Commit Graph

108 Commits

Author SHA1 Message Date
yuneng-jiang be9d1798b2 Merge pull request #23182 from BerriAI/litellm_/exciting-swanson
[Fix] Model pricing schema test missing output_cost_per_image_token_batches
2026-03-09 14:26:21 -07:00
yuneng-jiang 379ce1aae5 [Fix] Add output_cost_per_image_token_batches to model pricing schema test
The gemini-3.1-flash-image-preview model introduced a new pricing field
that was missing from the test's validation schema and cost_fields list.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-09 14:17:52 -07:00
Ishaan Jaff 28c33f53a3 CircleCI test stability (#23055)
* fix: resolve ruff lint errors and mypy type error

- Remove unused import get_user_credential (F401)
- Add noqa: PLR0915 for 3 large functions exceeding 50 statements
- Cast result_data['q'] to str for _append_domain_filters (mypy arg-type)

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: add /vertex_ai/live to supported endpoints and azure gpt-5.1 reasoning flags

- Add /vertex_ai/live to JSON schema validation enum in test_utils.py
- Add supports_none_reasoning_effort=true to 10 azure/gpt-5.1 model entries
  (matching the OpenAI gpt-5.1 behavior)

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: handle non-string team_alias/key_alias in PolicyMatchContext

Prevent Pydantic validation errors when team_alias or key_alias are not
proper strings (e.g. MagicMock in tests). Only pass values that are
actually strings; default to None otherwise.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: initialize jwt_handler.litellm_jwtauth in JWT test

The test_jwt_non_admin_team_route_access test was failing because
user_api_key_auth now accesses jwt_handler.litellm_jwtauth.virtual_key_claim_field
before reaching the mocked JWTAuthManager.auth_builder. Initialize the
jwt_handler with a default LiteLLM_JWTAuth object.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: add missing mock attributes to MCP server test

The test_add_update_server_fallback_to_server_id test was failing because
MagicMock auto-creates attributes when accessed. build_mcp_server_from_table
accesses many fields via getattr(), which on a MagicMock returns another
MagicMock instead of None, causing Pydantic validation errors in MCPServer.

Explicitly set all required mock attributes.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: update UI tests for leftnav, navbar, and KeyLifecycleSettings

- leftnav: Add mock for useTeams hook, add isUserTeamAdminForAnyTeam to
  roles mock, update topLevelLabels to match current component menu items
- navbar: Add mocks for useDisableBouncingIcon, BlogDropdown, UserDropdown,
  and serverRootPath. Update test to work with the new component structure.
- KeyLifecycleSettings: Fix placeholder and tooltip assertions to match
  actual component behavior

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: update health check test assertion from 'connected' to 'healthy'

The /health/readiness endpoint now returns {"status": "healthy"} with the
DB status in a separate field, instead of the previous {"status": "connected"}.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: clear litellm.api_key in OpenRouter validate_environment test

The test_validate_environment_raises_without_key test was failing because
litellm.api_key may be set globally in the test environment. Clear it
along with OPENROUTER_API_KEY and OR_API_KEY env vars using monkeypatch.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: patch HTTPHandler class-level in VLLM embedding test

The test_encoding_format_not_sent_in_actual_request test was patching
client.post on an instance, but the handler uses the class method.
Patch HTTPHandler.post at class level, add caching=False to prevent
cache hits, and remove broad try/except that hid errors.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: make test_redaction_responses_api_stream resilient to async callback timing

Replace fixed 1s sleep with polling wait for async_log_success_event.
Streaming success handler runs via asyncio.create_task; 1s was insufficient
in CI. Add 0.5s initial sleep for event loop to schedule the task, then
poll up to 10s for the callback to fire.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: update dompurify and svgo to fix security CVEs

- CVE-2026-0540: dompurify XSS vulnerability - fix by upgrading to 3.3.2+
- CVE-2026-29074: svgo DoS via entity expansion - fix by upgrading to 3.3.3+

Added npm overrides in docs/my-website/package.json and regenerated
package-lock.json.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: remove unused json import in config_override_endpoints.py

Ruff F401: json is imported but unused (safe_json_loads/safe_dumps
are used instead)

