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54 lines
3.5 KiB
Plaintext
54 lines
3.5 KiB
Plaintext
---
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title: MongoDB
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slug: /bundles-mongodb
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---
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import Icon from "@site/src/components/icon";
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import PartialParams from '@site/docs/_partial-hidden-params.mdx';
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import PartialConditionalParams from '@site/docs/_partial-conditional-params.mdx';
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import PartialVectorSearchResults from '@site/docs/_partial-vector-search-results.mdx';
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import PartialVectorStoreInstance from '@site/docs/_partial-vector-store-instance.mdx';
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<Icon name="Blocks" aria-hidden="true" /> [**Bundles**](/components-bundle-components) contain custom components that support specific third-party integrations with Langflow.
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This page describes the components that are available in the **MongoDB** bundle.
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## MongoDB Atlas
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The **MongoDB Atlas** component reads and writes to MongoDB Atlas vector stores using an instance of [`MongoDBAtlasVectorSearch`](https://docs.langchain.com/oss/python/integrations/vectorstores/mongodb_atlas).
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<details>
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<summary>About vector store instances</summary>
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<PartialVectorStoreInstance />
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</details>
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<PartialVectorSearchResults />
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### MongoDB Atlas parameters
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You can inspect a vector store component's parameters to learn more about the inputs it accepts, the features it supports, and how to configure it.
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<PartialParams />
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<PartialConditionalParams />
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For information about accepted values and functionality, see the [MongoDB Atlas documentation](https://www.mongodb.com/docs/atlas/atlas-vector-search/tutorials/vector-search-quick-start/) or inspect [component code](/concepts-components#component-code).
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| Name | Type | Description |
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| ------------------------- | ------------ | ----------------------------------------- |
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| mongodb_atlas_cluster_uri | SecretString | Input parameter. The connection URI for your MongoDB Atlas cluster. Required. |
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| enable_mtls | Boolean | Input parameter. Enable mutual TLS authentication. Default: `false`. |
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| mongodb_atlas_client_cert | SecretString | Input parameter. Client certificate combined with private key for mTLS authentication. Required if mTLS is enabled. |
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| db_name | String | Input parameter. The name of the database to use. Required. |
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| collection_name | String | Input parameter. The name of the collection to use. Required. |
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| index_name | String | Input parameter. The name of the Atlas Search index, it should be a Vector Search. Required. |
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| insert_mode | String | Input parameter. How to insert new documents into the collection. The options are "append" or "overwrite". Default: "append". |
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| embedding | Embeddings | Input parameter. The embedding model to use. |
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| number_of_results | Integer | Input parameter. Number of results to return in similarity search. Default: 4. |
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| index_field | String | Input parameter. The field to index. Default: "embedding". |
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| filter_field | String | Input parameter. The field to filter the index. |
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| number_dimensions | Integer | Input parameter. Embedding vector dimension count. Default: 1536. |
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| similarity | String | Input parameter. The method used to measure similarity between vectors. The options are "cosine", "euclidean", or "dotProduct". Default: "cosine". |
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| quantization | String | Input parameter. Quantization reduces memory costs by converting 32-bit floats to smaller data types. The options are "scalar" or "binary". | |