> ## Documentation Index > Fetch the complete documentation index at: https://gligabao.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Datasets > A dataset is the hard, per-user container for everything gligabao stores. A dataset is a hard logical container. Every artifact, entity and edge belongs to exactly one dataset (`dataset_id`), and datasets never share nodes: the same entity remembered into two datasets is two separate rows, and query only sees the graph of the dataset it targets. Its embeddings are isolated the same way, in vector datasets of its own, one per purpose (see [Vectors](#vectors)). * Every dataset is owned by a `user_id`, and that ownership covers all its artifacts, entities and edges. All endpoints require `user_id` (see [Identity](https://gligabao.mintlify.site/concepts/identity.md)) (a non-empty string of at most 128 bytes): in the JSON body for `POST`, in the query string for `GET` and `DELETE`. A missing or invalid one returns `400`. A user only sees and changes their own datasets; names are unique per user, so two users can each have a dataset called `work`. * `remember` and `query` take an optional `dataset` (name). If omitted, the default dataset `main` is used. There is no dataset until it is created: `main` is created for a user by their first `remember`. * `remember` creates the dataset on demand if it does not exist. `query` on a dataset that does not exist (or was deleted) returns `404`. * Names are 1-64 characters of letters, digits, `.`, `_`, `-`, starting with a letter or digit. Invalid names return `400`. * A dataset has `id`, `user_id`, `name`, `description`, `tags` (list of strings), `created_at`, `deleted` and `deleted_at`. ## Vectors The vector store isolates vectors by dataset too (a chromem collection, a Pinecone namespace; see [Vector storage](https://gligabao.mintlify.site/guides/vectors.md#datasets)): a gligabao dataset keeps its vectors in one vector dataset per purpose, an index, named `dataset--` after the dataset's numeric `id` (`memory_core.VectorDataset`): | Index | Vector dataset | Vectors | | - | - | - | | entities | `dataset--entities` | one per entity, ID `entity-`, metadata `kind`, `entity_id`, `name`, `type`; text `Name (type): description` | | edges | `dataset--edges` | one per edge, ID `edge-`, metadata `kind`, `edge_id`, `source`, `target`, `relation`; text is the edge's description | | chunks | `dataset--chunks` | one per chunk of a [chunked](https://gligabao.mintlify.site/guides/chunking.md) text, ID `chunk-`, metadata `kind`, `artifact_id`, `parent_id`, `index`; text is the chunk's text | They are keyed by the id, not the name, so: * datasets never share vectors, including two users' datasets with the same name; * a name reused after a delete is a new dataset with a new id, and so new, empty vector datasets; * no setup is needed on create: a vector dataset appears with the first vector stored in it, and a dataset without vectors has none. `remember` writes both indexes, see [Vector storage](https://gligabao.mintlify.site/guides/vectors.md#what-remember-writes) for what is embedded and how a failure is handled. `query` does not read vectors yet. ## Soft delete Deleting sets `deleted = true` (and `deleted_at`); no relational rows are removed. A deleted dataset is invisible to list, remember and query. Its name can be reused: creating (or remembering into) that name makes a new dataset with a new id and an empty graph. The old rows stay in the database under the old id. The vectors are the exception: they are removed with the dataset (`DeleteAll` on each of its `dataset--` vector datasets), since a deleted dataset can never be read again and its vectors could only take up memory or storage. If that cleanup fails, the delete still succeeds (the vector datasets are unreachable) and the error is logged. ## Endpoints `POST /v1/gb/datasets`: `{"user_id": "u1", "name": "work", "tags": ["project"], "description": "optional"}` returns `201` with the dataset. `409` if a live dataset with that name exists, `400` for a bad name. `GET /v1/gb/datasets?user_id=u1`: lists that user's datasets: `{"datasets": [{"id": 1, "user_id": "u1", "name": "main", "tags": [], "created_at": "...", "deleted": false}, ...]}`, oldest first. `?include_deleted=true` also lists soft-deleted ones. `DELETE /v1/gb/datasets/{name}?user_id=u1`: soft-deletes the dataset and removes its vectors. `204`, or `404` if the user has no live dataset with that name. `GET /v1/gb/datasets/{name}/graph?user_id=u1`: exports the dataset's whole graph as JSON; see [Graph export](https://gligabao.mintlify.site/api-reference/graph.md). This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.