* add moonshot/kimi-k2.6 to model registry
* add moonshot/kimi-k2.6 to backup model registry
* add tests for moonshot/kimi-k2.6 model registry
* fix moonshot/kimi-k2.6 pricing and add reasoning support
* fix moonshot/kimi-k2.6 pricing and add reasoning support in backup
* update kimi-k2.6 tests: fix pricing, add tool_choice and reasoning checks
* fix: load kimi-k2.6 registry tests from local backup instead of remote cost map
* Add supported providers to prompt caching doc
* Move Z.ai / GLM to cache_control marker list
* Mark xAI models as supporting prompt caching
* Narrow xAI prompt caching flag to models with documented cache pricing
* Add prompt caching flag to grok-4, grok-4-0709, grok-4-latest
---------
Co-authored-by: Michael Riad Zaky <michaelr@Michaels-MacBook-Air.local>
* feat(proxy): add NO_OPENAPI env var to disable /openapi.json endpoint (#25696)
* feat(proxy): add NO_OPENAPI env var to disable /openapi.json endpoint - Fixes#25538
* test(proxy): add tests for _get_openapi_url
---------
Co-authored-by: Progressive-engg <lov.kumari55@gmail.com>
* feat(prometheus): add api_provider label to spend metric (#25693)
* feat(prometheus): add api_provider label to spend metric
Add `api_provider` to `litellm_spend_metric` labels so users can
build Grafana dashboards that break down spend by cloud provider
(e.g. bedrock, anthropic, openai, azure, vertex_ai).
The `api_provider` label already exists in UserAPIKeyLabelValues and
is populated from `standard_logging_payload["custom_llm_provider"]`,
but was not included in the spend metric's label list.
* add api_provider to requests metric + add test
Address review feedback:
- Add api_provider to litellm_requests_metric too (same call-site as
spend metric, keeps label sets in sync)
- Add test_api_provider_in_spend_and_requests_metrics following the
existing pattern in test_prometheus_labels.py
* fix: ensure `litellm_metadata` is attached to `pre_call` guardrail to align with `post_call` guardrail (#25641)
* fix: ensure `litellm_metadata` is attached to pre_call to align with post_call
* refactor: remove unused BaseTranslation._ensure_litellm_metadata
* refactor: module level imports for ensure_litellm_metadata and CodeQL
* fix: update based off of Codex comment
* revert: undo usage of `_guardrail_litellm_metadata`
* feat: add pricing entry for openrouter/google/gemini-3.1-flash-lite-preview (#25610)
* fix(bedrock): skip synthetic tool injection for json_object with no schema (#25740)
When response_format={"type": "json_object"} is sent without a JSON
schema, _create_json_tool_call_for_response_format builds a tool with an
empty schema (properties: {}). The model follows the empty schema and
returns {} instead of the actual JSON the caller asked for.
This patch:
- Skips synthetic json_tool_call injection when no schema is provided.
The model already returns JSON when the prompt asks for it.
- Fixes finish_reason: after _filter_json_mode_tools strips all
synthetic tool calls, finish_reason stays "tool_calls" instead of
"stop". Callers (like the OpenAI SDK) misinterpret this as a pending
tool invocation.
json_schema requests with an explicit schema are unchanged.
Co-authored-by: Claude <noreply@anthropic.com>
* fix(utils): allowed_openai_params must not forward unset params as None
`_apply_openai_param_overrides` iterated `allowed_openai_params` and
unconditionally wrote `optional_params[param] = non_default_params.pop(param, None)`
for each entry. If the caller listed a param name but did not actually
send that param in the request, the pop returned `None` and `None` was
still written to `optional_params`. The openai SDK then rejected it as
a top-level kwarg:
AsyncCompletions.create() got an unexpected keyword argument 'enable_thinking'
Reproducer (from #25697):
allowed_openai_params = ["chat_template_kwargs", "enable_thinking"]
body = {"chat_template_kwargs": {"enable_thinking": False}}
Here `enable_thinking` is only present nested inside
`chat_template_kwargs`, so the helper should forward
`chat_template_kwargs` and leave `enable_thinking` alone. Instead it
wrote `optional_params["enable_thinking"] = None`.
