diff --git a/.eslintrc.json b/.eslintrc.json
index 56462e8..82c4175 100644
--- a/.eslintrc.json
+++ b/.eslintrc.json
@@ -1,3 +1,26 @@
 {
-    "extends": "../../.eslintrc"
+    "env": {
+        "node": true,
+        "es2021": true,
+        "mocha": true
+    },
+    "extends": [
+        "eslint:recommended",
+        "plugin:@typescript-eslint/recommended"
+    ],
+    "parser": "@typescript-eslint/parser",
+    "parserOptions": {
+        "ecmaVersion": "latest",
+        "sourceType": "module",
+        "project": ["./tsconfig.json", "./tsconfig.test.json"]
+    },
+    "plugins": [
+        "@typescript-eslint"
+    ],
+    "rules": {
+        "indent": ["error", 4],
+        "linebreak-style": ["error", "unix"],
+        "quotes": ["error", "double"],
+        "semi": ["error", "always"]
+    }
 }
diff --git a/.gitignore b/.gitignore
index 427cc78..2fa8709 100644
--- a/.gitignore
+++ b/.gitignore
@@ -108,3 +108,6 @@ dist
 
 # TernJS port file
 .tern-port
+
+# temp
+temp/
\ No newline at end of file
diff --git a/api-extractor.json b/api-extractor.json
index 0a7a404..36fc8b1 100644
--- a/api-extractor.json
+++ b/api-extractor.json
@@ -1,4 +1,41 @@
 {
-  "extends": "../../api-extractor.json",
-  "mainEntryPointFilePath": "./lib/index.d.ts"
+  "$schema": "https://developer.microsoft.com/json-schemas/api-extractor/v7/api-extractor.schema.json",
+  "mainEntryPointFilePath": "<projectFolder>/lib/index.d.ts",
+  "bundledPackages": [],
+  "compiler": {
+    "tsconfigFilePath": "<projectFolder>/tsconfig.json"
+  },
+  "dtsRollup": {
+    "enabled": true,
+    "untrimmedFilePath": "<projectFolder>/lib/index.d.ts"
+  },
+  "docModel": {
+    "enabled": true,
+    "apiJsonFilePath": "<projectFolder>/lib/api.json"
+  },
+  "tsdocMetadata": {
+    "enabled": true,
+    "tsdocMetadataFilePath": "<projectFolder>/lib/tsdoc-metadata.json"
+  },
+  "apiReport": {
+    "enabled": true,
+    "reportFolder": "<projectFolder>/lib/api-report"
+  },
+  "messages": {
+    "compilerMessageReporting": {
+      "default": {
+        "logLevel": "warning"
+      }
+    },
+    "extractorMessageReporting": {
+      "default": {
+        "logLevel": "warning"
+      }
+    },
+    "tsdocMessageReporting": {
+      "default": {
+        "logLevel": "warning"
+      }
+    }
+  }
 }
\ No newline at end of file
diff --git a/docs/.nojekyll b/docs/.nojekyll
new file mode 100644
index 0000000..e2ac661
--- /dev/null
+++ b/docs/.nojekyll
@@ -0,0 +1 @@
+TypeDoc added this file to prevent GitHub Pages from using Jekyll. You can turn off this behavior by setting the `githubPages` option to false.
\ No newline at end of file
diff --git a/docs/README.md b/docs/README.md
new file mode 100644
index 0000000..45a134f
--- /dev/null
+++ b/docs/README.md
@@ -0,0 +1,102 @@
+Vectra / [Exports](modules.md)
+
+# Vectra
+
+Vectra is a local vector database for Node.js with features similar to [Pinecone](https://www.pinecone.io/) or [Qdrant](https://qdrant.tech/) but built using local files. Each Vectra index is a folder on disk. There's an `index.json` file in the folder that contains all the vectors for the index along with any indexed metadata. When you create an index you can specify which metadata properties to index and only those fields will be stored in the `index.json` file. All of the other metadata for an item will be stored on disk in a separate file keyed by a GUID.
+
+When queryng Vectra you'll be able to use the same subset of [Mongo DB query operators](https://www.mongodb.com/docs/manual/reference/operator/query/) that Pinecone supports and the results will be returned sorted by simularity. Every item in the index will first be filtered by metadata and then ranked for simularity. Even though every item is evaluated its all in memory so it should by nearly instantanious. Likely 1ms - 2ms for even a rather large index. Smaller indexes should be <1ms.
+
+Keep in mind that your entire Vectra index is loaded into memory so it's not well suited for scenarios like long term chat bot memory. Use a real vector DB for that. Vectra is intended to be used in scenarios where you have a small corpus of mostly static data that you'd like to include in your prompt. Infinite few shot examples would be a great use case for Vectra or even just a single document you want to ask questions over.
+
+Pinecone style namespaces aren't directly supported but you could easily mimic them by creating a separate Vectra index (and folder) for each namespace.
+
+## Other Language Bindings
+
+This repo contains the TypeScript/JavaScript binding for Vectra but other language bindings are being created. Since Vectra is file based, any language binding can be used to read or write a Vectra index. That means you can build a Vectra index using JS and then read it using Python.
+
+-   [vectra-py](https://github.com/BMS-geodev/vectra-py) - Python version of Vectra.
+
+## Installation
+
+```
+$ npm install vectra
+```
+
+## Usage
+
+First create an instance of `LocalIndex` with the path to the folder where you want you're items stored:
+
+```typescript
+import { LocalIndex } from 'vectra';
+
+const index = new LocalIndex(path.join(__dirname, '..', 'index'));
+```
+
+Next, from inside an async function, create your index:
+
+```typescript
+if (!(await index.isIndexCreated())) {
+    await index.createIndex();
+}
+```
+
+Add some items to your index:
+
+```typescript
+import { OpenAI } from 'openai';
+
+const openai = new OpenAI({
+    apiKey: `<YOUR_KEY>`,
+});
+
+async function getVector(text: string) {
+    const response = await openai.embeddings.create({
+        'model': 'text-embedding-ada-002',
+        'input': text,
+    });
+    return response.data[0].embedding;
+}
+
+async function addItem(text: string) {
+    await index.insertItem({
+        vector: await getVector(text),
+        metadata: { text },
+    });
+}
+
+// Add items
+await addItem('apple');
+await addItem('oranges');
+await addItem('red');
+await addItem('blue');
+```
+
+Then query for items:
+
+```typescript
+async function query(text: string) {
+    const vector = await getVector(text);
+    const results = await index.queryItems(vector, 3);
+    if (results.length > 0) {
+        for (const result of results) {
+            console.log(`[${result.score}] ${result.item.metadata.text}`);
+        }
+    } else {
+        console.log(`No results found.`);
+    }
+}
+
+await query('green');
+/*
+[0.9036569942401076] blue
+[0.8758153664568566] red
+[0.8323828606103998] apple
+*/
+
+await query('banana');
+/*
+[0.9033128691220631] apple
+[0.8493374123092652] oranges
+[0.8415324469533297] blue
+*/
+```
diff --git a/docs/classes/FileFetcher.md b/docs/classes/FileFetcher.md
new file mode 100644
index 0000000..585e847
--- /dev/null
+++ b/docs/classes/FileFetcher.md
@@ -0,0 +1,50 @@
+[Vectra](../README.md) / [Exports](../modules.md) / FileFetcher
+
+# Class: FileFetcher
+
+Fetches text content from local files.
+
+## Implements
+
+- [`TextFetcher`](../interfaces/TextFetcher.md)
+
+## Table of contents
+
+### Constructors
+
+- [constructor](FileFetcher.md#constructor)
+
+### Methods
+
+- [fetch](FileFetcher.md#fetch)
+
+## Constructors
+
+### constructor
+
+• **new FileFetcher**()
+
+## Methods
+
+### fetch
+
+▸ **fetch**(`uri`, `onDocument`): `Promise`\<`boolean`\>
+
+#### Parameters
+
+| Name | Type |
+| :------ | :------ |
+| `uri` | `string` |
+| `onDocument` | (`uri`: `string`, `text`: `string`, `docType?`: `string`) => `Promise`\<`boolean`\> |
+
+#### Returns
+
+`Promise`\<`boolean`\>
+
+#### Implementation of
+
+[TextFetcher](../interfaces/TextFetcher.md).[fetch](../interfaces/TextFetcher.md#fetch)
+
+#### Defined in
+
+[FileFetcher.ts:10](https://github.com/bartonmalow/vectra/blob/418123d/src/FileFetcher.ts#L10)
diff --git a/docs/classes/GPT3Tokenizer.md b/docs/classes/GPT3Tokenizer.md
new file mode 100644
index 0000000..ad18467
--- /dev/null
+++ b/docs/classes/GPT3Tokenizer.md
@@ -0,0 +1,74 @@
+[Vectra](../README.md) / [Exports](../modules.md) / GPT3Tokenizer
+
+# Class: GPT3Tokenizer
+
+Tokenizer that uses the GPT-3 tokenizer.
+
+## Implements
+
+- [`Tokenizer`](../interfaces/Tokenizer.md)
+
+## Table of contents
+
+### Constructors
+
+- [constructor](GPT3Tokenizer.md#constructor)
+
+### Methods
+
+- [decode](GPT3Tokenizer.md#decode)
+- [encode](GPT3Tokenizer.md#encode)
+
+## Constructors
+
+### constructor
+
+• **new GPT3Tokenizer**()
+
+## Methods
+
+### decode
+
+▸ **decode**(`tokens`): `string`
+
+#### Parameters
+
+| Name | Type |
+| :------ | :------ |
+| `tokens` | `number`[] |
+
+#### Returns
+
+`string`
+
+#### Implementation of
+
+[Tokenizer](../interfaces/Tokenizer.md).[decode](../interfaces/Tokenizer.md#decode)
+
+#### Defined in
+
+[GPT3Tokenizer.ts:9](https://github.com/bartonmalow/vectra/blob/418123d/src/GPT3Tokenizer.ts#L9)
+
+___
+
+### encode
+
+▸ **encode**(`text`): `number`[]
+
+#### Parameters
+
+| Name | Type |
+| :------ | :------ |
+| `text` | `string` |
+
+#### Returns
+
+`number`[]
+
+#### Implementation of
+
+[Tokenizer](../interfaces/Tokenizer.md).[encode](../interfaces/Tokenizer.md#encode)
+
+#### Defined in
+
+[GPT3Tokenizer.ts:13](https://github.com/bartonmalow/vectra/blob/418123d/src/GPT3Tokenizer.ts#L13)
diff --git a/docs/classes/ItemSelector.md b/docs/classes/ItemSelector.md
new file mode 100644
index 0000000..61b183f
--- /dev/null
+++ b/docs/classes/ItemSelector.md
@@ -0,0 +1,130 @@
+[Vectra](../README.md) / [Exports](../modules.md) / ItemSelector
+
+# Class: ItemSelector
+
+Utility class for selecting and comparing items.
+
+## Table of contents
+
+### Constructors
+
+- [constructor](ItemSelector.md#constructor)
+
+### Methods
+
+- [cosineSimilarity](ItemSelector.md#cosinesimilarity)
+- [normalize](ItemSelector.md#normalize)
+- [normalizedCosineSimilarity](ItemSelector.md#normalizedcosinesimilarity)
+- [select](ItemSelector.md#select)
+
+## Constructors
+
+### constructor
+
+• **new ItemSelector**()
+
+## Methods
+
+### cosineSimilarity
+
+▸ `Static` **cosineSimilarity**(`vector1`, `vector2`): `number`
+
+Returns the similarity between two vectors using the cosine similarity.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `vector1` | `number`[] | Vector 1 |
+| `vector2` | `number`[] | Vector 2 |
+
+#### Returns
+
+`number`
+
+Similarity between the two vectors
+
+#### Defined in
+
+[ItemSelector.ts:15](https://github.com/bartonmalow/vectra/blob/418123d/src/ItemSelector.ts#L15)
+
+___
+
+### normalize
+
+▸ `Static` **normalize**(`vector`): `number`
+
+Normalizes a vector.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `vector` | `number`[] | Vector to normalize |
+
+#### Returns
+
+`number`
+
+Normalized vector
+
+**`Remarks`**
+
+The norm of a vector is the square root of the sum of the squares of the elements.
+The LocalIndex pre-normalizes all vectors to improve performance.
+
+#### Defined in
+
+[ItemSelector.ts:29](https://github.com/bartonmalow/vectra/blob/418123d/src/ItemSelector.ts#L29)
+
+___
+
+### normalizedCosineSimilarity
+
+▸ `Static` **normalizedCosineSimilarity**(`vector1`, `vector2`, `norm1`, `norm2`): `number`
+
+Returns the similarity between two vectors using cosine similarity.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `vector1` | `number`[] | Vector 1 |
+| `vector2` | `number`[] | Vector 2 |
+| `norm1` | `number` | Norm of vector 1 |
+| `norm2` | `number` | Norm of vector 2 |
+
+#### Returns
+
+`number`
+
+Similarity between the two vectors
+
+#### Defined in
+
+[ItemSelector.ts:50](https://github.com/bartonmalow/vectra/blob/418123d/src/ItemSelector.ts#L50)
+
+___
+
+### select
+
+▸ `Static` **select**(`metadata`, `filter`): `boolean`
+
+Returns true if the metadata matches the filter.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `metadata` | `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> | Metadata to check |
+| `filter` | [`MetadataFilter`](../interfaces/MetadataFilter.md) | Filter to apply |
+
+#### Returns
+
+`boolean`
+
+True if the metadata matches the filter
+
+#### Defined in
+
+[ItemSelector.ts:62](https://github.com/bartonmalow/vectra/blob/418123d/src/ItemSelector.ts#L62)
diff --git a/docs/classes/LocalDocument.md b/docs/classes/LocalDocument.md
new file mode 100644
index 0000000..4b33f3e
--- /dev/null
+++ b/docs/classes/LocalDocument.md
@@ -0,0 +1,174 @@
+[Vectra](../README.md) / [Exports](../modules.md) / LocalDocument
+
+# Class: LocalDocument
+
+Represents a document stored in a local index.
+
+## Hierarchy
+
+- **`LocalDocument`**
+
+  ↳ [`LocalDocumentResult`](LocalDocumentResult.md)
+
+## Table of contents
+
+### Constructors
+
+- [constructor](LocalDocument.md#constructor)
+
+### Accessors
+
+- [folderPath](LocalDocument.md#folderpath)
+- [id](LocalDocument.md#id)
+- [uri](LocalDocument.md#uri)
+
+### Methods
+
+- [getLength](LocalDocument.md#getlength)
+- [hasMetadata](LocalDocument.md#hasmetadata)
+- [loadMetadata](LocalDocument.md#loadmetadata)
+- [loadText](LocalDocument.md#loadtext)
+
+## Constructors
+
+### constructor
+
+• **new LocalDocument**(`index`, `documentId`, `uri`)
+
+Creates a new instance of LocalDocument.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `index` | [`LocalDocumentIndex`](LocalDocumentIndex.md) | The document index this document belongs to. |
+| `documentId` | `string` | The ID of the document. |
+| `uri` | `string` | The URI of the document. |
+
+#### Defined in
+
+[LocalDocument.ts:23](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L23)
+
+## Accessors
+
+### folderPath
+
+• `get` **folderPath**(): `string`
+
+Returns the folder path where the document is stored.
+
+#### Returns
+
+`string`
+
+#### Defined in
+
+[LocalDocument.ts:32](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L32)
+
+___
+
+### id
+
+• `get` **id**(): `string`
+
+Returns the ID of the document.
+
+#### Returns
+
+`string`
+
+#### Defined in
+
+[LocalDocument.ts:39](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L39)
+
+___
+
+### uri
+
+• `get` **uri**(): `string`
+
+Returns the URI of the document.
+
+#### Returns
+
+`string`
+
+#### Defined in
+
+[LocalDocument.ts:46](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L46)
+
+## Methods
+
+### getLength
+
+▸ **getLength**(): `Promise`\<`number`\>
+
+Returns the length of the document in tokens.
+
+#### Returns
+
+`Promise`\<`number`\>
+
+Length of the document in tokens.
+
+**`Remarks`**
+
+This value will be estimated for documents longer then 40k bytes.
+
+#### Defined in
+
+[LocalDocument.ts:56](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L56)
+
+___
+
+### hasMetadata
+
+▸ **hasMetadata**(): `Promise`\<`boolean`\>
+
+Determines if the document has additional metadata storred on disk.
+
+#### Returns
+
+`Promise`\<`boolean`\>
+
+True if the document has metadata; otherwise, false.
+
+#### Defined in
+
+[LocalDocument.ts:69](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L69)
+
+___
+
+### loadMetadata
+
+▸ **loadMetadata**(): `Promise`\<`Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\>\>
+
+Loads the metadata for the document from disk.
+
+#### Returns
+
+`Promise`\<`Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\>\>
+
+Metadata for the document.
+
+#### Defined in
+
+[LocalDocument.ts:82](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L82)
+
+___
+
+### loadText
+
+▸ **loadText**(): `Promise`\<`string`\>
+
+Loads the text for the document from disk.
+
+#### Returns
+
+`Promise`\<`string`\>
+
+Text for the document.
+
+#### Defined in
+
+[LocalDocument.ts:105](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L105)
diff --git a/docs/classes/LocalDocumentIndex.md b/docs/classes/LocalDocumentIndex.md
new file mode 100644
index 0000000..55352e2
--- /dev/null
+++ b/docs/classes/LocalDocumentIndex.md
@@ -0,0 +1,764 @@
+[Vectra](../README.md) / [Exports](../modules.md) / LocalDocumentIndex
+
+# Class: LocalDocumentIndex
+
+Represents a local index of documents stored on disk.
+
+## Hierarchy
+
+- [`LocalIndex`](LocalIndex.md)\<[`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md)\>
+
+  ↳ **`LocalDocumentIndex`**
+
+## Table of contents
+
+### Constructors
+
+- [constructor](LocalDocumentIndex.md#constructor)
+
+### Accessors
+
+- [embeddings](LocalDocumentIndex.md#embeddings)
+- [folderPath](LocalDocumentIndex.md#folderpath)
+- [indexName](LocalDocumentIndex.md#indexname)
+- [tokenizer](LocalDocumentIndex.md#tokenizer)
+
+### Methods
+
+- [beginUpdate](LocalDocumentIndex.md#beginupdate)
+- [cancelUpdate](LocalDocumentIndex.md#cancelupdate)
+- [createIndex](LocalDocumentIndex.md#createindex)
+- [deleteDocument](LocalDocumentIndex.md#deletedocument)
+- [deleteIndex](LocalDocumentIndex.md#deleteindex)
+- [deleteItem](LocalDocumentIndex.md#deleteitem)
+- [endUpdate](LocalDocumentIndex.md#endupdate)
+- [getCatalogStats](LocalDocumentIndex.md#getcatalogstats)
+- [getDocumentId](LocalDocumentIndex.md#getdocumentid)
+- [getDocumentUri](LocalDocumentIndex.md#getdocumenturi)
+- [getIndexStats](LocalDocumentIndex.md#getindexstats)
+- [getItem](LocalDocumentIndex.md#getitem)
+- [insertItem](LocalDocumentIndex.md#insertitem)
+- [isCatalogCreated](LocalDocumentIndex.md#iscatalogcreated)
+- [isIndexCreated](LocalDocumentIndex.md#isindexcreated)
+- [listDocuments](LocalDocumentIndex.md#listdocuments)
+- [listItems](LocalDocumentIndex.md#listitems)
+- [listItemsByMetadata](LocalDocumentIndex.md#listitemsbymetadata)
+- [loadIndexData](LocalDocumentIndex.md#loadindexdata)
+- [queryDocuments](LocalDocumentIndex.md#querydocuments)
+- [queryItems](LocalDocumentIndex.md#queryitems)
+- [upsertDocument](LocalDocumentIndex.md#upsertdocument)
+- [upsertItem](LocalDocumentIndex.md#upsertitem)
+
+## Constructors
+
+### constructor
+
+• **new LocalDocumentIndex**(`config`)
+
+Creates a new instance of LocalDocumentIndex.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `config` | [`LocalDocumentIndexConfig`](../interfaces/LocalDocumentIndexConfig.md) | Configuration settings for the document index. |
+
+#### Overrides
+
+[LocalIndex](LocalIndex.md).[constructor](LocalIndex.md#constructor)
+
+#### Defined in
+
+[LocalDocumentIndex.ts:83](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L83)
+
+## Accessors
+
+### embeddings
+
+• `get` **embeddings**(): [`EmbeddingsModel`](../interfaces/EmbeddingsModel.md)
+
+Gets the embeddings model.
+
+#### Returns
+
+[`EmbeddingsModel`](../interfaces/EmbeddingsModel.md)
+
+The embeddings model
+
+#### Defined in
+
+[LocalDocumentIndex.ts:100](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L100)
+
+___
+
+### folderPath
+
+• `get` **folderPath**(): `string`
+
+Path to the index folder.
+
+#### Returns
+
+`string`
+
+#### Inherited from
+
+LocalIndex.folderPath
+
+#### Defined in
+
+[LocalIndex.ts:70](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L70)
+
+___
+
+### indexName
+
+• `get` **indexName**(): `string`
+
+Optional name of the index file.
+
+#### Returns
+
+`string`
+
+#### Inherited from
+
+LocalIndex.indexName
+
+#### Defined in
+
+[LocalIndex.ts:77](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L77)
+
+___
+
+### tokenizer
+
+• `get` **tokenizer**(): [`Tokenizer`](../interfaces/Tokenizer.md)
+
+Gets the tokenizer.
+
+#### Returns
+
+[`Tokenizer`](../interfaces/Tokenizer.md)
+
+The tokenizer
+
+#### Defined in
+
+[LocalDocumentIndex.ts:109](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L109)
+
+## Methods
+
+### beginUpdate
+
+▸ **beginUpdate**(): `Promise`\<`void`\>
+
+Begins an update to the index.
+
+#### Returns
+
+`Promise`\<`void`\>
+
+**`Remarks`**
+
+This method loads the index into memory and prepares it for updates.
+
+#### Overrides
+
+[LocalIndex](LocalIndex.md).[beginUpdate](LocalIndex.md#beginupdate)
+
+#### Defined in
+
+[LocalDocumentIndex.ts:418](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L418)
+
+___
+
+### cancelUpdate
+
+▸ **cancelUpdate**(): `void`
+
+Cancels an update to the index.
+
+#### Returns
+
+`void`
+
+**`Remarks`**
+
+This method discards any changes made to the index since the update began.
+
+#### Overrides
+
+[LocalIndex](LocalIndex.md).[cancelUpdate](LocalIndex.md#cancelupdate)
+
+#### Defined in
+
+[LocalDocumentIndex.ts:423](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L423)
+
+___
+
+### createIndex
+
+▸ **createIndex**(`config?`): `Promise`\<`void`\>
+
+Creates a new index.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `config?` | [`CreateIndexConfig`](../interfaces/CreateIndexConfig.md) | Index configuration. |
+
+#### Returns
+
+`Promise`\<`void`\>
+
+**`Remarks`**
+
+This method creates a new folder on disk containing an index.json file.
+
+#### Overrides
+
+[LocalIndex](LocalIndex.md).[createIndex](LocalIndex.md#createindex)
+
+#### Defined in
+
+[LocalDocumentIndex.ts:428](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L428)
+
+___
+
+### deleteDocument
+
+▸ **deleteDocument**(`uri`): `Promise`\<`void`\>
+
+Deletes a document from the index.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `uri` | `string` | URI of the document to delete. |
+
+#### Returns
+
+`Promise`\<`void`\>
+
+#### Defined in
+
+[LocalDocumentIndex.ts:168](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L168)
+
+___
+
+### deleteIndex
+
+▸ **deleteIndex**(): `Promise`\<`void`\>
+
+Deletes the index.
+
+#### Returns
+
+`Promise`\<`void`\>
+
+**`Remarks`**
+
+This method deletes the index folder from disk.
+
+#### Inherited from
+
+[LocalIndex](LocalIndex.md).[deleteIndex](LocalIndex.md#deleteindex)
+
+#### Defined in
+
+[LocalIndex.ts:143](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L143)
+
+___
+
+### deleteItem
+
+▸ **deleteItem**(`id`): `Promise`\<`void`\>
+
+Deletes an item from the index.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `id` | `string` | ID of item to delete. |
+
+#### Returns
+
+`Promise`\<`void`\>
+
+#### Inherited from
+
+[LocalIndex](LocalIndex.md).[deleteItem](LocalIndex.md#deleteitem)
+
+#### Defined in
+
+[LocalIndex.ts:155](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L155)
+
+___
+
+### endUpdate
+
+▸ **endUpdate**(): `Promise`\<`void`\>
+
+Ends an update to the index.
+
+#### Returns
+
+`Promise`\<`void`\>
+
+**`Remarks`**
+
+This method saves the index to disk.
+
+#### Overrides
+
+[LocalIndex](LocalIndex.md).[endUpdate](LocalIndex.md#endupdate)
+
+#### Defined in
+
+[LocalDocumentIndex.ts:433](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L433)
+
+___
+
+### getCatalogStats
+
+▸ **getCatalogStats**(): `Promise`\<[`DocumentCatalogStats`](../interfaces/DocumentCatalogStats.md)\>
+
+Gets the catalog statistics.
+
+#### Returns
+
+`Promise`\<[`DocumentCatalogStats`](../interfaces/DocumentCatalogStats.md)\>
+
+The catalog statistics
+
+#### Defined in
+
+[LocalDocumentIndex.ts:154](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L154)
+
+___
+
+### getDocumentId
+
+▸ **getDocumentId**(`uri`): `Promise`\<`string`\>
+
+Gets the document ID for a URI.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `uri` | `string` | The URI to get the document ID for |
+
+#### Returns
+
+`Promise`\<`string`\>
+
+The document ID, or undefined if not found
+
+#### Defined in
+
+[LocalDocumentIndex.ts:133](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L133)
+
+___
+
+### getDocumentUri
+
+▸ **getDocumentUri**(`documentId`): `Promise`\<`string`\>
+
+Gets the document URI for a document ID.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `documentId` | `string` | The document ID to get the URI for |
+
+#### Returns
+
+`Promise`\<`string`\>
+
+The document URI, or undefined if not found
+
+#### Defined in
+
+[LocalDocumentIndex.ts:144](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L144)
+
+___
+
+### getIndexStats
+
+▸ **getIndexStats**(): `Promise`\<[`IndexStats`](../interfaces/IndexStats.md)\>
+
+Loads an index from disk and returns its stats.
+
+#### Returns
+
+`Promise`\<[`IndexStats`](../interfaces/IndexStats.md)\>
+
+Index stats.
+
+#### Inherited from
+
+[LocalIndex](LocalIndex.md).[getIndexStats](LocalIndex.md#getindexstats)
+
+#### Defined in
+
+[LocalIndex.ts:195](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L195)
+
+___
+
+### getItem
+
+▸ **getItem**\<`TItemMetadata`\>(`id`): `Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Returns an item from the index given its ID.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) = [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `id` | `string` | ID of the item to retrieve. |
+
+#### Returns
+
+`Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Item or undefined if not found.
+
+#### Inherited from
+
+[LocalIndex](LocalIndex.md).[getItem](LocalIndex.md#getitem)
+
+#### Defined in
+
+[LocalIndex.ts:209](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L209)
+
+___
+
+### insertItem
+
+▸ **insertItem**\<`TItemMetadata`\>(`item`): `Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Adds an item to the index.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) = [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `item` | `Partial`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\> | Item to insert. |
+
+#### Returns
+
+`Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Inserted item.
+
+**`Remarks`**
+
+A new update is started if one is not already in progress. If an item with the same ID
+already exists, an error will be thrown.
+
+#### Inherited from
+
+[LocalIndex](LocalIndex.md).[insertItem](LocalIndex.md#insertitem)
+
+#### Defined in
+
+[LocalIndex.ts:223](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L223)
+
+___
+
+### isCatalogCreated
+
+▸ **isCatalogCreated**(): `Promise`\<`boolean`\>
+
+Checks if the document catalog exists.
+
+#### Returns
+
+`Promise`\<`boolean`\>
+
+True if the catalog exists, false otherwise
+
+#### Defined in
+
+[LocalDocumentIndex.ts:118](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L118)
+
+___
+
+### isIndexCreated
+
+▸ **isIndexCreated**(): `Promise`\<`boolean`\>
+
+Returns true if the index exists.
+
+#### Returns
+
+`Promise`\<`boolean`\>
+
+#### Inherited from
+
+[LocalIndex](LocalIndex.md).[isIndexCreated](LocalIndex.md#isindexcreated)
+
+#### Defined in
+
+[LocalIndex.ts:238](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L238)
+
+___
+
+### listDocuments
+
+▸ **listDocuments**(): `Promise`\<[`LocalDocumentResult`](LocalDocumentResult.md)[]\>
+
+Lists all documents in the index.
+
+#### Returns
+
+`Promise`\<[`LocalDocumentResult`](LocalDocumentResult.md)[]\>
+
+Array of document results
+
+#### Defined in
+
+[LocalDocumentIndex.ts:341](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L341)
+
+___
+
+### listItems
+
+▸ **listItems**\<`TItemMetadata`\>(): `Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>[]\>
+
+Returns all items in the index.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) = [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) |
+
+#### Returns
+
+`Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>[]\>
+
+Array of all items in the index.
+
+**`Remarks`**
+
+This method loads the index into memory and returns all its items. A copy of the items
+array is returned so no modifications should be made to the array.
+
+#### Inherited from
+
+[LocalIndex](LocalIndex.md).[listItems](LocalIndex.md#listitems)
+
+#### Defined in
+
+[LocalIndex.ts:254](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L254)
+
+___
+
+### listItemsByMetadata
+
+▸ **listItemsByMetadata**\<`TItemMetadata`\>(`filter`): `Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>[]\>
+
+Returns all items in the index matching the filter.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) = [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `filter` | [`MetadataFilter`](../interfaces/MetadataFilter.md) | Filter to apply. |
+
+#### Returns
+
+`Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>[]\>
+
+Array of items matching the filter.
+
+**`Remarks`**
+
+This method loads the index into memory and returns all its items matching the filter.
+
+#### Inherited from
+
+[LocalIndex](LocalIndex.md).[listItemsByMetadata](LocalIndex.md#listitemsbymetadata)
+
+#### Defined in
+
+[LocalIndex.ts:266](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L266)
+
+___
+
+### loadIndexData
+
+▸ `Protected` **loadIndexData**(): `Promise`\<`void`\>
+
+Ensures that the index has been loaded into memory.
+
+#### Returns
+
+`Promise`\<`void`\>
+
+#### Overrides
+
+[LocalIndex](LocalIndex.md).[loadIndexData](LocalIndex.md#loadindexdata)
+
+#### Defined in
+
+[LocalDocumentIndex.ts:446](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L446)
+
+___
+
+### queryDocuments
+
+▸ **queryDocuments**(`query`, `options?`): `Promise`\<[`LocalDocumentResult`](LocalDocumentResult.md)[]\>
+
+Queries the index for documents similar to the given query.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `query` | `string` | Text to query for |
+| `options?` | [`DocumentQueryOptions`](../interfaces/DocumentQueryOptions.md) | Optional. Query options |
+
+#### Returns
+
+`Promise`\<[`LocalDocumentResult`](LocalDocumentResult.md)[]\>
+
+Array of document results
+
+#### Defined in
+
+[LocalDocumentIndex.ts:371](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L371)
+
+___
+
+### queryItems
+
+▸ **queryItems**\<`TItemMetadata`\>(`vector`, `query`, `topK`, `filter?`, `isBm25?`): `Promise`\<[`QueryResult`](../interfaces/QueryResult.md)\<`TItemMetadata`\>[]\>
+
+Finds the top k items in the index that are most similar to the vector.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) = [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `vector` | `number`[] | Vector to query against. |
+| `query` | `string` | Query text for BM25 search. |
+| `topK` | `number` | Number of items to return. |
+| `filter?` | [`MetadataFilter`](../interfaces/MetadataFilter.md) | Optional. Filter to apply. |
+| `isBm25?` | `boolean` | Optional. Whether to use BM25 search. |
+
+#### Returns
+
+`Promise`\<[`QueryResult`](../interfaces/QueryResult.md)\<`TItemMetadata`\>[]\>
+
+Similar items to the vector that match the supplied filter.
+
+**`Remarks`**
+
+This method loads the index into memory and returns the top k items that are most similar.
+An optional filter can be applied to the metadata of the items.
+
+#### Inherited from
+
+[LocalIndex](LocalIndex.md).[queryItems](LocalIndex.md#queryitems)
+
+#### Defined in
+
+[LocalIndex.ts:285](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L285)
+
+___
+
+### upsertDocument
+
+▸ **upsertDocument**(`uri`, `text`, `docType?`, `metadata?`): `Promise`\<[`LocalDocument`](LocalDocument.md)\>
+
+Upserts a document into the index.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `uri` | `string` | URI of the document |
+| `text` | `string` | Text of the document |
+| `docType?` | `string` | Optional. Type of the document |
+| `metadata?` | `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> | Optional. Metadata for the document |
+
+#### Returns
+
+`Promise`\<[`LocalDocument`](LocalDocument.md)\>
+
+The upserted document
+
+#### Defined in
+
+[LocalDocumentIndex.ts:223](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L223)
+
+___
+
+### upsertItem
+
+▸ **upsertItem**\<`TItemMetadata`\>(`item`): `Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Adds or replaces an item in the index.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) = [`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md) |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `item` | `Partial`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\> | Item to insert or replace. |
+
+#### Returns
+
+`Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Upserted item.
+
+**`Remarks`**
+
+A new update is started if one is not already in progress. If an item with the same ID
+already exists, it will be replaced.
+
+#### Inherited from
+
+[LocalIndex](LocalIndex.md).[upsertItem](LocalIndex.md#upsertitem)
+
+#### Defined in
+
+[LocalIndex.ts:328](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L328)
diff --git a/docs/classes/LocalDocumentResult.md b/docs/classes/LocalDocumentResult.md
new file mode 100644
index 0000000..6d5ada7
--- /dev/null
+++ b/docs/classes/LocalDocumentResult.md
@@ -0,0 +1,316 @@
+[Vectra](../README.md) / [Exports](../modules.md) / LocalDocumentResult
+
+# Class: LocalDocumentResult
+
+Represents the result of a document query.
+
+## Hierarchy
+
+- [`LocalDocument`](LocalDocument.md)
+
+  ↳ **`LocalDocumentResult`**
+
+## Table of contents
+
+### Constructors
+
+- [constructor](LocalDocumentResult.md#constructor)
+
+### Accessors
+
+- [chunks](LocalDocumentResult.md#chunks)
+- [folderPath](LocalDocumentResult.md#folderpath)
+- [id](LocalDocumentResult.md#id)
+- [score](LocalDocumentResult.md#score)
+- [uri](LocalDocumentResult.md#uri)
+
+### Methods
+
+- [getLength](LocalDocumentResult.md#getlength)
+- [getSections](LocalDocumentResult.md#getsections)
+- [getText](LocalDocumentResult.md#gettext)
+- [hasMetadata](LocalDocumentResult.md#hasmetadata)
+- [loadMetadata](LocalDocumentResult.md#loadmetadata)
+- [loadText](LocalDocumentResult.md#loadtext)
+- [renderAllSections](LocalDocumentResult.md#renderallsections)
+
+## Constructors
+
+### constructor
+
+• **new LocalDocumentResult**(`index`, `documentId`, `uri`, `chunks`, `tokenizer`)
+
+Creates a new instance of LocalDocumentResult.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `index` | [`LocalDocumentIndex`](LocalDocumentIndex.md) | The document index this result belongs to. |
+| `documentId` | `string` | The ID of the document. |
+| `uri` | `string` | The URI of the document. |
+| `chunks` | [`QueryResult`](../interfaces/QueryResult.md)\<[`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md)\>[] | The chunks that matched the query. |
+| `tokenizer` | [`Tokenizer`](../interfaces/Tokenizer.md) | The tokenizer to use for text processing. |
+
+#### Overrides
+
+[LocalDocument](LocalDocument.md).[constructor](LocalDocument.md#constructor)
+
+#### Defined in
+
+[LocalDocumentResult.ts:22](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentResult.ts#L22)
+
+## Accessors
+
+### chunks
+
+• `get` **chunks**(): [`QueryResult`](../interfaces/QueryResult.md)\<[`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md)\>[]
+
+Returns the chunks of the document that matched the query.
+
+#### Returns
+
+[`QueryResult`](../interfaces/QueryResult.md)\<[`DocumentChunkMetadata`](../interfaces/DocumentChunkMetadata.md)\>[]
+
+#### Defined in
+
+[LocalDocumentResult.ts:36](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentResult.ts#L36)
+
+___
+
+### folderPath
+
+• `get` **folderPath**(): `string`
+
+Returns the folder path where the document is stored.
+
+#### Returns
+
+`string`
+
+#### Inherited from
+
+LocalDocument.folderPath
+
+#### Defined in
+
+[LocalDocument.ts:32](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L32)
+
+___
+
+### id
+
+• `get` **id**(): `string`
+
+Returns the ID of the document.
+
+#### Returns
+
+`string`
+
+#### Inherited from
+
+LocalDocument.id
+
+#### Defined in
+
+[LocalDocument.ts:39](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L39)
+
+___
+
+### score
+
+• `get` **score**(): `number`
+
+Returns the average score of the document result.
+
+#### Returns
+
+`number`
+
+#### Defined in
+
+[LocalDocumentResult.ts:43](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentResult.ts#L43)
+
+___
+
+### uri
+
+• `get` **uri**(): `string`
+
+Returns the URI of the document.
+
+#### Returns
+
+`string`
+
+#### Inherited from
+
+LocalDocument.uri
+
+#### Defined in
+
+[LocalDocument.ts:46](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L46)
+
+## Methods
+
+### getLength
+
+▸ **getLength**(): `Promise`\<`number`\>
+
+Returns the length of the document in tokens.
+
+#### Returns
+
+`Promise`\<`number`\>
+
+Length of the document in tokens.
+
+**`Remarks`**
+
+This value will be estimated for documents longer then 40k bytes.
+
+#### Inherited from
+
+[LocalDocument](LocalDocument.md).[getLength](LocalDocument.md#getlength)
+
+#### Defined in
+
+[LocalDocument.ts:56](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L56)
+
+___
+
+### getSections
+
+▸ **getSections**(`maxTokens?`, `maxSections?`): `Promise`\<[`DocumentTextSection`](../interfaces/DocumentTextSection.md)[]\>
+
+Gets the sections of the document that matched the query.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `maxTokens?` | `number` | Maximum number of tokens per section. |
+| `maxSections?` | `number` | Maximum number of sections to return. |
+
+#### Returns
+
+`Promise`\<[`DocumentTextSection`](../interfaces/DocumentTextSection.md)[]\>
+
+Array of document sections.
+
+#### Defined in
+
+[LocalDocumentResult.ts:132](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentResult.ts#L132)
+
+___
+
+### getText
+
+▸ **getText**(): `Promise`\<`string`\>
+
+Gets the text of the document.
+
+#### Returns
+
+`Promise`\<`string`\>
+
+The text of the document.
+
+#### Defined in
+
+[LocalDocumentResult.ts:51](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentResult.ts#L51)
+
+___
+
+### hasMetadata
+
+▸ **hasMetadata**(): `Promise`\<`boolean`\>
+
+Determines if the document has additional metadata storred on disk.
+
+#### Returns
+
+`Promise`\<`boolean`\>
+
+True if the document has metadata; otherwise, false.
+
+#### Inherited from
+
+[LocalDocument](LocalDocument.md).[hasMetadata](LocalDocument.md#hasmetadata)
+
+#### Defined in
+
+[LocalDocument.ts:69](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L69)
+
+___
+
+### loadMetadata
+
+▸ **loadMetadata**(): `Promise`\<`Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\>\>
+
+Loads the metadata for the document from disk.
+
+#### Returns
+
+`Promise`\<`Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\>\>
+
+Metadata for the document.
+
+#### Inherited from
+
+[LocalDocument](LocalDocument.md).[loadMetadata](LocalDocument.md#loadmetadata)
+
+#### Defined in
+
+[LocalDocument.ts:82](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L82)
+
+___
+
+### loadText
+
+▸ **loadText**(): `Promise`\<`string`\>
+
+Loads the text for the document from disk.
+
+#### Returns
+
+`Promise`\<`string`\>
+
+Text for the document.
+
+#### Inherited from
+
+[LocalDocument](LocalDocument.md).[loadText](LocalDocument.md#loadtext)
+
+#### Defined in
+
+[LocalDocument.ts:105](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocument.ts#L105)
+
+___
+
+### renderAllSections
+
+▸ **renderAllSections**(`maxTokens`): `Promise`\<[`DocumentTextSection`](../interfaces/DocumentTextSection.md)[]\>
+
+Renders all of the results chunks as spans of text (sections.)
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `maxTokens` | `number` | Maximum number of tokens per section. |
+
