テキストモデル
レスポンス
CometAPI の POST /v1/responses を使用して、マルチモーダル入力、ステートフルなチャット、組み込みツール、関数呼び出しに対応した高度なモデル出力を生成します。
POST
/
v1
/
responses
from openai import OpenAI
client = OpenAI(
base_url="https://api.cometapi.com/v1",
api_key="<COMETAPI_KEY>",
)
response = client.responses.create(
model="gpt-5.4",
input="Tell me a three sentence bedtime story about a unicorn.",
)
print(response.output_text){
"id": "resp_0a153ae8201f73bc0069a7e8044cc481",
"object": "response",
"created_at": 1772611588,
"status": "completed",
"background": false,
"completed_at": 1772611589,
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4.1-nano",
"output": [
{
"id": "msg_0a153ae8201f73bc0069a7e8049a8881",
"type": "message",
"status": "completed",
"content": [
{
"type": "output_text",
"annotations": [],
"text": "Four."
}
],
"role": "assistant"
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"prompt_cache_key": null,
"prompt_cache_retention": null,
"reasoning": {
"effort": null,
"summary": null
},
"safety_identifier": null,
"service_tier": "auto",
"store": true,
"temperature": 1,
"text": {
"format": {
"type": "text"
},
"verbosity": "medium"
},
"tool_choice": "auto",
"tools": [],
"top_p": 1,
"truncation": "disabled",
"usage": {
"input_tokens": 19,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 9,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 28
},
"user": null,
"metadata": {}
}概要
Responses API は、CometAPI の高度なモデル応答生成エンドポイントです。Chat Completions よりも豊富なインターフェースを提供し、マルチモーダル（Multimodal）入力、ステートフルな会話、ツール連携、構造化出力を単一のエンドポイントですべて扱えます。主な機能
- マルチモーダル入力 — テキスト、画像、ファイル（PDF を含む）、URL を入力として受け付けます
- ステートフルな会話 —
previous_response_idまたはconversationを使ってレスポンスを連結し、自分でメッセージ履歴を管理する必要はありません - 組み込みツール —
web_search_preview、file_search、code_interpreterなどをセットアップ不要で利用できます - 関数呼び出し — モデルが構造化された引数で呼び出せるカスタム関数を定義できます
- 構造化出力 —
text.formatパラメータを通じて JSON Schema に準拠した出力を要求できます - 推論モデル — o-series および gpt-5 モデル向けに
reasoning.effortパラメータで推論の深さを設定できます - ストリーミング（Streaming） — SSE を介して、きめ細かなイベントタイプ（
response.output_text.delta、response.completedなど）でレスポンスをストリーミングできます
重要な注意事項
モデルごとの差異 — モデルプロバイダーによって対応するリクエストパラメータや返されるレスポンスフィールドが異なる場合があります。CometAPI で利用可能なすべてのモデルが、すべてのパラメータをサポートしているわけではありません。
パススルーの原則 — CometAPI はリクエストをモデルプロバイダーに転送し、そのレスポンスを変更せずに返すため、元の API と一貫した出力を受け取れます。透明性を高めるため、レスポンスオブジェクトには多くのリクエストパラメータ（
temperature、tools、reasoning など）もそのまま含まれます。ストリーミングイベント
stream が true に設定されている場合、API は次の順序でサーバー送信イベント（SSE）を送信します。
response.created— Response オブジェクトが初期化されますresponse.in_progress— 生成が開始されますresponse.output_item.added— 新しい出力項目（メッセージまたはツール呼び出し）response.content_part.added— コンテンツパートが開始されますresponse.output_text.delta— テキストチャンク（テキスト断片を含むdeltaフィールドを持ちます）response.output_text.done— このコンテンツパートのテキスト生成が完了しますresponse.content_part.done— コンテンツパートが終了しますresponse.output_item.done— 出力項目が完了しますresponse.completed—usageデータを含む完全なレスポンス
リファレンスドキュメント
詳細なパラメータ説明については、上部のインタラクティブな API プレイグラウンドを参照してください。プロバイダーのドキュメントについては、以下を参照してください。承認
Bearer token authentication. Use your CometAPI key.
