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The **Oracle AI Optimizer and Toolkit** (the **AI Optimizer**) 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 VectorSearch and SelectAI, the Sandbox enables users to enhance existing Large Language Models (LLMs) through RAG.
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## AI Optimizer Features
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-[Configuring Embedding and Chat Models](https://oracle-samples.github.io/ai-optimizer/client/configuration/model_config)
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-[Splitting and Embedding Documentation](https://oracle-samples.github.io/ai-optimizer/client/tools/split_embed)
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-[Modifying System Prompts (Prompt Engineering)](https://oracle-samples.github.io/ai-optimizer/client/tools/prompt_eng)
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-[Experimenting with **LLM** Parameters](https://oracle-samples.github.io/ai-optimizer/client/chatbot)
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-[Testbed for auto-generated or existing Q&A datasets](https://oracle-samples.github.io/ai-optimizer/client/testbed)
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-[Configuring Embedding and Chat Models](https://oracle.github.io/ai-optimizer/client/configuration/model_config)
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-[Splitting and Embedding Documentation](https://oracle.github.io/ai-optimizer/client/tools/split_embed)
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-[Modifying System Prompts (Prompt Engineering)](https://oracle.github.io/ai-optimizer/client/tools/prompt_eng)
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-[Experimenting with **LLM** Parameters](https://oracle.github.io/ai-optimizer/client/chatbot)
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-[Testbed for auto-generated or existing Q&A datasets](https://oracle.github.io/ai-optimizer/client/testbed)
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## Getting Started
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The **AI Optimizer** 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.
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For more information, including more details on **Setup and Configuration** please visit the [documentation](https://oracle-samples.github.io/ai-optimizer).
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For more information, including more details on **Setup and Configuration** please visit the [documentation](https://oracle.github.io/ai-optimizer).
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### Prerequisites
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- API Keys for Third-Party Models
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- On-Premises Models<sub>\*</sub>
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<sub>\*Oracle recommends running On-Premises Models on hardware with GPUs. For more information, please review the [Infrastructure](https://oracle-samples.github.io/ai-optimizer/infrastructure) documentation.</sub>
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<sub>\*Oracle recommends running On-Premises Models on hardware with GPUs. For more information, please review the [Infrastructure](https://oracle.github.io/ai-optimizer/infrastructure) documentation.</sub>
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#### Bare-Metal Installation
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To run the application on bare-metal; download the [source](https://github.com/oracle-samples/ai-optimizer) and from `src/`:
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To run the application on bare-metal; download the [source](https://github.com/oracle/ai-optimizer) and from `src/`:
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1. Create and activate a Python Virtual Environment:
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1. Navigate to `http://localhost:8501`.
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1.[Configure](https://oracle-samples.github.io/ai-optimizer/client/configuration) the **AI Optimizer**.
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1.[Configure](https://oracle.github.io/ai-optimizer/client/configuration) the **AI Optimizer**.
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#### Container Installation
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To run the application in a container; download the [source](https://github.com/oracle-samples/ai-optimizer):
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To run the application in a container; download the [source](https://github.com/oracle/ai-optimizer):
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1. Build the all-in-one image.
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1. Navigate to `http://localhost:8501`.
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1.[Configure](https://oracle-samples.github.io/ai-optimizer/client/configuration/index.html) the **AI Optimizer**.
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1.[Configure](https://oracle.github.io/ai-optimizer/client/configuration/index.html) the **AI Optimizer**.
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#### Got OCI?
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Choose either a light-weight Virtual Machine or robust Oracle Kubernetes Engine deployment, both with an Oracle Autonomous Database 23ai:
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[![Deploy to Oracle Cloud][magic_button]][magic_arch_stack]
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For more information, please visit the [IaC Documentation](https://oracle-samples.github.io/ai-optimizer/advanced/iac/index.html).
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For more information, please visit the [IaC Documentation](https://oracle.github.io/ai-optimizer/advanced/iac/index.html).
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## Contributing
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## Description
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This directory contains the documentation for the the [**Oracle AI Optimizer & Toolkit**](https://github.com/oracle-samples/ai-optimizer).
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This directory contains the documentation for the the [**Oracle AI Optimizer & Toolkit**](https://github.com/oracle/ai-optimizer).
You will use the URL for the pushed images when [configuring](#configure-valuesyaml) the [values.yaml](https://github.com/oracle-samples/ai-optimizer/blob/main/helm/values.yaml).
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You will use the URL for the pushed images when [configuring](#configure-valuesyaml) the [values.yaml](https://github.com/oracle/ai-optimizer/blob/main/helm/values.yaml).
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### Configure values.yaml
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The [values.yaml](https://github.com/oracle-samples/ai-optimizer/blob/main/helm/values.yaml) allows you to customize the deployment by overriding settings such as image versions, resource requests, service configurations, and more. You can modify this file directly or supply your own overrides during installation using the -f or --set flags.
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The [values.yaml](https://github.com/oracle/ai-optimizer/blob/main/helm/values.yaml) allows you to customize the deployment by overriding settings such as image versions, resource requests, service configurations, and more. You can modify this file directly or supply your own overrides during installation using the -f or --set flags.
