miso.ai Product Recommendations API

openapi: 3.2.0
info:
  title: Miso Ask Product Recommendations API
  description: '

    # Overview

    Miso’s approach to personalization is to train machine learning Engines on three core data sets:


    1. Your site’s log of historical and real-time interactions,

    2. Your catalog of products and content, and

    3. Your users. Miso provides the output of its Engines to you, so you can build search and recommendation

    experiences that are personalized down to the individual level (n=1 personalization).


    To see how Miso works and explore the power of its Engines, we recommend following

    [this tutorial](https://docs.askmiso.com/) to get

    started with our Playground data. Integrating your site or application with Miso happens in three basic steps:


    1. Upload your data

    2. Train your Engines

    3. Build search and recommendation experiences with the output of your Engines.



    Miso provides two main integration points. The first is your [Dojo Dashboard](https://dojo.askmiso.com/),

    which is used to set up your Engines with the conversions you want to optimize and your training schedule.

    Dojo is also a great way to get familiar with Miso by manually uploading data and exploring the output of

    Miso’s Engines. In Dojo’s Sandboxes, you can tweak your Engine settings and see visual examples of Miso’s search

    and recommendations running on your live data.


    The second integration point is Miso’s API, which lets you automatically manage your data in Miso and build

    experiences that leverage the output of Miso’s personalization Engines.



    Miso’s API is composed of two major groups of REST API endpoints: Data APIs and Engine APIs.


    ### Data APIs

    Data APIs collect input to Miso''s personalization Engines. These APIs all support high-throughput

    data ingestion through bulk insert, and satisfy GDPR and CCPA compliance by letting users delete their data

    from Miso. Subcategories of Data APIs are:


    * [Interaction APIs](#tag/Interaction-APIs), for managing your Interaction records. By uploading historical and real-time Interaction

    records, you tell Miso how users are engaging with the products and content on your site, and in turn, Miso’s

    Engines learn how to optimize your conversion funnels.

    * [Product / Content APIs](#tag/Product-Content-APIs), for managing your Product / Content records. These records provide a deep semantic

    understanding of your catalog and keep Miso up to date about your offerings so it can make smart and timely

    suggestions. The `product_id` is how Miso links Product / Content records to your Interaction records.

    * [User APIs](#tag/User-APIs), for managing your User records. These records tell Miso about your site’s users and visitors,

    so Miso can build an understanding of user segmentation and behavior in relation to products and content.

    The `user_id` is how Miso links User records to your Interaction records.


    As a rule of thumb, we recommend batching up data to avoid timeout risks. For the Product / Content and User

    Upload APIs, we recommend limiting each API upload call to about 100 records at a time. For the Interaction

    Upload API, we recommend limiting your calls to around 10,000 records at a time.


    ### Engine APIs

    Engine APIs provide the output of Miso''s personalization Engines. We designed these APIs with a focus on low

    latency and high availability. Most of these APIs'' 95th percentile response time is under 75ms,

    and the services are replicated to at least three separate instances for high availability.

    The types of Engine APIs are:


    * [Search APIs](#tag/Search-APIs), for getting Miso’s personalized search results for a user, with search-as-you-type and

    autocompletion.

    * [Recommendation APIs](#tag/Recommendation-APIs), for retrieving Miso’s recommendations that match users with

    the products, categories, and product attributes that are likely to drive conversions.


    # Authentication

    [View your API Keys in your Dojo Dashboard.](https://dojo.askmiso.com/docs/api-browser)


    There are three environments in Miso:

    * **Playground**, a read-only tutorial environment with sample data.

    * **Development**, for staging, QA, and experimentation.

    * **Production**, where you run your live integration with Miso.


    Access a Miso environment by passing in the corresponding API key in your API calls. There is one publishable

    key and one secret key per environment.


    API Key can passed with query parameter `api_key`, or using the `X-API-KEY` header.

