airbyte 0.8.0-beta2, Mar 27 25

airbyte 0.8.0-beta2 published on Thursday, Mar 27, 2025 by airbytehq

airbyte.DestinationSnowflakeCortex

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airbyte 0.8.0-beta2 published on Thursday, Mar 27, 2025 by airbytehq

Example Usage

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package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.airbyte.DestinationSnowflakeCortex;
import com.pulumi.airbyte.DestinationSnowflakeCortexArgs;
import com.pulumi.airbyte.inputs.DestinationSnowflakeCortexConfigurationArgs;
import com.pulumi.airbyte.inputs.DestinationSnowflakeCortexConfigurationEmbeddingArgs;
import com.pulumi.airbyte.inputs.DestinationSnowflakeCortexConfigurationEmbeddingFakeArgs;
import com.pulumi.airbyte.inputs.DestinationSnowflakeCortexConfigurationIndexingArgs;
import com.pulumi.airbyte.inputs.DestinationSnowflakeCortexConfigurationIndexingCredentialsArgs;
import com.pulumi.airbyte.inputs.DestinationSnowflakeCortexConfigurationProcessingArgs;
import com.pulumi.airbyte.inputs.DestinationSnowflakeCortexConfigurationProcessingTextSplitterArgs;
import com.pulumi.airbyte.inputs.DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparatorArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var myDestinationSnowflakecortex = new DestinationSnowflakeCortex("myDestinationSnowflakecortex", DestinationSnowflakeCortexArgs.builder()
            .configuration(DestinationSnowflakeCortexConfigurationArgs.builder()
                .embedding(DestinationSnowflakeCortexConfigurationEmbeddingArgs.builder()
                    .fake()
                    .build())
                .indexing(DestinationSnowflakeCortexConfigurationIndexingArgs.builder()
                    .credentials(DestinationSnowflakeCortexConfigurationIndexingCredentialsArgs.builder()
                        .password("AIRBYTE_PASSWORD")
                        .build())
                    .database("AIRBYTE_DATABASE")
                    .defaultSchema("AIRBYTE_SCHEMA")
                    .host("AIRBYTE_ACCOUNT")
                    .role("AIRBYTE_ROLE")
                    .username("AIRBYTE_USER")
                    .warehouse("AIRBYTE_WAREHOUSE")
                    .build())
                .omit_raw_text(true)
                .processing(DestinationSnowflakeCortexConfigurationProcessingArgs.builder()
                    .chunkOverlap(3)
                    .chunkSize(6147)
                    .fieldNameMappings(DestinationSnowflakeCortexConfigurationProcessingFieldNameMappingArgs.builder()
                        .fromField("...my_from_field...")
                        .toField("...my_to_field...")
                        .build())
                    .metadataFields("...")
                    .textFields("...")
                    .textSplitter(DestinationSnowflakeCortexConfigurationProcessingTextSplitterArgs.builder()
                        .bySeparator(DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparatorArgs.builder()
                            .keepSeparator(true)
                            .separators("...")
                            .build())
                        .build())
                    .build())
                .build())
            .definitionId("4e970f65-b8a4-4398-b19e-2a5644731a72")
            .workspaceId("d33dd7fd-91b5-4245-9a6e-0c987c8003c9")
            .build());

    }
}

resources:
  myDestinationSnowflakecortex:
    type: airbyte:DestinationSnowflakeCortex
    properties:
      configuration:
        embedding:
          fake: {}
        indexing:
          credentials:
            password: AIRBYTE_PASSWORD
          database: AIRBYTE_DATABASE
          defaultSchema: AIRBYTE_SCHEMA
          host: AIRBYTE_ACCOUNT
          role: AIRBYTE_ROLE
          username: AIRBYTE_USER
          warehouse: AIRBYTE_WAREHOUSE
        omit_raw_text: true
        processing:
          chunkOverlap: 3
          chunkSize: 6147
          fieldNameMappings:
            - fromField: '...my_from_field...'
              toField: '...my_to_field...'
          metadataFields:
            - '...'
          textFields:
            - '...'
          textSplitter:
            bySeparator:
              keepSeparator: true
              separators:
                - '...'
      definitionId: 4e970f65-b8a4-4398-b19e-2a5644731a72
      workspaceId: d33dd7fd-91b5-4245-9a6e-0c987c8003c9

Create DestinationSnowflakeCortex Resource

Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

Constructor syntax

new DestinationSnowflakeCortex(name: string, args: DestinationSnowflakeCortexArgs, opts?: CustomResourceOptions);

@overload
def DestinationSnowflakeCortex(resource_name: str,
                               args: DestinationSnowflakeCortexArgs,
                               opts: Optional[ResourceOptions] = None)

@overload
def DestinationSnowflakeCortex(resource_name: str,
                               opts: Optional[ResourceOptions] = None,
                               configuration: Optional[DestinationSnowflakeCortexConfigurationArgs] = None,
                               workspace_id: Optional[str] = None,
                               definition_id: Optional[str] = None,
                               name: Optional[str] = None)

func NewDestinationSnowflakeCortex(ctx *Context, name string, args DestinationSnowflakeCortexArgs, opts ...ResourceOption) (*DestinationSnowflakeCortex, error)

public DestinationSnowflakeCortex(string name, DestinationSnowflakeCortexArgs args, CustomResourceOptions? opts = null)

public DestinationSnowflakeCortex(String name, DestinationSnowflakeCortexArgs args)
public DestinationSnowflakeCortex(String name, DestinationSnowflakeCortexArgs args, CustomResourceOptions options)

type: airbyte:DestinationSnowflakeCortex
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

Parameters

name string: The unique name of the resource.
args DestinationSnowflakeCortexArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

resource_name str: The unique name of the resource.
args DestinationSnowflakeCortexArgs: The arguments to resource properties.
opts ResourceOptions: Bag of options to control resource's behavior.

ctx Context: Context object for the current deployment.
name string: The unique name of the resource.
args DestinationSnowflakeCortexArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

name string: The unique name of the resource.
args DestinationSnowflakeCortexArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

name String: The unique name of the resource.
args DestinationSnowflakeCortexArgs: The arguments to resource properties.
options CustomResourceOptions: Bag of options to control resource's behavior.

