diff --git a/ai/common.sh b/ai/common.sh
new file mode 100755
index 00000000..c90ab8fd
--- /dev/null
+++ b/ai/common.sh
@@ -0,0 +1,105 @@
+#!/bin/bash
+
+# ==============================
+# COMMON FUNCTIONS
+# ==============================
+
+RED="\033[31m"
+BLUE="\033[94m"
+GREEN="\033[32m"
+ENDCOLOR="\033[0m"
+
+function print_error {
+    echo -e "${RED}\n==========================================${ENDCOLOR}"
+    echo -e "${RED} FAILED${ENDCOLOR}"
+    echo -e "${RED}==========================================\n${ENDCOLOR}"
+    echo -e "${RED}$1${ENDCOLOR}"
+    echo -e ""
+}
+function print_msg {
+    echo -e "${BLUE}$1${ENDCOLOR}"
+}
+function print_success {
+    echo -e "${GREEN}$1${ENDCOLOR}"
+}
+
+# Helper function to check whether prerequisites are installed
+function check_prerequisites {
+    # Ensure that jq tool is installed
+    if ! command -v jq &>/dev/null; then
+        print_error "'jq' tool is not installed"
+        exit 1
+    fi
+}
+
+# ==============================
+# COMMON IBMCLOUD HELPERS
+# ==============================
+
+# helper function to check whether IBM Cloud CLI plugins should get updated, or not
+function ensure_plugin_is_up_to_date() {
+    echo "Checking $1 ..."
+    # check whether plugin is installed
+    if ! ibmcloud plugin show $1 -q >/dev/null; then
+        # install it
+        ibmcloud plugin install $1 -f --quiet
+    else 
+        # check whether there is an update available
+        ibmcloud plugin update $1 -f --quiet
+    fi
+}
+
+function target_region {
+    print_msg "\nTargetting IBM Cloud region '$1' ..."
+    current_region=$(ibmcloud target --output JSON |jq -r '.region|.name')
+    if [[ "$current_region" != "$1" ]]; then
+        ibmcloud target -r $1 --quiet
+    fi
+}
+
+function target_resource_group {
+    print_msg "\nTargetting resource group '$1' ..."
+    current_resource_group_guid=$(ibmcloud target --output JSON |jq -r '.resource_group|.guid')
+    new_resource_group_guid=$(ibmcloud resource group $1 -output json|jq -r '.[0].id')
+    if [[ "$current_resource_group_guid" != "$new_resource_group_guid" ]]; then
+        ibmcloud target -g $1 --quiet
+    fi
+     echo "Done"
+}
+
+function does_instance_exist {
+    (( $(ibmcloud resource search "service_name:\"$1\" AND name:\"$2\"" --output JSON|jq -r '.items|length') > 0 ))
+}
+
+function does_serviceid_exist {
+    (( $(ibmcloud resource search "type:serviceid AND name:\"$1\"" --output JSON|jq -r '.items|length') > 0 ))
+}
+
+function has_bucket_name_with_prefix {
+    buckets=$(ibmcloud cos buckets -output json)
+    COS_BUCKET_NAME=""
+    if [[ "$(echo "${buckets}" | jq -r '.Buckets')" != "null" ]]; then
+        for bucket in $(echo "${buckets}" | jq -r '.Buckets|.[] | @base64'); do
+            _jq() {
+                echo ${bucket} | base64 --decode | jq -r ${1}
+            }
+            bucket_name=$(_jq '.Name')
+            if [[ "$bucket_name" =~ ^$1-* ]]; then 
+                COS_BUCKET_NAME=$bucket_name
+            fi
+        done
+    fi
+    echo $COS_BUCKET_NAME
+}
+
+
+function abortScript() {
+    if [[ "${CLEANUP_ON_ERROR}" == true ]]; then
+        clean
+    else
+        print_msg "\nSkipping deletion of the created IBM Cloud resources. Please be aware that the created resources will occur costs in your account."
+        echo "$ ibmcloud resource service-instances --type all -g $resource_group_name --location $REGION"
+        ibmcloud resource service-instances --type all -g $resource_group_name --location $REGION
+    fi
+    exit 1
+}
\ No newline at end of file
diff --git a/ai/langchain-skills-agent/.env.sample b/ai/langchain-skills-agent/.env.sample
new file mode 100644
index 00000000..7b4b2c7d
--- /dev/null
+++ b/ai/langchain-skills-agent/.env.sample
@@ -0,0 +1,14 @@
+# LLM Configuration (OpenAI-compatible API)
+# Configure your inference backend here
+
+# IBM watsonx.ai
+INFERENCE_BASE_URL=https://eu-de.ml.cloud.ibm.com
+INFERENCE_API_KEY="YOUR_API_KEY"
+INFERENCE_MODEL_NAME="meta-llama/llama-3-2-11b-vision-instruct"
+INFERENCE_PROJECT_ID="YOUR_PROJECT_ID"
+
+
+# IBM Cloud Configuration (for deployment)
+REGION=eu-de
+PROJECT_NAME=langchain-skills-agent-project
+NAME_PREFIX=ce-langchain-agent
\ No newline at end of file
diff --git a/ai/langchain-skills-agent/.gitignore b/ai/langchain-skills-agent/.gitignore
new file mode 100644
index 00000000..e4d72c7b
--- /dev/null
+++ b/ai/langchain-skills-agent/.gitignore
@@ -0,0 +1,16 @@
+# Environment files
+.env
+
+# Python
+__pycache__/
+*.py[oc]
+.venv/
+*.egg-info
+
+# IDE
+.vscode/
+.idea/
+
+# OS
+.DS_Store
+Thumbs.db
\ No newline at end of file
diff --git a/ai/langchain-skills-agent/README.md b/ai/langchain-skills-agent/README.md
new file mode 100644
index 00000000..82b6711b
--- /dev/null
+++ b/ai/langchain-skills-agent/README.md
@@ -0,0 +1,341 @@
+# LangChain Skills Agent on Code Engine
+
+A modular, skill-based agent built with LangChain that demonstrates a clean architecture for organizing agent capabilities. This agent provides weather forecasting, travel recommendations, and currency conversion through a dynamic skill loading system.
+
+## Why IBM Cloud Code Engine
+
+[IBM Cloud Code Engine](https://www.ibm.com/products/code-engine) is a great fit for containerized agents because it provides:
+
+- **Serverless containers**: Deploy container images without managing infrastructure.
+- **Automatic scaling**: Scale to zero when idle and scale up on demand.
+- **Pay-per-use pricing**: Cost-efficient for intermittent workloads common to agents.
+- **Simple deployment**: Integrates with container registries and CI/CD pipelines.
+- **Managed endpoint**: Provides a secure http endpoint with a managed certificate.
+
+## The architecture
+
+![architecture](./images/architecture.png)
+
+## 🎯 Overview
+
+This agent showcases a **skill-based setup** where each capability is:
+- Self-contained in its own directory
+- Documented with metadata in a `skill.md` file
+- Implemented as a LangChain tool
+- Dynamically discovered and loaded at runtime
+
+
+### Key Features
+
+- **🔧 Modular Skills**: Each skill is independent and easy to add/remove
+- **📝 Metadata-Driven**: Skills include YAML frontmatter with configuration
+- **🔄 Dynamic Loading**: Skills are automatically discovered from the `skills/` directory
+- **🚀 Production Ready**: Containerized and deployable to IBM Cloud Code Engine
+- **🎨 Clean Architecture**: Clear separation of concerns and easy to extend
+
+## 📦 Included Skills
+
+### 1. Weather Forecast 🌤️
+Get current weather and multi-day forecasts for any location worldwide.
+
+**Example:**
+```
+"What's the weather in Tokyo for the next 5 days?"
+```
+
+### 2. Travel Recommendations ✈️
+Personalized destination suggestions based on preferences, budget, and season.
+
+**Example:**
+```
+"Recommend beach destinations for a moderate budget in summer"
+```
+
+### 3. Currency Converter 💱
+Convert between 30+ currencies with exchange rates.
+
+**Example:**
+```
+"Convert 1000 USD to EUR"
+```
+
+## 🏗️ Architecture
+
+```
+langchain-skills-agent/
+├── src/
+│   ├── main.py              # FastAPI app & agent entrypoint
+│   ├── agents.py            # LangChain agent configuration
+│   ├── skill_loader.py      # Dynamic skill discovery & loading
+│   ├── skills/              # Skill directory
+│   │   ├── weather_forecast/
+│   │   │   ├── skill.md     # Metadata & documentation
+│   │   │   └── __init__.py  # Tool implementation
+│   │   ├── travel_recommendations/
+│   │   │   ├── skill.md
+│   │   │   └── __init__.py
+│   │   └── currency_converter/
+│   │       ├── skill.md
+│   │       └── __init__.py
+│   └── frontend/
+│       └── landing_page.py  # Web UI
+├── deploy.sh                # IBM Cloud deployment script
+├── .env.sample              # Environment configuration template
+└── payload/
+    └── payload.json         # Example request payload
+```
+
+## 🚀 Quick Start
+
+### Prerequisites
+
+1. **LLM Backend**: Configure an OpenAI-compatible API endpoint
+   - [IBM watsonx.ai](https://www.ibm.com/products/watsonx-ai) (recommended)
+
+2. **IBM Cloud CLI** (for deployment):
+   ```bash
+   curl -fsSL https://clis.cloud.ibm.com/install/linux | sh
+   ```
+
+### Local Development
+
+1. **Clone and setup**:
+   ```bash
+   cd langchain-skills-agent
+   cp .env.sample .env
+   # Edit .env with your API credentials
+   ```
+
+2. **Install dependencies**:
+   ```bash
+   cd src
+   pip install -e .
+   # or with uv:
+   uv sync
+   ```
+
+3. **Run locally**:
+   ```bash
+   python main.py
+   ```
+
+4. **Test the agent**:
+   ```bash
+   # Visit the landing page
+   open http://localhost:8080
+
+   # Or use the API
+   curl -X POST http://localhost:8080/runs \
+     -H "Content-Type: application/json" \
+     -d @payload/payload.json
+   ```
+
+## ☁️ Deploy to IBM Cloud Code Engine
+
+### Configuration
+
+1. **Copy and configure environment**:
+   ```bash
+   cp .env.sample .env
+   ```
+
+2. **Edit `.env`** with your credentials:
+   ```bash
+   INFERENCE_BASE_URL=https://eu-de.ml.cloud.ibm.com
+   INFERENCE_API_KEY="YOUR_API_KEY"
+   INFERENCE_MODEL_NAME="meta-llama/llama-3-2-11b-vision-instruct"
+   INFERENCE_PROJECT_ID="YOUR_PROJECT_ID"
+   ```
+
+### Deploy
+
+1. **Login to IBM Cloud**:
+   ```bash
+   ibmcloud login --sso
+   # or with API key:
+   ibmcloud login --apikey "$IBMCLOUD_APIKEY"
+   ```
+
+2. **Run deployment**:
+   ```bash
+   ./deploy.sh
+   ```
+
+3. **The script will**:
+   - Create a Code Engine project
+   - Build and deploy the containerized agent
+   - Configure secrets from your `.env` file
+   - Provide the agent URL
+
+### Cleanup
+
+Remove all created resources:
+```bash
+./deploy.sh clean
+```
+
+## 🔌 API Endpoints
+
+### `GET /`
+Landing page with agent information and documentation
+
+### `GET /agents`
+List available agents
+
+### `POST /runs`
+Execute the agent with a query
+
+**Request:**
+```json
+{
+  "messages": [
+    {
+      "role": "user",
+      "content": "What's the weather in Paris?"
+    }
+  ]
+}
+```
+
+### `GET /info`
+Get agent information and loaded skills
+
+### `GET /health`
+Health check endpoint
+
+## 🛠️ Adding New Skills
+
+1. **Create skill directory**:
+   ```bash
+   mkdir -p src/skills/my_new_skill
+   ```
+
+2. **Create `skill.md`** with metadata:
+   ```markdown
+   ---
+   name: "My New Skill"
+   description: "What this skill does"
+   version: "1.0.0"
+   category: "utility"
+   parameters:
+     - name: input
+       type: string
+       required: true
+       description: "Input parameter"
+   ---
+
+   # My New Skill
+
+   Detailed documentation here...
+   ```
+
+3. **Create `__init__.py`** with implementation:
+   ```python
+   from langchain.tools import tool
+
+   @tool
+   def my_new_skill(input: str) -> str:
+       """Tool description for the LLM."""
+       # Implementation here
+       return result
+   ```
+
+4. **Restart the agent** - the skill will be automatically discovered!
+
+## 📊 Skill Metadata Format
+
+Each `skill.md` file uses YAML frontmatter:
+
+```yaml
+---
+name: "Skill Name"
+description: "Brief description"
+version: "1.0.0"
+category: "category_name"
+parameters:
+  - name: param_name
+    type: string|integer|float|boolean
+    required: true|false
+    default: default_value
+    description: "Parameter description"
+---
+```
+
+## 🔧 Configuration
+
+### Environment Variables
+
+| Variable | Description | Example |
+|----------|-------------|---------|
+| `INFERENCE_BASE_URL` | LLM API endpoint | `https://eu-de.ml.cloud.ibm.com` |
+| `INFERENCE_API_KEY` | API key for LLM | `your-api-key` |
+| `INFERENCE_MODEL_NAME` | Model identifier | `watsonx/meta-llama/llama-3-3-70b-instruct` |
+| `INFERENCE_PROJECT_ID` | Project ID (watsonx.ai) | `your-project-id` |
+| `OPENWEATHER_API_KEY` | Weather API key (optional) | `your-key` |
+| `EXCHANGE_RATE_API_KEY` | Exchange rate API key (optional) | `your-key` |
+
+## 🎨 Architecture Highlights
+
+### Dynamic Skill Loading
+
+The `skill_loader.py` module:
+1. Scans the `skills/` directory
+2. Parses `skill.md` metadata
+3. Imports Python modules
+4. Registers tools with LangChain
+5. Makes them available to the agent
+
+### LangChain Integration
+
+- Uses `ChatWatxonx` for Watsonx-compatible APIs
+- Implements `create_tool_calling_agent` for tool use
+- Provides `AgentExecutor` for orchestration
+- Supports async operations
+
+### ACP SDK Integration
+
+- Compatible with Agent Communication Protocol
+- Provides standard agent endpoints
+- Supports message-based interaction
+- Easy integration with agent platforms
+
+## 📚 Learn More
+
+- [LangChain Documentation](https://python.langchain.com/)
+- [IBM Cloud Code Engine](https://cloud.ibm.com/docs/codeengine)
+- [IBM watsonx.ai](https://www.ibm.com/products/watsonx-ai)
+- [Agent Communication Protocol](https://github.com/IBM/agent-communication-protocol)
+
+## 🤝 Contributing
+
+To extend this agent:
+
+1. Add new skills in `src/skills/`
+2. Follow the skill structure (metadata + implementation)
+3. Skills are automatically discovered
+4. Test locally before deploying
+
+## 📝 License
+
+This is a sample implementation for educational purposes.
