Generative response

You can use Yandex Search API text search together with YandexGPT's generative AI capabilities to get a single concise and coherent generative response to your query, to generate which the AI model analyzes relevant Yandex Search API text search results across specified websites. The response can be generated in Russian, Kazakh and Uzbek. The generation language depends on the search type and query language.

By default, you can send no more than one synchronous query per second to get a generative response. For more information about Yandex Search API limits, see Quotas and limits in Yandex Search API.

You need the search-api.webSearch.user role to run queries.

For more information on the pricing of generative responses to queries, see Yandex Search API pricing policy.

API request body format

The names of the request body fields are different in REST API and gRPC API: the former uses camelCase, while the latter, snake_case.

Each query seeking a generative response must contain the following request body in JSON format:

{
          "messages": [
            {
              "content": "<message_1_text>",
              "role": "ROLE_USER"
            },
            {
              "content": "<model_2_response>",
              "role": "ROLE_ASSISTANT"
            },
            {
              "content": "<message_3_text>",
              "role": "ROLE_USER"
            },
            {
              "content": "<model_4_response>",
              "role": "ROLE_ASSISTANT"
            },
            ...
            {
              "content": "<message_n_text>",
              "role": "ROLE_USER"
            }
          ],
          "site": {
            "site": [
              "<website_1_address_for_search>",
              "<website_2_address_for_search>",
              ...
              "<website_5_address_for_search>"
            ]
          },
          "host": {
            "host": [
              "<host_1_for_search>",
              "<host_2_for_search>",
              ...
              "<host_5_for_search>"
            ]
          },
          "url": {
            "url": [
              "<page_1_for_search>",
              "<page_2_for_search>",
              ...
              "<page_10_for_search>"
            ]
          },
          "folderId": "<folder_ID>",
          "fixMisspell": true|false,
          "enableNrfmDocs": true|false,
          "searchFilters": [
            {
              "date": "<document_update_date>",
              "lang": "<document_language>",
              "format": "<document_format>"
            }
          ]
          "searchType": "string",
          "getPartialResults": true|false,
          "metadata": {
            "fields": "object"
          }
        }

Where:

  • messages: Single search query or a search query with context in the form of chat with the model. It is specified as an array of objects, each one containing two elements:

    • content: Text of a user message or model's response (depending on the role value).
    • role: Message sender's role. The possible values are:
      • ROLE_USER: Means the message is sent by the user, and the content field contains the user's query.
      • ROLE_ASSISTANT: Means the message is sent by the model, and the content field contains the model's response.

  • Set the search scope in the site, host, and url fields. Note that the site, host, and url fields are mutually exclusive; you can only set one of them. If neither of these fields is set, the search will be performed across the entire Yandex search index.

    • site: Restricts the search to a specific array of websites. Not more than 5 websites per search.

      For example, for the yandex.cloud website, the search will target all *.yandex.cloud/* documents, i.e., the results will include pages with the following URLs:

      • yandex.cloud/
      • subdomain.yandex.cloud/
      • yandex.cloud/path/
      • subdomain.yandex.cloud/path/

      You can use the site field to specify the exact path to the search area, e.g., https://yandex.cloud/en/docs.

    • host: Restricts the search to a specific array of hosts. Not more than 5 hosts per search.

      For example, for the yandex.cloud/ host, the search will target all yandex.cloud/* documents, i.e., the results will include pages with the following URLs:

      • yandex.cloud/
      • yandex.cloud/path/

      Unlike site-based restrictions, host-based restrictions do not apply to subdomains. You also cannot provide a specific path to the search area in the host field.

    • url: Restricts the search to a specific array of pages, e.g., https://yandex.cloud/en/docs/serverless-containers/concepts/container and https://yandex.cloud/en/docs/container-registry/concepts/docker-image. Not more than 10 pages per search.

  • folderId: Folder ID.

  • fixMisspell: This parameter enables checking the query text for typos. If the parameter is set, the query text is checked for typos before it is sent. If there are typos, the fixedMisspellQuery field is added to the response, containing the fixed query text that was sent to the model. This is an optional setting. The possible values are true or false.

  • enableNrfmDocs: This parameter determines whether search results will include documents which are not directly accessible from the home page. It only applies if the search scope is set by the site parameter. For example, if you want the results to include a page that is not accessible through any of the links on the home page, set enableNrfmDocs to true. This is an optional setting. The possible values are true or false.

