Configuration

Complete guide to configuring Almanac for local development with Docker containers.

Environment Variables

All configuration is done through environment variables in packages/server/.env.

Quick Setup

cd packages/server
cp .env.example .env
# Edit .env with your settings

Local Development with Docker

Almanac uses Docker Compose to run all required services locally. No production/cloud services needed!

Starting Services

# Start only databases (MongoDB, Redis, Qdrant, Memgraph)
docker compose up -d

# Start everything including server and client
docker compose --profile app up -d

Local Services

The following services run in Docker containers:

• MongoDB (port 27017): Document database

• Redis (port 6379): Cache and session storage

• Qdrant (port 6333): Vector database for embeddings

• Memgraph (port 7687): Graph database for entities and relationships

• Server (port 3000): API server (when using --profile app)

• Client (port 5173): Web UI (when using --profile app)

All data is persisted in .data/ directory in the project root.

LLM Configuration

Almanac requires LLM models for three purposes:

1. Chat Model: Query understanding, entity extraction, relationship extraction

2. Embedding Model: Vector embeddings for semantic search

3. Reranking Model (Optional): Improve search result relevance

OpenRouter Configuration

OpenRouter provides access to many open-source models with a simple API. Get your API key from: https://openrouter.ai/

# Get your API key from: https://openrouter.ai/
LLM_API_KEY=sk-or-v1-...
LLM_BASE_URL=

# Recommended Models
LLM_CHAT_MODEL=fireworks/models/gpt-oss-120b
LLM_EXTRACTION_MODEL=xai/grok-4-1-fast-reasoning
LLM_EMBEDDING_MODEL=openai/Qwen/Qwen3-Embedding-4B
LLM_INDEX_CONFIG_MODEL=fireworks/models/gpt-oss-120b

# Optional: Reranking
RERANKER_ENABLED=true
RERANKER_BASE_URL=https://openrouter.ai/v1/rerank
RERANKER_MODEL=deepinfra/Qwen/Qwen3-Reranker-4B

Why These Models?

• Chat: fireworks/models/gpt-oss-120b - High quality reasoning for complex queries

• Extraction: xai/grok-4-1-fast-reasoning - Fast and accurate entity/relationship extraction

• Embedding: openai/Qwen/Qwen3-Embedding-4B - Balanced quality and performance for semantic search

• Reranker: deepinfra/Qwen/Qwen3-Reranker-4B - Improved search result relevance

Database Configuration

All databases run in local Docker containers. Default configuration works out of the box!

MongoDB

MONGO_HOST=localhost
MONGO_PORT=27017
MONGO_USERNAME=admin
MONGO_PASSWORD=admin123
MONGO_DB_NAME=almanac

Docker Service: mongodb (mongo:8.2.2) Data Location: .data/mongodb/

Redis

REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_PASSWORD=
REDIS_DB=0

Docker Service: redis (redis:alpine3.22) Data Location: .data/redis/

Qdrant (Vector Database)

QDRANT_HOST=localhost
QDRANT_PORT=6333
QDRANT_API_KEY=

Docker Service: qdrant (qdrant/qdrant:v1.16.0) Data Location: .data/qdrant/ Admin UI: http://localhost:6333/dashboard

Vector Sizes by Model:

• text-embedding-3-large: 3072

• text-embedding-3-small: 1536

• qwen/qwen3-embedding-8b: 1024

• qwen/qwen3-embedding-4b: 1024

• nomic-embed-text: 768

Memgraph (Graph Database)

MEMGRAPH_HOST=localhost
MEMGRAPH_PORT=7687
MEMGRAPH_USERNAME=
MEMGRAPH_PASSWORD=

Docker Service: memgraph (memgraph/memgraph:3.7.0) Data Location: .data/memgraph/

Logging Configuration

# Log level: debug, info, warn, error
LOG_LEVEL=info

# MCP Debug Logs (full responses vs. length only)
MCP_DEBUG_LOGS=false

Performance Configuration

Concurrency

Control parallel operations for better performance:

# Database indexing concurrency
DB_INDEXING_CONCURRENCY=32

# Vector indexing concurrency
VECTOR_INDEXING_CONCURRENCY=32

# Graph extraction concurrency
GRAPH_EXTRACTION_CONCURRENCY=32

Adjust based on your system resources:

• High-end systems: 32-64

• Mid-range systems: 16-32

• Low-end systems: 8-16

Security

Encryption

Required for storing sensitive data (OAuth tokens, API keys):

# Generate a key:
node -e "console.log(require('crypto').randomBytes(32).toString('hex'))"

# Add to .env:
ENCRYPTION_KEY=your-generated-64-character-hex-string

Indexing Configuration

Entity Extraction

# Maximum entities per document (optional, no limit if not set)
MAX_ENTITIES_PER_DOCUMENT=1000

# Dynamic limit: 1 entity per X characters (optional)
# Lower value = more entities (e.g., 40 = generous)
# Higher value = fewer entities (e.g., 150 = conservative)
# ENTITY_CHARS_PER_ENTITY=40

Toxic Document Filter

Filters out documents that look like lists, bibliographies, or indexes:

