mirror of
https://github.com/hanzoai/dataroom.git
synced 2026-10-30 18:41:07 +00:00
zeekay
9dff9e667e
Drop the dual-licensed `ee/` tree entirely. All features previously
locked behind the Hanzo Dataroom Commercial License are now part of the
AGPL-3.0 core and freely available — custom domains, branded viewing,
advanced analytics, watermarks, access controls, Q&A, AI vector stores,
workflows, SAML SSO, dataroom invitations, conversations, templates.
Layout changes:
* `ee/features/{ai,conversations,workflows,permissions,storage,templates,
dataroom-invitations,access-notifications,security,conversions}/` →
`features/<name>/` (AGPL).
* `ee/limits/` → `lib/billing/limits/` with every plan resolving to an
unlimited profile (no users/links/documents/domains/datarooms cap,
conversations and watermarks always on).
* `ee/stripe/` → `lib/billing/legacy/` (already a compat shim over
`@hanzoai/commerce`; renewal-reminder webhook is now a no-op).
* `ee/features/billing/cancellation/` deleted. Pause/unpause/cancel/
retention routes now compile against `lib/billing/cancellation.ts`
stubs that return 410 Gone; `isTeamPaused`/`isTeamPausedById` in
`lib/billing/paused.ts` always report active. `CancellationModal` is
a no-op shim in `components/billing/`.
* `app/(ee)/api/*` route group folded into `app/api/*` (SAML auth,
SCIM, AI chat, workflows, FAQ, link-upload).
Build: `npm run build` green.
52 lines
1.6 KiB
TypeScript
52 lines
1.6 KiB
TypeScript
import { openai } from "@/features/ai/lib/models/openai";
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import { DocumentStorageType } from "@prisma/client";
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import { toFile } from "openai";
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import path from "path";
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import { getFile } from "@/lib/files/get-file";
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/**
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* Process a document and prepare it for vector store upload
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* Downloads the file from storage and returns it as a buffer
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* @param filePath - The file path/key in storage
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* @param storageType - The storage type (S3_PATH or VERCEL_BLOB)
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* @returns File ID
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*/
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export async function processDocumentForVectorStore(
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filePath: string,
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storageType: DocumentStorageType,
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): Promise<{ fileId: string }> {
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try {
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// Get the file URL
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const fileUrl = await getFile({
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type: storageType,
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data: filePath,
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isDownload: true,
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});
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// Fetch the file
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const response = await fetch(fileUrl);
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if (!response.ok) {
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throw new Error(`Failed to fetch file: ${response.statusText}`);
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}
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// Extract filename from the original file path (not the presigned URL)
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const fileName = path.basename(filePath);
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// Convert response to buffer and create a properly named file
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// This prevents OpenAI from inferring extension from URL query params
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// const buffer = await response.arrayBuffer();
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const file = await toFile(response, fileName, { type: "application/pdf" });
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const fileResponse = await openai.files.create({
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file,
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purpose: "assistants",
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});
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return { fileId: fileResponse.id };
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} catch (error) {
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console.error("Error processing document for vector store:", error);
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throw new Error("Failed to process document for vector store");
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}
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}
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