CometAPI POST /v1/responses를 사용하여 기본 제공 도구와 함수 호출을 포함한 멀티모달 모델 응답 및 대화 기록을 생성합니다.
POST
/
v1
/
responses
import osfrom openai import OpenAIclient = OpenAI( base_url="https://api.cometapi.com/v1", api_key=os.environ["COMETAPI_KEY"],)response = client.responses.create( model="gpt-6-astra", input="Tell me a three sentence bedtime story about a unicorn.", reasoning={ "effort": "low", },)print(response.output_text)
{ "id": "resp_example", "object": "response", "created_at": 1788763707, "status": "completed", "background": false, "completed_at": 1788763711, "error": null, "incomplete_details": null, "model": "gpt-6-astra", "output": [ { "id": "msg_example", "type": "message", "status": "completed", "content": [ { "type": "output_text", "annotations": [], "logprobs": [], "text": "A little unicorn named Luna followed a trail of silver fireflies to a meadow where the flowers chimed softly in the breeze. She curled beneath a willow tree, tucked her hooves into the cool grass, and wished sweet dreams for every creature in the forest. As the moon wrapped the meadow in gentle light, Luna closed her eyes and drifted into dreams of dancing among the stars." } ], "phase": "final_answer", "role": "assistant" } ], "parallel_tool_calls": true, "previous_response_id": null, "reasoning": { "context": "all_turns", "effort": "low", "mode": "standard", "summary": null }, "store": true, "text": { "format": { "type": "text" }, "verbosity": "medium" }, "tool_choice": "auto", "tools": [], "usage": { "input_tokens": 17, "input_tokens_details": { "cache_write_tokens": 0, "cached_tokens": 0 }, "output_tokens": 81, "output_tokens_details": { "reasoning_tokens": 0 }, "total_tokens": 98 }}
응답 API를 사용하여 gpt-6-astra와 함께 텍스트, 이미지, 파일 및 대화 기록을 전송합니다. 예제에서는 웹 검색, 맞춤 함수 호출, 구조화된 출력, 추론 및 스트리밍도 보여 줍니다.
다음 OpenAI 응답 레퍼런스 에서는 전체 API 형식을 설명하며, 여기의 예제에서는 CometAPI에 맞게 해당 형식을 구성합니다.
텍스트 전용 대화에서는 사용자 메시지와 어시스턴트의 텍스트 응답을 유지한 다음, 다음 사용자 메시지를 추가합니다:
import osfrom openai import OpenAIclient = OpenAI( base_url="https://api.cometapi.com/v1", api_key=os.environ["COMETAPI_KEY"],)input_items = [ {"role": "user", "content": "My project is named Cedar and uses Python. Remember these two facts."}]response = client.responses.create( model="gpt-6-astra", input=input_items, reasoning={"effort": "low"},)input_items.append({"role": "assistant", "content": response.output_text})input_items.append({ "role": "user", "content": "What is my project's name and programming language?",})follow_up = client.responses.create( model="gpt-6-astra", input=input_items, reasoning={"effort": "low"},)print(follow_up.output_text)
response.output_text 는 응답의 어시스턴트 텍스트를 결합하는 SDK 편의 속성입니다. 함수 호출 대화에는 아래에 설명된 대로 도구 호출 및 결과 항목도 필요합니다.
import osfrom openai import OpenAIclient = OpenAI( base_url="https://api.cometapi.com/v1", api_key=os.environ["COMETAPI_KEY"],)response = client.responses.create( model="gpt-6-astra", input="Search the web for the NASA Artemis II mission overview and cite the official NASA page.", tools=[ { "type": "web_search", }, ], reasoning={ "effort": "low", },)print(response.output_text)
애플리케이션에 검색 결과 또는 인용이 필요한 경우 반환된 web_search_call 항목과 메시지의 URL 주석을 확인하세요. 다른 기본 제공 도구에는 각각의 구성이 필요하며, 자세한 내용은 다음 OpenAI 도구 가이드에서 확인할 수 있습니다..
import osfrom openai import OpenAIclient = OpenAI( base_url="https://api.cometapi.com/v1", api_key=os.environ["COMETAPI_KEY"],)response = client.responses.create( model="gpt-6-astra", input="What is the weather in Boston, MA, in celsius? Use the weather tool.", tools=[ { "type": "function", "name": "get_current_weather", "description": "Get the current weather for a city.", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "City and state, for example Boston, MA.", }, "unit": { "type": "string", "enum": [ "celsius", "fahrenheit", ], "description": "Temperature unit.", }, }, "required": [ "location", "unit", ], "additionalProperties": False, }, "strict": True, }, ], tool_choice="auto", reasoning={ "effort": "low", },)print(response.output)
함수 호출은 function_call 출력 항목으로 나타납니다. 해당 arguments 필드는 JSON으로 인코딩된 문자열입니다. 함수를 실행한 다음, 원래 입력과 반환된 출력 항목에서 응답 항목의 id 필드를 제외하여 다음 요청을 구성합니다. 함수의 name, arguments, call_id 값은 유지하고, 일치하는 function_call_output 및 call_id과 output에 결과를 포함한 항목을 추가합니다.
import osfrom openai import OpenAIclient = OpenAI( base_url="https://api.cometapi.com/v1", api_key=os.environ["COMETAPI_KEY"],)stream = client.responses.create( model="gpt-6-astra", input="Tell me a three sentence bedtime story about a unicorn.", reasoning={ "effort": "low", }, stream=True,)for event in stream: if event.type == "response.output_text.delta": print(event.delta, end="")
텍스트 응답에는 response.created, response.in_progress, response.completed 같은 수명 주기 이벤트가 포함됩니다. 텍스트는 response.output_text.delta 이벤트로 도착합니다. 도구 및 추론 이벤트는 요청에 따라 달라지므로, 모든 응답에 같은 순서가 있다고 가정하지 말고 type에 따라 이벤트를 처리하세요.
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.
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.
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.
An ID for a stored response that is accessible to the selected model and request context. Cannot be combined with conversation. The conversation-history example sends prior input and output items explicitly.
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.
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.
Tools available to the model. This page demonstrates web_search and custom function tools. Other tool types require their own configuration; see the official tool reference.
Number of token alternatives to include for models supporting log probabilities. Requires message.output_text.logprobs in include. Omit for GPT-6 Astra.
Number of top log probabilities returned per token position.
마지막 수정일 2026년 9월 8일
⌘I
import osfrom openai import OpenAIclient = OpenAI( base_url="https://api.cometapi.com/v1", api_key=os.environ["COMETAPI_KEY"],)response = client.responses.create( model="gpt-6-astra", input="Tell me a three sentence bedtime story about a unicorn.", reasoning={ "effort": "low", },)print(response.output_text)
{ "id": "resp_example", "object": "response", "created_at": 1788763707, "status": "completed", "background": false, "completed_at": 1788763711, "error": null, "incomplete_details": null, "model": "gpt-6-astra", "output": [ { "id": "msg_example", "type": "message", "status": "completed", "content": [ { "type": "output_text", "annotations": [], "logprobs": [], "text": "A little unicorn named Luna followed a trail of silver fireflies to a meadow where the flowers chimed softly in the breeze. She curled beneath a willow tree, tucked her hooves into the cool grass, and wished sweet dreams for every creature in the forest. As the moon wrapped the meadow in gentle light, Luna closed her eyes and drifted into dreams of dancing among the stars." } ], "phase": "final_answer", "role": "assistant" } ], "parallel_tool_calls": true, "previous_response_id": null, "reasoning": { "context": "all_turns", "effort": "low", "mode": "standard", "summary": null }, "store": true, "text": { "format": { "type": "text" }, "verbosity": "medium" }, "tool_choice": "auto", "tools": [], "usage": { "input_tokens": 17, "input_tokens_details": { "cache_write_tokens": 0, "cached_tokens": 0 }, "output_tokens": 81, "output_tokens_details": { "reasoning_tokens": 0 }, "total_tokens": 98 }}
{"docsConfig":{"theme":"luma","$schema":"https://mintlify.com/docs.json","name":"CometAPI Documentation","description":"CometAPI developer documentation for unified API access to GPT, Claude, Gemini, Grok, Llama, DeepSeek, Mistral, Qwen, and more, including API reference, quickstart guides, and integration tutorials.","colors":{"primary":"#00ACE2","light":"#00ACE2","dark":"#0274C3"},"logo":{"light":"https://mintcdn.com/cometapi/cmhWX83dzrkf2F-2/logo/comet-light.svg?fit=max\u0026auto=format\u0026n=cmhWX83dzrkf2F-2\u0026q=85\u0026s=7ae2fde0df7785d111912bce23157ef2","dark":"https://mintcdn.com/cometapi/cmhWX83dzrkf2F-2/logo/comet-dark.svg?fit=max\u0026auto=format\u0026n=cmhWX83dzrkf2F-2\u0026q=85\u0026s=2d25d0a1c0376b7a3b5b2b06c4149fbc"},"favicon":"https://mintcdn.com/cometapi/cmhWX83dzrkf2F-2/logo/comet.svg?fit=max\u0026auto=format\u0026n=cmhWX83dzrkf2F-2\u0026q=85\u0026s=bd1150b78a8058af98088b06cbe67cdc","api":{"playground":{"display":"interactive","proxy":true},"examples":{"defaults":"required","prefill":true}},"navbar":{"links":[{"href":"https://www.cometapi.com/models/","label":"Models"}],"primary":{"type":"button","label":"Dashboard","href":"https://www.cometapi.com/console"}},"footer":{},"seo":{"metatags":{"og:site_name":"CometAPI Docs","og:type":"website","twitter:card":"summary_large_image","canonical":"https://apidoc.cometapi.com","author":"CometAPI","copyright":"Copyright 2026 CometAPI","category":"Technology","distribution":"global","coverage":"Worldwide"},"indexing":"navigable"},"integrations":{"posthog":{"apiKey":"phc_y3KwBz46V9TGDjqPtDrpuSahVg3bDky6eyzGsD8vuCYS","sessionRecording":false}},"contextual":{"options":["copy","view","chatgpt","claude","perplexity"],"display":"header"},"interaction":{"drilldown":false},"metadata":{"timestamp":true},"styling":{"latex":false},"navigation":{"languages":[{"language":"en","href":""},{"language":"zh-Hans","href":"zh-Hans"},{"language":"zh-Hant","href":"zh-Hant"},{"language":"ja","href":"ja"},{"language":"ko","href":"ko"},{"language":"fr","href":"fr"},{"language":"de","href":"de"},{"language":"es","href":"es"},{"language":"it","href":"it"},{"language":"pt","href":"pt"},{"language":"ru","href":"ru"},{"language":"ar","href":"ar"},{"language":"vi","href":"vi"},{"language":"id","href":"id"},{"language":"tr","href":"tr"},{"language":"pl","href":"pl"},{"language":"nl","href":"nl"},{"language":"no","href":"no"},{"language":"uk","href":"uk"}]}},"deployment":{"deploymentMetadataValue":{"subdomain":"cometapi","hasAudioNarration":false,"actualSubdomain":"cometapi","customDomains":["apidoc.cometapi.com"],"gitSource":{"type":"github","owner":"cometapi-dev","repo":"cometapi-docs","deployBranch":"main","contentDirectory":"","isPrivate":true,"mountPath":"","label":""},"chroma":{"liveDeploymentHistoryId":"6ae2ec350f3a19b455e9452e","collectionId":"ac249683-b28e-4ebb-9061-39e00c026722","schemaVersion":"v3","latestBuiltDeploymentHistoryId":"6ae2ec350f3a19b455e9452e"},"entitlements":{},"buildId":"6ae2ec350f3a19b455e9452e","clientVersion":"0.0.4067","searchFilterCounts":[{"language":"en","tag":"API","count":109},{"language":"en","tag":"Video Models","count":66},{"language":"en","tag":"Integrations","count":53},{"language":"en","tag":"Docs","count":35},{"language":"en","tag":"Kling","count":33},{"language":"en","tag":"Image Models","count":28},{"language":"en","tag":"AI chat clients","count":14},{"language":"en","tag":"Runway","count":13},{"language":"en","tag":"Midjourney","count":10},{"language":"en","tag":"AI coding agents","count":10}]},"assistantConfig":{"enableAskAiButton":false,"enableStarterQuestions":false,"enableAskAiSearchBar":true},"basePath":"","hasChatPermissions":false,"hasWebMcpPermissions":false,"toggles":[{"name":"kill-isr","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"agent-mintlify-slack","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"agent-integrations-settings","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"rbac-expansion","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"automations-pr-grouping","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"custom-prefix","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"analytics-v7","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"user-flows-analytics","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"no-publish-flow","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"workos-onboarding","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"llms-txt-v2","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"snapshot-serving-live","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"stripTemperatureMiddleware","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"support-platform-pylon-zendesk","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"snapshot-serving","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"instant-rollback","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"granular-notifications-server","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"granular-notifications","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"automations-fable","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"fixed-ai-action-pricing","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"automation-resolve-merge-conflict","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"scoped-publishing","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"mintql","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"page-level-analytics","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"editor-version-history-v2","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"billing-page-v2","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"full-page-search","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"workspace-projects","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"assistant-v5","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"fork-pr-previews","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"revalidation-jwt","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"vite-origin","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"workos-sso-scim","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"hobby-abuse-scan","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"dashboard-inbox","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"workos-signup","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"turbopuffer-dual-write","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"workos-enabled","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"approve-review-flow","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"sso-setup-deadline-banner","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false},{"name":"turbopuffer-serve","enabled":true,"variant":{"name":"disabled","enabled":false,"feature_enabled":true},"impressionData":false}],"googleFontsInlined":false},"customCss":[{"filePath":"style.css","content":"img[src*=\"cloudfront.net/flags/\"]{display:none!important}div.relative:has(>img[src*=\"cloudfront.net/flags/\"]){display:none!important}#localization-select-item-zh-Hans{display:none!important}nav a.link[class~=\"bg-gray-950/[0.03]\"]{background-color:rgb(var(--primary) / 0.12);box-shadow:inset 0 0 0 1px rgb(var(--primary) / 0.38), 0 1px 2px rgb(var(--primary) / 0.08);color:rgb(var(--primary))}nav a.link[class~=\"bg-gray-950/[0.03]\"]:hover,nav a.link[class~=\"bg-gray-950/[0.03]\"]:focus-visible{background-color:rgb(var(--primary) / 0.18);box-shadow:inset 0 0 0 1px rgb(var(--primary) / 0.58), 0 1px 2px rgb(var(--primary) / 0.1);color:rgb(var(--primary))}nav a.link[class~=\"bg-gray-950/[0.03]\"]:focus-visible{outline:2px solid rgb(var(--primary) / 0.45);outline-offset:2px}.dark nav a.link[class~=\"bg-gray-950/[0.03]\"]{background-color:rgb(var(--primary-light) / 0.2);box-shadow:inset 0 0 0 1px rgb(var(--primary-light) / 0.55), 0 1px 2px rgb(var(--primary-light) / 0.16);color:rgb(var(--primary-light))}.dark nav a.link[class~=\"bg-gray-950/[0.03]\"]:hover,.dark nav a.link[class~=\"bg-gray-950/[0.03]\"]:focus-visible{background-color:rgb(var(--primary-light) / 0.28);box-shadow:inset 0 0 0 1px rgb(var(--primary-light) / 0.7), 0 1px 2px rgb(var(--primary-light) / 0.18);color:rgb(var(--primary-light))}.integration-logo-grid{display:grid;grid-template-columns:repeat(3, minmax(0, 1fr));gap:12px;margin:16px 0 28px}.integration-logo-card{align-items:center;background:rgba(127, 127, 127, 0.04);border:1px solid rgba(127, 127, 127, 0.22);border-radius:8px;color:inherit;display:flex;gap:14px;min-height:72px;padding:14px 16px;text-decoration:none!important;transition:background 160ms ease, border-color 160ms ease, transform 160ms ease}.integration-logo-card:hover,.integration-logo-card:focus-visible{background:rgba(0, 172, 226, 0.08);border-color:rgba(0, 172, 226, 0.55);transform:translateY(-1px)}.integration-logo-card:focus-visible{outline:2px solid rgba(0, 172, 226, 0.45);outline-offset:2px}.integration-logo-mark{align-items:center;background:#fff;background-position:center;background-repeat:no-repeat;background-size:28px 28px;border:1px solid rgba(127, 127, 127, 0.18);border-radius:8px;display:flex;flex:0 0 38px;height:38px;justify-content:center;overflow:hidden;width:38px}.integration-logo-body{display:flex;flex-direction:column;gap:2px;min-width:0}.integration-logo-title{font-size:0.95rem;font-weight:600;line-height:1.3}.integration-logo-subtitle{color:rgba(90, 90, 90, 0.92);font-size:0.78rem;line-height:1.3;overflow:hidden;text-overflow:ellipsis;white-space:nowrap}.integration-card-arrow{color:rgba(90, 90, 90, 0.7);flex:0 0 16px;font-size:0.9rem;margin-left:auto;text-align:right}.integration-card-arrow::before{content:\"\\2197\"}.integration-logo-ai-sdk{background-image:url(\"/images/integrations/logos/ai-sdk.png\")}.integration-logo-agno{background-image:url(\"/images/integrations/logos/agno.png\")}.integration-logo-claude-code{background-image:url(\"/images/integrations/logos/claude-code.png\")}.integration-logo-claude-desktop{background-image:url(\"/images/integrations/logos/claude-desktop.png\")}.integration-logo-codex{background-image:url(\"/images/integrations/logos/codex.png\")}.integration-logo-dify{background-image:url(\"/images/integrations/logos/dify.png\")}.integration-logo-gemini-cli{background-image:url(\"/images/integrations/logos/gemini-cli.png\")}.integration-logo-hermes-agent{background-image:url(\"/images/integrations/logos/hermes-agent.png\");background-size:34px 