Create a new question

This API is used to submit questions to Miso.

After a question is submitted, a question_id is returned. Then you can use question_id to check the latest status of it's answer as it is being compiled.

Body·

required

application/json

question
Type: string · Question
required

The question for which an answer is requested.
anonymous_id
Type: string · Anonymous Id

The anonymous visitor who made this query.
boost_fq
Type: string · Boost Fq
Defines a query in Elasticsearch query-string syntax (Lucene) that can be used to boost a subset of products to the top of the ranking. 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 will not boost a low performance product only because it matches the boosting query.
cite_end
Type: string · Cite End

The citation end marker. Example: ] or }
cite_link
Type: integer

Set to 1 to include a link on each citation in the answer text.
cite_start
Type: string · Cite Start

The citation start marker. Example: [ or {
context_product_id
Type: string

The product_id of the content the reader is viewing, for example the article on an article page. On a first question it grounds the question in that article, so a question like "are there other articles about this?" resolves to the article's actual subject instead of returning a false "I don't know". Ignored on follow-ups, where the conversation already carries the context.
fq
Type: string · Fq
Defines a query in Elasticsearch query-string syntax (Lucene) 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 *]"}
```
jwt_token
Type: string

A signed JWT identifying the reader. Use it with a publishable key from the browser, instead of sending user_id in the body.
log_user_history
Type: boolean

Whether to save this question to the reader's history. Set false for a per-question private mode. See the User History APIs.
metadata
Type: object

Any data you want stored alongside the request. Returned with the answer and available in your usage data, so you can attribute questions to a page, a placement, or a campaign.
parent_question_id
Type: string · Parent Question IdFormat: uuid

The UUID of the parent question if the current question is a follow-up to a previous question.

Responses

application/json
application/json

post/v1/ask/questions

curl 'https://api.askmiso.com/v1/ask/questions?api_key=YOUR_SECRET_TOKEN' \
  --request POST \
  --header 'Content-Type: application/json' \
  --data '{
  "anonymous_id": "visitor-8f3a1c",
  "question": "How do interest rate cuts affect mortgages?"
}'

Show Schema

{
  "data": {
    "question_id": "123e4567-e89b-12d3-a456-426614174000"
  },
  "message": "success"
}

Successful Response