Litellm dev 12 07 2024 (#7086)

* fix(main.py): support passing max retries to azure/openai embedding integrations

Fixes https://github.com/BerriAI/litellm/issues/7003

* feat(team_endpoints.py): allow updating team model aliases

Closes https://github.com/BerriAI/litellm/issues/6956

* feat(router.py): allow specifying model id as fallback - skips any cooldown check

Allows a default model to be checked if all models in cooldown

s/o @micahjsmith

* docs(reliability.md): add fallback to specific model to docs

* fix(utils.py): new 'is_prompt_caching_valid_prompt' helper util

Allows user to identify if messages/tools have prompt caching

Related issue: https://github.com/BerriAI/litellm/issues/6784

* feat(router.py): store model id for prompt caching valid prompt

Allows routing to that model id on subsequent requests

* fix(router.py): only cache if prompt is valid prompt caching prompt

prevents storing unnecessary items in cache

* feat(router.py): support routing prompt caching enabled models to previous deployments

Closes https://github.com/BerriAI/litellm/issues/6784

* test: fix linting errors

* feat(databricks/): convert basemodel to dict and exclude none values

allow passing pydantic message to databricks

* fix(utils.py): ensure all chat completion messages are dict

* (feat) Track `custom_llm_provider` in LiteLLMSpendLogs (#7081)

* add custom_llm_provider to SpendLogsPayload

* add custom_llm_provider to SpendLogs

* add custom llm provider to SpendLogs payload

* test_spend_logs_payload

* Add MLflow to the side bar (#7031)

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* (bug fix) SpendLogs update DB catch all possible DB errors for retrying  (#7082)

* catch DB_CONNECTION_ERROR_TYPES

* fix DB retry mechanism for SpendLog updates

* use DB_CONNECTION_ERROR_TYPES in auth checks

* fix exp back off for writing SpendLogs

* use _raise_failed_update_spend_exception to ensure errors print as NON blocking

* test_update_spend_logs_multiple_batches_with_failure

* (Feat) Add StructuredOutputs support for Fireworks.AI (#7085)

* fix model cost map fireworks ai "supports_response_schema": true,

* fix supports_response_schema

* fix map openai params fireworks ai

* test_map_response_format

* test_map_response_format

* added deepinfra/Meta-Llama-3.1-405B-Instruct (#7084)

* bump: version 1.53.9 → 1.54.0

* fix deepinfra

* litellm db fixes LiteLLM_UserTable (#7089)

* ci/cd queue new release

* fix llama-3.3-70b-versatile

* refactor - use consistent file naming convention `AI21/` -> `ai21`  (#7090)

* fix refactor - use consistent file naming convention

* ci/cd run again

* fix naming structure

* fix use consistent naming (#7092)

---------

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Yuki Watanabe <31463517+B-Step62@users.noreply.github.com>
Co-authored-by: ali sayyah <ali.sayyah2@gmail.com>

litellm/main.py

@@ -77,7 +77,7 @@ from litellm.utils import (
     read_config_args,
     supports_httpx_timeout,
     token_counter,
-    validate_chat_completion_user_messages,
+    validate_chat_completion_messages,
 )
 
 from ._logging import verbose_logger
@@ -931,7 +931,7 @@ def completion(  # type: ignore # noqa: PLR0915
             )  # support region-based pricing for bedrock
 
         ### VALIDATE USER MESSAGES ###
-        validate_chat_completion_user_messages(messages=messages)
+        messages = validate_chat_completion_messages(messages=messages)
 
         ### TIMEOUT LOGIC ###
         timeout = timeout or kwargs.get("request_timeout", 600) or 600
@@ -3274,6 +3274,7 @@ def embedding(  # noqa: PLR0915
     client = kwargs.pop("client", None)
     rpm = kwargs.pop("rpm", None)
     tpm = kwargs.pop("tpm", None)
+    max_retries = kwargs.get("max_retries", None)
     litellm_logging_obj: LiteLLMLoggingObj = kwargs.get("litellm_logging_obj")  # type: ignore
     cooldown_time = kwargs.get("cooldown_time", None)
     mock_response: Optional[List[float]] = kwargs.get("mock_response", None)  # type: ignore
@@ -3422,6 +3423,7 @@ def embedding(  # noqa: PLR0915
                 optional_params=optional_params,
                 client=client,
                 aembedding=aembedding,
+                max_retries=max_retries,
             )
         elif (
             model in litellm.open_ai_embedding_models
@@ -3466,6 +3468,7 @@ def embedding(  # noqa: PLR0915
                 optional_params=optional_params,
                 client=client,
                 aembedding=aembedding,
+                max_retries=max_retries,
             )
         elif custom_llm_provider == "databricks":
             api_base = (