* fix(cost): split a provider-reported total between input and output by the cost map rate ratio
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(cost): expect the kyma reported-cost headers to follow the cost map rate split
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(cost): keep the kyma test file at its original formatting
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): price the response-cost header split from the served model, not the request alias
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): bill the requested model's rates when the response names an unpriced model
Fireworks answers chat and /v1/messages calls with a display name such as
"Qwen 3.8 Max" in the response's model field. The cost path priced that
name, the Fireworks calculator fell back to its free default bucket without
raising, and the call billed $0 even though the requested model has a row.
When the response model resolves to no cost-map row or rule that declares
rates and the requested model does, price from the requested model. A priced
response model still wins, so dated snapshots keep their own rates, and an
unpriced requested model such as a router alias leaves the result unchanged.
* perf(cost): check the exact cost-map row before generalization rules when picking the priced model
* fix(cost): apply the priced fallback to the provider response model streaming records
* perf(cost): skip the served model's rule lookup when the requested model has no rates
* fix(cost): price the requested model without a model arg and keep Fireworks size buckets behind the proxy
When completion_cost runs with no model, the requested model now comes from the
call's hidden litellm_model_name, so a display-name response still bills at the
requested model's rates. A Fireworks model whose name carries a parameter size
counts as priced through its size bucket.
The Fireworks per-token lookup now treats a cost-map row that prices nothing, like
the empty row the Router registers for an unlisted deployment, as missing, so an
unlisted Fireworks model bills at its size bucket instead of $0 even when Fireworks
echoes its slug. The "row prices anything" helpers move to llm_cost_calc/utils so
the Fireworks lookup can reuse them without a circular import.
* fix(fireworks): keep prices from a matching fallback rule for an unlisted model
An unlisted Fireworks model that only a fallback generalization rule prices
has no raw cost map row, so the empty-row check sent it to the size bucket
and dropped the rule's rates. The Fireworks lookup now keeps the model info
when the row or a matching rule declares a rate.
* fix(cost): price a bare response model under the requested provider and drop the unlisted Fireworks bucket change
The logging payload picks the pricing model without a provider, so a bare echo
like mistral-large-latest failed its price check and the requested alias took
over model_map_key. The served name is now priced under the requested model's
provider, and an echo that is the requested name minus its provider prefix
skips the checks.
Treating the Router's empty price row as missing let unlisted Fireworks
deployments bill from a name guess, which misprices dedicated deployment ids
and routes some short names to another provider's rates. That change and its
tests go back to the merge base, so unlisted Fireworks models keep billing $0
behind the proxy as on main.
* perf(cost): read the response model's price row without building full model info
An unpriced display name like Qwen 3.8 Max made the price check build full
model info, and Fireworks' supported params lookup scans the whole cost map
for an unknown name. The row check now resolves the cost map key through the
cached model info helper, so that pick takes about 0.45 ms instead of several.
A regional test covers a Bedrock call whose response names an unpriced display
name with no model passed, which bills the requested model's regional row.
The duplicate get_model_info wrapper goes, since its twin already does the
same thing.
* fix(cost): keep the served model's filled-in and size-bucket rates, and cache misses
A served row priced only by a fill_missing_for_providers rule bills those
rates on main, but the price check read only the raw row and billed the
requested alias instead. It now merges the rule's fill-in keys through the
helper model info lookup uses.
A served Fireworks or Together AI id that names its parameter count keeps its
size-bucket price, as on main, instead of switching to the requested row.
The served model is checked first, cost map misses are cached and cleared with
the model info cache, and the rules are read only for a name that resolved
through one. A priced snapshot behind an Azure deployment name takes about
19 us of CPU time against 7 us on the merge base, down from about 300 us.
* fix(cost): bill the requested model's listed rates over a served size-bucket guess
A served Fireworks or Together AI name that is not in the cost map but names
its parameter count, like a display name with a size in it, now bills at the
requested model's listed rates instead of the provider's size-bucket price.
The bucket price still applies when the requested model has no rates, as on
main
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(cost): a provider slug the price map lacks no longer bills the turn at zero
Anthropic names the dated build in `message_start`, so a streamed turn carries
`provider_response_model="claude-opus-5-20250930"` while the price map holds
`claude-opus-5`. `_select_model_name_for_cost_calc` prefers the reported name
over `response.model`, and `get_model_info` answers a model it has never heard
of with zero rates rather than raising -- so the turn is billed 0.0 with nothing
in the logs to explain it.
Same usage, only that field varying, on main:
provider_response_model absent -> 0.00079
provider_response_model=claude-opus-5 -> 0.00079
provider_response_model=claude-opus-5-20250930 -> 0.0
Missing is harmless; the damage is a name that is present and unpriced.