# Disabled by default (may be too aggressive)
ENABLE_TOXIC_DOCUMENT_FILTER=false

Detection heuristics: >50 entities, <5 relationships, <20 char avg entity names

Data Source Sync Configuration

Sync Schedule

Almanac uses hybrid scheduling for automatic syncs:

1. On startup: Syncs data sources that missed their last scheduled sync

2. While running: Syncs all enabled data sources according to cron schedule

# Only sync data modified after this date (default: 60 days ago)
# SYNC_CUTOFF_DATE=2025-12-01T00:00:00.000Z

# Maximum records to sync per data source (optional, no limit by default)
# SYNC_MAX_RECORDS=1000

# Cron schedule for automatic syncs (default: daily at midnight)
# SYNC_CRON_SCHEDULE=0 0 * * *

Cron Schedule Examples:

• 0 * * * * - Every hour

• 0 0 * * * - Every day at midnight (DEFAULT)

• 0 */6 * * * - Every 6 hours

• 0 0 * * 0 - Every Sunday at midnight

Note: Times are interpreted in your local server timezone.

OAuth Configuration (Optional)

For data sources requiring OAuth (Slack, GitHub, Notion), you'll need to:

1. Create OAuth apps in each service

2. Add credentials to .env

3. Configure redirect URIs to point to your local server

These are only needed if you want to connect these specific data sources.

Complete Example

Here's a complete .env file for local development using OpenRouter:

# === Logging ===
LOG_LEVEL=info
MCP_DEBUG_LOGS=false

# === Local Docker Databases ===
# MongoDB
MONGO_HOST=localhost
MONGO_PORT=27017
MONGO_USERNAME=admin
MONGO_PASSWORD=admin123
MONGO_DB_NAME=almanac

# Redis
REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_PASSWORD=
REDIS_DB=0

# Memgraph
MEMGRAPH_HOST=localhost
MEMGRAPH_PORT=7687
MEMGRAPH_USERNAME=
MEMGRAPH_PASSWORD=

# Qdrant
QDRANT_HOST=localhost
QDRANT_PORT=6333
QDRANT_API_KEY=

# === LLM Configuration (OpenRouter) ===
# Get your API key from: https://openrouter.ai/
LLM_API_KEY=sk-or-v1-your-key-here
LLM_BASE_URL=

# Recommended Models
LLM_CHAT_MODEL=fireworks/models/gpt-oss-120b
LLM_EXTRACTION_MODEL=xai/grok-4-1-fast-reasoning
LLM_EMBEDDING_MODEL=openai/Qwen/Qwen3-Embedding-4B
LLM_INDEX_CONFIG_MODEL=fireworks/models/gpt-oss-120b

# === Reranker (Optional) ===
RERANKER_ENABLED=true
RERANKER_BASE_URL=https://openrouter.ai/v1/rerank
RERANKER_MODEL=deepinfra/Qwen/Qwen3-Reranker-4B

# === Security ===
# Generate with: node -e "console.log(require('crypto').randomBytes(32).toString('hex'))"
ENCRYPTION_KEY=your-64-character-hex-string-here

# === Performance ===
DB_INDEXING_CONCURRENCY=32
VECTOR_INDEXING_CONCURRENCY=32
GRAPH_EXTRACTION_CONCURRENCY=32

# === Indexing ===
MAX_ENTITIES_PER_DOCUMENT=1000
ENABLE_TOXIC_DOCUMENT_FILTER=false

# === Sync Configuration ===
# SYNC_CUTOFF_DATE=2025-12-01T00:00:00.000Z
# SYNC_MAX_RECORDS=1000
# SYNC_CRON_SCHEDULE=0 0 * * *

Docker Management

Viewing Logs

# All services
docker compose logs -f

# Specific service
docker compose logs -f mongodb
docker compose logs -f server

Stopping Services

# Stop all services
docker compose down

# Stop and remove volumes (delete all data!)
docker compose down -v

Accessing Services

# MongoDB shell
docker exec -it almanac_mongodb mongosh -u admin -p admin123

# Redis CLI
docker exec -it almanac_redis redis-cli

# Memgraph shell
docker exec -it almanac_memgraph mgconsole

Troubleshooting

Services Won't Start

# Check if ports are already in use
lsof -i :27017  # MongoDB
lsof -i :6379   # Redis
lsof -i :6333   # Qdrant
lsof -i :7687   # Memgraph

# Stop conflicting services or change ports in docker-compose.yml

Database Connection Failed

Error: Failed to connect to MongoDB

Fix: Ensure Docker containers are running:

docker compose ps
docker compose up -d

Out of Memory

Error: JavaScript heap out of memory

Fix: Reduce concurrency settings:

DB_INDEXING_CONCURRENCY=16
VECTOR_INDEXING_CONCURRENCY=16
GRAPH_EXTRACTION_CONCURRENCY=16

Qdrant Collection Issues

If you need to delete and recreate collections:

# Access Qdrant UI
open http://localhost:6333/dashboard

# Or use API
curl -X DELETE http://localhost:6333/collections/almanac

Next Steps

• Quick Start - Start using Almanac

• Installation - Detailed setup instructions

• Custom MCP Servers - Add data sources

• Query & Search - Query your data