@@ -62,7 +62,7 @@ def __init__(
             self.default_headers[header_name] = header_value
         self.cookie = cookie
         # Set default User-Agent.
-        self.user_agent = 'python-client/2.1.3'
+        self.user_agent = 'python-client/2.1.5'
         self.client_side_validation = configuration.client_side_validation
 
     def __enter__(self):
 
@@ -15,12 +15,12 @@ class AddressInfo(BaseModel):
     """
     AddressInfo
     """ # noqa: E501
-    borough: Optional[StrictStr] = Field(default=None, description=r"administrative unit or district the local establishment belongs to")
-    address: Optional[StrictStr] = Field(default=None, description=r"street address of the local establishment")
-    city: Optional[StrictStr] = Field(default=None, description=r"name of the city where the local establishment is located")
-    zip: Optional[StrictStr] = Field(default=None, description=r"ZIP code of the local establishment")
-    region: Optional[StrictStr] = Field(default=None, description=r"DMA region the local establishment belongs to")
-    country_code: Optional[StrictStr] = Field(default=None, description=r"ISO country code of the local establishment")
+    borough: Optional[StrictStr] = Field(default=None, description=r"*administrative unit or district the local establishment belongs to*")
+    address: Optional[StrictStr] = Field(default=None, description=r"*street address of the local establishment*")
+    city: Optional[StrictStr] = Field(default=None, description=r"*name of the city where the local establishment is located*")
+    zip: Optional[StrictStr] = Field(default=None, description=r"*ZIP code of the local establishment*")
+    region: Optional[StrictStr] = Field(default=None, description=r"*DMA region the local establishment belongs to*")
+    country_code: Optional[StrictStr] = Field(default=None, description=r"*ISO country code of the local establishment*")
     __properties: ClassVar[List[str]] = [
         "borough", 
         "address", 
 
@@ -17,7 +17,7 @@ class AiOptimizationChatGptLlmScraperLocationsCountryResultInfo(BaseModel):
     """ # noqa: E501
     location_code: Optional[StrictInt] = Field(default=None, description=r"*location code*")
     location_name: Optional[StrictStr] = Field(default=None, description=r"*full name of the location*")
-    location_code_parent: Optional[StrictInt] = Field(default=None, description=r"*the code of the superordinate location*. example:. `'location_code': 9041134,'location_name': 'Vienna International Airport,Lower Austria,Austria','location_code_parent': 20044`. where `location_code_parent` corresponds to:. `'location_code': 20044,'location_name': 'Lower Austria,Austria'`")
+    location_code_parent: Optional[StrictStr] = Field(default=None, description=r"*the code of the superordinate location*. example:. `'location_code': 9041134,'location_name': 'Vienna International Airport,Lower Austria,Austria','location_code_parent': 20044`. where `location_code_parent` corresponds to:. `'location_code': 20044,'location_name': 'Lower Austria,Austria'`")
     country_iso_code: Optional[StrictStr] = Field(default=None, description=r"*ISO country code of the location*")
     location_type: Optional[StrictStr] = Field(default=None, description=r"*location type*")
     __properties: ClassVar[List[str]] = [
 
@@ -17,7 +17,7 @@ class AiOptimizationChatGptLlmScraperLocationsResultInfo(BaseModel):
     """ # noqa: E501
     location_code: Optional[StrictInt] = Field(default=None, description=r"*location code*")
     location_name: Optional[StrictStr] = Field(default=None, description=r"*full name of the location*")
-    location_code_parent: Optional[StrictInt] = Field(default=None, description=r"*the code of the superordinate location*. example:. `'location_code': 9041134,'location_name': 'Vienna International Airport,Lower Austria,Austria','location_code_parent': 20044`. where `location_code_parent` corresponds to:. `'location_code': 20044,'location_name': 'Lower Austria,Austria'`")
+    location_code_parent: Optional[StrictStr] = Field(default=None, description=r"*the code of the superordinate location*. example:. `'location_code': 9041134,'location_name': 'Vienna International Airport,Lower Austria,Austria','location_code_parent': 20044`. where `location_code_parent` corresponds to:. `'location_code': 20044,'location_name': 'Lower Austria,Austria'`")
     country_iso_code: Optional[StrictStr] = Field(default=None, description=r"*ISO country code of the location*")
     location_type: Optional[StrictStr] = Field(default=None, description=r"*location type*")
     __properties: ClassVar[List[str]] = [
 
