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>

tests/llm_translation/test_azure_openai.py

@@ -8,6 +8,7 @@ sys.path.insert(
 import pytest
 from litellm.llms.azure.common_utils import process_azure_headers
 from httpx import Headers
+from base_embedding_unit_tests import BaseLLMEmbeddingTest
 
 
 def test_process_azure_headers_empty():
@@ -188,3 +189,15 @@ def test_process_azure_endpoint_url(api_base, model, expected_endpoint):
     }
     result = azure_chat_completion.create_azure_base_url(**input_args)
     assert result == expected_endpoint, "Unexpected endpoint"
+
+
+class TestAzureEmbedding(BaseLLMEmbeddingTest):
+    def get_base_embedding_call_args(self) -> dict:
+        return {
+            "model": "azure/azure-embedding-model",
+            "api_key": os.getenv("AZURE_API_KEY"),
+            "api_base": os.getenv("AZURE_API_BASE"),
+        }
+
+    def get_custom_llm_provider(self) -> litellm.LlmProviders:
+        return litellm.LlmProviders.AZURE