> ## Documentation Index
> Fetch the complete documentation index at: https://docs.together.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Create completion
> Generate text completions for a given prompt using a language, code, or image model.
## OpenAPI
````yaml POST /completions
openapi: 3.1.0
info:
title: Together APIs
description: The Together REST API. See https://docs.together.ai for more details.
version: 2.0.0
termsOfService: https://www.together.ai/terms-of-service
contact:
name: Together Support
url: https://www.together.ai/contact
license:
name: MIT
url: https://github.com/togethercomputer/openapi/blob/main/LICENSE
servers:
- url: https://api.together.ai/v1
security:
- bearerAuth: []
paths:
/completions:
post:
tags:
- Completion
summary: Create completion
description: >-
Generate text completions for a given prompt using a language, code, or
image model.
operationId: completions
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/CompletionRequest'
responses:
'200':
description: '200'
content:
application/json:
schema:
$ref: '#/components/schemas/CompletionResponse'
text/event-stream:
schema:
$ref: '#/components/schemas/CompletionStream'
'400':
description: BadRequest
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorData'
'401':
description: Unauthorized
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorData'
'404':
description: NotFound
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorData'
'429':
description: RateLimit
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorData'
'503':
description: Overloaded
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorData'
'504':
description: Timeout
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorData'
deprecated: false
x-codeSamples:
- lang: Python
label: Together AI SDK (v2)
source: |
# Docs for v1 can be found by changing the above selector ^
from together import Together
import os
client = Together(
api_key=os.environ.get("TOGETHER_API_KEY"),
)
response = client.completions.create(
model="Qwen/Qwen3.5-9B",
prompt="The largest city in France is",
max_tokens=1
)
print(response.choices[0].text)
- lang: Python
label: Together AI SDK (v1)
source: |
from together import Together
import os
client = Together(
api_key=os.environ.get("TOGETHER_API_KEY"),
)
response = client.completions.create(
model="Qwen/Qwen3.5-9B",
prompt="The largest city in France is",
max_tokens=1
)
print(response.choices[0].text)
- lang: TypeScript
label: Together AI SDK (TypeScript)
source: |
import Together from "together-ai";
const client = new Together({
apiKey: process.env.TOGETHER_API_KEY,
});
const response = await client.completions.create({
model: "Qwen/Qwen3.5-9B",
prompt: "The largest city in France is",
max_tokens: 1,
});
console.log(response.choices[0].text);
- lang: JavaScript
label: Together AI SDK (JavaScript)
source: |
import Together from "together-ai";
const client = new Together({
apiKey: process.env.TOGETHER_API_KEY,
});
const response = await client.completions.create({
model: "Qwen/Qwen3.5-9B",
prompt: "The largest city in France is",
max_tokens: 1
});
console.log(response.choices[0].text);
- lang: Shell
label: cURL
source: |
curl -X POST "https://api.together.ai/v1/completions" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "Qwen/Qwen3.5-9B",
"prompt": "The largest city in France is",
"max_tokens": 1
}'
components:
schemas:
CompletionRequest:
type: object
required:
- model
- prompt
properties:
prompt:
type: string
description: A string providing context for the model to complete.
example: [INST] What is the capital of France? [/INST]
model:
type: string
description: >
The name of the model to query.
[See all of Together AI's
chat
models](https://docs.together.ai/docs/serverless-models#chat-models)
example: mistralai/Mixtral-8x7B-Instruct-v0.1
anyOf:
- type: string
enum:
- meta-llama/Llama-2-70b-hf
- mistralai/Mistral-7B-v0.1
- mistralai/Mixtral-8x7B-v0.1
- Meta-Llama/Llama-Guard-7b
- type: string
max_tokens:
type: integer
description: The maximum number of tokens to generate.
stop:
type: array
description: >-
A list of string sequences that truncate (stop) inference text
output. For example, "" stops generation as soon as the model
generates the given token.
items:
type: string
temperature:
type: number
description: >-
A decimal number from 0-1 that determines the degree of randomness
in the response. A temperature less than 1 favors more correctness
and is appropriate for question answering or summarization. A value
closer to 1 introduces more randomness in the output.
format: float
top_p:
type: number
description: >-
A percentage (also called the nucleus parameter) that's used to
dynamically adjust the number of choices for each predicted token
based on the cumulative probabilities. It specifies a probability
threshold below which all less likely tokens are filtered out. This
technique helps maintain diversity and generate more fluent and
natural-sounding text.
format: float
top_k:
type: integer
description: >-
An integer that's used to limit the number of choices for the next
predicted word or token. It specifies the maximum number of tokens
to consider at each step, based on their probability of occurrence.
This technique helps to speed up the generation process and can
improve the quality of the generated text by focusing on the most
likely options.
format: int32
repetition_penalty:
type: number
description: >-
A number that controls the diversity of generated text by reducing
the likelihood of repeated sequences. Higher values decrease
repetition.
format: float
stream:
type: boolean
description: >-
If true, stream tokens as Server-Sent Events as the model generates
them instead of waiting for the full model response. The stream
terminates with `data: [DONE]`. If false, return a single JSON
object containing the results.
logprobs:
type: integer
minimum: 0
maximum: 20
description: >-
An integer between 0 and 20 of the top k tokens to return log
probabilities for at each generation step, instead of only the
sampled token. Log probabilities help assess model confidence in
token predictions.
echo:
type: boolean
description: >-
If true, the response contains the prompt. Can be used with
`logprobs` to return prompt logprobs.
