mirror of
https://github.com/BerriAI/litellm.git
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Litellm merge pr (#7161)
* build: merge branch * test: fix openai naming * fix(main.py): fix openai renaming * style: ignore function length for config factory * fix(sagemaker/): fix routing logic * fix: fix imports * fix: fix override
This commit is contained in:
Krish Dholakia
GitHub
parent
d5aae81c6d
commit
350cfc36f7
88 changed files with 3617 additions and 4421 deletions
288
litellm/utils.py
288
litellm/utils.py
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@ -2923,22 +2923,16 @@ def get_optional_params( # noqa: PLR0915
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)
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_check_valid_arg(supported_params=supported_params)
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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 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 is not None:
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optional_params["temperature"] = temperature
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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 is not None:
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optional_params["stop_sequences"] = stop
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optional_params = litellm.ReplicateConfig().map_openai_params(
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non_default_params=non_default_params,
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optional_params=optional_params,
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model=model,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "predibase":
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supported_params = get_supported_openai_params(
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model=model, custom_llm_provider=custom_llm_provider
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@ -2954,7 +2948,14 @@ def get_optional_params( # noqa: PLR0915
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)
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_check_valid_arg(supported_params=supported_params)
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optional_params = litellm.HuggingfaceConfig().map_openai_params(
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non_default_params=non_default_params, optional_params=optional_params
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non_default_params=non_default_params,
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optional_params=optional_params,
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model=model,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "together_ai":
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## check if unsupported param passed in
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@ -2973,53 +2974,6 @@ def get_optional_params( # noqa: PLR0915
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else False
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),
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)
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elif custom_llm_provider == "ai21":
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## check if unsupported param passed in
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supported_params = get_supported_openai_params(
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model=model, custom_llm_provider=custom_llm_provider
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)
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_check_valid_arg(supported_params=supported_params)
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if stream:
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optional_params["stream"] = stream
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if n is not None:
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optional_params["numResults"] = n
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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 is not None:
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optional_params["temperature"] = temperature
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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 is not None:
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optional_params["stopSequences"] = stop
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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 is not None:
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optional_params["presencePenalty"] = {"scale": presence_penalty}
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elif (
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custom_llm_provider == "palm"
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): # https://developers.generativeai.google/tutorials/curl_quickstart
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## check if unsupported param passed in
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supported_params = get_supported_openai_params(
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model=model, custom_llm_provider=custom_llm_provider
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)
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_check_valid_arg(supported_params=supported_params)
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if temperature is not None:
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optional_params["temperature"] = temperature
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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 is not None:
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optional_params["candidate_count"] = n
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if stop is not None:
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if isinstance(stop, str):
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optional_params["stop_sequences"] = [stop]
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elif isinstance(stop, list):
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optional_params["stop_sequences"] = stop
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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 == "vertex_ai" and (
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model in litellm.vertex_chat_models
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or model in litellm.vertex_code_chat_models
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@ -3120,12 +3074,25 @@ def get_optional_params( # noqa: PLR0915
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_check_valid_arg(supported_params=supported_params)
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if "codestral" in model:
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optional_params = litellm.MistralTextCompletionConfig().map_openai_params(
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non_default_params=non_default_params, optional_params=optional_params
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model=model,
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non_default_params=non_default_params,
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optional_params=optional_params,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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else:
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optional_params = litellm.MistralConfig().map_openai_params(
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model=model,
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non_default_params=non_default_params,
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optional_params=optional_params,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "vertex_ai" and model in litellm.vertex_ai_ai21_models:
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supported_params = get_supported_openai_params(
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@ -3326,29 +3293,28 @@ def get_optional_params( # noqa: PLR0915
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model=model,
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non_default_params=non_default_params,
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optional_params=optional_params,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "nlp_cloud":
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supported_params = get_supported_openai_params(
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model=model, custom_llm_provider=custom_llm_provider
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)
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_check_valid_arg(supported_params=supported_params)
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optional_params = litellm.NLPCloudConfig().map_openai_params(
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non_default_params=non_default_params,