34px}.integration-logo-langchain{background-image:url(\"/images/integrations/logos/langchain.png\")}.integration-logo-langflow{background-image:url(\"/images/integrations/logos/langflow.png\")}.integration-logo-langfuse{background-image:url(\"/images/integrations/logos/langfuse.png\")}.integration-logo-litellm{background-image:url(\"/images/integrations/logos/litellm.png\")}.integration-logo-llamaindex{background-image:url(\"/images/integrations/logos/llamaindex.png\")}.integration-logo-lobe-chat{background-image:url(\"/images/integrations/logos/lobe-chat.jpg\")}.integration-logo-make{background-image:url(\"/images/integrations/logos/make.jpg\")}.integration-logo-n8n{background-image:url(\"/images/integrations/logos/n8n.png\")}.integration-logo-open-webui{background-image:url(\"/images/integrations/logos/open-webui.png\")}.integration-logo-workbuddy-ai{background-image:url(\"/images/integrations/logos/workbuddy-ai.svg\")}.integration-logo-openclaw{background-image:url(\"/images/integrations/logos/openclaw.svg\")}.integration-logo-opencode{background-image:url(\"/images/integrations/logos/opencode.png\")}.integration-logo-pi{background-image:url(\"/images/integrations/logos/pi.svg\")}.integration-logo-promptfoo{background-image:url(\"/images/integrations/logos/promptfoo.png\")}.dark .integration-logo-card{background:rgba(255, 255, 255, 0.035);border-color:rgba(255, 255, 255, 0.14)}.dark .integration-logo-card:hover,.dark .integration-logo-card:focus-visible{background:rgba(0, 172, 226, 0.14);border-color:rgba(0, 172, 226, 0.65)}.dark .integration-logo-mark{background-color:rgba(255, 255, 255, 0.96)}.dark .integration-logo-subtitle{color:rgba(255, 255, 255, 0.66)}.dark .integration-card-arrow{color:rgba(255, 255, 255, 0.64)}@media (max-width: 1024px){.integration-logo-grid{grid-template-columns:repeat(2, minmax(0, 1fr))}}@media (max-width: 640px){.integration-logo-grid{grid-template-columns:1fr}.integration-logo-card{min-height:68px}}"}],"page":{"pagePath":"ko/api/text/responses","slug":"/ko/api/text/responses","pageMetadata":{"title":"모델 응답 생성","sidebarTitle":"모델 응답 생성","openapi":"api/openapi/text/post-responses.openapi.json POST /v1/responses","description":"CometAPI POST /v1/responses를 사용하여 기본 제공 도구와 함수 호출을 포함한 멀티모달 모델 응답 및 대화 기록을 생성합니다.","keywords":["CometAPI","responses api","post /v1/responses","openai responses","multimodal input","conversation history","function calling","tool integration"],"noindex":true,"href":"/ko/api/text/responses"},"description":{"compiledSource":"\"use strict\";\nconst {jsx: _jsx} = arguments[0];\nconst {useMDXComponents: _provideComponents} = arguments[0];\nfunction _createMdxContent(props) {\n const _components = {\n p: \"p\",\n ..._provideComponents(),\n ...props.components\n };\n return _jsx(_components.p, {\n children: \"CometAPI POST /v1/responses를 사용하여 기본 제공 도구와 함수 호출을 포함한 멀티모달 모델 응답 및 대화 기록을 생성합니다.\"\n });\n}\nfunction MDXContent(props = {}) {\n const {wrapper: MDXLayout} = {\n ..._provideComponents(),\n ...props.components\n };\n return MDXLayout ? _jsx(MDXLayout, {\n ...props,\n children: _jsx(_createMdxContent, {\n ...props\n })\n }) : _createMdxContent(props);\n}\nreturn {\n default: MDXContent\n};\n","frontmatter":{},"scope":{}},"pageType":"default","mdx":{"mdxSource":{"compiledSource":"\"use strict\";const{Fragment:_Fragment,jsx:_jsx,jsxs:_jsxs}=arguments[0];const{useMDXComponents:_provideComponents}=arguments[0];function _createMdxContent(props){const _components={a:`a`,code:`code`,hr:`hr`,p:`p`,pre:`pre`,span:`span`,..._provideComponents(),...props.components},{CodeBlock,Heading,Note,Tip}=_components;if(!CodeBlock)_missingMdxReference(`CodeBlock`,true);if(!Heading)_missingMdxReference(`Heading`,true);if(!Note)_missingMdxReference(`Note`,true);if(!Tip)_missingMdxReference(`Tip`,true);return _jsxs(_Fragment,{children:[_jsxs(_components.p,{children:[`응답 API를 사용하여 `,_jsx(_components.code,{children:`gpt-6-astra`}),`와 함께 텍스트, 이미지, 파일 및 대화 기록을 전송합니다. 예제에서는 웹 검색, 맞춤 함수 호출, 구조화된 출력, 추론 및 스트리밍도 보여 줍니다.`]}),`\n`,_jsx(Note,{children:_jsxs(_components.p,{children:[`다음 `,_jsx(_components.a,{href:`https://developers.openai.com/api/reference/typescript/resources/responses/methods/create`,children:`OpenAI 응답 레퍼런스`}),` 에서는 전체 API 형식을 설명하며, 여기의 예제에서는 CometAPI에 맞게 해당 형식을 구성합니다.`]})}),`\n`,_jsx(_components.hr,{}),`\n`,_jsx(Heading,{level:`2`,id:`대화-이어가기`,children:`대화 이어가기`}),`\n`,_jsx(_components.p,{children:`텍스트 전용 대화에서는 사용자 메시지와 어시스턴트의 텍스트 응답을 유지한 다음, 다음 사용자 메시지를 추가합니다:`}),`\n`,_jsx(CodeBlock,{filename:``,numberOfLines:`32`,language:`python`,children:_jsx(_components.pre,{className:`shiki shiki-themes github-light-default dark-plus`,style:{backgroundColor:`#ffffff`,\"--shiki-dark-bg\":`#0B0C0E`,color:`#1f2328`,\"--shiki-dark\":`#D4D4D4`},language:`python`,children:_jsxs(_components.code,{language:`python`,numberOfLines:`32`,children:[_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` os`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`from`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` openai `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`client `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` base_url`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"https://api.cometapi.com/v1\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` api_key`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`os.environ[`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"COMETAPI_KEY\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`],`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`input_items `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` [`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` {`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"role\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"user\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`, `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"content\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"My project is named Cedar and uses Python. Remember these two facts.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`}`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`]`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`response `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` client.responses.create(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` model`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"gpt-6-astra\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` input`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`input_items,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` reasoning`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`{`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"effort\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"low\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`},`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`input_items.append({`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"role\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"assistant\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`, `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"content\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: response.output_text})`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`input_items.append({`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"role\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"user\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"content\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"What is my project's name and programming language?\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`})`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`follow_up `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` client.responses.create(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` model`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"gpt-6-astra\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` input`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`input_items,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` reasoning`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`{`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"effort\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"low\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`},`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#DCDCAA`},children:`print`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`(follow_up.output_text)`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`]})})}),`\n`,_jsxs(_components.p,{children:[_jsx(_components.code,{children:`response.output_text`}),` 는 응답의 어시스턴트 텍스트를 결합하는 SDK 편의 속성입니다. 함수 호출 대화에는 아래에 설명된 대로 도구 호출 및 결과 항목도 필요합니다.`]}),`\n`,_jsx(_components.hr,{}),`\n`,_jsx(Heading,{level:`2`,id:`웹-검색-사용`,children:`웹 검색 사용`}),`\n`,_jsxs(_components.p,{children:[`정보를 검색하고 출처 인용을 포함하려면 `,_jsx(_components.code,{children:`web_search`}),` 도구를 추가합니다:`]}),`\n`,_jsx(CodeBlock,{filename:``,numberOfLines:`23`,language:`python`,children:_jsx(_components.pre,{className:`shiki shiki-themes github-light-default dark-plus`,style:{backgroundColor:`#ffffff`,\"--shiki-dark-bg\":`#0B0C0E`,color:`#1f2328`,\"--shiki-dark\":`#D4D4D4`},language:`python`,children:_jsxs(_components.code,{language:`python`,numberOfLines:`23`,children:[_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` os`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`from`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` openai `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`client `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` base_url`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"https://api.cometapi.com/v1\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` api_key`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`os.environ[`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"COMETAPI_KEY\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`],`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`response `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` client.responses.create(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` model`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"gpt-6-astra\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` input`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"Search the web for the NASA Artemis II mission overview and cite the official NASA page.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` tools`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`[`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` {`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"web_search\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` ],`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` reasoning`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`{`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"effort\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"low\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#DCDCAA`},children:`print`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`(response.output_text)`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`]})})}),`\n`,_jsxs(_components.p,{children:[`애플리케이션에 검색 결과 또는 인용이 필요한 경우 반환된 `,_jsx(_components.code,{children:`web_search_call`}),` 항목과 메시지의 URL 주석을 확인하세요. 다른 기본 제공 도구에는 각각의 구성이 필요하며, 자세한 내용은 다음 `,_jsx(_components.a,{href:`https://developers.openai.com/api/docs/guides/tools`,children:`OpenAI 도구 가이드에서 확인할 수 있습니다.`}),`.`]}),`\n`,_jsx(_components.hr,{}),`\n`,_jsx(Heading,{level:`2`,id:`사용자-지정-함수-호출`,children:`사용자 지정 함수 호출`}),`\n`,_jsx(_components.p,{children:`함수 인수를 정의하고 모델이 함수를 요청하도록 합니다:`}),`\n`,_jsx(CodeBlock,{filename:``,numberOfLines:`49`,language:`python`,children:_jsx(_components.pre,{className:`shiki shiki-themes github-light-default dark-plus`,style:{backgroundColor:`#ffffff`,\"--shiki-dark-bg\":`#0B0C0E`,color:`#1f2328`,\"--shiki-dark\":`#D4D4D4`},language:`python`,children:_jsxs(_components.code,{language:`python`,numberOfLines:`49`,children:[_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` os`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`from`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` openai `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`client `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` base_url`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"https://api.cometapi.com/v1\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` api_key`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`os.environ[`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"COMETAPI_KEY\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`],`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`response `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` client.responses.create(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` model`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"gpt-6-astra\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` input`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"What is the weather in Boston, MA, in celsius? Use the weather tool.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` tools`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`[`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` {`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"function\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"name\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"get_current_weather\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"description\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"Get the current weather for a city.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"parameters\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"object\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"properties\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"location\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"string\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"description\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"City and state, for example Boston, MA.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"unit\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"string\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"enum\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: [`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"celsius\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"fahrenheit\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` ],`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"description\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"Temperature unit.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"required\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: [`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"location\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"unit\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` ],`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"additionalProperties\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#569CD6`},children:`False`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"strict\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#569CD6`},children:`True`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` ],`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` tool_choice`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"auto\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` reasoning`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`{`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"effort\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"low\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#DCDCAA`},children:`print`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`(response.output)`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`]})})}),`\n`,_jsxs(_components.p,{children:[`함수 호출은 `,_jsx(_components.code,{children:`function_call`}),` 출력 항목으로 나타납니다. 해당 `,_jsx(_components.code,{children:`arguments`}),` 필드는 JSON으로 인코딩된 문자열입니다. 함수를 실행한 다음, 원래 입력과 반환된 출력 항목에서 응답 항목의 `,_jsx(_components.code,{children:`id`}),` 필드를 제외하여 다음 요청을 구성합니다. 함수의 `,_jsx(_components.code,{children:`name`}),`, `,_jsx(_components.code,{children:`arguments`}),`, `,_jsx(_components.code,{children:`call_id`}),` 값은 유지하고, 일치하는 `,_jsx(_components.code,{children:`function_call_output`}),` 및 `,_jsx(_components.code,{children:`call_id`}),`과 `,_jsx(_components.code,{children:`output`}),`에 결과를 포함한 항목을 추가합니다.