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Environment Configuration Guide

This document explains how to configure Flexible GraphRAG using environment variables and configuration files.

Configuration Files

File Purpose
.env Your main configuration file — copy from flexible-graphrag/env-sample.txt
flexible-graphrag/env-sample.txt Template with all options and inline examples

env-sample.txt Structure

The configuration file opens with DB selection and framework config, followed by per-service settings:

Section 1: DB Selection

PG_GRAPH_DB=neo4j               # Property graph: neo4j | arcadedb | falkordb | ladybug | memgraph |
                                 #   nebula | neptune | neptune_analytics | arangodb | apache_age |
                                 #   cosmos_gremlin | hugegraph | surrealdb | tigergraph | spanner | none
RDF_GRAPH_DB=none               # RDF store: fuseki | oxigraph | graphdb | neptune_rdf | none
VECTOR_DB=qdrant                # Vector: qdrant | elasticsearch | opensearch | chroma | milvus |
                                 #   weaviate | pinecone | postgres | lancedb | neo4j | none
SEARCH_DB=elasticsearch         # Search: bm25 | elasticsearch | opensearch | none

Section 2: Framework Config

CHUNKER_BACKEND=llamaindex      # llamaindex | langchain
GRAPH_BACKEND=llamaindex        # llamaindex | langchain (auto for LC-only stores)
VECTOR_BACKEND=llamaindex       # llamaindex | langchain
SEARCH_BACKEND=llamaindex       # llamaindex | langchain
KG_EXTRACTOR_BACKEND=llamaindex # llamaindex | langchain
RETRIEVAL_FUSION=llamaindex     # llamaindex | langchain (EnsembleRetriever/RRF)

Sections 3+: Service-specific settings (LLM, embeddings, graph DBs, vector DBs, etc.)

Database Configuration Patterns

Per-Store Config (Recommended)

Use {TYPE}_*_DB_CONFIG — takes precedence over generic fallbacks:

# Property graph
PG_GRAPH_DB=neo4j
NEO4J_GRAPH_DB_CONFIG={"uri": "bolt://localhost:7687", "username": "neo4j", "password": "password"}

# Vector
VECTOR_DB=qdrant
QDRANT_VECTOR_DB_CONFIG={"host": "localhost", "port": 6333}

# Search
SEARCH_DB=elasticsearch
ELASTICSEARCH_SEARCH_DB_CONFIG={"hosts": ["http://localhost:9200"], "index_name": "hybrid_search"}

# RDF
RDF_GRAPH_DB=fuseki
FUSEKI_BASE_URL=http://localhost:3030
FUSEKI_DATASET=flexible-graphrag

Individual Variables (Legacy)

NEO4J_URI=bolt://localhost:7687
NEO4J_USER=neo4j
NEO4J_PASSWORD=password
ELASTICSEARCH_URL=http://localhost:9200
QDRANT_HOST=localhost
QDRANT_PORT=6333

Easy Database Switching

# Current: OpenAI + Qdrant + Elasticsearch + Neo4j
LLM_PROVIDER=openai
VECTOR_DB=qdrant
SEARCH_DB=elasticsearch
PG_GRAPH_DB=neo4j

# Switch to: Ollama + Milvus (LC backend) + OpenSearch + ArangoDB (LC-only)
LLM_PROVIDER=ollama
VECTOR_DB=milvus
VECTOR_BACKEND=langchain
SEARCH_DB=opensearch
PG_GRAPH_DB=arangodb
# GRAPH_BACKEND auto-set to langchain for arangodb

Configuration Best Practices

Development: Start with the defaults — Neo4j for graph, Qdrant for vector, Elasticsearch for search.

Vector-only RAG (no KG extraction, faster ingest):

PG_GRAPH_DB=none
ENABLE_KNOWLEDGE_GRAPH=false
VECTOR_DB=qdrant

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