Fix: only forward a param if it was actually present in
`non_default_params`. Behavior is unchanged for the happy path (param
sent → still forwarded), and the explicit `None` leakage is gone.
Adds a regression test exercising the helper in isolation so the test
does not depend on any provider-specific `map_openai_params` plumbing.
Fixes#25697
---------
Co-authored-by: lovek629 <59618812+lovek629@users.noreply.github.com>
Co-authored-by: Progressive-engg <lov.kumari55@gmail.com>
Co-authored-by: Ori Kotek <ori.k@codium.ai>
Co-authored-by: Alexander Grattan <51346343+agrattan0820@users.noreply.github.com>
Co-authored-by: Mohana Siddhartha Chivukula <103447836+iamsiddhu3007@users.noreply.github.com>
Co-authored-by: Amiram Mizne <amiramm@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
Add Baseten Model API pricing entries for Nemotron, GLM, Kimi, GPT OSS, and DeepSeek models with validated model slugs. Include a focused regression test to assert provider and per-token pricing values.
Made-with: Cursor
* fix(vertex_ai): support pluggable (executable) credential_source for WIF auth (#24700)
The WIF credential dispatch in load_auth() only handled identity_pool and
aws credential types. When credential_source.executable was present (used
for Azure Managed Identity via Workload Identity Federation), it fell
through to identity_pool.Credentials which rejected it with MalformedError.
Add dispatch to google.auth.pluggable.Credentials for executable-type
credential sources, following the same pattern as the existing identity_pool
and aws helpers.
Fixes authentication for Azure Container Apps → GCP Vertex AI via WIF
with executable credential sources.
* feat(logging): add component and logger fields to JSON logs for 3rd p… (#24447)
* feat(logging): add component and logger fields to JSON logs for 3rd party filtering
* Let user-supplied extra fields win over auto-generated component/logger, tighten test assertions
* Feat - Add organization into the metrics metadata for org_id & org_alias (#24440)
* Add org_id and org_alias label names to Prometheus metric definitions
* Add user_api_key_org_alias to StandardLoggingUserAPIKeyMetadata
* Populate user_api_key_org_alias in pre-call metadata
* Pass org_id and org_alias into per-request Prometheus metric labels
* Add test for org labels on per-request Prometheus metrics
* chore: resolve test mockdata
* Address review: populate org_alias from DB view, add feature flag, use .get() for org metadata
* Add org labels to failure path and verify flag behavior in test
* Fix test: build flag-off enum_values without org fields
* Gate org labels behind feature flag in get_labels() instead of static metric lists
* Scope org label injection to metrics that carry team context, remove orphaned budget label defs, add test teardown
* Use explicit metric allowlist for org label injection instead of team heuristic
* Fix duplicate org label guard, move _org_label_metrics to class constant
* Reset custom_prometheus_metadata_labels after duplicate label assertion
* fix: emit org labels by default, remove flag, fix missing org_alias in all metadata paths
* fix: emit org labels by default, no opt-in flag required
* fix: write org_alias to metadata unconditionally in proxy_server.py
* fix: 429s from batch creation being converted to 500 (#24703)
* add us gov models (#24660)
* add us gov models
* added max tokens
* Litellm dev 04 02 2026 p1 (#25052)
* fix: replace hardcoded url
* fix: Anthropic web search cost not tracked for Chat Completions
The ModelResponse branch in response_object_includes_web_search_call()
only checked url_citation annotations and prompt_tokens_details, missing
Anthropic's server_tool_use.web_search_requests field. This caused
_handle_web_search_cost() to never fire for Anthropic Claude models.