`]}),`\n`,_jsx(_components.hr,{}),`\n`,_jsx(Heading,{level:`2`,id:`구조화된-출력-요청`,children:`구조화된 출력 요청`}),`\n`,_jsxs(_components.p,{children:[`스키마를 따르는 JSON을 요청하려면 `,_jsx(_components.code,{children:`text.format`}),`을 사용합니다:`]}),`\n`,_jsx(CodeBlock,{filename:``,numberOfLines:`56`,language:`python`,children:_jsx(_components.pre,{className:`shiki shiki-themes github-light-default dark-plus`,style:{backgroundColor:`#ffffff`,\"--shiki-dark-bg\":`#0B0C0E`,color:`#1f2328`,\"--shiki-dark\":`#D4D4D4`},language:`python`,children:_jsxs(_components.code,{language:`python`,numberOfLines:`56`,children:[_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` os`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`from`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` openai `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`client `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` base_url`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"https://api.cometapi.com/v1\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` api_key`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`os.environ[`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"COMETAPI_KEY\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`],`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`response `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` client.responses.create(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` model`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"gpt-6-astra\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` input`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"List 3 programming languages with their main use cases.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` text`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`{`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"format\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"json_schema\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"name\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"languages\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"strict\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#569CD6`},children:`True`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"schema\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"object\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"properties\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"languages\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"array\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"items\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"object\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"properties\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"name\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"string\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"description\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"Programming language name.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"use_case\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: {`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"string\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"description\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"Main use case for the language.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"required\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: [`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"name\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"use_case\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` ],`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"additionalProperties\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#569CD6`},children:`False`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"description\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"Three programming languages and their main uses.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"required\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: [`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"languages\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` ],`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"additionalProperties\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#569CD6`},children:`False`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` reasoning`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`{`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"effort\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"low\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#DCDCAA`},children:`print`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`(response.output_text)`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`]})})}),`\n`,_jsx(_components.p,{children:`JSON을 파싱하기 전에 응답이 완료되었고 요청을 거부하지 않았는지 확인합니다. 출력 토큰(Token) 한도에 도달한 응답은 불완전할 수 있습니다.`}),`\n`,_jsx(_components.hr,{}),`\n`,_jsx(Heading,{level:`2`,id:`추론-구성`,children:`추론 구성`}),`\n`,_jsxs(_components.p,{children:[`모델의 추론 수준을 선택하려면 `,_jsx(_components.code,{children:`reasoning.effort`}),` 값을 설정합니다:`]}),`\n`,_jsx(CodeBlock,{filename:``,numberOfLines:`18`,language:`python`,children:_jsx(_components.pre,{className:`shiki shiki-themes github-light-default dark-plus`,style:{backgroundColor:`#ffffff`,\"--shiki-dark-bg\":`#0B0C0E`,color:`#1f2328`,\"--shiki-dark\":`#D4D4D4`},language:`python`,children:_jsxs(_components.code,{language:`python`,numberOfLines:`18`,children:[_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` os`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`from`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` openai `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`client `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` base_url`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"https://api.cometapi.com/v1\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` api_key`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`os.environ[`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"COMETAPI_KEY\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`],`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`response `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` client.responses.create(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` model`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"gpt-6-astra\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` input`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"Solve this step by step: what is 15`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#569CD6`},children:`% o`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`f 240?\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` reasoning`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`{`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"effort\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"high\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#DCDCAA`},children:`print`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`(response.output_text)`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`]})})}),`\n`,_jsxs(_components.p,{children:[`예시에서는 일반 작업에 `,_jsx(_components.code,{children:`low`}),`를 사용하고 추론 예시에는 `,_jsx(_components.code,{children:`high`}),`를 사용합니다. `,_jsx(_components.code,{children:`max_output_tokens`}),`에는 추론 토큰(Token)과 표시되는 출력 토큰(Token)이 모두 포함됩니다.`]}),`\n`,_jsx(_components.hr,{}),`\n`,_jsx(Heading,{level:`2`,id:`응답-스트리밍-streaming`,children:`응답 스트리밍(Streaming)`}),`\n`,_jsxs(_components.p,{children:[`서버 전송 이벤트를 수신하려면 `,_jsx(_components.code,{children:`stream`}),` 값을 `,_jsx(_components.code,{children:`true`}),`로 설정합니다:`]}),`\n`,_jsx(CodeBlock,{filename:``,numberOfLines:`21`,language:`python`,children:_jsx(_components.pre,{className:`shiki shiki-themes github-light-default dark-plus`,style:{backgroundColor:`#ffffff`,\"--shiki-dark-bg\":`#0B0C0E`,color:`#1f2328`,\"--shiki-dark\":`#D4D4D4`},language:`python`,children:_jsxs(_components.code,{language:`python`,numberOfLines:`21`,children:[_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` os`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`from`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` openai `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`client `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` OpenAI(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` base_url`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"https://api.cometapi.com/v1\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` api_key`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`os.environ[`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"COMETAPI_KEY\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`],`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`stream `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` client.responses.create(`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` model`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"gpt-6-astra\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` input`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"Tell me a three sentence bedtime story about a unicorn.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` reasoning`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`{`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"effort\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"low\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` stream`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#569CD6`},children:`True`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`for`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` event `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`in`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` stream:`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:` if`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` event.type `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`==`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"response.output_text.delta\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`:`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#DCDCAA`},children:` print`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`(event.delta, `}),_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:`end`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`)`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`]})})}),`\n`,_jsxs(_components.p,{children:[`텍스트 응답에는 `,_jsx(_components.code,{children:`response.created`}),`, `,_jsx(_components.code,{children:`response.in_progress`}),`, `,_jsx(_components.code,{children:`response.completed`}),` 같은 수명 주기 이벤트가 포함됩니다. 텍스트는 `,_jsx(_components.code,{children:`response.output_text.delta`}),` 이벤트로 도착합니다. 도구 및 추론 이벤트는 요청에 따라 달라지므로, 모든 응답에 같은 순서가 있다고 가정하지 말고 `,_jsx(_components.code,{children:`type`}),`에 따라 이벤트를 처리하세요.`]}),`\n`,_jsx(_components.hr,{}),`\n`,_jsx(Tip,{children:_jsxs(_components.p,{children:[`다음에 대한 OpenAI 가이드를 참조하세요: `,_jsx(_components.a,{href:`https://developers.openai.com/api/docs/guides/images-vision`,children:`이미지 입력`}),`, `,_jsx(_components.a,{href:`https://developers.openai.com/api/docs/guides/file-inputs`,children:`파일 입력`}),`, `,_jsx(_components.a,{href:`https://developers.openai.com/api/docs/guides/structured-outputs`,children:`구조화된 출력`}),`, `,_jsx(_components.a,{href:`https://developers.openai.com/api/docs/guides/function-calling`,children:`함수 호출(Function Calling)`}),`, `,_jsx(_components.a,{href:`https://developers.openai.com/api/docs/guides/conversation-state`,children:`대화 상태`}),`, 및 `,_jsx(_components.a,{href:`https://developers.openai.com/api/docs/guides/reasoning`,children:`추론`}),`.`]})})]})}function MDXContent(props={}){const{wrapper:MDXLayout}={..._provideComponents(),...props.components};return MDXLayout?_jsx(MDXLayout,{...props,children:_jsx(_createMdxContent,{...props})}):_createMdxContent(props)}return{default:MDXContent};function _missingMdxReference(id,component){throw new Error(`Expected `+(component?`component`:`object`)+\" `\"+id+\"` to be defined: you likely forgot to import, pass, or provide it.\")}","frontmatter":{},"scope":{"config":{},"pageMetadata":{"title":"모델 응답 생성","sidebarTitle":"모델 응답 생성","openapi":"api/openapi/text/post-responses.openapi.json POST /v1/responses","description":"CometAPI POST /v1/responses를 사용하여 기본 제공 도구와 함수 호출을 포함한 멀티모달 모델 응답 및 대화 기록을 생성합니다.","keywords":["CometAPI","responses api","post /v1/responses","openai responses","multimodal input","conversation history","function calling","tool integration"],"noindex":true,"href":"/ko/api/text/responses"}}},"mdxSourceWithNoJs":null},"mdxExtracts":{"tableOfContents":[{"title":"대화 이어가기","slug":"대화-이어가기","depth":2,"children":[]},{"title":"웹 검색 사용","slug":"웹-검색-사용","depth":2,"children":[]},{"title":"사용자 지정 함수 호출","slug":"사용자-지정-함수-호출","depth":2,"children":[]},{"title":"구조화된 출력 요청","slug":"구조화된-출력-요청","depth":2,"children":[]},{"title":"추론 구성","slug":"추론-구성","depth":2,"children":[]},{"title":"응답 스트리밍(Streaming)","slug":"응답-스트리밍-streaming","depth":2,"children":[]}],"codeExamples":{}},"jsLinks":["/_mintlify/custom/cometapi/430a303ac1007180/analytics.js"],"openApiReferenceData":{"operation":{"summary":"Create Response","operationId":"createResponse","requestBody":"109dc995-179a-4933-bbda-7e9ad8103962","responses":{"200":"bfe7ede8-b069-437a-9f3d-e89bdcd0421c"},"x-codeSamples":[{"lang":"Python","label":"Text Input","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"Tell me a three sentence bedtime story about a unicorn.\",\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output_text)\n"},{"lang":"Python","label":"Image Input","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=[\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Describe the road and surrounding landscape in this image.\",\n },\n {\n \"type\": \"input_image\",\n \"image_url\": \"https://images.unsplash.com/photo-1500530855697-b586d89ba3ee?w=1200\",\n },\n ],\n },\n ],\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output_text)\n"},{"lang":"Python","label":"File Input","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=[\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Summarize the main topics in this shareholder letter.\",\n },\n {\n \"type\": \"input_file\",\n \"file_url\": \"https://www.berkshirehathaway.com/letters/2024ltr.pdf\",\n },\n ],\n },\n ],\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output_text)\n"},{"lang":"Python","label":"Web Search","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"Search the web for the NASA Artemis II mission overview and cite the official NASA page.\",\n tools=[\n {\n \"type\": \"web_search\",\n },\n ],\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output_text)\n"},{"lang":"Python","label":"Streaming","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nstream = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"Tell me a three sentence bedtime story about a unicorn.\",\n reasoning={\n \"effort\": \"low\",\n },\n stream=True,\n)\n\nfor event in stream:\n if event.type == \"response.output_text.delta\":\n print(event.delta, end=\"\")\n"},{"lang":"Python","label":"Functions","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"What is the weather in Boston, MA, in celsius? Use the weather tool.\",\n tools=[\n {\n \"type\": \"function\",\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather for a city.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"City and state, for example Boston, MA.\",\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"celsius\",\n \"fahrenheit\",\n ],\n \"description\": \"Temperature unit.\",\n },\n },\n \"required\": [\n \"location\",\n \"unit\",\n ],\n \"additionalProperties\": False,\n },\n \"strict\": True,\n },\n ],\n tool_choice=\"auto\",\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output)\n"},{"lang":"Python","label":"Reasoning","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"Solve this step by step: what is 15% of 240?\",\n reasoning={\n \"effort\": \"high\",\n },\n)\n\nprint(response.output_text)\n"},{"lang":"Python","label":"Structured Output","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"List 3 programming languages with their main use cases.\",\n text={\n \"format\": {\n \"type\": \"json_schema\",\n \"name\": \"languages\",\n \"strict\": True,\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"languages\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"description\": \"Programming language name.\",\n },\n \"use_case\": {\n \"type\": \"string\",\n \"description\": \"Main use case for the language.\",\n },\n },\n \"required\": [\n \"name\",\n \"use_case\",\n ],\n \"additionalProperties\": False,\n },\n \"description\": \"Three programming languages and their main uses.\",\n },\n },\n \"required\": [\n \"languages\",\n ],\n \"additionalProperties\": False,\n },\n },\n },\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output_text)\n"},{"lang":"JavaScript","label":"Text Input","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"Tell me a three sentence bedtime story about a unicorn.\",\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"lang":"JavaScript","label":"Image Input","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Describe the road and surrounding landscape in this image.\"\n },\n {\n \"type\": \"input_image\",\n \"image_url\": \"https://images.unsplash.com/photo-1500530855697-b586d89ba3ee?w=1200\"\n }\n ]\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"lang":"JavaScript","label":"File Input","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Summarize the main topics in this shareholder letter.\"\n },\n {\n \"type\": \"input_file\",\n \"file_url\": \"https://www.berkshirehathaway.com/letters/2024ltr.pdf\"\n }\n ]\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"lang":"JavaScript","label":"Web Search","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"Search the web for the NASA Artemis II mission overview and cite the official NASA page.