- Add encoding_format parameter to supported parameters table
- Document float and base64 encoding format options
- Add usage examples for both encoding formats
- Update parameter documentation for amazon.titan-embed-text-v2:0
- Test encoding_format='float' parameter mapping and response handling
- Test encoding_format='base64' parameter mapping to binary format
- Verify parameter transformation and response processing
- Mock AWS API responses for both float and binary formats
- Ensure OpenAI compatibility with new encoding_format support
- Add encoding_format to supported OpenAI parameters list
- Implement encoding_format to embeddingTypes parameter mapping
- Map 'float' to ['float'] and 'base64' to ['binary'] formats
- Handle response with proper fallback: binary > float > embedding field
- Support both float and binary response formats per AWS documentation
Fixes#14685 - UnsupportedParamsError when using encoding_format with Titan V2
- Add embeddingTypes parameter to AmazonTitanV2EmbeddingRequest
- Add embeddingsByType response field for binary format support
- Update type hints for enhanced embedding response handling
The Admin UI is already built before packaging, so the second invocation of docker/build_admin_ui.sh after PyJWT adjustments was unnecessary. Removing it speeds up the builder stage, reduces cache invalidation, and doesn’t change the resulting wheel or runtime image.
Add documentation for using AWS Bedrock Application Inference Profiles
with image generation APIs, specifically for Nova Canvas models.
The documentation includes:
- SDK examples showing model_id parameter usage
- Proxy configuration examples
- Follows the same pattern as chat completions inference profiles
Follow the same pattern as chat completions and embeddings by extracting
model_id from optional_params into a variable, even though it's not used
in image generation. This maintains code consistency across Bedrock services.
- Add Asia/Bangkok (UTC+7) to timezone_map in duration_parser.py
- Update documentation to include Bangkok in common timezone values
- Add test case to verify Bangkok timezone functionality
- Change parameter from request_metadata to requestMetadata to match camelCase convention
- Consistent with guardrailConfig and performanceConfig naming pattern
- Update all references in transformation code and error messages
- Update tests and documentation to use correct parameter name
- Fix type checking for parameter validation
- Add requestMetadata field to CommonRequestObject type definition
- Support request_metadata parameter in get_supported_openai_params
- Add comprehensive validation for AWS Bedrock constraints:
* Maximum 16 key-value pairs
* Key length 1-256 characters
* Value length 0-256 characters
* Character set validation [a-zA-Z0-9\s:_@0=/+,.-]
- Transform request_metadata to top-level requestMetadata field in API request
- Maintain backward compatibility with existing functionality
- Enable metadata logging and traceability for multi-cloud environments
- Test requestMetadata parameter support in get_supported_openai_params
- Test transformation to top-level field in Bedrock API request
- Test validation of AWS constraints: max 16 items, key/value length limits
- Test character set validation for keys and values
- Cover edge cases including empty values and special characters
- Ensure compatibility with existing test patterns
- Apply Black formatting to all Bedrock CountTokens files
- Clean up imports and remove unused variables in tests
- Fix indentation and simplify test structure
- Fix pyright type error with type ignore annotation
- All tests continue to pass after cleanup
- Add endpoint integration test in test_proxy_token_counter.py
- Add unit tests for transformation logic in bedrock/count_tokens/
- Test model extraction from request body vs endpoint path
- Test input format detection (converse vs invokeModel)
- Test request transformation from Anthropic to Bedrock format
- All tests follow existing codebase patterns and pass successfully
* fix: iscoroutine removed from hot path
* fix: replace all instances & separate concerns
1. Replaced all instances of iscoroutine with is_async_callable
2. Place the coroutine checker in its own file
* fix: PR comment changes
* fix: missing config setting declaration
* fix: revert non-performance related changes
* fix: revert to initial implementation
* fix: remove dead const