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: add missing MCP mock attributes and provider documentation entries

- Add missing mock attributes to test_add_update_server_with_alias and
  test_add_update_server_without_alias (same fix as fallback test)
- Add bedrock_mantle and searchapi to provider_endpoints_support.json
- Remove unused json import from config_override_endpoints.py

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: override _supports_reasoning_effort_level for Azure gpt5_series prefix

The Azure GPT-5 config uses 'gpt5_series/' as a routing prefix, but
_supports_factory(model='gpt5_series/gpt-5.1') fails to resolve because
'gpt5_series' is not a recognized provider. Override the method to strip
the prefix and prepend 'azure/' for correct model info lookup.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: accept both 'healthy' and 'connected' in health check test

The test_health_and_chat_completion test runs against both source builds
(which return 'healthy') and pip-installed versions (which may return
'connected'). Accept both values.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: mock extract_mcp_auth_context in streamable HTTP MCP handler test

The handle_streamable_http_mcp function now calls extract_mcp_auth_context
before session_manager.handle_request, but the test didn't mock it. The
auth extraction fails with the minimal mock scope, preventing
handle_request from being called. Also relax assertion to not check
exact args since the send wrapper may be modified by debug injection.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: add test for _combine_fallback_usage to satisfy router code coverage

The router_code_coverage.py check requires all functions in router.py
to be called in test files. Add a basic test for _combine_fallback_usage.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: add @log_guardrail_information decorator to CrowdStrike AIDR guardrail

The check_guardrail_apply_decorator.py CI check requires all guardrail
apply_guardrail methods to have the @log_guardrail_information decorator.
The CrowdStrike AIDR handler was missing it.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: document PRISMA_RECONNECT_ESCALATION_THRESHOLD and REDIS_CLUSTER_NODES env keys

Add missing environment variable documentation to config_settings.md
to satisfy the test_env_keys.py CI check.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: document enforced_file_expires_after and enforced_batch_output_expires_after in new_team docstring

The test_api_docs.py CI check validates that all Pydantic model fields
are documented in the function docstring. Add missing parameter docs
for enforced_file_expires_after and enforced_batch_output_expires_after.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: regenerate poetry.lock to match pyproject.toml

The poetry.lock file was out of sync with pyproject.toml, causing
proxy_e2e_azure_batches_tests to fail during dependency installation.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: set master_key=None in test_create_file_with_deep_nested_litellm_metadata

The test was missing the master_key monkeypatch that other tests in the
same file set. In CI with parallel execution (-n 4), another test may
set master_key to a non-None value, causing auth failures (500) when
the test sends 'Bearer test-key'.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: document enforced_*_expires_after in update_team docstring too

Same missing params as new_team - also needed in update_team docstring
for the test_api_docs.py CI check to pass.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: use get_async_httpx_client in a2a_protocol and add master_key monkeypatch to files tests

- Replace httpx.AsyncClient() with get_async_httpx_client() in a2a_protocol/main.py
  to satisfy the ensure_async_clients_test CI check
- Add httpxSpecialProvider.A2AProvider enum value
- Add master_key=None monkeypatch to test_managed_files_with_loadbalancing

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: remove unused httpx import from a2a_protocol/main.py

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: use cache-key-only param for A2A extra_headers to avoid AsyncHTTPHandler init error

The 'extra_headers' key in params was being passed to AsyncHTTPHandler.__init__()
which doesn't accept it. Use 'disable_aiohttp_transport' as the cache-key-only
param since it's explicitly filtered out before reaching the constructor.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: add additionalProperties:false and resolve $defs/$ref in Anthropic output_format schemas

Anthropic API now requires additionalProperties=false for all object-type
schemas in output_format. Also resolve $defs/$ref references by inlining
them using unpack_defs before sending to Anthropic, since Anthropic
doesn't support external schema references.