The reported name still wins whenever it resolves to a rate -- it is the most
specific truth about what served the turn. It is only passed over when charging
by it would produce a silent zero, and then the response's own model is used:
the name the deployment resolved to, and the one an unstreamed turn is already
priced by.
This is not specific to Anthropic or to streaming. Any provider reporting a more
specific slug than the map carries -- dated, regional, build-suffixed -- is
affected, and only streamed turns carry the field, which is why it reads as a
streaming bug from the outside.
Reported in #42161.
* address review: drop explanatory comments, stop pinning vendor slugs in tests
Three points from the review, two of which were right.
The helper docstrings explained behaviour the code already shows, which AGENTS.md
rules out. Removed.
The tests asserted that `claude-opus-5` is in the price map and
`claude-opus-5-20250930` is not. Both are facts we do not own: if Anthropic registers
the dated build, the test breaks without any litellm change. They now use a name that
is ours, and assert the invariant instead, that what the provider reports cannot change
the price of a turn the map cannot quote it by.
Picking that name needed care. An arbitrary string makes `get_model_info` raise, which
a caller upstream already handles, so the test passed with or without the fix and
defended nothing. A `claude-` prefixed name reaches the zero-rate fallback that this
bug rides on, so `claude-test-42161` reproduces it and stays ours.
The third point, that lines 801 and 828 exceed 120 characters, does not hold: they are
98 and 39.
* Pass completion_response_model as str or None to _priced_provider_response_model
basedpyright counted the bare variable as partially unknown (reportUnknownArgumentType +1 over the budget).
* test(cost): isolate runtime registration replay cases
---------
Co-authored-by: Eduardo Pessin <eduardopessin@users.noreply.github.com>
* feat(cost): parse 12-hour cache write rates for batch and ultrafast tiers
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): bill 12-hour batch cache writes once when only the 12hr batch key exists
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(vertex-ai): support gemini 3.1 flash tts
* fix(vertex-ai): keep TTS metadata compatible with the cost map guard
* fix(vertex-ai): preserve existing Gemini TTS models and voice mappings
* fix(vertex-ai): recognize provider-stripped TTS model names
* test(vertex-ai): match current speech HTTP error response
* fix(vertex-ai): preserve nested speech locale and voice
* fix(vertex-ai): use provider speech media type in proxy
* fix(gemini): preserve TTS dispatch and nested speech settings
* test(gemini): run TTS regressions in CI shards
* fix(vertex-ai): account for Gemini Cloud TTS audio cost
* fix(vertex-ai): bill Gemini TTS without optional audio decoder
* test(gemini): cover TTS mapping and billing edge cases
* test(vertex-ai): cover Gemini voice normalization in provider shard
* fix(vertex-ai): keep Gemini TTS routing with generic provider metadata
* chore(vertex-ai): remove obsolete lint suppressions
* fix(gemini): strip audio format from speech configuration
* chore(vertex-ai): remove obsolete mutation suppressions
* fix(vertex-ai): preserve FLAC billing and wrapped audio headers
* fix(vertex-ai): reject unmeasurable FLAC before billing
* fix(vertex-ai): reconcile speech support with current provider mappings
* fix(vertex-ai): validate speech mappings and usage types
* fix(vertex-ai): preserve speech mapper override forwarding
* fix(gemini): map voice aliases across speech request forms
* fix(vertex-ai): send only formats the speech bridge cannot serve to Cloud TTS
Gemini TTS detection now goes by model name, so newer Vertex Gemini TTS
models keep working, and only mp3, opus, alaw, mulaw and other container
formats move to Cloud Text-to-Speech. wav and pcm requests stay on
generateContent as on main.
A Cloud TTS response whose duration cannot be measured now returns the
audio unbilled with a warning instead of raising after a paid call. FLAC
handling is removed because Cloud TTS has no FLAC encoding.
The cost map, the google_genai mappers and the proxy error path go back
to main, since those changes were outside this feature.
* fix(vertex_ai): keep Gemini TTS formats, region and instructions on routes that serve them
Only mp3, opus, alaw and mulaw go to Cloud Text-to-Speech. Every other
format gets a local 400 that lists the supported ones, before Google is
called.
Cloud TTS uses the deployment's us or eu regional host. Other regions
and a custom api_base get a 400 that says to request wav or pcm.
instructions is sent as the Cloud TTS style prompt, and a request with
no voice keeps the Gemini model.
get_usage_object is back to main's code, so dict usages still go
through Usage.__init__, and the proxy no longer labels pcm16 or
linear16 output as WAV.
* fix(vertex_ai): send Gemini TTS to every regional Cloud TTS host and keep speak tags as text
Cloud Text-to-Speech serves Gemini TTS on a host named after each Vertex
location, so a non-global vertex_location now uses
{location}-texttospeech.googleapis.com instead of only the us and eu hosts.
