forked from phoenix-oss/llama-stack-mirror
chore: more API validators (#2165)
# What does this PR do? We added: * make sure docstrings are present with 'params' and 'returns' * fail if someone sets 'returns: None' * fix the failing APIs Signed-off-by: Sébastien Han <seb@redhat.com>
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Sébastien Han
GitHub
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commit
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23 changed files with 1304 additions and 574 deletions
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@ -845,13 +845,13 @@ class Inference(Protocol):
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"""Generate a completion for the given content using the specified model.
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:param model_id: The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint.
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:param content: The content to generate a completion for
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:param sampling_params: (Optional) Parameters to control the sampling strategy
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:param response_format: (Optional) Grammar specification for guided (structured) decoding
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:param content: The content to generate a completion for.
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:param sampling_params: (Optional) Parameters to control the sampling strategy.
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:param response_format: (Optional) Grammar specification for guided (structured) decoding.
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:param stream: (Optional) If True, generate an SSE event stream of the response. Defaults to False.
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:param logprobs: (Optional) If specified, log probabilities for each token position will be returned.
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:returns: If stream=False, returns a CompletionResponse with the full completion.
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If stream=True, returns an SSE event stream of CompletionResponseStreamChunk
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If stream=True, returns an SSE event stream of CompletionResponseStreamChunk.
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"""
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...
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@ -864,6 +864,15 @@ class Inference(Protocol):
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response_format: ResponseFormat | None = None,
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logprobs: LogProbConfig | None = None,
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) -> BatchCompletionResponse:
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"""Generate completions for a batch of content using the specified model.
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:param model_id: The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint.
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:param content_batch: The content to generate completions for.
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:param sampling_params: (Optional) Parameters to control the sampling strategy.
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:param response_format: (Optional) Grammar specification for guided (structured) decoding.
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:param logprobs: (Optional) If specified, log probabilities for each token position will be returned.
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:returns: A BatchCompletionResponse with the full completions.
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"""
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raise NotImplementedError("Batch completion is not implemented")
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@webmethod(route="/inference/chat-completion", method="POST")
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@ -883,9 +892,9 @@ class Inference(Protocol):
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"""Generate a chat completion for the given messages using the specified model.
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:param model_id: The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint.
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:param messages: List of messages in the conversation
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:param sampling_params: Parameters to control the sampling strategy
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:param tools: (Optional) List of tool definitions available to the model
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:param messages: List of messages in the conversation.
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:param sampling_params: Parameters to control the sampling strategy.
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:param tools: (Optional) List of tool definitions available to the model.
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:param tool_choice: (Optional) Whether tool use is required or automatic. Defaults to ToolChoice.auto.
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.. deprecated::
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Use tool_config instead.
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@ -902,7 +911,7 @@ class Inference(Protocol):
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:param logprobs: (Optional) If specified, log probabilities for each token position will be returned.
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:param tool_config: (Optional) Configuration for tool use.
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:returns: If stream=False, returns a ChatCompletionResponse with the full completion.
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If stream=True, returns an SSE event stream of ChatCompletionResponseStreamChunk
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If stream=True, returns an SSE event stream of ChatCompletionResponseStreamChunk.
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"""
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...
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@ -917,6 +926,17 @@ class Inference(Protocol):
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response_format: ResponseFormat | None = None,
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logprobs: LogProbConfig | None = None,
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) -> BatchChatCompletionResponse:
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"""Generate chat completions for a batch of messages using the specified model.
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:param model_id: The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint.
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:param messages_batch: The messages to generate completions for.
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:param sampling_params: (Optional) Parameters to control the sampling strategy.
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:param tools: (Optional) List of tool definitions available to the model.
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:param tool_config: (Optional) Configuration for tool use.
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:param response_format: (Optional) Grammar specification for guided (structured) decoding.
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:param logprobs: (Optional) If specified, log probabilities for each token position will be returned.
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:returns: A BatchChatCompletionResponse with the full completions.
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"""
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raise NotImplementedError("Batch chat completion is not implemented")
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@webmethod(route="/inference/embeddings", method="POST")
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@ -935,7 +955,7 @@ class Inference(Protocol):
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:param output_dimension: (Optional) Output dimensionality for the embeddings. Only supported by Matryoshka models.
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:param text_truncation: (Optional) Config for how to truncate text for embedding when text is longer than the model's max sequence length.
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:param task_type: (Optional) How is the embedding being used? This is only supported by asymmetric embedding models.
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:returns: An array of embeddings, one for each content. Each embedding is a list of floats. The dimensionality of the embedding is model-specific; you can check model metadata using /models/{model_id}
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:returns: An array of embeddings, one for each content. Each embedding is a list of floats. The dimensionality of the embedding is model-specific; you can check model metadata using /models/{model_id}.