+
+## 🆘 Troubleshooting
+
+### Skills not loading
+- Check that `skill.md` has valid YAML frontmatter
+- Ensure `__init__.py` exports the tool function
+- Verify the tool function name matches the directory name
+
+### API errors
+- Verify your `.env` configuration
+- Check API key validity
+- Ensure the model name is correct for your provider
+
+### Deployment issues
+- Confirm IBM Cloud CLI is installed and logged in
+- Check that Code Engine plugin is up to date
+- Verify resource group and region settings
+
+---
+
+**Built with ❤️ using LangChain and IBM Cloud Code Engine**
\ No newline at end of file
diff --git a/ai/langchain-skills-agent/deploy.sh b/ai/langchain-skills-agent/deploy.sh
new file mode 100755
index 00000000..87edfdc0
--- /dev/null
+++ b/ai/langchain-skills-agent/deploy.sh
@@ -0,0 +1,147 @@
+#!/bin/bash
+
+# ==============================
+# ENVIRONMENT SETUP
+# ==============================
+
+source .env
+
+REGION="${REGION:=eu-de}"
+NAME_PREFIX="${NAME_PREFIX:=ce-langchain-agent}"
+
+ce_project_name=${PROJECT_NAME:-${NAME_PREFIX}-project}
+resource_group_name=${NAME_PREFIX}-rg
+
+# ==============================
+# COMMON FUNCTIONS
+# ==============================
+
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+source "${SCRIPT_DIR}/../common.sh"
+
+# Clean up previous run
+function clean() {
+    (
+        target_resource_group $resource_group_name
+
+        ibmcloud ce project select --name ${ce_project_name} --quiet 2>/dev/null
+        if [ $? == 0 ]; then
+            ibmcloud ce project delete --name ${ce_project_name} --force --hard --no-wait 2>/dev/null
+        fi
+
+        ibmcloud resource group $resource_group_name --quiet 2>/dev/null
+        if [[ $? == 0 ]]; then
+            COUNTER=0
+            # some resources (e.g. boot volumes) are deleted with some delay. Hence, the script waits before exiting with an error
+            while (( "$(ibmcloud resource service-instances --type all -g $resource_group_name --location $REGION --output json | jq -r '. | length')" > 0 )); do
+                sleep 5
+                COUNTER=$((COUNTER + 1))
+                if ((COUNTER > 3)); then
+                    print_error "Cleanup failed! Please make sure to delete remaining resources manually to avoid unwanted charges."
+                    ibmcloud resource service-instances --type all -g $resource_group_name --location $REGION
+                    exit 1
+                fi
+            done
+        fi
+
+	ibmcloud resource group-delete $resource_group_name --force 2>/dev/null
+    )
+}
+
+if [[ "$1" == "clean" ]]; then
+    print_msg "\nCleaning up the created IBM Cloud resources ..."
+    clean
+    print_success "\n==========================================\n DONE\n==========================================\n"
+    exit 0
+fi
+
+# ==============================
+# MAIN SCRIPT FLOW
+# ==============================
+
+# Ensure that latest versions of used IBM Cloud ClI is installed
+print_msg "\nPulling latest IBM Cloud CLI release ..."
+ibmcloud update --force
+
+# Ensure that latest versions of used IBM Cloud CLI plugins are installed
+print_msg "\nInstalling required IBM Cloud CLI plugins ..."
+ensure_plugin_is_up_to_date code-engine
+
+print_msg "\n======================================================"
+print_msg " Setting up \"LangChain Skills Agent\" sample"
+print_msg "======================================================\n"
+
+target_region $REGION
+
+#
+# Create the resource group, if it does not exist
+ibmcloud resource group $resource_group_name --quiet
+if [ $? != 0 ]; then
+    print_msg "\nCreating resource group '$resource_group_name' ..."
+    ibmcloud resource group-create $resource_group_name
+fi
+target_resource_group $resource_group_name
+
+if ! does_instance_exist codeengine "$ce_project_name"; then
+    print_msg "\nCreating the Code Engine project '$ce_project_name' ..."
+    ibmcloud ce project create --name $ce_project_name
+    if [ $? -ne 0 ]; then
+        print_error "Code Engine project creation failed!"
+        abortScript
+    fi
+else
+    print_msg "\nSelecting the Code Engine project '$ce_project_name' ..."
+    ibmcloud ce project select --name $ce_project_name
+fi
+project_guid=$(ibmcloud ce project get --name $ce_project_name --output json | jq -r '.guid')
+
+print_msg "\nCreating code engine secret for the agent with parameters from .env file"
+ibmcloud ce secret create --name langchain-agent-secret --from-literal INFERENCE_BASE_URL="$INFERENCE_BASE_URL" \
+--from-literal INFERENCE_API_KEY="$INFERENCE_API_KEY" \
+--from-literal INFERENCE_MODEL_NAME="$INFERENCE_MODEL_NAME" \
+--from-literal INFERENCE_PROJECT_ID="$INFERENCE_PROJECT_ID" \
+--from-literal OPENWEATHER_API_KEY="$OPENWEATHER_API_KEY" \
+--from-literal EXCHANGE_RATE_API_KEY="$EXCHANGE_RATE_API_KEY"
+
+print_msg "\nCreating the LangChain agent as a code engine application"
+ibmcloud ce app create --name langchain-agent --env-from-secret langchain-agent-secret --build-source ./src --cpu 1 --memory 4G -p 8080  --wait-timeout 600 --min-scale 1 --visibility public
+
+while true; do
+    ibmcloud ce app list
+    not_ready_apps=$(ibmcloud ce app list | grep -e "langchain-agent" | grep "Not Ready")
+    if [  "$not_ready_apps" == "" ]; then
+      break # all apps are ready
+    fi
+    print_msg "\nWaiting for all applications to be ready (sleep 15s)..."
+    sleep 15
+done
+
+print_msg "\n"
+print_msg "\nLangChain agent application is ready."
+print_msg "\n"
+
+url=$(ibmcloud ce app get --name langchain-agent -o json | jq -r '.status.url')
+print_msg "\nAgent is reachable under the following url:"
+echo $url
+
+print_msg "\n"
+print_msg "\nList the agents:"
+curl -s -X GET $url/agents | jq
+
+print_msg "\n"
+print_msg "\nGet agent info (including loaded skills):"
+curl -s -X GET $url/info | jq
+
+print_msg "\n"
+print_msg "\nCalling the agent with an example query"
+cat payload/payload.json | jq
+
+curl -s -X POST $url/runs -H "Content-Type: application/json" -d @payload/payload.json | jq
+
+print_success "\n=========================================="
+print_success " SUCCESS"
+print_success "==========================================\n"
+print_msg "\n"
+print_msg "\nrun ./deploy.sh clean to remove all created resources"
+
+# Made with Bob
diff --git a/ai/langchain-skills-agent/images/architecture.png b/ai/langchain-skills-agent/images/architecture.png
new file mode 100644
index 00000000..f2c4f0c8
Binary files /dev/null and b/ai/langchain-skills-agent/images/architecture.png differ
diff --git a/ai/langchain-skills-agent/payload/payload.json b/ai/langchain-skills-agent/payload/payload.json
new file mode 100644
index 00000000..e91edfb8
--- /dev/null
+++ b/ai/langchain-skills-agent/payload/payload.json
@@ -0,0 +1,9 @@
+{
+  "agent_name": "Travel_Weather_Assistant",
+  "input": [{
+    "role": "user", 
+    "parts": [{
+      "content": "{\"message\": \"What's the weather like in Paris for the next 3 days? Also, can you recommend some good travel destinations for someone who loves beaches and culture? And please convert 500 USD to EUR for my trip budget.\"}"
+    }]
+  }]
+}
diff --git a/ai/langchain-skills-agent/src/.ceignore b/ai/langchain-skills-agent/src/.ceignore
new file mode 100644
index 00000000..1d17dae1
--- /dev/null
+++ b/ai/langchain-skills-agent/src/.ceignore
@@ -0,0 +1 @@
+.venv
diff --git a/ai/langchain-skills-agent/src/.dockerignore b/ai/langchain-skills-agent/src/.dockerignore
new file mode 100644
index 00000000..0b883683
--- /dev/null
+++ b/ai/langchain-skills-agent/src/.dockerignore
@@ -0,0 +1,33 @@
+__pycache__/
+.my_cache_dir
+.pytest_cache
+.ruff_cache
+*.pyc
+*.pyo
+*.pyd
+*.db
+*.sqlite3
+
+.env
+.venv
+*.env
+
+**/.env
+**/.venv
+**/*.env
+
+.git
+.gitignore
+Dockerfile
+.dockerignore
+
+*.log
+*.bak
+*.swp
+
+.vscode/
+.idea/
+
+# OS-specific
+.DS_Store
+Thumbs.db
\ No newline at end of file
diff --git a/ai/langchain-skills-agent/src/.gitignore b/ai/langchain-skills-agent/src/.gitignore
new file mode 100644
index 00000000..a5ea1e65
--- /dev/null
+++ b/ai/langchain-skills-agent/src/.gitignore
@@ -0,0 +1,24 @@
+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+.mypy_cache
+.coverage
+.python-version
+
+# Virtual environments
+.venv
+
+# Environment files
+.env
+
+# IDE
+.vscode/
+.idea/
+
+# Cache
+.ruff_cache
+.pytest_cache
\ No newline at end of file
diff --git a/ai/langchain-skills-agent/src/Procfile b/ai/langchain-skills-agent/src/Procfile
new file mode 100644
index 00000000..629b83ad
--- /dev/null
+++ b/ai/langchain-skills-agent/src/Procfile
@@ -0,0 +1 @@
+web: python main.py
diff --git a/ai/langchain-skills-agent/src/README.md b/ai/langchain-skills-agent/src/README.md
new file mode 100644
index 00000000..c3c8b007
--- /dev/null
+++ b/ai/langchain-skills-agent/src/README.md
@@ -0,0 +1,76 @@
+# LangChain Skills Agent - Source Code
+
+This directory contains the source code for the LangChain Skills Agent.
+
+## Structure
+
+```
+src/
+├── main.py              # FastAPI application and agent entrypoint
+├── agents.py            # LangChain agent configuration and LLM setup
+├── skill_loader.py      # Dynamic skill discovery and loading system
+├── pyproject.toml       # Python dependencies
+├── Dockerfile           # Container build configuration
+├── ruff.toml            # Code linting configuration
+├── skills/              # Skills directory (auto-discovered)
+│   ├── weather_forecast/
+│   ├── travel_recommendations/
+│   └── currency_converter/
+└── frontend/            # Web UI components
+    ├── __init__.py
+    └── landing_page.py
+```
+
+## Key Files
+
+### `main.py`
+- FastAPI application setup
+- ACP SDK integration
+- Agent endpoint implementation
+- Health check and info endpoints
+
+### `agents.py`
+- LLM configuration (ChatOpenAI)
+- Agent prompt template
+- Agent executor creation
+- Configuration management
+
+### `skill_loader.py`
+- Automatic skill discovery
+- Metadata parsing from `skill.md` files
+- Dynamic module importing
+- Tool registration with LangChain
+
+### `skills/`
+Each skill directory contains:
+- `skill.md`: Metadata and documentation (YAML frontmatter)
+- `__init__.py`: Tool implementation using `@tool` decorator
+
+## Development
+
+### Install Dependencies
+
+```bash
+# Using pip
+pip install -e .
+
+# Using uv (recommended)
+uv sync
+```
+
+### Run Locally
+
+```bash
+python main.py
+```
+
+The agent will be available at `http://localhost:8080`
+
+### Add a New Skill
+
+1. Create a new directory in `skills/`
+2. Add `skill.md` with metadata
+3. Add `__init__.py` with tool implementation
+4. Restart the agent - it will be auto-discovered!
+
+See the main README.md for detailed instructions.
\ No newline at end of file
diff --git a/ai/langchain-skills-agent/src/agents.py b/ai/langchain-skills-agent/src/agents.py
new file mode 100644
index 00000000..7f402024
--- /dev/null
+++ b/ai/langchain-skills-agent/src/agents.py
@@ -0,0 +1,93 @@
+"""LangChain Agent Configuration
+
+This module configures the LLM and creates the LangChain agent with loaded skills.
+Uses the modern approach with tool binding instead of deprecated AgentExecutor.
+"""
+
+import os
+from typing import Any, List
+
+from dotenv import load_dotenv
+from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_ibm import ChatWatsonx
+
+load_dotenv()
+
+
+def create_llm():
+    """Create and configure the LLM instance.
+    
+    Returns:
+        Configured ChatWatsonx instance
+    """
+
+    parameters = {
+        "temperature": 0.7,
+        "max_tokens": 2048,
+    }
+
+    return ChatWatsonx(
+        model_id=os.getenv("INFERENCE_MODEL_NAME", "gpt-3.5-turbo"),
+        url=os.getenv("INFERENCE_BASE_URL"),
+        api_key=os.getenv("INFERENCE_API_KEY", ""),
+        project_id=os.getenv("INFERENCE_PROJECT_ID"),
+        params=parameters
+    )
+
+
+
+def get_system_message() -> str:
+    """Get the system message for the agent.
+    
+    Returns:
+        System message string
+    """
+    return """You are a helpful travel and weather assistant with access to specialized skills.
