Text Generation
Multimodal Responses API
POST
Documentation Index
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- Fully compatible with the OpenAI Responses API format
- Supports multimodal input (text and images)
- Supports tool extensions: web search, file search, function calling, remote MCP
Authorizations
All endpoints require Bearer Token authentication.Get your API Key:Visit the API Key management page to obtain your API Key.Add it to the request header:
Body
Model name.Supported models include:
gpt-5— GPT-5 base modelgpt-5-pro— GPT-5 Pro (this endpoint only)gpt-5-codex— GPT-5 Codex code model (this endpoint only)gpt-5.1-codex— GPT-5.1 Codex code model (this endpoint only)gpt-5.1-codex-mini— GPT-5.1 Codex Mini (this endpoint only)gpt-5.2-codex— GPT-5.2 Codex code model (this endpoint only)gpt-5.3-codex— GPT-5.3 Codex code model (this endpoint only)- Plus every model supported by
/v1/chat/completions
gpt-5-pro and all Codex models are only available on this endpoint (/v1/responses). They are not supported on /v1/chat/completions.Input content. Accepts a string or an array of messages.A string is treated as plain text input; the array form supports multi-turn conversations and multimodal content:
Tool list (optional).Supported tool types:
web_search— Web searchfile_search— File searchfunction— Function callingremote_mcp— Remote MCP service
Controls output randomness, range 0–2.Default: 1.0
Maximum number of tokens to generate.
Whether to use streaming output.Default: false
Response
Unique identifier of the response.
Object type, always
response.Creation timestamp.
Name of the model that actually served the request (e.g.,
gpt-5-2025-08-07).Response status.Possible values:
completed— Donein_progress— Processingfailed— Failedcancelled— Cancelled
Output content array.
Token usage statistics.
Reasoning configuration (thinking models only).
The sampling temperature actually used.
The nucleus sampling parameter actually used.
Tool selection strategy.
List of tools used.
Whether parallel tool calls are allowed.
Whether the conversation history is stored.
Service tier.
Truncation strategy.
Text format configuration.
Whether this is a background task.
Error info, if any.
Metadata.
Examples
Image analysis
Video analysis
Using the web search tool
Using function calling
Content Types
input_text
Text input. Properties:type: always"input_text"text: text content (string)
input_image
Image input. Properties:type: always"input_image"image_url: image URL or base64-encoded data URI
- JPEG
- PNG
- GIF
- WebP
- Max file size: 20MB
- Recommended resolution: up to 2048x2048 pixels
input_video
Video input (supported by some models). Properties:type: always"input_video"video_url: video URL
- MP4
- MOV
- AVI
- WebM
- Max file size: 200MB
- Max duration: 10 minutes
- Recommended resolution: 1080p
Tools in Detail
Web search
The web search tool gives the model access to real-time information from the internet. Configuration example:- Latest news and current events
- Real-time data (stocks, weather, exchange rates, etc.)
- Latest technical docs and references
- Fact verification
File search
The file search tool lets the model search through documents you have uploaded. Configuration example:- Analyzing internal company documents
- Searching technical specifications and manuals
- Querying contracts and legal documents
- Knowledge-base Q&A systems
Function calling
Define custom functions so the model can call external APIs or perform specific actions. Full configuration example:name: function name (required)description: function description (required)parameters: parameter definitions in JSON Schema formattype: parameter typeproperties: parameter property definitionsrequired: list of required parameters
- Calling third-party APIs
- Running database queries
- Triggering business workflows
- Integrating with internal systems
Remote MCP
Connect to a remote Model Context Protocol (MCP) service to extend the model’s capabilities. Configuration example:url: MCP server URL (required)auth_token: authentication token (optional)timeout: timeout in seconds, default 30
- Connecting to enterprise AI services
- Using domain-specific models
- Accessing protected data sources
- Integrating distributed AI systems
Tool Response Format
When the model uses a tool, the response includes tool call information:- The model receives user input
- Decides whether a tool is needed
- If yes, returns a tool call request
- The client executes the tool call
- The result is returned to the model
- The model produces the final response
Notes
-
Image URL requirements:
- Must be a publicly accessible URL
- Or use a base64-encoded data URI
-
Token billing:
- Images consume tokens based on resolution
- High-resolution images are auto-resized to optimize cost
- Tool calls also consume additional tokens
-
Content order:
- The order of items in the content array affects how the model interprets them
- We recommend placing the text instruction first, followed by images/videos
-
Multimodal mixing:
- A single request can mix multiple text and image inputs
- Multi-turn conversations preserve context
-
Tool usage limits:
- When multiple tools are available, the model picks the most appropriate one
- Function calling requires explicit function and parameter definitions
- Web search results may be subject to regional and time limits
-
API compatibility:
- Fully compatible with the OpenAI Responses API format
- Existing OpenAI code can be migrated seamlessly
- Supports all OpenAI tool extensions