* fix(websearch_interception): drop stream_options when forcing stream=False and replay it on the final stream
* test(websearch_interception): type the conversion helpers and drive the replay test through mock_response
* test(websearch_interception): pin the replay test's values as Final and record follow-ups immutably
* fix(proxy): strip every agentic-loop control key from client bodies, the web search keys included
* fix(interception): move stream_options off forced non-stream calls for code interpreter and headroom, and keep adapters from replaying nested calls
* test: annotate new interception test locals with Final
* fix(responses): drop params a deployment hook removed on sync Responses calls
* test: drive the sync Responses stream_options regression through a mock transport and real Azure config
* test: type the agentic loop recorder and capture the sent request on an object
* test(integration): cover interception stream_options on chat, responses, messages and the SDK
* test(integration): assert the follow-up error text and release a held burst on failure
* test(integration): pin the follow-up failure contract and wait for the replacement worker before teardown
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix: support OpenAI SDK 3.x while retaining 2.x compatibility
* fix: preserve HTTPX compatibility across OpenAI SDK versions
* refactor: trim OpenAI SDK compatibility patch
* refactor: simplify SDK client defaults
* test: cover SDK compatibility across provider routes
* fix: use shared names for SDK transport helpers
* fix: address SDK compatibility review feedback
* test(openai): send requests through the SDK API factory clients
* fix(exceptions): keep the provider response on PaymentRequiredError under httpx 2
* ci(base-sdk): count httpx2 as base-only when a base dependency brings it in
OpenAI SDK 3 depends on httpx2, so the litellm-core install at highest resolution pulls it in through openai. The base-only check now resolves the declared base dependency closure of litellm and litellm-core and accepts extras-only modules owned by a distribution inside that closure
* test: cover OpenAI SDK 3 client paths end to end and read SDK HTTP headers case-insensitively
* test: read C02 spend rows once, wait out the worker healthcheck on respawn, and resolve module owners on Python 3.10
---------
Co-authored-by: Marcus Wood <marcuswood@openai.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(gemini): map OpenAI voice names to Gemini prebuilt TTS voices
* test(gemini): type the voice mapping test helpers
* fix(gemini): leave nova out of the voice mapping since Gemini accepts it as given
* test(gemini): add integration cells for the OpenAI voice mapping on Gemini and Vertex TTS
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(databricks): keep #/$defs refs in json_schema response_format for non-Claude models
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(databricks): type the json_schema response_format override
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(databricks): integration cells for json_schema $defs refs across endpoints
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(databricks): split stacked loop in streaming json_schema cell
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(databricks): mark BaseConfig dict contract on json_schema override
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(databricks): cover json_schema refs on every endpoint, edge refs, sad paths and an outage burst
---------
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(bedrock): keep GPT tool-result images beside the tool result
Bedrock gpt-6.1-sol rejects an image nested in toolResult.content. Put it on the same user turn instead.
* fix(bedrock): read tool-result image support from the price map
OpenAI GPT rows on Bedrock Converse reject an image inside toolResult.content, so those images sit beside the tool result.
* fix: sync price-map test schema and import order
CI validates model_prices_and_context_window.json against an inline schema in test_utils, and ruff checks import order in converse_transformation.
* fix(bedrock): satisfy basedpyright in tool-result image helper
Drop Final assignments inside loops and use TypedDict key checks so the lint type-check gate stays within its merge-base ceiling.
* test(bedrock): cover tool-result image placement helper
Exercise Claude no-op paths, text-only GPT tool results, status preservation, and split text/image tool content for codecov.
* refactor(bedrock): reuse the shared tool-result image placeholder text
---------
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
* feat(decisions): add Databricks ai_decide as a /v1/decisions provider and auto-router decider
* fix(decisions): reject Databricks endpoint names carrying URL separators and keep the provider wiring under llms/
* fix(decisions): reject dot-segment Databricks endpoint names and add Databricks to the dashboard's OSS classifier editor
* fix(ui): name every OSS classifier provider in the classifier radio copy
* feat(decisions): register the Databricks OpenJev decider as an evaluation-mode cost-map entry
* fix(cost-map): declare zero cache rates on the databricks-openjev-qwen35-4b entry
* fix(proxy): reconcile every DB deployment when a registry miss lands on an auto router
A /model/new for an auto router lands on one replica. A request routed to
that auto router on a sibling replica missed it, the model read-through
loaded only the auto router's own row, and the pre-routing hook then picked
a tier the sibling had not loaded, so the caller got a 400 "no healthy
deployments for <tier>" until the next periodic reload. An auto router miss
now runs the full add_deployment reconcile, tiers included. Found by the
audit's two-worker rig on this PR's routing cells; CircleCI's one-worker
proxy never opens the window.
* test(integration): audit cells for Databricks decisions and the Databricks auto-router classifier
Wire cells for /v1/decisions with databricks/<endpoint> deployments, routing
cells for the complexity router's databricks classifier on all three
endpoints with the Postgres rows read back, management cells for the
classifier's spend writes and for the evaluation-mode health check of a
Databricks serving endpoint.