  • searchFilters: Additional text to add to each query. It is used to provide the date:, mime:, and lang: search operators. For example, if you provide "date": ">20250101", the query response will only return documents updated after January 1, 2025. This is an optional setting. The date, lang, and format fields are mutually exclusive: you can only provide one of them in the request body.

  • searchType: Search type, affects the search area and response language. The possible values are:

    • SEARCH_TYPE_RU: For the Russian search type. The response will be generated in Russian.
    • SEARCH_TYPE_KK: For the Kazakh search type.
    • SEARCH_TYPE_UZ: For the Uzbek search type.

  • getPartialResults: Decides whether to send intermediate response generation results or to wait for the final generation results and send the whole response. This is an optional setting. The possible values are true or false. The default value is false.

  • metadata: Additional search parameters. This is an optional setting.

Request body example:
{
          "messages": [
            {
              "content": "What is containerization and how is it implemented in Yandex Cloud?",
              "role": "ROLE_USER"
            }
          ],
          "site": {
            "site": [
                "https://ru.wikipedia.org/wiki/Контейнеризация",
                "https://yandex.cloud/ru/docs/serverless-containers/",
                "https://yandex.cloud/ru/docs/container-registry/"
            ]
          },
          "folderId": "aoevhr118rhc********",
          "fixMisspell": "true",
          "enableNrfmDocs": "true",
          "searchFilters": [
            {
              "date": ">20250101"
            }
          ]
        }
        
{
          "messages": [
            {
              "content": "<message_1_text>",
              "role": "ROLE_USER"
            },
            {
              "content": "<model_1_response>",
              "role": "ROLE_ASSISTANT"
            },
            {
              "content": "<message_2_text>",
              "role": "ROLE_USER"
            },
            {
              "content": "<model_3_response>",
              "role": "ROLE_ASSISTANT"
            },
            ...
            {
              "content": "<message_n_text>",
              "role": "ROLE_USER"
            }
          ],
          "site": {
            "site": [
              "<website_1_address_for_search>",
              "<website_2_address_for_search>",
              ...
              "<website_5_address_for_search>"
            ]
          },
          "host": {
            "host": [
              "<host_1_for_search>",
              "<host_2_for_search>",
              ...
              "<host_5_for_search>"
            ]
          },
          "url": {
            "url": [
              "<page_1_for_search>",
              "<page_2_for_search>",
              ...
              "<page_10_for_search>"
            ]
          },
          "folder_id": "<folder_ID>",
          "fix_misspell": true|false,
          "enable_nrfm_docs": true|false,
          "search_filters": [
            {
              "date": "<document_update_date>",
              "lang": "<document_language>",
              "format": "<document_format>"
            }
          ]
        }

Where:

  • messages: Single search query or a search query with context in the form of chat with the model. It is specified as an array of objects, each one containing two elements:

    • content: Text of a user message or model's response (depending on the role value).
    • role: Message sender's role. The possible values are:
      • ROLE_USER: Means the message is sent by the user, and the content field contains the user's query.
      • ROLE_ASSISTANT: Means the message is sent by the model, and the content field contains the model's response.

  • Set the search scope in the site, host, and url fields. Note that the site, host, and url fields are mutually exclusive; you can only set one of them. If neither of these fields is set, the search will be performed across the entire Yandex search index.

    • site: Restricts the search to a specific array of websites. Not more than 5 websites per search.

      For example, for the yandex.cloud website, the search will target all *.yandex.cloud/* documents, i.e., the results will include pages with the following URLs:

      • yandex.cloud/
      • subdomain.yandex.cloud/
      • yandex.cloud/path/
      • subdomain.yandex.cloud/path/

      You can use the site field to specify the exact path to the search area, e.g., https://yandex.cloud/en/docs.

    • host: Restricts the search to a specific array of hosts. Not more than 5 hosts per search.

      For example, for the yandex.cloud/ host, the search will target all yandex.cloud/* documents, i.e., the results will include pages with the following URLs:

      • yandex.cloud/
      • yandex.cloud/path/

      Unlike site-based restrictions, host-based restrictions do not apply to subdomains. You also cannot provide a specific path to the search area in the host field.

    • url: Restricts the search to a specific array of pages, e.g., https://yandex.cloud/en/docs/serverless-containers/concepts/container and https://yandex.cloud/en/docs/container-registry/concepts/docker-image. Not more than 10 pages per search.

