OpenAI's chat completions response includes prompt_tokens_details.
cached_tokens when prompt caching kicks in - previously dropped
entirely. Now extracted in LlmClient and forwarded to Langfuse as the
flat cache_read_input_tokens usage key.
Used the flat key rather than OpenAI's nested prompt_tokens_details
shape: the installed @langfuse/tracing SDK's usageDetails type is
Record<string, number> | OpenAiUsage (a 3-field camelCase shape, no
_details nesting) even though the wire schema in @langfuse/core
supports nesting - a gap in the SDK's public types, not something
worth fighting with a cast.
Verified: full suite (82/82) passing, tsc/eslint clean.
Each pipeline invocation (runAsync/searchAsync) now gets a fresh
sessionId, wrapped via the new Tracer.runWithSession() (implemented
with @langfuse/tracing's propagateAttributes, since v5 has no direct
sessionId/tags option on startObservation) so it shows up in
Langfuse's Sessions view. The session is also tagged with what
triggered the run: "cron", "api-list", "api-trigger", "api-search".
Verified: full test suite (79/79) passing, tsc/eslint clean, real
docker compose build + container smoke test against /health.
- ApiClient: strip query string from ApiError messages so API keys
(e.g. TMDb's api_key query param) never leak into 500 response
bodies or logs.
- LlmTool: accept an optional defaultModel, wired from AppConfig's
LLM_MODEL, so Langfuse prompts that omit a model config fall back
to the configured LLM rather than silently requesting gpt-4o-mini.
- RecommendationPipeline: restore the Go original's graceful
degradation — library/Radarr fetch failures, per-suggestion TMDb
resolution failures, and per-signal TMDb similarity/recommendation
failures are now logged and skipped instead of aborting the whole
run (applies to both runInternal and searchAsync).
- RecommendationsController: validate the ?count= query param
(must be a positive integer) instead of silently producing NaN.
- Commit the Langfuse prompt definitions (langfuse/*.prompt.json) and
add a README covering setup, prompt seeding, cache invalidation,
and the HTTP API surface — the branch was not otherwise runnable by
anyone but the author.