* chore(github_copilot): sync model catalog with Copilot's served models
* test(github_copilot): assert catalog invariants instead of pinning vendor facts
* fix(github_copilot): keep thinking capabilities on served Claude catalog rows
* fix(github_copilot): keep supports_reasoning on catalog rows that shadow the family fallback
* fix(model-catalog): preserve merged Copilot Haiku metadata
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(microsoft_365_copilot): add Microsoft 365 Copilot chat provider with OAuth token exchange
* fix(ui): create a credential for credential-only auth types in Add Model
* fix(microsoft_365_copilot): accept max_tokens and list the chat model
* fix(microsoft_365_copilot): register provider model set
* fix(ui): hide other auth types' fields when credential-only types are filtered
* fix(health): do not inherit stored auth settings when a connection test brings its own api_key
* docs(health): restore connection-test inheritance docstrings
* fix(lint): suppress justified provider boundary casts
* fix(lint): satisfy M365 type-discipline gate
* fix(types): eliminate type-check gate regressions
* style: shorten suppression reasons so ruff format leaves them on one line
* refactor(types): drop shared-file type widening unrelated to the Copilot provider
* fix(health): pass caller headers as secret_fields to connection-test probes
* fix(types): type connection-test probe and token counter locally
* fix(lint): drop cast import from connection-test header getter
* chore: remove explanatory comments flagged by review
* fix(proxy): gate OAuth client credentials behind proxy admin
* fix(router): skip cooldown on caller-scoped OAuth auth failures
* fix(router): skip fallback cooldown on caller-scoped OAuth auth failures
* fix(router): type caller-scoped cooldown lookups
* fix(ci): include Microsoft 365 Copilot tests in unit shard
* fix(proxy): keep saved endpoint when test_connection retests a deployment by id
* fix(m365): collapse doubled Graph replies
* fix(m365): preserve trailing system messages
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock): list the account's invocable models behind bedrock/* when check_provider_endpoint is on
* fix(bedrock): sign the listing query RFC 3986 style and raise BedrockError on a failed listing
* test(utils): keep test_utils.py at main's formatting, only the Bedrock discovery test is new
* fix(bedrock): chain BedrockModelInfo's constructor so the passthrough config keeps its event parser
* fix(bedrock): list discovered ids without the provider prefix so partial wildcards filter
get_valid_models returns bare vendor ids for every other provider and for the static bedrock catalog, and the proxy's wildcard expansion adds the provider prefix itself. The lister prefixed its ids, so a partial wildcard like bedrock/anthropic.* never matched the proxy's filter and listed uncallable bedrock/anthropic.bedrock/<id> entries
* test(bedrock): integration cells for wildcard discovery through the proxy and the SDK
* fix(proxy): keep a partial wildcard a filter when its deployment repeats the prefix
The wildcard expansion guessed filter-or-alias by whether any provider id carried the prefix. A deployment such as model_name bedrock/anthropic.* over model bedrock/anthropic.* can only ever route names that share the prefix, so when the account has no on-demand anthropic.* id (every Anthropic model behind an inference profile) the guess fell into the alias branch and listed bedrock/anthropic.<every id>, none of them callable. A deployment whose model repeats the suffix now always filters, and lists nothing when nothing matches
* fix(proxy): prefix every discovered id under a custom wildcard prefix that starts a vendor id
* test(bedrock): Final and read-only annotations in the wildcard discovery tests
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(bedrock): route Grok 4.7 tools with reasoning to native Chat Completions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock): mint unique tool call ids on native Chat Completions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock): send a blank text block for Converse tool results with no supported content
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(bedrock): default Grok on Bedrock to native Chat Completions and leave Converse unchanged
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock): gate tool call id minting to Grok on native Chat Completions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(bedrock): check the Grok tool call id gate at both call sites
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock): remint positional tool call ids on native Chat Completions for every model
AWS returned call_0, call_1 for GPT 5.6 as well as Grok on 2026-10-09 (and unique ids for GPT 5.6 earlier the same day), so the id format is not fixed per model. Drop the Grok-only gate and remint any call_<digits> id on the route
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock): drop stop sequences for Grok instead of forwarding them to a 400
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>
* test(integration): poll the partition lock witness off the event loop
The witness poll ran a blocking psycopg connect and query on the test's event loop, so the partition DDL task only progressed during the 20ms sleeps and missed the 3s deadline on loaded runners. Polling through asyncio.to_thread lets the DDL reach the held lock concurrently, and the deadline is 10s since it only bounds how long the DDL takes to start waiting
* test(e2e): retry the reasoning turn until the model emits a reasoning item
Whether gpt-5.4-mini emits a reasoning item next to a forced function call is up to the model, and it skipped it on four scheduled runs while a same-SHA rerun passed. The first turn now retries up to three times before the unchanged reasoning-item assertion
* test(e2e): retry a Bedrock Converse model once when it reports no cache tokens
Opus on Bedrock Converse reported zero cache tokens on half of the scheduled runs while a same-SHA rerun passed. A model that comes back uncached is asked once more inside the 5 minute window, and the non-zero cache token assertion is unchanged
* test(e2e): poll until a deleted stored response stops being retrievable
Azure kept serving a just-deleted streamed response for a moment, so a single retrieve did not raise. Both delete tests now poll retrieve until it returns an error and still require a 4xx
* test(e2e): give the Together prompt cache five primed attempts
Together documents its prefix cache as best-effort, and three primed attempts came back with zero cached tokens once while a same-SHA rerun passed
* test(e2e): allow 30s for the idle RSS reading at session start
A loaded router replica took longer than 10s to answer the session-start memory read, which pytest reruns cannot recover. The RSS budget assertion is unchanged
* test(e2e): scope the MCP submission check to its own card
The register call timed out at 15s on a loaded stack and leaked a submitted server, so the retries matched two "3 passing, 1 failing" cards. Registration gets 60s and the check reads only the submitted server's card
* test(router): wait for the primary success record before counting it
The shadow fan-out test waited only for the two shadow success events and then asserted exactly one primary success, which the logging worker sometimes had not delivered yet. It needed a rerun on 5 of 59 main runs
* test(proxy): give the spend-log cleanup run a 1s budget
A 0.25s budget could expire before the first batch on a loaded xdist worker, leaving rows_deleted at 0. One second still stops the 50-batch, 5-second loop on the deadline, which is what the test proves
* test(autorouter): release the slow token count at 2.05s instead of 2.3s
The count only has to finish after a quarter of the 8s worker budget, and the planner gives it 3s, so releasing at 2.3s left 0.7s of slack that a loaded runner used up. 2.05s is still past the quarter mark with almost 1s of slack
* test(xai): run the reasoning-effort tests on grok-4.6 with a prompt that needs reasoning
grok-4.7 now returns reasoning tokens without any reasoning text, so reasoning_content was never set and both tests failed on every scheduled run. Called directly, grok-4.6 returned reasoning text 6 of 6 times on a step-by-step arithmetic prompt but only some of the time on a bare greeting
* test(integration): give the two worker-kill chaos tests the owned-proxy time budget
