airbyte 0.8.0-beta2, Mar 27 25

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

airbyte.DestinationWeaviate

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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.DestinationWeaviate;
import com.pulumi.airbyte.DestinationWeaviateArgs;
import com.pulumi.airbyte.inputs.DestinationWeaviateConfigurationArgs;
import com.pulumi.airbyte.inputs.DestinationWeaviateConfigurationEmbeddingArgs;
import com.pulumi.airbyte.inputs.DestinationWeaviateConfigurationEmbeddingFromFieldArgs;
import com.pulumi.airbyte.inputs.DestinationWeaviateConfigurationIndexingArgs;
import com.pulumi.airbyte.inputs.DestinationWeaviateConfigurationIndexingAuthArgs;
import com.pulumi.airbyte.inputs.DestinationWeaviateConfigurationIndexingAuthApiTokenArgs;
import com.pulumi.airbyte.inputs.DestinationWeaviateConfigurationProcessingArgs;
import com.pulumi.airbyte.inputs.DestinationWeaviateConfigurationProcessingTextSplitterArgs;
import com.pulumi.airbyte.inputs.DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeaderArgs;
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 myDestinationWeaviate = new DestinationWeaviate("myDestinationWeaviate", DestinationWeaviateArgs.builder()
            .configuration(DestinationWeaviateConfigurationArgs.builder()
                .embedding(DestinationWeaviateConfigurationEmbeddingArgs.builder()
                    .fromField(DestinationWeaviateConfigurationEmbeddingFromFieldArgs.builder()
                        .dimensions(1536)
                        .fieldName("embedding")
                        .build())
                    .build())
                .indexing(DestinationWeaviateConfigurationIndexingArgs.builder()
                    .additionalHeaders(DestinationWeaviateConfigurationIndexingAdditionalHeaderArgs.builder()
                        .headerKey("...my_header_key...")
                        .value("...my_value...")
                        .build())
                    .auth(DestinationWeaviateConfigurationIndexingAuthArgs.builder()
                        .apiToken(DestinationWeaviateConfigurationIndexingAuthApiTokenArgs.builder()
                            .token("...my_token...")
                            .build())
                        .build())
                    .batchSize(9)
                    .defaultVectorizer("text2vec-cohere")
                    .host("https://my-cluster.weaviate.network")
                    .tenantId("...my_tenant_id...")
                    .textField("...my_text_field...")
                    .build())
                .omit_raw_text(true)
                .processing(DestinationWeaviateConfigurationProcessingArgs.builder()
                    .chunkOverlap(4)
                    .chunkSize(4921)
                    .fieldNameMappings(DestinationWeaviateConfigurationProcessingFieldNameMappingArgs.builder()
                        .fromField("...my_from_field...")
                        .toField("...my_to_field...")
                        .build())
                    .metadataFields("...")
                    .textFields("...")
                    .textSplitter(DestinationWeaviateConfigurationProcessingTextSplitterArgs.builder()
                        .byMarkdownHeader(DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeaderArgs.builder()
                            .splitLevel(4)
                            .build())
                        .build())
                    .build())
                .build())
            .definitionId("37374193-1614-4ed2-9e81-293bdd2b75ef")
            .workspaceId("3a2f5d63-fb57-4357-9913-ad72f8c70fbf")
            .build());

    }
}

resources:
  myDestinationWeaviate:
    type: airbyte:DestinationWeaviate
    properties:
      configuration:
        embedding:
          fromField:
            dimensions: 1536
            fieldName: embedding
        indexing:
          additionalHeaders:
            - headerKey: '...my_header_key...'
              value: '...my_value...'
          auth:
            apiToken:
              token: '...my_token...'
          batchSize: 9
          defaultVectorizer: text2vec-cohere
          host: https://my-cluster.weaviate.network
          tenantId: '...my_tenant_id...'
          textField: '...my_text_field...'
        omit_raw_text: true
        processing:
          chunkOverlap: 4
          chunkSize: 4921
          fieldNameMappings:
            - fromField: '...my_from_field...'
              toField: '...my_to_field...'
          metadataFields:
            - '...'
          textFields:
            - '...'
          textSplitter:
            byMarkdownHeader:
              splitLevel: 4
      definitionId: 37374193-1614-4ed2-9e81-293bdd2b75ef
      workspaceId: 3a2f5d63-fb57-4357-9913-ad72f8c70fbf

Create DestinationWeaviate Resource

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

Constructor syntax

new DestinationWeaviate(name: string, args: DestinationWeaviateArgs, opts?: CustomResourceOptions);

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

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

func NewDestinationWeaviate(ctx *Context, name string, args DestinationWeaviateArgs, opts ...ResourceOption) (*DestinationWeaviate, error)

public DestinationWeaviate(string name, DestinationWeaviateArgs args, CustomResourceOptions? opts = null)

public DestinationWeaviate(String name, DestinationWeaviateArgs args)
public DestinationWeaviate(String name, DestinationWeaviateArgs args, CustomResourceOptions options)

type: airbyte:DestinationWeaviate
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 DestinationWeaviateArgs: 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 DestinationWeaviateArgs: 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 DestinationWeaviateArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

