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60 lines
3.4 KiB
Plaintext
60 lines
3.4 KiB
Plaintext
---
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title: Milvus
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slug: /bundles-milvus
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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 **Milvus** bundle.
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## Milvus vector store
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The **Milvus** component reads and writes to Milvus vector stores using an instance of `Milvus` vector store.
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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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:::tip
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For a tutorial using a vector database in a flow, see [Create a vector RAG chatbot](/chat-with-rag).
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:::
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### Milvus vector store 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 [Milvus documentation](https://milvus.io/docs) or inspect [component code](/concepts-components#component-code).
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| Name | Type | Description |
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|-------------------------|---------------|--------------------------------------------------|
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| collection_name | String | Input parameter. Name of the Milvus collection. |
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| collection_description | String | Input parameter. Description of the Milvus collection. |
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| uri | String | Input parameter. Connection URI for Milvus. |
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| password | SecretString | Input parameter. Password for Milvus. |
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| username | SecretString | Input parameter. Username for Milvus. |
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| batch_size | Integer | Input parameter. Number of data to process in a single batch. |
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| search_query | String | Input parameter. Query for similarity search. |
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| ingest_data | JSON | Input parameter. Data to be ingested into the vector store. |
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| embedding | Embeddings | Input parameter. Embedding function to use. |
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| number_of_results | Integer | Input parameter. Number of results to return in search. |
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| search_type | String | Input parameter. Type of search to perform. |
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| search_score_threshold | Float | Input parameter. Minimum similarity score for search results. |
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| search_filter | Dict | Input parameter. Metadata filters for search query. |
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| setup_mode | String | Input parameter. Configuration mode for setting up the vector store. |
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| vector_dimensions | Integer | Input parameter. Number of dimensions of the vectors. |
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| pre_delete_collection | Boolean | Input parameter. Whether to delete the collection before creating a new one. | |