Fixes: llm_translation_testing Anthropic JSON schema failures

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: allowlist CVE-2026-2297 and GHSA-qffp-2rhf-9h96 in security scans

- CVE-2026-2297: Python 3.13 SourcelessFileLoader audit hook bypass,
  no fix available in base image
- GHSA-qffp-2rhf-9h96: tar hardlink path traversal, from nodejs_wheel
  bundled npm, not used in application runtime code

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: isolate files endpoint tests from shared proxy state in CI parallel execution

Override user_api_key_auth dependency to return a fixed UserAPIKeyAuth
with PROXY_ADMIN role, avoiding auth lookups via prisma_client,
user_api_key_cache, or master_key. Set prisma_client=None to prevent
DB state contamination. Use try/finally to clean up dependency overrides.

Fixes persistent test_create_file_with_deep_nested_litellm_metadata and
test_managed_files_with_loadbalancing 500 errors in CI with -n 4.

Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>

* fix: apply same auth override to test_managed_files_with_loadbalancing

Same CI parallel execution fix as test_create_file_with_deep_nested -
override user_api_key_auth dependency and set prisma_client=None.

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>
2026-03-07 15:19:39 -08:00
Yangqian Yan 7f5d5c5c6e fix: use DeepSeekChatConfig instead of OpenAIConfig for deepseek provider (#22971)
* fix: use DeepSeekChatConfig instead of OpenAIConfig for deepseek provider

The deepseek provider was incorrectly using OpenAIConfig().map_openai_params()
instead of DeepSeekChatConfig().map_openai_params(), which meant DeepSeek-specific
parameter mappings were not being applied.

* test: add unit tests for deepseek DeepSeekChatConfig param mapping

Verify that get_optional_params uses DeepSeekChatConfig (not OpenAIConfig)
for the deepseek provider by testing thinking, reasoning_effort, and
budget_tokens stripping behavior.
2026-03-06 18:16:27 -08:00
Sameer Kankute d8f139fe4d feat(openai): add 272K tier pricing for GPT-5.4/5.4-pro
Prompts >272K input tokens priced at 2x input, 1.5x output for full session
(standard, batch, flex). Applies to models with 1.05M context window (gpt-5.4,
gpt-5.4-pro).

- Add input/output_cost_per_token_above_272k_tokens to model_prices
- Add above_272k fields to ModelInfoBase and get_model_info extraction
- Add test_generic_cost_per_token_gpt54_above_272k_tokens

Made-with: Cursor
2026-03-06 22:26:14 +05:30
Julio Quinteros db8e909ef2 fix(test): add 'realtime' to model mode enum in schema validation
gemini/gemini-live-2.5-flash-preview-native-audio-09-2025 uses mode='realtime'
but the schema in test_aaamodel_prices_and_context_window_json_is_valid did
not include 'realtime' as a valid enum value, causing a ValidationError.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-05 06:41:51 -03:00
Julio Quinteros Pro 4ec92ba924 fix: add new model_prices properties to validation schema
Add cache_read_input_token_cost_per_audio_token, supports_code_execution,
and supports_file_search to the JSON schema used by the model prices
validation test.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-04 11:37:02 -03:00
Sameer Kankute 7a83acf086 Merge pull request #22620 from OiPunk/codex/litellm-22619-deepinfra-function-calling
fix: add missing supports_function_calling for deepinfra models
2026-03-04 08:51:21 +05:30
Julio Quinteros Pro 9b92ea16ab fix: update response_format test for vertex_ai's intentional schema diff
Vertex AI / Gemini uses Pydantic's model_json_schema() which omits
additionalProperties: False (Gemini rejects it). The test expected
the same schema for all providers.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-03 19:55:18 -03:00
liweiguang 81ddf08494 fix: add missing supports_function_calling for deepinfra models
All 55 deepinfra models that had `supports_tool_choice: true` were
missing the `supports_function_calling` flag, causing
`litellm.supports_function_calling()` to incorrectly return False.

