Merge branch 'main' into ppaolucc-mcp-server-may2026-I

Author: ppaolucc-it

ai/generative-ai-service/coding-assistant/README.md

@@ -2,17 +2,22 @@
 
 A practical guide for configuring Cline to call OCI Generative AI models through OCI's OpenAI-compatible API.
 
+Cline is an AI coding assistant that works inside your IDE and can help with day-to-day development tasks such as explaining unfamiliar code, generating new files, refactoring existing logic, writing tests, debugging errors, and summarizing repository structure. By connecting Cline to OCI Generative AI, developers can use OCI-hosted models directly from their coding environment while keeping model access, deployment choices, and enterprise controls within Oracle Cloud Infrastructure.
+
+This setup is useful when teams want AI-assisted development workflows that can use either on-demand OCI Generative AI models for quick setup or Dedicated AI Cluster (DAC)-hosted models for production-grade isolation, performance, and customization.
+
 ## Overview
 
 This tutorial walks through configuring Cline to use OCI Generative AI models through the OCI OpenAI-compatible API.
 
 The process involves:
 
 1. Selecting an OCI Generative AI model
-2. Understanding the OCI OpenAI-compatible API endpoint URL
-3. Creating an OCI Generative AI API key
-4. Configuring Cline with the OCI OpenAI-compatible base URL, API key, and model ID
-5. Testing the setup with an example prompt
+2. Choosing whether to use the model on demand or from a Dedicated AI Cluster (DAC)
+3. Understanding the OCI OpenAI-compatible API endpoint URL
+4. Creating an OCI Generative AI API key
+5. Configuring Cline with the OCI OpenAI-compatible base URL, API key, and model ID
+6. Testing the setup with an example prompt
 
 OCI provides OpenAI-compatible APIs for model inference, including Chat Completions and Responses. This tutorial uses the OCI Generative AI OpenAI-compatible API documented here:
 
@@ -42,21 +47,30 @@ Example regions include:
 - `uk-london-1`
 - `eu-frankfurt-1`
 
-The region is used in the OpenAI-compatible base URL.
+The region is used in the OpenAI-compatible URL.
 
-Example:
+On-demand example:
 
 ```text
 https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/openai/v1
 ```
 
-**Important:** Create the OCI Generative AI API key in the same region where you plan to use the model.
+DAC Chat Completions example:
+
+```text
+https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/openai/v1/chat/completions
+```
+
 
 ### 2. Choose a Model
 
-Select the OCI Generative AI model that you want Cline to use.
+Select the OCI Generative AI model that you want Cline to use. OCI Generative AI models can be used either on demand or from a Dedicated AI Cluster (DAC). The Cline setup is different for each option, so choose the deployment path first.
+
+#### On-Demand Models
+
+On-demand models are shared, OCI-hosted models that are ready to call directly through the OpenAI-compatible API. This is the simplest setup for testing, prototyping, and lighter usage patterns.
 
-Example model IDs:
+Example OCI Model Names:
 
 ```text
 xai.grok-code-fast-1
@@ -66,20 +80,54 @@ openai.gpt-oss-120b
 google.gemini-2.5-flash
 ```
 
