OpenTech workshop. Fill in more labs.

.spellcheck-en-custom.txt

@@ -1,9 +1,12 @@
-Akers
-Augumented
 acp
 ACP
-Arize
+ai
+Akers
+Anthropic
 api
+Arize
+Augumented
+auth
 beeai
 BeeAI's
 BJ
@@ -19,6 +22,7 @@ config
 configs
 Coreutils
 csv
+customizable
 dataframe
 dataset
 datetime
@@ -39,15 +43,18 @@ groq
 Hargrave
 Homebrew
 Huggingface
+hostable
 ibm
 ImageMagick
 inferencing
 InstructLab
+integrations
 ipynb
 ipython
 jupyter
 Jupyter
 Kaggle
+Kubernetes
 Langchain
 localhost
 LLM
@@ -118,6 +125,7 @@ url
 uv
 verifiers
 virtualenv
+watsonx
 workspaces
 WSL
 Vectorization

docs/opentech/agentstack/overview/README.md

@@ -0,0 +1,66 @@
+---
+title: Introduction to Agent Stack
+description: Introduction to Agent Stack
+logo: images/BeeAI-Logo-White.png
+---
+
+# Introduction to Agent Stack
+
+In this demo. You'll master the fundamental components of **Agent Stack** by building and running a Conference Prep Agent that helps field marketing teams prepare for conference season.
+
+Through hands-on exercises, you'll learn how to create intelligent agents with real-world applications.
+
+<hr>
+
+## 🎯 Scenario
+
+The Field Marketing Lead has asked you to help prepare their team for conference season. You'll create a **Conference Prep Agent** that intelligently combines multiple information sources to provide comprehensive conference preparation materials.
+
+Your agent will integrate three powerful tools:
+
+1. **Web Search** – Collect relevant news and up-to-date information about attendees, speakers, and industry trends
+2. **Wikipedia Tool** – Provide company history and background details on organizations and key people
+3. **Internal Knowledge Base** – Access the team's internal notes and artifacts for context-specific information
+
+<hr>
+
+## 📚 What You'll Learn
+
+Through interactive coding exercises, you'll gain hands-on experience with:
+
+### Agent Stack
+
+- **Serving agents** – Run an agent from source and see it automatically register with Agent Stack
+- **UI forms** – Use a form as input to the agent with the Agent Stack UI
+- **Monitoring** – Monitor and debug agents with built-in logging and tracing capabilities
+
+### Agent Core Components
+
+- **System Prompts** – Learn the foundation of agent behavior by crafting effective prompts that guide your agent's responses
+- **RequirementAgent** – Explore BeeAI Framework's powerful agent implementation that provides fine-grained control over agent behavior
+- **LLM Providers** – Work with both local and hosted model options to understand deployment flexibility
+
+### Advanced Features
+
+- **Memory Systems** – Implement conversation context to maintain coherent, contextual interactions across sessions
+- **Tools Integration** – Extend agent capabilities by integrating external APIs and data sources
+- **Conditional Requirements** – Enforce business logic and rules to ensure compliance and consistency
+
+<hr>
+
+## Workshop Structure
+
+To ensure a smooth experience, follow the steps in this order:
+
+1. ✅ [Prework](../pre-work/README.md) – Install dependencies and gather API keys
+2. 🔧 [Setup](../setup/README.md) – Get the code and environment ready
+4. 🤖 [Run the agent](../run/README.md) – Assemble and run your agent
+
+<hr>
+
+## Learn more about Agent Stack
+
+- 📚 **Agent Stack documentation**: [https://agentstack.beeai.dev/introduction/welcome](https://agentstack.beeai.dev/introduction/welcome)
+- 🧠 **GitHub repository**: [https://github.com/i-am-bee/agentstack](https://github.com/i-am-bee/agentstack)
+
+Ready to build your first intelligent agent? Let's dive in! 🐝