    '
  version: 1.1.4
servers:
- url: https://api.askmiso.com
tags:
- name: Product Recommendations
  description: APIs for recommending related products based on a given product.
paths:
  /v1/recommendation/product_to_products:
    post:
      tags:
      - Product Recommendations
      summary: Product to Products API
      description: "The Product to Products API returns the products that are related to an anchor product (often the product the user\nis currently engaging with) and are also likely to drive conversions by connecting with the user’s interests. It is\ndifferent from the User to Products API as it not only considers the user’s interests but also considers the\nrecommended products' relevancy to the anchor product.\n\n### Applicable scenarios\nThis API is frequently used in product detail page to show related products that users can consume\nfurther, such as \"Related products you may like\" on Amazon or \"Up next video\" on Youtube. It is one of Miso's best\nperforming APIs. Our customers usually see more than 30% and some times 110% relative lift in click-through rate after\ndeploying this a feature using this API.\n\n### Basic usage\nTo use this API, you just need to let Miso knows the `user_id` (or `anonymous_id`) and the `product_id` you\nwant to get related recommendations for. For example, the following request will return the products that are\nrelated to the movie `Toy Story`.\n```\nPOST https://api.askmiso.com/v1/recommendation/product_to_products\n{\n    \"user_id\": \"user_123\",\n    \"product_id\": [\"toy-story-1995\"],\n    \"rows\": 3,\n    \"fl\": [\"title\"]\n}\n```\n* **product_id**: the id of the anchor product\n* **rows**: the number of related products to return\n* **fl**: like in other Miso API, you can use `fl` to control which fields to return for each Product\n\nThe response will be like:\n```javascript\n{\n    \"message\": \"success\",\n    \"data\": {\n        \"took\": 56,\n        \"miso_id\": \"f98b1904-ddce-11eb-be53-fa1729b23183\",\n        \"products\": [\n            {\n                \"product_id\": \"toy-story-2-1999\",\n                \"title\": \"Toy Story 2 (1999)\"\n            },\n            {\n                \"product_id\": \"toy-story-3-2010\",\n                \"title\": \"Toy Story 3 (2010)\"\n            },\n            {\n                \"product_id\": \"the-lion-king-1994\",\n                \"title\": \"The Lion King (1994)\"\n            }\n        ]\n    }\n}\n```\n* **products**: a list of products related to the anchor product\n* **products[ ].product_id**: the id of the recommended product\n* **products[ ].title**: the title of the recommended product. You can use `fl` parameter to make Miso return more fields\n\n### Boosting and filtering\nLike every Miso API, you can utilize `fq` and `boost_fq` to fine-tune the recommendations returned by Miso, and\nMiso will guarantee to return the required number of recommendations that meet the given criteria.\n\nFor example, the following request still recommends movies related to \"Toy Story\" but limits the recommendations\nto only the movies released after year 2010.\n```\nPOST https://api.askmiso.com/v1/recommendation/product_to_products\n{\n    \"user_id\": \"user_123\",\n    \"product_id\": [\"toy-story-1995\"],\n    \"rows\": 3,\n    \"fl\": [\"title\"],\n    \"fq\": \"custom_attributes.year: [2010 TO *]\"\n}\n```\n\nFor another example, the following request will *boost* the movies that are acted by `Tom Hanks`. The boosting is\ndifferent from filtering as it only prioritizes those products that match the boosting criteria and are relevant to\nthe anchor products, but it will not limit the results to only such products.\n```\nPOST https://api.askmiso.com/v1/recommendation/product_to_products\n{\n    \"user_id\": \"user_123\",\n    \"product_id\": [\"toy-story-1995\"],\n    \"rows\": 3,\n    \"fl\": [\"title\"],\n    \"boost_fq\": \"custom_attributes.actors:\\\"Tom Hanks\\\"\"\n}\n```\n\n### Multiple anchor products\nIn the scenarios where you want to recommend products related to **multiple** anchor products, for example,\nfor shopping cart cross-sell or up-sell, you can utilize `product_ids`\nparameter and have multiple product ids in it.\n\nFor instance, the following request recommends products related to movies \"Toy Story\" and \"Monsters, Inc.\"\nthat will be of interest to the the current user.\n```\nPOST https://api.askmiso.com/v1/recommendation/product_to_products\n{\n    \"user_id\": \"user_123\",\n    \"product_ids\": [\"toy-story-1995\", \"monsters-inc-2001\"],\n    \"rows\": 3,\n    \"fl\": [\"title\"]\n}\n```"
      operationId: product_to_products_v1_recommendation_product_to_products_post
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/YMALRequest'
        required: true
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProductToProductsResponse'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
      security:
      - Secret API Key: []
components:
  schemas:
    GeoQuery:
      title: GeoQuery
      type: object
      properties:
        filter:
          title: Filter
          type: array
          items:
            $ref: '#/components/schemas/GeoDistanceQuery'
          description: When set, filter result to include only products within certain geographic range from given point.
          default: []
        boost:
          title: Boost
          type: array
          items:
            $ref: '#/components/schemas/GeoDistanceQueryBoost'
          description: When set, boost products within certain geographic range from given point.
          default: []
    HTTPValidationError:
      title: HTTPValidationError
      type: object
      properties:
        detail:
          title: Detail
          type: array
          items:
            $ref: '#/components/schemas/ValidationError'
    Search:
      title: search
      required:
      - type
      type: object
      properties:
        type:
          title: Type
          enum:
          - search
          type: string
          description: '

