PR #18945 added support for capturing Anthropic server-side tool results
(bash_code_execution_tool_result, etc.) in provider_specific_fields, but
the data never reached the Responses API output because:
1. Non-streaming: provider_specific_fields wasn't copied into _hidden_params
2. Streaming: chunk delta's provider_specific_fields wasn't accumulated
3. Tool results weren't mapped to standard output items
This fix:
- Copies provider_specific_fields to _hidden_params in transform_response()
- Accumulates provider_specific_fields from streaming chunk deltas
- Maps bash_code_execution_tool_result to code_interpreter_call output items
with code and outputs (matching OpenAI's native shape)
- Removes redundant function_call items for server-side tools
- Adds OutputCodeInterpreterCall type to the output union
- Promote _fetch_managed_vector_stores_by_uuids from @staticmethod to a module-level
async helper get_managed_vector_store_rows_by_uuids, following the same standalone
helper pattern as get_team_object / get_key_object so the hot-path DB read is a
named importable function rather than an inline prisma_client.db.* call
- Pass no-log=True to both inner _call_aresponses sub-calls so they do not fire
independent billing/monitoring callbacks; cost is accumulated in the synthesized
response's _hidden_params for the outer responses() call
- Add test_H11b covering the primary queries (plural array) function-tool schema,
complementing H11 which exercises only the backward-compat singular query path
Made-with: Cursor
- Re-add should_use_emulated_file_search() to emulated_handler.py so H5/H6/H7/H13 tests don't fail with ImportError
- Remove per-file-id deduplication from _build_search_results_for_include so all chunks are returned (matching OpenAI native file_search behaviour); update test_H14 to assert 2 results
- Extract raw prisma DB query in check_vector_store_ids_access into a static _fetch_managed_vector_stores_by_uuids helper so the hot request path uses a named, testable function instead of an inline prisma_client.db.* call
- Remove developer-local path from test module docstring
Made-with: Cursor
Add _is_reasoning_effort_level_explicitly_disabled to use opt-out semantics
for minimal effort: unknown/unlisted models pass through, only blocked when
the model map explicitly sets supports_minimal_reasoning_effort=false.
xhigh keeps opt-in semantics (must be explicitly supported).
Adds test for unknown-model passthrough and explicit-disabled detection.
Made-with: Cursor
- Add try/except httpx.HTTPStatusError blocks in _async_cancel_batch for
both POST cancel and GET retrieve calls, with verbose_logger error logging
- Fix endpoint extraction inconsistency: compute endpoint from URL without
:cancel suffix so it matches behaviour of create_batch/retrieve_batch
- Add explicit validation that api_base ends with ':cancel' before
stripping it, raising a descriptive error for unsupported custom proxy
URL rewriting scenarios
- Use string-based patch() in test instead of patch.object() for robustness
against import order changes
Made-with: Cursor
_get_token_and_url_context_caching() was hardcoding model=None when
calling _check_custom_proxy(), which raises ValueError when api_base
is set because Gemini proxy URLs need the model name:
{api_base}/models/{model}:cachedContents
Fixes#23846
Azure GPT-5.4+ models now get the same auto-routing treatment as OpenAI
when both `reasoning_effort` and `tools` are used in `litellm.completion()`.
Previously, `reasoning_effort` was silently dropped for Azure; now the
request is bridged to the Responses API which supports both parameters.
Fixes#23914
Fixes#23890 — Mistral's Voxtral transcription with `diarize=true` returns
`segments` (with speaker_id, timestamps) and `language`, but these fields
were dropped when mapping the response to TranscriptionResponse.
The count_tokens handler unconditionally overrode vertex_location to
us-central1 for Claude models, ignoring the user-configured
vertex_count_tokens_location parameter. Also, us-central1 is no longer
a supported region — Google now supports us-east5, europe-west1, and
asia-southeast1.
Now vertex_count_tokens_location takes precedence, vertex_location is
used as fallback, and us-east5 is the default only when neither is set.
Fixes#23872
Models like gemini-3.1-flash-lite-preview send the final streaming chunk
with empty content (text:"") alongside finishReason:"STOP", instead of
omitting content entirely. The existing fix (PR #21577) only handled
chunks without content, so this case was missed.
Now, after processing candidates, if tool_calls were seen in earlier
chunks and a choice has finish_reason="stop", it is overridden to
"tool_calls" to match the OpenAI spec.
Fixes#22900
Strip internal logging ids from emulated sub-calls, dedupe included search_results by file_id, clean unused imports, and add unit coverage for dedupe behavior.
