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.
56 lines
1.6 KiB
TypeScript
56 lines
1.6 KiB
TypeScript
import { logger, metadata, task } from "@trigger.dev/sdk/v3";
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import { openai } from "@/features/ai/lib/models/openai";
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import type { AddToVectorStorePayload } from "./types";
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/**
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* Add an existing OpenAI file to a vector store
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* This is used when a document has already been processed and we just need to add it
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* to a new vector store (e.g., when adding to a dataroom)
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*/
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export const addFileToVectorStoreTask = task({
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id: "add-file-to-vector-store",
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retry: { maxAttempts: 3 },
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queue: {
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concurrencyLimit: 10,
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},
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run: async (
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payload: AddToVectorStorePayload,
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): Promise<{ vectorStoreFileId: string }> => {
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const { fileId, vectorStoreId, metadata: fileMetadata } = payload;
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logger.info("Adding file to vector store", {
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fileId,
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vectorStoreId,
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documentId: fileMetadata.documentId,
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});
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metadata.set("status", "indexing");
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metadata.set("step", "Adding to vector store...");
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metadata.set("progress", 80);
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// Add file to vector store with metadata
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const vectorStoreFile = await openai.vectorStores.files.create(
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vectorStoreId,
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{
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file_id: fileId,
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attributes: fileMetadata,
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},
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);
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metadata.set("status", "completed");
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metadata.set("step", "Indexed successfully");
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metadata.set("progress", 100);
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metadata.set("vectorStoreFileId", vectorStoreFile.id);
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logger.info("File added to vector store successfully", {
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fileId,
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vectorStoreFileId: vectorStoreFile.id,
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documentId: fileMetadata.documentId,
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});
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return { vectorStoreFileId: vectorStoreFile.id };
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},
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});
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