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---
title: PrivateGPT
weight: 1600
---
# PrivateGPT
[PrivateGPT](https://docs.privategpt.dev/) is a production-ready AI project that allows you to inquire about your documents using Large Language Models (LLMs) with offline support.
PrivateGPT supports Qdrant as a vectorstore for ingesting and retrieving documents.
## Installation
To enable Qdrant, install the qdrant extra within your PrivateGPT project first.
```bash
poetry install --extras qdrant
```
## Configuration
Qdrant settings can be configured by setting values to the qdrant property in the `settings.yaml` file. By default, Qdrant tries to connect to an instance at http://localhost:3000.
Example:
```yaml
vectorstore:
database: qdrant
qdrant:
url: "https://xyz-example.eu-central.aws.cloud.qdrant.io:6333"
api_key: "<your-api-key>"
```
The available [configuration options](https://docs.privategpt.dev/manual/storage/vector-stores#qdrant-configuration) are:
| Field | Description |
|--------------|-------------|
| location | If `:memory:` - use in-memory Qdrant instance.<br>If `str` - use it as a `url` parameter.|
| url | Either host or str of `Optional[scheme], host, Optional[port], Optional[prefix]`.<br> 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.<br>Example: `service/v1` will result in `http://localhost:6333/service/v1/{qdrant-endpoint}` for REST API.|
| timeout | Timeout for REST and gRPC API requests.<br>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.|
## Next steps
Find the PrivateGPT docs [here](https://docs.privategpt.dev/).