+
+Your capabilities include:
+- Providing weather forecasts for any location
+- Recommending travel destinations based on preferences
+- Converting currencies for travel planning
+
+When users ask questions:
+1. Understand their needs clearly
+2. Use the appropriate skills to gather information
+3. Provide comprehensive, well-formatted responses
+4. Be friendly and helpful
+
+Always format your responses in a clear, readable way. Use the skills available to you to provide accurate and helpful information."""
+
+
+def create_langchain_agent(tools: List):
+    """Create a LangChain agent with the provided tools using modern approach.
+    
+    Args:
+        tools: List of LangChain tools (from skills)
+    
+    Returns:
+        LLM instance with tools bound
+    """
+    llm = create_llm()
+    
+    # Bind tools to the LLM (modern approach)
+    llm_with_tools = llm.bind_tools(tools)
+    
+    return llm_with_tools
+
+
+def get_agent_info() -> dict:
+    """Get information about the configured agent.
+    
+    Returns:
+        Dictionary with agent configuration details
+    """
+    return {
+        "name": "Travel & Weather Assistant",
+        "description": "A LangChain-powered agent with weather, travel, and currency conversion skills",
+        "model": os.getenv("INFERENCE_MODEL_NAME", "gpt-3.5-turbo"),
+        "base_url": os.getenv("INFERENCE_BASE_URL", "Not configured"),
+        "version": "1.0.0",
+    }
+
+# Made with Bob
diff --git a/ai/langchain-skills-agent/src/frontend/__init__.py b/ai/langchain-skills-agent/src/frontend/__init__.py
new file mode 100644
index 00000000..ad6dcbde
--- /dev/null
+++ b/ai/langchain-skills-agent/src/frontend/__init__.py
@@ -0,0 +1,3 @@
+# Frontend module for the LangChain Skills Agent
+
+# Made with Bob
diff --git a/ai/langchain-skills-agent/src/frontend/landing_page.py b/ai/langchain-skills-agent/src/frontend/landing_page.py
new file mode 100644
index 00000000..4b8610e5
--- /dev/null
+++ b/ai/langchain-skills-agent/src/frontend/landing_page.py
@@ -0,0 +1,213 @@
+"""Landing Page for LangChain Skills Agent"""
+
+
+def render_landing_page(name: str) -> str:
+    """Render a simple HTML landing page for the agent.
+    
+    Args:
+        name: Name of the agent
+    
+    Returns:
+        HTML string for the landing page
+    """
+    html = f"""
+    <!DOCTYPE html>
+    <html lang="en">
+    <head>
+        <meta charset="UTF-8">
+        <meta name="viewport" content="width=device-width, initial-scale=1.0">
+        <title>{name} - LangChain Skills Agent</title>
+        <style>
+            * {{
+                margin: 0;
+                padding: 0;
+                box-sizing: border-box;
+            }}
+            
+            body {{
+                font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, sans-serif;
+                background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+                min-height: 100vh;
+                display: flex;
+                align-items: center;
+                justify-content: center;
+                padding: 20px;
+            }}
+            
+            .container {{
+                background: white;
+                border-radius: 20px;
+                box-shadow: 0 20px 60px rgba(0, 0, 0, 0.3);
+                max-width: 800px;
+                width: 100%;
+                padding: 40px;
+            }}
+            
+            h1 {{
+                color: #333;
+                font-size: 2.5em;
+                margin-bottom: 10px;
+                text-align: center;
+            }}
+            
+            .subtitle {{
+                color: #666;
+                text-align: center;
+                font-size: 1.1em;
+                margin-bottom: 30px;
+            }}
+            
+            .badge {{
+                display: inline-block;
+                background: #667eea;
+                color: white;
+                padding: 5px 15px;
+                border-radius: 20px;
+                font-size: 0.9em;
+                margin-bottom: 20px;
+            }}
+            
+            .skills {{
+                display: grid;
+                grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+                gap: 20px;
+                margin: 30px 0;
+            }}
+            
+            .skill-card {{
+                background: #f8f9fa;
+                padding: 20px;
+                border-radius: 10px;
+                border-left: 4px solid #667eea;
+            }}
+            
+            .skill-card h3 {{
+                color: #333;
+                font-size: 1.2em;
+                margin-bottom: 10px;
+            }}
+            
+            .skill-card p {{
+                color: #666;
+                font-size: 0.95em;
+                line-height: 1.5;
+            }}
+            
+            .endpoints {{
+                background: #f8f9fa;
+                padding: 20px;
+                border-radius: 10px;
+                margin-top: 30px;
+            }}
+            
+            .endpoints h2 {{
+                color: #333;
+                font-size: 1.5em;
+                margin-bottom: 15px;
+            }}
+            
+            .endpoint {{
+                background: white;
+                padding: 15px;
+                border-radius: 5px;
+                margin-bottom: 10px;
+                font-family: 'Courier New', monospace;
+                font-size: 0.9em;
+            }}
+            
+            .method {{
+                display: inline-block;
+                padding: 3px 8px;
+                border-radius: 3px;
+                font-weight: bold;
+                margin-right: 10px;
+            }}
+            
+            .get {{
+                background: #61affe;
+                color: white;
+            }}
+            
+            .post {{
+                background: #49cc90;
+                color: white;
+            }}
+            
+            .footer {{
+                text-align: center;
+                margin-top: 30px;
+                color: #999;
+                font-size: 0.9em;
+            }}
+            
+            .icon {{
+                font-size: 2em;
+                margin-bottom: 10px;
+            }}
+        </style>
+    </head>
+    <body>
+        <div class="container">
+            <div style="text-align: center;">
+                <div class="icon">🤖</div>
+                <h1>{name}</h1>
+                <p class="subtitle">LangChain-Powered Skills-Based Agent</p>
+                <span class="badge">✨ Skill-Based Architecture</span>
+            </div>
+            
+            <div class="skills">
+                <div class="skill-card">
+                    <h3>🌤️ Weather Forecast</h3>
+                    <p>Get current weather and multi-day forecasts for any location worldwide.</p>
+                </div>
+                
+                <div class="skill-card">
+                    <h3>✈️ Travel Recommendations</h3>
+                    <p>Personalized destination suggestions based on preferences and budget.</p>
+                </div>
+                
+                <div class="skill-card">
+                    <h3>💱 Currency Converter</h3>
+                    <p>Convert between 30+ currencies with current exchange rates.</p>
+                </div>
+            </div>
+            
+            <div class="endpoints">
+                <h2>📡 API Endpoints</h2>
+                
+                <div class="endpoint">
+                    <span class="method get">GET</span>
+                    <span>/agents</span>
+                    <p style="margin-top: 5px; color: #666;">List available agents</p>
+                </div>
+                
+                <div class="endpoint">
+                    <span class="method post">POST</span>
+                    <span>/runs</span>
+                    <p style="margin-top: 5px; color: #666;">Execute agent with a query</p>
+                </div>
+                
+                <div class="endpoint">
+                    <span class="method get">GET</span>
+                    <span>/info</span>
+                    <p style="margin-top: 5px; color: #666;">Get agent and skills information</p>
+                </div>
+                
+                <div class="endpoint">
+                    <span class="method get">GET</span>
+                    <span>/health</span>
+                    <p style="margin-top: 5px; color: #666;">Health check endpoint</p>
+                </div>
+            </div>
+            
+            <div class="footer">
+                <p>Powered by LangChain • IBM Cloud Code Engine</p>
+                <p style="margin-top: 5px;">Skills are dynamically loaded from the skills/ directory</p>
+            </div>
+        </div>
+    </body>
+    </html>
+    """
+    return html
+
+# Made with Bob
diff --git a/ai/langchain-skills-agent/src/main.py b/ai/langchain-skills-agent/src/main.py
new file mode 100644
index 00000000..e80b181e
--- /dev/null
+++ b/ai/langchain-skills-agent/src/main.py
@@ -0,0 +1,201 @@
+"""LangChain Skills Agent - Main Application
+
+This is the main entry point for the LangChain-based agent with skill-based architecture.
+It provides a FastAPI server with ACP SDK integration for agent interactions.
+Uses modern LangChain approach with tool binding instead of deprecated AgentExecutor.
+"""
+
+import json
+import warnings
+from collections.abc import AsyncGenerator
+
+import uvicorn
+from acp_sdk.models import Message
+from acp_sdk.server import RunYield, RunYieldResume, agent, create_app
+from dotenv import load_dotenv
+from fastapi.responses import HTMLResponse
+from langchain_core.messages import HumanMessage, SystemMessage
+
+from agents import create_langchain_agent, get_agent_info, get_system_message
+from frontend.landing_page import render_landing_page
+from skill_loader import discover_skills, get_tools_from_skills, print_skills_summary
+
+warnings.filterwarnings("ignore")
+
+load_dotenv()
+
+# Agent metadata
+AGENT_NAME = "Travel_Weather_Assistant"
+AGENT_DESCRIPTION = "A LangChain-powered assistant with weather forecasting, travel recommendations, and currency conversion skills. Helps plan trips with real-time information."
+
+# Discover and load skills at startup
+print("\n🔍 Discovering skills...")
+skills = discover_skills()
+print_skills_summary(skills)
+
+# Extract tools for LangChain
+tools = get_tools_from_skills(skills)
+print(f"✓ Loaded {len(tools)} tool(s) for the agent\n")
+
+# Create the LangChain agent with tools bound
+llm_with_tools = create_langchain_agent(tools)
+
+# Create a tool map for easy lookup
+tool_map = {tool.name: tool for tool in tools}
+
+
+@agent(
+    name=AGENT_NAME,
+    description=AGENT_DESCRIPTION,
+)
+async def travel_weather_agent(
+    input: list[Message],
+) -> AsyncGenerator[RunYield, RunYieldResume]:
+    """Main agent function that processes user requests.
+    
+    Args:
+        input: List of messages from the user
+    
+    Yields:
+        Response messages with agent results
+    """
+    # Extract the user's message
+    user_message = input[0].parts[0].content or ""
+    
+    try:
+        # Try to parse as JSON if it looks like JSON
+        if user_message.strip().startswith("{"):
+            try:
+                parsed_input = json.loads(user_message)
+                # If it's a dict with a 'query' or 'message' field, use that
+                if isinstance(parsed_input, dict):
+                    user_message = parsed_input.get("query") or parsed_input.get("message") or user_message
+            except json.JSONDecodeError:
+                # Not valid JSON, use as-is
+                pass
+    except Exception:
+        # Any error, just use the original message
+        pass
+    
+    # Invoke the LangChain agent using modern approach
+    try:
+        # Create messages for the LLM
+        messages = [
+            SystemMessage(content=get_system_message()),
+            HumanMessage(content=user_message)
+        ]
+        
+        # Invoke the LLM with tools
+        response = await llm_with_tools.ainvoke(messages)
+        
+        # Check if the LLM wants to use tools
+        if response.tool_calls:
+            # Execute tool calls
+            tool_results = []
+            for tool_call in response.tool_calls:
+                tool_name = tool_call["name"]
+                tool_args = tool_call["args"]
+                
+                if tool_name in tool_map:
+                    tool = tool_map[tool_name]
+                    try:
+                        result = await tool.ainvoke(tool_args)
+                        tool_results.append(f"\n{result}\n")
+                    except Exception as e:
+                        tool_results.append(f"\nError calling {tool_name}: {str(e)}\n")
+            
+            # Combine tool results
+            output = "\n".join(tool_results)
+        else:
+            # No tool calls, use the LLM's direct response
+            output = response.content
+        
+        # Return the result
+        yield Message(
+            parts=[
+                {
+                    "content_type": "text/plain",
+                    "content": output,
+                },
+            ]
+        )
+    except Exception as e:
+        # Handle errors gracefully
+        error_message = f"❌ Error processing request: {str(e)}\n\nPlease try rephrasing your question or check the agent logs."
+        yield Message(
+            parts=[
+                {
+                    "content_type": "text/plain",
+                    "content": error_message,
+                },
+            ]
+        )
+
+
+# Create the FastAPI app with ACP SDK
+app = create_app(
+    travel_weather_agent,
+    dependencies=[],
+)
+
+
+@app.get(
+    "/",
+    response_class=HTMLResponse,
+    include_in_schema=False,
+)
+async def landing_page():
+    """Serve the landing page."""
+    return render_landing_page(name=AGENT_NAME)
+
+
+@app.get("/info")
+async def agent_info():
+    """Get information about the agent and loaded skills."""
+    agent_data = get_agent_info()
+    
+    # Add skills information
+    skills_info = [
+        {
+            "name": skill.metadata.name,
+            "description": skill.metadata.description,
+            "category": skill.metadata.category,
+            "version": skill.metadata.version,
+        }
+        for skill in skills
+    ]
+    
+    return {
+        "agent": agent_data,
+        "skills": skills_info,
+        "skills_count": len(skills),
+    }
+
+
+@app.get("/health")
+async def health_check():
+    """Health check endpoint."""
+    return {
+        "status": "healthy",
+        "agent": AGENT_NAME,
+        "skills_loaded": len(skills),
+    }
+
+
+def main():
+    """Run the application."""
+    uvicorn.run(
+        "main:app",
+        host="0.0.0.0",
+        port=8080,
+        workers=1,
+        log_level="info",
+        headers=[("server", "acp")],
+        reload=True,
+    )
+
+
+if __name__ == "__main__":
+    main()
+
+# Made with Bob
diff --git a/ai/langchain-skills-agent/src/pyproject.toml b/ai/langchain-skills-agent/src/pyproject.toml
new file mode 100644
index 00000000..7bd801e0
--- /dev/null
+++ b/ai/langchain-skills-agent/src/pyproject.toml
@@ -0,0 +1,30 @@
+[project]
+name = "langchain-skills-agent"
+version = "1.0.0"
+description = "A LangChain-powered agent with skill-based architecture for weather, travel, and currency conversion"
+readme = "README.md"
+requires-python = ">=3.13,<3.14.0"
+dependencies = [
+    "acp-sdk>=1.0.3",
+    "fastapi>=0.135.0",
+    "langchain>=1.2.0",
+    "langchain-community>=0.3.0",
+    "langchain-core>=1.2.0",
+    "langchain-ibm>=1.0.3",
+    "python-dotenv>=1.2.0",
+    "pyyaml>=6.0.0",
+    "uvicorn==0.34.0",
+]
+
+[tool.poetry]
+package-mode = false
+
+[dependency-groups]
+dev = ["ruff>=0.11.10"]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["."]
diff --git a/ai/langchain-skills-agent/src/ruff.toml b/ai/langchain-skills-agent/src/ruff.toml
new file mode 100644
index 00000000..9445e7d6
--- /dev/null
+++ b/ai/langchain-skills-agent/src/ruff.toml
@@ -0,0 +1,72 @@
+# Exclude a variety of commonly ignored directories.