  • folder_id: Folder ID.

  • fix_misspell: This parameter enables checking the query text for typos. If the parameter is set, the query text is checked for typos before it is sent. If there are typos, the fixed_misspell_query field is added to the response, containing the fixed query text that was sent to the model. This is an optional setting. The possible values are true or false.

  • enable_nrfm_docs: This parameter determines whether search results will include documents which are not directly accessible from the home page. It only applies if the search scope is set by the site parameter. For example, if you want the results to include a page that is not accessible through any of the links on the home page, set enable_nrfm_docs to true. This is an optional setting. The possible values are true or false.

  • search_filters: Additional text to add to each query. It is used to provide the date:, mime:, and lang: search operators. For example, if you provide "date": ">20250101", the query response will only return documents updated after January 1, 2025. This is an optional setting. The date, lang, and format fields are mutually exclusive: you can only provide one of them in the request body.

  • search_type: Search type, affects the search area and response language. The possible values are:

    • SEARCH_TYPE_RU: For the Russian search type. The response will be generated in Russian.
    • SEARCH_TYPE_KK: For the Kazakh search type.
    • SEARCH_TYPE_UZ: For the Uzbek search type.

  • get_partial_results: Decides whether to send intermediate response generation results or to wait for the final generation results and send the whole response. This is an optional setting. The possible values are true or false. The default value is false.

  • metadata: Additional search parameters. This is an optional setting.

Request body example:
{
          "messages": [
            {
              "content": "What is containerization and how is it implemented in Yandex Cloud?",
              "role": "ROLE_USER"
            }
          ],
          "site": {
            "site": [
                "https://ru.wikipedia.org/wiki/Контейнеризация",
                "https://yandex.cloud/en/docs/serverless-containers/",
                "https://yandex.cloud/en/docs/container-registry/"
            ]
          },
          "folder_id": "aoevhr118rhc********",
          "fix_misspell": "true",
          "enable_nrfm_docs": "true",
          "search_filters": [
            {
              "date": ">20250101"
            }
          ]
        }

Sending a request via the API

To send a request via the API, use the search method for GenSearch. Install cURL and jq if needed:

curl \
          --request POST \
          --header "Authorization: Bearer <IAM_token>" \
          --data "@<file_path>" \
          "https://searchapi.api.cloud.yandex.net/v2/gen/search" \
          | jq

Where:

  • <IAM_token>: IAM token of a user or service account with the search-api.webSearch.user role.
  • <file_path>: Path to the file with the request body.

To send a query, use the GenSearchService/Search call. Install gRPCurl and jq if needed:

grpcurl \
          -rpc-header "Authorization: Bearer <IAM_token>" \
          -d @ < <file_path> \
          searchapi.api.cloud.yandex.net:443 yandex.cloud.searchapi.v2.GenSearchService/Search \
          | jq

Where:

  • <IAM_token>: IAM token of a user or service account with the search-api.webSearch.user role.
  • <file_path>: Path to the file with the request body.

Sending a request via Yandex Cloud ML SDK

To send a request for a generative response via Yandex Cloud ML SDK, run the following Python code. This example illustrates the key aspects of using ML SDK to get a generative response:

#!/usr/bin/env python3
        
        from __future__ import annotations
        
        import pprint
        
        from yandex_ai_studio_sdk import AIStudio
        
        
        def main() -> None:
        
            sdk = AIStudio(
                folder_id="<folder_ID>",
                auth="<API_key>",
            )
            sdk.setup_default_logging()
        
            search = sdk.search_api.generative(
                # You can use only one of the three params: site, host, or url
                site=["yandex.cloud", "yandex.ru"],
                # host=['yandex.cloud/', 'yandex.ru/'],
                # url=['https://yandex.cloud/ru/docs/serverless-containers/concepts/container', 'https://yandex.cloud/ru/docs/container-registry/concepts/docker-image'],
                fix_misspell=True,
                enable_nrfm_docs=True,
                search_filters=[
                    {"date": ">20250101"},
                    {"lang": "ru"},
                    {"format": "pdf"},
                ],
            )
        