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

name String: The unique name of the resource.
args DestinationWeaviateArgs: 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 destinationWeaviateResource = new Airbyte.DestinationWeaviate("destinationWeaviateResource", new()
{
    Configuration = new Airbyte.Inputs.DestinationWeaviateConfigurationArgs
    {
        Embedding = new Airbyte.Inputs.DestinationWeaviateConfigurationEmbeddingArgs
        {
            AzureOpenAi = new Airbyte.Inputs.DestinationWeaviateConfigurationEmbeddingAzureOpenAiArgs
            {
                ApiBase = "string",
                Deployment = "string",
                OpenaiKey = "string",
            },
            Cohere = new Airbyte.Inputs.DestinationWeaviateConfigurationEmbeddingCohereArgs
            {
                CohereKey = "string",
            },
            Fake = null,
            FromField = new Airbyte.Inputs.DestinationWeaviateConfigurationEmbeddingFromFieldArgs
            {
                Dimensions = 0,
                FieldName = "string",
            },
            NoExternalEmbedding = null,
            OpenAi = new Airbyte.Inputs.DestinationWeaviateConfigurationEmbeddingOpenAiArgs
            {
                OpenaiKey = "string",
            },
            OpenAiCompatible = new Airbyte.Inputs.DestinationWeaviateConfigurationEmbeddingOpenAiCompatibleArgs
            {
                BaseUrl = "string",
                Dimensions = 0,
                ApiKey = "string",
                ModelName = "string",
            },
        },
        Indexing = new Airbyte.Inputs.DestinationWeaviateConfigurationIndexingArgs
        {
            Auth = new Airbyte.Inputs.DestinationWeaviateConfigurationIndexingAuthArgs
            {
                ApiToken = new Airbyte.Inputs.DestinationWeaviateConfigurationIndexingAuthApiTokenArgs
                {
                    Token = "string",
                },
                NoAuthentication = null,
                UsernamePassword = new Airbyte.Inputs.DestinationWeaviateConfigurationIndexingAuthUsernamePasswordArgs
                {
                    Password = "string",
                    Username = "string",
                },
            },
            Host = "string",
            AdditionalHeaders = new[]
            {
                new Airbyte.Inputs.DestinationWeaviateConfigurationIndexingAdditionalHeaderArgs
                {
                    HeaderKey = "string",
                    Value = "string",
                },
            },
            BatchSize = 0,
            DefaultVectorizer = "string",
            TenantId = "string",
            TextField = "string",
        },
        Processing = new Airbyte.Inputs.DestinationWeaviateConfigurationProcessingArgs
        {
            ChunkSize = 0,
            ChunkOverlap = 0,
            FieldNameMappings = new[]
            {
                new Airbyte.Inputs.DestinationWeaviateConfigurationProcessingFieldNameMappingArgs
                {
                    FromField = "string",
                    ToField = "string",
                },
            },
            MetadataFields = new[]
            {
                "string",
            },
            TextFields = new[]
            {
                "string",
            },
            TextSplitter = new Airbyte.Inputs.DestinationWeaviateConfigurationProcessingTextSplitterArgs
            {
                ByMarkdownHeader = new Airbyte.Inputs.DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeaderArgs
                {
                    SplitLevel = 0,
                },
                ByProgrammingLanguage = new Airbyte.Inputs.DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguageArgs
                {
                    Language = "string",
                },
                BySeparator = new Airbyte.Inputs.DestinationWeaviateConfigurationProcessingTextSplitterBySeparatorArgs
                {
                    KeepSeparator = false,
                    Separators = new[]
                    {
                        "string",
                    },
                },
            },
        },
        OmitRawText = false,
    },
    WorkspaceId = "string",
    DefinitionId = "string",
    Name = "string",
});

