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latestOpenAPI 3.0.22026-08-0426137631.3 KB
Search APIs

Autocomplete API

The Autocompletion API provides real-time, personalized, typo resistant typeahead for your search bar. You send this API what users are currently typing, and the API returns the complete search query suggestions.

Personalized typeahead

Personalized typeahead is an extreme example of personalized search. The personalization starts immediately when users enter even just one character. The typeahead results are personalized so that the entries most likely to drive conversion for the current user are ranked at the top. Miso will predict what the user is looking for in real-time based on their interests and past behaviors.

Basic usage

The request schema of Autocompletion API is similar to that of Search API: you put the search query users typed so far, and the user_id or anonymous_id for Miso to identify the current user. For example, when a user types the first character r, you send Miso the following request:

POST /v1/search/autocomplete
{
   "q":"r",
   "user_id":"user-123"
}

The response will be like:

{
  "message": "success",
  "data": {
    "took": 50,
    "miso_id": "e93a6d02-0a7a-11eb-a896-d28586dc1386",
    "completions": {
      "title": [
        {
          "text": "Robin Hood: Prince of Thieves (1991)",
          "text_with_markups": "R<mark>obin Hood: Prince of Thieves (1991)</mark>",
          "product": {
            "product_id": "tmdb-8367"
          }
        },
        {
          "text": "Reservoir Dogs (1992)",
          "text_with_markups": "R<mark>eservoir Dogs (1992)</mark>",
          "product": {
            "product_id": "tmdb-500"
          }
        },
        ...
      ]
    }
  }
}
  • took: the amount of time (in milliseconds) Miso took to answer the query
  • completions: an dictionary of autocompletion candidates from different sources. By default, we only run autocompletion against the titles of products, but you can choose to get autocompletion candidates from other fields using the completion_fields parameters.
  • completions.title[].text: the text of completion candidates
  • completions.title[].text_with_markups: the completion candidates with the part of text that users haven't typed yet surrounded by <mark> HTML tags.
  • completions.title[].product: the product record whose title matches the autocompletion candidate. This object can be used to implement direct-to-product links: when they click on the link they will go directly to the product page instead of the search result page. By default, only the product_id field is returned, you use fl request parameter to get more fields returned in the product object.

Typo resistance

Miso's autocompletion algorithm accepts up to 4 typos in the query string. For example, users may try to find the movie Robin Hood, but make two typos in the query, which becomes robonhood instead (robin->robon, and a space is missing).

POST /v1/search/autocomplete
{
   "q":"robanhood",
   "user_id":"user-123"
}

Miso can still find the movie "Robin Hood: Prince of Thieves" as a autocompletion candidate.

{
  "message": "success",
  "data": {
    "took": 50,
    "miso_id": "e93a6d02-0a7a-11eb-a896-d28586dc1386",
    "completions": {
      "title": [
        {
          "text": "Robin Hood: Prince of Thieves (1991)",
          "text_with_markups": "Rob<mark>in Hood: Prince of Thieves (1991)</mark>",
          "product": {
            "product_id": "tmdb-8367"
          }
        },
        ...
      ]
    }
  }
}

Completion fields

The auto-completions are made against your product attributes. By default, Miso finds completion candidates from the title field. The completion_fields parameter lets you specify the attributes you want to perform auto-completion for. For example, the following query will return auto-completion candidates from the title and a custom attribute field:custom_attributes.director.

POST /v1/search/autocomplete
{
  "q": "rob",
  "user_id": "user-123",
  "completion_fields": [
    "title",
    "custom_attributes.director"
  ]
}

The response will be like the following:

{
  "message": "success",
  "data": {
    "took": 52,
    "miso_id": "16d95080-0bb0-11eb-948d-66359cf29022",
    "completions": {
      "title": [
        {
          "text": "Robin Hood: Prince of Thieves (1991)",
          "text_with_markups": "Rob<mark>in Hood: Prince of Thieves (1991)</mark>",
          "product": {
            "product_id": "tmdb-8367"
          }
        },
        {
          "text": "RoboCop (1987)",
          "text_with_markups": "Rob<mark>oCop (1987)</mark>",
          "product": {
            "product_id": "tmdb-5548"
          }
        },
        ...
      ],
      "custom_attributes.director": [
        {
          "text": "Robert Z. Leonard",
          "text_with_markups": "<mark>Rob</mark>ert Z. Leonard",
        },
        ...
      ]
    }
  }
}
post/v1/search/autocomplete

Request body

engine_idstring

The engine you want to get results from. When you have more than one engine, you can use this parameter to specify the specific engine you want to get results from. If not specified, the default engine will be used.

user_idstring

The user who made the query and for whom Miso will personalize the results. For an anonymous visitor, use anonymous_id instead.

anonymous_idstring

The anonymous visitor who made the query and for whom Miso will personalize the results. Either user_id or anonymous_id needs to be specified for personalization to work.

user_hashstring

The hash of user_id (or anonymous_id) encrypted by your Secret API Key. user_hash is required to prevent unauthorized API access if you are making API calls with a Publishable API Key.

