OpenAI

The OpenAI adapter provides access to OpenAI's models, including GPT-4o, GPT-5, image generation (DALL-E), text-to-speech (TTS), and audio transcription (Whisper).

Installation

npm install @tanstack/ai-openai

npm install @tanstack/ai-openai

Basic Usage

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Hello!" }],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Hello!" }],
});

Basic Usage - Custom API Key

typescript

import { chat } from "@tanstack/ai";
import { createOpenaiChat } from "@tanstack/ai-openai";

const adapter = createOpenaiChat(process.env.OPENAI_API_KEY!, {
  // ... your config options
});

const stream = chat({
  adapter: adapter("gpt-5.2"),
  messages: [{ role: "user", content: "Hello!" }],
});

import { chat } from "@tanstack/ai";
import { createOpenaiChat } from "@tanstack/ai-openai";

const adapter = createOpenaiChat(process.env.OPENAI_API_KEY!, {
  // ... your config options
});

const stream = chat({
  adapter: adapter("gpt-5.2"),
  messages: [{ role: "user", content: "Hello!" }],
});

Configuration

typescript

import { createOpenaiChat, type OpenAIChatConfig } from "@tanstack/ai-openai";

const config: Omit<OpenAIChatConfig, 'apiKey'> = {
  organization: "org-...", // Optional
  baseURL: "https://api.openai.com/v1", // Optional, for custom endpoints
};

const adapter = createOpenaiChat(process.env.OPENAI_API_KEY!, config);

import { createOpenaiChat, type OpenAIChatConfig } from "@tanstack/ai-openai";

const config: Omit<OpenAIChatConfig, 'apiKey'> = {
  organization: "org-...", // Optional
  baseURL: "https://api.openai.com/v1", // Optional, for custom endpoints
};

const adapter = createOpenaiChat(process.env.OPENAI_API_KEY!, config);

Example: Chat Completion

typescript

import { chat, toServerSentEventsResponse } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";

export async function POST(request: Request) {
  const { messages } = await request.json();

  const stream = chat({
    adapter: openaiText("gpt-5.2"),
    messages,
  });

  return toServerSentEventsResponse(stream);
}

import { chat, toServerSentEventsResponse } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";

export async function POST(request: Request) {
  const { messages } = await request.json();

  const stream = chat({
    adapter: openaiText("gpt-5.2"),
    messages,
  });

  return toServerSentEventsResponse(stream);
}

Example: With Tools

typescript

import { chat, toolDefinition } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { z } from "zod";

const getWeatherDef = toolDefinition({
  name: "get_weather",
  description: "Get the current weather",
  inputSchema: z.object({
    location: z.string(),
  }),
});

const getWeather = getWeatherDef.server(async ({ location }) => {
  // Fetch weather data
  return { temperature: 72, conditions: "sunny" };
});

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages,
  tools: [getWeather],
});

import { chat, toolDefinition } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { z } from "zod";

const getWeatherDef = toolDefinition({
  name: "get_weather",
  description: "Get the current weather",
  inputSchema: z.object({
    location: z.string(),
  }),
});

const getWeather = getWeatherDef.server(async ({ location }) => {
  // Fetch weather data
  return { temperature: 72, conditions: "sunny" };
});

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages,
  tools: [getWeather],
});

Model Options

OpenAI supports various provider-specific options:

typescript

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages,
  modelOptions: {
    temperature: 0.7,
    max_tokens: 1000,
    top_p: 0.9,
    frequency_penalty: 0.5,
    presence_penalty: 0.5,
    stop: ["END"],
  },
});

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages,
  modelOptions: {
    temperature: 0.7,
    max_tokens: 1000,
    top_p: 0.9,
    frequency_penalty: 0.5,
    presence_penalty: 0.5,
    stop: ["END"],
  },
});

Reasoning

Enable reasoning for models that support it (e.g., GPT-5, O3). This allows the model to show its reasoning process, which is streamed as thinking chunks:

typescript

modelOptions: {
  reasoning: {
    effort: "medium", // "none" | "minimal" | "low" | "medium" | "high"
    summary: "detailed", // "auto" | "detailed" (optional)
  },
}

modelOptions: {
  reasoning: {
    effort: "medium", // "none" | "minimal" | "low" | "medium" | "high"
    summary: "detailed", // "auto" | "detailed" (optional)
  },
}

When reasoning is enabled, the model's reasoning process is streamed separately from the response text and appears as a collapsible thinking section in the UI.

