LightRAG Tuning — 2026-05

LightRAG Tuning — May 2026

Last Updated: 2026-05-12 (MC #100467)
Status: LIVE

Current Config (LIVE as of 2026-05-12 21:13)

Why These Values

AgentForge audit (Chip Huyen lens, MC #100451) identified 2 quick-win retrieval optimizations:

• Cosine 0.5: Industry standard for 768-dim embeddings (bge-m3). Filters false-positive chunks that pollute LLM context with noise. Expected: 8-12% token savings per query.
• Chunks 10: Broader context window for multi-faceted queries (e.g., "explain Pillar #9 DR strategy"). Reduces re-query loops when 5 chunks = incomplete answer. Expected: 6-10% fewer re-queries.

Proveo validation (MC #100458): 8/10 test queries rated ≥3/5 quality, +15-30% context delta likely (ceiling estimate — API lacks chunk-count telemetry).

What We Did NOT Touch (and Why)

Forbidden changes until MC #100009 backlog stabilization ships:

• embedding_batch_num: 10 — raising risks OOM on bge-m3 (already at memory ceiling)
• max_parallel_insert: 2 — parallelism = more heap pressure
• max_async: 4 — async I/O ceiling, won't help if bottleneck = compute
• embedding_model switch (e.g., to smaller all-MiniLM-L6-v2) — would BREAK all existing embeddings, require full re-index

Reason: These params affect the ingest pipeline. LightRAG already has 121K doc backlog + memory pressure. Retrieval-tuning (cosine, chunks) is safe because it's query-time only.

Validation Summary

Proveo 10-query test suite (MC #100458):

Proveo verdict: REQUEST_CHANGES (functional pass, but lacks chunk-count telemetry to machine-verify actual cost impact)

Open Work

• MC #100467: This documentation (COMPLETE)
• MC #100468: TEI reranker investigation (bge-reranker-base unavailable in Ollama) — highest ROI optimization (15-30% quality lift) deferred
• MC #100469: API chunk-count telemetry (add chunks_retrieved to /query response for cost verification)

How to Verify Live State

curl -s http://localhost:9621/health | jq .configuration
# Look for: cosine_threshold=0.5, related_chunk_number=10, enable_rerank=false

Evidence snapshots:

• Before: /tmp/lightrag-baseline-100458-raw.json
• After: /tmp/lightrag-postverify-100458.json

How to Revert (If Needed)

cd /Users/makinja/system/docker/lightrag

# Revert .env
sed -i '' '/# Retrieval Tuning/,+3d' .env

# Revert compose
git checkout docker-compose.yml  # or manual edit if not git-tracked

# Recreate container
docker compose down && docker compose up -d lightrag

# Verify restoration
curl -s http://localhost:9621/health | jq '.configuration.cosine_threshold, .configuration.related_chunk_number'
# Expected after rollback: 0.2, 5

Related Resources

• ADR-026: ~/system/specs/adr-026-lightrag-tuning-2026-05-12.md
• AgentForge audit: ~/system/artifacts/lightrag-100458/lightrag-audit-100451.md
• FlowForge report: ~/system/artifacts/lightrag-100458/flowforge-100458-report.md
• Proveo validation: ~/system/artifacts/lightrag-100458/proveo-100458-validation.md