Google answers for regions it does not serve.
Gemini TTS voices reject SSML, so input that contains <speak> is sent as
text for Gemini TTS models. Chirp keeps the SSML auto-detect.
Removes the proxy alaw and mulaw media-type entries. Cloud TTS returns
those encodings with a WAV header, so the response is labeled audio/wav
and the entries never applied.
Adds a regression test that custom per-token pricing bills the usage a
speech response reports.
* fix(vertex_ai): map Gemini TTS regions to Google's Cloud TTS locations and keep a bad voice from cooling down the deployment
US and EU Vertex regions go to the us and eu Cloud TTS hosts, northamerica-northeast1 to its own, global or unset to global, and any other region gets a local 400. A Cloud TTS 404 on the Gemini path, such as a misspelled voice, comes back as a 400 so the router keeps the deployment serving wav. Usage reads the sent request from the response instead of the logging object.
* fix(vertex_ai): default Gemini TTS Cloud formats to a Gemini voice and validate speakers
Parse only usage fields from the sent Cloud TTS request, so a numeric speakingRate no longer fails after Google bills it.
Send the Gemini voice Kore when no voice is named, and reject Cloud TTS voice names unless drop_params is set.
Reject malformed speaker entries unless drop_params is set, and translate Cloud TTS speaker fields on wav and chat audio.
Use the Vertex default region when no location is set, so mp3 and wav share a region.
* test(vertex_ai): cover two-speaker Gemini TTS mp3 through aspeech with fake credentials
Replaces two tests that patched the Vertex TTS config's own token and URL methods.
* fix(vertex_ai): reject malformed Gemini TTS voices and keep beta Chirp and Lyria params unmapped
* fix(vertex_ai): drop unknown Gemini TTS voice keys on wav and pcm instead of rejecting them
* fix(vertex_ai): reject unknown Gemini TTS voice keys on wav, pcm, and chat audio unless drop_params is set
* fix(vertex_ai): honor every drop_params setting in the Gemini TTS voice key check
Global drop_params, batch row and deployment drop_params on Vertex batch
file uploads now drop unknown voice keys. A voice object with both
speechConfig and speech_config gets a 400 for the ignored speech_config.
* fix(gemini): drop unknown nested voice fields under drop_params and detect TTS by served model
* fix(gemini): filter unknown speech config fields with fixed-depth helpers and pass audio params through unchanged
* fix(gemini): camel-case snake replicated voice keys so drop_params keeps them
* fix(vertex-ai): reject voice fields Cloud TTS cannot send unless drop_params is set
* fix(vertex-ai): reject wrong-typed Cloud TTS voice values and check speakers as sent
Gemini TTS on mp3, opus, alaw, or mulaw now answers 400 for a voice field whose value Cloud TTS cannot send, such as a list languageCode or a string voiceConfig, and for nested voice fields under a speaker that also names speakerId. drop_params still drops them.
* fix(vertex-ai): reject wrong-typed speech config wrappers and speakerId overriding a prebuilt voice on Cloud TTS
* fix(vertex-ai): keep speakers and voice_config beside a speech_config wrapper on Cloud TTS
* fix(vertex-ai): pick Cloud TTS voices from the same speech config the WAV path sends to Gemini
* fix(files): carry the deployment's drop_params on model= file uploads so Vertex batch rows drop unknown voice keys
* fix(gemini): keep a structured speech voice when the model is a model_alias_map alias for a Gemini TTS model
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(cost): price base_model deployments past rule-only cost map entries and warn when base_model has no rates
* fix(router): warn on unpriced base_model from add_deployment too and honour model_info prices
* refactor(cost): drop the unpriced base_model startup warning, keep the one-line ladder fix
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost-map): add volcengine doubao-seed-2-1-pro-260915 and doubao-seed-2-1-lite-260915
Pro row absorbed from #47372, lite row added from the same Volcengine Ark pricing and model list docs
Co-authored-by: donghongfei <1247543758@qq.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(cost-map): cover volcengine doubao-seed-2-1-pro-260915 row
Co-authored-by: donghongfei <1247543758@qq.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost-map): add undated azure/eu and azure/us rows for o1, o3, o3-mini, o4-mini, gpt-4o, gpt-4o-mini
Absorbed from #47499
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: donghongfei <1247543758@qq.com>
* fix(batches): apply the Vertex regional endpoint uplift to batch cost
batch_cost_calculator takes vertex_location and multiplies by the model's
regional_endpoint_uplift_multiplier through get_vertex_regional_endpoint_uplift,
and every batch cost path (aretrieve_batch pricing, completed-batch logging,
native Vertex batch rows, the proxy batch cost poll and its per-line items)
resolves the deployment's location and passes it down
Co-authored-by: Mrun25 <165297479+Mrun25@users.noreply.github.com>
* test(logging): point the resolver tests at resolve_vertex_location_for_cost
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Mrun25 <165297479+Mrun25@users.noreply.github.com>
* fix(test-harness): preserve sibling auth modules in isolated worker configs
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(integration): expect servers in MCP connect-flow descriptions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(integration): expect ptu_hours in daily activity metrics after #43043
