Fragments now carry a memory type in metadata (legacy fragments count as
procedural) with SearchByType filtering, and EpisodeCapture summarizes a
finished turn with the local LLM and stores it as episodic memory, so the
agent can answer "what did we do yesterday?". Includes an E2E test against
a live llama.cpp server (gated) and taxonomy unit tests.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Backend.Upsert never received the fragment's Content, so ChromaDB (and
any backend) stored the vector but silently dropped the actual text —
saved memories had nothing to retrieve later. Backend.Search now also
takes the raw query text, and a failed/missing embedding no longer
hard-fails Add/Search: it degrades to a nil vector so a lexical-capable
backend can still index/find the content (Chroma has no such fallback
and now says so explicitly instead of misbehaving).
Adds pkg/rag/backends/sqlitevec: a zero-dependency backend (pure-Go
SQLite, no external service) that does cosine similarity when a real
embedding vector is available and falls back to FTS5/BM25 full-text
search otherwise. Adds pkg/rag/embeddings.OpenAICompatible, covering
both a local llama.cpp server (`--embeddings` enabled) and real OpenAI
(or any OpenAI-shaped /embeddings endpoint) through the same client.
Also fixes token usage tracking for llama.cpp streaming: the client
never requested `stream_options.include_usage` nor parsed a usage-only
SSE event, and even when present, the agent loop's RunStream dropped
any chunk with no Delta/ReasoningDelta — silently discarding the only
chunk that carries usage.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
