Context Filter
Technical documentation page from **GPT Researcher**, *"Context Filter"*, rewritten on **September 26, 2026** by **Assaf Elovic**, the project's creator, the day he made **Jev** (a model from **TypeSafe**) the default context filter. About **2,200 words**, including a reproducible benchmark. **(A)** The design thesis: the context filter is *"the biggest lever on report quality after the research itself"*: *"what it discards, the writer never sees"*. **(B)** The mechanism: each scraped page is split into **1,000-character** chunks. Jev scores each chunk on a four-level usefulness scale (0 to 3), and only chunks at **≥ 1.5** are kept, ten at most. Without an API key, a local **BM25** fallback with a relative threshold takes over. **(C)** The benchmark: 28 tasks replayed on the same pages. **73%** relevant passages for Jev versus **46%** for embeddings, **15-10-3** in head-to-head, at the same cost (~$0.115 per report). **(D)** The most transferable finding: *"the threshold matters more than the ranking"*. Without a threshold, Jev drops back to 50%. The gain comes from less noise, not more content. Extends, on the web-search side, the comparison of retrieval strategies from [[comparethemarket-context-retrieval-ai-code-review-gkg-rag-2026-03-06]].
Assaf Elovic · créateur de GPT Researcher · auteur de la page (documentation officielle docs.gptr.dev, non signée).