Edge 0.7 documentation updates (#2391)

* docs(edge): add "Modify the Vector Schema" step to quickstart

Documents the new Edge 0.7 API for adding and removing named vector
fields on an existing shard without recreating it, with Python and
Rust snippets.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* docs(edge): mention quantization support in quickstart

Adds a note after the EdgeConfig snippet that Edge supports all four
quantization methods (Scalar, Product, Binary, TurboQuant), with a
link to the quantization guide.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* docs(edge): add On-Device BM25 page for Edge 0.7

New guide covering the built-in BM25 sparse embedder: configuring a
sparse vector shard, creating a Bm25/EdgeBm25 embedder, embedding and
upserting documents, and querying. Includes Python and Rust snippets.
Also adds the page to the Edge index navigation table.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* docs(edge): add WAL segment size configuration to quickstart

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Upgrade code snippets to Edge 0.7.2

* Review feedback

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

qdrant-landing/content/documentation/edge/edge-quickstart.md

@@ -26,6 +26,8 @@ Set up a configuration by creating an instance of `EdgeConfig`. For example:
 
 {{< code-snippet path="/documentation/headless/snippets/edge/quickstart/" block="configure-edge-shard" >}}
 
+Qdrant Edge supports all Qdrant quantization methods: Scalar, Product, Binary, and TurboQuant. Configure quantization globally on `EdgeConfig.quantization_config` or override per-vector on `EdgeVectorParams.quantization_config`. See the [Quantization](/documentation/manage-data/quantization/) guide for configuration details.
+
 ## Initialize the Edge Shard
 
 Now you can create a new `EdgeShard` using `EdgeShard.create` (Python) or `EdgeShard::new` (Rust), passing the storage directory and configuration:
@@ -44,6 +46,18 @@ To retrieve a point by ID, use the `retrieve` method:
 
 {{< code-snippet path="/documentation/headless/snippets/edge/quickstart/" block="retrieve-point" >}}
 
+## Modify the Vector Schema
+
+You can add or remove named vectors to an existing Edge Shard's schema. This is useful when migrating to a new embedding model or adding hybrid search to an Edge Shard that already contains data.
+
+For example, to add a sparse vector for [BM25 keyword search](/documentation/edge/edge-bm25/):
+
+{{< code-snippet path="/documentation/headless/snippets/edge/quickstart/" block="modify-vector-schema" >}}
+
+Existing points aren't automatically populated with the new vector. Re-upsert them to add their values for the new field.
+
+To remove a named vector, use `UpdateOperation.delete_vector_name("text")` (Python) or `VectorNameOperations::DeleteVectorName` (Rust).
+
 ## Create a Payload Index
 
 To optimize operations like [filtering](#filtering) and [faceting](#faceting) on payload fields, first create a payload index on the fields you plan to use with these operations:
@@ -90,6 +104,14 @@ After closing an Edge Shard, you can reopen it by loading its data and configura
 
 {{< code-snippet path="/documentation/headless/snippets/edge/quickstart/" block="load-edge-shard" >}}
 
+## Custom WAL Size
+
+Qdrant Edge uses a Write-Ahead Log (WAL) to record every update before it's applied to storage. The WAL file is pre-allocated to 32 MB by default, inflating backup sizes and OS storage reports. To reduce the size, set `wal_options` on `EdgeConfig` when calling `new` or `load`. WAL options are only available in Rust.
+
+For example, to set the WAL size to 4 MB:
+
+{{< code-snippet path="/documentation/headless/snippets/edge/quickstart/" block="wal-options" >}}
+
 ## More 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).