CreateCompletionRequest class abstract
CreateCompletionRequest
Properties:
- model - ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.
- prompt
- suffix - The suffix that comes after a completion of inserted text.
- maxTokens - The maximum number of tokens to generate in the completion. The token count of your prompt plus
max_tokens
cannot exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096). - temperature - 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. - topP - 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. - n - How many completions to generate for each prompt. Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for
max_tokens
andstop
. - stream - Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a
data: [DONE]
message. - logprobs - Include the log probabilities on the
logprobs
most likely tokens, as well the chosen tokens. For example, iflogprobs
is 5, the API will return a list of the 5 most likely tokens. The API will always return thelogprob
of the sampled token, so there may be up tologprobs+1
elements in the response. The maximum value forlogprobs
is 5. If you need more than this, please contact us through our Help center and describe your use case. - echo - Echo back the prompt in addition to the completion
- stop
- presencePenalty - 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.
- frequencyPenalty - 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.
- bestOf - Generates
best_of
completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot be streamed. When used withn
,best_of
controls the number of candidate completions andn
specifies how many to return –best_of
must be greater thann
. Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings formax_tokens
andstop
. - logitBias - Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this tokenizer tool (which works for both GPT-2 and GPT-3) to convert text to token IDs. 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. As an example, you can pass
{\"50256\": -100}
to prevent the <|endoftext|> token from being generated. - user - A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
- Annotations
-
- @BuiltValue()
Constructors
- CreateCompletionRequest([void updates(CreateCompletionRequestBuilder b)])
-
factory
Properties
- bestOf → int?
-
Generates
best_of
completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot be streamed. When used withn
,best_of
controls the number of candidate completions andn
specifies how many to return –best_of
must be greater thann
. Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings formax_tokens
andstop
.no setter - echo → bool?
-
Echo back the prompt in addition to the completion
no setter
- frequencyPenalty → num?
-
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.
no setter
- hashCode → int
-
The hash code for this object.
no setterinherited
- logitBias → JsonObject?
-
Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this tokenizer tool (which works for both GPT-2 and GPT-3) to convert text to token IDs. 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. As an example, you can pass
{\"50256\": -100}
to prevent the <|endoftext|> token from being generated.no setter - logprobs → int?
-
Include the log probabilities on the
logprobs
most likely tokens, as well the chosen tokens. For example, iflogprobs
is 5, the API will return a list of the 5 most likely tokens. The API will always return thelogprob
of the sampled token, so there may be up tologprobs+1
elements in the response. The maximum value forlogprobs
is 5. If you need more than this, please contact us through our Help center and describe your use case.no setter - maxTokens → int?
-
The maximum number of tokens to generate in the completion. The token count of your prompt plus
max_tokens
cannot exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096).no setter - model → String
-
ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.
no setter
- n → int?
-
How many completions to generate for each prompt. Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for
max_tokens
andstop
.no setter - presencePenalty → num?
-
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.
no setter
- prompt → CreateCompletionRequestPrompt?
-
no setter
- runtimeType → Type
-
A representation of the runtime type of the object.
no setterinherited
- stop → CreateCompletionRequestStop?
-
no setter
- stream → bool?
-
Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a
data: [DONE]
message.no setter - suffix → String?
-
The suffix that comes after a completion of inserted text.
no setter
- temperature → num?
-
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.no setter - topP → num?
-
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.no setter - user → String?
-
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
no setter
Methods
-
noSuchMethod(
Invocation invocation) → dynamic -
Invoked when a nonexistent method or property is accessed.
inherited
-
rebuild(
dynamic updates(CreateCompletionRequestBuilder)) → CreateCompletionRequest -
Rebuilds the instance.
inherited
-
toBuilder(
) → CreateCompletionRequestBuilder -
Converts the instance to a builder
B
.inherited -
toString(
) → String -
A string representation of this object.
inherited
Operators
-
operator ==(
Object other) → bool -
The equality operator.
inherited
Static Properties
-
serializer
→ Serializer<
CreateCompletionRequest> -
no setter