* refactor(typing): replace pass-through Any with object in 13 annotations
* docs(client): say dict[str, object] in the models get docstring
* refactor(typing): drop the unused Span aliases in base_cache and levo
* refactor(typing): take a Mapping in delete_nested_value and cover the fresh copy
* fix(typing): deep-copy a read-only Mapping in delete_nested_value through a dict
* fix(proxy): buffer tool discoveries in redis and let the leader write LiteLLM_ToolTable in one statement
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): declare the redis family on the tool discovery buffer and drop the blind except and cast
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): satisfy LIT010 and LIT014 in the tool discovery buffer
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): mark the aggregation fold Final
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): requeue drained tool rows to redis when the write provably did not apply
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): drain tool discoveries on their own lock and scheduler job, not the spend commit
* chore(proxy): suppress the untyped apscheduler add_job on the tool discovery job
* refactor(proxy): move the LiteLLM_ToolTable bulk upsert into its own module next to the other bulk upserts
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): name the LiteLLM_ToolTable bulk write span so the prisma span check resolves it
* refactor(proxy): move the tool discovery drain out of DBSpendUpdateWriter into tool_registry_writer
* refactor(proxy): share db_write_failure_is_requeue_safe from exception_handler so the spend writer stays untouched
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Add OpenCode Go model discovery, protocol routing, session affinity, and published pricing metadata. Cover Chat Completions, Responses, Messages, and Gemini through the existing provider adapters.
Fixes#31568
* feat(ui): configure the default Usage time range
* fix(ui): retain the selected calendar preset during input sync
* fix(ui): preserve fallback dates when applying across DST
* fix(router): route decisions calls only to deployments whose provider supports decisions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(router): account for indirect route helper coverage
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(router): pin the chat leg so the mixed-group check is deterministic
Weights pick the Bedrock leg for chat instead of relying on simple-shuffle landing on both legs. The route filter now passes the candidate list through unchanged in type, so the pre-existing selector lines lose their pyright ignores
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: joshua <joshua@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(typing): narrow Any sources across providers, proxy and guardrails (wave 1)
* refactor(typing): narrow Any sources across hubs, providers and proxy (wave 2)
* refactor(typing): validate RunwayML task JSON and let dotprompt loaders accept exported prompts
* fix: restore pass-through behavior on paths the typing pass tightened
MCP client IP extraction trusts X-Forwarded-For only when use_x_forwarded_for is True, dotprompt skips a malformed JSON prompt entry instead of raising, RunwayML task payloads pass through unvalidated, and a malformed provider body raises the same AttributeError as before at the CompactifAI, Gemini, and mock transport parse sites
* fix(runwayml): keep a malformed 2xx task body on the 500 path
* fix(edenai,cli): keep a non-object body in the error and fail on a malformed migration report
EdenAI's embedding and image generation parse dropped a non-object body from the error
they raised, so the message no longer named what the provider sent. A helper now raises
with the body in the message, and both paths have a regression test.
`lite encryption migrate` exited 0 with no message when the proxy's report was not an
object or its residual_legacy was not a number, where base crashed. It now fails with a
message naming the value.
The CompactifAI and Gemini image-edit non-object body tests accept TypeError or
AttributeError, which both base and this branch raise, so they guard against a
ValidationError instead of pinning one class. RunwayML's async parse gets the same
non-object body test as the sync one.
* fix: keep base's error classes, duck-typed checks and fail-closed guardrails the typing pass changed
* test: annotate the new regression tests' locals with Final
* test: annotate the remaining new test locals with Final
* feat: add OpenAI 12-hour cache write pricing
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix: omit empty cache-write response fields
* style: format cache-write fields
* fix(cost): bill openai 30m and 12h cache writes from the usage split, add gpt-5.6 rates
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): apply the 12h long-context write rate only above the token threshold
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cost): key cache write rates by TTL instead of growing the rate tuple
_get_token_base_cost returned a positional 6-tuple and every cache lifetime added a slot to it, to the off-peak helper and to every caller. It now returns a TokenBaseCosts dataclass whose cache write rates live in one mapping keyed by TTL. The TTLs come from the ephemeral_*_input_tokens fields on CacheCreationTokenDetails, so supporting a new lifetime only means adding that usage field and its rate key
A lifetime with no rate of its own now always falls back to the cache creation rate after off-peak pricing is applied. Before this the non-tiered 12h rate and the tiered 1h rate fell back to the rate from before off-peak, so the same request billed differently depending on the pricing path
* refactor(cost): hardcode the cache write TTLs as a Literal instead of parsing usage field names
Parsing ephemeral_*_input_tokens names saved nothing, since a new TTL still needs a usage field and provider parsing code. The TTLs are now a CacheWriteTTL Literal with an explicit rate key per TTL
* refactor(cost): resolve cache write lifetime rates to floats at lookup
Decide the 1h and 12h cost map key in the threshold loop, then resolve each
rate once after off-peak with the base write rate as the default, so no None
flows through the cost code. Add an integration case for a 12h write on a
row without a 12h rate
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(cost): name every cache write TTL, marking 5m and 30m as base rate
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(cost): list every cache write TTL in one rate key table, None meaning the base write rate
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(cost): drop base rate entries from the cache write rate table and rely on fallback
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(cost): key cache write rates by plain string TTL
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(cost): fill missing cache write TTL rates with the base write rate after off-peak
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(cost): default missing cache write TTL rates to the base write rate inline
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(cost): rename cache write rate key table to make clear it only covers long TTLs
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(cost): list every cache write TTL and bill writes of an unknown TTL at the base write rate
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(cost): resolve tiered cache write TTL rates after off-peak instead of passing None
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(cost): carry cache write TTL rates on TokenRates and drop TokenBaseCosts
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* refactor(cost): define TokenRates before its first use to drop the string annotation
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(cost): build the TokenRates TTL default with default_factory and type tiers as Mapping
MappingProxyType({}) as a dataclass default is rejected on Python 3.11, where
mappingproxy is unhashable, so import litellm failed there. The tier type
moves from dict[str, object] to Mapping[str, object] (LIT001), with tier_rate
accepting a Mapping to match.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(cost): type select_tier_for_input tiers as Mapping so tier_rate callers stay typed
The tier returned as a bare dict made every tier_rate call site a partially
unknown argument once tier_rate took Mapping[str, object]. The range bounds are
now validated with a TypeAdapter instead of indexing an unknown list.