Summarization

Summarize long text content:

typescript

import { summarize } from "@tanstack/ai";
import { openaiSummarize } from "@tanstack/ai-openai";

const result = await summarize({
  adapter: openaiSummarize("gpt-5-mini"),
  text: "Your long text to summarize...",
  maxLength: 100,
  style: "concise", // "concise" | "bullet-points" | "paragraph"
});

console.log(result.summary);

import { summarize } from "@tanstack/ai";
import { openaiSummarize } from "@tanstack/ai-openai";

const result = await summarize({
  adapter: openaiSummarize("gpt-5-mini"),
  text: "Your long text to summarize...",
  maxLength: 100,
  style: "concise", // "concise" | "bullet-points" | "paragraph"
});

console.log(result.summary);

Image Generation

Generate images with DALL-E:

typescript

import { generateImage } from "@tanstack/ai";
import { openaiImage } from "@tanstack/ai-openai";

const result = await generateImage({
  adapter: openaiImage("gpt-image-1"),
  prompt: "A futuristic cityscape at sunset",
  numberOfImages: 1,
  size: "1024x1024",
});

console.log(result.images);

import { generateImage } from "@tanstack/ai";
import { openaiImage } from "@tanstack/ai-openai";

const result = await generateImage({
  adapter: openaiImage("gpt-image-1"),
  prompt: "A futuristic cityscape at sunset",
  numberOfImages: 1,
  size: "1024x1024",
});

console.log(result.images);

Image Model Options

typescript

const result = await generateImage({
  adapter: openaiImage("gpt-image-1"),
  prompt: "...",
  modelOptions: {
    quality: "hd", // "standard" | "hd"
    style: "natural", // "natural" | "vivid"
  },
});

const result = await generateImage({
  adapter: openaiImage("gpt-image-1"),
  prompt: "...",
  modelOptions: {
    quality: "hd", // "standard" | "hd"
    style: "natural", // "natural" | "vivid"
  },
});

Text-to-Speech

Generate speech from text:

typescript

import { generateSpeech } from "@tanstack/ai";
import { openaiTTS } from "@tanstack/ai-openai";

const result = await generateSpeech({
  adapter: openaiTTS("tts-1"),
  text: "Hello, welcome to TanStack AI!",
  voice: "alloy",
  format: "mp3",
});

// result.audio contains base64-encoded audio
console.log(result.format); // "mp3"

import { generateSpeech } from "@tanstack/ai";
import { openaiTTS } from "@tanstack/ai-openai";

const result = await generateSpeech({
  adapter: openaiTTS("tts-1"),
  text: "Hello, welcome to TanStack AI!",
  voice: "alloy",
  format: "mp3",
});

// result.audio contains base64-encoded audio
console.log(result.format); // "mp3"

TTS Voices

Available voices: alloy, echo, fable, onyx, nova, shimmer, ash, ballad, coral, sage, verse

TTS Model Options

typescript

const result = await generateSpeech({
  adapter: openaiTTS("tts-1-hd"),
  text: "High quality speech",
  modelOptions: {
    speed: 1.0, // 0.25 to 4.0
  },
});

const result = await generateSpeech({
  adapter: openaiTTS("tts-1-hd"),
  text: "High quality speech",
  modelOptions: {
    speed: 1.0, // 0.25 to 4.0
  },
});