+For on-demand models, the Cline **Model ID** is the OCI Model Name.
+
+#### Dedicated AI Cluster (DAC)-Hosted Models
+
+DAC-hosted models run on dedicated infrastructure in your tenancy. Use a DAC-hosted model when you need production-grade control over model hosting and inference. DACs provide several advantages:
+
+- **Flexibility:** Import supported Hugging Face-format models from Hugging Face or Object Storage, test imported models with shorter commitments, choose fine-tuned or quantized versions, and right-size based on visible hardware specifications.
+- **Isolation:** Run workloads on dedicated GPU resources inside your tenancy, which helps protect sensitive data, avoids shared-resource contention, and supports regulated workloads.
+- **Predictable latency:** Dedicated infrastructure can provide more stable time-to-first-token and inference response times than shared model endpoints, especially for scaling production applications.
+- **Fine-tuning support:** Host fine-tuned models alongside base models, run multiple fine-tuned models on a single cluster, and control model lifecycle and upgrade cadence.
+- **Cost efficiency at scale:** For inference-heavy workloads, DACs can reduce effective price per token by keeping dedicated resources highly utilized and hosting multiple models on one cluster.
+- **Deployment near data:** Deploy in supported OCI regions, including regulated regions where available, to support data residency, lower latency, and simpler security reviews.
+- **Simplified management:** OCI manages the infrastructure while you manage model deployment, scaling, fine-tuning, and application integration.
+
+Before configuring Cline for a DAC-hosted model, make sure the model endpoint is already created and active.
+
+1. Open the OCI Console
+2. Navigate to **Analytics & AI -> Generative AI**
+3. Go to **Endpoints**
+4. Confirm that the endpoint for your DAC-hosted model is **Active**
+5. Keep note of the endpoint region and DAC endpoint OCID
+
+For DAC-hosted models, the Cline **Model ID** is the DAC endpoint OCID.
+
+```text
+ocid1.generativeaiendpoint.<region>..<unique_id>
+```
+
 ### 3. Understand the OCI OpenAI-Compatible API Endpoint URL
 
-All calls from Cline go through the OCI OpenAI-compatible API endpoint URL:
+Cline uses a different OCI OpenAI-compatible endpoint format depending on whether the model is on demand or DAC-hosted.
+
+For on-demand models, configure the base URL **without** `/chat/completions`:
 
 ```text
 https://inference.generativeai.<region>.oci.oraclecloud.com/openai/v1
 ```
 
-This base URL is the endpoint you configure in Cline.
+For DAC-hosted models, configure the full Chat Completions URL **with** `/chat/completions`:
+
+```text
+https://inference.generativeai.<region>.oci.oraclecloud.com/openai/v1/chat/completions
+```
 
 Keep note of the following values:
 
 - Region
-- Model ID
+- OCI Model Name or DAC endpoint OCID
 - Compartment
 
 ### 4. Create an OCI Generative AI API Key
@@ -94,18 +142,18 @@ Keep note of the following values:
 cline-genai-key
 ```
 
-6. Optionally add a description
+6. Add a description if needed
 7. Configure key names and expiration dates
 8. Click **Create**
-9. Copy one of the generated key values immediately
+9. Copy one of the generated key values
 
 OCI Generative AI API keys are service-specific credentials and are different from OCI IAM API keys.
 
-**Important:** Store the key securely. Do not commit it to GitHub or place it in source code.
+⚠️ Store the key securely. Do not commit it to GitHub or place it in source code.
 
-### 5. Build the OCI OpenAI-Compatible Base URL
+### 5. Build the OCI OpenAI-Compatible URL
 
-Use the following base URL format for Cline:
+For on-demand models, use the following base URL format for Cline:
 
 ```text
 https://inference.generativeai.<region>.oci.oraclecloud.com/openai/v1
@@ -117,6 +165,14 @@ Example for US Midwest Chicago:
 https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/openai/v1
 ```
 
+For DAC-hosted models, use the full Chat Completions URL shown in the DAC section.
+
+Example for UK South London:
+
+```text
+https://inference.generativeai.uk-london-1.oci.oraclecloud.com/openai/v1/chat/completions
+```
+
 
 ### 6. Configure Cline
 
@@ -130,29 +186,43 @@ Open VS Code or PyCharm and configure Cline:
 OpenAI Compatible
 ```
 
-4. Set **Base URL** to your OCI base URL:
+4. Set **Base URL** to your OCI URL.
+
+For on-demand models:
 
 ```text
 https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/openai/v1
 ```
 
+For DAC-hosted models:
+
+```text
+https://inference.generativeai.uk-london-1.oci.oraclecloud.com/openai/v1/chat/completions
+```
+
 5. Paste your OCI Generative AI API key into the **API Key** field
-6. Set **Model ID** to your OCI model ID
+6. Set **Model ID** to your OCI Model Name or DAC endpoint OCID
 