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* fix(responses): honor per-call custom pricing on the native Responses API path
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(responses): narrow the custom pricing regression test to the type gates
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(main): expose register_custom_pricing_for_request for the responses path
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(responses): mark custom pricing test locals Final
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): price per-call custom rates request-locally instead of registering them globally
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): bind per-call rates on the request logging object instead of inferring them in Logging
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): keep Router deployments on the cost-map pricing path
Router inherits cache rates onto the deployment's cost-map entry, so a routed
Responses call binds no request-local price and keeps billing cached tokens at
the inherited rate. Moves the deployment-id lookup to router_utils so the
Responses and completion paths share it.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): gate request-local pricing on the typed deployment model_info
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>
* fix(router): keep image requests off deployments declared supports_vision false in pre-call checks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): type the vision pre-call helpers so the basedpyright gate holds
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(router): keep the pre-call index set typed without a mutable annotation
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(router): cover the vision pre-call helpers directly for the router coverage check
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(router): type the vision pre-call test helpers
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(router): cover the no-params and unresolvable-provider vision branches
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: joshua <joshua@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): await the per-request rollup enqueues and report their failures
The daily and entity spend rollups ran in an unreferenced asyncio task that
nothing awaited or drained, so a shutdown after the spend log was enqueued
could drop every rollup for that request, and a malformed metadata payload
dropped the request from all daily tables at debug level. The rollups now run
inline in update_database, each helper failure is logged through
spend_log_error with the request id, and unreadable metadata only costs the
row its metadata-derived fields
Resolves LIT-6027
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): type the rollup failure helpers for the lint gates
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): track the rollup enqueue task so shutdown drains it
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(spend): shutdown drain waits for an in-flight rollup enqueue
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(spend): register the rollup task without blocking the cost callback
Awaiting the rollups inline made a blocked queue put stall increment_spend_counters, so budget checks could run on stale counters. The task is now only registered via spawn_logging_task; drain_logging_tasks still waits for it on shutdown
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: joshua <joshua@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(chat): support PDF, text, Word, and Excel attachments
* test(chat): match the document attachment recovery banner
---------
Co-authored-by: Ishaan <ishaan@berri.ai>
Move the liteadmin-builder pin from litellm-admin-agent ef501e9 to
5661c80, which ships certifi 2026.10.19 and aiohttp 3.14.5 in the
/opt/liteadmin venv. That certifi drops emSign ECC Root CA - G3, whose
intermediates were revoked; the earlier bundled-CA updates did not
reach this venv because it installs from the agent's own lock file.
The only other change in ef501e9..5661c80 is the AgentChat bump from
litellm-admin-agent#24 (Slack follow-up routing with models that reject
structured output).
* fix(aws_polly): read the engine from the bare model name
speech() strips the aws_polly/ prefix before AWSPollyTextToSpeechConfig sees
the model, so _extract_engine_from_model got a bare "standard", found no
slash and returned the neural default. Every Polly request went out with
Engine: neural whatever the model named.
Take the last path segment instead, which covers both the bare name and the
prefixed one.
