yhoshi3/RaLLe
RaLLe: A Framework for Developing and Evaluating Retrieval-Augmented Large Language Models
This tool helps AI researchers and developers working with Large Language Models (LLMs) to quickly build, test, and refine their Retrieval-Augmented LLM (R-LLM) applications. It takes various LLMs and data retrieval methods as input, allowing you to combine them, and outputs performance metrics and prompt insights to optimize your R-LLM's effectiveness. The target user is an AI/ML practitioner focused on improving how LLMs access and use external information.
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Use this if you are developing R-LLMs and need a straightforward way to experiment with different retrieval mechanisms, LLM backends, and prompt strategies, then objectively evaluate their performance.
Not ideal if you are an end-user simply looking to apply an existing R-LLM solution, rather than actively developing or evaluating one.
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55
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4
Language
Python
License
MIT
Category
Last pushed
Oct 16, 2023
Commits (30d)
0
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