\",\n \"tools\": [\n {\n \"type\": \"web_search\"\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"lang":"JavaScript","label":"Streaming","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst stream = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"Tell me a three sentence bedtime story about a unicorn.\",\n \"reasoning\": {\n \"effort\": \"low\"\n },\n \"stream\": true\n});\n\nfor await (const event of stream) {\n if (event.type === \"response.output_text.delta\") {\n process.stdout.write(event.delta);\n }\n}\n"},{"lang":"JavaScript","label":"Functions","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"What is the weather in Boston, MA, in celsius? Use the weather tool.\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather for a city.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"City and state, for example Boston, MA.\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"celsius\",\n \"fahrenheit\"\n ],\n \"description\": \"Temperature unit.\"\n }\n },\n \"required\": [\n \"location\",\n \"unit\"\n ],\n \"additionalProperties\": false\n },\n \"strict\": true\n }\n ],\n \"tool_choice\": \"auto\",\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output);\n"},{"lang":"JavaScript","label":"Reasoning","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"Solve this step by step: what is 15% of 240?\",\n \"reasoning\": {\n \"effort\": \"high\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"lang":"JavaScript","label":"Structured Output","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"List 3 programming languages with their main use cases.\",\n \"text\": {\n \"format\": {\n \"type\": \"json_schema\",\n \"name\": \"languages\",\n \"strict\": true,\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"languages\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"description\": \"Programming language name.\"\n },\n \"use_case\": {\n \"type\": \"string\",\n \"description\": \"Main use case for the language.\"\n }\n },\n \"required\": [\n \"name\",\n \"use_case\"\n ],\n \"additionalProperties\": false\n },\n \"description\": \"Three programming languages and their main uses.\"\n }\n },\n \"required\": [\n \"languages\"\n ],\n \"additionalProperties\": false\n }\n }\n },\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"lang":"Shell","label":"Text Input","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"Tell me a three sentence bedtime story about a unicorn.\",\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"},{"lang":"Shell","label":"Image Input","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Describe the road and surrounding landscape in this image.\"\n },\n {\n \"type\": \"input_image\",\n \"image_url\": \"https://images.unsplash.com/photo-1500530855697-b586d89ba3ee?w=1200\"\n }\n ]\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"},{"lang":"Shell","label":"File Input","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Summarize the main topics in this shareholder letter.\"\n },\n {\n \"type\": \"input_file\",\n \"file_url\": \"https://www.berkshirehathaway.com/letters/2024ltr.pdf\"\n }\n ]\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"},{"lang":"Shell","label":"Web Search","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"Search the web for the NASA Artemis II mission overview and cite the official NASA page.\",\n \"tools\": [\n {\n \"type\": \"web_search\"\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"},{"lang":"Shell","label":"Streaming","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n --no-buffer \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"Tell me a three sentence bedtime story about a unicorn.\",\n \"reasoning\": {\n \"effort\": \"low\"\n },\n \"stream\": true\n}'\n"},{"lang":"Shell","label":"Functions","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"What is the weather in Boston, MA, in celsius? Use the weather tool.\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather for a city.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"City and state, for example Boston, MA.\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"celsius\",\n \"fahrenheit\"\n ],\n \"description\": \"Temperature unit.\"\n }\n },\n \"required\": [\n \"location\",\n \"unit\"\n ],\n \"additionalProperties\": false\n },\n \"strict\": true\n }\n ],\n \"tool_choice\": \"auto\",\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"},{"lang":"Shell","label":"Reasoning","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"Solve this step by step: what is 15% of 240?\",\n \"reasoning\": {\n \"effort\": \"high\"\n }\n}'\n"},{"lang":"Shell","label":"Structured Output","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"List 3 programming languages with their main use cases.\",\n \"text\": {\n \"format\": {\n \"type\": \"json_schema\",\n \"name\": \"languages\",\n \"strict\": true,\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"languages\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"description\": \"Programming language name.\"\n },\n \"use_case\": {\n \"type\": \"string\",\n \"description\": \"Main use case for the language.\"\n }\n },\n \"required\": [\n \"name\",\n \"use_case\"\n ],\n \"additionalProperties\": false\n },\n \"description\": \"Three programming languages and their main uses.\"\n }\n },\n \"required\": [\n \"languages\"\n ],\n \"additionalProperties\": false\n }\n }\n },\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"}],"description":"CometAPI POST /v1/responses를 사용하여 기본 제공 도구와 함수 호출을 포함한 멀티모달 모델 응답 및 대화 기록을 생성합니다.","method":"post","type":"path","servers":["b01d2edf-97bf-4b97-9e4d-5f137173c1a0"],"security":["a56a7049-0d12-4ef3-a068-aa63f5be54a6"],"path":"/v1/responses","baseUrlOptions":["https://api.cometapi.com"],"title":"Create Response","codeSamples":[{"label":"Text Input","lang":"Python","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"Tell me a three sentence bedtime story about a unicorn.\",\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output_text)\n"},{"label":"Image Input","lang":"Python","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=[\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Describe the road and surrounding landscape in this image.\",\n },\n {\n \"type\": \"input_image\",\n \"image_url\": \"https://images.unsplash.com/photo-1500530855697-b586d89ba3ee?w=1200\",\n },\n ],\n },\n ],\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output_text)\n"},{"label":"File Input","lang":"Python","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=[\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Summarize the main topics in this shareholder letter.\",\n },\n {\n \"type\": \"input_file\",\n \"file_url\": \"https://www.berkshirehathaway.com/letters/2024ltr.pdf\",\n },\n ],\n },\n ],\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output_text)\n"},{"label":"Web Search","lang":"Python","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"Search the web for the NASA Artemis II mission overview and cite the official NASA page.\",\n tools=[\n {\n \"type\": \"web_search\",\n },\n ],\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output_text)\n"},{"label":"Streaming","lang":"Python","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nstream = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"Tell me a three sentence bedtime story about a unicorn.\",\n reasoning={\n \"effort\": \"low\",\n },\n stream=True,\n)\n\nfor event in stream:\n if event.type == \"response.output_text.delta\":\n print(event.delta, end=\"\")\n"},{"label":"Functions","lang":"Python","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"What is the weather in Boston, MA, in celsius? Use the weather tool.\",\n tools=[\n {\n \"type\": \"function\",\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather for a city.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"City and state, for example Boston, MA.\",\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"celsius\",\n \"fahrenheit\",\n ],\n \"description\": \"Temperature unit.\",\n },\n },\n \"required\": [\n \"location\",\n \"unit\",\n ],\n \"additionalProperties\": False,\n },\n \"strict\": True,\n },\n ],\n tool_choice=\"auto\",\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output)\n"},{"label":"Reasoning","lang":"Python","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"Solve this step by step: what is 15% of 240?\",\n reasoning={\n \"effort\": \"high\",\n },\n)\n\nprint(response.output_text)\n"},{"label":"Structured Output","lang":"Python","source":"import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"https://api.cometapi.com/v1\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nresponse = client.responses.create(\n model=\"gpt-6-astra\",\n input=\"List 3 programming languages with their main use cases.\",\n text={\n \"format\": {\n \"type\": \"json_schema\",\n \"name\": \"languages\",\n \"strict\": True,\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"languages\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"description\": \"Programming language name.\",\n },\n \"use_case\": {\n \"type\": \"string\",\n \"description\": \"Main use case for the language.\",\n },\n },\n \"required\": [\n \"name\",\n \"use_case\",\n ],\n \"additionalProperties\": False,\n },\n \"description\": \"Three programming languages and their main uses.\",\n },\n },\n \"required\": [\n \"languages\",\n ],\n \"additionalProperties\": False,\n },\n },\n },\n reasoning={\n \"effort\": \"low\",\n },\n)\n\nprint(response.output_text)\n"},{"label":"Text Input","lang":"JavaScript","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"Tell me a three sentence bedtime story about a unicorn.\",\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"label":"Image Input","lang":"JavaScript","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Describe the road and surrounding landscape in this image.\"\n },\n {\n \"type\": \"input_image\",\n \"image_url\": \"https://images.unsplash.com/photo-1500530855697-b586d89ba3ee?w=1200\"\n }\n ]\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"label":"File Input","lang":"JavaScript","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Summarize the main topics in this shareholder letter.\"\n },\n {\n \"type\": \"input_file\",\n \"file_url\": \"https://www.berkshirehathaway.com/letters/2024ltr.pdf\"\n }\n ]\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"label":"Web Search","lang":"JavaScript","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"Search the web for the NASA Artemis II mission overview and cite the official NASA page.\",\n \"tools\": [\n {\n \"type\": \"web_search\"\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"label":"Streaming","lang":"JavaScript","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst stream = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"Tell me a three sentence bedtime story about a unicorn.\",\n \"reasoning\": {\n \"effort\": \"low\"\n },\n \"stream\": true\n});\n\nfor await (const event of stream) {\n if (event.type === \"response.output_text.delta\") {\n process.stdout.write(event.delta);\n }\n}\n"},{"label":"Functions","lang":"JavaScript","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"What is the weather in Boston, MA, in celsius? Use the weather tool.\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather for a city.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"City and state, for example Boston, MA.\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"celsius\",\n \"fahrenheit\"\n ],\n \"description\": \"Temperature unit.\"\n }\n },\n \"required\": [\n \"location\",\n \"unit\"\n ],\n \"additionalProperties\": false\n },\n \"strict\": true\n }\n ],\n \"tool_choice\": \"auto\",\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output);\n"},{"label":"Reasoning","lang":"JavaScript","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"Solve this step by step: what is 15% of 240?\",\n \"reasoning\": {\n \"effort\": \"high\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"label":"Structured Output","lang":"JavaScript","source":"import OpenAI from \"openai\";\n\nconst client = new OpenAI({\n baseURL: \"https://api.cometapi.com/v1\",\n apiKey: process.env.COMETAPI_KEY,\n});\n\nconst response = await client.responses.create({\n \"model\": \"gpt-6-astra\",\n \"input\": \"List 3 programming languages with their main use cases.\",\n \"text\": {\n \"format\": {\n \"type\": \"json_schema\",\n \"name\": \"languages\",\n \"strict\": true,\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"languages\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"description\": \"Programming language name.\"\n },\n \"use_case\": {\n \"type\": \"string\",\n \"description\": \"Main use case for the language.\"\n }\n },\n \"required\": [\n \"name\",\n \"use_case\"\n ],\n \"additionalProperties\": false\n },\n \"description\": \"Three programming languages and their main uses.\"\n }\n },\n \"required\": [\n \"languages\"\n ],\n \"additionalProperties\": false\n }\n }\n },\n \"reasoning\": {\n \"effort\": \"low\"\n }\n});\n\nconsole.log(response.output_text);\n"},{"label":"Text Input","lang":"Shell","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"Tell me a three sentence bedtime story about a unicorn.\",\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"},{"label":"Image Input","lang":"Shell","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Describe the road and surrounding landscape in this image.\"\n },\n {\n \"type\": \"input_image\",\n \"image_url\": \"https://images.unsplash.com/photo-1500530855697-b586d89ba3ee?w=1200\"\n }\n ]\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"},{"label":"File Input","lang":"Shell","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Summarize the main topics in this shareholder letter.\"\n },\n {\n \"type\": \"input_file\",\n \"file_url\": \"https://www.berkshirehathaway.com/letters/2024ltr.pdf\"\n }\n ]\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"},{"label":"Web Search","lang":"Shell","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"Search the web for the NASA Artemis II mission overview and cite the official NASA page.\",\n \"tools\": [\n {\n \"type\": \"web_search\"\n }\n ],\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"},{"label":"Streaming","lang":"Shell","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n --no-buffer \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"Tell me a three sentence bedtime story about a unicorn.\",\n \"reasoning\": {\n \"effort\": \"low\"\n },\n \"stream\": true\n}'\n"},{"label":"Functions","lang":"Shell","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"What is the weather in Boston, MA, in celsius? Use the weather tool.\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather for a city.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"City and state, for example Boston, MA.\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"celsius\",\n \"fahrenheit\"\n ],\n \"description\": \"Temperature unit.\"\n }\n },\n \"required\": [\n \"location\",\n \"unit\"\n ],\n \"additionalProperties\": false\n },\n \"strict\": true\n }\n ],\n \"tool_choice\": \"auto\",\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"},{"label":"Reasoning","lang":"Shell","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"Solve this step by step: what is 15% of 240?\",\n \"reasoning\": {\n \"effort\": \"high\"\n }\n}'\n"},{"label":"Structured Output","lang":"Shell","source":"curl https://api.cometapi.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $COMETAPI_KEY\" \\\n -d '{\n \"model\": \"gpt-6-astra\",\n \"input\": \"List 3 programming languages with their main use cases.\",\n \"text\": {\n \"format\": {\n \"type\": \"json_schema\",\n \"name\": \"languages\",\n \"strict\": true,\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"languages\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"description\": \"Programming language name.\"\n },\n \"use_case\": {\n \"type\": \"string\",\n \"description\": \"Main use case for the language.\"\n }\n },\n \"required\": [\n \"name\",\n \"use_case\"\n ],\n \"additionalProperties\": false\n },\n \"description\": \"Three programming languages and their main uses.\"\n }\n },\n \"required\": [\n \"languages\"\n ],\n \"additionalProperties\": false\n }\n }\n },\n \"reasoning\": {\n \"effort\": \"low\"\n }\n}'\n"}],"requiredOnlyExamples":true,"requestExampleType":"codeSamples","responseExampleType":"generated","prefillPlaygroundWithExample":true,"prefillPlaygroundExamples":[{"body.model":"gpt-6-astra","body.input.oneOf.0":"Tell me a three sentence bedtime story about a unicorn.","body.reasoning.effort":"low"},{"body.model":"gpt-6-astra","body.input.oneOf.1.items.0":{"role":"user","content":[{"type":"input_text","text":"Describe the road and surrounding landscape in this image."},{"type":"input_image","image_url":"https://images.unsplash.com/photo-1500530855697-b586d89ba3ee?w=1200"}]},"body.reasoning.effort":"low"},{"body.model":"gpt-6-astra","body.input.oneOf.1.items.0":{"role":"user","content":[{"type":"input_text","text":"Summarize the main topics in this shareholder letter."