#let me ask a few random questions.

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violet moon
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hello

unkempt fieldBOT
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Hi @violet moon. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:

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Hello! I'm here to help answer questions about OpenAI. Feel free to ask away — just keep in mind that I'm specialized in OpenAI-related topics, so I'll do my best to assist with anything in that area!

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

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@violet moon Kapa.ai is still learning and improving, please let me know how I did by reacting below.

violet moon
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@unkempt field can the Codex desktop IDE use OpenAI API keys directly, or does it depend on the signed-in OpenAI account session?

unkempt fieldBOT
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Let me check the knowledge base for you again. One moment! :books:

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Yes, the Codex desktop app (and CLI/IDE extension) supports both authentication methods — you don't have to rely solely on a signed-in ChatGPT account session:

  1. Sign in with ChatGPT – Opens a browser OAuth flow and uses your ChatGPT subscription credits. This is required for features like Codex cloud threads and "fast mode." [Codex Auth]

  2. Sign in with an API key – You supply an OpenAI API key directly (obtainable from the OpenAI dashboard). Usage is then billed through your OpenAI Platform account at standard API rates. [Codex Auth]

A few caveats when using an API key:

  • Features that rely on ChatGPT credits (e.g., fast mode, cloud threads) are not available — Codex falls back to standard API pricing instead. [Codex Auth; Codex App]
  • For programmatic/CI-CD workflows, OpenAI recommends using API key authentication. [Codex Auth]

So in short: the Codex desktop app is not locked to a ChatGPT account session — it can use an OpenAI API key directly, though with some feature limitations.

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

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@violet moon Kapa.ai is still learning and improving, please let me know how I did by reacting below.

violet moon
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@unkempt field what official OpenAI docs or products should someone study first if they want an AI to use browser tools and other external tools well?

unkempt fieldBOT
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Let me check the knowledge base for you again. One moment! :books:

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Based on the knowledge sources, here's a focused reading path for someone who wants an AI to use browser/web tools and other external tools effectively:

Start with the Core Platform Concepts

  1. Tools overview – Get a high-level map of every tool type available (web search, file search, code interpreter, shell, computer use, image generation, MCP, function calling, etc.). [Available Tools]

  2. Responses API – This is the recommended API for all new agentic projects. It's "agentic by default," supports built-in tools natively, and lets the model call multiple tools within a single request. [Migrate to Responses]

  3. Built-in tools deployment guide – Explains why to prefer built-in tools: OpenAI models are specifically trained and evaluated around these tool shapes, leading to better tool selection and fewer failures. [Leverage Built-in Tools]

Then Study the Agents SDK

  1. Agents SDK documentation – Covers orchestration, tool execution, handoffs, guardrails, and state management for multi-step agentic workflows. [Agents SDK]

  2. SDK Tools reference – Specifically covers WebSearchTool, FileSearchTool, CodeInterpreterTool, HostedMCPTool, ImageGenerationTool, ShellTool, ComputerTool, and function tools in one place. [SDK Tools]

For External Service Integration

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  1. MCP (Model Context Protocol) guide – If you want the AI to connect to external services (APIs, databases, third-party tools), MCP is the recommended approach. It reduces latency by letting the model communicate directly with remote tool servers instead of routing everything through your backend. [MCP Tool Guide]

  2. Function calling guide – For custom tools that don't fit a hosted pattern, function calling lets you wrap any external API or logic as a tool the model can invoke. [Function Calling]

Suggested Order

Tools overview → Responses API → Agents SDK → SDK Tools reference → MCP guide → Function calling

This path moves from "what exists" to "how to wire it all together," which is the most efficient route to building agents that use browser and external tools well.

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

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@violet moon Kapa.ai is still learning and improving, please let me know how I did by reacting below.

violet moon
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@unkempt field for new OpenAI agent and tool workflows, is the Responses API the recommended surface over Chat Completions right now?

unkempt fieldBOT
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Let me check the knowledge base for you again. One moment! :books:

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Yes, the Responses API is clearly the recommended surface for new agent and tool workflows. Here's the evidence:

  • Official recommendation: "While Chat Completions remains supported, Responses is recommended for all new projects." [Migrate to Responses]

  • Agentic by default: The Responses API is designed as an agentic loop, allowing the model to call multiple tools (web search, file search, code interpreter, image generation, remote MCP servers, custom functions) within a single API request — something Chat Completions cannot do natively. [Migrate to Responses]

  • Better performance with reasoning models: Reasoning models like o3, o4-mini, and GPT-5 perform measurably better on the Responses API. For example, switching to Responses with previous_response_id improved Tau-Bench Retail scores from 73.9% to 78.2%. [GPT-5 Prompting Guide]

  • Built-in tools are in-distribution: OpenAI models are specifically trained and evaluated around the Responses API's tool shapes, leading to better tool selection and fewer failures than with custom-built alternatives. [Leverage Built-in Tools]

  • Lower costs: Internal tests show 40–80% improvement in cache utilization compared to Chat Completions. [Migrate to Responses]

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  • Future-proofed: Starting with GPT-5.4, tool calling is not supported in Chat Completions with reasoning: none, making migration increasingly necessary for reasoning model workflows. [Additional Differences]

The Agents SDK also defaults to the Responses API path (OpenAIResponsesModel) as its recommended model interface. [Agents SDK Models]

In short: for any new agentic or tool-heavy workflow, the Responses API is the right choice today.

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

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@violet moon Kapa.ai is still learning and improving, please let me know how I did by reacting below.

exotic citrus
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