@@ -22,9 +22,9 @@ class AiOptimizationLlmMentionsMultiTargetMetricsLiveItem(BaseModel):
     language: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*language-based grouping*. array of objects containing mention metrics segmented by content language")
     platform: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*platform-based grouping*. array of group elements containing mention metrics segmented by AI platform")
     sources_domain: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*found top source domains relevant to the target*. array of objects containing data on top domains that are cited as sources in LLM responses. learn more about the sources and how to retrieve LLM citation data at our [Help Center](https://dataforseo.com/help-center/how-to-get-llm-citation-data-with-llm-mentions-api)")
-    search_results_domain: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*found top search results domains relevant to the target*. array of objects containing data on top domains that appear in search results related to LLM queries")
-    brand_entities_title: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*data on brand entities relevant to the target*. array of objects containing data on brand entity titles that appear in search results related to LLM queries")
-    brand_entities_category: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*data on brand entities relevant to the target*. array of objects containing data on brand entity categories that appear in search results related to LLM queries")
+    search_results_domain: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*found top search results domains relevant to the target*. array of objects containing data on top domains that appear in search results related to LLM queries;. **Note:** available only for `chat_gpt`")
+    brand_entities_title: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*data on brand entities relevant to the target*. array of objects containing data on brand entity titles that appear in search results related to LLM queries. **Note:** available only for `chat_gpt`")
+    brand_entities_category: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*data on brand entities relevant to the target*. array of objects containing data on brand entity categories that appear in search results related to LLM queries;. **Note:** available only for `chat_gpt`")
     total: Optional[AggregatedMetricsInfoTotalInfo] = Field(default=None, description=r"*data on total mentions and search volume for the target*")
     __properties: ClassVar[List[str]] = [
         "key", 
 
@@ -26,13 +26,13 @@ class AiOptimizationLlmMentionsSearchMentionsLiveItem(BaseModel):
     question: Optional[StrictStr] = Field(default=None, description=r"*relevant question*")
     answer: Optional[StrictStr] = Field(default=None, description=r"*relevant answer in markdown format*. content of the result formatted in the [markdown markup language](https://en.wikipedia.org/wiki/Markdown)")
     sources: Optional[List[Optional[Sources]]] = Field(default=None, description=r"*array of sources*. the sources the model cited or relied on in its final answer. learn more about the sources and how to retrieve LLM citation data at our [Help Center](https://dataforseo.com/help-center/how-to-get-llm-citation-data-with-llm-mentions-api)")
-    search_results: Optional[List[Optional[SearchResults]]] = Field(default=None, description=r"*array of search results*. all web search outputs the model retrieved when looking up information, including duplicates and unused entries")
+    search_results: Optional[List[Optional[SearchResults]]] = Field(default=None, description=r"*array of search results*. all web search outputs the model retrieved when looking up information, including duplicates and unused entries. **Note:** available only for `chat_gpt`")
     ai_search_volume: Optional[StrictInt] = Field(default=None, description=r"*current AI search volume rate of a keyword*. learn more about this metric [here](https://dataforseo.com/help-center/how-the-ai-search-volume-metric-works-in-llm-mentions)")
     monthly_searches: Optional[List[Optional[MonthlySearchesInfo]]] = Field(default=None, description=r"*monthly AI search volume rates*. array of objects with AI search volume rates in a certain month of a year")
     first_response_at: Optional[StrictStr] = Field(default=None, description=r"*date and time when the response data was first recorded*. in the UTC format: “yyyy-mm-dd hh-mm-ss +00:00”. example:. `2025-10-21 06:25:30 +00:00`")
     last_response_at: Optional[StrictStr] = Field(default=None, description=r"*date and time when the response data was last updated*. in the UTC format: “yyyy-mm-dd hh-mm-ss +00:00”. example:. `2025-10-21 06:25:30 +00:00`")
-    brand_entities: Optional[List[Optional[BrandEntities]]] = Field(default=None, description=r"*array of brand entities*. contains information on brands mentioned in the response")
-    fan_out_queries: Optional[List[Optional[StrictStr]]] = Field(default=None, description=r"*array of fan-out queries*. contains related search queries derived from the main query to provide a more comprehensive response")
+    brand_entities: Optional[List[Optional[BrandEntities]]] = Field(default=None, description=r"*array of brand entities*. contains information on brands mentioned in the response. **Note:** available only for `chat_gpt`")
+    fan_out_queries: Optional[List[Optional[StrictStr]]] = Field(default=None, description=r"*array of fan-out queries*. contains related search queries derived from the main query to provide a more comprehensive response. **Note:** available only for `chat_gpt`")
     is_web_search_based: Optional[StrictBool] = Field(default=None, description=r"*indicates whether the response was generated using web search results*. if `true`, the model retrieved live web search results to produce the response. if `false`, the response was generated from the model's internal knowledge")
     __properties: ClassVar[List[str]] = [
         "platform", 
 
