completion_create_params
Classes:
| Name | Description |
|---|---|
CompletionCreateParamsBase |
|
CompletionCreateParamsNonStreaming |
|
CompletionCreateParamsStreaming |
|
Function |
|
ResponseFormat |
|
Attributes:
| Name | Type | Description |
|---|---|---|
CompletionCreateParams |
|
|
FunctionCall |
|
module-attribute
CompletionCreateParams = Union[
CompletionCreateParamsNonStreaming,
CompletionCreateParamsStreaming,
]
module-attribute
FunctionCall = Union[
Literal["none", "auto"],
ChatCompletionFunctionCallOptionParam,
]
Attributes:
| Name | Type | Description |
|---|---|---|
frequency_penalty |
Optional[float]
|
Number between -2.0 and 2.0. |
function_call |
FunctionCall
|
Deprecated in favor of |
functions |
Iterable[Function]
|
Deprecated in favor of |
logit_bias |
Optional[Dict[str, int]]
|
Modify the likelihood of specified tokens appearing in the completion. |
logprobs |
Optional[bool]
|
Whether to return log probabilities of the output tokens or not. |
max_tokens |
Optional[int]
|
The maximum number of tokens that can be generated in the chat |
messages |
Required[Iterable[ChatCompletionMessageParam]]
|
A list of messages comprising the conversation so far. |
model |
Required[Union[str, Literal['gpt-4-0125-preview', 'gpt-4-turbo-preview', 'gpt-4-1106-preview', 'gpt-4-vision-preview', 'gpt-4', 'gpt-4-0314', 'gpt-4-0613', 'gpt-4-32k', 'gpt-4-32k-0314', 'gpt-4-32k-0613', 'gpt-3.5-turbo', 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0301', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-1106', 'gpt-3.5-turbo-0125', 'gpt-3.5-turbo-16k-0613']]]
|
ID of the model to use. |
n |
Optional[int]
|
How many chat completion choices to generate for each input message. |
presence_penalty |
Optional[float]
|
Number between -2.0 and 2.0. |
response_format |
ResponseFormat
|
An object specifying the format that the model must output. |
seed |
Optional[int]
|
This feature is in Beta. If specified, our system will make a best effort to |
stop |
Union[Optional[str], List[str]]
|
Up to 4 sequences where the API will stop generating further tokens. |
temperature |
Optional[float]
|
What sampling temperature to use, between 0 and 2. |
tool_choice |
ChatCompletionToolChoiceOptionParam
|
Controls which (if any) function is called by the model. |
tools |
Iterable[ChatCompletionToolParam]
|
A list of tools the model may call. |
top_logprobs |
Optional[int]
|
An integer between 0 and 20 specifying the number of most likely tokens to |
top_p |
Optional[float]
|
An alternative to sampling with temperature, called nucleus sampling, where the |
user |
str
|
A unique identifier representing your end-user, which can help OpenAI to monitor |
instance-attribute
Number between -2.0 and 2.0.
Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
See more information about frequency and presence penalties.
instance-attribute
function_call: FunctionCall
Deprecated in favor of tool_choice.
Controls which (if any) function is called by the model. none means the model
will not call a function and instead generates a message. auto means the model
can pick between generating a message or calling a function. Specifying a
particular function via {"name": "my_function"} forces the model to call that
function.
none is the default when no functions are present. auto is the default if
functions are present.
instance-attribute
Deprecated in favor of tools.
A list of functions the model may generate JSON inputs for.
instance-attribute
Modify the likelihood of specified tokens appearing in the completion.
Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.
instance-attribute
Whether to return log probabilities of the output tokens or not.
If true, returns the log probabilities of each output token returned in the
content of message. This option is currently not available on the
gpt-4-vision-preview model.
instance-attribute
The maximum number of tokens that can be generated in the chat completion.