            # You can pass a string as a query
            search_result = search.run("Yandex Cloud generative Search API params")
        
            # You can examine the search_result structure via pprint
            # to get to know how to work with it:
            pprint.pprint(search_result)
            print()
        
            queries = [
                # You can also pass a {'text', 'role'} dict like in the completions models
                {"text": "Gen search api params", "role": "user"},
                "With examples",
            ]
        
            # And you can pass an array of any allowed types
            search_result = search.run(queries)  # type: ignore[arg-type]
            print(search_result.text)
            print()
        
            # Also search result itself could be used as one of the queries for a better context
            queries.append(search_result)  # type: ignore[arg-type]
            queries.append("Get me more examples of how to use Generative Search API with gprc")
        
            search_result = search.run(queries)  # type: ignore[arg-type]
            print(search_result.text)
            print()
        
        
        if __name__ == "__main__":
            main()

Where:

Provide the search query text in the .run method and use the relevant search_api.generative object properties to set the parameters of your search:

  • The site, host, and url properties define the search scope. Note that the site, host, and url properties are mutually exclusive; you can only set one of them. If neither of these fields is set, the search will be performed across the entire Yandex search index.

    • site: Restricts the search to a specific array of websites. Not more than 5 websites per search.

      For example, for the yandex.cloud website, the search will target all *.yandex.cloud/* documents, i.e., the results will include pages with the following URLs:

      • yandex.cloud/
      • subdomain.yandex.cloud/
      • yandex.cloud/path/
      • subdomain.yandex.cloud/path/

      In the site property, you can specify the exact path to the search area, e.g., https://yandex.cloud/en/docs.

    • host: Restricts the search to a specific array of hosts. Not more than 5 hosts per search.

      For example, for the yandex.cloud/ host, the search will target all yandex.cloud/* documents, i.e., the results will include pages with the following URLs:

      • yandex.cloud/
      • yandex.cloud/path/

      Unlike site-based restrictions, host-based restrictions do not apply to subdomains. You also cannot provide a specific path to the search area in the host property.

    • url: Restricts the search to a specific array of pages, e.g., https://yandex.cloud/en/docs/serverless-containers/concepts/container and https://yandex.cloud/en/docs/container-registry/concepts/docker-image. Not more than 10 pages per search.

  • fix_misspell: This parameter enables checking the query text for typos. If the parameter is set, the query text is checked for typos before it is sent. If there are typos, the fixed_misspell_query field is added to the response, containing the fixed query text that was sent to the model. This is an optional setting. The possible values are true or false.

  • enable_nrfm_docs: This parameter determines whether search results will include documents which are not directly accessible from the home page. It only applies if the search scope is set by the site parameter. For example, if you want the results to include a page that is not accessible through any of the links on the home page, set enable_nrfm_docs to true. This is an optional setting. The possible values are true or false.

  • search_filters: Additional text to add to each query. It is used to provide the date:, mime:, and lang: search operators. For example, if you provide "date": ">20250101", the query response will only return documents updated after January 1, 2025. This is an optional setting.

For the ML SDK library source code and use cases, visit this GitHub repository. For more on Yandex Cloud ML SDK, see this AI Studio guide.

Generative response

Yandex Search API returns a JSON format response with the following syntax:

Note

The response contains no required fields. It may not return a field if there is no relevant data.

{
          "message": {
            "content": "<response_text>",
            "role": "ROLE_ASSISTANT"
          },
          "sources": [
            {
              "used": false|true,
              "url": "<link_to_found_document_1>",
              "title": "<title_of_found_document_1>"
            },
            {
              "used": false|true,
              "url": "<link_to_found_document_2>",
              "title": "<title_of_found_document_2>"
            },
            ...
            {
              "used": false|true,
              "url": "<link_to_found_document_n>",
              "title": "<title_of_found_document_n>"
            }
          ],
          "searchQueries": [
            {
              "text": "<query_1_text>",
              "reqId": "<query_1_ID>"
            },
            {
              "text": "<query_2_text>",
              "reqId": "<query_2_ID>"
            },
            ...
            {
              "text": "<query_n_text>",
              "reqId": "<query_n_ID>"
            },
          ],
          "isAnswerRejected": false|true,
          "isBulletAnswer": false|true,
          "fixedMisspellQuery": "<fixed_query_text >"
        }

Where:

  • message.content: Text of the generative response. The footnotes within the text refer to sources, the list and order of which are given in the sources field.

