Commit Graph

1 Commits

Author SHA1 Message Date
leetcrypt
e5e1ad8dee feat(ai): in-RAM semantic recall (RAG) for conversation context
Give the agent recall of things said beyond the verbatim window, without
breaking the RAM-only philosophy — nothing is persisted to disk.

- MemoryIndex: a capped, in-memory pool of embedded messages with pure-Python
  cosine search (no numpy). Retains far more than the rolling transcript so old
  lines can be surfaced on demand; oldest evicted past the cap to bound RAM.
- OllamaEmbedder: local embeddings via nomic-embed-text, on by default and
  independent of the chat provider (reuses the Ollama host when chat is Ollama).
- Bridge: captured room messages (live + backfilled) are embedded on a
  background worker so a slow embedder can't stall frame draining. On a /ai
  question the agent retrieves top-k relevant lines, drops weak (<min_score) and
  windowed-duplicate hits, and prepends them as a clearly-fenced "recalled
  context" preamble — kept at user role, never elevated to system, so untrusted
  room text informs without instructing. Falls back to recency-only if the
  embedder is unreachable.
- CLI: --no-rag, --embed-model, --embed-host, --rag-top-k.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-06-02 17:59:01 -07:00