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2 changes: 1 addition & 1 deletion doc/requirements.txt
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
sphinx
sphinx-rtd-theme
sphinx_toolbox
pydata_sphinx_theme
python_docs_theme
4 changes: 2 additions & 2 deletions doc/source/index.rst
Original file line number Diff line number Diff line change
Expand Up @@ -99,8 +99,8 @@ Synthetic Data
user_guide/synthetic_data.rst


Select AI Agents
================
AI Agent
========

.. toctree::
:numbered:
Expand Down
93 changes: 71 additions & 22 deletions doc/source/user_guide/agent.rst
Original file line number Diff line number Diff line change
Expand Up @@ -72,6 +72,12 @@ Python layer and persist the tool in the Database using
- - ``tool_name``
- ``profile_name``

.. note::

Use ``select_ai.agent.AsyncTool.create_<tool>`` for corresponding async
methods. For e.g. ``await select_ai.agent.AsyncTool.create_rag_tool()``
can be used to create an RAG tool in an async application.

.. latex:clearpage::

.. autoclass:: select_ai.agent.ToolAttributes
Expand Down Expand Up @@ -131,9 +137,9 @@ List Tools

output::

Tool(tool_name=MOVIE_SQL_TOOL, attributes=ToolAttributes(instruction='This tool is used to work with SQL queries using natural language. Input should be a natural language query about data or database operations. The tool behavior depends on the configured action: RUNSQL - generates and executes the SQL query returning actual data; SHOWSQL - generates and displays the SQL statement without executing it; EXPLAINSQL - generates SQL and provides a natural language explanation of what the query does. Always provide clear, specific questions about the data you want to retrieve or analyze.', function='dbms_cloud_ai_agent.sql_tool', tool_params=SQLToolParams(_REQUIRED_FIELDS=None, credential_name=None, endpoint=None, notification_type=None, profile_name='oci_ai_profile', recipient=None, sender=None, slack_channel=None, smtp_host=None), tool_inputs=None, tool_type='SQL'), description=My Select AI MOVIE SQL agent tool)

Tool(tool_name=LLM_CHAT_TOOL, attributes=ToolAttributes(instruction='This tool is used to work with SQL queries using natural language. Input should be a natural language query about data or database operations. The tool behavior depends on the configured action: RUNSQL - generates and executes the SQL query returning actual data; SHOWSQL - generates and displays the SQL statement without executing it; EXPLAINSQL - generates SQL and provides a natural language explanation of what the query does. Always provide clear, specific questions about the data you want to retrieve or analyze.', function='dbms_cloud_ai_agent.sql_tool', tool_params=SQLToolParams(_REQUIRED_FIELDS=None, credential_name=None, endpoint=None, notification_type=None, profile_name='oci_ai_profile', recipient=None, sender=None, slack_channel=None, smtp_host=None), tool_inputs=None, tool_type='SQL'), description=My Select AI agent tool)
WEB_SEARCH_TOOL
MOVIE_SQL_TOOL
LLM_CHAT_TOOL

.. latex:clearpage::

Expand Down Expand Up @@ -193,7 +199,8 @@ List Tasks

output::

Task(task_name=ANALYZE_MOVIE_TASK, attributes=TaskAttributes(instruction='Help the user with their request about movies. User question: {query}. You can use SQL tool to search the data from database', tools='["MOVIE_SQL_TOOL"]', input=None, enable_human_tool=False), description=Movie task involving a human)
WEB_SEARCH_TASK
ANALYZE_MOVIE_TASK

.. latex:clearpage::

Expand Down Expand Up @@ -225,7 +232,11 @@ Create Agent

output::

Created Agent: Agent(agent_name=MOVIE_ANALYST, attributes=AgentAttributes(profile_name='LLAMA_4_MAVERICK', role='You are an AI Movie Analyst. Your can help answer a variety of questions related to movies. ', enable_human_tool=False), description=None)
Created Agent: Agent(agent_name=MOVIE_ANALYST,
attributes=AgentAttributes(profile_name='LLAMA_4_MAVERICK',
role='You are an AI Movie Analyst.
Your can help answer a variety of questions related to movies. ',
enable_human_tool=False), description=None)


.. latex:clearpage::
Expand Down Expand Up @@ -261,7 +272,12 @@ Run Team

output::

