Commit Graph
5 Commits
Author SHA1 Message Date
Cameron CordesandClaude Opus 5.5 070f20b295 feat(embeddings): record the embedding contract and refuse a mismatched config (#189)
Stored vectors are only searchable with the backend, model, width and
prefixes that built them, and nothing enforced that: changing [embedding]
(or backend) without reembed_embeddings silently broke similarity search,
and the per-row dim check missed same-width model or prefix swaps.

- embedding_contract: one row (backend, model, dim, both prefixes). The
  server checks it once after migrations; the src/bin tools check it on
  their first embed. No row yet = record the running config.
- On a mismatch every embed (embed_many, so queries and documents) fails
  with a message naming each changed field and the fix. Mixing vector
  spaces corrupts the corpus for good; refusing only pauses semantic
  search until the config is put back or the corpus re-embedded.
- reembed_embeddings bypasses the guard and records the contract after a
  full run (all four tables, no --limit, not --dry-run).
- A DB error in the check leaves embedding allowed and is logged.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-11-03 12:06:54 -05:00
Cameron CordesandClaude Opus 5.5 09b9e87396 docs: document llm.toml and llama-swap metadata discovery
README, CLAUDE.md and .env.example now point at llm.toml for LLM settings
(OPENROUTER_API_KEY stays in env) and describe the legacy env override
window, the discovered picker and the startup cross-check. ADR-0003 records
the move and amends ADR-0002's deployment-config home; CONTEXT.md's
Deployment config / Hard default entries follow. Source comments and the
"set LLAMA_SWAP_URL" error strings name the llm.toml keys.

Also fixes README's AGENTIC_MAX_ITERATIONS default (10 -> 12, what the
code uses).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-26 17:40:42 -04:00
Cameron CordesandClaude Opus 5.5 aa3536afee refactor(ai): read LLM settings from LlmConfig instead of env
Every LLM env reader now goes through ai::config::llm_config():
build_ollama / build_llamacpp / build_openrouter take config sections
(OPENROUTER_API_KEY is still read from env), and the backend switch,
embedding dim + prefixes, Ollama / llama.cpp / TTS timeouts, TTS voice and
ref length, agentic caps, chat turn timeout and the unified-search model
read their sections. LocalLlm::from_env -> from_config; the
test_daily_summary and populate_knowledge bins take Ollama defaults from
the config. env_max_iterations / env_default_num_ctx are renamed to
max_chat_iterations / default_num_ctx.

The picker still uses picker.include (= LLAMA_SWAP_ALLOWED_MODELS) until
discovery lands. Legacy env vars keep working through the config's
override layer; checked against the deployed .env, which resolves to the
same values. The LLM_BACKEND parsing tests move to ai::config.

llm.example.toml now leaves the embed prefixes empty: copying the
nomic prefixes onto a corpus embedded without them breaks search.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-26 17:30:24 -04:00
Cameron CordesandClaude Fable 5 efd05db523 Make the embedding model swappable via env for A/B testing
Trialing Qwen3-Embedding-0.6B (1024-dim, instruct-prefixed queries)
against nomic required code changes at every hardcoded seam; now it's a
config flip plus a reembed_embeddings run.

- EMBEDDING_DIM env (default 768) replaces every hardcoded dim check:
  daily summary / calendar / search / location DAOs, Ollama batch
  validation, reembed_embeddings
- entities gains the dim guard it never had — a wrong-dim vector
  silently kills dedup/recall (cosine over mismatched lengths is 0),
  so store None and warn instead
- embed_query / embed_document split with EMBED_QUERY_PREFIX /
  EMBED_DOCUMENT_PREFIX (literal \n expanded): retrieval models treat
  the two sides differently — nomic wants search_query:/search_document:,
  Qwen3 wants Instruct:...\nQuery: on queries only. All query-side
  call sites and all corpus writers now declare their side.
- document the contract in CLAUDE.md: change the model or any of these
  vars → re-run reembed_embeddings or search is garbage

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-06-11 21:40:40 -04:00
Cameron CordesandClaude Fable 5 a022a3d15d Fix RAG vector-space mismatch and search_rag retrieval quality
Queries embedded via llama-swap were searching corpora embedded via
Ollama (measured: spaces diverged). Introduce LocalLlm — the local
Ollama + llama-swap pair with LLM_BACKEND dispatch baked in — and route
all embedding writers through it; anything embedding via a concrete
client reintroduces the bug.

- search_rag: embed the model's query verbatim (no metadata boilerplate),
  make date optional — no time-decay when omitted, so "when did X
  happen?" queries rank purely by similarity across all time
- reembed_embeddings bin: re-embed summaries / calendar / search /
  knowledge entities via the active backend, with old-new cosine report
  per table and truncate-and-retry for inputs over the embed server's
  physical batch size
- import_calendar, import_search_history: embed through LocalLlm
- search_messages / get_sms_messages: render sender → recipient so sent
  messages are attributable to a conversation
- insight job failures: store the one-line anyhow context chain ({:#})
  instead of the Debug dump the client was shown verbatim
- serialize env_dispatch tests behind a lock (parallel-runner flake)

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-06-11 19:06:52 -04:00