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add param mapping to docs
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2 changed files with 28 additions and 3 deletions
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@ -217,8 +217,8 @@ def completion(
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metadata = kwargs.get('metadata', None)
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fallbacks = kwargs.get('fallbacks', [])
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######## end of unpacking kwargs ###########
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openai_params = ["functions", "function_call", "temperature", "temperature", "top_p", "n", "stream", "stop", "max_tokens", "presence_penalty", "frequency_penalty", "logit_bias", "user", "metadata"]
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litellm_params = ["acompletion", "caching", "return_async", "mock_response", "api_key", "api_version", "api_base", "force_timeout", "logger_fn", "verbose", "custom_llm_provider", "litellm_logging_obj", "litellm_call_id", "use_client", "id", "metadata", "fallbacks"]
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openai_params = ["functions", "function_call", "temperature", "temperature", "top_p", "n", "stream", "stop", "max_tokens", "presence_penalty", "frequency_penalty", "logit_bias", "user"]
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litellm_params = ["metadata", "acompletion", "caching", "return_async", "mock_response", "api_key", "api_version", "api_base", "force_timeout", "logger_fn", "verbose", "custom_llm_provider", "litellm_logging_obj", "litellm_call_id", "use_client", "id", "metadata", "fallbacks"]
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default_params = openai_params + litellm_params
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non_default_params = {k: v for k,v in kwargs.items() if k not in default_params} # model-specific params - pass them straight to the model/provider
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if mock_response:
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