The database contains 100 movies with various titles, genres, and release dates. The list includes a wide range of genres such as Action, Comedy, Drama, Thriller, Romance, Adventure, Mystery, Sci-Fi, Historical, Biography, War, Sports, Music, Documentary, Animated, Fantasy, Horror, Western, Family, and more. The release dates are primarily in January and February of 2019. Here is a summary of the movies:
The database contains 100 movies with various titles, genres, and release
dates. The list includes a wide range of genres such as Action, Comedy, Drama,
Thriller, Romance, Adventure, Mystery, Sci-Fi, Historical, Biography, War,
Sports, Music, Documentary, Animated, Fantasy, Horror, Western, Family,
and more. The release dates are primarily in January and February of 2019.
Here is a summary of the movies:

1. Action Movie (Action, 2019-01-01)
2. Comedy Film (Comedy, 2019-01-02)
Expand All @@ -286,25 +302,58 @@ Web Search Agent using OpenAI's GPT model

.. literalinclude:: ../../../samples/agent/websearch_agent.py
:language: python
:lines: 14-

output::

Created credential: OPENAI_CRED
Created profile: OPENAI_PROFILE
Created tool: WEB_SEARCH_TOOL
The key features of Oracle Database Machine Learning, as highlighted on the Oracle website, include:

- In-database machine learning: Build, train, and deploy machine learning models directly inside the Oracle Database, eliminating the need to move data.
- Support for multiple languages: Use SQL, Python, and R for machine learning tasks, allowing flexibility for data scientists and developers.
- Automated machine learning (AutoML): Automates feature selection, model selection, and hyperparameter tuning to speed up model development.
- Scalability and performance: Utilizes Oracle Database’s scalability, security, and high performance for machine learning workloads.
- Integration with Oracle Cloud: Seamlessly integrates with Oracle Cloud Infrastructure for scalable and secure deployment.
- Security and governance: Inherits Oracle Database’s robust security, data privacy, and governance features.
- Prebuilt algorithms: Offers a wide range of in-database algorithms for classification, regression, clustering, anomaly detection, and more.
- No data movement: Keeps data secure and compliant by performing analytics and machine learning where the data resides.

These features enable organizations to operationalize machine learning at scale, improve productivity, and maintain data security and compliance.

The main topic at the URL https://www.oracle.com/artificial-intelligence/database-machine-learning is Oracle's database machine learning capabilities, specifically how Oracle integrates artificial intelligence and machine learning features directly into its database products. The page highlights how users can leverage these built-in AI and ML tools to analyze data, build predictive models, and enhance business applications without moving data outside the Oracle Database environment.

The main topic of the website https://openai.com is artificial intelligence research and development. OpenAI focuses on creating and promoting advanced AI technologies, including products like ChatGPT, and provides information about their research, products, and mission to ensure that artificial general intelligence benefits all of humanity.
The key features of Oracle Database Machine Learning, as highlighted on the
Oracle website, include:

- In-database machine learning: Build, train, and deploy machine learning
models directly inside the Oracle Database, eliminating the need to move
data.
- Support for multiple languages: Use SQL, Python, and R for machine
learning tasks, allowing flexibility for data scientists and developers.
- Automated machine learning (AutoML): Automates feature selection, model
selection, and hyperparameter tuning to speed up model development.
- Scalability and performance: Utilizes Oracle Database’s scalability,
security, and high performance for machine learning workloads.
- Integration with Oracle Cloud: Seamlessly integrates with Oracle
Cloud Infrastructure for scalable and secure deployment.
- Security and governance: Inherits Oracle Database’s robust security,
data privacy, and governance features.
- Prebuilt algorithms: Offers a wide range of in-database algorithms for
classification, regression, clustering, anomaly detection, and more.
- No data movement: Keeps data secure and compliant by performing
analytics and machine learning where the data resides.

These features enable organizations to operationalize machine learning at
scale, improve productivity, and maintain data security and compliance.

The main topic at the URL https://www.oracle.com/artificial-intelligence/database-machine-learning
is Oracle's database machine learning capabilities, specifically how Oracle
integrates artificial intelligence and machine learning features directly
into its database products. The page highlights how users can leverage these
built-in AI and ML tools to analyze data, build predictive models, and enhance
business applications without moving data outside the Oracle Database
environment.

The main topic of the website https://openai.com is artificial
intelligence research and development. OpenAI focuses on creating and
promoting advanced AI technologies, including products like ChatGPT, and
provides information about their research, products, and mission to ensure
that artificial general intelligence benefits all of humanity.


**************
Async AI Agent
**************

.. toctree::
:numbered:
:maxdepth: 3

async_agent.rst
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