Overview
This node performs a semantic search using the Peerag RAG API. It is useful for retrieving the most relevant documents or information based on a natural language query. Common scenarios include knowledge base search, document retrieval, and enhancing chatbot responses by finding contextually relevant data.
Use Case Examples
- A user inputs a query to find the top 5 most relevant documents with a minimum relevance score of 0.7.
- A workflow that filters search results based on a score threshold to ensure only highly relevant results are processed further.
Properties
| Name | Meaning |
|---|---|
| Query | The natural language query string to search for relevant documents or information. |
| Top K | The maximum number of top relevant results to return from the search. |
| Score Threshold | The minimum relevance score a result must have to be included in the output. |
Output
JSON
json- The JSON response from the Peerag RAG API containing the search results, including documents and their relevance scores.
Dependencies
- Peerag RAG API endpoint requiring an API key credential named 'peeragApi' with a baseUrl property.
Troubleshooting
- Ensure the 'peeragApi' credential is correctly configured with a valid base URL and API key.
- Check network connectivity to the Peerag API endpoint.
- Verify that the query string is not empty to avoid empty or invalid search requests.
- If the API returns errors, check the response for details such as rate limits or invalid parameters.
Links
- Peerag API Documentation - Official documentation for the Peerag RAG API used for semantic search.