docs/opentech/agentstack/pre-work/README.md

@@ -0,0 +1,57 @@
+---
+title: Prework
+description: Prework Instructions
+logo: images/BeeAI-Logo-White.png
+---
+
+# Agent Stack: Prework Instructions
+
+Welcome to the Introduction to Agent Stack.
+Please complete the following setup steps **before** the workshop.
+
+---
+
+## Python Environment Manager
+
+### `uv` (Recommended)
+
+We recommend using [`uv`](https://github.com/astral-sh/uv) as your Python package and environment manager.
+
+- If you’re unfamiliar with `uv`, refer to the [uv installation guide](https://github.com/astral-sh/uv#installation)
+- `uv` is a fast and modern alternative to pip and virtualenv, fully compatible with both
+
+---
+
+## Local Model
+
+### Install Ollama
+
+!!! note
+    To run the Granite model locally, we recommend having at least **16GB of RAM** for optimal performance.
+
+To run models locally on your machine:
+
+1. Download and install Ollama: [https://ollama.com/download](https://ollama.com/download)
+2. Run or pull the Granite model:
+
+   ```bash
+   ollama pull granite4:micro-h
+   ```
+
+   or
+
+   ```bash
+   ollama run granite4:micro-h
+   ```
+
+### Granite model links
+
+- Ollama models: [Granite 4](https://ollama.com/library/granite4)
+- Ollama models: [Granite 3.3](https://ollama.com/library/granite3.3)
+- Granite docs: [Granite](https://www.ibm.com/granite/docs/models/granite)
+
+---
+
+## You're Ready
+
+Once you've completed these steps, you're ready to setup the project.

