docs: assorted one-line defects, plus a stale gRPC section and a silently wrong tab

docs/deploy/configuration/env-vars/index.md

@@ -42,7 +42,7 @@ import APITable from '@site/src/components/APITable';
 | `DEFAULT_SHARDING_COUNT` | Default `desiredCount` for new single-tenant collections, used when the collection definition does not specify one. An explicit `desiredCount` in the class creation request still takes precedence. A value of `0` (default) uses the cluster node count. Multi-tenant collections are unaffected. Must be `<= 512`. Runtime-configurable. Default: `0`<br/>Added in `v1.37` | `string - number` | `12` |
 | `DEFAULT_VECTOR_INDEX` | Default vector index type for new collections (and named vectors), used when the collection definition does not specify one. An explicit `vectorIndexType` in the collection definition still takes precedence. Available values: `hnsw`, `flat`, `dynamic`, and `hfresh`. Runtime-configurable. Default: `hnsw`<br/>Added in `v1.37.3` | `string` | `flat` |
 | `DEFAULT_VECTORIZER_MODULE` | Default vectorizer module - can be overridden by the vectorizer in the collection definition. | `string` | `text2vec-contextionary` |
-| `API_BASED_MODULES_DISABLED` | Weaviate automatically enables the usage of all [API based modules](../../../weaviate/model-providers/index.md#api-based). Set this variable to `true` in order to limit access and only allow specific modules through the [`ENABLE_MODULES`](#ENABLE_MODULES) variable. Default: `false`<br/> Added in `v1.33` | `boolean` | `true` |
+| `API_BASED_MODULES_DISABLED` | Weaviate automatically enables the usage of all [API-based modules](../../../weaviate/model-providers/index.md#api-based). Set this variable to `true` in order to limit access and only allow specific modules through the [`ENABLE_MODULES`](#ENABLE_MODULES) variable. Default: `false`<br/> Added in `v1.33` | `boolean` | `true` |
 | `DISABLE_LAZY_LOAD_SHARDS` | When `false`, enable lazy shard loading to improve mean time to recovery in multi-tenant deployments. **Deprecated in `v1.36.6`.** Use `LAZY_LOAD_SHARD_COUNT_THRESHOLD` and `LAZY_LOAD_SHARD_SIZE_THRESHOLD_GB` instead. Weaviate now auto-detects when lazy loading is needed per collection. | `string` | `false` |
 | `DISABLE_TELEMETRY` | Disable [telemetry](/deploy/configuration/telemetry.md) data collection | boolean | `false` |
 | `DISK_USE_READONLY_PERCENTAGE` | If disk usage is higher than the given percentage all shards on the affected node will be marked as `READONLY`, meaning all future write requests will fail. See [Disk Pressure Warnings and Limits for details](/deploy/configuration/persistence.md#disk-pressure-warnings-and-limits). | `string - number` | `90` |
@@ -51,7 +51,7 @@ import APITable from '@site/src/components/APITable';
 | `ENABLE_MODULES` | Specify which modules are enabled and can be used. | `string - comma separated names` | `text2vec-openai,generative-openai` |
 | `ENABLE_TOKENIZER_GSE` | Enable the [`GSE` tokenizer](/weaviate/config-refs/collections.mdx) for use | `boolean` | `true` |
 | `ENABLE_TOKENIZER_KAGOME_JA` | Enable the [`Kagome` tokenizer for Japanese](/weaviate/config-refs/collections.mdx) for use | `boolean` | `true` |
-| `ENABLE_TOKENIZER_KAGOME_KR` | Enable the [`Kagome` tokenizer for Korean](/weaviate/config-refs/collections.mdx#) for use | `boolean` | `true` |
+| `ENABLE_TOKENIZER_KAGOME_KR` | Enable the [`Kagome` tokenizer for Korean](/weaviate/config-refs/collections.mdx) for use | `boolean` | `true` |
 | `EXPORT_DEFAULT_BUCKET` | Storage bucket name for [collection exports](/docs/deploy/configuration/export.md). Required for S3, GCS, and Azure backends.<br/>Added in `v1.37` | `string` | `my-export-bucket` |
 | `EXPORT_DEFAULT_PATH` | Optional base path prefix for exported files within the bucket for [collection exports](/docs/deploy/configuration/export.md). Defaults to `""` (no prefix). _Changed in `v1.37.1`: previously required to be explicitly set._<br/>Added in `v1.37` | `string` | `exports/my-cluster` |
 | `EXPORT_ENABLED` | Enable the [collection export](/docs/deploy/configuration/export.md) API. Default: `false`<br/>Added in `v1.37` | `boolean` | `true` |

