LiteLLM Minor Fixes & Improvements (09/23/2024) (#5842) (#5858)

* LiteLLM Minor Fixes & Improvements (09/23/2024)  (#5842)

* feat(auth_utils.py): enable admin to allow client-side credentials to be passed

Makes it easier for devs to experiment with finetuned fireworks ai models

* feat(router.py): allow setting configurable_clientside_auth_params for a model

Closes https://github.com/BerriAI/litellm/issues/5843

* build(model_prices_and_context_window.json): fix anthropic claude-3-5-sonnet max output token limit

Fixes https://github.com/BerriAI/litellm/issues/5850

* fix(azure_ai/): support content list for azure ai

Fixes https://github.com/BerriAI/litellm/issues/4237

* fix(litellm_logging.py): always set saved_cache_cost

Set to 0 by default

* fix(fireworks_ai/cost_calculator.py): add fireworks ai default pricing

handles calling 405b+ size models

* fix(slack_alerting.py): fix error alerting for failed spend tracking

Fixes regression with slack alerting error monitoring

* fix(vertex_and_google_ai_studio_gemini.py): handle gemini no candidates in streaming chunk error

* docs(bedrock.md): add llama3-1 models

* test: fix tests

* fix(azure_ai/chat): fix transformation for azure ai calls

litellm/llms/azure_ai/chat/handler.py

@@ -0,0 +1,59 @@
+from typing import Any, Callable, List, Optional, Union
+
+from httpx._config import Timeout
+
+from litellm.llms.bedrock.chat.invoke_handler import MockResponseIterator
+from litellm.llms.OpenAI.openai import OpenAIChatCompletion
+from litellm.types.utils import ModelResponse
+from litellm.utils import CustomStreamWrapper
+
+from .transformation import AzureAIStudioConfig
+
+
+class AzureAIChatCompletion(OpenAIChatCompletion):
+    def completion(
+        self,
+        model_response: ModelResponse,
+        timeout: Union[float, Timeout],
+        optional_params: dict,
+        logging_obj: Any,
+        model: Optional[str] = None,
+        messages: Optional[list] = None,
+        print_verbose: Optional[Callable[..., Any]] = None,
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+        acompletion: bool = False,
+        litellm_params=None,
+        logger_fn=None,
+        headers: Optional[dict] = None,
+        custom_prompt_dict: dict = {},
+        client=None,
+        organization: Optional[str] = None,
+        custom_llm_provider: Optional[str] = None,
+        drop_params: Optional[bool] = None,
+    ):
+
+        transformed_messages = AzureAIStudioConfig()._transform_messages(
+            messages=messages  # type: ignore
+        )
+
+        return super().completion(
+            model_response,
+            timeout,
+            optional_params,
+            logging_obj,
+            model,
+            transformed_messages,
+            print_verbose,
+            api_key,
+            api_base,
+            acompletion,
+            litellm_params,
+            logger_fn,
+            headers,
+            custom_prompt_dict,
+            client,
+            organization,
+            custom_llm_provider,
+            drop_params,
+        )