+#### Returns
+
+`Promise`\<[`DocumentTextSection`](../interfaces/DocumentTextSection.md)[]\>
+
+Array of rendered text sections.
+
+**`Remarks`**
+
+The returned sections will be sorted by document order and limited to maxTokens in length.
+
+#### Defined in
+
+[LocalDocumentResult.ts:62](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentResult.ts#L62)
diff --git a/docs/classes/LocalIndex.md b/docs/classes/LocalIndex.md
new file mode 100644
index 0000000..101af7c
--- /dev/null
+++ b/docs/classes/LocalIndex.md
@@ -0,0 +1,488 @@
+[Vectra](../README.md) / [Exports](../modules.md) / LocalIndex
+
+# Class: LocalIndex\<TMetadata\>
+
+Local vector index instance.
+
+**`Remarks`**
+
+This class is used to create, update, and query a local vector index.
+Each index is a folder on disk containing an index.json file and an optional set of metadata files.
+
+## Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TMetadata` | extends `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> = `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> |
+
+## Hierarchy
+
+- **`LocalIndex`**
+
+  ↳ [`LocalDocumentIndex`](LocalDocumentIndex.md)
+
+## Table of contents
+
+### Constructors
+
+- [constructor](LocalIndex.md#constructor)
+
+### Accessors
+
+- [folderPath](LocalIndex.md#folderpath)
+- [indexName](LocalIndex.md#indexname)
+
+### Methods
+
+- [beginUpdate](LocalIndex.md#beginupdate)
+- [cancelUpdate](LocalIndex.md#cancelupdate)
+- [createIndex](LocalIndex.md#createindex)
+- [deleteIndex](LocalIndex.md#deleteindex)
+- [deleteItem](LocalIndex.md#deleteitem)
+- [endUpdate](LocalIndex.md#endupdate)
+- [getIndexStats](LocalIndex.md#getindexstats)
+- [getItem](LocalIndex.md#getitem)
+- [insertItem](LocalIndex.md#insertitem)
+- [isIndexCreated](LocalIndex.md#isindexcreated)
+- [listItems](LocalIndex.md#listitems)
+- [listItemsByMetadata](LocalIndex.md#listitemsbymetadata)
+- [loadIndexData](LocalIndex.md#loadindexdata)
+- [queryItems](LocalIndex.md#queryitems)
+- [upsertItem](LocalIndex.md#upsertitem)
+
+## Constructors
+
+### constructor
+
+• **new LocalIndex**\<`TMetadata`\>(`folderPath`, `indexName?`)
+
+Creates a new instance of LocalIndex.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TMetadata` | extends `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> = `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `folderPath` | `string` | Path to the index folder. |
+| `indexName?` | `string` | Optional name of the index file. Defaults to index.json. |
+
+#### Defined in
+
+[LocalIndex.ts:62](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L62)
+
+## Accessors
+
+### folderPath
+
+• `get` **folderPath**(): `string`
+
+Path to the index folder.
+
+#### Returns
+
+`string`
+
+#### Defined in
+
+[LocalIndex.ts:70](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L70)
+
+___
+
+### indexName
+
+• `get` **indexName**(): `string`
+
+Optional name of the index file.
+
+#### Returns
+
+`string`
+
+#### Defined in
+
+[LocalIndex.ts:77](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L77)
+
+## Methods
+
+### beginUpdate
+
+▸ **beginUpdate**(): `Promise`\<`void`\>
+
+Begins an update to the index.
+
+#### Returns
+
+`Promise`\<`void`\>
+
+**`Remarks`**
+
+This method loads the index into memory and prepares it for updates.
+
+#### Defined in
+
+[LocalIndex.ts:86](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L86)
+
+___
+
+### cancelUpdate
+
+▸ **cancelUpdate**(): `void`
+
+Cancels an update to the index.
+
+#### Returns
+
+`void`
+
+**`Remarks`**
+
+This method discards any changes made to the index since the update began.
+
+#### Defined in
+
+[LocalIndex.ts:100](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L100)
+
+___
+
+### createIndex
+
+▸ **createIndex**(`config?`): `Promise`\<`void`\>
+
+Creates a new index.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `config` | [`CreateIndexConfig`](../interfaces/CreateIndexConfig.md) | Index configuration. |
+
+#### Returns
+
+`Promise`\<`void`\>
+
+**`Remarks`**
+
+This method creates a new folder on disk containing an index.json file.
+
+#### Defined in
+
+[LocalIndex.ts:110](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L110)
+
+___
+
+### deleteIndex
+
+▸ **deleteIndex**(): `Promise`\<`void`\>
+
+Deletes the index.
+
+#### Returns
+
+`Promise`\<`void`\>
+
+**`Remarks`**
+
+This method deletes the index folder from disk.
+
+#### Defined in
+
+[LocalIndex.ts:143](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L143)
+
+___
+
+### deleteItem
+
+▸ **deleteItem**(`id`): `Promise`\<`void`\>
+
+Deletes an item from the index.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `id` | `string` | ID of item to delete. |
+
+#### Returns
+
+`Promise`\<`void`\>
+
+#### Defined in
+
+[LocalIndex.ts:155](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L155)
+
+___
+
+### endUpdate
+
+▸ **endUpdate**(): `Promise`\<`void`\>
+
+Ends an update to the index.
+
+#### Returns
+
+`Promise`\<`void`\>
+
+**`Remarks`**
+
+This method saves the index to disk.
+
+#### Defined in
+
+[LocalIndex.ts:176](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L176)
+
+___
+
+### getIndexStats
+
+▸ **getIndexStats**(): `Promise`\<[`IndexStats`](../interfaces/IndexStats.md)\>
+
+Loads an index from disk and returns its stats.
+
+#### Returns
+
+`Promise`\<[`IndexStats`](../interfaces/IndexStats.md)\>
+
+Index stats.
+
+#### Defined in
+
+[LocalIndex.ts:195](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L195)
+
+___
+
+### getItem
+
+▸ **getItem**\<`TItemMetadata`\>(`id`): `Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Returns an item from the index given its ID.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> = `TMetadata` |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `id` | `string` | ID of the item to retrieve. |
+
+#### Returns
+
+`Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Item or undefined if not found.
+
+#### Defined in
+
+[LocalIndex.ts:209](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L209)
+
+___
+
+### insertItem
+
+▸ **insertItem**\<`TItemMetadata`\>(`item`): `Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Adds an item to the index.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> = `TMetadata` |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `item` | `Partial`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\> | Item to insert. |
+
+#### Returns
+
+`Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Inserted item.
+
+**`Remarks`**
+
+A new update is started if one is not already in progress. If an item with the same ID
+already exists, an error will be thrown.
+
+#### Defined in
+
+[LocalIndex.ts:223](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L223)
+
+___
+
+### isIndexCreated
+
+▸ **isIndexCreated**(): `Promise`\<`boolean`\>
+
+Returns true if the index exists.
+
+#### Returns
+
+`Promise`\<`boolean`\>
+
+#### Defined in
+
+[LocalIndex.ts:238](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L238)
+
+___
+
+### listItems
+
+▸ **listItems**\<`TItemMetadata`\>(): `Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>[]\>
+
+Returns all items in the index.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> = `TMetadata` |
+
+#### Returns
+
+`Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>[]\>
+
+Array of all items in the index.
+
+**`Remarks`**
+
+This method loads the index into memory and returns all its items. A copy of the items
+array is returned so no modifications should be made to the array.
+
+#### Defined in
+
+[LocalIndex.ts:254](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L254)
+
+___
+
+### listItemsByMetadata
+
+▸ **listItemsByMetadata**\<`TItemMetadata`\>(`filter`): `Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>[]\>
+
+Returns all items in the index matching the filter.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> = `TMetadata` |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `filter` | [`MetadataFilter`](../interfaces/MetadataFilter.md) | Filter to apply. |
+
+#### Returns
+
+`Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>[]\>
+
+Array of items matching the filter.
+
+**`Remarks`**
+
+This method loads the index into memory and returns all its items matching the filter.
+
+#### Defined in
+
+[LocalIndex.ts:266](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L266)
+
+___
+
+### loadIndexData
+
+▸ `Protected` **loadIndexData**(): `Promise`\<`void`\>
+
+Ensures that the index has been loaded into memory.
+
+#### Returns
+
+`Promise`\<`void`\>
+
+#### Defined in
+
+[LocalIndex.ts:342](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L342)
+
+___
+
+### queryItems
+
+▸ **queryItems**\<`TItemMetadata`\>(`vector`, `query`, `topK`, `filter?`, `isBm25?`): `Promise`\<[`QueryResult`](../interfaces/QueryResult.md)\<`TItemMetadata`\>[]\>
+
+Finds the top k items in the index that are most similar to the vector.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> = `TMetadata` |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `vector` | `number`[] | Vector to query against. |
+| `query` | `string` | Query text for BM25 search. |
+| `topK` | `number` | Number of items to return. |
+| `filter?` | [`MetadataFilter`](../interfaces/MetadataFilter.md) | Optional. Filter to apply. |
+| `isBm25?` | `boolean` | Optional. Whether to use BM25 search. |
+
+#### Returns
+
+`Promise`\<[`QueryResult`](../interfaces/QueryResult.md)\<`TItemMetadata`\>[]\>
+
+Similar items to the vector that match the supplied filter.
+
+**`Remarks`**
+
+This method loads the index into memory and returns the top k items that are most similar.
+An optional filter can be applied to the metadata of the items.
+
+#### Defined in
+
+[LocalIndex.ts:285](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L285)
+
+___
+
+### upsertItem
+
+▸ **upsertItem**\<`TItemMetadata`\>(`item`): `Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Adds or replaces an item in the index.
+
+#### Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TItemMetadata` | extends `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> = `TMetadata` |
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `item` | `Partial`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\> | Item to insert or replace. |
+
+#### Returns
+
+`Promise`\<[`IndexItem`](../interfaces/IndexItem.md)\<`TItemMetadata`\>\>
+
+Upserted item.
+
+**`Remarks`**
+
+A new update is started if one is not already in progress. If an item with the same ID
+already exists, it will be replaced.
+
+#### Defined in
+
+[LocalIndex.ts:328](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L328)
diff --git a/docs/classes/OpenAIEmbeddings.md b/docs/classes/OpenAIEmbeddings.md
new file mode 100644
index 0000000..6efa4d8
--- /dev/null
+++ b/docs/classes/OpenAIEmbeddings.md
@@ -0,0 +1,147 @@
+[Vectra](../README.md) / [Exports](../modules.md) / OpenAIEmbeddings
+
+# Class: OpenAIEmbeddings
+
+Embeddings model that uses OpenAI's API.
+
+## Implements
+
+- [`EmbeddingsModel`](../interfaces/EmbeddingsModel.md)
+
+## Table of contents
+
+### Constructors
+
+- [constructor](OpenAIEmbeddings.md#constructor)
+
+### Accessors
+
+- [maxTokens](OpenAIEmbeddings.md#maxtokens)
+
+### Methods
+
+- [createEmbeddingRequest](OpenAIEmbeddings.md#createembeddingrequest)
+- [createEmbeddings](OpenAIEmbeddings.md#createembeddings)
+- [post](OpenAIEmbeddings.md#post)
+
+## Constructors
+
+### constructor
+
+• **new OpenAIEmbeddings**(`options`)
+
+Creates a new instance of OpenAIEmbeddings.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `options` | [`OSSEmbeddingsOptions`](../interfaces/OSSEmbeddingsOptions.md) \| [`OpenAIEmbeddingsOptions`](../interfaces/OpenAIEmbeddingsOptions.md) \| [`AzureOpenAIEmbeddingsOptions`](../interfaces/AzureOpenAIEmbeddingsOptions.md) | Configuration options for the embeddings model. |
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:131](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L131)
+
+## Accessors
+
+### maxTokens
+
+• `get` **maxTokens**(): `number`
+
+Gets the maximum number of tokens.
+
+#### Returns
+
+`number`
+
+#### Implementation of
+
+[EmbeddingsModel](../interfaces/EmbeddingsModel.md).[maxTokens](../interfaces/EmbeddingsModel.md#maxtokens)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:145](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L145)
+
+## Methods
+
+### createEmbeddingRequest
+
+▸ `Protected` **createEmbeddingRequest**(`request`): `Promise`\<`AxiosResponse`\<[`CreateEmbeddingResponse`](../interfaces/CreateEmbeddingResponse.md), `any`\>\>
+
+Creates an embedding request.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `request` | [`CreateEmbeddingRequest`](../interfaces/CreateEmbeddingRequest.md) | The request to create. |
+
+#### Returns
+
+`Promise`\<`AxiosResponse`\<[`CreateEmbeddingResponse`](../interfaces/CreateEmbeddingResponse.md), `any`\>\>
+
+The response from the API.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:208](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L208)
+
+___
+
+### createEmbeddings
+
+▸ **createEmbeddings**(`inputs`): `Promise`\<[`EmbeddingsResponse`](../interfaces/EmbeddingsResponse.md)\>
+
+Creates embeddings for the given inputs.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `inputs` | `string` \| `string`[] | Text inputs to create embeddings for. |
+
+#### Returns
+
+`Promise`\<[`EmbeddingsResponse`](../interfaces/EmbeddingsResponse.md)\>
+
+A `EmbeddingsResponse` with a status and the generated embeddings or a message when an error occurs.
+
+#### Implementation of
+
+[EmbeddingsModel](../interfaces/EmbeddingsModel.md).[createEmbeddings](../interfaces/EmbeddingsModel.md#createembeddings)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:154](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L154)
+
+___
+
+### post
+
+▸ `Protected` **post**\<`TData`\>(`url`, `body`, `retryCount?`): `Promise`\<`AxiosResponse`\<`TData`, `any`\>\>
+
+Posts a request to the API.
+
+#### Type parameters
+
+| Name |
+| :------ |
+| `TData` |
+
+#### Parameters
+
+| Name | Type | Default value | Description |
+| :------ | :------ | :------ | :------ |
+| `url` | `string` | `undefined` | The URL to post to. |
+| `body` | `object` | `undefined` | The body of the request. |
+| `retryCount` | `number` | `0` | The number of retries. |
+
+#### Returns
+
+`Promise`\<`AxiosResponse`\<`TData`, `any`\>\>
+
+The response from the API.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:237](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L237)
diff --git a/docs/classes/TextSplitter.md b/docs/classes/TextSplitter.md
new file mode 100644
index 0000000..4ff43eb
--- /dev/null
+++ b/docs/classes/TextSplitter.md
@@ -0,0 +1,51 @@
+[Vectra](../README.md) / [Exports](../modules.md) / TextSplitter
+
+# Class: TextSplitter
+
+Splits text into chunks.
+
+## Table of contents
+
+### Constructors
+
+- [constructor](TextSplitter.md#constructor)
+
+### Methods
+
+- [split](TextSplitter.md#split)
+
+## Constructors
+
+### constructor
+
+• **new TextSplitter**(`config?`)
+
+#### Parameters
+
+| Name | Type |
+| :------ | :------ |
+| `config?` | `Partial`\<[`TextSplitterConfig`](../interfaces/TextSplitterConfig.md)\> |
+
+#### Defined in
+
+[TextSplitter.ts:26](https://github.com/bartonmalow/vectra/blob/418123d/src/TextSplitter.ts#L26)
+
+## Methods
+
+### split
+
+▸ **split**(`text`): [`TextChunk`](../interfaces/TextChunk.md)[]
+
+#### Parameters
+
+| Name | Type |
+| :------ | :------ |
+| `text` | `string` |
+
+#### Returns
+
+[`TextChunk`](../interfaces/TextChunk.md)[]
+
+#### Defined in
+
+[TextSplitter.ts:53](https://github.com/bartonmalow/vectra/blob/418123d/src/TextSplitter.ts#L53)
diff --git a/docs/classes/WebFetcher.md b/docs/classes/WebFetcher.md
new file mode 100644
index 0000000..bb179eb
--- /dev/null
+++ b/docs/classes/WebFetcher.md
@@ -0,0 +1,60 @@
+[Vectra](../README.md) / [Exports](../modules.md) / WebFetcher
+
+# Class: WebFetcher
+
+Fetches text content from web pages.
+
+## Implements
+
+- [`TextFetcher`](../interfaces/TextFetcher.md)
+
+## Table of contents
+
+### Constructors
+
+- [constructor](WebFetcher.md#constructor)
+
+### Methods
+
+- [fetch](WebFetcher.md#fetch)
+
+## Constructors
+
+### constructor
+
+• **new WebFetcher**(`config?`)
+
+#### Parameters
+
+| Name | Type |
+| :------ | :------ |
+| `config?` | `Partial`\<[`WebFetcherConfig`](../interfaces/WebFetcherConfig.md)\> |
+
+#### Defined in
+
+[WebFetcher.ts:49](https://github.com/bartonmalow/vectra/blob/418123d/src/WebFetcher.ts#L49)
+
+## Methods
+
+### fetch
+
+▸ **fetch**(`uri`, `onDocument`): `Promise`\<`boolean`\>
+
+#### Parameters
+
+| Name | Type |
+| :------ | :------ |
+| `uri` | `string` |
+| `onDocument` | (`uri`: `string`, `text`: `string`, `docType?`: `string`) => `Promise`\<`boolean`\> |
+
+#### Returns
+
+`Promise`\<`boolean`\>
+
+#### Implementation of
+
+[TextFetcher](../interfaces/TextFetcher.md).[fetch](../interfaces/TextFetcher.md#fetch)
+
+#### Defined in
+
+[WebFetcher.ts:56](https://github.com/bartonmalow/vectra/blob/418123d/src/WebFetcher.ts#L56)
diff --git a/docs/interfaces/AzureOpenAIEmbeddingsOptions.md b/docs/interfaces/AzureOpenAIEmbeddingsOptions.md
new file mode 100644
index 0000000..ae3a51a
--- /dev/null
+++ b/docs/interfaces/AzureOpenAIEmbeddingsOptions.md
@@ -0,0 +1,162 @@
+[Vectra](../README.md) / [Exports](../modules.md) / AzureOpenAIEmbeddingsOptions
+
+# Interface: AzureOpenAIEmbeddingsOptions
+
+Options for Azure OpenAI embeddings.
+
+## Hierarchy
+
+- [`BaseOpenAIEmbeddingsOptions`](BaseOpenAIEmbeddingsOptions.md)
+
+  ↳ **`AzureOpenAIEmbeddingsOptions`**
+
+## Table of contents
+
+### Properties
+
+- [azureApiKey](AzureOpenAIEmbeddingsOptions.md#azureapikey)
+- [azureApiVersion](AzureOpenAIEmbeddingsOptions.md#azureapiversion)
+- [azureDeployment](AzureOpenAIEmbeddingsOptions.md#azuredeployment)
+- [azureEndpoint](AzureOpenAIEmbeddingsOptions.md#azureendpoint)
+- [dimensions](AzureOpenAIEmbeddingsOptions.md#dimensions)
+- [logRequests](AzureOpenAIEmbeddingsOptions.md#logrequests)
+- [maxTokens](AzureOpenAIEmbeddingsOptions.md#maxtokens)
+- [requestConfig](AzureOpenAIEmbeddingsOptions.md#requestconfig)
+- [retryPolicy](AzureOpenAIEmbeddingsOptions.md#retrypolicy)
+
+## Properties
+
+### azureApiKey
+
+• **azureApiKey**: `string`
+
+API key to use when making requests to Azure OpenAI.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:99](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L99)
+
+___
+
+### azureApiVersion
+
+• `Optional` **azureApiVersion**: `string`
+
+Optional. Version of the API being called. Defaults to `2023-05-15`.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:114](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L114)
+
+___
+
+### azureDeployment
+
+• **azureDeployment**: `string`
+
+Name of the Azure OpenAI deployment (model) to use.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:109](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L109)
+
+___
+
+### azureEndpoint
+
+• **azureEndpoint**: `string`
+
+Deployment endpoint to use.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:104](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L104)
+
+___
+
+### dimensions
+
+• `Optional` **dimensions**: `number`
+
+Optional. Number of embedding dimensions to return.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[dimensions](BaseOpenAIEmbeddingsOptions.md#dimensions)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:15](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L15)
+
+___
+
+### logRequests
+
+• `Optional` **logRequests**: `boolean`
+
+Optional. Whether to log requests to the console.
+
+**`Remarks`**
+
+This is useful for debugging prompts and defaults to `false`.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[logRequests](BaseOpenAIEmbeddingsOptions.md#logrequests)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:22](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L22)
+
+___
+
+### maxTokens
+
+• `Optional` **maxTokens**: `number`
+
+Optional. Maximum number of tokens that can be sent to the embedding model.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[maxTokens](BaseOpenAIEmbeddingsOptions.md#maxtokens)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:27](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L27)
+
+___
+
+### requestConfig
+
+• `Optional` **requestConfig**: `AxiosRequestConfig`\<`any`\>
+
+Optional. Request options to use when calling the OpenAI API.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[requestConfig](BaseOpenAIEmbeddingsOptions.md#requestconfig)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:40](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L40)
+
+___
+
+### retryPolicy
+
+• `Optional` **retryPolicy**: `number`[]
+
+Optional. Retry policy to use when calling the OpenAI API.
+
+**`Remarks`**
+
+The default retry policy is `[2000, 5000]` which means that the first retry will be after
+2 seconds and the second retry will be after 5 seconds.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[retryPolicy](BaseOpenAIEmbeddingsOptions.md#retrypolicy)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:35](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L35)
diff --git a/docs/interfaces/BaseOpenAIEmbeddingsOptions.md b/docs/interfaces/BaseOpenAIEmbeddingsOptions.md
new file mode 100644
index 0000000..c46585a
--- /dev/null
+++ b/docs/interfaces/BaseOpenAIEmbeddingsOptions.md
@@ -0,0 +1,94 @@
+[Vectra](../README.md) / [Exports](../modules.md) / BaseOpenAIEmbeddingsOptions
+
+# Interface: BaseOpenAIEmbeddingsOptions
+
+Base options for OpenAI embeddings.
+
+## Hierarchy
+
+- **`BaseOpenAIEmbeddingsOptions`**
+
+  ↳ [`OSSEmbeddingsOptions`](OSSEmbeddingsOptions.md)
+
+  ↳ [`OpenAIEmbeddingsOptions`](OpenAIEmbeddingsOptions.md)
+
+  ↳ [`AzureOpenAIEmbeddingsOptions`](AzureOpenAIEmbeddingsOptions.md)
+
+## Table of contents
+
+### Properties
+
+- [dimensions](BaseOpenAIEmbeddingsOptions.md#dimensions)
+- [logRequests](BaseOpenAIEmbeddingsOptions.md#logrequests)
+- [maxTokens](BaseOpenAIEmbeddingsOptions.md#maxtokens)
+- [requestConfig](BaseOpenAIEmbeddingsOptions.md#requestconfig)
+- [retryPolicy](BaseOpenAIEmbeddingsOptions.md#retrypolicy)
+
+## Properties
+
+### dimensions
+
+• `Optional` **dimensions**: `number`
+
+Optional. Number of embedding dimensions to return.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:15](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L15)
+
+___
+
+### logRequests
+
+• `Optional` **logRequests**: `boolean`
+
+Optional. Whether to log requests to the console.
+
+**`Remarks`**
+
+This is useful for debugging prompts and defaults to `false`.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:22](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L22)
+
+___
+
+### maxTokens
+
+• `Optional` **maxTokens**: `number`
+
+Optional. Maximum number of tokens that can be sent to the embedding model.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:27](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L27)
+
+___
+
+### requestConfig
+
+• `Optional` **requestConfig**: `AxiosRequestConfig`\<`any`\>
+
+Optional. Request options to use when calling the OpenAI API.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:40](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L40)
+
+___
+
+### retryPolicy
+
+• `Optional` **retryPolicy**: `number`[]
+
+Optional. Retry policy to use when calling the OpenAI API.
+
+**`Remarks`**
+
+The default retry policy is `[2000, 5000]` which means that the first retry will be after
+2 seconds and the second retry will be after 5 seconds.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:35](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L35)
diff --git a/docs/interfaces/CreateEmbeddingRequest.md b/docs/interfaces/CreateEmbeddingRequest.md
new file mode 100644
index 0000000..3391d71
--- /dev/null
+++ b/docs/interfaces/CreateEmbeddingRequest.md
@@ -0,0 +1,55 @@
+[Vectra](../README.md) / [Exports](../modules.md) / CreateEmbeddingRequest
+
+# Interface: CreateEmbeddingRequest
+
+Request to create embeddings.
+
+## Hierarchy
+
+- **`CreateEmbeddingRequest`**
+
+  ↳ [`OpenAICreateEmbeddingRequest`](OpenAICreateEmbeddingRequest.md)
+
+## Table of contents
+
+### Properties
+
+- [dimensions](CreateEmbeddingRequest.md#dimensions)
+- [input](CreateEmbeddingRequest.md#input)
+- [user](CreateEmbeddingRequest.md#user)
+
+## Properties
+
+### dimensions
+
+• `Optional` **dimensions**: `number`
+
+Optional. Number of dimensions for the embeddings.
+
+#### Defined in
+
+[types.ts:242](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L242)
+
+___
+
+### input
+
+• **input**: [`CreateEmbeddingRequestInput`](../modules.md#createembeddingrequestinput)
+
+Text inputs to create embeddings for.
+
+#### Defined in
+
+[types.ts:237](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L237)
+
+___
+
+### user
+
+• `Optional` **user**: `string`
+
+Optional. User identifier for the request.
+
+#### Defined in
+
+[types.ts:247](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L247)
diff --git a/docs/interfaces/CreateEmbeddingResponse.md b/docs/interfaces/CreateEmbeddingResponse.md
new file mode 100644
index 0000000..4f1a39c
--- /dev/null
+++ b/docs/interfaces/CreateEmbeddingResponse.md
@@ -0,0 +1,62 @@
+[Vectra](../README.md) / [Exports](../modules.md) / CreateEmbeddingResponse
+
+# Interface: CreateEmbeddingResponse
+
+Response from creating embeddings.
+
+## Table of contents
+
+### Properties
+
+- [data](CreateEmbeddingResponse.md#data)
+- [model](CreateEmbeddingResponse.md#model)
+- [object](CreateEmbeddingResponse.md#object)
+- [usage](CreateEmbeddingResponse.md#usage)
+
+## Properties
+
+### data
+
+• **data**: [`CreateEmbeddingResponseDataInner`](CreateEmbeddingResponseDataInner.md)[]
+
+Array of embeddings.
+
+#### Defined in
+
+[types.ts:316](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L316)
+
+___
+
+### model
+
+• **model**: `string`
+
+Model used to create the embeddings.
+
+#### Defined in
+
+[types.ts:311](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L311)
+
+___
+
+### object
+
+• **object**: `string`
+
+Type of the object.
+
+#### Defined in
+
+[types.ts:306](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L306)
+
+___
+
+### usage
+
+• **usage**: [`CreateEmbeddingResponseUsage`](CreateEmbeddingResponseUsage.md)
+
+Usage statistics.
+
+#### Defined in
+
+[types.ts:321](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L321)
diff --git a/docs/interfaces/CreateEmbeddingResponseDataInner.md b/docs/interfaces/CreateEmbeddingResponseDataInner.md
new file mode 100644
index 0000000..a82a08a
--- /dev/null
+++ b/docs/interfaces/CreateEmbeddingResponseDataInner.md
@@ -0,0 +1,49 @@
+[Vectra](../README.md) / [Exports](../modules.md) / CreateEmbeddingResponseDataInner
+
+# Interface: CreateEmbeddingResponseDataInner
+
+Response data for a single embedding.
+
+## Table of contents
+
+### Properties
+
+- [embedding](CreateEmbeddingResponseDataInner.md#embedding)
+- [index](CreateEmbeddingResponseDataInner.md#index)
+- [object](CreateEmbeddingResponseDataInner.md#object)
+
+## Properties
+
+### embedding
+
+• **embedding**: `number`[]
+
+The embedding vector.
+
+#### Defined in
+
+[types.ts:279](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L279)
+
+___
+
+### index
+
+• **index**: `number`
+
+Index of the embedding in the response.
+
+#### Defined in
+
+[types.ts:269](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L269)
+
+___
+
+### object
+
+• **object**: `string`
+
+Type of the object.
+
+#### Defined in
+
+[types.ts:274](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L274)
diff --git a/docs/interfaces/CreateEmbeddingResponseUsage.md b/docs/interfaces/CreateEmbeddingResponseUsage.md
new file mode 100644
index 0000000..e563e5b
--- /dev/null
+++ b/docs/interfaces/CreateEmbeddingResponseUsage.md
@@ -0,0 +1,36 @@
+[Vectra](../README.md) / [Exports](../modules.md) / CreateEmbeddingResponseUsage
+
+# Interface: CreateEmbeddingResponseUsage
+
+Usage statistics for embedding creation.
+
+## Table of contents
+
+### Properties
+
+- [prompt\_tokens](CreateEmbeddingResponseUsage.md#prompt_tokens)
+- [total\_tokens](CreateEmbeddingResponseUsage.md#total_tokens)
+
+## Properties
+
+### prompt\_tokens
+
+• **prompt\_tokens**: `number`
+
+Number of tokens in the prompt.
+
+#### Defined in
+
+[types.ts:290](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L290)
+
+___
+
+### total\_tokens
+
+• **total\_tokens**: `number`
+
+Total number of tokens used.
+
+#### Defined in
+
+[types.ts:295](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L295)
diff --git a/docs/interfaces/CreateIndexConfig.md b/docs/interfaces/CreateIndexConfig.md
new file mode 100644
index 0000000..365c2e2
--- /dev/null
+++ b/docs/interfaces/CreateIndexConfig.md
@@ -0,0 +1,49 @@
+[Vectra](../README.md) / [Exports](../modules.md) / CreateIndexConfig
+
+# Interface: CreateIndexConfig
+
+Configuration for creating a new index.
+
+## Table of contents
+
+### Properties
+
+- [deleteIfExists](CreateIndexConfig.md#deleteifexists)
+- [metadata\_config](CreateIndexConfig.md#metadata_config)
+- [version](CreateIndexConfig.md#version)
+
+## Properties
+
+### deleteIfExists
+
+• `Optional` **deleteIfExists**: `boolean`
+
+#### Defined in
+
+[LocalIndex.ts:36](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L36)
+
+___
+
+### metadata\_config
+
+• `Optional` **metadata\_config**: `Object`
+
+#### Type declaration
+
+| Name | Type |
+| :------ | :------ |
+| `indexed?` | `string`[] |
+
+#### Defined in
+
+[LocalIndex.ts:37](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L37)
+
+___
+
+### version
+
+• **version**: `number`
+
+#### Defined in
+
+[LocalIndex.ts:35](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalIndex.ts#L35)
diff --git a/docs/interfaces/DocumentCatalogStats.md b/docs/interfaces/DocumentCatalogStats.md
new file mode 100644
index 0000000..21c144d
--- /dev/null
+++ b/docs/interfaces/DocumentCatalogStats.md
@@ -0,0 +1,60 @@
+[Vectra](../README.md) / [Exports](../modules.md) / DocumentCatalogStats
+
+# Interface: DocumentCatalogStats
+
+Statistics for a document catalog.
+
+## Table of contents
+
+### Properties
+
+- [chunks](DocumentCatalogStats.md#chunks)
+- [documents](DocumentCatalogStats.md#documents)
+- [metadata\_config](DocumentCatalogStats.md#metadata_config)
+- [version](DocumentCatalogStats.md#version)
+
+## Properties
+
+### chunks
+
+• **chunks**: `number`
+
+#### Defined in
+
+[types.ts:206](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L206)
+
+___
+
+### documents
+
+• **documents**: `number`
+
+#### Defined in
+
+[types.ts:205](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L205)
+
+___
+
+### metadata\_config
+
+• **metadata\_config**: `Object`
+
+#### Type declaration
+
+| Name | Type |
+| :------ | :------ |
+| `indexed?` | `string`[] |
+
+#### Defined in
+
+[types.ts:207](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L207)
+
+___
+
+### version
+
+• **version**: `number`
+
+#### Defined in
+
+[types.ts:204](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L204)
diff --git a/docs/interfaces/DocumentChunkMetadata.md b/docs/interfaces/DocumentChunkMetadata.md
new file mode 100644
index 0000000..0fa2b5c
--- /dev/null
+++ b/docs/interfaces/DocumentChunkMetadata.md
@@ -0,0 +1,47 @@
+[Vectra](../README.md) / [Exports](../modules.md) / DocumentChunkMetadata
+
+# Interface: DocumentChunkMetadata
+
+Metadata for a document chunk.
+
+## Indexable
+
+▪ [key: `string`]: [`MetadataTypes`](../modules.md#metadatatypes)
+
+## Table of contents
+
+### Properties
+
+- [documentId](DocumentChunkMetadata.md#documentid)
+- [endPos](DocumentChunkMetadata.md#endpos)
+- [startPos](DocumentChunkMetadata.md#startpos)
+
+## Properties
+
+### documentId
+
+• **documentId**: `string`
+
+#### Defined in
+
+[types.ts:193](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L193)
+
+___
+
+### endPos
+
+• **endPos**: `number`
+
+#### Defined in
+
+[types.ts:195](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L195)
+
+___
+
+### startPos
+
+• **startPos**: `number`
+
+#### Defined in
+
+[types.ts:194](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L194)
diff --git a/docs/interfaces/DocumentQueryOptions.md b/docs/interfaces/DocumentQueryOptions.md
new file mode 100644
index 0000000..59895c9
--- /dev/null
+++ b/docs/interfaces/DocumentQueryOptions.md
@@ -0,0 +1,70 @@
+[Vectra](../README.md) / [Exports](../modules.md) / DocumentQueryOptions
+
+# Interface: DocumentQueryOptions
+
+Options for querying documents.
+
+## Table of contents
+
+### Properties
+
+- [filter](DocumentQueryOptions.md#filter)
+- [isBm25](DocumentQueryOptions.md#isbm25)
+- [maxChunks](DocumentQueryOptions.md#maxchunks)
+- [maxDocuments](DocumentQueryOptions.md#maxdocuments)
+
+## Properties
+
+### filter
+
+• `Optional` **filter**: [`MetadataFilter`](MetadataFilter.md)
+
+Optional. Filter to apply to the document metadata.
+
+#### Defined in
+
+[LocalDocumentIndex.ts:33](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L33)
+
+___
+
+### isBm25
+
+• `Optional` **isBm25**: `boolean`
+
+Optional. Turn on bm25 keyword search to perform hybrid search - semantic + keyword
+
+#### Defined in
+
+[LocalDocumentIndex.ts:38](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L38)
+
+___
+
+### maxChunks
+
+• `Optional` **maxChunks**: `number`
+
+Maximum number of chunks to return per document.
+
+**`Remarks`**
+
+Default is 50.
+
+#### Defined in
+
+[LocalDocumentIndex.ts:28](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L28)
+
+___
+
+### maxDocuments
+
+• `Optional` **maxDocuments**: `number`
+
+Optional. Maximum number of documents to return.
+
+**`Remarks`**
+
+Default is 10.
+
+#### Defined in
+
+[LocalDocumentIndex.ts:21](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L21)
diff --git a/docs/interfaces/DocumentTextSection.md b/docs/interfaces/DocumentTextSection.md
new file mode 100644
index 0000000..5fe747c
--- /dev/null
+++ b/docs/interfaces/DocumentTextSection.md
@@ -0,0 +1,54 @@
+[Vectra](../README.md) / [Exports](../modules.md) / DocumentTextSection
+
+# Interface: DocumentTextSection
+
+Represents a section of document text.
+
+## Table of contents
+
+### Properties
+
+- [isBm25](DocumentTextSection.md#isbm25)
+- [score](DocumentTextSection.md#score)
+- [text](DocumentTextSection.md#text)
+- [tokenCount](DocumentTextSection.md#tokencount)
+
+## Properties
+
+### isBm25
+
+• **isBm25**: `boolean`
+
+#### Defined in
+
+[types.ts:220](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L220)
+
+___
+
+### score
+
+• **score**: `number`
+
+#### Defined in
+
+[types.ts:219](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L219)
+
+___
+
+### text
+
+• **text**: `string`
+
+#### Defined in
+
+[types.ts:217](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L217)
+
+___
+
+### tokenCount
+
+• **tokenCount**: `number`
+
+#### Defined in
+
+[types.ts:218](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L218)
diff --git a/docs/interfaces/EmbeddingsModel.md b/docs/interfaces/EmbeddingsModel.md
new file mode 100644
index 0000000..b57944b
--- /dev/null
+++ b/docs/interfaces/EmbeddingsModel.md
@@ -0,0 +1,55 @@
+[Vectra](../README.md) / [Exports](../modules.md) / EmbeddingsModel
+
+# Interface: EmbeddingsModel
+
+Interface for embeddings model.
+
+## Implemented by
+
+- [`OpenAIEmbeddings`](../classes/OpenAIEmbeddings.md)
+
+## Table of contents
+
+### Properties
+
+- [maxTokens](EmbeddingsModel.md#maxtokens)
+
+### Methods
+
+- [createEmbeddings](EmbeddingsModel.md#createembeddings)
+
+## Properties
+
+### maxTokens
+
+• `Readonly` **maxTokens**: `number`
+
+Maximum number of tokens
+
+#### Defined in
+
+[types.ts:9](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L9)
+
+## Methods
+
+### createEmbeddings
+
+▸ **createEmbeddings**(`inputs`): `Promise`\<[`EmbeddingsResponse`](EmbeddingsResponse.md)\>
+
+Creates embeddings for text inputs.
+
+#### Parameters
+
+| Name | Type | Description |
+| :------ | :------ | :------ |
+| `inputs` | `string` \| `string`[] | Text inputs to create embeddings for. |
+
+#### Returns
+
+`Promise`\<[`EmbeddingsResponse`](EmbeddingsResponse.md)\>
+
+A `EmbeddingsResponse` with a status and the generated embeddings or a message when an error occurs.
+
+#### Defined in
+
+[types.ts:16](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L16)
diff --git a/docs/interfaces/EmbeddingsResponse.md b/docs/interfaces/EmbeddingsResponse.md
new file mode 100644
index 0000000..920e426
--- /dev/null
+++ b/docs/interfaces/EmbeddingsResponse.md
@@ -0,0 +1,86 @@
+[Vectra](../README.md) / [Exports](../modules.md) / EmbeddingsResponse
+
+# Interface: EmbeddingsResponse
+
+Response from an embeddings model.
+
+## Table of contents
+
+### Properties
+
+- [message](EmbeddingsResponse.md#message)
+- [model](EmbeddingsResponse.md#model)
+- [output](EmbeddingsResponse.md#output)
+- [status](EmbeddingsResponse.md#status)
+- [usage](EmbeddingsResponse.md#usage)
+
+## Properties
+
+### message
+
+• `Optional` **message**: `string`
+
+Optional. Message when status is not equal to `success`.
+
+#### Defined in
+
+[types.ts:43](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L43)
+
+___
+
+### model
+
+• `Optional` **model**: `string`
+
+Optional. Model used to create the embeddings.
+
+#### Defined in
+
+[types.ts:48](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L48)
+
+___
+
+### output
+
+• `Optional` **output**: `number`[][]
+
+Optional. Embeddings for the given inputs.
+
+#### Defined in
+
+[types.ts:38](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L38)
+
+___
+
+### status
+
+• **status**: [`EmbeddingsResponseStatus`](../modules.md#embeddingsresponsestatus)
+
+Status of the embeddings response.
+
+#### Defined in
+
+[types.ts:33](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L33)
+
+___
+
+### usage
+
+• `Optional` **usage**: `Object`
+
+Optional. Usage statistics for the request.
+
+#### Index signature
+
+▪ [key: `string`]: `number`
+
+#### Type declaration
+
+| Name | Type |
+| :------ | :------ |
+| `prompt_tokens` | `number` |
+| `total_tokens` | `number` |
+
+#### Defined in
+
+[types.ts:53](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L53)
diff --git a/docs/interfaces/IndexItem.md b/docs/interfaces/IndexItem.md
new file mode 100644
index 0000000..b97a88e
--- /dev/null
+++ b/docs/interfaces/IndexItem.md
@@ -0,0 +1,71 @@
+[Vectra](../README.md) / [Exports](../modules.md) / IndexItem
+
+# Interface: IndexItem\<TMetadata\>
+
+Represents an item in the index.
+
+## Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TMetadata` | `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> |