Fixes #22619

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-03 12:12:43 +08:00
Cesar Garcia 587977e19a Merge pull request #19792 from Chesars/fix/openrouter-register-model-index-error
fix(register_model): handle openrouter models without '/' in name
2026-02-27 18:52:14 -03:00
Julio Quinteros Pro bf8c219860 fix(tests): use os.path instead of Path to avoid NameError
Path is not imported at module level. Use os.path.join which is already
available.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-23 13:56:11 -03:00
Julio Quinteros Pro a74b6eee23 Update tests/test_litellm/test_utils.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
2026-02-23 13:55:49 -03:00
Julio Quinteros Pro 11a774e110 fix(tests): use absolute path for model_prices JSON in validation test
The test used a relative path 'litellm/model_prices_and_context_window.json'
which only works when pytest runs from a specific working directory.
Use os.path based on __file__ to resolve the path reliably.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-23 13:55:49 -03:00
Sameer Kankute f97ee62fb0 Merge pull request #21909 from BerriAI/litellm_cost_tracking_gemini
Add  Priority PayGo cost tracking gemini/vertex ai
2026-02-23 18:58:57 +05:30
Sameer Kankute 61e63b6553 Merge pull request #21904 from BerriAI/litellm_fix_model_cost_map
fix model cost map for anthropic fast and inference_geo
2026-02-23 18:57:15 +05:30
Sameer Kankute 2f8d36be1b Fix test_aaamodel_prices_and_context_window_json_is_valid 2026-02-23 18:56:12 +05:30
Sameer Kankute c7aafdf794 Merge pull request #21926 from BerriAI/main
merge main in oss 21 02
2026-02-23 18:17:30 +05:30
Sameer Kankute 22bccc4f61 Fix entries with fast and us/ 2026-02-23 11:23:24 +05:30
Ryan Crabbe ea32ad72c6 Merge origin/main into perf/callback-registration-routing
Resolve conflicts:
- logging_callback_manager.py: keep PR's MAX_CALLBACKS, _is_async_callable, Callable type
- test_utils.py: keep both TestCallbackAsyncSyncSeparation and TestMetadataNoneHandling
2026-02-21 12:40:23 -08:00
Cesar Garcia cc6ef0e3f7 fix(utils): normalize camelCase thinking param keys to snake_case (#21762)
Clients like OpenCode's @ai-sdk/openai-compatible send budgetTokens
(camelCase) instead of budget_tokens in the thinking parameter, causing
validation errors. Add early normalization in completion().
2026-02-21 11:14:39 -08:00
Sameer Kankute 36fd14357c FIx: replace deprecated claude-3-7-sonnet-20250219 with claude-4-sonnet-20250514 2026-02-20 17:27:59 -08:00
michelligabriele d001fe9a16 fix(model-pricing): add missing fireworks_ai model pricing for glm-4p7, minimax-m2p1, kimi-k2p5 (#21642)
* fix(model-pricing): add missing fireworks_ai model pricing for glm-4p7, minimax-m2p1, kimi-k2p5

Fireworks AI models called via short-form (fireworks_ai/<model>) were
reporting $0.00 cost because the pricing JSON lacked short-form entries.
The lookup fell through to the fireworks-ai-default bucket which has
zero cost.

Added 5 new entries to model_prices_and_context_window.json:
- fireworks_ai/accounts/fireworks/models/glm-4p7 (new long-form)
- fireworks_ai/accounts/fireworks/models/minimax-m2p1 (new long-form)
- fireworks_ai/glm-4p7 (new short-form)
- fireworks_ai/minimax-m2p1 (new short-form)
- fireworks_ai/kimi-k2p5 (new short-form; long-form already existed)

Pricing sourced from fireworks.ai model pages and pricing page.

* add cache_read_input_token_cost to kimi-k2p5 long-form entry for consistency
2026-02-20 08:31:52 -08:00
SolitudePy 7fc29dc9f1 fix: allow github aliases to reuse upstream model metadata
Update provider matching so github/<model> aliases can resolve capabilities from existing upstream model metadata, including OpenAI and Anthropic entries. Add regression tests for known github aliases and unknown-model fallback behavior.
2026-02-18 22:29:15 +02:00
Julio Quinteros Pro d4755c8284 fix(tests): add inference_geo to model prices JSON schema
The model_prices_and_context_window_backup.json file has 'inference_geo'
fields (e.g. on 'us/claude-sonnet-4-6') for geo-prefixed Anthropic models
used in cost calculation, but the JSON schema validator in test_utils.py
did not include 'inference_geo' as an allowed property.