+exclude = [
+    ".bzr",
+    ".direnv",
+    ".eggs",
+    ".git",
+    ".git-rewrite",
+    ".hg",
+    ".ipynb_checkpoints",
+    ".mypy_cache",
+    ".nox",
+    ".pants.d",
+    ".pyenv",
+    ".pytest_cache",
+    ".pytype",
+    ".ruff_cache",
+    ".svn",
+    ".tox",
+    ".venv",
+    ".local",
+    ".vscode",
+    ".cache",
+    "__pypackages__",
+    "_build",
+    "buck-out",
+    "build",
+    "dist",
+    "node_modules",
+    "site-packages",
+    "venv",
+    "bin",
+]
+
+# Same as Black.
+line-length = 200
+indent-width = 4
+
+# Assume Python 3.12
+target-version = "py312"
+
+[lint]
+# Enable Pyflakes (`F`) and a subset of the pycodestyle (`E`)  codes by default.
+select = [
+    "E4",
+    "E7",
+    "E9",
+    "I",     # Import-related issues
+    "F",     # Formatting issues
+    "Q",     # Quote style issues
+    "UP039", # Pyupgrade issues (removal of unnecessary parentheses in class definitions)
+]
+ignore = []
+
+# Allow fix for all enabled rules (when `--fix`) is provided.
+fixable = ["ALL"]
+unfixable = []
+
+# Allow unused variables when underscore-prefixed.
+dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
+
+[format]
+# Like Black, use double quotes for strings.
+quote-style = "double"
+
+# Like Black, indent with spaces, rather than tabs.
+indent-style = "space"
+
+# Like Black, respect magic trailing commas.
+skip-magic-trailing-comma = false
+
+# Like Black, automatically detect the appropriate line ending.
+line-ending = "auto"
\ No newline at end of file
diff --git a/ai/langchain-skills-agent/src/skill_loader.py b/ai/langchain-skills-agent/src/skill_loader.py
new file mode 100644
index 00000000..48c70da5
--- /dev/null
+++ b/ai/langchain-skills-agent/src/skill_loader.py
@@ -0,0 +1,183 @@
+"""Dynamic Skill Loader for LangChain Agent
+
+This module discovers and loads skills from the skills/ directory.
+Each skill is expected to have:
+- A skill.md file with metadata (YAML frontmatter)
+- An __init__.py file with the tool implementation
+"""
+
+import importlib
+import os
+from pathlib import Path
+from typing import Any, Dict, List
+
+import yaml
+
+
+class SkillMetadata:
+    """Represents metadata for a skill."""
+    
+    def __init__(self, data: Dict[str, Any]):
+        self.name = data.get("name", "Unknown")
+        self.description = data.get("description", "")
+        self.version = data.get("version", "1.0.0")
+        self.category = data.get("category", "general")
+        self.parameters = data.get("parameters", [])
+    
+    def __repr__(self):
+        return f"SkillMetadata(name={self.name}, category={self.category}, version={self.version})"
+
+
+class Skill:
+    """Represents a loaded skill with metadata and tool."""
+    
+    def __init__(self, name: str, metadata: SkillMetadata, tool: Any):
+        self.name = name
+        self.metadata = metadata
+        self.tool = tool
+    
+    def __repr__(self):
+        return f"Skill(name={self.name}, tool={self.tool.__name__ if hasattr(self.tool, '__name__') else 'unknown'})"
+
+
+def parse_skill_metadata(skill_md_path: Path) -> SkillMetadata:
+    """Parse skill.md file and extract YAML frontmatter metadata.
+    
+    Args:
+        skill_md_path: Path to the skill.md file
+    
+    Returns:
+        SkillMetadata object with parsed metadata
+    """
+    with open(skill_md_path, 'r', encoding='utf-8') as f:
+        content = f.read()
+    
+    # Extract YAML frontmatter (between --- markers)
+    if content.startswith('---'):
+        parts = content.split('---', 2)
+        if len(parts) >= 3:
+            yaml_content = parts[1].strip()
+            metadata_dict = yaml.safe_load(yaml_content)
+            return SkillMetadata(metadata_dict)
+    
+    # Return empty metadata if no frontmatter found
+    return SkillMetadata({})
+
+
+def load_skill(skill_dir: Path) -> Skill:
+    """Load a single skill from a directory.
+    
+    Args:
+        skill_dir: Path to the skill directory
+    
+    Returns:
+        Skill object with metadata and tool
+    
+    Raises:
+        ImportError: If skill module cannot be imported
+        FileNotFoundError: If required files are missing
+    """
+    skill_name = skill_dir.name
+    skill_md_path = skill_dir / "skill.md"
+    
+    # Check if skill.md exists
+    if not skill_md_path.exists():
+        raise FileNotFoundError(f"skill.md not found in {skill_dir}")
+    
+    # Parse metadata
+    metadata = parse_skill_metadata(skill_md_path)
+    
+    # Import the skill module
+    module_path = f"skills.{skill_name}"
+    try:
+        skill_module = importlib.import_module(module_path)
+    except ImportError as e:
+        raise ImportError(f"Failed to import skill module {module_path}: {e}")
+    
+    # Get the tool from the module
+    # Convention: the tool function has the same name as the directory (with underscores)
+    tool_name = skill_name  # e.g., "weather_forecast"
+    
+    if not hasattr(skill_module, tool_name):
+        raise AttributeError(f"Skill module {module_path} does not have a '{tool_name}' function")
+    
+    tool = getattr(skill_module, tool_name)
+    
+    return Skill(name=skill_name, metadata=metadata, tool=tool)
+
+
+def discover_skills(skills_dir: Path = None) -> List[Skill]:
+    """Discover and load all skills from the skills directory.
+    
+    Args:
+        skills_dir: Path to the skills directory (defaults to ./skills)
+    
+    Returns:
+        List of loaded Skill objects
+    """
+    if skills_dir is None:
+        # Default to skills/ directory relative to this file
+        current_dir = Path(__file__).parent
+        skills_dir = current_dir / "skills"
+    
+    if not skills_dir.exists():
+        print(f"Warning: Skills directory not found at {skills_dir}")
+        return []
+    
+    skills = []
+    
+    # Iterate through subdirectories in skills/
+    for item in skills_dir.iterdir():
+        if item.is_dir() and not item.name.startswith('_'):
+            try:
+                skill = load_skill(item)
+                skills.append(skill)
+                print(f"✓ Loaded skill: {skill.metadata.name} ({skill.name})")
+            except Exception as e:
+                print(f"✗ Failed to load skill from {item.name}: {e}")
+    
+    return skills
+
+
+def get_tools_from_skills(skills: List[Skill]) -> List[Any]:
+    """Extract LangChain tools from loaded skills.
+    
+    Args:
+        skills: List of Skill objects
+    
+    Returns:
+        List of LangChain tool objects
+    """
+    return [skill.tool for skill in skills]
+
+
+def print_skills_summary(skills: List[Skill]) -> None:
+    """Print a summary of loaded skills.
+    
+    Args:
+        skills: List of Skill objects
+    """
+    print("\n" + "=" * 60)
+    print(f"Loaded {len(skills)} skill(s):")
+    print("=" * 60)
+    
+    for skill in skills:
+        print(f"\n📦 {skill.metadata.name}")
+        print(f"   Category: {skill.metadata.category}")
+        print(f"   Version: {skill.metadata.version}")
+        print(f"   Description: {skill.metadata.description}")
+    
+    print("\n" + "=" * 60 + "\n")
+
+
+# Example usage
+if __name__ == "__main__":
+    # Test the skill loader
+    skills = discover_skills()
+    print_skills_summary(skills)
+    
+    # Get tools for LangChain
+    tools = get_tools_from_skills(skills)
+    print(f"Extracted {len(tools)} tool(s) for LangChain agent")
+
+# Made with Bob
diff --git a/ai/langchain-skills-agent/src/skills/currency_converter/__init__.py b/ai/langchain-skills-agent/src/skills/currency_converter/__init__.py
new file mode 100644
index 00000000..7862bc3e
--- /dev/null
+++ b/ai/langchain-skills-agent/src/skills/currency_converter/__init__.py
@@ -0,0 +1,124 @@
+"""Currency Converter Skill Implementation"""
+
+import os
+from typing import Dict
+
+from langchain_core.tools import tool
+
+# Mock exchange rates (base: USD)
+# In production, these would come from a real API
+MOCK_RATES: Dict[str, float] = {
+    "USD": 1.0,
+    "EUR": 0.92,
+    "GBP": 0.79,
+    "JPY": 149.50,
+    "CAD": 1.36,
+    "AUD": 1.52,
+    "CHF": 0.88,
+    "CNY": 7.24,
+    "INR": 83.12,
+    "MXN": 17.08,
+    "BRL": 4.97,
+    "ZAR": 18.65,
+    "KRW": 1319.50,
+    "SGD": 1.34,
+    "NZD": 1.63,
+    "HKD": 7.83,
+    "SEK": 10.36,
+    "NOK": 10.58,
+    "DKK": 6.87,
+    "PLN": 3.98,
+    "THB": 34.85,
+    "MYR": 4.47,
+    "IDR": 15678.0,
+    "PHP": 55.82,
+    "CZK": 22.45,
+    "ILS": 3.64,
+    "CLP": 912.50,
+    "AED": 3.67,
+    "SAR": 3.75,
+    "TRY": 32.15,
+}
+
+
+@tool
+def currency_converter(amount: float, from_currency: str, to_currency: str) -> str:
+    """Convert an amount from one currency to another.
+    
+    Args:
+        amount: The amount to convert (e.g., 100.0)
+        from_currency: Source currency code (e.g., 'USD', 'EUR', 'GBP')
+        to_currency: Target currency code (e.g., 'USD', 'EUR', 'GBP')
+    
+    Returns:
+        Formatted conversion result with exchange rate details
+    """
+    # Normalize currency codes to uppercase
+    from_currency = from_currency.upper()
+    to_currency = to_currency.upper()
+    
+    # Validate currency codes
+    if from_currency not in MOCK_RATES:
+        return f"❌ Error: Currency code '{from_currency}' is not supported.\n\nSupported currencies: {', '.join(sorted(MOCK_RATES.keys()))}"
+    
+    if to_currency not in MOCK_RATES:
+        return f"❌ Error: Currency code '{to_currency}' is not supported.\n\nSupported currencies: {', '.join(sorted(MOCK_RATES.keys()))}"
+    
+    # Check for API key (for future real API integration)
+    api_key = os.getenv("EXCHANGE_RATE_API_KEY")
+    
+    if api_key and api_key != "YOUR_KEY":
+        # TODO: Implement real API call when API key is available
+        pass
+    
+    # Perform conversion using mock rates
+    return _convert_currency(amount, from_currency, to_currency)
+
+
+def _convert_currency(amount: float, from_currency: str, to_currency: str) -> str:
+    """Perform the actual currency conversion."""
+    
+    # If same currency, no conversion needed
+    if from_currency == to_currency:
+        return f"💱 Currency Conversion\n{'=' * 50}\n\n✅ Same currency - no conversion needed!\n{amount:.2f} {from_currency} = {amount:.2f} {to_currency}"
+    
+    # Convert to USD first (base currency), then to target currency
+    amount_in_usd = amount / MOCK_RATES[from_currency]
+    converted_amount = amount_in_usd * MOCK_RATES[to_currency]
+    
+    # Calculate the direct exchange rate
+    exchange_rate = MOCK_RATES[to_currency] / MOCK_RATES[from_currency]
+    
+    # Format the result
+    result = [
+        "💱 Currency Conversion",
+        "=" * 50,
+        "",
+        "📊 Conversion Details:",
+        f"   Original Amount: {amount:,.2f} {from_currency}",
+        f"   Converted Amount: {converted_amount:,.2f} {to_currency}",
+        "",
+        "📈 Exchange Rate:",
+        f"   1 {from_currency} = {exchange_rate:.4f} {to_currency}",
+        f"   1 {to_currency} = {1/exchange_rate:.4f} {from_currency}",
+        "",
+        "🧮 Calculation:",
+        f"   {amount:,.2f} {from_currency} × {exchange_rate:.4f} = {converted_amount:,.2f} {to_currency}",
+        "",
+        "💡 Note: These are demonstration exchange rates.",
+        "   Configure EXCHANGE_RATE_API_KEY in your .env file for live rates.",
+        "   Always verify rates for actual financial transactions.",
+    ]
+    
+    return "\n".join(result)
+
+
+def get_supported_currencies() -> list[str]:
+    """Return list of supported currency codes."""
+    return sorted(MOCK_RATES.keys())
+
+
+# Export the tool
+__all__ = ["currency_converter", "get_supported_currencies"]
+
+# Made with Bob
diff --git a/ai/langchain-skills-agent/src/skills/currency_converter/skill.md b/ai/langchain-skills-agent/src/skills/currency_converter/skill.md
new file mode 100644
index 00000000..dbe33b6b
--- /dev/null
+++ b/ai/langchain-skills-agent/src/skills/currency_converter/skill.md
@@ -0,0 +1,73 @@
+---
+name: "Currency Converter"
+description: "Convert amounts between different currencies with current exchange rates"
+version: "1.0.0"
+category: "finance"
+parameters:
+  - name: amount
+    type: float
+    required: true
+    description: "Amount to convert"
+  - name: from_currency
+    type: string
+    required: true
+    description: "Source currency code (e.g., 'USD', 'EUR', 'GBP')"
+  - name: to_currency
+    type: string
+    required: true
+    description: "Target currency code (e.g., 'USD', 'EUR', 'GBP')"
+---
+
+# Currency Converter Skill
+
+This skill converts monetary amounts between different currencies using exchange rates.
