forked from diegoecab/oci-deal-accelerator
Diagram generation: ref-arch-driven procedure + spec validator + KB enrichment
The diagram path now follows a documented standard procedure (lookup the closest Oracle Architecture Center reference → confirm components → author absolute_layout → spec validator → render → visually verify) and ships persistent guardrails so layout regressions can't recur. Persistent procedure changes (apply to all users, all sessions): - tools/diagram_spec_validator.py — geometry checks (CONTAINER_TOO_THIN, CONTAINER_PADDING_VIOLATION, LABEL_OVERFLOW_PARENT) run BEFORE either renderer (drawio + PPTX). Catches the subnet-collapse / label-overflow bugs that the post-render drawio validator missed. - tools/oci_diagram_gen.py + tools/oci_pptx_diagram_gen.py — call the spec validator before emitting any output. Adds mysql / mysql_heatwave type aliases. - tools/archcenter_pattern_lookup.py — scores against cached page descriptions (not just the 1-line summary), supports --queries for multi-fragment composition, and applies synonym expansion via kb/architecture-center/synonyms.yaml so "LB HA cross AD" matches "load balancer high availability availability domain". - kb/architecture-center/synonyms.yaml — canonical synonym table (load balancer, autonomous database, data guard, …) used by the lookup scorer. KB enrichment: - tools/archcenter_description_fetcher.py + 121 cached _description.md under kb/diagram/assets/archcenter-refs/<slug>/. Removes the runtime dependency on docs.oracle.com when authoring specs and feeds the pattern-lookup scorer. - 110+ cached .drawio / .svg / .png references for offline reuse, plus the OCI Toolkit v24.2 import (kb/diagram/assets/oci-toolkit-drawio). Documentation: - docs/skill/output-formats.md — new "Standard diagram-generation procedure (MANDATORY)" + geometry rules + the new validator entry. - SKILL.md option 2 — references the mandatory procedure. - README.md — describes the spec validator, archcenter_pattern_lookup and description fetcher, and updates the KB-health table. Tooling that backs the procedure (cumulative across recent sessions): tools/archcenter_case_runner.py, archcenter_batch_driver.py, archcenter_zip_downloader.py, drawio_visual_validator.py, drawio_fidelity_eval.py, harvest_drawio_icon.py, import_oci_library.py, oci_pptx_diagram_gen.py, oci_pptx_render.py, refresh_pptx_icon_index.py. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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# Deploy agentic AI with Oracle Cloud Infrastructure AI Agent Platform
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- Source: https://docs.oracle.com/en/solutions/deploy-agentic-ai-agent-platform/index.html
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- Date: 2025-12
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- Type: reference-architecture
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- Services: genai, adb-s, functions
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- Tags: ai-ml, autonomous
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## Summary (catalog)
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Enterprise AI chatbot integrating Visual Builder, Digital Assistant, and OCI AI Agent Platform. RAG from unstructured data, structured queries via ADB-S, custom business logic through serverless Functions.
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## Architecture (fetched from source)
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Architecture
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This is an enterprise-grade OCI architecture for building advanced
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generative AI chatbots that blend conversational AI, secure data access, RAG, and
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extensible business logic.
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Users interact with a web application built using Oracle Visual Builder . The application integrates with Oracle Digital Assistant , which manages conversational interactions and routes user queries to the appropriate backend services. The Digital Assistant connects to the OCI Generative AI Agent Platform, which intelligently orchestrates requests to different tools:
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- The RAG Tool retrieves relevant information from OCI Object Storage for context-aware responses.
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- The SQL Tool queries structured data in the Oracle Autonomous AI Database ( Oracle Autonomous Transaction
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Processing ) to answer specific data-driven questions.
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- The Custom Tool invokes serverless functions for specialized tasks like
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document understanding or integrating external data (e.g., weather).
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Together, these services leverage Oracle Cloud Infrastructure to deliver an intelligent,
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responsive, and extensible AI-driven experience that combines conversational AI,
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real-time data access, and custom functionality.
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The following diagram illustrates this reference architecture.
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Description of the illustration agentic-ai-oci-ai-agent-arch.png
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agentic-ai-oci-ai-agent-arch-oracle.zip
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The architecture has the following components:
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- Region
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An OCI region
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is a localized geographic area that contains one
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or more data centers, hosting availability
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domains. Regions are independent of other regions,
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and vast distances can separate them (across
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countries or even continents).
