Oracle Cloud Infrastructure Documentation

Overview of Generative AI Agents Service

OCI Generative AI Agents is a fully managed service that combines the power of large language models (LLMs) with an intelligent retrieval system aimed at creating contextually relevant answers by searching your knowledge base.

OCI Generative AI Agents supports several ways to on-board your data where you and your customers can interact with your data using a chat interface or API.

Key Features
  • Supports several data on-boarding methods and interaction channels (chat interface or API)
  • Creates contextually relevant answers by searching your knowledge base
  • Provides source attribution for every answer
  • Offers hybrid search capabilities (lexical and semantic)
  • Includes content moderation options for input and output
  • Supports multi-turn conversations, where users can ask follow-up questions and receive answers that consider the context of previous questions and answers
  • Can interpret data from two-axis charts and reference tables in a PDF, without needing explicit descriptions of the visual elements

  • All the hyperlinks present in the PDF documents are extracted and displayed as hyperlinks in the chat response.

Knowledge Base Data Types

  • Service-Managed Option

    • OCI Object Storage files where you can have up to 1,000 text and PDF files of 100 MB each. And you can request an increase through limit request.

  • Bring Your Own (BYO) Options

    • Oracle Database 23ai vector search
    • OCI Search with OpenSearch ingested and indexed data
Benefits
  • Transparent Accountability: Track responses back to their source for clear visibility and accountability.
  • Seamless Updates: Update data sources without disrupting agent functionality, ensuring continuous operation.
  • Robust Architecture: Leverage a scalable and secure architecture that supports growing demands and maintains data integrity.
  • Version Control and Incremental Ingestion: Manage data updates with precision through incremental ingestion and version control.
  • Enhanced Customer Experience: Engage in more natural and intuitive conversations with customers, driving improved satisfaction and loyalty.

The Setup Process

To use OCI Generative AI Agents, you create a knowledge base, add your data, create an agent, and then set up endpoints for user interaction.

Use Cases

A retrieval-augmented generation (RAG) agent is a type of artificial intelligence application that combines retrieval and generation capabilities to produce responses. The RAG agent retrieves relevant documents or data from a knowledge source and then uses a language generation model to create a coherent and contextually relevant answer based on the retrieved information. This approach leverages both the factual accuracy of retrieval methods and the flexibility of generative models, making it useful for tasks that require both depth of knowledge and fluency in response generation. Example use cases include:

  • Customer Support: In the customer service industry, RAG agents can retrieve information from a company’s knowledge base to provide contextually relevant answers to customer inquiries, to help reduce response times.
  • Legal Research: Legal professionals can use RAG agents to assist in searching precedents and case law from vast legal databases.
  • Financial Analysis: In finance, RAG agents can analyze large volumes of financial data, reports, and news.
  • Educational Tutoring: RAG agents can function as personal tutors, providing students with explanations, resources, and answers to questions by accessing educational content.
  • Content Creation: In media and content creation, RAG agents can help writers and journalists by pulling information from specific topics and drafting suggestions.
  • Technical Support and Troubleshooting: RAG agents can guide users through technical troubleshooting processes by accessing and synthesizing technical manuals and support forums to offer step-by-step help.
  • Supply Chain Management: In supply chain and logistics, RAG agents can provide insights by retrieving and synthesizing information on inventory levels, supplier data, and logistic metrics to potentially optimize operations and help predict potential disruptions.
  • Real Estate Market Analysis: RAG agents can help real estate professionals by aggregating and analyzing data from several sources, including market trends, property listings, to support market analyses.
  • Travel Planning and Help: In the travel industry, RAG agents can serve as interactive travel guides, pulling information on destinations, weather, local attractions, to support personalized travel advice and itineraries.

Regions with Generative AI Agents

Oracle hosts its OCI services in regions and availability domains. A region is a localized geographic area, and an availability domain is one or more data centers in that region. OCI Generative AI Agents is hosted in the following regions:

Region Name Location Region Identifier Region Key
Germany Central (Frankfurt) Frankfurt eu-frankfurt-1 FRA
UK South (London) London uk-london-1 LHR
US Midwest (Chicago) Chicago us-chicago-1 ORD

See About Regions and Availability Domains for the list of available OCI regions, along with associated locations, region identifiers, region keys, and availability domains.

Accessing Generative AI Agents in the Console

  1. Sign in to the Console by using a supported browser.
  2. In the navigation bar of the Console, select a region that hosts Generative AI Agents, for example, US Midwest (Chicago).
  3. Open the navigation menu  and select Analytics & AI. Under AI Services, select Generative AI Agents.