> For the complete documentation index, see [llms.txt](https://docs.umbraco.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.umbraco.com/ai-in-umbraco/17.latest/add-ons/agent/api/stream-agui.md). # Stream (AG-UI) Runs an agent and streams events using the [AG-UI protocol](https://docs.ag-ui.com/) over Server-Sent Events (SSE). This endpoint is designed for AG-UI-compatible clients such as CopilotKit. Use [Stream Agent](/ai-in-umbraco/17.latest/add-ons/agent/api/stream.md) if you need a simpler Microsoft.Extensions.AI stream, or [Run Agent](/ai-in-umbraco/17.latest/add-ons/agent/api/run.md) for a non-streaming JSON response. ## Request ```http POST /umbraco/ai/management/api/v1/agents/{agentIdOrAlias}/stream-agui ``` ### Path Parameters | Parameter | Type | Description | | ---------------- | ------ | ---------------------------------------------------------------------- | | `agentIdOrAlias` | string | Agent GUID, alias, or the special value `auto` for automatic selection | {% hint style="info" %} Passing the alias `auto` enables automatic agent selection based on the user's prompt and the provided AG-UI context. When using `auto`, the AG-UI context must include a surface. {% endhint %} ### Request Body The request body follows the AG-UI `RunAgentInput` shape: {% code title="AG-UI Run Request" %} ```json { "threadId": "thread-123", "runId": "run-456", "messages": [ { "id": "msg-1", "role": "user", "content": "Help me write a blog post about AI" } ], "tools": [ { "name": "insert_content", "description": "Insert content at the cursor", "parameters": { "type": "object", "properties": { "content": { "type": "string" } }, "required": ["content"] } } ], "context": [ { "description": "surface", "value": "copilot" } ], "state": null, "forwardedProps": { "toolMetadata": [ { "toolName": "insert_content", "scope": "content-write", "isDestructive": false } ] } } ``` {% endcode %} ### Request Properties | Property | Type | Required | Description | | ---------------- | ------ | -------- | -------------------------------------------------------- | | `threadId` | string | Yes | The conversation thread identifier | | `runId` | string | Yes | The run identifier | | `messages` | array | Yes | Conversation messages in AG-UI format | | `tools` | array | No | Frontend tool definitions available to the agent | | `context` | array | No | AG-UI context items (each has `description` and `value`) | | `state` | object | No | Current state as JSON | | `resume` | object | No | Resume information for continuing from an interrupt | | `forwardedProps` | object | No | Additional properties forwarded to the agent | AG-UI message `role` values are: `user`, `assistant`, `system`, `tool`, or `developer`. ## Response The endpoint returns `Content-Type: text/event-stream`. Each event is emitted as a single SSE `data:` line containing the JSON-serialized event, followed by a blank line. There is no `event:` line - the event type is embedded in the JSON payload as a `type` discriminator: ``` data: {"type":"RUN_STARTED","threadId":"thread-123","runId":"run-456"} data: {"type":"TEXT_MESSAGE_START","messageId":"msg-1","role":"assistant"} data: {"type":"TEXT_MESSAGE_CONTENT","messageId":"msg-1","delta":"Here's a"} data: {"type":"TEXT_MESSAGE_CONTENT","messageId":"msg-1","delta":" blog post"} data: {"type":"TEXT_MESSAGE_END","messageId":"msg-1"} data: {"type":"RUN_FINISHED","threadId":"thread-123","runId":"run-456"} ``` ### Event Types Event type values are UPPER\_SNAKE\_CASE and match the official AG-UI specification. | Event type | Category | Description | | ---------------------- | --------- | ---------------------------------------------------------- | | `RUN_STARTED` | Lifecycle | Agent run has begun | | `RUN_FINISHED` | Lifecycle | Agent run completed successfully | | `RUN_ERROR` | Lifecycle | Agent run failed | | `STEP_STARTED` | Lifecycle | A step within the run has begun | | `STEP_FINISHED` | Lifecycle | A step within the run has finished | | `TEXT_MESSAGE_START` | Message | Beginning of a text message | | `TEXT_MESSAGE_CONTENT` | Message | Text content delta | | `TEXT_MESSAGE_END` | Message | End of a text message | | `TEXT_MESSAGE_CHUNK` | Message | Combined message chunk | | `TOOL_CALL_START` | Tools | Tool call initiated | | `TOOL_CALL_ARGS` | Tools | Tool arguments delta | | `TOOL_CALL_END` | Tools | Tool call arguments complete | | `TOOL_CALL_RESULT` | Tools | Tool result | | `TOOL_CALL_CHUNK` | Tools | Combined tool call chunk | | `STATE_SNAPSHOT` | State | Full state snapshot | | `STATE_DELTA` | State | State change (JSON Patch) | | `MESSAGES_SNAPSHOT` | State | Full messages snapshot | | `ACTIVITY_SNAPSHOT` | Activity | Activity snapshot | | `ACTIVITY_DELTA` | Activity | Activity change | | `CUSTOM` | Special | Custom event (used for e.g. `agent_selected` in auto mode) | | `RAW` | Special | Passthrough raw event | ### Auto Agent Selection When `agentIdOrAlias` is `auto`, the stream is prepended with a `CUSTOM` event named `agent_selected` describing which agent was chosen: ``` data: {"type":"CUSTOM","name":"agent_selected","value":{"agentId":"3fa85f64-...","agentName":"Content Assistant","agentAlias":"content-assistant"}} ``` ### Error Responses HTTP-level errors are returned as problem details (not as SSE). Errors that occur during streaming are emitted as `RUN_ERROR` events in the stream. {% code title="404 Not Found" %} ```json { "type": "https://tools.ietf.org/html/rfc7231#section-6.5.4", "title": "AIAgent not found", "status": 404, "detail": "The specified agent could not be found." } ``` {% endcode %} {% code title="400 Bad Request (auto mode without surface)" %} ```json { "type": "https://tools.ietf.org/html/rfc7231#section-6.5.1", "title": "Surface is required for auto agent selection", "status": 400, "detail": "The AG-UI context must include a surface to use 'auto' agent selection." } ``` {% endcode %} ## Examples ### Consume with cURL {% code title="cURL" %} ```bash curl -N -X POST "https://your-site.com/umbraco/ai/management/api/v1/agents/content-assistant/stream-agui" \ -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \ -H "Content-Type: application/json" \ -H "Accept: text/event-stream" \ -d '{ "threadId": "thread-123", "runId": "run-456", "messages": [ { "id": "msg-1", "role": "user", "content": "Help me write a title" } ] }' ``` {% endcode %} ## Related * [Run Agent](/ai-in-umbraco/17.latest/add-ons/agent/api/run.md) - Non-streaming JSON response * [Stream Agent](/ai-in-umbraco/17.latest/add-ons/agent/api/stream.md) - Microsoft.Extensions.AI SSE stream * [Streaming](/ai-in-umbraco/17.latest/add-ons/agent/streaming.md) - AG-UI event handling details * [Frontend Tools](/ai-in-umbraco/17.latest/add-ons/agent/frontend-tools.md) - Tool definitions --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.umbraco.com/ai-in-umbraco/17.latest/add-ons/agent/api/stream-agui.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.