project-lyra/ENVIRONMENT_VARIABLES.md

Environment Variables Reference

This document describes all environment variables used across Project Lyra services.

Quick Start

1. Copy environment templates:

   cp .env.example .env
   cp cortex/.env.example cortex/.env
   cp neomem/.env.example neomem/.env
   cp intake/.env.example intake/.env
   

2. Edit .env and add your credentials:

   • OPENAI_API_KEY: Your OpenAI API key
   • POSTGRES_PASSWORD: Database password
   • NEO4J_PASSWORD: Graph database password
   • NEOMEM_API_KEY: Generate a secure token

3. Update service URLs if your infrastructure differs from defaults

File Structure

Root .env - Shared Infrastructure

Contains all shared configuration used by multiple services:

• LLM backend options (PRIMARY, SECONDARY, CLOUD, FALLBACK)
• Database credentials (Postgres, Neo4j)
• API keys (OpenAI)
• Internal service URLs
• Feature flags

Service-Specific .env Files

Each service has minimal overrides for service-specific parameters:

• cortex/.env: Cortex operational parameters
• neomem/.env: NeoMem LLM naming convention mappings
• intake/.env: Intake summarization parameters

Environment Loading Order

Docker Compose loads environment files in this order (later overrides earlier):

1. Service-specific .env (e.g., cortex/.env)
2. Root .env

This means service-specific files can override root values when needed.

Global Variables (Root .env)

Global Configuration

Variable	Default	Description
LOCAL_TZ_LABEL	America/New_York	Timezone for logs and timestamps
DEFAULT_SESSION_ID	default	Default chat session identifier

LLM Backend Options

Each service chooses which backend to use from these available options.

Primary Backend (vLLM on MI50 GPU)

Variable	Default	Description
LLM_PRIMARY_PROVIDER	vllm	Provider type
LLM_PRIMARY_URL	http://10.0.0.43:8000	vLLM server endpoint
LLM_PRIMARY_MODEL	/model	Model path for vLLM

Secondary Backend (Ollama on 3090 GPU)

Variable	Default	Description
LLM_SECONDARY_PROVIDER	ollama	Provider type
LLM_SECONDARY_URL	http://10.0.0.3:11434	Ollama server endpoint
LLM_SECONDARY_MODEL	qwen2.5:7b-instruct-q4_K_M	Ollama model name

Cloud Backend (OpenAI)

Variable	Default	Description
LLM_CLOUD_PROVIDER	openai_chat	Provider type
LLM_CLOUD_URL	https://api.openai.com/v1	OpenAI API endpoint
LLM_CLOUD_MODEL	gpt-4o-mini	OpenAI model to use
OPENAI_API_KEY	required	OpenAI API authentication key

Fallback Backend (llama.cpp/LM Studio)

Variable	Default	Description
LLM_FALLBACK_PROVIDER	openai_completions	Provider type (llama.cpp mimics OpenAI)
LLM_FALLBACK_URL	http://10.0.0.41:11435	Fallback server endpoint
LLM_FALLBACK_MODEL	llama-3.2-8b-instruct	Fallback model name

LLM Global Settings

Variable	Default	Description
LLM_TEMPERATURE	0.7	Sampling temperature (0.0-2.0)

Database Configuration

PostgreSQL (with pgvector)

Variable	Default	Description
POSTGRES_USER	neomem	PostgreSQL username
POSTGRES_PASSWORD	required	PostgreSQL password
POSTGRES_DB	neomem	Database name
POSTGRES_HOST	neomem-postgres	Container name/hostname
POSTGRES_PORT	5432	PostgreSQL port

Neo4j Graph Database

Variable	Default	Description
NEO4J_URI	bolt://neomem-neo4j:7687	Neo4j connection URI
NEO4J_USERNAME	neo4j	Neo4j username
NEO4J_PASSWORD	required	Neo4j password
NEO4J_AUTH	neo4j/<password>	Neo4j auth string

Memory Services (NeoMem)

Variable	Default	Description
NEOMEM_API	http://neomem-api:7077	NeoMem API endpoint
NEOMEM_API_KEY	required	NeoMem API authentication token
NEOMEM_HISTORY_DB	postgresql://...	PostgreSQL connection string for history
EMBEDDER_PROVIDER	openai	Embedding provider (used by NeoMem)
EMBEDDER_MODEL	text-embedding-3-small	Embedding model name

Internal Service URLs

All using Docker container names for network communication:

Variable	Default	Description
INTAKE_API_URL	http://intake:7080	Intake summarizer service
CORTEX_API	http://cortex:7081	Cortex reasoning service
CORTEX_URL	http://cortex:7081/reflect	Cortex reflection endpoint
CORTEX_URL_INGEST	http://cortex:7081/ingest	Cortex ingest endpoint
RAG_API_URL	http://rag:7090	RAG service (if enabled)
RELAY_URL	http://relay:7078	Relay orchestration service
PERSONA_URL	http://persona-sidecar:7080/current	Persona service (optional)