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(integration): kill every serving worker once the SCIM push blocks on the row lock
* fix(cost): price exact cost-map names before price-free capability rule matches
* test(streaming): price a priced alias stream at its deployment model and keep the unpriceable case unmapped
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): price an explicit base_model under its own provider after candidate reordering
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): retain priced generalized candidates and skip explicit-pricing lookups
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(cost): assert custom pricing makes no remote model-info requests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cost): keep the per-candidate pricing provider final
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): pin a Bedrock application profile prompt for the one-hour ttl its base model sends
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(integration): assert the Nova Sonic tool-call argument delta carries the full arguments
* fix(cost): sort cost candidates from the static cost map and rules, without provider lookups
* test(integration): bill route-priced Bedrock chat streams and responses, and pin application profiles for an hour on messages and cache hits
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Yuneng Jiang <yuneng@berri.ai>
* fix(openai_like): surface provider response headers on non-streaming chat completions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(openai_like): mark the header test locals Final
* fix(proxy): leave out response header values HTTP cannot carry
Non-streaming OpenAI-like chat now forwards every provider header, so on the
httpx transport a provider header value outside latin-1 made the proxy answer
500 after the provider had served the call. get_custom_headers now leaves such
a value out and keeps the other headers, which also ends the same 500 on
streaming
Adds integration cells for the provider request id on non-streaming chat and
the Responses bridge, LiteLLM headers an upstream cannot overwrite, spend
parity under an upstream cost header, the latin-1 case, and the logging
callback payload
* fix(cost): ignore an upstream response cost header that is negative or not a number
* test(integration): cover invalid upstream cost headers and non-latin-1 headers on every endpoint
* fix(prometheus): keep deployment metrics when a provider rate-limit header is not a number
* test(prometheus): type the rate-limit header test and drop its clock reads
* test(integration): cover deployment metrics under an unparseable provider rate-limit header
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(openai): route gpt-transcribe to GPT audio transcription config
* test(openai): move gpt-transcribe tests under tests/unit
* fix(openai): bill gpt-transcribe from provider usage seconds when duration is unknown
Fall back to the provider-reported usage.seconds when neither a measured
file duration nor a response duration is available, so json responses
for undecodable uploads are no longer billed at zero. Move the routing
test next to the other provider config tests and replace the structure
test with a behavior test.
* fix(openai): bill provider usage seconds only for gpt transcription models
* fix(cost): decide provider-billed transcription seconds from the deployment model, not its pricing id
* test(integration): cover gpt-transcribe default request, provider-billed spend, and health probe
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(responses): write one spend-log row per native WebSocket turn
Each response.create turn on a native Responses WebSocket connection logs and bills as its own call when its terminal event arrives, keyed by the resp_ id the client saw, instead of one row at socket close that sums every turn
* test(responses): mock the websocket slot release and mark the per-turn start time naive
* style(responses): keep the per-turn start time line within ruff format
* refactor(responses): type websocket turn events as read-only mappings
* fix(responses): settle the websocket budget reservation on the first turn only
Every per-turn logging copy carried the connection's admission reservation, so two turns whose cost callbacks overlapped could both reconcile it. The first turn keeps the reservation and later turns charge their cost directly
* fix(proxy): keep the legacy limiter's websocket slot until disconnect
A websocket turn callback no longer decrements current_requests in the legacy limiter. The socket's slot is released once from arelease_max_parallel_requests_on_disconnect, which now dispatches to the legacy handler as well
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(vertex_ai): route Model Garden models through the generateContent adapter
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(vertex_ai): annotate generateContent route test parameters
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(vertex_ai): type litellm_params in get_vertex_ai_model_route
* fix(vertex_ai): bill and log Model Garden generateContent calls like chat completions
Streamed Model Garden calls through the generateContent adapter now request
stream usage where the deployment supports it, keep cached-token details, and
look up the provider-relative cost key, so they bill like the non-stream call.
The adapter forwards router metadata, passes upstream errors through with their
status, countTokens falls back to local counting for non-Gemini routes, and the
native Gemini config is limited to the Gemini routes.
