Hybrid search memory for AI agents — SQLite FTS5 + Ollama vector embeddings
Project description
Hybrid Search Memory
Keyword (BM25) + vector (cosine similarity) search over memory files and workspace documents.
Usage
# Search (hybrid mode by default — falls back to keyword-only if Ollama is down)
uv run python skills/hybrid-memory/scripts/hybrid_cli.py search "query text"
uv run python skills/hybrid-memory/scripts/hybrid_cli.py search "query" --mode keyword
uv run python skills/hybrid-memory/scripts/hybrid_cli.py search "query" --mode vector
# Ingest all memory files + TOOLS.md/MEMORY.md/AGENTS.md
uv run python skills/hybrid-memory/scripts/hybrid_cli.py ingest-memory
# Ingest a directory
uv run python skills/hybrid-memory/scripts/hybrid_cli.py ingest --path memory/ --pattern "*.md"
uv run python skills/hybrid-memory/scripts/hybrid_cli.py ingest --path memory/ --incremental
# Store a single document
uv run python skills/hybrid-memory/scripts/hybrid_cli.py store --doc-id ID --text "content"
uv run python skills/hybrid-memory/scripts/hybrid_cli.py store --doc-id ID --file path/to/file.md
# Other
uv run python skills/hybrid-memory/scripts/hybrid_cli.py delete --doc-id ID
uv run python skills/hybrid-memory/scripts/hybrid_cli.py reindex
uv run python skills/hybrid-memory/scripts/hybrid_cli.py stats
When to Use
- Hybrid search: exact keyword matches + semantic similarity. Best for credential lookups, config values, specific terms.
- Tiered memory: LLM-powered tree navigation. Best for broad semantic questions, "what happened last week".
Use hybrid search first (fast, precise), fall back to tiered memory if results are insufficient.
Architecture
- Chunker: Markdown-aware splitting with heading context, configurable size/overlap
- FTS5: SQLite full-text search with BM25 ranking
- Vector: Ollama
nomic-embed-textembeddings + cosine similarity - Merger: Weighted combination (keyword=0.3, vector=0.7), normalization, deduplication
Gracefully degrades to keyword-only when Ollama is unavailable.
Config
Edit config.json or pass CLI flags. DB stored in data/hybrid_search.db.
Project details
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