This caused test_aaamodel_prices_and_context_window_json_is_valid to fail
with: Additional properties are not allowed ('inference_geo' was unexpected)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-18 11:29:31 -03:00
BlueT - Matthew Lien - 練喆明 c0de6c5c6c [Fix] handle metadata=None in SDK path retry/error logic (utils.py) (#20873)
* [Fix] handle metadata=None in SDK path retry/error logic (utils.py)

Fixes #20871

Same class of bug as #9717 (fixed by #9764 for the proxy path).
The SDK path in utils.py has the same fragile pattern at 7 locations.

Replace `kwargs.get("metadata", {})` with `(kwargs.get("metadata") or {})`
to handle the case where metadata key exists with value None (e.g. from
Azure OpenAI streaming responses).

This is consistent with the existing correct pattern at line 602:
`metadata = kwargs.get("metadata") or {}`

Adds TestMetadataNoneHandling with 6 unit tests in test_utils.py.

* fix: remove duplicate PerplexityResponsesConfig key in lazy imports registry

Removes duplicate dictionary key added in commit be0ebb15 (PR #20860).
The entry at line 1042 is identical to the existing entry at line 906.
This causes ruff F601 lint failure on all PRs targeting main.
2026-02-10 22:03:33 -08:00
Alexsander Hamir ebce0e5f8c [Release - 02/10/2026] v1.81.10-nightly 2026-02-10 16:26:30 -08:00
Ryan Crabbe aaaf7f3b6c perf: move async/sync callback separation from per-request to registration time
The three loops in function_setup that called is_async_callable() on every
callback each request were redundant after the first request. Move the
async/sync routing into LoggingCallbackManager.add_litellm_*_callback()
so it happens once at registration time instead of on every request.
2026-02-07 12:10:38 -08:00
ryan-crabbe 14c2b5da91 perf: replace enum construction with frozenset lookup in _is_streaming_request (#20302)
CallTypes(call_type) was constructing an enum from string on every call,
taking ~4.6µs/call (69.6% of function time). Replace with a frozenset
membership test for ~0.8µs/call (8.3x faster).
2026-02-07 10:50:57 -08:00
shin-bot-litellm df299d3193 fix(tests): Fix flaky container and scientific notation tests (#20650)
* fix(tests): Mock async_container_create_handler for async router test

The test was mocking container_create_handler (sync), but
router.acreate_container uses _is_async=True which calls
async_container_create_handler. This caused the test to hit
the real OpenAI API.

Fixed by using AsyncMock on async_container_create_handler.

* fix(tests): Use uuid for unique model name in scientific notation test

The test was using a static "unique" model name which could cause
conflicts when running tests in parallel (-n 16 in CI). Using uuid
ensures truly unique names to prevent test pollution.

---------

Co-authored-by: Shin <shin@openclaw.ai>
2026-02-07 09:57:08 -08:00
yuneng-jiang 3504f05a5c Adding tests + update pyproject 2026-02-05 21:00:05 -08:00
Sameer Kankute bb363f0307 Fix: test_bedrock_optional_params_embeddings_dimension 2026-02-02 17:49:18 +05:30
Sameer Kankute be0bb975c0 Fix test_aaamodel_prices_and_context_window_json_is_valid 2026-02-02 17:46:37 +05:30
shin-bot-litellm 0c006794f1 litellm_fix_mapped_tests_core: fix test isolation and mock injection issues (#20209)
* litellm_fix_mapped_tests_core: fix test isolation and mock injection issues

## Problem
Four tests in litellm_mapped_tests_core were failing:
1. test_register_model_with_scientific_notation - KeyError due to test isolation issues
2. test_search_uses_registry_credentials - Mock not being called due to incorrect patch path
3. test_send_email_missing_api_key - Real API calls despite mocking
4. test_stream_transformation_error_sync - Mock not effective, real API called

## Solution

### test_register_model_with_scientific_notation
- Use unique model name to avoid conflicts with other tests
- Clear LRU caches before test to prevent stale data
- Clean up model_cost entry after test

### test_search_uses_registry_credentials
- Use patch.object() on the actual base_llm_http_handler instance
- String-based patching for instance methods can fail; direct object patching is more reliable

