The legacy SSE streaming path (chat_turn_stream -> run_streaming_turn ->
run_bootstrap/continuation_streaming) built its LLM spans from
Context::current(), which is always the empty root context here: the codebase
threads OTel contexts explicitly and never attaches one, there is no
context-aware tokio layer, and the turn runs on a tokio::spawn. So every
llm.request span on that path was an orphaned root span, uncorrelated with the
HTTP request.
Thread the handler's extracted request context down through
chat_turn_stream -> chat_turn_stream_inner -> run_streaming_turn ->
run_bootstrap_streaming / run_continuation_streaming, and use it for the
describe_image and agentic-loop calls. Mirrors the non-streaming path, which
already threads parent_cx -> loop_cx.
Also rename the block-scoped db 'cx' in run_streaming_turn to db_cx so it no
longer shadows the new parameter.
Addresses the P2 refactoring follow-ups parked on issue #130:
- otel::with_traceparent(builder, &SpanContext) — one shared W3C
traceparent injector. Replaces the 4-line inline header loop in
llamacpp (3x) and openrouter (3x) and removes ollama's private
inject_traceparent method (4 call sites now use the shared helper).
Takes &SpanContext (not &dyn Span) because the Span trait is not dyn
compatible in opentelemetry 0.31.
- otel::record_http_failure(span, status, message) and
otel::set_http_status(span, status) — collapse the repeated
'set http.status_code attribute + set_status(Status::error)'
boilerplate across all three clients (~10 sites).
Net -45 lines. The remaining if-let-Some(span.as_mut()) guards (token
attributes, parse-failure status) stay inline rather than growing a
SpanHandle wrapper type for a pattern that's already readable.
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.
Records the config boundary the #127 owner-default columns establish:
.env = boot-time deployment config + secrets (never DB), user_ai_prefs
single row = per-request owner defaults (hot-tunable, no secrets),
resolution request param -> owner default -> hard default, and the
safe-by-default privacy posture for default_backend. Adds the
Configuration glossary section to CONTEXT.md (owner default,
deployment config, hard default).
Closes#127.
Grows user_ai_prefs with five nullable owner-default columns and makes
them the server-side fallback layer: request param -> stored pref ->
hard default, at insight generation (agentic + standard), all three
insight-chat turn variants, and reel creation.
- PUT /prefs accepts the fields with the existing three-state partial
update semantics (TriState generalized to TriState<T> for the numeric
reel_max_segments); validation (canonical BackendKind::parse,
MemoriesSpan::from_str) runs before any write.
- GET /prefs returns the new fields.
- capture_prefs reads the existing row and carries the AI owner-defaults
through unchanged (the upsert overwrites all columns), mirroring only
the effective reel span/segments.
- MemoriesSpan gains Display + FromStr so stored spans round-trip
losslessly.
1463/0 tests (+27), clippy clean.
Cameron Cordes