> ## Documentation Index
> Fetch the complete documentation index at: https://apidoc.cometapi.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Создание Chat Completion
> Используйте CometAPI POST /v1/chat/completions для отправки многостадийных диалогов чат-моделям с настройками Streaming, temperature и max_tokens.
CometAPI направляет Chat Completions нескольким провайдерам, включая OpenAI, Claude и Gemini, через единый OpenAI-совместимый интерфейс. Переключайтесь между моделями, изменяя параметр `model`; большинство OpenAI-совместимых SDK работают при установке `base_url` в `https://api.cometapi.com/v1`.
Параметры запроса и поля ответа могут существенно различаться у разных провайдеров моделей. Если вам требуется полный список параметров или поведение, специфичное для провайдера, обращайтесь к официальной документации провайдера используемой модели. Например, `reasoning_effort` применяется только к reasoning-моделям (o-series, GPT-5.1+), а некоторые модели не поддерживают `logprobs` или `n` > 1.
Для моделей OpenAI Pro, reasoning-моделей o-series и моделей Codex используйте конечную точку [Responses](/ru/api/text/responses) вместо неё. Эти семейства моделей имеют более полную поддержку в API Responses.
***
## Роли сообщений
| Роль | Описание |
| ----------- | -------------------------------------------------------------------------------------------------------------------------------------- |
| `system` | Задаёт поведение и индивидуальность ассистента. Размещается в начале диалога. |
| `developer` | Заменяет `system` для новых моделей (o1+). Содержит инструкции, которым модель должна следовать независимо от пользовательского ввода. |
| `user` | Сообщения от конечного пользователя. |
| `assistant` | Предыдущие ответы модели, используемые для сохранения истории диалога. |
| `tool` | Результаты вызовов инструментов или функций. Должны включать `tool_call_id`, соответствующий исходному вызову инструмента. |
Для новых моделей (GPT-4.1, серии GPT-5, o-series) для сообщений с инструкциями предпочтительнее использовать `developer` вместо `system`. Работают оба варианта, но `developer` обеспечивает более строгое следование инструкциям.
***
## Отправка Multimodal-ввода
Многие модели поддерживают изображения и аудио наряду с текстом. Чтобы отправлять Multimodal-сообщения, используйте формат массива для `content`:
```json theme={null}
{
"role": "user",
"content": [
{"type": "text", "text": "Describe this image"},
{
"type": "image_url",
"image_url": {
"url": "https://example.com/image.png",
"detail": "high"
}
}
]
}
```
Параметр `detail` управляет глубиной анализа изображений:
* `low` — быстрее, использует меньше Tokens (фиксированная стоимость)
* `high` — подробный анализ, расходуется больше Tokens
* `auto` — решение принимает модель (по умолчанию)
***
## Потоковая передача ответов
Чтобы получать результат постепенно, установите `stream` в `true`. Ответ передаётся в виде **Server-Sent Events (SSE)**, где каждое событие содержит объект `chat.completion.chunk`:
```
data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","choices":[{"index":0,"delta":{"role":"assistant"},"finish_reason":null}]}
data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]}
data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","choices":[{"index":0,"delta":{"content":"!"},"finish_reason":null}]}
data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}
data: [DONE]
```
Чтобы включить статистику использования Tokens в потоковые ответы, установите `stream_options.include_usage` в `true`. Данные об использовании появляются в последнем чанке перед `[DONE]`.
***
## Запрос структурированного вывода
Чтобы принудительно вернуть корректный JSON, соответствующий определённой схеме, используйте `response_format`:
```json JSON Schema Mode theme={null}
{
"response_format": {
"type": "json_schema",
"json_schema": {
"name": "result",
"strict": true,
"schema": {
"type": "object",
"properties": {
"answer": {"type": "string"},
"confidence": {"type": "number"}
},
"required": ["answer", "confidence"],
"additionalProperties": false
}
}
}
}
```
```json JSON Object Mode theme={null}
{
"response_format": {"type": "json_object"}
}
```
Режим JSON Schema (`json_schema`) гарантирует, что вывод в точности соответствует вашей схеме. Режим JSON Object (`json_object`) гарантирует только корректный JSON — структура не проверяется.
