> ## Documentation Index > Fetch the complete documentation index at: https://phidatainc.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Agent OS Gateway > Front a single AgentOS gateway over remote AgentOS, Agno A2A, and Google ADK agents plus a local conditional story workflow. Example showing how to use an AgentOS instance as a gateway to remote agents, teams and workflows. ```python 05_agent_os_gateway.py theme={null} """ Example showing how to use an AgentOS instance as a gateway to remote agents, teams and workflows. This gateway demonstrates combining multiple remote agent sources: 1. AgentOS protocol agents (from server.py on port 7778) 2. Agno A2A protocol agents (from agno_a2a_server.py on port 7779) 3. Google ADK A2A protocol agents (from adk_server.py on port 7780) 4. Local agents and workflows Prerequisites: - Start server.py on port 7778 - Start agno_a2a_server.py on port 7779 - Start adk_server.py on port 7780 (requires GOOGLE_API_KEY) # Note: - Remote Workflows via Websocket are not yet supported - If authorization is enabled on remote servers and all endpoints are protected, not all of the functions work correctly on the gateway. Specifically /config, /workflows, /workflows/{workflow_id}, /agents, /teams, /agent/{agent_id}, /team/{team_id} need to be unprotected for the gateway to work correctly. """ from agno.agent import Agent, RemoteAgent from agno.db.postgres import PostgresDb from agno.models.openai import OpenAIChat from agno.os import AgentOS from agno.team import RemoteTeam from agno.workflow import RemoteWorkflow, Workflow from agno.workflow.agent import WorkflowAgent from agno.workflow.condition import Condition from agno.workflow.step import Step from agno.workflow.types import StepInput # --------------------------------------------------------------------------- # Create Example # --------------------------------------------------------------------------- # Setup the database db = PostgresDb(id="basic-db", db_url="postgresql+psycopg://ai:ai@localhost:5532/ai") # === SETUP ADVANCED WORKFLOW === story_writer = Agent( name="Story Writer", model=OpenAIChat(id="gpt-5.2"), instructions="You are tasked with writing a 100 word story based on a given topic", ) story_editor = Agent( name="Story Editor", model=OpenAIChat(id="gpt-5.2"), instructions="Review and improve the story's grammar, flow, and clarity", ) story_formatter = Agent( name="Story Formatter", model=OpenAIChat(id="gpt-5.2"), instructions="Break down the story into prologue, body, and epilogue sections", ) def needs_editing(step_input: StepInput) -> bool: """Determine if the story needs editing based on length and complexity""" story = step_input.previous_step_content or "" # Check if story is long enough to benefit from editing word_count = len(story.split()) # Edit if story is more than 50 words or contains complex punctuation return word_count > 50 or any(punct in story for punct in ["!", "?", ";", ":"]) def add_references(step_input: StepInput): """Add references to the story""" previous_output = step_input.previous_step_content if isinstance(previous_output, str): return previous_output + "\n\nReferences: https://www.agno.com" write_step = Step( name="write_story", description="Write initial story", agent=story_writer, ) edit_step = Step( name="edit_story", description="Edit and improve the story", agent=story_editor, ) format_step = Step( name="format_story", description="Format the story into sections", agent=story_formatter, ) # Create a WorkflowAgent that will decide when to run the workflow workflow_agent = WorkflowAgent(model=OpenAIChat(id="gpt-5.2"), num_history_runs=4) advanced_workflow = Workflow( name="Story Generation with Conditional Editing", description="A workflow that generates stories, conditionally edits them, formats them, and adds references", agent=workflow_agent, steps=[ write_step, Condition( name="editing_condition", description="Check if story needs editing", evaluator=needs_editing, steps=[edit_step], ), format_step, add_references, ], db=db, ) # Setup our AgentOS app agent_os = AgentOS( description="Gateway combining AgentOS, Agno A2A, and Google ADK agents", agents=[ # AgentOS protocol agents (from server.py on port 7778) RemoteAgent(base_url="http://localhost:7778", agent_id="assistant-agent"), RemoteAgent(base_url="http://localhost:7778", agent_id="researcher-agent"), # Agno A2A protocol agents (from agno_a2a_server.py on port 7779) RemoteAgent( base_url="http://localhost:7779/a2a/agents/assistant-agent-2", agent_id="assistant-agent-2", protocol="a2a", a2a_protocol="rest", ), RemoteAgent( base_url="http://localhost:7779/a2a/agents/researcher-agent-2", agent_id="researcher-agent-2", protocol="a2a", a2a_protocol="rest", ), # Google ADK A2A protocol agent (from adk_server.py on port 7780) RemoteAgent( base_url="http://localhost:7780", agent_id="facts_agent", protocol="a2a", a2a_protocol="json-rpc", ), # Local agents story_writer, story_editor, story_formatter, ], teams=[RemoteTeam(base_url="http://localhost:7778", team_id="research-team")], workflows=[ RemoteWorkflow(base_url="http://localhost:7778", workflow_id="qa-workflow"), advanced_workflow, ], ) app = agent_os.get_app() # --------------------------------------------------------------------------- # Run Example # --------------------------------------------------------------------------- if __name__ == "__main__": """ Run your AgentOS gateway. This gateway combines: - Remote AgentOS agents (port 7778) - Remote Agno A2A agents (port 7779) - Remote Google ADK agents (port 7780) - Local agents and workflows All accessible via a single API on port 7777. """ agent_os.serve(app="05_agent_os_gateway:app", reload=True, port=7777) ``` ## Run the Example ```bash theme={null} uv pip install -U "agno[a2a,os]" "psycopg[binary]" chromadb ddgs google-adk openai ``` ```bash Mac/Linux theme={null} export GOOGLE_API_KEY="your_google_api_key_here" export OPENAI_API_KEY="your_openai_api_key_here" ``` ```bash Windows theme={null} $Env:GOOGLE_API_KEY="your_google_api_key_here" $Env:OPENAI_API_KEY="your_openai_api_key_here" ``` Clone the repository and run the remaining commands from its root: ```bash theme={null} git clone https://github.com/agno-agi/agno.git cd agno ``` In a separate terminal, start the [remote AgentOS server](/examples/agent-os/remote/server) on port 7778: ```bash theme={null} python cookbook/05_agent_os/remote/server.py ``` In a separate terminal, start the [Agno A2A server](/examples/agent-os/remote/agno-a2a-server) on port 7779: ```bash theme={null} python cookbook/05_agent_os/remote/agno_a2a_server.py ``` In a separate terminal, start the [Google ADK A2A server](/examples/agent-os/remote/adk-server) on port 7780. This server uses `GOOGLE_API_KEY`. ```bash theme={null} python cookbook/05_agent_os/remote/adk_server.py ``` Run the example from the repository root: ```bash theme={null} python cookbook/05_agent_os/remote/05_agent_os_gateway.py ``` Full source: [cookbook/05\_agent\_os/remote/05\_agent\_os\_gateway.py](https://github.com/agno-agi/agno/blob/main/cookbook/05_agent_os/remote/05_agent_os_gateway.py)