Hey community,
I've been experimenting with a cool technique to improve the quality of my agent's outputs.
The idea is simple: using a second LLM to evaluate the output of your base LLM. This helps ensure the quality and correctness of the AI's responses.
How It Works:
1. Send a prompt to LLM
2. Take that output and send it to a "judge" LLM
3. The judge evaluates the response based on criteria like relevance, coherence, and accuracy
Benefits-
- Improved output quality
- Automated evaluation process
- Detailed feedback for iterative improvements
- Easy integration with Portkey's API
I've created a GitHub repo with the full code and setup instructions. Check it out: https://git.new/PortkeyLLMasJudge
Has anyone else tried similar techniques for improving LLM outputs? I'd love to hear your thoughts and experiences!
[link] [comments]