            Used to record a search event with the keywords and filters the user used. What a user searches for

            is a very powerful signal about their interests and what they will eventually buy or consume, so it is important

            to capture this information with high fidelity.

            '
        user_id:
          title: User Id
          maxLength: 512
          type: string
          description: "Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your\n        User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have\n        not signed in, see `anonymous_id`."
          example: user_1234
        anonymous_id:
          title: Anonymous Id
          maxLength: 1024
          type: string
          description: "A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed\n        in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id`\n        is not given, we will default it to `SHA1(<API key>:<IP address>:<user agent>:<date>)`. When a visitor signs\n        in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id`\n        along with the past interactions associated with it."
          example: 86D51273AD8BF84217E1567B6CBE7152D7034404
        timestamp:
          title: Timestamp
          type: string
          description: '

            The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we

            will default to the server''s time. If you''re importing data from the past, make sure you provide a

            timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution.


            Example:

            ```

            {"timestamp": "2018-11-07T00:25:00.073876Z"}

            ```

            '
          format: date-time
        miso_id:
          title: Miso Id
          type: string
          description: '

            Miso-generated unique Id for each recommendation or search result. Maintaining this Id for

            subsequent page views is important to Miso''s performance, as we use `miso_id` to track and fine-tune the

            performance of personalization and search results. When a user clicks on a recommendation or search result,

            you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the

            interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`,

            `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn''t.


            Example:

            ```

            {"misoId": "123e4567-e89b-12d3-a456-426614174000"}

            ```

            '
          format: uuid
          example: 123e4567-e89b-12d3-a456-426614174000
        context:
          title: Context
          allOf:
          - $ref: '#/components/schemas/WebBasedContext'
          description: "\nDictionary of extra information that provides useful context about an interaction. We use context\ninformation to make recommendations tailored not only for each user, but also for their current browsing context.\nFor example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile\nphone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very\ndifferent interests than a user who visits your site directly.\n\nContext information is also useful for personalization for entirely new visitors, as we can immediately\npersonalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through).\n\nExample:\n```\n{\"context\": {\n    \"campaign\":\n    {\n        \"name\": \"spring_sale\",\n        \"source\": \"Google\",\n        \"medium\": \"cpc\",\n        \"term\": \"running+shoes\",\n        \"content\": \"textlink\"\n    },\n    \"truncated_ip\": \"1.1.1.0\",\n    \"locale\": \"en-US\",\n    \"region\": \"US East\",\n    \"page\":\n        {\n            \"url\": \"https://example.com/miso-tshirt-123ABC\",\n            \"referrer\": \"https://example.com/\",\n            \"title\": \"My Product Page\"\n        },\n        \"user_agent\": \"Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)\"\n    },\n    \"custom_context\": {\n        \"other_context_var_1\": \"value_1\",\n        \"other_context_var_2\": \"value_2\"\n    }\n}\n```\n"
        search:
          title: Search
          allOf:
          - $ref: '#/components/schemas/SearchInformation'
          description: '

            The search keywords and filters the user uses. This is only required by `search` interaction.

