microsoft/synthetic-rag-index
Service to import data from various sources and index it in AI Search. Increases data relevance and reduces final size by 90%+. Useful for RAG scenarios with LLM. Hosted in Azure with serverless architecture.
This service helps businesses transform large collections of documents like PDFs, images, and Office files into a highly relevant and compact dataset for AI search. It intelligently processes your raw data, reducing its size by over 90% while ensuring the most important information is easily searchable. This is ideal for knowledge managers, data scientists, or anyone building AI-powered question-answering systems.
No commits in the last 6 months.
Use this if you need to create a highly efficient and relevant search index from diverse document formats for use in AI-driven applications, especially for retrieving answers from large bodies of text.
Not ideal if you require a production-ready solution today, as this project is currently a proof-of-concept for demonstrating serverless AI search capabilities.
Stars
36
Forks
11
Language
Python
License
Apache-2.0
Category
Last pushed
Oct 11, 2024
Commits (30d)
0
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