* test(aws_polly): move imports to the top of the file
* docs(aws_polly): update the engine comment to the bare model name
* feat(proxy): add LITELLM_OFFLINE_MODE to stop every request the proxy makes on its own
* fix(ui): name LITELLM_OFFLINE_MODE where the cost map panel says local mode is forced
* test: isolate the offline-mode tokenizer tests from the local Hugging Face cache
* test: cover the offline policy templates and the cached Kimi K3 tokenizer
* test(integration): count Kimi K3 tokens in the offline-mode egress test
* refactor(token_counter): skip non-bundled tokenizers in offline mode instead of listing downloaded ones
---------
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
* feat(chat): port Moyai UI with Model Hub and images
* feat(chat): add Models sidebar with embedded Model Hub
* feat(chat): polish Model Hub with provider cards and logos
* refactor(chat): use a provider dropdown in Model Hub
* feat(chat): keep workspace switching visible with a Chat identity
* Add minimal opt-in Chat usage metrics and prioritize Chat in workspace selector
* fix(chat): enable usage metrics by default only when chat is used
* fix(chat): count requesting users with frontend-only metrics
* feat(chat): send default-on request metrics to litellm-tel
The router plants its deployment fields in litellm_metadata for Interactions
calls, while the proxy put the request's metadata (spend_logs_metadata, tags,
key fields) under metadata. The spend log resolves litellm_metadata and only
carries user_api_key* fields over, so spend_logs_metadata never reached
LiteLLM_SpendLogs. Route /interactions like /responses so both land in
litellm_metadata.
Fixes#47841
Co-authored-by: Igor Tavares <2163472+igorborgest@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* feat(ui): sort every teams table data column
* fix(ui): order unlimited team limits as infinity and verify org scope
* fix(ui): validate team sort filters without recursion
* feat(ui): sort every users table data column
* fix(ui): order unlimited user budgets as infinity and verify org scope
* fix(ui): cover user sort queries and document pagination bound
* fix(ui): preserve Aria usage token breakdown and viewer model access
* fix(ui): make Aria conversations easier to read and reply to
* fix(ui): wrap long headings in assistant tables
* feat(ui): simplify Aria and add usage charts with PDF answer export
* fix(ui): retain full chart values in Aria PDF exports
* fix(deps): upgrade vulnerable Python dependencies
* fix(deps): lock patched Python dependency versions
* fix(otel): preserve JSON export with the updated SDK
* test(otel): cover JSON export with the updated SDK
* test(otel): update SDK log records and worker discovery
* fix(ui): align Lens peer dependency with patched Next.js
* fix(otel): hand the AgentOps exporter a session it owns for the JWT header
OpenTelemetry 1.45 moved the OTLP HTTP exporter's requests.Session behind a
transport, so writing the minted JWT to the exporter's private _session raised,
was swallowed, and every AgentOps batch went out unauthenticated. The exporter
now creates the session, passes it through the public session= argument and
sets the Authorization header on it
The tests now drive a real export, serving the token endpoint with respx and
capturing the OTLP POST with requests_mock, instead of reading SDK internals
* fix(otel): skip FastAPI instrumentation once the app has started
opentelemetry-instrumentation-fastapi 0.66b1 wraps build_middleware_stack instead
of calling add_middleware, so instrumenting an app whose middleware stack is
already built no longer raises. The call silently did nothing while we still
registered the global response propagator. Check the built stack up front and
skip both, which is what the existing test expects
* test(otel): assert exported requests and span flags instead of SDK internals
OpenTelemetry 1.45 dropped the exporter's private _headers and sets the W3C
random-trace-id flag on new traces, so traceresponse ends in -03. The Langtrace
and Langfuse tests now export through requests_mock and check the URL and headers
the collector receives, and the traceresponse tests expect the server span's own
trace flags
* fix(deps): bump dashboard zod to 4.6.6 and make the vendored Lens use it
zod 4.6.5 is flagged by the dependency scan and blocks osv-scan on every PR. A
root bump alone leaves the vendored Lens tarball, which pins zod 4.6.5 exactly,
on its own nested copy, so a top-level zod override points every consumer at the
root version and the lock carries a single zod 4.6.6
* test(ui): stub the tag summary fetch the client panel retry refreshes
Retrying the model breakdown refetches /tag/summary, which this integration test
left on the real network. When that request failed before the assertion, the
panel switched to its summary error and unmounted the model row, so the test
passed or failed by timing
* fix(deps): drop the duplicated Lens override from the dashboard package.json
* style(ui): format the client panel fetch stub
---------
Co-authored-by: Yuneng Jiang <yuneng@berri.ai>
* feat(ui): consolidate gateway and usage assistants as Aria Agent
* refactor(ui): give Aria an original blue sprite mascot
* feat(ui): prompt shared Aria from usage and retire duplicate usage agent
* fix(ui): keep Aria naming consistent and reachable across dashboard
* feat(ui): open Aria in a floating popup with suggested questions
* fix(ui): simplify the shared Aria Agent title
* feat(proxy): add LITELLM_DISABLE_LATEST_RELEASE_CHECK to stop the release check
The dashboard asks the proxy for the latest LiteLLM release, and the proxy fetches it from api.github.com on every cache miss. Deployments that block or audit outbound traffic had no way to turn that off. With LITELLM_DISABLE_LATEST_RELEASE_CHECK=true the endpoint returns null without making a request, which the dashboard already treats as no upgrade banner.
* fix(proxy): regenerate dashboard types for the release check flag
The endpoint docstring feeds the OpenAPI description, so the ui-api-types
check needs schema.d.ts regenerated. The docstring now says the flag skips
every outbound request, which stays true once the changelog feed is read
too
---------
Co-authored-by: Sujit Nirmal <nirmalsujit891@gmail.com>
Co-authored-by: yucheng-berri <293926326+yucheng-berri@users.noreply.github.com>
