> ## Documentation Index
> Fetch the complete documentation index at: https://doc.lucidworks.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Recommend Items for Item Stage

export const schema = {
  "type": "object",
  "title": "Recommend Items for Item",
  "description": "This stage returns item-item recommendations or boost similar items for an item ",
  "required": ["boostingMethod", "boostingParam"],
  "properties": {
    "skip": {
      "type": "boolean",
      "title": "Skip This Stage",
      "description": "Set to true to skip this stage.",
      "default": false,
      "hints": ["advanced"]
    },
    "label": {
      "type": "string",
      "title": "Label",
      "description": "A unique label for this stage.",
      "hints": ["advanced"],
      "maxLength": 255
    },
    "condition": {
      "type": "string",
      "title": "Condition",
      "description": "Define a conditional script that must result in true or false. This can be used to determine if the stage should process or not.",
      "hints": ["code", "code/javascript", "advanced"]
    },
    "numRecommendations": {
      "type": "integer",
      "title": "Number of Recommendations",
      "default": 10
    },
    "modelID": {
      "type": "string",
      "title": "Model ID",
      "default": "*"
    },
    "collection": {
      "type": "string",
      "title": "Recommendation Collection",
      "description": "If left blank, the default recommendation collection for the collection being queried will be used."
    },
    "resultsLocation": {
      "type": "string",
      "title": "Results Location",
      "description": "If As Response is chosen, then the result of the RPC call will be the one and only response.  In all other cases, the stage will put the response from the REST/RPC call into the target location using the resultsKey. ",
      "enum": ["As Boosts", "As Response"],
      "default": "As Boosts"
    },
    "modelIdField": {
      "type": "string",
      "title": "Model ID Field",
      "description": "the name of the field in the recommendation collection where model ID is stored",
      "default": "modelId",
      "hints": ["advanced"]
    },
    "scaleRange": {
      "type": "object",
      "title": "Scale Boosts",
      "description": "Scale the boost values to a [min,max] range",
      "required": ["scaleMin", "scaleMax"],
      "properties": {
        "scaleMin": {
          "type": "number",
          "title": "Minimum value of the scale range"
        },
        "scaleMax": {
          "type": "number",
          "title": "Maximum value of the scale range"
        }
      },
      "hints": ["advanced"]
    },
    "foldInUpdates": {
      "type": "boolean",
      "title": "Estimate Recent Results",
      "description": "Update recommendations based on user activity that has happened since the last recommendation job run",
      "hints": ["advanced"]
    },
    "boostFieldName": {
      "type": "string",
      "title": "Boost Field",
      "description": "The field name to boost the values on.",
      "default": "id",
      "hints": ["advanced"]
    },
    "boostingMethod": {
      "type": "string",
      "title": "Boost Method",
      "description": "The boost method to use. query-parser should be chosen if defType!=edismax for main query.",
      "enum": ["query-param", "query-parser"],
      "default": "query-param",
      "hints": ["advanced"]
    },
    "boostingParam": {
      "type": "string",
      "title": "Boost Param",
      "description": "’Boost' multiplies scores by the boost values whereas 'bq' adds optional clauses to main query.",
      "enum": ["boost", "bq"],
      "default": "boost",
      "hints": ["advanced"]
    },
    "itemIdParam": {
      "type": "string",
      "title": "Item ID Request Parameter",
      "description": "The name of the request parameter containing the item ID",
      "default": "item_id"
    },
    "itemIdField": {
      "type": "string",
      "title": "Item ID Field",
      "description": "the name of the field in the recommendation collection where user ID is stored",
      "default": "itemId",
      "hints": ["advanced"]
    },
    "otherItemIdField": {
      "type": "string",
      "title": "Recommended item ID Field",
      "description": "the name of the field in the recommendation collection where similar item recommendation is stored",
      "default": "otherItemId",
      "hints": ["advanced"]
    },
    "similarityScoreField": {
      "type": "string",
      "title": "Similarity Score Field",
      "description": "the name of the field in the recommendation collection where item similarity is stored",
      "default": "sim",
      "hints": ["advanced"]
    }
  },
  "category": "Results Relevancy",
  "categoryPriority": 6,
  "unsafe": false
};

export const SchemaParamFields = ({schema}) => {
  const sanitize = str => {
    if (typeof str !== "string") return str;
    return str.replace(/^"(.*)"$/s, "$1").replace(/\\/g, "").replace(/"/g, "'");
  };
  const formatDescription = str => {
    const s = sanitize(str);
    return (/[.!?]\)*$/).test(s) ? s : `${s}.`;
  };
  const {description, properties = {}, required: requiredProps = []} = schema;
  const visibleProps = useMemo(() => Object.entries(properties).filter(([, prop]) => !prop.hints?.includes("hidden")), [properties]);
  return <div>
      {description && <p>{formatDescription(description)}</p>}

