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## Vectorstores
PrivateGPT supports [Qdrant](https://qdrant.tech/), [Chroma](https://www.trychroma.com/) and [PGVector](https://github.com/pgvector/pgvector) as vectorstore providers. Qdrant being the default.
In order to select one or the other, set the `vectorstore.database` property in the `settings.yaml` file to `qdrant`, `chroma` or `postgres`.
```yaml
vectorstore:
database: qdrant
```
### Qdrant configuration
To enable Qdrant, set the `vectorstore.database` property in the `settings.yaml` file to `qdrant`.
Qdrant settings can be configured by setting values to the `qdrant` property in the `settings.yaml` file.
The available configuration options are:
| Field | Description |
|--------------|-------------|
| location | If `:memory:` - use in-memory Qdrant instance. If `str` - use it as a `url` parameter.|
| url | Either host or str of 'Optional[scheme], host, Optional[port], Optional[prefix]'. Eg. `http://localhost:6333` |
| port | Port of the REST API interface. Default: `6333` |
| grpc_port | Port of the gRPC interface. Default: `6334` |
| prefer_grpc | If `true` - use gRPC interface whenever possible in custom methods. |
| https | If `true` - use HTTPS(SSL) protocol.|
| api_key | API key for authentication in Qdrant Cloud.|
| prefix | If set, add `prefix` to the REST URL path. Example: `service/v1` will result in `http://localhost:6333/service/v1/{qdrant-endpoint}` for REST API.|
| timeout | Timeout for REST and gRPC API requests. Default: 5.0 seconds for REST and unlimited for gRPC |
| host | Host name of Qdrant service. If url and host are not set, defaults to 'localhost'.|
| path | Persistence path for QdrantLocal. Eg. `local_data/private_gpt/qdrant`|
| force_disable_check_same_thread | Force disable check_same_thread for QdrantLocal sqlite connection, defaults to True.|
By default Qdrant tries to connect to an instance of Qdrant server at `http://localhost:3000`.
To obtain a local setup (disk-based database) without running a Qdrant server, configure the `qdrant.path` value in settings.yaml:
```yaml
qdrant:
path: local_data/private_gpt/qdrant
```
### Chroma configuration
To enable Chroma, set the `vectorstore.database` property in the `settings.yaml` file to `chroma` and install the `chroma` extra.
```bash
poetry install --extras chroma
```
By default `chroma` will use a disk-based database stored in local_data_path / "chroma_db" (being local_data_path defined in settings.yaml)
### PGVector
To use the PGVector store a [postgreSQL](https://www.postgresql.org/) database with the PGVector extension must be used.
To enable PGVector, set the `vectorstore.database` property in the `settings.yaml` file to `postgres` and install the `vector-stores-postgres` extra.
```bash
poetry install --extras vector-stores-postgres
```
PGVector settings can be configured by setting values to the `postgres` property in the `settings.yaml` file.
The available configuration options are:
| Field | Description |
|---------------|-----------------------------------------------------------|
| **host** | The server hosting the Postgres database. Default is `localhost` |
| **port** | The port on which the Postgres database is accessible. Default is `5432` |
| **database** | The specific database to connect to. Default is `postgres` |
| **user** | The username for database access. Default is `postgres` |
| **password** | The password for database access. (Required) |
| **schema_name** | The database schema to use. Default is `private_gpt` |
For example:
```yaml
vectorstore:
database: postgres
postgres:
host: localhost
port: 5432
database: postgres
user: postgres
password: <PASSWORD>
schema_name: private_gpt
```
The following table will be created in the database
```
postgres=# \d private_gpt.data_embeddings
Table "private_gpt.data_embeddings"
Column | Type | Collation | Nullable | Default
-----------+-------------------+-----------+----------+---------------------------------------------------------
id | bigint | | not null | nextval('private_gpt.data_embeddings_id_seq'::regclass)
text | character varying | | not null |
metadata_ | json | | |
node_id | character varying | | |
embedding | vector(768) | | |
Indexes:
"data_embeddings_pkey" PRIMARY KEY, btree (id)
postgres=#
```
The dimensions of the embeddings columns will be set based on the `embedding.embed_dim` value. If the embedding model changes this table may need to be dropped and recreated to avoid a dimension mismatch.
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