* feat(proxy_cli.py): add new 'log_config' cli param
Allows passing logging.conf to uvicorn on startup
* docs(cli.md): add logging conf to uvicorn cli docs
* fix(get_llm_provider_logic.py): fix default api base for litellm_proxy
Fixes https://github.com/BerriAI/litellm/issues/6332
* feat(openai_like/embedding): Add support for jina ai embeddings
Closes https://github.com/BerriAI/litellm/issues/6337
* docs(deploy.md): update entrypoint.sh filepath post-refactor
Fixes outdated docs
* feat(prometheus.py): emit time_to_first_token metric on prometheus
Closes https://github.com/BerriAI/litellm/issues/6334
* fix(prometheus.py): only emit time to first token metric if stream is True
enables more accurate ttft usage
* test: handle vertex api instability
* fix(get_llm_provider_logic.py): fix import
* fix(openai.py): fix deepinfra default api base
* fix(anthropic/transformation.py): remove anthropic beta header (#6361)
* refactor(redis_cache.py): use a default cache value when writing to redis
prevent redis from blowing up in high traffic
* refactor(redis_cache.py): refactor all cache writes to use self.get_ttl
ensures default ttl always used when writing to redis
Prevents redis db from blowing up in prod
* fix get_response_headers
* unit testing for get headers
* unit testing for anthropic / azure openai headers
* increase test coverage for test_completion_response_ratelimit_headers
* fix test rate limit headers
* feat(custom_logger.py): expose new `async_dataset_hook` for modifying/rejecting argilla items before logging
Allows user more control on what gets logged to argilla for annotations
* feat(google_ai_studio_endpoints.py): add new `/azure/*` pass through route
enables pass-through for azure provider
* feat(utils.py): support checking ollama `/api/show` endpoint for retrieving ollama model info
Fixes https://github.com/BerriAI/litellm/issues/6322
* fix(user_api_key_auth.py): add `/key/delete` to an allowed_ui_routes
Fixes https://github.com/BerriAI/litellm/issues/6236
* fix(user_api_key_auth.py): remove type ignore
* fix(user_api_key_auth.py): route ui vs. api token checks differently
Fixes https://github.com/BerriAI/litellm/issues/6238
* feat(internal_user_endpoints.py): support setting models as a default internal user param
Closes https://github.com/BerriAI/litellm/issues/6239
* fix(user_api_key_auth.py): fix exception string
* fix(user_api_key_auth.py): fix error string
* fix: fix test
* refactor(main.py): streaming_chunk_builder
use <100 lines of code
refactor each component into a separate function - easier to maintain + test
* fix(utils.py): handle choices being None
openai pydantic schema updated
* fix(main.py): fix linting error
* feat(streaming_chunk_builder_utils.py): update stream chunk builder to support rebuilding audio chunks from openai
* test(test_custom_callback_input.py): test message redaction works for audio output
* fix(streaming_chunk_builder_utils.py): return anthropic token usage info directly
* fix(stream_chunk_builder_utils.py): run validation check before entering chunk processor
* fix(main.py): fix import
* refactor - use helpers for name space and hashing
* use openai to get the relevant supported params
* use helpers for getting cache key
* fix test caching
* use get/set helpers for preset cache keys
* make get_cache_key under 100 LOC
* fix _get_model_param_value
* fix _get_caching_group
* fix linting error
* add unit testing for get cache key
* test_generate_streaming_content
* add check for os.environ vars when readin config.yaml
* use base class for reading from config.yaml
* fix import
* fix linting
* add unit tests for base config class
* fix order of reading elements from config.yaml
* unit tests for reading configs from files
* fix user_config_file_path
* use simpler implementation
* use helper to get_config
* working unit tests for reading configs
