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https://github.com/BerriAI/litellm.git
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fix(utils.py): check for none params
This commit is contained in:
Krrish Dholakia
parent
8cced8eabc
commit
60d2dff74a
1 changed files with 86 additions and 86 deletions
170
litellm/utils.py
170
litellm/utils.py
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@ -1749,15 +1749,15 @@ def get_optional_params( # use the openai defaults
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# handle anthropic params
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if stream:
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optional_params["stream"] = stream
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if stop:
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if stop is not None:
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if type(stop) == str:
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stop = [stop] # openai can accept str/list for stop
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optional_params["stop_sequences"] = stop
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_tokens_to_sample"] = max_tokens
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elif custom_llm_provider == "cohere":
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## check if unsupported param passed in
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@ -1766,21 +1766,21 @@ def get_optional_params( # use the openai defaults
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# handle cohere params
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if stream:
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optional_params["stream"] = stream
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_tokens"] = max_tokens
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if n:
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if n is not None:
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optional_params["num_generations"] = n
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if logit_bias != {}:
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optional_params["logit_bias"] = logit_bias
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if top_p:
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if top_p is not None:
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optional_params["p"] = top_p
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if frequency_penalty:
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if frequency_penalty is not None:
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optional_params["frequency_penalty"] = frequency_penalty
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if presence_penalty:
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if presence_penalty is not None:
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optional_params["presence_penalty"] = presence_penalty
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if stop:
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if stop is not None:
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optional_params["stop_sequences"] = stop
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elif custom_llm_provider == "maritalk":
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## check if unsupported param passed in
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@ -1789,17 +1789,17 @@ def get_optional_params( # use the openai defaults
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# handle cohere params
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if stream:
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optional_params["stream"] = stream
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_tokens"] = max_tokens
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if logit_bias != {}:
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optional_params["logit_bias"] = logit_bias
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if top_p:
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if top_p is not None:
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optional_params["p"] = top_p
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if presence_penalty:
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if presence_penalty is not None:
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optional_params["repetition_penalty"] = presence_penalty
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if stop:
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if stop is not None:
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optional_params["stopping_tokens"] = stop
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elif custom_llm_provider == "replicate":
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## check if unsupported param passed in
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@ -1809,18 +1809,18 @@ def get_optional_params( # use the openai defaults
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if stream:
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optional_params["stream"] = stream
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return optional_params
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if max_tokens:
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if max_tokens is not None:
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if "vicuna" in model or "flan" in model:
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optional_params["max_length"] = max_tokens
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elif "meta/codellama-13b" in model:
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optional_params["max_tokens"] = max_tokens
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else:
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optional_params["max_new_tokens"] = max_tokens
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if stop:
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if stop is not None:
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optional_params["stop_sequences"] = stop
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elif custom_llm_provider == "huggingface":
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## check if unsupported param passed in
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@ -1864,15 +1864,15 @@ def get_optional_params( # use the openai defaults
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if stream:
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optional_params["stream_tokens"] = stream
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_tokens"] = max_tokens
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if frequency_penalty:
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if frequency_penalty is not None:
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optional_params["repetition_penalty"] = frequency_penalty # https://docs.together.ai/reference/inference
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if stop:
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if stop is not None:
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optional_params["stop"] = stop
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elif custom_llm_provider == "ai21":
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## check if unsupported param passed in
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@ -1881,36 +1881,36 @@ def get_optional_params( # use the openai defaults
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if stream:
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optional_params["stream"] = stream
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if n:
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if n is not None:
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optional_params["numResults"] = n
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if max_tokens:
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if max_tokens is not None:
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optional_params["maxTokens"] = max_tokens
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["topP"] = top_p
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if stop:
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if stop is not None:
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optional_params["stopSequences"] = stop
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if frequency_penalty:
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if frequency_penalty is not None:
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optional_params["frequencyPenalty"] = {"scale": frequency_penalty}
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if presence_penalty:
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if presence_penalty is not None:
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optional_params["presencePenalty"] = {"scale": presence_penalty}
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elif custom_llm_provider == "palm": # https://developers.generativeai.google/tutorials/curl_quickstart
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## check if unsupported param passed in
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supported_params = ["temperature", "top_p", "stream", "n", "stop", "max_tokens"]
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_check_valid_arg(supported_params=supported_params)
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if stream:
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optional_params["stream"] = stream
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if n:
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if n is not None:
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optional_params["candidate_count"] = n
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if stop:
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if stop is not None:
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optional_params["stop_sequences"] = stop
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_output_tokens"] = max_tokens
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elif (
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custom_llm_provider == "vertex_ai"
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@ -1919,13 +1919,13 @@ def get_optional_params( # use the openai defaults
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supported_params = ["temperature", "top_p", "max_tokens", "stream"]
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_check_valid_arg(supported_params=supported_params)
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if stream:
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optional_params["stream"] = stream
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_output_tokens"] = max_tokens
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elif custom_llm_provider == "sagemaker":
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if "llama-2" in model:
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@ -1940,11 +1940,11 @@ def get_optional_params( # use the openai defaults
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supported_params = ["temperature", "max_tokens", "stream"]
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_check_valid_arg(supported_params=supported_params)
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_new_tokens"] = max_tokens
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if stream:
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optional_params["stream"] = stream
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@ -1958,13 +1958,13 @@ def get_optional_params( # use the openai defaults
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_check_valid_arg(supported_params=supported_params)
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# params "maxTokens":200,"temperature":0,"topP":250,"stop_sequences":[],
