Tinfoil bills voxtral-tts $0.002 and whisper-large-v3-turbo $0.01 per REQUEST,
with $0 per token for both. Reading only the two token prices in its model list
made TTS look free and left STT billed at an older catalog's $0.05/1M tokens, so
neither matched what the co-op actually pays.
LiteLLM cannot express a per-request charge on the audio paths: per-request
pricing exists only on the search/rerank/MCP paths via input_cost_per_query, and
input_cost_per_request is read only by the proxy's cost-tracking settings, never
by the model cost calculator.
So patch_audio_request_cost.py, a build-time patch in the same shape as
patch_image_cost.py, makes response_cost_calculator honour a declared
input_cost_per_request. That function is the single funnel for every call type —
the proxy dispatches audio as `aspeech` and `transcription` and reaches it
through Logging._response_cost_calculator — so one insertion covers both. The
charge resolves from the per-deployment custom_pricing the logging layer builds
from our model_info, then the shared cost map, then call metadata, and the patch
is inert for any model that declares nothing.
config.yaml declares the real charges: $0.002/request for voxtral-tts, and
$0.01/request for whisper with its token price corrected to $0.
Verified before committing: the patch applies to the installed 1.103.2 anchors
and compiles; the helper's resolution order passes unit checks (all branches,
plus inert and garbage cases); the resulting config validates as YAML with all
12 entries intact. End-to-end spend is proven after deploy by a real TTS/STT call.
Refs code/litellm#5
The 3301 'address already in use' on process-level restarts left an unmanaged
old proxy serving (pre-update code/flags) while the new one died. Also: if the
proxy never binds, exit 1 instead of exec-ing LiteLLM against a dead 3301 —
that masqueraded as a provider outage. Cache continuity: with
TINFOIL_USER_CACHE_SECRET now pinned (env, 2026-10-22), restarts keep Tinfoil's
prompt-cache warm either way.
The 2026-10-02 outage had three causes the runbook now prevents:
- floating tag drift (README now mandates exact-tag pinning)
- 256MB default cgroup cap OOM-killing the prisma migration engine
(manifest now sets memoryLimit: 2147483648)
- no _prisma_migrations ledger -> P3005 crash-loop on boot
(start.sh now exports LITELLM_MIGRATION_DIR=/app/data/migrations)
README 'Updating LiteLLM' section rewritten from the old (wrong)
floating-tag procedure into a runbook with rules + verify checklist.
- Dockerfile: pin ghcr.io/berriai/litellm:v1.84.0 (was floating
main-v1.74.0-stable, which silently moved to a newer digest).
v1.84.0 is the fix line for CVE-2026-35029 (auth bypass on
/config/update, fixed 1.83.0) and CVE-2026-59822 (MCP session
auth bypass, fixed 1.84.0, CISA KEV).
- Drop the v1.74.0-era sed CORS patch: upstream v1.84.0 moved the
file and now reads LITELLM_CORS_ORIGINS natively.
- start.sh: export LITELLM_CORS_ORIGINS (the native v1.84.0 var)
instead of LITELLM_CORS_ALLOWED_ORIGINS (the old sed-patch var
that v1.84.0 ignores) — keeps CORS locked to chat.inference.coop.
- CloudronManifest: upstreamVersion 1.74.0 -> 1.84.0.
Live gateway already runs v1.84.0 (image digest
sha256:dc532d896ba8..., built 2026-10-02 04:50 UTC); this commit
makes the repo mirror the deployed packaging per the no-drift rule.
LITELLM_CORS_ORIGINS also set as a Cloudron env var on the app so
the running container honours it without a rebuild.
num_retries=2 (retries transient connection errors), retry_policy with
TimeoutErrorRetries=0 (a timed-out generation is already billed by Tinfoil, so
re-hitting it re-bills). Combined with timeout=180, this hedges connection
errors without the silent re-billing that caused the Tinfoil spend gap.
DeepSeek V4.1 Flash is a reasoning model; 30s timeout caused LiteLLM to
abandon in-flight generations (falling back to GPT-OSS) while Tinfoil still
completed and billed them. num_retries re-hit Tinfoil up to 3x. Result: Tinfoil
billed ~2x the tokens LiteLLM logged. Generous timeout + zero retries stops
the silent re-billing.
Ubuntu
inference-bot