oh-my-pi/docs/mnemosyne-memory-backend.md

Mnemosyne memory backend

Oh My Pi can use @oh-my-pi/pi-mnemosyne as a local long-term memory backend.

Set:

memory:
  backend: mnemosyne

Example:

memory:
  backend: mnemosyne
mnemosyne:
  scoping: per-project-tagged

With this backend enabled, the coding agent:

1. Opens one or more local Mnemosyne SQLite databases according to the configured bank scoping.
2. Recalls relevant memories into a <memories> block for the first model turn of a session and refreshes the base prompt if recall happens from the agent_start listener.
3. Retains completed conversation turns into the retain bank after agent turns, no more often than mnemosyne.retainEveryNTurns.
4. Adds recalled memory as extra compaction context when compaction asks the memory backend for preCompactionContext.
5. Uses the normal /memory view, /memory stats, /memory diagnose, /memory clear, and /memory enqueue commands through the shared memory backend interface.

Recalled memory is background context, not instructions. Current user messages and tool output take precedence when they conflict.

Settings

Setting	Default	Description
memory.backend	off	Set to mnemosyne to enable this backend.
mnemosyne.dbPath	agent memories dir	Optional SQLite database path.
mnemosyne.bank	project directory name	Base bank name passed to Mnemosyne; the coding-agent wrapper scopes from this base according to mnemosyne.scoping.
mnemosyne.scoping	per-project	Memory visibility mode: global = one shared bank, per-project = isolated project memory, per-project-tagged = project-local writes plus global recall visibility.
mnemosyne.autoRecall	true	Recall memory on the first turn of a session.
mnemosyne.autoRetain	true	Retain completed turns automatically.
mnemosyne.retainEveryNTurns	4	Minimum user turns between automatic retain writes.
mnemosyne.recallLimit	8	Maximum recalled memories in the prompt block.
mnemosyne.recallContextTurns	3	Prior user-bounded turns included in recall queries.
mnemosyne.recallMaxQueryChars	4000	Maximum composed recall query length.
mnemosyne.injectionTokenLimit	5000	Approximate token budget for memory prompt injection.
mnemosyne.debug	false	Enable debug logging for backend failures.
mnemosyne.noEmbeddings	false	Pass noEmbeddings to Mnemosyne and force FTS-only recall.
mnemosyne.embeddingModel	env/default	Embedding model passed to Mnemosyne.
mnemosyne.embeddingApiUrl	env/default	OpenAI-compatible embedding endpoint passed to Mnemosyne.
mnemosyne.embeddingApiKey	env/default	Embedding API key passed to Mnemosyne.
mnemosyne.llmMode	smol	smol uses the configured pi-ai smol model, remote uses the settings below, and none disables LLM calls.
mnemosyne.llmBaseUrl	env/default	OpenAI-compatible LLM endpoint for llmMode: remote.
mnemosyne.llmApiKey	env/default	LLM API key for llmMode: remote.
mnemosyne.llmModel	env/default	LLM model id for llmMode: remote.

Scoping

The coding-agent wrapper applies scoping on top of the underlying Mnemosyne package:

• global uses one shared bank for recall and writes.
• per-project writes to and recalls from a bank derived from the current git repository root (or cwd) plus a stable hash.
• per-project-tagged writes to the project-local bank and recalls from both the project-local bank and the shared global bank, with duplicate recall results merged.

The combined project-plus-global behavior lives in the wrapper. The @oh-my-pi/pi-mnemosyne package itself still exposes banks and constructor options directly, including bank for selecting a bank name. Project-local banks other than the shared bank are stored as sibling bank databases managed by Mnemosyne's BankManager.

LLM and embeddings

The backend passes these settings to the Mnemosyne constructor; if a setting is omitted, Mnemosyne falls back to its MNEMOSYNE_* environment defaults. The backend does not download or run a local GGUF LLM. LLM-dependent paths use a configured pi-ai model, a dynamic completion function, a remote OpenAI-compatible endpoint, or deterministic no-LLM fallbacks.

FTS-only:

memory:
  backend: mnemosyne
mnemosyne:
  noEmbeddings: true

Equivalent constructor shape:

new Mnemosyne({ noEmbeddings: true });

Remote embeddings:

mnemosyne:
  embeddingModel: text-embedding-3-small
  embeddingApiUrl: https://api.openai.com/v1
  embeddingApiKey: ${OPENAI_API_KEY}

Equivalent constructor shape:

new Mnemosyne({
  embeddingModel: "text-embedding-3-small",
  embeddingApiUrl: "https://api.openai.com/v1",
  embeddingApiKey,
});

Remote LLM:

mnemosyne:
  llmMode: remote
  llmBaseUrl: https://api.openai.com/v1
  llmApiKey: ${OPENAI_API_KEY}
  llmModel: gpt-4.1-mini

Equivalent constructor shapes:

new Mnemosyne({ llm: { baseUrl, apiKey, model } });
new Mnemosyne({ llmBaseUrl: baseUrl, llmApiKey: apiKey, llmModel: model });

Dynamic function LLM for rotating OAuth tokens:

new Mnemosyne({
  llm: async (prompt, opts) => {
    const token = await getFreshOauthToken();
    return await completeWithPiAi(prompt, {
      token,
      maxTokens: opts?.maxTokens,
      temperature: opts?.temperature,
    });
  },
});

pi-ai smol model LLM:

mnemosyne:
  llmMode: smol

The coding agent resolves its configured smol role and passes a dynamic completion function so every Mnemosyne LLM call can fetch the current provider credentials at call time:

new Mnemosyne({
  llm: async (prompt, opts) => completeSmolWithCurrentAuth(prompt, opts),
});

Operational notes

• The default shared database lives under the agent memories directory in mnemosyne/mnemosyne.db; project-scoped banks use sibling database paths under that Mnemosyne directory.
• /memory clear removes every scoped Mnemosyne SQLite database and sidecar WAL/SHM files for the active configuration.
• /memory enqueue forces retention of the current session, flushes pending fact extractions, and runs Mnemosyne sleep/consolidation.
• /memory stats and /memory diagnose render backend-specific bank statistics/diagnostics when the Mnemosyne backend is active.
• Subagents do not own separate Mnemosyne retain loops; they alias the parent state when a parent Mnemosyne state exists, and otherwise remain inert.