* 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>
* fix(proxy): enforce key-level model allowlist for custom auth
custom_auth_run_common_checks only runs common_checks (team/user/project model checks).
Custom auth now also enforces key-level model restrictions via can_key_call_model.
Move the custom-auth key-access regression tests to test_user_api_key_auth.py and keep test_custom_auth_end_user_budget.py focused on end-user budget behavior.
Made-with: Cursor
* fix(proxy): gate custom-auth key model checks behind opt-in
Keep key-level model allowlist enforcement in custom auth behind `custom_auth_run_common_checks` to preserve backwards compatibility, and update tests to verify default non-enforcement and opt-in enforcement behavior.
Made-with: Cursor
* test(proxy): isolate custom auth default check from shared settings state
Patch `proxy_server.general_settings` to an empty dict in the default custom-auth key-access test so it remains deterministic under shared module state.
Made-with: Cursor
* test(proxy): strengthen custom auth post-check assertions
Tighten custom auth regression tests by asserting exact can_key_call_model args and remove an unused common_checks mock from the default behavior path.
Made-with: Cursor
* fix(agentcore): parse A2A JSON-RPC responses in AgentCore provider
* fix(prompt-templates): ensure_alternating_roles handles tool-call chains
* feat(auth): add JWT claim routing overrides for OAuth2 validation
Made-with: Cursor
* docs(auth): document JWT-to-OAuth2 routing overrides
Add generic docs for running JWT and OAuth2 together, including routing_overrides YAML examples and list-based selector behavior for iss/client_id/aud.
Made-with: Cursor
---------
Co-authored-by: Milan <milan@berri.ai>
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
- Add pop_vertex_request_labels / vertex_request_labels_from_litellm_params in common_utils
- Vertex embeddings: pass litellm_params, set predict body labels; Gemini uses shared helper
- Imagen: top-level labels from metadata; rerank: userLabels for Discovery Engine Rank API
- Thread litellm_params through rerank handler and all BaseRerankConfig implementations
Made-with: Cursor
* update bedrock models in tests
* updated more tests and model_prices_and_context_window
* fix model id and pricing
* replace more sonnet models
* update tests
* git push
* update pricing
* flaky total cost
* monkey patch
* relax the cost change
* fix and revert some changes
* revert the pricing
* chore: move cost/pricing changes to bedrock-cost-fixes branch
* chore: split Bedrock file-api beta stripping to separate branch
Removes strip_unsupported_file_api_betas_for_bedrock_invoke from this branch;
see litellm_bedrock_invoke_strip_file_api_betas for that fix.
Made-with: Cursor
Main rewrote the same tests we moved. Resolution: keep the tests only
in the unit test directory, adopting main's improved patterns (AsyncMock,
assert_called_once, stronger content assertions on streaming).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Move test_chat_completion_snowflake and test_chat_completion_snowflake_stream
from tests/llm_translation/ to tests/test_litellm/llms/snowflake/chat/ so
they run as part of `make test-unit` without requiring API credentials.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Wildcard openrouter/* deployments pass custom_llm_provider=openrouter with
the full openrouter/provider/model id; OpenRouter expects provider/model.
Strip the outer openrouter/ only when the remainder contains a slash so
native ids like openrouter/auto stay intact.
Adds regression test for proxy wildcard path.
Made-with: Cursor
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
Wrap cost-map-dependent tests in try/finally to restore
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] and litellm.model_cost,
preventing test-ordering sensitivity.
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.
The `dimensions` parameter was correctly mapped to `outputDimensionality`
in `optional_params` but never placed in the request body. The Vertex AI
predict endpoint expects it under a `parameters` field.
Add `parameters` dict to `VertexMultimodalEmbeddingRequest` TypedDict and
populate it from `optional_params` in `transform_embedding_request`.
Fixes#24392
Gemini API returns a DOCUMENT modality in promptTokensDetails for PDF
inputs, but the token parser only handled TEXT, IMAGE, AUDIO, and VIDEO.
DOCUMENT tokens were silently dropped, causing cost to be undercounted
by up to 99% for PDF-heavy requests.
Map DOCUMENT tokens to text_tokens since Gemini bills documents at the
text token rate. Applied to all four modality parser loops:
promptTokensDetails, cacheTokensDetails, responseTokensDetails, and
candidatesTokensDetails.
Fixes#24375
Replace _is_gemini_3_model() substring check with a
web_search_billing_unit field in model_prices JSON:
- "per_query": each search query billed individually (Gemini 3.x)
- "per_prompt" (default): flat fee per grounded API call (Gemini 2.x)
Add web_search_billing_unit to 23 Gemini 3.x model entries.
Update docs and tests accordingly.
Add tests for the gpt-5.1/5.2/5.4 reasoning.effort interaction:
- gpt-5.1 with no reasoning allows flexible temperature
- gpt-5.1 with effort='high' drops temperature
- gpt-5.4 with effort='none' allows flexible temperature
- Gemini 2.x charges per grounded prompt (flat $0.035), clamped to 1
regardless of internal query count
- Gemini 3.x charges per search query ($0.014 each)
- Extract web_search_requests from groundingMetadata in non-streaming
responses (parity with streaming path)
- Add search_context_cost_per_query to vertex_ai and base Gemini entries
- Move tests to tests/test_litellm/ (CI directory)
The Responses API map_openai_params passed all params through without
applying model-specific validation. GPT-5 models (except gpt-5-chat)
only accept temperature=1 unless reasoning.effort="none" on models
that support it (5.1, 5.2, 5.4).
Reuse the existing OpenAIGPT5Config logic from chat completions to
validate temperature in the Responses API path. With drop_params=True,
unsupported temperature values are silently dropped; without it,
UnsupportedParamsError is raised.
Fixes#16090
When Gemini sends tool call arguments in the same streaming chunk as a
content block transition, the Anthropic adapter discarded the
processed_chunk containing the input_json_delta. This caused tool_use
blocks to arrive with empty input: {}.
Queue the processed_chunk alongside the block transition events when it
contains input_json_delta data. Applied to both sync and async paths.
Fixes#24134
Allows wrapping multiple inputs in a nested list to produce a single
combined embedding (text + image = 1 vector). Flat lists continue to
produce separate embeddings per input (OpenAI-compatible default).
Examples:
input=["text", "image"] → 2 separate embeddings
input=[["text", "image"]] → 1 combined embedding
input=[["text", "image"], "x"] → 2 embeddings (1 combined + 1 separate)
When multiple inputs were passed to the Gemini embedding endpoint and any
contained multimodal data (images, audio, etc.), LiteLLM incorrectly used
the `embedContent` endpoint which combines all inputs into a single
aggregated embedding. Now uses `batchEmbedContents` with each input as a
separate request, returning N embeddings for N inputs as expected.
Also fixes hardcoded index=0 in batch embedding responses.
