ChatGPT: Managing request and response roles with advanced schema orchestration

Graziano Stefanelli
Aug 26
3 min read

The latest updates to ChatGPT’s API introduce refined role management and advanced schema orchestration capabilities. These improvements make handling structured conversations, integrating external tools, and returning machine-readable outputs more reliable for developers and enterprise workflows. With better role definitions, strict response enforcement, and segmentation options, multi-step automation and dynamic user interactions are becoming more robust.

Role management in ChatGPT has been redesigned.

The request-response system now operates on a streamlined set of officially recognized roles that control how information flows through the conversation. These roles are system, user, assistant, tool, and function, each serving a distinct purpose.

Older experimental mentions of image, file, or api roles have not been implemented. Instead, image inputs are handled directly inside user messages via the image_url object, ensuring full compatibility without introducing additional roles.

Role	Purpose	Key Notes
system	Sets overall behavior and context for the session	Applied at the beginning of every request
user	Provides input prompts, questions, or data	Supports text, image, and file URLs
assistant	Returns responses generated by ChatGPT	Handles both free-form and structured outputs
tool	Represents an external function/tool invoked by the model	Integrates third-party APIs or services
function	Returns the results of a specific tool call	Enables function chaining and task orchestration

This structure brings greater consistency in scenarios involving multiple inputs, third-party calls, or mixed modalities.

Segmented responses improve multi-role conversations.

A new segmentation feature provides developers with an ordered array of {role, content} objects when enabled via segmented:true. This improves reliability in workflows where messages come from different roles in the same session, making it easier to separate:

User queries
Model-generated summaries
Function call outputs
External API responses

By default, responses are returned as a single unified message. With segmentation enabled, the API maintains strict ordering for all role outputs, improving integration with multi-agent architectures and downstream logging.

Schema orchestration enforces structured outputs.

ChatGPT now provides stronger schema enforcement for applications requiring predictable, machine-readable responses. Developers can define a JSON Schema and use the response_format:"json_schema" parameter.

Key updates include:

Limit / Feature	Current Value	Notes
Schema size limit	32,000 bytes	Reduced from older unofficial reports of 40,000
Max properties	128	Ensures stability for large structures
Nesting depth	3 levels	Helps avoid memory bottlenecks
Strict mode (strict:true)	Enforced retries	GPT-5 retries up to two times to guarantee JSON compliance

This strict mode is exclusive to GPT-5, whereas GPT-4o attempts best-effort validation without retries. When combined with segmentation, schema outputs can now be aligned directly with corresponding tool calls or user instructions.

Parallel tool calls and orchestration improvements.

The API supports parallel tool calling to speed up workflows involving multiple external services. At present, GPT-5 allows 10 concurrent tool calls per request, while an upcoming Enterprise configuration scheduled for release later this year will increase this limit to 25 parallel calls.

Additionally, Secure-Fetch headers have been introduced for tool calls, adding a SHA-256 checksum and 24-hour signed URLs to improve reliability and data integrity when working with sensitive APIs.

Context limits and performance consistency have expanded.

GPT-5 maintains an extended context window of up to 128,000 tokens per request, shared across messages and schemas. This higher limit allows developers to handle multi-step workflows, multi-document conversations, and larger datasets in a single session without truncation issues.

When combined with segmented roles and enforced schemas, this provides more predictable outputs, even in advanced use cases involving file parsing, structured reporting, and live tool orchestration.

Key takeaways for developers.

Roles are streamlined to five supported types: system, user, assistant, tool, function.
Segmented responses give granular control for multi-agent and multi-step tasks.
Schema orchestration now includes strict retry logic in GPT-5 for higher reliability.
Parallel tool calls are supported, with Enterprise expansions planned.
Secure-Fetch integration strengthens data protection and workflow stability.

These updates make ChatGPT’s API a more consistent and developer-friendly environment for advanced applications where multiple roles, structured outputs, and dynamic orchestration are required.

____________

DATA STUDIOS

datastudios.org