Also routes vertex_ai/claude-* models to the Anthropic cost calculator
instead of the Gemini one, since Claude on Vertex uses the same
server_tool_use billing structure as the direct Anthropic API.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* fix(anthropic): pass logging_obj to client.post for litellm_overhead_time_ms (#24071)
When LITELLM_DETAILED_TIMING=true, litellm_overhead_time_ms was null for
Anthropic because the handler did not pass logging_obj to client.post(),
so track_llm_api_timing could not set llm_api_duration_ms. Pass
logging_obj=logging_obj at all four post() call sites (make_call,
make_sync_call, acompletion, completion). Add test to ensure make_call
passes logging_obj to client.post.
Made-with: Cursor
* sap - add additional parameters for grounding
- additional parameter for grounding added for the sap provider
* sap - fix models
* (sap) add filtering, masking, translation SAP GEN AI Hub modules
* (sap) add tests and docs for new SAP modules
* (sap) add support of multiple modules config
* (sap) code refactoring
* (sap) rename file
* test(): add safeguard tests
* (sap) update tests
* (sap) update docs, solve merge conflict in transformation.py
* (sap) linter fix
* (sap) Align embedding request transformation with current API
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) mock commit
* (sap) run black formater
* (sap) add literals to models, add negative tests, fix test for tool transformation
* (sap) fix formating
* (sap) fix models
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) commit for rerun bot review
* (sap) minor improve
* (sap) fix after bot review
* (sap) lint fix
* docs(sap): update documentation
* fix(sap): change creds priority
* fix(sap): change creds priority
* fix(sap): fix sap creds unit test
* fix(sap): linter fix
* fix(sap): linter fix
* linter fix
* (sap) update logic of fetching creds, add additional tests
* (sap) clean up code
* (sap) fix after review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) add a possibility to put the service key by both variants
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) update test
* (sap) update service key resolve function
* (sap) run black formater
* (sap) fix validate credentials, add negative tests for credential fetching
* (sap) fix validate credentials, add negative tests for credential fetching
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) lint fix
* (sap) lint fix
* feat: support service_tier in gemini
* chore: add a service_tier field mapping from openai to gemini
* fix: use x-gemini-service-tier header in response
* docs: add service_tier to gemini docs
* chore: add defaut/standard mapping, and some tests
* chore: tidying up some case insensitivity
* chore: remove unnecessary guard
* fix: remove redundant test file
* fix: handle 'auto' case-insensitively
* fix: return service_tier on final steamed chunk
* chore: black
* feat: enable supports_service_tier to gemini models
* Fix get_standard_logging_metadata tests
* Fix test_get_model_info_bedrock_models
* Fix test_get_model_info_bedrock_models
* Fix remaining tests
* Fix mypy issues
* Fix tests
* Fix merge conflicts
* Fix code qa
* Fix code qa
* Fix code qa
* Fix greptile review
---------
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: Josh <36064836+J-Byron@users.noreply.github.com>
Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: milan-berri <milan@berri.ai>
Co-authored-by: Alperen Kömürcü <alperen.koemuercue@sap.com>
Co-authored-by: Vasilisa Parshikova <vasilisa.parshikova@sap.com>
Co-authored-by: Lin Xu <lin.xu03@sap.com>
Co-authored-by: Mark McDonald <macd@google.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
* fix: expose reasoning effort fields in get_model_info and add together_ai/gpt-oss-120b
- litellm/utils.py: pass supports_none_reasoning_effort and
supports_xhigh_reasoning_effort through _get_model_info_helper so
get_model_info() returns them (previously silently dropped). Fixes#25096.
- model_prices_and_context_window.json: add together_ai/openai/gpt-oss-120b
with supports_reasoning: true so reasoning_effort is accepted for this
model without requiring drop_params. Fixes#25132.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: consolidate duplicate together_ai/openai/gpt-oss-120b entry and sync backup file
* fix: link commit to GitHub account for CLA verification
---------
Co-authored-by: Austin Varga <austin@knowmi.ai>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(pricing): add unversioned vertex_ai/claude-haiku-4-5 entry
Missing unversioned entry causes cost tracking to return $0.00 for
all requests using vertex_ai/claude-haiku-4-5. All other Vertex AI
Claude models have both versioned and unversioned entries.
