# Vector databases > Vector databases - Validation record checking the ability of the deployment to serve as a vector > database. This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context. Companion generated at `2026-05-06T18:17:09.835868+00:00` (UTC). ## Primary page - [Vector databases](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html): Full documentation for this topic (HTML). ## Sections on this page - [classdatarobot.models.genai.vector_database.CustomModelVectorDatabaseValidation](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.CustomModelVectorDatabaseValidation): In-page section heading. - [classdatarobot.models.genai.vector_database.SupportedEmbeddings](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.SupportedEmbeddings): In-page section heading. - [classdatarobot.models.genai.vector_database.SupportedTextChunkings](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.SupportedTextChunkings): In-page section heading. - [classdatarobot.models.genai.vector_database.VectorDatabase](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase): In-page section heading. - [classmethodget_supported_embeddings(dataset_id=None, use_case=None)](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.get_supported_embeddings): In-page section heading. - [submit_export_dataset_job()](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.submit_export_dataset_job): In-page section heading. - [classmethodget_supported_retrieval_settings()](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.get_supported_retrieval_settings): In-page section heading. - [classmethodcreate(dataset_id, chunking_parameters=None, use_case=None, name=None, parent_vector_database_id=None, update_llm_blueprints=None, update_deployments=None, external_vector_database_connection=None, metadata_dataset_id=None, metadata_combination_strategy=None)](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.create): In-page section heading. - [classmethodcreate_from_custom_model(name, use_case=None, validation_id=None, prompt_column_name=None, target_column_name=None, deployment_id=None, model_id=None)](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.create_from_custom_model): In-page section heading. - [classmethodget(vector_database_id)](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.get): In-page section heading. - [classmethodlist(use_case=None, playground=None, search=None, sort=None, completed_only=None)](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.list): In-page section heading. - [update(name=None, credential_id=None)](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.update): In-page section heading. - [update_connected(dataset_id, metadata_dataset_id=None, metadata_combination_strategy=None)](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.update_connected): In-page section heading. - [delete()](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.delete): In-page section heading. - [classmethodget_supported_text_chunkings()](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.get_supported_text_chunkings): In-page section heading. - [download_text_and_embeddings_asset(file_path=None, part=None)](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.download_text_and_embeddings_asset): In-page section heading. - [send_to_custom_model_workshop(maximum_memory=None, resource_bundle_id=None, replicas=None, network_egress_policy=None)](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.send_to_custom_model_workshop): In-page section heading. - [deploy(default_prediction_server_id=None, prediction_environment_id=None, credential_id=None, maximum_memory=None, resource_bundle_id=None, replicas=None, network_egress_policy=None)](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabase.deploy): In-page section heading. - [classdatarobot.models.genai.vector_database.SupportedRetrievalSetting](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.SupportedRetrievalSetting): In-page section heading. - [classdatarobot.models.genai.vector_database.VectorDatabaseDatasetExportJob](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.VectorDatabaseDatasetExportJob): In-page section heading. - [classdatarobot.models.genai.chat_prompt.Citation](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.chat_prompt.Citation): In-page section heading. - [classdatarobot.models.genai.llm_blueprint.VectorDatabaseSettings](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.llm_blueprint.VectorDatabaseSettings): In-page section heading. - [classdatarobot.models.genai.vector_database.ChunkingParameters](https://docs.datarobot.com/en/docs/api/reference/sdk/gen-vector-databases.html#datarobot.models.genai.vector_database.ChunkingParameters): In-page section heading. ## Related documentation - [Developer documentation](https://docs.datarobot.com/en/docs/api/index.html): Linked from this page. - [API reference](https://docs.datarobot.com/en/docs/api/reference/index.html): Linked from this page. - [Python API client](https://docs.datarobot.com/en/docs/api/reference/sdk/index.html): Linked from this page. - [Generative AI](https://docs.datarobot.com/en/docs/api/reference/sdk/tag-genai.html): Linked from this