            '
      additionalProperties: false
    AddToCollection:
      title: add_to_collection
      required:
      - type
      type: object
      properties:
        type:
          title: Type
          enum:
          - add_to_collection
          type: string
          description: '

            Used when a user adds a product to their personal collection. This is a strong

            signal of their interest in the product.

            '
        product_ids:
          title: Product Ids
          type: array
          items:
            type: string
            maxLength: 512
          description: '

            Products or content the user is interacting with. This field is required by

            almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso.

            Therefore, it is important to keep this consistent between the two datasets.


            Example:

            ```

            {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]}

            ```

            '
          default: []
          example:
          - 123ABC-BLACK
        product_group_ids:
          title: Product Group Ids
          type: array
          items:
            type: string
            maxLength: 512
          description: '

            The product groups the user is interacting with. You only need this field if you model product

            variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a

            user is interacting with a *product group* rather than a specific product variant, for example, when the user

            is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or

            color (i.e. a product variant) yet.


            In such situations, the `product_id` is not applicable because we only know the user is interested in

            this T-shirt (a product group), but don''t know which particular product variant the user is interested in.

            Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`.


            In the situations where specific `product_ids` are available, for example, when user selected a particular size

            of the T-Shirt, use `product_ids` instead.



            Example:

            ```

            {"product_group_ids": ["123ABC"]}

            ```

            '
          example:
          - 123ABC
        user_id:
          title: User Id
          maxLength: 512
          type: string
          description: "Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your\n        User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have\n        not signed in, see `anonymous_id`."
          example: user_1234
        anonymous_id:
          title: Anonymous Id
          maxLength: 1024
          type: string
          description: "A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed\n        in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id`\n        is not given, we will default it to `SHA1(<API key>:<IP address>:<user agent>:<date>)`. When a visitor signs\n        in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id`\n        along with the past interactions associated with it."
          example: 86D51273AD8BF84217E1567B6CBE7152D7034404
        timestamp:
          title: Timestamp
          type: string
          description: '

            The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we

            will default to the server''s time. If you''re importing data from the past, make sure you provide a

            timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution.


            Example:

            ```

            {"timestamp": "2018-11-07T00:25:00.073876Z"}

            ```

            '
          format: date-time
        miso_id:
          title: Miso Id
          type: string
          description: '

            Miso-generated unique Id for each recommendation or search result. Maintaining this Id for

            subsequent page views is important to Miso''s performance, as we use `miso_id` to track and fine-tune the

            performance of personalization and search results. When a user clicks on a recommendation or search result,

            you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the

            interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`,

            `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn''t.


            Example:

            ```

            {"misoId": "123e4567-e89b-12d3-a456-426614174000"}

            ```

            '
          format: uuid
          example: 123e4567-e89b-12d3-a456-426614174000
        context:
          title: Context
          allOf:
          - $ref: '#/components/schemas/WebBasedContext'
          description: "\nDictionary of extra information that provides useful context about an interaction. We use context\ninformation to make recommendations tailored not only for each user, but also for their current browsing context.\nFor example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile\nphone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very\ndifferent interests than a user who visits your site directly.\n\nContext information is also useful for personalization for entirely new visitors, as we can immediately\npersonalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through).\n\nExample:\n```\n{\"context\": {\n    \"campaign\":\n    {\n        \"name\": \"spring_sale\",\n        \"source\": \"Google\",\n        \"medium\": \"cpc\",\n        \"term\": \"running+shoes\",\n        \"content\": \"textlink\"\n    },\n    \"truncated_ip\": \"1.1.1.0\",\n    \"locale\": \"en-US\",\n    \"region\": \"US East\",\n    \"page\":\n        {\n            \"url\": \"https://example.com/miso-tshirt-123ABC\",\n            \"referrer\": \"https://example.com/\",\n            \"title\": \"My Product Page\"\n        },\n        \"user_agent\": \"Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)\"\n    },\n    \"custom_context\": {\n        \"other_context_var_1\": \"value_1\",\n        \"other_context_var_2\": \"value_2\"\n    }\n}\n```\n"
      additionalProperties: false
    Like:
      title: like
      required:
      - type
      type: object
      properties:
        type:
          title: Type
          enum:
          - like
          type: string
          description: '