},{"type":"input_file","file_url":"https://www.berkshirehathaway.com/letters/2024ltr.pdf"}]},"body.reasoning.effort":"low"},{"body.model":"gpt-6-astra","body.input.oneOf.0":"Search the web for the NASA Artemis II mission overview and cite the official NASA page.","body.reasoning.effort":"low","body.tools.items.0":{"type":"web_search"}},{"body.model":"gpt-6-astra","body.input.oneOf.0":"Tell me a three sentence bedtime story about a unicorn.","body.reasoning.effort":"low","body.stream":true},{"body.model":"gpt-6-astra","body.input.oneOf.0":"What is the weather in Boston, MA, in celsius? Use the weather tool.","body.reasoning.effort":"low","body.tool_choice.oneOf.0":"auto","body.tools.items.0":{"type":"function","name":"get_current_weather","description":"Get the current weather for a city.","parameters":{"type":"object","properties":{"location":{"type":"string","description":"City and state, for example Boston, MA."},"unit":{"type":"string","enum":["celsius","fahrenheit"],"description":"Temperature unit."}},"required":["location","unit"],"additionalProperties":false},"strict":true}},{"body.model":"gpt-6-astra","body.input.oneOf.0":"Solve this step by step: what is 15% of 240?","body.reasoning.effort":"high"},{"body.model":"gpt-6-astra","body.input.oneOf.0":"List 3 programming languages with their main use cases.","body.reasoning.effort":"low","body.text.format.type":"json_schema","body.text.format.name":"languages","body.text.format.schema":{"type":"object","properties":{"languages":{"type":"array","items":{"type":"object","properties":{"name":{"type":"string","description":"Programming language name."},"use_case":{"type":"string","description":"Main use case for the language."}},"required":["name","use_case"],"additionalProperties":false},"description":"Three programming languages and their main uses."}},"required":["languages"],"additionalProperties":false},"body.text.format.strict":true}]},"dependencies":{"parameters":{},"requestBody":{"required":true,"content":{"application/json":{"schema":{"type":"object","required":["model","input"],"properties":{"model":{"type":"string","description":"Model ID to use for this request. See the [Models page](/overview/models) for current options.","example":"gpt-6-astra","default":"gpt-6-astra","isRequired":true,"uniqueKey":"model","typeLabel":"string"},"input":{"oneOf":[{"type":"string","description":"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.","isRequired":true,"uniqueKey":"input.oneOf.0","typeLabel":"string"},{"type":"array","items":{"type":"object","uniqueKey":"input.oneOf.1.items.[INDEX]","typeLabel":"object"},"description":"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.","isRequired":true,"uniqueKey":"input.oneOf.1","typeLabel":"object[]"}],"isRequired":true,"uniqueKey":"input","typeLabel":"string | object[]"},"instructions":{"type":"string","description":"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.","uniqueKey":"instructions","typeLabel":"string"},"background":{"type":"boolean","description":"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.","uniqueKey":"background","typeLabel":"boolean"},"context_management":{"type":"array","description":"Context management configuration for this request. Controls how the model manages context when the conversation exceeds the context window.","items":{"type":"object","properties":{"type":{"type":"string","description":"The type of context management.","uniqueKey":"context_management.items.[INDEX].type","typeLabel":"string"},"compact_threshold":{"type":"number","description":"The threshold at which context compaction is triggered.","uniqueKey":"context_management.items.[INDEX].compact_threshold","typeLabel":"number"}},"uniqueKey":"context_management.items.[INDEX]","typeLabel":"object"},"uniqueKey":"context_management","typeLabel":"object[]"},"conversation":{"oneOf":[{"type":"string","description":"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`.","uniqueKey":"conversation.oneOf.0","typeLabel":"string"},{"type":"object","description":"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`.","uniqueKey":"conversation.oneOf.1","typeLabel":"object"},{"type":"null","description":"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`.","uniqueKey":"conversation.oneOf.2","typeLabel":"null"}],"uniqueKey":"conversation","typeLabel":"string | object | null"},"include":{"type":"array","description":"Additional output data to include in the response. Use this to request extra information that is not included by default.","items":{"type":"string","enum":["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"],"uniqueKey":"include.items.[INDEX]","typeLabel":"enum\u003cstring>"},"uniqueKey":"include","typeLabel":"enum\u003cstring>[]"},"max_output_tokens":{"type":"integer","description":"An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.","uniqueKey":"max_output_tokens","typeLabel":"integer"},"max_tool_calls":{"type":"integer","description":"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.","uniqueKey":"max_tool_calls","typeLabel":"integer"},"metadata":{"type":"object","description":"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.","additionalProperties":{"type":"string","uniqueKey":"metadata.additionalProperties","typeLabel":"string"},"uniqueKey":"metadata","typeLabel":"object"},"parallel_tool_calls":{"type":"boolean","description":"Whether to allow the model to run tool calls in parallel.","uniqueKey":"parallel_tool_calls","typeLabel":"boolean"},"previous_response_id":{"type":"string","description":"An ID for a stored response that is accessible to the selected model and request context. Cannot be combined with conversation. The conversation-history example sends prior input and output items explicitly.","uniqueKey":"previous_response_id","typeLabel":"string"},"prompt":{"type":"object","description":"Reference to a prompt template and its variables.","properties":{"id":{"type":"string","description":"The ID of the prompt template.","uniqueKey":"prompt.id","typeLabel":"string"},"variables":{"type":"object","description":"Key-value pairs for template variables.","additionalProperties":{"type":"string","uniqueKey":"prompt.variables.additionalProperties","typeLabel":"string"},"uniqueKey":"prompt.variables","typeLabel":"object"},"version":{"type":"string","description":"The version of the prompt template to use.","uniqueKey":"prompt.version","typeLabel":"string"}},"uniqueKey":"prompt","typeLabel":"object"},"prompt_cache_key":{"type":"string","description":"A key used to cache responses for similar requests, helping optimize cache hit rates. Replaces the deprecated `user` field for caching purposes.","uniqueKey":"prompt_cache_key","typeLabel":"string"},"prompt_cache_retention":{"type":"string","description":"Legacy prompt-cache retention setting. Refer to the selected model documentation for prompt_cache_options and supported retention settings.","enum":["in_memory","24h"],"deprecated":true,"uniqueKey":"prompt_cache_retention","typeLabel":"enum\u003cstring>"},"reasoning":{"type":"object","description":"Reasoning configuration for the selected model.","properties":{"effort":{"type":"string","description":"Model-dependent reasoning effort. The examples use low for general tasks and high for the reasoning example. See the selected model reference for supported levels.","uniqueKey":"reasoning.effort","typeLabel":"string"},"generate_summary":{"type":"string","description":"Deprecated alias. Use summary for a reasoning summary when supported.","enum":["auto","concise","detailed"],"deprecated":true,"uniqueKey":"reasoning.generate_summary","typeLabel":"enum\u003cstring>"},"summary":{"type":"string","description":"Request a summary of the model reasoning when supported by the selected model.","enum":["auto","concise","detailed"],"uniqueKey":"reasoning.summary","typeLabel":"enum\u003cstring>"}},"uniqueKey":"reasoning","typeLabel":"object"},"safety_identifier":{"type":"string","description":"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.","maxLength":64,"uniqueKey":"safety_identifier","typeLabel":"string"},"service_tier":{"type":"string","description":"Specifies the processing tier for the request. When set, the response will include the actual `service_tier` used.\n\n- `auto`: Uses the tier configured in project settings (default behavior).\n- `default`: Standard pricing and performance.\n- `flex`: Flexible processing with potential cost savings.\n- `priority`: Priority processing with faster response times.","enum":["auto","default","flex","priority"],"uniqueKey":"service_tier","typeLabel":"enum\u003cstring>"},"store":{"type":"boolean","description":"Request response storage for later retrieval, when supported by the selected model and request context.","uniqueKey":"store","typeLabel":"boolean"},"stream":{"type":"boolean","description":"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.","uniqueKey":"stream","typeLabel":"boolean"},"stream_options":{"type":"object","description":"Options for streaming responses. Only set this when `stream` is `true`.","properties":{"include_obfuscation":{"type":"boolean","description":"Whether to include obfuscation data in streaming events.","uniqueKey":"stream_options.include_obfuscation","typeLabel":"boolean"}},"uniqueKey":"stream_options","typeLabel":"object"},"temperature":{"type":"number","description":"Sampling temperature. Omit this field for GPT-6 Astra.","minimum":0,"maximum":2,"uniqueKey":"temperature","typeLabel":"number"},"text":{"type":"object","description":"Configuration for text output. Use this to request structured JSON output via JSON mode or JSON Schema.","properties":{"format":{"type":"object","description":"The format of the text output.","properties":{"type":{"type":"string","description":"The output format type. `text` returns plain text, `json_object` returns valid JSON, `json_schema` returns JSON conforming to a provided schema.","enum":["text","json_object","json_schema"],"uniqueKey":"text.format.type","typeLabel":"enum\u003cstring>"},"name":{"type":"string","description":"Name of the output schema when type is json_schema.","uniqueKey":"text.format.name","typeLabel":"string"},"schema":{"type":"object","description":"JSON Schema describing the requested output when type is json_schema.","uniqueKey":"text.format.schema","typeLabel":"object"},"strict":{"type":"boolean","description":"Require the supported JSON Schema to be followed for a completed, non-refusal structured response.","uniqueKey":"text.format.strict","typeLabel":"boolean"}},"uniqueKey":"text.format","typeLabel":"object"},"verbosity":{"type":"string","description":"Controls the verbosity of the text output.","enum":["low","medium","high"],"uniqueKey":"text.verbosity","typeLabel":"enum\u003cstring>"}},"uniqueKey":"text","typeLabel":"object"},"tool_choice":{"oneOf":[{"type":"string","description":"Controls how the model selects which tool(s) to call.\n\n- `auto` (default): The model decides whether and which tools to call.\n- `none`: The model will not call any tools.\n- `required`: The model must call at least one tool.\n- An object specifying a particular tool to use.","uniqueKey":"tool_choice.oneOf.0","typeLabel":"string"},{"type":"object","description":"Controls how the model selects which tool(s) to call.\n\n- `auto` (default): The model decides whether and which tools to call.\n- `none`: The model will not call any tools.\n- `required`: The model must call at least one tool.\n- An object specifying a particular tool to use.","uniqueKey":"tool_choice.oneOf.1","typeLabel":"object"}],"uniqueKey":"tool_choice","typeLabel":"string | object"},"tools":{"type":"array","description":"Tools available to the model. This page demonstrates web_search and custom function tools. Other tool types require their own configuration; see the official tool reference.","items":{"type":"object","uniqueKey":"tools.items.[INDEX]","typeLabel":"object"},"uniqueKey":"tools","typeLabel":"object[]"},"top_logprobs":{"type":"integer","description":"Number of token alternatives to include for models supporting log probabilities. Requires message.output_text.logprobs in include. Omit for GPT-6 Astra.","minimum":0,"maximum":20,"uniqueKey":"top_logprobs","typeLabel":"integer"},"top_p":{"type":"number","description":"Nucleus sampling threshold. Omit this field for GPT-6 Astra. For sampling overrides, adjust either top_p or temperature.","minimum":0,"maximum":1,"uniqueKey":"top_p","typeLabel":"number"},"truncation":{"type":"string","description":"The truncation strategy for handling inputs that exceed the model's context window.\n\n- `auto`: The model truncates the input by dropping items from the beginning of the conversation to fit.\n- `disabled` (default): The request fails with a 400 error if the input exceeds the context window.","enum":["auto","disabled"],"uniqueKey":"truncation","typeLabel":"enum\u003cstring>"},"user":{"type":"string","description":"Deprecated. Use `safety_identifier` and `prompt_cache_key` instead. A stable identifier for your end-user.","deprecated":true,"uniqueKey":"user","typeLabel":"string"}},"default":{"model":"gpt-6-astra","input":"Tell me a three sentence bedtime story about a unicorn.","reasoning":{"effort":"low"}},"uniqueKey":"","typeLabel":"object"},"examples":{"Text Input":{"title":"Text Input","value":{"model":"gpt-6-astra","input":"Tell me a three sentence bedtime story about a unicorn.","reasoning":{"effort":"low"}}},"Image Input":{"title":"Image Input","value":{"model":"gpt-6-astra","input":[{"role":"user","content":[{"type":"input_text","text":"Describe the road and surrounding landscape in this image."},{"type":"input_image","image_url":"https://images.unsplash.com/photo-1500530855697-b586d89ba3ee?w=1200"}]}],"reasoning":{"effort":"low"}}},"File Input":{"title":"File Input","value":{"model":"gpt-6-astra","input":[{"role":"user","content":[{"type":"input_text","text":"Summarize the main topics in this shareholder letter."},{"type":"input_file","file_url":"https://www.berkshirehathaway.com/letters/2024ltr.pdf"}]}],"reasoning":{"effort":"low"}}},"Web Search":{"title":"Web Search","value":{"model":"gpt-6-astra","input":"Search the web for the NASA Artemis II mission overview and cite the official NASA page.","tools":[{"type":"web_search"}],"reasoning":{"effort":"low"}}},"Streaming":{"title":"Streaming","value":{"model":"gpt-6-astra","input":"Tell me a three sentence bedtime story about a unicorn.","reasoning":{"effort":"low"},"stream":true}},"Functions":{"title":"Functions","value":{"model":"gpt-6-astra","input":"What is the weather in Boston, MA, in celsius? Use the weather tool.","tools":[{"type":"function","name":"get_current_weather","description":"Get the current weather for a city.","parameters":{"type":"object","properties":{"location":{"type":"string","description":"City and state, for example Boston, MA."},"unit":{"type":"string","enum":["celsius","fahrenheit"],"description":"Temperature unit."}},"required":["location","unit"],"additionalProperties":false},"strict":true}],"tool_choice":"auto","reasoning":{"effort":"low"}}},"Reasoning":{"title":"Reasoning","value":{"model":"gpt-6-astra","input":"Solve this step by step: what is 15% of 240?","reasoning":{"effort":"high"}}},"Structured Output":{"title":"Structured Output","value":{"model":"gpt-6-astra","input":"List 3 programming languages with their main use cases.","text":{"format":{"type":"json_schema","name":"languages","strict":true,"schema":{"type":"object","properties":{"languages":{"type":"array","items":{"type":"object","properties":{"name":{"type":"string","description":"Programming language name."},"use_case":{"type":"string","description":"Main use case for the language."}},"required":["name","use_case"],"additionalProperties":false},"description":"Three programming languages and their main uses."}},"required":["languages"],"additionalProperties":false}}},"reasoning":{"effort":"low"}}}},"exampleType":"examples"}},"exampleType":"examples"},"responses":{"bfe7ede8-b069-437a-9f3d-e89bdcd0421c":{"description":"The generated Response object.","content":{"application/json":{"schema":{"type":"object","properties":{"id":{"type":"string","description":"Unique identifier for the response.","example":"resp_example","uniqueKey":"id","typeLabel":"string"},"object":{"type":"string","description":"The object type, always `response`.","enum":["response"],"example":"response","uniqueKey":"object","typeLabel":"enum\u003cstring>"},"created_at":{"type":"integer","description":"Unix timestamp (in seconds) of when the response was created.","example":1788763707,"uniqueKey":"created_at","typeLabel":"integer"},"status":{"type":"string","description":"The status of the response.","enum":["completed","in_progress","failed","cancelled","queued","incomplete"],"example":"completed","uniqueKey":"status","typeLabel":"enum\u003cstring>"},"background":{"type":"boolean","description":"Whether the response was run in the background.","example":false,"uniqueKey":"background","typeLabel":"boolean"},"completed_at":{"oneOf":[{"type":"integer","description":"Unix timestamp of when the response was completed, or `null` if still in progress.","example":1788763711,"uniqueKey":"completed_at.oneOf.0","typeLabel":"integer"},{"type":"null","description":"Unix timestamp of when the response was completed, or `null` if still in progress.","example":1788763711,"uniqueKey":"completed_at.oneOf.1","typeLabel":"null"}],"uniqueKey":"completed_at","typeLabel":"integer | null"},"error":{"oneOf":[{"type":"object","description":"Error information if the response failed, or `null` on success.","properties":{"code":{"type":"string","description":"The error code.","uniqueKey":"error.oneOf.0.code","typeLabel":"string"},"message":{"type":"string","description":"A human-readable error message.","uniqueKey":"error.oneOf.0.message","typeLabel":"string"}},"uniqueKey":"error.oneOf.0","typeLabel":"object"},{"type":"null","description":"Error information if the response failed, or `null` on success.","properties":{"code":{"type":"string","description":"The error code."