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.
Composes the two existing engines (Path A orchestration):
- Translate NL -> StructuredQuery via local LLM, respecting LLM_BACKEND
(resolve_backend(Local) -> ollama or llama-swap; no hybrid).
- Forward-geocode the place name into a gps circle.
- Structured filters (tags/EXIF/geo/date/media) build a candidate set of EXIF
rows; CLIP ranks within it, joined by content_hash. Degenerate cases match
existing behavior: semantic-only -> plain CLIP; filters-only -> date-sorted.
- Echoes the interpreted query (incl. resolved place) for editable client chips.
Refactor: extracted reusable cores from clip_search (score_photos, resolve_hits,
parse_library_scope, score_error_response) shared by both endpoints. Removed the
Phase 1 allow-until-wired attributes now that nl_query + geo are consumed.
fmt + clippy clean; 23 backend tests pass (7 geo, 12 nl_query, 4 unified).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Foundation for the /photos/search/unified endpoint (Phase 2). Two new,
fully unit-tested pieces, not yet wired into a route (allow-until-wired,
mirroring llm_client.rs):
- ai/nl_query.rs: translate a free-text query into a StructuredQuery via one
grounded LLM call. Two-stage — the model emits names/ISO dates, then a pure
resolve step maps tag names against the real vocab and converts dates to
unix seconds. Hallucinated (non-vocab) tags are surfaced in unmatched_tags
rather than silently used as hard filters — the anti-noise guard. 12 tests.
- geo::forward_geocode + bbox_to_circle: resolve a place name to a circle via
Nominatim /search, collapsing the bounding box to centroid + circumscribing
radius so "Portland" and "Italy" both map onto the existing gps circle
filter with no schema change. Radius is the max centroid-to-corner distance
(corners aren't equidistant on a sphere). 4 tests.
fmt + clippy clean; 19 new tests pass.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Cameron Cordes
