> ## 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.
# チャット補完を作成
> CometAPI の POST /v1/chat/completions を使用して、ストリーミング、temperature、max_tokens を制御しながら、複数メッセージの会話をチャットモデルに送信します。
CometAPI は、OpenAI、Claude、Gemini などのチャット補完を、単一の OpenAI 互換インターフェースを通じて複数のプロバイダーにルーティングします。`model` パラメータを変更してモデルを切り替えます。ほとんどの OpenAI 互換 SDK は、`base_url` を `https://api.cometapi.com/v1` に設定することで使用できます。
リクエストパラメータとレスポンスフィールドは、モデルプロバイダーによって大きく異なる場合があります。完全なパラメータ一覧やプロバイダー固有の動作が必要な場合は、使用するモデルの提供元の公式ドキュメントを確認してください。たとえば、`reasoning_effort` は推論モデル（o-series、GPT-5.1+）にのみ適用され、一部のモデルは `logprobs` または `n` > 1 をサポートしていません。
OpenAI Pro モデル、o-series 推論モデル、および Codex モデルでは、 [レスポンス](/ja/api/text/responses) エンドポイントを代わりに使用してください。これらのモデルファミリーは、Responses API でより完全にサポートされています。
***
## メッセージのロール
| ロール | 説明 |
| ----------- | -------------------------------------------------------------- |
| `system` | アシスタントの動作と個性を設定します。会話の先頭に配置します。 |
| `developer` | 新しいモデル（o1+）では `system` の代わりとなります。ユーザー入力にかかわらずモデルが従うべき指示を提供します。 |
| `user` | エンドユーザーからのメッセージです。 |
| `assistant` | 会話履歴を維持するために使用される、以前のモデルレスポンスです。 |
| `tool` | ツールまたは関数呼び出しの結果です。元のツール呼び出しと一致する `tool_call_id` を含める必要があります。 |
新しいモデル（GPT-4.1、GPT-5 シリーズ、o-series）では、指示メッセージに `system` ではなく `developer` を使用することを推奨します。どちらも使用できますが、`developer` のほうがより強力な指示追従動作を提供します。
***
## マルチモーダル入力を送信する
多くのモデルは、テキストに加えて画像と音声をサポートしています。マルチモーダルメッセージを送信するには、`content` に配列形式を使用します。
```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"
}
}
]
}
```
`detail` パラメータは画像分析の詳細度を制御します。
* `low` — より高速で、使用トークン数が少ない（固定コスト)
* `high` — 詳細な分析で、より多くのトークンを消費
* `auto` — モデルが決定（デフォルト)
***
## レスポンスをストリーミングする
段階的な出力を受け取るには、`stream` を `true` に設定します。レスポンスは **Server-Sent Events（SSE)**）として配信され、各イベントには `chat.completion.chunk` オブジェクトが含まれます。
```
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]
```
ストリーミングレスポンスにトークン使用量の統計を含めるには、`stream_options.include_usage` を `true` に設定します。使用量データは、`[DONE]` の前の最後のチャンクに表示されます。
***
## 構造化出力をリクエストする
特定のスキーマに一致する有効な JSON をモデルに返させるには、`response_format` を使用します。
```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"}
}
```
JSON Schema モード（`json_schema`）では、出力がスキーマに完全に一致することが保証されます。JSON Object モード（`json_object`）では有効な JSON のみが保証され、構造は強制されません。
***
## ツールと関数を呼び出す
モデルが外部関数を呼び出せるようにするには、ツール定義を指定します。
```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"
}
```
モデルがツールを呼び出すと判断した場合、レスポンスには `finish_reason: "tool_calls"` が含まれ、`message.tool_calls` 配列には関数名と引数が格納されます。次に関数を実行し、一致する `tool_call_id` を含む `tool` メッセージとして結果を送り返します。
***
## プロバイダー間の注意事項
| パラメータ | OpenAI GPT | Claude（互換) | Gemini（互換) |
| ------------------ | ------------------ | ---------------- | --------------------------------- |
| `temperature` | 0–2 | 0–1 | 0–2 |
| `top_p` | 0–1 | 0–1 | 0–1 |
| `n` | 1–128 | 1 のみ | 1–8 |
| `stop` | 最大 4 | 最大 4 | 最大 5 |
| `tools` | ✅ | ✅ | ✅ |
| `response_format` | ✅ | ✅ (json\_schema) | ✅ |
| `logprobs` | ✅ | ❌ | ❌ |
| `reasoning_effort` | o-series, GPT-5.1+ | ❌ | ❌ (Gemini ネイティブでは `thinking` を使用) |
* **`max_tokens`** — 従来のパラメータです。ほとんどのモデルで動作しますが、新しい OpenAI モデルでは非推奨です。
* **`max_completion_tokens`** — GPT-4.1、GPT-5 シリーズ、および o-series モデルに推奨されるパラメータです。出力トークンと推論トークンの両方を含むため、推論モデルでは必須です。
CometAPI は、異なるプロバイダーへのルーティング時にマッピングを自動的に処理します。
* **`system`** — 従来の指示用ロールです。すべてのモデルで動作します。
* **`developer`** — o1 モデルで導入されました。新しいモデルに対してより強力な指示追従を提供します。古いモデルでは `system` の動作にフォールバックします。
GPT-4.1+ または o-series モデルを対象とする新規プロジェクトでは、`developer` を使用してください。
***
## よくある質問
### レート制限を処理するには？
`429 Too Many Requests` が発生した場合は、指数バックオフを実装してください。
```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
```
### 会話コンテキストを維持するには？
会話履歴全体を `messages` 配列に含めます。
```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?"},
]
```
### `finish_reason` とは何を意味しますか？
| 値 | 意味 |
| ---------------- | ---------------------------------------------------- |
| `stop` | 自然な補完、または停止シーケンスに到達しました。 |
| `length` | `max_tokens` または `max_completion_tokens` の上限に到達しました。 |
| `tool_calls` | モデルが 1 つ以上のツールまたは関数呼び出しを実行しました。 |
| `content_filter` | コンテンツポリシーにより出力がフィルタリングされました。 |
### コストを管理するには？
1. 出力長を制限するには `max_completion_tokens` を使用します。
2. 知能とコストのバランスには `gpt-5.6-terra` を使用し、効率的な大量ワークロードには `gpt-5.6-luna` を使用します。
3. プロンプトは簡潔にし、重複したコンテキストを避けてください。
4. `usage` レスポンスフィールドでトークン使用量を監視します。
## 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.
````