> ## Documentation Index > Fetch the complete documentation index at: https://agno-v2-update-deprecated-models.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Running Teams > Execute teams with Team.run() and process their output. Run your team with `Team.run()` (sync) or `Team.arun()` (async). ## Basic Execution ```python theme={null} from agno.team import Team from agno.agent import Agent from agno.models.openai import OpenAIResponses from agno.tools.hackernews import HackerNewsTools from agno.tools.yfinance import YFinanceTools from agno.utils.pprint import pprint_run_response news_agent = Agent(name="News Agent", role="Get tech news", tools=[HackerNewsTools()]) finance_agent = Agent(name="Finance Agent", role="Get stock data", tools=[YFinanceTools()]) team = Team( name="Research Team", members=[news_agent, finance_agent], model=OpenAIResponses(id="gpt-4o") ) # Run and get response response = team.run("What are the trending AI stories?") print(response.content) # Run with streaming stream = team.run("What are the trending AI stories?", stream=True) for chunk in stream: print(chunk.content, end="", flush=True) ``` ## Execution Flow When you call `run()`: 1. **Pre-hooks execute** (if configured) 2. **Reasoning runs** (if enabled) to plan the task 3. **Context is built** with system message, history, memories, and session state 4. **Model decides** whether to respond directly, use tools, or delegate to members 5. **Members execute** their tasks (concurrently in async mode) 6. **Leader synthesizes** member results into a final response 7. **Post-hooks execute** (if configured) 8. **Session and metrics are stored** (if database configured) In `TeamMode.tasks`, the leader uses task management tools to build and execute a shared task list, looping until the goal is complete or `max_iterations` is reached. Teams can pause for human-in-the-loop requirements (e.g., approvals or user input). When a run requires confirmation, the run returns with pending requirements so you can collect input or resolve approvals before continuing. Team execution flow Team execution flow ## Streaming Enable streaming with `stream=True`. This returns an iterator of events instead of a single response. ```python theme={null} stream = team.run("What are the top AI stories?", stream=True) for chunk in stream: print(chunk.content, end="", flush=True) ``` Streaming is not supported in `TeamMode.tasks`. If you set `stream=True`, the run falls back to non-streaming execution. ### Stream All Events By default, only content is streamed. Set `stream_events=True` to get tool calls, reasoning steps, and other internal events: ```python theme={null} stream = team.run( "What are the trending AI stories?", stream=True, stream_events=True ) for event in stream: if event.event == TeamRunEvent.run_content: print(event.content, end="", flush=True) elif event.event == TeamRunEvent.tool_call_started: print(f"Tool call started") elif event.event == TeamRunEvent.tool_call_completed: print(f"Tool call completed") ``` ### Stream Member Events When using `arun()` with multiple members, they execute concurrently. Member events arrive as they happen, not in order. Disable member event streaming with `stream_member_events=False`: ```python theme={null} team = Team( name="Research Team", members=[news_agent, finance_agent], model=OpenAIResponses(id="gpt-4o"), stream_member_events=False ) ``` ## Run Output `Team.run()` returns a `TeamRunOutput` object containing: | Field | Description | | ------------------ | --------------------------------- | | `content` | The final response text | | `messages` | All messages sent to the model | | `metrics` | Token usage, execution time, etc. | | `member_responses` | Responses from delegated members | See [TeamRunOutput reference](/reference/teams/team-response) for the full schema. ## Async Execution Use `arun()` for async execution. Members run concurrently when the leader delegates to multiple members at once. ```python theme={null} import asyncio async def main(): response = await team.arun("Research AI trends and stock performance") print(response.content) asyncio.run(main()) ``` ## Tasks Mode Tasks mode runs an iterative loop that creates, executes, and updates tasks until the goal is complete. ```python theme={null} from agno.team.mode import TeamMode from agno.models.openai import OpenAIResponses team = Team( name="Ops Team", members=[news_agent, finance_agent], model=OpenAIResponses(id="gpt-4o"), mode=TeamMode.tasks, max_iterations=6 ) response = team.run("Compile a short report on recent AI agent frameworks.") print(response.content) ``` ## Specifying User and Session Associate runs with a user and session for history tracking: ```python theme={null} team.run( "Get my monthly report", user_id="john@example.com", session_id="session_123" ) ``` See [Sessions](/sessions/overview) for details. ## Passing Files Pass images, audio, video, or files to the team: ```python theme={null} from agno.media import Image team.run( "Analyze this image", images=[Image(url="https://example.com/image.jpg")] ) ``` See [Multimodal](/multimodal/overview) for details. ## Structured Output Pass an output schema to get structured responses: ```python theme={null} from pydantic import BaseModel class Report(BaseModel): overview: str findings: list[str] response = team.run("Analyze the market", output_schema=Report) ``` See [Input & Output](/input-output/overview) for details. ## Cancelling Runs Cancel a running team with `Team.cancel_run()`. See [Run Cancellation](/run-cancellation/overview). ## Print Response For development, use `print_response()` to display formatted output: ```python theme={null} team.print_response("What are the top AI stories?", stream=True) # Show member responses too team.print_response("What are the top AI stories?", show_members_responses=True) ``` ### Core Events | Event | Description | | ------------------------- | -------------------------- | | `TeamRunStarted` | Run started | | `TeamRunContent` | Response text chunk | | `TeamRunContentCompleted` | Content streaming complete | | `TeamRunCompleted` | Run completed successfully | | `TeamRunError` | Error occurred | | `TeamRunCancelled` | Run was cancelled | ### Tool Events | Event | Description | | ----------------------- | ------------------- | | `TeamToolCallStarted` | Tool call started | | `TeamToolCallCompleted` | Tool call completed | ### Reasoning Events | Event | Description | | ------------------------ | --------------------- | | `TeamReasoningStarted` | Reasoning started | | `TeamReasoningStep` | Single reasoning step | | `TeamReasoningCompleted` | Reasoning completed | ### Memory Events | Event | Description | | --------------------------- | ----------------------- | | `TeamMemoryUpdateStarted` | Memory update started | | `TeamMemoryUpdateCompleted` | Memory update completed | ### Hook Events | Event | Description | | ----------------------- | ------------------- | | `TeamPreHookStarted` | Pre-hook started | | `TeamPreHookCompleted` | Pre-hook completed | | `TeamPostHookStarted` | Post-hook started | | `TeamPostHookCompleted` | Post-hook completed | ## Developer Resources * [Team reference](/reference/teams/team) * [TeamRunOutput schema](/reference/teams/team-response) * [Team examples](/cookbook/teams/overview)