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Litellm dev 12 12 2024 (#7203)
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* fix(azure/): support passing headers to azure openai endpoints

Fixes https://github.com/BerriAI/litellm/issues/6217

* fix(utils.py): move default tokenizer to just openai

hf tokenizer makes network calls when trying to get the tokenizer - this slows down execution time calls

* fix(router.py): fix pattern matching router - add generic "*" to it as well

Fixes issue where generic "*" model access group wouldn't show up

* fix(pattern_match_deployments.py): match to more specific pattern

match to more specific pattern

allows setting generic wildcard model access group and excluding specific models more easily

* fix(proxy_server.py): fix _delete_deployment to handle base case where db_model list is empty

don't delete all router models  b/c of empty list

Fixes https://github.com/BerriAI/litellm/issues/7196

* fix(anthropic/): fix handling response_format for anthropic messages with anthropic api

* fix(fireworks_ai/): support passing response_format + tool call in same message

Addresses https://github.com/BerriAI/litellm/issues/7135

* Revert "fix(fireworks_ai/): support passing response_format + tool call in same message"

This reverts commit 6a30dc6929.

* test: fix test

* fix(replicate/): fix replicate default retry/polling logic

* test: add unit testing for router pattern matching

* test: update test to use default oai tokenizer

* test: mark flaky test

* test: skip flaky test
This commit is contained in:
Krish Dholakia 2024-12-13 08:54:03 -08:00 • committed by GitHub
parent 15a0572a06
commit e68bb4e051
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19 changed files with 496 additions and 103 deletions
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5
litellm/main.py
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@ -3171,6 +3171,7 @@ def embedding( # noqa: PLR0915
proxy_server_request = kwargs.get("proxy_server_request", None)
aembedding = kwargs.get("aembedding", None)
extra_headers = kwargs.get("extra_headers", None)
headers = kwargs.get("headers", None)
### CUSTOM MODEL COST ###
input_cost_per_token = kwargs.get("input_cost_per_token", None)
output_cost_per_token = kwargs.get("output_cost_per_token", None)
@ -3281,9 +3282,6 @@ def embedding( # noqa: PLR0915
"azure_ad_token", None
) or get_secret_str("AZURE_AD_TOKEN")
if extra_headers is not None:
optional_params["extra_headers"] = extra_headers
api_key = (
api_key
or litellm.api_key
@ -3311,6 +3309,7 @@ def embedding( # noqa: PLR0915
client=client,
aembedding=aembedding,
max_retries=max_retries,
headers=headers or extra_headers,
)
elif (
model in litellm.open_ai_embedding_models