steve
2030976b85
- Add configurable device selection for embeddings (embedding.device) and Docling ingestion (ingestion.device) with env var overrides (KB_DEVICE, KB_INGEST_DEVICE) to control GPU/CPU usage per component - Add `kb doctor` command for safe GPU diagnostics - Add Dockerfile (NVIDIA CUDA) and compose.yaml for containerised GPU usage - Add OpenSpec v2 change (kb-v2-client-server): proposal, design, specs, and tasks for client-server architecture with Go CLI, FastAPI engine, async ingestion queue, and GPU-vendor-agnostic Docker deployment - Add uv.lock for reproducible installs - Gitignore examples/ directory (test data only) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
kb-search
CLI knowledge base with hybrid search (full-text + semantic vector search).
Install
pipx install kb-search
Quickstart
# Initialise (downloads embedding model ~90MB)
kb init
# Add documents
kb add ~/docs/manual.pdf --tags admin
kb add ~/notes/ --recursive
kb add --note "Always restart nginx after config changes" --tags ops
# Search
kb search "how to install git"
kb search "deploy process" --tags ops --type pdf
kb search "authentication" --format human
# Manage
kb list --format human
kb tags
kb status
How it works
- Ingestion: Documents are chunked (PDFs via Docling, markdown by headers, code by AST/functions) and embedded locally
- Storage: Everything in a single SQLite database (
~/.kb/kb.db) using FTS5 for keyword search and sqlite-vec for vector search - Search: Hybrid retrieval combining BM25 keyword scoring and vector similarity via Reciprocal Rank Fusion
- Output: JSON (for LLM tool use) or human-readable terminal format
Configuration
Optional YAML config at ~/.kb/config.yaml. Works with zero configuration.
kb config # View current config
kb config set chunking.pdf.max_tokens 2048 # Change a value
ENV overrides: KB_DATA_DIR, KB_MODEL, KB_DEFAULT_TOP, KB_DEFAULT_FORMAT
Claude Code Skill
This tool is designed to be wrapped as a Claude Code skill. See SKILL.md for the skill definition.