Constructor example

The following reference example uses placeholder values for all input properties.

var destinationSnowflakeCortexResource = new Airbyte.DestinationSnowflakeCortex("destinationSnowflakeCortexResource", new()
{
    Configuration = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationArgs
    {
        Embedding = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationEmbeddingArgs
        {
            AzureOpenAi = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAiArgs
            {
                ApiBase = "string",
                Deployment = "string",
                OpenaiKey = "string",
            },
            Cohere = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationEmbeddingCohereArgs
            {
                CohereKey = "string",
            },
            Fake = null,
            OpenAi = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationEmbeddingOpenAiArgs
            {
                OpenaiKey = "string",
            },
            OpenAiCompatible = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatibleArgs
            {
                BaseUrl = "string",
                Dimensions = 0,
                ApiKey = "string",
                ModelName = "string",
            },
        },
        Indexing = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationIndexingArgs
        {
            Credentials = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationIndexingCredentialsArgs
            {
                Password = "string",
            },
            Database = "string",
            DefaultSchema = "string",
            Host = "string",
            Role = "string",
            Username = "string",
            Warehouse = "string",
        },
        Processing = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationProcessingArgs
        {
            ChunkSize = 0,
            ChunkOverlap = 0,
            FieldNameMappings = new[]
            {
                new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationProcessingFieldNameMappingArgs
                {
                    FromField = "string",
                    ToField = "string",
                },
            },
            MetadataFields = new[]
            {
                "string",
            },
            TextFields = new[]
            {
                "string",
            },
            TextSplitter = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationProcessingTextSplitterArgs
            {
                ByMarkdownHeader = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeaderArgs
                {
                    SplitLevel = 0,
                },
                ByProgrammingLanguage = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguageArgs
                {
                    Language = "string",
                },
                BySeparator = new Airbyte.Inputs.DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparatorArgs
                {
                    KeepSeparator = false,
                    Separators = new[]
                    {
                        "string",
                    },
                },
            },
        },
        OmitRawText = false,
    },
    WorkspaceId = "string",
    DefinitionId = "string",
    Name = "string",
});

example, err := airbyte.NewDestinationSnowflakeCortex(ctx, "destinationSnowflakeCortexResource", &airbyte.DestinationSnowflakeCortexArgs{
Configuration: &.DestinationSnowflakeCortexConfigurationArgs{
Embedding: &.DestinationSnowflakeCortexConfigurationEmbeddingArgs{
AzureOpenAi: &.DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAiArgs{
ApiBase: pulumi.String("string"),
Deployment: pulumi.String("string"),
OpenaiKey: pulumi.String("string"),
},
Cohere: &.DestinationSnowflakeCortexConfigurationEmbeddingCohereArgs{
CohereKey: pulumi.String("string"),
},
Fake: &.DestinationSnowflakeCortexConfigurationEmbeddingFakeArgs{
},
OpenAi: &.DestinationSnowflakeCortexConfigurationEmbeddingOpenAiArgs{
OpenaiKey: pulumi.String("string"),
},
OpenAiCompatible: &.DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatibleArgs{
BaseUrl: pulumi.String("string"),
Dimensions: pulumi.Float64(0),
ApiKey: pulumi.String("string"),
ModelName: pulumi.String("string"),
},
},
Indexing: &.DestinationSnowflakeCortexConfigurationIndexingArgs{
Credentials: &.DestinationSnowflakeCortexConfigurationIndexingCredentialsArgs{
Password: pulumi.String("string"),
},
Database: pulumi.String("string"),
DefaultSchema: pulumi.String("string"),
Host: pulumi.String("string"),
Role: pulumi.String("string"),
Username: pulumi.String("string"),
Warehouse: pulumi.String("string"),
},
Processing: &.DestinationSnowflakeCortexConfigurationProcessingArgs{
ChunkSize: pulumi.Float64(0),
ChunkOverlap: pulumi.Float64(0),
FieldNameMappings: .DestinationSnowflakeCortexConfigurationProcessingFieldNameMappingArray{
&.DestinationSnowflakeCortexConfigurationProcessingFieldNameMappingArgs{
FromField: pulumi.String("string"),
ToField: pulumi.String("string"),
},
},
MetadataFields: pulumi.StringArray{
pulumi.String("string"),
},
TextFields: pulumi.StringArray{
pulumi.String("string"),
},
TextSplitter: &.DestinationSnowflakeCortexConfigurationProcessingTextSplitterArgs{
ByMarkdownHeader: &.DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeaderArgs{
SplitLevel: pulumi.Float64(0),
},
ByProgrammingLanguage: &.DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguageArgs{
Language: pulumi.String("string"),
},
BySeparator: &.DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparatorArgs{
KeepSeparator: pulumi.Bool(false),
Separators: pulumi.StringArray{
pulumi.String("string"),
},
},
},
},
OmitRawText: pulumi.Bool(false),
},
WorkspaceId: pulumi.String("string"),
DefinitionId: pulumi.String("string"),
Name: pulumi.String("string"),
})

var destinationSnowflakeCortexResource = new DestinationSnowflakeCortex("destinationSnowflakeCortexResource", DestinationSnowflakeCortexArgs.builder()
    .configuration(DestinationSnowflakeCortexConfigurationArgs.builder()
        .embedding(DestinationSnowflakeCortexConfigurationEmbeddingArgs.builder()
            .azureOpenAi(DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAiArgs.builder()
                .apiBase("string")
                .deployment("string")
                .openaiKey("string")
                .build())
            .cohere(DestinationSnowflakeCortexConfigurationEmbeddingCohereArgs.builder()
                .cohereKey("string")
                .build())
            .fake()
            .openAi(DestinationSnowflakeCortexConfigurationEmbeddingOpenAiArgs.builder()
                .openaiKey("string")
                .build())
            .openAiCompatible(DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatibleArgs.builder()
                .baseUrl("string")
                .dimensions(0)
                .apiKey("string")
                .modelName("string")
                .build())
            .build())
        .indexing(DestinationSnowflakeCortexConfigurationIndexingArgs.builder()
            .credentials(DestinationSnowflakeCortexConfigurationIndexingCredentialsArgs.builder()
                .password("string")
                .build())
            .database("string")
            .defaultSchema("string")
            .host("string")
            .role("string")
            .username("string")
            .warehouse("string")
            .build())
        .processing(DestinationSnowflakeCortexConfigurationProcessingArgs.builder()
            .chunkSize(0)
            .chunkOverlap(0)
            .fieldNameMappings(DestinationSnowflakeCortexConfigurationProcessingFieldNameMappingArgs.builder()
                .fromField("string")
                .toField("string")
                .build())
            .metadataFields("string")
            .textFields("string")
            .textSplitter(DestinationSnowflakeCortexConfigurationProcessingTextSplitterArgs.builder()
                .byMarkdownHeader(DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeaderArgs.builder()
                    .splitLevel(0)
                    .build())
                .byProgrammingLanguage(DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguageArgs.builder()
                    .language("string")
                    .build())
                .bySeparator(DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparatorArgs.builder()
                    .keepSeparator(false)
                    .separators("string")
                    .build())
                .build())
            .build())
        .omitRawText(false)
        .build())
    .workspaceId("string")
    .definitionId("string")
    .name("string")
    .build());

