Normalize JSON Schema type custom to object for Bedrock invoke and
_bedrock_tools_pt, ensure stable names for tools without name, and
avoid KeyError in the Anthropic messages adapter when translating
tools to OpenAI format for bedrock/converse.
Made-with: Cursor
Anthropic/Claude Code use input_schema.type "custom"; Bedrock rejects it.
- Add normalize_json_schema_custom_types_to_object and use it for Invoke,
chat invoke, and _bedrock_tools_pt (Anthropic input_schema + OpenAI params).
- Coerce invalid root types to object for Converse toolSpec.
- Tests for invoke transform, converse _bedrock_tools_pt, and unit helper.
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
* added support for nova grounding for amazon nova model
* added citations support
* added integration tests
* removing test file
* refactor: Use web_search_options for Nova grounding instead of system_tool
---------
Co-authored-by: Juhie <juhiechandra@gmail.com>
Co-authored-by: Juhie <75068056+juhiechandra@users.noreply.github.com>
Resolves issue #17910 where Amazon Nova models (like amazon.nova-pro-v1:0)
were incorrectly identified as Amazon Titan models, causing requests to
use textGenerationConfig instead of inferenceConfig.
The fix moves the "nova" check before the initial provider check on the
split model name. This ensures that models containing "nova" (like
amazon.nova-pro-v1:0 or amazon.nova-2-lite-v1:0) are correctly identified
as Nova models, rather than matching "amazon" first.
* refactor(passthrough_endpoints-success-handler): refactor llm passthrough logging logic
isolate the llm translation work to enable cost tracking on sdk
* feat: initial implementation of passthrough SDK cost calculation
enables bedrock passthrough cost tracking to work
* feat(cost_calculator.py): working cost calculation for bedrock passthrough
* feat(litellm_logging.py): consider allm_passthrough in cost tracking
allows async calls (e.g. via proxy) to work
* feat(bedrock/passthrough): working event stream decoding for bedrock passthrough calls + logging instrumentation for passthrough sdk calls (log on stream completion)
Enables bedrock streaming cost calculation
* feat(litellm_logging.py): support streaming passthrough cost tracking
* feat(passthrough/main.py): working async streaming cost calculation
Closes https://github.com/BerriAI/litellm/issues/11359
* feat(proxy_server.py): fix passthrough routing when llm router enabled
* feat: further fixes
* feat(bedrock/): working bedrock passthrough cost tracking (non-streaming)
* feat(litellm_logging.py): working usage tracking for bedrock passthrough calls
ensures tokens are logged
* feat(bedrock/passthrough): add converse passthrough cost tracking support
* feat(base_llm/passthrough): remove redundant function
* refactor(litellm_logging.py): refactor function to be below 50 LOC
* test: update test
* test: remove redundant test
* feat: initial commit adding bedrock support via the new sdk passthrough logic
ensures correct sequencing of tasks (pre call checks etc. can run before signing request)
* fix(route_llm_requests.py): passthrough to allm_passthrough_route if no model found
* feat(bedrock/passthrough): working bedrock passthrough via sdk support
* fix(passthrough/main.py): re-add data and json
* feat(passthrough/main): support async passthrough calls to bedrock
* feat(passthrough/main.py): async streaming + completion support
* feat(llm_passthrough_endpoints.py): migrate bedrock passthrough calls to to new bedrock passthrough sdk
Enables calls to work correctly
* fix: fix linting errors
* test: update test
* fix: add flag for disabling use_aiohttp_transport
* feat: add _create_async_transport
* feat: fixes for transport
* add httpx-aiohttp
* feat: fixes for transport
* refactor: fixes for transport
* build: fix deps
* fixes: test fixes
* fix: ensure aiohttp does not auto set content type
* test: test fixes
* feat: add LiteLLMAiohttpTransport
* fix: fixes for responses API handling
* test: fixes for responses API handling
* test: fixes for responses API handling
* feat: fixes for transport
* fix: base embedding handler
* test: test_async_http_handler_force_ipv4
* test: fix failing deepeval test
* fix: add YARL for bedrock urls
* fix: issues with transport
* fix: comment out linting issues
* test fix
* test: XAI is unstable
* test: fixes for using respx
* test: XAI fixes
* test: XAI fixes
* test: infinity testing fixes