Each test spends about 50s on the burst and then up to graceful_stop_seconds() stopping its owned proxy, which overran the 90s default pytest timeout on loaded runners. They now use the same 2 * graceful_stop_seconds() + 120 budget as other owned-proxy tests
* test(integration): compare regional image responses without their created timestamp
Two identical generations that straddle a second boundary differ only in created, which failed the byte-for-byte comparison. Every other field and both spend rows are still compared
* test(integration): count only the S3 logger's flush task
The set of asyncio tasks created while the logger starts also picked up client close finalizers left by earlier tests, so the count ranged from 1 to 8. The test now counts the periodic_flush task it owns and cancels
* test(integration): send guardrail timeout probes eight at a time
All 44 probes went at once to a two-worker proxy, so on a loaded runner some guardrails used their whole 1s timeout before their request left the proxy, and the sink never saw them. A different set of providers failed on each run. Eight in flight still overlaps the waits
* test(integration): count a killed Arize chaos worker as gone once it is a zombie
psutil reports an unreaped zombie as still running, so the 10s death check failed whenever the supervisor was slow to reap the SIGKILLed worker, and the stop then overran the 90s default timeout. The test now accepts a zombie or a missing process and has the owned-proxy time budget
* test(integration): send the Typesafe connection test its real model and endpoint
The test passed the proxy alias as litellm_params.model, and /health/test_connection lays the request over the stored deployment, so the alias replaced the real typesafe/ model and the check failed with "LLM Provider NOT provided" on every run since it landed in #45481. It now sends the provider model, api_base and api_key directly
* test(integration): keep DB-stored models out of the usage-routing Redis read test
The owned proxy inherited store_model_in_db and the job's shared database, so a model another test left behind joined the router and added its cooldown key to the MGET the test compares exactly. Reproduced locally with one /model/new model present (3 failed), and green with model loading from the database turned off
* test(vertex_ai): prove the batch upload streams by laziness instead of peak memory
The two tracemalloc ratio tests flaked on unrelated PRs because peak memory on a shared xdist worker includes other threads' allocations and garbage from earlier tests. They are replaced by deterministic checks of the same property: the upload stream parses and maps a row only when it is pulled, so a body whose tail is not JSON yields its valid rows first, and a Path source reflects a row rewritten on disk after the upload started. Making the parse, the output, or the file read eager fails these tests
* test(integration): keep the alias test_connection call as a known bug
* test: type the counting mapper and the Bedrock rerun helper
* test: annotate the new test locals as Final and build them as tuples
* test(vertex_ai): prove pull-driven transforms with the garbage tail alone
The two offline tests in tests/local_testing/test_anthropic_prompt_caching.py failed on main because
#24071 started passing logging_obj to client.post, so assert_called_with on the patched
AsyncHTTPHandler.post no longer matched. The request bodies themselves were still correct
Both now live in tests/unit/llms/anthropic/chat and assert the body and headers that reach the
wire through respx instead of patching our own HTTP handler. The coverage allowlist entry keeps the
five tests that still need provider credentials
Moves 58 legacy nodes (cyberark, logging callback manager, langfuse handler and helpers, SQS, app crypto, bedrock nova and invoke, cloudflare, litellm_proxy, nvidia nim, replicate, triton, convert_dict_to_response, get_model_info, vcr live-call probe) into the tests/unit files that mirror the modules they exercise. Calls that reached huggingface.co, langfuse or 0.0.0.0 are refused at the HTTP boundary with respx. Tests that need credentials, a license, a spawned server, sleeps, a subprocess, or assert nothing stay in their legacy files
* fix(anthropic): count a leading system run through count_tokens' system parameter
Anthropic's count_tokens rejects role "system" at the head of messages, so
/v1/responses/input_tokens with instructions, and /v1/messages/count_tokens
with a system-role message, fell back to the local tokenizer. The shared
Anthropic count_tokens transformation now lifts the leading run of system
messages into the top-level system parameter, the way the chat path sends
it, after any system the caller set. Anthropic direct, Azure AI Anthropic,
and Bedrock Mantle share that transformation.
* test(integration): cover the count_tokens leading-system lift across Anthropic, Azure AI and Bedrock Mantle
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(bedrock): split the <reasoning> tag for gpt-oss only on native Chat Completions
The native Chat Completions route moved a leading <reasoning>...</reasoning>
block into reasoning_content for every model, while only gpt-oss writes its
reasoning inline. A GPT 5.6 or Grok answer that starts with a literal
<reasoning> tag lost that text, streaming and non-streaming alike. Both paths
now split only when the model id is gpt-oss.
* fix(bedrock): drive the inline reasoning split from a cost-map flag
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
#45214 routed both decision formats through the shared decisions IR in
litellm/llms/base_llm/decisions/transformation.py and litellm/types/decisions.py.
That left litellm/llms/base_llm/decisions/systemone.py (to_system_one_request,
question_keys, to_decisions_response, the SystemOne* models and their adapter)
and litellm/types/openai_decisions.py with no importer outside their own unit
tests, so both modules and both test files go.
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(guardrails): run each mode only on streaming, non-streaming, or both
Add stream_scope so a rail can target streaming inference, non-streaming inference, or both per pre, during, and post mode
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(guardrails): honor stream_scope in pipelines and dashboard types
Pipeline steps skipped the stream_scope filter, direct construction ignored mixed-case maps, and schema.d.ts was stale.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(guardrails): skip unmatched stream_scope steps instead of allowing
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(ui): keep stored stream_scope keys for modes not on screen
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(ci): format stream_scope helpers and update fork MCP unit tests
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(mcp): keep hang cancellation tests from timing out during setup
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(guardrails): honor path-defined streaming for stream_scope
Passthrough routes like Gemini streamGenerateContent decide streaming from the URL, so stamp that onto hook data before guardrails run.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(rust): copy AnthropicModelCapabilities instead of cloning
Clippy treats clone-on-Copy as an error, which failed rust-lint on the messages request tests.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(guardrails): trust only server stream classification
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(guardrails): keep streaming marker through deepcopy
scan_raw_request snapshots copy each field, so a plain object() marker would lose identity and skip streaming-only rails.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(cost-map): drop duplicate perceptron-mk1.5 row
Two main cost-map PRs both added the OpenRouter model, so the merge left a second key that CI rejects.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(rust): expect native transcription 429 as RustUpstreamError
HTTP status errors from native routes map through route_error_to_pyerr, so the wheel SIGINT child was dying on an outdated RuntimeError check and never reached the hang probe.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(tests): follow Google Interactions OpenAPI without hardcoded names
The live spec dropped CreateModelInteractionParams and renamed the item path to {interactionsId}. Misc CI failed because the compliance tests still looked those names up as literals.
