How to limit elastic suggestion with complex conditions?

Limiting elastic query is not complicated, for example:

`  "query":{
    "bool":{ 
      "must":[
        {"terms":{"brand":["micromax","samsung"]}},
        {
        "bool":{
          "should":[
            { "range": { "price": { "gte": 6000, "lte": 10000 } } },
            { "range": { "price": { "gte": 16000, "lte": 30000 } } }
            ] 
        }
        } 
      ] 
    }
  }`

But how can limit elastic suggestion with complex conditions (a condition with 'match', 'must', 'should', 'not',... on different fields)?

Is it possible to set a complex condition in 'collate'?

If you follow what the post says you can create an index and make your suggestion with aggregation. Note that I used an analyzer and the aggs is in the keyword type field.
In this example, you search for "micr" and receive the suggestion "micromax". If you change the price, the suggestion will not return results if the price is greater than 10.
That way you can apply restriction rules (the way you want) in your suggestion.

Mapping

PUT index
{
  "settings": {
    "analysis": {
      "analyzer": {
        "autocomplete": {
          "tokenizer": "my_tokenizer"
        }
      },
      "tokenizer": {
        "my_tokenizer": {
          "type": "ngram",
          "min_gram": 3,
          "max_gram": 3,
          "token_chars": [
            "letter",
            "digit"
          ]
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "brand": {
        "type": "text",
        "fields": {
          "autocomplete": {
            "type": "text",
            "analyzer": "autocomplete"
          },
          "raw_term": {
            "type": "keyword"
          }
        }
      }
    }
  }
}

Data

POST index/_doc
{
 "brand":"micromax",
 "price":10
}


POST index/_doc
{
 "brand":"samsung",
 "price":10
}

Query

GET index/_search
{
  "size": 0,
  "query": {
    "bool": {
      "filter": [
        {
          "range": {
            "price": {
              "gte": 10,
              "lte": 20
            }
          }
        }
      ],
      "must": [
        {
          "match": {
            "brand.autocomplete": "micr"
          }
        }
      ]
    }
  },
  "aggs": {
    "suggestion": {
      "terms": {
        "field": "brand.raw_term",
        "size": 10
      }
    }
  }
}

Result:

{
 "took": 1,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 1,
      "relation": "eq"
    },
    "max_score": null,
    "hits": []
  },
  "aggregations": {
    "suggestion": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "micromax",
          "doc_count": 1
        }
      ]
    }
  }
}