> ## Documentation Index > Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # TeamFactory > Build a Team per request whose members, model, and instructions depend on the caller. v2.6.0 (Introduced in v2.6.0) A `TeamFactory` produces a fresh `Team` for each request. Register it in `AgentOS(teams=[...])` alongside any prototype teams. ```python basic_team_factory.py theme={null} from agno.agent import Agent from agno.db.sqlite import SqliteDb from agno.factory import RequestContext from agno.models.openai import OpenAIResponses from agno.os import AgentOS from agno.team import Team, TeamFactory db = SqliteDb(db_file="tmp/team_factory.db") def build_support_team(ctx: RequestContext) -> Team: user_id = ctx.user_id or "anonymous" billing_agent = Agent( name="Billing Agent", role="Handle billing inquiries", model=OpenAIResponses(id="gpt-5.4"), instructions=f"You handle billing questions for tenant {user_id}. Be concise.", ) tech_agent = Agent( name="Tech Support Agent", role="Handle technical issues", model=OpenAIResponses(id="gpt-5.4"), instructions=f"You handle technical support for tenant {user_id}. Be concise.", ) return Team( name="Support Team", model=OpenAIResponses(id="gpt-5.4"), members=[billing_agent, tech_agent], db=db, instructions=[ f"You are the support team leader for tenant {user_id}.", "Route billing questions to the Billing Agent and technical issues to the Tech Support Agent.", ], markdown=True, ) support_team_factory = TeamFactory( id="support-team", db=db, factory=build_support_team, name="Per-tenant Support Team", description="Builds a support team with billing and tech agents per tenant.", ) agent_os = AgentOS(teams=[support_team_factory], db=db) app = agent_os.get_app() if __name__ == "__main__": agent_os.serve(app="basic_team_factory:app", port=7777, reload=True) ``` ## Run the Example **1. Install dependencies** ```bash theme={null} uv pip install -U "agno[os,openai]" ``` **2. Export your OpenAI API key** ```bash Mac/Linux theme={null} export OPENAI_API_KEY="your_openai_api_key_here" ``` ```powershell Windows theme={null} $Env:OPENAI_API_KEY="your_openai_api_key_here" ``` **3. Start AgentOS** Save the code above as `basic_team_factory.py`, then run: ```bash theme={null} python basic_team_factory.py ``` **4. Run the team** In another terminal, run: ```bash theme={null} curl -X POST http://localhost:7777/teams/support-team/runs \ -F 'message=I need help with billing and a technical issue' \ -F 'user_id=tenant_42' \ -F 'stream=false' ``` See the [Factories reference](https://agno-v2.mintlify.site/reference/agent-os/factories.md) for the full constructor signature and parameter list. ## Members That Scale with the Caller Member composition can change per request. A common pattern: scale team size and model quality with a subscription tier from `ctx.trusted.claims`. ```python theme={null} def build_research_team(ctx: RequestContext) -> Team: tier = ctx.trusted.claims.get("tier", "free") model_id = TIER_MODELS.get(tier, "gpt-4.1-mini") members = [researcher(model_id), writer(model_id)] if tier == "enterprise": members.append(reviewer(model_id)) return Team(name="Research Team", model=OpenAIResponses(id=model_id), members=members, db=db) ``` The `tier` claim comes from verified middleware, so the `tier` cannot be changed by the request body. See [Authorization From Verified Context](https://agno-v2.mintlify.site/agent-os/factories/agent-factory.md#authorization-from-verified-context) for the trust model and [JWT Role Factory](https://agno-v2.mintlify.site/examples/agent-os/factories/jwt-role-factory.md) for an end-to-end JWT example. ## Async Factories Use an async callable when you need to fetch context from a database, an HTTP service, or any other awaitable resource. ```python async_team_factory.py theme={null} async def build_team(ctx: RequestContext) -> Team: members = await load_members_for_tenant(ctx.user_id) return Team( name="Tenant Team", model=OpenAIResponses(id="gpt-5.4"), members=members, db=db, ) team_factory = TeamFactory(id="tenant-team", db=db, factory=build_team) ``` ## With an Input Schema Declare a Pydantic model on the factory to validate client-supplied `factory_input` before the factory runs. ```python team_factory_input.py theme={null} from pydantic import BaseModel class TeamConfig(BaseModel): include_reviewer: bool = False def build_team(ctx: RequestContext) -> Team: cfg: TeamConfig = ctx.input members = [researcher, writer] if cfg.include_reviewer: members.append(reviewer) return Team(name="Research", model=OpenAIResponses(id="gpt-5.4"), members=members, db=db) team_factory = TeamFactory( id="research-team", db=db, factory=build_team, input_schema=TeamConfig, ) ``` > [!NOTE] > > `AgentFactory` and `TeamFactory` instances cannot be passed inside `members`. Build per-member customization inside the team's factory. ## Error Handling Raise `FactoryPermissionError` from inside the factory to reject unauthorized callers with HTTP 403. AgentOS raises `FactoryValidationError` (400) automatically when `factory_input` fails `input_schema` validation. ```python theme={null} from agno.factory import FactoryPermissionError def build_team(ctx: RequestContext) -> Team: if "teams:run" not in ctx.trusted.scopes: raise FactoryPermissionError("Missing 'teams:run' scope") ... ``` See the [Factories reference](https://agno-v2.mintlify.site/reference/agent-os/factories.md) for the full exception hierarchy and the post-resolve behavior. ## Developer Resources * [Factories overview](https://agno-v2.mintlify.site/agent-os/factories/overview.md) * [RequestContext fields](https://agno-v2.mintlify.site/reference/agent-os/factories.md#requestcontext) * [Factories reference](https://agno-v2.mintlify.site/reference/agent-os/factories.md) * [Factory examples](https://agno-v2.mintlify.site/examples/agent-os/factories/overview.md) This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.