ボディ
application/json
Model ID to use for this request. See the Models page for current options.
例:
"gpt-5.4"
Text, image, or file inputs to the model, used to generate a response. Can be a simple string for text-only input, or an array of input items for multimodal content (images, files) and multi-turn conversations.
A system (or developer) message inserted into the model's context. When used with previous_response_id, instructions from the previous response are not carried over — this makes it easy to swap system messages between turns.
Whether to run the model response in the background. Background responses do not return output directly — you retrieve the result later via the response ID.
Context management configuration for this request. Controls how the model manages context when the conversation exceeds the context window.
Show child attributes
Show child attributes
The conversation this response belongs to. Items from the conversation are prepended to input for context. Input and output items are automatically added to the conversation after the response completes. Cannot be used with previous_response_id.
Additional output data to include in the response. Use this to request extra information that is not included by default.
利用可能なオプション:
web_search_call.action.sources, code_interpreter_call.outputs, computer_call_output.output.image_url, file_search_call.results, message.input_image.image_url, message.output_text.logprobs, reasoning.encrypted_content An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.
The maximum number of total calls to built-in tools that can be processed in a response. This limit applies across all built-in tool calls, not per individual tool. Any further tool call attempts by the model will be ignored.
Set of up to 16 key-value pairs that can be attached to the response. Useful for storing additional information in a structured format. Keys have a maximum length of 64 characters; values have a maximum length of 512 characters.
Show child attributes
Show child attributes
Whether to allow the model to run tool calls in parallel.
The unique ID of a previous response. Use this to create multi-turn conversations without manually managing conversation state. Cannot be used with conversation.
Reference to a prompt template and its variables.
Show child attributes
Show child attributes
A key used to cache responses for similar requests, helping optimize cache hit rates. Replaces the deprecated user field for caching purposes.
The retention policy for the prompt cache. Set to 24h to keep cached prefixes active for up to 24 hours.
利用可能なオプション:
in-memory, 24h Configuration options for reasoning models (o-series and gpt-5). Controls the depth of reasoning before generating a response.
Show child attributes
Show child attributes
A stable identifier for your end-users, used to help detect policy violations. Should be a hashed username or email — do not send identifying information directly.
Maximum string length:
64Specifies the processing tier for the request. When set, the response will include the actual service_tier used.
auto: Uses the tier configured in project settings (default behavior).default: Standard pricing and performance.flex: Flexible processing with potential cost savings.priority: Priority processing with faster response times.
利用可能なオプション:
auto, default, flex, priority Whether to store the generated response for later retrieval via API.
If set to true, the response data will be streamed to the client as it is generated using server-sent events (SSE). Events include response.created, response.output_text.delta, response.completed, and more.
Options for streaming responses. Only set this when stream is true.
Show child attributes
Show child attributes
Sampling temperature between 0 and 2. Higher values (e.g., 0.8) increase randomness; lower values (e.g., 0.2) make output more focused and deterministic. We recommend adjusting either this or top_p, but not both.
必須範囲:
0 <= x <= 2Configuration for text output. Use this to request structured JSON output via JSON mode or JSON Schema.
Show child attributes
Show child attributes
Controls how the model selects which tool(s) to call.
auto(default): The model decides whether and which tools to call.none: The model will not call any tools.required: The model must call at least one tool.- An object specifying a particular tool to use.
An array of tools the model may call while generating a response. CometAPI supports three categories:
- Built-in tools: Platform-provided tools like
web_search_previewandfile_search. - Function calls: Custom functions you define, enabling the model to call your own code with structured arguments.
- MCP tools: Integrations with third-party systems via MCP servers.
Number of most likely tokens to return at each position (0–20), each with an associated log probability. Must include message.output_text.logprobs in the include parameter to receive logprobs.
