clef-compactor

Query-aware RAG context compaction using Cloudflare's Clef.

Your retrieval pipeline returns 12 chunks. Your LLM reads all of them. You pay for all of them. clef-compactor scores each document against the query using Clef's 64k context window and cuts the noise.

Delete, do not rewrite. Documents are kept verbatim or removed with an auditable reason. Never summarized.

Quick start

pip install clef-compactor
export CLEF_ACCOUNT_ID=your_id
export CLEF_API_TOKEN=your_token

from clef_compactor import ClefCompactor

compactor = ClefCompactor()
result = compactor.compact(
    question="What is the refund policy?",
    documents=retrieved_chunks,
    token_budget=1000,
)
# result.kept: documents that survived
# result.dropped: [{doc, score, reason}] for the ones cut
# result.total_output_tokens < result.total_input_tokens

CLI

clef-compact -q "refund policy" -d "doc1..." "doc2..." --budget 1000

Why Clef for compaction?

Clef's 64k context window means you can score more documents in a single pass than with laya (32k). The quality is higher (BFCL 98.76 vs laya's 38.13), which means fewer false positives when scoring document relevance.

For sub-10ms local compaction, see laya-compactor.

License

Apache 2.0