* 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>
## Problem
Tests using mocked HTTP clients were hitting real APIs because:
1. HTTP client cache was returning previously cached real clients
2. isinstance checks failed due to module identity issues from sys.path
### Tests affected:
- test_send_email_missing_api_key
- test_send_email_multiple_recipients (resend & sendgrid)
- test_search_uses_registry_credentials
- test_vector_store_create_with_simple_provider_name
- test_vector_store_create_with_provider_api_type
- test_vector_store_create_with_ragflow_provider
- test_image_edit_merges_headers_and_extra_headers
- test_retrieve_container_basic (container API tests)
## Solution
1. Add clear_client_cache fixture (autouse=True) to clear
litellm.in_memory_llm_clients_cache before each test
2. Fix isinstance checks to use type name comparison
(avoids module identity issues from sys.path.insert)
## Why not disable_aiohttp_transport
The default transport is aiohttp, so tests should work with it.
Clearing the cache ensures mocks are used instead of cached real clients.
## Regression
PR #19829 (commit f95572e3ed) added @respx.mock but cached clients
from earlier tests were being reused, bypassing the mocks.
Co-authored-by: shin-bot-litellm <shin-bot-litellm@users.noreply.github.com>
* fix: make HTTPHandler mockable in OIDC secret manager tests
- Add _get_oidc_http_handler() factory function to make HTTPHandler
easily mockable in tests
- Update test_oidc_github_success to patch factory function instead
of HTTPHandler directly
- Update Google OIDC tests for consistency
- Fixes test_oidc_github_success failure where mock was bypassed
This change allows tests to properly mock HTTPHandler instances used
for OIDC token requests, fixing the test failure where the mock was
not being used.
* fix: patch base_llm_http_handler method directly in container tests
- Use patch.object to patch container_create_handler method directly
on the base_llm_http_handler instance instead of patching the module
- Fixes test_provider_support[openai] failure where mock wasn't applied
- Also fixes test_error_handling_integration with same approach
The issue was that patching 'litellm.containers.main.base_llm_http_handler'
didn't work because the module imports it with 'from litellm.main import',
creating a local reference. Using patch.object patches the method on the
actual object instance, which works regardless of import style.
* fix: resolve flaky test_openai_env_base by clearing cache
- Add cache clearing at start of test_openai_env_base to prevent cache pollution
- Ensures no cached clients from previous tests interfere with respx mocks
- Fixes intermittent failures where aiohttp transport was used instead of httpx
- Test-only change with low risk, no production code modifications
Resolves flaky test marked with @pytest.mark.flaky(retries=3, delay=1)
Both parametrized versions (OPENAI_API_BASE and OPENAI_BASE_URL) now pass consistently
* test: add explicit mock verification in test_provider_support
- Capture mock handler with 'as mock_handler' for explicit validation
- Add assert_called_once() to verify mock was actually used
- Ensures test verifies no real API calls are made
- Follows same pattern as test_openai_env_base validation
Add `ocr` and `aocr` entries to the CallTypes enum to fix the
ValueError that occurs when using the /v1/ocr endpoint with
guardrails enabled.
The OCR endpoint uses route_type="aocr", but the CallTypes enum
was missing these values, causing guardrail hooks to fail when
trying to instantiate CallTypes("aocr").
Fixes#17381
* Add openai metadata filed in the request
* Add docs related to openai metadata
* Add utils
* test_completion_openai_metadata[True]
* Added support for though signature for gemini 3 in responses api (#16872)
* Added support for though signature for gemini 3
* Update docs with all supported endpoints and cost tracking
* Added config based routing support for batches and files
* fix lint errors
* Litellm anthropic image url support (#16868)
* Add image as url support to anthropic
* fix mypy errors
* fix tests
* Fix: Populate spend_logs_metadata in batch and files endpoints (#16921)
* Add spend-logs-metadata to the metadata
* Add tests for spend logs metadata in batches
* use better names
* Remove support for penalty param for gemini 3 (#16907)
* Remove support for penalty param
* remove halucinated model names
* fix mypy/test errors
* fix tests
* fix too many lines error
* fix too many lines error
* Add config for cicd test case
* Fix final tests
* fix batch tests
* fix batch tests
This commit adds support for custom Anthropic-compatible API endpoints
that don't follow the standard /v1/messages or /v1/complete path convention.
## Changes
- Added LITELLM_ANTHROPIC_DISABLE_URL_SUFFIX environment variable
- When set to true, prevents automatic appending of /v1/messages (for anthropic)
- When set to true, prevents automatic appending of /v1/complete (for anthropic_text)
- Added debug logging to indicate when suffix is being skipped
- Maintained full backward compatibility - existing deployments are unaffected
* fix(main.py): fix async retryer
Fixes https://github.com/BerriAI/litellm/issues/12830
* fix(forward_clientside_headers_by_model_group.py): filter out 'content-type' from forwardable headers
clientside content-type != proxy content type, can cause requests to hang
* fix(main.py): fix async retryer
Fixes https://github.com/BerriAI/litellm/issues/12830
* fix(forward_clientside_headers_by_model_group.py): filter out 'content-type' from forwardable headers
clientside content-type != proxy content type, can cause requests to hang
* test(tests/): update tests
* fix(main.py): handle router custom azure model name for responses api bridge
* fix(responses/handler): ensure azure model name is stripped before sending to provider
Fixes model name error
* fix(google_genai/main.py): handle stream=true being set in kwargs
* docs: cleanup icons from sidebar
* fix(test-litellm.yml): add google-genai to test litellmyml
* fix(main.py): strip 'responses/' from bridge
* fix(main.py): fix linting errors
* fix(types/openai.py): allow item to be none
handle azure streaming response
* fix(base.py): allow extra fields + handle azure item = none value in response output item added event
* fix(main.py): correctly handle removing responses/
* test(test_main.py): add unit tests