'n':
type: integer
description: The number of completions to generate for each prompt.
minimum: 1
maximum: 128
safety_model:
type: string
description: >-
The name of the moderation model used to validate tokens. Choose
from the available moderation models found
[here](https://docs.together.ai/docs/inference-models#moderation-models).
example: safety_model_name
anyOf:
- type: string
enum:
- Meta-Llama/Llama-Guard-7b
- type: string
min_p:
type: number
description: >-
A number between 0 and 1 that can be used as an alternative to top-p
and top-k.
format: float
presence_penalty:
type: number
description: >-
A number between -2.0 and 2.0 where a positive value increases the
likelihood of a model talking about new topics.
format: float
frequency_penalty:
type: number
description: >-
A number between -2.0 and 2.0 where a positive value decreases the
likelihood of repeating tokens that have already been mentioned.
format: float
logit_bias:
type: object
additionalProperties:
type: number
format: float
description: >-
Adjusts the likelihood of specific tokens appearing in the generated
output.
example:
'105': 21.4
'1024': -10.5
seed:
type: integer
description: Seed value for reproducibility.
example: 42
CompletionResponse:
type: object
properties:
id:
type: string
choices:
$ref: '#/components/schemas/CompletionChoicesData'
prompt:
$ref: '#/components/schemas/PromptPart'
description: >-
When `echo` is true, the prompt is included in the response.
Additionally, when `logprobs` is also provided, log probability
information is provided on the prompt.
usage:
$ref: '#/components/schemas/UsageData'
created:
type: integer
model:
type: string
object:
description: The object type, which is always `text.completion`.
const: text.completion
required:
- id
- choices
- usage
- created
- prompt
- model
- object
CompletionStream:
oneOf:
- $ref: '#/components/schemas/CompletionEvent'
- $ref: '#/components/schemas/StreamSentinel'
ErrorData:
type: object
required:
- error
properties:
error:
type: object
properties:
message:
type: string
nullable: false
type:
type: string
nullable: false
param:
type: string
nullable: true
default: null
code:
type: string
nullable: true
default: null
required:
- type
- message
CompletionChoicesData:
type: array
items:
type: object
properties:
text:
type: string
example: >-
The capital of France is Paris. It's located in the north-central
part of the country and is one of the most populous and visited
cities in the world, known for its iconic landmarks like the
Eiffel Tower, Louvre Museum, Notre-Dame Cathedral, and more. Paris
is also the capital of the Île-de-France region and is a major
global center for art, fashion, gastronomy, and culture.
seed:
type: integer
finish_reason:
$ref: '#/components/schemas/FinishReason'
logprobs:
$ref: '#/components/schemas/LogprobsPart'
PromptPart:
type: array
items:
type: object
properties:
text:
type: string
example: [INST] What is the capital of France? [/INST]
logprobs:
$ref: '#/components/schemas/LogprobsPart'
UsageData:
type: object
properties:
prompt_tokens:
type: integer
completion_tokens:
type: integer
total_tokens:
type: integer
required:
- prompt_tokens
- completion_tokens
- total_tokens
nullable: true
CompletionEvent:
type: object
required:
- data
properties:
data:
$ref: '#/components/schemas/CompletionChunk'
StreamSentinel:
type: object
required:
- data
properties:
data:
title: stream_signal
type: string
enum:
- '[DONE]'
FinishReason:
type: string
enum:
- stop
- eos
- length
- tool_calls
- function_call
LogprobsPart:
type: object
properties:
token_ids:
type: array
items:
type: number
description: List of token IDs corresponding to the logprobs
tokens:
type: array
items:
type: string
description: List of token strings
token_logprobs:
type: array
items:
type: number
description: List of token log probabilities
top_logprobs:
$ref: '#/components/schemas/TopLogprobs'
CompletionChunk:
type: object
required:
- id
- token
- choices
- usage
- finish_reason
properties:
id:
type: string
token:
$ref: '#/components/schemas/CompletionToken'
created:
type: integer
object:
description: The object type, which is always `completion.chunk`.
const: completion.chunk
choices:
title: CompletionChoices
type: array
items:
$ref: '#/components/schemas/CompletionChoice'
usage:
allOf:
- $ref: '#/components/schemas/UsageData'
- nullable: true
seed:
type: integer
finish_reason:
allOf:
- $ref: '#/components/schemas/FinishReason'
- nullable: true
TopLogprobs:
description: Top log probabilities for the tokens.
type: object
additionalProperties:
type: number
CompletionToken:
type: object
required:
- id
- text
- logprob
- special
properties:
id:
type: integer
text:
type: string
logprob:
type: number
special:
type: boolean
CompletionChoice:
type: object
required:
- index
properties:
text:
type: string
index:
type: integer
delta:
title: CompletionChoiceDelta
type: object
required:
- role
properties:
token_id:
type: integer
role:
type: string
enum:
- system
- user
- assistant
- function
- tool
content:
type: string
nullable: true
reasoning:
type: string
nullable: true
tool_calls:
type: array
items:
$ref: '#/components/schemas/ToolChoice'
function_call:
type: object
deprecated: true
nullable: true
properties:
arguments:
type: string
name:
type: string
required:
- arguments
- name
ToolChoice:
type: object
required:
- id
- type
- function
- index
properties:
index:
type: number
id:
type: string
type:
type: string
enum:
- function
function:
type: object
required:
- name
- arguments
properties:
name:
type: string
example: function_name
arguments:
type: string
securitySchemes:
bearerAuth:
type: http
scheme: bearer
x-bearer-format: bearer
x-default: default
````