Explainability

Explainability traces model responses back to their origins—whether retrieved context in an agentic workflow or training examples from fine-tuning. This allows you to see which inputs influenced specific outputs.

The Explainability SDK provides two capabilities for understanding model outputs:

Context attribution — Identifies which retrieved sources influenced each statement in an agent's response. Works with any SeekrFlow agent that uses file search, web search, or other tools.
Training data attribution — Identifies which fine-tuning examples influenced a fine-tuned model's response.