* fix(team_endpoints.py): ensure 404 raised when team not found
* fix(key_management_endpoints.py): fix adding tags to key when metadata is empty
* fix(key_management_endpoints.py): refactor set metadata field to use common function across keys + teams
reduces scope for errors + easier testing
* fix: fix linting error
* fix(invoke_handler.py): fix converse streaming - return signature + ensure consistency with anthropic api response
* build(model_prices_and_context_window.json): fix anthropic api claude-3-7 max output tokens
with beta header this is 128k
Resolves https://github.com/BerriAI/litellm/issues/8964
* feat(handler.py): handle new anthropic 'thinking_delta' block on streaming
Fixes https://github.com/BerriAI/litellm/issues/8825
* fix(transformation.py): support a 'format' parameter for image's
allow user to specify mime type
* fix: pass mimetype via 'format' param
* feat(gemini/chat/transformation.py): support 'format' param for gemini
* fix(factory.py): support 'format' param on sync bedrock converse calls
* feat(bedrock/converse_transformation.py): support 'format' param for bedrock async calls
* refactor(factory.py): move to supporting 'format' param in base helper
ensures consistency in param support
* feat(gpt_transformation.py): filter out 'format' param
don't send invalid param to openai
* fix(gpt_transformation.py): fix translation
* fix: fix translation error
* Fix missing signature_delta in thinking blocks when streaming from Claude 3.7 (#8797)
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* test: update test to enforce signature found
* feat(refactor-signature-param-to-be-'signature'-instead-of-'signature_delta'): keeps it in sync with anthropic
* fix: fix linting error
---------
Co-authored-by: Martin Krasser <krasserm@googlemail.com>
* fix(core_helpers.py): handle litellm_metadata instead of 'metadata'
* feat(batches/): ensure batches logs are written to db
makes batches response dict compatible
* fix(cost_calculator.py): handle batch response being a dictionary
* fix(batches/main.py): modify retrieve endpoints to use @client decorator
enables logging to work on retrieve call
* fix(batches/main.py): fix retrieve batch response type to be 'dict' compatible
* fix(spend_tracking_utils.py): send unique uuid for retrieve batch call type
create batch and retrieve batch share the same id
* fix(spend_tracking_utils.py): prevent duplicate retrieve batch calls from being double counted
* refactor(batches/): refactor cost tracking for batches - do it on retrieve, and within the established litellm_logging pipeline
ensures cost is always logged to db
* fix: fix linting errors
* fix: fix linting error
* fix(common_utils.py): handle $id in response schema when calling vertex ai
Fixes issue where `$id` present in response_schema was not accepted by vertex ai
* test(test_vertex.py): add unit test to ensure $id stripped out of vertex schema
* test(test_router_tag_routing.py): add unit test for tag-based routing on embeddings
* fix(router.py): pass request kwargs on async embeddings to async_get_available_deployment function
* fix(router.py): require request kwargs to always be passed in
ensures tag-based routing always works, across endpoints
* feat(langfuse_prompt_management.py): support using prompt management per langfuse project with key/team based logging
* fix: fix linting error
* fix: fix test
* fix: fix test
* fix: fix test
* fix: fix linting error
* fix(route_llm_request.py): move to using common router, even for client-side credentials
ensures fallbacks / cooldown logic still works
* test(test_route_llm_request.py): add unit test for route request
* feat(router.py): generate unique model id when clientside credential passed in
Prevents cooldowns for api key 1 from impacting api key 2
* test(test_router.py): update testing to ensure original litellm params not mutated
* fix(router.py): upsert clientside call into llm router model list
enables cooldown logic to work accurately
* fix: fix linting error
* test(test_router_utils.py): add direct test for new util on router