***
## Вызов инструментов и функций
Чтобы позволить модели вызывать внешние функции, предоставьте определения инструментов:
```json theme={null}
{
"tools": [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get current weather for a city",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "City name"}
},
"required": ["location"]
}
}
}
],
"tool_choice": "auto"
}
```
Когда модель решает вызвать инструмент, ответ будет содержать `finish_reason: "tool_calls"`, а массив `message.tool_calls` будет включать имя функции и аргументы. Затем выполните функцию и отправьте результат обратно как сообщение `tool` с соответствующим `tool_call_id`.
***
## Примечания по провайдерам
| Параметр | OpenAI GPT | Claude (через compat) | Gemini (через compat) |
| ------------------ | ------------------ | --------------------- | ----------------------------------------------- |
| `temperature` | 0–2 | 0–1 | 0–2 |
| `top_p` | 0–1 | 0–1 | 0–1 |
| `n` | 1–128 | Только 1 | 1–8 |
| `stop` | До 4 | До 4 | До 5 |
| `tools` | ✅ | ✅ | ✅ |
| `response_format` | ✅ | ✅ (json\_schema) | ✅ |
| `logprobs` | ✅ | ❌ | ❌ |
| `reasoning_effort` | o-series, GPT-5.1+ | ❌ | ❌ (используйте `thinking` для нативного Gemini) |
* **`max_tokens`** — Устаревший параметр. Работает с большинством моделей, но не рекомендуется для новых моделей OpenAI.
* **`max_completion_tokens`** — Рекомендуемый параметр для моделей GPT-4.1, серии GPT-5 и моделей o-series. Обязателен для reasoning-моделей, так как включает как выходные Tokens, так и Tokens рассуждений.
CometAPI автоматически обрабатывает сопоставление при маршрутизации к разным провайдерам.
* **`system`** — Традиционная роль для инструкций. Работает со всеми моделями.
* **`developer`** — Представлена в моделях o1. Обеспечивает более строгое следование инструкциям в новых моделях. В старых моделях используется поведение `system`.
Используйте `developer` для новых проектов, ориентированных на модели GPT-4.1+ или o-series.
***
## Часто задаваемые вопросы
### Как обрабатывать ограничения скорости?
При возникновении `429 Too Many Requests` реализуйте экспоненциальную задержку повторных попыток:
```python theme={null}
import os
import time
import random
from openai import OpenAI, RateLimitError
client = OpenAI(
base_url="https://api.cometapi.com/v1",
api_key=os.environ["COMETAPI_KEY"],
)
def chat_with_retry(messages, max_retries=3):
for i in range(max_retries):
try:
return client.chat.completions.create(
model="gpt-5.6-sol",
messages=messages,
)
except RateLimitError:
if i < max_retries - 1:
wait_time = (2 ** i) + random.random()
time.sleep(wait_time)
else:
raise
```
### Как сохранять контекст диалога?
Включайте полную историю диалога в массив `messages`:
```python theme={null}
messages = [
{"role": "developer", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is Python?"},
{"role": "assistant", "content": "Python is a high-level programming language..."},
{"role": "user", "content": "What are its main advantages?"},
]
```
### Что означает `finish_reason`?
| Значение | Смысл |
| ---------------- | --------------------------------------------------------------- |
| `stop` | Естественное завершение или достижение стоп-последовательности. |
| `length` | Достигнут лимит `max_tokens` или `max_completion_tokens`. |
| `tool_calls` | Модель вызвала один или несколько инструментов или функций. |
| `content_filter` | Вывод был отфильтрован в соответствии с политикой контента. |
### Как контролировать расходы?
1. Используйте `max_completion_tokens` для ограничения длины вывода.
2. Используйте `gpt-5.6-terra` для баланса между интеллектуальностью и стоимостью или `gpt-5.6-luna` для эффективных высоконагруженных задач.
3. Делайте Prompt краткими — избегайте избыточного контекста.
4. Отслеживайте использование Tokens в поле ответа `usage`.