+
+## Features
+
+- Convert between major world currencies
+- Support for 30+ currency codes
+- Real-time exchange rates (when API configured)
+- Clear conversion breakdown
+- Handles decimal amounts
+- Validates currency codes
+
+## Usage
+
+The skill accepts an amount and source/target currency codes.
+
+## Example
+
+```python
+result = currency_converter(
+    amount=100.0,
+    from_currency="USD",
+    to_currency="EUR"
+)
+```
+
+## Supported Currencies
+
+- USD (US Dollar)
+- EUR (Euro)
+- GBP (British Pound)
+- JPY (Japanese Yen)
+- CAD (Canadian Dollar)
+- AUD (Australian Dollar)
+- CHF (Swiss Franc)
+- CNY (Chinese Yuan)
+- And many more...
+
+## Output Format
+
+Returns a formatted string with:
+- Original amount and currency
+- Converted amount and currency
+- Exchange rate used
+- Calculation breakdown
+
+## Notes
+
+- Uses demonstration exchange rates by default
+- Configure EXCHANGE_RATE_API_KEY for live rates
+- Rates are approximate and for informational purposes
+- Always verify rates for financial transactions
\ No newline at end of file
diff --git a/ai/langchain-skills-agent/src/skills/travel_recommendations/__init__.py b/ai/langchain-skills-agent/src/skills/travel_recommendations/__init__.py
new file mode 100644
index 00000000..b1967977
--- /dev/null
+++ b/ai/langchain-skills-agent/src/skills/travel_recommendations/__init__.py
@@ -0,0 +1,174 @@
+"""Travel Recommendations Skill Implementation"""
+
+from langchain_core.tools import tool
+
+
+@tool
+def travel_recommendations(
+    preferences: str,
+    budget: str = "moderate",
+    season: str = "current"
+) -> str:
+    """Get personalized travel destination recommendations.
+    
+    Args:
+        preferences: Travel preferences (e.g., 'beach vacation', 'cultural sites', 'adventure')
+        budget: Budget level - 'budget', 'moderate', or 'luxury' (default: 'moderate')
+        season: Preferred season - 'spring', 'summer', 'fall', 'winter', or 'current' (default: 'current')
+    
+    Returns:
+        Formatted travel recommendations with destinations and details
+    """
+    # Normalize inputs
+    budget = budget.lower()
+    season = season.lower()
+    preferences = preferences.lower()
+    
+    # Generate recommendations based on preferences
+    return _generate_recommendations(preferences, budget, season)
+
+
+def _generate_recommendations(preferences: str, budget: str, season: str) -> str:
+    """Generate travel recommendations based on criteria."""
+    
+    # Define destination database with various attributes
+    destinations = {
+        "beach": [
+            {
+                "name": "Bali, Indonesia",
+                "highlights": "Stunning beaches, temples, rice terraces, vibrant culture",
+                "activities": ["Surfing", "Temple visits", "Yoga retreats", "Snorkeling"],
+                "budget_range": {"budget": "$30-50/day", "moderate": "$60-100/day", "luxury": "$150+/day"},
+                "best_season": ["spring", "summer", "fall"]
+            },
+            {
+                "name": "Algarve, Portugal",
+                "highlights": "Golden cliffs, pristine beaches, charming villages",
+                "activities": ["Beach hopping", "Coastal hiking", "Wine tasting", "Golf"],
+                "budget_range": {"budget": "$40-60/day", "moderate": "$80-120/day", "luxury": "$180+/day"},
+                "best_season": ["spring", "summer", "fall"]
+            },
+            {
+                "name": "Cancún, Mexico",
+                "highlights": "Caribbean beaches, Mayan ruins, vibrant nightlife",
+                "activities": ["Snorkeling", "Cenote diving", "Mayan ruins tours", "Beach clubs"],
+                "budget_range": {"budget": "$50-70/day", "moderate": "$90-140/day", "luxury": "$200+/day"},
+                "best_season": ["winter", "spring"]
+            }
+        ],
+        "culture": [
+            {
+                "name": "Kyoto, Japan",
+                "highlights": "Ancient temples, traditional gardens, geisha culture",
+                "activities": ["Temple visits", "Tea ceremonies", "Bamboo forest walks", "Traditional crafts"],
+                "budget_range": {"budget": "$60-80/day", "moderate": "$100-150/day", "luxury": "$220+/day"},
+                "best_season": ["spring", "fall"]
+            },
+            {
+                "name": "Rome, Italy",
+                "highlights": "Ancient ruins, Renaissance art, world-class cuisine",
+                "activities": ["Colosseum tours", "Vatican museums", "Food tours", "Historic walks"],
+                "budget_range": {"budget": "$50-70/day", "moderate": "$90-130/day", "luxury": "$200+/day"},
+                "best_season": ["spring", "fall"]
+            },
+            {
+                "name": "Istanbul, Turkey",
+                "highlights": "Byzantine architecture, bazaars, East-meets-West culture",
+                "activities": ["Mosque visits", "Bazaar shopping", "Bosphorus cruise", "Turkish baths"],
+                "budget_range": {"budget": "$30-50/day", "moderate": "$60-100/day", "luxury": "$150+/day"},
+                "best_season": ["spring", "fall"]
+            }
+        ],
+        "adventure": [
+            {
+                "name": "Queenstown, New Zealand",
+                "highlights": "Adventure capital, stunning landscapes, outdoor activities",
+                "activities": ["Bungee jumping", "Skiing", "Hiking", "Jet boating"],
+                "budget_range": {"budget": "$60-80/day", "moderate": "$110-160/day", "luxury": "$240+/day"},
+                "best_season": ["summer", "winter"]
+            },
+            {
+                "name": "Patagonia, Chile/Argentina",
+                "highlights": "Dramatic mountains, glaciers, pristine wilderness",
+                "activities": ["Trekking", "Glacier hiking", "Wildlife watching", "Kayaking"],
+                "budget_range": {"budget": "$50-70/day", "moderate": "$90-140/day", "luxury": "$200+/day"},
+                "best_season": ["summer", "fall"]
+            },
+            {
+                "name": "Iceland",
+                "highlights": "Volcanoes, waterfalls, Northern Lights, geothermal pools",
+                "activities": ["Glacier hiking", "Hot springs", "Northern Lights tours", "Volcano tours"],
+                "budget_range": {"budget": "$80-100/day", "moderate": "$130-180/day", "luxury": "$260+/day"},
+                "best_season": ["summer", "winter"]
+            }
+        ]
+    }
+    
+    # Determine which category matches preferences
+    selected_destinations = []
+    if "beach" in preferences or "ocean" in preferences or "sea" in preferences:
+        selected_destinations.extend(destinations["beach"])
+    if "culture" in preferences or "history" in preferences or "art" in preferences or "museum" in preferences:
+        selected_destinations.extend(destinations["culture"])
+    if "adventure" in preferences or "hiking" in preferences or "outdoor" in preferences or "mountain" in preferences:
+        selected_destinations.extend(destinations["adventure"])
+    
+    # If no specific match, provide a mix
+    if not selected_destinations:
+        selected_destinations = destinations["beach"][:1] + destinations["culture"][:1] + destinations["adventure"][:1]
+    
+    # Limit to top 3 destinations
+    selected_destinations = selected_destinations[:3]
+    
+    # Build the response
+    result = [
+        "✈️  Personalized Travel Recommendations",
+        "=" * 60,
+        "",
+        f"📋 Your Preferences: {preferences.title()}",
+        f"💰 Budget Level: {budget.title()}",
+        f"🌍 Season: {season.title()}",
+        "",
+        "🎯 Recommended Destinations:",
+        ""
+    ]
+    
+    for i, dest in enumerate(selected_destinations, 1):
+        budget_info = dest["budget_range"].get(budget, dest["budget_range"]["moderate"])
+        
+        result.extend([
+            f"{i}. {dest['name']}",
+            "   " + "-" * 55,
+            f"   ✨ Highlights: {dest['highlights']}",
+            f"   💵 Estimated Cost: {budget_info}",
+            "   🎯 Top Activities:",
+        ])
+        
+        for activity in dest["activities"]:
+            result.append(f"      • {activity}")
+        
+        # Add seasonal note
+        if season != "current" and season in dest["best_season"]:
+            result.append(f"   ✅ Perfect for {season} travel!")
+        elif season != "current":
+            result.append(f"   ℹ️  Best visited in: {', '.join(dest['best_season'])}")
+        
+        result.append("")
+    
+    result.extend([
+        "💡 Travel Tips:",
+        "   • Book flights 2-3 months in advance for best prices",
+        "   • Consider shoulder season for fewer crowds and better deals",
+        "   • Check visa requirements well in advance",
+        "   • Get travel insurance for peace of mind",
+        "",
+        "🔄 Use the currency_converter skill to convert prices to your currency!"
+    ])
+    
+    return "\n".join(result)
+
+
+# Export the tool
+__all__ = ["travel_recommendations"]
+
+# Made with Bob
diff --git a/ai/langchain-skills-agent/src/skills/travel_recommendations/skill.md b/ai/langchain-skills-agent/src/skills/travel_recommendations/skill.md
new file mode 100644
index 00000000..08a2e25e
--- /dev/null
+++ b/ai/langchain-skills-agent/src/skills/travel_recommendations/skill.md
@@ -0,0 +1,65 @@
+---
+name: "Travel Recommendations"
+description: "Get personalized travel destination recommendations based on preferences"
+version: "1.0.0"
+category: "travel"
+parameters:
+  - name: preferences
+    type: string
+    required: true
+    description: "Travel preferences (e.g., 'beach vacation', 'cultural sites', 'adventure')"
+  - name: budget
+    type: string
+    required: false
+    default: "moderate"
+    description: "Budget level: 'budget', 'moderate', or 'luxury'"
+  - name: season
+    type: string
+    required: false
+    default: "current"
+    description: "Preferred travel season or 'current'"
+---
+
+# Travel Recommendations Skill
+
+This skill provides personalized travel destination recommendations based on user preferences, budget, and season.
+
+## Features
+
+- Destination suggestions tailored to interests
+- Budget-appropriate recommendations
+- Seasonal considerations
+- Activity suggestions for each destination
+- Estimated costs and travel tips
+- Cultural highlights and must-see attractions
+
+## Usage
+
+The skill accepts travel preferences, budget level, and preferred season to generate recommendations.
+
+## Example
+
+```python
+result = travel_recommendations(
+    preferences="beach and culture",
+    budget="moderate",
+    season="summer"
+)
+```
+
+## Output Format
+
+Returns a formatted guide with:
+- Recommended destinations (3-5 locations)
+- Why each destination fits the criteria
+- Estimated budget ranges
+- Best time to visit
+- Top activities and attractions
+- Travel tips
+
+## Notes
+
+- Considers current travel trends and seasonal factors
+- Provides diverse options across different regions
+- Includes practical travel advice
+- Budget estimates in USD (can be converted using currency_converter skill)
\ No newline at end of file
diff --git a/ai/langchain-skills-agent/src/skills/weather_forecast/__init__.py b/ai/langchain-skills-agent/src/skills/weather_forecast/__init__.py
new file mode 100644
index 00000000..7d159a08
--- /dev/null
+++ b/ai/langchain-skills-agent/src/skills/weather_forecast/__init__.py
@@ -0,0 +1,87 @@
+"""Weather Forecast Skill Implementation"""
+
+import os
+from datetime import datetime, timedelta
+
+from langchain_core.tools import tool
+
+
+@tool
+def weather_forecast(location: str, days: int = 3) -> str:
+    """Get weather forecast for a location.
+    
+    Args:
+        location: City name or location (e.g., 'Paris', 'New York', 'Tokyo')
+        days: Number of forecast days (1-7), defaults to 3
+    
+    Returns:
+        Formatted weather forecast information
+    """
+    # Validate days parameter
+    days = max(1, min(days, 7))
+    
+    # Check if we have an API key (for future real API integration)
+    api_key = os.getenv("OPENWEATHER_API_KEY")
+    
+    if api_key and api_key != "YOUR_KEY":
+        # TODO: Implement real API call when API key is available
+        # For now, return mock data even if key exists
+        pass
+    
+    # Generate mock weather data for demonstration
+    return _generate_mock_weather(location, days)
+
+
+def _generate_mock_weather(location: str, days: int) -> str:
+    """Generate realistic mock weather data for demonstration purposes."""
+    
+    # Mock weather conditions
+    conditions = ["Sunny", "Partly Cloudy", "Cloudy", "Light Rain", "Clear"]
+    
+    # Base temperatures (varies by location name for variety)
+    base_temp = 15 + (len(location) % 10)
+    
+    result = [
+        f"🌤️  Weather Forecast for {location}",
+        "=" * 50,
+        "",
+        "📍 Current Conditions:",
+        f"   Temperature: {base_temp}°C ({base_temp * 9/5 + 32:.1f}°F)",
+        f"   Condition: {conditions[len(location) % len(conditions)]}",
+        f"   Humidity: {60 + (len(location) % 30)}%",
+        f"   Wind: {5 + (len(location) % 15)} km/h",
+        "",
+        f"📅 {days}-Day Forecast:",
+        ""
+    ]
+    
+    # Generate forecast for each day
+    for i in range(days):
+        date = datetime.now() + timedelta(days=i+1)
+        day_name = date.strftime("%A, %B %d")
+        
+        # Vary temperature slightly each day
+        high_temp = base_temp + (i % 5) + 2
+        low_temp = base_temp - (i % 3)
+        condition = conditions[(len(location) + i) % len(conditions)]
+        
+        result.extend([
+            f"   {day_name}:",
+            f"   • High: {high_temp}°C ({high_temp * 9/5 + 32:.1f}°F)",
+            f"   • Low: {low_temp}°C ({low_temp * 9/5 + 32:.1f}°F)",
+            f"   • Condition: {condition}",
+            ""
+        ])
+    
+    result.extend([
+        "💡 Note: This is demonstration data. Configure OPENWEATHER_API_KEY",
+        "   in your .env file for real weather data.",
+    ])
+    
+    return "\n".join(result)
+
+
+# Export the tool
+__all__ = ["weather_forecast"]
+
+# Made with Bob
diff --git a/ai/langchain-skills-agent/src/skills/weather_forecast/skill.md b/ai/langchain-skills-agent/src/skills/weather_forecast/skill.md
new file mode 100644
index 00000000..6e6816ac
--- /dev/null
+++ b/ai/langchain-skills-agent/src/skills/weather_forecast/skill.md
@@ -0,0 +1,53 @@
+---
+name: "Weather Forecast"
+description: "Get current weather and forecast for any location worldwide"
+version: "1.0.0"
+category: "weather"
+parameters:
+  - name: location
+    type: string
+    required: true
+    description: "City name (e.g., 'Paris', 'New York') or coordinates"
+  - name: days
+    type: integer
+    required: false
+    default: 3
+    description: "Number of forecast days (1-7)"
+---
+
+# Weather Forecast Skill
+
+This skill provides comprehensive weather information for any location worldwide.
