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# What this sample demonstrates
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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.
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Key features showcased:
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- **HarnessAgent** — a pre-configured agent that wraps a `ChatClientAgent` with function invocation, per-service-call persistence, and context-window compaction
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- **ToolApproval** — the agent is wrapped with `UseToolApproval()` to allow auto-approving tools once confirmed
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- **Web Search** — the agent can search the web for current information via `ResponseTool.CreateWebSearchTool()`
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- **TodoProvider** — the agent creates and manages a todo list to track research questions
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- **AgentModeProvider** — the agent switches between "plan" mode (breaking down the topic) and "execute" mode (answering each research question)
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- **TodoCompletionLoopEvaluator** — in "execute" mode the agent loops automatically, re-invoking itself until every todo item is complete (capped by `LoopAgentOptions.MaxIterations`). The loop is scoped to "execute" mode, so "plan" mode stays interactive. The `HarnessAgent` wraps itself in a `LoopAgent` automatically whenever `LoopEvaluators` is supplied.
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- **Interactive conversation** — you can review the agent's plan, provide feedback, and approve before execution begins
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- **Streaming output** — responses are streamed token-by-token for a natural experience
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- **`/todos` command** — view the current todo list at any time without invoking the agent
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- **Mode-based coloring** — console output is colored based on the agent's current mode (cyan for plan, green for execute)
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## Prerequisites
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Before running this sample, ensure you have:
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1. An Azure AI Foundry project with a deployed model (e.g., `gpt-5.4`)
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2. Azure CLI installed and authenticated (`az login`)
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## Environment Variables
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Set the following environment variables:
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```bash
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# Required: Your Azure AI Foundry OpenAI endpoint
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export AZURE_FOUNDRY_OPENAI_ENDPOINT="https://your-project.services.ai.azure.com/openai/v1/"
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# Optional: Model deployment name (defaults to gpt-5.4)
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export FOUNDRY_MODEL="gpt-5.4"
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```
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## Running the Sample
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```bash
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cd dotnet
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dotnet run --project samples/02-agents/Harness/Harness_Step01_Research
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```
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## What to Expect
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The sample starts an interactive conversation loop. You can:
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1. **Enter a research topic** — the agent will analyze it and create a plan with todos
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2. **Review and adjust** — provide feedback on the plan, ask for changes, or approve it
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3. **Type `/todos`** — to see the current todo list at any time
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4. **Watch execution** — once approved, the agent will switch to "execute" mode and process each todo autonomously until the whole plan is complete
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5. **Type `exit`** — to end the session
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The prompt and agent output are colored by the current mode: **cyan** during planning, **green** during execution.
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