必須範囲:
0 <= x <= 20Nucleus sampling parameter. The model considers tokens with top_p cumulative probability mass. For example, 0.1 means only the top 10% probability tokens are considered. We recommend adjusting either this or temperature, but not both.
必須範囲:
0 <= x <= 1The truncation strategy for handling inputs that exceed the model's context window.
auto: The model truncates the input by dropping items from the beginning of the conversation to fit.disabled(default): The request fails with a 400 error if the input exceeds the context window.
利用可能なオプション:
auto, disabled Deprecated. Use safety_identifier and prompt_cache_key instead. A stable identifier for your end-user.
レスポンス
200 - application/json
The generated Response object.
Unique identifier for the response.
例:
"resp_0a153ae8201f73bc0069a7e8044cc481"
The object type, always response.
利用可能なオプション:
response 例:
"response"
Unix timestamp (in seconds) of when the response was created.
例:
1772611588
The status of the response.
利用可能なオプション:
completed, in_progress, failed, cancelled, queued 例:
"completed"
Whether the response was run in the background.
例:
false
Unix timestamp of when the response was completed, or null if still in progress.
例:
1772611589
Error information if the response failed, or null on success.
Show child attributes
Show child attributes
Details about why the response is incomplete, if applicable.
Show child attributes
Show child attributes
The system instructions used for this response.
The maximum output token limit that was applied.
The model used for the response.
例:
"gpt-4.1-nano"
An array of output items generated by the model. Each item can be a message, function call, or other output type.
Show child attributes
Show child attributes
A convenience field containing the concatenated text output from all output message items.
Whether parallel tool calls were enabled.
The ID of the previous response, if this is a multi-turn conversation.
The reasoning configuration that was used.
Show child attributes
Show child attributes
The service tier actually used to process the request.
例:
"default"
Whether the response was stored.
The temperature value used.
例:
1
The text configuration used.
Show child attributes
Show child attributes
The tool choice setting used.
The tools that were available for this response.
The top_p value used.
例:
1
The truncation strategy used.
Token usage statistics for this response.
Show child attributes
Show child attributes
The user identifier, if provided.
The metadata attached to this response.
Show child attributes
Show child attributes
Content filter results applied to the response, if any.
The frequency penalty applied to the request.
Maximum number of tool calls allowed, if set.
The presence penalty applied to the request.
Cache key for prompt caching, if applicable.
Prompt cache retention policy, if applicable.
Safety system identifier for the response, if applicable.
Number of top log probabilities returned per token position.
⌘I
from openai import OpenAI
client = OpenAI(
base_url="https://api.cometapi.com/v1",
api_key="<COMETAPI_KEY>",
)
response = client.responses.create(
model="gpt-5.4",
input="Tell me a three sentence bedtime story about a unicorn.",
)
print(response.output_text){
"id": "resp_0a153ae8201f73bc0069a7e8044cc481",
"object": "response",
"created_at": 1772611588,
"status": "completed",
"background": false,
"completed_at": 1772611589,
"error": null,
"incomplete_details": null,
"instructions": null,
"max_output_tokens": null,
"model": "gpt-4.1-nano",
"output": [
{
"id": "msg_0a153ae8201f73bc0069a7e8049a8881",
"type": "message",
"status": "completed",
"content": [
{
"type": "output_text",
"annotations": [],
"text": "Four."
}
],
"role": "assistant"
}
],
"parallel_tool_calls": true,
"previous_response_id": null,
"prompt_cache_key": null,
"prompt_cache_retention": null,
"reasoning": {
"effort": null,
"summary": null
},
"safety_identifier": null,
"service_tier": "auto",
"store": true,
"temperature": 1,
"text": {
"format": {
"type": "text"
},
"verbosity": "medium"
},
"tool_choice": "auto",
"tools": [],
"top_p": 1,
"truncation": "disabled",
"usage": {
"input_tokens": 19,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 9,
"output_tokens_details": {
"reasoning_tokens": 0
},
"total_tokens": 28
},
"user": null,
"metadata": {}
}