docs/opentech/agentstack/run/README.md

@@ -0,0 +1,113 @@
+---
+title: Agent Stack
+description: Run the Agent Stack and use your agents in the UI
+logo: images/BeeAI-Logo-White.png
+---
+
+# Interact with your agents using Agent Stack
+
+Agent Stack is an open, self-hostable infrastructure for deploying AI agents built with any framework. A Linux Foundation project built on the Agent2Agent Protocol (A2A), Agent Stack gives you everything needed to move agents from local development to shared production environments—without vendor lock-in.
+
+## What Agent Stack provides
+
+Agent Stack provides everything you need to deploy and operate agents in production:
+
+* Self-hostable server to run your agents
+* Web UI for testing and sharing deployed agents
+* CLI for deploying and managing agents
+* Runtime services your agents can access:
+
+    * LLM Service — Switch between 15+ providers (Anthropic, OpenAI, watsonx.ai, Ollama) without code changes
+    * Embeddings & vector search for RAG and semantic search
+    * File storage — S3-compatible uploads/downloads
+    * Document text extraction via Docling
+    * External integrations via MCP protocol (APIs, Slack, Google Drive, etc.) with OAuth
+    * Secrets management for API keys and credentials
+* SDK (`agentstack-sdk`) for standardized A2A service requests
+* HELM charts for Kubernetes deployments with customizable storage, databases, and auth
+
+## Lab
+
+### 1. Install Agent Stack
+
+Install Agent Stack using the [installation instructions in the documentation](https://agentstack.beeai.dev/introduction/quickstart#installation).
+
+#### Follow the "One-Line Install"
+
+To install a specific version of Agent Stack, set the `AGENTSTACK_VERSION` environment variable before running the install script.  For example:
+
+```bash
+sh -c "$(AGENTSTACK_VERSION=0.4.1 curl -LsSf https://raw.githubusercontent.com/i-am-bee/agentstack/HEAD/install.sh)"
+```
+
+### 2. Start the Agent Stack (optionally with Phoenix and Docling enabled)
+
+Agent Stack includes OpenTelemetry instrumentation to collect traces and metrics. Telemetry data helps with performance monitoring, error tracking, usage analytics, and debugging agent interactions.
+
+> Important License Notice: Phoenix is disabled by default in Agent Stack. When you enable Phoenix, be aware that Arize Phoenix is licensed under the Elastic License v2 (ELv2), which has specific terms regarding commercial use and distribution. By enabling Phoenix, you acknowledge that you are responsible for ensuring compliance with the ELv2 license terms for your specific use case. Please review the Phoenix license before enabling this feature in production environments.
+
+* To start the Agent Stack with Arize Phoenix use `--set phoenix.enabled=true`
+* To start the Agent Stack with Docling use `--set docling.enabled=true`
+
+```shell
+agentstack platform start --set phoenix.enabled=true --set docling.enabled=true
+```
+
+### 3. Launch the UI
+
+In your terminal, run:
+
+```shell
+agentstack ui
+```
+
+You should be prompted to select a model provider and model if you did not already set these.
+For this lab, use Ollama and granite4:micro-h. for the language model.
+
+You should see the UI launch in your browser.
+
+!!! insight
+    If you navigate to the menu bar on the left hand side you will see a list of agents. These example agents come with Agent Stack.  We'll add our custom agent in steps that follow.
+
+### 4. Serve the agent
+
+In your terminal, run the agent:
+
+```shell
+uv run src/agent.py --directory agentstack
+```
+
+!!! insight
+    If you take a look at the code pay special attention to the metadata in the `@server.agent` decorator. The metadata is used by the UI.
+
+### 5. Run the agent
+
+1. Navigate to the menu bar on the left hand side of the UI and select the Conference Prep Agent. You might need to refresh the page.
+
+2. Notice that we build a form UI.
+
+    * `Task` is the main input to the agent.
+    * `Company name` is especially useful if your task doesn't mention the company name
+    * `Style` suggests the type of output you want. `detailed` is typically longer and may include source citations. `list` is a good option if you like bullet points.
+    * The `Event` name and `Event date` are used here primarily for UI demo purposes.
+
+3. Experiment with the different form fields. Try using one of the following tasks:
+
+    * Brief me for a Shopify meeting at the conference. Give me an overview of the company, some recent news about them, and anything important I need to know from our internal notes.
+
+    * I'm planning on meeting the Moderna rep at the next conference. Remind me where we left off on previous discussions.
+
+    * Build a security talking sheet for Siemens Energy. How does their strategy compare to their competitors'?
+
+4. Try different inputs.
+
+5. Explore:
+
+    * the trajectory steps (look in "How did I get this answer?")
+    * the captured details in Arize Phoenix
+        * browse to `http://localhost:6006/`
+        * open project "default"
+        * Select "All" (not Root Spans)
+        * Most details show up after the run
+        * Look under "All" and not "Root"
+    * source citations (not always present)

docs/opentech/agentstack/setup/README.md

@@ -0,0 +1,45 @@
+---
+title: Setup Instructions
+description: Setup the repo and environment
+logo: images/BeeAI-Logo-White.png
+---
+
+# Setup Instructions
+
+## Get the Demo Code
+
+**Option A: Clone with Git (Recommended):**
+
+```bash
+git clone https://github.com/IBM/beeai-workshop.git
+```
+
+**Option B: Download ZIP:**
+
+If you're not comfortable with Git, [download the ZIP](https://github.com/IBM/beeai-workshop/archive/refs/heads/main.zip) file and extract it to your desired location.
+
+---
+
+## Navigate to the demo folder
+
+Navigate to the specific demo folder:
+
+```bash
+cd beeai-workshop/opentech
+```
+
+**Important:**  
+Make sure to open the specific `opentech` folder, not the entire `beeai-workshop` directory.  
+This ensures proper project structure and dependencies are detected.
+
+---
+
+## Install Project Dependencies
+
+1. **Install all required dependencies:**
+
+    ```bash
+    uv --directory agentstack sync
+    ```
+
+This ensures you have the correct versions of all packages used in the lab, installed in the correct environment.