docs: minor updates for js migration guides (#1451)

Co-authored-by: Will Jones <willjones127@gmail.com>

docs/src/js/namespaces/embedding/README.md

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+[**@lancedb/lancedb**](../../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../../globals.md) / embedding
+
+# embedding
+
+## Index
+
+### Classes
+
+- [EmbeddingFunction](classes/EmbeddingFunction.md)
+- [EmbeddingFunctionRegistry](classes/EmbeddingFunctionRegistry.md)
+- [OpenAIEmbeddingFunction](classes/OpenAIEmbeddingFunction.md)
+
+### Interfaces
+
+- [EmbeddingFunctionConfig](interfaces/EmbeddingFunctionConfig.md)
+
+### Type Aliases
+
+- [OpenAIOptions](type-aliases/OpenAIOptions.md)
+
+### Functions
+
+- [LanceSchema](functions/LanceSchema.md)
+- [getRegistry](functions/getRegistry.md)
+- [register](functions/register.md)

docs/src/js/namespaces/embedding/classes/EmbeddingFunction.md

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+[**@lancedb/lancedb**](../../../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../../../globals.md) / [embedding](../README.md) / EmbeddingFunction
+
+# Class: `abstract` EmbeddingFunction<T, M>
+
+An embedding function that automatically creates vector representation for a given column.
+
+## Extended by
+
+- [`OpenAIEmbeddingFunction`](OpenAIEmbeddingFunction.md)
+
+## Type Parameters
+
+• **T** = `any`
+
+• **M** *extends* `FunctionOptions` = `FunctionOptions`
+
+## Constructors
+
+### new EmbeddingFunction()
+
+> **new EmbeddingFunction**<`T`, `M`>(): [`EmbeddingFunction`](EmbeddingFunction.md)<`T`, `M`>
+
+#### Returns
+
+[`EmbeddingFunction`](EmbeddingFunction.md)<`T`, `M`>
+
+## Methods
+
+### computeQueryEmbeddings()
+
+> **computeQueryEmbeddings**(`data`): `Promise`<`number`[] \| `Float32Array` \| `Float64Array`>
+
+Compute the embeddings for a single query
+
+#### Parameters
+
+• **data**: `T`
+
+#### Returns
+
+`Promise`<`number`[] \| `Float32Array` \| `Float64Array`>
+
+***
+
+### computeSourceEmbeddings()
+
+> `abstract` **computeSourceEmbeddings**(`data`): `Promise`<`number`[][] \| `Float32Array`[] \| `Float64Array`[]>
+
+Creates a vector representation for the given values.
+
+#### Parameters
+
+• **data**: `T`[]
+
+#### Returns
+
+`Promise`<`number`[][] \| `Float32Array`[] \| `Float64Array`[]>
+
+***
+
+### embeddingDataType()
+
+> `abstract` **embeddingDataType**(): `Float`<`Floats`>
+
+The datatype of the embeddings
+
+#### Returns
+
+`Float`<`Floats`>
+
+***
+
+### ndims()
+
+> **ndims**(): `undefined` \| `number`
+
+The number of dimensions of the embeddings
+
+#### Returns
+
+`undefined` \| `number`
+
+***
+
+### sourceField()
+
+> **sourceField**(`optionsOrDatatype`): [`DataType`<`Type`, `any`>, `Map`<`string`, [`EmbeddingFunction`](EmbeddingFunction.md)<`any`, `FunctionOptions`>>]
+
+sourceField is used in combination with `LanceSchema` to provide a declarative data model
+
+#### Parameters
+
+• **optionsOrDatatype**: `DataType`<`Type`, `any`> \| `Partial`<`FieldOptions`<`DataType`<`Type`, `any`>>>
+
+The options for the field or the datatype
+
+#### Returns
+
+[`DataType`<`Type`, `any`>, `Map`<`string`, [`EmbeddingFunction`](EmbeddingFunction.md)<`any`, `FunctionOptions`>>]
+
+#### See
+
+lancedb.LanceSchema
+
+***
+
+### toJSON()
+
+> `abstract` **toJSON**(): `Partial`<`M`>
+
+Convert the embedding function to a JSON object
+It is used to serialize the embedding function to the schema
+It's important that any object returned by this method contains all the necessary
+information to recreate the embedding function
+
+It should return the same object that was passed to the constructor
+If it does not, the embedding function will not be able to be recreated, or could be recreated incorrectly
+
+#### Returns
+
+`Partial`<`M`>
+
+#### Example
+
+```ts
+class MyEmbeddingFunction extends EmbeddingFunction {
+  constructor(options: {model: string, timeout: number}) {
+    super();
+    this.model = options.model;
+    this.timeout = options.timeout;
+  }
+  toJSON() {
+    return {
+      model: this.model,
+      timeout: this.timeout,
+    };
+}
+```
+
+***
+
+### vectorField()
+
+> **vectorField**(`optionsOrDatatype`?): [`DataType`<`Type`, `any`>, `Map`<`string`, [`EmbeddingFunction`](EmbeddingFunction.md)<`any`, `FunctionOptions`>>]
+
+vectorField is used in combination with `LanceSchema` to provide a declarative data model
+
+#### Parameters
+
+• **optionsOrDatatype?**: `DataType`<`Type`, `any`> \| `Partial`<`FieldOptions`<`DataType`<`Type`, `any`>>>
+
+#### Returns
+
+[`DataType`<`Type`, `any`>, `Map`<`string`, [`EmbeddingFunction`](EmbeddingFunction.md)<`any`, `FunctionOptions`>>]
+
+#### See
+
+lancedb.LanceSchema

