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src/content/docs/autorag/configuration/metadata-filtering.mdx

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Metadata filtering narrows down search results based on metadata, so only relevant content is retrieved. The filter narrows down results prior to retrieval, so that you only query the scope of documents that matter.
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Here is an example of metadata filtering in [Workers Binding](/autorag/usage/workers-binding/) but it can be easily adapted to use the [REST API](/autorag/usage/rest-api/) instead.
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Here is an example of metadata filtering using [Workers Binding](/autorag/usage/workers-binding/) but it can be easily adapted to use the [REST API](/autorag/usage/rest-api/) instead.
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```js
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const answer = await env.AI.autorag("my-autorag").search({
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The directory to the object. For example, the `folder` of the object at `llama/logistics/llama-logistics.mdx` is `llama/logistics/`. Note that the `folder` does not include a leading `/`.
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Note that `folder` filter only includes files exactly on that folder, so files in subdirectories are not included. For example, specifying `folder: "llama/"` will match files in `llama/` but does not match files in `llama/logistics`.
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Note that `folder` filter only includes files exactly in that folder, so files in subdirectories are not included. For example, specifying `folder: "llama/"` will match files in `llama/` but does not match files in `llama/logistics`.
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### `modified_date`
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### Comparison filter
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You can compare a metadata attribute (e.g. `folder` or `modified_date`) with a target value using a comparison filter.
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You can compare a metadata attribute (for example, `folder` or `modified_date`) with a target value using a comparison filter.
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```js
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filters: {
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- No nesting combinations of `and`'s and `or`'s, meaning you can only pick 1 `and` or 1 `or`.
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- When using `or`:
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- Only the `eq` operator is allowed.
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- All conditions must filter on the **same key** (e.g. all on `folder`)
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- All conditions must filter on the **same key** (for example, all on `folder`)
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## Response
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src/content/docs/autorag/how-to/bring-your-own-generation-model.mdx

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When using `AI Search`, AutoRAG leverages a Workers AI model to generate the response. If you want to use a model outside of Workers AI, you can use AutoRAG for search while leveraging a model outside of Workers AI to generate responses.
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Here is an example of how you can use an OpenAI model to generate your responses. This example is done using [Workers Binding](/autorag/usage/workers-binding/) but can be easily adapted to use the [REST API](/autorag/usage/rest-api/) instead.
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Here is an example of how you can use an OpenAI model to generate your responses. This example uses [Workers Binding](/autorag/usage/workers-binding/), but can be easily adapted to use the [REST API](/autorag/usage/rest-api/) instead.
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```ts
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import { openai } from "@ai-sdk/openai";

src/content/docs/autorag/how-to/multitenancy.mdx

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customer-b/contracts/
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```
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When indexing, AutoRAG will automatically store the folder path as metadata under the `folder` attribute. It’s recommended to enforce folder separation during upload or indexing to prevent accidental data access across tenants.
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When indexing, AutoRAG will automatically store the folder path as metadata under the `folder` attribute. It is recommended to enforce folder separation during upload or indexing to prevent accidental data access across tenants.
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## 2. Search Using Folder Filters
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src/content/docs/autorag/how-to/simple-search-engine.mdx

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order: 5
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---
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Using the `search` method you can implement a simple but fast search engine. This example is done using [Workers Binding](/autorag/usage/workers-binding/) but can be easily adapted to use the [REST API](/autorag/usage/rest-api/) instead.
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By using the `search` method, you can implement a simple but fast search engine. This example uses [Workers Binding](/autorag/usage/workers-binding/), but can be easily adapted to use the [REST API](/autorag/usage/rest-api/) instead.
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To replicate this example remember to:
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- Disable `rewrite_query` as you want to match the original user query
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- Disable `rewrite_query`, as you want to match the original user query
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- Configure your AutoRAG to have small chunk sizes, usually 256 tokens is enough
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```ts

src/content/partials/autorag/ai-search-api-params.mdx

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`filters` <Type text="object" /> <MetaInfo text="optional" />
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Narrow down search results based on metadata, like folder and date, so only relevant content is retrieved. For more details, see [Metadata filtering](/autorag/configuration/metadata-filtering).
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Narrow down search results based on metadata, like folder and date, so only relevant content is retrieved. For more details, refer to [Metadata filtering](/autorag/configuration/metadata-filtering).

src/content/partials/autorag/search-api-params.mdx

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`filters` <Type text="object" /> <MetaInfo text="optional" />
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Narrow down search results based on metadata, like folder and date, so only relevant content is retrieved. For more details, see [Metadata filtering](/autorag/configuration/metadata-filtering).
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Narrow down search results based on metadata, like folder and date, so only relevant content is retrieved. For more details, refer to [Metadata filtering](/autorag/configuration/metadata-filtering).

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