Transcription

Transcribe audio to text:

typescript

import { generateTranscription } from "@tanstack/ai";
import { openaiTranscription } from "@tanstack/ai-openai";

const result = await generateTranscription({
  adapter: openaiTranscription("whisper-1"),
  audio: audioFile, // File object or base64 string
  language: "en",
});

console.log(result.text); // Transcribed text

import { generateTranscription } from "@tanstack/ai";
import { openaiTranscription } from "@tanstack/ai-openai";

const result = await generateTranscription({
  adapter: openaiTranscription("whisper-1"),
  audio: audioFile, // File object or base64 string
  language: "en",
});

console.log(result.text); // Transcribed text

Transcription Model Options

typescript

const result = await generateTranscription({
  adapter: openaiTranscription("whisper-1"),
  audio: audioFile,
  modelOptions: {
    response_format: "verbose_json", // Get timestamps
    temperature: 0,
    prompt: "Technical terms: API, SDK",
  },
});

// Access segments with timestamps
console.log(result.segments);

const result = await generateTranscription({
  adapter: openaiTranscription("whisper-1"),
  audio: audioFile,
  modelOptions: {
    response_format: "verbose_json", // Get timestamps
    temperature: 0,
    prompt: "Technical terms: API, SDK",
  },
});

// Access segments with timestamps
console.log(result.segments);

Environment Variables

Set your API key in environment variables:

OPENAI_API_KEY=sk-...

OPENAI_API_KEY=sk-...

API Reference

openaiText(config?)

Creates an OpenAI chat adapter using environment variables.

Returns: An OpenAI chat adapter instance.

createOpenaiChat(apiKey, config?)

Creates an OpenAI chat adapter with an explicit API key.

Parameters:

apiKey - Your OpenAI API key
config.organization? - Organization ID (optional)
config.baseURL? - Custom base URL (optional)

Returns: An OpenAI chat adapter instance.

openaiSummarize(config?)

Creates an OpenAI summarization adapter using environment variables.

Returns: An OpenAI summarize adapter instance.

createOpenaiSummarize(apiKey, config?)

Creates an OpenAI summarization adapter with an explicit API key.

Returns: An OpenAI summarize adapter instance.

openaiImage(config?)

Creates an OpenAI image generation adapter using environment variables.

Returns: An OpenAI image adapter instance.

createOpenaiImage(apiKey, config?)

Creates an OpenAI image generation adapter with an explicit API key.

Returns: An OpenAI image adapter instance.

openaiTTS(config?)

Creates an OpenAI TTS adapter using environment variables.

Returns: An OpenAI TTS adapter instance.

createOpenaiTTS(apiKey, config?)

Creates an OpenAI TTS adapter with an explicit API key.

Returns: An OpenAI TTS adapter instance.

openaiTranscription(config?)

Creates an OpenAI transcription adapter using environment variables.

Returns: An OpenAI transcription adapter instance.

createOpenaiTranscription(apiKey, config?)

Creates an OpenAI transcription adapter with an explicit API key.

Returns: An OpenAI transcription adapter instance.

Next Steps

Getting Started - Learn the basics
Tools Guide - Learn about tools
Other Adapters - Explore other providers

Provider Tools

OpenAI exposes several native tools beyond user-defined function calls. Import them from @tanstack/ai-openai/tools and pass them into chat({ tools: [...] }).

For the full concept, a comparison matrix, and type-gating details, see Provider Tools.

webSearchTool

Enables the model to run a web search and return grounded results with citations. Pass a WebSearchToolConfig object (typed from the OpenAI SDK) to configure the tool.

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { webSearchTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "What's new in AI this week?" }],
  tools: [webSearchTool({ type: "web_search" })],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { webSearchTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "What's new in AI this week?" }],
  tools: [webSearchTool({ type: "web_search" })],
});

Supported models: GPT-4o, GPT-5, and Responses API-capable models. See Provider Tools.

webSearchPreviewTool

The preview variant of web search with additional options for controlling search context size and user location. Use this when you want fine-grained control over the search context sent to the model.