* test(guardrails): reproduce stream_scope bedrock and passthrough field gaps
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): cover invalid stored stream_scope reads
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(guardrails): classify bedrock stream actions and keep caller is_streaming_request
Co-authored-by: Shivi Jain <mobile.350017@gmail.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(guardrails): make stream_scope_allows public and drop mutable builds
Co-authored-by: Shivi Jain <mobile.350017@gmail.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(guardrails): classify pass-through and Bedrock stream scopes
Co-authored-by: Shivi Jain <mobile.350017@gmail.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(guardrails): harden stream classification and validation
Co-authored-by: Shivi Jain <mobile.350017@gmail.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): add stream scope integration audit
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): avoid mutating passthrough custom body
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): run stream scope audit without enterprise license
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): keep stored scope restart cell on one worker
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): scope stream scope audit sink assertions to the rail under test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): assert logging_only scope absence behind an ordered barrier rail
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): assert one logging_only scan per phase after the barrier rail
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): set request scope on pass-through stream fixtures
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(guardrails): tolerate invalid YAML stream_scope in v1 guardrails list
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore: merge main into litellm_guardrail_stream_scope_fixes
Update pass-through pre-call test callbacks for main's endpoint_type argument
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): add request paths to pass-through fixtures
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): cover websocket pass-through stream scope and LIT-9050 outage spend rows
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* chore(lint): remove unused type discipline suppressions
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(guardrails): script the vertex live upstream in the websocket stream scope test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(guardrails): keep stream marker json-serializable and restore pass-through helper names
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(lint): allow required Bedrock action re-export
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(guardrails): strip the stream marker from pass-through payloads
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(guardrails): drop stream marker by value in scans and snapshots, plain-tuple stream scope state
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): render tag-scoped guardrail modes read-only in the custom code editor
A guardrail whose litellm_params.mode is the tag-scoped dict {tags, default}
crashed the Custom Code editor on open: normalizeMode wrapped the dict into
the mode array and StreamScopeFields rendered it as a React child (error #31,
whole dashboard unmounted). Treat a non-string non-array mode as no editable
modes, show formatGuardrailMode(mode) in a disabled input (read-only, matching
the guardrail info view), and keep mode/stream_scope out of the update payload
for such guardrails.
* fix(ui): resolve merge fallout in guardrails components
Deduplicate toModeArray import after the merge, and move the read-only
guardrail details block back into GuardrailReadOnlyDetails (now rendering
the shared mode/logging-only rows plus the stream-scope detail) so
guardrail_info.tsx stays under the 800-line lint budget. Guardrails UI
suite: 298 passed.
* fix(ui): drop duplicate toModeArray import reintroduced by merge
* chore(pass-through): document the deliberate in-place marker strip as mutable-ok
The clear/update on _parsed_body is load-bearing: rebinding to a fresh
mapping instead breaks 75 pass-through tests because the marker-free body
must propagate through the caller's request dict so downstream guardrail
scans and snapshots never observe the server streaming marker.
* fix(guardrails): move stream_scope after timeout in CustomGuardrail init
Inserting stream_scope before the existing timeout parameter shifted the
positional slot of timeout, so positional callers constructed with their
timeout bound to stream_scope (ValueError) and timeout silently None.
Restores the base parameter order; keyword callers are unaffected.
* fix(guardrails): typing pass for the lint gates
stream_scope leaves the declared constructor parameters (restoring the
base positional surface; keyword construction unchanged), unknown config
values crossing the new stream-scope code paths get typed locals or
cast-ok boundaries, and the passthrough payload literals are annotated.
All three lint gates pass against current main; the guardrail suites are
unchanged (236+5019 passing; one known anyio-driver failure pre-existing
on base).
* style: sort cast imports for the ruff gate
* chore(pass-through): drop unused BEDROCK_STREAMING_ACTIONS re-export
The streaming check now uses is_bedrock_streaming_endpoint; nothing in
the repo imports the name from this module.
---------
Co-authored-by: Shivi Jain <mobile.350017@gmail.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: yucheng <yucheng@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: gabriele <gabriele@berri.ai>
* feat(gemini): accept file content blocks with video_metadata on multimodal embeddings
* test(gemini): annotate the embedding mock helper and keep the type comment short
* fix(gemini-embeddings): keep file blocks through a partial embedding cache hit and validate video_metadata strictly
* test(caching): type the partial-hit cache test and pin its clock
* fix(gemini-embeddings): accept the Files API URI /v1/files returns as a file block's file_id
* fix(gemini-embeddings): 400 on bad input shapes, drop unknown block keys under drop_params, cache multi-block inputs
A bare object `input` answered 500 from both the caching handler and the
transformation; both now answer 400. An unresolved `files/` reference on
vertex_ai/ answered a ValueError 500; it now answers 400 naming the gemini/
provider. An empty `format` passed through to the provider; it now answers 400
naming file.format. Unknown block keys (`detail`, an unknown video_metadata
key, a top-level block key) are dropped under drop_params, global or
per-request, and still answer 400 without it. The embedding cache counted
file blocks against `max_messages`, so a request with 5 or more blocks was
never cached; file blocks no longer count.
