prane-eth/iRAT

Replanning and Controlled Retrieval for Robust LLM Reasoning

25
/ 100
Experimental

This tool helps AI developers create more reliable and accurate AI systems using Large Language Models (LLMs). It takes a reasoning problem or query as input and produces a robust, verified answer by using advanced techniques to ensure the LLM's thought process is sound and factual. It's designed for AI researchers and engineers building and refining LLM-powered applications.

No commits in the last 6 months.

Use this if you are developing or fine-tuning AI applications and need to improve the logical consistency and factual accuracy of your LLM's responses, especially for complex, multi-step reasoning tasks.

Not ideal if you are an end-user looking for a ready-to-use application, as this project is a developer tool for building more robust LLM systems.

AI development LLM engineering natural language processing AI model reliability AI reasoning
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 4 / 25
Maturity 11 / 25
Community 8 / 25

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Last pushed

Sep 25, 2025

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