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

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### Generated
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- [python v0.32.1] .
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### Releases
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- [PyPI v0.32.1] https://pypi.org/project/airbyte-api/0.32.1 - .
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- [PyPI v0.32.1] https://pypi.org/project/airbyte-api/0.32.1 - .
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## 2023-08-21 14:53:00
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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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- [python v0.32.2] .
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### Releases
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- [PyPI v0.32.2] https://pypi.org/project/airbyte-api/0.32.2 - .

‎docs/models/operations/listjobsrequest.md

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| `job_type` | [Optional[shared.JobTypeEnum]](../../models/shared/jobtypeenum.md) | :heavy_minus_sign: | Filter the Jobs by jobType. |
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| `limit` | *Optional[int]* | :heavy_minus_sign: | Set the limit on the number of Jobs returned. The default is 20 Jobs. |
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| `offset` | *Optional[int]* | :heavy_minus_sign: | Set the offset to start at when returning Jobs. The default is 0. |
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| `order_by` | *Optional[str]* | :heavy_minus_sign: | The field and method to use for ordering. Currently allowed are createdAt and updatedAt. |
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| `status` | [Optional[shared.JobStatusEnum]](../../models/shared/jobstatusenum.md) | :heavy_minus_sign: | The Job status you want to filter by |
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| `updated_at_end` | [date](https://docs.python.org/3/library/datetime.html#date-objects) | :heavy_minus_sign: | The end date to filter by |
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| `updated_at_start` | [date](https://docs.python.org/3/library/datetime.html#date-objects) | :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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| `destination_type` | [DestinationLangchainLangchain](../../models/shared/destinationlangchainlangchain.md) | :heavy_check_mark: | N/A |
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| `embedding` | *Any* | :heavy_check_mark: | Embedding configuration |
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| `indexing` | *Any* | :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` | [Optional[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` | [Optional[DestinationLangchainEmbeddingOpenAIMode]](../../models/shared/destinationlangchainembeddingopenaimode.md) | :heavy_minus_sign: | N/A |
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| `openai_key` | *str* | :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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| `collection_name` | *Optional[str]* | :heavy_minus_sign: | Name of the collection to use. | |
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| `destination_path` | *str* | :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` | [Optional[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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