Oracle AI Microservices Sandbox

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Description

The Oracle AI Microservices Sandbox provides a streamlined environment where developers and data scientists can explore the potential of Generative Artificial Intelligence (GenAI) combined with Retrieval-Augmented Generation (RAG) capabilities. By integrating Oracle Database 23ai AI Vector Search, the Sandbox enables users to enhance existing Large Language Models (LLMs) through RAG.

Sandbox Features

• Configuring Embedding and Chat Models
• Splitting and Embedding Documentation
• Storing Embedded Documents into the Oracle Database
• Modifying System Prompts (Prompt Engineering)
• Experimenting with LLM Parameters
• Testing Framework on auto-generated or existing Q&A datasets

Getting Started

The Oracle AI Microservices Sandbox is available to install in your own environment, which may be a developer's desktop, on-premises data center environment, or a cloud provider. It can be run either on bare-metal, within a container, or in a Kubernetes Cluster.

For more information, including more details on Setup and Configuration please visit the documentation.

Prerequisites

• Oracle Database 23ai incl. Oracle Database 23ai Free
• Python 3.11 (for running Bare-Metal)
• Container Runtime e.g. docker/podman (for running in a Container)
• Access to an Embedding and Chat Model:
  • API Keys for Third-Party Models
  • On-Premises Models_*

_{*Oracle recommends running On-Premises Models on hardware with GPUs. For more information, please review the Infrastructure documentation.}

Bare-Metal Installation

To run the application on bare-metal; download the source and from the top-level directory:

1. Create and activate a Python Virtual Environment:

   python3.11 -m venv .venv
   source .venv/bin/activate
   pip3 install --upgrade pip wheel

2. Install the Python modules:

   pip3 install -r app/requirements.txt

3. Exit from your shell and run again:

   source .venv/bin/activate

4. Start Streamlit:

   cd app/src
   streamlit run oaim-sandbox.py --server.port 8501

5. Navigate to http://localhost:8501.

6. Configure the Sandbox.

Container Installation

To run the application in a container; download the source and from the top-level directory:

1. Build the image.

   From the app/ directory, build Image:

   podman build -t oaim-sandbox .

2. Start the Container:

   podman run -p 8501:8501 -it --rm oaim-sandbox

3. Navigate to http://localhost:8501.

4. Configure the Sandbox.

Contributing

This project welcomes contributions from the community. Before submitting a pull request, please review our contribution guide.

Security

Please consult the security guide for our responsible security vulnerability disclosure process.

License

Copyright (c) 2024 Oracle and/or its affiliates. Released under the Universal Permissive License v1.0 as shown at https://oss.oracle.com/licenses/upl/

See LICENSE for more details.