Made-with: Cursor
Include all function_call items when building emulated follow-up input and update tests to assert real emulated routing + Responses-format function tool structure.
Made-with: Cursor
Add Vertex batch cancellation support in LiteLLM batch APIs, route proxy cancel fallback using request provider headers, and return post-cancel batch state via retrieve to keep response shape compatible.
Made-with: Cursor
* fix(fireworks): skip #transform=inline for base64 data URLs
Closes#23583
Appending #transform=inline to a data: URL corrupted the base64 payload,
causing binascii.Error (Incorrect padding) when Fireworks AI attempted to
decode the image. Data URLs are already inlined so the fragment is a no-op
anyway — guard both the str and dict image_url branches to skip the suffix
when the URL starts with "data:".
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(fireworks): skip #transform=inline for base64 data URLs
Closes#23583
* fix(fireworks): skip #transform=inline for base64 data URLs
Closes#23583
* fix(fireworks): skip #transform=inline for base64 data URLs
Closes#23583
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
Add avideo_create_character, avideo_get_character, avideo_edit, and avideo_extension
to the skip condition since Azure video calls don't use initialize_azure_sdk_client.
Tests now properly skip with expected behavior instead of failing:
- test_ensure_initialize_azure_sdk_client_always_used[avideo_create_character] ✓
- test_ensure_initialize_azure_sdk_client_always_used[avideo_get_character] ✓
- test_ensure_initialize_azure_sdk_client_always_used[avideo_edit] ✓
- test_ensure_initialize_azure_sdk_client_always_used[avideo_extension] ✓
Made-with: Cursor
* fix: Fixes https://github.com/BerriAI/litellm/issues/23185
* fix(responses/main.py): ensure litellm metadata custom cost works
* refactor: move all logging updates to a common function, to have just 1 place to update logging kwarg updates
- Fix __main__ block: test returns None now, so always exited 1
- Close litellm_async_client in test_ssl_verification_with_aiohttp_transport
- Save/restore litellm.force_ipv4 and litellm.disable_aiohttp_transport
in test_force_ipv4_transport and test_aiohttp_disabled_transport
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
count_aiohttp_sessions() iterates every object in the Python GC,
which hangs in CI when xdist workers have millions of loaded objects.
Replace with direct session.closed checks — same coverage, no hang.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Remove real HTTP call to example.com in test_force_ipv4_transport
(hangs in CI when network is slow/unavailable)
- Close leaked aiohttp.ClientSession in test_ssl_verification_with_aiohttp_transport
- Add cleanup for transports in test_aiohttp_transport_trust_env_setting
- Add cleanup for handler in test_ssl_security_level
- Add cleanup for transport in test_ssl_context_transport
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add sagemaker_nova provider for Nova models on SageMaker
Add support for custom/fine-tuned Amazon Nova models (Nova Micro, Nova Lite,
Nova 2 Lite) deployed on SageMaker Inference real-time endpoints.
Nova uses OpenAI-compatible request/response format with additional
Nova-specific parameters (top_k, reasoning_effort, allowed_token_ids,
truncate_prompt_tokens) and requires stream:true in the request body.
Nova endpoints also reject 'model' in the request body.
Changes:
- New provider: sagemaker_nova/<endpoint-name>
- SagemakerNovaConfig inherits from SagemakerChatConfig
- Override transform_request to strip 'model' from request body
- Override supports_stream_param_in_request_body (True for Nova)
- Extend get_supported_openai_params with Nova-specific params
- Refactored SagemakerChatConfig to use custom_llm_provider param
instead of hardcoded strings (backwards-compatible)
- Consolidated main.py routing for sagemaker_chat and sagemaker_nova
- 22 unit tests + 9 integration tests (skip-gated)
- Documentation with SDK, streaming, multimodal, and proxy examples
- All tests verified against live SageMaker Nova endpoint
* fix: move integration tests to tests/local_testing/ per test directory policy
* fix: remove unused module-level SagemakerNovaConfig instance
The sagemaker_nova_config singleton was never imported or used — the
ProviderConfigManager creates its own instance via the lambda registered
in utils.py. Removing this leftover boilerplate.
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* fix(bedrock): respect s3_region_name for batch file uploads (#23569)
* fix(bedrock): respect s3_region_name for batch file uploads (GovCloud fix)
* fix: s3_region_name always wins over aws_region_name for S3 signing (Greptile feedback)
* fix: _filter_headers_for_aws_signature - Bedrock KB (#23571)
* fix: _filter_headers_for_aws_signature
* fix: filter None header values in all post-signing re-merge paths
Addresses Greptile feedback: None-valued headers were being filtered
during SigV4 signing but re-merged back into the final headers dict
afterward, which would cause downstream HTTP client failures.