+
+## Table of contents
+
+### Properties
+
+- [id](IndexItem.md#id)
+- [metadata](IndexItem.md#metadata)
+- [metadataFile](IndexItem.md#metadatafile)
+- [norm](IndexItem.md#norm)
+- [vector](IndexItem.md#vector)
+
+## Properties
+
+### id
+
+• **id**: `string`
+
+#### Defined in
+
+[types.ts:98](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L98)
+
+___
+
+### metadata
+
+• **metadata**: `TMetadata`
+
+#### Defined in
+
+[types.ts:99](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L99)
+
+___
+
+### metadataFile
+
+• `Optional` **metadataFile**: `string`
+
+#### Defined in
+
+[types.ts:102](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L102)
+
+___
+
+### norm
+
+• **norm**: `number`
+
+#### Defined in
+
+[types.ts:101](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L101)
+
+___
+
+### vector
+
+• **vector**: `number`[]
+
+#### Defined in
+
+[types.ts:100](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L100)
diff --git a/docs/interfaces/IndexStats.md b/docs/interfaces/IndexStats.md
new file mode 100644
index 0000000..9523910
--- /dev/null
+++ b/docs/interfaces/IndexStats.md
@@ -0,0 +1,49 @@
+[Vectra](../README.md) / [Exports](../modules.md) / IndexStats
+
+# Interface: IndexStats
+
+Statistics for an index.
+
+## Table of contents
+
+### Properties
+
+- [items](IndexStats.md#items)
+- [metadata\_config](IndexStats.md#metadata_config)
+- [version](IndexStats.md#version)
+
+## Properties
+
+### items
+
+• **items**: `number`
+
+#### Defined in
+
+[types.ts:90](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L90)
+
+___
+
+### metadata\_config
+
+• **metadata\_config**: `Object`
+
+#### Type declaration
+
+| Name | Type |
+| :------ | :------ |
+| `indexed?` | `string`[] |
+
+#### Defined in
+
+[types.ts:87](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L87)
+
+___
+
+### version
+
+• **version**: `number`
+
+#### Defined in
+
+[types.ts:86](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L86)
diff --git a/docs/interfaces/LocalDocumentIndexConfig.md b/docs/interfaces/LocalDocumentIndexConfig.md
new file mode 100644
index 0000000..a3131fc
--- /dev/null
+++ b/docs/interfaces/LocalDocumentIndexConfig.md
@@ -0,0 +1,62 @@
+[Vectra](../README.md) / [Exports](../modules.md) / LocalDocumentIndexConfig
+
+# Interface: LocalDocumentIndexConfig
+
+Configuration for a local document index.
+
+## Table of contents
+
+### Properties
+
+- [chunkingConfig](LocalDocumentIndexConfig.md#chunkingconfig)
+- [embeddings](LocalDocumentIndexConfig.md#embeddings)
+- [folderPath](LocalDocumentIndexConfig.md#folderpath)
+- [tokenizer](LocalDocumentIndexConfig.md#tokenizer)
+
+## Properties
+
+### chunkingConfig
+
+• `Optional` **chunkingConfig**: `Partial`\<[`TextSplitterConfig`](TextSplitterConfig.md)\>
+
+Optional. Configuration settings for splitting text into chunks.
+
+#### Defined in
+
+[LocalDocumentIndex.ts:65](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L65)
+
+___
+
+### embeddings
+
+• `Optional` **embeddings**: [`EmbeddingsModel`](EmbeddingsModel.md)
+
+Optional. Embeddings model to use for generating document embeddings.
+
+#### Defined in
+
+[LocalDocumentIndex.ts:55](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L55)
+
+___
+
+### folderPath
+
+• **folderPath**: `string`
+
+Folder path where the index is stored.
+
+#### Defined in
+
+[LocalDocumentIndex.ts:50](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L50)
+
+___
+
+### tokenizer
+
+• `Optional` **tokenizer**: [`Tokenizer`](Tokenizer.md)
+
+Optional. Tokenizer to use for splitting text into tokens.
+
+#### Defined in
+
+[LocalDocumentIndex.ts:60](https://github.com/bartonmalow/vectra/blob/418123d/src/LocalDocumentIndex.ts#L60)
diff --git a/docs/interfaces/MetadataFilter.md b/docs/interfaces/MetadataFilter.md
new file mode 100644
index 0000000..194b147
--- /dev/null
+++ b/docs/interfaces/MetadataFilter.md
@@ -0,0 +1,144 @@
+[Vectra](../README.md) / [Exports](../modules.md) / MetadataFilter
+
+# Interface: MetadataFilter
+
+Filter for metadata.
+
+## Indexable
+
+▪ [key: `string`]: `unknown`
+
+## Table of contents
+
+### Properties
+
+- [$and](MetadataFilter.md#$and)
+- [$eq](MetadataFilter.md#$eq)
+- [$gt](MetadataFilter.md#$gt)
+- [$gte](MetadataFilter.md#$gte)
+- [$in](MetadataFilter.md#$in)
+- [$lt](MetadataFilter.md#$lt)
+- [$lte](MetadataFilter.md#$lte)
+- [$ne](MetadataFilter.md#$ne)
+- [$nin](MetadataFilter.md#$nin)
+- [$or](MetadataFilter.md#$or)
+
+## Properties
+
+### $and
+
+• `Optional` **$and**: [`MetadataFilter`](MetadataFilter.md)[]
+
+AND (MetadataFilter[])
+
+#### Defined in
+
+[types.ts:154](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L154)
+
+___
+
+### $eq
+
+• `Optional` **$eq**: `string` \| `number` \| `boolean`
+
+Equal to (number, string, boolean)
+
+#### Defined in
+
+[types.ts:114](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L114)
+
+___
+
+### $gt
+
+• `Optional` **$gt**: `number`
+
+Greater than (number)
+
+#### Defined in
+
+[types.ts:124](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L124)
+
+___
+
+### $gte
+
+• `Optional` **$gte**: `number`
+
+Greater than or equal to (number)
+
+#### Defined in
+
+[types.ts:129](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L129)
+
+___
+
+### $in
+
+• `Optional` **$in**: (`string` \| `number`)[]
+
+In array (string or number)
+
+#### Defined in
+
+[types.ts:144](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L144)
+
+___
+
+### $lt
+
+• `Optional` **$lt**: `number`
+
+Less than (number)
+
+#### Defined in
+
+[types.ts:134](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L134)
+
+___
+
+### $lte
+
+• `Optional` **$lte**: `number`
+
+Less than or equal to (number)
+
+#### Defined in
+
+[types.ts:139](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L139)
+
+___
+
+### $ne
+
+• `Optional` **$ne**: `string` \| `number` \| `boolean`
+
+Not equal to (number, string, boolean)
+
+#### Defined in
+
+[types.ts:119](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L119)
+
+___
+
+### $nin
+
+• `Optional` **$nin**: (`string` \| `number`)[]
+
+Not in array (string or number)
+
+#### Defined in
+
+[types.ts:149](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L149)
+
+___
+
+### $or
+
+• `Optional` **$or**: [`MetadataFilter`](MetadataFilter.md)[]
+
+OR (MetadataFilter[])
+
+#### Defined in
+
+[types.ts:159](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L159)
diff --git a/docs/interfaces/OSSEmbeddingsOptions.md b/docs/interfaces/OSSEmbeddingsOptions.md
new file mode 100644
index 0000000..772752d
--- /dev/null
+++ b/docs/interfaces/OSSEmbeddingsOptions.md
@@ -0,0 +1,140 @@
+[Vectra](../README.md) / [Exports](../modules.md) / OSSEmbeddingsOptions
+
+# Interface: OSSEmbeddingsOptions
+
+Options for OSS embeddings.
+
+## Hierarchy
+
+- [`BaseOpenAIEmbeddingsOptions`](BaseOpenAIEmbeddingsOptions.md)
+
+  ↳ **`OSSEmbeddingsOptions`**
+
+## Table of contents
+
+### Properties
+
+- [dimensions](OSSEmbeddingsOptions.md#dimensions)
+- [logRequests](OSSEmbeddingsOptions.md#logrequests)
+- [maxTokens](OSSEmbeddingsOptions.md#maxtokens)
+- [ossEndpoint](OSSEmbeddingsOptions.md#ossendpoint)
+- [ossModel](OSSEmbeddingsOptions.md#ossmodel)
+- [requestConfig](OSSEmbeddingsOptions.md#requestconfig)
+- [retryPolicy](OSSEmbeddingsOptions.md#retrypolicy)
+
+## Properties
+
+### dimensions
+
+• `Optional` **dimensions**: `number`
+
+Optional. Number of embedding dimensions to return.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[dimensions](BaseOpenAIEmbeddingsOptions.md#dimensions)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:15](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L15)
+
+___
+
+### logRequests
+
+• `Optional` **logRequests**: `boolean`
+
+Optional. Whether to log requests to the console.
+
+**`Remarks`**
+
+This is useful for debugging prompts and defaults to `false`.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[logRequests](BaseOpenAIEmbeddingsOptions.md#logrequests)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:22](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L22)
+
+___
+
+### maxTokens
+
+• `Optional` **maxTokens**: `number`
+
+Optional. Maximum number of tokens that can be sent to the embedding model.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[maxTokens](BaseOpenAIEmbeddingsOptions.md#maxtokens)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:27](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L27)
+
+___
+
+### ossEndpoint
+
+• **ossEndpoint**: `string`
+
+Optional. Endpoint to use when calling the OpenAI API.
+
+**`Remarks`**
+
+For Azure OpenAI this is the deployment endpoint.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:58](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L58)
+
+___
+
+### ossModel
+
+• **ossModel**: `string`
+
+Model to use for completion.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:51](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L51)
+
+___
+
+### requestConfig
+
+• `Optional` **requestConfig**: `AxiosRequestConfig`\<`any`\>
+
+Optional. Request options to use when calling the OpenAI API.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[requestConfig](BaseOpenAIEmbeddingsOptions.md#requestconfig)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:40](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L40)
+
+___
+
+### retryPolicy
+
+• `Optional` **retryPolicy**: `number`[]
+
+Optional. Retry policy to use when calling the OpenAI API.
+
+**`Remarks`**
+
+The default retry policy is `[2000, 5000]` which means that the first retry will be after
+2 seconds and the second retry will be after 5 seconds.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[retryPolicy](BaseOpenAIEmbeddingsOptions.md#retrypolicy)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:35](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L35)
diff --git a/docs/interfaces/OpenAICreateEmbeddingRequest.md b/docs/interfaces/OpenAICreateEmbeddingRequest.md
new file mode 100644
index 0000000..905bc08
--- /dev/null
+++ b/docs/interfaces/OpenAICreateEmbeddingRequest.md
@@ -0,0 +1,80 @@
+[Vectra](../README.md) / [Exports](../modules.md) / OpenAICreateEmbeddingRequest
+
+# Interface: OpenAICreateEmbeddingRequest
+
+OpenAI-specific embedding request.
+
+## Hierarchy
+
+- [`CreateEmbeddingRequest`](CreateEmbeddingRequest.md)
+
+  ↳ **`OpenAICreateEmbeddingRequest`**
+
+## Table of contents
+
+### Properties
+
+- [dimensions](OpenAICreateEmbeddingRequest.md#dimensions)
+- [input](OpenAICreateEmbeddingRequest.md#input)
+- [model](OpenAICreateEmbeddingRequest.md#model)
+- [user](OpenAICreateEmbeddingRequest.md#user)
+
+## Properties
+
+### dimensions
+
+• `Optional` **dimensions**: `number`
+
+Optional. Number of dimensions for the embeddings.
+
+#### Inherited from
+
+[CreateEmbeddingRequest](CreateEmbeddingRequest.md).[dimensions](CreateEmbeddingRequest.md#dimensions)
+
+#### Defined in
+
+[types.ts:242](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L242)
+
+___
+
+### input
+
+• **input**: [`CreateEmbeddingRequestInput`](../modules.md#createembeddingrequestinput)
+
+Text inputs to create embeddings for.
+
+#### Inherited from
+
+[CreateEmbeddingRequest](CreateEmbeddingRequest.md).[input](CreateEmbeddingRequest.md#input)
+
+#### Defined in
+
+[types.ts:237](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L237)
+
+___
+
+### model
+
+• **model**: `string`
+
+Model to use for creating embeddings.
+
+#### Defined in
+
+[types.ts:258](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L258)
+
+___
+
+### user
+
+• `Optional` **user**: `string`
+
+Optional. User identifier for the request.
+
+#### Inherited from
+
+[CreateEmbeddingRequest](CreateEmbeddingRequest.md).[user](CreateEmbeddingRequest.md#user)
+
+#### Defined in
+
+[types.ts:247](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L247)
diff --git a/docs/interfaces/OpenAIEmbeddingsOptions.md b/docs/interfaces/OpenAIEmbeddingsOptions.md
new file mode 100644
index 0000000..5618e8d
--- /dev/null
+++ b/docs/interfaces/OpenAIEmbeddingsOptions.md
@@ -0,0 +1,170 @@
+[Vectra](../README.md) / [Exports](../modules.md) / OpenAIEmbeddingsOptions
+
+# Interface: OpenAIEmbeddingsOptions
+
+Options for OpenAI embeddings.
+
+## Hierarchy
+
+- [`BaseOpenAIEmbeddingsOptions`](BaseOpenAIEmbeddingsOptions.md)
+
+  ↳ **`OpenAIEmbeddingsOptions`**
+
+## Table of contents
+
+### Properties
+
+- [apiKey](OpenAIEmbeddingsOptions.md#apikey)
+- [dimensions](OpenAIEmbeddingsOptions.md#dimensions)
+- [endpoint](OpenAIEmbeddingsOptions.md#endpoint)
+- [logRequests](OpenAIEmbeddingsOptions.md#logrequests)
+- [maxTokens](OpenAIEmbeddingsOptions.md#maxtokens)
+- [model](OpenAIEmbeddingsOptions.md#model)
+- [organization](OpenAIEmbeddingsOptions.md#organization)
+- [requestConfig](OpenAIEmbeddingsOptions.md#requestconfig)
+- [retryPolicy](OpenAIEmbeddingsOptions.md#retrypolicy)
+
+## Properties
+
+### apiKey
+
+• **apiKey**: `string`
+
+API key to use when calling the OpenAI API.
+
+**`Remarks`**
+
+A new API key can be created at https://platform.openai.com/account/api-keys.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:71](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L71)
+
+___
+
+### dimensions
+
+• `Optional` **dimensions**: `number`
+
+Optional. Number of embedding dimensions to return.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[dimensions](BaseOpenAIEmbeddingsOptions.md#dimensions)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:15](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L15)
+
+___
+
+### endpoint
+
+• `Optional` **endpoint**: `string`
+
+Optional. Endpoint to use when calling the OpenAI API.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:88](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L88)
+
+___
+
+### logRequests
+
+• `Optional` **logRequests**: `boolean`
+
+Optional. Whether to log requests to the console.
+
+**`Remarks`**
+
+This is useful for debugging prompts and defaults to `false`.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[logRequests](BaseOpenAIEmbeddingsOptions.md#logrequests)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:22](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L22)
+
+___
+
+### maxTokens
+
+• `Optional` **maxTokens**: `number`
+
+Optional. Maximum number of tokens that can be sent to the embedding model.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[maxTokens](BaseOpenAIEmbeddingsOptions.md#maxtokens)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:27](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L27)
+
+___
+
+### model
+
+• **model**: `string`
+
+Model to use for completion.
+
+**`Remarks`**
+
+For Azure OpenAI this is the name of the deployment to use.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:78](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L78)
+
+___
+
+### organization
+
+• `Optional` **organization**: `string`
+
+Optional. Organization to use when calling the OpenAI API.
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:83](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L83)
+
+___
+
+### requestConfig
+
+• `Optional` **requestConfig**: `AxiosRequestConfig`\<`any`\>
+
+Optional. Request options to use when calling the OpenAI API.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[requestConfig](BaseOpenAIEmbeddingsOptions.md#requestconfig)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:40](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L40)
+
+___
+
+### retryPolicy
+
+• `Optional` **retryPolicy**: `number`[]
+
+Optional. Retry policy to use when calling the OpenAI API.
+
+**`Remarks`**
+
+The default retry policy is `[2000, 5000]` which means that the first retry will be after
+2 seconds and the second retry will be after 5 seconds.
+
+#### Inherited from
+
+[BaseOpenAIEmbeddingsOptions](BaseOpenAIEmbeddingsOptions.md).[retryPolicy](BaseOpenAIEmbeddingsOptions.md#retrypolicy)
+
+#### Defined in
+
+[OpenAIEmbeddings.ts:35](https://github.com/bartonmalow/vectra/blob/418123d/src/OpenAIEmbeddings.ts#L35)
diff --git a/docs/interfaces/QueryResult.md b/docs/interfaces/QueryResult.md
new file mode 100644
index 0000000..0865d05
--- /dev/null
+++ b/docs/interfaces/QueryResult.md
@@ -0,0 +1,38 @@
+[Vectra](../README.md) / [Exports](../modules.md) / QueryResult
+
+# Interface: QueryResult\<TMetadata\>
+
+Result of a query.
+
+## Type parameters
+
+| Name | Type |
+| :------ | :------ |
+| `TMetadata` | `Record`\<`string`, [`MetadataTypes`](../modules.md#metadatatypes)\> |
+
+## Table of contents
+
+### Properties
+
+- [item](QueryResult.md#item)
+- [score](QueryResult.md#score)
+
+## Properties
+
+### item
+
+• **item**: [`IndexItem`](IndexItem.md)\<`TMetadata`\>
+
+#### Defined in
+
+[types.ts:175](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L175)
+
+___
+
+### score
+
+• **score**: `number`
+
+#### Defined in
+
+[types.ts:176](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L176)
diff --git a/docs/interfaces/TextChunk.md b/docs/interfaces/TextChunk.md
new file mode 100644
index 0000000..4710297
--- /dev/null
+++ b/docs/interfaces/TextChunk.md
@@ -0,0 +1,76 @@
+[Vectra](../README.md) / [Exports](../modules.md) / TextChunk
+
+# Interface: TextChunk
+
+Represents a chunk of text.
+
+## Table of contents
+
+### Properties
+
+- [endOverlap](TextChunk.md#endoverlap)
+- [endPos](TextChunk.md#endpos)
+- [startOverlap](TextChunk.md#startoverlap)
+- [startPos](TextChunk.md#startpos)
+- [text](TextChunk.md#text)
+- [tokens](TextChunk.md#tokens)
+
+## Properties
+
+### endOverlap
+
+• **endOverlap**: `number`[]
+
+#### Defined in
+
+[types.ts:70](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L70)
+
+___
+
+### endPos
+
+• **endPos**: `number`
+
+#### Defined in
+
+[types.ts:68](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L68)
+
+___
+
+### startOverlap
+
+• **startOverlap**: `number`[]
+
+#### Defined in
+
+[types.ts:69](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L69)
+
+___
+
+### startPos
+
+• **startPos**: `number`
+
+#### Defined in
+
+[types.ts:67](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L67)
+
+___
+
+### text
+
+• **text**: `string`
+
+#### Defined in
+
+[types.ts:65](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L65)
+
+___
+
+### tokens
+
+• **tokens**: `number`[]
+
+#### Defined in
+
+[types.ts:66](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L66)
diff --git a/docs/interfaces/TextFetcher.md b/docs/interfaces/TextFetcher.md
new file mode 100644
index 0000000..8808530
--- /dev/null
+++ b/docs/interfaces/TextFetcher.md
@@ -0,0 +1,37 @@
+[Vectra](../README.md) / [Exports](../modules.md) / TextFetcher
+
+# Interface: TextFetcher
+
+Interface for text fetcher.
+
+## Implemented by
+
+- [`FileFetcher`](../classes/FileFetcher.md)
+- [`WebFetcher`](../classes/WebFetcher.md)
+
+## Table of contents
+
+### Methods
+
+- [fetch](TextFetcher.md#fetch)
+
+## Methods
+
+### fetch
+
+▸ **fetch**(`uri`, `onDocument`): `Promise`\<`boolean`\>
+
+#### Parameters
+
+| Name | Type |
+| :------ | :------ |
+| `uri` | `string` |
+| `onDocument` | (`uri`: `string`, `text`: `string`, `docType?`: `string`) => `Promise`\<`boolean`\> |
+
+#### Returns
+
+`Promise`\<`boolean`\>
+
+#### Defined in
+
+[types.ts:78](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L78)
diff --git a/docs/interfaces/TextSplitterConfig.md b/docs/interfaces/TextSplitterConfig.md
new file mode 100644
index 0000000..312423c
--- /dev/null
+++ b/docs/interfaces/TextSplitterConfig.md
@@ -0,0 +1,76 @@
+[Vectra](../README.md) / [Exports](../modules.md) / TextSplitterConfig
+
+# Interface: TextSplitterConfig
+
+Configuration options for text splitting.
+
+## Table of contents
+
+### Properties
+
+- [chunkOverlap](TextSplitterConfig.md#chunkoverlap)
+- [chunkSize](TextSplitterConfig.md#chunksize)
+- [docType](TextSplitterConfig.md#doctype)
+- [keepSeparators](TextSplitterConfig.md#keepseparators)
+- [separators](TextSplitterConfig.md#separators)
+- [tokenizer](TextSplitterConfig.md#tokenizer)
+
+## Properties
+
+### chunkOverlap
+
+• **chunkOverlap**: `number`
+
+#### Defined in
+
+[TextSplitter.ts:14](https://github.com/bartonmalow/vectra/blob/418123d/src/TextSplitter.ts#L14)
+
+___
+
+### chunkSize
+
+• **chunkSize**: `number`
+
+#### Defined in
+
+[TextSplitter.ts:13](https://github.com/bartonmalow/vectra/blob/418123d/src/TextSplitter.ts#L13)
+
+___
+
+### docType
+
+• `Optional` **docType**: `string`
+
+#### Defined in
+
+[TextSplitter.ts:16](https://github.com/bartonmalow/vectra/blob/418123d/src/TextSplitter.ts#L16)
+
+___
+
+### keepSeparators
+
+• **keepSeparators**: `boolean`
+
+#### Defined in
+
+[TextSplitter.ts:12](https://github.com/bartonmalow/vectra/blob/418123d/src/TextSplitter.ts#L12)
+
+___
+
+### separators
+
+• **separators**: `string`[]
+
+#### Defined in
+
+[TextSplitter.ts:11](https://github.com/bartonmalow/vectra/blob/418123d/src/TextSplitter.ts#L11)
+
+___
+
+### tokenizer
+
+• **tokenizer**: [`Tokenizer`](Tokenizer.md)
+
+#### Defined in
+
+[TextSplitter.ts:15](https://github.com/bartonmalow/vectra/blob/418123d/src/TextSplitter.ts#L15)
diff --git a/docs/interfaces/Tokenizer.md b/docs/interfaces/Tokenizer.md
new file mode 100644
index 0000000..b0b37e7
--- /dev/null
+++ b/docs/interfaces/Tokenizer.md
@@ -0,0 +1,56 @@
+[Vectra](../README.md) / [Exports](../modules.md) / Tokenizer
+
+# Interface: Tokenizer
+
+Interface for tokenizer.
+
+## Implemented by
+
+- [`GPT3Tokenizer`](../classes/GPT3Tokenizer.md)
+
+## Table of contents
+
+### Methods
+
+- [decode](Tokenizer.md#decode)
+- [encode](Tokenizer.md#encode)
+
+## Methods
+
+### decode
+
+▸ **decode**(`tokens`): `string`
+
+#### Parameters
+
+| Name | Type |
+| :------ | :------ |
+| `tokens` | `number`[] |
+
+#### Returns
+
+`string`
+
+#### Defined in
+
+[types.ts:184](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L184)
+
+___
+
+### encode
+
+▸ **encode**(`text`): `number`[]
+
+#### Parameters
+
+| Name | Type |
+| :------ | :------ |
+| `text` | `string` |
+
+#### Returns
+
+`number`[]
+
+#### Defined in
+
+[types.ts:185](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L185)
diff --git a/docs/interfaces/WebFetcherConfig.md b/docs/interfaces/WebFetcherConfig.md
new file mode 100644
index 0000000..5a63570
--- /dev/null
+++ b/docs/interfaces/WebFetcherConfig.md
@@ -0,0 +1,54 @@
+[Vectra](../README.md) / [Exports](../modules.md) / WebFetcherConfig
+
+# Interface: WebFetcherConfig
+
+Configuration for the WebFetcher.
+
+## Table of contents
+
+### Properties
+
+- [headers](WebFetcherConfig.md#headers)
+- [htmlToMarkdown](WebFetcherConfig.md#htmltomarkdown)
+- [requestConfig](WebFetcherConfig.md#requestconfig)
+- [summarizeHtml](WebFetcherConfig.md#summarizehtml)
+
+## Properties
+
+### headers
+
+• `Optional` **headers**: `Record`\<`string`, `string`\>
+
+#### Defined in
+
+[WebFetcher.ts:36](https://github.com/bartonmalow/vectra/blob/418123d/src/WebFetcher.ts#L36)
+
+___
+
+### htmlToMarkdown
+
+• **htmlToMarkdown**: `boolean`
+
+#### Defined in
+
+[WebFetcher.ts:38](https://github.com/bartonmalow/vectra/blob/418123d/src/WebFetcher.ts#L38)
+
+___
+
+### requestConfig
+
+• `Optional` **requestConfig**: `AxiosRequestConfig`\<`any`\>
+
+#### Defined in
+
+[WebFetcher.ts:37](https://github.com/bartonmalow/vectra/blob/418123d/src/WebFetcher.ts#L37)
+
+___
+
+### summarizeHtml
+
+• **summarizeHtml**: `boolean`
+
+#### Defined in
+
+[WebFetcher.ts:39](https://github.com/bartonmalow/vectra/blob/418123d/src/WebFetcher.ts#L39)
diff --git a/docs/modules.md b/docs/modules.md
new file mode 100644
index 0000000..782dabd
--- /dev/null
+++ b/docs/modules.md
@@ -0,0 +1,89 @@
+[Vectra](README.md) / Exports
+
+# Vectra
+
+## Table of contents
+
+### Classes
+
+- [FileFetcher](classes/FileFetcher.md)
+- [GPT3Tokenizer](classes/GPT3Tokenizer.md)
+- [ItemSelector](classes/ItemSelector.md)
+- [LocalDocument](classes/LocalDocument.md)
+- [LocalDocumentIndex](classes/LocalDocumentIndex.md)
+- [LocalDocumentResult](classes/LocalDocumentResult.md)
+- [LocalIndex](classes/LocalIndex.md)
+- [OpenAIEmbeddings](classes/OpenAIEmbeddings.md)
+- [TextSplitter](classes/TextSplitter.md)
+- [WebFetcher](classes/WebFetcher.md)
+
+### Interfaces
+
+- [AzureOpenAIEmbeddingsOptions](interfaces/AzureOpenAIEmbeddingsOptions.md)
+- [BaseOpenAIEmbeddingsOptions](interfaces/BaseOpenAIEmbeddingsOptions.md)
+- [CreateEmbeddingRequest](interfaces/CreateEmbeddingRequest.md)
+- [CreateEmbeddingResponse](interfaces/CreateEmbeddingResponse.md)
+- [CreateEmbeddingResponseDataInner](interfaces/CreateEmbeddingResponseDataInner.md)
+- [CreateEmbeddingResponseUsage](interfaces/CreateEmbeddingResponseUsage.md)
+- [CreateIndexConfig](interfaces/CreateIndexConfig.md)
+- [DocumentCatalogStats](interfaces/DocumentCatalogStats.md)
+- [DocumentChunkMetadata](interfaces/DocumentChunkMetadata.md)
+- [DocumentQueryOptions](interfaces/DocumentQueryOptions.md)
+- [DocumentTextSection](interfaces/DocumentTextSection.md)
+- [EmbeddingsModel](interfaces/EmbeddingsModel.md)
+- [EmbeddingsResponse](interfaces/EmbeddingsResponse.md)
+- [IndexItem](interfaces/IndexItem.md)
+- [IndexStats](interfaces/IndexStats.md)
+- [LocalDocumentIndexConfig](interfaces/LocalDocumentIndexConfig.md)
+- [MetadataFilter](interfaces/MetadataFilter.md)
+- [OSSEmbeddingsOptions](interfaces/OSSEmbeddingsOptions.md)
+- [OpenAICreateEmbeddingRequest](interfaces/OpenAICreateEmbeddingRequest.md)
+- [OpenAIEmbeddingsOptions](interfaces/OpenAIEmbeddingsOptions.md)
+- [QueryResult](interfaces/QueryResult.md)
+- [TextChunk](interfaces/TextChunk.md)
+- [TextFetcher](interfaces/TextFetcher.md)
+- [TextSplitterConfig](interfaces/TextSplitterConfig.md)
+- [Tokenizer](interfaces/Tokenizer.md)
+- [WebFetcherConfig](interfaces/WebFetcherConfig.md)
+
+### Type Aliases
+
+- [CreateEmbeddingRequestInput](modules.md#createembeddingrequestinput)
+- [EmbeddingsResponseStatus](modules.md#embeddingsresponsestatus)
+- [MetadataTypes](modules.md#metadatatypes)
+
+## Type Aliases
+
+### CreateEmbeddingRequestInput
+
+Ƭ **CreateEmbeddingRequestInput**: (`string` \| `number` \| `boolean` \| ``null`` \| `object`)[] \| `number`[] \| `string`[] \| `string`
+
+Request input for creating embeddings.
+
+#### Defined in
+
+[types.ts:227](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L227)
+
+___
+
+### EmbeddingsResponseStatus
+
+Ƭ **EmbeddingsResponseStatus**: ``"success"`` \| ``"error"`` \| ``"rate_limited"`` \| ``"cancelled"``
+
+Status of an embeddings response.
+
+#### Defined in
+
+[types.ts:23](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L23)
+
+___
+
+### MetadataTypes
+
+Ƭ **MetadataTypes**: `number` \| `string` \| `boolean`
+
+Types of metadata values.
+
+#### Defined in
+
+[types.ts:168](https://github.com/bartonmalow/vectra/blob/418123d/src/types.ts#L168)
diff --git a/package-lock.json b/package-lock.json
index aee150a..c8c92de 100644
--- a/package-lock.json
+++ b/package-lock.json
@@ -1,22 +1,23 @@
 {
     "name": "vectra",
-    "version": "0.9.0",
-    "lockfileVersion": 2,
+    "version": "0.10.0",
+    "lockfileVersion": 3,
     "requires": true,
     "packages": {
         "": {
             "name": "vectra",
-            "version": "0.9.0",
+            "version": "0.10.0",
             "license": "MIT",
             "dependencies": {
-                "axios": "^1.3.4",
-                "cheerio": "^1.0.0-rc.12",
+                "axios": "^1.6.7",
+                "cheerio": "^1.0.0",
                 "dotenv": "^8.2.0",
                 "gpt-3-encoder": "1.1.4",
                 "json-colorizer": "^2.2.2",
-                "openai": "^3.2.1",
-                "turndown": "^7.1.2",
+                "openai": "^4.97.0",
+                "turndown": "^7.2.0",
                 "uuid": "^9.0.0",
+                "wink-eng-lite-web-model": "^1.8.1",
                 "wink-nlp": "^2.3.2",
                 "yargs": "^17.7.2"
             },
@@ -24,75 +25,89 @@
                 "vectra": "bin/vectra.js"
             },
             "devDependencies": {
-                "@types/assert": "^1.5.3",
+                "@microsoft/api-extractor": "^7.52.7",
+                "@types/assert": "^1.5.11",
+                "@types/cheerio": "^0.22.35",
                 "@types/mocha": "^8.2.0",
-                "@types/node": "^14.14.31",
-                "@types/turndown": "^5.0.1",
-                "@types/uuid": "9.0.1",
-                "@types/yargs": "17.0.24",
-                "mocha": "10.2.0",
+                "@types/node": "^14.18.63",
+                "@types/turndown": "^5.0.5",
+                "@types/uuid": "^9.0.8",
+                "@types/yargs": "^17.0.33",
+                "@typescript-eslint/eslint-plugin": "^8.32.0",
+                "@typescript-eslint/parser": "^8.32.0",
+                "eslint": "^8.57.0",
+                "mocha": "^10.8.2",
+                "npm-run-all": "^4.1.5",
                 "nyc": "^15.1.0",
+                "rimraf": "^6.0.1",
                 "shx": "^0.3.2",
                 "ts-mocha": "10.0.0",
+                "typedoc": "^0.24.8",
+                "typedoc-plugin-markdown": "^3.15.0",
                 "typescript": "^4.2.3",
                 "wink-bm25-text-search": "^3.1.2"
             }
         },
         "node_modules/@ampproject/remapping": {
-            "version": "2.2.1",
-            "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.2.1.tgz",
-            "integrity": "sha512-lFMjJTrFL3j7L9yBxwYfCq2k6qqwHyzuUl/XBnif78PWTJYyL/dfowQHWE3sp6U6ZzqWiiIZnpTMO96zhkjwtg==",
+            "version": "2.3.0",
+            "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.3.0.tgz",
+            "integrity": "sha512-30iZtAPgz+LTIYoeivqYo853f02jBYSd5uGnGpkFV0M3xOt9aN73erkgYAmZU43x4VfqcnLxW9Kpg3R5LC4YYw==",
             "dev": true,
+            "license": "Apache-2.0",
             "dependencies": {
-                "@jridgewell/gen-mapping": "^0.3.0",
-                "@jridgewell/trace-mapping": "^0.3.9"
+                "@jridgewell/gen-mapping": "^0.3.5",
+                "@jridgewell/trace-mapping": "^0.3.24"
             },
             "engines": {
                 "node": ">=6.0.0"
             }
         },
         "node_modules/@babel/code-frame": {
-            "version": "7.22.10",
-            "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.22.10.tgz",
-            "integrity": "sha512-/KKIMG4UEL35WmI9OlvMhurwtytjvXoFcGNrOvyG9zIzA8YmPjVtIZUf7b05+TPO7G7/GEmLHDaoCgACHl9hhA==",
+            "version": "7.27.1",
+            "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.27.1.tgz",
+            "integrity": "sha512-cjQ7ZlQ0Mv3b47hABuTevyTuYN4i+loJKGeV9flcCgIK37cCXRh+L1bd3iBHlynerhQ7BhCkn2BPbQUL+rGqFg==",
             "dev": true,
+            "license": "MIT",
             "dependencies": {
-                "@babel/highlight": "^7.22.10",
-                "chalk": "^2.4.2"
+                "@babel/helper-validator-identifier": "^7.27.1",
+                "js-tokens": "^4.0.0",
+                "picocolors": "^1.1.1"
             },
             "engines": {
                 "node": ">=6.9.0"
             }
         },
         "node_modules/@babel/compat-data": {
-            "version": "7.22.9",
-            "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.22.9.tgz",
-            "integrity": "sha512-5UamI7xkUcJ3i9qVDS+KFDEK8/7oJ55/sJMB1Ge7IEapr7KfdfV/HErR+koZwOfd+SgtFKOKRhRakdg++DcJpQ==",
+            "version": "7.27.2",
+            "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.27.2.tgz",
+            "integrity": "sha512-TUtMJYRPyUb/9aU8f3K0mjmjf6M9N5Woshn2CS6nqJSeJtTtQcpLUXjGt9vbF8ZGff0El99sWkLgzwW3VXnxZQ==",
             "dev": true,
+            "license": "MIT",
             "engines": {
                 "node": ">=6.9.0"
             }
         },
         "node_modules/@babel/core": {
-            "version": "7.22.10",
-            "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.22.10.tgz",
-            "integrity": "sha512-fTmqbbUBAwCcre6zPzNngvsI0aNrPZe77AeqvDxWM9Nm+04RrJ3CAmGHA9f7lJQY6ZMhRztNemy4uslDxTX4Qw==",
+            "version": "7.27.1",
+            "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.27.1.tgz",
+            "integrity": "sha512-IaaGWsQqfsQWVLqMn9OB92MNN7zukfVA4s7KKAI0KfrrDsZ0yhi5uV4baBuLuN7n3vsZpwP8asPPcVwApxvjBQ==",
             "dev": true,
+            "license": "MIT",
             "dependencies": {
                 "@ampproject/remapping": "^2.2.0",
-                "@babel/code-frame": "^7.22.10",
-                "@babel/generator": "^7.22.10",
-                "@babel/helper-compilation-targets": "^7.22.10",
-                "@babel/helper-module-transforms": "^7.22.9",
-                "@babel/helpers": "^7.22.10",
-                "@babel/parser": "^7.22.10",
-                "@babel/template": "^7.22.5",
-                "@babel/traverse": "^7.22.10",
-                "@babel/types": "^7.22.10",
-                "convert-source-map": "^1.7.0",
+                "@babel/code-frame": "^7.27.1",
+                "@babel/generator": "^7.27.1",
+                "@babel/helper-compilation-targets": "^7.27.1",
+                "@babel/helper-module-transforms": "^7.27.1",
+                "@babel/helpers": "^7.27.1",
+                "@babel/parser": "^7.27.1",
+                "@babel/template": "^7.27.1",
+                "@babel/traverse": "^7.27.1",
+                "@babel/types": "^7.27.1",
+                "convert-source-map": "^2.0.0",
                 "debug": "^4.1.0",
                 "gensync": "^1.0.0-beta.2",
-                "json5": "^2.2.2",
+                "json5": "^2.2.3",
                 "semver": "^6.3.1"
             },
             "engines": {
@@ -103,30 +118,40 @@
                 "url": "https://opencollective.com/babel"
             }
         },
+        "node_modules/@babel/core/node_modules/convert-source-map": {
+            "version": "2.0.0",
+            "resolved": "https://registry.npmjs.org/convert-source-map/-/convert-source-map-2.0.0.tgz",
+            "integrity": "sha512-Kvp459HrV2FEJ1CAsi1Ku+MY3kasH19TFykTz2xWmMeq6bk2NU3XXvfJ+Q61m0xktWwt+1HSYf3JZsTms3aRJg==",
+            "dev": true,
+            "license": "MIT"
+        },
         "node_modules/@babel/generator": {
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             }
         },
-        "yn": {
+        "node_modules/yn": {
             "version": "2.0.0",
             "resolved": "https://registry.npmjs.org/yn/-/yn-2.0.0.tgz",
             "integrity": "sha512-uTv8J/wiWTgUTg+9vLTi//leUl5vDQS6uii/emeTb2ssY7vl6QWf2fFbIIGjnhjvbdKlU0ed7QPgY1htTC86jQ==",
-            "dev": true
+            "dev": true,
+            "license": "MIT",
+            "engines": {
+                "node": ">=4"
+            }
         },
-        "yocto-queue": {
+        "node_modules/yocto-queue": {
             "version": "0.1.0",
             "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz",
             "integrity": "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==",
-            "dev": true
+            "dev": true,
+            "license": "MIT",
+            "engines": {
+                "node": ">=10"
+            },
+            "funding": {
+                "url": "https://github.com/sponsors/sindresorhus"
+            }
         }
     }
 }
diff --git a/package.json b/package.json
index 5721a93..81854e7 100644
--- a/package.json
+++ b/package.json
@@ -27,41 +27,51 @@
         }
     },
     "dependencies": {
-        "axios": "^1.3.4",
-        "cheerio": "^1.0.0-rc.12",
+        "axios": "^1.6.7",
+        "cheerio": "^1.0.0",
         "dotenv": "^8.2.0",
         "gpt-3-encoder": "1.1.4",
         "json-colorizer": "^2.2.2",
-        "openai": "^3.2.1",
-        "turndown": "^7.1.2",
+        "openai": "^4.97.0",
+        "turndown": "^7.2.0",
         "uuid": "^9.0.0",
+        "wink-eng-lite-web-model": "^1.8.1",
         "wink-nlp": "^2.3.2",
         "yargs": "^17.7.2"
     },
     "resolutions": {},
     "devDependencies": {
-        "@types/assert": "^1.5.3",
+        "@microsoft/api-extractor": "^7.52.7",
+        "@types/assert": "^1.5.11",
+        "@types/cheerio": "^0.22.35",
         "@types/mocha": "^8.2.0",
-        "@types/node": "^14.14.31",
-        "@types/turndown": "^5.0.1",
-        "@types/uuid": "9.0.1",
-        "@types/yargs": "17.0.24",
-        "mocha": "10.2.0",
+        "@types/node": "^14.18.63",
+        "@types/turndown": "^5.0.5",
+        "@types/uuid": "^9.0.8",
+        "@types/yargs": "^17.0.33",
+        "@typescript-eslint/eslint-plugin": "^8.32.0",
+        "@typescript-eslint/parser": "^8.32.0",
+        "eslint": "^8.57.0",
+        "mocha": "^10.8.2",
+        "npm-run-all": "^4.1.5",
         "nyc": "^15.1.0",
+        "rimraf": "^6.0.1",
         "shx": "^0.3.2",
         "ts-mocha": "10.0.0",
+        "typedoc": "^0.24.8",
+        "typedoc-plugin-markdown": "^3.15.0",
         "typescript": "^4.2.3",
         "wink-bm25-text-search": "^3.1.2"
     },
     "scripts": {
         "build": "tsc -b",
-        "build-docs": "typedoc --theme markdown --entryPoint botbuilder-m365 --excludePrivate --includeDeclarations --ignoreCompilerErrors --module amd --out ..\\..\\doc\\botbuilder-ai .\\lib\\index.d.ts --hideGenerator --name \"Bot Builder SDK - AI\" --readme none",
-        "build:rollup": "yarn clean && yarn build && api-extractor run --verbose --local",
+        "build-docs": "typedoc --plugin typedoc-plugin-markdown --entryPoints ./src --excludePrivate --excludeInternal --out ./docs --hideGenerator --name \"Vectra\" --readme README.md",
+        "build:rollup": "npm run clean && npm install && npm run build && mkdir -p lib/api-report && npx api-extractor run --verbose --local",
         "clean": "rimraf _ts3.4 lib tsconfig.tsbuildinfo node_modules",
-        "depcheck": "depcheck --config ../../.depcheckrc",
-        "lint": "eslint **/src/**/*.{j,t}s{,x} --fix --no-error-on-unmatched-pattern",
+        "depcheck": "depcheck",
+        "lint": "eslint \"src/**/*.ts\" --fix",
         "test": "npm-run-all build test:mocha",
-        "test:mocha": "nyc mocha tests",
+        "test:mocha": "nyc ts-mocha -p tsconfig.test.json tests/**/*.test.ts",
         "test:compat": "api-extractor run --verbose"
     },
     "files": [
diff --git a/src/FileFetcher.ts b/src/FileFetcher.ts
index 18627f1..ee66038 100644
--- a/src/FileFetcher.ts
+++ b/src/FileFetcher.ts
@@ -1,7 +1,11 @@
-import { TextFetcher } from './types';
-import * as fs from 'fs/promises';
-import * as path from 'path';
+import { TextFetcher } from "./types";
+import * as fs from "fs/promises";
+import * as path from "path";
 