* fix(caching): answer 400 for an object embedding input on the cache lookup
* test(gemini-embeddings): annotate the new embedding tests with return types and Final
* test(gemini-embeddings): annotate the transformation and files batch tests with return types and Final
* test(gemini-embeddings): audit file content blocks on the wire, in the cache, in batch uploads and under chaos
Integration cells for gemini/ and vertex_ai/ embedding file blocks with video_metadata: the batchEmbedContents and embedContent wire shapes, format overrides, nested and repeated inputs, every malformed block answering 400 before any provider call, drop_params at the request, deployment and YAML levels, the OpenAI SDK sync and async clients, Redis cache fills, hits, partial hits and the metadata in the key with zero-spend hit rows, chat, responses and messages controls, the vertex_ai/ batch JSONL upload, a mixed fast/slow/malformed/dropped burst and a worker kill. The wire peer now reads chunked request bodies, which the streamed GCS media upload sends
* test(integration): treat an upload the client abandons before its terminating chunk as a disconnect, never a stored request
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(voyage): rebrand to VoyageAI by MongoDB, refresh model list, support both contextual input shapes
* fix(voyage): send auto-chunking params for flat contextual inputs
A flat list[str] or bare str for the contextualized embeddings endpoint is
only valid as documents with enable_auto_chunking=True and input_type=document,
or as queries with input_type=query. Default those params for non-query flat
inputs so the request matches the live API contract, while letting caller-set
values win. Nested list[list[str]] still passes through unchanged.
Tests now assert the auto-chunking params instead of only echoing inputs.
* feat(voyage): route MongoDB-issued keys to ai.mongodb.com
Mirror voyageai.util.get_default_base_url from the official SDK: a key with
the `al-` prefix is issued by MongoDB and is only valid on ai.mongodb.com,
every other key on api.voyageai.com. The choice now lives in one shared
helper that the embedding, contextual, multimodal, and rerank configs all
use for both the default base URL and the Authorization header, so the host
and the key always agree.
Also drops the voyage-4-nano and voyage-multilingual-2 model map entries:
voyage-4-nano is not served on the Voyage API and voyage-multilingual-2 is
an older model, so neither belongs in this change.
* fix(voyage): restore MongoDB routing on contextual endpoint and re-add voyage-4-nano after upstream merge
The upstream merge replaced the contextual config's get_complete_url with a
Voyage-only host and dropped voyage-4-nano from the model map. Reapply the
al- key routing via get_default_base_url and add voyage-4-nano (open-weight,
per docs.voyageai.com) so the branch keeps its task changes on top of upstream.
* fix(voyage): drop voyage-4-nano and the contextual tests upstream already covers
voyage-4-nano is not served on the Voyage API, so it does not belong in the
model map. The contextual input tests duplicate
tests/test_litellm/llms/voyage/test_voyage_contextual_embedding.py, which
landed upstream with the auto-chunking fix this branch was carrying.
* test(voyage): drop sys.path.insert from the voyage common utils test
* fix(voyage): route rerank on the key it authenticates with
get_complete_url picked the rerank host from the environment while the auth
header carried the request key, so an explicit MongoDB-issued key was posted
to api.voyageai.com. validate_environment now hands the resolved key to the
config instance and get_complete_url reads it back, so the host and the
credential always come from one key. The config is built per request, so
nothing carries over between them.
* test: allow ultrafast pricing keys in model prices schema
* test: drop ultrafast schema keys now added upstream
* test(integration): prove voyage key-based host routing on the wire
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(fireworks_ai): forward the LiteLLM user id as user behind fireworks_forward_user_id
* fix(fireworks_ai): keep the forwarded user id when the caller sends extra_body.user
* fix(vertex_ai): forward the inline-tools-2026-09-15 beta to Vertex and Anthropic
* test(vertex_ai): trim the inline-tools beta test docstrings and type their locals
* test(vertex_ai): add audit cells for inline-tools beta forwarding on Vertex Anthropic
* test(vertex_ai): send legal whitespace in the hostile beta header audit cell
* test(vertex_ai): close the SDK clients in the inline-tools audit cells
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* test: move 76 live top-level tests to offline unit and integration coverage
* test: keep the mock-param opt-in guard valid once the top-level senders are gone
* test: address review on offline replacements
* docs(test): drop the deleted harness test file from the harness check command
* test: make the key rebind, team member delete and routes integration tests exercise the legacy paths
* test: make fallback, rpm and spend integration contracts deterministic and clean up their rows, assert the rpm limit in usage-based routing
* test: expect the no-deployments error at the rpm limit and cover the strategy check without pre-call checks
* test: hand member cleanups to the scenario instead of growing a budget list, flatten callback kinds
* test: scope the admin health check to the test's own deployment
---------
Co-authored-by: yuneng <yuneng@berri.ai>
* test: make legacy live tests in spend, batches, openai endpoints and audio dirs offline (partial)
* test: migrate wave-1b live tests offline (guardrails, images, ocr, search, openai endpoints)
* test: fix wave-1b review items, add responses/ocr integration tests and firecrawl unit test
* test: anthropic messages router/bedrock/openai-bridge unit tests for wave-1b nodes
* test: anthropic messages logging, prompt-caching and tool-search unit tests; drop migrated base nodes
* test: finish pass_through_unit_tests nodes, logging drain fix and mutations
* test: migrate anthropic passthrough tests to integration wire tests
* test: fix passthrough migration wire spend row lookup and wildcard config
* test: migrate hosted vllm and openai file passthrough tests offline
* test: move assemblyai and vertex passthrough nodes to in-process unit tests
* test: restore unlisted router node and fix logging worker drain in passthrough unit tests
* test: drop spend-row BUG skip and sharpen non-streaming skip reason for anthropic messages
* test: use public presidio alias after merge
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test: restore the batch and file unit tests the migration rewrote away
* test: restore full legacy intent in anthropic messages router unit tests
Drop the false BUG skip on non-streaming aanthropic_messages logging (success
callbacks do fire; the skipped body filtered on the wrong model), assert the
logged model_group, messages, cost and usage, cover streaming logging for both
Anthropic and Bedrock invoke, assert dict content blocks for Anthropic, Bedrock
invoke and the OpenAI bridge, add the Bedrock invoke leg of the router test,
fall back from a real 401, test system-prompt caching and streaming
message_start cache fields on converse and invoke, send the legacy tool-search
tools and beta header, remove the type: ignore and bare dict helper, and add
in-process native /anthropic passthrough spend logging tests
* test: fix passthrough migration wire tests and drop false native spend BUG skip
The native spend row test read rows by the shared master-key digest, so it
matched other tests' rows; read each row by its own message id instead and
assert tokens, total, spend, tags, provider, api_base and end_user on both the
non-streaming and streaming native routes. Merge the streaming test that never
checked spend, assert exact tags from litellm_metadata, stop rebinding a Final
in a loop, require cost > 0, and add the chat-completions bridge cost case the
legacy test covered
* test: harden the spend, OCR, image, search and guardrail migration replacements
The OCR spend tests now build fresh kwargs per case instead of mutating a
shared fixture, and every payload case asserts the exact logged spend. The
OCR wire test reads its spend row by request id and checks exact page
pricing. Image edit, Nova Canvas, DuckDuckGo, Firecrawl, Bedrock guardrail
and Presidio replacements now fake only the provider HTTP boundary (respx or
an in-process aiohttp server) and assert the outbound request, so the
DuckDuckGo limit, Azure base_model pricing and guardrail masking are proven
rather than assumed
* test: cover Exa and Perplexity search structure and max_results offline and retire the two base search methods
* test: drive batch and file replacements through the provider HTTP boundary and real logging callback
Replace monkeypatched litellm.afile_content and AsyncHTTPHandler doubles with respx routes,
read batch logging metadata from a registered success callback instead of get_logging_payload,
use the real managed-files hook for the GEN-2166 regression, assert outbound request bodies,
pin poller ownership explicitly in the migrated DB-sync tests, and require the scripted
upstream to be hit in the responses error-status wire tests
* test: assert file content download headers pass through the proxy
* test: point spend coverage references at the tests that replaced the retired spend job
* test: assert passthrough identity, spend and route dispatch from the code under test
The AssemblyAI non-admin test asserted metadata it wrote itself and leaked a
background poll to the real AssemblyAI host. It now drives assemblyai_proxy_route
with a real Request and waits for the success callback for its own transcript id.
