Summary
Hosted/server OpenBot deployments need administrator-controlled model and reasoning-effort settings in the web UI, with optional overrides per built-in coworker and per task.
This request is specifically for the browser-accessed Hosted/server product, rather than the Desktop setup flow.
Current behaviour
A Hosted OpenBot deployment can select a shared model through deployment configuration such as BOT_MODEL. Built-in coworkers inherit that shared runtime model.
The Hosted UI currently does not let an administrator or user:
- view or change the deployment's default chat model and reasoning effort;
- assign a different model or effort to an individual built-in coworker;
- select an allowed model or effort when starting a task or conversation; or
- see which model and effort actually handled a run.
Existing work covers parts of this problem but not the Hosted UI or all harnesses:
The Python agent-langgraph-agui harness used by the ChatGPT-plan path does not currently expose the same reasoning-effort control added to the TypeScript Responses API Bot.
Requested behaviour
Add Hosted/server model controls with this resolution order:
- task or conversation override;
- built-in coworker override;
- Hosted deployment default;
- provider default.
Hosted administration
Provide an Admin setting for the default provider, model and reasoning effort. The page should show the effective values and whether each value comes from Hosted configuration or the provider default.
Administrators should be able to define an allow-list of models and effort levels available to users. Credentials must remain server-side and must never be returned to the browser.
Per-coworker settings
Add optional model and reasoning-effort fields to built-in coworker configuration. Leaving either field unset should inherit the Hosted deployment default.
Remote AG-UI and Mastra coworkers should continue to report that their endpoint owns model selection unless OpenBot has a truthful capability contract for changing it.
Per-task settings
When starting a task or conversation, let the user choose from the administrator-approved models and effort levels. Existing conversations should show their effective selection, and changing it should apply only to subsequent runs.
An optional administrator-defined routing policy could select a model or effort from task characteristics, but the chosen effective values must remain visible and auditable.
Harness support
Pass model and effort settings through every supported Hosted harness that can honour them, including agent-langgraph-agui when it is using a ChatGPT plan. Unsupported provider/model/effort combinations should be rejected before a run with a clear explanation rather than silently ignored.
Acceptance criteria
- A Hosted administrator can set and change the deployment-wide default model and reasoning effort from the web UI.
- A built-in coworker can inherit those defaults or define an approved override.
- A user can select an approved model and effort for a task or conversation.
- The effective provider, model and effort are displayed for each run and recorded in the audit trail.
- The same settings are available through the server API for managed deployments.
agent-langgraph-agui forwards supported effort settings on the ChatGPT-plan path.- Invalid or unsupported combinations fail before inference with an actionable error.
- Existing deployments retain their current behaviour when no new settings are configured.
Why this matters
Different work has different latency, capability and cost requirements. Routine classification or drafting may suit a faster model and lower effort, while research, planning or infrastructure work may require a stronger model and higher effort. Hosted OpenBot already lets organisations define specialised coworkers and govern their tools; model and effort policy should be governed at the same levels rather than requiring environment-file edits and container recreation for the whole deployment.
Summary
Hosted/server OpenBot deployments need administrator-controlled model and reasoning-effort settings in the web UI, with optional overrides per built-in coworker and per task.
This request is specifically for the browser-accessed Hosted/server product, rather than the Desktop setup flow.
Current behaviour
A Hosted OpenBot deployment can select a shared model through deployment configuration such as
BOT_MODEL. Built-in coworkers inherit that shared runtime model.The Hosted UI currently does not let an administrator or user:
Existing work covers parts of this problem but not the Hosted UI or all harnesses:
BOT_REASONING_EFFORTfor the TypeScriptagent-langgraphResponses API Bot.The Python
agent-langgraph-aguiharness used by the ChatGPT-plan path does not currently expose the same reasoning-effort control added to the TypeScript Responses API Bot.Requested behaviour
Add Hosted/server model controls with this resolution order:
Hosted administration
Provide an Admin setting for the default provider, model and reasoning effort. The page should show the effective values and whether each value comes from Hosted configuration or the provider default.
Administrators should be able to define an allow-list of models and effort levels available to users. Credentials must remain server-side and must never be returned to the browser.
Per-coworker settings
Add optional model and reasoning-effort fields to built-in coworker configuration. Leaving either field unset should inherit the Hosted deployment default.
Remote AG-UI and Mastra coworkers should continue to report that their endpoint owns model selection unless OpenBot has a truthful capability contract for changing it.
Per-task settings
When starting a task or conversation, let the user choose from the administrator-approved models and effort levels. Existing conversations should show their effective selection, and changing it should apply only to subsequent runs.
An optional administrator-defined routing policy could select a model or effort from task characteristics, but the chosen effective values must remain visible and auditable.
Harness support
Pass model and effort settings through every supported Hosted harness that can honour them, including
agent-langgraph-aguiwhen it is using a ChatGPT plan. Unsupported provider/model/effort combinations should be rejected before a run with a clear explanation rather than silently ignored.Acceptance criteria
agent-langgraph-aguiforwards supported effort settings on the ChatGPT-plan path.Why this matters
Different work has different latency, capability and cost requirements. Routine classification or drafting may suit a faster model and lower effort, while research, planning or infrastructure work may require a stronger model and higher effort. Hosted OpenBot already lets organisations define specialised coworkers and govern their tools; model and effort policy should be governed at the same levels rather than requiring environment-file edits and container recreation for the whole deployment.