* fix(google_genai): keep adapter stream usage, admin opt-out, single failure count, and base_model routing
Streamed generateContent through the chat adapter now ends with the upstream usage, honors
always_include_stream_usage false and the caller's stream_options, counts one failure per
failed call, and routes Vertex deployments by their base_model like chat does
* fix(google_genai): ask for stream usage on every adapter stream so Claude streams end with usage
* test(google_genai): expect the trailing usage chunk on bridged OpenAI streams
The OpenAI bridge test now sends the usage chunk OpenAI returns for include_usage and expects it translated into usageMetadata. The response_format support helper goes back to its single-purpose form since its only other caller is gone.
* fix(google_genai): end adapter streams with one STOP event carrying usage, and keep upstream usage after the finish chunk
* fix(google_genai): send the held STOP event when no usage arrives, keep a caller's stream_options, and route countTokens like generateContent
* test(integration): cover the moved Vertex routes, adapter stream usage, the shared iterator and usage settings over the wire
* test(integration): add cache-hit twins for the stream usage setting and non-stream cells for every iterator member
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(cost): price AgentCore web search at $7 per 1,000 queries
* feat(search): honor input_cost_per_query set on a search tool (#46560)
* feat(search): honor input_cost_per_query set on a search tool
* feat(search): record the search tool price on proxy-created logging objects
* chore(search): type the search tool price lookups and shard tests/unit/search
* chore(openapi): regenerate snapshot and ui types for search tool input_cost_per_query
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Kerry Lu <klu@berri.ai>
* fix(cost_calculator): price an explicit base_model from its own row when the deployment provider row has no rates
A chatgpt/ deployment with model_info.base_model recorded zero spend because the
base model was looked up under the chatgpt provider, which resolves to the
deliberately unpriced chatgpt/ row. When the deployment provider's row for the
base model declares no rates, price it under the provider of the base model's
own row instead. Deployments whose provider row declares rates are unchanged.
(cherry picked from commit 42d9a8693e)
* test(integration): bill a chatgpt base_model deployment from the priced row on a live proxy
Co-authored-by: sla55er <stiliyanmarkov@gmail.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: sla55er <stiliyanmarkov@gmail.com>
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
cost_discount_config keys may now be <provider>/<model-pattern> with fnmatch globs, so a discount can target a subset of a provider's models. An exact pattern beats a glob, the glob with the longest literal wins, and the bare provider key is the fallback. PATCH /config/cost_discount_config validates the provider half only, and the admin UI cost tracking page gains a Model pattern field and a Models column
Resolves LIT-8465
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test: migrate local_testing SDK and provider tests out of build_and_test
* test: cover sagemaker region, hf template and nova paths end to end
Region rows now go through litellm.completion on the sagemaker/ handler that
the legacy tests exercised, the prompt template test mocks the Hugging Face
tokenizer config instead of switching to custom_prompt_dict, streaming tests
assert role, finish reason and body, and Nova single turn and streaming run
through litellm.completion with a recorded request body
* test: tighten migrated integration tests for local OpenAI routes, timeouts and air-gapped boot
Split the catch-all providers migration file by behavior. The fake endpoint
route tests now hit the owned upstream directly, as the legacy harness tests
did. LM Studio asserts the outbound key, path and stripped model. The embedding
timeout test asserts the proxy maps a deployment timeout to a 408 and forwards
the read timeout to the provider client, instead of timing out the test client
The Azure streaming tool-call test also asserts the second identical stream is
served from the Redis cache with the same reassembled tool call
The Docker network test always skipped in CI because the security job has no
litellm/litellm image and no egress to pull one, and it tested a published image
rather than the checkout. It now boots the checkout proxy with every outbound
HTTP connection refused and asserts readiness, the bundled cost map fallback and
that the cost map host is the only egress attempted
* test: tighten the migrated e2e rows for local_testing SDK and provider tests
Drop the duplicated Anthropic covers marker and the Anthropic cell wrongly claimed by
the Bedrock and Vertex cache tests. Keep the file-wide Anthropic model as it is on main.