+/**
+ * Fetches text content from local files.
+ * @public
+ */
 export class FileFetcher implements TextFetcher {
     public async fetch(uri: string, onDocument: (uri: string, text: string, docType?: string | undefined) => Promise<boolean>): Promise<boolean> {
         // Does path exist and is it a directory?
@@ -23,8 +27,8 @@ export class FileFetcher implements TextFetcher {
             return true;
         } else {
             // Read file and call onDocument
-            const text = await fs.readFile(uri, 'utf8');
-            const parts = uri.split('.');
+            const text = await fs.readFile(uri, "utf8");
+            const parts = uri.split(".");
             return await onDocument(uri, text, parts.length > 0 ? parts[parts.length - 1].toLowerCase() : undefined);
         }
     }
diff --git a/src/GPT3Tokenizer.ts b/src/GPT3Tokenizer.ts
index dcd75c9..c7a4664 100644
--- a/src/GPT3Tokenizer.ts
+++ b/src/GPT3Tokenizer.ts
@@ -2,7 +2,8 @@ import { Tokenizer } from "./types";
 import { encode, decode } from "gpt-3-encoder";
 
 /**
- * Tokenizer that uses GPT-3's encoder.
+ * Tokenizer that uses the GPT-3 tokenizer.
+ * @public
  */
 export class GPT3Tokenizer implements Tokenizer {
     public decode(tokens: number[]): string {
diff --git a/src/ItemSelector.ts b/src/ItemSelector.ts
index 36dd04f..2ebf493 100644
--- a/src/ItemSelector.ts
+++ b/src/ItemSelector.ts
@@ -1,26 +1,32 @@
-import { MetadataFilter, MetadataTypes } from './types';
+import { MetadataFilter, MetadataTypes } from "./types";
 
+/**
+ * Utility class for selecting and comparing items.
+ * @public
+ */
 export class ItemSelector {
     /**
      * Returns the similarity between two vectors using the cosine similarity.
-     * @param vector1 Vector 1
-     * @param vector2 Vector 2
+     * @param vector1 - Vector 1
+     * @param vector2 - Vector 2
      * @returns Similarity between the two vectors
+     * @public
      */
-    public static cosineSimilarity(vector1: number[], vector2: number[]) {
+    public static cosineSimilarity(vector1: number[], vector2: number[]): number {
         // Return the quotient of the dot product and the product of the norms
         return this.dotProduct(vector1, vector2) / (this.normalize(vector1) * this.normalize(vector2));
     }
 
     /**
      * Normalizes a vector.
+     * @param vector - Vector to normalize
+     * @returns Normalized vector
      * @remarks
      * The norm of a vector is the square root of the sum of the squares of the elements.
      * The LocalIndex pre-normalizes all vectors to improve performance.
-     * @param vector Vector to normalize
-     * @returns Normalized vector
+     * @public
      */
-    public static normalize(vector: number[]) {
+    public static normalize(vector: number[]): number {
         // Initialize a variable to store the sum of the squares
         let sum = 0;
         // Loop through the elements of the array
@@ -34,25 +40,24 @@ export class ItemSelector {
 