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { webSearchPreviewTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Latest news about TypeScript" }],
  tools: [
    webSearchPreviewTool({
      type: "web_search_preview_2025_03_11",
      search_context_size: "high",
    }),
  ],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { webSearchPreviewTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Latest news about TypeScript" }],
  tools: [
    webSearchPreviewTool({
      type: "web_search_preview_2025_03_11",
      search_context_size: "high",
    }),
  ],
});

Supported models: GPT-4o and above. See Provider Tools.

fileSearchTool

Searches OpenAI vector stores that you have pre-populated, letting the model retrieve relevant document chunks. Provide the vector_store_ids to search and optionally limit results with max_num_results (1–50).

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { fileSearchTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "What does the handbook say about PTO?" }],
  tools: [
    fileSearchTool({
      type: "file_search",
      vector_store_ids: ["vs_abc123"],
      max_num_results: 5,
    }),
  ],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { fileSearchTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "What does the handbook say about PTO?" }],
  tools: [
    fileSearchTool({
      type: "file_search",
      vector_store_ids: ["vs_abc123"],
      max_num_results: 5,
    }),
  ],
});

Supported models: GPT-4o and above. See Provider Tools.

imageGenerationTool

Allows the model to generate images inline during a conversation using DALL-E/GPT-Image. Pass quality, size, and style options via the config object.

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { imageGenerationTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Draw a logo for my app" }],
  tools: [
    imageGenerationTool({
      quality: "high",
      size: "1024x1024",
    }),
  ],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { imageGenerationTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Draw a logo for my app" }],
  tools: [
    imageGenerationTool({
      quality: "high",
      size: "1024x1024",
    }),
  ],
});

Supported models: GPT-5 and GPT-Image-capable models. See Provider Tools.

codeInterpreterTool

Gives the model a sandboxed Python execution environment. The container field configures the execution environment; pass the full CodeInterpreterToolConfig object.

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { codeInterpreterTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Analyse this CSV and plot a chart" }],
  tools: [
    codeInterpreterTool({ type: "code_interpreter", container: { type: "auto" } }),
  ],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { codeInterpreterTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Analyse this CSV and plot a chart" }],
  tools: [
    codeInterpreterTool({ type: "code_interpreter", container: { type: "auto" } }),
  ],
});

Supported models: GPT-4o and above. See Provider Tools.

mcpTool

Connects the model to a remote MCP (Model Context Protocol) server, exposing all its capabilities as callable tools. Provide either server_url or connector_id — not both.

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { mcpTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "List my GitHub issues" }],
  tools: [
    mcpTool({
      server_url: "https://mcp.example.com",
      server_label: "github",
    }),
  ],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { mcpTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "List my GitHub issues" }],
  tools: [
    mcpTool({
      server_url: "https://mcp.example.com",
      server_label: "github",
    }),
  ],
});

Supported models: GPT-4o and above. See Provider Tools.

computerUseTool

Lets the model observe a virtual desktop via screenshots and interact with it using keyboard and mouse events. Provide the display dimensions and the execution environment type.

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { computerUseTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("computer-use-preview"),
  messages: [{ role: "user", content: "Open Chrome and navigate to example.com" }],
  tools: [
    computerUseTool({
      type: "computer_use_preview",
      display_width: 1024,
      display_height: 768,
      environment: "browser",
    }),
  ],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { computerUseTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("computer-use-preview"),
  messages: [{ role: "user", content: "Open Chrome and navigate to example.com" }],
  tools: [
    computerUseTool({
      type: "computer_use_preview",
      display_width: 1024,
      display_height: 768,
      environment: "browser",
    }),
  ],
});

Supported models: computer-use-preview. See Provider Tools.

localShellTool

Provides the model with a local shell for executing system commands. Takes no arguments — the tool is enabled simply by including it in the tools array.