docs/src/js/namespaces/embedding/classes/EmbeddingFunctionRegistry.md

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+[**@lancedb/lancedb**](../../../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../../../globals.md) / [embedding](../README.md) / EmbeddingFunctionRegistry
+
+# Class: EmbeddingFunctionRegistry
+
+This is a singleton class used to register embedding functions
+and fetch them by name. It also handles serializing and deserializing.
+You can implement your own embedding function by subclassing EmbeddingFunction
+or TextEmbeddingFunction and registering it with the registry
+
+## Constructors
+
+### new EmbeddingFunctionRegistry()
+
+> **new EmbeddingFunctionRegistry**(): [`EmbeddingFunctionRegistry`](EmbeddingFunctionRegistry.md)
+
+#### Returns
+
+[`EmbeddingFunctionRegistry`](EmbeddingFunctionRegistry.md)
+
+## Methods
+
+### functionToMetadata()
+
+> **functionToMetadata**(`conf`): `Record`<`string`, `any`>
+
+#### Parameters
+
+• **conf**: [`EmbeddingFunctionConfig`](../interfaces/EmbeddingFunctionConfig.md)
+
+#### Returns
+
+`Record`<`string`, `any`>
+
+***
+
+### get()
+
+> **get**<`T`, `Name`>(`name`): `Name` *extends* `"openai"` ? `EmbeddingFunctionCreate`<[`OpenAIEmbeddingFunction`](OpenAIEmbeddingFunction.md)> : `undefined` \| `EmbeddingFunctionCreate`<`T`>
+
+Fetch an embedding function by name
+
+#### Type Parameters
+
+• **T** *extends* [`EmbeddingFunction`](EmbeddingFunction.md)<`unknown`, `FunctionOptions`>
+
+• **Name** *extends* `string` = `""`
+
+#### Parameters
+
+• **name**: `Name` *extends* `"openai"` ? `"openai"` : `string`
+
+The name of the function
+
+#### Returns
+
+`Name` *extends* `"openai"` ? `EmbeddingFunctionCreate`<[`OpenAIEmbeddingFunction`](OpenAIEmbeddingFunction.md)> : `undefined` \| `EmbeddingFunctionCreate`<`T`>
+
+***
+
+### getTableMetadata()
+
+> **getTableMetadata**(`functions`): `Map`<`string`, `string`>
+
+#### Parameters
+
+• **functions**: [`EmbeddingFunctionConfig`](../interfaces/EmbeddingFunctionConfig.md)[]
+
+#### Returns
+
+`Map`<`string`, `string`>
+
+***
+
+### register()
+
+> **register**<`T`>(`this`, `alias`?): (`ctor`) => `any`
+
+Register an embedding function
+
+#### Type Parameters
+
+• **T** *extends* `EmbeddingFunctionConstructor`<[`EmbeddingFunction`](EmbeddingFunction.md)<`any`, `FunctionOptions`>> = `EmbeddingFunctionConstructor`<[`EmbeddingFunction`](EmbeddingFunction.md)<`any`, `FunctionOptions`>>
+
+#### Parameters
+
+• **this**: [`EmbeddingFunctionRegistry`](EmbeddingFunctionRegistry.md)
+
+• **alias?**: `string`
+
+#### Returns
+
+`Function`
+
+##### Parameters
+
+• **ctor**: `T`
+
+##### Returns
+
+`any`
+
+#### Throws
+
+Error if the function is already registered
+
+***
+
+### reset()
+
+> **reset**(`this`): `void`
+
+reset the registry to the initial state
+
+#### Parameters
+
+• **this**: [`EmbeddingFunctionRegistry`](EmbeddingFunctionRegistry.md)
+
+#### Returns
+
+`void`

