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* [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces Also clean up follow-on docs, environment guidance, package metadata, and lab test stability. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix deleted semantic-kernel sample links Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * improve foundry language * Fix A2A Foundry sample regression Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
161 lines
7.4 KiB
Markdown
161 lines
7.4 KiB
Markdown
# DevUI Samples
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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.
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## What is DevUI?
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DevUI is a sample application that provides:
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- A web interface for testing agents and workflows
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- OpenAI-compatible API endpoints
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- Directory-based entity discovery
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- In-memory entity registration
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- Sample entity gallery
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> **Note**: DevUI is a sample app for development and testing. For production use, build your own custom interface using the Agent Framework SDK.
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## Quick Start
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### Option 1: In-Memory Mode (Simplest)
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Run a single sample directly. This demonstrates how to wrap agents and workflows programmatically without needing a directory structure:
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```bash
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cd python/samples/02-agents/devui
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python in_memory_mode.py
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```
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This opens your browser at http://localhost:8090 with pre-configured agents and a basic workflow.
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### Option 2: Directory Discovery
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Launch DevUI to discover all samples in this folder:
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```bash
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cd python/samples/02-agents/devui
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devui
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```
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This starts the server at http://localhost:8080 with all agents and workflows available.
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## Sample Structure
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Each agent/workflow follows a strict structure required by DevUI's discovery system:
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```
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agent_name/
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├── __init__.py # Must export: agent = Agent(...)
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├── agent.py # Agent implementation
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└── .env.example # Example environment variables
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```
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## Available Samples
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### Agents
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| Sample | Description | Features | Required Environment Variables |
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| ------------------------------------------------ | ------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
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| [**weather_agent_azure/**](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` |
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| [**foundry_agent/**](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` |
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### Workflows
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| Sample | Description | Features | Required Environment Variables |
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| -------------------------------------------- | ----------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- |
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| [**declarative/**](declarative/) | Declarative YAML workflow with conditional branching | YAML-based workflow definition, conditional logic, no Python code required | None - uses mock data |
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| [**workflow_agents/**](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` |
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| [**spam_workflow/**](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 |
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| [**fanout_workflow/**](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 |
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### Standalone Examples
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| Sample | Description | Features |
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| ------------------------------------------ | ------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- |
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| [**in_memory_mode.py**](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 |
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## Environment Variables
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Each sample that requires API keys includes a `.env.example` file. To use:
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1. Copy `.env.example` to `.env` in the same directory
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2. Fill in your actual API keys
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3. DevUI automatically loads `.env` files from entity directories
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Alternatively, set environment variables globally:
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```bash
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export OPENAI_API_KEY="your-key-here"
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export OPENAI_CHAT_MODEL="gpt-4o"
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```
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## Using DevUI with Your Own Agents
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To make your agent discoverable by DevUI:
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1. Create a folder for your agent
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2. Add an `__init__.py` that exports `agent` or `workflow`
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3. (Optional) Add a `.env` file for environment variables
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Example:
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```python
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# my_agent/__init__.py
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from agent_framework import Agent
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from agent_framework.openai import OpenAIChatClient
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agent = Agent(
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name="MyAgent",
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description="My custom agent",
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client=OpenAIChatClient(),
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# ... your configuration
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)
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```
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Then run:
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```bash
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devui /path/to/my/agents/folder
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```
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## API Usage
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DevUI exposes OpenAI-compatible endpoints:
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```bash
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curl -X POST http://localhost:8080/v1/responses \
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-H "Content-Type: application/json" \
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-d '{
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"model": "agent-framework",
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"input": "What is the weather in Seattle?",
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"extra_body": {"entity_id": "agent_directory_weather-agent_<uuid>"}
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}'
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```
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List available entities:
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```bash
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curl http://localhost:8080/v1/entities
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```
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## Learn More
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- [DevUI Documentation](../../../packages/devui/README.md)
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- [Agent Framework Documentation](https://docs.microsoft.com/agent-framework)
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- [Sample Guidelines](../../SAMPLE_GUIDELINES.md)
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## Troubleshooting
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**Missing API keys**: Check your `.env` files or environment variables.
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**Import errors**: Make sure you've installed the devui package:
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```bash
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pip install agent-framework-devui --pre
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```
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**Port conflicts**: DevUI uses ports 8080 (directory mode) and 8090 (in-memory mode) by default. Close other services or specify a different port:
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```bash
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devui --port 8888
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```
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