mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Merge branch 'main' into test-it-bump-aaip210b2
This commit is contained in:
Roger Barreto
GitHub
+4
@@ -31,6 +31,10 @@ public sealed class ToolCallDisplayObserver : ConsoleObserver
|
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{
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await ux.WriteInfoLineAsync($"🔧 Calling tool: {ToolCallFormatter.Format(this._formatters, functionCall)}...", ConsoleColor.DarkYellow);
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}
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else if (content is WebSearchToolCallContent)
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{
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// Handled by OpenAIResponsesWebSearchDisplayObserver when present; skip here to avoid duplication.
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}
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else if (content is ToolCallContent toolCall)
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{
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await ux.WriteInfoLineAsync($"🔧 Calling tool: {toolCall}...", ConsoleColor.DarkYellow);
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+9
-9
@@ -6,26 +6,26 @@ using Microsoft.Extensions.AI;
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namespace Harness.Shared.Console.ToolFormatters;
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/// <summary>
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/// Formats <c>SubAgents_*</c> tool calls with human-readable details
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/// Formats <c>BackgroundAgents_*</c> tool calls with human-readable details
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/// for task start, continue, wait, and result retrieval operations.
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/// </summary>
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public sealed class SubAgentToolFormatter : ToolCallFormatter
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public sealed class BackgroundAgentToolFormatter : ToolCallFormatter
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{
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/// <inheritdoc/>
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public override bool CanFormat(FunctionCallContent call) => call.Name.StartsWith("SubAgents_", StringComparison.Ordinal);
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public override bool CanFormat(FunctionCallContent call) => call.Name.StartsWith("BackgroundAgents_", StringComparison.Ordinal);
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/// <inheritdoc/>
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public override string? FormatDetail(FunctionCallContent call) => call.Name switch
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{
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"SubAgents_StartTask" => FormatStartSubTask(call),
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"SubAgents_WaitForFirstCompletion" => FormatIdList(call, "taskIds", "Wait for"),
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"SubAgents_GetTaskResults" => FormatSingleId(call, "taskId"),
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"SubAgents_ContinueTask" => FormatContinueTask(call),
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"SubAgents_ClearCompletedTask" => FormatSingleId(call, "taskId"),
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"BackgroundAgents_StartTask" => FormatStartBackgroundTask(call),
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"BackgroundAgents_WaitForFirstCompletion" => FormatIdList(call, "taskIds", "Wait for"),
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"BackgroundAgents_GetTaskResults" => FormatSingleId(call, "taskId"),
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"BackgroundAgents_ContinueTask" => FormatContinueTask(call),
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"BackgroundAgents_ClearCompletedTask" => FormatSingleId(call, "taskId"),
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_ => null,
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};
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private static string? FormatStartSubTask(FunctionCallContent call)
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private static string? FormatStartBackgroundTask(FunctionCallContent call)
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{
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string? agentName = GetStringArgumentValue(call, "agentName");
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string? description = GetStringArgumentValue(call, "description");
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+45
-1
@@ -19,7 +19,7 @@ public sealed class TodoToolFormatter : ToolCallFormatter
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public override string? FormatDetail(FunctionCallContent call) => call.Name switch
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{
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"TodoList_Add" => FormatAddTodos(call),
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"TodoList_Complete" => FormatIdList(call, "ids", "Complete"),
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"TodoList_Complete" => FormatCompleteTodos(call),
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"TodoList_Remove" => FormatIdList(call, "ids", "Remove"),
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_ => null,
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};
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@@ -64,6 +64,50 @@ public sealed class TodoToolFormatter : ToolCallFormatter
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return sb.ToString();
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}
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private static string? FormatCompleteTodos(FunctionCallContent call)
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{
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if (call.Arguments?.TryGetValue("items", out object? itemsObj) != true || itemsObj is null)
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{
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return null;
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}
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var entries = new List<(int Id, string? Reason)>();
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if (itemsObj is JsonElement jsonArray && jsonArray.ValueKind == JsonValueKind.Array)
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{
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foreach (JsonElement item in jsonArray.EnumerateArray())
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{
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if (!item.TryGetProperty("id", out JsonElement idElement) || !idElement.TryGetInt32(out int id))
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{
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continue;
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}
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string? reason = item.TryGetProperty("reason", out JsonElement reasonElement)
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||||
? reasonElement.GetString()
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: null;
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||||
entries.Add((id, reason));
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||||
}
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||||
}
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||||
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if (entries.Count == 0)
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||||
{
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||||
return null;
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||||
}
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||||
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var sb = new StringBuilder();
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||||
for (int i = 0; i < entries.Count; i++)
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{
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string connector = i < entries.Count - 1 ? "├─" : "└─";
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sb.Append($"\n {connector} Complete #{entries[i].Id}");
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if (!string.IsNullOrEmpty(entries[i].Reason))
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||||
{
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||||
sb.Append($" — {Truncate(entries[i].Reason!, 80)}");
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||||
}
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||||
}
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||||
return sb.ToString();
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}
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private static string? FormatIdList(FunctionCallContent call, string paramName, string verb)
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{
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List<int>? ids = GetIntListArgumentValue(call, paramName);
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+1
-1
@@ -56,7 +56,7 @@ public abstract class ToolCallFormatter
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[
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new TodoToolFormatter(),
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new ModeToolFormatter(),
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new SubAgentToolFormatter(),
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new BackgroundAgentToolFormatter(),
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new FileMemoryToolFormatter(),
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new WebSearchToolFormatter(),
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new FallbackToolFormatter(),
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+206
@@ -0,0 +1,206 @@
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// Copyright (c) Microsoft. All rights reserved.