docs/src/js/namespaces/embedding/classes/OpenAIEmbeddingFunction.md

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+[**@lancedb/lancedb**](../../../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../../../globals.md) / [embedding](../README.md) / OpenAIEmbeddingFunction
+
+# Class: OpenAIEmbeddingFunction
+
+An embedding function that automatically creates vector representation for a given column.
+
+## Extends
+
+- [`EmbeddingFunction`](EmbeddingFunction.md)<`string`, `Partial`<[`OpenAIOptions`](../type-aliases/OpenAIOptions.md)>>
+
+## Constructors
+
+### new OpenAIEmbeddingFunction()
+
+> **new OpenAIEmbeddingFunction**(`options`): [`OpenAIEmbeddingFunction`](OpenAIEmbeddingFunction.md)
+
+#### Parameters
+
+• **options**: `Partial`<[`OpenAIOptions`](../type-aliases/OpenAIOptions.md)> = `...`
+
+#### Returns
+
+[`OpenAIEmbeddingFunction`](OpenAIEmbeddingFunction.md)
+
+#### Overrides
+
+[`EmbeddingFunction`](EmbeddingFunction.md).[`constructor`](EmbeddingFunction.md#constructors)
+
+## Methods
+
+### computeQueryEmbeddings()
+
+> **computeQueryEmbeddings**(`data`): `Promise`<`number`[]>
+
+Compute the embeddings for a single query
+
+#### Parameters
+
+• **data**: `string`
+
+#### Returns
+
+`Promise`<`number`[]>
+
+#### Overrides
+
+[`EmbeddingFunction`](EmbeddingFunction.md).[`computeQueryEmbeddings`](EmbeddingFunction.md#computequeryembeddings)
+
+***
+
+### computeSourceEmbeddings()
+
+> **computeSourceEmbeddings**(`data`): `Promise`<`number`[][]>
+
+Creates a vector representation for the given values.
+
+#### Parameters
+
+• **data**: `string`[]
+
+#### Returns
+
+`Promise`<`number`[][]>
+
+#### Overrides
+
+[`EmbeddingFunction`](EmbeddingFunction.md).[`computeSourceEmbeddings`](EmbeddingFunction.md#computesourceembeddings)
+
+***
+
+### embeddingDataType()
+
+> **embeddingDataType**(): `Float`<`Floats`>
+
+The datatype of the embeddings
+
+#### Returns
+
+`Float`<`Floats`>
+
+#### Overrides
+
+[`EmbeddingFunction`](EmbeddingFunction.md).[`embeddingDataType`](EmbeddingFunction.md#embeddingdatatype)
+
+***
+
+### ndims()
+
+> **ndims**(): `number`
+
+The number of dimensions of the embeddings
+
+#### Returns
+
+`number`
+
+#### Overrides
+
+[`EmbeddingFunction`](EmbeddingFunction.md).[`ndims`](EmbeddingFunction.md#ndims)
+
+***
+
+### sourceField()
+
+> **sourceField**(`optionsOrDatatype`): [`DataType`<`Type`, `any`>, `Map`<`string`, [`EmbeddingFunction`](EmbeddingFunction.md)<`any`, `FunctionOptions`>>]
+
+sourceField is used in combination with `LanceSchema` to provide a declarative data model
+
+#### Parameters
+
+• **optionsOrDatatype**: `DataType`<`Type`, `any`> \| `Partial`<`FieldOptions`<`DataType`<`Type`, `any`>>>
+
+The options for the field or the datatype
+
+#### Returns
+
+[`DataType`<`Type`, `any`>, `Map`<`string`, [`EmbeddingFunction`](EmbeddingFunction.md)<`any`, `FunctionOptions`>>]
+
+#### See
+
+lancedb.LanceSchema
+
+#### Inherited from
+
+[`EmbeddingFunction`](EmbeddingFunction.md).[`sourceField`](EmbeddingFunction.md#sourcefield)
+
+***
+
+### toJSON()
+
+> **toJSON**(): `object`
+
+Convert the embedding function to a JSON object
+It is used to serialize the embedding function to the schema
+It's important that any object returned by this method contains all the necessary
+information to recreate the embedding function
+
+It should return the same object that was passed to the constructor
+If it does not, the embedding function will not be able to be recreated, or could be recreated incorrectly
+
+#### Returns
+
+`object`
+
+##### model
+
+> **model**: `string` & `object` \| `"text-embedding-ada-002"` \| `"text-embedding-3-small"` \| `"text-embedding-3-large"`
+
+#### Example
+
+```ts
+class MyEmbeddingFunction extends EmbeddingFunction {
+  constructor(options: {model: string, timeout: number}) {
+    super();
+    this.model = options.model;
+    this.timeout = options.timeout;
+  }
+  toJSON() {
+    return {
+      model: this.model,
+      timeout: this.timeout,
+    };
+}
+```
+
+#### Overrides
+
+[`EmbeddingFunction`](EmbeddingFunction.md).[`toJSON`](EmbeddingFunction.md#tojson)
+
+***
+
+### vectorField()
+
+> **vectorField**(`optionsOrDatatype`?): [`DataType`<`Type`, `any`>, `Map`<`string`, [`EmbeddingFunction`](EmbeddingFunction.md)<`any`, `FunctionOptions`>>]
+
+vectorField is used in combination with `LanceSchema` to provide a declarative data model
+
+#### Parameters
+
+• **optionsOrDatatype?**: `DataType`<`Type`, `any`> \| `Partial`<`FieldOptions`<`DataType`<`Type`, `any`>>>
+
+#### Returns
+
+[`DataType`<`Type`, `any`>, `Map`<`string`, [`EmbeddingFunction`](EmbeddingFunction.md)<`any`, `FunctionOptions`>>]
+
+#### See
+
+lancedb.LanceSchema
+
+#### Inherited from
+
+[`EmbeddingFunction`](EmbeddingFunction.md).[`vectorField`](EmbeddingFunction.md#vectorfield)