  • sources: Array of source documents that were found during the query, could be used by YandexGPT as data sources when forming the response, and can be footnoted in the message.content field. Each source document contains the following fields:

    • used: Indicates whether the document was used to generate the response. The possible values are true or false.
    • url: Document URL.
    • title: Document title. It may be missing from the results if the website owner did not define the page header.

  • searchQueries: List of additional search queries sent by the generative model to the search engine. Each query contains the following fields:

    • text: Search query text.
    • reqId: Yandex Search API unique query ID.

  • isAnswerRejected: Indicates the model's refusal to provide a response for ethical reasons:

    • false: Model has returned a response.
    • true: Model has refused to return a response.

  • isBulletAnswer: Indicates a bullet response where the model cannot give a proper response and suggests a set of bullets with various information:

    • false: Model gave a good answer.
    • true: Model suggested a set of bullets.

  • fixedMisspellQuery: Fixed query text. This parameter is optional. It appears in the response only if you provide fixMisspell in the request body and typos were found in the query text.

Here is an example of a generative response with website limitation:
[
          {
            "message": {
              "content": "**Containerization** (OS-level virtualization) is a **virtualization method** 
              in which the OS kernel manages several isolated user-space instances 
              instead of a single one. [1] These instances (containers or zones) are identical
              to a separate OS instance in terms of the processes running inside them. [1] vCPU 
              provides complete container isolation, so applications from different containers 
              have no impact on one another. [1]\n\n**In Yandex Cloud, containerization is implemented with the help of 
              Yandex Serverless Containers**. [5][6] A container allows you to run an application 
              contained in a Docker image, in Yandex Cloud. [6] \n\n**Some aspects of containerization in 
              Yandex Cloud:**\n\n* **Creating a container revision**. [6] You can only create a container revision 
              from a Docker image uploaded to a registry in Yandex Container Registry. [6] Other registries are not 
              supported. [6] The revision contains all the information you need to run the container. [6]\n* 
              **Invoking a container**. [6] Once you have created a revision, you can invoke the container via HTTPS 
              using a trigger or the Yandex API Gateway extension. [6]\n* **Scaling a container**. [6] If 
              the container is invoked faster than the instance can process the request, the service scales the container 
              by running additional instances of it. [6] This enables concurrent request 
              processing. [6]\n* **Provisioned instances**. [6] A provisioned instance 
              is a container instance that is guaranteed not to have a cold start when you run it. [6]",
              "role": "ROLE_ASSISTANT"
            },
            "sources": [
              {
                "used": false,
                "url": "https://ru.wikipedia.org/wiki/%D0%9A%D0%BE%D0%BD%D1%82%D0%B5%D0%B9%D0%BD%D0%B5%D1%80%D0%B8%D0%B7%D0%B0%D1%86%D0%B8%D1%8F",
                "title": "Containerization (Wikipedia)"
              },
              {
                "used": true,
                "url": "https://yandex.cloud/ru/docs/serverless-containers/tutorials/functions-framework-to-container",
                "title": "Developing functions in Functions Framework and deploying them to Yandex Serverless Containers | Yandex Cloud documentation"
              },
              {
                "used": false,
                "url": "https://yandex.cloud/ru/docs/container-registry/",
                "title": "Yandex Container Registry | Yandex Cloud documentation"
              },
              {
                "used": false,
                "url": "https://yandex.cloud/ru/docs/container-registry/concepts/docker-image",
                "title": "Docker image. What is it and how does it work? | Yandex Cloud documentation"
              },
              {
                "used": false,
                "url": "https://yandex.cloud/ru/docs/serverless-containers/operations/",
                "title": "How to work with Yandex Serverless Containers | Yandex Cloud documentation"
              },
              {
                "used": true,
                "url": "https://yandex.cloud/ru/docs/serverless-containers/concepts/container",
                "title": "Container in Yandex Serverless Containers | Yandex Cloud documentation"
              },
              {
                "used": true,
                "url": "https://yandex.cloud/ru/docs/container-registry/operations/docker-image/docker-image-push",
                "title": "Pushing a Docker image to a registry in Container Registry | Yandex Cloud documentation"
              },
              {
                "used": false,
                "url": "https://yandex.cloud/ru/docs/serverless-containers/tutorials/deploy-app-container",
                "title": "Running a containerized app in Yandex Serverless Containers | Yandex Cloud documentation"
              },
              {
                "used": false,
                "url": "https://yandex.cloud/ru/docs/container-registry/tutorials/fault-tolerance",
                "title": "Configuring a fault-tolerant architecture in Yandex Cloud | Yandex Cloud documentation"
              },
              {
                "used": false,
                "url": "https://yandex.cloud/ru/docs/serverless-containers/tf-ref",
                "title": "Terraform reference for Yandex Serverless Containers | Yandex Cloud documentation"
              }
            ],
            "searchQueries": [
              {
                "text": "what is containerization and how is it implemented in yandex cloud date 2025 01 01 date 2025 01 01 date 2025 01 01",
                "reqId": "1742492744075717-6834712924673670818-e23cqdex********-BAL"
              },
              {
                "text": "how containerization is implemented in yandex cloud date 2025 01 01 date 2025 01 01 date 2025 01 01",
                "reqId": "1742492744352285-5531077099747983300-hhsihxn5********-BAL"
              },
              {
                "text": "what is containerization date 2025 01 01 date 2025 01 01 date 2025 01 01",
                "reqId": "1742492744351443-10540017330195862709-gai4ndrg********-BAL"
              }
            ],
            "isAnswerRejected": false,
            "isBulletAnswer": false,
            "fixedMisspellQuery": "What is containerization and how is it implemented in Yandex Cloud?"
          }
        ]
        