destination_snowflake_cortex_resource = airbyte.DestinationSnowflakeCortex("destinationSnowflakeCortexResource",
    configuration={
        "embedding": {
            "azure_open_ai": {
                "api_base": "string",
                "deployment": "string",
                "openai_key": "string",
            },
            "cohere": {
                "cohere_key": "string",
            },
            "fake": {},
            "open_ai": {
                "openai_key": "string",
            },
            "open_ai_compatible": {
                "base_url": "string",
                "dimensions": 0,
                "api_key": "string",
                "model_name": "string",
            },
        },
        "indexing": {
            "credentials": {
                "password": "string",
            },
            "database": "string",
            "default_schema": "string",
            "host": "string",
            "role": "string",
            "username": "string",
            "warehouse": "string",
        },
        "processing": {
            "chunk_size": 0,
            "chunk_overlap": 0,
            "field_name_mappings": [{
                "from_field": "string",
                "to_field": "string",
            }],
            "metadata_fields": ["string"],
            "text_fields": ["string"],
            "text_splitter": {
                "by_markdown_header": {
                    "split_level": 0,
                },
                "by_programming_language": {
                    "language": "string",
                },
                "by_separator": {
                    "keep_separator": False,
                    "separators": ["string"],
                },
            },
        },
        "omit_raw_text": False,
    },
    workspace_id="string",
    definition_id="string",
    name="string")

const destinationSnowflakeCortexResource = new airbyte.DestinationSnowflakeCortex("destinationSnowflakeCortexResource", {
    configuration: {
        embedding: {
            azureOpenAi: {
                apiBase: "string",
                deployment: "string",
                openaiKey: "string",
            },
            cohere: {
                cohereKey: "string",
            },
            fake: {},
            openAi: {
                openaiKey: "string",
            },
            openAiCompatible: {
                baseUrl: "string",
                dimensions: 0,
                apiKey: "string",
                modelName: "string",
            },
        },
        indexing: {
            credentials: {
                password: "string",
            },
            database: "string",
            defaultSchema: "string",
            host: "string",
            role: "string",
            username: "string",
            warehouse: "string",
        },
        processing: {
            chunkSize: 0,
            chunkOverlap: 0,
            fieldNameMappings: [{
                fromField: "string",
                toField: "string",
            }],
            metadataFields: ["string"],
            textFields: ["string"],
            textSplitter: {
                byMarkdownHeader: {
                    splitLevel: 0,
                },
                byProgrammingLanguage: {
                    language: "string",
                },
                bySeparator: {
                    keepSeparator: false,
                    separators: ["string"],
                },
            },
        },
        omitRawText: false,
    },
    workspaceId: "string",
    definitionId: "string",
    name: "string",
});

type: airbyte:DestinationSnowflakeCortex
properties:
    configuration:
        embedding:
            azureOpenAi:
                apiBase: string
                deployment: string
                openaiKey: string
            cohere:
                cohereKey: string
            fake: {}
            openAi:
                openaiKey: string
            openAiCompatible:
                apiKey: string
                baseUrl: string
                dimensions: 0
                modelName: string
        indexing:
            credentials:
                password: string
            database: string
            defaultSchema: string
            host: string
            role: string
            username: string
            warehouse: string
        omitRawText: false
        processing:
            chunkOverlap: 0
            chunkSize: 0
            fieldNameMappings:
                - fromField: string
                  toField: string
            metadataFields:
                - string
            textFields:
                - string
            textSplitter:
                byMarkdownHeader:
                    splitLevel: 0
                byProgrammingLanguage:
                    language: string
                bySeparator:
                    keepSeparator: false
                    separators:
                        - string
    definitionId: string
    name: string
    workspaceId: string

DestinationSnowflakeCortex Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

The DestinationSnowflakeCortex resource accepts the following input properties:

Configuration DestinationSnowflakeCortexConfiguration: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
WorkspaceId string
DefinitionId string: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
Name string: Name of the destination e.g. dev-mysql-instance.

Configuration DestinationSnowflakeCortexConfigurationArgs: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
WorkspaceId string
DefinitionId string: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
Name string: Name of the destination e.g. dev-mysql-instance.

configuration DestinationSnowflakeCortexConfiguration: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
workspaceId String
definitionId String: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
name String: Name of the destination e.g. dev-mysql-instance.

configuration DestinationSnowflakeCortexConfiguration: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
workspaceId string
definitionId string: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
name string: Name of the destination e.g. dev-mysql-instance.

configuration DestinationSnowflakeCortexConfigurationArgs: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
workspace_id str
definition_id str: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
name str: Name of the destination e.g. dev-mysql-instance.

configuration Property Map: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
workspaceId String
definitionId String: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
name String: Name of the destination e.g. dev-mysql-instance.

Outputs

All input properties are implicitly available as output properties. Additionally, the DestinationSnowflakeCortex resource produces the following output properties:

CreatedAt double
DestinationId string
DestinationType string
Id string: The provider-assigned unique ID for this managed resource.
ResourceAllocation DestinationSnowflakeCortexResourceAllocation: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.

CreatedAt float64
DestinationId string
DestinationType string
Id string: The provider-assigned unique ID for this managed resource.
ResourceAllocation DestinationSnowflakeCortexResourceAllocation: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.

createdAt Double
destinationId String
destinationType String
id String: The provider-assigned unique ID for this managed resource.
resourceAllocation DestinationSnowflakeCortexResourceAllocation: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.

createdAt number
destinationId string
destinationType string
id string: The provider-assigned unique ID for this managed resource.
resourceAllocation DestinationSnowflakeCortexResourceAllocation: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.

created_at float
destination_id str
destination_type str
id str: The provider-assigned unique ID for this managed resource.
resource_allocation DestinationSnowflakeCortexResourceAllocation: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.

createdAt Number
destinationId String
destinationType String
id String: The provider-assigned unique ID for this managed resource.
resourceAllocation Property Map: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.

Look up Existing DestinationSnowflakeCortex Resource

Get an existing DestinationSnowflakeCortex resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

public static get(name: string, id: Input<ID>, state?: DestinationSnowflakeCortexState, opts?: CustomResourceOptions): DestinationSnowflakeCortex

@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        configuration: Optional[DestinationSnowflakeCortexConfigurationArgs] = None,
        created_at: Optional[float] = None,
        definition_id: Optional[str] = None,
        destination_id: Optional[str] = None,
        destination_type: Optional[str] = None,
        name: Optional[str] = None,
        resource_allocation: Optional[DestinationSnowflakeCortexResourceAllocationArgs] = None,
        workspace_id: Optional[str] = None) -> DestinationSnowflakeCortex

func GetDestinationSnowflakeCortex(ctx *Context, name string, id IDInput, state *DestinationSnowflakeCortexState, opts ...ResourceOption) (*DestinationSnowflakeCortex, error)

public static DestinationSnowflakeCortex Get(string name, Input<string> id, DestinationSnowflakeCortexState? state, CustomResourceOptions? opts = null)

public static DestinationSnowflakeCortex get(String name, Output<String> id, DestinationSnowflakeCortexState state, CustomResourceOptions options)

resources:  _:    type: airbyte:DestinationSnowflakeCortex    get:      id: ${id}