Send the 2023-06-01 version header to Anthropic through the deployment's extra_headers
so the header actually reaches the provider, and mark the creation-token case 1h then
5m like the legacy test did
Reuse the Bedrock file's own registration for the pydantic response test, swap the
hand-built PNGs for the shared cat.jpg fixture, assert the SageMaker Nova image answer
names the cat and that top_logprobs=3 is honored, and register the SageMaker Nova opt-in
markers the same way as the other opt-in markers
* test: restore lost assertions in migrated test_main tests
Restore the role alternation check in test_completion_anthropic_hanging, the
embedding and streaming response-header checks, the logit_bias drop check and
the gemini system and safety settings checks. Add an azure 429 retry-after
test for test_exception_with_headers, trigger the router fallback with
mock_timeout like the legacy test, and stop the mock timeout tests sleeping 3s
* test: restore lost legacy assertions in migrated vertex ai unit tests
* test: tighten migrated cost, streaming and embedding tests and scope the hosted mock guard
* test: strengthen migrated anthropic, azure, bedrock and cohere provider tests
Assert full request bodies and usage instead of presence checks, restore the
dummy-tool and custom_llm_provider assertions the legacy tests made, add the
async and per-model variants the legacy parametrization covered, split
streamed tool arguments across deltas, and move the Azure chat streaming
tests to the azure.py mirror file
* test: tighten migrated llms provider tests and cover legacy intents lost in the move
Strengthen the migrated fireworks, gemini, mistral, together, openai text completion, openrouter, perplexity and openai error tests so they assert what the legacy tests proved (cost, provider tag, usage-only-on-last-chunk, function_call rebuild, reasoning param, sync/async/stream error fields). Replace the huggingface and jina tests that doubled litellm code with respx end-to-end tests. Add the tests the pre-existing mapped tests never covered: cohere 400 mapping, token-array text completion, hosted_vllm/llamafile/lm_studio env api base embeddings, watsonx embedding auth, ollama ssl_verify client and ollama vision prompt
* test: cover residual legacy paths for anthropic tool streams, watsonx async stream, ollama http images and caller async embedding clients
* test: restore single request assertions in the deep_infra and azure_ai embedding tests
* test: drop a no-op streaming cost flag from the openai streaming cost test
* test: cover residual legacy-test lines in caching, main, utils, replicate, vertex and bedrock invoke
* test: cover streamed audio assembly, choice membership, untranslated responses events and the stream log guard
* test: pin cost rates in unit tests, use sdk for cohere e2e, drop vertex llama e2e
* test: send the vertex maps e2e request through the openai sdk
* test: drop the local_testing jobs that select no tests after the migrations
* test: wait for the streamed cache entry and keep custom Mistral rates test-local
* test: keep untouched Mistral test lines as they were
---------
Co-authored-by: yuneng <yuneng@berri.ai>
* test: move the unit half of 126 mixed legacy files into tests/unit
* test: restore litellm globals that moved tests set
* test: finalize migration test cleanup
* test: restore original bodies of moved legacy tests
The move into tests/unit had rewritten 612 test bodies, and some of the rewrites dropped assertions. Each moved test now carries its original body from the legacy file, with only the imports, helpers, fake provider credentials and monkeypatched env it needs to run under tests/unit
test_timeout_streaming goes back to tests/local_testing because it needs the fake OpenAI endpoint server. The image payload fixture moves with its only user, and two tests that leaked global state (a registered model cost entry and queued logging tasks) are now isolated
* test: drop module imports shadowed by restored local imports
* test: assert on LiteLLM output in no-assertion moved tests and isolate leaks
Twenty no-assertion candidates get one assertion on the value LiteLLM returns, with the original lines unchanged. Four tests go back to their legacy files because they only check types or imports, write into the working directory, or cannot assert without a body change
Two moved tests leaked globals into later tests in the same worker, so monkeypatch fixtures now restore the retry-after header parser and the end user cost tracking flags
* test: drain queued logging tasks before the Phoenix span test
The moved Phoenix test counted spans from logging tasks that earlier tests had queued, so the drain fixture moves to tests/unit/conftest.py and both it and the Datadog batch test use it. test_factory_function goes back to its legacy file because its returned wrapper calls the real Assistants API and cannot be asserted on without a body change
---------
Co-authored-by: yuneng <yuneng@berri.ai>
* fix(cost): price batch image completion tokens at image batch rate
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(integration): cover default vertex batch output transformation for image cost
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): sync model prices schema
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cost): simplify batch completion cost with rate helpers
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): keep global batch pricing fallback for image-only deployment rates
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(test): rename connect tunnel helper to https redirect
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): merge deployment batch rates over global pricing
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(model_prices): put flash-image batch image rate on the GA row
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(cost): drop redundant comment in batch fallback
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cost): use _batch_or_half for the batch image rate
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(cost): price nano banana 2.1 fixtures off the real cost map rows
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(cost): use the vertex 4k image token count in the batch cost test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: kerry <kerry@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(vertex_ai): add regional endpoint uplift to gemini-3.1-flash-image
Google prices Gemini 3.1 Flash Image at 1.1x on non-global endpoints for
input, text output and image output, but the cost map row had no
regional_endpoint_uplift_multiplier, so regional calls billed at the
global rate.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* test(integration): cover regional uplift spend for gemini-3.1-flash-image
* test(integration): read the proxy salt from the environment in the uplift spend cells
---------
Co-authored-by: Nate Armstrong <narmstrong@Nates-MacBook-Pro.local>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(vertex_ai): apply regional endpoint uplift on image generation cost path
completion_cost had vertex_location but never passed it to the image
generation cost router, so a regional_endpoint_uplift_multiplier on a
Vertex image row would be ignored. No image row carries the multiplier
yet, so nothing is misbilled today. Pass the location through to the
Vertex image calculator for both the token-based price and the
per-image fallback.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* test(vertex_ai): cover regional image cost through the proxy logging path
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(images): hand image_edit's vertex_location to its cost resolver
* test(integration): audit Vertex image regional uplift billing
* test(integration): require every spend row after a proxy restart
* test(integration): reject extra spend rows after a proxy restart
---------
Co-authored-by: Nate Armstrong <narmstrong@Nates-MacBook-Pro.local>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(cost): bill per-second transcription models outside chat modes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): restore request-time billing for per-second transcription models
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): bill audio length for per-second transcription models when known
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: kerry <kerry@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock_mantle): route Claude chat completions to the native Messages endpoint
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock_mantle): price Claude chat on the Mantle row and route region-prefixed ids
A Mantle request always carries a region, so a Claude id with no bedrock_mantle/<region>/ row fell through the model-info lookup to the bare Bedrock row, which the bedrock provider family also matches, and billed about 10 percent under the Mantle price. The lookup now tries the provider's region-free row before the bare model. The Claude route test asserts the Mantle row, a region-prefixed Claude id is covered end to end, and the provider config map references the Mantle config directly.
