Completions
Create a completion
Creates a completion from the supplied request.
Isi Permintaan
The request body.
model
string | enum
diperlukan
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.
enum
prompt
string | string[] | OpenAI.integer[] | OpenAI.integer[][] | null
diperlukan
The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays. Note that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document.
best_of
integer | null
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 with n, best_of controls the number of candidate completions and n specifies how many to return – best_of must be greater than n. 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 and stop.
echo
boolean | null
Echo back the prompt in addition to the completion
frequency_penalty
number | null
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.
logit_bias
object | null
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 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.
logprobs
integer | null
Include the log probabilities on the logprobs most likely output tokens, as well the chosen tokens. For example, if logprobs is 5, the API will return a list of the 5 most likely tokens. The API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response. The maximum value for logprobs is 5.
max_tokens
integer | null
The maximum number of tokens that can be generated in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length. Example Python code for counting tokens.
n
integer | null
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 and stop.
presence_penalty
number | null
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.
seed
integer | null
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.
stop
string | string[] | null
Not supported with latest reasoning models o3 and o4-mini. Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
stream
boolean | null
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. Example Python code.
stream_options
OpenAI.ChatCompletionStreamOptions | null
Options for streaming response. Only set this when you set stream: true.
include_usage
boolean
If set, an additional chunk will be streamed before the data: [DONE] message. The usage field on this chunk shows the token usage statistics for the entire request, and the choices field will always be an empty array. All other chunks will also include a usage field, but with a null value. NOTE: If the stream is interrupted, you may not receive the final usage chunk which contains the total token usage for the request.
include_obfuscation
boolean
When true, stream obfuscation will be enabled. Stream obfuscation adds random characters to an obfuscation field on streaming delta events to normalize payload sizes as a mitigation to certain side-channel attacks. These obfuscation fields are included by default, but add a small amount of overhead to the data stream. You can set include_obfuscation to false to optimize for bandwidth if you trust the network links between your application and the OpenAI API.
suffix
string | null
The suffix that comes after a completion of inserted text. This parameter is only supported for gpt-3.5-turbo-instruct.
temperature
number | null
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.
top_p
number | null
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.
user
string
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
Respons
The request has succeeded.
Isi
id
string
diperlukan
A unique identifier for the completion.
choices
OpenAI.CreateCompletionResponseChoices[]
diperlukan
The list of completion choices the model generated for the input prompt.
created
integer
diperlukan
The Unix timestamp (in seconds) of when the completion was created.
model
string
diperlukan
The model used for completion.
system_fingerprint
string
This fingerprint represents the backend configuration that the model runs with. Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.
object
enum
diperlukan
The object type, which is always "text_completion"
usage
OpenAI.CompletionUsage
Usage statistics for the completion request.
completion_tokens_details
OpenAI.CompletionUsageCompletionTokensDetails
prompt_tokens_details
OpenAI.CompletionUsagePromptTokensDetails
Minta
curl https://api.openai.com/v1/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "VAR_completion_model_id",
"prompt": "Say this is a test",
"max_tokens": 7,
"temperature": 0
}'import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("OPENAI_API_KEY"), # This is the default and can be omitted
)
for completion in client.completions.create(
model="gpt-3.5-turbo-instruct",
prompt="This is a test.",
):
print(completion)import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const completion = await openai.completions.create({
model: "VAR_completion_model_id",
prompt: "Say this is a test.",
max_tokens: 7,
temperature: 0,
});
console.log(completion);
}
main();import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
});
const completion = await client.completions.create({
model: 'gpt-3.5-turbo-instruct',
prompt: 'This is a test.',
});
console.log(completion);package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
completion, err := client.Completions.New(context.TODO(), openai.CompletionNewParams{
Model: openai.CompletionNewParamsModelGPT3_5TurboInstruct,
Prompt: openai.CompletionNewParamsPromptUnion{
OfString: openai.String("This is a test."),
},
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v
", completion)
}package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.completions.Completion;
import com.openai.models.completions.CompletionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
CompletionCreateParams params = CompletionCreateParams.builder()
.model(CompletionCreateParams.Model.GPT_3_5_TURBO_INSTRUCT)
.prompt("This is a test.")
.build();
Completion completion = client.completions().create(params);
}
}require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
completion = openai.completions.create(model: :"gpt-3.5-turbo-instruct", prompt: "This is a test.")
puts(completion)Tanggapan
{
"id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
"object": "text_completion",
"created": 1589478378,
"model": "VAR_completion_model_id",
"system_fingerprint": "fp_44709d6fcb",
"choices": [
{
"text": "
This is indeed a test",
"index": 0,
"logprobs": null,
"finish_reason": "length"
}
],
"usage": {
"prompt_tokens": 5,
"completion_tokens": 7,
"total_tokens": 12
}
}Minta
curl https://api.openai.com/v1/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
"model": "VAR_completion_model_id",
"prompt": "Say this is a test",
"max_tokens": 7,
"temperature": 0,
"stream": true
}'import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("OPENAI_API_KEY"), # This is the default and can be omitted
)
for completion in client.completions.create(
model="gpt-3.5-turbo-instruct",
prompt="This is a test.",
):
print(completion)import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const stream = await openai.completions.create({
model: "VAR_completion_model_id",
prompt: "Say this is a test.",
stream: true,
});
for await (const chunk of stream) {
console.log(chunk.choices[0].text)
}
}
main();import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
});
const completion = await client.completions.create({
model: 'gpt-3.5-turbo-instruct',
prompt: 'This is a test.',
});
console.log(completion);package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithAPIKey("My API Key"),
)
completion, err := client.Completions.New(context.TODO(), openai.CompletionNewParams{
Model: openai.CompletionNewParamsModelGPT3_5TurboInstruct,
Prompt: openai.CompletionNewParamsPromptUnion{
OfString: openai.String("This is a test."),
},
})
if err != nil {
panic(err.Error())
}
fmt.Printf("%+v
", completion)
}package com.openai.example;
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.completions.Completion;
import com.openai.models.completions.CompletionCreateParams;
public final class Main {
private Main() {}
public static void main(String[] args) {
OpenAIClient client = OpenAIOkHttpClient.fromEnv();
CompletionCreateParams params = CompletionCreateParams.builder()
.model(CompletionCreateParams.Model.GPT_3_5_TURBO_INSTRUCT)
.prompt("This is a test.")
.build();
Completion completion = client.completions().create(params);
}
}require "openai"
openai = OpenAI::Client.new(api_key: "My API Key")
completion = openai.completions.create(model: :"gpt-3.5-turbo-instruct", prompt: "This is a test.")
puts(completion)Tanggapan
{
"id": "cmpl-7iA7iJjj8V2zOkCGvWF2hAkDWBQZe",
"object": "text_completion",
"created": 1690759702,
"choices": [
{
"text": "This",
"index": 0,
"logprobs": null,
"finish_reason": null
}
],
"model": "gpt-3.5-turbo-instruct"
"system_fingerprint": "fp_44709d6fcb",
}