## OpenAPI
````yaml api/openapi/text/post-chat.openapi.json POST /v1/chat/completions
openapi: 3.1.0
info:
title: Chat Completions API
version: 1.0.0
servers:
- url: https://api.cometapi.com
security:
- bearerAuth: []
paths:
/v1/chat/completions:
post:
summary: Chat Completions
description: >-
Routes chat requests across multiple model providers. Request parameters
and response fields can vary significantly by provider, so check the
official documentation for the provider behind the model you use when
you need provider-specific parameters or behavior details.
operationId: chat_completions
requestBody:
required: true
content:
application/json:
schema:
type: object
required:
- model
- messages
properties:
model:
type: string
description: >-
Model ID to use for this request. See the [Models
page](/overview/models) for current options.
example: gpt-4.1
default: gpt-5.6-sol
messages:
type: array
description: >-
A list of messages forming the conversation. Each message
has a `role` (`system`, `user`, `assistant`, or `developer`)
and `content` (text string or multimodal content array).
items:
type: object
properties:
role:
type: string
enum:
- system
- user
- assistant
- tool
- developer
description: >-
The role of the message author. Common values:
`system` (recommended for system-level instructions),
`user`, `assistant`, `tool`. Newer OpenAI models may
also accept `developer` instead of `system`.
content:
type: string
description: >-
The message content. Can be a text string or an array
of content objects for multimodal input (text +
images).
default:
- role: system
content: You are a helpful assistant.
- role: user
content: Hello!
stream:
type: boolean
description: >-
If `true`, partial response tokens are delivered
incrementally via server-sent events (SSE). The stream ends
with a `data: [DONE]` message.
temperature:
type: number
description: >-
Sampling temperature between 0 and 2. Higher values (e.g.,
0.8) produce more random output; lower values (e.g., 0.2)
make output more focused and deterministic. Recommended to
adjust this or `top_p`, but not both.
minimum: 0
maximum: 2
default: 1
top_p:
type: number
description: >-
Nucleus sampling parameter. The model considers only the
tokens whose cumulative probability reaches `top_p`. For
example, 0.1 means only the top 10% probability tokens are
considered. Recommended to adjust this or `temperature`, but
not both.
minimum: 0
maximum: 1
default: 1
'n':
type: integer
description: >-
Number of completion choices to generate for each input
message. Defaults to 1.
default: 1
stop:
type: string
description: >-
Up to 4 sequences where the API will stop generating further
tokens. Can be a string or an array of strings.
max_tokens:
type: integer
description: >-
Maximum number of tokens to generate in the completion. The
total of input + output tokens is capped by the model's
context length.
presence_penalty:
type: number
description: >-
Number between -2.0 and 2.0. Positive values penalize tokens
based on whether they have already appeared, encouraging the
model to explore new topics.
minimum: -2
maximum: 2
default: 0
frequency_penalty:
type: number
description: >-
Number between -2.0 and 2.0. Positive values penalize tokens
proportionally to how often they have appeared, reducing
verbatim repetition.
minimum: -2
maximum: 2
default: 0
logit_bias:
type: object
description: >-
A JSON object mapping token IDs to bias values from -100 to
100. The bias is added to the model's logits before
sampling. Values between -1 and 1 subtly adjust likelihood;
-100 or 100 effectively ban or force selection of a token.
user:
type: string
description: >-
A unique identifier for your end-user. Helps with abuse
detection and monitoring.
max_completion_tokens:
type: integer
description: >-
An upper bound for the number of tokens to generate,
including visible output tokens and reasoning tokens. Use
this instead of `max_tokens` for GPT-4.1+, GPT-5 series, and
o-series models.
response_format:
type: object
description: >-
Specifies the output format. Use `{"type": "json_object"}`
for JSON mode, or `{"type": "json_schema", "json_schema":
{...}}` for strict structured output.
properties:
type:
type: string
enum:
- text
- json_object
- json_schema
description: >-
Output format type: `text` (default), `json_object`, or
`json_schema`.
json_schema:
type: object
description: The JSON Schema definition.
tools:
type: array
description: >-
A list of tools the model may call. Currently supports
`function` type tools.
items:
type: object
properties:
type:
type: string
enum:
- function
description: Tool type. Use `function`.
function:
type: object
properties:
name:
type: string
description: >-
Function name. The model repeats it inside
`tool_calls` when it calls the tool.
description:
type: string
description: >-
What the function does. The model uses this text
to decide when to call it.
parameters:
type: object
description: >-
JSON Schema object that describes the function
arguments.