* docs(config_settings.md): document param
* test: test_openai_image_edit_litellm_sdk
* test: remove deprecated test
* bump respx==0.22.0
* test: test_xai_message_name_filtering
* test: fix anthropic test after bumping httpx
* use n 4 for mapped tests (#11109)
* fix: use 1 session per event loop
* test: test_client_session_helper
* fix: linting error
* fix: resolving GET requests on httpx 0.28.1
* test fixes proxy unit tests
* fix: add ssl verify settings
* fix: proxy unit tests
* fix: refactor
* tests: basic unit tests for aiohttp transports
* tests: fixes xai
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* add test_function_calling_with_tool_response to base llm tests
* run test suite for nova
* update test_function_calling_with_tool_response
* allowed ToolJsonSchemaBlock keys
* fix ToolJsonSchemaBlock
* add back pytest fixture
* test: test_prompt_caching
* fix(main.py): use base model instead of user model if given
Fixes https://github.com/BerriAI/litellm/issues/10760
* feat(azure/image_generation/__init__.py): make azure image gen check more robust
Fixes https://github.com/BerriAI/litellm/issues/10760
* fix(user_api_key_auth.py): support bearer token auth for `x-litellm-api-key` header
Fixes earlier regression on vertex ai passthrough auth
* fix(user_api_key_auth.py): refactor get api key into separate function
enables easier testing
* fix: cleanup
* fix: fix linting error
* fix: cleanup
* test: update tests
* Support pdf url's to openai (#10640)
* fix(gpt_transformation.py): support pdf url input to openai
pass as base64 as openai doesn't support image url's
* fix(openai.py): support async message transformation
allows async get request to convert url to base64
* fix(gpt_transformation.py): fix linting errrors and use common components across sync + async flows
* fix: fix linting errors
* fix(openai.py): pop correct var
* Fix sagemaker chat calls - content length error (#10607)
* fix(sagemaker_chat/): support passing dynamic aws params
previously being ignored
* refactor(sagemaker/chat): more refactoring
* fix(sagemaker_chat/): make sure streaming is correctly handled post-refactor
* refactor: more refactoring to support using signed json str
* fix(sagemaker/chat): working sync streaming post refactor
* fix(sagemaker/chat): support async streaming post refactor
* fix(llm_http_handler.py): await async function
* fix: remove print statements
* test: update test
* test: update test
* fix(llm_http_handler.py): retain passing in data as json str
* test: update test
* fix(base_model_iterator.py): fix linting error
* test: test auth
* fix: fix linting error
* test: update test
* test: update translation test
* fix(gpt_transformation.py): handle awaitable/non-awaitable object
* fix: handle async flow for message transformation on openai compatible api's
* test: cleanup testing
* test: update test
* test(test_router.py): use model with higher quota
* test: simplify test
* test: update test
* test(base_llm_unit_tests.py): return '<thinking>' tag in response content
* fix(converse_transformation.py): extract `<thinking>` block from nova tool use response
Fixes https://github.com/BerriAI/litellm/issues/9063
* fix(factory.py): handle non-signature reasoning blocks to bedrock
pass as text input - bedrock raises ""User messages cannot contain reasoning content. Please remove the r
easoning content and try again." otherwise
* fix(main.py): Add drop params support for gpt
Fixes https://github.com/BerriAI/litellm/issues/10501
* fix(converse_transformation.py): fix linting error
* fix(utils.py): fix linting error
* test: cleanup test
* test: skip test until we have bedrock prompt caching permission
* fix(anthropic/chat/transformation.py): Don't set tool choice on response_format conversion when thinking is enabled
Not allowed by Anthropic
Fixes https://github.com/BerriAI/litellm/issues/8901
* refactor: move test to base anthropic chat tests
ensures consistent behaviour across vertex/anthropic/bedrock
* fix(anthropic/chat/transformation.py): if thinking token is specified and max tokens is not - ensure max token to anthropic is higher than thinking tokens
* feat(converse_transformation.py): correctly handle thinking + response format on Bedrock Converse
Fixes https://github.com/BerriAI/litellm/issues/8901
* fix(converse_transformation.py): correctly handle adding max tokens
* test: handle service unavailable error