* fix(router): skip misleading tags error when no candidates (e.g. cooldown)
Return early from get_deployments_for_tag when healthy_deployments is empty so
tag-based routing does not raise no_deployments_with_tag_routing after cooldown
filters all deployments. Adds regression test.
Made-with: Cursor
* feat(oci): add embedding support and update model catalog
- Add OCIEmbeddingConfig for OCI GenAI embedding models
- Add 16 new chat models (Cohere, Meta Llama, xAI Grok, Google Gemini)
- Add 8 embedding models (Cohere embed v3.0, v4.0)
- Update documentation with embedding examples
- Update pricing for all new models
* test(oci): add unit tests for OCI embedding support
- 17 unit tests covering OCIEmbeddingConfig
- Tests for URL generation, param mapping, request/response transform
- Tests for model pricing JSON completeness
* style(oci): format with black and ruff
* fix(oci): correct embedding request body format
OCI embedText API expects inputs, truncate, and inputType at the
top level of the request body, not nested under embedTextDetails.
Fixed transformation and updated tests accordingly.
Verified with real OCI API: 3/3 embedding models working.
* docs: clarify tag routing early return and test intent
Made-with: Cursor
* fix(oci): address code review findings from Greptile
- P1: Fix signing URL mismatch with custom api_base by accepting
api_base parameter in transform_embedding_request
- P2: Remove encoding_format from supported params (OCI does not
support it, was silently dropped)
- P2: Raise ValueError for token-array inputs instead of silently
converting to string representation
- Add test for token-list rejection
* fix(mcp): add STS AssumeRole support for MCP SigV4 authentication
MCPSigV4Auth only supported static AWS credentials or the boto3 default
credential chain. Production Kubernetes environments typically authenticate
via IAM role assumption (sts:AssumeRole), which was not possible.
Add aws_role_name and aws_session_name parameters to the MCP SigV4 auth
stack. When aws_role_name is provided, MCPSigV4Auth calls sts:AssumeRole
to obtain temporary credentials before signing requests. Explicit keys,
if also provided, are used as the source identity for the STS call;
otherwise ambient credentials (pod role, instance profile) are used.
* fix: stop logging credential values and add missing redaction patterns
Replaces raw credential values in debug/error log messages with
boolean presence checks or type names. Adds PEM block, GCP token,
JWT, SAS token, and service-account blob patterns to the redaction
filter. Fixes private_key pattern to capture full PEM blocks instead
of stopping at the first whitespace.
Addresses: Vertex AI credential JSON (including RSA private key)
being logged to stderr on health check failures.
* fix: log only field names for UserAPIKeyAuth, not full object
* style: apply black formatting to experimental_mcp_client/client.py
* style: fix black/isort formatting and mypy error in proxy_server.py
- Fix black formatting in experimental_mcp_client/client.py (done in prev commit)
- Fix black/isort formatting in key_management_endpoints.py, proxy_server.py, transformation.py
- Fix mypy: iterate over optional list safely (access_group_ids or []) in proxy_server.py
* fix(test): patch check_migration.verbose_logger directly to fix xdist ordering issue
When test_proxy_cli.py tests run before test_check_migration.py in the same
xdist worker, litellm.proxy.db.check_migration is already in sys.modules.
Patching litellm._logging.verbose_logger has no effect on the already-bound
reference. Patch the correct target (check_migration.verbose_logger) and
import the module before patching so the order doesn't matter.
* fix(mypy): make api_base Optional in PydanticAIProviderConfig to match base class signature
---------
Co-authored-by: Ihsan Soydemir <soydemir.ihsan@gmail.com>
Co-authored-by: Milan <milan@berri.ai>
Co-authored-by: Daniel Gandolfi <danielgandolfi@gmail.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: user <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
* Litellm ishaan april1 (#25103)
* fix(proxy): enforce upperbound key params on key/update and add custom_key_update hook
The /key/update endpoint did not enforce upperbound_key_generate_params,
allowing users to bypass configured limits (tpm_limit, rpm_limit,
max_budget, duration, budget_duration) by updating an existing key
instead of generating a new one.