+
+## Features
+
+- Current weather conditions (temperature, humidity, wind speed)
+- Multi-day forecast (up to 7 days)
+- Weather descriptions and conditions
+- Temperature in Celsius and Fahrenheit
+- Wind speed and direction
+- Humidity and pressure information
+
+## Usage
+
+The skill accepts a location (city name or coordinates) and optionally the number of forecast days.
+
+## Example
+
+```python
+result = weather_forecast(location="Paris", days=3)
+```
+
+## Output Format
+
+Returns a formatted string with:
+- Current conditions
+- Daily forecasts with high/low temperatures
+- Weather descriptions
+- Additional meteorological data
+
+## Notes
+
+- Uses OpenWeatherMap API (or mock data if API key not configured)
+- Handles location parsing and validation
+- Provides user-friendly error messages for invalid locations
\ No newline at end of file
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diff --git a/ai/langflow/README.md b/ai/langflow/README.md
new file mode 100644
index 00000000..0fe0303d
--- /dev/null
+++ b/ai/langflow/README.md
@@ -0,0 +1,67 @@
+# LangFlow on IBM Code Engine
+
+![](./images/architecture.png)
+
+## What is LangFlow
+
+- [LangFlow](https://www.langflow.org/) is an open-source, Python-based **low-code visual framework** designed for rapid prototyping and deployment of **LLM-powered applications**.
+- It allows you to **visually define pipelines** that connect **Agents**, **Tools** and **LLMs** so you can build, test, and iterate on behaviors without writing glue code.
+- It comes with batteries included and supports all major LLMs, vector databases and a **growing library of AI tools**.
+
+## Why Code Engine is a great fit
+
+Using **[IBM Cloud Code Engine](https://www.ibm.com/products/code-engine)** you can expose both the developer visual editor and the end-user interface via an out-of-the-box system domain, making it easy to share and host LangFlow apps.
+
+- **Managed runtime:** Code Engine runs containers without managing servers, lowering operational overhead.
+- **Public endpoints:** Apps get a reachable URL out of the box, simplifying access for developers and end users.
+- **Scalability & cost control:** Configure CPU/memory and min/max scale for predictable resource use and autoscaling when needed.
+- **Integrates with COS:** Object storage (IBM Cloud Object Storage) can be mounted as a persistent data store for flows, state and uploads.
+- **Secure secrets & PDS:** Use Code Engine secrets and Persistent Data Stores (PDS) to store credentials and mount COS buckets securely.
+
+## Deploy 
+
+This repository includes a convenience script `deploy.sh` that automates the common steps (creating a Code Engine project, creating a COS instance and bucket, creating a service key, creating a CE secret and PDS, and deploying the image).
+
+**Prerequisites**
+
+Create an IBM Cloud account on the target Code Engine provider (e.g., IBM Cloud Code Engine) and [login into your IBM Cloud account using the IBM Cloud CLI](https://cloud.ibm.com/docs/codeengine?topic=codeengine-install-cli).
+
+
+**Deploy** 
+Run the bundled script from this folder which automates the steps above and configures COS/PDS integration:
+
+```bash
+./deploy.sh
+```
+
+The script accepts optional environment variables to customize region and naming, e.g.:
+
+```bash
+REGION=eu-de NAME_PREFIX=ce-langflow ./deploy.sh
+```
+
+Notes on persistence
+
+- The deployment mounts an IBM Cloud Object Storage bucket as a Persistent Data Store so LangFlow can persist flows and state across restarts.
+- The script creates a secret (`langflow-cos-secret`) containing HMAC credentials and a PDS (`langflow-store`) that points the app at the bucket.
+
+## Access the environment
+
+After deployment, retrieve the app URL with:
+
+```bash
+ibmcloud ce app get --name langflow -o json | jq -r '.status.url'
+```
+
+The script also prints the reachable URL, for example:
+
+```
+https://langflow.26pr644bfbfc.eu-de.codeengine.appdomain.cloud
+```
+
+## Use LangFlow
+
+Open the URL in a browser window to access the visual editor of [LangFlow](https://www.langflow.org/) and start desiging you first flow. If you already have a flow, you can import it as well.
+
+![](./images/langflow_ui.png)
+
diff --git a/ai/langflow/deploy.sh b/ai/langflow/deploy.sh
new file mode 100755
index 00000000..8d9d752f
--- /dev/null
+++ b/ai/langflow/deploy.sh
@@ -0,0 +1,179 @@
+#!/bin/bash
+
+# ==============================
+# ENVIRONMENT SETUP
+# ==============================
+
+REGION="${REGION:=eu-de}"
+NAME_PREFIX="${NAME_PREFIX:=ce-langflow}"
+
+# Generate a short uuid for some resources
+uuid=$(uuidgen | tr '[:upper:]' '[:lower:]' | awk -F- '{print $1}')
+
+ce_project_name=${PROJECT_NAME:-${NAME_PREFIX}-project}
+resource_group_name=${NAME_PREFIX}-rg
+cos_name="${NAME_PREFIX}--cos"
+cos_key_name="${NAME_PREFIX}--cos-key"
+cos_bucket_name_langflow_store="${NAME_PREFIX}-langflow-store-${uuid}"
+
+# ==============================
+# COMMON FUNCTIONS
+# ==============================
+
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+source "${SCRIPT_DIR}/../common.sh"
+
+# Clean up previous run
+function clean() {
+    (
+        target_resource_group $resource_group_name
+
+        ibmcloud ce project select --name ${ce_project_name} --quiet 2>/dev/null
+        if [ $? == 0 ]; then
+            ibmcloud ce project delete --name ${ce_project_name} --force --hard --no-wait 2>/dev/null
+        fi
+
+        ibmcloud resource service-key-delete ${cos_key_name} --force 2>/dev/null
+        ibmcloud cos bucket-delete --bucket ${cos_bucket_name_langflow_store} --force 2>/dev/null
+        ibmcloud resource service-instance-delete ${cos_name} -f -q 2>/dev/null
+
+        ibmcloud resource group $resource_group_name --quiet 2>/dev/null
+        if [[ $? == 0 ]]; then
+            COUNTER=0
+            # some resources (e.g. boot volumes) are deleted with some delay. Hence, the script waits before exiting with an error
+            while (( "$(ibmcloud resource service-instances --type all -g $resource_group_name --location $REGION --output json | jq -r '. | length')" > 0 )); do
+                sleep 5
+                COUNTER=$((COUNTER + 1))
+                if ((COUNTER > 3)); then
+                    print_error "Cleanup failed! Please make sure to delete remaining resources manually to avoid unwanted charges."
+                    ibmcloud resource service-instances --type all -g $resource_group_name --location $REGION
+                    exit 1
+                fi
+            done
+        fi
+
+	ibmcloud resource group-delete $resource_group_name --force 2>/dev/null
+    )
+}
+
+if [[ "$1" == "clean" ]]; then
+    print_msg "\nCleaning up the created IBM Cloud resources ..."
+    clean
+    print_success "\n==========================================\n DONE\n==========================================\n"
+    exit 0
+fi
+
+# ==============================
+# MAIN SCRIPT FLOW
+# ==============================
+
+# Ensure that latest versions of used IBM Cloud ClI is installed
+print_msg "\nPulling latest IBM Cloud CLI release ..."
+ibmcloud update --force
+
+# Ensure that latest versions of used IBM Cloud CLI plugins are installed
+print_msg "\nInstalling required IBM Cloud CLI plugins ..."
+ensure_plugin_is_up_to_date code-engine
+
+print_msg "\n======================================================"
+print_msg " Setting up \"Code Engine LangFlow\" sample"
+print_msg "======================================================\n"
+
+target_region $REGION
+
+#
+# Create the resource group, if it does not exist
+ibmcloud resource group $resource_group_name --quiet
+if [ $? != 0 ]; then
+    print_msg "\nCreating resource group '$resource_group_name' ..."
+    ibmcloud resource group-create $resource_group_name
+fi
+target_resource_group $resource_group_name
+
+if ! does_instance_exist codeengine "$ce_project_name"; then
+    print_msg "\nCreating the Code Engine project '$ce_project_name' ..."
+    ibmcloud ce project create --name $ce_project_name
+    if [ $? -ne 0 ]; then
+        print_error "Code Engine project creation failed!"
+        abortScript
+    fi
+else
+    print_msg "\nSelecting the Code Engine project '$ce_project_name' ..."
+    ibmcloud ce project select --name $ce_project_name
+fi
+project_guid=$(ibmcloud ce project get --name $ce_project_name --output json | jq -r '.guid')
+
+
+#
+# Creating COS instance and bucket
+if ! does_instance_exist cloud-object-storage "$cos_name"; then
+    print_msg "\nCreating COS instance '${cos_name}' ..."
+    ibmcloud resource service-instance-create $cos_name cloud-object-storage standard global -d premium-global-deployment-iam
+    if [ $? -ne 0 ]; then
+        print_error "Cloud Object Storage creation failed!"
+        abortScript
+    fi
+fi
+
+COS_ID=$(ibmcloud resource service-instance $cos_name --output json | jq -r '.[0] | .id')
+ibmcloud cos config crn --crn ${COS_ID} --force >/dev/null 2>&1
+ibmcloud cos config auth --method IAM >/dev/null
+ibmcloud cos config region --region $REGION >/dev/null
+ibmcloud cos config endpoint-url --url s3.${REGION}.cloud-object-storage.appdomain.cloud >/dev/null
+
+# Make sure all COS buckets do exist
+res=$(has_bucket_name_with_prefix "${NAME_PREFIX}-langflow-store-")
+if [[ "$res" == "" ]]; then
+    print_msg "\nCreating COS bucket '${cos_bucket_name_langflow_store}' ..."
+    ibmcloud cos bucket-create --bucket ${cos_bucket_name_langflow_store} --ibm-service-instance-id $COS_ID
+else
+    cos_bucket_name_langflow_store=$res
+fi
+
+
+# Create COS credentials
+if ! does_serviceid_exist "${cos_key_name}"; then
+    print_msg "\nCreating COS service key '${cos_key_name}' ..."
+    ibmcloud resource service-key-create ${cos_key_name} --parameters '{"HMAC":true}' --instance-id $COS_ID
+fi
+
+print_msg "\nCOS instance '${COS_ID}' configured..."
+
+
+print_msg "\nCreating a Code Engine Persistant Data Store 'langflow-cos-secret' to access the COS bucket as the task state store ..."
+create_or_update=update
+if ! ibmcloud ce secret get --name langflow-cos-secret >/dev/null 2>&1; then
+    create_or_update="create --format hmac"
+fi
+ibmcloud ce secret $create_or_update --name langflow-cos-secret \
+    --secret-access-key $(ibmcloud resource service-key ${cos_key_name} --output JSON | jq -r '.[0] | .credentials | .cos_hmac_keys | .secret_access_key') \
+    --access-key-id $(ibmcloud resource service-key ${cos_key_name} --output JSON | jq -r '.[0] | .credentials | .cos_hmac_keys | .access_key_id')
+
+if ! ibmcloud ce pds get --name langflow-store >/dev/null 2>&1; then
+    ibmcloud ce pds create --name langflow-store \
+        --cos-bucket-name ${cos_bucket_name_langflow_store} \
+        --cos-bucket-location ${REGION} \
+        --cos-access-secret langflow-cos-secret
+fi
+
+print_msg "\nDeploy the LangFlow application to Code Engine"
+ibmcloud ce app create --name langflow --image langflowai/langflow:latest --cpu 4 --memory 8G -p 7860  --wait-timeout 600 --min-scale 1 --visibility public --env LANGFLOW_SAVE_DB_IN_CONFIG_DIR=True --mount-data-store /app/data=langflow-store:data
+while true; do
+    ibmcloud ce app list
+    not_ready_apps=$(ibmcloud ce app list | grep -e "langflow" | grep "Not Ready")
+    if [  "$not_ready_apps" == "" ]; then
+      break # all apps are ready
+    fi
+    print_msg "\nWaiting for all applications to be ready (sleep 15s)..."
+    sleep 15
+done
+
+print_msg "\nLangFlow application is ready."
+
+url=$(ibmcloud ce app get --name langflow -o json | jq -r '.status.url')
+print_msg "\nLangFlow application is reachable under the following url:"
+print_msg "$url"
+print_msg "\nrun ./deploy.sh clean to remove all created resources"
+print_success "\n=========================================="
+print_success " SUCCESS"
+print_success "==========================================\n"
diff --git a/ai/langflow/images/architecture.png b/ai/langflow/images/architecture.png
new file mode 100644
index 00000000..65de62f5
Binary files /dev/null and b/ai/langflow/images/architecture.png differ
diff --git a/ai/langflow/images/langflow_ui.png b/ai/langflow/images/langflow_ui.png
new file mode 100644
index 00000000..364519a1
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diff --git a/ai/mcp_server_fastmcp/.gitignore b/ai/mcp_server_fastmcp/.gitignore
new file mode 100644
index 00000000..0300decc
--- /dev/null
+++ b/ai/mcp_server_fastmcp/.gitignore
@@ -0,0 +1 @@
+**/.venv
diff --git a/ai/mcp_server_fastmcp/README.md b/ai/mcp_server_fastmcp/README.md
new file mode 100644
index 00000000..d88ff5a5
--- /dev/null
+++ b/ai/mcp_server_fastmcp/README.md
@@ -0,0 +1,148 @@
+FastMCP — Fast, tiny MCP server example
+======================================
+
+Overview
+--------
+This directory contains a minimal FastMCP server example and a companion client. FastMCP demonstrates a tiny, runnable implementation of an MCP-compatible service (Model Context Protocol) intended for local testing and quick deployment to cloud platforms.