example, err := airbyte.NewDestinationWeaviate(ctx, "destinationWeaviateResource", &airbyte.DestinationWeaviateArgs{
Configuration: &.DestinationWeaviateConfigurationArgs{
Embedding: &.DestinationWeaviateConfigurationEmbeddingArgs{
AzureOpenAi: &.DestinationWeaviateConfigurationEmbeddingAzureOpenAiArgs{
ApiBase: pulumi.String("string"),
Deployment: pulumi.String("string"),
OpenaiKey: pulumi.String("string"),
},
Cohere: &.DestinationWeaviateConfigurationEmbeddingCohereArgs{
CohereKey: pulumi.String("string"),
},
Fake: &.DestinationWeaviateConfigurationEmbeddingFakeArgs{
},
FromField: &.DestinationWeaviateConfigurationEmbeddingFromFieldArgs{
Dimensions: pulumi.Float64(0),
FieldName: pulumi.String("string"),
},
NoExternalEmbedding: &.DestinationWeaviateConfigurationEmbeddingNoExternalEmbeddingArgs{
},
OpenAi: &.DestinationWeaviateConfigurationEmbeddingOpenAiArgs{
OpenaiKey: pulumi.String("string"),
},
OpenAiCompatible: &.DestinationWeaviateConfigurationEmbeddingOpenAiCompatibleArgs{
BaseUrl: pulumi.String("string"),
Dimensions: pulumi.Float64(0),
ApiKey: pulumi.String("string"),
ModelName: pulumi.String("string"),
},
},
Indexing: &.DestinationWeaviateConfigurationIndexingArgs{
Auth: &.DestinationWeaviateConfigurationIndexingAuthArgs{
ApiToken: &.DestinationWeaviateConfigurationIndexingAuthApiTokenArgs{
Token: pulumi.String("string"),
},
NoAuthentication: &.DestinationWeaviateConfigurationIndexingAuthNoAuthenticationArgs{
},
UsernamePassword: &.DestinationWeaviateConfigurationIndexingAuthUsernamePasswordArgs{
Password: pulumi.String("string"),
Username: pulumi.String("string"),
},
},
Host: pulumi.String("string"),
AdditionalHeaders: .DestinationWeaviateConfigurationIndexingAdditionalHeaderArray{
&.DestinationWeaviateConfigurationIndexingAdditionalHeaderArgs{
HeaderKey: pulumi.String("string"),
Value: pulumi.String("string"),
},
},
BatchSize: pulumi.Float64(0),
DefaultVectorizer: pulumi.String("string"),
TenantId: pulumi.String("string"),
TextField: pulumi.String("string"),
},
Processing: &.DestinationWeaviateConfigurationProcessingArgs{
ChunkSize: pulumi.Float64(0),
ChunkOverlap: pulumi.Float64(0),
FieldNameMappings: .DestinationWeaviateConfigurationProcessingFieldNameMappingArray{
&.DestinationWeaviateConfigurationProcessingFieldNameMappingArgs{
FromField: pulumi.String("string"),
ToField: pulumi.String("string"),
},
},
MetadataFields: pulumi.StringArray{
pulumi.String("string"),
},
TextFields: pulumi.StringArray{
pulumi.String("string"),
},
TextSplitter: &.DestinationWeaviateConfigurationProcessingTextSplitterArgs{
ByMarkdownHeader: &.DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeaderArgs{
SplitLevel: pulumi.Float64(0),
},
ByProgrammingLanguage: &.DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguageArgs{
Language: pulumi.String("string"),
},
BySeparator: &.DestinationWeaviateConfigurationProcessingTextSplitterBySeparatorArgs{
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 destinationWeaviateResource = new DestinationWeaviate("destinationWeaviateResource", DestinationWeaviateArgs.builder()
    .configuration(DestinationWeaviateConfigurationArgs.builder()
        .embedding(DestinationWeaviateConfigurationEmbeddingArgs.builder()
            .azureOpenAi(DestinationWeaviateConfigurationEmbeddingAzureOpenAiArgs.builder()
                .apiBase("string")
                .deployment("string")
                .openaiKey("string")
                .build())
            .cohere(DestinationWeaviateConfigurationEmbeddingCohereArgs.builder()
                .cohereKey("string")
                .build())
            .fake()
            .fromField(DestinationWeaviateConfigurationEmbeddingFromFieldArgs.builder()
                .dimensions(0)
                .fieldName("string")
                .build())
            .noExternalEmbedding()
            .openAi(DestinationWeaviateConfigurationEmbeddingOpenAiArgs.builder()
                .openaiKey("string")
                .build())
            .openAiCompatible(DestinationWeaviateConfigurationEmbeddingOpenAiCompatibleArgs.builder()
                .baseUrl("string")
                .dimensions(0)
                .apiKey("string")
                .modelName("string")
                .build())
            .build())
        .indexing(DestinationWeaviateConfigurationIndexingArgs.builder()
            .auth(DestinationWeaviateConfigurationIndexingAuthArgs.builder()
                .apiToken(DestinationWeaviateConfigurationIndexingAuthApiTokenArgs.builder()
                    .token("string")
                    .build())
                .noAuthentication()
                .usernamePassword(DestinationWeaviateConfigurationIndexingAuthUsernamePasswordArgs.builder()
                    .password("string")
                    .username("string")
                    .build())
                .build())
            .host("string")
            .additionalHeaders(DestinationWeaviateConfigurationIndexingAdditionalHeaderArgs.builder()
                .headerKey("string")
                .value("string")
                .build())
            .batchSize(0)
            .defaultVectorizer("string")
            .tenantId("string")
            .textField("string")
            .build())
        .processing(DestinationWeaviateConfigurationProcessingArgs.builder()
            .chunkSize(0)
            .chunkOverlap(0)
            .fieldNameMappings(DestinationWeaviateConfigurationProcessingFieldNameMappingArgs.builder()
                .fromField("string")
                .toField("string")
                .build())
            .metadataFields("string")
            .textFields("string")
            .textSplitter(DestinationWeaviateConfigurationProcessingTextSplitterArgs.builder()
                .byMarkdownHeader(DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeaderArgs.builder()
                    .splitLevel(0)
                    .build())
                .byProgrammingLanguage(DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguageArgs.builder()
                    .language("string")
                    .build())
                .bySeparator(DestinationWeaviateConfigurationProcessingTextSplitterBySeparatorArgs.builder()
                    .keepSeparator(false)
                    .separators("string")
                    .build())
                .build())
            .build())
        .omitRawText(false)
        .build())
    .workspaceId("string")
    .definitionId("string")
    .name("string")
    .build());

