> ## Documentation Index > Fetch the complete documentation index at: https://agno-v2-codex-docs-audit-20260719-0149.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Agent SDK > Build your agent platform in pure Python. Agno is a Python SDK for building agents and multi-agent systems. It provides three primitives (agents, teams, and workflows) plus capabilities such as storage, memory, knowledge, learning, and compression. A primitive and its capabilities form a component in your agent platform. Everything is pure Python. No new DSL to learn, no YAML to manage. ```bash theme={null} uv pip install -U "agno[openai,sqlite]" ``` ```python theme={null} from agno.agent import Agent from agno.db.sqlite import SqliteDb from agno.tools.workspace import Workspace workbench = Agent( name="Workbench", model="openai:gpt-5.5", db=SqliteDb(db_file="workbench.db"), tools=[Workspace(".")], add_history_to_context=True, markdown=True, ) workbench.print_response("Inventory this folder.") ``` An agent (the primitive) with a model, tools, storage, and session history (the capabilities) is a component you can serve on the AgentOS runtime. ## Primitives | Primitive | Description | | ------------------------------- | ------------------------------------------------------------------ | | [Agent](/agents/overview) | Model-driven programs with tools and instructions | | [Team](/teams/overview) | Multiple agents working together as a team | | [Workflow](/workflows/overview) | Explicit step-based orchestration for agents, teams, and functions | ## Capabilities ### Model and tools | Capability | What it adds | | ---------------------------------------- | ------------------------------------------------------- | | [Models](/models/overview) | 30+ providers behind one API | | [Tools](/tools/overview) | 100+ integrations and the ability to write your own | | [Skills](/skills/overview) | Composable abilities you can attach to agents and teams | | [Multimodal](/multimodal/overview) | Image, audio, and video input and output | | [Structured I/O](/input-output/overview) | Type-safe input and output with Pydantic schemas | ### Memory and context | Capability | What it adds | | ------------------------------------------------ | ------------------------------------------------------------------------ | | [Storage](/database/overview) | Durability and persistence with supported database backends | | [Sessions](/sessions/overview) | Multi-turn session management with summaries, history, and metrics | | [State](/state/overview) | Session and agentic state agents can read and update mid-run | | [Memory](/memory/overview) | Store facts about each user and recall them in later conversations | | [Knowledge](/knowledge/overview) | Search over documents, URLs, and databases | | [Learning](/learning/overview) | Agents that improve over time with learned behavior and decisions | | [Compression](/compression/overview) | Compress tool call results to save context space | | [Context Providers](/context-providers/overview) | Inject live data from Calendar, Gmail, Drive, Slack, Wiki, MCP, and more | ### Control and safety | Capability | What it adds | | ----------------------------------- | ------------------------------------------------------------- | | [Guardrails](/guardrails/overview) | Input validation, PII detection, and prompt injection defense | | [Hooks](/hooks/overview) | Lifecycle hooks for input, output, and state | | [Human-in-the-Loop](/hitl/overview) | Pause runs for approval, input, or external execution | ### Operations | Capability | What it adds | | ------------------------------------------------------ | ----------------------------------------------------------------------------- | | [Background execution](/background-execution/overview) | Long-running runs that don't block your API | | [Evals](/evals/overview) | Measure accuracy, performance, and reliability; agent-as-judge | | [Observability](/observability/overview) | Tracing with Langfuse, Logfire, Arize, The Context Company, and 12+ providers | | [Scheduler](/scheduler/overview) | Run agents, teams, and workflows on recurring schedules | ## Components A primitive + capabilities + configuration becomes a live **component** of your agent platform. You can create components in code, through a no-code UI, or via the AgentOS API. Change code-defined components in Python. Components created via the API or no-code UI have draft and published configuration versions that you can promote or roll back. The `/components` API lets you build, version, and operate components over HTTP. ### Versioned components When components are created via the API, they carry a versioned configuration. Published versions are immutable, and run requests accept a `version` parameter so you can pin clients to a specific version. A `current` pointer decides which version your production API serves: set it to a newer version to promote, or an earlier one to roll back. Tune a component's instructions, model, or tools and publish the change as a new version. Promote the new version or roll back to an earlier version based on its results. ## Learn more Agents, teams, and workflows in pure Python. Create agents with models, tools, and instructions. Assemble a full platform on the AgentOS runtime.