Local Vector Memory

Store, search, and manage local vector memories using Ollama embeddings with Qdrant, supporting Chinese and English text without cloud dependencies.

Local Vector Memory Skill

Zero-cloud vector memory using Ollama embeddings + Qdrant local storage.

Prerequisites

bash

# Ollama with embedding model
ollama pull qwen3-embedding:4b

# Install the package
pip install local-vector-memory

Quick Reference

bash

lvm init                    # Initialize database
lvm add "text to remember"  # Store a memory
lvm search "query"          # Semantic search
lvm search "query" --limit 3 --json  # Structured output
lvm stats                   # Show stats
lvm reindex --dir ~/notes   # Reindex markdown files
lvm delete "source_name"    # Delete by source

Python Library Usage

python

from local_vector_memory.core import LocalVectorMemory

lvm = LocalVectorMemory()  # uses env defaults
lvm.add("OpenClaw baseUrl must not end with /v1")
results = lvm.search("how to configure ollama")
for r in results:
    print(f"[{r['score']}] {r['source']}: {r['text'][:100]}")

Configuration

Env Var	Default	Description
LVM_OLLAMA_URL	http://localhost:11434	Must be localhost (SSRF protected)
LVM_MODEL	qwen3-embedding:4b	Embedding model
LVM_DIMS	2560	Vector dimensions
LVM_DB_PATH	~/.local-vector-memory/qdrant	Storage path
LVM_CHUNK_SIZE	400	Chunk size in chars
LVM_CHUNK_OVERLAP	50	Overlap between chunks

Embedding Model Selection

Model	Dims	Size	Chinese Hit Rate	Best For
qwen3-embedding:4b	2560	~2.5GB	100%	Chinese/English mixed
bge-m3	1024	~570MB	40%	Multilingual, low RAM
nomic-embed-text	768	274MB	30%	English-only, minimal RAM

Integration Patterns

With OpenClaw

Add to HEARTBEAT.md or cron for periodic reindexing:

bash

lvm reindex --dir ~/.openclaw/workspace/memory

As a backup search layer

When memory_search doesn't find what you need:

bash

lvm search "query" --json

Security

• Ollama URL restricted to localhost only (SSRF protection)
• Path traversal blocked in reindex glob patterns
• Input length limits enforced (100K text, 10K query)
• All data stored locally, no network calls except to local Ollama

Links

• PyPI: https://pypi.org/project/local-vector-memory/
• GitHub: https://github.com/JanCong/local-vector-memory