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Documentation Index

Fetch the complete documentation index at: https://agno-v2-shaloo-ai-support-link.mintlify.app/llms.txt

Use this file to discover all available pages before exploring further.

Build production-grade agents via AgentOS Studio’s visual canvas. Wire up models, tools, and structured I/O into complex agentic workflows. Deploy instantly. No-code required.

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Creating Agents

Create a new agent by selecting components from your Registry and configuring them in the properties panel:
SettingDescription
ModelSelect from registered models
ToolsAttach registered tools and toolkits
InstructionsSystem-level instructions for the agent
Input/Output SchemaStructured I/O using registered Pydantic schemas
MemoryEnable memory for multi-turn conversations
KnowledgeAttach knowledge bases for RAG
Switch to the advanced JSON config editor for fine-grained control over agent settings.

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Using Agents

Use Studio-built Agents in multiple ways:
  • Chat directly with the agent via the Chat page
  • Add to Teams for multi-agent collaboration
  • Use in Workflows as step executors for automation pipelines

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Save and Run

Once your agent is configured:
  1. Save your agent to persist it to the registry
  2. Navigate to the Chat page to interact with your agent
  3. Send messages and receive responses in real-time
  4. View tool calls, reasoning, and outputs as the agent works

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Code Equivalent

Agents built in Studio are native instances of the ‘Agent’ class in the SDK. 
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.websearch import WebSearchTools

agent = Agent(
    name="Research Agent",
    model=OpenAIChat(id="gpt-5-mini"),
    tools=[WebSearchTools()],
    instructions="Research topics thoroughly using web search.",
    markdown=True,
)

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Developer Resources