      {visibleProps.map(([name, prop]) => {
    const isRequired = requiredProps.includes(name);
    const hasDefault = prop.default !== undefined;
    const rawDefault = prop.default;
    const isComplexDefault = hasDefault && (typeof rawDefault === "object" || typeof rawDefault === "string" && (rawDefault.length > 20 || rawDefault.includes('"')));
    const fieldProps = {
      key: name,
      body: prop.title || name,
      type: prop.type,
      ...prop.title && ({
        post: [<><span className="text-stone-400 dark:text-stone-500">API property: </span>{name}</>]
      }),
      ...isRequired && ({
        required: true
      }),
      ...!isComplexDefault && hasDefault ? {
        default: sanitize(String(rawDefault))
      } : {}
    };
    const isObject = prop.type === "object" && prop.properties;
    const isArrayOfObjects = prop.type === "array" && prop.items?.type === "object" && prop.items.properties;
    return <ParamField {...fieldProps}>
            {prop.description && <p>{formatDescription(prop.description)}</p>}

            {isComplexDefault && <div className="flex">
                <p>
                  <strong>Default:</strong>
                </p>
                <pre className="!my-0">
                  <code>
                    {JSON.stringify(rawDefault, null, 2)}
                  </code>
                </pre>
              </div>}

            {isArrayOfObjects && <div className="flex">
              <p>
                <strong>Object attributes:</strong>
              </p>
              <pre className="!my-0">
                <code>
                  {'{\n'}
                  {Object.entries(prop.items.properties).map(([iname, iprop]) => <>
                      {`  ${iname}`}
                      {prop.items?.required?.includes(iname) && <span style={{
      color: 'red'
    }}> required</span>}
                      {`: {\n    display name: ${sanitize(iprop.title || '')}\n    type: ${iprop.type}\n  }\n`}
                    </>)}
                  {'}'}
                </code>
              </pre>
              </div>}

            {isObject && <Expandable title="properties">
                <SchemaParamFields schema={{
      properties: prop.properties,
      required: prop.required
    }} />
              </Expandable>}
          </ParamField>;
  })}
    </div>;
};

export const LwTemplate = ({title = "Key questions to get you started", icon = "sparkles", cta = "Powered by Agent Studio", linkHref = "https://lucidworks.com/demo/?utm_source=docs&utm_medium=referral&utm_campaign=docs_cta_ai"}) => {
  const [isLoaded, setIsLoaded] = useState(false);
  useEffect(() => {
    const timer = setTimeout(() => {
      setIsLoaded(true);
    }, 500);
    return () => clearTimeout(timer);
  }, []);
  return <div className="lw-template-container">
      <Card title={title} icon={icon}>
        {isLoaded && <span dangerouslySetInnerHTML={{
    __html: `<lw-template id="a029c1a9-28be-427e-b0e1-5d918920246a"></lw-template
            >`
  }} />}
        <Link href={linkHref} className="agent-studio-link text-left text-gray-600 gap-2 dark:text-gray-400 text-sm font-medium flex flex-row items-center hover:text-primary dark:hover:text-primary-light group-hover:text-primary group-hover:dark:text-primary-light">Powered by Lucidworks Agent Studio</Link>
      </Card>
    </div>;
};

[localhost link]: http://localhost:3000/docs/4/fusion-ai/reference/query-pipeline-stages/recommend-items-for-item-query-stage

[mintlify link]: https://doc.lucidworks.com/docs/4/fusion-ai/reference/query-pipeline-stages/recommend-items-for-item-query-stage

[old doc.lw link]: https://doc.lucidworks.com/fusion/5.9/514

The Recommend Items for Item query pipeline stage uses signals about users' item choices to recommend related items based on a specific item. Relationships between items can be based on different criteria, such as click patterns, people who bought this also bought that, percentage match of document tags, and so on.

Given an item ID, this stage performs a secondary query to the `_items_for_item_recommendations` collection to find related items, then retrieves those items from the main collection.

This pipeline stage uses items-for-item recommendations that have been precomputed by an [ALS Recommender](/docs/4/fusion-ai/reference/jobs/als-recommender).

**See also [Items-for-item Recommendations](/docs/4/fusion-ai/concepts/boosting/items-for-item) to learn how to configure this recommender type and fetch recommendations.**

<LwTemplate />

## Prerequisites

**Enable recommendations:**

Before creating a Recommend Items for Item stage, enable recommendations.

* **Fusion UI** – In Collections Manager, click the settings icon next to the collection > **Enable Recommendations**.
* **Using the REST API** – Use this command to enable recommendations:

  ```bash theme={"dark"}
  curl -u admin:<password> -X PUT \http://<hostname>:<port>/api/v1/collections/<collection-name>/features/recommendations -H 'content-type: application/json' -d '{"enabled":true}'
  ```

<Note>
  When you enable recommendations, Fusion creates a query pipeline that already contains this stage, and that is configured for boosting. The query pipeline is `COLLECTION_NAME_items_for_item_recommendations`.
</Note>

## Using live signals

The **Estimate Recent Results** option uses live signals to augment items-for-user recommendations with real-time recommendations.

When this is enabled, Fusion first looks up items (from previously-generated recommendations) that are similar to the new items. If there are none then it looks up similar users (who also interacted with that item) to get a list of recommendations based on the new items. It then combines those new recommendations with the job-based recommendations already generated for that user (if any), to generate a final list of recommendations.

## Configuration

<Tip>
  When entering configuration values in the UI, use *unescaped* characters, such as `\t` for the tab character. When entering configuration values in the API, use *escaped* characters, such as `\\t` for the tab character.
</Tip>

<SchemaParamFields schema={schema} />