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Only a subset of the most important settings are documented here, review the `values.yaml` file for more configuration options.
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| server.oci_config.user | string |`""`| User OCID. Required when specifying keySecretName. |
| server.oci_config.region | string |`""`| Region. Required when oke is true. |
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| server.oci_config.fileSecretName | string |`""`| Secret containing an OCI config file and the key_file(s). Use the [scripts/oci_config.py](https://github.com/oracle-samples/ai-optimizer/blob/main/helm/scripts/oci_config.py) script to help create the secret based on an existing ~.oci/config file |
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| server.oci_config.fileSecretName | string |`""`| Secret containing an OCI config file and the key_file(s). Use the [scripts/oci_config.py](https://github.com/oracle/ai-optimizer/blob/main/helm/scripts/oci_config.py) script to help create the secret based on an existing ~.oci/config file |
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| server.oci_config.keySecretName | string |`""`| Secret containing a single API key corresponding to above tenancy configuration This used by OraOperator when not running in OKE |
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###### Examples
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1. (Optional) Configure for Oracle Cloud Infrastructure
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If you already have an OCI API configuration file, use the [scripts/oci_config.py](https://github.com/oracle-samples/ai-optimizer/blob/main/helm/scripts/oci_config.py) helper script to turn it into a secret for OCI connectivity:
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If you already have an OCI API configuration file, use the [scripts/oci_config.py](https://github.com/oracle/ai-optimizer/blob/main/helm/scripts/oci_config.py) helper script to turn it into a secret for OCI connectivity:
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```sh
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kubectl create namespace ai-optimizer
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The {{< full_app_ref >}} can easily be deployed in Oracle Cloud Infrastructure (**OCI**) using Infrastructure as Code (**IaC**) provided in the source [opentofu](https://github.com/oracle-samples/ai-optimizer/tree/main/opentofu) directory.
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The {{< full_app_ref >}} can easily be deployed in Oracle Cloud Infrastructure (**OCI**) using Infrastructure as Code (**IaC**) provided in the source [opentofu](https://github.com/oracle/ai-optimizer/tree/main/opentofu) directory.
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Choose between deploying a light-weight [Virtual Machine](#virtual-machine) or robust [Oracle Kubernetes Engine (**OKE**)](#oracle-kubernetes-engine) along with the **Oracle Autonomous Database** for a fully configured {{< short_app_ref >}} environment, ready to use.
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While the **IaC** can be run from a command-line with prior experience, the steps outlined here use [Oracle Cloud Resource Manager](https://docs.oracle.com/en-us/iaas/Content/ResourceManager/Concepts/resourcemanager.htm) to simplify the process. To get started:
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{{< imagelink url="https://cloud.oracle.com/resourcemanager/stacks/create?zipUrl=https://github.com/oracle-samples/ai-optimizer/releases/latest/download/ai-optimizer-iac.zip" src="https://oci-resourcemanager-plugin.plugins.oci.oraclecloud.com/latest/deploy-to-oracle-cloud.svg" alt="Deploy to Oracle Cloud" >}}
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{{< imagelink url="https://cloud.oracle.com/resourcemanager/stacks/create?zipUrl=https://github.com/oracle/ai-optimizer/releases/latest/download/ai-optimizer-iac.zip" src="https://oci-resourcemanager-plugin.plugins.oci.oraclecloud.com/latest/deploy-to-oracle-cloud.svg" alt="Deploy to Oracle Cloud" >}}
At a minimum, a Large _Language Model_ (LLM) must be configured in {{< short_app_ref >}} for basic functionality. For Retrieval-Augmented Generation (**RAG**), an _Embedding Model_ will also need to be configured.
If there is a specific model API that you would like to use, please [open an issue in GitHub](https://github.com/oracle-samples/ai-optimizer/issues/new).
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If there is a specific model API that you would like to use, please [open an issue in GitHub](https://github.com/oracle/ai-optimizer/issues/new).
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{{% /notice %}}
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| Type | API | Location |
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#### API
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The {{< short_app_ref >}} supports a number of model API's. When adding a model, choose the most appropriate Model API. If unsure, or the specific API is not listed, try *CompatOpenAI* or *CompatOpenAIEmbeddings* before [opening an issue](https://github.com/oracle-samples/ai-optimizer/issues/new) requesting an additional model API support.
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The {{< short_app_ref >}} supports a number of model API's. When adding a model, choose the most appropriate Model API. If unsure, or the specific API is not listed, try *CompatOpenAI* or *CompatOpenAIEmbeddings* before [opening an issue](https://github.com/oracle/ai-optimizer/issues/new) requesting an additional model API support.
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There are a number of local AI Model runners that use OpenAI compatible API's, including:
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The {{< short_app_ref >}} provides an easy to use front-end for experimenting with **LLM** parameters and **RAG**.
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1. Download and Unzip the [latest release](https://github.com/oracle-samples/ai-optimizer/releases/latest) of the {{< short_app_ref >}}:
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1. Download and Unzip the [latest release](https://github.com/oracle/ai-optimizer/releases/latest) of the {{< short_app_ref >}}:
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