The total length of input tokens and generated tokens is limited by the model's context length. Example Python code for counting tokens.
instance-attribute
messages: Required[Iterable[ChatCompletionMessageParam]]
A list of messages comprising the conversation so far.
instance-attribute
model: Required[
Union[
str,
Literal[
"gpt-4-0125-preview",
"gpt-4-turbo-preview",
"gpt-4-1106-preview",
"gpt-4-vision-preview",
"gpt-4",
"gpt-4-0314",
"gpt-4-0613",
"gpt-4-32k",
"gpt-4-32k-0314",
"gpt-4-32k-0613",
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-0301",
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-1106",
"gpt-3.5-turbo-0125",
"gpt-3.5-turbo-16k-0613",
],
]
]
ID of the model to use.
See the model endpoint compatibility table for details on which models work with the Chat API.
instance-attribute
How many chat completion choices to generate for each input message.
Note that you will be charged based on the number of generated tokens across all
of the choices. Keep n as 1 to minimize costs.
instance-attribute
Number between -2.0 and 2.0.
Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
See more information about frequency and presence penalties.
instance-attribute
response_format: ResponseFormat
An object specifying the format that the model must output.
Compatible with
GPT-4 Turbo and
all GPT-3.5 Turbo models newer than gpt-3.5-turbo-1106.
Setting to { "type": "json_object" } enables JSON mode, which guarantees the
message the model generates is valid JSON.
Important: when using JSON mode, you must also instruct the model to
produce JSON yourself via a system or user message. Without this, the model may
generate an unending stream of whitespace until the generation reaches the token
limit, resulting in a long-running and seemingly "stuck" request. Also note that
the message content may be partially cut off if finish_reason="length", which
indicates the generation exceeded max_tokens or the conversation exceeded the
max context length.
instance-attribute
This feature is in Beta. If specified, our system will make a best effort to
sample deterministically, such that repeated requests with the same seed and
parameters should return the same result. Determinism is not guaranteed, and you
should refer to the system_fingerprint response parameter to monitor changes
in the backend.
instance-attribute
Up to 4 sequences where the API will stop generating further tokens.
instance-attribute
What sampling temperature to use, between 0 and 2.
Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
We generally recommend altering this or top_p but not both.
instance-attribute
tool_choice: ChatCompletionToolChoiceOptionParam
Controls which (if any) function is called by the model. none means the model
will not call a function and instead generates a message. auto means the model
can pick between generating a message or calling a function. Specifying a
particular function via
{"type": "function", "function": {"name": "my_function"}} forces the model to
call that function.
none is the default when no functions are present. auto is the default if
functions are present.
instance-attribute
tools: Iterable[ChatCompletionToolParam]
A list of tools the model may call.
Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
instance-attribute
An integer between 0 and 20 specifying the number of most likely tokens to
return at each token position, each with an associated log probability.
logprobs must be set to true if this parameter is used.
instance-attribute
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
instance-attribute
user: str
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
Attributes:
| Name | Type | Description |
|---|---|---|
stream |
Optional[Literal[False]]
|
If set, partial message deltas will be sent, like in ChatGPT. |
instance-attribute
stream: Optional[Literal[False]]
If set, partial message deltas will be sent, like in ChatGPT.
Tokens will be sent as data-only
server-sent events
as they become available, with the stream terminated by a data: [DONE]
message.
Example Python code.
Attributes:
| Name | Type | Description |
|---|---|---|
stream |
Required[Literal[True]]
|
If set, partial message deltas will be sent, like in ChatGPT. |
instance-attribute
If set, partial message deltas will be sent, like in ChatGPT.
Tokens will be sent as data-only
server-sent events
as they become available, with the stream terminated by a data: [DONE]
message.
Example Python code.
Attributes:
| Name | Type | Description |
|---|---|---|
description |
str
|
A description of what the function does, used by the model to choose when and |
name |
Required[str]
|
The name of the function to be called. |
parameters |
FunctionParameters
|
The parameters the functions accepts, described as a JSON Schema object. |
instance-attribute
description: str
A description of what the function does, used by the model to choose when and how to call the function.
instance-attribute
name: Required[str]
The name of the function to be called.
Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
instance-attribute
parameters: FunctionParameters
The parameters the functions accepts, described as a JSON Schema object.
See the guide for examples, and the JSON Schema reference for documentation about the format.
Omitting parameters defines a function with an empty parameter list.
Attributes:
| Name | Type | Description |
|---|---|---|
type |
Literal['text', 'json_object']
|
Must be one of |