Filter the matched mentions. Provide a single condition {"field","op","value"} or an {"and":[…]} / {"or":[…]} group of conditions (nest groups for mixed logic), up to 8 conditions. Operators: =, <>, <, <=, >, >=, in, not_in, like, not_like, ilike, not_ilike, match, not_match (use an array value with in / not_in). Filterable fields: ai_search_volume (monthly AI search volume); platform (LLM engine, e.g. chat_gpt, google, perplexity); model (model name that produced the answer). Example: {"and":[{"field":"ai_search_volume","op":">","value":1000},{"field":"platform","op":"=","value":"chat_gpt"}]}
| Name | Type | Description | Notes |
|---|---|---|---|
| var_field | str | Field to filter on. See the endpoint's list of filterable fields. | |
| op | str | Comparison operator. | |
| value | DataForSeoFilterValue | ||
| var_and | List[DataForSeoFilter] | Sub-expressions that must all match. | |
| var_or | List[DataForSeoFilter] | Sub-expressions where at least one must match. |
from unifapi.models.geo_mentions_search_request_filters import GeoMentionsSearchRequestFilters
# TODO update the JSON string below
json = "{}"
# create an instance of GeoMentionsSearchRequestFilters from a JSON string
geo_mentions_search_request_filters_instance = GeoMentionsSearchRequestFilters.from_json(json)
# print the JSON string representation of the object
print(GeoMentionsSearchRequestFilters.to_json())
# convert the object into a dict
geo_mentions_search_request_filters_dict = geo_mentions_search_request_filters_instance.to_dict()
# create an instance of GeoMentionsSearchRequestFilters from a dict
geo_mentions_search_request_filters_from_dict = GeoMentionsSearchRequestFilters.from_dict(geo_mentions_search_request_filters_dict)