* test(bedrock_mantle): cover supported params for Claude and open-weight Mantle ids
* test(bedrock_mantle): audit the Claude chat bridge on the integration rig
Adds the deterministic cells from the /audit of the Mantle Claude chat
bridge: wire-level translation on every chat, responses, and messages
route, SigV4 and bearer auth, region prefixes, api_base suffixes,
unsupported params with and without drop_params, malformed model ids,
upstream errors, the response-cache hit, the health check, pricing from
the Mantle row for Claude and non-Claude ids with a bare Bedrock twin,
and chaos cells for a mixed burst, an upstream outage, slow streams,
and a worker kill on an owned two-worker proxy
---------
Co-authored-by: jesus <jesus@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(cost): price streamed aliases that only match a capability rule from the deployment model
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cost): satisfy basedpyright delta after the cost-candidate sort
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* perf(cost): skip the capability-rule check for exact cost-map keys
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(spend): price streamed alias rows from the deployment's own rates
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(spend): isolate streamed alias deployments with per-run model names
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(streaming): keep the unpriceable-stamp case on a truly unmapped model
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): treat capability-rule matches as unmapped in every cost lookup
Route every model-info lookup on cost paths through get_priced_model_info
and _cached_get_priced_model_info_helper, which raise ModelNotMappedError
when the only match is a pricing-free fallback-generalizations rule. An
alias that matches a capability rule now falls through to the deployment's
real model instead of billing 0, and the earlier candidate-sorting fix is
reverted since the priced helper is the single choke point.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(spend): assert the rule alias bills the same as the plain alias
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): treat router-registered rule-only model_cost entries as unmapped
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): count string rates and check pricing before the capability-rule match
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(cost): repoint cost-path patches at get_priced_model_info
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(cost): give the model_cost row cast a cast-ok reason
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): type the lazy get_priced_model_info export
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cost): narrow the fix to ordering rule-only cost candidates last
Drops get_priced_model_info and its call-site swaps, the lazy-import entry,
and the cost-path code check. Only the candidate sort in completion_cost and
pricing_entry_for_cost_calc stays, with its tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(spend): cover rule-only base_model billing on every endpoint, client and failure mode
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: kerry <kerry@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(streaming): keep the provider's served service_tier on streamed chunks and spend rows
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(streaming): satisfy type-discipline and strict ruff budgets
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(streaming): stamp the served service_tier on every Responses bridge chunk
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(anthropic-adapter): expose streamed chunks so disconnects bill partial spend
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(service-tier): cover anthropic and responses served-tier billing paths
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(anthropic-adapter): return a chunks-exposing stream so disconnects bill partial spend
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(service-tier): bill disconnects through the router's anthropic stream wrapper
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style: apply ruff format to the anthropic stream changes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(coverage): ignore delegating properties the ast scan cannot see
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style: keep the cast-ok reasons on the cast call line
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(integration): cover served service_tier billing for streamed chat and messages, complete and disconnected
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(anthropic-cache): delegate chunks/messages/model through the messages stream cache writer
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(streaming): keep service_tier on OpenAI-compatible parsed chunks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(streaming): parameterize delegated chunks and messages types
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(tests): follow the anthropic pass_through rename after merging main
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(anthropic): drain the logging worker between response cache tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(spend): cover azure, databricks, responses bridge and gemini served tiers in the stream billing integration test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(databricks): keep the served service_tier on streamed chunks and bill it
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(databricks): type the served service_tier chunk without a loose kwargs dict
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): bill the served service_tier over the requested one
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cost): drop explanatory comment from the tier resolution
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: kerry <kerry@berri.ai>
* feat(cost_calculator): add cost_per_second for chat per-second pricing