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optional_params=optional_params,
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model=model,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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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 is not None:
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optional_params["temperature"] = temperature
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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 is not None:
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optional_params["presence_penalty"] = presence_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 is not None:
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optional_params["num_return_sequences"] = n
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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 == "petals":
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supported_params = get_supported_openai_params(
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model=model, custom_llm_provider=custom_llm_provider
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@ -3435,7 +3401,14 @@ def get_optional_params( # noqa: PLR0915
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)
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_check_valid_arg(supported_params=supported_params)
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optional_params = litellm.MistralConfig().map_openai_params(
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non_default_params=non_default_params, optional_params=optional_params
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non_default_params=non_default_params,
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optional_params=optional_params,
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model=model,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "text-completion-codestral":
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supported_params = get_supported_openai_params(
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@ -3443,7 +3416,14 @@ def get_optional_params( # noqa: PLR0915
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)
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_check_valid_arg(supported_params=supported_params)
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optional_params = litellm.MistralTextCompletionConfig().map_openai_params(
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non_default_params=non_default_params, optional_params=optional_params
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non_default_params=non_default_params,
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optional_params=optional_params,
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model=model,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "databricks":
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@ -3470,6 +3450,11 @@ def get_optional_params( # noqa: PLR0915
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model=model,
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non_default_params=non_default_params,
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optional_params=optional_params,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "cerebras":
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supported_params = get_supported_openai_params(
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@ -3480,6 +3465,11 @@ def get_optional_params( # noqa: PLR0915
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non_default_params=non_default_params,
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optional_params=optional_params,
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model=model,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "xai":
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supported_params = get_supported_openai_params(
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@ -3491,7 +3481,7 @@ def get_optional_params( # noqa: PLR0915
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non_default_params=non_default_params,
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optional_params=optional_params,
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)
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elif custom_llm_provider == "ai21_chat":
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elif custom_llm_provider == "ai21_chat" or custom_llm_provider == "ai21":
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supported_params = get_supported_openai_params(
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model=model, custom_llm_provider=custom_llm_provider
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)
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@ -3500,6 +3490,11 @@ def get_optional_params( # noqa: PLR0915
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non_default_params=non_default_params,
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optional_params=optional_params,
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model=model,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "fireworks_ai":
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supported_params = get_supported_openai_params(
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@ -3525,6 +3520,11 @@ def get_optional_params( # noqa: PLR0915
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non_default_params=non_default_params,
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optional_params=optional_params,
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model=model,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "hosted_vllm":
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supported_params = get_supported_openai_params(
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@ -3594,55 +3594,17 @@ def get_optional_params( # noqa: PLR0915
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)
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_check_valid_arg(supported_params=supported_params)
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if functions is not None:
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optional_params["functions"] = functions
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if function_call is not None:
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optional_params["function_call"] = function_call
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if temperature is not None:
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optional_params["temperature"] = temperature
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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 n is not None:
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optional_params["n"] = n
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if stream is not None:
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optional_params["stream"] = stream
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if stop is not None:
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optional_params["stop"] = stop
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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 presence_penalty is not None:
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optional_params["presence_penalty"] = presence_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 logit_bias is not None:
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optional_params["logit_bias"] = logit_bias
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if user is not None:
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optional_params["user"] = user
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if response_format is not None:
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optional_params["response_format"] = response_format
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if seed is not None:
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optional_params["seed"] = seed
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if tools is not None:
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optional_params["tools"] = tools
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if tool_choice is not None:
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optional_params["tool_choice"] = tool_choice
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if max_retries is not None:
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optional_params["max_retries"] = max_retries
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# OpenRouter-only parameters
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extra_body = {}
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transforms = passed_params.pop("transforms", None)
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models = passed_params.pop("models", None)
