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Nappai Documentation

Weaviate

This component connects Nappai to Weaviate, a smart search engine that understands the meaning of your data. You can use it to store information and then easily search for similar items. Think of it as a highly efficient search tool within Nappai.

Relationship with Weaviate

This component directly interacts with the Weaviate API. Weaviate stores your data as “vectors,” which are mathematical representations that allow for very fast and accurate similarity searches. This component handles all the technical details of connecting to Weaviate, storing your data, and retrieving search results.

Inputs

  • Index Name: The name of the location in Weaviate where your data will be stored. Think of this as the name of a folder in your filing cabinet. This is required.
  • Text Key: (Advanced) Specifies which part of your data contains the actual text you want to search. Defaults to “text”.
  • Search Query: The words or phrases you use to search for information.
  • Ingest Data: The information you want to store in Weaviate.
  • Embedding: (Advanced) This is the method used to convert your data into a format Weaviate understands for searching. This is handled automatically in most cases.
  • Number of Results: (Advanced) How many search results you want to see. Defaults to 4.
  • Search By Text: (Advanced) Specifies whether to search by the text directly or by the vector representation.
  • Credential: Your access key to your Weaviate account. This is how Nappai knows it’s you.

Outputs

This component doesn’t have explicit outputs in the sense of creating new data objects on the dashboard. Instead, the results of a search are used directly within Nappai’s workflow. The search returns a list of the most relevant items found in Weaviate, which are then used by other Nappai components.

Usage Example

Let’s say you have a collection of customer reviews and want to find reviews similar to a specific one. You would:

  1. Provide the name of your Weaviate index (Index Name).
  2. Enter your Weaviate access key (Credential).
  3. Paste the text of the review you want to compare (Search Query).
  4. Nappai will then return a list of similar customer reviews from Weaviate.

Templates

This component is used in many Nappai workflows. You’ll find it integrated into various templates, often in combination with other components for data processing and analysis. Check the specific template documentation for details on its configuration within that workflow.

  • VectorStoreInfo: Provides information about the vector store being used.
  • Self Query Retriever: Uses Weaviate and an AI model to refine search queries.
  • Many other components: Weaviate often works with components that process data before sending it to Weaviate (like “Entities extraction” or “Summarizer”) or components that use the search results (like “Google Sheet Writer” to export the results).

Tips and Best Practices

  • Make sure your Weaviate index is correctly configured before using this component.
  • Use clear and concise search queries for better results.
  • Experiment with the advanced settings (Number of Results, Search By Text) to fine-tune your searches.

Security Considerations

Protect your Weaviate API key (Credential). Do not share it with unauthorized individuals. Treat it like a password.