Core methodology
UltraRAG utilizes the innovative RAGEval evaluation system to achieve multi-dimensional reliability assurance:
- Multi-stage assessment mechanisms: Three phases of validation including pre-processing assessment, retrieval quality assessment, and generation effectiveness assessment
- Multidimensional indicator system: Simultaneously measure 12 core metrics such as retrieval recall, generation relevance, factual accuracy, etc.
- Adversarial testing: Built-in noise injection and counter sample test module to verify system anti-jamming capability
Operation Guide
- Select the "RAGEval Evaluation" module in the WebUI.
- Upload a test dataset or use the built-in benchmark dataset
- Configure the evaluation parameters (it is recommended to use the default presets for the first time)
- View the three-color visualization report after initiating the assessment:
- Green indicates passing threshold
- Yellow alerts potential risks
- Critical defects are marked in red
Optimization Recommendations
For common problems: when yellow/red indicators appear, the system will automatically recommend the corresponding fine-tuning strategy, and users can quickly iterate through the "one-click optimization" function.
This answer comes from the articleUltraRAG: A One-Stop RAG System Solution to Simplify Data Construction and Model Fine-TuningThe
May not be reproduced without permission:AI productivity tools " How to improve the assessment robustness and result credibility of RAG systems?