Extract the upperbound enforcement logic from _common_key_generation_helper()
into a standalone _enforce_upperbound_key_params() function and call it from
both the generate and update paths. For updates, None values are skipped
(not filled with defaults) since they mean "don't change this field".
Also adds a custom_key_update config option and user_custom_key_update global,
mirroring the existing custom_key_generate pattern, so custom key validation
logic can fire during key updates as well.
* fix(proxy): invoke custom_key_update hook in bulk update path
The user_custom_key_update hook was only called in update_key_fn
(single key update) but not in _process_single_key_update (bulk
update path), allowing custom validation to be bypassed via the
/key/update/bulk endpoint. Mirror the hook invocation in both paths.
* fix(proxy): pass UpdateKeyRequest to hook in bulk path, not BulkUpdateKeyRequestItem
Move the custom_key_update hook invocation to after UpdateKeyRequest
is constructed so the hook receives the same type in both single and
bulk update paths. Previously the bulk path passed
BulkUpdateKeyRequestItem (5 fields only), which would cause
AttributeError for hooks accessing fields like tpm_limit or models.
* fix(bedrock): promote cache usage to message_delta for Claude Code (#24850)
Ensure Bedrock/Anthropic-compatible streaming exposes cache usage where Claude Code reads it by promoting message_stop usage onto message_delta and preserving usage fields in fake-streamed message_delta events.
Made-with: Cursor
* fix(search): Support self-hosted Firecrawl response format in search transform (#24866)
The `transform_search_response` method only handled Firecrawl Cloud (v2)
response format where `data` is a dict with `web`/`news` keys. Self-hosted
Firecrawl (v1) returns `data` as a flat list of result objects, causing an
`AttributeError: 'list' object has no attribute 'get'`.
Detect the response format by checking if `data` is a list (self-hosted)
or dict (cloud) and handle both cases.
Cloud format: {"data": {"web": [...], "news": [...]}}
Self-hosted: {"success": true, "data": [{"url": "...", "title": "...", ...}]}
Co-authored-by: Synergy <synergyoclaw@gmail.com>
* feat: add environment and user tracking to prompt management (#24855)
* feat: add environment and user tracking to prompt management
- Add environment (development/staging/production) and created_by columns to LiteLLM_PromptTable
- Update unique constraint to [prompt_id, version, environment]
- All CRUD endpoints support environment filtering and user tracking
- Redesigned prompt detail page with environment tabs and version history
- UI: environment filter on list page, environment selector in editor
- 8 new tests for environment and user tracking
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: Black formatting and add environments to PromptInfoResponse TypeScript type
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: address Greptile review findings
- P1: delete_prompt scopes in-memory cleanup to environment when provided
- P2: dotprompt_content parsed directly regardless of environment flag
- P2: use distinct for environments query
- P2: fix double-fetch on initial mount in prompt_info.tsx
- fix: remove unsupported select kwarg from find_many
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: address remaining Greptile review comments
- Remove unused useCallback import (index.tsx)
- Remove unused ENV_COLORS variable (prompt_info.tsx)
- P1: in-memory fallback in get_prompt_versions now respects environment filter
- P1: reset selectedEnv when promptId changes to avoid stale state
- Cyclic imports are pre-existing pattern, not introduced by this PR
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: scope patch_prompt to environment using primary key
- Add environment query param to patch_prompt endpoint
- Look up target row by composite key (prompt_id + version + environment)
- Update by primary key (id) to target exactly one row
- Fixes Greptile finding: patch with multiple environments no longer ambiguous
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: use actual start_time for failed request spend logs (#24906)
async_post_call_failure_hook set both start_time and end_time to
datetime.now(), making all failed requests show duration=0. Use the
actual start_time from litellm_logging_obj instead, so spend logs
reflect the real request duration on timeout and other failures.
