Principle:Truera Trulens Context Filter Guardrail
| Knowledge Sources | |
|---|---|
| Domains | Guardrails, RAG |
| Last Updated | 2026-02-14 08:00 GMT |
Overview
A runtime guardrail pattern that filters retrieved contexts based on quality scores before they reach the LLM generation step.
Description
Context Filter Guardrail implements a pre-generation quality gate in RAG pipelines. It decorates the retrieval method and evaluates each retrieved context against a feedback function. Contexts scoring below the threshold are removed before the LLM sees them.
This prevents hallucinations caused by irrelevant or low-quality retrieval results by ensuring only relevant contexts reach the generation step. The filtering is synchronous — it happens at runtime before the LLM is called.
Usage
Use this principle in RAG applications where retrieval quality varies and you want to prevent irrelevant contexts from reaching the LLM. Apply the decorator to the retrieval method. Choose a threshold based on your tolerance for filtering (higher thresholds filter more aggressively).
Theoretical Basis
Context filtering implements a quality gate pattern:
Pseudo-code Logic:
# Abstract context filtering
contexts = retrieval_method(query)
filtered = [c for c in contexts if score(query, c) > threshold]
response = llm.generate(query, filtered)
The filtering is concurrent — each context is scored in parallel using a thread pool for low latency.