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

resource_name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

The following state arguments are supported:

Configuration DestinationSnowflakeCortexConfiguration: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
CreatedAt double
DefinitionId string: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
DestinationId string
DestinationType string
Name string: Name of the destination e.g. dev-mysql-instance.
ResourceAllocation DestinationSnowflakeCortexResourceAllocation: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.
WorkspaceId string

Configuration DestinationSnowflakeCortexConfigurationArgs: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
CreatedAt float64
DefinitionId string: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
DestinationId string
DestinationType string
Name string: Name of the destination e.g. dev-mysql-instance.
ResourceAllocation DestinationSnowflakeCortexResourceAllocationArgs: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.
WorkspaceId string

configuration DestinationSnowflakeCortexConfiguration: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
createdAt Double
definitionId String: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
destinationId String
destinationType String
name String: Name of the destination e.g. dev-mysql-instance.
resourceAllocation DestinationSnowflakeCortexResourceAllocation: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.
workspaceId String

configuration DestinationSnowflakeCortexConfiguration: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
createdAt number
definitionId string: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
destinationId string
destinationType string
name string: Name of the destination e.g. dev-mysql-instance.
resourceAllocation DestinationSnowflakeCortexResourceAllocation: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.
workspaceId string

configuration DestinationSnowflakeCortexConfigurationArgs: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
created_at float
definition_id str: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
destination_id str
destination_type str
name str: Name of the destination e.g. dev-mysql-instance.
resource_allocation DestinationSnowflakeCortexResourceAllocationArgs: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.
workspace_id str

configuration Property Map: The configuration model for the Vector DB based destinations. This model is used to generate the UI for the destination configuration, as well as to provide type safety for the configuration passed to the destination.
createdAt Number
definitionId String: The UUID of the connector definition. One of configuration.destinationType or definitionId must be provided. Requires replacement if changed.
destinationId String
destinationType String
name String: Name of the destination e.g. dev-mysql-instance.
resourceAllocation Property Map: actor or actor definition specific resource requirements. if default is set, these are the requirements that should be set for ALL jobs run for this actor definition. it is overriden by the job type specific configurations. if not set, the platform will use defaults. these values will be overriden by configuration at the connection level.
workspaceId String

Supporting Types

DestinationSnowflakeCortexConfiguration, DestinationSnowflakeCortexConfigurationArgs

Embedding DestinationSnowflakeCortexConfigurationEmbedding: Embedding configuration
Indexing DestinationSnowflakeCortexConfigurationIndexing: Snowflake can be used to store vector data and retrieve embeddings.
Processing DestinationSnowflakeCortexConfigurationProcessing
OmitRawText bool: Do not store the text that gets embedded along with the vector and the metadata in the destination. If set to true, only the vector and the metadata will be stored - in this case raw text for LLM use cases needs to be retrieved from another source. Default: false

Embedding DestinationSnowflakeCortexConfigurationEmbedding: Embedding configuration
Indexing DestinationSnowflakeCortexConfigurationIndexing: Snowflake can be used to store vector data and retrieve embeddings.
Processing DestinationSnowflakeCortexConfigurationProcessing
OmitRawText bool: Do not store the text that gets embedded along with the vector and the metadata in the destination. If set to true, only the vector and the metadata will be stored - in this case raw text for LLM use cases needs to be retrieved from another source. Default: false

embedding DestinationSnowflakeCortexConfigurationEmbedding: Embedding configuration
indexing DestinationSnowflakeCortexConfigurationIndexing: Snowflake can be used to store vector data and retrieve embeddings.
processing DestinationSnowflakeCortexConfigurationProcessing
omitRawText Boolean: Do not store the text that gets embedded along with the vector and the metadata in the destination. If set to true, only the vector and the metadata will be stored - in this case raw text for LLM use cases needs to be retrieved from another source. Default: false

embedding DestinationSnowflakeCortexConfigurationEmbedding: Embedding configuration
indexing DestinationSnowflakeCortexConfigurationIndexing: Snowflake can be used to store vector data and retrieve embeddings.
processing DestinationSnowflakeCortexConfigurationProcessing
omitRawText boolean: Do not store the text that gets embedded along with the vector and the metadata in the destination. If set to true, only the vector and the metadata will be stored - in this case raw text for LLM use cases needs to be retrieved from another source. Default: false

embedding DestinationSnowflakeCortexConfigurationEmbedding: Embedding configuration
indexing DestinationSnowflakeCortexConfigurationIndexing: Snowflake can be used to store vector data and retrieve embeddings.
processing DestinationSnowflakeCortexConfigurationProcessing
omit_raw_text bool: Do not store the text that gets embedded along with the vector and the metadata in the destination. If set to true, only the vector and the metadata will be stored - in this case raw text for LLM use cases needs to be retrieved from another source. Default: false

embedding Property Map: Embedding configuration
indexing Property Map: Snowflake can be used to store vector data and retrieve embeddings.
processing Property Map
omitRawText Boolean: Do not store the text that gets embedded along with the vector and the metadata in the destination. If set to true, only the vector and the metadata will be stored - in this case raw text for LLM use cases needs to be retrieved from another source. Default: false

DestinationSnowflakeCortexConfigurationEmbedding, DestinationSnowflakeCortexConfigurationEmbeddingArgs

AzureOpenAi DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAi: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
Cohere DestinationSnowflakeCortexConfigurationEmbeddingCohere: Use the Cohere API to embed text.
Fake DestinationSnowflakeCortexConfigurationEmbeddingFake: Use a fake embedding made out of random vectors with 1536 embedding dimensions. This is useful for testing the data pipeline without incurring any costs.
OpenAi DestinationSnowflakeCortexConfigurationEmbeddingOpenAi: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
OpenAiCompatible DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatible: Use a service that's compatible with the OpenAI API to embed text.