+
+![](./images/architecture.png)
+
+About MCP and FastMCP
+---------------------
+
+MCP (Model Context Protocol) is a lightweight, transport-agnostic convention for exchanging model prompts, context, and responses between clients and model-serving services. It emphasizes:
+
+- **Transport flexibility**: works over HTTP, SSE, WebSocket, stdio and other streamable transports.
+- **Streaming-first behavior**: supports incremental/streaming responses for low-latency UX.
+- **Simple JSON semantics**: easy to implement and interoperate between services.
+
+**[FastMCP](https://gofastmcp.com/getting-started/welcome) is the standard framework for building MCP applications.** 
+
+The [Direct Http Server](https://gofastmcp.com/deployment/http#direct-http-server) example provides a minimal reference implementation meant for experimentation and quick deployments. It focuses on a very small API surface and fast startup so you can iterate locally or run tiny instances in cloud platforms like Code Engine.
+
+
+Why Code Engine?
+-----------------
+
+[IBM Cloud Code Engine](https://www.ibm.com/products/code-engine) is a great fit for containerized MCP Servers because it provides:
+
+- **Serverless containers**: Deploy container images without managing infrastructure.
+- **Automatic scaling**: Scale to zero when idle and scale up on demand.
+- **Pay-per-use pricing**: Cost-efficient for intermittent workloads common to agents.
+- **Simple deployment**: Integrates with container registries and CI/CD pipelines.
+- **Managed endpoint**: Provides a secure http endpoint with a managed certificate.
+
+A very tiny MCP Server
+----------------------
+
+The Python source code for the MCP server is located in [./server/main.py](./server/main.py):
+
+```python
+from fastmcp import FastMCP
+
+mcp = FastMCP("My FastMCP Server on Code Engine")
+
+@mcp.tool
+def process_data(input: str) -> str:
+    """Process data on the server"""
+    """ADD YOUR BUSINESS LOGIC HERE"""
+    return f"Processed: {input}"
+
+if __name__ == "__main__":
+    mcp.run(transport="http", host="0.0.0.0", port=8080)
+```
+
+Deploying the server to Code Engine
+----------------------------------
+
+**Prerequisites**
+Create an IBM Cloud account on the target Code Engine provider (e.g., IBM Cloud Code Engine) and [login into your IBM Cloud account using the IBM Cloud CLI](https://cloud.ibm.com/docs/codeengine?topic=codeengine-install-cli).
+
+**Deploy**
+
+1. Authenticate and login to IBM Cloud:
+
+```bash
+ibmcloud login --sso
+ibmcloud login --apikey "$IBMCLOUD_APIKEY" -r us-south
+
+```
+
+2. Run the included deploy script from this folder. The script creates a new Code Engine project in the specified region and automates build/push/deploy steps to create a new application in Code Engine. 
+
+```bash
+NAME_PREFIX=ce-fastmcp REGION=eu-de ./deploy.sh
+```
+
+3. The deploy script will print the URL under which the MCP Server is publicly accessible
+
+```
+FastMCP application is reachable under the following url:
+https://fastmcp.26n4g2nfyw7s.eu-de.codeengine.appdomain.cloud/mcp
+```
+
+🚀 The example was successful and you can now use the MCP server in your chat application 🚀
+
+Building and using the client
+-----------------------------
+The `client` directory contains a small Python client to exercise the server.
+
+1. Create a virtual environment and install dependencies:
+
+```bash
+python3 -m venv .venv
+source .venv/bin/activate
+pip install -r client/requirements.txt
+```
+
+2. Run the client
+
+Start the client by replacing the application URL from above as the `MCP_SERVER_URL` environment variable, e.g.
+
+```bash
+MCP_SERVER_URL="https://fastmcp.26n4g2nfyw7s.eu-de.codeengine.appdomain.cloud/mcp" python client.py
+```
+
+3. Inspect and adapt
+- Open `client/client.py` to find example calls. The client is intentionally minimal so you can adapt it to your tooling or CI.
+
+Using this example with Claude Desktop
+-------------------------------------
+Claude Desktop can connect to local or remote MCP servers by registering them in its `claude_desktop_config.json` (Claude -> Settings -> Developer -> Edit Config). 
+
+
+Example `claude_desktop_config.json` entry that point to your deployed application URL:
+
+```json
+{
+  "mcpServer": {
+    "FastMCP (Code Engine)": {
+      "command": "npx",
+      "args": [
+        "mcp-remote",
+        "https://fastmcp.26n4g2nfyw7s.eu-de.codeengine.appdomain.cloud/mcp"
+      ]
+    }
+  }
+}
+```
+
+Save settings and restart Claude Desktop; the remote MCP server should appear as a selectable tool in Claude Desktop.
+
+![](./images/claude_tool.png)
+
+You can now chat with the MCP Server, e.g.
+
+**_"How does the server process: Hello, World!"_**
+
+Claude will detect the tool and call, respond with the response implemented in `process_data`, e.g. **_Processed: Hello, World!_**
+
+![](./images/claude_chat.png)
+
+Note, the LLM even detected the simplicity of our MCP Server.
+
+
+What's next?
+------------
+
+You now have a very simple reference architecture to deploy any MCP server of your choice. 
\ No newline at end of file
diff --git a/ai/mcp_server_fastmcp/client/client.py b/ai/mcp_server_fastmcp/client/client.py
new file mode 100644
index 00000000..b8a54220
--- /dev/null
+++ b/ai/mcp_server_fastmcp/client/client.py
@@ -0,0 +1,30 @@
+import asyncio
+import os
+from fastmcp import Client, FastMCP
+
+mcp_server_url = os.getenv("MCP_SERVER_URL", default="http://localhost:8080/mcp")
+
+# HTTP server
+client = Client(mcp_server_url)
+
+# Local Python script
+#client = Client("../src/main.py")
+
+async def main():
+    async with client:
+        # Basic server interaction
+        await client.ping()
+
+        # List available operations
+        tools = await client.list_tools()
+        print("Available tools:", tools)
+        resources = await client.list_resources()
+        print("Available resources:", resources)
+        prompts = await client.list_prompts()
+        print("Available prompts:", prompts)
+
+        # Execute operations
+        result = await client.call_tool("process_data", {"input": "Hello, FastMCP!"})
+        print(result)
+
+asyncio.run(main())
\ No newline at end of file
diff --git a/ai/mcp_server_fastmcp/client/requirements.txt b/ai/mcp_server_fastmcp/client/requirements.txt
new file mode 100644
index 00000000..35a7d0c6
--- /dev/null
+++ b/ai/mcp_server_fastmcp/client/requirements.txt
@@ -0,0 +1 @@
+fastmcp
\ No newline at end of file
diff --git a/ai/mcp_server_fastmcp/deploy.sh b/ai/mcp_server_fastmcp/deploy.sh
new file mode 100755
index 00000000..4229c824
--- /dev/null
+++ b/ai/mcp_server_fastmcp/deploy.sh
@@ -0,0 +1,121 @@
+#!/bin/bash
+
+# ==============================
+# ENVIRONMENT SETUP
+# ==============================
+
+REGION="${REGION:=eu-de}"
+NAME_PREFIX="${NAME_PREFIX:=ce-fastmcp}"
+
+ce_project_name=${PROJECT_NAME:-${NAME_PREFIX}-project}
+resource_group_name=${NAME_PREFIX}-rg
+
+# ==============================
+# COMMON FUNCTIONS
+# ==============================
+
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+source "${SCRIPT_DIR}/../common.sh"
+
+# Clean up previous run
+function clean() {
+    (
+        target_resource_group $resource_group_name
+
+        ibmcloud ce project select --name ${ce_project_name} --quiet 2>/dev/null
+        if [ $? == 0 ]; then
+            ibmcloud ce project delete --name ${ce_project_name} --force --hard --no-wait 2>/dev/null
+        fi
+
+        ibmcloud resource group $resource_group_name --quiet 2>/dev/null
+        if [[ $? == 0 ]]; then
+            COUNTER=0
+            # some resources (e.g. boot volumes) are deleted with some delay. Hence, the script waits before exiting with an error
+            while (( "$(ibmcloud resource service-instances --type all -g $resource_group_name --location $REGION --output json | jq -r '. | length')" > 0 )); do
+                sleep 5
+                COUNTER=$((COUNTER + 1))
+                if ((COUNTER > 3)); then
+                    print_error "Cleanup failed! Please make sure to delete remaining resources manually to avoid unwanted charges."
+                    ibmcloud resource service-instances --type all -g $resource_group_name --location $REGION
+                    exit 1
+                fi
+            done
+        fi
+
+	ibmcloud resource group-delete $resource_group_name --force 2>/dev/null
+    )
+}
+
+if [[ "$1" == "clean" ]]; then
+    print_msg "\nCleaning up the created IBM Cloud resources ..."
+    clean
+    print_success "\n==========================================\n DONE\n==========================================\n"
+    exit 0
+fi
+
+# ==============================
+# MAIN SCRIPT FLOW
+# ==============================
+
+# Ensure that latest versions of used IBM Cloud ClI is installed
+print_msg "\nPulling latest IBM Cloud CLI release ..."
+ibmcloud update --force
+
+# Ensure that latest versions of used IBM Cloud CLI plugins are installed
+print_msg "\nInstalling required IBM Cloud CLI plugins ..."
+ensure_plugin_is_up_to_date code-engine
+
+print_msg "\n======================================================"
+print_msg " Setting up \"Code Engine AI Agent\" sample"
+print_msg "======================================================\n"
+
+target_region $REGION
+
+#
+# Create the resource group, if it does not exist
+ibmcloud resource group $resource_group_name --quiet
+if [ $? != 0 ]; then
+    print_msg "\nCreating resource group '$resource_group_name' ..."
+    ibmcloud resource group-create $resource_group_name
+fi
+target_resource_group $resource_group_name
+
+if ! does_instance_exist codeengine "$ce_project_name"; then
+    print_msg "\nCreating the Code Engine project '$ce_project_name' ..."
+    ibmcloud ce project create --name $ce_project_name
+    if [ $? -ne 0 ]; then
+        print_error "Code Engine project creation failed!"
+        abortScript
+    fi
+else
+    print_msg "\nSelecting the Code Engine project '$ce_project_name' ..."
+    ibmcloud ce project select --name $ce_project_name
+fi
+project_guid=$(ibmcloud ce project get --name $ce_project_name --output json | jq -r '.guid')
+
+print_msg "\nCreating the MCP Server as a code engine application"
+ibmcloud ce app create --name fastmcp --build-source ./server --build-strategy buildpacks  --cpu 1 --memory 4G -p 8080  --wait-timeout 600 --min-scale 0 --visibility public
+
+while true; do
+    ibmcloud ce app list
+    not_ready_apps=$(ibmcloud ce app list | grep -e "fastmcp" | grep "Not Ready")
+    if [  "$not_ready_apps" == "" ]; then
+      break # all apps are ready
+    fi
+    print_msg "\nWaiting for all applications to be ready (sleep 15s)..."
+    sleep 15
+done
+
+print_msg "\n"
+print_msg "\nFastMCP application is ready."
+print_msg "\n"
+
+url=$(ibmcloud ce app get --name fastmcp -o json | jq -r '.status.url')
+print_msg "\nFastMCP application is reachable under the following url:"
+print_msg "\n$url/mcp"
+
+print_success "\n=========================================="
+print_success " SUCCESS"
+print_success "==========================================\n"
+print_msg "\n"
+print_msg "\nrun ./deploy.sh clean to remove all created resources"
diff --git a/ai/mcp_server_fastmcp/images/architecture.png b/ai/mcp_server_fastmcp/images/architecture.png
new file mode 100644
index 00000000..2ea0cc0b
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diff --git a/ai/mcp_server_fastmcp/images/claude_chat.png b/ai/mcp_server_fastmcp/images/claude_chat.png
new file mode 100644
index 00000000..652f6c3f
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diff --git a/ai/mcp_server_fastmcp/images/claude_tool.png b/ai/mcp_server_fastmcp/images/claude_tool.png
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diff --git a/ai/mcp_server_fastmcp/server/Procfile b/ai/mcp_server_fastmcp/server/Procfile
new file mode 100644
index 00000000..bcf68048
--- /dev/null
+++ b/ai/mcp_server_fastmcp/server/Procfile
@@ -0,0 +1 @@
+web: python main.py
\ No newline at end of file
diff --git a/ai/mcp_server_fastmcp/server/main.py b/ai/mcp_server_fastmcp/server/main.py
new file mode 100644
index 00000000..7de7b4d0
--- /dev/null
+++ b/ai/mcp_server_fastmcp/server/main.py
@@ -0,0 +1,12 @@
+from fastmcp import FastMCP
+
+mcp = FastMCP("My FastMCP Server on Code Engine")
+
+@mcp.tool
+def process_data(input: str) -> str:
+    """Process data on the server"""
+    """ADD YOUR BUSINESS LOGIC HERE"""
+    return f"Processed: {input}"
+
+if __name__ == "__main__":
+    mcp.run(transport="http", host="0.0.0.0", port=8080)
\ No newline at end of file
diff --git a/ai/mcp_server_fastmcp/server/requirements.txt b/ai/mcp_server_fastmcp/server/requirements.txt
new file mode 100644
index 00000000..35a7d0c6
--- /dev/null
+++ b/ai/mcp_server_fastmcp/server/requirements.txt
@@ -0,0 +1 @@
+fastmcp
\ No newline at end of file
diff --git a/ai/promptfoo/.gitignore b/ai/promptfoo/.gitignore
new file mode 100644
index 00000000..3ab0d981
--- /dev/null
+++ b/ai/promptfoo/.gitignore
@@ -0,0 +1 @@
+promptfooconfig.yaml
diff --git a/ai/promptfoo/README.md b/ai/promptfoo/README.md
new file mode 100644
index 00000000..cebab270
--- /dev/null
+++ b/ai/promptfoo/README.md
@@ -0,0 +1,152 @@
+# promptfoo on IBM Cloud Code Engine
+
+![](./images/architecture.png)
+
+## What is promptfoo
+
+- [promptfoo](https://www.promptfoo.dev/) is an open-source **LLM testing, evaluation, and red-teaming framework** that helps you build reliable LLM applications.
