HectorSin fbead80a36 docs: setup documentation structure for i18n (en/ko)

Signed-off-by: HectorSin <kkang15634@ajou.ac.kr>

2026-01-14 12:17:24 +09:00

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FalkorDB

Use FalkorDB as both a graph and vector store (hybrid store) through a community-maintained adapter

FalkorDB is an open-source graph database optimized for GraphRAG. It supports both cloud-hosted and self-hosted deployments.

Cognee can use FalkorDB as both a [vector store](/setup-configuration/vector-stores) and a [graph store](/setup-configuration/graph-stores) backend through this [community-maintained](/setup-configuration/community-maintained/overview) [adapter](https://github.com/topoteretes/cognee-community/tree/main/packages/hybrid/falkordb).

Installation

This adapter is a separate package from core Cognee. Before installing, complete the Cognee installation and ensure your environment is configured with LLM and embedding providers. After that, install the adapter package:

uv pip install cognee-community-hybrid-adapter-falkor

Configuration

Run a local FalkorDB instance:

docker run -p 6379:6379 -p 3000:3000 -it --rm falkordb/falkordb:edge

Configure in Python:

from cognee_community_hybrid_adapter_falkor import register
from cognee import config

config.set_vector_db_config(
        {
            "vector_db_provider": "falkor",
            "vector_db_url": "localhost",
            "vector_db_port": 6379,
        }
    )
config.set_graph_db_config(
    {
        "graph_database_provider": "falkor",
        "graph_database_url": "localhost",
        "graph_database_port": 6379,
    }
)

Or via environment variables:

VECTOR_DB_PROVIDER="falkor"
VECTOR_DB_URL="http://localhost:6379"
VECTOR_DB_KEY=""

GRAPH_DATABASE_PROVIDER="falkor"
GRAPH_DATABASE_URL="localhost"
GRAPH_DATABASE_PORT="6379"

Important Notes

Import `register` from the adapter package before using FalkorDB with Cognee. This registers the adapter with Cognee's provider system. Ensure `EMBEDDING_DIMENSIONS` matches your embedding model. See [Embedding Providers](/setup-configuration/embedding-providers) for configuration.

Changing dimensions requires recreating collections or running prune.prune_system().

Resources

Official documentation GitHub repository FAQ docs assistant example. Official vector providers All community integrations Configuration guide

To find navigation and other pages in this documentation, fetch the llms.txt file at: https://docs.cognee.ai/llms.txt

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