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- Oracle Services Network
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The Oracle Services Network (OSN) is a conceptual network on OCI that is reserved for Oracle services. These services have public IP addresses that you can reach over the internet. Hosts outside Oracle Cloud can access the OSN privately by using Oracle Cloud
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Infrastructure FastConnect or VPN Connect. Hosts in your VCNs can access the OSN privately through a service gateway.
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- Oracle Visual Builder
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Oracle Visual Builder is an intuitive development experience on top of a development and hosting
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platform that empowers you to create engaging responsive applications. Focusing
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on ease of use and a visual development approach, it provides an easy way for
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you to create applications that are hosted in Oracle’s secure and scalable cloud
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platform.
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- Oracle Digital Assistant
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Oracle Digital Assistant is a platform that allows you to create and deploy digital assistants for your users. With Oracle Digital Assistant , you can create AI-driven interfaces (or chatbots) for business applications through text, chat, and voice interfaces. Each digital assistant has a collection of one or more specialized skills to help users complete a variety of tasks in natural language conversations. For example, an individual digital assistant might have skills that focus on specific types of tasks such as tracking inventory, submitting time cards, and creating expense reports.
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- OCI AI Agent Platform
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Oracle Cloud Infrastructure (OCI) AI
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Agent Platform provides a fully managed, cloud native solution that lets you
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build, deploy, and manage AI agents. By leveraging state-of-the-art large
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language models (LLMs), the AI agents you create can revolutionize the way you
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interact with customers, perform complex tasks autonomously, automate workflows,
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approach business problems. The service integrates across the Oracle stack,
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including databases and cloud infrastructure, enabling efficient data retrieval
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and API interactions.
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- OCI Object Storage
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OCI Object Storage provides access to large amounts of structured and unstructured data of any content type, including database backups, analytic data, and rich content such as images and videos. You can safely and securely store data directly from applications or from within the cloud platform. You can scale storage without experiencing any degradation in performance or service reliability.
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- Oracle Autonomous Transaction
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Processing
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Oracle Autonomous Transaction
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Processing is a self-driving, self-securing, self-repairing database service that is optimized for transaction processing workloads. You do not need to configure or manage any hardware, or install any software. OCI handles creating, backing up, patching, upgrading, and tuning the database.
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- Oracle AI Database 26ai
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Oracle AI Database 26ai with AI Vector Search lets you query data
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by meaning rather than keywords. Vector
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representations (embeddings) capture the semantics
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of text, images, audio, and more so you can find
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similar content efficiently. Built-in SQL distance
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functions allow similarity searches using vectors.
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You can combine semantic similarity and other
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search criteria to ground large language models
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(RAG) for more accurate and relevant
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answers.
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- OCI Functions
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Oracle Cloud Infrastructure
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Functions is a fully-managed, multitenant, highly scalable, on-demand, Functions-as-a-Service (FaaS) platform. It is powered by the Fn Project open source engine. OCI Functions enables you to deploy your code, and either call it directly or trigger it in response to events. OCI Functions uses Docker containers hosted in Oracle Cloud Infrastructure
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Registry .
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Deploy
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To deploy this architecture, follow the instructions in this Live
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Lab:
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Build Agentic AI Solution with Multi-Tool Capabilities powered by
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OCI AI Agent Framework
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Explore More
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Learn more about deploying AI agents using Oracle Cloud
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Infrastructure .
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Review these additional resources:
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- Deploy an ODA Chatbot powered by Generative AI
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Agents (LiveLab)
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- Deploy a Chatbot powered by
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Generative AI Agents using 23ai Vector DB (LiveLab)
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- OCI AI Agents
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- OCI AI Agents
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Documentation
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- Overview of Digital Assistants and
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Skills
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- Oracle Cloud
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Infrastructure Documentation
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- Well-architected framework
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for Oracle Cloud Infrastructure
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Acknowledgments
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- Authors : Luke Farley, Abhinav Jain
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- Contributor : Kaushik Kundu
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Title and Copyright Information
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Deploy agentic AI using Oracle Cloud Infrastructure AI Agent Platform
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G39281-01
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December 2025
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Copyright © 2025,
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Oracle and/or its affiliates.
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