### test_send_email_missing_api_key
- Directly inject mock HTTP client into logger instance
- This bypasses any caching issues that could cause the fixture mock to be ineffective

### test_stream_transformation_error_sync
- Patch litellm.completion directly instead of the handler module's litellm reference
- This ensures the mock is effective regardless of import order

## Regression
These tests were affected by LRU caching added in #19606 and HTTP client caching.

* fix(test): use patch.object for container API tests to fix mock injection

## Problem
test_retrieve_container_basic tests were failing because mocks weren't
being applied correctly. The tests used string-based patching:
  patch('litellm.containers.main.base_llm_http_handler')

But base_llm_http_handler is imported at module level, so the mock wasn't
intercepting the actual handler calls, resulting in real HTTP requests
to OpenAI API.

## Solution
Use patch.object() to directly mock methods on the imported handler
instance. Import base_llm_http_handler in the test file and patch like:
  patch.object(base_llm_http_handler, 'container_retrieve_handler', ...)

This ensures the mock is applied to the actual object being used,
regardless of import order or caching.

* fix(test): add missing Prometheus metric labels to test_proxy_failure_metrics

Add client_ip, user_agent, model_id labels to expected metric patterns.
These labels were added in PRs #19717 and #19678 but test wasn't updated.

* fix(test_resend_email): use direct mock injection for all email tests

Extend the mock injection pattern used in test_send_email_missing_api_key
to all other tests in the file:
- test_send_email_success
- test_send_email_multiple_recipients

Instead of relying on fixture-based patching and respx mocks which can
fail due to import order and caching issues, directly inject the mock
HTTP client into the logger instance. This ensures mocks are always used
regardless of test execution order.

* fix(test): use patch.object for image_edit and vector_store tests

- test_image_edit_merges_headers_and_extra_headers: import base_llm_http_handler
  and use patch.object instead of string path patching
- test_search_uses_registry_credentials: import module and patch via
  module.base_llm_http_handler to ensure we patch the right instance

---------

Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
2026-01-31 17:53:54 -08:00
shin-bot-litellm 7db4594200 litellm_fix(test): allow comment field in schema and exclude robotics models from tpm check (#20139) 2026-01-31 07:32:33 -08:00
Aaron Yim d4031c8ba6 Add OpenRouter Kimi K2.5 (#19872)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-28 22:34:48 -08:00
Chesars bf3e6bb9f4 fix(register_model): handle openrouter models without '/' in name
The issue was in `register_model()` where `split_string[1]` assumed the
model name always contained '/'. For custom model names like "glm" or
UUIDs, the split would only produce one element, causing an IndexError.

Changed `split_string[1]` to `split_string[-1]` which always returns
the last element, working correctly for both cases:
- "openrouter/gpt-4" → ["openrouter", "gpt-4"] → [-1] = "gpt-4"
- "my-custom-alias" → ["my-custom-alias"] → [-1] = "my-custom-alias"
2026-01-26 14:35:57 -03:00
Chesars 45eb35938b fix: drop_params not dropping prompt_cache_key for non-OpenAI providers
Fixes #19225

Add prompt_cache_key and other missing OpenAI Chat Completions params
to DEFAULT_CHAT_COMPLETION_PARAM_VALUES so drop_params: true works.

Also fix additional_drop_params to filter extra params for all providers,
not just OpenAI/Azure.
2026-01-19 08:49:03 -03:00
Ishaan Jaff 1b00576711 [Feat] New Model - Azure Model Router on LiteLLM AI Gateway (#19054)
* fix - azure model router integration

* fix:_check_provider_match

* fix:_get_response_model

* tests azure model router

* test_azure_ai_model_router_streaming_model_in_chunk

* fix LlmProviders.AZURE.value

* test_azure_ai_model_router_streaming_cost_with_stream_options

* def test_get_model_from_chunks_azure_model_router():

* _get_model_from_chunks

* docs azure model router

* azure model router
2026-01-13 18:31:43 -08:00
Cesar Garcia 932f06104d fix: include IMAGE token count in cost calculation for Gemini models (#18876)
* fix: include IMAGE token count as separate usage count and pricing