 Example:
 
 ```text
 xai.grok-code-fast-1
 ```
 
+For a DAC-hosted model, use the DAC endpoint OCID instead:
+
+```text
+ocid1.generativeaiendpoint.<region>..<unique_id>
+```
+
 7. Save the configuration
 
 ### 7. Test the Connection in Cline
 
 Use a simple prompt first:
 
 ```text
-Write a one-sentence commit message for a change that adds OCI Generative AI support to a Cline tutorial.
+Hello. Reply with one sentence confirming that the connection works.
 ```
 
 If the setup is correct, Cline should return a normal response from the OCI-hosted model.
@@ -186,9 +256,9 @@ Check that:
 
 Check that:
 
-- The model ID is correct
 - The model is available in the selected region
 - The model supports OpenAI-compatible chat completion requests
+- If using a DAC-hosted model, the OCI Generative AI endpoint is active and the Model ID field uses the DAC endpoint OCID
 
 ### Authorization Error
 
@@ -204,19 +274,25 @@ Check that:
 Check that:
 
 - The base URL uses the correct region
-- The URL ends with:
+- For on-demand models, the URL ends with:
 
 ```text
 /openai/v1
 ```
 
+- For DAC-hosted models, the URL ends with:
+
+```text
+/openai/v1/chat/completions
+```
+
 - Your network can reach OCI public endpoints
+- Private endpoints are reachable from your machine if using private networking
 
 ## Recommended Tests
 
 Run the following tests in Cline:
 
-- Simple math prompt
 - Short coding task
 - Code explanation prompt
 - Refactoring prompt
@@ -229,10 +305,12 @@ If this was only a test setup:
 
 1. Remove the API key from Cline
 2. Revoke or deactivate the OCI Generative AI API key
+3. If using a DAC-hosted model only for testing, delete the endpoint before deleting the Dedicated AI Cluster
 
 ## OCI Services Used
 
-- **OCI Generative AI** - Model inference
+- **OCI Generative AI** - Model inference and endpoints
+- **OCI Generative AI Dedicated AI Clusters** - Dedicated hosting for deployed models
 - **OCI IAM** - Policies and authorization
 - **OCI Generative AI API Keys** - API key authentication
 - **Cline** - AI coding assistant in VS Code or PyCharm

app-dev/app-integration-and-automation/shared-assets/README.md

@@ -37,6 +37,42 @@ This section contains various examples related to Application Integration: demo
 