destination_weaviate_resource = airbyte.DestinationWeaviate("destinationWeaviateResource",
    configuration={
        "embedding": {
            "azure_open_ai": {
                "api_base": "string",
                "deployment": "string",
                "openai_key": "string",
            },
            "cohere": {
                "cohere_key": "string",
            },
            "fake": {},
            "from_field": {
                "dimensions": 0,
                "field_name": "string",
            },
            "no_external_embedding": {},
            "open_ai": {
                "openai_key": "string",
            },
            "open_ai_compatible": {
                "base_url": "string",
                "dimensions": 0,
                "api_key": "string",
                "model_name": "string",
            },
        },
        "indexing": {
            "auth": {
                "api_token": {
                    "token": "string",
                },
                "no_authentication": {},
                "username_password": {
                    "password": "string",
                    "username": "string",
                },
            },
            "host": "string",
            "additional_headers": [{
                "header_key": "string",
                "value": "string",
            }],
            "batch_size": 0,
            "default_vectorizer": "string",
            "tenant_id": "string",
            "text_field": "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 destinationWeaviateResource = new airbyte.DestinationWeaviate("destinationWeaviateResource", {
    configuration: {
        embedding: {
            azureOpenAi: {
                apiBase: "string",
                deployment: "string",
                openaiKey: "string",
            },
            cohere: {
                cohereKey: "string",
            },
            fake: {},
            fromField: {
                dimensions: 0,
                fieldName: "string",
            },
            noExternalEmbedding: {},
            openAi: {
                openaiKey: "string",
            },
            openAiCompatible: {
                baseUrl: "string",
                dimensions: 0,
                apiKey: "string",
                modelName: "string",
            },
        },
        indexing: {
            auth: {
                apiToken: {
                    token: "string",
                },
                noAuthentication: {},
                usernamePassword: {
                    password: "string",
                    username: "string",
                },
            },
            host: "string",
            additionalHeaders: [{
                headerKey: "string",
                value: "string",
            }],
            batchSize: 0,
            defaultVectorizer: "string",
            tenantId: "string",
            textField: "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:DestinationWeaviate
properties:
    configuration:
        embedding:
            azureOpenAi:
                apiBase: string
                deployment: string
                openaiKey: string
            cohere:
                cohereKey: string
            fake: {}
            fromField:
                dimensions: 0
                fieldName: string
            noExternalEmbedding: {}
            openAi:
                openaiKey: string
            openAiCompatible:
                apiKey: string
                baseUrl: string
                dimensions: 0
                modelName: string
        indexing:
            additionalHeaders:
                - headerKey: string
                  value: string
            auth:
                apiToken:
                    token: string
                noAuthentication: {}
                usernamePassword:
                    password: string
                    username: string
            batchSize: 0
            defaultVectorizer: string
            host: string
            tenantId: string
            textField: 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

DestinationWeaviate 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 DestinationWeaviate resource accepts the following input properties:

Configuration DestinationWeaviateConfiguration: 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 DestinationWeaviateConfigurationArgs: 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 DestinationWeaviateConfiguration: 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 DestinationWeaviateConfiguration: 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 DestinationWeaviateConfigurationArgs: 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 DestinationWeaviate resource produces the following output properties:

CreatedAt double
DestinationId string
DestinationType string
Id string: The provider-assigned unique ID for this managed resource.
ResourceAllocation DestinationWeaviateResourceAllocation: 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 DestinationWeaviateResourceAllocation: 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 DestinationWeaviateResourceAllocation: 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 DestinationWeaviateResourceAllocation: 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 DestinationWeaviateResourceAllocation: 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 DestinationWeaviate Resource

Get an existing DestinationWeaviate 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?: DestinationWeaviateState, opts?: CustomResourceOptions): DestinationWeaviate

@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        configuration: Optional[DestinationWeaviateConfigurationArgs] = 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[DestinationWeaviateResourceAllocationArgs] = None,
        workspace_id: Optional[str] = None) -> DestinationWeaviate

func GetDestinationWeaviate(ctx *Context, name string, id IDInput, state *DestinationWeaviateState, opts ...ResourceOption) (*DestinationWeaviate, error)

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

public static DestinationWeaviate get(String name, Output<String> id, DestinationWeaviateState state, CustomResourceOptions options)

resources:  _:    type: airbyte:DestinationWeaviate    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 DestinationWeaviateConfiguration: 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 DestinationWeaviateResourceAllocation: 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 DestinationWeaviateConfigurationArgs: 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 DestinationWeaviateResourceAllocationArgs: 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 DestinationWeaviateConfiguration: 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 DestinationWeaviateResourceAllocation: 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 DestinationWeaviateConfiguration: 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 DestinationWeaviateResourceAllocation: 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 DestinationWeaviateConfigurationArgs: 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 DestinationWeaviateResourceAllocationArgs: 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

DestinationWeaviateConfiguration, DestinationWeaviateConfigurationArgs

Embedding DestinationWeaviateConfigurationEmbedding: Embedding configuration
Indexing DestinationWeaviateConfigurationIndexing: Indexing configuration
Processing DestinationWeaviateConfigurationProcessing
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 DestinationWeaviateConfigurationEmbedding: Embedding configuration
Indexing DestinationWeaviateConfigurationIndexing: Indexing configuration
Processing DestinationWeaviateConfigurationProcessing
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 DestinationWeaviateConfigurationEmbedding: Embedding configuration
indexing DestinationWeaviateConfigurationIndexing: Indexing configuration
processing DestinationWeaviateConfigurationProcessing
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 DestinationWeaviateConfigurationEmbedding: Embedding configuration
indexing DestinationWeaviateConfigurationIndexing: Indexing configuration
processing DestinationWeaviateConfigurationProcessing
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 DestinationWeaviateConfigurationEmbedding: Embedding configuration
indexing DestinationWeaviateConfigurationIndexing: Indexing configuration
processing DestinationWeaviateConfigurationProcessing
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: Indexing configuration
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

DestinationWeaviateConfigurationEmbedding, DestinationWeaviateConfigurationEmbeddingArgs