docs/deploy/installation-guides/embedded.md

@@ -44,6 +44,7 @@ To configure Embedded Weaviate, set these variables in your instantiation code o
 | :-- | :-- | :-- | :-- |
 | `additional_env_vars` | string | None. | Pass additional environment variables, such as API keys, to the server. |
 | `binary_path` | string | varies | Binary download directory. If the binary is not present, the client downloads the binary. <br/><br/> If `XDG_CACHE_HOME` is set, its value is used verbatim as the default. No subdirectory is appended, so `XDG_CACHE_HOME=/foo` makes the default exactly `/foo`.<br/><br/>If `XDG_CACHE_HOME` is not set, the default is: `~/.cache/weaviate-embedded/` |
+| `grpc_port` | integer | 50060 | The Weaviate server gRPC port. The client passes this value to the server as `GRPC_PORT`. |
 | `hostname` | string | 127.0.0.1 | Hostname or IP address  |
 | `persistence_data_path` | string | varies | Data storage directory.<br/><br/> If `XDG_DATA_HOME` is set, its value is used verbatim as the default. No subdirectory is appended, so `XDG_DATA_HOME=/foo` makes the default exactly `/foo`.<br/><br/>If `XDG_DATA_HOME` is not set, the default is: `~/.local/share/weaviate` |
 | `port` | integer | 8079 | The Weaviate server request port. |
@@ -71,7 +72,7 @@ The following modules are enabled by default:
 - `text2vec-huggingface`
 - `text2vec-openai`
 
-To enabled additional modules, add them to your instantiation code.
+To enable additional modules, add them to your instantiation code.
 
 For example, to add the `backup-s3` module, instantiate your client like this:
 
@@ -130,7 +131,7 @@ Embedded Weaviate is supported for Python and TypeScript clients.
 
 ### Python clients
 
-[Python](docs/weaviate/client-libraries/python/index.mdx) v3 client support is new in `v3.15.4` for Linux and `v3.21.0` for macOS. The Python client v4 requires server version v1.23.7 or higher.
+[Python](docs/weaviate/client-libraries/python/index.mdx) v3 client support is new in `v3.15.4` for Linux and `v3.21.0` for macOS. The Python client requires Weaviate `v1.23.7` or later.
 
 ### TypeScript clients
 

docs/deploy/production/aws/network-security.md

@@ -28,7 +28,7 @@ Access control is the cornerstone of this network security strategy. It implemen
 
 #### Private subnet strategy
 
-Network isolation is the foundation of our this strategy. Critical infrastructure should reside in private subnets with no direct internet connectivity. This eliminates internet-based attacks and forces all access through controlled entry points.
+Network isolation is the foundation of this strategy. Critical infrastructure should reside in private subnets with no direct internet connectivity. This eliminates internet-based attacks and forces all access through controlled entry points.
 
 #### Core components
 
@@ -124,8 +124,6 @@ Data transfer for backups and application data can be secured, this is what is n
 
 ### Scaling and performance strategies
 
-#### Application load balancer (ALB) configuration
-
 #### SSL/TLS management
 
 - Automated certificate provisioning through AWS Certificate Manager.
@@ -166,8 +164,6 @@ Secure scaling policies maintains security posture during capacity changes.
 
 ### High availability and disaster recovery
 
-#### Multi-AZ architecture
-
 #### Weaviate configuration
 
 - **Minimum** 3 replicas distributed across AZs.
@@ -185,7 +181,7 @@ Secure scaling policies maintains security posture during capacity changes.
 #### Network visibility
 
 - VPC flow logs to capture traffic metadata for security analysis.
-- Real0time streaming to SIEMs.
+- Real-time streaming to SIEMs.
 - Baseline establishment and anomaly detection.
 
 #### Security monitoring

docs/weaviate/api/graphql/get.md

@@ -229,8 +229,8 @@ The following search operators are available.
 | --- | --- | --- | --- |
 | `nearObject` | Vector search using a Weaviate object | *none* | [Learn more](./search-operators.md#nearobject) |
 | `nearVector` | Vector search using a raw vector | *none* | [Learn more](./search-operators.md#nearvector) |
-| `nearText` | Vector search using a text query | Text embedding model |  |
-| `nearImage` | Vector search using an image | Multi-modal embedding model |
+| `nearText` | Vector search using a text query | Text embedding model | [Learn more](./search-operators.md#neartext) |
+| `nearImage` | Vector search using an image | Multi-modal embedding model | [Learn more](./search-operators.md#multimodal-search) |
 | `hybrid` | Combine vector and BM25 search results |  *none* | [Learn more](../graphql/search-operators.md#hybrid) |
 | `bm25`   | Keyword search with BM25F ranking  | *none* | [Learn more](../graphql/search-operators.md#bm25) |
 

docs/weaviate/concepts/interface.md

@@ -6,7 +6,7 @@ image: og/docs/concepts.jpg
 # tags: ['architecture', 'interface', 'API design']
 ---
 