The Vertex spend test matches its log by call id instead of taking the first event.
The OpenAI files wire test hit the native /{provider}/v1/files route; it now calls
/openai/files so the passthrough is what forwards the upload and delete.
* test: mock only the HTTP boundary in the migrated audio tests
Vertex TTS tests no longer replace _ensure_access_token or AsyncHTTPHandler.post;
the token comes from a mocked Google OAuth endpoint and the synthesize call from
respx. Speech tests assert the outbound body, the transcription cache test polls
for the cache write instead of relying on test ordering, and the model pass-through
test checks the multipart model field per model.
* test: wait on a logger event instead of polling the clock in anthropic messages unit tests
Recorders keep payloads in a rebound tuple and set an asyncio.Event; tests
await it with asyncio.wait_for instead of a sleep-and-deadline poll loop
* test: freeze module-level batch and file response fixtures as Final MappingProxyType
* test: fake the presidio analyzer with an in-memory aiohttp connector
The blocked-entity tests started an aiohttp TestServer, which binds a local
socket. They now hand the guardrail a ClientSession whose connector answers
/analyze and /anonymize in process, so no socket is opened and the outbound
analyze text and entities are still asserted
* test: type anthropic messages router test helpers with LiteLLM's Anthropic TypedDicts
Messages, cached system blocks and tool-search tools now use
AnthropicMessagesUserMessageParam, AnthropicMessagesTextParam,
AnthropicToolSearchToolRegex and AnthropicMessagesTool instead of bare
dict shapes; tools are converted to plain dicts only at the acreate call,
whose tools parameter is list[dict]
* test: type batch limiter helpers with TypedDicts and wait on the logging callback event instead of polling
* test: give the migrated OCR, image and presidio helpers precise types
OCR spend helpers take ReadOnly TypedDicts for kwargs and responses and use
LiteLLM's OCRResponse/OCRUsageInfo instead of local pydantic stand-ins; spend
metadata is validated with a TypeAdapter. The presidio fake uses LiteLLM's
PresidioAnalyzeRequest/ResponseItem types, and the image-edit logger validates
the logged payload instead of storing an untyped dict
* test: signal callback and cache events instead of polling
Recorders keep tuples and set an asyncio.Event, thread-safely, when the payload
for this test's transcript id or upstream URL arrives. The transcription cache
test waits on a Cache subclass that signals after async_add_cache. No clock
polling or sleeps remain in these tests.
* test: assert the batch limiter hook updates the caller's request in place
* test: tolerate model-list probes and read native passthrough rows by owned key
The router's OpenAI-compatible model-info refresh (litellm/router.py:10710)
sends GET /v1/models to configured openai api_bases, so the wire answers it
with an empty list and excludes it from the provider-call assertions. Native
/anthropic spend rows are now read by a per-request virtual key digest and
call_type, then the row's request_id is checked against the message id
* test: expect the OCR alias in the proxy response model
The proxy restamps every OpenAI-compatible response model to the name the
client requested (_override_openai_response_model), so /v1/ocr returns the
scenario alias. The upstream model is now checked on the drained request body
instead of inside the peer, where a failed assert never reached the test
---------
Co-authored-by: yuneng <yuneng@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test: make 77 legacy live tests offline in litellm_utils, router_unit and responses dirs
* test: restore lost coverage in litellm_utils offline replacements
Bound live health-check tasks to the concurrency limit so eager task
creation behind a semaphore fails, route the Langfuse trace-id check
through completion -> Logging.get_trace_id with all four metadata
combinations, run the callback dedup checks through acompletion, pass
the dynamic key via litellm_params, cover the env-inferred default
model list, and add the per-provider audio transcription config lookup
* test: restore router coverage lost in the offline move
Add the missing non-stream LIT-3058 header/count-once test, pin the UTC minute on every
usage-counter test, assert router-level client reuse for transcription, and replace the
private selector-attribute checks with routing outcomes per strategy. Assert outbound bodies
for speech, rerank, image, assistants and moderation, add timeouts to event waits, and drop
the router_unit_tests husk files that no longer hold tests
* test: restore sync stream, router sync stream, error event and field-type coverage for migrated responses tests
Add the sync streaming logging and sync Router.responses streaming cases the
offline replacements dropped, port the legacy per-event and response field-type
validation, assert raw headers, the float created_at conversion, MCP tool headers,
the search_context_size input, and add an offline replacement for the in-stream
context-window error event. Remove helpers left dead in the legacy file.