AzureOpenAi DestinationWeaviateConfigurationEmbeddingAzureOpenAi: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
Cohere DestinationWeaviateConfigurationEmbeddingCohere: Use the Cohere API to embed text.
Fake DestinationWeaviateConfigurationEmbeddingFake: 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.
FromField DestinationWeaviateConfigurationEmbeddingFromField: Use a field in the record as the embedding. This is useful if you already have an embedding for your data and want to store it in the vector store.
NoExternalEmbedding DestinationWeaviateConfigurationEmbeddingNoExternalEmbedding: Do not calculate and pass embeddings to Weaviate. Suitable for clusters with configured vectorizers to calculate embeddings within Weaviate or for classes that should only support regular text search.
OpenAi DestinationWeaviateConfigurationEmbeddingOpenAi: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
OpenAiCompatible DestinationWeaviateConfigurationEmbeddingOpenAiCompatible: Use a service that's compatible with the OpenAI API to embed text.

AzureOpenAi DestinationWeaviateConfigurationEmbeddingAzureOpenAi: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
Cohere DestinationWeaviateConfigurationEmbeddingCohere: Use the Cohere API to embed text.
Fake DestinationWeaviateConfigurationEmbeddingFake: 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.
FromField DestinationWeaviateConfigurationEmbeddingFromField: Use a field in the record as the embedding. This is useful if you already have an embedding for your data and want to store it in the vector store.
NoExternalEmbedding DestinationWeaviateConfigurationEmbeddingNoExternalEmbedding: Do not calculate and pass embeddings to Weaviate. Suitable for clusters with configured vectorizers to calculate embeddings within Weaviate or for classes that should only support regular text search.
OpenAi DestinationWeaviateConfigurationEmbeddingOpenAi: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
OpenAiCompatible DestinationWeaviateConfigurationEmbeddingOpenAiCompatible: Use a service that's compatible with the OpenAI API to embed text.

azureOpenAi DestinationWeaviateConfigurationEmbeddingAzureOpenAi: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
cohere DestinationWeaviateConfigurationEmbeddingCohere: Use the Cohere API to embed text.
fake DestinationWeaviateConfigurationEmbeddingFake: 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.
fromField DestinationWeaviateConfigurationEmbeddingFromField: Use a field in the record as the embedding. This is useful if you already have an embedding for your data and want to store it in the vector store.
noExternalEmbedding DestinationWeaviateConfigurationEmbeddingNoExternalEmbedding: Do not calculate and pass embeddings to Weaviate. Suitable for clusters with configured vectorizers to calculate embeddings within Weaviate or for classes that should only support regular text search.
openAi DestinationWeaviateConfigurationEmbeddingOpenAi: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
openAiCompatible DestinationWeaviateConfigurationEmbeddingOpenAiCompatible: Use a service that's compatible with the OpenAI API to embed text.

azureOpenAi DestinationWeaviateConfigurationEmbeddingAzureOpenAi: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
cohere DestinationWeaviateConfigurationEmbeddingCohere: Use the Cohere API to embed text.
fake DestinationWeaviateConfigurationEmbeddingFake: 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.
fromField DestinationWeaviateConfigurationEmbeddingFromField: Use a field in the record as the embedding. This is useful if you already have an embedding for your data and want to store it in the vector store.
noExternalEmbedding DestinationWeaviateConfigurationEmbeddingNoExternalEmbedding: Do not calculate and pass embeddings to Weaviate. Suitable for clusters with configured vectorizers to calculate embeddings within Weaviate or for classes that should only support regular text search.
openAi DestinationWeaviateConfigurationEmbeddingOpenAi: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
openAiCompatible DestinationWeaviateConfigurationEmbeddingOpenAiCompatible: Use a service that's compatible with the OpenAI API to embed text.

azure_open_ai DestinationWeaviateConfigurationEmbeddingAzureOpenAi: Use the Azure-hosted OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
cohere DestinationWeaviateConfigurationEmbeddingCohere: Use the Cohere API to embed text.
fake DestinationWeaviateConfigurationEmbeddingFake: 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.
from_field DestinationWeaviateConfigurationEmbeddingFromField: Use a field in the record as the embedding. This is useful if you already have an embedding for your data and want to store it in the vector store.
no_external_embedding DestinationWeaviateConfigurationEmbeddingNoExternalEmbedding: Do not calculate and pass embeddings to Weaviate. Suitable for clusters with configured vectorizers to calculate embeddings within Weaviate or for classes that should only support regular text search.
open_ai DestinationWeaviateConfigurationEmbeddingOpenAi: Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
open_ai_compatible DestinationWeaviateConfigurationEmbeddingOpenAiCompatible: 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.
fromField Property Map: Use a field in the record as the embedding. This is useful if you already have an embedding for your data and want to store it in the vector store.
noExternalEmbedding Property Map: Do not calculate and pass embeddings to Weaviate. Suitable for clusters with configured vectorizers to calculate embeddings within Weaviate or for classes that should only support regular text search.
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.