AzureOpenAi DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAi: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
Cohere DestinationSnowflakeCortexConfigurationEmbeddingCohere: Use the Cohere API to embed text.
Fake DestinationSnowflakeCortexConfigurationEmbeddingFake: Use a fake embedding made out of random vectors with 1536 embedding dimensions. This is useful for testing the data pipeline without incurring any costs.
OpenAi DestinationSnowflakeCortexConfigurationEmbeddingOpenAi: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
OpenAiCompatible DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatible: Use a service that's compatible with the OpenAI API to embed text.

azureOpenAi DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAi: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
cohere DestinationSnowflakeCortexConfigurationEmbeddingCohere: Use the Cohere API to embed text.
fake DestinationSnowflakeCortexConfigurationEmbeddingFake: Use a fake embedding made out of random vectors with 1536 embedding dimensions. This is useful for testing the data pipeline without incurring any costs.
openAi DestinationSnowflakeCortexConfigurationEmbeddingOpenAi: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
openAiCompatible DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatible: Use a service that's compatible with the OpenAI API to embed text.

azureOpenAi DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAi: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
cohere DestinationSnowflakeCortexConfigurationEmbeddingCohere: Use the Cohere API to embed text.
fake DestinationSnowflakeCortexConfigurationEmbeddingFake: Use a fake embedding made out of random vectors with 1536 embedding dimensions. This is useful for testing the data pipeline without incurring any costs.
openAi DestinationSnowflakeCortexConfigurationEmbeddingOpenAi: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
openAiCompatible DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatible: Use a service that's compatible with the OpenAI API to embed text.

azure_open_ai DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAi: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
cohere DestinationSnowflakeCortexConfigurationEmbeddingCohere: Use the Cohere API to embed text.
fake DestinationSnowflakeCortexConfigurationEmbeddingFake: Use a fake embedding made out of random vectors with 1536 embedding dimensions. This is useful for testing the data pipeline without incurring any costs.
open_ai DestinationSnowflakeCortexConfigurationEmbeddingOpenAi: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
open_ai_compatible DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatible: Use a service that's compatible with the OpenAI API to embed text.

azureOpenAi Property Map: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
cohere Property Map: Use the Cohere API to embed text.
fake Property Map: Use a fake embedding made out of random vectors with 1536 embedding dimensions. This is useful for testing the data pipeline without incurring any costs.
openAi Property Map: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
openAiCompatible Property Map: Use a service that's compatible with the OpenAI API to embed text.

DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAi, DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAiArgs

ApiBase string: The base URL for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
Deployment string: The deployment for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
OpenaiKey string: The API key for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource

ApiBase string: The base URL for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
Deployment string: The deployment for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
OpenaiKey string: The API key for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource

apiBase String: The base URL for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
deployment String: The deployment for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
openaiKey String: The API key for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource

apiBase string: The base URL for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
deployment string: The deployment for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
openaiKey string: The API key for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource

api_base str: The base URL for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
deployment str: The deployment for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
openai_key str: The API key for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource

apiBase String: The base URL for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
deployment String: The deployment for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource
openaiKey String: The API key for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource

DestinationSnowflakeCortexConfigurationEmbeddingCohere, DestinationSnowflakeCortexConfigurationEmbeddingCohereArgs

CohereKey string

CohereKey string

cohereKey String

cohereKey string

cohere_key str

cohereKey String

DestinationSnowflakeCortexConfigurationEmbeddingOpenAi, DestinationSnowflakeCortexConfigurationEmbeddingOpenAiArgs

OpenaiKey string

OpenaiKey string

openaiKey String

openaiKey string

openai_key str

openaiKey String

DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatible, DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatibleArgs

BaseUrl string: The base URL for your OpenAI-compatible service
Dimensions double: The number of dimensions the embedding model is generating
ApiKey string: Default: ""
ModelName string: The name of the model to use for embedding. Default: "text-embedding-ada-002"

BaseUrl string: The base URL for your OpenAI-compatible service
Dimensions float64: The number of dimensions the embedding model is generating
ApiKey string: Default: ""
ModelName string: The name of the model to use for embedding. Default: "text-embedding-ada-002"

baseUrl String: The base URL for your OpenAI-compatible service
dimensions Double: The number of dimensions the embedding model is generating
apiKey String: Default: ""
modelName String: The name of the model to use for embedding. Default: "text-embedding-ada-002"

baseUrl string: The base URL for your OpenAI-compatible service
dimensions number: The number of dimensions the embedding model is generating
apiKey string: Default: ""
modelName string: The name of the model to use for embedding. Default: "text-embedding-ada-002"

base_url str: The base URL for your OpenAI-compatible service
dimensions float: The number of dimensions the embedding model is generating
api_key str: Default: ""
model_name str: The name of the model to use for embedding. Default: "text-embedding-ada-002"

baseUrl String: The base URL for your OpenAI-compatible service
dimensions Number: The number of dimensions the embedding model is generating
apiKey String: Default: ""
modelName String: The name of the model to use for embedding. Default: "text-embedding-ada-002"

DestinationSnowflakeCortexConfigurationIndexing, DestinationSnowflakeCortexConfigurationIndexingArgs

Credentials DestinationSnowflakeCortexConfigurationIndexingCredentials
Database string: Enter the name of the database that you want to sync data into
DefaultSchema string: Enter the name of the default schema
Host string: Enter the account name you want to use to access the database. This is usually the identifier before .snowflakecomputing.com
Role string: Enter the role that you want to use to access Snowflake
Username string: Enter the name of the user you want to use to access the database
Warehouse string: Enter the name of the warehouse that you want to use as a compute cluster

Credentials DestinationSnowflakeCortexConfigurationIndexingCredentials
Database string: Enter the name of the database that you want to sync data into
DefaultSchema string: Enter the name of the default schema
Host string: Enter the account name you want to use to access the database. This is usually the identifier before .snowflakecomputing.com
Role string: Enter the role that you want to use to access Snowflake
Username string: Enter the name of the user you want to use to access the database
Warehouse string: Enter the name of the warehouse that you want to use as a compute cluster

credentials DestinationSnowflakeCortexConfigurationIndexingCredentials
database String: Enter the name of the database that you want to sync data into
defaultSchema String: Enter the name of the default schema
host String: Enter the account name you want to use to access the database. This is usually the identifier before .snowflakecomputing.com
role String: Enter the role that you want to use to access Snowflake
username String: Enter the name of the user you want to use to access the database
warehouse String: Enter the name of the warehouse that you want to use as a compute cluster

credentials DestinationSnowflakeCortexConfigurationIndexingCredentials
database string: Enter the name of the database that you want to sync data into
defaultSchema string: Enter the name of the default schema
host string: Enter the account name you want to use to access the database. This is usually the identifier before .snowflakecomputing.com
role string: Enter the role that you want to use to access Snowflake
username string: Enter the name of the user you want to use to access the database
warehouse string: Enter the name of the warehouse that you want to use as a compute cluster

credentials DestinationSnowflakeCortexConfigurationIndexingCredentials
database str: Enter the name of the database that you want to sync data into
default_schema str: Enter the name of the default schema
host str: Enter the account name you want to use to access the database. This is usually the identifier before .snowflakecomputing.com
role str: Enter the role that you want to use to access Snowflake
username str: Enter the name of the user you want to use to access the database
warehouse str: Enter the name of the warehouse that you want to use as a compute cluster

credentials Property Map
database String: Enter the name of the database that you want to sync data into
defaultSchema String: Enter the name of the default schema
host String: Enter the account name you want to use to access the database. This is usually the identifier before .snowflakecomputing.com
role String: Enter the role that you want to use to access Snowflake
username String: Enter the name of the user you want to use to access the database
warehouse String: Enter the name of the warehouse that you want to use as a compute cluster