            Used to record when a user indicates a `like` for a product.

            '
        product_ids:
          title: Product Ids
          type: array
          items:
            type: string
            maxLength: 512
          description: '

            Products or content the user is interacting with. This field is required by

            almost all the interaction types. We use `product_ids` to refer to the product / content records that you upload to Miso.

            Therefore, it is important to keep this consistent between the two datasets.


            Example:

            ```

            {"product_ids": ["123ABC-BLACK", "123EFG-YELLOW"]}

            ```

            '
          default: []
          example:
          - 123ABC-BLACK
        product_group_ids:
          title: Product Group Ids
          type: array
          items:
            type: string
            maxLength: 512
          description: '

            The product groups the user is interacting with. You only need this field if you model product

            variants using `product_id` and `product_group_id` (see Product API). If so, you should use this field, when a

            user is interacting with a *product group* rather than a specific product variant, for example, when the user

            is viewing the master page of a T-shirt (i.e. a product group), but has not selected the specific size or

            color (i.e. a product variant) yet.


            In such situations, the `product_id` is not applicable because we only know the user is interested in

            this T-shirt (a product group), but don''t know which particular product variant the user is interested in.

            Therefore, we use `product_group_ids` to capture such interactions in place of `product_ids`.


            In the situations where specific `product_ids` are available, for example, when user selected a particular size

            of the T-Shirt, use `product_ids` instead.



            Example:

            ```

            {"product_group_ids": ["123ABC"]}

            ```

            '
          example:
          - 123ABC
        user_id:
          title: User Id
          maxLength: 512
          type: string
          description: "Identifies the signed-in user who performed the interaction. We will use `user_id` to link Interaction records to your\n        User records. Therefore, it is important to keep this consistent between the two datasets.For visitors who have\n        not signed in, see `anonymous_id`."
          example: user_1234
        anonymous_id:
          title: Anonymous Id
          maxLength: 1024
          type: string
          description: "A pseudo-unique substitute for the User Id. We use `anonymous_id` to identify a visitor who has not signed\n        in. `anonymous_id` can be implemented using mechanisms such as cookies or browser localStorage. If `anonymous_id`\n        is not given, we will default it to `SHA1(<API key>:<IP address>:<user agent>:<date>)`. When a visitor signs\n        in and the `user_id` and `anonymous_id` are both present, the `anonymous_id` will be linked to the `user_id`\n        along with the past interactions associated with it."
          example: 86D51273AD8BF84217E1567B6CBE7152D7034404
        timestamp:
          title: Timestamp
          type: string
          description: '

            The ISO-8601 timestamp specifying when the interaction occurred. If the interaction just happened, leave it out and we

            will default to the server''s time. If you''re importing data from the past, make sure you provide a

            timestamp. It is recommended to include milliseconds in the timestamp to provide a higher time resolution.


            Example:

            ```

            {"timestamp": "2018-11-07T00:25:00.073876Z"}

            ```

            '
          format: date-time
        miso_id:
          title: Miso Id
          type: string
          description: '

            Miso-generated unique Id for each recommendation or search result. Maintaining this Id for

            subsequent page views is important to Miso''s performance, as we use `miso_id` to track and fine-tune the

            performance of personalization and search results. When a user clicks on a recommendation or search result,

            you should pass the associated `miso_id` to the next page view, and associate the `miso_id` with the

            interactions that take place on the page (e.g. `product_detail_page_view`, `add_to_cart`,

            `add_to_collection`, `like`, etc.). In this way, Miso will learn which recommendations work and which didn''t.


