main.rs re-declared nearly every module (`mod ai; mod database; …`)
that lib.rs also declared, so the ~100k-line crate compiled twice in
every build (lib for the src/bin tools, bin for the server) and the
test suite ran most tests twice. watcher.rs even reached into the lib
copy via `image_api::` from inside the bin copy.
The six bin-only modules (backfill, handlers, hls_stats, knowledge,
reels, watcher) move into lib.rs; main.rs keeps only startup wiring
over `use image_api::…`. A few items main calls become `pub`, and the
dead_code allowances that only existed because each copy saw half the
callers are gone. CLAUDE.md says not to reintroduce `mod` in main.rs.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
LlmClient methods no longer take an OpenTelemetry Context. llm.request is
now a tracing span (otel.kind=client, llm.provider/operation/model) that
parents on the caller's ambient span; traceparent injection reads the
span's OTel context via OpenTelemetrySpanExt.
The src/ai feature spans (handlers, insight generation, chat, persona
chat, daily summaries, TTS) move to #[instrument] / info_span!, and every
LLM-bearing tokio::spawn carries its parent span with .instrument(): the
streaming chat turn (chat_turn_stream_inner), async chat / persona turns,
background insight jobs and TTS jobs. Sub-spans in the agentic loops
(ai.chat.loop, ai.agentic.loop) instrument each LLM / tool await.
DAO calls keep their explicit Context (derived from the tracing span)
until the DAO migration (#141).
tests/otel_llm_spans.rs pins nesting + traceparent for the blocking and
streaming paths across a spawn on a multi-thread runtime.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Add OpenTelemetry tracing to every LLM client call so an insight/chat
turn is a single trace from HTTP entry to each downstream inference.
- LlmClient trait: thread a &opentelemetry::Context through all 5
methods (generate, chat_with_tools, chat_with_tools_stream,
generate_embeddings, describe_image), matching the DAO convention of
explicit context threading rather than ambient Context::current().
- otel::start_llm_request_span: single shared helper that every
provider (openrouter / llamacpp / ollama) funnels through, so the
span shape is identical: name llm.request, SpanKind::Client,
llm.provider / llm.operation / llm.model.
- Per-method spans in all three clients with the spec's operation enum
(chat | chat_stream | embeddings | describe_image | generate); stream
spans are owned and moved into the async_stream generator so they end
when the response drains, not when headers arrive.
- llm.tokens.input / llm.tokens.output recorded on non-stream and
stream completion; llm.cost_usd from usage.cost (OpenRouter);
http.status_code + error status on failure.
- W3C traceparent injected on outgoing LLM HTTP requests (llama-swap,
Ollama, OpenRouter) gated on span_context.is_valid() so debug
no-op-tracer builds don't send an all-zero parent.
- Turn-level spans (ai.chat.turn.execute, ai.persona_chat.turn.execute)
now carry llm.backend + llm.model; with_entry streaming paths thread
the turn context (turn_cx) to child describe_image / agentic-loop
calls instead of the ambient context.
clippy clean; 690 lib + 775 integration + 4 doc tests green.
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>
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>
Cameron CordesandClaude Opus 5.5