Made-with: Cursor
* feat(router): tag_regex routing — route by User-Agent regex without per-developer tag config (#23594)
* feat(router): add tag_regex support for header-based routing
Adds a new `tag_regex` field to litellm_params that lets operators route
requests based on regex patterns matched against request headers — primarily
User-Agent — without requiring per-developer tag configuration.
Use case: route all Claude Code traffic (User-Agent: claude-code/x.y.z) to
a dedicated deployment by setting:
tag_regex:
- "^User-Agent: claude-code\\/"
in the deployment's litellm_params. Works alongside existing `tags` routing;
exact tag match takes precedence over regex match. Unmatched requests fall
through to deployments tagged `default`.
The matched deployment, pattern, and user_agent are recorded in
`metadata["tag_routing"]` so they flow through to SpendLogs automatically.
* fix(tag_regex): address backwards-compat, metadata overwrite, and warning noise
Three issues from code review:
1. Backwards-compat: `has_tag_filter` was widened to activate on any non-empty
User-Agent, which would raise ValueError for existing deployments using plain
tags without a `default` fallback. Fix: only activate header-based regex
filtering when at least one candidate deployment has `tag_regex` configured.
2. Metadata overwrite: `metadata["tag_routing"]` was overwritten for every
matching deployment in the loop, leaving inaccurate provenance when multiple
deployments match. Fix: write only for the first match.
3. Warning noise: an invalid regex pattern logged one warning per header string
rather than once per pattern. Fix: compile first (catching re.error once),
then iterate over header strings.
Also adds two new tests covering these cases, and adds docs page for
tag_regex routing with a Claude Code walk-through.
* refactor(tag_regex): remove unnecessary _healthy_list copy
* docs: merge tag_regex section into tag_routing.md, remove standalone page
- Add ## Regex-based tag routing (tag_regex) section to existing
tag_routing.md instead of a separate page
- Remove tag_regex_routing.md standalone doc (odd UX to have a separate
page for a sub-feature)
- Remove proxy/tag_regex_routing from sidebars.js
- Add match_any=False debug warning in tag_based_routing.py when regex
routing fires under strict mode (regex always uses OR semantics)
* fix(tag_regex): address greptile review - security docs, strict-mode enforcement, validation order
- Strengthen security note in tag_routing.md: explicitly state User-Agent
is client-supplied and can be set to any value; frame tag_regex as a
traffic classification hint, not an access-control mechanism
- Move tag_regex startup validation before _add_deployment() so an invalid
pattern never leaves partial router state
- Enforce match_any=False strict-tag policy: when a deployment has both
tags and tag_regex and the strict tag check fails, skip the regex fallback
rather than silently bypassing the operator's intent
- Extract per-deployment match logic into _match_deployment() helper to
keep get_deployments_for_tag() readable
- Add two new tests: strict-mode blocks regex fallback, regex-only
deployment still matches under match_any=False
* fix(ci): apply Black formatting to 14 files and stabilize flaky caplog tests
- Run Black formatter on 14 files that were failing the lint check
- Replace caplog-based assertions in TestAliasConflicts with
unittest.mock.patch on verbose_logger.warning for xdist compatibility
- The caplog fixture can produce empty text in pytest-xdist workers
in certain CI environments, causing flaky test failures
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* PR #22867 added _remove_scope_from_cache_control for Bedrock and Azure AI but omitted Vertex AI. This applies the same pattern to VertexAIPartnerModelsAnthropicMessagesConfig."
* PR #22867 added _remove_scope_from_cache_control for Bedrock and Azure AI but omitted Vertex AI. This applies the same pattern to VertexAIPartnerModelsAnthropicMessagesConfig."
* PR #22867 added _remove_scope_from_cache_control to AzureAnthropicMessagesConfig
but missed VertexAIPartnerModelsAnthropicMessagesConfi Rather than duplicating the method again, moved it up to the base AnthropicMessagesConfig so all providers
inherit it, and removed the now-redundant copy from the Azure AI subclass.
* PR #22867 added _remove_scope_from_cache_control to AzureAnthropicMessagesConfig
but missed VertexAIPartnerModelsAnthropicMessagesConfi Rather than duplicating the method again, moved it up to the base AnthropicMessagesConfig so all providers
inherit it, and removed the now-redundant copy from the Azure AI subclass.
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