DestinationWeaviateConfigurationEmbeddingAzureOpenAi, DestinationWeaviateConfigurationEmbeddingAzureOpenAiArgs

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

DestinationWeaviateConfigurationEmbeddingCohere, DestinationWeaviateConfigurationEmbeddingCohereArgs

CohereKey string

CohereKey string

cohereKey String

cohereKey string

cohere_key str

cohereKey String

DestinationWeaviateConfigurationEmbeddingFromField, DestinationWeaviateConfigurationEmbeddingFromFieldArgs

Dimensions double: The number of dimensions the embedding model is generating
FieldName string: Name of the field in the record that contains the embedding

Dimensions float64: The number of dimensions the embedding model is generating
FieldName string: Name of the field in the record that contains the embedding

dimensions Double: The number of dimensions the embedding model is generating
fieldName String: Name of the field in the record that contains the embedding

dimensions number: The number of dimensions the embedding model is generating
fieldName string: Name of the field in the record that contains the embedding

dimensions float: The number of dimensions the embedding model is generating
field_name str: Name of the field in the record that contains the embedding

dimensions Number: The number of dimensions the embedding model is generating
fieldName String: Name of the field in the record that contains the embedding

DestinationWeaviateConfigurationEmbeddingOpenAi, DestinationWeaviateConfigurationEmbeddingOpenAiArgs

OpenaiKey string

OpenaiKey string

openaiKey String

openaiKey string

openai_key str

openaiKey String

DestinationWeaviateConfigurationEmbeddingOpenAiCompatible, DestinationWeaviateConfigurationEmbeddingOpenAiCompatibleArgs

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"

DestinationWeaviateConfigurationIndexing, DestinationWeaviateConfigurationIndexingArgs

Auth DestinationWeaviateConfigurationIndexingAuth: Authentication method
Host string: The public endpoint of the Weaviate cluster.
AdditionalHeaders List<DestinationWeaviateConfigurationIndexingAdditionalHeader>: Additional HTTP headers to send with every request.
BatchSize double: The number of records to send to Weaviate in each batch. Default: 128
DefaultVectorizer string: The vectorizer to use if new classes need to be created. Default: "none"; must be one of ["none", "text2vec-cohere", "text2vec-huggingface", "text2vec-openai", "text2vec-palm", "text2vec-contextionary", "text2vec-transformers", "text2vec-gpt4all"]
TenantId string: The tenant ID to use for multi tenancy. Default: ""
TextField string: The field in the object that contains the embedded text. Default: "text"

Auth DestinationWeaviateConfigurationIndexingAuth: Authentication method
Host string: The public endpoint of the Weaviate cluster.
AdditionalHeaders []DestinationWeaviateConfigurationIndexingAdditionalHeader: Additional HTTP headers to send with every request.
BatchSize float64: The number of records to send to Weaviate in each batch. Default: 128
DefaultVectorizer string: The vectorizer to use if new classes need to be created. Default: "none"; must be one of ["none", "text2vec-cohere", "text2vec-huggingface", "text2vec-openai", "text2vec-palm", "text2vec-contextionary", "text2vec-transformers", "text2vec-gpt4all"]
TenantId string: The tenant ID to use for multi tenancy. Default: ""
TextField string: The field in the object that contains the embedded text. Default: "text"

auth DestinationWeaviateConfigurationIndexingAuth: Authentication method
host String: The public endpoint of the Weaviate cluster.
additionalHeaders List<DestinationWeaviateConfigurationIndexingAdditionalHeader>: Additional HTTP headers to send with every request.
batchSize Double: The number of records to send to Weaviate in each batch. Default: 128
defaultVectorizer String: The vectorizer to use if new classes need to be created. Default: "none"; must be one of ["none", "text2vec-cohere", "text2vec-huggingface", "text2vec-openai", "text2vec-palm", "text2vec-contextionary", "text2vec-transformers", "text2vec-gpt4all"]
tenantId String: The tenant ID to use for multi tenancy. Default: ""
textField String: The field in the object that contains the embedded text. Default: "text"

auth DestinationWeaviateConfigurationIndexingAuth: Authentication method
host string: The public endpoint of the Weaviate cluster.
additionalHeaders DestinationWeaviateConfigurationIndexingAdditionalHeader[]: Additional HTTP headers to send with every request.
batchSize number: The number of records to send to Weaviate in each batch. Default: 128
defaultVectorizer string: The vectorizer to use if new classes need to be created. Default: "none"; must be one of ["none", "text2vec-cohere", "text2vec-huggingface", "text2vec-openai", "text2vec-palm", "text2vec-contextionary", "text2vec-transformers", "text2vec-gpt4all"]
tenantId string: The tenant ID to use for multi tenancy. Default: ""
textField string: The field in the object that contains the embedded text. Default: "text"

auth DestinationWeaviateConfigurationIndexingAuth: Authentication method
host str: The public endpoint of the Weaviate cluster.
additional_headers Sequence[DestinationWeaviateConfigurationIndexingAdditionalHeader]: Additional HTTP headers to send with every request.
batch_size float: The number of records to send to Weaviate in each batch. Default: 128
default_vectorizer str: The vectorizer to use if new classes need to be created. Default: "none"; must be one of ["none", "text2vec-cohere", "text2vec-huggingface", "text2vec-openai", "text2vec-palm", "text2vec-contextionary", "text2vec-transformers", "text2vec-gpt4all"]
tenant_id str: The tenant ID to use for multi tenancy. Default: ""
text_field str: The field in the object that contains the embedded text. Default: "text"

auth Property Map: Authentication method
host String: The public endpoint of the Weaviate cluster.
additionalHeaders List<Property Map>: Additional HTTP headers to send with every request.
batchSize Number: The number of records to send to Weaviate in each batch. Default: 128
defaultVectorizer String: The vectorizer to use if new classes need to be created. Default: "none"; must be one of ["none", "text2vec-cohere", "text2vec-huggingface", "text2vec-openai", "text2vec-palm", "text2vec-contextionary", "text2vec-transformers", "text2vec-gpt4all"]
tenantId String: The tenant ID to use for multi tenancy. Default: ""
textField String: The field in the object that contains the embedded text. Default: "text"

