Local RAG

Semantic search over indexed local files with parent-child chunking for precise retrieval with full context.

Architecture

Memory strategy: Embedding model loaded first → freed with gc.collect() → reranker loaded → freed after scoring. This keeps peak RAM ~400MB on ARM.

Chunking Strategy

• Child chunks: 128 words, 24 overlap → embedded for semantic search
• Parent chunks: 768 words → stored as full context, returned to user
• When a child matches → its parent is returned, giving surrounding context

Running

All scripts must use the venv Python:

VENV=~/.local/share/local-rag/venv/bin/python

Indexing

# Incremental index (default — skips unchanged files via SHA-256 hash)
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/index.py

# Re-index from scratch
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/index.py --reindex

# Custom paths
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/index.py --paths ~/Documenti ~/Progetti

# Batch indexing (per-subfolder with git checkpoints, for low-RAM systems)
bash ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/index-batch.sh

Querying

# Basic query
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/query.py "what are the termination clauses?"

# More results
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/query.py "Falcon LLM" --top-k 30 --top-n 5

# JSON output for programmatic use
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/query.py "transformer architecture" --json

# With timeout
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/query.py "deep learning" --timeout 60

Options:

• --top-k N — Child candidates from vector search (default: 20)
• --top-n N — Final parent results after reranking (default: 3)
• --json — JSON output
• --timeout N — Max seconds per query (default: 120)

Monitoring

$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/monitor.py              # Status
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/monitor.py --watch      # Auto-refresh
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/monitor.py --log        # Logs
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/monitor.py --errors     # Errors only
$VENV ~/.openclaw/workspace/skills/lookupmark-local-rag/scripts/monitor.py --git        # Git checkpoints

Supported Formats

Documents only (no code files):

• Text: .txt, .md, .csv, .json, .yaml, .yml, .toml, .tex, .bib
• Documents: .pdf (pdfminer.six), .docx (python-docx), .pptx

Excluded: .py, .js, .sh, .ipynb, .html, .css and all code files.

Limits (for 4GB ARM)

• PDF max size: 5MB (larger PDFs cause OOM with pdfminer)
• Max file size: 30MB
• Embedding batch size: 1 (conservative)
• Excluded dirs: .git, .venv, node_modules, __pycache__, labs, exercises, src, scripts, ablation, test*, fixtures

Storage

Security

• ALLOWED_ROOTS: Only ~/Documenti/github/thesis, ~/Documenti/github/polito, ~/Documenti, ~/Scaricati
• BLOCKED_PATTERNS: .ssh, .gnupg, .env, credentials, tokens, .config/openclaw
• Credentials directory is blacklisted — never indexed

Workflow

1. Run index.py — builds/rebuilds the index (incremental via SHA-256 hash check)
2. Run periodically to pick up new/changed files (daily cron recommended)
3. Use query.py to search with natural language
4. Results include: file path, relevance score, matched snippet, full parent context
5. Check monitor.py for stats and queries.log for query history