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Node Details

  • Name: Weaviate

  • Type: Weaviate

  • Version: 3.0

  • Category: Vector Stores

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Base Classes

  • Weaviate

  • VectorStoreRetriever

  • BaseRetriever

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Input Parameters

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Required Parameters

  1. Embeddings: The embedding model to use for vectorizing the data.

  2. Weaviate Scheme: The scheme to use for connecting to Weaviate (https or http).

  3. Weaviate Host: The host address of the Weaviate instance (e.g., localhost:8080).

  4. Weaviate Index: The name of the Weaviate index to use.

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Optional Parameters

  1. Document: List of documents to be inserted into the vector store.

  2. Record Manager: Keeps track of records to prevent duplication.

  3. Weaviate Text Key: The key used for storing text data in Weaviate.

  4. Weaviate Metadata Keys: JSON array of metadata keys to be stored in Weaviate.

  5. Top K: Number of top results to fetch (default: 4).

  6. Weaviate Search Filter: JSON object for filtering search results.

  7. MMR Parameters: Additional parameters for Maximal Marginal Relevance search.

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Credential (Optional)

  • Weaviate API Key: Required only when using Weaviate cloud hosted service.

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Outputs

  1. Weaviate Retriever: A retriever object for querying the Weaviate vector store.

  2. Weaviate Vector Store: The Weaviate vector store object.

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Functionality

  1. Upsert: Allows inserting or updating documents in the Weaviate vector store.

  2. Delete: Enables deletion of documents from the vector store based on their IDs.

  3. Initialization: Sets up the Weaviate client and creates a vector store instance.

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Use Cases

  • Semantic search applications

  • Recommendation systems

  • Document similarity analysis

  • Knowledge management systems

  • Any application requiring efficient storage and retrieval of vector embeddings

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Notes

  • The node supports both local and cloud-hosted Weaviate instances.

  • It integrates with a record manager for tracking and preventing duplicate entries.

  • The node allows for customization of text and metadata keys for flexible data storage.

  • It supports advanced querying capabilities through Weaviate’s filtering mechanism.