config.example.toml

[server]
host = "0.0.0.0"
port = 8080
worker_threads = 4
timeout_seconds = 60
rate_limit_per_minute = 100  # Max requests per IP per minute (can also set via MEMORYOS_RATE_LIMIT env var)

[llm]
default_provider = "openai"
default_model = "gpt-4o-mini"

# Add one or more providers below. The key (e.g. "openai") must match default_provider.
# Supported provider types: openai, gemini, claude, ollama, deepseek, openrouter, azure-openai, cohere, groq, mistral
[llm.providers.openai]
type = "openai"
base_url = "https://api.openai.com/v1"
api_key = "sk-your-openai-key"
# api_key_env = "OPENAI_API_KEY"  # Alternative: read from env var

# Example: add more providers
# [llm.providers.ollama]
# type = "ollama"
# base_url = "http://localhost:11434/v1"
# api_key = ""

# [llm.providers.deepseek]
# type = "deepseek"
# base_url = "https://api.deepseek.com/v1"
# api_key_env = "DEEPSEEK_API_KEY"

[storage.redis]
url = "redis://localhost:6379"
ttl_seconds = 3600
max_messages = 20

[storage.vector]
url = "http://localhost:6334"

# Embedding configuration (optional)
# If not configured, will use fallback simple embedding
[embedding]
# api_key = "sk-your-embedding-key"  # Or set OPENAI_API_KEY env var
# base_url = "https://api.openai.com/v1"
# model = "text-embedding-3-small"

# Authentication configuration
[auth]
enabled = false
# admin_keys = ["admin-secret-key"]  # Admin API keys for management endpoints
# api_keys = ["user-api-key-1"]      # Regular API keys for normal endpoints
# use_redis_store = false             # Use Qdrant for persistent API key storage