Keep legacy input_cost_per_second and output_cost_per_second as aliases for chat, completion, embedding and responses. When both legacy fields are set, input_cost_per_second wins
Move Bedrock commitment rows to cost_per_second so they bill once
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cost_calculator): drop legacy per-second fields from chat paths
Keep Azure chat token pricing generic and update inert Voxtral rates and SageMaker examples
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost_calculator): recognize output-only per-second rates
Include output_cost_per_second when checking whether a deployment cost entry has pricing so output-only legacy aliases remain attached to the deployment during cost selection
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(pricing): cover cost_per_second and legacy per-second aliases through the proxy
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cost_calculator): drop output_cost_per_second as a chat per-second alias
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(cost_calculator): restore output_cost_per_second as a chat per-second fallback
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost-map): keep input_cost_per_second on bedrock commitment rows for older clients
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: kerry <kerry@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(cost-map): add bedrock_mantle rows for claude opus 5.5 and sonnet 5.5
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* revert(cost-map): keep bedrock_mantle claude 5.5 change to cost map rows only
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: kerry <kerry@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(xai): add native xAI batches and files support
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(xai): tighten batch handler typing and avoid Final redeclaration on star import
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(xai): walk batch result pages iteratively
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(xai): stop paging on empty pagination token and honor litellm.xai_key
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(xai): import NotRequired and TypedDict from typing_extensions for Python 3.10
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(batches): accept image and video endpoints on batch create
* test(xai): lock batch endpoint, auth, and result contracts
The batches test package collided with litellm/batches under pytest prepend, so the All Other Providers shard could not collect the new tests.
* fix(xai): price grok batch usage at xAI's 20 percent batch discount
* fix(xai): map not-found file reads to 404, bill batch reasoning tokens, and add 200k batch tier rates
* refactor(xai): drop routine prose and move tests under tests/unit
* fix(health): hand the resolved provider to list_batches in batch-mode health checks
* test(xai): make tests/unit/llms/xai/batches a package
* fix(xai): walk every page of the files list by pagination_token
---------
Co-authored-by: Mubashir Osmani <mubashir@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* ci: run the unit_selection.sh shard files on every event instead of only fork pull requests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: rename fork-flag to unit-flag now that it applies on every event
* test: move tests/test_litellm root and small trees into tests/unit
Pure renames, no content changes. Follow-up commits in this PR fix
references, merge the three files that already existed in tests/unit,
keep live-provider tests in tests/test_litellm and wire CI.
* test: carry tests/test_litellm conftest isolation into tests/unit
Callback lists, routing fallbacks, cached HTTP clients, logger state, AWS,
proxy-URL and keychain env, and session-end client cleanup now reset for
unit tests too. The environment isolation owns its MonkeyPatch so a test's
own monkeypatch is undone before the model-cost teardown runs.
* test: merge, split and prune the moved root and small-tree tests
Merge batches/test_batch_utils.py and the chat_completions and messages
dispatch tests into the files that already existed in tests/unit. Keep
the live Gemini interactions tests, the async image-fetch format test and
the OpenAI embedding scorer test in tests/test_litellm since they need
real network or keys. Put test_router.py under tests/unit/test_router so
the existing package no longer shadows it. Delete eight tests the audit
found superseded by stronger ones kept in this move.
* ci: run the moved root and small-tree tests under their legacy flags
Add the misc and responses-caching-types flags to unit_selection.sh and
CircleCI, extend enterprise-routing and mcp-integration, and point the
legacy GHA shards, Makefile, redis-compat workflow, merge smoke manifest
and change classifier at the new paths.
* test: make the new tests/unit directories packages
tests/unit/test_package_layout.py requires every directory to carry an
__init__.py, and without one the moved and retained
test_litellm_responses_bridge.py modules collide on import.
* test: scope the unit socket block to tests/unit in shared sessions
The GHA shards collect the legacy test-path and the unit selection in one
pytest session. The unit conftest's loopback-only block leaked into legacy
modules that reach the network at import. The legacy conftest now lifts the
restriction at collect and setup time, and the unit conftest re-applies it
when collecting its own modules.
* test: give the shard-script tests their own GITHUB_OUTPUT
They only passed where the runner set it. The CircleCI unit job's env
allowlist drops it, so the script's redirect failed there.
* test: point the router and module-deletion checks at tests/unit
router_code_coverage and code_qa_check_tests only searched tests/test_litellm,
so the moved router tests no longer counted. The two silent-experiment tests
the audit deleted were the only direct callers of those methods; they are
replaced with tests that assert the forwarded shadow request and the
recursion guard.
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-09-25 11:30:43 -07:00
Renamed from tests/test_litellm/test_cost_calculator.py (Browse further)