page. - [CustomModelVersion](https://docs.datarobot.com/en/docs/api/reference/sdk/custom-models.html#datarobot.CustomModelVersion): Linked from this page. - [Deployment](https://docs.datarobot.com/en/docs/api/reference/sdk/deployment-management.html#datarobot.models.Deployment): Linked from this page. ## Documentation content ### class datarobot.models.genai.vector_database.CustomModelVectorDatabaseValidation Validation record checking the ability of the deployment to serve as a vector database. - Variables: ### class datarobot.models.genai.vector_database.SupportedEmbeddings All supported embedding models including the recommended default model. - Variables: ### class datarobot.models.genai.vector_database.SupportedTextChunkings Supported text chunking configurations which includes a set of recommended chunking parameters for each supported embedding model. - Variables: text_chunking_configs – All supported text chunking configurations. ### class datarobot.models.genai.vector_database.VectorDatabase Metadata for a DataRobot vector database accessible to the user. - Variables: #### classmethod get_supported_embeddings(dataset_id=None, use_case=None) Get all supported and the recommended embedding models. - Parameters: - Returns: supported_embeddings – The supported embedding models. - Return type: SupportedEmbeddings #### submit_export_dataset_job() Submit the vector database dataset export job. - Returns: result – The result of the vector database dataset export job containing the exported dataset id. - Return type: VectorDatabaseDatasetExportJob #### classmethod get_supported_retrieval_settings() Get supported retrieval settings. - Returns: supported_retrieval_settings – The supported retriever settings. - Return type: SupportedRetrievalSettings #### classmethod create(dataset_id, chunking_parameters=None, use_case=None, name=None, parent_vector_database_id=None, update_llm_blueprints=None, update_deployments=None, external_vector_database_connection=None, metadata_dataset_id=None, metadata_combination_strategy=None) Create a new vector database. - Parameters: - Returns: vector database – The created vector database with execution status ‘new’. - Return type: VectorDatabase #### classmethod create_from_custom_model(name, use_case=None, validation_id=None, prompt_column_name=None, target_column_name=None, deployment_id=None, model_id=None) Create a new vector database from validated custom model deployment. - Parameters: - Returns: vector database – The created vector database. - Return type: VectorDatabase #### classmethod get(vector_database_id) Retrieve a single vector database. - Parameters: vector_database_id ( str ) – The ID of the vector database you want to retrieve. - Returns: vector database – The requested vector database. - Return type: VectorDatabase #### classmethod list(use_case=None, playground=None, search=None, sort=None, completed_only=None) List all vector databases associated with a specific use case available to the user. - Parameters: - Returns: vectorbases – A list of vector databases available to the user. - Return type: list[VectorDatabase] #### update(name=None, credential_id=None) Update the vector database. - Parameters: - Returns: vector database – The updated vector database. - Return type: VectorDatabase #### update_connected(dataset_id, metadata_dataset_id=None, metadata_combination_strategy=None) Update a connected vector database. - Parameters: - Returns: vector database – The updated vector database. - Return type: VectorDatabase #### delete() Delete the vector database. - Return type: None #### classmethod get_supported_text_chunkings() Get all supported text chunking configurations which includes a set of recommended chunking parameters for each supported embedding model. - Returns: supported_text_chunkings – The supported text chunking configurations. - Return type: SupportedTextChunkings #### download_text_and_embeddings_asset(file_path=None, part=None) Download a parquet file with text chunks and corresponding embeddings created by a vector database. - Parameters: - Return type: None #### send_to_custom_model_workshop(maximum_memory=None, resource_bundle_id=None, replicas=None, network_egress_policy=None) Create a new CustomModelVersion for this vector database. - Parameters: - Return type: CustomModelVersion #### deploy(default_prediction_server_id=None, prediction_environment_id=None, credential_id=None, maximum_memory=None, resource_bundle_id=None, replicas=None, network_egress_policy=None) Create a new Custom Model for this vector database and deploy it on a new Deployment. - Parameters: - Return type: Deployment ### class datarobot.models.genai.vector_database.SupportedRetrievalSetting A single supported retrieval setting. - Variables: ### class datarobot.models.genai.vector_database.VectorDatabaseDatasetExportJob Response for the vector database dataset export job. - Variables: ### class datarobot.models.genai.chat_prompt.Citation Citation for documents retrieved from a vector database. - Variables: ### class datarobot.models.genai.llm_blueprint.VectorDatabaseSettings Settings for a DataRobot GenAI vector database associated with an LLM blueprint. - Variables: ### class datarobot.models.genai.vector_database.ChunkingParameters Parameters defining how documents are split and embedded. - Variables: