raglite-chromadb 1.0.1

Local-first RAG-lite CLI: condense docs into structured Markdown, then index/query with Chroma + hybrid search

RAGLite

RAGLite is a local-first CLI that turns a folder of docs (PDF/HTML/TXT/MD) into structured, low-fluff Markdown — and then makes it searchable with Chroma 🧠 + ripgrep 🔎.

Core idea: compression-before-embeddings ✂️➡️🧠

What you get

For each input file:

• *.execution-notes.md — practical run/operate notes (checks, failure modes, commands)
• *.tool-summary.md — compact index entry (purpose, capabilities, entrypoints, footguns)

Optionally:

• raglite index stores embeddings in Chroma 🧠 (one DB, many collections)
• raglite query runs hybrid search 🔎 (vector + keyword)

Why local + open-source?

If you want a private, local setup (no managed “fancy vector DB” required), RAGLite keeps everything on your machine:

• Distilled Markdown artifacts are plain files you can audit + version control
• Indexing uses Chroma (open-source, local) and keyword search uses ripgrep
• You can still swap in a hosted vector DB later if you outgrow local

Engines

RAGLite supports two backends:

• OpenClaw (recommended): uses your local OpenClaw Gateway /v1/responses endpoint for higher-quality, format-following condensation.
• Ollama: uses POST /api/generate for fully local inference (often less reliable at strict templates).

Prereqs

• Python 3.11+
• An LLM engine:
  • OpenClaw (recommended) 🦞, or
  • Ollama 🦙
• For search:
  • Chroma (open-source, local) 🧠 at http://127.0.0.1:8100

Install

# from repo root
python3 -m venv .venv
source .venv/bin/activate
pip install -e .

Quickstart (60s)

# 0) Setup
cd ~/Projects/raglite
source .venv/bin/activate

# 1) Condense → Index (one command)
raglite run /path/to/docs \
  --out ./raglite_out \
  --engine ollama --ollama-model llama3.2:3b \
  --collection my-docs \
  --chroma-url http://127.0.0.1:8100 \
  --skip-indexed

# 2) Query
raglite query ./raglite_out \
  --collection my-docs \
  "rollback procedure"

Usage

1) Distill docs ✍️

raglite condense /path/to/docs \
  --out ./raglite_out \
  --engine openclaw

(Or fully local: --engine ollama --ollama-model llama3.2:3b.)

2) Index distilled output (Chroma)

raglite index ./raglite_out \
  --collection my-docs \
  --chroma-url http://127.0.0.1:8100

3) Query (hybrid)

raglite query ./raglite_out \
  --collection my-docs \
  --top-k 5 \
  --keyword-top-k 5 \
  "rollback procedure"

Useful flags

• --skip-existing : don’t redo files that already have both outputs
• --skip-indexed : don’t re-embed chunks that are already indexed
• --nodes : write per-section nodes + per-doc/root indices
• --node-max-chars 1200 : keep nodes embed-friendly
• --sleep-ms 200 : throttle between files (helps avoid timeouts)
• --max-chars 180000 : cap extracted text per file before summarizing

Output layout

RAGLite preserves folder structure under your --out dir:

<out>/
  some/subdir/file.execution-notes.md
  some/subdir/file.tool-summary.md

(Default output folder is `./raglite_out`.)

Notes / gotchas

• PDF extraction is best-effort: scanned PDFs without embedded text won’t be great.
• If you use --engine openclaw, pass --gateway-token or set OPENCLAW_GATEWAY_TOKEN.
• Indexing defaults to high-signal artifacts (nodes/summaries/notes) and skips *.outline.md unless you opt in.

Roadmap

Current (implemented)

• condense — condense/summarize documents into Markdown artifacts
• index — chunk + embed + store in Chroma collections
• query — retrieve relevant chunks (vector + keyword)
• run — one-command pipeline (condense → index)
• Outline + nodes + indices: --outline, --nodes, root index.md + per-doc *.index.md

Next (near-term)

• Detect deletions (prune removed chunks from Chroma)
• Batch upserts to Chroma for speed
• Better query output formatting (snippets + anchors)
• raglite doctor (dependency checks)

(Full: ROADMAP.md)

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Built to turn “docs” into usable, searchable tool knowledge.