OpenMemory/models.yml at main · CaviraOSS/OpenMemory · GitHub

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# OpenMemory Embedding Models Configuration
# Configure which models to use for each brain sector and provider
# Provider settings (URLs, API keys, etc.) are in .env

# Sector-specific model mappings
# Each sector can use different models optimized for that type of memory

episodic:
  ollama: nomic-embed-text
  openai: text-embedding-3-small
  gemini: models/gemini-embedding-001
  aws: amazon.titan-embed-text-v2:0
  local: all-MiniLM-L6-v2

semantic:
  ollama: nomic-embed-text
  openai: text-embedding-3-small
  gemini: models/gemini-embedding-001
  aws: amazon.titan-embed-text-v2:0
  local: all-MiniLM-L6-v2

procedural:
  ollama: nomic-embed-text
  openai: text-embedding-3-small
  gemini: models/gemini-embedding-001
  aws: amazon.titan-embed-text-v2:0
  local: all-MiniLM-L6-v2

emotional:
  ollama: nomic-embed-text
  openai: text-embedding-3-small
  gemini: models/gemini-embedding-001
  aws: amazon.titan-embed-text-v2:0
  local: all-MiniLM-L6-v2

reflective:
  ollama: nomic-embed-text
  openai: text-embedding-3-large
  gemini: models/gemini-embedding-001
  aws: amazon.titan-embed-text-v2:0
  local: all-mpnet-base-v2
# Available Ollama models (pull with: ollama pull <model>)
# - nomic-embed-text (768d, recommended)
# - mxbai-embed-large (1024d)
# - snowflake-arctic-embed (1024d)
# - all-minilm (384d, fast)

# OpenAI models:
# - text-embedding-3-small (1536d)
# - text-embedding-3-large (3072d)

# Gemini models:
# - models/gemini-embedding-001 (3072d native, configurable via outputDimensionality) - current GA
# - models/text-embedding-004 (768d) - deprecated, returns 404
# - models/embedding-001 (768d) - deprecated

#AWS models:
# - amazon.titan-embed-text-v2:0 (1024d, 512d, 256)