agent-framework/dotnet/samples/02-agents/Harness/Harness_Step01_Research

What this sample demonstrates

This sample demonstrates how to use a HarnessAgent with the Harness AIContextProviders (TodoProvider and AgentModeProvider) for interactive research tasks with web search capabilities powered by Azure AI Foundry. The HarnessAgent pre-configures function invocation, per-service-call chat history persistence, and context-window compaction.

Key features showcased:

• HarnessAgent — a pre-configured agent that wraps a ChatClientAgent with function invocation, per-service-call persistence, and context-window compaction
• ToolApproval — the agent is wrapped with UseToolApproval() to allow auto-approving tools once confirmed
• Web Search — the agent can search the web for current information via ResponseTool.CreateWebSearchTool()
• TodoProvider — the agent creates and manages a todo list to track research questions
• AgentModeProvider — the agent switches between "plan" mode (breaking down the topic) and "execute" mode (answering each research question)
• Interactive conversation — you can review the agent's plan, provide feedback, and approve before execution begins
• Streaming output — responses are streamed token-by-token for a natural experience
• /todos command — view the current todo list at any time without invoking the agent
• Mode-based coloring — console output is colored based on the agent's current mode (cyan for plan, green for execute)

Prerequisites

Before running this sample, ensure you have:

1. An Azure AI Foundry project with a deployed model (e.g., gpt-5.4)
2. Azure CLI installed and authenticated (az login)

Environment Variables

Set the following environment variables:

# Required: Your Azure AI Foundry OpenAI endpoint
export AZURE_FOUNDRY_OPENAI_ENDPOINT="https://your-project.services.ai.azure.com/openai/v1/"

# Optional: Model deployment name (defaults to gpt-5.4)
export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4"

Running the Sample

cd dotnet
dotnet run --project samples/02-agents/Harness/Harness_Step01_Research

What to Expect

The sample starts an interactive conversation loop. You can:

1. Enter a research topic — the agent will analyze it and create a plan with todos
2. Review and adjust — provide feedback on the plan, ask for changes, or approve it
3. Type /todos — to see the current todo list at any time
4. Watch execution — once approved, tell the agent to proceed and it will work through each todo
5. Type exit — to end the session

The prompt and agent output are colored by the current mode: cyan during planning, green during execution.