DestinationWeaviateConfigurationIndexingAdditionalHeader, DestinationWeaviateConfigurationIndexingAdditionalHeaderArgs

HeaderKey string
Value string

HeaderKey string
Value string

headerKey String
value String

headerKey string
value string

header_key str
value str

headerKey String
value String

DestinationWeaviateConfigurationIndexingAuth, DestinationWeaviateConfigurationIndexingAuthArgs

ApiToken DestinationWeaviateConfigurationIndexingAuthApiToken: Authenticate using an API token (suitable for Weaviate Cloud)
NoAuthentication DestinationWeaviateConfigurationIndexingAuthNoAuthentication: Do not authenticate (suitable for locally running test clusters, do not use for clusters with public IP addresses)
UsernamePassword DestinationWeaviateConfigurationIndexingAuthUsernamePassword: Authenticate using username and password (suitable for self-managed Weaviate clusters)

ApiToken DestinationWeaviateConfigurationIndexingAuthApiToken: Authenticate using an API token (suitable for Weaviate Cloud)
NoAuthentication DestinationWeaviateConfigurationIndexingAuthNoAuthentication: Do not authenticate (suitable for locally running test clusters, do not use for clusters with public IP addresses)
UsernamePassword DestinationWeaviateConfigurationIndexingAuthUsernamePassword: Authenticate using username and password (suitable for self-managed Weaviate clusters)

apiToken DestinationWeaviateConfigurationIndexingAuthApiToken: Authenticate using an API token (suitable for Weaviate Cloud)
noAuthentication DestinationWeaviateConfigurationIndexingAuthNoAuthentication: Do not authenticate (suitable for locally running test clusters, do not use for clusters with public IP addresses)
usernamePassword DestinationWeaviateConfigurationIndexingAuthUsernamePassword: Authenticate using username and password (suitable for self-managed Weaviate clusters)

apiToken DestinationWeaviateConfigurationIndexingAuthApiToken: Authenticate using an API token (suitable for Weaviate Cloud)
noAuthentication DestinationWeaviateConfigurationIndexingAuthNoAuthentication: Do not authenticate (suitable for locally running test clusters, do not use for clusters with public IP addresses)
usernamePassword DestinationWeaviateConfigurationIndexingAuthUsernamePassword: Authenticate using username and password (suitable for self-managed Weaviate clusters)

api_token DestinationWeaviateConfigurationIndexingAuthApiToken: Authenticate using an API token (suitable for Weaviate Cloud)
no_authentication DestinationWeaviateConfigurationIndexingAuthNoAuthentication: Do not authenticate (suitable for locally running test clusters, do not use for clusters with public IP addresses)
username_password DestinationWeaviateConfigurationIndexingAuthUsernamePassword: Authenticate using username and password (suitable for self-managed Weaviate clusters)

apiToken Property Map: Authenticate using an API token (suitable for Weaviate Cloud)
noAuthentication Property Map: Do not authenticate (suitable for locally running test clusters, do not use for clusters with public IP addresses)
usernamePassword Property Map: Authenticate using username and password (suitable for self-managed Weaviate clusters)

DestinationWeaviateConfigurationIndexingAuthApiToken, DestinationWeaviateConfigurationIndexingAuthApiTokenArgs

Token string: API Token for the Weaviate instance

Token string: API Token for the Weaviate instance

token String: API Token for the Weaviate instance

token string: API Token for the Weaviate instance

token str: API Token for the Weaviate instance

token String: API Token for the Weaviate instance

DestinationWeaviateConfigurationIndexingAuthUsernamePassword, DestinationWeaviateConfigurationIndexingAuthUsernamePasswordArgs

Password string: Password for the Weaviate cluster
Username string: Username for the Weaviate cluster

Password string: Password for the Weaviate cluster
Username string: Username for the Weaviate cluster

password String: Password for the Weaviate cluster
username String: Username for the Weaviate cluster

password string: Password for the Weaviate cluster
username string: Username for the Weaviate cluster

password str: Password for the Weaviate cluster
username str: Username for the Weaviate cluster

password String: Password for the Weaviate cluster
username String: Username for the Weaviate cluster

DestinationWeaviateConfigurationProcessing, DestinationWeaviateConfigurationProcessingArgs

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<DestinationWeaviateConfigurationProcessingFieldNameMapping>: 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 DestinationWeaviateConfigurationProcessingTextSplitter: 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 []DestinationWeaviateConfigurationProcessingFieldNameMapping: 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 DestinationWeaviateConfigurationProcessingTextSplitter: 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<DestinationWeaviateConfigurationProcessingFieldNameMapping>: 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 DestinationWeaviateConfigurationProcessingTextSplitter: 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 DestinationWeaviateConfigurationProcessingFieldNameMapping[]: 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 DestinationWeaviateConfigurationProcessingTextSplitter: 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[DestinationWeaviateConfigurationProcessingFieldNameMapping]: 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 DestinationWeaviateConfigurationProcessingTextSplitter: 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.

