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README.md

DevUI Samples

This folder contains sample agents and workflows designed to work with the Agent Framework DevUI - a lightweight web interface for running and testing agents interactively.

What is DevUI?

DevUI is a sample application that provides:

  • A web interface for testing agents and workflows
  • OpenAI-compatible API endpoints
  • Directory-based entity discovery
  • In-memory entity registration
  • Sample entity gallery

Note: DevUI is a sample app for development and testing. For production use, build your own custom interface using the Agent Framework SDK.

Quick Start

Option 1: In-Memory Mode (Simplest)

Run a single sample directly. This demonstrates how to wrap agents and workflows programmatically without needing a directory structure:

cd python/samples/02-agents/devui
python in_memory_mode.py

This opens your browser at http://localhost:8090 with pre-configured agents and a basic workflow.

Option 2: Directory Discovery

Launch DevUI to discover all samples in this folder:

cd python/samples/02-agents/devui
devui

This starts the server at http://localhost:8080 with all agents and workflows available.

Sample Structure

Each agent/workflow follows a strict structure required by DevUI's discovery system:

agent_name/
├── __init__.py      # Must export: agent = Agent(...)
├── agent.py         # Agent implementation
└── .env.example     # Example environment variables

Available Samples

Agents

Sample Description Features Required Environment Variables
weather_agent_azure/ Weather agent using Azure OpenAI with API key authentication Azure OpenAI integration, function calling, mock weather tools AZURE_OPENAI_API_KEY, AZURE_OPENAI_DEPLOYMENT_NAME, AZURE_OPENAI_ENDPOINT
foundry_agent/ Weather agent using Azure AI Agent (Foundry) with Azure CLI authentication (run az login first) Azure AI Agent integration, Azure CLI authentication, mock weather tools FOUNDRY_PROJECT_ENDPOINT, FOUNDRY_MODEL

Workflows

Sample Description Features Required Environment Variables
declarative/ Declarative YAML workflow with conditional branching YAML-based workflow definition, conditional logic, no Python code required None - uses mock data
workflow_agents/ Content review workflow with agents as executors Agents as workflow nodes, conditional routing based on structured outputs, quality-based paths (Writer -> Reviewer -> Editor/Publisher) AZURE_OPENAI_API_KEY, AZURE_OPENAI_DEPLOYMENT_NAME, AZURE_OPENAI_ENDPOINT
spam_workflow/ 5-step email spam detection workflow with branching logic Sequential execution, conditional branching (spam vs. legitimate), multiple executors, mock spam detection None - uses mock data
fanout_workflow/ Advanced data processing workflow with parallel execution Fan-out/fan-in patterns, complex state management, multi-stage processing (validation -> transformation -> quality assurance) None - uses mock data

Standalone Examples

Sample Description Features
in_memory_mode.py Demonstrates programmatic entity registration without directory structure In-memory agent and workflow registration, multiple entities served from a single file, includes basic workflow, simplest way to get started

Environment Variables

Each sample that requires API keys includes a .env.example file. To use:

  1. Copy .env.example to .env in the same directory
  2. Fill in your actual API keys
  3. DevUI automatically loads .env files from entity directories

Alternatively, set environment variables globally:

export OPENAI_API_KEY="your-key-here"
export OPENAI_CHAT_MODEL="gpt-4o"

Using DevUI with Your Own Agents

To make your agent discoverable by DevUI:

  1. Create a folder for your agent
  2. Add an __init__.py that exports agent or workflow
  3. (Optional) Add a .env file for environment variables

Example:

# my_agent/__init__.py
from agent_framework import Agent
from agent_framework.openai import OpenAIChatClient

agent = Agent(
    name="MyAgent",
    description="My custom agent",
    client=OpenAIChatClient(),
    # ... your configuration
)

Then run:

devui /path/to/my/agents/folder

API Usage

DevUI exposes OpenAI-compatible endpoints:

curl -X POST http://localhost:8080/v1/responses \
  -H "Content-Type: application/json" \
  -d '{
    "model": "agent-framework",
    "input": "What is the weather in Seattle?",
    "extra_body": {"entity_id": "agent_directory_weather-agent_<uuid>"}
  }'

List available entities:

curl http://localhost:8080/v1/entities

Learn More

Troubleshooting

Missing API keys: Check your .env files or environment variables.

Import errors: Make sure you've installed the devui package:

pip install agent-framework-devui --pre

Port conflicts: DevUI uses ports 8080 (directory mode) and 8090 (in-memory mode) by default. Close other services or specify a different port:

devui --port 8888