 ## Demos
 
+- [Developer Coaching - Unlocking AI-Driven Automation with Oracle Integration Cloud](https://youtu.be/uXpIVhgdvDA?si=RSbBr4XS-ep0jUrC)
+
+    In this session we have explored how developers can build intelligent, real-world AI workflows using Oracle Integration Cloud together with OCI AI Services, with minimal custom code. Key theme is around Customer Support.
+
+    Some of the live demos included:
+
+    ✅ OCI Language for real-time sentiment analysis of customer interactions  
+    ✅ OCI Speech for converting speech to text in automated workflows  
+    ✅ Human-in-the-loop escalation
+
+    ✅ OCI Generative AI for dynamic AI-powered content generation  
+    ✅ Native Actions in OIC to orchestrate end-to-end intelligent automation
+
+    ✅ Exposing Integrations as AI-callable tools with MCP Server in OIC  
+
+    The focus is on practical implementation patterns for AI-driven customer support scenarios, showing how quickly developers can bring AI capabilities directly into enterprise workflows.
+
+- [Developer Coaching - Beyond Integration - Designing Agentic AI with Oracle Integration & MCP](https://youtu.be/UyU3-TwGSGU?si=X1zCN3CFqksgBl8t)
+
+    This session covers following key topic
+
+    ✅ 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝘄𝗶𝘁𝗵 𝗢𝗿𝗮𝗰𝗹𝗲 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 — How OIC fits into agentic architectures where AI agents reason, select tools, and invoke OIC flows to orchestrate real business processes.
+
+    ✅ 𝗘𝘅𝗽𝗼𝘀𝗲 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝘀 𝗠𝗖𝗣 𝗧𝗼𝗼𝗹𝘀 — Publishing OIC integrations as Model Context Protocol (MCP) endpoints — discoverable, callable, and OAuth-secured for AI agents.
+
+    𝗟𝗶𝘃𝗲 𝗠𝗖𝗣 𝘁𝗼𝗼𝗹 𝗰𝗮𝗹𝗹𝘀 𝗱𝗲𝗺𝗼𝗻𝘀𝘁𝗿𝗮𝘁𝗲𝗱 𝗳𝗿𝗼𝗺:
+    → 𝗣𝗼𝘀𝘁𝗺𝗮𝗻
+    → 𝗟𝗮𝗻𝗴𝗙𝗹𝗼𝘄
+    → 𝗙𝘂𝘀𝗶𝗼𝗻 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗦𝘁𝘂𝗱𝗶𝗼
+
+    ✅ 𝗢𝗜𝗖 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 — Building workflows where AI agents invoke multiple integrations to trigger, orchestrate, and enrich enterprise processes.
+
+    ✅ 𝗥𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗗𝗲𝗺𝗼𝘀 — Invoice automation using OCI Document Understanding & ERP Cloud, and Expense Report approval with human-in-the-loop workflows.
+
+    If you're building new integrations or modernising existing ones, this session offers practical skills to design intelligent, scalable, and secure agentic solutions.
+
 - [Developer Coaching - From Build to Insight Oracle Integration’s Embedded AI Features](https://youtu.be/yXXxpwrbacQ?si=Qs1dabQm_sQHoFGy)
 
     This developer coaching session highlights how Oracle Integration’s embedded AI features simplify and accelerate the design, build, and optimization of integrations.
@@ -294,6 +330,28 @@ This section contains various examples related to Application Integration: demo
 
 ## Blogs
 
+-[How We Built an AI Agent on Top of Enterprise Systems](https://www.linkedin.com/pulse/how-we-built-ai-agent-top-enterprise-systems-harris-qureshi-ask2f/)
+
+One thing most enterprise AI projects get wrong:
+
+They connect the AI directly to the API and call it done.
+
+No governance. No audit trail. No identity propagation. No error handling. No way to reach systems securely on-premise, multi-cloud, or legacy.
+
+In Part 1, I wrote about why the future is AI unlocking enterprise systems — not replacing them.
+
+This is Part 2. The architecture. The protocol. Exactly how we built it.
+
+-[The Enterprise AI Moment Nobody Is Talking About](https://www.linkedin.com/pulse/enterprise-ai-moment-nobody-talking-harris-qureshi-ct0nf/)
+
+The future isn't AI replacing your enterprise systems.
+
+It's AI unlocking them.
+
+Most enterprises are sitting on years of data, logic, and investment — and their people still can't get a straight answer without navigating a maze of screens.
+
+That's changing. Here's how — and what to get right before you start.
+
 -[A Beginner’s Guide to Using OCI Generative AI with Oracle Integration](https://www.linkedin.com/pulse/beginners-guide-using-oci-generative-ai-oracle-harris-qureshi-wqcof/)
 
 Designed for Oracle Integration developers, this beginner-friendly guide walks you through:

app-dev/developer-tools-and-lowcode/batch/video-transcoding/20190530-SPITZRf-0001-Stars of Cephus~small.mp4

@@ -0,0 +1,16 @@
+
+FROM ubuntu:22.04
+
+RUN apt-get update && \
+    apt-get install -y ffmpeg curl python3 python3-pip unzip && \
+    pip3 install oci-cli && \
+    rm -rf /var/lib/apt/lists/*
+
+RUN mkdir -p /video && chmod 777 /video
+
+WORKDIR /video
+
+COPY entrypoint.sh /entrypoint.sh
+RUN chmod +x /entrypoint.sh
+
+ENTRYPOINT ["/entrypoint.sh"]