Glossary

Local Search Index for RAG

A local search index for RAG is an on-premise or self-hosted search engine (like Elasticsearch, Meilisearch, or SQLite FTS) used as a retrieval backend in a Retrieval-Augmented Generation pipeline, providing fast, private, and cost-free searches over a curated corpus.

Definition

A local search index for RAG is an on-premise or self-hosted search engine (like Elasticsearch, Meilisearch, or SQLite FTS) used as a retrieval backend in a Retrieval-Augmented Generation pipeline, providing fast, private, and cost-free searches over a curated corpus.

In Depth

RAG systems need a retrieval step to find relevant documents before the LLM generates a response. A local search index stores and searches a curated corpus of documents on the developer's own infrastructure. This provides zero-latency, zero-cost, and fully private retrieval, but only over the documents that have been indexed. For questions that go beyond the local corpus, a hybrid approach combines local search with a live search API. The local index handles known-domain queries (company docs, product catalog, historical data), while the search API handles open-domain queries (competitor info, current events, public sentiment). Scavio's API serves as the live search layer in this architecture, complementing rather than replacing the local index.

Example Usage

Real-World Example

A customer support bot searches a local Meilisearch index of help articles first. If the confidence score is below 0.7, it falls back to Scavio's Google endpoint to search the public web for the answer, ensuring coverage even when the internal docs are incomplete.

Platforms

Local Search Index for RAG is relevant across the following platforms, all accessible through Scavio's unified API:

  • Google
  • Reddit
  • YouTube

Related Terms

Frequently Asked Questions

A local search index for RAG is an on-premise or self-hosted search engine (like Elasticsearch, Meilisearch, or SQLite FTS) used as a retrieval backend in a Retrieval-Augmented Generation pipeline, providing fast, private, and cost-free searches over a curated corpus.

A customer support bot searches a local Meilisearch index of help articles first. If the confidence score is below 0.7, it falls back to Scavio's Google endpoint to search the public web for the answer, ensuring coverage even when the internal docs are incomplete.

Local Search Index for RAG is relevant to Google, Reddit, YouTube. Scavio provides a unified API to access data from all of these platforms.

RAG systems need a retrieval step to find relevant documents before the LLM generates a response. A local search index stores and searches a curated corpus of documents on the developer's own infrastructure. This provides zero-latency, zero-cost, and fully private retrieval, but only over the documents that have been indexed. For questions that go beyond the local corpus, a hybrid approach combines local search with a live search API. The local index handles known-domain queries (company docs, product catalog, historical data), while the search API handles open-domain queries (competitor info, current events, public sentiment). Scavio's API serves as the live search layer in this architecture, complementing rather than replacing the local index.

Local Search Index for RAG

Start using Scavio to work with local search index for rag across Google, Amazon, YouTube, Walmart, and Reddit.