You should generate the user_hash via HMAC scheme: you encrypt the desired user_id (or anonymous_id) with your Secret API Key on your backend server, and then let the front-end code send the generated user_hash to Miso APIs to verify the identity of the API caller.

As long as the Secret API Key is kept secret, the user_hash prevents a malicious attacker from making unauthorized API calls or impersonating any of your users.

Miso APIs accept the case-incentive "hex digest" of user hash, a sample Python 3 code to generate it on your backend server is as follow:

import hashlib
import hmac

YOUR_MISO_SECRET_API_KEY = "039c501ac8dfcac91"
key_bytes = YOUR_MISO_SECRET_API_KEY.encode()
user_id = "USER_123" # or anonymous_id
user_id_bytes = user_id.encode()
user_hash = hmac.new(
    key_bytes,
    user_id_bytes,
    hashlib.sha256).hexdigest()
# user_hash is "7eb04da5e..."

You can find more examples for other languages in this Github Gist

user_cohortobject

The user cohort you want to cold-start the recommendation with. For example, the following query will make recommendations based on the preferences of the users whose country="United States", and gender="Female" in the User Profile dataset.

{
    "user_cohort": {
        "country": "United States",
        "gender": "Female"
    }
}
rowsinteger

Number of search results to return.

typestring

The type of products to return. Use this parameter to make the API return only a certain type of products (see Product APIs).

This is particularly useful for sites that have multiple types of products: For example, on a marketplace site, YOu may model merchandise and store as two types of products. You can then use type parameter to limit the recommendation or search results to return only one kind of them.

For instance, the following query will return only store products:

{"type": "store"}

For another example, on a travel website, you might have: hotel, thing to do, and restaurant, three kinds of products. You can use type parameter to limit results to one kind of them. For instance, the following query will limit the results to only hotels product:

{"type": "hotel"}
dedupe_product_group_idboolean

Whether to dedupe product based on product_group_id. If dedupe_product_group_id=true, Miso will prevent products with the same product_group_id from showing multiple times in the search or recommendation results.

This is particular useful when one product has multiple variants (for example, different sizes, colors, or materials), and you only want to show this product only once in the search or recommendation results. Miso will then return the variant that is most likely to be of the user's interest.

fqstring

Defines a query in Solr syntax that can be used to restrict the superset of products to return, without influencing the overall ranking. fq can enable users to drill down to products with specific features based on different product attributes

For example, the query below limits the search results to only show products whose size is either M or S and brand is Nike:

{"fq": "size:(\"M\" OR \"S\") AND brand:\"Nike\""}

You can use fq to apply filters against your custom attributes as well. For example, the query below limits the search results to only products whose designer attribute is Calvin Klein

{"fq": "attributes.designer:\"Calvin Klein\""}

fq can also limit search results by numerical range. For example, the following query limits the results to products that have rating >= 4.

{"fq": "rating:[4 TO *]"}
boost_fqstring

Defines a query in Solr syntax that can be used to boost a subset of products to the top of the ranking, or to specific boost positions (See boost_positions parameter below.) For example, the query below will promote all the relevant products whose brand is Nike to the top of recommendation list:

{
    "boost_fq": "brand:\"Nike\""
}

For a slightly more complex example, the query below will promote the Nike products which have also been tagged as ON SALE to the top of the ranking:

{
   "boost_fq": "brand:\"Nike\" AND tags:\"ON SALE\""
}

It is worth mentioning that, Miso will only boost products that are relevant and have high likelihood to convert, and will not boost a low performance product only because it matches the boosting query.

Depending on your boosting rules, in certain cases, you would like to prevent recommendation results from being too monotone due to boosting. With Miso, you have two tools to do so.

First, you can specify boost_positions to place promoted products at specific positions in the ranking. For example, the query below will place boosted products only at the first and fourth places in the ranking (positions are 0-based), and place the remaining products in their original ranking, skipping these two positions.