DestinationSnowflakeCortexConfigurationIndexingCredentials, DestinationSnowflakeCortexConfigurationIndexingCredentialsArgs

Password string: Enter the password you want to use to access the database

Password string: Enter the password you want to use to access the database

password String: Enter the password you want to use to access the database

password string: Enter the password you want to use to access the database

password str: Enter the password you want to use to access the database

password String: Enter the password you want to use to access the database

DestinationSnowflakeCortexConfigurationProcessing, DestinationSnowflakeCortexConfigurationProcessingArgs

ChunkSize double: Size of chunks in tokens to store in vector store (make sure it is not too big for the context if your LLM)
ChunkOverlap double: Size of overlap between chunks in tokens to store in vector store to better capture relevant context. Default: 0
FieldNameMappings List<DestinationSnowflakeCortexConfigurationProcessingFieldNameMapping>: List of fields to rename. Not applicable for nested fields, but can be used to rename fields already flattened via dot notation.
MetadataFields List<string>: List of fields in the record that should be stored as metadata. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered metadata fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array. When specifying nested paths, all matching values are flattened into an array set to a field named by the path.
TextFields List<string>: List of fields in the record that should be used to calculate the embedding. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered text fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array.
TextSplitter DestinationSnowflakeCortexConfigurationProcessingTextSplitter: Split text fields into chunks based on the specified method.

ChunkSize float64: Size of chunks in tokens to store in vector store (make sure it is not too big for the context if your LLM)
ChunkOverlap float64: Size of overlap between chunks in tokens to store in vector store to better capture relevant context. Default: 0
FieldNameMappings []DestinationSnowflakeCortexConfigurationProcessingFieldNameMapping: List of fields to rename. Not applicable for nested fields, but can be used to rename fields already flattened via dot notation.
MetadataFields []string: List of fields in the record that should be stored as metadata. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered metadata fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array. When specifying nested paths, all matching values are flattened into an array set to a field named by the path.
TextFields []string: List of fields in the record that should be used to calculate the embedding. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered text fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array.
TextSplitter DestinationSnowflakeCortexConfigurationProcessingTextSplitter: Split text fields into chunks based on the specified method.

chunkSize Double: Size of chunks in tokens to store in vector store (make sure it is not too big for the context if your LLM)
chunkOverlap Double: Size of overlap between chunks in tokens to store in vector store to better capture relevant context. Default: 0
fieldNameMappings List<DestinationSnowflakeCortexConfigurationProcessingFieldNameMapping>: List of fields to rename. Not applicable for nested fields, but can be used to rename fields already flattened via dot notation.
metadataFields List<String>: List of fields in the record that should be stored as metadata. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered metadata fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array. When specifying nested paths, all matching values are flattened into an array set to a field named by the path.
textFields List<String>: List of fields in the record that should be used to calculate the embedding. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered text fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array.
textSplitter DestinationSnowflakeCortexConfigurationProcessingTextSplitter: Split text fields into chunks based on the specified method.

chunkSize number: Size of chunks in tokens to store in vector store (make sure it is not too big for the context if your LLM)
chunkOverlap number: Size of overlap between chunks in tokens to store in vector store to better capture relevant context. Default: 0
fieldNameMappings DestinationSnowflakeCortexConfigurationProcessingFieldNameMapping[]: List of fields to rename. Not applicable for nested fields, but can be used to rename fields already flattened via dot notation.
metadataFields string[]: List of fields in the record that should be stored as metadata. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered metadata fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array. When specifying nested paths, all matching values are flattened into an array set to a field named by the path.
textFields string[]: List of fields in the record that should be used to calculate the embedding. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered text fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array.
textSplitter DestinationSnowflakeCortexConfigurationProcessingTextSplitter: Split text fields into chunks based on the specified method.

chunk_size float: Size of chunks in tokens to store in vector store (make sure it is not too big for the context if your LLM)
chunk_overlap float: Size of overlap between chunks in tokens to store in vector store to better capture relevant context. Default: 0
field_name_mappings Sequence[DestinationSnowflakeCortexConfigurationProcessingFieldNameMapping]: List of fields to rename. Not applicable for nested fields, but can be used to rename fields already flattened via dot notation.
metadata_fields Sequence[str]: List of fields in the record that should be stored as metadata. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered metadata fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array. When specifying nested paths, all matching values are flattened into an array set to a field named by the path.
text_fields Sequence[str]: List of fields in the record that should be used to calculate the embedding. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered text fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array.
text_splitter DestinationSnowflakeCortexConfigurationProcessingTextSplitter: Split text fields into chunks based on the specified method.

chunkSize Number: Size of chunks in tokens to store in vector store (make sure it is not too big for the context if your LLM)
chunkOverlap Number: Size of overlap between chunks in tokens to store in vector store to better capture relevant context. Default: 0
fieldNameMappings List<Property Map>: List of fields to rename. Not applicable for nested fields, but can be used to rename fields already flattened via dot notation.
metadataFields List<String>: List of fields in the record that should be stored as metadata. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered metadata fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array. When specifying nested paths, all matching values are flattened into an array set to a field named by the path.
textFields List<String>: List of fields in the record that should be used to calculate the embedding. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered text fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. user.name will access the name field in the user object. It's also possible to use wildcards to access all fields in an object, e.g. users.*.name will access all names fields in all entries of the users array.
textSplitter Property Map: Split text fields into chunks based on the specified method.

DestinationSnowflakeCortexConfigurationProcessingFieldNameMapping, DestinationSnowflakeCortexConfigurationProcessingFieldNameMappingArgs

FromField string: The field name in the source
ToField string: The field name to use in the destination

FromField string: The field name in the source
ToField string: The field name to use in the destination

fromField String: The field name in the source
toField String: The field name to use in the destination

fromField string: The field name in the source
toField string: The field name to use in the destination

from_field str: The field name in the source
to_field str: The field name to use in the destination

fromField String: The field name in the source
toField String: The field name to use in the destination

DestinationSnowflakeCortexConfigurationProcessingTextSplitter, DestinationSnowflakeCortexConfigurationProcessingTextSplitterArgs

ByMarkdownHeader DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeader: Split the text by Markdown headers down to the specified header level. If the chunk size fits multiple sections, they will be combined into a single chunk.
ByProgrammingLanguage DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguage: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
BySeparator DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparator: Split the text by the list of separators until the chunk size is reached, using the earlier mentioned separators where possible. This is useful for splitting text fields by paragraphs, sentences, words, etc.

