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Edge v0.6 docs (#2199)

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* Initial Rust snippets

* Update content for Rust

* Upgrade Rust to 1.94.0; test Edge code snippets against dev

* Temporarily test against Edge shim crate

* Move to EdgeShardConfig and EdgeVectorParams

* Add docs for payload indexing, filtering, facet(), and optimize()

* De-emphasize on-device use case

* Update link to Rust examples on Github

* Flattened API

* Switch to new/create and load to initialize shards

* Fixups for released packages

* Mention recover_partial_snapshot on method list

* Link to Github dev branch for examples

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Co-authored-by: xzfc <xzfcpw@gmail.com>
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# What Is Qdrant Edge?
Qdrant Edge is a lightweight, embedded vector search engine for AI on devices like robots, kiosks, home assistants, and mobile phones. Designed for real-time vector search on edge devices with limited computational resources, Qdrant Edge allows applications to use Qdrant's functionality even with intermittent or no internet connectivity.
Qdrant Edge is a lightweight, embedded vector search engine for in-process retrieval with a minimal memory footprint and no background services. Qdrant Edge is designed for applications requiring low-latency vector search in environments with limited or intermittent connectivity, such as robots, kiosks, home assistants, and mobile phones.
Qdrant Edge does not run as a separate process. Instead, it runs inside an application process. Data is stored and queried locally on the device, ensuring low-latency access and enhanced privacy since data does not need to be transmitted to an external server. That said, Qdrant Edge provides APIs to [synchronize data with a Qdrant server](/documentation/edge/edge-data-synchronization-patterns/). This enables you to offload heavy computations such as indexing to more powerful server instances, back up and restore data, and centrally aggregate data from multiple edge devices.
Unlike Qdrant Server, which uses a client-server architecture, Qdrant Edge runs inside the application process. Think of it as SQLite, but for vector search. Data is stored and queried locally, ensuring low-latency access and enhanced privacy since data does not need to be transmitted to an external server. That said, Qdrant Edge provides APIs to [synchronize data with a Qdrant server](/documentation/edge/edge-data-synchronization-patterns/). This enables you to offload heavy computations such as indexing to more powerful server instances, back up and restore data, and centrally aggregate data from multiple edge devices.
## Qdrant Edge Shard
Qdrant Edge is built around the concept of an **Edge Shard**: a self-contained storage unit that can operate independently on edge devices. Each Edge Shard manages its own data, including vector and payload storage, and can perform local search and retrieval operations.
Qdrant Edge is built around the concept of an **Edge Shard**: a self-contained storage unit that can operate independently. Each Edge Shard manages its own data, including vector and payload storage, and can perform local search and retrieval operations.
![Qdrant Edge Shards operate on edge devices](/documentation/edge/qdrant-edge.png)
To work with a Qdrant Edge Shard from a Python application, use the [Python Bindings for Qdrant Edge](https://pypi.org/project/qdrant-edge-py/) package. This package provides an `EdgeShard` class with methods to manage data, query it, and restore snapshots:
To work with a Qdrant Edge Shard, use the [Python Bindings for Qdrant Edge](https://pypi.org/project/qdrant-edge-py/) package or the [`qdrant-edge` Rust crate](https://crates.io/crates/qdrant-edge). This library provides an `EdgeShard` class with methods to manage data, query it, and restore snapshots:
- `new` (Rust) / `create` (Python): Creates a new Edge Shard at the given path with the provided configuration. Fails if the path already contains data.
- `load`: Initializes an Edge Shard by reading existing data and optionally the configuration from disk.
- `update`: Updates the data.
- `query`: Queries the data.
- `facet`: Returns the top N distinct values of a payload field, sorted by the number of points that have each value.
- `scroll`: Returns all points.
- `count`: Returns the number of points.
- `retrieve`: Retrieves points with the given IDs.
- `flush`: Flushes the data to ensure that all writes have been persisted to disk.
- `close`: Cleanly destroys the shard instance, ensuring the data is flushed. The data is persisted on disk and can be used to create another shard.
- `close`: Cleanly destroys the shard instance, ensuring the data is flushed (Python). The data is persisted on disk and can be used to create another shard. In Rust, use the `Drop` trait to ensure the shard is closed when it goes out of scope.
- `optimize`: Optimizes the Edge Shard by removing data marked for deletion, merging segments, and creating indexes.
- `info`: Returns metadata information about the shard.
- `unpack_snapshot`: Unpacks a snapshot on disk.
- `snapshot_manifest`: Returns the current shard’s snapshot manifest.
- `update_from_snapshot`: Applies a snapshot to the shard.
- `recover_partial_snapshot` (Rust) / `update_from_snapshot` (Python): Applies a snapshot to the shard.
## Using Qdrant Edge
To get started with Qdrant Edge, refer to the [Qdrant Edge Quickstart Guide](/documentation/edge/edge-quickstart/).
| Type | Guide | What you'll learn |
|--------------|----------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------|
| **Beginner** | [Qdrant Edge Quickstart](/documentation/edge/edge-quickstart/) | Get started with Qdrant Edge and learn the basics of managing and querying data |
| **Beginner** | [On-Device Embeddings](/documentation/edge/edge-fastembed-embeddings/) | Generate vector embeddings directly on edge devices using FastEmbed |
| **Reference** | [Data Synchronization Patterns](/documentation/edge/edge-data-synchronization-patterns/) | Overview of patterns for synchronizing data between Edge Shards and Qdrant server collections |
| **Advanced** | [Synchronize with a Server](/documentation/edge/edge-synchronization-guide/) | Synchronize an Edge Shard with a Qdrant server collection to offload indexing and synchronize data between devices |
### More Examples
## More Examples
More examples and advanced usage of Qdrant Edge API can be found in the [GitHub repository](https://github.com/qdrant/qdrant/tree/master/lib/edge/python/examples).
The Qdrant GitHub repository contains examples of using the Qdrant Edge API in [Python](https://github.com/qdrant/qdrant/tree/dev/lib/edge/python/examples) and [Rust](https://github.com/qdrant/qdrant/tree/dev/lib/edge/publish/examples).