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Knowledge graph memory skill for haiku.skills using Graphiti and FalkorDB

Project description

graphiti-memory

Knowledge graph memory skill for haiku.skills using Graphiti and FalkorDB.

Enables agents to remember facts across conversations, recall relevant context, and forget outdated information.

Prerequisites

FalkorDB

Run FalkorDB via Docker:

docker run -p 6379:6379 -p 3000:3000 \
  -v falkordb_data:/var/lib/falkordb/data \
  falkordb/falkordb:latest
  • Port 6379 — Redis-compatible protocol (what the skill connects to)
  • Port 3000 — Web UI for browsing the graph
  • The volume mount ensures data persists across container restarts

Ollama models

The skill uses Ollama for LLM and embeddings by default. Pull the required models:

ollama pull gpt-oss
ollama pull qwen3-embedding:4b

Configuration

All configuration is via environment variables:

FalkorDB

Variable Default Description
FALKORDB_URI falkor://localhost:6379 FalkorDB connection URI. Format: falkor://[user:password@]host:port[/database]

LLM

Variable Default Description
OLLAMA_BASE_URL http://localhost:11434 Ollama server URL (shared with haiku.rag)
GRAPHITI_LLM_MODEL gpt-oss Model for entity extraction and edge resolution
GRAPHITI_SMALL_LLM_MODEL Same as GRAPHITI_LLM_MODEL Smaller model for lightweight LLM tasks

Embeddings

Variable Default Description
GRAPHITI_EMBEDDING_MODEL qwen3-embedding:4b Embedding model name
GRAPHITI_EMBEDDING_DIM 2560 Embedding vector dimensions (must match the model)

Multi-tenancy

Variable Default Description
GRAPHITI_GROUP_ID default Namespace for isolating memories between tenants/agents

Tools

  • remember — Store facts, observations, and context into the knowledge graph
  • recall — Search the knowledge graph for relevant memories
  • forget — Remove outdated or incorrect memories

Installation

uv add haiku-skills-graphiti-memory

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