DestinationWeaviateConfigurationProcessingFieldNameMapping, DestinationWeaviateConfigurationProcessingFieldNameMappingArgs

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

DestinationWeaviateConfigurationProcessingTextSplitter, DestinationWeaviateConfigurationProcessingTextSplitterArgs

ByMarkdownHeader DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeader: 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 DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguage: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
BySeparator DestinationWeaviateConfigurationProcessingTextSplitterBySeparator: 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 DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeader: 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 DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguage: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
BySeparator DestinationWeaviateConfigurationProcessingTextSplitterBySeparator: 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 DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeader: 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 DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguage: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
bySeparator DestinationWeaviateConfigurationProcessingTextSplitterBySeparator: 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 DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeader: 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 DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguage: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
bySeparator DestinationWeaviateConfigurationProcessingTextSplitterBySeparator: 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 DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeader: 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 DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguage: Split the text by suitable delimiters based on the programming language. This is useful for splitting code into chunks.
by_separator DestinationWeaviateConfigurationProcessingTextSplitterBySeparator: 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.

DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeader, DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeaderArgs

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

DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguage, DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguageArgs

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"]

DestinationWeaviateConfigurationProcessingTextSplitterBySeparator, DestinationWeaviateConfigurationProcessingTextSplitterBySeparatorArgs

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".

DestinationWeaviateResourceAllocation, DestinationWeaviateResourceAllocationArgs

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

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

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

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

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

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

DestinationWeaviateResourceAllocationDefault, DestinationWeaviateResourceAllocationDefaultArgs

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

DestinationWeaviateResourceAllocationJobSpecific, DestinationWeaviateResourceAllocationJobSpecificArgs

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 DestinationWeaviateResourceAllocationJobSpecificResourceRequirements: 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 DestinationWeaviateResourceAllocationJobSpecificResourceRequirements: 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 DestinationWeaviateResourceAllocationJobSpecificResourceRequirements: 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 DestinationWeaviateResourceAllocationJobSpecificResourceRequirements: 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 DestinationWeaviateResourceAllocationJobSpecificResourceRequirements: 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)

DestinationWeaviateResourceAllocationJobSpecificResourceRequirements, DestinationWeaviateResourceAllocationJobSpecificResourceRequirementsArgs

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/destinationWeaviate:DestinationWeaviate my_airbyte_destination_weaviate ""

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.DestinationWeaviate

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Example Usage

Create DestinationWeaviate Resource

Constructor syntax

Parameters

Constructor example

DestinationWeaviate Resource Properties

Inputs

Outputs

Look up Existing DestinationWeaviate Resource

Supporting Types

DestinationWeaviateConfiguration, DestinationWeaviateConfigurationArgs

DestinationWeaviateConfigurationEmbedding, DestinationWeaviateConfigurationEmbeddingArgs

DestinationWeaviateConfigurationEmbeddingAzureOpenAi, DestinationWeaviateConfigurationEmbeddingAzureOpenAiArgs

DestinationWeaviateConfigurationEmbeddingCohere, DestinationWeaviateConfigurationEmbeddingCohereArgs

DestinationWeaviateConfigurationEmbeddingFromField, DestinationWeaviateConfigurationEmbeddingFromFieldArgs

DestinationWeaviateConfigurationEmbeddingOpenAi, DestinationWeaviateConfigurationEmbeddingOpenAiArgs

DestinationWeaviateConfigurationEmbeddingOpenAiCompatible, DestinationWeaviateConfigurationEmbeddingOpenAiCompatibleArgs

DestinationWeaviateConfigurationIndexing, DestinationWeaviateConfigurationIndexingArgs

DestinationWeaviateConfigurationIndexingAdditionalHeader, DestinationWeaviateConfigurationIndexingAdditionalHeaderArgs

DestinationWeaviateConfigurationIndexingAuth, DestinationWeaviateConfigurationIndexingAuthArgs

DestinationWeaviateConfigurationIndexingAuthApiToken, DestinationWeaviateConfigurationIndexingAuthApiTokenArgs

DestinationWeaviateConfigurationIndexingAuthUsernamePassword, DestinationWeaviateConfigurationIndexingAuthUsernamePasswordArgs

DestinationWeaviateConfigurationProcessing, DestinationWeaviateConfigurationProcessingArgs

DestinationWeaviateConfigurationProcessingFieldNameMapping, DestinationWeaviateConfigurationProcessingFieldNameMappingArgs

DestinationWeaviateConfigurationProcessingTextSplitter, DestinationWeaviateConfigurationProcessingTextSplitterArgs

DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeader, DestinationWeaviateConfigurationProcessingTextSplitterByMarkdownHeaderArgs

DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguage, DestinationWeaviateConfigurationProcessingTextSplitterByProgrammingLanguageArgs

DestinationWeaviateConfigurationProcessingTextSplitterBySeparator, DestinationWeaviateConfigurationProcessingTextSplitterBySeparatorArgs

DestinationWeaviateResourceAllocation, DestinationWeaviateResourceAllocationArgs

DestinationWeaviateResourceAllocationDefault, DestinationWeaviateResourceAllocationDefaultArgs

DestinationWeaviateResourceAllocationJobSpecific, DestinationWeaviateResourceAllocationJobSpecificArgs

DestinationWeaviateResourceAllocationJobSpecificResourceRequirements, DestinationWeaviateResourceAllocationJobSpecificResourceRequirementsArgs

Import

Package Details

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