{
          "message": {
            "content": "<response_text>",
            "role": "ROLE_ASSISTANT"
          },
          "sources": [
            {
              "url": "<link_to_found_document_1>",
              "title": "<title_of_found_document_1>",
              "used": false|true
            },
            {
              "url": "<link_to_found_document_2>",
              "title": "<title_of_found_document_2>",
              "used": false|true
            },
            ...
            {
              "url": "<link_to_found_document_n>",
              "title": "<title_of_found_document_n>",
              "used": false|true
            }
          ],
          "search_queries": [
            {
              "text": "<query_1_text>",
              "req_id": "<query_1_ID>"
            },
            {
              "text": "<query_2_text>",
              "req_id": "<query_2_ID>"
            },
            ...
            {
              "text": "<query_n_text>",
              "req_id": "<query_n_ID>"
            },
          ],
          "is_answer_rejected": false|true,
          "is_bullet_answer": false|true,
          "fixed_misspell_query": "<fixed_query_text >"
        }

Where:

  • message.content: Text of the generative response. The footnotes within the text refer to sources, the list and order of which are given in the sources field.

  • sources: Array of source documents that were found during the query, could be used by YandexGPT as data sources when forming the response, and can be footnoted in the message.content field. Each source document contains the following fields:

    • url: Document URL.
    • title: Document title.
    • used: Indicates whether the document was used to generate the response. The possible values are true or false.

  • search_queries: List of additional search queries sent by the generative model to the search engine. Each query contains the following fields:

    • text: Search query text.
    • req_id: Yandex Search API unique query ID.

  • is_answer_rejected: Indicates the model's refusal to provide a response for ethical reasons:

    • false: Model has returned a response.
    • true: Model has refused to return a response.

  • is_bullet_answer: Indicates a bullet response where the model cannot give a proper response and suggests a set of bullets with various information:

    • false: Model gave a good answer.
    • true: Model suggested a set of bullets.

  • fixed_misspell_query: Fixed query text. This parameter is optional. It appears in the response only if you provide fix_misspell in the request body and typos were found in the query text.

