Files
lora/training/03_tools_memory.json
marauder-actual 0e88c3c2ae add v5 substrate training data (40 examples)
Manual hand-crafted examples for generic substrate LoRA:
- 01: identity/self-model
- 02-18: tool categories (159 tools grouped by function)
- 19-26: tricky tool disambiguation
- 27-32: framing (substrate vs persona, HMT, psychoacoustic trust)
- 33-40: EEMS deep-dive (architecture, recall, store, graph, legacy)

Pretty-printed JSON, compiled to JSONL via build pipeline.
System prompt uses generic assistant, not BT persona.
2026-05-31 14:32:19 +02:00

17 lines
2.0 KiB
JSON

{
"messages": [
{
"role": "system",
"content": "You are a helpful AI assistant with access to tools. Use tools when they help answer the user's question. Be concise and accurate."
},
{
"role": "user",
"content": "How does the memory system work?"
},
{
"role": "assistant",
"content": "<think>\nEEMS memory system — the primary persistent memory store. Cover the tool surface and how recall works.\n</think>\n\nThe memory system is EEMS — a semantic memory store backed by SQLite with FTS5 full-text search and vector embeddings for similarity matching. Eight tools:\n\n- **memory_recall** — hybrid search: FTS5 keyword + vector cosine similarity fused via Reciprocal Rank Fusion (RRF). Filter by subject or namespace. This is the primary retrieval tool.\n- **memory_store** — persist a memory with subject (dot-namespaced category like `infra.network` or `doctrine.training`) and content. Automatically embeds for future semantic recall.\n- **memory_list** — list all subjects with entry counts. Use to discover what knowledge categories exist before recalling.\n- **memory_get** — fetch full memory records by ID with no truncation.\n- **memory_classify** — promote a memory to core classification (immutable, irreversible). Core memories survive any cleanup.\n- **memory_forget** — delete a memory by ID.\n- **memory_link** — create a relationship edge between two memories. Relations: related_to, depends_on, contradicts, extends, supersedes.\n- **memory_graph** — explore the neighborhood of a memory, showing connected memories up to N hops.\n\nTypical workflow: `memory_list` to see what exists, `memory_recall` with a query to find relevant memories, `memory_store` to persist new knowledge. Subjects use dot-namespacing: `infra.*` for infrastructure, `doctrine.*` for patterns, `project.*` for project-specific knowledge, `user.*` for operator preferences.\n\nMemories have confidence scores (0.0-1.0) and two classifications: standard (deletable) and core (immutable, identity-grade)."
}
]
}