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { localShellTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Run the test suite and summarise failures" }],
  tools: [localShellTool()],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { localShellTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Run the test suite and summarise failures" }],
  tools: [localShellTool()],
});

Supported models: GPT-5.x and other agent-capable models. See Provider Tools.

shellTool

A function-style shell tool that exposes shell execution as a structured function call. Takes no arguments.

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { shellTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Count lines in all JS files" }],
  tools: [shellTool()],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { shellTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Count lines in all JS files" }],
  tools: [shellTool()],
});

Supported models: GPT-5.x and other agent-capable models. See Provider Tools.

applyPatchTool

Lets the model apply unified-diff patches to modify files directly. Takes no arguments — include it in the tools array to enable patch application.

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { applyPatchTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Fix the import paths in src/index.ts" }],
  tools: [applyPatchTool()],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { applyPatchTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Fix the import paths in src/index.ts" }],
  tools: [applyPatchTool()],
});

Supported models: GPT-5.x and other agent-capable models. See Provider Tools.

customTool

Defines a custom Responses API tool with an explicit name, description, and format. Use this when none of the structured tool types fits your use case. Unlike branded provider tools, customTool returns a plain Tool and is accepted by any chat model.

typescript

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { customTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Look up order #1234" }],
  tools: [
    customTool({
      type: "custom",
      name: "lookup_order",
      description: "Look up the status of a customer order by order ID",
    }),
  ],
});

import { chat } from "@tanstack/ai";
import { openaiText } from "@tanstack/ai-openai";
import { customTool } from "@tanstack/ai-openai/tools";

const stream = chat({
  adapter: openaiText("gpt-5.2"),
  messages: [{ role: "user", content: "Look up order #1234" }],
  tools: [
    customTool({
      type: "custom",
      name: "lookup_order",
      description: "Look up the status of a customer order by order ID",
    }),
  ],
});

Supported models: all Responses API models. See Provider Tools.

Installation#

Basic Usage#

Basic Usage - Custom API Key#

Configuration#

Example: Chat Completion#

Example: With Tools#

Model Options#

Reasoning#

Summarization#

Image Generation#

Image Model Options#

Text-to-Speech#

TTS Voices#

TTS Model Options#

Transcription#

Transcription Model Options#

Environment Variables#

API Reference#

openaiText(config?)#

createOpenaiChat(apiKey, config?)#

openaiSummarize(config?)#

createOpenaiSummarize(apiKey, config?)#

openaiImage(config?)#

createOpenaiImage(apiKey, config?)#

openaiTTS(config?)#

createOpenaiTTS(apiKey, config?)#

openaiTranscription(config?)#

createOpenaiTranscription(apiKey, config?)#

Next Steps#

Provider Tools#

webSearchTool#

webSearchPreviewTool#

fileSearchTool#

imageGenerationTool#

codeInterpreterTool#

mcpTool#

computerUseTool#

localShellTool#

shellTool#

applyPatchTool#

customTool#

Installation

Basic Usage

Basic Usage - Custom API Key

Configuration

Example: Chat Completion

Example: With Tools

Model Options

Reasoning

Summarization

Image Generation

Image Model Options

Text-to-Speech

TTS Voices

TTS Model Options

Transcription

Transcription Model Options

Environment Variables

API Reference

openaiText(config?)

createOpenaiChat(apiKey, config?)

openaiSummarize(config?)

createOpenaiSummarize(apiKey, config?)

openaiImage(config?)

createOpenaiImage(apiKey, config?)

openaiTTS(config?)

createOpenaiTTS(apiKey, config?)

openaiTranscription(config?)

createOpenaiTranscription(apiKey, config?)

Next Steps

Provider Tools

webSearchTool

webSearchPreviewTool

fileSearchTool

imageGenerationTool

codeInterpreterTool

mcpTool

computerUseTool

localShellTool

shellTool

applyPatchTool

customTool