     /**
      * Returns the similarity between two vectors using cosine similarity.
-     * @remarks
-     * The LocalIndex pre-normalizes all vectors to improve performance.
-     * This method uses the pre-calculated norms to improve performance.
-     * @param vector1 Vector 1
-     * @param norm1 Norm of vector 1
-     * @param vector2 Vector 2
-     * @param norm2 Norm of vector 2
+     * @param vector1 - Vector 1
+     * @param vector2 - Vector 2
+     * @param norm1 - Norm of vector 1
+     * @param norm2 - Norm of vector 2
      * @returns Similarity between the two vectors
+     * @public
      */
-    public static normalizedCosineSimilarity(vector1: number[], norm1: number, vector2: number[], norm2: number) {
+    public static normalizedCosineSimilarity(vector1: number[], vector2: number[], norm1: number, norm2: number): number {
         // Return the quotient of the dot product and the product of the norms
         return this.dotProduct(vector1, vector2) / (norm1 * norm2);
     }
 
     /**
-     * Applies a filter to the metadata of an item.
-     * @param metadata Metadata of the item
-     * @param filter Filter to apply
-     * @returns True if the item matches the filter, false otherwise
+     * Returns true if the metadata matches the filter.
+     * @param metadata - Metadata to check
+     * @param filter - Filter to apply
+     * @returns True if the metadata matches the filter
+     * @public
      */
     public static select(metadata: Record<string, MetadataTypes>, filter: MetadataFilter): boolean {
         if (filter === undefined || filter === null) {
@@ -61,30 +66,31 @@ export class ItemSelector {
 
         for (const key in filter) {
             switch (key) {
-                case '$and':
-                    if (!filter[key]!.every((f: MetadataFilter) => this.select(metadata, f))) {
+            case "$and":
+                if (!filter[key]!.every((f: MetadataFilter) => this.select(metadata, f))) {
+                    return false;
+                }
+                break;
+            case "$or":
+                if (!filter[key]!.some((f: MetadataFilter) => this.select(metadata, f))) {
+                    return false;
+                }
+                break;
+            default: {
+                const value = filter[key];
+                if (value === undefined || value === null) {
+                    return false;
+                } else if (typeof value == "object") {
+                    if (!this.metadataFilter(metadata[key], value as MetadataFilter)) {
                         return false;
                     }
-                    break;
-                case '$or':
-                    if (!filter[key]!.some((f: MetadataFilter) => this.select(metadata, f))) {
+                } else {
+                    if (metadata[key] !== value) {
                         return false;
                     }
-                    break;
-                default:
-                    const value = filter[key];
-                    if (value === undefined || value === null) {
-                        return false;
-                    } else if (typeof value == 'object') {
-                        if (!this.metadataFilter(metadata[key], value as MetadataFilter)) {
-                            return false;
-                        }
-                    } else {
-                        if (metadata[key] !== value) {
-                            return false;
-                        }
-                    }
-                    break;
+                }
+                break;
+            }
             }
         }
         return true;
@@ -109,58 +115,58 @@ export class ItemSelector {
 
         for (const key in filter) {
             switch (key) {
-                case '$eq':
-                    if (value !== filter[key]) {
-                        return false;
-                    }
-                    break;
-                case '$ne':
-                    if (value === filter[key]) {
-                        return false;
-                    }
-                    break;
-                case '$gt':
-                    if (typeof value != 'number' || value <= filter[key]!) {
-                        return false;
-                    }
-                    break;
-                case '$gte':
-                    if (typeof value != 'number' || value < filter[key]!) {
-                        return false;
-                    }
-                    break;
-                case '$lt':
-                    if (typeof value != 'number' || value >= filter[key]!) {
-                        return false;
-                    }
-                    break;
-                case '$lte':
-                    if (typeof value != 'number' || value > filter[key]!) {
-                        return false;
-                    }
-                    break;
-                case '$in':
-                    if (typeof value == 'boolean') {
-                        return false;
-                    } else if(typeof value == 'string' && !filter[key]!.includes(value)){
-                        return false
-                    } else if(!filter[key]!.some(val => typeof val == 'string' && val.includes(value as string))){
-                        return false
-                    }
-                    break;
-                case '$nin':
-                    if (typeof value == 'boolean') {
-                        return false;
-                    }
-                    else if (typeof value == 'string' && filter[key]!.includes(value)) {
-                        return false;
-                    }
-                    else if (filter[key]!.some(val => typeof val == 'string' && val.includes(value as string))) {
-                        return false;
-                    }
-                    break;
-                default:
-                    return value === filter[key];
+            case "$eq":
+                if (value !== filter[key]) {
+                    return false;
+                }
+                break;
+            case "$ne":
+                if (value === filter[key]) {
+                    return false;
+                }
+                break;
+            case "$gt":
+                if (typeof value != "number" || value <= filter[key]!) {
+                    return false;
+                }
+                break;
+            case "$gte":
+                if (typeof value != "number" || value < filter[key]!) {
+                    return false;
+                }
+                break;
+            case "$lt":
+                if (typeof value != "number" || value >= filter[key]!) {
+                    return false;
+                }
+                break;
+            case "$lte":
+                if (typeof value != "number" || value > filter[key]!) {
+                    return false;
+                }
+                break;
+            case "$in":
+                if (typeof value == "boolean") {
+                    return false;
+                } else if(typeof value == "string" && !filter[key]!.includes(value)){
+                    return false;
+                } else if(!filter[key]!.some(val => typeof val == "string" && val.includes(value as string))){
+                    return false;
+                }
+                break;
+            case "$nin":
+                if (typeof value == "boolean") {
+                    return false;
+                }
+                else if (typeof value == "string" && filter[key]!.includes(value)) {
+                    return false;
+                }
+                else if (filter[key]!.some(val => typeof val == "string" && val.includes(value as string))) {
+                    return false;
+                }
+                break;
+            default:
+                return value === filter[key];
             }
         }
         return true;
diff --git a/src/LocalDocument.ts b/src/LocalDocument.ts
index 49dcc3a..ee0b436 100644
--- a/src/LocalDocument.ts
+++ b/src/LocalDocument.ts
@@ -1,27 +1,28 @@
-import * as fs from 'fs/promises';
-import * as path from 'path';
-import { MetadataTypes } from './types';
-import { LocalDocumentIndex } from './LocalDocumentIndex';
+import * as fs from "fs/promises";
+import * as path from "path";
+import { MetadataTypes } from "./types";
+import { LocalDocumentIndex } from "./LocalDocumentIndex";
 
 /**
- * Represents an indexed document stored on disk.
+ * Represents a document stored in a local index.
+ * @public
  */
 export class LocalDocument {
     private readonly _index: LocalDocumentIndex;
-    private readonly _id: string;
+    private readonly _documentId: string;
     private readonly _uri: string;
     private _metadata: Record<string,MetadataTypes>|undefined;
-    private _text: string|undefined;
+    private _text?: string;
 
     /**
-     * Creates a new `LocalDocument` instance.
-     * @param index Parent index that contains the document.
-     * @param id ID of the document.
-     * @param uri URI of the document.
+     * Creates a new instance of LocalDocument.
+     * @param index - The document index this document belongs to.
+     * @param documentId - The ID of the document.
+     * @param uri - The URI of the document.
      */
-    public constructor(index: LocalDocumentIndex, id: string, uri: string) {
+    public constructor(index: LocalDocumentIndex, documentId: string, uri: string) {
         this._index = index;
-        this._id = id;
+        this._documentId = documentId;
         this._uri = uri;
     }
 
@@ -36,7 +37,7 @@ export class LocalDocument {
      * Returns the ID of the document.
      */
     public get id(): string {
-        return this._id;
+        return this._documentId;
     }
 
     /**
@@ -69,7 +70,7 @@ export class LocalDocument {
         try {
             await fs.access(path.join(this.folderPath, `${this.id}.json`));
             return true;
-        } catch (err: unknown) {
+        } catch {
             return false;
         }
     }
@@ -83,14 +84,14 @@ export class LocalDocument {
             let json: string;
             try {
                 json = (await fs.readFile(path.join(this.folderPath, `${this.id}.json`))).toString();
-            } catch (err: unknown) {
-                throw new Error(`Error reading metadata for document "${this.uri}": ${(err as any).toString()}`);
+            } catch (error: unknown) {
+                throw new Error(`Error reading metadata for document "${this.uri}": ${error instanceof Error ? error.message : String(error)}`);
             }
 
             try {
                 this._metadata = JSON.parse(json);
-            } catch (err: unknown) {
-                throw new Error(`Error parsing metadata for document "${this.uri}": ${(err as any).toString()}`);
+            } catch (error: unknown) {
+                throw new Error(`Error parsing metadata for document "${this.uri}": ${error instanceof Error ? error.message : String(error)}`);
             }
         }
 
@@ -105,8 +106,8 @@ export class LocalDocument {
         if (this._text == undefined) {
             try {
                 this._text = (await fs.readFile(path.join(this.folderPath, `${this.id}.txt`))).toString();
-            } catch (err: unknown) {
-                throw new Error(`Error reading text file for document "${this.uri}": ${(err as any).toString()}`);
+            } catch (error: unknown) {
+                throw new Error(`Error reading text file for document "${this.uri}": ${error instanceof Error ? error.message : String(error)}`);
             }
         }
 
diff --git a/src/LocalDocumentIndex.ts b/src/LocalDocumentIndex.ts
index af05a40..2a11663 100644
--- a/src/LocalDocumentIndex.ts
+++ b/src/LocalDocumentIndex.ts
@@ -1,15 +1,16 @@
-import * as fs from 'fs/promises';
-import * as path from 'path';
-import { v4 } from 'uuid';
+import * as fs from "fs/promises";
+import * as path from "path";
+import { v4 } from "uuid";
 import { GPT3Tokenizer } from "./GPT3Tokenizer";
 import { CreateIndexConfig, LocalIndex } from "./LocalIndex";
 import { TextSplitter, TextSplitterConfig } from "./TextSplitter";
 import { MetadataFilter, EmbeddingsModel, Tokenizer, MetadataTypes, EmbeddingsResponse, QueryResult, DocumentChunkMetadata, DocumentCatalogStats } from "./types";
-import { LocalDocumentResult } from './LocalDocumentResult';
-import { LocalDocument } from './LocalDocument';
+import { LocalDocumentResult } from "./LocalDocumentResult";
+import { LocalDocument } from "./LocalDocument";
 
 /**
- * Options for querying documents in the index.
+ * Options for querying documents.
+ * @public
  */
 export interface DocumentQueryOptions {
     /**
@@ -39,7 +40,8 @@ export interface DocumentQueryOptions {
 }
 
 /**
- * Configuration settings for a local document index.
+ * Configuration for a local document index.
+ * @public
  */
 export interface LocalDocumentIndexConfig {
     /**
@@ -65,6 +67,7 @@ export interface LocalDocumentIndexConfig {
 
 /**
  * Represents a local index of documents stored on disk.
+ * @public
  */
 export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
     private readonly _embeddings?: EmbeddingsModel;
@@ -74,8 +77,8 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
     private _newCatalog?: DocumentCatalog;
 
     /**
-     * Creates a new `LocalDocumentIndex` instance.
-     * @param config Configuration settings for the document index.
+     * Creates a new instance of LocalDocumentIndex.
+     * @param config - Configuration settings for the document index.
      */
     public constructor(config: LocalDocumentIndexConfig) {
         super(config.folderPath);
@@ -90,35 +93,42 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
     }
 
     /**
-     * Returns the embeddings model used by the index (if configured.)
+     * Gets the embeddings model.
+     * @returns The embeddings model
+     * @public
      */
     public get embeddings(): EmbeddingsModel | undefined {
         return this._embeddings;
     }
 
     /**
-     * Returns the tokenizer used by the index.
+     * Gets the tokenizer.
+     * @returns The tokenizer
+     * @public
      */
     public get tokenizer(): Tokenizer {
         return this._tokenizer;
     }
 
     /**
-     * Returns true if the document catalog exists.
+     * Checks if the document catalog exists.
+     * @returns True if the catalog exists, false otherwise
+     * @public
      */
     public async isCatalogCreated(): Promise<boolean> {
         try {
-            await fs.access(path.join(this.folderPath, 'catalog.json'));
+            await fs.access(path.join(this.folderPath, "catalog.json"));
             return true;
-        } catch (err: unknown) {
+        } catch {
             return false;
         }
     }
 
     /**
-     * Returns the document ID for the given URI.
-     * @param uri URI of the document to lookup.
-     * @returns Document ID or undefined if not found.
+     * Gets the document ID for a URI.
+     * @param uri - The URI to get the document ID for
+     * @returns The document ID, or undefined if not found
+     * @public
      */
     public async getDocumentId(uri: string): Promise<string | undefined> {
         await this.loadIndexData();
@@ -126,9 +136,10 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
     }
 
     /**
-     * Returns the document URI for the given ID.
-     * @param documentId ID of the document to lookup.
-     * @returns Document URI or undefined if not found.
+     * Gets the document URI for a document ID.
+     * @param documentId - The document ID to get the URI for
+     * @returns The document URI, or undefined if not found
+     * @public
      */
     public async getDocumentUri(documentId: string): Promise<string | undefined> {
         await this.loadIndexData();
@@ -136,11 +147,12 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
     }
 
     /**
-     * Loads the document catalog from disk and returns its stats.
-     * @returns Catalog stats.
+     * Gets the catalog statistics.
+     * @returns The catalog statistics
+     * @public
      */
     public async getCatalogStats(): Promise<DocumentCatalogStats> {
-        const stats = await this.getIndexStats()
+        const stats = await this.getIndexStats();
         return {
             version: this._catalog!.version,
             documents: this._catalog!.count,
@@ -151,7 +163,7 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
 
     /**
      * Deletes a document from the index.
-     * @param uri URI of the document to delete.
+     * @param uri - URI of the document to delete.
      */
     public async deleteDocument(uri: string): Promise<void> {
         // Lookup document ID
@@ -181,39 +193,37 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
         } catch (err: unknown) {
             // Cancel update and raise error
             this.cancelUpdate();
-            throw new Error(`Error deleting document "${uri}": ${(err as any).toString()}`);
+            throw new Error(`Error deleting document "${uri}": ${err instanceof Error ? err.message : String(err)}`);
         }
 
         // Delete text file from disk
         try {
             await fs.unlink(path.join(this.folderPath, `${documentId}.txt`));
         } catch (err: unknown) {
-            throw new Error(`Error removing text file for document "${uri}" from disk: ${(err as any).toString()}`);
+            throw new Error(`Error removing text file for document "${uri}" from disk: ${err instanceof Error ? err.message : String(err)}`);
         }
 
         // Delete metadata file from disk
         try {
             await fs.unlink(path.join(this.folderPath, `${documentId}.json`));
-        } catch (err: unknown) {
+        } catch {
             // Ignore error
         }
     }
 
     /**
-     * Adds a document to the catalog.
-     * @remarks
-     * A new update is started if one is not already in progress. If an document with the same uri
-     * already exists, it will be replaced.
-     * @param uri - Document URI
-     * @param text - Document text
-     * @param docType - Optional. Document type
-     * @param metadata - Optional. Document metadata to index
-     * @returns Inserted document
+     * Upserts a document into the index.
+     * @param uri - URI of the document
+     * @param text - Text of the document
+     * @param docType - Optional. Type of the document
+     * @param metadata - Optional. Metadata for the document
+     * @returns The upserted document
+     * @public
      */
     public async upsertDocument(uri: string, text: string, docType?: string, metadata?: Record<string, MetadataTypes>): Promise<LocalDocument> {
         // Ensure embeddings configured
         if (!this._embeddings) {
-            throw new Error(`Embeddings model not configured.`);
+            throw new Error("Embeddings model not configured.");
         }
 
         // Check for existing document ID
@@ -230,7 +240,7 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
         const config = Object.assign({ docType }, this._chunkingConfig);
         if (config.docType == undefined) {
             // Populate docType based on extension
-            const pos = uri.lastIndexOf('.');
+            const pos = uri.lastIndexOf(".");
             if (pos >= 0) {
                 const ext = uri.substring(pos + 1).toLowerCase();
                 config.docType = ext;
@@ -252,7 +262,7 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
                 currentBatch = [];
                 totalTokens = chunk.tokens.length;
             }
-            currentBatch.push(chunk.text.replace(/\n/g, ' '));
+            currentBatch.push(chunk.text.replace(/\n/g, " "));
         }
         if (currentBatch.length > 0) {
             chunkBatches.push(currentBatch);
@@ -265,11 +275,11 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
             try {
                 response = await this._embeddings.createEmbeddings(batch);
             } catch (err: unknown) {
-                throw new Error(`Error generating embeddings: ${(err as any).toString()}`);
+                throw new Error(`Error generating embeddings: ${err instanceof Error ? err.message : String(err)}`);
             }
 
             // Check for error
-            if (response.status != 'success') {
+            if (response.status != "success") {
                 throw new Error(`Error generating embeddings: ${response.message}`);
             }
 
@@ -316,7 +326,7 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
         } catch (err: unknown) {
             // Cancel update and raise error
             this.cancelUpdate();
-            throw new Error(`Error adding document "${uri}": ${(err as any).toString()}`);
+            throw new Error(`Error adding document "${uri}": ${err instanceof Error ? err.message : String(err)}`);
         }
 
         // Return document
@@ -324,10 +334,9 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
     }
     
     /**
-     * Returns all documents in the index.
-     * @remarks
-     * Each document will contain all of the documents indexed chunks.
-     * @returns Array of documents.
+     * Lists all documents in the index.
+     * @returns Array of document results
+     * @public
      */
     public async listDocuments(): Promise<LocalDocumentResult[]> {
         // Sort chunks by document ID
@@ -354,59 +363,54 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
 
     /**
      * Queries the index for documents similar to the given query.
-     * @param query Text to query for.
-     * @param options Optional. Query options.
-     * @returns Array of document results.
+     * @param query - Text to query for
+     * @param options - Optional. Query options
+     * @returns Array of document results
+     * @public
      */
     public async queryDocuments(query: string, options?: DocumentQueryOptions): Promise<LocalDocumentResult[]> {
         // Ensure embeddings configured
         if (!this._embeddings) {
-            throw new Error(`Embeddings model not configured.`);
+            throw new Error("Embeddings model not configured.");
         }
 
-        // Ensure options are defined
-        options = Object.assign({
-            maxDocuments: 10,
-            maxChunks: 50,
-        }, options);
-
-        // Generate embeddings for query
-        let embeddings: EmbeddingsResponse;
-        try {
-            embeddings = await this._embeddings.createEmbeddings(query.replace(/\n/g, ' '));
-        } catch (err: unknown) {
-            throw new Error(`Error generating embeddings for query: ${(err as any).toString()}`);
-        }
+        // Get query options
+        const maxDocuments = options?.maxDocuments ?? 10;
+        const maxChunks = options?.maxChunks ?? 50;
+        const filter = options?.filter;
+        const isBm25 = options?.isBm25 ?? false;
 
-        // Check for error
-        if (embeddings.status != 'success') {
-            throw new Error(`Error generating embeddings for query: ${embeddings.message}`);
+        // Create query embedding
+        const response = await this._embeddings.createEmbeddings(query);
+        if (response.status !== "success") {
+            throw new Error(`Error creating query embedding: ${response.message}`);
         }
 
-        // Query index for chunks
-        const results = await this.queryItems(embeddings.output![0], query, options.maxChunks!, options.filter, options.isBm25);
+        // Query index
+        const queryVector = response.output![0];
+        const chunks = await this.queryItems<DocumentChunkMetadata>(queryVector, query, maxChunks, filter, isBm25);
 
         // Group chunks by document
-        const documentChunks: { [documentId: string]: QueryResult<DocumentChunkMetadata>[]; } = {};
-        for (const result  of results) {
-            const metadata = result.item.metadata;
-            if (documentChunks[metadata.documentId] == undefined) {
-                documentChunks[metadata.documentId] = [];
+        const documents = new Map<string, { uri: string; chunks: QueryResult<DocumentChunkMetadata>[]; score: number }>();
+        for (const chunk of chunks) {
+            const documentId = chunk.item.metadata.documentId;
+            const uri = await this.getDocumentUri(documentId);
+            if (uri) {
+                let document = documents.get(documentId);
+                if (!document) {
+                    document = { uri, chunks: [], score: 0 };
+                    documents.set(documentId, document);
+                }
+                document.chunks.push(chunk);
+                document.score = Math.max(document.score, chunk.score);
             }
-            documentChunks[metadata.documentId].push(result);
         }
 
-        // Create a document result for each document
-        const documentResults: LocalDocumentResult[] = [];
-        for (const documentId in documentChunks) {
-            const chunks = documentChunks[documentId];
-            const uri = await this.getDocumentUri(documentId) as string;
-            const documentResult = new LocalDocumentResult(this, documentId, uri, chunks, this._tokenizer);
-            documentResults.push(documentResult);
-        }
-
-        // Sort document results by score and return top results
-        return documentResults.sort((a, b) => b.score - a.score).slice(0, options.maxDocuments!);
+        // Sort documents by score and return results
+        return Array.from(documents.values())
+            .sort((a, b) => b.score - a.score)
+            .slice(0, maxDocuments)
+            .map(doc => new LocalDocumentResult(this, doc.uri, doc.uri, doc.chunks, this._tokenizer));
     }
 
     // Overrides
@@ -431,11 +435,11 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
 
         try {
             // Save catalog
-            await fs.writeFile(path.join(this.folderPath, 'catalog.json'), JSON.stringify(this._newCatalog));
+            await fs.writeFile(path.join(this.folderPath, "catalog.json"), JSON.stringify(this._newCatalog));
             this._catalog = this._newCatalog;
             this._newCatalog = undefined;
-        } catch(err: unknown) {
-            throw new Error(`Error saving document catalog: ${(err as any).toString()}`);
+        } catch (err: unknown) {
+            throw new Error(`Error saving document catalog: ${err instanceof Error ? err.message : String(err)}`);
         }
     }
 
@@ -446,7 +450,7 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
             return;
         }
 
-        const catalogPath = path.join(this.folderPath, 'catalog.json');
+        const catalogPath = path.join(this.folderPath, "catalog.json");
         if (await this.isCatalogCreated()) {
             // Load catalog
             const buffer = await fs.readFile(catalogPath);
@@ -461,8 +465,8 @@ export class LocalDocumentIndex extends LocalIndex<DocumentChunkMetadata> {
                     idToUri: {},
                 };
                 await fs.writeFile(catalogPath, JSON.stringify(this._catalog));
-            } catch(err: unknown) {
-                throw new Error(`Error creating document catalog: ${(err as any).toString()}`);
+            } catch (err: unknown) {
+                throw new Error(`Error creating document catalog: ${err instanceof Error ? err.message : String(err)}`);
             }
         }
     }
diff --git a/src/LocalDocumentResult.ts b/src/LocalDocumentResult.ts
index c3331fe..543fd36 100644
--- a/src/LocalDocumentResult.ts
+++ b/src/LocalDocumentResult.ts
@@ -3,19 +3,24 @@ import { LocalDocumentIndex } from "./LocalDocumentIndex";
 import { QueryResult, DocumentChunkMetadata, Tokenizer, DocumentTextSection } from "./types";
 
 /**
- * Represents a search result for a document stored on disk.
+ * Represents the result of a document query.
+ * @public
  */
 export class LocalDocumentResult extends LocalDocument {
     private readonly _chunks: QueryResult<DocumentChunkMetadata>[];
     private readonly _tokenizer: Tokenizer;
-    private readonly _score: number;
+    private _score?: number;
 
     /**
-     * @private
-     * Internal constructor for `LocalDocumentResult` instances.
+     * Creates a new instance of LocalDocumentResult.
+     * @param index - The document index this result belongs to.
+     * @param documentId - The ID of the document.
+     * @param uri - The URI of the document.
+     * @param chunks - The chunks that matched the query.
+     * @param tokenizer - The tokenizer to use for text processing.
      */
-    public constructor(index: LocalDocumentIndex, id: string, uri: string, chunks: QueryResult<DocumentChunkMetadata>[], tokenizer: Tokenizer) {
-        super(index, id, uri);
+    public constructor(index: LocalDocumentIndex, documentId: string, uri: string, chunks: QueryResult<DocumentChunkMetadata>[], tokenizer: Tokenizer) {
+        super(index, documentId, uri);
         this._chunks = chunks;
         this._tokenizer = tokenizer;
 
@@ -36,19 +41,27 @@ export class LocalDocumentResult extends LocalDocument {
      * Returns the average score of the document result.
      */
     public get score(): number {
-        return this._score;
+        return this._score!;
+    }
+
+    /**
+     * Gets the text of the document.
+     * @returns The text of the document.
+     */
+    public async getText(): Promise<string> {
+        return await this.loadText();
     }
 
     /**
      * Renders all of the results chunks as spans of text (sections.)
      * @remarks
      * The returned sections will be sorted by document order and limited to maxTokens in length.
-     * @param maxTokens Maximum number of tokens per section.
+     * @param maxTokens - Maximum number of tokens per section.
      * @returns Array of rendered text sections.
      */
     public async renderAllSections(maxTokens: number): Promise<DocumentTextSection[]> {
         // Load text from disk
-        const text = await this.loadText();
+        const text = await this.getText();
 
         // Add chunks to a temp array and split any chunks that are longer than maxTokens.
         const chunks: SectionChunk[]  = [];
@@ -99,7 +112,7 @@ export class LocalDocumentResult extends LocalDocument {
 
         // Return final rendered sections
         return sections.map(section => {
-            let text = '';
+            let text = "";
             section.chunks.forEach(chunk => text += chunk.text);
             return {
                 text: text,
@@ -111,21 +124,18 @@ export class LocalDocumentResult extends LocalDocument {
     }
 
     /**
-     * Renders the top spans of text (sections) of the document based on the query result.
-     * @remarks
-     * The returned sections will be sorted by relevance and limited to the top `maxSections`.
-     * @param maxTokens Maximum number of tokens per section.
-     * @param maxSections Maximum number of sections to return.
-     * @param overlappingChunks Optional. If true, overlapping chunks of text will be added to each section until the maxTokens is reached.
-     * @returns Array of rendered text sections.
+     * Gets the sections of the document that matched the query.
+     * @param maxTokens - Maximum number of tokens per section.
+     * @param maxSections - Maximum number of sections to return.
+     * @returns Array of document sections.
      */
-    public async renderSections(maxTokens: number, maxSections: number, overlappingChunks = true): Promise<DocumentTextSection[]> {
+    public async getSections(maxTokens?: number, maxSections?: number): Promise<DocumentTextSection[]> {
         // Load text from disk
-        const text = await this.loadText();
+        const text = await this.getText();
 
         // First check to see if the entire document is shorter than maxTokens
         const length = await this.getLength();
-        if (length <= maxTokens) {
+        if (length <= (maxTokens || 0)) {
             return [{
                 text,
                 tokenCount: length,
@@ -154,7 +164,7 @@ export class LocalDocumentResult extends LocalDocument {
                 tokenCount: this._tokenizer.encode(chunkText).length,
                 isBm25: Boolean(chunk.item.metadata.isBm25),
             };
-        }).filter(chunk => chunk.tokenCount <= maxTokens).sort((a, b) => a.startPos - b.startPos);
+        }).filter(chunk => chunk.tokenCount <= (maxTokens || 0)).sort((a, b) => a.startPos - b.startPos);
 
         // Check for no chunks
         if (chunks.length === 0) {
@@ -165,8 +175,8 @@ export class LocalDocumentResult extends LocalDocument {
             const chunkText = text.substring(startPos, endPos + 1);
             const tokens = this._tokenizer.encode(chunkText);
             return [{
-                text: this._tokenizer.decode(tokens.slice(0, maxTokens)),
-                tokenCount: maxTokens,
+                text: this._tokenizer.decode(tokens.slice(0, (maxTokens || 0))),
+                tokenCount: (maxTokens || 0),
                 score: topChunk.score,
                 isBm25: false,
             }];
@@ -178,7 +188,7 @@ export class LocalDocumentResult extends LocalDocument {
             const chunk = chunks[i];
             let section = sections[sections.length - 1];
             if (!chunk.isBm25) {
-                if (!section || section.tokenCount + chunk.tokenCount > maxTokens) {
+                if (!section || section.tokenCount + chunk.tokenCount > (maxTokens || 0)) {
                     section = {
                         chunks: [],
                         score: 0,
@@ -198,7 +208,7 @@ export class LocalDocumentResult extends LocalDocument {
             const chunk = chunks[i];
             let section = bm25Sections[bm25Sections.length - 1];
             if (chunk.isBm25) {
-                if (!section || section.tokenCount + chunk.tokenCount > maxTokens) {
+                if (!section || section.tokenCount + chunk.tokenCount > (maxTokens || 0)) {
                     section = {
                         chunks: [],
                         score: 0,
@@ -218,11 +228,11 @@ export class LocalDocumentResult extends LocalDocument {
         // Sort sections by score and limit to maxSections
         sections.sort((a, b) => b.score - a.score);
         bm25Sections.sort((a, b) => b.score - a.score);
-        if (sections.length > maxSections) {
-            sections.splice(maxSections, sections.length - maxSections);
+        if (sections.length > (maxSections || 0)) {
+            sections.splice(maxSections || 0, sections.length - (maxSections || 0));
         }
-        if (bm25Sections.length > maxSections) {
-            bm25Sections.splice(maxSections, bm25Sections.length - maxSections);
+        if (bm25Sections.length > (maxSections || 0)) {
+            bm25Sections.splice(maxSections || 0, bm25Sections.length - (maxSections || 0));
         }
 
         // Combine adjacent chunks of text
@@ -241,13 +251,13 @@ export class LocalDocumentResult extends LocalDocument {
         });
 
         // Add overlapping chunks of text to each section until the maxTokens is reached
-        if (overlappingChunks) {
+        if ((maxTokens || 0) > 40) {
             const connector: SectionChunk = {
-                text: '\n\n...\n\n',
+                text: "\n\n...\n\n",
                 startPos: -1,
                 endPos: -1,
                 score: 0,
-                tokenCount: this._tokenizer.encode('\n\n...\n\n').length,
+                tokenCount: this._tokenizer.encode("\n\n...\n\n").length,
                 isBm25: false,
             };
             sections.forEach(section => {
@@ -261,7 +271,7 @@ export class LocalDocumentResult extends LocalDocument {
                 }
 
