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ci: regenerated with OpenAPI Doc 1.0.0, Speakeay CLI 1.74.3
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‎README.md‎

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@@ -21,7 +21,7 @@ The Developer Portal UI can also be used to help build your integration by showi
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### Gradle
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```groovy
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implementation 'com.airbyte.api:public-api:0.36.1'
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implementation 'com.airbyte.api:public-api:0.36.2'
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```
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<!-- End SDK Installation -->
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‎RELEASES.md‎

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### Generated
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- [java v0.36.1] .
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### Releases
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- [Maven Central v0.36.1] https://central.sonatype.com/artifact/com.airbyte/api/0.36.1 - .
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- [Maven Central v0.36.1] https://central.sonatype.com/artifact/com.airbyte/api/0.36.1 - .
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## 2023-08-21 14:52:53
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### Changes
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Based on:
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- OpenAPI Doc 1.0.0
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- Speakeasy CLI 1.74.3 (2.86.6) https://github.com/speakeasy-api/speakeasy
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### Generated
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- [java v0.36.2] .
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### Releases
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- [Maven Central v0.36.2] https://central.sonatype.com/artifact/com.airbyte/api/0.36.2 - .

‎docs/models/operations/ListJobsRequest.md‎

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| `jobType` | [com.airbyte.api.models.shared.JobTypeEnum](../../models/shared/JobTypeEnum.md) | :heavy_minus_sign: | Filter the Jobs by jobType. |
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| `limit` | *Integer* | :heavy_minus_sign: | Set the limit on the number of Jobs returned. The default is 20 Jobs. |
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| `offset` | *Integer* | :heavy_minus_sign: | Set the offset to start at when returning Jobs. The default is 0. |
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| `orderBy` | *String* | :heavy_minus_sign: | The field and method to use for ordering. Currently allowed are createdAt and updatedAt. |
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| `status` | [com.airbyte.api.models.shared.JobStatusEnum](../../models/shared/JobStatusEnum.md) | :heavy_minus_sign: | The Job status you want to filter by |
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| `updatedAtEnd` | [OffsetDateTime](https://docs.oracle.com/javase/8/docs/api/java/time/OffsetDateTime.html) | :heavy_minus_sign: | The end date to filter by |
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| `updatedAtStart` | [OffsetDateTime](https://docs.oracle.com/javase/8/docs/api/java/time/OffsetDateTime.html) | :heavy_minus_sign: | The start date to filter by |

‎docs/models/shared/DestinationLangchain.md‎

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# DestinationLangchain
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The values required to configure the destination.
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## Fields
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| Field | Type | Required | Description |
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| ------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- |
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| `destinationType` | [DestinationLangchainLangchain](../../models/shared/DestinationLangchainLangchain.md) | :heavy_check_mark: | N/A |
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| `embedding` | *Object* | :heavy_check_mark: | Embedding configuration |
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| `indexing` | *Object* | :heavy_check_mark: | Indexing configuration |
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| `processing` | [DestinationLangchainProcessingConfigModel](../../models/shared/DestinationLangchainProcessingConfigModel.md) | :heavy_check_mark: | N/A |

‎docs/models/shared/DestinationLangchainEmbeddingFake.md‎

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# DestinationLangchainEmbeddingFake
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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.
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## Fields
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| Field | Type | Required | Description |
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| ----------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------- |
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| `mode` | [DestinationLangchainEmbeddingFakeMode](../../models/shared/DestinationLangchainEmbeddingFakeMode.md) | :heavy_minus_sign: | N/A |

‎docs/models/shared/DestinationLangchainEmbeddingFakeMode.md‎

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# DestinationLangchainEmbeddingFakeMode
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## Values
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| Name | Value |
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| ------ | ------ |
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| `FAKE` | fake |

‎docs/models/shared/DestinationLangchainEmbeddingOpenAI.md‎

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# DestinationLangchainEmbeddingOpenAI
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Use the OpenAI API to embed text. This option is using the text-embedding-ada-002 model with 1536 embedding dimensions.
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## Fields
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| Field | Type | Required | Description |
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| --------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- |
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| `mode` | [DestinationLangchainEmbeddingOpenAIMode](../../models/shared/DestinationLangchainEmbeddingOpenAIMode.md) | :heavy_minus_sign: | N/A |
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| `openaiKey` | *String* | :heavy_check_mark: | N/A |

‎docs/models/shared/DestinationLangchainEmbeddingOpenAIMode.md‎

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# DestinationLangchainEmbeddingOpenAIMode
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## Values
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| Name | Value |
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| -------- | -------- |
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| `OPENAI` | openai |

‎docs/models/shared/DestinationLangchainIndexingChromaLocalPersistance.md‎

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# DestinationLangchainIndexingChromaLocalPersistance
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Chroma is a popular vector store that can be used to store and retrieve embeddings. It will build its index in memory and persist it to disk by the end of the sync.
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## Fields
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| Field | Type | Required | Description | Example |
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| --------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
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| `collectionName` | *String* | :heavy_minus_sign: | Name of the collection to use. | |
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| `destinationPath` | *String* | :heavy_check_mark: | Path to the directory where chroma files will be written. The files will be placed inside that local mount. | /local/my_chroma_db |
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| `mode` | [DestinationLangchainIndexingChromaLocalPersistanceMode](../../models/shared/DestinationLangchainIndexingChromaLocalPersistanceMode.md) | :heavy_minus_sign: | N/A | |

‎docs/models/shared/DestinationLangchainIndexingChromaLocalPersistanceMode.md‎

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# DestinationLangchainIndexingChromaLocalPersistanceMode
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## Values
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| Name | Value |
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| -------------- | -------------- |
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| `CHROMA_LOCAL` | chroma_local |

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