LiteLLM Minor Fixes & Improvements (09/26/2024) (#5925) (#5937)

* LiteLLM Minor Fixes & Improvements (09/26/2024)  (#5925)

* fix(litellm_logging.py): don't initialize prometheus_logger if non premium user

Prevents bad error messages in logs

Fixes https://github.com/BerriAI/litellm/issues/5897

* Add Support for Custom Providers in Vision and Function Call Utils (#5688)

* Add Support for Custom Providers in Vision and Function Call Utils Lookup

* Remove parallel function call due to missing model info param

* Add Unit Tests for Vision and Function Call Changes

* fix-#5920: set header value to string to fix "'int' object has no att… (#5922)

* LiteLLM Minor Fixes & Improvements (09/24/2024) (#5880)

* 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

* feat(azure_ai/embed): Add azure ai embeddings support

Closes https://github.com/BerriAI/litellm/issues/5861

* fix(azure_ai/embed): enable async embedding

* feat(azure_ai/embed): support azure ai multimodal embeddings

* fix(azure_ai/embed): support async multi modal embeddings

* feat(together_ai/embed): support together ai embedding calls

* feat(rerank/main.py): log source documents for rerank endpoints to langfuse

improves rerank endpoint logging

* fix(langfuse.py): support logging `/audio/speech` input to langfuse

* test(test_embedding.py): fix test

* test(test_completion_cost.py): fix helper util

* fix-#5920: set header value to string to fix "'int' object has no attribute 'encode'"

---------

Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>

* Revert "fix-#5920: set header value to string to fix "'int' object has no att…" (#5926)

This reverts commit a554ae2695.

* build(model_prices_and_context_window.json): add azure ai cohere rerank model pricing

Enables cost tracking for azure ai cohere rerank models

* fix(litellm_logging.py): fix debug log to be clearer

Closes https://github.com/BerriAI/litellm/issues/5909

* test(test_utils.py): fix test name

* fix(azure_ai/cost_calculator.py): support cost tracking for azure ai rerank models

* fix(azure_ai): fix azure ai base model cost tracking for rerank endpoints

* fix(converse_handler.py): support new llama 3-2 models

Fixes https://github.com/BerriAI/litellm/issues/5901

* fix(litellm_logging.py): ensure response is redacted for standard message logging

Fixes https://github.com/BerriAI/litellm/issues/5890#issuecomment-2378242360

* fix(cost_calculator.py): use 'get_model_info' for cohere rerank cost calculation

allows user to set custom cost for model

* fix(config.yml): fix docker hub auht

* build(config.yml): add docker auth to all tests

* fix(db/create_views.py): fix linting error

* fix(main.py): fix circular import

* fix(azure_ai/__init__.py): fix circular import

* fix(main.py): fix import

* fix: fix linting errors

* test: fix test

* fix(proxy_server.py): pass premium user value on startup

used for prometheus init

---------

Co-authored-by: Cole Murray <colemurray.cs@gmail.com>
Co-authored-by: bravomark <62681807+bravomark@users.noreply.github.com>

* handle streaming for azure ai studio error

* [Perf Proxy] parallel request limiter - use one cache update call (#5932)

* fix parallel request limiter - use one cache update call

* ci/cd run again

* run ci/cd again

* use docker username password

* fix config.yml

* fix config

* fix config

* fix config.yml

* ci/cd run again

* use correct typing for batch set cache

* fix async_set_cache_pipeline

* fix only check user id tpm / rpm limits when limits set

* fix test_openai_azure_embedding_with_oidc_and_cf

* test: fix test

* test(test_rerank.py): fix test

---------

Co-authored-by: Cole Murray <colemurray.cs@gmail.com>
Co-authored-by: bravomark <62681807+bravomark@users.noreply.github.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>

litellm/proxy/proxy_server.py

@@ -505,7 +505,9 @@ prompt_injection_detection_obj: Optional[_OPTIONAL_PromptInjectionDetection] = N
 store_model_in_db: bool = False
 open_telemetry_logger = None
 ### INITIALIZE GLOBAL LOGGING OBJECT ###
-proxy_logging_obj = ProxyLogging(user_api_key_cache=user_api_key_cache)
+proxy_logging_obj = ProxyLogging(
+    user_api_key_cache=user_api_key_cache, premium_user=premium_user
+)
 ### REDIS QUEUE ###
 async_result = None
 celery_app_conn = None
@@ -567,7 +569,9 @@ def get_custom_headers(
 
     try:
         return {
-            key: value for key, value in headers.items() if value not in exclude_values
+            key: str(value)
+            for key, value in headers.items()
+            if value not in exclude_values
         }
     except Exception as e:
         verbose_proxy_logger.error(f"Error setting custom headers: {e}")