},"message":{"type":"string","description":"A human-readable error message."}},"uniqueKey":"error.oneOf.1","typeLabel":"null"}],"uniqueKey":"error","typeLabel":"object | null"},"incomplete_details":{"oneOf":[{"type":"object","description":"Details about why the response is incomplete, if applicable.","properties":{"reason":{"type":"string","description":"The reason the response is incomplete.","enum":["max_output_tokens","content_filter"],"uniqueKey":"incomplete_details.oneOf.0.reason","typeLabel":"enum\u003cstring>"}},"uniqueKey":"incomplete_details.oneOf.0","typeLabel":"object"},{"type":"null","description":"Details about why the response is incomplete, if applicable.","properties":{"reason":{"type":"string","description":"The reason the response is incomplete.","enum":["max_output_tokens","content_filter"]}},"uniqueKey":"incomplete_details.oneOf.1","typeLabel":"null"}],"uniqueKey":"incomplete_details","typeLabel":"object | null"},"instructions":{"oneOf":[{"type":"string","description":"The system instructions used for this response.","uniqueKey":"instructions.oneOf.0","typeLabel":"string"},{"type":"null","description":"The system instructions used for this response.","uniqueKey":"instructions.oneOf.1","typeLabel":"null"}],"uniqueKey":"instructions","typeLabel":"string | null"},"max_output_tokens":{"oneOf":[{"type":"integer","description":"The maximum output token limit that was applied.","uniqueKey":"max_output_tokens.oneOf.0","typeLabel":"integer"},{"type":"null","description":"The maximum output token limit that was applied.","uniqueKey":"max_output_tokens.oneOf.1","typeLabel":"null"}],"uniqueKey":"max_output_tokens","typeLabel":"integer | null"},"model":{"type":"string","description":"The model used for the response.","example":"gpt-6-astra","uniqueKey":"model","typeLabel":"string"},"output":{"type":"array","description":"An array of output items generated by the model. Each item can be a message, function call, or other output type.","items":{"type":"object","properties":{"id":{"type":"string","description":"Unique identifier for the output item.","uniqueKey":"output.items.[INDEX].id","typeLabel":"string"},"type":{"type":"string","description":"The type of output item.","enum":["message","function_call","web_search_call","file_search_call","code_interpreter_call","computer_call","reasoning"],"uniqueKey":"output.items.[INDEX].type","typeLabel":"enum\u003cstring>"},"status":{"type":"string","description":"The status of this output item.","enum":["completed","in_progress"],"uniqueKey":"output.items.[INDEX].status","typeLabel":"enum\u003cstring>"},"role":{"type":"string","description":"The role of the message (present when `type` is `message`).","enum":["assistant"],"uniqueKey":"output.items.[INDEX].role","typeLabel":"enum\u003cstring>"},"content":{"type":"array","description":"The content parts of the message (present when `type` is `message`).","items":{"type":"object","properties":{"type":{"type":"string","description":"The content type.","enum":["output_text"],"uniqueKey":"output.items.[INDEX].content.items.[INDEX].type","typeLabel":"enum\u003cstring>"},"text":{"type":"string","description":"The generated text content.","uniqueKey":"output.items.[INDEX].content.items.[INDEX].text","typeLabel":"string"},"annotations":{"type":"array","description":"Annotations such as file citations or URL citations.","items":{"type":"object","uniqueKey":"output.items.[INDEX].content.items.[INDEX].annotations.items.[INDEX]","typeLabel":"object"},"uniqueKey":"output.items.[INDEX].content.items.[INDEX].annotations","typeLabel":"object[]"},"logprobs":{"type":"array","description":"Log probability information (when requested via `include`).","items":{"type":"object","uniqueKey":"output.items.[INDEX].content.items.[INDEX].logprobs.items.[INDEX]","typeLabel":"object"},"uniqueKey":"output.items.[INDEX].content.items.[INDEX].logprobs","typeLabel":"object[]"}},"uniqueKey":"output.items.[INDEX].content.items.[INDEX]","typeLabel":"object"},"uniqueKey":"output.items.[INDEX].content","typeLabel":"object[]"},"name":{"type":"string","description":"The name of the function being called (present when `type` is `function_call`).","uniqueKey":"output.items.[INDEX].name","typeLabel":"string"},"arguments":{"type":"string","description":"The JSON-encoded arguments for the function call (present when `type` is `function_call`).","uniqueKey":"output.items.[INDEX].arguments","typeLabel":"string"},"call_id":{"type":"string","description":"The unique call identifier (present when `type` is `function_call`).","uniqueKey":"output.items.[INDEX].call_id","typeLabel":"string"},"phase":{"type":"string","description":"Message phase reported by the model, such as final_answer.","uniqueKey":"output.items.[INDEX].phase","typeLabel":"string"}},"uniqueKey":"output.items.[INDEX]","typeLabel":"object"},"uniqueKey":"output","typeLabel":"object[]"},"parallel_tool_calls":{"type":"boolean","description":"Whether parallel tool calls were enabled.","uniqueKey":"parallel_tool_calls","typeLabel":"boolean"},"previous_response_id":{"oneOf":[{"type":"string","description":"The ID of the previous response, if this is a multi-turn conversation.","uniqueKey":"previous_response_id.oneOf.0","typeLabel":"string"},{"type":"null","description":"The ID of the previous response, if this is a multi-turn conversation.","uniqueKey":"previous_response_id.oneOf.1","typeLabel":"null"}],"uniqueKey":"previous_response_id","typeLabel":"string | null"},"reasoning":{"type":"object","description":"The reasoning configuration that was used.","properties":{"effort":{"oneOf":[{"type":"string","description":"The reasoning effort level.","uniqueKey":"reasoning.effort.oneOf.0","typeLabel":"string"},{"type":"null","description":"The reasoning effort level.","uniqueKey":"reasoning.effort.oneOf.1","typeLabel":"null"}],"uniqueKey":"reasoning.effort","typeLabel":"string | null"},"summary":{"oneOf":[{"type":"string","description":"The reasoning summary setting.","uniqueKey":"reasoning.summary.oneOf.0","typeLabel":"string"},{"type":"null","description":"The reasoning summary setting.","uniqueKey":"reasoning.summary.oneOf.1","typeLabel":"null"}],"uniqueKey":"reasoning.summary","typeLabel":"string | null"},"context":{"oneOf":[{"type":"string","description":"Reasoning context mode reported by the model.","uniqueKey":"reasoning.context.oneOf.0","typeLabel":"string"},{"type":"null","description":"Reasoning context mode reported by the model.","uniqueKey":"reasoning.context.oneOf.1","typeLabel":"null"}],"uniqueKey":"reasoning.context","typeLabel":"string | null"},"mode":{"oneOf":[{"type":"string","description":"Reasoning execution mode reported by the model.","uniqueKey":"reasoning.mode.oneOf.0","typeLabel":"string"},{"type":"null","description":"Reasoning execution mode reported by the model.","uniqueKey":"reasoning.mode.oneOf.1","typeLabel":"null"}],"uniqueKey":"reasoning.mode","typeLabel":"string | null"}},"uniqueKey":"reasoning","typeLabel":"object"},"service_tier":{"type":"string","description":"The service tier actually used to process the request.","uniqueKey":"service_tier","typeLabel":"string"},"store":{"type":"boolean","description":"Whether the response was stored.","uniqueKey":"store","typeLabel":"boolean"},"temperature":{"type":"number","description":"The temperature value used.","uniqueKey":"temperature","typeLabel":"number"},"text":{"type":"object","description":"The text configuration used.","properties":{"format":{"type":"object","properties":{"type":{"type":"string","description":"Format type: `text` (default), `json_object`, or `json_schema`.","uniqueKey":"text.format.type","typeLabel":"string"}},"description":"Output text format configuration.","uniqueKey":"text.format","typeLabel":"object"},"verbosity":{"type":"string","description":"The verbosity level used.","uniqueKey":"text.verbosity","typeLabel":"string"}},"uniqueKey":"text","typeLabel":"object"},"tool_choice":{"oneOf":[{"type":"string","description":"The tool choice setting used.","uniqueKey":"tool_choice.oneOf.0","typeLabel":"string"},{"type":"object","description":"The tool choice setting used.","uniqueKey":"tool_choice.oneOf.1","typeLabel":"object"}],"uniqueKey":"tool_choice","typeLabel":"string | object"},"tools":{"type":"array","description":"The tools that were available for this response.","items":{"type":"object","uniqueKey":"tools.items.[INDEX]","typeLabel":"object"},"uniqueKey":"tools","typeLabel":"object[]"},"top_p":{"type":"number","description":"The `top_p` value used.","uniqueKey":"top_p","typeLabel":"number"},"truncation":{"type":"string","description":"The truncation strategy used.","uniqueKey":"truncation","typeLabel":"string"},"usage":{"type":"object","description":"Token usage statistics for this response.","properties":{"input_tokens":{"type":"integer","description":"Number of input tokens consumed.","example":17,"uniqueKey":"usage.input_tokens","typeLabel":"integer"},"input_tokens_details":{"type":"object","description":"Breakdown of input token usage.","properties":{"cached_tokens":{"type":"integer","description":"Number of input tokens that were cached.","example":0,"uniqueKey":"usage.input_tokens_details.cached_tokens","typeLabel":"integer"},"cache_write_tokens":{"type":"integer","description":"Input tokens written to the prompt cache, when reported.","uniqueKey":"usage.input_tokens_details.cache_write_tokens","typeLabel":"integer"}},"uniqueKey":"usage.input_tokens_details","typeLabel":"object"},"output_tokens":{"type":"integer","description":"Number of output tokens generated.","example":81,"uniqueKey":"usage.output_tokens","typeLabel":"integer"},"output_tokens_details":{"type":"object","description":"Breakdown of output token usage.","properties":{"reasoning_tokens":{"type":"integer","description":"Number of tokens used for reasoning.","example":0,"uniqueKey":"usage.output_tokens_details.reasoning_tokens","typeLabel":"integer"}},"uniqueKey":"usage.output_tokens_details","typeLabel":"object"},"total_tokens":{"type":"integer","description":"Total number of tokens (input + output).","example":98,"uniqueKey":"usage.total_tokens","typeLabel":"integer"}},"uniqueKey":"usage","typeLabel":"object"},"user":{"oneOf":[{"type":"string","description":"The user identifier, if provided.","uniqueKey":"user.oneOf.0","typeLabel":"string"},{"type":"null","description":"The user identifier, if provided.","uniqueKey":"user.oneOf.1","typeLabel":"null"}],"uniqueKey":"user","typeLabel":"string | null"},"metadata":{"type":"object","description":"The metadata attached to this response.","additionalProperties":{"type":"string","uniqueKey":"metadata.additionalProperties","typeLabel":"string"},"uniqueKey":"metadata","typeLabel":"object"},"content_filters":{"oneOf":[{"type":["array","null"],"description":"Content filter results applied to the response, if any.","uniqueKey":"content_filters.oneOf.0","typeLabel":"array"},{"type":"null","description":"Content filter results applied to the response, if any.","uniqueKey":"content_filters.oneOf.1","typeLabel":"null"}],"uniqueKey":"content_filters","typeLabel":"array | null"},"frequency_penalty":{"type":"number","description":"The frequency penalty applied to the request.","uniqueKey":"frequency_penalty","typeLabel":"number"},"max_tool_calls":{"oneOf":[{"type":["integer","null"],"description":"Maximum number of tool calls allowed, if set.","uniqueKey":"max_tool_calls.oneOf.0","typeLabel":"integer"},{"type":"null","description":"Maximum number of tool calls allowed, if set.","uniqueKey":"max_tool_calls.oneOf.1","typeLabel":"null"}],"uniqueKey":"max_tool_calls","typeLabel":"integer | null"},"presence_penalty":{"type":"number","description":"The presence penalty applied to the request.","uniqueKey":"presence_penalty","typeLabel":"number"},"prompt_cache_key":{"oneOf":[{"type":["string","null"],"description":"Cache key for prompt caching, if applicable.","uniqueKey":"prompt_cache_key.oneOf.0","typeLabel":"string"},{"type":"null","description":"Cache key for prompt caching, if applicable.","uniqueKey":"prompt_cache_key.oneOf.1","typeLabel":"null"}],"uniqueKey":"prompt_cache_key","typeLabel":"string | null"},"prompt_cache_retention":{"oneOf":[{"type":["string","null"],"description":"Prompt cache retention policy, if applicable.","uniqueKey":"prompt_cache_retention.oneOf.0","typeLabel":"string"},{"type":"null","description":"Prompt cache retention policy, if applicable.","uniqueKey":"prompt_cache_retention.oneOf.1","typeLabel":"null"}],"uniqueKey":"prompt_cache_retention","typeLabel":"string | null"},"safety_identifier":{"oneOf":[{"type":["string","null"],"description":"Safety system identifier for the response, if applicable.","uniqueKey":"safety_identifier.oneOf.0","typeLabel":"string"},{"type":"null","description":"Safety system identifier for the response, if applicable.","uniqueKey":"safety_identifier.oneOf.1","typeLabel":"null"}],"uniqueKey":"safety_identifier","typeLabel":"string | null"},"top_logprobs":{"type":"integer","description":"Number of top log probabilities returned per token position.","uniqueKey":"top_logprobs","typeLabel":"integer"}},"uniqueKey":"","typeLabel":"object"},"example":{"id":"resp_example","object":"response","created_at":1788763707,"status":"completed","background":false,"completed_at":1788763711,"error":null,"incomplete_details":null,"model":"gpt-6-astra","output":[{"id":"msg_example","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"A little unicorn named Luna followed a trail of silver fireflies to a meadow where the flowers chimed softly in the breeze. She curled beneath a willow tree, tucked her hooves into the cool grass, and wished sweet dreams for every creature in the forest. As the moon wrapped the meadow in gentle light, Luna closed her eyes and drifted into dreams of dancing among the stars."}],"phase":"final_answer","role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"context":"all_turns","effort":"low","mode":"standard","summary":null},"store":true,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"usage":{"input_tokens":17,"input_tokens_details":{"cache_write_tokens":0,"cached_tokens":0},"output_tokens":81,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":98}},"examples":{"Example":{"title":"Example","value":{"id":"resp_example","object":"response","created_at":1788763707,"status":"completed","background":false,"completed_at":1788763711,"error":null,"incomplete_details":null,"model":"gpt-6-astra","output":[{"id":"msg_example","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"A little unicorn named Luna followed a trail of silver fireflies to a meadow where the flowers chimed softly in the breeze. She curled beneath a willow tree, tucked her hooves into the cool grass, and wished sweet dreams for every creature in the forest. As the moon wrapped the meadow in gentle light, Luna closed her eyes and drifted into dreams of dancing among the stars."}],"phase":"final_answer","role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"context":"all_turns","effort":"low","mode":"standard","summary":null},"store":true,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"usage":{"input_tokens":17,"input_tokens_details":{"cache_write_tokens":0,"cached_tokens":0},"output_tokens":81,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":98}}}},"exampleType":"examples"}},"exampleType":"examples"}},"security":{"a56a7049-0d12-4ef3-a068-aa63f5be54a6":{"bearerAuth":{"type":"http","scheme":"bearer","description":"Bearer token authentication. Use your CometAPI key.","scopes":[]}}},"servers":{"b01d2edf-97bf-4b97-9e4d-5f137173c1a0":{"url":"https://api.cometapi.com"}},"processedSecurityOptions":[{"schemes":[{"scheme":{"type":"http","scheme":"bearer","description":"Bearer token authentication. Use your CometAPI key.","scopes":[]},"schema":{"title":"Bearer Auth","type":"string","isRequired":true,"description":"Bearer token authentication. Use your CometAPI key.","format":"bearer","typeLabel":"string\u003cbearer>","deprecated":false},"schemeName":"bearerAuth","name":"Authorization"}],"title":"bearerAuth"}]},"originalFileLocation":"api/openapi/text/post-responses.openapi.json"},"subdomain":"cometapi","siteName":"CometAPI Documentation","title":"모델 응답 생성 - CometAPI Documentation","navMaps":{"firstHrefInVersion":{},"firstHrefInLanguage":{"en":{"href":"/api/text/responses","matchLevel":1},"zh-Hans":{"href":"/zh-Hans/api/text/responses","matchLevel":1,"noindex":true},"zh-Hant":{"href":"/zh-Hant/api/text/responses","matchLevel":1,"noindex":true},"ja":{"href":"/ja/api/text/responses","matchLevel":1,"noindex":true},"ko":{"href":"/ko/api/text/responses","matchLevel":0},"fr":{"href":"/fr/api/text/responses","matchLevel":1,"noindex":true},"de":{"href":"/de/api/text/responses","matchLevel":1,"noindex":true},"es":{"href":"/es/api/text/responses","matchLevel":1,"noindex":true},"it":{"href":"/it/api/text/responses","matchLevel":1,"noindex":true},"pt":{"href":"/pt/api/text/responses","matchLevel":1,"noindex":true},"ru":{"href":"/ru/api/text/responses","matchLevel":1,"noindex":true},"ar":{"href":"/ar/api/text/responses","matchLevel":1,"noindex":true},"vi":{"href":"/vi/api/text/responses","matchLevel":1,"noindex":true},"id":{"href":"/id/api/text/responses","matchLevel":1,"noindex":true},"tr":{"href":"/tr/api/text/responses","matchLevel":1,"noindex":true},"pl":{"href":"/pl/api/text/responses","matchLevel":1,"noindex":true},"nl":{"href":"/nl/api/text/responses","matchLevel":1,"noindex":true},"no":{"href":"/no/api/text/responses","matchLevel":1,"noindex":true},"uk":{"href":"/uk/api/text/responses","matchLevel":1,"noindex":true}}},"lastModified":"2026-09-08T03:43:44.830Z","gitLastModified":"2026-09-08T02:59:59.000Z","originalFileLocation":"ko/api/text/responses.mdx","locale":"ko"},"headHtml":"\u003cscript data-mint-head>(function(){var d=document.documentElement,p=null;if(!p){try{p=localStorage.getItem(\"isDarkMode\")}catch(e){}if(p==='true')p='dark';else if(p==='false')p='light';if(p!