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LiteLLM Minor Fixes & Improvements (01/16/2025) - p2 (#7828)
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* fix(vertex_ai/gemini/transformation.py): handle 'http://' image urls

* test: add base test for `http:` url's

* fix(factory.py/get_image_details): follow redirects

allows http calls to work

* fix(codestral/): fix stream chunk parsing on last chunk of stream

* Azure ad token provider (#6917)

* Update azure.py

Added optional parameter azure ad token provider

* Added parameter to main.py

* Found token provider arg location

* Fixed embeddings

* Fixed ad token provider

---------

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

* fix: fix linting errors

* fix(main.py): leave out o1 route for azure ad token provider, for now

get v0 out for sync azure gpt route to begin with

* test: skip http:// test for fireworks ai

model does not support it

* refactor: cleanup dead code

* fix: revert http:// url passthrough for gemini

google ai studio raises errors

* test: fix test

---------

Co-authored-by: bahtman <anton@baht.dk>
This commit is contained in:
Krish Dholakia 2025-02-02 23:17:50 -08:00 • committed by GitHub
parent 10d3da7660
commit 97b8de17ab
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9 changed files with 107 additions and 27 deletions
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12
litellm/llms/codestral/completion/transformation.py
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@ -5,6 +5,7 @@ import litellm
from litellm.llms.openai.completion.transformation import OpenAITextCompletionConfig
from litellm.types.llms.databricks import GenericStreamingChunk
class CodestralTextCompletionConfig(OpenAITextCompletionConfig):
"""
Reference: https://docs.mistral.ai/api/#operation/createFIMCompletion
@ -77,6 +78,7 @@ class CodestralTextCompletionConfig(OpenAITextCompletionConfig):
return optional_params
def _chunk_parser(self, chunk_data: str) -> GenericStreamingChunk:
text = ""
is_finished = False
finish_reason = None
@ -90,7 +92,15 @@ class CodestralTextCompletionConfig(OpenAITextCompletionConfig):
"is_finished": is_finished,
"finish_reason": finish_reason,
}
chunk_data_dict = json.loads(chunk_data)
try:
chunk_data_dict = json.loads(chunk_data)
except json.JSONDecodeError:
return {
"text": "",
"is_finished": is_finished,
"finish_reason": finish_reason,
}
original_chunk = litellm.ModelResponse(**chunk_data_dict, stream=True)
_choices = chunk_data_dict.get("choices", []) or []
_choice = _choices[0]