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route = passed_params.pop("route", None)
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if transforms is not None:
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extra_body["transforms"] = transforms
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if models is not None:
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extra_body["models"] = models
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if route is not None:
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extra_body["route"] = route
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optional_params["extra_body"] = (
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extra_body # openai client supports `extra_body` param
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optional_params = litellm.OpenrouterConfig().map_openai_params(
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non_default_params=non_default_params,
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optional_params=optional_params,
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model=model,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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elif custom_llm_provider == "watsonx":
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supported_params = get_supported_openai_params(
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model=model, custom_llm_provider=custom_llm_provider
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@ -3727,7 +3689,11 @@ def get_optional_params( # noqa: PLR0915
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optional_params=optional_params,
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model=model,
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api_version=api_version, # type: ignore
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drop_params=drop_params,
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drop_params=(
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drop_params
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if drop_params is not None and isinstance(drop_params, bool)
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else False
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),
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)
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else: # assume passing in params for text-completion openai
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supported_params = get_supported_openai_params(
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@ -6271,7 +6237,7 @@ from litellm.llms.base_llm.transformation import BaseConfig
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class ProviderConfigManager:
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@staticmethod
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def get_provider_chat_config(
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def get_provider_chat_config( # noqa: PLR0915
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model: str, provider: litellm.LlmProviders
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) -> BaseConfig:
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"""
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@ -6333,6 +6299,60 @@ class ProviderConfigManager:
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return litellm.LMStudioChatConfig()
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elif litellm.LlmProviders.GALADRIEL == provider:
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return litellm.GaladrielChatConfig()
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elif litellm.LlmProviders.REPLICATE == provider:
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return litellm.ReplicateConfig()
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elif litellm.LlmProviders.HUGGINGFACE == provider:
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return litellm.HuggingfaceConfig()
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elif litellm.LlmProviders.TOGETHER_AI == provider:
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return litellm.TogetherAIConfig()
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elif litellm.LlmProviders.OPENROUTER == provider:
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return litellm.OpenrouterConfig()
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elif litellm.LlmProviders.GEMINI == provider:
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return litellm.GoogleAIStudioGeminiConfig()
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elif (
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litellm.LlmProviders.AI21 == provider
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or litellm.LlmProviders.AI21_CHAT == provider
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):
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return litellm.AI21ChatConfig()
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elif litellm.LlmProviders.AZURE == provider:
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return litellm.AzureOpenAIConfig()
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elif litellm.LlmProviders.AZURE_AI == provider:
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return litellm.AzureAIStudioConfig()
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elif litellm.LlmProviders.AZURE_TEXT == provider:
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return litellm.AzureOpenAITextConfig()
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elif litellm.LlmProviders.HOSTED_VLLM == provider:
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return litellm.HostedVLLMChatConfig()
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elif litellm.LlmProviders.NLP_CLOUD == provider:
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return litellm.NLPCloudConfig()
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elif litellm.LlmProviders.OOBABOOGA == provider:
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return litellm.OobaboogaConfig()
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elif litellm.LlmProviders.OLLAMA_CHAT == provider:
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return litellm.OllamaChatConfig()
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elif litellm.LlmProviders.DEEPINFRA == provider:
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return litellm.DeepInfraConfig()
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elif litellm.LlmProviders.PERPLEXITY == provider:
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return litellm.PerplexityChatConfig()
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elif (
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litellm.LlmProviders.MISTRAL == provider
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or litellm.LlmProviders.CODESTRAL == provider
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):
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return litellm.MistralConfig()
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elif litellm.LlmProviders.NVIDIA_NIM == provider:
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return litellm.NvidiaNimConfig()
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elif litellm.LlmProviders.CEREBRAS == provider:
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return litellm.CerebrasConfig()
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elif litellm.LlmProviders.VOLCENGINE == provider:
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return litellm.VolcEngineConfig()
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elif litellm.LlmProviders.TEXT_COMPLETION_CODESTRAL == provider:
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return litellm.MistralTextCompletionConfig()
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elif litellm.LlmProviders.SAMBANOVA == provider:
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return litellm.SambanovaConfig()
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elif litellm.LlmProviders.MARITALK == provider:
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return litellm.MaritalkConfig()
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elif litellm.LlmProviders.CLOUDFLARE == provider:
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return litellm.CloudflareChatConfig()
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elif litellm.LlmProviders.ANTHROPIC_TEXT == provider:
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return litellm.AnthropicTextConfig()
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elif litellm.LlmProviders.VLLM == provider:
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return litellm.VLLMConfig()
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elif litellm.LlmProviders.OLLAMA == provider:
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|
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