Here is an example of a generative response with website limitation:
{
          "message": {
            "content": "**Containerization** (OS-level virtualization) is a **virtualization method** 
            in which the OS kernel manages several isolated user-space instances 
            instead of a single one. [1] These instances (containers or zones) are identical 
            to a separate OS instance in terms of the processes running inside them. [1] vCPU provides 
            complete container isolation, so applications from different containers have no impact 
            on one another. [1]\n\n**In Yandex Cloud, containerization is implemented with the help of 
            Yandex Serverless Containers**. [7] It allows you to run an application 
            contained in a Docker image, in Yandex Cloud. [7] \n\n**Some aspects of containerization in 
            Yandex Cloud:**\n\n* **Creating a container revision**. [7] You can only create a revision 
            from a Docker image uploaded to a registry in Yandex Container Registry. [7] Other registries are not supported. 
            supported. [7] The revision contains all the information you need to run the container. [7]\n* **Invoking 
            a container**. [7] Once you have created a revision, you can invoke the container via HTTPS using a trigger 
            or the Yandex API Gateway extension. [7]\n* **Scaling a container**. [7] If the container is invoked 
            faster than the instance can process the request, the service scales the container by running 
            its additional instances. [7] This ensures parallel processing of queries. [7]\n* 
            **Provisioned instances**. [7] This is a container instance that is guaranteed not to have 
            a cold start when you run it. [7] In a provisioned instance, before the container is invoked, 
            the Serverless Containers runtime components are initialized, and the user application is loaded and initialized. [7]",
            "role": "ROLE_ASSISTANT"
          },
          "sources": [
            {
              "url": "https://ru.wikipedia.org/wiki/%D0%9A%D0%BE%D0%BD%D1%82%D0%B5%D0%B9%D0%BD%D0%B5%D1%80%D0%B8%D0%B7%D0%B0%D1%86%D0%B8%D1%8F",
              "title": "Containerization (Wikipedia)",
              "used": false
            },
            {
              "url": "https://yandex.cloud/ru/docs/serverless-containers/tutorials/functions-framework-to-container",
              "title": "Developing functions in Functions Framework and deploying them to Yandex Serverless Containers | Yandex Cloud documentation",
              "used": true
            },
            {
              "url": "https://yandex.cloud/ru/docs/container-registry/",
              "title": "Yandex Container Registry | Yandex Cloud documentation",
              "used": false
            },
            {
              "url": "https://yandex.cloud/ru/docs/container-registry/concepts/docker-image",
              "title": "Docker image. What is it and how does it work? | Yandex Cloud documentation",
              "used": false
            },
            {
              "url": "https://yandex.cloud/ru/docs/container-registry/operations/docker-image/docker-image-push",
              "title": "Pushing a Docker image to a registry in Container Registry | Yandex Cloud documentation",
              "used": false
            },
            {
              "url": "https://yandex.cloud/ru/docs/serverless-containers/tutorials/deploy-app-container",
              "title": "Running a containerized app in Yandex Serverless Containers | Yandex Cloud documentation",
              "used": false
            },
            {
              "url": "https://yandex.cloud/ru/docs/serverless-containers/concepts/container",
              "title": "Container in Yandex Serverless Containers | Yandex Cloud documentation",
              "used": false
            },
            {
              "url": "https://yandex.cloud/ru/docs/serverless-containers/tf-ref",
              "title": "Terraform reference for Yandex Serverless Containers | Yandex Cloud documentation",
              "used": true
            },
            {
              "url": "https://yandex.cloud/ru/docs/serverless-containers/operations/",
              "title": "How to work with Yandex Serverless Containers | Yandex Cloud documentation",
              "used": false
            },
            {
              "url": "https://yandex.cloud/ru/docs/container-registry/tutorials/fault-tolerance",
              "title": "Configuring a fault-tolerant architecture in Yandex Cloud | Yandex Cloud documentation",
              "used": false
            }
          ],
          "search_queries": [
            {
              "text": "what is containerization and how is it implemented in yandex cloud date 2025 01 01 date 2025 01 01 date 2025 01 01",
              "req_id": "1742493532407414-13584885235180537459-jjleoq7t********-BAL"
            },
            {
              "text": "how containerization is implemented in yandex cloud date 2025 01 01 date 2025 01 01 date 2025 01 01",
              "req_id": "1742493532717030-17218638161437229208-rs6g5w5h********-BAL"
            },
            {
              "text": "what is containerization date 2025 01 01 date 2025 01 01 date 2025 01 01",
              "req_id": "1742493532716328-3123354248981714225-rs6g5w5h********-BAL"
            }
          ],
          "is_answer_rejected": false,
          "is_bullet_answer": false,
          "fixed_misspell_query": "What is containerization and how is it implemented in Yandex Cloud?"
        }

Response features

Based on the query and search results, Yandex Search API may include the following warnings in a generative response:

  • If no relevant documents were found:

    No results found.
    Rephrase your query or ask something else.

  • If Yandex Search API has found the relevant source documents but was unable to extract information:

    Failed to extract the requested information from the documents. You can try opening them yourself or view the search results.

  • If Yandex Search API has found the source documents and succeeded extracting the information but is doubtful about response quality, it will preface its response with:

    There is various information on this topic online. You can find its overview below.

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