> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.privategpt.dev/llms.txt. > For full documentation content, see https://docs.privategpt.dev/llms-full.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.privategpt.dev/_mcp/server. ## Vectorstores PrivateGPT supports [Qdrant](https://qdrant.tech/), [Milvus](https://milvus.io/), [Chroma](https://www.trychroma.com/), [PGVector](https://github.com/pgvector/pgvector) and [ClickHouse](https://github.com/ClickHouse/ClickHouse) 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`, `milvus`, `chroma`, `postgres` and `clickhouse`. ```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 ``` ### Milvus configuration To enable Milvus, set the `vectorstore.database` property in the `settings.yaml` file to `milvus` and install the `milvus` extra. ```bash poetry install --extras vector-stores-milvus ``` The available configuration options are: | Field | Description | | ---------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | uri | Default is set to "local\_data/private\_gpt/milvus/milvus\_local.db" as a local file; you can also set up a more performant Milvus server on docker or k8s e.g.[http://localhost:19530](http://localhost:19530), as your uri; To use Zilliz Cloud, adjust the uri and token to Endpoint and Api key in Zilliz Cloud. | | token | Pair with Milvus server on docker or k8s or zilliz cloud api key. | | collection\_name | The name of the collection, set to default "milvus\_db". | | overwrite | Overwrite the data in collection if it existed, set to default as True. | To obtain a local setup (disk-based database) without running a Milvus server, configure the uri value in settings.yaml, to store in local\_data/private\_gpt/milvus/milvus\_local.db. ### 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: 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. ### ClickHouse To utilize ClickHouse as the vector store, a [ClickHouse](https://github.com/ClickHouse/ClickHouse) database must be employed. To enable ClickHouse, set the `vectorstore.database` property in the `settings.yaml` file to `clickhouse` and install the `vector-stores-clickhouse` extra. ```bash poetry install --extras vector-stores-clickhouse ``` ClickHouse settings can be configured by setting values to the `clickhouse` property in the `settings.yaml` file. The available configuration options are: | Field | Description | | -------------------------- | --------------------------------------------------------------------------- | | **host** | The server hosting the ClickHouse database. Default is `localhost` | | **port** | The port on which the ClickHouse database is accessible. Default is `8123` | | **username** | The username for database access. Default is `default` | | **password** | The password for database access. (Optional) | | **database** | The specific database to connect to. Default is `__default__` | | **secure** | Use https/TLS for secure connection to the server. Default is `false` | | **interface** | The protocol used for the connection, either 'http' or 'https'. (Optional) | | **settings** | Specific ClickHouse server settings to be used with the session. (Optional) | | **connect\_timeout** | Timeout in seconds for establishing a connection. (Optional) | | **send\_receive\_timeout** | Read timeout in seconds for http connection. (Optional) | | **verify** | Verify the server certificate in secure/https mode. (Optional) | | **ca\_cert** | Path to Certificate Authority root certificate (.pem format). (Optional) | | **client\_cert** | Path to TLS Client certificate (.pem format). (Optional) | | **client\_cert\_key** | Path to the private key for the TLS Client certificate. (Optional) | | **http\_proxy** | HTTP proxy address. (Optional) | | **https\_proxy** | HTTPS proxy address. (Optional) | | **server\_host\_name** | Server host name to be checked against the TLS certificate. (Optional) | For example: ```yaml vectorstore: database: clickhouse clickhouse: host: localhost port: 8443 username: admin password: database: embeddings secure: false ``` The following table will be created in the database: ``` clickhouse-client :) \d embeddings.llama_index Table "llama_index" № | name | type | default_type | default_expression | comment | codec_expression | ttl_expression ----|-----------|----------------------------------------------|--------------|--------------------|---------|------------------|--------------- 1 | id | String | | | | | 2 | doc_id | String | | | | | 3 | text | String | | | | | 4 | vector | Array(Float32) | | | | | 5 | node_info | Tuple(start Nullable(UInt64), end Nullable(UInt64)) | | | | | 6 | metadata | String | | | | | clickhouse-client ``` 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.