=='light'\u0026\u0026p!=='dark'\u0026\u0026p!=='system')p=\"system\"}var r=p==='system'?(matchMedia(\"(prefers-color-scheme: dark)\").matches?'dark':'light'):p;d.classList.remove(r==='dark'?'light':'dark');d.classList.add(r);d.setAttribute(\"data-theme-preference\",p)})();\u003c/script>\u003cmeta data-mint-head name=\"description\" content=\"CometAPI POST /v1/responses를 사용하여 기본 제공 도구와 함수 호출을 포함한 멀티모달 모델 응답 및 대화 기록을 생성합니다.\">\u003cmeta data-mint-head name=\"application-name\" content=\"CometAPI Documentation\">\u003cmeta data-mint-head name=\"generator\" content=\"Mintlify\">\u003cmeta data-mint-head name=\"robots\" content=\"noindex\">\u003clink data-mint-head rel=\"icon\" type=\"image/png\" sizes=\"192x192\" href=\"/mintlify-assets/_mintlify/favicons/cometapi/Jhcr00uAqm6Ci9Vs/_generated/favicon/android-chrome-192x192.png\" media=\"(prefers-color-scheme: light)\">\u003clink data-mint-head rel=\"apple-touch-icon\" type=\"image/png\" sizes=\"180x180\" href=\"/mintlify-assets/_mintlify/favicons/cometapi/Jhcr00uAqm6Ci9Vs/_generated/favicon/apple-touch-icon.png\">\u003clink data-mint-head rel=\"icon\" type=\"image/png\" sizes=\"16x16\" href=\"/mintlify-assets/_mintlify/favicons/cometapi/Jhcr00uAqm6Ci9Vs/_generated/favicon/favicon-16x16.png\" media=\"(prefers-color-scheme: light)\">\u003clink data-mint-head rel=\"icon\" type=\"image/png\" sizes=\"32x32\" href=\"/mintlify-assets/_mintlify/favicons/cometapi/Jhcr00uAqm6Ci9Vs/_generated/favicon/favicon-32x32.png\" media=\"(prefers-color-scheme: light)\">\u003clink data-mint-head rel=\"shortcut icon\" type=\"image/x-icon\" href=\"/mintlify-assets/_mintlify/favicons/cometapi/Jhcr00uAqm6Ci9Vs/_generated/favicon/favicon.ico\" media=\"(prefers-color-scheme: light)\">\u003clink data-mint-head rel=\"icon\" type=\"image/png\" sizes=\"192x192\" href=\"/mintlify-assets/_mintlify/favicons/cometapi/Jhcr00uAqm6Ci9Vs/_generated/favicon-dark/android-chrome-192x192.png\" media=\"(prefers-color-scheme: dark)\">\u003clink data-mint-head rel=\"icon\" type=\"image/png\" sizes=\"16x16\" href=\"/mintlify-assets/_mintlify/favicons/cometapi/Jhcr00uAqm6Ci9Vs/_generated/favicon-dark/favicon-16x16.png\" media=\"(prefers-color-scheme: dark)\">\u003clink data-mint-head rel=\"icon\" type=\"image/png\" sizes=\"32x32\" href=\"/mintlify-assets/_mintlify/favicons/cometapi/Jhcr00uAqm6Ci9Vs/_generated/favicon-dark/favicon-32x32.png\" media=\"(prefers-color-scheme: dark)\">\u003clink data-mint-head rel=\"shortcut icon\" type=\"image/x-icon\" href=\"/mintlify-assets/_mintlify/favicons/cometapi/Jhcr00uAqm6Ci9Vs/_generated/favicon-dark/favicon.ico\" media=\"(prefers-color-scheme: dark)\">\u003cmeta data-mint-head property=\"og:title\" content=\"모델 응답 생성 - CometAPI Documentation\">\u003cmeta data-mint-head property=\"og:description\" content=\"CometAPI POST /v1/responses를 사용하여 기본 제공 도구와 함수 호출을 포함한 멀티모달 모델 응답 및 대화 기록을 생성합니다.\">\u003cmeta data-mint-head property=\"og:site_name\" content=\"CometAPI Docs\">\u003cmeta data-mint-head property=\"og:url\" content=\"https://apidoc.cometapi.com/ko/api/text/responses\">\u003cmeta data-mint-head property=\"og:type\" content=\"website\">\u003cmeta data-mint-head property=\"og:image\" content=\"https://cometapi.mintlify.app/_mintlify/api/og/v2?division=%ED%85%8D%EC%8A%A4%ED%8A%B8+%EB%AA%A8%EB%8D%B8\u0026amp;title=%EB%AA%A8%EB%8D%B8+%EC%9D%91%EB%8B%B5+%EC%83%9D%EC%84%B1\u0026amp;description=CometAPI+POST+%2Fv1%2Fresponses%EB%A5%BC+%EC%82%AC%EC%9A%A9%ED%95%98%EC%97%AC+%EA%B8%B0%EB%B3%B8+%EC%A0%9C%EA%B3%B5+%EB%8F%84%EA%B5%AC%EC%99%80+%ED%95%A8%EC%88%98+%ED%98%B8%EC%B6%9C%EC%9D%84+%ED%8F%AC%ED%95%A8%ED%95%9C+%EB%A9%80%ED%8B%B0%EB%AA%A8%EB%8B%AC+%EB%AA%A8%EB%8D%B8+%EC%9D%91%EB%8B%B5+%EB%B0%8F+%EB%8C%80%ED%99%94+%EA%B8%B0%EB%A1%9D%EC%9D%84+%EC%83%9D%EC%84%B1%ED%95%A9%EB%8B%88%EB%8B%A4.\u0026amp;theme=8f4122d879437f2cf832428a\u0026amp;signature=32e980842b7ca5caf17f97d591249139b30555e31619c39a80f1ddde8695b3e1\">\u003cmeta data-mint-head property=\"og:image:width\" content=\"1200\">\u003cmeta data-mint-head property=\"og:image:height\" content=\"630\">\u003cmeta data-mint-head name=\"twitter:card\" content=\"summary_large_image\">\u003cmeta data-mint-head name=\"twitter:title\" content=\"모델 응답 생성 - CometAPI Documentation\">\u003cmeta data-mint-head name=\"twitter:description\" content=\"CometAPI POST /v1/responses를 사용하여 기본 제공 도구와 함수 호출을 포함한 멀티모달 모델 응답 및 대화 기록을 생성합니다.\">\u003cmeta data-mint-head name=\"twitter:image\" content=\"https://cometapi.mintlify.app/_mintlify/api/og/v2?division=%ED%85%8D%EC%8A%A4%ED%8A%B8+%EB%AA%A8%EB%8D%B8\u0026amp;title=%EB%AA%A8%EB%8D%B8+%EC%9D%91%EB%8B%B5+%EC%83%9D%EC%84%B1\u0026amp;description=CometAPI+POST+%2Fv1%2Fresponses%EB%A5%BC+%EC%82%AC%EC%9A%A9%ED%95%98%EC%97%AC+%EA%B8%B0%EB%B3%B8+%EC%A0%9C%EA%B3%B5+%EB%8F%84%EA%B5%AC%EC%99%80+%ED%95%A8%EC%88%98+%ED%98%B8%EC%B6%9C%EC%9D%84+%ED%8F%AC%ED%95%A8%ED%95%9C+%EB%A9%80%ED%8B%B0%EB%AA%A8%EB%8B%AC+%EB%AA%A8%EB%8D%B8+%EC%9D%91%EB%8B%B5+%EB%B0%8F+%EB%8C%80%ED%99%94+%EA%B8%B0%EB%A1%9D%EC%9D%84+%EC%83%9D%EC%84%B1%ED%95%A9%EB%8B%88%EB%8B%A4.\u0026amp;theme=8f4122d879437f2cf832428a\u0026amp;signature=32e980842b7ca5caf17f97d591249139b30555e31619c39a80f1ddde8695b3e1\">\u003cmeta data-mint-head name=\"twitter:image:width\" content=\"1200\">\u003cmeta data-mint-head name=\"twitter:image:height\" content=\"630\">\u003cmeta data-mint-head name=\"msapplication-config\" content=\"/mintlify-assets/_mintlify/favicons/cometapi/Jhcr00uAqm6Ci9Vs/_generated/favicon/browserconfig.xml\">\u003cmeta data-mint-head name=\"apple-mobile-web-app-title\" content=\"CometAPI Documentation\">\u003cmeta data-mint-head name=\"msapplication-TileColor\" content=\"#00ACE2\">\u003cmeta data-mint-head name=\"author\" content=\"CometAPI\">\u003cmeta data-mint-head name=\"copyright\" content=\"Copyright 2026 CometAPI\">\u003cmeta data-mint-head name=\"category\" content=\"Technology\">\u003cmeta data-mint-head name=\"distribution\" content=\"global\">\u003cmeta data-mint-head name=\"coverage\" content=\"Worldwide\">\u003clink data-mint-head rel=\"canonical\" href=\"https://apidoc.cometapi.com/ko/api/text/responses\">\u003clink data-mint-head rel=\"alternate\" type=\"application/xml\" href=\"/sitemap.xml\">\u003clink data-mint-head rel=\"alternate\" type=\"text/markdown\" href=\"/ko/api/text/responses.md\">\u003cscript data-mint-head type=\"application/ld+json\">{\"@context\":\"https://schema.org\",\"@type\":\"WebSite\",\"name\":\"CometAPI Documentation\",\"creator\":{\"@type\":\"Organization\",\"name\":\"Mintlify\",\"url\":\"https://mintlify.com\"}}\u003c/script>","siteName":"CometAPI Documentation","nav":{"global":null,"languages":[{"language":"en","pages":[{"title":"en","href":"/api/text/responses"}]},{"language":"zh-Hans","pages":[{"title":"zh-Hans","href":"/zh-Hans/api/text/responses"}]},{"language":"zh-Hant","pages":[{"title":"zh-Hant","href":"/zh-Hant/api/text/responses"}]},{"language":"ja","pages":[{"title":"ja","href":"/ja/api/text/responses"}]},{"language":"ko","tabs":[{"tab":"Docs","pages":[{"title":"Docs","href":"/ko"}]},{"tab":"API","groups":[{"group":"텍스트 모델","icon":"message","root":{"title":"텍스트 및 채팅 API","sidebarTitle":"텍스트 및 채팅 API","href":"/ko/api/text"},"expanded":false,"pages":[{"title":"채팅 완성 만들기","sidebarTitle":"채팅 완성 만들기","openapi":"api/openapi/text/post-chat.openapi.json POST /v1/chat/completions","description":"스트리밍(Streaming), 구조화된 출력 및 도구 호출을 지원하는 채팅 모델에 여러 메시지로 구성된 대화를 전송하려면 CometAPI POST /v1/chat/completions를 사용하세요.","href":"/ko/api/text/chat"},{"title":"모델 응답 생성","sidebarTitle":"모델 응답 생성","openapi":"api/openapi/text/post-responses.openapi.json POST /v1/responses","href":"/ko/api/text/responses"},{"title":"메시지 생성","sidebarTitle":"메시지 생성","openapi":"api/openapi/text/post-anthropic-messages.openapi.json POST /v1/messages","description":"텍스트 및 이미지 입력, 적응형 사고, 프롬프트 캐싱, 스트리밍(Streaming), 도구를 지원하는 CometAPI Messages 엔드포인트를 통해 Claude를 호출합니다.","href":"/ko/api/text/anthropic-messages"},{"title":"콘텐츠 생성","sidebarTitle":"콘텐츠 생성","openapi":"api/openapi/text/post-gemini-generating-content.openapi.json POST /v1beta/models/{model}:{operator}","href":"/ko/api/text/gemini-generating-content"}]},{"group":"이미지 모델","icon":"image","root":{"title":"이미지 생성 및 편집 API","sidebarTitle":"이미지 모델","href":"/ko/api/image/index"},"expanded":false,"pages":[{"group":"OpenAI","pages":[{"title":"이미지 생성","sidebarTitle":"이미지 생성","openapi":"api/openapi/image/openai/post-images.openapi.json POST /v1/images/generations","href":"/ko/api/image/openai/images"},{"title":"이미지 생성 작업 조회","sidebarTitle":"이미지 작업 조회","openapi":"api/openapi/image/openai/get-image-generation-task.openapi.json GET /v1/images/generations/{task_id}","href":"/ko/api/image/openai/image-generation-task"},{"title":"이미지 편집 생성","sidebarTitle":"이미지 편집 생성","openapi":"api/openapi/image/openai/post-image-editing.openapi.json POST /v1/images/edits","href":"/ko/api/image/openai/image-editing"}]},{"group":"Gemini","pages":[{"title":"Gemini로 이미지 생성","sidebarTitle":"Gemini로 이미지 생성","openapi":"api/openapi/image/gemini/post-gemini-generates-image.openapi.json POST /v1beta/models/{model}:generateContent","href":"/ko/api/image/gemini/gemini-generates-image"},{"title":"Gemini 이미지 모델 사용","sidebarTitle":"Gemini 이미지 모델 사용","href":"/ko/api/image/gemini/generate-image-guide"}]},{"group":"Grok","pages":[{"title":"Grok으로 이미지 생성","sidebarTitle":"이미지 생성","openapi":"api/openapi/image/grok/post-image-generation.openapi.json POST /v1/images/generations","href":"/ko/api/image/grok/image-generation"},{"title":"Grok으로 이미지 편집","sidebarTitle":"이미지 편집","openapi":"api/openapi/image/grok/post-image-editing.openapi.json POST /v1/images/edits","href":"/ko/api/image/grok/image-editing"}]},{"group":"Kling","pages":[{"title":"Kling으로 이미지 생성하기","sidebarTitle":"Kling으로 이미지 생성하기","openapi":"api/openapi/image/kling/post-image-generation.openapi.json POST /kling/v1/images/generations","href":"/ko/api/image/kling/image-generation"},{"title":"여러 이미지로 Kling 이미지 생성하기","sidebarTitle":"여러 이미지로 Kling 이미지 생성하기","openapi":"api/openapi/image/kling/post-multi-image-to-image.openapi.json POST /kling/v1/images/multi-image2image","href":"/ko/api/image/kling/multi-image-to-image"},{"title":"Kling으로 이미지 확장하기","sidebarTitle":"Kling으로 이미지 확장하기","openapi":"api/openapi/image/kling/post-image-expansion.openapi.json POST /kling/v1/images/editing/expand","href":"/ko/api/image/kling/image-expansion"},{"title":"Kling Omni 이미지 작업 생성","sidebarTitle":"Kling Omni 이미지 작업 생성","openapi":"api/openapi/image/kling/post-omni-image.openapi.json POST /kling/v1/images/omni-image","href":"/ko/api/image/kling/omni-image"},{"title":"Kling Omni 이미지 작업 가져오기","sidebarTitle":"Kling Omni 이미지 작업 가져오기","openapi":"api/openapi/image/kling/get-omni-image.openapi.json GET /kling/v1/images/omni-image/{task_id}","href":"/ko/api/image/kling/omni-image-query"}]},{"group":"Midjourney","pages":[{"title":"Midjourney API 시작하기","sidebarTitle":"Midjourney API 시작하기","href":"/ko/api/image/midjourney/midjourney-api-quick-start"},{"group":"작업 가져오기","pages":[{"title":"Midjourney 작업 목록 조회","sidebarTitle":"Midjourney 작업 목록 조회","openapi":"api/openapi/image/midjourney/task-fetching-api/post-list-by-condition.openapi.json POST /mj/task/list-by-condition","href":"/ko/api/image/midjourney/task-fetching-api/list-by-condition"},{"title":"Midjourney 작업 가져오기","sidebarTitle":"Midjourney 작업 가져오기","openapi":"api/openapi/image/midjourney/task-fetching-api/get-fetch-single-task.openapi.json GET /mj/task/{id}/fetch","href":"/ko/api/image/midjourney/task-fetching-api/fetch-single-task"}]},{"title":"Midjourney imagine 작업 생성","sidebarTitle":"Midjourney imagine 작업 생성","openapi":"api/openapi/image/midjourney/post-imagine.openapi.json POST /mj/submit/imagine","href":"/ko/api/image/midjourney/imagine"},{"title":"Midjourney 비디오 작업 생성","sidebarTitle":"Midjourney 비디오 작업 생성","openapi":"api/openapi/image/midjourney/post-submit-video.openapi.json POST /mj/submit/video","href":"/ko/api/image/midjourney/submit-video"},{"title":"Midjourney editor 작업 생성","sidebarTitle":"Midjourney editor 작업 생성","openapi":"api/openapi/image/midjourney/post-submit-editor.openapi.json POST /mj/submit/edits","href":"/ko/api/image/midjourney/submit-editor"},{"title":"Midjourney 액션 작업 생성","sidebarTitle":"Midjourney 액션 작업 생성","openapi":"api/openapi/image/midjourney/post-action.openapi.json POST /mj/submit/action","href":"/ko/api/image/midjourney/action"},{"title":"Midjourney blend 작업 생성","sidebarTitle":"Midjourney blend 작업 생성","openapi":"api/openapi/image/midjourney/post-blend.openapi.json POST /mj/submit/blend","href":"/ko/api/image/midjourney/blend"},{"title":"Midjourney로 이미지 설명하기","sidebarTitle":"Midjourney로 이미지 설명하기","openapi":"api/openapi/image/midjourney/post-describe.openapi.json POST /mj/submit/describe","href":"/ko/api/image/midjourney/describe"},{"title":"Midjourney modal 작업 생성","sidebarTitle":"Midjourney modal 작업 생성","openapi":"api/openapi/image/midjourney/post-modal.openapi.json POST /mj/submit/modal","href":"/ko/api/image/midjourney/modal"}]},{"group":"Replicate","pages":[{"title":"Replicate prediction 생성","sidebarTitle":"Replicate prediction 생성","openapi":"api/openapi/image/replicate/post-create-predictions-general.openapi.json POST /replicate/v1/models/{models}/predictions","href":"/ko/api/image/replicate/create-predictions-general"},{"title":"Replicate prediction 조회","sidebarTitle":"Replicate prediction 조회","openapi":"api/openapi/image/replicate/get-replicate-query.openapi.json GET /replicate/v1/predictions/{id}","href":"/ko/api/image/replicate/replicate-query"}]},{"group":"Seedream","pages":[{"title":"Seedream 이미지 작업 생성","sidebarTitle":"이미지 작업 생성","openapi":"api/openapi/image/seededit-seedream/post-bytedance-image-generation.openapi.json POST /v1/images/generations","href":"/ko/api/image/seededit-seedream/bytedance-image-generation"},{"title":"Seedream 이미지 작업 조회","sidebarTitle":"이미지 작업 조회","openapi":"api/openapi/image/seededit-seedream/get-bytedance-image-generation-task.openapi.json GET /v1/images/generations/{task_id}","href":"/ko/api/image/seededit-seedream/bytedance-image-generation-task"}]},{"group":"Flux","pages":[{"title":"FLUX 이미지 생성","sidebarTitle":"FLUX 이미지 생성","openapi":"api/openapi/image/flux/post-flux-generate-image.openapi.json POST /flux/v1/{model}","href":"/ko/api/image/flux/flux-generate-image"},{"title":"FLUX 이미지 결과 가져오기","sidebarTitle":"FLUX 이미지 결과 가져오기","openapi":"api/openapi/image/flux/get-flux-query.openapi.json GET /flux/v1/get_result","href":"/ko/api/image/flux/flux-query"}]}]},{"group":"비디오 모델","icon":"video","root":{"title":"동영상 생성 API","sidebarTitle":"동영상 모델","href":"/ko/api/video/index"},"expanded":false,"pages":[{"group":"Seedance","pages":[{"title":"Seedance 동영상 생성","sidebarTitle":"Seedance 동영상 생성","openapi":"api/openapi/video/seedance/post-seedance-create.openapi.json POST /v1/videos","href":"/ko/api/video/seedance/create"},{"title":"Seedance 비디오 조회","sidebarTitle":"Seedance 비디오 조회","openapi":"api/openapi/video/seedance/get-seedance-query.openapi.json GET /v1/videos/{id}","href":"/ko/api/video/seedance/query"}]},{"group":"HappyHorse","pages":[{"title":"HappyHorse 비디오 만들기","sidebarTitle":"HappyHorse 비디오 만들기","openapi":"api/openapi/video/happyhorse/post-create.openapi.json POST /v1/videos","href":"/ko/api/video/happyhorse/create"},{"title":"HappyHorse 비디오 조회","sidebarTitle":"HappyHorse 비디오 조회","openapi":"api/openapi/video/happyhorse/get-retrieve.openapi.json GET /v1/videos/{task_id}","href":"/ko/api/video/happyhorse/retrieve"},{"title":"HappyHorse 비디오 콘텐츠 다운로드","sidebarTitle":"HappyHorse 비디오 콘텐츠 다운로드","openapi":"api/openapi/video/happyhorse/get-retrieve-content.openapi.json GET /v1/videos/{task_id}/content","href":"/ko/api/video/happyhorse/retrieve-content"}]},{"group":"MiniMax H3","pages":[{"title":"MiniMax H3 동영상 만들기","sidebarTitle":"MiniMax H3 동영상 만들기","openapi":"api/openapi/video/minimax-h3/post-create.openapi.json POST /v1/videos","href":"/ko/api/video/minimax-h3/create"},{"title":"MiniMax H3 동영상 조회","sidebarTitle":"MiniMax H3 동영상 조회","openapi":"api/openapi/video/minimax-h3/get-retrieve.openapi.json GET /v1/videos/{task_id}","href":"/ko/api/video/minimax-h3/retrieve"},{"title":"MiniMax H3 비디오 콘텐츠 다운로드","sidebarTitle":"MiniMax H3 비디오 콘텐츠 다운로드","openapi":"api/openapi/video/minimax-h3/get-retrieve-content.openapi.json GET /v1/videos/{task_id}/content","href":"/ko/api/video/minimax-h3/retrieve-content"}]},{"group":"Flux 3","pages":[{"title":"Flux 3 비디오 생성","sidebarTitle":"Flux 3 비디오 생성","openapi":"api/openapi/video/flux-3/post-create.openapi.json POST /v1/videos","href":"/ko/api/video/flux-3/create"},{"title":"Flux 3 비디오 작업 조회","sidebarTitle":"Flux 3 비디오 작업 조회","openapi":"api/openapi/video/flux-3/get-retrieve.openapi.json