docs/src/js/namespaces/embedding/functions/LanceSchema.md

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+[**@lancedb/lancedb**](../../../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../../../globals.md) / [embedding](../README.md) / LanceSchema
+
+# Function: LanceSchema()
+
+> **LanceSchema**(`fields`): `Schema`
+
+Create a schema with embedding functions.
+
+## Parameters
+
+• **fields**: `Record`<`string`, `object` \| [`object`, `Map`<`string`, [`EmbeddingFunction`](../classes/EmbeddingFunction.md)<`any`, `FunctionOptions`>>]>
+
+## Returns
+
+`Schema`
+
+Schema
+
+## Example
+
+```ts
+class MyEmbeddingFunction extends EmbeddingFunction {
+// ...
+}
+const func = new MyEmbeddingFunction();
+const schema = LanceSchema({
+  id: new Int32(),
+  text: func.sourceField(new Utf8()),
+  vector: func.vectorField(),
+  // optional: specify the datatype and/or dimensions
+  vector2: func.vectorField({ datatype: new Float32(), dims: 3}),
+});
+
+const table = await db.createTable("my_table", data, { schema });
+```

docs/src/js/namespaces/embedding/functions/getRegistry.md

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+[**@lancedb/lancedb**](../../../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../../../globals.md) / [embedding](../README.md) / getRegistry
+
+# Function: getRegistry()
+
+> **getRegistry**(): [`EmbeddingFunctionRegistry`](../classes/EmbeddingFunctionRegistry.md)
+
+Utility function to get the global instance of the registry
+
+## Returns
+
+[`EmbeddingFunctionRegistry`](../classes/EmbeddingFunctionRegistry.md)
+
+`EmbeddingFunctionRegistry` The global instance of the registry
+
+## Example
+
+```ts
+const registry = getRegistry();
+const openai = registry.get("openai").create();

docs/src/js/namespaces/embedding/functions/register.md

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+[**@lancedb/lancedb**](../../../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../../../globals.md) / [embedding](../README.md) / register
+
+# Function: register()
+
+> **register**(`name`?): (`ctor`) => `any`
+
+## Parameters
+
+• **name?**: `string`
+
+## Returns
+
+`Function`
+
+### Parameters
+
+• **ctor**: `EmbeddingFunctionConstructor`<[`EmbeddingFunction`](../classes/EmbeddingFunction.md)<`any`, `FunctionOptions`>>
+
+### Returns
+
+`any`

docs/src/js/namespaces/embedding/interfaces/EmbeddingFunctionConfig.md

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+[**@lancedb/lancedb**](../../../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../../../globals.md) / [embedding](../README.md) / EmbeddingFunctionConfig
+
+# Interface: EmbeddingFunctionConfig
+
+## Properties
+
+### function
+
+> **function**: [`EmbeddingFunction`](../classes/EmbeddingFunction.md)<`any`, `FunctionOptions`>
+
+***
+
+### sourceColumn
+
+> **sourceColumn**: `string`
+
+***
+
+### vectorColumn?
+
+> `optional` **vectorColumn**: `string`

docs/src/js/namespaces/embedding/type-aliases/OpenAIOptions.md

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+[**@lancedb/lancedb**](../../../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../../../globals.md) / [embedding](../README.md) / OpenAIOptions
+
+# Type Alias: OpenAIOptions
+
+> **OpenAIOptions**: `object`
+
+## Type declaration
+
+### apiKey
+
+> **apiKey**: `string`
+
+### model
+
+> **model**: `EmbeddingCreateParams`\[`"model"`\]