* test: run numpydoc-backed unit tests in GHA and drop a test that pinned a crash
* test: restore sequence number, item id and content part checks in the responses stream validator
* test: match router logging events to the test's own deployment so late events from other tests are ignored
* test: restore the s3 cold storage history test to its original assertions
---------
Co-authored-by: yuneng <yuneng@berri.ai>
* feat(decisions): serve System One format at /v1/systemone and OpenAI format at /v1/decisions
The System One request format moves to /v1/systemone and /systemone. /v1/decisions and
/decisions now accept the OpenAI Decisions API format, translate it into a System One
request, route it through the same pipeline, and translate the answers back.
* fix(decisions): import assert_never from typing_extensions for Python 3.10
* fix(decisions): cap OpenAI-format questions at the System One limit
/v1/decisions accepted up to 200 questions, but the System One request it translates to takes at most 128, so 129 to 200 questions failed with an internal validation error. Both now share MAX_DECISION_QUESTIONS.
* fix(decisions): return 400 for bodies that are not JSON
* test(decisions): send System One bodies to /v1/systemone in integration tests
* feat(decisions): add OpenAI as a Decisions provider
System One requests to openai/ models are translated to OpenAI's Decisions shape on the way out and OpenAI's answers are translated back, so both /v1/systemone and /v1/decisions can route to gpt-6-luna.
* refactor(decisions): move the OpenAI wire translation into llms/openai
* feat(decisions): route both request formats through a shared decisions IR
System One and OpenAI-format bodies now convert to one internal representation, and each provider translates it to its own wire format. OpenAI deployments receive the caller's messages, images, names, typed choice values, level descriptions and safety_identifier unchanged. System One providers return a 400 for image input. Cached and cache-write tokens are priced on both response shapes, and provider response extras survive the round trip.
* fix(decisions): keep provider fields inside System One answers
* fix(decisions): load on Python 3.10 and 3.11 and bill cached tokens once under custom pricing
Decisions IR dataclasses used a mappingproxy default, which is only hashable from Python 3.12, so import litellm failed on 3.10 and 3.11. Decisions usage now reaches cost_per_token as a Usage with prompt_tokens_details, so custom pricing no longer adds cached and cache-write tokens on top of input_tokens that already include them
* fix(decisions): honor litellm OpenAI key and base settings for the openai provider
OpenAI decisions now resolve the key from litellm.api_key, litellm.openai_key, then OPENAI_API_KEY, and the base from litellm.api_base, OPENAI_BASE_URL, then OPENAI_API_BASE, matching other OpenAI calls. Providers own their configured key and base lookup through the endpoint config.
* test(decisions): clear every OpenAI base setting in the proxy OpenAI deployment test
* fix(decisions): send OpenAI instructions for System One questions without them and reject single-option questions
* fix(decisions): return guardrail_information on OpenAI-format decisions when requested
* refactor(decisions): validate proxy request data before reading guardrail settings
* fix(ollama): one stream id, 400 on non-text tool content, separated tool results, no empty message item
The ollama/ text stream minted a fresh chatcmpl- id per chunk; every chunk now carries the one id of its response.
A tool message with int content raised a TypeError inside ollama_pt and answered 500; it now answers 400 naming the
message index and the type it carried. Merged user, tool, and function turns and the text parts of one message were
joined with no separator; they are joined with a newline. A streamed tool call with no text rebuilds to content null
instead of an empty string, and the Responses bridge no longer opens a message item on a leading empty delta, so a
/v1/responses stream on a tool call completes with the function_call alone, as the non-stream call does
* fix(ollama): defer the BadRequestError annotation so litellm imports on Python 3.10 to 3.13
* fix(ollama): read the user run lazily, type the prompt helpers, and 400 on a non-string text part
* fix(ollama): 400 on a text or image_url part that carries no value
* fix(responses): stream bridged output items at contiguous indexes and reject non-object ollama content parts
The chat-completions bridge reserved output_index 0 for the message item, so a
tool-only stream announced its function_call at index 1 with no item at 0 and the
OpenAI SDK's responses.stream() accumulator raised IndexError. Items now take the
next index in emission order, reasoning included, and response.completed lists
the output in that streamed order.
ollama_pt answers 400 for a content part that is not an object and for an
image_url object without a url string, instead of a 500 or a silent drop.
* fix(responses): list only announced items in the bridged completed snapshot
The Responses bridge drops a message item from response.completed when the
stream never announced one and its text is empty, so a tool-only stream and a
reasoning-only stream end with the items the client saw. The chunk builder's
rebuilt content goes back to what main does; aligning it with the non-stream
shape is its own change for every provider's consumers
* style(responses): sort the itertools import with the other stdlib imports
* test(integration): add ollama prompt-tools and responses bridge audit cells
* refactor(proxy): expose public names for private proxy helpers
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep original class names behind public aliases
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): preserve internal callback filtering
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep _PROXY_ class names for managed files hooks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep old private names in package exports
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): preserve recursive auth helper name
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): align MCP limiter tests with server enforcement
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): match main's MCP limiter tests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep old private names bound in importing modules
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): preserve compatibility imports through strict lint
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): use exact pyright suppression in password helper test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(proxy): add reasons to compatibility import noqa comments
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): update IN-list baseline for renamed helpers
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(bedrock): map scheduled batch job status to in_progress
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(bedrock): cover batch retrieve status lifecycle through the proxy
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(bedrock): drop legacy covers marker and type job payload as Mapping
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(anthropic): fail closed when a token-file or inline-token federation credential is missing a rule or organization id
* refactor(anthropic): flatten the federation-request helper
* test(anthropic): annotate the new WIF regression tests
* test(anthropic): audit cells for legacy federation references missing an id
Integration cells drive the seven clients, files, skills, health, Test Connect and a mixed burst against deployments whose token file or inline token reference lacks a rule id or an organization id, asserting the named 401 and no outbound call, with controls for the static key, the environment ids, the blank reference, the unauthenticated call and the complete shapes. The unit test covers the environment ids completing a token file param
* test(anthropic): strip host federation ids from the audit proxies
* fix(anthropic): let /v1/messages mid-stream failures reach the proxy failure boundary
AnthropicStreamWrapper.async_anthropic_sse_wrapper swallowed every upstream
exception and emitted its own Anthropic error frame, so a provider drop on a
streamed /v1/messages call never reached the proxy's streaming boundary — no
failure spend row, no failure callbacks.
