Memory System

MindRoom uses Mem0 for persistent memory across conversations. Memory is automatically enabled for all agents and uses ChromaDB for semantic search.

Memory Scopes

Scope	User ID Format	Description
Agent	`agent_<name>`	User preferences, past conversations, learned context
Room	`room_<safe_room_id>`	Project context, technical decisions, shared knowledge
Team	`team_<agent1>+<agent2>+...`	Shared team conversations and findings

Notes: - Room IDs are sanitized (: → _, ! removed) for storage compatibility - Team IDs use sorted agent names joined with + - When searching agent memories, team memories are automatically included and deduplicated

Configuration

Configure memory in your config.yaml:

memory:
  embedder:
    provider: openai  # or "ollama"
    config:
      model: text-embedding-3-small
      host: null  # Optional: for self-hosted models

  llm:  # Optional: for memory extraction
    provider: openai  # or "ollama", "anthropic"
    config:
      model: gpt-4o-mini
      temperature: 0.1
      host: null  # For Ollama

The host field is converted internally to openai_base_url or ollama_base_url depending on the provider.

How Memory Works

Semantic Retrieval: Before responding, agents search for relevant memories (limit: 3 per scope)
Context Enhancement: Retrieved memories are prepended to the prompt with a note that they may not be relevant
Automatic Storage: After each conversation, Mem0 extracts and stores relevant information

Storage

Memories are stored in ChromaDB at <storage_path>/chroma/ with collection name mindroom_memories.

Mem0 Tool (Optional)

For explicit memory control, add the mem0 tool to an agent:

agents:
  assistant:
    tools: [mem0]

This provides functions: add_memory, search_memory, get_all_memories, delete_all_memories.