ByMarkdownHeader DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeader: Split the text by Markdown headers down to the specified header level. If the chunk size fits multiple sections, they will be combined into a single chunk.
ByProgrammingLanguage DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguage: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
BySeparator DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparator: Split the text by the list of separators until the chunk size is reached, using the earlier mentioned separators where possible. This is useful for splitting text fields by paragraphs, sentences, words, etc.

byMarkdownHeader DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeader: Split the text by Markdown headers down to the specified header level. If the chunk size fits multiple sections, they will be combined into a single chunk.
byProgrammingLanguage DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguage: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
bySeparator DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparator: Split the text by the list of separators until the chunk size is reached, using the earlier mentioned separators where possible. This is useful for splitting text fields by paragraphs, sentences, words, etc.

byMarkdownHeader DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeader: Split the text by Markdown headers down to the specified header level. If the chunk size fits multiple sections, they will be combined into a single chunk.
byProgrammingLanguage DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguage: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
bySeparator DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparator: Split the text by the list of separators until the chunk size is reached, using the earlier mentioned separators where possible. This is useful for splitting text fields by paragraphs, sentences, words, etc.

by_markdown_header DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeader: Split the text by Markdown headers down to the specified header level. If the chunk size fits multiple sections, they will be combined into a single chunk.
by_programming_language DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguage: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
by_separator DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparator: Split the text by the list of separators until the chunk size is reached, using the earlier mentioned separators where possible. This is useful for splitting text fields by paragraphs, sentences, words, etc.

byMarkdownHeader Property Map: Split the text by Markdown headers down to the specified header level. If the chunk size fits multiple sections, they will be combined into a single chunk.
byProgrammingLanguage Property Map: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
bySeparator Property Map: Split the text by the list of separators until the chunk size is reached, using the earlier mentioned separators where possible. This is useful for splitting text fields by paragraphs, sentences, words, etc.

DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeader, DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeaderArgs

SplitLevel double: Level of markdown headers to split text fields by. Headings down to the specified level will be used as split points. Default: 1

SplitLevel float64: Level of markdown headers to split text fields by. Headings down to the specified level will be used as split points. Default: 1

splitLevel Double: Level of markdown headers to split text fields by. Headings down to the specified level will be used as split points. Default: 1

splitLevel number: Level of markdown headers to split text fields by. Headings down to the specified level will be used as split points. Default: 1

split_level float: Level of markdown headers to split text fields by. Headings down to the specified level will be used as split points. Default: 1

splitLevel Number: Level of markdown headers to split text fields by. Headings down to the specified level will be used as split points. Default: 1

DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguage, DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguageArgs

Language string: Split code in suitable places based on the programming language. must be one of ["cpp", "go", "java", "js", "php", "proto", "python", "rst", "ruby", "rust", "scala", "swift", "markdown", "latex", "html", "sol"]

Language string: Split code in suitable places based on the programming language. must be one of ["cpp", "go", "java", "js", "php", "proto", "python", "rst", "ruby", "rust", "scala", "swift", "markdown", "latex", "html", "sol"]

language String: Split code in suitable places based on the programming language. must be one of ["cpp", "go", "java", "js", "php", "proto", "python", "rst", "ruby", "rust", "scala", "swift", "markdown", "latex", "html", "sol"]

language string: Split code in suitable places based on the programming language. must be one of ["cpp", "go", "java", "js", "php", "proto", "python", "rst", "ruby", "rust", "scala", "swift", "markdown", "latex", "html", "sol"]

language str: Split code in suitable places based on the programming language. must be one of ["cpp", "go", "java", "js", "php", "proto", "python", "rst", "ruby", "rust", "scala", "swift", "markdown", "latex", "html", "sol"]

language String: Split code in suitable places based on the programming language. must be one of ["cpp", "go", "java", "js", "php", "proto", "python", "rst", "ruby", "rust", "scala", "swift", "markdown", "latex", "html", "sol"]

DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparator, DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparatorArgs

KeepSeparator bool: Whether to keep the separator in the resulting chunks. Default: false
Separators List<string>: List of separator strings to split text fields by. The separator itself needs to be wrapped in double quotes, e.g. to split by the dot character, use ".". To split by a newline, use "\n".

KeepSeparator bool: Whether to keep the separator in the resulting chunks. Default: false
Separators []string: List of separator strings to split text fields by. The separator itself needs to be wrapped in double quotes, e.g. to split by the dot character, use ".". To split by a newline, use "\n".

keepSeparator Boolean: Whether to keep the separator in the resulting chunks. Default: false
separators List<String>: List of separator strings to split text fields by. The separator itself needs to be wrapped in double quotes, e.g. to split by the dot character, use ".". To split by a newline, use "\n".

keepSeparator boolean: Whether to keep the separator in the resulting chunks. Default: false
separators string[]: List of separator strings to split text fields by. The separator itself needs to be wrapped in double quotes, e.g. to split by the dot character, use ".". To split by a newline, use "\n".

keep_separator bool: Whether to keep the separator in the resulting chunks. Default: false
separators Sequence[str]: List of separator strings to split text fields by. The separator itself needs to be wrapped in double quotes, e.g. to split by the dot character, use ".". To split by a newline, use "\n".

keepSeparator Boolean: Whether to keep the separator in the resulting chunks. Default: false
separators List<String>: List of separator strings to split text fields by. The separator itself needs to be wrapped in double quotes, e.g. to split by the dot character, use ".". To split by a newline, use "\n".

DestinationSnowflakeCortexResourceAllocation, DestinationSnowflakeCortexResourceAllocationArgs

Default DestinationSnowflakeCortexResourceAllocationDefault: optional resource requirements to run workers (blank for unbounded allocations)
JobSpecifics List<DestinationSnowflakeCortexResourceAllocationJobSpecific>

Default DestinationSnowflakeCortexResourceAllocationDefault: optional resource requirements to run workers (blank for unbounded allocations)
JobSpecifics []DestinationSnowflakeCortexResourceAllocationJobSpecific

default_ DestinationSnowflakeCortexResourceAllocationDefault: optional resource requirements to run workers (blank for unbounded allocations)
jobSpecifics List<DestinationSnowflakeCortexResourceAllocationJobSpecific>

default DestinationSnowflakeCortexResourceAllocationDefault: optional resource requirements to run workers (blank for unbounded allocations)
jobSpecifics DestinationSnowflakeCortexResourceAllocationJobSpecific[]

default DestinationSnowflakeCortexResourceAllocationDefault: optional resource requirements to run workers (blank for unbounded allocations)
job_specifics Sequence[DestinationSnowflakeCortexResourceAllocationJobSpecific]

default Property Map: optional resource requirements to run workers (blank for unbounded allocations)
jobSpecifics List<Property Map>

DestinationSnowflakeCortexResourceAllocationDefault, DestinationSnowflakeCortexResourceAllocationDefaultArgs

CpuLimit string
CpuRequest string
EphemeralStorageLimit string
EphemeralStorageRequest string
MemoryLimit string
MemoryRequest string