GET /v1/videos/{task_id}","href":"/ko/api/video/flux-3/retrieve"},{"title":"Flux 3 비디오 콘텐츠 다운로드","sidebarTitle":"Flux 3 비디오 콘텐츠 다운로드","openapi":"api/openapi/video/flux-3/get-retrieve-content.openapi.json GET /v1/videos/{task_id}/content","href":"/ko/api/video/flux-3/retrieve-content"}]},{"group":"Veo 3","pages":[{"title":"Veo 3 동영상 만들기","sidebarTitle":"Veo 3 동영상 만들기","openapi":"api/openapi/video/veo3/post-create.openapi.json POST /v1/videos","href":"/ko/api/video/veo3/create"},{"title":"Veo 3 비디오 조회","sidebarTitle":"Veo 3 비디오 조회","openapi":"api/openapi/video/veo3/get-retrieve.openapi.json GET /v1/videos/{video_id}","href":"/ko/api/video/veo3/retrieve"}]},{"group":"Wan","pages":[{"title":"Wan 동영상 생성","sidebarTitle":"Wan 동영상 생성","openapi":"api/openapi/video/wan/post-create.openapi.json POST /v1/videos","href":"/ko/api/video/wan/create"},{"title":"Wan 비디오 조회","sidebarTitle":"Wan 비디오 조회","openapi":"api/openapi/video/wan/get-retrieve.openapi.json GET /v1/videos/{task_id}","href":"/ko/api/video/wan/retrieve"},{"title":"Wan 비디오 콘텐츠 다운로드","sidebarTitle":"Wan 비디오 콘텐츠 다운로드","openapi":"api/openapi/video/wan/get-retrieve-content.openapi.json GET /v1/videos/{task_id}/content","href":"/ko/api/video/wan/retrieve-content"}]},{"group":"xAI","pages":[{"title":"Grok으로 동영상 만들기","sidebarTitle":"Grok 동영상 만들기","openapi":"api/openapi/video/xai/post-video-generation.openapi.json POST /grok/v1/videos/generations","href":"/ko/api/video/xai/video-generation"},{"title":"xAI 비디오 편집 생성","sidebarTitle":"xAI 비디오 편집 생성","openapi":"api/openapi/video/xai/post-video-edit.openapi.json POST /grok/v1/videos/edits","href":"/ko/api/video/xai/video-edit"},{"title":"xAI 비디오 결과 가져오기","sidebarTitle":"xAI 비디오 결과 가져오기","openapi":"api/openapi/video/xai/get-get-video-generation-results.openapi.json GET /grok/v1/videos/{request_id}","href":"/ko/api/video/xai/get-video-generation-results"}]},{"group":"Vidu","pages":[{"title":"Vidu 동영상 생성","sidebarTitle":"Vidu 동영상 생성","openapi":"api/openapi/video/vidu/post-create.openapi.json POST /v1/videos","href":"/ko/api/video/vidu/create"},{"title":"Vidu 비디오 조회","sidebarTitle":"Vidu 비디오 조회","openapi":"api/openapi/video/vidu/get-retrieve.openapi.json GET /v1/videos/{task_id}","href":"/ko/api/video/vidu/retrieve"},{"title":"Vidu 비디오 콘텐츠 다운로드","sidebarTitle":"Vidu 비디오 콘텐츠 다운로드","openapi":"api/openapi/video/vidu/get-retrieve-content.openapi.json GET /v1/videos/{task_id}/content","href":"/ko/api/video/vidu/retrieve-content"}]},{"group":"Omni","tag":"Beta","pages":[{"title":"텍스트, 이미지 또는 동영상으로 Omni 동영상 만들기","sidebarTitle":"Omni 동영상 만들기","openapi":"api/openapi/video/omni/post-create.openapi.json POST /v1/videos","href":"/ko/api/video/omni/create"},{"title":"Omni 비디오 조회","sidebarTitle":"Omni 비디오 조회","openapi":"api/openapi/video/omni/get-retrieve.openapi.json GET /v1/videos/{task_id}","href":"/ko/api/video/omni/retrieve"},{"title":"Omni 비디오 콘텐츠 다운로드","sidebarTitle":"Omni 비디오 콘텐츠 다운로드","openapi":"api/openapi/video/omni/get-retrieve-content.openapi.json GET /v1/videos/{task_id}/content","href":"/ko/api/video/omni/retrieve-content"}]},{"group":"Kling","pages":[{"group":"멀티모달 비디오 편집","pages":[{"title":"Kling 편집 세션 초기화","sidebarTitle":"Kling 편집 세션 초기화","openapi":"api/openapi/video/kling/multimodal-video-editing/post-initialize-video-for-editing.openapi.json POST /kling/v1/videos/multi-elements/init-selection","href":"/ko/api/video/kling/multimodal-video-editing/initialize-video-for-editing"},{"title":"Kling 비디오 선택 추가","sidebarTitle":"Kling 비디오 선택 추가","openapi":"api/openapi/video/kling/multimodal-video-editing/post-add-video-selection.openapi.json POST /kling/v1/videos/multi-elements/add-selection","href":"/ko/api/video/kling/multimodal-video-editing/add-video-selection"},{"title":"Kling 비디오 선택 삭제","sidebarTitle":"Kling 비디오 선택 삭제","openapi":"api/openapi/video/kling/multimodal-video-editing/post-delete-video-selection.openapi.json POST /kling/v1/videos/multi-elements/delete-selection","href":"/ko/api/video/kling/multimodal-video-editing/delete-video-selection"},{"title":"Clear Kling 비디오 선택","sidebarTitle":"Clear Kling 비디오 선택","openapi":"api/openapi/video/kling/multimodal-video-editing/post-clear-video-selection.openapi.json POST /kling/v1/videos/multi-elements/clear-selection","href":"/ko/api/video/kling/multimodal-video-editing/clear-video-selection"},{"title":"Kling 비디오 선택 미리보기","sidebarTitle":"Kling 비디오 선택 미리보기","openapi":"api/openapi/video/kling/multimodal-video-editing/post-preview-selected-video-area.openapi.json POST /kling/v1/videos/multi-elements/preview-selection","href":"/ko/api/video/kling/multimodal-video-editing/preview-selected-video-area"},{"title":"Kling 멀티모달 편집 작업 생성","sidebarTitle":"Kling 멀티모달 편집 작업 생성","openapi":"api/openapi/video/kling/multimodal-video-editing/post-create-task.openapi.json POST /kling/v1/videos/multi-elements","href":"/ko/api/video/kling/multimodal-video-editing/create-task"}]},{"group":"모델별 경로","pages":[{"title":"모델별 Kling 텍스트-비디오 작업 생성","sidebarTitle":"텍스트-비디오","openapi":"api/openapi/video/kling/model-routes/post-text-to-video.openapi.json POST /text-to-video/{model}","href":"/ko/api/video/kling/model-routes/text-to-video"},{"title":"모델별 Kling 이미지-투-비디오 작업 생성","sidebarTitle":"이미지-비디오","openapi":"api/openapi/video/kling/model-routes/post-image-to-video.openapi.json POST /image-to-video/{model}","href":"/ko/api/video/kling/model-routes/image-to-video"},{"title":"Kling Omni 동영상 만들기","sidebarTitle":"Omni 동영상","openapi":"api/openapi/video/kling/model-routes/post-omni-video.openapi.json POST /omni-video/{model}","href":"/ko/api/video/kling/model-routes/omni-video"},{"title":"Kling 모션 제어 비디오 만들기","sidebarTitle":"모션 제어","openapi":"api/openapi/video/kling/model-routes/post-motion-control.openapi.json POST /motion-control/{model}","href":"/ko/api/video/kling/model-routes/motion-control"},{"title":"Kling 모델 라우트 작업 가져오기","sidebarTitle":"Kling 작업 가져오기","openapi":"api/openapi/video/kling/model-routes/get-tasks.openapi.json GET /tasks","href":"/ko/api/video/kling/model-routes/tasks"}]},{"title":"Kling 텍스트-투-비디오 작업 생성","sidebarTitle":"Kling 텍스트-투-비디오 작업 생성","openapi":"api/openapi/video/kling/post-text-to-video.openapi.json POST /kling/v1/videos/text2video","href":"/ko/api/video/kling/text-to-video"},{"title":"Kling 이미지-투-비디오 작업 생성","sidebarTitle":"Kling 이미지-투-비디오 작업 생성","openapi":"api/openapi/video/kling/post-image-to-video.openapi.json POST /kling/v1/videos/image2video","href":"/ko/api/video/kling/image-to-video"},{"title":"Kling Motion Control 작업 생성","sidebarTitle":"Kling Motion Control 작업 생성","openapi":"api/openapi/video/kling/post-motion-control.openapi.json POST /kling/v1/videos/motion-control","href":"/ko/api/video/kling/motion-control"},{"title":"Kling 멀티 이미지 비디오 작업 생성","sidebarTitle":"Kling 멀티 이미지 비디오 작업 생성","openapi":"api/openapi/video/kling/post-multi-image-to-video.openapi.json POST /kling/v1/videos/multi-image2video","href":"/ko/api/video/kling/multi-image-to-video"},{"title":"Kling 비디오 확장","sidebarTitle":"Kling 비디오 확장","openapi":"api/openapi/video/kling/post-video-extension.openapi.json POST /kling/v1/videos/video-extend","href":"/ko/api/video/kling/video-extension"},{"title":"Kling 음성 생성","sidebarTitle":"Kling 음성 생성","openapi":"api/openapi/video/kling/post-tts.openapi.json POST /kling/v1/audio/tts","href":"/ko/api/video/kling/tts"},{"title":"Kling 아바타 비디오 만들기","sidebarTitle":"Kling 아바타 비디오 만들기","openapi":"api/openapi/video/kling/post-avatar.openapi.json POST /kling/v1/videos/avatar/image2video","href":"/ko/api/video/kling/avatar"},{"title":"Kling 립싱크용 얼굴 식별","sidebarTitle":"Kling 립싱크용 얼굴 식별","openapi":"api/openapi/video/kling/post-lip-sync.openapi.json POST /kling/v1/videos/identify-face","href":"/ko/api/video/kling/lip-sync"},{"title":"Kling 고급 립싱크 작업 생성","sidebarTitle":"Kling 고급 립싱크 작업 생성","openapi":"api/openapi/video/kling/post-counterpart-creating-tasks.openapi.json POST /kling/v1/videos/advanced-lip-sync","href":"/ko/api/video/kling/counterpart-creating-tasks"},{"title":"Kling 비디오 효과 적용","sidebarTitle":"Kling 비디오 효과 적용","openapi":"api/openapi/video/kling/post-video-effects.openapi.json POST /kling/v1/videos/effects","href":"/ko/api/video/kling/video-effects"},{"title":"Kling 텍스트-오디오 생성","sidebarTitle":"Kling 텍스트-오디오 생성","openapi":"api/openapi/video/kling/post-text-to-audio.openapi.json POST /kling/v1/audio/text-to-audio","href":"/ko/api/video/kling/text-to-audio"},{"title":"Kling 비디오-오디오 생성","sidebarTitle":"Kling 비디오-오디오 생성","openapi":"api/openapi/video/kling/post-video-to-audio.openapi.json POST /kling/v1/audio/video-to-audio","href":"/ko/api/video/kling/video-to-audio"},{"title":"Kling으로 이미지 인식하기","sidebarTitle":"Kling으로 이미지 인식하기","openapi":"api/openapi/video/kling/post-image-recognize.openapi.json POST /kling/v1/videos/image-recognize","href":"/ko/api/video/kling/image-recognize"},{"title":"Kling 작업 조회","sidebarTitle":"Kling 작업 조회","openapi":"api/openapi/video/kling/get-individual-queries.openapi.json GET /kling/v1/{action}/{action2}/{task_id}","href":"/ko/api/video/kling/individual-queries"},{"title":"Kling Omni 비디오 만들기","sidebarTitle":"Kling Omni 비디오 만들기","openapi":"api/openapi/video/kling/post-omni-video.openapi.json POST /kling/v1/videos/omni-video","href":"/ko/api/video/kling/omni-video"},{"title":"Kling Omni 비디오 가져오기","sidebarTitle":"Kling Omni 비디오 가져오기","openapi":"api/openapi/video/kling/get-omni-query.openapi.json GET /kling/v1/videos/omni-video/{task_id}","href":"/ko/api/video/kling/omni-query"},{"title":"Kling 콜백 URL 사용하기","sidebarTitle":"Kling 콜백 URL 사용하기","href":"/ko/api/video/kling/callback_url"}]},{"group":"Runway","pages":[{"title":"Runway API 개요","sidebarTitle":"개요","href":"/ko/api/video/runway/overview"},{"group":"이미지","pages":[{"title":"Runway 이미지 생성","sidebarTitle":"Runway 이미지 생성","openapi":"api/openapi/video/runway/official-format/post-generate-an-image-from-text.openapi.json POST /runwayml/v1/text_to_image","href":"/ko/api/video/runway/official-format/generate-an-image-from-text"}]},{"group":"비디오","pages":[{"title":"Runway 이미지-비디오 작업 생성","sidebarTitle":"Runway 이미지-비디오 작업 생성","openapi":"api/openapi/video/runway/official-format/post-runway-images-raw-video.openapi.json POST /runwayml/v1/image_to_video","href":"/ko/api/video/runway/official-format/runway-images-raw-video"},{"title":"Runway 텍스트-동영상 작업 생성","sidebarTitle":"Runway 텍스트-동영상 작업 생성","openapi":"api/openapi/video/runway/official-format/post-generate-a-video-from-text.openapi.json POST /runwayml/v1/text_to_video","href":"/ko/api/video/runway/official-format/generate-a-video-from-text"},{"title":"Runway 비디오-투-비디오 작업 생성","sidebarTitle":"Runway 비디오-투-비디오 작업 생성","openapi":"api/openapi/video/runway/official-format/post-generate-a-video-from-a-video.openapi.json POST /runwayml/v1/video_to_video","href":"/ko/api/video/runway/official-format/generate-a-video-from-a-video"},{"title":"Runway 캐릭터 퍼포먼스 생성","sidebarTitle":"Runway 캐릭터 퍼포먼스 생성","openapi":"api/openapi/video/runway/official-format/post-control-a-character.openapi.json POST /runwayml/v1/character_performance","href":"/ko/api/video/runway/official-format/control-a-character"},{"title":"Runway 비디오 업스케일","sidebarTitle":"Runway 비디오 업스케일","openapi":"api/openapi/video/runway/official-format/post-upscale-a-video.openapi.json POST /runwayml/v1/video_upscale","href":"/ko/api/video/runway/official-format/upscale-a-video"}]},{"group":"오디오","pages":[{"title":"Runway 사운드 효과 생성","sidebarTitle":"Runway 사운드 효과 생성","openapi":"api/openapi/video/runway/official-format/post-generate-sound-effects.openapi.json POST /runwayml/v1/sound_effect","href":"/ko/api/video/runway/official-format/generate-sound-effects"},{"title":"텍스트로 Runway 음성 생성","sidebarTitle":"텍스트로 Runway 음성 생성","openapi":"api/openapi/video/runway/official-format/post-generate-speech-from-text.openapi.json POST /runwayml/v1/text_to_speech","href":"/ko/api/video/runway/official-format/generate-speech-from-text"},{"title":"Runway 음성 변환","sidebarTitle":"Runway 음성 변환","openapi":"api/openapi/video/runway/official-format/post-convert-speech.openapi.json POST /runwayml/v1/speech_to_speech","href":"/ko/api/video/runway/official-format/convert-speech"},{"title":"Runway 오디오 더빙","sidebarTitle":"Runway 오디오 더빙","openapi":"api/openapi/video/runway/official-format/post-dub-audio.openapi.json POST /runwayml/v1/voice_dubbing","href":"/ko/api/video/runway/official-format/dub-audio"},{"title":"Runway 음성 분리","sidebarTitle":"Runway 음성 분리","openapi":"api/openapi/video/runway/official-format/post-isolate-voice.openapi.json POST /runwayml/v1/voice_isolation","href":"/ko/api/video/runway/official-format/isolate-voice"}]},{"group":"작업","pages":[{"title":"Runway 작업 가져오기","sidebarTitle":"Runway 작업 가져오기","openapi":"api/openapi/video/runway/official-format/get-runway-to-get-task-details.openapi.json GET /runwayml/v1/tasks/{id}","href":"/ko/api/video/runway/official-format/runway-to-get-task-details"}]}]}]},{"group":"오디오 모델","icon":"volume-high","root":{"title":"오디오 API","sidebarTitle":"오디오 모델","href":"/ko/api/audio/index"},"expanded":false,"pages":[{"title":"음성 생성","sidebarTitle":"음성 생성","openapi":"api/openapi/audio/post-create-speech.openapi.json POST /v1/audio/speech","href":"/ko/api/audio/create-speech"},{"title":"음성 전사","sidebarTitle":"음성 전사","openapi":"api/openapi/audio/post-create-transcription.openapi.json POST /v1/audio/transcriptions","href":"/ko/api/audio/create-transcription"},{"title":"번역","sidebarTitle":"번역","openapi":"api/openapi/audio/post-create-translation.openapi.json POST /v1/audio/translations","href":"/ko/api/audio/create-translation"}]},{"group":"임베딩","icon":"database","root":{"title":"임베딩 API","sidebarTitle":"임베딩","href":"/ko/api/embeddings/index"},"expanded":false,"pages":[{"title":"임베딩 생성","sidebarTitle":"임베딩 생성","openapi":"api/openapi/text/post-embeddings.openapi.json POST /v1/embeddings","href":"/ko/api/text/embeddings"}]},{"group":"콘텐츠 검토","icon":"shield-check","expanded":false,"pages":[{"title":"모더레이션 생성","sidebarTitle":"모더레이션 생성","openapi":"api/openapi/content-moderation/create-moderation.openapi.json POST /v1/moderations","href":"/ko/api/content-moderation/create-moderation"}]},{"group":"API 키","icon":"key","expanded":false,"pages":[{"title":"현재 API 키 가져오기","sidebarTitle":"현재 API 키 가져오기","openapi":"api/openapi/api-keys/get-current-api-key.openapi.json GET /api/usage/token","href":"/ko/api/api-keys/get-current-api-key"},{"title":"API 키 나열","sidebarTitle":"API 키 나열","openapi":"api/openapi/api-keys/list-api-keys.openapi.json GET /api/token/","href":"/ko/api/api-keys/list-api-keys"},{"title":"API 키 생성","sidebarTitle":"API 키 생성","openapi":"api/openapi/api-keys/create-api-key.openapi.json POST /api/token/","href":"/ko/api/api-keys/create-api-key"},{"title":"API 키 검색","sidebarTitle":"API 키 검색","openapi":"api/openapi/api-keys/get-api-key.openapi.json GET /api/token/{id}","href":"/ko/api/api-keys/get-api-key"},{"title":"API 키 삭제","sidebarTitle":"API 키 삭제","openapi":"api/openapi/api-keys/delete-api-key.openapi.json DELETE /api/token/{id}","href":"/ko/api/api-keys/delete-api-key"},{"title":"API 키 업데이트","sidebarTitle":"API 키 업데이트","openapi":"api/openapi/api-keys/update-api-key.openapi.json PUT /api/token/","href":"/ko/api/api-keys/update-api-key"}]}]},{"tab":"Integrations","pages":[{"title":"Integrations","href":"/ko/integrations"}]}]},{"language":"fr","pages":[{"title":"fr","href":"/fr/api/text/responses"}]},{"language":"de","pages":[{"title":"de","href":"/de/api/text/responses"}]},{"language":"es","pages":[{"title":"es","href":"/es/api/text/responses"}]},{"language":"it","pages":[{"title":"it","href":"/it/api/text/responses"}]},{"language":"pt","pages":[{"title":"pt","href":"/pt/api/text/responses"}]},{"language":"ru","pages":[{"title":"ru","href":"/ru/api/text/responses"}]},{"language":"ar","pages":[{"title":"ar","href":"/ar/api/text/responses"}]},{"language":"vi","pages":[{"title":"vi","href":"/vi/api/text/responses"}]},{"language":"id","pages":[{"title":"id","href":"/id/api/text/responses"}]},{"language":"tr","pages":[{"title":"tr","href":"/tr/api/text/responses"}]},{"language":"pl","pages":[{"title":"pl","href":"/pl/api/text/responses"}]},{"language":"nl","pages":[{"title":"nl","href":"/nl/api/text/responses"}]},{"language":"no","pages":[{"title":"no","href":"/no/api/text/responses"}]},{"language":"uk","pages":[{"title":"uk","href":"/uk/api/text/responses"}]}]},"basePath":"","title":"모델 응답 생성 - CometAPI Documentation","buildId":"dpl_9VVk5y1P8k1ATeJguVngy9Q3cmbD","deploymentId":"dpl_9VVk5y1P8k1ATeJguVngy9Q3cmbD","dynamics":["c2aa737661","b0f84f53ff","a9bb46feb3","2b790eda92"],"chunks":["OpenApiReferenceProvider-DX1Meug0.js","utils-B_OMIQVC.js","cloneDeep-izs3Hzxb.js","_Uint8Array-BVIqJ90l.js","isObjectLike-C8vmzPEN.js","isArray-Dcu1dQ5t.js","utils-ChxhRPMa.js","toString-BX-iyh8G.js","isSymbol-CSH9U2Gm.js","addUniqueKeysToSchema-CuKvD8Iv.js","snippetPresets-C5d7p2hp.js","style-to-object-BY3JEAdk.js","v4-DIgz8zy6.js","Page-BAvA99GL.js","ApiExamples-CfHcE8m4.js","isEqual-BfaiBbcl.js","usePlaygroundInputsStore-C1zZV314.js","shallow-CmQhqCJn.js","getApiPlaygroundDisplay-YRo9s1O7.js","CodeSnippet-RN1MTdfk.js","CodeSnippets-DKLPHxJA.js","getPastedJson-bz0M41mU.js","icon-CsmhpPrv.js","MethodPill-CNGsVE77.js","DuplicateIcon-DilfU_Z2.js","createIcon-BdsYzQck.js","DynamicMarkdown-CbqEDjbV.js","SectionHeading-O6hXpFCN.js","axios-vUo_bRtp.js","Markdown-nKm-uidQ.js","clsx-ClVdStUn.js","lib-DuNMoZ05.js","lib-B8HbPgcC.js","html-void-elements-mCSPHezU.js","dist-CIQkMg3R.js","katex-YMM-FMeD.js","marked.esm-CZWythHk.js","AssistantPageLink-ImrFS4Fy.js"]}