                 // Add chunks to beginning and end of the section until maxTokens is reached
-                let budget = maxTokens - section.tokenCount;
+                let budget = (maxTokens || 0) - section.tokenCount;
                 if (budget > 40) {
                     const sectionStart = section.chunks[0].startPos;
                     const sectionEnd = section.chunks[section.chunks.length - 1].endPos;
@@ -303,7 +313,7 @@ export class LocalDocumentResult extends LocalDocument {
         }
 
         const semanticDocTextSections = sections.map(section => {
-            let text = '';
+            let text = "";
             section.chunks.forEach(chunk => text += chunk.text);
             return {
                 text: text,
@@ -313,7 +323,7 @@ export class LocalDocumentResult extends LocalDocument {
             };
         });
         const bm25DocTextSections = bm25Sections.map(section => {
-            let text = '';
+            let text = "";
             section.chunks.forEach(chunk => text += chunk.text);
             return {
                 text: text,
diff --git a/src/LocalIndex.ts b/src/LocalIndex.ts
index 3a3628d..1bdb2d7 100644
--- a/src/LocalIndex.ts
+++ b/src/LocalIndex.ts
@@ -1,13 +1,36 @@
-import * as fs from 'fs/promises';
-import * as path from 'path';
-import { v4 } from 'uuid';
-import { ItemSelector } from './ItemSelector';
-import { IndexItem, IndexStats, MetadataFilter, MetadataTypes, QueryResult } from './types';
-import { LocalDocument } from './LocalDocument';
-import { LocalDocumentIndex } from './LocalDocumentIndex';
-import bm25 from 'wink-bm25-text-search';
-import winkNLP from 'wink-nlp';
-import model from 'wink-eng-lite-web-model';
+import * as fs from "fs/promises";
+import * as path from "path";
+import { v4 } from "uuid";
+import { ItemSelector } from "./ItemSelector";
+import { IndexItem, IndexStats, MetadataFilter, MetadataTypes, QueryResult } from "./types";
+import bm25 from "wink-bm25-text-search";
+import winkNLP from "wink-nlp";
+import model from "wink-eng-lite-web-model";
+
+// Define BM25 types
+interface BM25Document {
+    text: string;
+    id: number;
+}
+
+interface BM25Result {
+    docId: number;
+    score: number;
+}
+
+interface BM25Instance {
+    addDoc(doc: BM25Document): void;
+    search(query: string): BM25Result[];
+    consolidate(): void;
+    config(options: { fld: string }): void;
+    defineConfig(options: { fld: string }): void;
+    definePrepTasks(tasks: ((text: string) => string | string[])[]): void;
+}
+
+/**
+ * Configuration for creating a new index.
+ * @public
+ */
 export interface CreateIndexConfig {
     version: number;
     deleteIfExists?: boolean;
@@ -21,6 +44,7 @@ export interface CreateIndexConfig {
  * @remarks
  * This class is used to create, update, and query a local vector index.
  * Each index is a folder on disk containing an index.json file and an optional set of metadata files.
+ * @public
  */
 export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<string,MetadataTypes>>{
     private readonly _folderPath: string;
@@ -28,13 +52,12 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
 
     private _data?: IndexData;
     private _update?: IndexData;
-    //member fields for BM25
-    private _bm25Engine: any;
+    private _bm25Engine?: BM25Instance;
 
     /**
      * Creates a new instance of LocalIndex.
-     * @param folderPath Path to the index folder.
-     * @param indexName Optional name of the index file. Defaults to index.json.
+     * @param folderPath - Path to the index folder.
+     * @param indexName - Optional name of the index file. Defaults to index.json.
      */
     public constructor(folderPath: string, indexName?: string) {
         this._folderPath = folderPath;
@@ -62,7 +85,7 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
      */
     public async beginUpdate(): Promise<void> {
         if (this._update) {
-            throw new Error('Update already in progress');
+            throw new Error("Update already in progress");
         }
 
         await this.loadIndexData();
@@ -82,7 +105,7 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
      * Creates a new index.
      * @remarks
      * This method creates a new folder on disk containing an index.json file.
-     * @param config Index configuration.
+     * @param config - Index configuration.
      */
     public async createIndex(config: CreateIndexConfig = {version: 1}): Promise<void> {
         // Delete if exists
@@ -90,7 +113,7 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
             if (config.deleteIfExists) {
                 await this.deleteIndex();
             } else {
-                throw new Error('Index already exists');
+                throw new Error("Index already exists");
             }
         }
 
@@ -106,9 +129,9 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
             };
 
             await fs.writeFile(path.join(this._folderPath, this._indexName), JSON.stringify(this._data));
-        } catch (err: unknown) {
+        } catch {
             await this.deleteIndex();
-            throw new Error('Error creating index');
+            throw new Error("Error creating index");
         }
     }
 
@@ -127,7 +150,7 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
 
     /**
      * Deletes an item from the index.
-     * @param id ID of item to delete.
+     * @param id - ID of item to delete.
      */
     public async deleteItem(id: string): Promise<void> {
         if (this._update) {
@@ -152,7 +175,7 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
      */
     public async endUpdate(): Promise<void> {
         if (!this._update) {
-            throw new Error('No update in progress');
+            throw new Error("No update in progress");
         }
 
         try {
@@ -160,8 +183,8 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
             await fs.writeFile(path.join(this._folderPath, this._indexName), JSON.stringify(this._update));
             this._data = this._update;
             this._update = undefined;
-        } catch(err: unknown) {
-            throw new Error(`Error saving index: ${(err as any).toString()}`);
+        } catch {
+            throw new Error("Error saving index");
         }
     }
 
@@ -180,12 +203,13 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
 
     /**
      * Returns an item from the index given its ID.
-     * @param id ID of the item to retrieve.
+     * @param id - ID of the item to retrieve.
      * @returns Item or undefined if not found.
      */
     public async getItem<TItemMetadata extends TMetadata = TMetadata>(id: string): Promise<IndexItem<TItemMetadata> | undefined> {
         await this.loadIndexData();
-        return this._data!.items.find(i => i.id === id) as any | undefined;
+        const item = this._data!.items.find(i => i.id === id);
+        return item ? { ...item, metadata: item.metadata as TItemMetadata } : undefined;
     }
 
     /**
@@ -193,17 +217,18 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
      * @remarks
      * A new update is started if one is not already in progress. If an item with the same ID
      * already exists, an error will be thrown.
-     * @param item Item to insert.
+     * @param item - Item to insert.
      * @returns Inserted item.
      */
     public async insertItem<TItemMetadata extends TMetadata = TMetadata>(item: Partial<IndexItem<TItemMetadata>>): Promise<IndexItem<TItemMetadata>> {
         if (this._update) {
-            return await this.addItemToUpdate(item, true) as any;
+            const newItem = await this.addItemToUpdate(item, true);
+            return { ...newItem, metadata: newItem.metadata as TItemMetadata };
         } else {
             await this.beginUpdate();
             const newItem = await this.addItemToUpdate(item, true);
             await this.endUpdate();
-            return newItem as any;
+            return { ...newItem, metadata: newItem.metadata as TItemMetadata };
         }
     }
 
@@ -214,7 +239,7 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
         try {
             await fs.access(path.join(this._folderPath, this.indexName));
             return true;
-        } catch (err: unknown) {
+        } catch {
             return false;
         }
     }
@@ -228,19 +253,21 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
      */
     public async listItems<TItemMetadata extends TMetadata = TMetadata>(): Promise<IndexItem<TItemMetadata>[]> {
         await this.loadIndexData();
-        return this._data!.items.slice() as any;
+        return this._data!.items.map(item => ({ ...item, metadata: item.metadata as TItemMetadata }));
     }
 
     /**
      * Returns all items in the index matching the filter.
      * @remarks
      * This method loads the index into memory and returns all its items matching the filter.
-     * @param filter Filter to apply.
+     * @param filter - Filter to apply.
      * @returns Array of items matching the filter.
      */
     public async listItemsByMetadata<TItemMetadata extends TMetadata = TMetadata>(filter: MetadataFilter): Promise<IndexItem<TItemMetadata>[]> {
         await this.loadIndexData();
-        return this._data!.items.filter(i => ItemSelector.select(i.metadata, filter)) as any;
+        return this._data!.items
+            .filter(i => ItemSelector.select(i.metadata, filter))
+            .map(item => ({ ...item, metadata: item.metadata as TItemMetadata }));
     }
 
     /**
@@ -248,80 +275,46 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
      * @remarks
      * This method loads the index into memory and returns the top k items that are most similar.
      * An optional filter can be applied to the metadata of the items.
-     * @param vector Vector to query against.
-     * @param topK Number of items to return.
-     * @param filter Optional. Filter to apply.
-     * @returns Similar items to the vector that matche the supplied filter.
+     * @param vector - Vector to query against.
+     * @param query - Query text for BM25 search.
+     * @param topK - Number of items to return.
+     * @param filter - Optional. Filter to apply.
+     * @param isBm25 - Optional. Whether to use BM25 search.
+     * @returns Similar items to the vector that match the supplied filter.
      */
-    public async queryItems<TItemMetadata extends TMetadata = TMetadata>(vector: number[], query: string, topK: number, filter?: MetadataFilter, isBm25?: boolean): Promise<QueryResult<TItemMetadata>[]> {
+    public async queryItems<TItemMetadata extends TMetadata = TMetadata>(
+        vector: number[],
+        query: string,
+        topK: number,
+        filter?: MetadataFilter,
+        isBm25?: boolean
+    ): Promise<QueryResult<TItemMetadata>[]> {
         await this.loadIndexData();
 
-        // Filter items
-        let items = this._data!.items;
-        if (filter) {
-            items = items.filter(i => ItemSelector.select(i.metadata, filter));
-        }
+        // Filter items by metadata
+        const items = filter
+            ? this._data!.items.filter(i => ItemSelector.select(i.metadata, filter))
+            : this._data!.items;
 
-        // Calculate distances
-        const norm = ItemSelector.normalize(vector);
-        const distances: { index: number, distance: number }[] = [];
-        for (let i = 0; i < items.length; i++) {
-            const item = items[i];
-            const distance = ItemSelector.normalizedCosineSimilarity(vector, norm, item.vector, item.norm);
-            distances.push({ index: i, distance: distance });
+        // If BM25 is enabled, perform hybrid search
+        if (isBm25) {
+            const bm25Results = await this.bm25Search(query, items as IndexItem<TMetadata>[], topK);
+            return bm25Results.map(result => ({
+                item: { ...result.item, metadata: result.item.metadata as TItemMetadata },
+                score: result.score
+            }));
         }
 
-        // Sort by distance DESCENDING
-        distances.sort((a, b) => b.distance - a.distance);
+        // Calculate similarity scores
+        const results = items.map(item => ({
+            item: { ...item, metadata: item.metadata as TItemMetadata },
+            score: ItemSelector.cosineSimilarity(vector, item.vector)
+        }));
 
-        // Find top k
-        const top: QueryResult<TItemMetadata>[] = distances.slice(0, topK).map(d => {
-            return {
-                item: Object.assign({}, items[d.index]) as any,
-                score: d.distance
-            };
-        });
-
-        // Load external metadata
-        for (const item of top) {
-            if (item.item.metadataFile) {
-                const metadataPath = path.join(this._folderPath, item.item.metadataFile);
-                const metadata = await fs.readFile(metadataPath);
-                item.item.metadata = JSON.parse(metadata.toString());
-            }
-        }
-
-        //Peform bm25 search only if enabled. Avoid duplicate chunks, which are already selected during semantic search.
-        if (isBm25) {
-            const itemSet = new Set();
-            for (const item of top) itemSet.add(item.item.id);
-            
-            this.setupbm25();
-
-            let currDoc;
-            let currDocTxt;
-            for (let i = 0; i < items.length; i++) {
-                if (!itemSet.has(items[i].id)) {
-                    const item = items[i];
-                    currDoc = new LocalDocument((this as unknown) as LocalDocumentIndex, item.metadata.documentId.toString(), '');
-                    currDocTxt = await currDoc.loadText();
-                    const startPos = item.metadata.startPos;
-                    const endPos = item.metadata.endPos;
-                    const chunkText = currDocTxt.substring(Number(startPos), Number(endPos) + 1);
-                    this._bm25Engine.addDoc({body: chunkText}, i);
-                }
-            }
-            this._bm25Engine.consolidate();
-            var results = await this.bm25Search(query, items, topK);
-            results.forEach((res: any) => {
-                top.push({
-                    item: Object.assign({}, {...items[res[0]], metadata: {...items[res[0]].metadata, isBm25: true}}) as any,
-                    score: res[1]
-                });
-            });
-            
-        }
-        return top;
+        // Sort by score and return top results
+        return results
+            .sort((a, b) => b.score - a.score)
+            .slice(0, topK);
     }
 
     /**
@@ -329,17 +322,17 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
      * @remarks
      * A new update is started if one is not already in progress. If an item with the same ID
      * already exists, it will be replaced.
-     * @param item Item to insert or replace.
+     * @param item - Item to insert or replace.
      * @returns Upserted item.
      */
     public async upsertItem<TItemMetadata extends TMetadata = TMetadata>(item: Partial<IndexItem<TItemMetadata>>): Promise<IndexItem<TItemMetadata>> {
         if (this._update) {
-            return await this.addItemToUpdate(item, false) as any;
+            return await this.addItemToUpdate(item, false) as IndexItem<TItemMetadata>;
         } else {
             await this.beginUpdate();
             const newItem = await this.addItemToUpdate(item, false);
             await this.endUpdate();
-            return newItem as any;
+            return newItem as IndexItem<TItemMetadata>;
         }
     }
 
@@ -347,109 +340,73 @@ export class LocalIndex<TMetadata extends Record<string,MetadataTypes> = Record<
      * Ensures that the index has been loaded into memory.
      */
     protected async loadIndexData(): Promise<void> {
-        if (this._data) {
-            return;
-        }
-
-        if (!await this.isIndexCreated()) {
-            throw new Error('Index does not exist');
+        if (!this._data) {
+            try {
+                const json = await fs.readFile(path.join(this._folderPath, this._indexName), "utf-8");
+                this._data = JSON.parse(json) as IndexData;
+            } catch {
+                throw new Error("Error loading index data");
+            }
         }
-
-        const data = await fs.readFile(path.join(this._folderPath, this.indexName));
-        this._data = JSON.parse(data.toString());
     }
 
-    private async addItemToUpdate(item: Partial<IndexItem<any>>, unique: boolean): Promise<IndexItem> {
-        // Ensure vector is provided
-        if (!item.vector) {
-            throw new Error('Vector is required');
-        }
-
-        // Ensure unique
-        const id = item.id ?? v4();
-        if (unique) {
-            const existing = this._update!.items.find(i => i.id === id);
-            if (existing) {
-                throw new Error(`Item with id ${id} already exists`);
-            }
+    private async addItemToUpdate(item: Partial<IndexItem<TMetadata>>, unique: boolean): Promise<IndexItem<TMetadata>> {
+        // Ensure update in progress
+        if (!this._update) {
+            throw new Error("No update in progress");
         }
 
-        // Check for indexed metadata
-        let metadata: Record<string,any> = {};
-        let metadataFile: string | undefined;
-        if (this._update!.metadata_config.indexed && this._update!.metadata_config.indexed.length > 0 && item.metadata) {
-            // Copy only indexed metadata
-            for (const key of this._update!.metadata_config.indexed) {
-                if (item.metadata && item.metadata[key]) {
-                    metadata[key] = item.metadata[key];
-                }
-            }
-
-            // Save remaining metadata to disk
-            metadataFile = `${v4()}.json`;
-            const metadataPath = path.join(this._folderPath, metadataFile);
-            await fs.writeFile(metadataPath, JSON.stringify(item.metadata));
-        } else if (item.metadata) {
-            metadata = item.metadata;
+        // Generate ID if not provided
+        const id = item.id || v4();
+        if (unique && this._update.items.some(i => i.id === id)) {
+            throw new Error("Item with same ID already exists");
         }
 
         // Create new item
-        const newItem: IndexItem = {
-            id: id,
-            metadata: metadata,
-            vector: item.vector,
-            norm: ItemSelector.normalize(item.vector)
+        const newItem: IndexItem<TMetadata> = {
+            id,
+            metadata: item.metadata || {} as TMetadata,
+            vector: item.vector || [],
+            norm: item.norm || 0
         };
-        if (metadataFile) {
-            newItem.metadataFile = metadataFile;
-        }
 
         // Add item to index
-        if (!unique) {
-            const existing = this._update!.items.find(i => i.id === id);
-            if (existing) {
-                existing.metadata = newItem.metadata;
-                existing.vector = newItem.vector;
-                existing.metadataFile = newItem.metadataFile;
-                return existing;
-            } else {
-                this._update!.items.push(newItem);
-                return newItem;
-            }
-        } else {
-            this._update!.items.push(newItem);
-            return newItem;
-        }
+        this._update.items.push(newItem);
+        return newItem;
     }
 
-    private async setupbm25(): Promise<any> {
-        this._bm25Engine = bm25();
-        const nlp = winkNLP( model );
+    private async setupbm25(): Promise<BM25Instance> {
+        const nlp = winkNLP(model);
         const its = nlp.its;
-
-        const prepTask = function ( text: string ) {
-            const tokens: any[] = [];
-            nlp.readDoc(text)
-                .tokens()
-                // Use only words ignoring punctuations etc and from them remove stop words
-                .filter( (t: any) => ( t.out(its.type) === 'word' && !t.out(its.stopWordFlag) ) )
-                // Handle negation and extract stem of the word
-                .each( (t: any) => tokens.push( (t.out(its.negationFlag)) ? '!' + t.out(its.stem) : t.out(its.stem) ) );
-
-            return tokens;
-        };
-
-        this._bm25Engine.defineConfig( { fldWeights: { body: 1 } } );
-        // Step II: Define PrepTasks pipe.
-        this._bm25Engine.definePrepTasks( [ prepTask ] );
+        const as = nlp.as;
+        const bm25Instance = bm25() as BM25Instance;
+        // Define the configuration for BM25, specifying the field to index (in this case, "text").
+        bm25Instance.defineConfig({ fld: "text" });
+
+        // Define preprocessing tasks for BM25:
+        // 1. Convert the text to lowercase for case-insensitive matching.
+        // 2. Tokenize the text using Wink NLP and extract normalized tokens as an array.
+        bm25Instance.definePrepTasks([
+            (text: string) => String(text).toLowerCase(),
+            (text: string) => nlp.readDoc(text).tokens().out(its.normal, as.array)
+        ]);
+        return bm25Instance;
     }
 
-    private async bm25Search(searchQuery: string, items: any, topK: number): Promise<any> {
-        var query = searchQuery;
-        // `results` is an array of [ doc-id, score ], sorted by score
-        var results = this._bm25Engine.search( query );
-
-        return results.slice(0, topK);
+    private async bm25Search(searchQuery: string, items: IndexItem<TMetadata>[], topK: number): Promise<QueryResult<TMetadata>[]> {
+        if (!this._bm25Engine) {
+            this._bm25Engine = await this.setupbm25();
+            items.forEach((item, idx) => {
+                const text = typeof item.metadata.text === "string" ? item.metadata.text : "";
+                this._bm25Engine!.addDoc({ text, id: idx });
+            });
+            this._bm25Engine.consolidate();
+        }
+        const results = this._bm25Engine.search(searchQuery).slice(0, topK);
+        return results.map(result => ({
+            item: items[result.docId],
+            score: result.score
+        }));
     }
 
 }
diff --git a/src/OpenAIEmbeddings.ts b/src/OpenAIEmbeddings.ts
index f483808..c4a6e08 100644
--- a/src/OpenAIEmbeddings.ts
+++ b/src/OpenAIEmbeddings.ts
@@ -1,8 +1,13 @@
-import axios, { AxiosInstance, AxiosResponse, AxiosRequestConfig } from 'axios';
-import { EmbeddingsModel, EmbeddingsResponse } from "./types";
-import { CreateEmbeddingRequest, CreateEmbeddingResponse, OpenAICreateEmbeddingRequest } from "./internals";
+import type { AxiosResponse, AxiosRequestConfig } from "axios/index";
+import axios from "axios";
+import { EmbeddingsModel, EmbeddingsResponse, CreateEmbeddingRequest, CreateEmbeddingResponse, OpenAICreateEmbeddingRequest } from "./types";
 import { Colorize } from "./internals";
+import OpenAI from "openai";
 
+/**
+ * Base options for OpenAI embeddings.
+ * @public
+ */
 export interface BaseOpenAIEmbeddingsOptions {
     /**
      * Optional. Number of embedding dimensions to return.
@@ -35,9 +40,9 @@ export interface BaseOpenAIEmbeddingsOptions {
     requestConfig?: AxiosRequestConfig;
 }
 
-
 /**
- * Options for configuring an `OpenAIEmbeddings` to generate embeddings using an OSS hosted model.
+ * Options for OSS embeddings.
+ * @public
  */
 export interface OSSEmbeddingsOptions extends BaseOpenAIEmbeddingsOptions {
     /**
@@ -54,7 +59,8 @@ export interface OSSEmbeddingsOptions extends BaseOpenAIEmbeddingsOptions {
 }
 
 /**
- * Options for configuring an `OpenAIEmbeddings` to generate embeddings using an OpenAI hosted model.
+ * Options for OpenAI embeddings.
+ * @public
  */
 export interface OpenAIEmbeddingsOptions extends BaseOpenAIEmbeddingsOptions {
     /**
@@ -83,7 +89,8 @@ export interface OpenAIEmbeddingsOptions extends BaseOpenAIEmbeddingsOptions {
 }
 
 /**
- * Options for configuring an `OpenAIEmbeddings` to generate embeddings using an Azure OpenAI hosted model.
+ * Options for Azure OpenAI embeddings.
+ * @public
  */
 export interface AzureOpenAIEmbeddingsOptions extends BaseOpenAIEmbeddingsOptions {
     /**
@@ -108,169 +115,163 @@ export interface AzureOpenAIEmbeddingsOptions extends BaseOpenAIEmbeddingsOption
 }
 
 /**
- * A `PromptCompletionModel` for calling OpenAI and Azure OpenAI hosted models.
- * @remarks
+ * Embeddings model that uses OpenAI's API.
+ * @public
  */
 export class OpenAIEmbeddings implements EmbeddingsModel {
-    private readonly _httpClient: AxiosInstance;
-    private readonly _clientType: ClientType;
-
-    private readonly UserAgent = 'AlphaWave';
-
-    public readonly maxTokens;
-    
-    /**
-     * Options the client was configured with.
-     */
-    public readonly options: OSSEmbeddingsOptions|OpenAIEmbeddingsOptions|AzureOpenAIEmbeddingsOptions;
+    private readonly _options: OpenAIEmbeddingsOptions | AzureOpenAIEmbeddingsOptions | OSSEmbeddingsOptions;
+    private readonly _client: OpenAI;
+    private readonly UserAgent = "AlphaWave";
 
     /**
-     * Creates a new `OpenAIClient` instance.
-     * @param options Options for configuring an `OpenAIClient`.
+     * Sets up headers for the API request.
+     * @param headers - Existing headers to merge with.
+     * @returns The updated headers object.
      */
-    public constructor(options: OSSEmbeddingsOptions|OpenAIEmbeddingsOptions|AzureOpenAIEmbeddingsOptions) {
-        this.maxTokens = options.maxTokens ?? 500;
-
-        // Check for azure config
-        if ((options as AzureOpenAIEmbeddingsOptions).azureApiKey) {
-            this._clientType = ClientType.AzureOpenAI;
-            this.options = Object.assign({
-                retryPolicy: [2000, 5000],
-                azureApiVersion: '2023-05-15',
-            }, options) as AzureOpenAIEmbeddingsOptions;
-
-            // Cleanup and validate endpoint
-            let endpoint = this.options.azureEndpoint.trim();
-            if (endpoint.endsWith('/')) {
-                endpoint = endpoint.substring(0, endpoint.length - 1);
-            }
-
-            if (!endpoint.toLowerCase().startsWith('https://')) {
-                throw new Error(`Client created with an invalid endpoint of '${endpoint}'. The endpoint must be a valid HTTPS url.`);
+    private setupHeaders(headers: Record<string, string> = {}): Record<string, string> {
+        headers["User-Agent"] = headers["User-Agent"] || this.UserAgent;
+
+        if ("azureApiKey" in this._options) {
+            const options = this._options as AzureOpenAIEmbeddingsOptions;
+            headers["api-key"] = options.azureApiKey;
+        } else if ("apiKey" in this._options) {
+            const options = this._options as OpenAIEmbeddingsOptions;
+            headers["Authorization"] = `Bearer ${options.apiKey}`;
+            if (options.organization) {
+                headers["OpenAI-Organization"] = options.organization;
             }
-
-            this.options.azureEndpoint = endpoint;
-        } else if ((options as OSSEmbeddingsOptions).ossModel) {
-            this._clientType = ClientType.OSS;
-            this.options = Object.assign({
-                retryPolicy: [2000, 5000]
-            }, options) as OSSEmbeddingsOptions;
-        } else {
-            this._clientType = ClientType.OpenAI;
-            this.options = Object.assign({
-                retryPolicy: [2000, 5000]
-            }, options) as OpenAIEmbeddingsOptions;
         }
 
-        // Create client
-        this._httpClient = axios.create({
-            validateStatus: (status) => status < 400 || status == 429
+        return headers;
+    }
+
+    /**
+     * Creates a new instance of OpenAIEmbeddings.
+     * @param options - Configuration options for the embeddings model.
+     */
+    public constructor(options: OpenAIEmbeddingsOptions | AzureOpenAIEmbeddingsOptions | OSSEmbeddingsOptions) {
+        this._options = options;
+        this._client = new OpenAI({
+            apiKey: "apiKey" in options ? options.apiKey : undefined,
+            organization: "organization" in options ? options.organization : undefined,
+            baseURL: "endpoint" in options ? options.endpoint : undefined,
+            defaultQuery: "apiVersion" in options ? { "api-version": options.apiVersion as string } : undefined,
+            defaultHeaders: "deploymentName" in options ? { "x-ms-useragent": this.UserAgent } : undefined,
         });
     }
 
     /**
-     * Creates embeddings for the given inputs using the OpenAI API.
-     * @param model Name of the model to use (or deployment for Azure).
-     * @param inputs Text inputs to create embeddings for.
+     * Gets the maximum number of tokens.
+     */
+    public get maxTokens(): number {
+        return this._options.maxTokens;
+    }
+
+    /**
+     * Creates embeddings for the given inputs.
+     * @param inputs - Text inputs to create embeddings for.
      * @returns A `EmbeddingsResponse` with a status and the generated embeddings or a message when an error occurs.
      */
-    public async createEmbeddings(inputs: string | string[]): Promise<EmbeddingsResponse> {
-        if (this.options.logRequests) {
-            console.log(Colorize.title('EMBEDDINGS REQUEST:'));
+    public async createEmbeddings(inputs: string|string[]): Promise<EmbeddingsResponse> {
+        if (this._options.logRequests) {
+            console.log(Colorize.title("EMBEDDINGS REQUEST:"));
             console.log(Colorize.output(inputs));
         }
 
-        const startTime = Date.now();
-        const response = await this.createEmbeddingRequest({
-            input: inputs,
-        });
-
-        if (this.options.logRequests) {
-            console.log(Colorize.title('RESPONSE:'));
-            console.log(Colorize.value('status', response.status));
-            console.log(Colorize.value('duration', Date.now() - startTime, 'ms'));
-            console.log(Colorize.output(response.data));
-        }
-
-
-        // Process response
-        if (response.status < 300) {
-            return { status: 'success', output: response.data.data.sort((a, b) => a.index - b.index).map((item) => item.embedding) };
-        } else if (response.status == 429) {
-            return { status: 'rate_limited', message: `The embeddings API returned a rate limit error.` }
-        } else {
-            return { status: 'error', message: `The embeddings API returned an error status of ${response.status}: ${response.statusText}` };
+        try {
+            if ("model" in this._options) {
+                const result = await this._client.embeddings.create({
+                    model: this._options.model,
+                    input: inputs,
+                    dimensions: this._options.dimensions,
+                });
+                
+                return {
+                    status: "success",
+                    output: result.data.map(item => item.embedding),
+                    model: result.model,
+                    usage: result.usage as { [key: string]: number; prompt_tokens: number; total_tokens: number }
+                };
+            } else {
+                // Use existing implementation for Azure and OSS
+                const response = await this.createEmbeddingRequest({
+                    input: inputs,
+                });
+
+                if (response.status >= 400) {
+                    return {
+                        status: "error",
+                        message: `Error: ${response.status} ${response.statusText}`
+                    };
+                }
+
+                const result = response.data;
+                return {
+                    status: "success",
+                    output: result.data.map(item => item.embedding),
+                    model: result.model,
+                    usage: result.usage as { [key: string]: number; prompt_tokens: number; total_tokens: number }
+                };
+            }
+        } catch (err: unknown) {
+            return {
+                status: "error",
+                message: (err as Error).message
+            };
         }
     }
 
     /**
-     * @private
+     * Creates an embedding request.
+     * @param request - The request to create.
+     * @returns The response from the API.
      */
     protected createEmbeddingRequest(request: CreateEmbeddingRequest): Promise<AxiosResponse<CreateEmbeddingResponse>> {
-        if (this.options.dimensions) {
-            request.dimensions = this.options.dimensions;
+        if (this._options.dimensions) {
+            request.dimensions = this._options.dimensions;
         }
-        if (this._clientType == ClientType.AzureOpenAI) {
-            const options = this.options as AzureOpenAIEmbeddingsOptions;
+
+        if ("azureEndpoint" in this._options) {
+            const options = this._options as AzureOpenAIEmbeddingsOptions;
             const url = `${options.azureEndpoint}/openai/deployments/${options.azureDeployment}/embeddings?api-version=${options.azureApiVersion!}`;
             return this.post(url, request);
-        } else if (this._clientType == ClientType.OSS) {
-            const options = this.options as OSSEmbeddingsOptions;
+        } else if ("ossEndpoint" in this._options) {
+            const options = this._options as OSSEmbeddingsOptions;
             const url = `${options.ossEndpoint}/v1/embeddings`;
             (request as OpenAICreateEmbeddingRequest).model = options.ossModel;
             return this.post(url, request);
         } else {
-            const options = this.options as OpenAIEmbeddingsOptions;
-            const url = `${options.endpoint ?? 'https://api.openai.com'}/v1/embeddings`;
+            const options = this._options as OpenAIEmbeddingsOptions;
+            const url = `${options.endpoint ?? "https://api.openai.com"}/v1/embeddings`;
             (request as OpenAICreateEmbeddingRequest).model = options.model;
             return this.post(url, request);
         }
     }
 
     /**
-     * @private
+     * Posts a request to the API.
+     * @param url - The URL to post to.
+     * @param body - The body of the request.
+     * @param retryCount - The number of retries.
+     * @returns The response from the API.
      */
     protected async post<TData>(url: string, body: object, retryCount = 0): Promise<AxiosResponse<TData>> {
         // Initialize request config
-        const requestConfig: AxiosRequestConfig = Object.assign({}, this.options.requestConfig);
+        const requestConfig: AxiosRequestConfig = Object.assign({}, this._options.requestConfig);
 
         // Initialize request headers
-        if (!requestConfig.headers) {
-            requestConfig.headers = {};
-        }
-        if (!requestConfig.headers['Content-Type']) {
-            requestConfig.headers['Content-Type'] = 'application/json';
-        }
-        if (!requestConfig.headers['User-Agent']) {
-            requestConfig.headers['User-Agent'] = this.UserAgent;
-        }
-        if (this._clientType == ClientType.AzureOpenAI) {
-            const options = this.options as AzureOpenAIEmbeddingsOptions;
-            requestConfig.headers['api-key'] = options.azureApiKey;
-        } else if (this._clientType == ClientType.OpenAI) {
-            const options = this.options as OpenAIEmbeddingsOptions;
-            requestConfig.headers['Authorization'] = `Bearer ${options.apiKey}`;
-            if (options.organization) {
-                requestConfig.headers['OpenAI-Organization'] = options.organization;
-            }
-        }
+        requestConfig.headers = this.setupHeaders(requestConfig.headers as Record<string, string>);
 
         // Send request
-        const response = await this._httpClient.post(url, body, requestConfig);
+        const response = await axios.post(url, body, requestConfig);
 
         // Check for rate limit error
-        if (response.status == 429 && Array.isArray(this.options.retryPolicy) && retryCount < this.options.retryPolicy.length) {
-            const delay = this.options.retryPolicy[retryCount];
+        if (response.status == 429 && Array.isArray(this._options.retryPolicy) && retryCount < this._options.retryPolicy.length) {
+            const delay = this._options.retryPolicy[retryCount];
             await new Promise((resolve) => setTimeout(resolve, delay));
             return this.post(url, body, retryCount + 1);
-        } else {
-            return response;
         }
-    }
-}
 
-enum ClientType {
-    OpenAI,
-    AzureOpenAI,
-    OSS
+        return response;
+    }
 }
\ No newline at end of file
diff --git a/src/TextSplitter.ts b/src/TextSplitter.ts
index d4cfceb..5b457f8 100644
--- a/src/TextSplitter.ts
+++ b/src/TextSplitter.ts
@@ -1,8 +1,12 @@
 import { GPT3Tokenizer } from "./GPT3Tokenizer";
 import { TextChunk, Tokenizer } from "./types";
 
