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Merge branch 'main' of https://github.com/BerriAI/litellm into litellm_ftr_bedrock_aws_session_token

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Brian Schultheiss 2024-06-26 08:11:34 -07:00
commit 1176272734
53 changed files with 2201 additions and 397 deletions
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34
litellm/main.py
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@ -348,6 +348,7 @@ async def acompletion(
or custom_llm_provider == "deepinfra"
or custom_llm_provider == "perplexity"
or custom_llm_provider == "groq"
or custom_llm_provider == "nvidia_nim"
or custom_llm_provider == "codestral"
or custom_llm_provider == "text-completion-codestral"
or custom_llm_provider == "deepseek"
@ -428,6 +429,7 @@ def mock_completion(
model: str,
messages: List,
stream: Optional[bool] = False,
n: Optional[int] = None,
mock_response: Union[str, Exception, dict] = "This is a mock request",
mock_tool_calls: Optional[List] = None,
logging=None,
@ -486,18 +488,32 @@ def mock_completion(
if kwargs.get("acompletion", False) == True:
return CustomStreamWrapper(
completion_stream=async_mock_completion_streaming_obj(
model_response, mock_response=mock_response, model=model
model_response, mock_response=mock_response, model=model, n=n
),
model=model,
custom_llm_provider="openai",
logging_obj=logging,
)
response = mock_completion_streaming_obj(
model_response, mock_response=mock_response, model=model
model_response,
mock_response=mock_response,
model=model,
n=n,
)
return response
model_response["choices"][0]["message"]["content"] = mock_response
if n is None:
model_response["choices"][0]["message"]["content"] = mock_response
else:
_all_choices = []
for i in range(n):
_choice = litellm.utils.Choices(
index=i,
message=litellm.utils.Message(
content=mock_response, role="assistant"
),
)
_all_choices.append(_choice)
model_response["choices"] = _all_choices
model_response["created"] = int(time.time())
model_response["model"] = model
@ -634,6 +650,7 @@ def completion(
headers = kwargs.get("headers", None) or extra_headers
num_retries = kwargs.get("num_retries", None) ## deprecated
max_retries = kwargs.get("max_retries", None)
cooldown_time = kwargs.get("cooldown_time", None)
context_window_fallback_dict = kwargs.get("context_window_fallback_dict", None)
organization = kwargs.get("organization", None)
### CUSTOM MODEL COST ###
@ -747,6 +764,7 @@ def completion(
"allowed_model_region",
"model_config",
"fastest_response",
"cooldown_time",
]
default_params = openai_params + litellm_params
@ -931,6 +949,7 @@ def completion(
input_cost_per_token=input_cost_per_token,
output_cost_per_second=output_cost_per_second,
output_cost_per_token=output_cost_per_token,
cooldown_time=cooldown_time,
)
logging.update_environment_variables(
model=model,
@ -944,6 +963,7 @@ def completion(
model,
messages,
stream=stream,
n=n,
mock_response=mock_response,
mock_tool_calls=mock_tool_calls,
logging=logging,
@ -1171,6 +1191,7 @@ def completion(
or custom_llm_provider == "deepinfra"
or custom_llm_provider == "perplexity"
or custom_llm_provider == "groq"
or custom_llm_provider == "nvidia_nim"
or custom_llm_provider == "codestral"
or custom_llm_provider == "deepseek"
or custom_llm_provider == "anyscale"
@ -2906,6 +2927,7 @@ async def aembedding(*args, **kwargs) -> EmbeddingResponse:
or custom_llm_provider == "deepinfra"
or custom_llm_provider == "perplexity"
or custom_llm_provider == "groq"
or custom_llm_provider == "nvidia_nim"
or custom_llm_provider == "deepseek"
or custom_llm_provider == "fireworks_ai"
or custom_llm_provider == "ollama"
@ -2985,6 +3007,7 @@ def embedding(
client = kwargs.pop("client", None)
rpm = kwargs.pop("rpm", None)
tpm = kwargs.pop("tpm", None)
cooldown_time = kwargs.get("cooldown_time", None)
max_parallel_requests = kwargs.pop("max_parallel_requests", None)
model_info = kwargs.get("model_info", None)
metadata = kwargs.get("metadata", None)
@ -3060,6 +3083,7 @@ def embedding(
"region_name",
"allowed_model_region",
"model_config",
"cooldown_time",
]
default_params = openai_params + litellm_params
non_default_params = {
@ -3120,6 +3144,7 @@ def embedding(
"aembedding": aembedding,
"preset_cache_key": None,
"stream_response": {},
"cooldown_time": cooldown_time,
},
)
if azure == True or custom_llm_provider == "azure":
@ -3481,6 +3506,7 @@ async def atext_completion(
or custom_llm_provider == "deepinfra"
or custom_llm_provider == "perplexity"
or custom_llm_provider == "groq"
or custom_llm_provider == "nvidia_nim"
or custom_llm_provider == "text-completion-codestral"
or custom_llm_provider == "deepseek"
or custom_llm_provider == "fireworks_ai"