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
This commit is contained in:
Krish Dholakia 2024-09-25 22:11:57 -07:00 committed by GitHub
parent e8c767f66b
commit ed5635e9a2
25 changed files with 1675 additions and 340 deletions

View file

@ -774,3 +774,21 @@ def test_usage_object_null_tokens():
usage_obj = litellm.Usage(prompt_tokens=2, completion_tokens=None, total_tokens=2)
assert usage_obj.completion_tokens == 0
def test_is_base64_encoded():
import base64
import requests
litellm.set_verbose = True
url = "https://dummyimage.com/100/100/fff&text=Test+image"
response = requests.get(url)
file_data = response.content
encoded_file = base64.b64encode(file_data).decode("utf-8")
base64_image = f"data:image/png;base64,{encoded_file}"
from litellm.utils import is_base64_encoded
assert is_base64_encoded(s=base64_image) is True