Select AI Agent for Python
select_ai, enabling you to leverage DBMS_CLOUD_AI
features within Autonomous AI Database directly
from Python. The module extends support for advanced generative AI workflows and
agent-based automation through the select_ai.agent
submodule.
What You Can Do
You can now design and orchestrate agentic workflows in Python with the following classes:
select_ai.agent.Toolselect_ai.agent.Taskselect_ai.agent.Agentselect_ai.agent.Team
These classes enable you to programmatically define tools, construct
tasks, configure agents, and assemble multi-agent teams in Python. This approach
closely mirrors the structure and capabilities provided by the
DBMS_CLOUD_AI_AGENT package in the database, giving you
flexible control and seamless integration with Autonomous AI Database AI operations.
Async Select AI Agent Support
The select_ai.agent module also includes asynchronous
versions of its core classes, enabling you to build and run agent workflows using
Python’s async and await. These async classes are
designed for co-routine-based applications and enable non-blocking interaction with
the database.
You can use the following async classes:
-
select_ai.agent.AsyncTool -
select_ai.agent.AsyncTask -
select_ai.agent.AsyncAgent -
select_ai.agent.AsyncTeam
See "Async AI agent examples" in Select AI for Python to explore.
These asynchronous classes support the same core functionality as their synchronous counterparts, including:
-
Creating tools for natural-language-to-SQL generation (NLSQL), web search, retrieval-augmented generation (RAG), PL/SQL, notifications, and custom functions
-
Configuring task logic and tool usage
-
Assigning agent roles and profiles
-
Assembling and running agent teams programmatically
This enables you to build scalable AI pipelines that integrate naturally with Python async applications.
For complete API reference, see Select AI for Python guide.
Parent topic: Select AI Agent