersion = await prisma.documentVersion.findUnique({
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where: { id: versionId },
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include: {
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document: {
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include: {
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datarooms: {
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include: {
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dataroom: true,
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folder: true,
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},
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},
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},
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},
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},
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});
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if (!documentVersion) {
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throw new Error("Document version not found");
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}
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const document = documentVersion.document;
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// Get dataroom and folder info if document is in a dataroom
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const dataroomDocument = document.datarooms[0]; // Get first dataroom association
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const metadata: DocumentMetadata = {
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documentId: document.id,
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documentName: document.name,
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versionId: documentVersion.id,
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teamId: document.teamId,
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dataroomId: dataroomDocument?.dataroomId,
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folderId: dataroomDocument?.folderId || document.folderId || undefined,
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};
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return metadata;
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} catch (error) {
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console.error("Error extracting document metadata:", error);
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throw new Error("Failed to extract document metadata");
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}
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}
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