Building a RAG System That Knows When It’s Wrong
📰 Medium · Python
Learn to build a RAG system with a citation gate, secondary judge, and 'I don't know' path for improved performance and transparency
Action Steps
- Build a RAG system using Python and the Hugging Face Transformers library
- Implement a microsecond-fast citation gate to filter out low-confidence responses
- Configure a cheap secondary judge to validate the primary model's outputs
- Test the system using a public evaluation set to measure performance
- Apply the 'I don't know' path to handle uncertain or unknown inputs
Who Needs to Know This
NLP engineers and researchers can benefit from this article to improve their RAG systems' accuracy and reliability
Key Insight
💡 Adding a citation gate, secondary judge, and 'I don't know' path can significantly improve a RAG system's performance and transparency
Share This
🚀 Improve your RAG system with a citation gate, secondary judge, and 'I don't know' path! 🤖
Key Takeaways
Learn to build a RAG system with a citation gate, secondary judge, and 'I don't know' path for improved performance and transparency
Full Article
How I added a microsecond-fast citation gate, a cheap secondary judge, and a real “I don’t know” path — with a public eval set so you can… Continue reading on Medium »
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