strict:
type: boolean
description: >-
If `true`, the model must produce arguments that
exactly match the JSON Schema.
description: The function definition the model may call.
tool_choice:
type:
- string
- object
description: >-
Controls how the model selects tools. `auto` (default):
model decides. `none`: no tools. `required`: must call a
tool.
default: auto
logprobs:
type: boolean
description: Whether to return log probabilities of the output tokens.
default: false
top_logprobs:
type: integer
description: >-
Number of most likely tokens to return at each position
(0-20). Requires `logprobs` to be `true`.
minimum: 0
maximum: 20
reasoning_effort:
type: string
description: >-
Controls the reasoning effort for o-series and GPT-5.1+
models.
enum:
- low
- medium
- high
stream_options:
type: object
description: Options for streaming. Only valid when `stream` is `true`.
properties:
include_usage:
type: boolean
description: >-
If true, includes usage stats in the final streaming
chunk.
service_tier:
type: string
description: Specifies the processing tier.
enum:
- auto
- default
- flex
- priority
default:
model: gpt-5.6-sol
messages:
- role: system
content: You are a helpful assistant.
- role: user
content: Hello!
examples:
Default:
summary: Default
value:
model: gpt-5.6-sol
messages:
- role: system
content: You are a helpful assistant.
- role: user
content: Hello!
Image Input:
summary: Image Input
value:
model: gpt-4.1
messages:
- role: user
content:
- type: text
text: What is in this image?
- type: image_url
image_url:
url: https://picsum.photos/1920/1080
max_tokens: 300
Streaming:
summary: Streaming
value:
model: gpt-5.6-sol
messages:
- role: system
content: You are a helpful assistant.
- role: user
content: Hello!
stream: true
Function Calling:
summary: Function Calling
value:
model: gpt-5.4
messages:
- role: user
content: What is the weather like in Boston today?
tools:
- type: function
function:
name: get_current_weather
description: Get the current weather in a given location
parameters:
type: object
properties:
location:
type: string
description: The city and state, e.g. San Francisco, CA
unit:
type: string
enum:
- celsius
- fahrenheit
description: Temperature unit.
required:
- location
tool_choice: auto
responses:
'200':
description: Successful chat completion response.
content:
application/json:
schema:
type: object
properties:
id:
type: string
description: Unique completion identifier.
example: chatcmpl-abc123
object:
type: string
enum:
- chat.completion
example: chat.completion
description: >-
Object type. Non-streaming responses use
`chat.completion`.
created:
type: integer
description: Unix timestamp of creation.
example: 1774412483
model:
type: string
description: The model used (may include version suffix).
example: gpt-5.4-2026-03-05
choices:
type: array
description: Array of completion choices.
items:
type: object
properties:
index:
type: integer
description: Index of this choice in the `choices` array.
message:
type: object
properties:
role:
type: string
enum:
- assistant
description: Role of the generated message, `assistant`.
content:
type:
- string
- 'null'
description: >-
The generated text. null when the model calls
tools.
refusal:
type:
- string
- 'null'
description: Refusal message if the model refused.
tool_calls:
type: array
description: Tool calls the model wants to make.
items:
type: object
properties:
id:
type: string
description: >-
Unique ID of the tool call. Send it back
as `tool_call_id` with the tool result
message.
type:
type: string
enum:
- function
description: Tool call type, `function`.
function:
type: object
properties:
name:
type: string
description: Name of the function to call.
arguments:
type: string
description: >-
Function arguments as a JSON-encoded
string. Parse before use; the model can
produce invalid JSON.
description: The function the model wants to call.
annotations:
type: array
items:
type: object
description: >-
Annotations attached to the message content,
such as URL citations, when the provider returns
them.
description: The assistant message generated by the model.
logprobs:
type:
- object
- 'null'
description: >-
Log probability details when the request sets
`logprobs`; otherwise `null`.
finish_reason:
type: string
enum:
- stop
- length
- tool_calls
- content_filter
description: >-
Why generation stopped: `stop`, `length`,
`tool_calls`, or `content_filter`.
usage:
type: object
properties:
prompt_tokens:
type: integer
example: 29
description: Tokens in the input messages.
completion_tokens:
type: integer
example: 2
description: >-
Tokens generated in the completion, including
reasoning tokens for reasoning models.
total_tokens:
type: integer
example: 31
description: Sum of prompt and completion tokens.
prompt_tokens_details:
type: object
properties:
cached_tokens:
type: integer
example: 0
description: >-
Prompt tokens served from the provider prompt
cache.
audio_tokens:
type: integer
example: 0
description: Prompt tokens that came from audio input.
description: Breakdown of prompt token sources.
completion_tokens_details:
type: object
properties:
reasoning_tokens:
type: integer
example: 0
description: >-
Tokens the model spent on internal reasoning.
