Select AI for Python enables you to ask questions of your database data using natural language (text-to-SQL), get generative AI responses using your trusted content (retrieval augmented generation), generate synthetic data using large language models, and other features – all from Python. With the general availability of Select AI Python, Python developers have access to the functionality of Select AI on Oracle Autonomous Database.
Select AI for Python enables you to leverage the broader Python ecosystem in combination with generative AI and database functionality - bridging the gap between the DBMS_CLOUD_AI PL/SQL package and Python's rich ecosystem. It provides intuitive objects and methods for AI model interaction.
- Installation
- Documentation
- Getting Started
- Command Line Interface
- Samples
- Help
- Contributing
- Security
- License
Install the Python package:
python3 -m pip install select_aiInstall the optional command line interface:
python3 -m pip install 'select_ai[cli]'The CLI extra includes A2A server support.
See Select AI for Python documentation
import select_ai
user = "<your_select_ai_user>"
password = "<your_select_ai_password>"
dsn = "<your_select_ai_db_connect_string>"
select_ai.connect(user=user, password=password, dsn=dsn)
profile = select_ai.Profile(profile_name="oci_ai_profile")
# run_sql returns a pandas dataframe
df = profile.run_sql(prompt="How many promotions?")
print(df.columns)
print(df)import asyncio
import select_ai
user = "<your_select_ai_user>"
password = "<your_select_ai_password>"
dsn = "<your_select_ai_db_connect_string>"
# This example shows how to asynchronously run sql
async def main():
await select_ai.async_connect(user=user, password=password, dsn=dsn)
async_profile = await select_ai.AsyncProfile(
profile_name="async_oci_ai_profile",
)
# run_sql returns a pandas df
df = await async_profile.run_sql("How many promotions?")
print(df)
asyncio.run(main())The optional select-ai command provides interactive chat, SQL, profile
management, and A2A server tools for Select AI:
select-ai chat --profile OCI_AI_PROFILEExpose one Oracle Database AI agent team as an A2A JSON-RPC HTTP server:
select-ai a2a serve --team SALES_ANALYST --port 8000The command obtains database connection settings from its options or the
SELECT_AI_* environment variables. Its Agent Card is available at
/.well-known/agent-card.json, and its JSON-RPC endpoint is
/a2a/jsonrpc/. Set --public-url when the server is behind a proxy or load
balancer so that clients receive its externally reachable URL.
For Autonomous Database mTLS, also set SELECT_AI_WALLET_LOCATION to the
directory containing the unzipped wallet and set SELECT_AI_WALLET_PASSWORD.
The CLI passes both values to the Select AI SDK as wallet_location and
wallet_password.
The server accepts both A2A 1.x and the A2A v0.3 JSON-RPC streaming protocol for compatibility with Gemini Enterprise.
Generate the A2A v0.3 Agent Card to paste into Gemini Enterprise after the service has a public URL:
select-ai a2a agent-card \
--team ORACLE_AI_DATABASE_AGENT \
--public-url https://YOUR-SERVICE.run.appDeploy the A2A server to Cloud Run using the instructions in gcloud/README.md.
For in-depth examples, see the /samples directory.
Questions can be asked in GitHub Discussions.
Problem reports can be raised in GitHub Issues.
This project welcomes contributions from the community. Before submitting a pull request, please review our contribution guide
Please consult the security guide for our responsible security vulnerability disclosure process
Copyright (c) 2025, 2026 Oracle and/or its affiliates.
Released under the Universal Permissive License v1.0 as shown at https://oss.oracle.com/licenses/upl/.