@@ -22,7 +22,7 @@ class AiOptimizationLlmMentionsTopMentionedDomainsLiteLiveRequestInfo(BaseModel)
     language_name: Optional[StrictStr] = Field(default=None, description=r"*full name of search language*. optional field. if you use this field, you don't need to specify `language_code`;. if you don't specify this field, the `language_code` with `en` value will be used by default;. you can receive the list of available languages of the search engine with their `language_name` by making a separate request to the `https://api.dataforseo.com/v3/ai_optimization/llm_mentions/locations_and_languages`. Note: `chat_gpt` data is available for `English` only")
     language_code: Optional[StrictStr] = Field(default=None, description=r"*search language code*. optional field. if you use this field, you don't need to specify `language_name`;. you can receive the list of available languages of the search engine with their `language_code`_by making a separate request to the `https://api.dataforseo.com/v3/ai_optimization/llm_mentions/locations_and_languages`. default value: `en`. Note: `chat_gpt` data is available for `en` onlyn")
     platform: Optional[StrictStr] = Field(default=None, description=r"*target platform*. optional field. possible values:. `chat_gpt`, `google`. default value: `google`. **Note:** if the `platform` is not specified, the data is returned for both platforms. **Note #2:**`chat_gpt` data is available for the `United States` and `English` only")
-    links_scope: Optional[StrictStr] = Field(default=None, description=r"*links source scope*. optional field. this parameter specifies which links will be used to extract domains and aggregation data. possible values: `sources`, `search_results`. default value: `sources`")
+    links_scope: Optional[StrictStr] = Field(default=None, description=r"*links source scope*. optional field. this parameter specifies which links will be used to extract domains and aggregation data. possible values: `sources`, `search_results`. default value: `sources`;. **Note:** if you specify `search_results`, the data will be available for `chat_gpt` only")
     filters: Optional[List[Optional[Any]]] = Field(default=None, description=r"*array of results filtering parameters*. optional field. **you can add several filters at once (8 filters maximum)**. you should set a logical operator `and`, `or` between the conditions. the following operators are supported:. `=`, `<>`, `in`, `not_in`, `like`, `not_like`, `ilike`, `not_ilike`, `match`, `not_match`. you can use the `%` operator with `like` and `not_like` to match any string of zero or more characters. example:. `['ai_search_volume','>',1000]`. The full list of possible filters is available [here.](/v3/ai_optimization/llm_mentions/filters/)")
     initial_dataset_filters: Optional[List[Optional[Any]]] = Field(default=None, description=r"*array of filter expressions applied before aggregation*. optional field. you can use this array to filter expressions applied to the raw mentions database before aggregation to limit the rows contributing to the result;. **you can add several filters at once (8 filters maximum)**. you should set a logical operator `and`, `or` between the conditions. the following operators are supported:. `=`, `<>`, `in`, `not_in`, `like`, `not_like`, `ilike`, `not_ilike`, `match`, `not_match`. you can use the `%` operator with `like` and `not_like` to match any string of zero or more characters. example:. `['ai_search_volume','>',1000]`. the full list of possible filters is available [here.](/v3/ai_optimization/llm_mentions/filters). learn more about the initial dataset filters in [this help center article.](https://dataforseo.com/help-center/what-are-the-initial-dataset-filters-and-how-do-they-work)")
     limit: Optional[StrictInt] = Field(default=None, description=r"*maximum number of results in the items array*. optional field. you can use this parameter to limit the number of data objects you receive in the `items` array. minimum value: `1`. maximum value: `1000`. default value: `100`")
 
@@ -22,9 +22,9 @@ class AiOptimizationLlmMentionsTopMentionedDomainsLiveItem(BaseModel):
     language: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*language-based grouping*. array of objects containing mention metrics segmented by content language")
     platform: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*platform-based grouping*. array of group elements containing mention metrics segmented by AI platform")
     sources_domain: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*found top source domains relevant to the target*. array of objects containing data on top domains that are cited as sources in LLM responses. learn more about the sources and how to retrieve LLM citation data at our [Help Center](https://dataforseo.com/help-center/how-to-get-llm-citation-data-with-llm-mentions-api)")
-    search_results_domain: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*found top search results domains relevant to the target*. array of objects containing data on top domains that appear in search results related to LLM queries")
-    brand_entities_title: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*data on brand entities relevant to the target*. array of objects containing data on brand entity titles that appear in search results related to LLM queries")
-    brand_entities_category: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*data on brand entities relevant to the target*. array of objects containing data on brand entity categories that appear in search results related to LLM queries")
+    search_results_domain: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*found top search results domains relevant to the target*. array of objects containing data on top domains that appear in search results related to LLM queries;. **Note:** available only for `chat_gpt`")
+    brand_entities_title: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*data on brand entities relevant to the target*. array of objects containing data on brand entity titles that appear in search results related to LLM queries;. **Note:** available only for `chat_gpt`")
+    brand_entities_category: Optional[List[Optional[AggregatedMetricsItemInfo]]] = Field(default=None, description=r"*data on brand entities relevant to the target*. array of objects containing data on brand entity categories that appear in search results related to LLM queries;. **Note:** available only for `chat_gpt`")
     total: Optional[AggregatedMetricsInfoTotalInfo] = Field(default=None, description=r"*aggregated mentions metrics summary*. contains overall aggregated LLM mention metrics across all dimensions")
     __properties: ClassVar[List[str]] = [
         "domain",