> ## Documentation Index
> Fetch the complete documentation index at: https://www.octogen.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Find products similar to a source product

> Use Octogen's More Like This endpoint to build related-product rails, substitutions, and similar-item recommendations from a product URL or UUID.

The More Like This endpoint finds products similar to a known source product. It is product-anchored: pass a product URL or indexed UUID, and Octogen derives the query from product enrichment, style, tags, audience, and optional facet constraints.

Use `POST /v1/products/more-like-this` when you already have a product and want related items. Use [`POST /v1/products/search`](/docs/guides/catalog-search) when the user starts from a keyword, facets, or an arbitrary price range.

## Basic similar-products request

<CodeGroup>
  ```bash curl theme={null}
  curl -sS https://api.octogen.ai/v1/products/more-like-this \
    -H "Authorization: Bearer $OCTO_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "source": {
        "url": "https://warrenlotas.com/products/black-hoodie"
      },
      "limit": 12
    }'
  ```

  ```python Python theme={null}
  import asyncio
  from octogen_ai_sdk import OctogenClient

  async def main() -> None:
      async with OctogenClient() as client:
          page = await client.more_like_this_products(
              source_url="https://warrenlotas.com/products/black-hoodie",
              limit=12,
          )
          for product in page.items:
              print(product.title, product.product_url)

  asyncio.run(main())
  ```

  ```typescript TypeScript theme={null}
  import { OctogenClient } from "@octogen-ai/sdk";

  const client = new OctogenClient();
  const page = await client.moreLikeThisProducts({
    source: { url: "https://warrenlotas.com/products/black-hoodie" },
    limit: 12,
  });

  for (const product of page.items) {
    console.log(product.title, product.productUrl);
  }
  ```
</CodeGroup>

## Scope to one catalog

Omit `catalog` to search across all active crawled catalogs. Pass `catalog` when a related-products rail should stay within the same merchant:

```json theme={null}
{
  "source": {
    "url": "https://warrenlotas.com/products/black-hoodie"
  },
  "catalog": "warrenlotas",
  "limit": 12
}
```

## Choose relative price behavior

`price_preference` is relative to the source product's `currentPrice`:

| Value    | Behavior                                       |
| -------- | ---------------------------------------------- |
| `any`    | No relative price filter. This is the default. |
| `lower`  | Prefer less expensive alternatives.            |
| `higher` | Prefer premium alternatives.                   |

```python theme={null}
page = await client.more_like_this_products(
    source_url="https://warrenlotas.com/products/black-hoodie",
    price_preference="higher",
    limit=8,
)
```

## Add include or exclude facets

Use `include_facets` to pin extra requirements and `exclude_facets` to remove unwanted matches. These filters use the same facet shape as catalog search.

<CodeGroup>
  ```bash curl theme={null}
  curl -sS https://api.octogen.ai/v1/products/more-like-this \
    -H "Authorization: Bearer $OCTO_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "source": {
        "url": "https://warrenlotas.com/products/black-hoodie"
      },
      "include_facets": [
        {"name": "gender", "values": ["unisex"]}
      ],
      "exclude_facets": [
        {"name": "color_family", "values": ["White"]}
      ],
      "limit": 12
    }'
  ```

  ```typescript TypeScript theme={null}
  import { FacetName, OctogenClient } from "@octogen-ai/sdk";

  const client = new OctogenClient();
  const page = await client.moreLikeThisProducts({
    source: { url: "https://warrenlotas.com/products/black-hoodie" },
    includeFacets: [{ name: FacetName.GENDER, values: ["unisex"] }],
    excludeFacets: [{ name: FacetName.COLOR_FAMILY, values: ["White"] }],
    limit: 12,
  });
  ```
</CodeGroup>

## Debug the derived query

Set `debug: true` to inspect the public, server-derived query fields used for retrieval:

```json theme={null}
{
  "source": {
    "uuid": "prod_01HX..."
  },
  "debug": true,
  "limit": 6
}
```

The response adds `effectiveQuery` with fields such as `text`, `retrievalEmbeddingColumns`, `facets`, `priceMin`, `priceMax`, and `limit`. Use this for diagnostics and logging, not as a stable replacement for the endpoint itself.

## Paginate similar products

More Like This uses the same cursor model as search. When a response contains `nextCursor`, pass it back as `cursor` with the same source and filters:

```typescript theme={null}
let cursor: string | undefined;

do {
  const page = await client.moreLikeThisProducts({
    source: { url: "https://warrenlotas.com/products/black-hoodie" },
    cursor,
    limit: 12,
  });
  cursor = page.nextCursor ?? undefined;
} while (cursor != null);
```

## Going further

For five worked recommendation strategies — same-look, attribute matching, broad discovery, attribute-retrieval ranked by style, and price-bounded similarity — with real requests and live results, see the [strategy recipes guide](/docs/guides/mlt-strategy-recipes).