Re-raise when the stream is proxy-managed (detached failure hook armed) so
async_streaming_data_generator runs post_call_failure_hook once and serializes
the error frame; when consumed standalone (SDK litellm.messages path), run the
logging object's async failure handler and keep the client-facing error frame.
Fixes#44742
* test(anthropic): satisfy PT012 single-statement rule in mid-stream error test
* fix(anthropic): dispatch both sync and async failure callbacks
* fix(anthropic): dispatch both sync and async failure callbacks
* test(anthropic): move the regression cases into the mapped test file
* refactor(anthropic): read the public detached-failure hook and drop the explanatory comments
* test(anthropic): drive the mid-stream failure tests through a real logging object
* fix(anthropic): re-raise the provider error from the chat wrapper envelope so the router keeps its pre-content retry
* test(integration): cover mid-stream failure bookkeeping of bridged /v1/messages streams
Nine integration cells for the chat bridge: raw httpx and the Anthropic SDK (sync and async) streams that fail after the first content delta now land exactly one failure SpendLogs row carrying the provider's error class, the non-streaming 500, the response-cache twin and a client that leaves mid-stream keep their bookkeeping, a 24-stream burst lands every call id once, and the standalone SDK stream reports the provider error to failure callbacks once.
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* feat(decisions): add the OpenAI Decisions spec types and the System One translation
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(decisions): share one DecisionsModel config and require model and usage on responses
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(decisions): rename the shared pydantic parent to DecisionsObjectBase
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(decisions): match the SDK on strict choice values and drop the invented min_length bounds
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(decisions): compose DecisionsRequest from model and body and read the translator top down
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(decisions): use the plural Decisions prefix only for the request and response envelopes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(decisions): import assert_never from typing_extensions for Python 3.10
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): dial the multi-region Live API host for realtime sessions
A realtime deployment with vertex_location us or eu dialed
{location}-aiplatform.googleapis.com, which Vertex does not serve for a
multi-region, so the WebSocket handshake came back 404. The URL builder now
resolves its host through the shared Vertex host resolver, which already
maps us and eu to aiplatform.{geo}.rep.googleapis.com and leaves regions
and global unchanged.
* test(vertex_ai): annotate the realtime multi-region URL tests
* fix(vertex_ai): skip the TLS argument when the realtime api_base is plain ws://
The Vertex realtime session and health-check connects passed the shared
TLS context to every websocket dial, so an api_base the transformation
already maps from http:// to ws:// failed with 'ssl argument is
incompatible with a ws:// URI' before any frame was sent. The OpenAI
realtime handler already skips the argument for ws://; the shared helper
now does the same for the Vertex path
* test(integration): cover the Vertex realtime multi-region host through the proxy
Fourteen cells on the scripted Gemini Live upstream: api_base overrides for
us, eu, us-central1 and global complete a turn; malformed locations are
refused before any dial; a missing location defaults to us-central1; the
realtime health check handshakes the override host and reports a malformed
location without dialing; a refused handshake reaches the client and the
next session connects; twelve concurrent sessions across locations each
reach the upstream once; an upstream outage closes every open session and
the proxy recovers
* test(realtime): type the health-check helpers and flatten the burst order
* test(http_handler): type the realtime TLS test signatures
* 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(openai-compat): send provider attribution headers on the default SDK path
Provider-specific headers set in validate_environment are never sent for
OpenAI-compatible providers on the default OpenAI SDK path, which doesn't
call it. Novita's X-Novita-Source has been silently missing as a result.
Add BaseConfig.get_attribution_headers() and merge it into the outbound
headers in _complete_custom_openai, which feeds both the SDK and the
experimental http-handler paths. Caller headers win, case-insensitively.
* feat(perplexity): send X-Pplx-Integration attribution header
Ports the change from #38565 onto the attribution-header hook so it is
sent on the default SDK path too.
Co-authored-by: Saleh Alghusson <1331721+qirh@users.noreply.github.com>
* test: capture attribution headers in-process instead of over a socket
Address review: unit tests now drive litellm.completion into an httpx
transport rather than a local HTTP server; type the header helper as
dict[str, str]; bind the merged headers to a Final instead of
rebinding headers in _complete_custom_openai.
* style: drop explanatory comments flagged by review
---------
Co-authored-by: Saleh Alghusson <1331721+qirh@users.noreply.github.com>
* fix(router): preserve native baseline identity and accounting
* fix(router): preserve injected system caches in native baselines
* fix(router): prepare native baselines through shared request owners
* fix(router): capture native baseline fields from the provider schema
* refactor(router): reuse native provider parameter discovery
* fix(router): keep long native baselines and abstain after compaction
Message history no longer counts against the settings snapshot budget, so long
and non-ASCII native sessions keep modeled baselines. Selected-tier compaction
now abstains because the baseline would otherwise inherit the compacted history.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
* fix(router): judge implicit caching against the selected request
The implicit-cache guard compared the selected response's cache usage with the
projected baseline's breakpoints, so selected-tier cache markers made a usable
unmarked baseline plan look like unexplained caching. The guard now checks the
selected wire request. Also removes a stamp-reuse branch that could never run
because routing clears the stamp first; every pass already captures caller
settings from fresh kwargs.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* fix(ollama): turn streamed prompt-based JSON tool calls into real tool calls
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ollama): separate replayed tool calls from text and tighten parser typing
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Mubashir Osmani <mubashir@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(bedrock): live e2e asserting nova sonic realtime delivers each assistant sentence once
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(bedrock): drop ticket reference from nova sonic e2e docstring
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(bedrock): forward each Nova Sonic assistant sentence once over the realtime API
Nova 2 Sonic sends every assistant text block twice, a SPECULATIVE preview
next to the audio and a FINAL transcript once the audio turn has ended. The
realtime bridge forwarded both, so voice clients rendered each sentence twice
and the FINAL copies opened extra responses after response.done, the last of
which never closed. FINAL assistant text blocks are now dropped whole, so a
turn carries each sentence once inside the one response with its audio
* test(bedrock): tag the live Nova Sonic test and type its helpers
* test(bedrock): pin that the Nova Sonic barge-in marker is dropped with its FINAL block
---------
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>