Fixes#24888
* feat(bedrock): add nova canvas image edit support (#24869)
* feat(bedrock): add nova canvas image edit support
* fix(bedrock): support PathLike inputs for nova image edit
* chore: sync schema.prisma copies from root
* fix(mypy): correct type-ignore code for delta_usage arg-type
* fix(mypy): cast status_code to str, suppress intentional str yield
* fix(lint): extract _create_content_block_chunks to fix PLR0915
* fix(lint): extract helpers to fix PLR0915 in prompt endpoints
---------
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: redhelix <amin.lalji@gmail.com>
Co-authored-by: Synergy <synergyoclaw@gmail.com>
Co-authored-by: Talha Anwar <37379131+talhaanwarch@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: madhu19991 <madhu@thunkai.com>
Co-authored-by: Srikanth @adobe <devarakondasrikanth@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(test): update model armor streaming test to handle string or int error code
---------
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: redhelix <amin.lalji@gmail.com>
Co-authored-by: Synergy <synergyoclaw@gmail.com>
Co-authored-by: Talha Anwar <37379131+talhaanwarch@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: madhu19991 <madhu@thunkai.com>
Co-authored-by: Srikanth @adobe <devarakondasrikanth@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
These models include the full 1M token context at standard pricing with no 2x surcharge above 200k tokens.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
Addresses Greptile review feedback: replace direct litellm.model_cost
lookup with the standard _supports_factory infrastructure used by
supports_reasoning, supports_native_streaming, etc.
- Add supports_native_structured_output() utility in litellm/utils.py
- Add supports_native_structured_output field to ModelInfoBase type
- Wire field into _get_model_info_helper return dict
- Delegate from Bedrock _supports_native_structured_outputs to utility
- Add field to JSON schema validator in test_utils.py
Main has two duplicate keys for vertex_ai/gemini-embedding-2-preview.
Our JSON round-trip collapsed them to the second (text-only) entry, but
PR #23599 intentionally keeps the first (multimodal pricing) entry.
Restore the multimodal entry to avoid conflicts.
Integration tested 28/28 (10 sync + 10 streaming + extras) on the
native outputConfig.textFormat path in us-west-2. deepseek.v3.2 does
not support native structured output (Bedrock returns 400).
Integration testing confirmed gemma-3 (4b/12b/27b) ignores the JSON
schema and returns free text, and nemotron-nano (9b/12b) errors with
"Tool calling is not supported in streaming mode" even on sync calls.
Remove the flag so these models fall back to the tool-call approach.
Also fix test assertions to match (nemotron-nano-3-30b is supported,
gemma-3 and nemotron-nano-12b are not).
Move the source of truth for which Bedrock models support native structured
outputs (outputConfig.textFormat) from a hardcoded substring set
(BEDROCK_NATIVE_STRUCTURED_OUTPUT_MODELS) to the cost JSON via a new
"supports_native_structured_output" flag. This makes it possible to add
support for new models (including Claude Sonnet 4.6, which was missing)
by updating the JSON alone, with no code changes needed.
- Remove incorrect supports_prompt_caching from gpt-4-0314 (predates the feature)
- Make data-URL detection case-insensitive in Gemini tool call result conversion
- Mock show_banner/generate_feedback_box in max_budget tests to prevent real I/O
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Set output_cost_per_second to 0.0 (was 0.0001) for whisper-1 and
azure/whisper-1: transcription is billed on input duration only,
not output duration
- Fix cost_per_second() in openai/cost_calculation.py: change elif to if
so input_cost_per_second is evaluated independently of output_cost_per_second,
and remove the erroneous completion_cost = 0.0 assignment that masked
any previously-set output cost
- Add TestCostPerSecondArithmetic unit tests covering both cost fields,
the None-guard, and zero-duration edge case
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