Feature Flags

Variable	Default	Description
CORTEX_ENABLED	true	Enable Cortex autonomous reflection
MEMORY_ENABLED	true	Enable NeoMem long-term memory
PERSONA_ENABLED	false	Enable persona sidecar
DEBUG_PROMPT	true	Enable debug logging for prompts

Service-Specific Variables

Cortex (cortex/.env)

Cortex operational parameters:

Variable	Default	Description
CORTEX_MODE	autonomous	Operation mode (autonomous/manual)
CORTEX_LOOP_INTERVAL	300	Seconds between reflection loops
CORTEX_REFLECTION_INTERVAL	86400	Seconds between deep reflections (24h)
CORTEX_LOG_LEVEL	debug	Logging verbosity
NEOMEM_HEALTH_CHECK_INTERVAL	300	NeoMem health check frequency
REFLECTION_NOTE_TARGET	trilium	Where to store reflection notes
REFLECTION_NOTE_PATH	/app/logs/reflections.log	Reflection output path
RELEVANCE_THRESHOLD	0.78	Memory retrieval relevance threshold

Note: Cortex uses LLM_PRIMARY (vLLM on MI50) by default from root .env.

NeoMem (neomem/.env)

NeoMem uses different variable naming conventions:

Variable	Default	Description
LLM_PROVIDER	ollama	NeoMem's LLM provider name
LLM_MODEL	qwen2.5:7b-instruct-q4_K_M	NeoMem's LLM model
LLM_API_BASE	http://10.0.0.3:11434	NeoMem's LLM endpoint (Ollama)

Note: NeoMem uses Ollama (SECONDARY) for reasoning and OpenAI for embeddings. Database credentials and OPENAI_API_KEY inherited from root .env.

Intake (intake/.env)

Intake summarization parameters:

Variable	Default	Description
SUMMARY_MODEL_NAME	/model	Model path for summarization
SUMMARY_API_URL	http://10.0.0.43:8000	LLM endpoint for summaries
SUMMARY_MAX_TOKENS	400	Max tokens for summary generation
SUMMARY_TEMPERATURE	0.4	Temperature for summaries (lower = more focused)
SUMMARY_INTERVAL	300	Seconds between summary checks
INTAKE_LOG_PATH	/app/logs/intake.log	Log file location
INTAKE_LOG_LEVEL	info	Logging verbosity

Note: Intake uses LLM_PRIMARY (vLLM) by default.

Multi-Backend LLM Strategy

Project Lyra supports flexible backend selection per service:

Root .env provides backend OPTIONS:

• PRIMARY: vLLM on MI50 GPU (high performance)
• SECONDARY: Ollama on 3090 GPU (local inference)
• CLOUD: OpenAI API (cloud fallback)
• FALLBACK: llama.cpp/LM Studio (CPU-only)

Services choose which backend to USE:

• Cortex → vLLM (PRIMARY) for autonomous reasoning
• NeoMem → Ollama (SECONDARY) + OpenAI embeddings
• Intake → vLLM (PRIMARY) for summarization
• Relay → Implements fallback cascade with user preference

This design eliminates URL duplication while preserving per-service flexibility.

Security Best Practices

1. Never commit .env files to git - they contain secrets
2. Use .env.example templates for documentation and onboarding
3. Rotate credentials regularly, especially:
   • OPENAI_API_KEY
   • NEOMEM_API_KEY
   • Database passwords
4. Use strong passwords for production databases
5. Restrict network access to LLM backends and databases

Troubleshooting

Services can't connect to each other

• Verify container names match in service URLs
• Check all services are on the lyra_net Docker network
• Use docker-compose ps to verify all services are running

LLM calls failing

• Verify backend URLs are correct for your infrastructure
• Check if LLM servers are running and accessible
• Test with curl <LLM_URL>/v1/models (OpenAI-compatible APIs)

Database connection errors

• Verify database credentials match in all locations
• Check if database containers are healthy: docker-compose ps
• Review database logs: docker-compose logs neomem-postgres

Environment variables not loading

• Verify env_file paths in docker-compose.yml
• Check file permissions: .env files must be readable
• Remember loading order: service .env overrides root .env

Migration from Old Setup

If you have the old multi-file setup with duplicated variables:

1. Backup existing files: All original .env files are in .env-backups/
2. Copy new templates: Use .env.example files as base
3. Merge credentials: Transfer your actual keys/passwords to new root .env
4. Test thoroughly: Verify all services start and communicate correctly

Support

For issues or questions:

• Check logs: docker-compose logs <service>
• Verify configuration: docker exec <container> env | grep <VAR>
• Review this documentation for variable descriptions