Billed as output tokens.
audio_tokens:
type: integer
example: 0
description: Completion tokens used for audio output.
accepted_prediction_tokens:
type: integer
example: 0
description: >-
Predicted-output tokens that matched the final
output and were accepted.
rejected_prediction_tokens:
type: integer
example: 0
description: >-
Predicted-output tokens that did not match the
final output and were discarded.
description: Breakdown of completion token usage.
description: >-
Token accounting for this request. Billing uses these
counts.
service_tier:
type: string
example: default
description: >-
Service tier that processed the request, when the provider
reports one.
system_fingerprint:
type:
- string
- 'null'
example: fp_490a4ad033
description: >-
Provider backend configuration fingerprint, when the
provider reports one.
example:
id: chatcmpl-DNA27oKtBUL8TmbGpBM3B3zhWgYfZ
object: chat.completion
created: 1774412483
model: gpt-4.1-nano-2025-04-14
choices:
- index: 0
message:
role: assistant
content: Four
refusal: null
annotations: []
logprobs: null
finish_reason: stop
usage:
prompt_tokens: 29
completion_tokens: 2
total_tokens: 31
prompt_tokens_details:
cached_tokens: 0
audio_tokens: 0
completion_tokens_details:
reasoning_tokens: 0
audio_tokens: 0
accepted_prediction_tokens: 0
rejected_prediction_tokens: 0
service_tier: default
system_fingerprint: fp_490a4ad033
'400':
description: >-
Request validation failed before the request could be processed
normally.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
example:
error:
code: ''
message: 'model name is required (request id: )'
type: comet_api_error
'401':
description: API key is missing, malformed, or invalid.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
example:
error:
code: ''
message: 'invalid token (request id: )'
type: comet_api_error
'500':
description: >-
Internal failure or a request-shape error surfaced as a
server-status response.
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
example:
error:
message: 'field messages is required (request id: )'
type: comet_api_error
param: ''
code: invalid_request
x-codeSamples:
- lang: Python
label: Default
source: |
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.cometapi.com/v1",
api_key=os.environ["COMETAPI_KEY"],
)
completion = client.chat.completions.create(
model="gpt-5.6-sol",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"},
],
)
print(completion.choices[0].message)
- lang: Python
label: Image Input
source: |
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.cometapi.com/v1",
api_key=os.environ["COMETAPI_KEY"],
)
completion = client.chat.completions.create(
model="gpt-4.1",
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What is in this image?"},
{
"type": "image_url",
"image_url": {"url": "https://picsum.photos/1920/1080"},
},
],
}
],
max_tokens=300,
)
print(completion.choices[0].message)
- lang: Python
label: Streaming
source: |
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.cometapi.com/v1",
api_key=os.environ["COMETAPI_KEY"],
)
stream = client.chat.completions.create(
model="gpt-5.4",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"},
],
stream=True,
)
for chunk in stream:
if chunk.choices[0].delta.content is not None:
print(chunk.choices[0].delta.content, end="")
- lang: Python
label: Functions
source: |
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.cometapi.com/v1",
api_key=os.environ["COMETAPI_KEY"],
)
completion = client.chat.completions.create(
model="gpt-4.1",
messages=[
{"role": "user", "content": "What is the weather like in Boston today?"}
],
tools=[
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
},
"required": ["location"],
},
},
}
],
tool_choice="auto",
)
print(completion.choices[0].message)
- lang: Python
label: Logprobs
source: |
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.cometapi.com/v1",
api_key=os.environ["COMETAPI_KEY"],
)
completion = client.chat.completions.create(
model="gpt-5.4",
messages=[
{"role": "user", "content": "Hello!"}
],
logprobs=True,
top_logprobs=2,
)
print(completion.choices[0].logprobs)
- lang: JavaScript
label: Default
source: |
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.cometapi.com/v1",
apiKey: process.env.COMETAPI_KEY,
});
const completion = await client.chat.completions.create({