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"""
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...
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@ -967,22 +987,23 @@ class Inference(Protocol):
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"""Generate an OpenAI-compatible completion for the given prompt using the specified model.
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:param model: The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint.
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:param prompt: The prompt to generate a completion for
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:param best_of: (Optional) The number of completions to generate
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:param echo: (Optional) Whether to echo the prompt
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:param frequency_penalty: (Optional) The penalty for repeated tokens
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:param logit_bias: (Optional) The logit bias to use
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:param logprobs: (Optional) The log probabilities to use
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:param max_tokens: (Optional) The maximum number of tokens to generate
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:param n: (Optional) The number of completions to generate
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:param presence_penalty: (Optional) The penalty for repeated tokens
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:param seed: (Optional) The seed to use
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:param stop: (Optional) The stop tokens to use
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:param stream: (Optional) Whether to stream the response
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:param stream_options: (Optional) The stream options to use
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:param temperature: (Optional) The temperature to use
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:param top_p: (Optional) The top p to use
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:param user: (Optional) The user to use
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:param prompt: The prompt to generate a completion for.
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:param best_of: (Optional) The number of completions to generate.
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:param echo: (Optional) Whether to echo the prompt.
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:param frequency_penalty: (Optional) The penalty for repeated tokens.
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:param logit_bias: (Optional) The logit bias to use.
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:param logprobs: (Optional) The log probabilities to use.
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:param max_tokens: (Optional) The maximum number of tokens to generate.
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:param n: (Optional) The number of completions to generate.
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:param presence_penalty: (Optional) The penalty for repeated tokens.
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:param seed: (Optional) The seed to use.
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:param stop: (Optional) The stop tokens to use.
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:param stream: (Optional) Whether to stream the response.
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:param stream_options: (Optional) The stream options to use.
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:param temperature: (Optional) The temperature to use.
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:param top_p: (Optional) The top p to use.
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:param user: (Optional) The user to use.
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:returns: An OpenAICompletion.
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"""
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...
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@ -1016,27 +1037,28 @@ class Inference(Protocol):
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"""Generate an OpenAI-compatible chat completion for the given messages using the specified model.
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:param model: The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint.
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:param messages: List of messages in the conversation
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:param frequency_penalty: (Optional) The penalty for repeated tokens
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:param function_call: (Optional) The function call to use
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:param functions: (Optional) List of functions to use
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:param logit_bias: (Optional) The logit bias to use
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:param logprobs: (Optional) The log probabilities to use
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:param max_completion_tokens: (Optional) The maximum number of tokens to generate
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:param max_tokens: (Optional) The maximum number of tokens to generate
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:param n: (Optional) The number of completions to generate
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:param parallel_tool_calls: (Optional) Whether to parallelize tool calls
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:param presence_penalty: (Optional) The penalty for repeated tokens
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:param response_format: (Optional) The response format to use
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:param seed: (Optional) The seed to use
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:param stop: (Optional) The stop tokens to use
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:param stream: (Optional) Whether to stream the response
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:param stream_options: (Optional) The stream options to use
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:param temperature: (Optional) The temperature to use
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:param tool_choice: (Optional) The tool choice to use
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:param tools: (Optional) The tools to use
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:param top_logprobs: (Optional) The top log probabilities to use
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:param top_p: (Optional) The top p to use
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:param user: (Optional) The user to use
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:param messages: List of messages in the conversation.
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:param frequency_penalty: (Optional) The penalty for repeated tokens.
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:param function_call: (Optional) The function call to use.
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:param functions: (Optional) List of functions to use.
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:param logit_bias: (Optional) The logit bias to use.
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:param logprobs: (Optional) The log probabilities to use.
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:param max_completion_tokens: (Optional) The maximum number of tokens to generate.
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:param max_tokens: (Optional) The maximum number of tokens to generate.
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:param n: (Optional) The number of completions to generate.
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:param parallel_tool_calls: (Optional) Whether to parallelize tool calls.
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:param presence_penalty: (Optional) The penalty for repeated tokens.
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:param response_format: (Optional) The response format to use.
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:param seed: (Optional) The seed to use.
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:param stop: (Optional) The stop tokens to use.
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:param stream: (Optional) Whether to stream the response.
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:param stream_options: (Optional) The stream options to use.
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:param temperature: (Optional) The temperature to use.
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:param tool_choice: (Optional) The tool choice to use.
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:param tools: (Optional) The tools to use.
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:param top_logprobs: (Optional) The top log probabilities to use.
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:param top_p: (Optional) The top p to use.
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:param user: (Optional) The user to use.
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:returns: An OpenAIChatCompletion.
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"""
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...
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