CpuLimit string
CpuRequest string
EphemeralStorageLimit string
EphemeralStorageRequest string
MemoryLimit string
MemoryRequest string

cpuLimit String
cpuRequest String
ephemeralStorageLimit String
ephemeralStorageRequest String
memoryLimit String
memoryRequest String

cpuLimit string
cpuRequest string
ephemeralStorageLimit string
ephemeralStorageRequest string
memoryLimit string
memoryRequest string

cpu_limit str
cpu_request str
ephemeral_storage_limit str
ephemeral_storage_request str
memory_limit str
memory_request str

cpuLimit String
cpuRequest String
ephemeralStorageLimit String
ephemeralStorageRequest String
memoryLimit String
memoryRequest String

DestinationSnowflakeCortexResourceAllocationJobSpecific, DestinationSnowflakeCortexResourceAllocationJobSpecificArgs

JobType string: enum that describes the different types of jobs that the platform runs. must be one of ["getspec", "checkconnection", "discoverschema", "sync", "resetconnection", "connection_updater", "replicate"]
ResourceRequirements DestinationSnowflakeCortexResourceAllocationJobSpecificResourceRequirements: optional resource requirements to run workers (blank for unbounded allocations)

JobType string: enum that describes the different types of jobs that the platform runs. must be one of ["getspec", "checkconnection", "discoverschema", "sync", "resetconnection", "connection_updater", "replicate"]
ResourceRequirements DestinationSnowflakeCortexResourceAllocationJobSpecificResourceRequirements: optional resource requirements to run workers (blank for unbounded allocations)

jobType String: enum that describes the different types of jobs that the platform runs. must be one of ["getspec", "checkconnection", "discoverschema", "sync", "resetconnection", "connection_updater", "replicate"]
resourceRequirements DestinationSnowflakeCortexResourceAllocationJobSpecificResourceRequirements: optional resource requirements to run workers (blank for unbounded allocations)

jobType string: enum that describes the different types of jobs that the platform runs. must be one of ["getspec", "checkconnection", "discoverschema", "sync", "resetconnection", "connection_updater", "replicate"]
resourceRequirements DestinationSnowflakeCortexResourceAllocationJobSpecificResourceRequirements: optional resource requirements to run workers (blank for unbounded allocations)

job_type str: enum that describes the different types of jobs that the platform runs. must be one of ["getspec", "checkconnection", "discoverschema", "sync", "resetconnection", "connection_updater", "replicate"]
resource_requirements DestinationSnowflakeCortexResourceAllocationJobSpecificResourceRequirements: optional resource requirements to run workers (blank for unbounded allocations)

jobType String: enum that describes the different types of jobs that the platform runs. must be one of ["getspec", "checkconnection", "discoverschema", "sync", "resetconnection", "connection_updater", "replicate"]
resourceRequirements Property Map: optional resource requirements to run workers (blank for unbounded allocations)

DestinationSnowflakeCortexResourceAllocationJobSpecificResourceRequirements, DestinationSnowflakeCortexResourceAllocationJobSpecificResourceRequirementsArgs

CpuLimit string
CpuRequest string
EphemeralStorageLimit string
EphemeralStorageRequest string
MemoryLimit string
MemoryRequest string

CpuLimit string
CpuRequest string
EphemeralStorageLimit string
EphemeralStorageRequest string
MemoryLimit string
MemoryRequest string

cpuLimit String
cpuRequest String
ephemeralStorageLimit String
ephemeralStorageRequest String
memoryLimit String
memoryRequest String

cpuLimit string
cpuRequest string
ephemeralStorageLimit string
ephemeralStorageRequest string
memoryLimit string
memoryRequest string

cpu_limit str
cpu_request str
ephemeral_storage_limit str
ephemeral_storage_request str
memory_limit str
memory_request str

cpuLimit String
cpuRequest String
ephemeralStorageLimit String
ephemeralStorageRequest String
memoryLimit String
memoryRequest String

Import

$ pulumi import airbyte:index/destinationSnowflakeCortex:DestinationSnowflakeCortex my_airbyte_destination_snowflake_cortex ""

To learn more about importing existing cloud resources, see Importing resources.

Package Details

Repository: airbyte airbytehq/terraform-provider-airbyte
License
Notes: This Pulumi package is based on the airbyte Terraform Provider.

airbyte 0.8.0-beta2 published on Thursday, Mar 27, 2025 by airbytehq

airbytehq/terraform-provider-airbyte

airbyte.DestinationSnowflakeCortex

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Example Usage

Create DestinationSnowflakeCortex Resource

Constructor syntax

Parameters

Constructor example

DestinationSnowflakeCortex Resource Properties

Inputs

Outputs

Look up Existing DestinationSnowflakeCortex Resource

Supporting Types

DestinationSnowflakeCortexConfiguration, DestinationSnowflakeCortexConfigurationArgs

DestinationSnowflakeCortexConfigurationEmbedding, DestinationSnowflakeCortexConfigurationEmbeddingArgs

DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAi, DestinationSnowflakeCortexConfigurationEmbeddingAzureOpenAiArgs

DestinationSnowflakeCortexConfigurationEmbeddingCohere, DestinationSnowflakeCortexConfigurationEmbeddingCohereArgs

DestinationSnowflakeCortexConfigurationEmbeddingOpenAi, DestinationSnowflakeCortexConfigurationEmbeddingOpenAiArgs

DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatible, DestinationSnowflakeCortexConfigurationEmbeddingOpenAiCompatibleArgs

DestinationSnowflakeCortexConfigurationIndexing, DestinationSnowflakeCortexConfigurationIndexingArgs

DestinationSnowflakeCortexConfigurationIndexingCredentials, DestinationSnowflakeCortexConfigurationIndexingCredentialsArgs

DestinationSnowflakeCortexConfigurationProcessing, DestinationSnowflakeCortexConfigurationProcessingArgs

DestinationSnowflakeCortexConfigurationProcessingFieldNameMapping, DestinationSnowflakeCortexConfigurationProcessingFieldNameMappingArgs

DestinationSnowflakeCortexConfigurationProcessingTextSplitter, DestinationSnowflakeCortexConfigurationProcessingTextSplitterArgs

DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeader, DestinationSnowflakeCortexConfigurationProcessingTextSplitterByMarkdownHeaderArgs

DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguage, DestinationSnowflakeCortexConfigurationProcessingTextSplitterByProgrammingLanguageArgs

DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparator, DestinationSnowflakeCortexConfigurationProcessingTextSplitterBySeparatorArgs

DestinationSnowflakeCortexResourceAllocation, DestinationSnowflakeCortexResourceAllocationArgs

DestinationSnowflakeCortexResourceAllocationDefault, DestinationSnowflakeCortexResourceAllocationDefaultArgs

DestinationSnowflakeCortexResourceAllocationJobSpecific, DestinationSnowflakeCortexResourceAllocationJobSpecificArgs

DestinationSnowflakeCortexResourceAllocationJobSpecificResourceRequirements, DestinationSnowflakeCortexResourceAllocationJobSpecificResourceRequirementsArgs

Import

Package Details

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