+- It enables you to **systematically test and compare** prompts, models, and RAG pipelines across providers, ensuring quality and safety before production.
+- Key capabilities include:
+  - **Testing & Evaluation:** Run automated tests with assertions, compare outputs across models, and track performance metrics
+  - **Red-teaming:** Identify vulnerabilities, jailbreaks, and harmful outputs with built-in security testing
+  - **Prompt Engineering:** Iterate on prompts with side-by-side comparisons and regression testing
+  - **CI/CD Integration:** Integrate into your development workflow to catch issues early
+  - **Web UI:** Visualize results, share findings with stakeholders, and collaborate on improvements
+- Supports all major LLM providers (OpenAI, Anthropic, Google, Azure, AWS, and more), local models, and custom providers.
+
+## Why Code Engine is a great fit
+
+Using **[IBM Cloud Code Engine](https://www.ibm.com/products/code-engine)** you can host promptfoo's web UI and create a centralized hub for your team's LLM testing and evaluation workflows.
+
+- **Managed runtime:** Code Engine runs containers without managing servers, lowering operational overhead.
+- **Public endpoints:** Apps get a reachable URL out of the box, making it easy to share test results, red-team findings, and evaluation reports with your team.
+- **Scalability & cost control:** Configure CPU/memory and min/max scale for predictable resource use and autoscaling when needed.
+- **Integrates with COS:** Object storage (IBM Cloud Object Storage) can be mounted as a persistent data store for test results, configurations, datasets, and historical comparisons.
+- **Secure secrets & PDS:** Use Code Engine secrets and Persistent Data Stores (PDS) to store credentials and mount COS buckets securely.
+- **Team collaboration:** Centralized deployment enables teams to share test suites, compare results, and maintain a single source of truth for LLM quality metrics.
+
+## Deploy 
+
+This repository includes a convenience script `deploy.sh` that automates the common steps (creating a Code Engine project, creating a COS instance and bucket, creating a service key, creating a CE secret and PDS, and deploying the image).
+
+**Prerequisites**
+
+Create an IBM Cloud account on the target Code Engine provider (e.g., IBM Cloud Code Engine) and [login into your IBM Cloud account using the IBM Cloud CLI](https://cloud.ibm.com/docs/codeengine?topic=codeengine-install-cli).
+
+
+**Deploy** 
+Run the bundled script from this folder which automates the steps above and configures COS/PDS integration:
+
+```bash
+./deploy.sh
+```
+
+The script accepts optional environment variables to customize region and naming, e.g.:
+
+```bash
+REGION=eu-de NAME_PREFIX=ce-promptfoo ./deploy.sh
+```
+
+Notes on persistence
+
+- The deployment mounts an IBM Cloud Object Storage bucket as a Persistent Data Store so promptfoo can persist evaluation results and configurations across restarts.
+- The script creates a secret (`promptfoo-cos-secret`) containing HMAC credentials and a PDS (`promptfoo-store`) that points the app at the bucket.
+
+## Access the environment
+
+After deployment, retrieve the app URL with:
+
+```bash
+ibmcloud ce app get --name promptfoo -o json | jq -r '.status.url'
+```
+
+The script also prints the reachable URL, for example:
+
+```
+https://promptfoo.26pr644bfbfc.eu-de.codeengine.appdomain.cloud
+```
+
+## Use promptfoo
+
+Open the URL in a browser window to access the web UI of [promptfoo](https://www.promptfoo.dev/) and view your evaluation results.
+
+## Use promptfoo CLI locally and share with the deployed application
+
+You can run promptfoo evaluations locally and share the results with your deployed Code Engine application. This allows you to:
+
+- Run evaluations on your local machine with your preferred configuration
+- View and share results through the hosted web UI
+- Collaborate with team members by pointing them to the shared URL
+
+### Setup
+
+1. Install promptfoo locally:
+
+```bash
+npm install -g promptfoo
+```
+
+2. Get your deployed application URL:
+
+```bash
+ibmcloud ce app get --name promptfoo -o json | jq -r '.status.url'
+```
+
+3. Configure your `promptfooconfig.yaml` to use the deployed application as the sharing endpoint:
+
+```yaml
+# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
+
+description: "My eval"
+
+sharing:
+  apiBaseUrl: https://promptfoo.26pr644bfbfc.eu-de.codeengine.appdomain.cloud
+
+prompts:
+  - "Write a tweet about {{topic}}"
+  - "Write a concise, funny tweet about {{topic}}"
+
+providers:
+  - id: "openai:gpt-4"
+    config:
+      apiKey: ${OPENAI_API_KEY}
+
+tests:
+  - vars:
+      topic: bananas
+
+  - vars:
+      topic: avocado toast
+    assert:
+      - type: icontains
+        value: avocado
+      - type: javascript
+        value: 1 / (output.length + 1)
+```
+
+4. Run your evaluation locally:
+
+```bash
+promptfoo eval
+```
+
+5. Share results in the deployed application:
+
+```bash
+promptfoo share
+```
+
+This will open the local viewer, but you can also access the shared results through your deployed Code Engine URL.
+
+![](./images/promptfoo_ui.png)
+
+### Sharing results
+
+When you run `promptfoo eval` with the `sharing.apiBaseUrl` configured, your evaluation results are automatically uploaded to the deployed application. Team members can then access these results by visiting the Code Engine URL.
+
+**Benefits:**
+- **Centralized results:** All team members can view evaluation results in one place
+- **No local setup required:** Stakeholders can review results without installing promptfoo
+- **Persistent storage:** Results are stored in COS and persist across application restarts
+- **Collaboration:** Share specific evaluation URLs with team members for review and discussion
+
diff --git a/ai/promptfoo/deploy.sh b/ai/promptfoo/deploy.sh
new file mode 100755
index 00000000..c3fe1a49
--- /dev/null
+++ b/ai/promptfoo/deploy.sh
@@ -0,0 +1,179 @@
+#!/bin/bash
+
+# ==============================
+# ENVIRONMENT SETUP
+# ==============================
+
+REGION="${REGION:=eu-de}"
+NAME_PREFIX="${NAME_PREFIX:=ce-promptfoo}"
+
+# Generate a short uuid for some resources
+uuid=$(uuidgen | tr '[:upper:]' '[:lower:]' | awk -F- '{print $1}')
+
+ce_project_name=${PROJECT_NAME:-${NAME_PREFIX}-project}
+resource_group_name=${NAME_PREFIX}-rg
+cos_name="${NAME_PREFIX}--cos"
+cos_key_name="${NAME_PREFIX}--cos-key"
+cos_bucket_name_promptfoo_store="${NAME_PREFIX}-promptfoo-store-${uuid}"
+
+# ==============================
+# COMMON FUNCTIONS
+# ==============================
+
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+source "${SCRIPT_DIR}/../common.sh"
+
+# Clean up previous run
+function clean() {
+    (
+        target_resource_group $resource_group_name
+
+        ibmcloud ce project select --name ${ce_project_name} --quiet 2>/dev/null
+        if [ $? == 0 ]; then
+            ibmcloud ce project delete --name ${ce_project_name} --force --hard --no-wait 2>/dev/null
+        fi
+
+        ibmcloud resource service-key-delete ${cos_key_name} --force 2>/dev/null
+        ibmcloud cos bucket-delete --bucket ${cos_bucket_name_promptfoo_store} --force 2>/dev/null
+        ibmcloud resource service-instance-delete ${cos_name} -f -q 2>/dev/null
+
+        ibmcloud resource group $resource_group_name --quiet 2>/dev/null
+        if [[ $? == 0 ]]; then
+            COUNTER=0
+            # some resources (e.g. boot volumes) are deleted with some delay. Hence, the script waits before exiting with an error
+            while (( "$(ibmcloud resource service-instances --type all -g $resource_group_name --location $REGION --output json | jq -r '. | length')" > 0 )); do
+                sleep 5
+                COUNTER=$((COUNTER + 1))
+                if ((COUNTER > 3)); then
+                    print_error "Cleanup failed! Please make sure to delete remaining resources manually to avoid unwanted charges."
+                    ibmcloud resource service-instances --type all -g $resource_group_name --location $REGION
+                    exit 1
+                fi
+            done
+        fi
+
+	ibmcloud resource group-delete $resource_group_name --force 2>/dev/null
+    )
+}
+
+if [[ "$1" == "clean" ]]; then
+    print_msg "\nCleaning up the created IBM Cloud resources ..."
+    clean
+    print_success "\n==========================================\n DONE\n==========================================\n"
+    exit 0
+fi
+
+# ==============================
+# MAIN SCRIPT FLOW
+# ==============================
+
+# Ensure that latest versions of used IBM Cloud ClI is installed
+print_msg "\nPulling latest IBM Cloud CLI release ..."
+ibmcloud update --force
+
+# Ensure that latest versions of used IBM Cloud CLI plugins are installed
+print_msg "\nInstalling required IBM Cloud CLI plugins ..."
+ensure_plugin_is_up_to_date code-engine
+
+print_msg "\n======================================================"
+print_msg " Setting up \"Code Engine promptfoo\" sample"
+print_msg "======================================================\n"
+
+target_region $REGION
+
+#
+# Create the resource group, if it does not exist
+ibmcloud resource group $resource_group_name --quiet
+if [ $? != 0 ]; then
+    print_msg "\nCreating resource group '$resource_group_name' ..."
+    ibmcloud resource group-create $resource_group_name
+fi
+target_resource_group $resource_group_name
+
+if ! does_instance_exist codeengine "$ce_project_name"; then
+    print_msg "\nCreating the Code Engine project '$ce_project_name' ..."
+    ibmcloud ce project create --name $ce_project_name
+    if [ $? -ne 0 ]; then
+        print_error "Code Engine project creation failed!"
+        abortScript
+    fi
+else
+    print_msg "\nSelecting the Code Engine project '$ce_project_name' ..."
+    ibmcloud ce project select --name $ce_project_name
+fi
+project_guid=$(ibmcloud ce project get --name $ce_project_name --output json | jq -r '.guid')
+
+
+#
+# Creating COS instance and bucket
+if ! does_instance_exist cloud-object-storage "$cos_name"; then
+    print_msg "\nCreating COS instance '${cos_name}' ..."
+    ibmcloud resource service-instance-create $cos_name cloud-object-storage standard global -d premium-global-deployment-iam
+    if [ $? -ne 0 ]; then
+        print_error "Cloud Object Storage creation failed!"
+        abortScript
+    fi
+fi
+
+COS_ID=$(ibmcloud resource service-instance $cos_name --output json | jq -r '.[0] | .id')
+ibmcloud cos config crn --crn ${COS_ID} --force >/dev/null 2>&1
+ibmcloud cos config auth --method IAM >/dev/null
+ibmcloud cos config region --region $REGION >/dev/null
+ibmcloud cos config endpoint-url --url s3.${REGION}.cloud-object-storage.appdomain.cloud >/dev/null
+
+# Make sure all COS buckets do exist
+res=$(has_bucket_name_with_prefix "${NAME_PREFIX}-promptfoo-store-")
+if [[ "$res" == "" ]]; then
+    print_msg "\nCreating COS bucket '${cos_bucket_name_promptfoo_store}' ..."
+    ibmcloud cos bucket-create --bucket ${cos_bucket_name_promptfoo_store} --ibm-service-instance-id $COS_ID
+else
+    cos_bucket_name_promptfoo_store=$res
+fi
+
+
+# Create COS credentials
+if ! does_serviceid_exist "${cos_key_name}"; then
+    print_msg "\nCreating COS service key '${cos_key_name}' ..."
+    ibmcloud resource service-key-create ${cos_key_name} --parameters '{"HMAC":true}' --instance-id $COS_ID
+fi
+
+print_msg "\nCOS instance '${COS_ID}' configured..."
+
+
+print_msg "\nCreating a Code Engine Persistant Data Store 'promptfoo-cos-secret' to access the COS bucket as the task state store ..."
+create_or_update=update
+if ! ibmcloud ce secret get --name promptfoo-cos-secret >/dev/null 2>&1; then
+    create_or_update="create --format hmac"
+fi
+ibmcloud ce secret $create_or_update --name promptfoo-cos-secret \
+    --secret-access-key $(ibmcloud resource service-key ${cos_key_name} --output JSON | jq -r '.[0] | .credentials | .cos_hmac_keys | .secret_access_key') \
+    --access-key-id $(ibmcloud resource service-key ${cos_key_name} --output JSON | jq -r '.[0] | .credentials | .cos_hmac_keys | .access_key_id')
+
+if ! ibmcloud ce pds get --name promptfoo-store >/dev/null 2>&1; then
+    ibmcloud ce pds create --name promptfoo-store \
+        --cos-bucket-name ${cos_bucket_name_promptfoo_store} \
+        --cos-bucket-location ${REGION} \
+        --cos-access-secret promptfoo-cos-secret
+fi
+
+print_msg "\nDeploy the promptfoo application to Code Engine"
+ibmcloud ce app create --name promptfoo --image ghcr.io/promptfoo/promptfoo:latest --cpu 4 --memory 8G -p 3000  --wait-timeout 600 --min-scale 1 --visibility public --mount-data-store /home/promptfoo/.promptfoo=promptfoo-store
+while true; do
+    ibmcloud ce app list
+    not_ready_apps=$(ibmcloud ce app list | grep -e "promptfoo" | grep "Not Ready")
+    if [  "$not_ready_apps" == "" ]; then
+      break # all apps are ready
+    fi
+    print_msg "\nWaiting for all applications to be ready (sleep 15s)..."
+    sleep 15
+done
+
+print_msg "\npromptfoo application is ready."
+
+url=$(ibmcloud ce app get --name promptfoo -o json | jq -r '.status.url')
+print_msg "\npromptfoo application is reachable under the following url:"
+print_msg "$url"
+print_msg "\nrun ./deploy.sh clean to remove all created resources"
+print_success "\n=========================================="
+print_success " SUCCESS"
+print_success "==========================================\n"
diff --git a/ai/promptfoo/images/architecture.png b/ai/promptfoo/images/architecture.png
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diff --git a/ai/promptfoo/images/promptfoo_ui.png b/ai/promptfoo/images/promptfoo_ui.png
new file mode 100644
index 00000000..9edf0131
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