            Example:

            ```

            {"misoId": "123e4567-e89b-12d3-a456-426614174000"}

            ```

            '
          format: uuid
          example: 123e4567-e89b-12d3-a456-426614174000
        context:
          title: Context
          allOf:
          - $ref: '#/components/schemas/WebBasedContext'
          description: "\nDictionary of extra information that provides useful context about an interaction. We use context\ninformation to make recommendations tailored not only for each user, but also for their current browsing context.\nFor example, a user browsing on a desktop may have different browsing behavior than a user browsing on mobile\nphone. As another example, a user who gets to the site via a certain campaign you run on Facebook may have very\ndifferent interests than a user who visits your site directly.\n\nContext information is also useful for personalization for entirely new visitors, as we can immediately\npersonalize their experiences based on their context alone (e.g. the referrer or the campaign they clicked through).\n\nExample:\n```\n{\"context\": {\n    \"campaign\":\n    {\n        \"name\": \"spring_sale\",\n        \"source\": \"Google\",\n        \"medium\": \"cpc\",\n        \"term\": \"running+shoes\",\n        \"content\": \"textlink\"\n    },\n    \"truncated_ip\": \"1.1.1.0\",\n    \"locale\": \"en-US\",\n    \"region\": \"US East\",\n    \"page\":\n        {\n            \"url\": \"https://example.com/miso-tshirt-123ABC\",\n            \"referrer\": \"https://example.com/\",\n            \"title\": \"My Product Page\"\n        },\n        \"user_agent\": \"Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0)\"\n    },\n    \"custom_context\": {\n        \"other_context_var_1\": \"value_1\",\n        \"other_context_var_2\": \"value_2\"\n    }\n}\n```\n"
      additionalProperties: false
    Page:
      title: Page
      required:
      - url
      type: object
      properties:
        url:
          title: Url
          type: string
          description: Url of the page
          example: https://example.com/miso-tshirt-123ABC
        referrer:
          title: Referrer
          type: string
          description: Url of the referrer page
          example: https://example.com/
        title:
          title: Title
          type: string
          description: Title of the page
          example: My Product Page
    WebBasedContext:
      title: WebBasedContext
      type: object
      properties:
        campaign:
          title: Campaign
          allOf:
          - $ref: '#/components/schemas/Campaign'
          description: '

            The campaign that resulted in the interaction. Campaign dictionary contains standard UTM parameters: `name`,

            `source`, `medium`, `term`, `content`. We use campaign information to infer users'' interests and fine-tune the

            personalization and search results based on the current user''s campaign information.

            '
        truncated_ip:
          title: Truncated Ip
          type: string
          description: '

            User''s truncated IP address. We use IP address to determine the country of the users.

            '
          format: ipv4
          example: 1.1.1.0
        locale:
          title: Locale
          type: string
          description: Locale string of the current session, for example en-US.
          example: en-US
        region:
          title: Region
          type: string
          description: '

            The region/location of the site the user is visiting. This is for sites that serve different regions or

            markets. You can define your own region keywords, for example, `US East`, `Europe`, `LATM`, etc.

            '
          example: US East
        page:
          title: Page
          allOf:
          - $ref: '#/components/schemas/Page'
          description: "The current page in the browser. Page dictionary containing referrer, title and url. we will use page view\n        as a pseudo interaction to infer users' interest. "
        user_agent:
          title: User Agent
          type: string
          description: "\nUser agent of the device making the request. We use this to determine if a user is browsing the site on\nmobile or desktop, and tailor the recommendations and search results accordingly.\n\nExample:\n```\n{\"user_agent\":\n    \"Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0) Gecko/20100101 Firefox/47.0\"}\n```\n"
          example: Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0) Gecko/20100101 Firefox/47.0
        custom_context:
          title: Custom Context
          type: object
          additionalProperties:
            anyOf:
            - type: boolean
            - type: integer
            - type: number
            - type: string
            - type: array
              items:
        

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