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# https://us-west-2.console.aws.amazon.com/bedrock/home?region=us-west-2#/providers?model=j2-ultra
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if max_tokens:
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if max_tokens is not None:
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optional_params["maxTokens"] = max_tokens
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if stop:
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if stop is not None:
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optional_params["stop_sequences"] = stop
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if top_p:
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if top_p is not None:
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optional_params["topP"] = top_p
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if stream:
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optional_params["stream"] = stream
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@ -1973,13 +1973,13 @@ def get_optional_params( # use the openai defaults
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_check_valid_arg(supported_params=supported_params)
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# anthropic params on bedrock
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# \"max_tokens_to_sample\":300,\"temperature\":0.5,\"top_p\":1,\"stop_sequences\":[\"\\\\n\\\\nHuman:\"]}"
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_tokens_to_sample"] = max_tokens
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if stop:
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if stop is not None:
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optional_params["stop_sequences"] = stop
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if stream:
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optional_params["stream"] = stream
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@ -1987,13 +1987,13 @@ def get_optional_params( # use the openai defaults
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supported_params = ["max_tokens", "temperature", "stop", "top_p", "stream"]
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_check_valid_arg(supported_params=supported_params)
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# see https://us-west-2.console.aws.amazon.com/bedrock/home?region=us-west-2#/providers?model=titan-large
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if max_tokens:
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if max_tokens is not None:
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optional_params["maxTokenCount"] = max_tokens
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if stop:
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if stop is not None:
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optional_params["stopSequences"] = stop
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if top_p:
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if top_p is not None:
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optional_params["topP"] = top_p
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if stream:
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optional_params["stream"] = stream
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@ -2003,86 +2003,86 @@ def get_optional_params( # use the openai defaults
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# handle cohere params
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if stream:
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optional_params["stream"] = stream
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_tokens"] = max_tokens
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if n:
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if n is not None:
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optional_params["num_generations"] = n
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if logit_bias != {}:
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optional_params["logit_bias"] = logit_bias
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if top_p:
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if top_p is not None:
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optional_params["p"] = top_p
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if frequency_penalty:
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if frequency_penalty is not None:
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optional_params["frequency_penalty"] = frequency_penalty
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if presence_penalty:
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if presence_penalty is not None:
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optional_params["presence_penalty"] = presence_penalty
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if stop:
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if stop is not None:
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optional_params["stop_sequences"] = stop
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elif model in litellm.aleph_alpha_models:
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supported_params = ["max_tokens", "stream", "top_p", "temperature", "presence_penalty", "frequency_penalty", "n", "stop"]
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_check_valid_arg(supported_params=supported_params)
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if max_tokens:
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if max_tokens is not None:
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optional_params["maximum_tokens"] = max_tokens
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if stream:
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optional_params["stream"] = stream
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if presence_penalty:
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if presence_penalty is not None:
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optional_params["presence_penalty"] = presence_penalty
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if frequency_penalty:
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if frequency_penalty is not None:
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optional_params["frequency_penalty"] = frequency_penalty
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if n:
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if n is not None:
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optional_params["n"] = n
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if stop:
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if stop is not None:
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optional_params["stop_sequences"] = stop
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elif custom_llm_provider == "ollama":
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supported_params = ["max_tokens", "stream", "top_p", "temperature", "frequency_penalty", "stop"]
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_check_valid_arg(supported_params=supported_params)
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if max_tokens:
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if max_tokens is not None:
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optional_params["num_predict"] = max_tokens
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if stream:
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optional_params["stream"] = stream
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if frequency_penalty:
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if frequency_penalty is not None:
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optional_params["repeat_penalty"] = frequency_penalty
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if stop:
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if stop is not None:
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optional_params["stop_sequences"] = stop
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elif model in litellm.nlp_cloud_models or custom_llm_provider == "nlp_cloud":
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supported_params = ["max_tokens", "stream", "temperature", "top_p", "presence_penalty", "frequency_penalty", "n", "stop"]
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_check_valid_arg(supported_params=supported_params)
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_length"] = max_tokens
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if stream:
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optional_params["stream"] = stream
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if presence_penalty:
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if presence_penalty is not None:
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optional_params["presence_penalty"] = presence_penalty
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if frequency_penalty:
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if frequency_penalty is not None:
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optional_params["frequency_penalty"] = frequency_penalty
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if n:
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if n is not None:
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optional_params["num_return_sequences"] = n
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if stop:
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if stop is not None:
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optional_params["stop_sequences"] = stop
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elif model in litellm.petals_models or custom_llm_provider == "petals":
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supported_params = ["max_tokens", "temperature", "top_p", "stream"]
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_check_valid_arg(supported_params=supported_params)
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# max_new_tokens=1,temperature=0.9, top_p=0.6
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if max_tokens:
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if max_tokens is not None:
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optional_params["max_new_tokens"] = max_tokens
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if temperature:
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p:
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if top_p is not None:
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optional_params["top_p"] = top_p
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if stream:
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optional_params["stream"] = stream
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@ -2090,7 +2090,7 @@ def get_optional_params( # use the openai defaults
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supported_params = ["temperature", "top_p", "n", "stream", "stop", "max_tokens", "presence_penalty", "frequency_penalty", "logit_bias", "user"]
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_check_valid_arg(supported_params=supported_params)
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optional_params = non_default_params
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if temperature != None:
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if temperature is not None:
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if temperature == 0 and model == "mistralai/Mistral-7B-Instruct-v0.1": # this model does no support temperature == 0
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temperature = 0.0001 # close to 0
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optional_params["temperature"] = temperature
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