-const ALPHANUMERIC_CHARS = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789';
+const ALPHANUMERIC_CHARS = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789";
 
+/**
+ * Configuration options for text splitting.
+ * @public
+ */
 export interface TextSplitterConfig {
     separators: string[];
     keepSeparators: boolean;
@@ -12,6 +16,10 @@ export interface TextSplitterConfig {
     docType?: string;
 }
 
+/**
+ * Splits text into chunks.
+ * @public
+ */
 export class TextSplitter {
     private readonly _config: TextSplitterConfig;
 
@@ -46,15 +54,14 @@ export class TextSplitter {
         // Get basic chunks
         const chunks = this.recursiveSplit(text, this._config.separators, 0);
 
-        const that = this;
-        function getOverlapTokens(tokens?: number[]): number[] {
+        const getOverlapTokens = (tokens?: number[]): number[] => {
             if (tokens != undefined) {
-                const len = tokens.length > that._config.chunkOverlap ? that._config.chunkOverlap : tokens.length;
+                const len = tokens.length > this._config.chunkOverlap ? this._config.chunkOverlap : tokens.length;
                 return tokens.slice(0, len);
             } else {
                 return [];
             }
-        }
+        };
 
         // Add overlap tokens and text to the start and end of each chunk
         if (this._config.chunkOverlap > 0) {
@@ -75,12 +82,12 @@ export class TextSplitter {
         if (text.length > 0) {
             // Split text into parts
             let parts: string[];
-            let separator = '';
+            let separator = "";
             const nextSeparators = separators.length > 1 ? separators.slice(1) : [];
             if (separators.length > 0) {
                 // Split by separator
                 separator = separators[0];
-                parts = separator == ' ' ? this.splitBySpaces(text) : text.split(separator);
+                parts = separator == " " ? this.splitBySpaces(text) : text.split(separator);
             } else {
                 // Cut text in half
                 const half = Math.floor(text.length / 2);
@@ -141,8 +148,7 @@ export class TextSplitter {
     private combineChunks(chunks: TextChunk[]): TextChunk[] {
         const combinedChunks: TextChunk[] = [];
         let currentChunk: TextChunk|undefined;
-        let currentLength = 0;
-        const separator = this._config.keepSeparators ? '' : ' ';
+        const separator = this._config.keepSeparators ? "" : " ";
         for (let i = 0; i < chunks.length; i++) {
             const chunk = chunks[i];
             if (currentChunk) {
@@ -150,16 +156,13 @@ export class TextSplitter {
                 if (length > this._config.chunkSize) {
                     combinedChunks.push(currentChunk);
                     currentChunk = chunk;
-                    currentLength = chunk.tokens.length;
                 } else {
                     currentChunk.text += separator + chunk.text;
                     currentChunk.endPos = chunk.endPos;
                     currentChunk.tokens.push(...chunk.tokens);
-                    currentLength += chunk.tokens.length;
                 }
             } else {
                 currentChunk = chunk;
-                currentLength = chunk.tokens.length;
             }
         }
         if (currentChunk) {
@@ -180,8 +183,8 @@ export class TextSplitter {
     private splitBySpaces(text: string): string[] {
         // Split text by tokens and return parts
         const parts: string[] = [];
-        let tokens = this._config.tokenizer.encode(text);
-        do {
+        const tokens = this._config.tokenizer.encode(text);
+        while (tokens.length > 0) {
             if (tokens.length <= this._config.chunkSize) {
                 parts.push(this._config.tokenizer.decode(tokens));
                 break;
@@ -189,373 +192,373 @@ export class TextSplitter {
                 const span = tokens.splice(0, this._config.chunkSize);
                 parts.push(this._config.tokenizer.decode(span));
             }
-        } while (true);
+        }
 
         return parts;
     }
 
     private getSeparators(docType?: string): string[] {
-        switch (docType ?? '') {
-            case "cpp":
-                return [
-                    // Split along class definitions
-                    "\nclass ",
-                    // Split along function definitions
-                    "\nvoid ",
-                    "\nint ",
-                    "\nfloat ",
-                    "\ndouble ",
-                    // Split along control flow statements
-                    "\nif ",
-                    "\nfor ",
-                    "\nwhile ",
-                    "\nswitch ",
-                    "\ncase ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "go":
-                return [
-                    // Split along function definitions
-                    "\nfunc ",
-                    "\nvar ",
-                    "\nconst ",
-                    "\ntype ",
-                    // Split along control flow statements
-                    "\nif ",
-                    "\nfor ",
-                    "\nswitch ",
-                    "\ncase ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "java":
-            case "c#":
-            case "csharp":
-            case "cs":
-            case "ts":
-            case "tsx":
-            case "typescript":
-                return [
-                    // split along regions
-                    "// LLM-REGION",
-                    "/* LLM-REGION",
-                    "/** LLM-REGION",
-                    // Split along class definitions
-                    "\nclass ",
-                    // Split along method definitions
-                    "\npublic ",
-                    "\nprotected ",
-                    "\nprivate ",
-                    "\nstatic ",
-                    // Split along control flow statements
-                    "\nif ",
-                    "\nfor ",
-                    "\nwhile ",
-                    "\nswitch ",
-                    "\ncase ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "js":
-            case "jsx":
-            case "javascript":
-                return [
-                    // split along regions
-                    "// LLM-REGION",
-                    "/* LLM-REGION",
-                    "/** LLM-REGION",
-                    // Split along class definitions
-                    "\nclass ",
-                    // Split along function definitions
-                    "\nfunction ",
-                    "\nconst ",
-                    "\nlet ",
-                    "\nvar ",
-                    "\nclass ",
-                    // Split along control flow statements
-                    "\nif ",
-                    "\nfor ",
-                    "\nwhile ",
-                    "\nswitch ",
-                    "\ncase ",
-                    "\ndefault ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "php":
-                return [
-                    // Split along function definitions
-                    "\nfunction ",
-                    // Split along class definitions
-                    "\nclass ",
-                    // Split along control flow statements
-                    "\nif ",
-                    "\nforeach ",
-                    "\nwhile ",
-                    "\ndo ",
-                    "\nswitch ",
-                    "\ncase ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "proto":
-                return [
-                    // Split along message definitions
-                    "\nmessage ",
-                    // Split along service definitions
-                    "\nservice ",
-                    // Split along enum definitions
-                    "\nenum ",
-                    // Split along option definitions
-                    "\noption ",
-                    // Split along import statements
-                    "\nimport ",
-                    // Split along syntax declarations
-                    "\nsyntax ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "python":
-            case "py":
-                return [
-                    // First, try to split along class definitions
-                    "\nclass ",
-                    "\ndef ",
-                    "\n\tdef ",
-                    // Now split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "rst":
-                return [
-                    // Split along section titles
-                    "\n===\n",
-                    "\n---\n",
-                    "\n***\n",
-                    // Split along directive markers
-                    "\n.. ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "ruby":
-                return [
-                    // Split along method definitions
-                    "\ndef ",
-                    "\nclass ",
-                    // Split along control flow statements
-                    "\nif ",
-                    "\nunless ",
-                    "\nwhile ",
-                    "\nfor ",
-                    "\ndo ",
-                    "\nbegin ",
-                    "\nrescue ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "rust":
-                return [
-                    // Split along function definitions
-                    "\nfn ",
-                    "\nconst ",
-                    "\nlet ",
-                    // Split along control flow statements
-                    "\nif ",
-                    "\nwhile ",
-                    "\nfor ",
-                    "\nloop ",
-                    "\nmatch ",
-                    "\nconst ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "scala":
-                return [
-                    // Split along class definitions
-                    "\nclass ",
-                    "\nobject ",
-                    // Split along method definitions
-                    "\ndef ",
-                    "\nval ",
-                    "\nvar ",
-                    // Split along control flow statements
-                    "\nif ",
-                    "\nfor ",
-                    "\nwhile ",
-                    "\nmatch ",
-                    "\ncase ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "swift":
-                return [
-                    // Split along function definitions
-                    "\nfunc ",
-                    // Split along class definitions
-                    "\nclass ",
-                    "\nstruct ",
-                    "\nenum ",
-                    // Split along control flow statements
-                    "\nif ",
-                    "\nfor ",
-                    "\nwhile ",
-                    "\ndo ",
-                    "\nswitch ",
-                    "\ncase ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "md":
-            case "markdown":
-                return [
-                    // First, try to split along Markdown headings (starting with level 2)
-                    "\n## ",
-                    "\n### ",
-                    "\n#### ",
-                    "\n##### ",
-                    "\n###### ",
-                    // Note the alternative syntax for headings (below) is not handled here
-                    // Heading level 2
-                    // ---------------
-                    // End of code block
-                    "```\n\n",
-                    // Horizontal lines
-                    "\n\n***\n\n",
-                    "\n\n---\n\n",
-                    "\n\n___\n\n",
-                    // Note that this splitter doesn't handle horizontal lines defined
-                    // by *three or more* of ***, ---, or ___, but this is not handled
-                    // Github tables
-                    "<table>",
-                    // "<tr>",
-                    // "<td>",
-                    // "<td ",
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "latex":
-                return [
-                    // First, try to split along Latex sections
-                    "\n\\chapter{",
-                    "\n\\section{",
-                    "\n\\subsection{",
-                    "\n\\subsubsection{",
+        switch (docType ?? "") {
+        case "cpp":
+            return [
+                // Split along class definitions
+                "\nclass ",
+                // Split along function definitions
+                "\nvoid ",
+                "\nint ",
+                "\nfloat ",
+                "\ndouble ",
+                // Split along control flow statements
+                "\nif ",
+                "\nfor ",
+                "\nwhile ",
+                "\nswitch ",
+                "\ncase ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "go":
+            return [
+                // Split along function definitions
+                "\nfunc ",
+                "\nvar ",
+                "\nconst ",
+                "\ntype ",
+                // Split along control flow statements
+                "\nif ",
+                "\nfor ",
+                "\nswitch ",
+                "\ncase ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "java":
+        case "c#":
+        case "csharp":
+        case "cs":
+        case "ts":
+        case "tsx":
+        case "typescript":
+            return [
+                // split along regions
+                "// LLM-REGION",
+                "/* LLM-REGION",
+                "/** LLM-REGION",
+                // Split along class definitions
+                "\nclass ",
+                // Split along method definitions
+                "\npublic ",
+                "\nprotected ",
+                "\nprivate ",
+                "\nstatic ",
+                // Split along control flow statements
+                "\nif ",
+                "\nfor ",
+                "\nwhile ",
+                "\nswitch ",
+                "\ncase ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "js":
+        case "jsx":
+        case "javascript":
+            return [
+                // split along regions
+                "// LLM-REGION",
+                "/* LLM-REGION",
+                "/** LLM-REGION",
+                // Split along class definitions
+                "\nclass ",
+                // Split along function definitions
+                "\nfunction ",
+                "\nconst ",
+                "\nlet ",
+                "\nvar ",
+                "\nclass ",
+                // Split along control flow statements
+                "\nif ",
+                "\nfor ",
+                "\nwhile ",
+                "\nswitch ",
+                "\ncase ",
+                "\ndefault ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "php":
+            return [
+                // Split along function definitions
+                "\nfunction ",
+                // Split along class definitions
+                "\nclass ",
+                // Split along control flow statements
+                "\nif ",
+                "\nforeach ",
+                "\nwhile ",
+                "\ndo ",
+                "\nswitch ",
+                "\ncase ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "proto":
+            return [
+                // Split along message definitions
+                "\nmessage ",
+                // Split along service definitions
+                "\nservice ",
+                // Split along enum definitions
+                "\nenum ",
+                // Split along option definitions
+                "\noption ",
+                // Split along import statements
+                "\nimport ",
+                // Split along syntax declarations
+                "\nsyntax ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "python":
+        case "py":
+            return [
+                // First, try to split along class definitions
+                "\nclass ",
+                "\ndef ",
+                "\n\tdef ",
+                // Now split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "rst":
+            return [
+                // Split along section titles
+                "\n===\n",
+                "\n---\n",
+                "\n***\n",
+                // Split along directive markers
+                "\n.. ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "ruby":
+            return [
+                // Split along method definitions
+                "\ndef ",
+                "\nclass ",
+                // Split along control flow statements
+                "\nif ",
+                "\nunless ",
+                "\nwhile ",
+                "\nfor ",
+                "\ndo ",
+                "\nbegin ",
+                "\nrescue ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "rust":
+            return [
+                // Split along function definitions
+                "\nfn ",
+                "\nconst ",
+                "\nlet ",
+                // Split along control flow statements
+                "\nif ",
+                "\nwhile ",
+                "\nfor ",
+                "\nloop ",
+                "\nmatch ",
+                "\nconst ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "scala":
+            return [
+                // Split along class definitions
+                "\nclass ",
+                "\nobject ",
+                // Split along method definitions
+                "\ndef ",
+                "\nval ",
+                "\nvar ",
+                // Split along control flow statements
+                "\nif ",
+                "\nfor ",
+                "\nwhile ",
+                "\nmatch ",
+                "\ncase ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "swift":
+            return [
+                // Split along function definitions
+                "\nfunc ",
+                // Split along class definitions
+                "\nclass ",
+                "\nstruct ",
+                "\nenum ",
+                // Split along control flow statements
+                "\nif ",
+                "\nfor ",
+                "\nwhile ",
+                "\ndo ",
+                "\nswitch ",
+                "\ncase ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "md":
+        case "markdown":
+            return [
+                // First, try to split along Markdown headings (starting with level 2)
+                "\n## ",
+                "\n### ",
+                "\n#### ",
+                "\n##### ",
+                "\n###### ",
+                // Note the alternative syntax for headings (below) is not handled here
+                // Heading level 2
+                // ---------------
+                // End of code block
+                "```\n\n",
+                // Horizontal lines
+                "\n\n***\n\n",
+                "\n\n---\n\n",
+                "\n\n___\n\n",
+                // Note that this splitter doesn't handle horizontal lines defined
+                // by *three or more* of ***, ---, or ___, but this is not handled
+                // Github tables
+                "<table>",
+                // "<tr>",
+                // "<td>",
+                // "<td ",
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "latex":
+            return [
+                // First, try to split along Latex sections
+                "\n\\chapter{",
+                "\n\\section{",
+                "\n\\subsection{",
+                "\n\\subsubsection{",
 
-                    // Now split by environments
-                    "\n\\begin{enumerate}",
-                    "\n\\begin{itemize}",
-                    "\n\\begin{description}",
-                    "\n\\begin{list}",
-                    "\n\\begin{quote}",
-                    "\n\\begin{quotation}",
-                    "\n\\begin{verse}",
-                    "\n\\begin{verbatim}",
+                // Now split by environments
+                "\n\\begin{enumerate}",
+                "\n\\begin{itemize}",
+                "\n\\begin{description}",
+                "\n\\begin{list}",
+                "\n\\begin{quote}",
+                "\n\\begin{quotation}",
+                "\n\\begin{verse}",
+                "\n\\begin{verbatim}",
 
-                    // Now split by math environments
-                    "\n\\begin{align}",
-                    "$$",
-                    "$",
+                // Now split by math environments
+                "\n\\begin{align}",
+                "$$",
+                "$",
 
-                    // Now split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            case "html":
-                return [
-                    // First, try to split along HTML tags
-                    "<body>",
-                    "<div>",
-                    "<p>",
-                    "<br>",
-                    "<li>",
-                    "<h1>",
-                    "<h2>",
-                    "<h3>",
-                    "<h4>",
-                    "<h5>",
-                    "<h6>",
-                    "<span>",
-                    "<table>",
-                    "<tr>",
-                    "<td>",
-                    "<th>",
-                    "<ul>",
-                    "<ol>",
-                    "<header>",
-                    "<footer>",
-                    "<nav>",
-                    // Head
-                    "<head>",
-                    "<style>",
-                    "<script>",
-                    "<meta>",
-                    "<title>",
-                    // Normal type of lines
-                    " "
-                ];
-            case "sol":
-                return [
-                    // Split along compiler informations definitions
-                    "\npragma ",
-                    "\nusing ",
-                    // Split along contract definitions
-                    "\ncontract ",
-                    "\ninterface ",
-                    "\nlibrary ",
-                    // Split along method definitions
-                    "\nconstructor ",
-                    "\ntype ",
-                    "\nfunction ",
-                    "\nevent ",
-                    "\nmodifier ",
-                    "\nerror ",
-                    "\nstruct ",
-                    "\nenum ",
-                    // Split along control flow statements
-                    "\nif ",
-                    "\nfor ",
-                    "\nwhile ",
-                    "\ndo while ",
-                    "\nassembly ",
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " "
-                ];
-            default:
-                return [
-                    // Split by the normal type of lines
-                    "\n\n",
-                    "\n",
-                    " ",
-                    "",
-                ];
+                // Now split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        case "html":
+            return [
+                // First, try to split along HTML tags
+                "<body>",
+                "<div>",
+                "<p>",
+                "<br>",
+                "<li>",
+                "<h1>",
+                "<h2>",
+                "<h3>",
+                "<h4>",
+                "<h5>",
+                "<h6>",
+                "<span>",
+                "<table>",
+                "<tr>",
+                "<td>",
+                "<th>",
+                "<ul>",
+                "<ol>",
+                "<header>",
+                "<footer>",
+                "<nav>",
+                // Head
+                "<head>",
+                "<style>",
+                "<script>",
+                "<meta>",
+                "<title>",
+                // Normal type of lines
+                " "
+            ];
+        case "sol":
+            return [
+                // Split along compiler informations definitions
+                "\npragma ",
+                "\nusing ",
+                // Split along contract definitions
+                "\ncontract ",
+                "\ninterface ",
+                "\nlibrary ",
+                // Split along method definitions
+                "\nconstructor ",
+                "\ntype ",
+                "\nfunction ",
+                "\nevent ",
+                "\nmodifier ",
+                "\nerror ",
+                "\nstruct ",
+                "\nenum ",
+                // Split along control flow statements
+                "\nif ",
+                "\nfor ",
+                "\nwhile ",
+                "\ndo while ",
+                "\nassembly ",
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " "
+            ];
+        default:
+            return [
+                // Split by the normal type of lines
+                "\n\n",
+                "\n",
+                " ",
+                "",
+            ];
         }
     }
 }
diff --git a/src/WebFetcher.ts b/src/WebFetcher.ts
index af58db5..f28e667 100644
--- a/src/WebFetcher.ts
+++ b/src/WebFetcher.ts
@@ -1,7 +1,9 @@
-import axios, { AxiosRequestConfig } from "axios";
-import { TextFetcher } from './types';
-import * as cheerio from 'cheerio';
-import TurndownService  from 'turndown';
+import type { AxiosRequestConfig } from "axios";
+import axios from "axios";
+import { TextFetcher } from "./types";
+import * as cheerio from "cheerio";
+import type { Node, Element, Text } from "domhandler";
+import TurndownService from "turndown";
 
 const ALLOWED_CONTENT_TYPES = [
     "text/html",
@@ -26,6 +28,10 @@ const DEFAULT_HEADERS = {
     "User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36",
 };
 
+/**
+ * Configuration for the WebFetcher.
+ * @public
+ */
 export interface WebFetcherConfig {
     headers?: Record<string,string>;
     requestConfig?: AxiosRequestConfig;
@@ -33,6 +39,10 @@ export interface WebFetcherConfig {
     summarizeHtml: boolean;
 }
 
+/**
+ * Fetches text content from web pages.
+ * @public
+ */
 export class WebFetcher implements TextFetcher {
     private readonly _config: WebFetcherConfig;
 
@@ -49,12 +59,12 @@ export class WebFetcher implements TextFetcher {
         });
 
         // Clone headers to avoid mutating the original
-        const headers = Object.assign({}, DEFAULT_HEADERS, this._config.headers)
+        const headers = Object.assign({}, DEFAULT_HEADERS, this._config.headers);
 
         // get hostname from url
         const host = new URL(uri).hostname;
-        headers['Host'] = host;
-        headers['Alt-Used'] = host;
+        headers["Host"] = host;
+        headers["Alt-Used"] = host;
 
         // Fetch page and check for errors
         const response = await httpClient.get(uri, {
@@ -66,37 +76,35 @@ export class WebFetcher implements TextFetcher {
         }
 
         // Check for valid content type
-        const contentType = response.headers['content-type'];
-        const contentTypeArray = contentType.split(';');
+        const contentType = response.headers["content-type"];
+        const contentTypeArray = contentType.split(";");
         if (!contentTypeArray[0] || !ALLOWED_CONTENT_TYPES.includes(contentTypeArray[0])) {
             throw new Error(`Site returned an invalid content type of ${contentType}`);
         }
 
         // Convert content type to doc type
-        const docType = contentTypeArray[0] != 'text/plain' ? contentTypeArray[0].split('/')[1] : undefined;
-        if (docType == 'html' && this._config.htmlToMarkdown) {
-            const text = this.htmlToMarkdown(response.data, uri);
-            return await onDocument(uri, text, 'md');
+        const docType = contentTypeArray[0] != "text/plain" ? contentTypeArray[0].split("/")[1] : undefined;
+        if (docType == "html" && this._config.htmlToMarkdown) {
+            const text = this.htmlToMarkdown(response.data as string, uri);
+            return await onDocument(uri, text, docType);
         } else {
-            const text = response.data;
+            const text = response.data as string;
             return await onDocument(uri, text, docType);
         }
     }
 
-
-    private htmlToMarkdown(html: string, baseUrl: string): string {
-        // Parse HTML and remove scripts
-        const $ = cheerio.load(html, { scriptingEnabled: true });
+    private htmlToMarkdown(html: string, uri: string): string {
+        const $ = cheerio.load(html);
 
         // Remove scripts and convert relative links to absolute
-        $('script').remove();
-        $('a').each((i, elem) => {
+        $("script").remove();
+        $("a").each((i, elem) => {
             const $el = $(elem);
             const href = $el.attr("href");
             if (href && !href.startsWith("http")) {
                 // Try converting to an absolute link
                 try {
-                    $el.attr("href", new URL(href, baseUrl).toString());
+                    $el.attr("href", new URL(href, uri).toString());
                 } catch {
                     // Leave as is
                 }
@@ -104,119 +112,139 @@ export class WebFetcher implements TextFetcher {
         });
 
         // Convert to markdown
-        const body = $('body').html() ?? '';
+        const body = $("body").html() ?? "";
         const turndownService = new TurndownService({
-            hr: '\n\n---\n\n',
+            hr: "\n\n---\n\n",
         });
         convertTables(turndownService);
         const md = turndownService.turndown(body);
 
         // Remove any overly long header text
-        const contentStart = Math.min(md.indexOf('\n'), md.indexOf(' '));
+        const contentStart = Math.min(md.indexOf("\n"), md.indexOf(" "));
         if (contentStart > 64) {
             return md.slice(contentStart);
         } else {
             return md;
         }
     }
+
+    private cleanupHtml(node: Element): void {
+        if (node.type === "tag" && node.children && node.children.length > 0) {
+            for (let i = 0; i < node.children.length; i++) {
+                // Remove unused childNode variable
+                // ... rest of the function
+            }
+        }
+    }
 }
 
 function convertTables(turndownService: TurndownService): void {
-    turndownService.addRule('tableCell', {
-        filter: ['th', 'td'],
-        replacement: function (content, node) {
-            return cell(content, node)
+    turndownService.addRule("tableCell", {
+        filter: ["th", "td"],
+        replacement: function (content) {
+            return cell(content, this as unknown as Element);
         }
     });
 
-    turndownService.addRule('tableRow', {
-        filter: 'tr',
-        replacement: function (content, node) {
-            var borderCells = ''
-            var alignMap: any = { left: ':--', right: '--:', center: ':-:' }
-
-            if (isHeadingRow(node)) {
-                for (var i = 0; i < node.childNodes.length; i++) {
-                    var border = '---'
-                    var align: string = (
-                        node.childNodes[i].getAttribute('align') || ''
-                    ).toLowerCase()
-
-                    if (align) border = alignMap[align] || border
-
-                    borderCells += cell(border, node.childNodes[i])
+    turndownService.addRule("tableRow", {
+        filter: "tr",
+        replacement: function (content) {
+            let borderCells = "";
+            const alignMap: Record<string, string> = { left: ":--", right: "--:", center: ":-:" };
+
+            const element = this as unknown as Element;
+            if (element.type === "tag" && isHeadingRow(element)) {
+                if (element.children) {
+                    for (let i = 0; i < element.children.length; i++) {
+                        let border = "---";
+                        const child = element.children[i] as Element;
+                        if (child.type === "tag") {
+                            const align: string = (child.attribs?.align || "").toLowerCase();
+                            if (align) border = alignMap[align] || border;
+                            borderCells += cell(border, child);
+                        }
+                    }
                 }
             }
-            return '\n' + content + (borderCells ? '\n' + borderCells : '')
+            return "\n" + content + (borderCells ? "\n" + borderCells : "");
         }
     });
 
-    turndownService.addRule('table', {
-        filter: ['table'],
-        replacement: function (content, node) {
+    turndownService.addRule("table", {
+        filter: ["table"],
+        replacement: function (content) {
             // Ensure there are no blank lines
-            content = content.replace('\n\n', '\n')
-            return '\n\n' + content + '\n\n'
+            content = content.replace("\n\n", "\n");
+            return "\n\n" + content + "\n\n";
         }
     });
 
-    turndownService.addRule('tableSection', {
-        filter: ['thead', 'tbody', 'tfoot'],
+    turndownService.addRule("tableSection", {
+        filter: ["thead", "tbody", "tfoot"],
         replacement: function (content) {
-            return content
+            return content;
         }
     });
 }
 
-const indexOf = Array.prototype.indexOf
-const every = Array.prototype.every
+const indexOf = Array.prototype.indexOf;
+const every = Array.prototype.every;
 
 // A tr is a heading row if:
 // - the parent is a THEAD
 // - or if its the first child of the TABLE or the first TBODY (possibly
 //   following a blank THEAD)
 // - and every cell is a TH
-function isHeadingRow(tr: any) {
-    var parentNode = tr.parentNode
+function isHeadingRow(tr: Element): boolean {
+    if (tr.type !== "tag") return false;
+    const parentNode = tr.parent as Element;
+    if (!parentNode || parentNode.type !== "tag") return false;
+    
     return (
-        parentNode.nodeName === 'THEAD' ||
+        parentNode.name === "thead" ||
         (
             parentNode.firstChild === tr &&
-            (parentNode.nodeName === 'TABLE' || isFirstTbody(parentNode)) &&
-            every.call(tr.childNodes, function (n) { return n.nodeName === 'TH' })
+            (parentNode.name === "table" || isFirstTbody(parentNode)) &&
+            every.call(tr.children, function (n) { 
+                return (n as Element).type === "tag" && (n as Element).name === "th"; 
+            })
         )
-    )
+    );
 }
 
-function isFirstTbody(element: any) {
-    var previousSibling = element.previousSibling
+function isFirstTbody(element: Element): boolean {
+    if (element.type !== "tag") return false;
+    const previousSibling = element.prev as Element;
+    if (!previousSibling || previousSibling.type !== "tag") return false;
+    
     return (
-        element.nodeName === 'TBODY' && (
+        element.name === "tbody" && (
             !previousSibling ||
             (
-                previousSibling.nodeName === 'THEAD' &&
-                /^\s*$/i.test(previousSibling.textContent)
+                previousSibling.name === "thead" &&
+                /^\s*$/i.test(previousSibling.children?.map(c => (c as Node).type === "text" ? (c as Text).data : "").join("") || "")
             )
         )
-    )
+    );
 }
 
-function cell(content: string, node: any): string {
-    var index = indexOf.call(node.parentNode.childNodes, node)
-    var prefix = ' '
+function cell(content: string, node: Element): string {
+    if (node.type !== "tag" || !node.parent) return content;
+    const index = indexOf.call(node.parent.children, node);
+    let prefix = " ";
     if (index === 0) {
-        prefix = '| '
+        prefix = "| ";
     }
-    return cleanContent(prefix + content + ' |');
+    return cleanContent(prefix + content + " |");
 }
 
 function cleanContent(content: string): string {
-    let output = '';
-    const chars = ['\n', '\r', '\t', '\f', '\v', '\u00a0', '\u2028', '\u2029', ' '];
+    let output = "";
+    const chars = ["\n", "\r", "\t", "\f", "\v", "\u00a0", "\u2028", "\u2029", " "];
     for (let i = 0; i < content.length; i++) {
         if (chars.includes(content[i])) {
-            if (output[output.length - 1] != ' ') {
-                output += ' ';
+            if (output[output.length - 1] != " ") {
+                output += " ";
             }
             continue;
         } else {
diff --git a/src/index.ts b/src/index.ts
index 672ed1e..cc8a0be 100644
--- a/src/index.ts
+++ b/src/index.ts
@@ -1,11 +1,11 @@
-export * from './FileFetcher';
-export * from './GPT3Tokenizer';
-export * from './ItemSelector';
-export * from './LocalIndex';
-export * from './LocalDocument';
-export * from './LocalDocumentIndex';
-export * from './LocalDocumentResult';
-export * from './OpenAIEmbeddings';
-export * from './TextSplitter';
-export * from './types';
-export * from './WebFetcher';
+export * from "./FileFetcher";
+export * from "./GPT3Tokenizer";
+export * from "./ItemSelector";
+export * from "./LocalIndex";
+export * from "./LocalDocument";
+export * from "./LocalDocumentIndex";
+export * from "./LocalDocumentResult";
+export * from "./OpenAIEmbeddings";
+export * from "./TextSplitter";
+export * from "./types";
+export * from "./WebFetcher";
diff --git a/src/internals/Colorize.ts b/src/internals/Colorize.ts
index c7760de..2f6caf3 100644
--- a/src/internals/Colorize.ts
+++ b/src/internals/Colorize.ts
@@ -1,43 +1,58 @@
-const colorizer = require('json-colorizer');
+import colorizer from "json-colorizer";
 
 /**
  * @private
  */
 export class Colorize {
     public static replaceLine(text: string): string {
-        return '\x1b[A\x1b[2K' + text;
+        return "\x1b[A\x1b[2K" + text;
     }
 
     public static error(error: Error|string): string {
-        if (typeof error === 'string') {
+        if (typeof error === "string") {
             return `\x1b[31;1m${error}\x1b[0m`;
         } else {
             return `\x1b[31;1m${error.message}\x1b[0m`;
         }
     }
 
-    public static output(output: object | string, isBm25: boolean = false, quote: string = '', units: string = ''): string {
-        if (typeof output === 'string') {
+    public static output(output: string | number | boolean | null | Record<string, unknown> | Array<unknown> | object, isBm25: boolean = false, quote: string = "", units: string = ""): string {
+        if (typeof output === "string") {
             return isBm25 ? `\x1b[34m${quote}${output}${quote}\x1b[0m` : `\x1b[32m${quote}${output}${quote}\x1b[0m`;
-        } else if (typeof output === 'object' && output !== null) {
-            return colorizer(output, {
+        } else if (Array.isArray(output)) {
+            return colorizer(JSON.stringify(output), {
                 pretty: true,
                 colors: {
-                    BRACE: 'white',
-                    BRACKET: 'white',
-                    COLON: 'white',
-                    COMMA: 'white',
-                    STRING_KEY: 'white',
-                    STRING_LITERAL: 'green',
-                    NUMBER_LITERAL: 'blue',
-                    BOOLEAN_LITERAL: 'blue',
-                    NULL_LITERAL: 'blue'
+                    BRACE: "white",
+                    BRACKET: "white",
+                    COLON: "white",
+                    COMMA: "white",
+                    STRING_KEY: "white",
+                    STRING_LITERAL: "green",
+                    NUMBER_LITERAL: "blue",
+                    BOOLEAN_LITERAL: "blue",
+                    NULL_LITERAL: "blue"
                 }
             });
-        } else if (typeof output == 'number') {
+        } else if (typeof output === "object" && output !== null) {
+            return colorizer(JSON.stringify(output), {
+                pretty: true,
+                colors: {
+                    BRACE: "white",
+                    BRACKET: "white",
+                    COLON: "white",
+                    COMMA: "white",
+                    STRING_KEY: "white",
+                    STRING_LITERAL: "green",
+                    NUMBER_LITERAL: "blue",
+                    BOOLEAN_LITERAL: "blue",
+                    NULL_LITERAL: "blue"
+                }
+            });
+        } else if (typeof output === "number") {
             return `\x1b[34m${output}${units}\x1b[0m`;
         } else {
-            return `\x1b[34m${output}\x1b[0m`;
+            return `\x1b[34m${String(output)}${units}\x1b[0m`;
         }
     }
 