-You can manage and use Weaviate through its APIs. Weaviate has a RESTful API and a GraphQL API. The client libraries broadly mirror this API surface, although feature coverage can vary by language; see the [client library pages](/weaviate/client-libraries/index.mdx) for what each one supports. Some clients, e.g. the Python client, have additional functionality, such as full schema management and batching operations. This way, Weaviate is easy to use in custom projects. Additionally, the APIs are intuitive, so it is easy to integrate into your existing data landscape.
+You can manage and use Weaviate through its APIs. Weaviate has RESTful, GraphQL, and gRPC APIs. The client libraries broadly mirror this API surface, although feature coverage can vary by language; see the [client library pages](/weaviate/client-libraries/index.mdx) for what each one supports. Some clients, e.g. the Python client, have additional functionality, such as full schema management and batching operations. This way, Weaviate is easy to use in custom projects. Additionally, the APIs are intuitive, so it is easy to integrate into your existing data landscape.
 
 This page contains information on how Weaviate's APIs are designed, and how you can use Weaviate Console to search through your Weaviate instance with GraphQL.
 
@@ -125,9 +125,11 @@ There are currently three main functions in a GraphQL request: "Get{}", "Explore
 
 ## gRPC API support
 
-Starting with version `1.19`, Weaviate is introducing support for the gRPC (gRPC Remote Procedure Calls) API, with the aim of making Weaviate even faster over time.
+Alongside the RESTful and GraphQL APIs, Weaviate serves a gRPC API. gRPC is built on HTTP/2 and Protocol Buffers, which makes it faster and more efficient than sending the equivalent request as JSON over HTTP. It was introduced in Weaviate `v1.19.0` and has been considered stable since `v1.23.7`.
 
-This will not result in any user-facing API changes. As of May 2023, gRPC has been added at a very small scale, with the goal of rolling it out further over time to the core library as well as the clients.
+gRPC carries most of the search and batch import traffic that the client libraries generate, so a Weaviate deployment usually exposes a gRPC port (`50051` by default, configurable with the `GRPC_PORT` [environment variable](/deploy/configuration/env-vars/index.md)) in addition to the REST port. Client coverage is not uniform: the [Python](/weaviate/client-libraries/python/index.mdx), [TypeScript](/weaviate/client-libraries/typescript/index.mdx), [Java](/weaviate/client-libraries/java/index.mdx), and [C#](/weaviate/client-libraries/csharp.mdx) clients use gRPC for queries and batch operations, while the [Go](/weaviate/client-libraries/go.md) client uses it for batch imports and reaches gRPC search through its experimental API.
+
+For the Protobuf definitions and for ways to call the API without a client library, see the [gRPC API reference](../api/grpc.md).
 
 ## Weaviate Console
 
@@ -137,7 +139,7 @@ The [Weaviate Console](/go/console?utm_content=others) is a dashboard to manage
 
 ## Weaviate Clients
 
-Weaviate has several client libraries: in [C#](/weaviate/client-libraries/csharp.mdx), [Go](/weaviate/client-libraries/go.md), [Java](/weaviate/client-libraries/java/index.mdx), [Python](/weaviate/client-libraries/python/index.mdx) and [TypeScript/JavaScript](/weaviate/client-libraries/typescript/index.mdx). The client libraries broadly mirror the server API surface, although feature coverage varies by language. See the [client library pages](/weaviate/client-libraries/index.mdx) for what each one supports. Some clients, e.g. the Python client, have additional functionality, such as full schema management and batching operations. This way, Weaviate is easy to use in custom projects. The APIs are intuitive to use, so it is easy to integrate Weaviate into your existing data landscape.
+Weaviate has several client libraries: in [C#](/weaviate/client-libraries/csharp.mdx), [Go](/weaviate/client-libraries/go.md), [Java](/weaviate/client-libraries/java/index.mdx), [Python](/weaviate/client-libraries/python/index.mdx), and [TypeScript/JavaScript](/weaviate/client-libraries/typescript/index.mdx). The client libraries broadly mirror the server API surface, although feature coverage varies by language. See the [client library pages](/weaviate/client-libraries/index.mdx) for what each one supports. Some clients, e.g. the Python client, have additional functionality, such as full schema management and batching operations. This way, Weaviate is easy to use in custom projects. The APIs are intuitive to use, so it is easy to integrate Weaviate into your existing data landscape.
 