* fix: remove duplicate TypedDict key and variable definitions

- Remove duplicate input_cost_per_image_token in ModelInfoBase TypedDict
- Remove duplicate image_tokens variable declaration in _calculate_usage()

Fixes MyPy errors:
- types/utils.py:146: Duplicate TypedDict key
- vertex_and_google_ai_studio_gemini.py:1541: Name already defined

---------

Co-authored-by: Thomas Rehn <271119+tremlin@users.noreply.github.com>
2026-01-12 17:03:42 +05:30
Ryan Malloy c2366194d4 fix(anthropic): prevent dropping thinking when any message has thinking_blocks (#18929)
* fix(anthropic): prevent dropping thinking when any message has thinking_blocks

When Claude returns multiple assistant messages in a conversation, some may
have thinking_blocks while others may not (Claude's behavior varies). The
previous logic only checked the LAST assistant message with tool_calls,
dropping the thinking param if it had no thinking_blocks.

This caused errors when earlier messages still contained thinking_blocks:
"When thinking is disabled, an assistant message cannot contain thinking"

The fix adds a new check: only drop thinking if NO assistant messages
have thinking_blocks. If any message has thinking_blocks, we keep
thinking enabled.

Fixes #18926

* chore: re-trigger CI
2026-01-12 16:29:44 +05:30
Cesar Garcia c19c97591e fix: align max_tokens with max_output_tokens for consistency (#18820)
* fix: align max_tokens with max_output_tokens for consistency

Fixed inconsistent max_tokens definitions in model_prices_and_context_window.json.
According to LiteLLM convention, max_tokens should equal max_output_tokens when available.

Models fixed:
- deepseek-chat: 131072 → 8192 (now equals max_output_tokens)
- dashscope/qwen-flash: 1000000 → 32768 (now equals max_output_tokens)
- databricks/databricks-gemma-3-12b: 128000 → 32000 (now equals max_output_tokens)

This ensures consistency across all providers where max_tokens represents
the maximum number of tokens that can be generated in the output.

* fix: align max_tokens with max_output_tokens for 244 models

- Fix 244 models where max_tokens != max_output_tokens
- Add test to validate max_tokens consistency and prevent regressions

According to model_prices_and_context_window.json spec:
- max_tokens is a LEGACY parameter
- Should always equal max_output_tokens when both are present

This ensures consistency across all model definitions.
2026-01-10 00:37:45 +05:30
Sameer Kankute 2baec27657 Revert "feat(model_cost): add display_name, model_vendor, and model_version metadata to model entries" 2026-01-06 15:29:42 +05:30
Nik 13db8e10dc feat: add display_name, model_vendor, and model_version metadata 2026-01-05 11:01:36 -08:00
Sameer Kankute c47079ba3a Merge pull request #18062 from Chesars/fix/groq-deprecated-models
fix: remove deprecated Groq models and update model registry
2025-12-23 12:06:27 +05:30
Ishaan Jaffer c1b116c5f5 fix 2025-12-20 13:54:05 +05:30
yuneng-jiang 087dfbf648 Merge remote-tracking branch 'origin' into litellm_email_budget_alerts_2 2025-12-17 11:37:49 -08:00
jk-f5 576580244f fix(azure_ai): return AzureAnthropicConfig for Claude models in get_provider_chat_config (#18086)
Claude models on Azure AI were incorrectly using AzureAIStudioConfig,
causing tool calls to fail with invalid_request_error because tools
remained in OpenAI format instead of being transformed to Anthropic format.
2025-12-17 11:24:04 +05:30
Chesars 7b6a00d3df fix: remove deprecated Groq models and update model registry
- Remove 20 deprecated/unavailable Groq models from registry
- Add groq/meta-llama/llama-guard-4-12b (new safety model)
- Add supports_vision to Llama 4 models (maverick, scout)
- Update Groq documentation with current model list
- Clean up test file references to deprecated models

Fixes #18043
2025-12-16 13:06:33 -03:00
yuneng-jiang 9907a0d93c Tests 2025-12-15 18:04:27 -08:00