model: "gpt-5.6-sol",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Hello!" },
],
});
console.log(completion.choices[0].message);
- lang: JavaScript
label: Image Input
source: |
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.cometapi.com/v1",
apiKey: process.env.COMETAPI_KEY,
});
const completion = await client.chat.completions.create({
model: "gpt-4.1",
messages: [
{
role: "user",
content: [
{ type: "text", text: "What is in this image?" },
{
type: "image_url",
image_url: { url: "https://picsum.photos/1920/1080" },
},
],
},
],
max_tokens: 300,
});
console.log(completion.choices[0].message);
- lang: JavaScript
label: Streaming
source: |
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.cometapi.com/v1",
apiKey: process.env.COMETAPI_KEY,
});
const stream = await client.chat.completions.create({
model: "gpt-5.6-sol",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Hello!" },
],
stream: true,
});
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content || "");
}
- lang: JavaScript
label: Functions
source: |
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.cometapi.com/v1",
apiKey: process.env.COMETAPI_KEY,
});
const completion = await client.chat.completions.create({
model: "gpt-4.1",
messages: [
{ role: "user", content: "What is the weather like in Boston today?" },
],
tools: [
{
type: "function",
function: {
name: "get_current_weather",
description: "Get the current weather in a given location",
parameters: {
type: "object",
properties: {
location: { type: "string", description: "The city and state" },
unit: { type: "string", enum: ["celsius", "fahrenheit"] },
},
required: ["location"],
},
},
},
],
tool_choice: "auto",
});
console.log(completion.choices[0].message);
- lang: JavaScript
label: Logprobs
source: |
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.cometapi.com/v1",
apiKey: process.env.COMETAPI_KEY,
});
const completion = await client.chat.completions.create({
model: "gpt-5.4",
messages: [
{ role: "user", content: "Hello!" },
],
logprobs: true,
top_logprobs: 2,
});
console.log(completion.choices[0].logprobs);
- lang: Shell
label: Default
source: |
curl https://api.cometapi.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $COMETAPI_KEY" \
-d '{
"model": "gpt-5.6-sol",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"}
]
}'
- lang: Shell
label: Image Input
source: |
curl https://api.cometapi.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $COMETAPI_KEY" \
-d '{
"model": "gpt-4.1",
"messages": [
{
"role": "user",
"content": [
{"type": "text", "text": "What is in this image?"},
{"type": "image_url", "image_url": {"url": "https://picsum.photos/1920/1080"}}
]
}
],
"max_tokens": 300
}'
- lang: Shell
label: Streaming
source: |
curl https://api.cometapi.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $COMETAPI_KEY" \
-d '{
"model": "gpt-5.6-sol",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"}
],
"stream": true
}'
- lang: Shell
label: Functions
source: |
curl https://api.cometapi.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $COMETAPI_KEY" \
-d '{
"model": "gpt-4.1",
"messages": [
{"role": "user", "content": "What is the weather like in Boston today?"}
],
"tools": [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city and state"},
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
},
"required": ["location"]
}
}
}
],
"tool_choice": "auto"
}'
- lang: Shell
label: Logprobs
source: |
curl https://api.cometapi.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $COMETAPI_KEY" \
-d '{
"model": "gpt-5.4",
"messages": [
{"role": "user", "content": "Hello!"}
],
"logprobs": true,
"top_logprobs": 2
}'
components:
schemas:
ErrorResponse:
type: object
required:
- error
properties:
error:
type: object
required:
- message
- type
properties:
message:
type: string
description: Human-readable error message. It often includes a request id.
type:
type: string
description: CometAPI error type, such as `comet_api_error`.
param:
type:
- string
- 'null'
description: Related parameter when the platform provides one.
code:
type:
- string
- 'null'
description: Error code. Request-shape errors may use `invalid_request`.
description: Error envelope returned for failed requests.
securitySchemes:
bearerAuth:
type: http
scheme: bearer
description: Bearer token authentication. Use your CometAPI key.
````