 ## Further resources
 

docs/weaviate/configuration/rbac/manage-groups.mdx

@@ -303,4 +303,3 @@ Groups assigned to role 'testRole':
 import DocsFeedback from "/_includes/docs-feedback.mdx";
 
 <DocsFeedback />
-````

docs/weaviate/recipes.mdx

@@ -3,7 +3,7 @@ title: Weaviate Recipes (code examples)
 hide_table_of_contents: true
 ---
 
-This page contains recipes for common Weaviate operations. You can also check out the original [Jupyter Notebooks](https://github.com/weaviate/recipes) the recipes where created from.
+This page contains recipes for common Weaviate operations. You can also check out the original [Jupyter Notebooks](https://github.com/weaviate/recipes) the recipes were created from.
 
 import RecipesCards from "@site/src/components/RecipesCards";
 

docs/weaviate/search/boost.md

@@ -18,6 +18,8 @@ import BoostPreview from '/_includes/feature-notes/boost.mdx';
 
 Apply boost to vector, hybrid, BM25, near-text, near-vector, near-object, near-image, and near-media queries.
 
+The examples on this page are Python only, because `boost` is currently available in the Python client and not yet in the TypeScript, Go, Java, or C# clients.
+
 ## How it works
 
 A boost is a **post-retrieval rescorer**:

docs/weaviate/search/generative.md

@@ -52,7 +52,7 @@ To use RAG with a [generative model integration](../model-providers/index.md):
   </TabItem>
   <TabItem value="go" label="Go">
 
-```ts
+```go
 // Go support coming soon
 ```
 
@@ -96,7 +96,7 @@ The second review is for the Stadt Krems 2009 Steinterrassen Riesling from Austr
 
 :::tip
 
-For more information on the available modeld and their additional options, see the [model providers section](../model-providers/index.md).
+For more information on the available models and their additional options, see the [model providers section](../model-providers/index.md).
 
 :::
 ## Named vectors
@@ -168,7 +168,7 @@ The second review is for the Stadt Krems 2009 Steinterrassen Riesling from Austr
 ## Single prompt search
 
 Single prompt search returns a generated response for each object in the query results.<br/>
-Define object `properties` – using `{prop-name}` syntax – to interpolate retrieved content in the prompt.<br/>
+Define object `properties` with the `{prop-name}` syntax to interpolate retrieved content in the prompt.<br/>
 The properties you use in the prompt do not have to be among the properties you retrieve in the query.
 
 <Tabs className="code" groupId="languages">
@@ -268,8 +268,8 @@ You can use *generative parameters* to specify additional options when performin
   <TabItem value="java" label="Java">
     <FilteredTextBlock
       text={JavaV6Code}
-      startMarker="// START SingleGenerativeParametersTS"
-      endMarker="// END SingleGenerativeParametersTS"
+      startMarker="// START SingleGenerativeParametersPython"
+      endMarker="// END SingleGenerativeParametersPython"
       language="java"
     />
   </TabItem>

docs/weaviate/starter-guides/custom-vectors.mdx

@@ -71,13 +71,13 @@ Weaviate is open source. You can [run Weaviate](/deploy/index.mdx) locally, in t
 
 ### Client library
 
-[Client libraries](/weaviate/client-libraries) simplify working with Weaviate. Clients are available for multiple programming languages. This guide provides examples in Python, Typescript, and cURL.
+[Client libraries](/weaviate/client-libraries) simplify working with Weaviate. Clients are available for multiple programming languages. This guide provides examples in Python, TypeScript, Java, C#, and cURL.
 
 To install a client library, use the installer for the client language:
 
 <Tabs className="code" groupId="languages">
 <TabItem value="py" label="Python">
-The v4 client requires Weaviate `v1.23.7` and later.<br/><br/>
+The Python client requires Weaviate `v1.23.7` or later.<br/><br/>
 
 ```bash
 pip install -U weaviate-client
@@ -101,6 +101,13 @@ npm install weaviate-client
 </dependency>
 ```
 
+</TabItem>
+<TabItem value="csharp" label="C#">
+
+```bash
+dotnet add package Weaviate.Client --version ||site.csharp_client_version||
+```
+
 </TabItem>
 </Tabs>