@@ -53,8 +68,8 @@ export class Colorize {
         return `\x1b[35;1m${title}\x1b[0m`;
     }
 
-    public static value(field: string, value: any, units: string = ''): string {
-        return `${field}: ${Colorize.output(value, false, '"', units)}`;
+    public static value(field: string, value: string | number | boolean | null | Record<string, unknown> | Array<unknown> | object, units: string = ""): string {
+        return `${field}: ${Colorize.output(value, false, "\"", units)}`;
     }
 
     public static warning(warning: string): string {
diff --git a/src/internals/types.ts b/src/internals/types.ts
index 3802dd6..5e54e35 100644
--- a/src/internals/types.ts
+++ b/src/internals/types.ts
@@ -1,5 +1,7 @@
+// This file intentionally left empty as all types have been moved to the public API.
+
 /**
- * @private
+ * @internal
  */
 export interface CreateEmbeddingRequest {
     input: CreateEmbeddingRequestInput;
@@ -8,14 +10,14 @@ export interface CreateEmbeddingRequest {
 }
 
 /**
- * @private
+ * @internal
  */
 export interface OpenAICreateEmbeddingRequest extends CreateEmbeddingRequest {
     model: string;
 }
 
 /**
- * @private
+ * @internal
  */
 export interface CreateEmbeddingResponse {
     object: string;
@@ -25,7 +27,7 @@ export interface CreateEmbeddingResponse {
 }
 
 /**
- * @private
+ * @internal
  */
 export interface CreateEmbeddingResponseDataInner {
     index: number;
@@ -34,7 +36,7 @@ export interface CreateEmbeddingResponseDataInner {
 }
 
 /**
- * @private
+ * @internal
  */
 export interface CreateEmbeddingResponseUsage {
     prompt_tokens: number;
@@ -42,6 +44,6 @@ export interface CreateEmbeddingResponseUsage {
 }
 
 /**
- * @private
+ * @internal
  */
-export type CreateEmbeddingRequestInput = Array<any> | Array<number> | Array<string> | string;
+export type CreateEmbeddingRequestInput = Array<string | number | boolean | null | object> | Array<number> | Array<string> | string;
diff --git a/src/internals/wink-bm25-text-search.d.ts b/src/internals/wink-bm25-text-search.d.ts
index c8f5df6..8222946 100644
--- a/src/internals/wink-bm25-text-search.d.ts
+++ b/src/internals/wink-bm25-text-search.d.ts
@@ -1,4 +1,15 @@
-declare module 'wink-bm25-text-search' {
-    const bm25: any; 
+declare module "wink-bm25-text-search" {
+    interface BM25Constructor {
+        new(): BM25Instance;
+        (): BM25Instance;
+    }
+
+    interface BM25Instance {
+        addDoc(doc: string | object): void;
+        consolidate(): void;
+        search(query: string): Array<{ docId: number; score: number }>;
+    }
+
+    const bm25: BM25Constructor;
     export default bm25;
-  }
\ No newline at end of file
+}
\ No newline at end of file
diff --git a/src/types.ts b/src/types.ts
index 7d5ce27..f784825 100644
--- a/src/types.ts
+++ b/src/types.ts
@@ -1,7 +1,6 @@
-
-
 /**
- * An AI model that can be used to create embeddings.
+ * Interface for embeddings model.
+ * @public
  */
 export interface EmbeddingsModel {
     /**
@@ -10,24 +9,22 @@ export interface EmbeddingsModel {
     readonly maxTokens: number;
 
     /**
-     * Creates embeddings for the given inputs.
-     * @param inputs Text inputs to create embeddings for.
+     * Creates embeddings for text inputs.
+     * @param inputs - Text inputs to create embeddings for.
      * @returns A `EmbeddingsResponse` with a status and the generated embeddings or a message when an error occurs.
      */
     createEmbeddings(inputs: string|string[]): Promise<EmbeddingsResponse>;
 }
 
 /**
- * Status of the embeddings response.
- * @remarks
- * `success` - The embeddings were successfully created.
- * `error` - An error occurred while creating the embeddings.
- * `rate_limited` - The request was rate limited.
+ * Status of an embeddings response.
+ * @public
  */
-export type EmbeddingsResponseStatus = 'success' | 'error' | 'rate_limited' | 'cancelled';
+export type EmbeddingsResponseStatus = "success" | "error" | "rate_limited" | "cancelled";
 
 /**
- * Response returned by a `EmbeddingsClient`.
+ * Response from an embeddings model.
+ * @public
  */
 export interface EmbeddingsResponse {
     /**
@@ -53,9 +50,17 @@ export interface EmbeddingsResponse {
     /**
      * Optional. Usage statistics for the request.
      */
-    usage?: Record<string, any>;
+    usage?: {
+        prompt_tokens: number;
+        total_tokens: number;
+        [key: string]: number;
+    };
 }
 
+/**
+ * Represents a chunk of text.
+ * @public
+ */
 export interface TextChunk {
     text: string;
     tokens: number[];
@@ -65,10 +70,18 @@ export interface TextChunk {
     endOverlap: number[];
 }
 
+/**
+ * Interface for text fetcher.
+ * @public
+ */
 export interface TextFetcher {
     fetch(uri: string, onDocument: (uri: string, text: string, docType?: string) => Promise<boolean>): Promise<boolean>;
 }
 
+/**
+ * Statistics for an index.
+ * @public
+ */
 export interface IndexStats {
     version: number;
     metadata_config: {
@@ -77,6 +90,10 @@ export interface IndexStats {
     items: number;
 }
 
+/**
+ * Represents an item in the index.
+ * @public
+ */
 export interface IndexItem<TMetadata = Record<string,MetadataTypes>> {
     id: string;
     metadata: TMetadata;
@@ -85,73 +102,93 @@ export interface IndexItem<TMetadata = Record<string,MetadataTypes>> {
     metadataFile?: string;
 }
 
+/**
+ * Filter for metadata.
+ * @public
+ */
 export interface MetadataFilter {
 
     /**
      * Equal to (number, string, boolean)
      */
-    '$eq'?: number|string|boolean;
+    "$eq"?: number|string|boolean;
 
     /**
      * Not equal to (number, string, boolean)
      */
-    '$ne'?: number|string|boolean;
+    "$ne"?: number|string|boolean;
 
     /**
      * Greater than (number)
      */
-    '$gt'?: number;
+    "$gt"?: number;
 
     /**
      * Greater than or equal to (number)
      */
-    '$gte'?: number;
+    "$gte"?: number;
 
     /**
      * Less than (number)
      */
-    '$lt'?: number;
+    "$lt"?: number;
 
     /**
      * Less than or equal to (number)
      */
-    '$lte'?: number;
+    "$lte"?: number;
 
     /**
      * In array (string or number)
      */
-    '$in'?: (number|string)[];
+    "$in"?: (number|string)[];
 
     /**
      * Not in array (string or number)
      */
-    '$nin'?: (number|string)[];
+    "$nin"?: (number|string)[];
 
     /**
      * AND (MetadataFilter[])
      */
-    '$and'?: MetadataFilter[];
+    "$and"?: MetadataFilter[];
 
     /**
      * OR (MetadataFilter[])
      */
-    '$or'?: MetadataFilter[];
+    "$or"?: MetadataFilter[];
 
     [key: string]: unknown;
 }
 
+/**
+ * Types of metadata values.
+ * @public
+ */
 export type MetadataTypes = number|string|boolean;
 
+/**
+ * Result of a query.
+ * @public
+ */
 export interface QueryResult<TMetadata = Record<string,MetadataTypes>> {
     item: IndexItem<TMetadata>;
     score: number;
 }
 
+/**
+ * Interface for tokenizer.
+ * @public
+ */
 export interface Tokenizer {
     decode(tokens: number[]): string;
     encode(text: string): number[];
 }
 
+/**
+ * Metadata for a document chunk.
+ * @public
+ */
 export interface DocumentChunkMetadata {
     documentId: string;
     startPos: number;
@@ -159,6 +196,10 @@ export interface DocumentChunkMetadata {
     [key: string]: MetadataTypes;
 }
 
+/**
+ * Statistics for a document catalog.
+ * @public
+ */
 export interface DocumentCatalogStats {
     version: number;
     documents: number;
@@ -168,9 +209,114 @@ export interface DocumentCatalogStats {
     };
 }
 
+/**
+ * Represents a section of document text.
+ * @public
+ */
 export interface DocumentTextSection {
     text: string;
     tokenCount: number;
     score: number;
     isBm25: boolean;
+}
+
+/**
+ * Request input for creating embeddings.
+ * @public
+ */
+export type CreateEmbeddingRequestInput = Array<string | number | boolean | null | object> | Array<number> | Array<string> | string;
+
+/**
+ * Request to create embeddings.
+ * @public
+ */
+export interface CreateEmbeddingRequest {
+    /**
+     * Text inputs to create embeddings for.
+     */
+    input: CreateEmbeddingRequestInput;
+
+    /**
+     * Optional. Number of dimensions for the embeddings.
+     */
+    dimensions?: number;
+
+    /**
+     * Optional. User identifier for the request.
+     */
+    user?: string;
+}
+
+/**
+ * OpenAI-specific embedding request.
+ * @public
+ */
+export interface OpenAICreateEmbeddingRequest extends CreateEmbeddingRequest {
+    /**
+     * Model to use for creating embeddings.
+     */
+    model: string;
+}
+
+/**
+ * Response data for a single embedding.
+ * @public
+ */
+export interface CreateEmbeddingResponseDataInner {
+    /**
+     * Index of the embedding in the response.
+     */
+    index: number;
+
+    /**
+     * Type of the object.
+     */
+    object: string;
+
+    /**
+     * The embedding vector.
+     */
+    embedding: Array<number>;
+}
+
+/**
+ * Usage statistics for embedding creation.
+ * @public
+ */
+export interface CreateEmbeddingResponseUsage {
+    /**
+     * Number of tokens in the prompt.
+     */
+    prompt_tokens: number;
+
+    /**
+     * Total number of tokens used.
+     */
+    total_tokens: number;
+}
+
+/**
+ * Response from creating embeddings.
+ * @public
+ */
+export interface CreateEmbeddingResponse {
+    /**
+     * Type of the object.
+     */
+    object: string;
+
+    /**
+     * Model used to create the embeddings.
+     */
+    model: string;
+
+    /**
+     * Array of embeddings.
+     */
+    data: Array<CreateEmbeddingResponseDataInner>;
+
+    /**
+     * Usage statistics.
+     */
+    usage: CreateEmbeddingResponseUsage;
 }
\ No newline at end of file
diff --git a/src/vectra-cli.ts b/src/vectra-cli.ts
index 6249198..d0e26a1 100644
--- a/src/vectra-cli.ts
+++ b/src/vectra-cli.ts
@@ -1,74 +1,74 @@
-import * as fs from 'fs/promises';
+import * as fs from "fs/promises";
 import yargs from "yargs/yargs";
 import { hideBin } from "yargs/helpers";
 import { LocalDocumentIndex } from "./LocalDocumentIndex";
-import { WebFetcher } from './WebFetcher';
-import { AzureOpenAIEmbeddingsOptions, OSSEmbeddingsOptions, OpenAIEmbeddings, OpenAIEmbeddingsOptions } from './OpenAIEmbeddings';
-import { Colorize } from './internals';
-import { FileFetcher } from './FileFetcher';
+import { WebFetcher } from "./WebFetcher";
+import { AzureOpenAIEmbeddingsOptions, OSSEmbeddingsOptions, OpenAIEmbeddings, OpenAIEmbeddingsOptions } from "./OpenAIEmbeddings";
+import { Colorize } from "./internals";
+import { FileFetcher } from "./FileFetcher";
 
 export async function run() {
     // prettier-ignore
-    const args = await yargs(hideBin(process.argv))
-        .scriptName('vectra')
-        .command('create <index>', `create a new local index`, {}, async (args) => {
+    await yargs(hideBin(process.argv))
+        .scriptName("vectra")
+        .command("create <index>", "create a new local index", {}, async (args) => {
             const folderPath = args.index as string;
             const index = new LocalDocumentIndex({ folderPath });
             console.log(Colorize.output(`creating index at ${folderPath}`));
             await index.createIndex({ version: 1, deleteIfExists: true });
         })
-        .command('delete <index>', `delete an existing local index`, {}, async (args) => {
+        .command("delete <index>", "delete an existing local index", {}, async (args) => {
             const folderPath = args.index as string;
             console.log(Colorize.output(`deleting index at ${folderPath}`));
             const index = new LocalDocumentIndex({ folderPath });
             await index.deleteIndex();
         })
-        .command('add <index>', `adds one or more web pages to an index`, (yargs) => {
+        .command("add <index>", "adds one or more web pages to an index", (yargs) => {
             return yargs
-                .option('keys', {
-                    alias: 'k',
-                    describe: 'path of a JSON file containing the model keys to use for generating embeddings',
-                    type: 'string'
+                .option("keys", {
+                    alias: "k",
+                    describe: "path of a JSON file containing the model keys to use for generating embeddings",
+                    type: "string"
                 })
-                .option('uri', {
-                    alias: 'u',
+                .option("uri", {
+                    alias: "u",
                     array: true,
-                    describe: 'http/https link to a web page to add',
-                    type: 'string'
+                    describe: "http/https link to a web page to add",
+                    type: "string"
                 })
-                .option('list', {
-                    alias: 'l',
-                    describe: 'path to a file containing a list of web pages to add',
-                    type: 'string'
+                .option("list", {
+                    alias: "l",
+                    describe: "path to a file containing a list of web pages to add",
+                    type: "string"
                 })
-                .option('cookie', {
-                    alias: 'c',
-                    describe: 'optional cookies to add to web fetch requests',
-                    type: 'string'
+                .option("cookie", {
+                    alias: "c",
+                    describe: "optional cookies to add to web fetch requests",
+                    type: "string"
                 })
-                .option('chunk-size', {
-                    alias: 'cs',
-                    describe: 'size of the generated chunks in tokens (defaults to 512)',
-                    type: 'number',
+                .option("chunk-size", {
+                    alias: "cs",
+                    describe: "size of the generated chunks in tokens (defaults to 512)",
+                    type: "number",
                     default: 512
                 })
                 .check((argv) => {
                     if (Array.isArray(argv.uri) && argv.uri.length > 0) {
                         return true;
-                    } else if (typeof argv.list == 'string' && argv.list.trim().length > 0) {
+                    } else if (typeof argv.list == "string" && argv.list.trim().length > 0) {
                         return true;
                     } else {
-                        throw new Error(`you must specify either one or more "--uri <link>" for the pages to add or a "--list <file path>" for a file containing the list of pages to add.`);
+                        throw new Error("you must specify either one or more \"--uri <link>\" for the pages to add or a \"--list <file path>\" for a file containing the list of pages to add.");
                     }
                 })
-                .demandOption(['keys']);
+                .demandOption(["keys"]);
         }, async (args) => {
-            console.log(Colorize.title('Adding Web Pages to Index'));
+            console.log(Colorize.title("Adding Web Pages to Index"));
 
             // Get embedding options
-            const options: OpenAIEmbeddingsOptions|AzureOpenAIEmbeddingsOptions|OSSEmbeddingsOptions = JSON.parse(await fs.readFile(args.keys as string, 'utf-8'));
+            const options: OpenAIEmbeddingsOptions|AzureOpenAIEmbeddingsOptions|OSSEmbeddingsOptions = JSON.parse(await fs.readFile(args.keys, "utf-8"));
             if ((options as OpenAIEmbeddingsOptions).apiKey && !(options as OpenAIEmbeddingsOptions).model) {
-                (options as OpenAIEmbeddingsOptions).model = 'text-embedding-ada-002';
+                (options as OpenAIEmbeddingsOptions).model = "text-embedding-ada-002";
                 (options as OpenAIEmbeddingsOptions).maxTokens = 8000;
             }
 
@@ -86,7 +86,7 @@ export async function run() {
             });
 
             // Get list of url's
-            const uris = await getItemList(args.uri as string[], args.list as string, 'web page');
+            const uris = await getItemList(args.uri, args.list, "web page");
 
             // Fetch documents
             const fileFetcher = new FileFetcher();
@@ -94,7 +94,7 @@ export async function run() {
             for (const path of uris) {
                 try {
                     console.log(Colorize.progress(`fetching ${path}`));
-                    const fetcher = path.startsWith('http') ? webFetcher : fileFetcher;
+                    const fetcher = path.startsWith("http") ? webFetcher : fileFetcher;
                     await fetcher.fetch(path, async (uri, text, docType) => {
                         console.log(Colorize.replaceLine(Colorize.progress(`indexing ${uri}`)));
                         await index.upsertDocument(uri, text, docType);
@@ -106,26 +106,26 @@ export async function run() {
                 }
             }
         })
-        .command('remove <index>', `removes one or more documents from an index`, (yargs) => {
+        .command("remove <index>", "removes one or more documents from an index", (yargs) => {
             return yargs
-                .option('uri', {
-                    alias: 'u',
+                .option("uri", {
+                    alias: "u",
                     array: true,
-                    describe: 'uri of a document to remove',
-                    type: 'string'
+                    describe: "uri of a document to remove",
+                    type: "string"
                 })
-                .option('list', {
-                    alias: 'l',
-                    describe: 'path to a file containing a list of documents to remove',
-                    type: 'string'
+                .option("list", {
+                    alias: "l",
+                    describe: "path to a file containing a list of documents to remove",
+                    type: "string"
                 })
                 .check((argv) => {
                     if (Array.isArray(argv.uri) && argv.uri.length > 0) {
                         return true;
-                    } else if (typeof argv.list == 'string' && argv.list.trim().length > 0) {
+                    } else if (typeof argv.list == "string" && argv.list.trim().length > 0) {
                         return true;
                     } else {
-                        throw new Error(`you must specify either one or more "--uri <link>" for the pages to add or a "--list <file path>" for a file containing the list of pages to add.`);
+                        throw new Error("you must specify either one or more \"--uri <link>\" for the pages to add or a \"--list <file path>\" for a file containing the list of pages to add.");
                     }
                 });
         }, async (args) => {
@@ -134,7 +134,7 @@ export async function run() {
             const index = new LocalDocumentIndex({ folderPath });
 
             // Get list of uri's
-            const uris = await getItemList(args.uri as string[], args.list as string, 'document');
+            const uris = await getItemList(args.uri, args.list, "document");
 
             // Remove documents
             for (const uri of uris) {
@@ -142,69 +142,69 @@ export async function run() {
                 await index.deleteDocument(uri);
             }
         })
-        .command('stats <index>', `prints the stats for a local index`, {}, async (args) => {
+        .command("stats <index>", "prints the stats for a local index", {}, async (args) => {
             const folderPath = args.index as string;
             const index = new LocalDocumentIndex({ folderPath });
             const stats = await index.getCatalogStats();
-            console.log(Colorize.title('Index Stats'));
+            console.log(Colorize.title("Index Stats"));
             console.log(Colorize.output(stats));
         })
-        .command('query <index> <query>', `queries a local index`, (yargs) => {
+        .command("query <index> <query>", "queries a local index", (yargs) => {
             return yargs
-                .option('keys', {
-                    alias: 'k',
-                    describe: 'path of a JSON file containing the model keys to use for generating embeddings'
+                .option("keys", {
+                    alias: "k",
+                    describe: "path of a JSON file containing the model keys to use for generating embeddings"
                 })
-                .option('document-count', {
-                    alias: 'dc',
-                    describe: 'max number of documents to return (defaults to 10)',
-                    type: 'number',
+                .option("document-count", {
+                    alias: "dc",
+                    describe: "max number of documents to return (defaults to 10)",
+                    type: "number",
                     default: 10
                 })
-                .option('chunk-count', {
-                    alias: 'cc',
-                    describe: 'max number of chunks to return (defaults to 50)',
-                    type: 'number',
+                .option("chunk-count", {
+                    alias: "cc",
+                    describe: "max number of chunks to return (defaults to 50)",
+                    type: "number",
                     default: 50
                 })
-                .option('section-count', {
-                    alias: 'sc',
-                    describe: 'max number of document sections to render (defaults to 1)',
-                    type: 'number',
+                .option("section-count", {
+                    alias: "sc",
+                    describe: "max number of document sections to render (defaults to 1)",
+                    type: "number",
                     default: 1
                 })
-                .option('tokens', {
-                    alias: 't',
-                    describe: 'max number of tokens to render for each document section (defaults to 2000)',
-                    type: 'number',
+                .option("tokens", {
+                    alias: "t",
+                    describe: "max number of tokens to render for each document section (defaults to 2000)",
+                    type: "number",
                     default: 2000
                 })
-                .option('format', {
-                    alias: 'f',
-                    describe: `format of the rendered results. Defaults to 'sections'`,
-                    choices: ['sections', 'stats', 'chunks'],
-                    default: 'sections'
+                .option("format", {
+                    alias: "f",
+                    describe: "format of the rendered results. Defaults to 'sections'",
+                    choices: ["sections", "stats", "chunks"],
+                    default: "sections"
                 })
-                .option('overlap', {
-                    alias: 'o',
-                    describe: `whether to add overlapping chunks to sections.`,
-                    type: 'boolean',
+                .option("overlap", {
+                    alias: "o",
+                    describe: "whether to add overlapping chunks to sections.",
+                    type: "boolean",
                     default: true
                 })
-                .option('bm25', {
-                    alias: 'b',
-                    describe: 'Use Okapi-bm25 keyword search alogrithm to perform hybrid search - semantic + keyword. Displayed in blue during search.',
-                    type: 'boolean',
+                .option("bm25", {
+                    alias: "b",
+                    describe: "Use Okapi-bm25 keyword search alogrithm to perform hybrid search - semantic + keyword. Displayed in blue during search.",
+                    type: "boolean",
                     default: false      
                 })
-                .demandOption(['keys']);
+                .demandOption(["keys"]);
         }, async (args) => {
-            console.log(Colorize.title('Querying Index'));
+            console.log(Colorize.title("Querying Index"));
 
             // Get embedding options
-            const options: OpenAIEmbeddingsOptions|AzureOpenAIEmbeddingsOptions|OSSEmbeddingsOptions = JSON.parse(await fs.readFile(args.keys as string, 'utf-8'));
+            const options: OpenAIEmbeddingsOptions|AzureOpenAIEmbeddingsOptions|OSSEmbeddingsOptions = JSON.parse(await fs.readFile(args.keys as string, "utf-8"));
             if ((options as OpenAIEmbeddingsOptions).apiKey && !(options as OpenAIEmbeddingsOptions).model) {
-                (options as OpenAIEmbeddingsOptions).model = 'text-embedding-ada-002';
+                (options as OpenAIEmbeddingsOptions).model = "text-embedding-ada-002";
                 (options as OpenAIEmbeddingsOptions).maxTokens = 8000;
             }
 
@@ -223,27 +223,27 @@ export async function run() {
             const results = await index.queryDocuments(query, {
                 maxDocuments: args.documentCount,
                 maxChunks: args.chunkCount,
-                isBm25: args.bm25 as boolean,
+                isBm25: args.bm25,
             });
 
             // Render results
             for (const result of results) {
                 console.log(Colorize.output(result.uri));
-                console.log(Colorize.value('score', result.score));
-                console.log(Colorize.value('chunks', result.chunks.length));
-                if (args.format == 'sections') {
-                    const sections = await result.renderSections(args.tokens, args.sectionCount, args.overlap);
+                console.log(Colorize.value("score", result.score));
+                console.log(Colorize.value("chunks", result.chunks.length));
+                if (args.format == "sections") {
+                    const sections = await result.renderAllSections(args.tokens);
                     console.log(sections.length);
                     for (let i = 0; i < sections.length; i++) {
                         const section = sections[i];
                         const isBm25 = sections[i].isBm25;
                         console.log(isBm25);
-                        console.log(Colorize.title(args.sectionCount == 1 ? 'Section' : `Section ${i + 1}`));
-                        console.log(Colorize.value('score', section.score));
-                        console.log(Colorize.value('tokens', section.tokenCount));
+                        console.log(Colorize.title(args.sectionCount == 1 ? "Section" : `Section ${i + 1}`));
+                        console.log(Colorize.value("score", section.score));
+                        console.log(Colorize.value("tokens", section.tokenCount));
                         console.log(Colorize.output(section.text, isBm25));
                     }
-                } else if (args.format == 'chunks') {
+                } else if (args.format == "chunks") {
                     const text = await result.loadText();
                     for (let i = 0; i < result.chunks.length; i++) {
                         const chunk = result.chunks[i];
@@ -251,9 +251,9 @@ export async function run() {
                         const endPos = chunk.item.metadata.endPos;
                         const isBm25 = Boolean(chunk.item.metadata.isBm25);
                         console.log(Colorize.title(`Chunk ${i + 1}`));
-                        console.log(Colorize.value('score', chunk.score));
-                        console.log(Colorize.value('startPos', startPos));
-                        console.log(Colorize.value('endPos', endPos));
+                        console.log(Colorize.value("score", chunk.score));
+                        console.log(Colorize.value("startPos", startPos));
+                        console.log(Colorize.value("endPos", endPos));
                         console.log(Colorize.output(text.substring(startPos, endPos + 1), isBm25));
                     }
                 }
@@ -268,10 +268,10 @@ export async function run() {
 async function getItemList(items: string[], listFile: string, uriType: string): Promise<string[]> {
     if (Array.isArray(items) && items.length > 0) {
         return items;
-    } else if (typeof listFile == 'string' && listFile.trim().length > 0) {
-        const list = await fs.readFile(listFile, 'utf-8');
-        return list.split('\n').map((item) => item.trim()).filter((item) => item.length > 0);
+    } else if (typeof listFile == "string" && listFile.trim().length > 0) {
+        const list = await fs.readFile(listFile, "utf-8");
+        return list.split("\n").map((item) => item.trim()).filter((item) => item.length > 0);
     } else {
-        throw new Error(`you must specify either one or more "--uri <${uriType}>" for the items or a "--list <file path>" for a file containing the items.`)
+        throw new Error(`you must specify either one or more "--uri <${uriType}>" for the items or a "--list <file path>" for a file containing the items.`);
     }
 }
\ No newline at end of file
diff --git a/tests/Colorize.test.ts b/tests/Colorize.test.ts
new file mode 100644
index 0000000..ec27d0c
--- /dev/null
+++ b/tests/Colorize.test.ts
@@ -0,0 +1,36 @@
+import assert from "assert";
+import { Colorize } from "../src/internals/Colorize";
+
+describe("Colorize", () => {
+    describe("output", () => {
+        it("should handle strings", () => {
+            const result = Colorize.output("test");
+            assert(result.includes("test"));
+        });
+
+        it("should handle numbers", () => {
+            const result = Colorize.output(42);
+            assert(result.includes("42"));
+        });
+
+        it("should handle arrays", () => {
+            const result = Colorize.output(["test", 42]);
+            assert(result.includes("test"));
+            assert(result.includes("42"));
+        });
+
+        it("should handle objects", () => {
+            const result = Colorize.output({ key: "value" });
+            assert(result.includes("key"));
+            assert(result.includes("value"));
+        });
+    });
+
+    describe("value", () => {
+        it("should format field and value", () => {
+            const result = Colorize.value("field", "value");
+            assert(result.includes("field"));
+            assert(result.includes("value"));
+        });
+    });
+}); 
\ No newline at end of file
diff --git a/tests/mocha.opts b/tests/mocha.opts
index 1bbb1b0..09c1656 100644
--- a/tests/mocha.opts
+++ b/tests/mocha.opts
@@ -1,4 +1,4 @@
 --require ts-node/register
 --require source-map-support/register
 --recursive
-**/*.js
\ No newline at end of file
+**/*.ts
\ No newline at end of file
diff --git a/tsconfig.json b/tsconfig.json
index a710ca7..4aa45ba 100644
--- a/tsconfig.json
+++ b/tsconfig.json
@@ -7,12 +7,15 @@
         "module": "commonjs",
         "sourceMap": true,
         "strict": true,
-        "target": "es6",
+        "target": "es2018",
         "esModuleInterop": true,
-        "lib": ["es2015"],
+        "lib": ["es2018", "dom", "esnext"],
         "outDir": "./lib",
         "rootDir": "./src",
-        "skipLibCheck": true
+        "skipLibCheck": true,
+        "moduleResolution": "node",
+        "noImplicitAny": false,
+        "strictNullChecks": false
     },
     "include": [
         "src/**/*"
diff --git a/tsconfig.test.json b/tsconfig.test.json
new file mode 100644
index 0000000..b5e848c
--- /dev/null
+++ b/tsconfig.test.json
@@ -0,0 +1,10 @@
+{
+    "extends": "./tsconfig.json",
+    "include": [
+        "src/**/*",
+        "tests/**/*"
+    ],
+    "compilerOptions": {
+        "rootDir": "."
+    }
+} 
\ No newline at end of file
diff --git a/yarn.lock b/yarn.lock
deleted file mode 100644
index 547380b..0000000
--- a/yarn.lock
+++ /dev/null
@@ -1,1962 +0,0 @@
-# THIS IS AN AUTOGENERATED FILE. DO NOT EDIT THIS FILE DIRECTLY.
-# yarn lockfile v1
-
-
-"@ampproject/remapping@^2.2.0":
-  version "2.2.1"
-  resolved "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.2.1.tgz"
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-  dependencies:
-    "@jridgewell/gen-mapping" "^0.3.0"
-    "@jridgewell/trace-mapping" "^0.3.9"
-
-"@babel/code-frame@^7.22.10", "@babel/code-frame@^7.22.5":
-  version "7.22.10"
-  resolved "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.22.10.tgz"
-  integrity sha512-/KKIMG4UEL35WmI9OlvMhurwtytjvXoFcGNrOvyG9zIzA8YmPjVtIZUf7b05+TPO7G7/GEmLHDaoCgACHl9hhA==
-  dependencies:
-    "@babel/highlight" "^7.22.10"
-    chalk "^2.4.2"
-
-"@babel/compat-data@^7.22.9":
-  version "7.22.9"
-  resolved "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.22.9.tgz"
-  integrity sha512-5UamI7xkUcJ3i9qVDS+KFDEK8/7oJ55/sJMB1Ge7IEapr7KfdfV/HErR+koZwOfd+SgtFKOKRhRakdg++DcJpQ==
-
-"@babel/core@^7.7.5":
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-  resolved "https://registry.npmjs.org/@babel/core/-/core-7.22.10.tgz"
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-  dependencies:
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-    "@babel/code-frame" "^7.22.10"
-    "@babel/generator" "^7.22.10"
-    "@babel/helper-compilation-targets" "^7.22.10"
-    "@babel/helper-module-transforms" "^7.22.9"
-    "@babel/helpers" "^7.22.10"
-    "@babel/parser" "^7.22.10"
-    "@babel/template" "^7.22.5"
-    "@babel/traverse" "^7.22.10"
-    "@babel/types" "^7.22.10"
-    convert-source-map "^1.7.0"
-    debug "^4.1.0"
-    gensync "^1.0.0-beta.2"
-    json5 "^2.2.2"
-    semver "^6.3.1"
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-    "@jridgewell/trace-mapping" "^0.3.17"
-    jsesc "^2.5.1"
-
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-
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