image_edit was not forwarding model_info/metadata to the logging object,
so custom_pricing was never detected. After PR #20679 stripped custom
pricing fields from the shared backend key, image_edit cost became 0.
Fixes#22244
Fixes#22285 — extra_headers passed to litellm.image_generation() were
silently dropped on the openai/litellm_proxy/openai_compatible_providers
code path. The azure and azure_ai paths already forwarded them correctly.
Add headers parameter to image_generation() and aimage_generation() methods
in OpenAI provider, and pass headers from images/main.py to ensure custom
headers like cf-aig-authorization are properly forwarded to the OpenAI API.
Aligns behavior with completion() method and Azure provider implementation.
- Remove direct import of ImageEditRequestUtils from images.utils
- Add __getattr__ handler to lazy load ImageEditRequestUtils when accessed
- Create _get_ImageEditRequestUtils() helper function with caching
- Use importlib instead of sys to avoid importing sys inside functions
- Update image_edit() to use helper function for accessing ImageEditRequestUtils
- Add TYPE_CHECKING import for proper type hints
This defers the heavy import from images.utils until ImageEditRequestUtils is actually needed, improving import time when from .images.main import * is executed.
* feat(custom_llm): add image_edit and aimage_edit support
Add support for image_edit and aimage_edit methods in CustomLLM class,
allowing users to implement custom image editing providers.
Changes:
- Add image_edit() and aimage_edit() methods to CustomLLM base class
- Add custom provider detection in litellm.image_edit() function
- Add tests for sync and async image_edit with custom handlers
* docs: add image_edit to CustomLLM documentation
- Add /v1/images/edits to supported routes
- Add Image Edit section with example
- Update Custom Handler Spec with image_edit methods
Add direct Stability AI REST API support for image generation endpoints.
This enables using Stability's SD3, SD3.5, and Stable Image models via
LiteLLM's OpenAI-compatible interface.
Changes:
- Add STABILITY provider to LlmProviders enum
- Create StabilityImageGenerationConfig with multipart/form-data support
- Add OpenAI size to Stability aspect_ratio mapping
- Register provider in ProviderConfigManager
- Add 9 Stability models to model_prices_and_context_window.json
- Add documentation at docs/providers/stability.md
- Add 25 unit tests
Supported models:
- stability/sd3, sd3-large, sd3-large-turbo, sd3-medium
- stability/sd3.5-large, sd3.5-large-turbo, sd3.5-medium
- stability/stable-image-ultra, stable-image-core
* fix: lazy load utils.py imports
Lazy-load most functions and response types from utils.py to avoid loading
tiktoken and other heavy dependencies at import time. This significantly
reduces memory usage when importing completion from litellm.
* 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
* feat: add input_fidelity parameter for OpenAI image generation
- Add input_fidelity to OpenAIImageGenerationOptionalParams type
- Update image_generation function signature to accept input_fidelity
- Add input_fidelity to default_params in get_optional_params_image_gen
- Include input_fidelity in openai_params list for proper handling
- Update documentation with input_fidelity parameter description
- Add test for input_fidelity parameter functionality
This enables control over how closely the model follows the input prompt
for gpt-image-1 model, improving prompt adherence and image quality.
* feat: add input_fidelity to optional parameters for image generation
- Include input_fidelity in the list of OpenAIImageGenerationOptionalParams
- This addition enhances the flexibility of image generation by allowing control over input fidelity.
* test: enhance test for gpt-image-1 with input_fidelity parameter
- Update test_gpt_image_1_with_input_fidelity to include mocking of OpenAI response
- Validate that the OpenAI client is called with correct parameters, including input_fidelity
- Improve response validation to ensure expected output structure and values
* add support of bearer token for bedrock integration
* fix linting issue
* fix type checking issue
* reoder arguments to address type checking issue
* switch to use get_secret_str to fetch env variable
Co-authored-by: 0x-fang <fanggong@amazon.com>
