'openai' 검색 결과

Use OpenAI Codex CLI to review code changes, challenge an implementation by looking for ways it could fail, or discuss technical questions. Three modes provide an independent opinion, with follow-up questions supported in ongoing consultations.

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• Get an independent review of code changes
• Challenge code to uncover possible failures
• Continue a technical consultation with follow-up questions

Generate, remix, and manage short video clips through OpenAI's Sora API. Use it to create cinematic shots, produce b-roll—supplementary footage for an edit—or try different versions of a video concept.

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• Creating cinematic shots
• Producing supplementary footage for an edit
• Trying different versions of a video concept

Turn written text into spoken audio using OpenAI's API and built-in voices. Use it to create narrated explanations, audio versions of lectures, or quick voiceover tracks from prepared scripts.

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• Creating narration for an explainer
• Turning lecture text into audio
• Making a quick video voiceover

Generate and edit project images with OpenAI's Image API, including UI mockups, icons, illustrations, social cards, and visual references. This catalog entry helps agents discover the skill; the complete workflow requires installing the upstream bundle.

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• Creating UI mockup images
• Generating icons and illustrations
• Preparing social card images

Ask AI questions, generate code, and summarize text through 9Router using OpenAI or Anthropic request formats. Receive responses incrementally with streaming, and use provider combinations that automatically try another provider when needed.

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• Ask an AI model questions through 9Router
• Generate code from written instructions
• Summarize text with a selected model

Add Codex as the agent that plans tasks and coordinates tools in NanoClaw. Choose it for individual groups alongside Claude, with conversation history and session resume using a ChatGPT subscription or OpenAI API key.

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• Adding Codex as a NanoClaw agent provider
• Choosing Claude or Codex for each group
• Setting up ChatGPT or API key authentication

Build and troubleshoot ChatGPT apps with an MCP server that exposes tools and an optional interactive widget. Use current official documentation and examples to create scaffolds, configure security settings, and guide local validation and deployment when requested.

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• Create a ChatGPT app scaffold from an official example
• Design tools and connect an MCP server to a widget
• Refactor or troubleshoot an existing Apps SDK app

Turn speech from audio or video recordings into text using OpenAI. Save transcripts as text or JSON, with optional speaker labels and reference recordings to help identify known speakers in meetings or interviews.

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• Transcribe recorded meetings
• Label speakers in interviews
• Extract spoken text from audio or video

Improve research through up to four rounds of external language model review, fixes, and reassessment. Use an OpenAI-compatible API to identify weaknesses, prioritize changes, and keep a cumulative record of reviewer responses, actions, and experiment results.

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• Identify weaknesses before submitting research
• Revise research using an external model's feedback
• Track review scores, changes, and experiment results

Find and run local AI models with llama.cpp. Choose GGUF model files and quantization levels that fit available memory, launch a command line session or local server, and test an OpenAI-compatible API on your computer.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find models to run on a local computer
• Choose quantization for available memory
• Launch and test a local OpenAI-compatible API

Build, refactor, and troubleshoot ChatGPT apps with an MCP server, which exposes tools to the assistant, and an interactive widget. Use official documentation and examples to plan tools, scaffold code, configure security settings, and validate local operation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Scaffolding a ChatGPT app with a server and widget
• Planning app tools and their inputs
• Refactoring an existing Apps SDK demo

Azure OpenAI is Microsoft's hosted service for OpenAI models (GPT, gpt-image, Whisper, embeddings) on Azure infrastructure. Use when calling OpenAI models through Azure, authenticating with Managed Identity or Entra ID, setting up content filters, or deploying with enterprise compliance, regional data residency or private networking.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Azure OpenAI SDK for .NET. Client library for Azure OpenAI and OpenAI services. Use for chat completions, embeddings, image generation, audio transcription, and assistants. Triggers: "Azure OpenAI", "AzureOpenAIClient", "ChatClient", "chat completions .NET", "GPT-4", "embeddings", "DALL-E", "Whis...

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OpenAI Apps SDK / ChatGPT plugins (developers.openai.com/plugins) のリファレンス。 ChatGPT 内アプリを MCP サーバーとして公開する側の API。 window.openai, useOpenAiGlobal, registerAppTool, ui://widget, _meta, openai/outputTemplate, OAuth, plugin.json / mcp.json (Agent Plugins), MCP Events, Plugin Extensions, Checkout API, 接続テスト・審査・申請。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

여러 관점으로 정리한 중요한 의사결정 초안에 Codex의 외부 비평을 한 차례 추가합니다. 결론의 약점, 누락된 실패 가능성, 반대 의견의 반영 여부를 확인합니다.

• 판단이 어려운 중요 초안 검토
• 초안에 빠진 실패 가능성 확인
• 강한 반대 의견의 누락 확인

Delegate feature development, code refactoring, and pull request reviews to OpenAI Codex CLI. The skill also covers monitoring long tasks and fixing multiple issues in parallel using separate Git working directories.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding a feature to an existing project
• Refactoring an authentication module
• Reviewing proposed code changes

Connect AI agents to OmniRoute for text and image generation, speech synthesis, transcription, and web search. Use OpenAI-compatible APIs and create embeddings, numerical representations of text, through documented requests.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add text generation to an AI agent
• Generate or edit images from instructions
• Turn text into speech or transcribe audio

Helps design focused AI products built on APIs such as OpenAI and Anthropic. Covers product strategy, prompts, model selection, user experience, usage tracking, and cost management for tools aimed at solving specific customer problems.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning an AI SaaS product for a specific problem
• Designing prompts for product features
• Balancing model choices, costs, and user experience

Build voice applications and phone agents with guidance on OpenAI Realtime API, Vapi, Deepgram, ElevenLabs, and LiveKit. Choose services for speech recognition, voice generation, and live communication, while addressing response delays and interruptions.

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• Build a voice assistant that responds in real time
• Create a phone support agent with Vapi
• Connect speech recognition and voice generation

Set up Langfuse to record LLM application activity, costs, and response times. Manage prompt versions, organize evaluation datasets, and compare results to investigate failures and guide improvements using recorded evidence.

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• Investigating failures in LLM applications
• Comparing prompt versions and evaluation scores
• Monitoring LLM costs and response times

Add OpenCode as an agent runtime in NanoClaw to use models from OpenAI, Google, OpenRouter, DeepSeek, and other supported services. The skill covers installation, authentication, group selection, and default model changes.

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• Adding OpenCode to an existing NanoClaw installation
• Switching an agent group to OpenCode
• Changing the default model without signing in again

Call Gemini and OpenMaaS models such as Llama, DeepSeek, and Qwen through Google Cloud Agent Platform. Prepare authentication and SDK code, run prompts, configure connection endpoints, and troubleshoot common request errors.

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• Send a test prompt to Gemini
• Call Llama or DeepSeek with the OpenAI SDK
• Write code to call an existing custom endpoint

Guides you through running large language models on CPUs, Apple Silicon, and AMD or Intel GPUs. Covers choosing GGUF model files, reducing memory through quantization, and starting an OpenAI-compatible chat server.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Running a local LLM on an Apple Silicon Mac
• Trying LLM inference on a CPU-only machine
• Choosing a model format that fits available memory

Guide for ingesting the latest OpenAI TypeSpec specification into the openai-dotnet SDK. Use this when asked to update or ingest OpenAI API specs, copy base TypeSpec files from upstream, fix client TSP compile errors, or run code generation for new API areas.

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