{
   "boost_fq": "brand:\"Nike\" AND tags:\"ON SALE\"",
   "boost_positions": [0, 3]
}

The second tool is diversification. diversification parameter, on a best-effort basis, will try to maintain a minimum distance between products that have the same attributes. For example, the following query will place products made by the same brand apart from each other.

{
   "boost_fq": "brand:\"Nike\" AND tags:\"ON SALE\"",
   "diversification": {
       "brand": {"minimum_distance": 1}
    }
}
boost_positionsinteger[]

Defines a list of 0-based positions you want to place the boosted products at.

For example, the query below will promote products whose brand is Nike as the top and second recommendations:

{
    "boost_fq": "brand:\"Nike\"",
    "boost_positions": [0, 1]
}

If boost_positions is not specified (which is the default behavior), all the boosted products will be ranked higher than the rest of the products.

boost_rule_namestring

Name of the boosting rule. Use this to identify a boosting rule in _boosted_rules in the response

qstring required

The search query users typed so far. Please keep the trailing spaces (if any) intact so that we know whether the user has finished typing the last word or is still typing it. For example, the following query means the user has finished typing the word Fight:

{"q": "Fight "}

On the other hand, the following query means the user has not finished typing the last word Clu:

{"q": "Fight Clu"}
languagestring

Two-letter (639-1) language code of the search query. If given, the autocomplete results will be from that specific language. If not given, the autocomplete results will be from the primary language of the environment. Example query:

{"language": "en"}
min_query_usersinteger

Limits the query completion results to historical queries that have been made by at least this number of unique users. This parameter has no effect when completion_fields does not include historical_queries. We do not recommend setting min_query_users lower than 5. When min_query_users is too small, we might risk showing queries that contain typos or are too personal to the users who made the query.

completion_fieldsstring[]

Controls the sources of autocompletion candidates. Miso performs autocompletion by matching what the user has typed so far to either the title of products or to other attributes.

By default, we only autocomplete against the value in the title field. The completion_fields parameter lets you specify the attributes you want to perform autocompletion against. For example, the following query will limit the autocompletion candidates to the title and tags of products:

{"completion_fields": ["title", "tags"]}

Autocompletion also works on custom attributes. For example, if you have a custom attribute for the designer_name of the product, the following query limits autocompletion candidates to only the designer names:

{"candidates": ["custom_attributes.designer_name"]}
flstring[]

List of fields to retrieve. For example, the following request retrieves only the title field of each product along with the product_id, which is always returned.

{"fl": ["title"]}

You can also match field names by using * as a wildcard. For example, the query below retrieves the title and any custom attributes under the attributes dictionary.

{"fl": ["title", "attributes.*"]}

The following retrieves all the available fields:

{"fl": ["*"]}

For the lowest latency, use an empty array to retrieve just the product_id field (which is the default).

{"fl": []}

Example request

{
  "additional_interactions": [
    {
      "duration": 61.5,
      "product_ids": [
        "123ABC-BLACK"
      ],
      "product_group_ids": [
        "123ABC"
      ],
      "user_id": "user_1234",
      "anonymous_id": "86D51273AD8BF84217E1567B6CBE7152D7034404",
      "miso_id": "123e4567-e89b-12d3-a456-426614174000",
      "context": {
        "campaign": {
          "name": "spring_sale",
          "source": "Google",
          "medium": "cpc",
          "term": "running+shoes",
          "content": "textlink"
        },
        "truncated_ip": "1.1.1.0",
        "locale": "en-US",
        "region": "US East",
        "page": {
          "url": "https://example.com/miso-tshirt-123ABC",
          "referrer": "https://example.com/",
          "title": "My Product Page"
        },
        "user_agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:47.0) Gecko/20100101 Firefox/47.0",
        "custom_context": {
          "session_variable_1": [
            "value_1",
            "value_2"
          ]
        }
      }
    }
  ]
}

Response

Successful Response

messagestring

Example response

{
  "data": {
    "miso_id": "123e4567-e89b-12d3-a456-426614174000",
    "completions": {
      "title": [
        {
          "text": "Miso Japanese Shiba Inu Dog Eating Miso Soup T-Shirt",
          "type": "title",
          "product": {
            "product_id": "123ABC-S-Black"
          }
        }
      ],
      "brand": [
        {
          "text": "Miso",
          "type": "brand"
        },
        {
          "text": "Mitsui",
          "type": "brand"
        }
      ]
    }
  }
}