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#pragma warning disable OPENAI001 // Suppress experimental API warnings for Responses API usage.
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using System.Text;
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using Harness.Shared.Console;
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using Harness.Shared.Console.Observers;
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using Microsoft.Agents.AI;
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using Microsoft.Extensions.AI;
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using OpenAI.Responses;
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namespace SampleApp;
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||||
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/// <summary>
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||||
/// Displays web search activity in the scroll area. Shows search queries,
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/// page opens, and find-in-page actions as they stream in from the API.
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/// </summary>
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internal sealed class OpenAIResponsesWebSearchDisplayObserver : ConsoleObserver
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{
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private const int MaxQueryDisplayLength = 120;
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/// <inheritdoc/>
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public override async Task OnContentAsync(IUXStateDriver ux, AIContent content, AIAgent agent, AgentSession session)
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{
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if (content is WebSearchToolResultContent resultContent
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&& resultContent.RawRepresentation is WebSearchCallResponseItem wscri)
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{
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await WriteActionAsync(ux, wscri, resultContent.Outputs);
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}
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}
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private static async Task WriteActionAsync(IUXStateDriver ux, WebSearchCallResponseItem wscri, IList<AIContent>? outputs)
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||||
{
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||||
WebSearchAction? action = wscri.Action;
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||||
if (action is null)
|
||||
{
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||||
await ux.WriteInfoLineAsync("🌐 Web Search Tool (no action details)", ConsoleColor.DarkCyan);
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return;
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}
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switch (action)
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||||
{
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case WebSearchFindInPageAction findInPage:
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await WriteFindInPageAsync(ux, findInPage);
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break;
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case WebSearchOpenPageAction openPage:
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await WriteOpenPageAsync(ux, openPage);
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break;
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case WebSearchSearchAction search:
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await WriteSearchAsync(ux, search, outputs);
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break;
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default:
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await ux.WriteInfoLineAsync("🌐 Web Search Tool (unknown action)", ConsoleColor.DarkCyan);
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break;
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}
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}
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private static async Task WriteSearchAsync(IUXStateDriver ux, WebSearchSearchAction search, IList<AIContent>? outputs)
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||||
{
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// Read queries directly from the typed action.
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||||
IList<string> queries = search.Queries;
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||||
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||||
if (queries.Count == 0)
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||||
{
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await ux.WriteInfoLineAsync("🌐 Web Search Tool: search", ConsoleColor.DarkCyan);
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return;
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}
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var sb = new StringBuilder();
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sb.Append("🌐 Web Search Tool: search");
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// Show the search queries.
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bool hasResults = outputs is { Count: > 0 };
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for (int i = 0; i < queries.Count; i++)
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||||
{
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||||
string connector = (i < queries.Count - 1 || hasResults) ? "├─" : "└─";
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||||
string query = Truncate(queries[i], MaxQueryDisplayLength);
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sb.Append($"\n {connector} \"{query}\"");
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}
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||||
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// Show search result sources (URLs + titles) when available.
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// Sources come from M.E.AI's Outputs when IncludedResponseProperty.WebSearchCallActionSources is set,
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// or directly from the SDK's WebSearchSearchAction.Sources.
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if (hasResults)
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{
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sb.Append("\n │");
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for (int i = 0; i < outputs!.Count; i++)
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||||
{
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||||
string connector = i < outputs.Count - 1 ? "├─" : "└─";
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string line = FormatOutput(outputs[i]);
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sb.Append($"\n {connector} {line}");
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}
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}
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else if (search.Sources is { Count: > 0 } sources)
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{
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sb.Append("\n │");
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for (int i = 0; i < sources.Count; i++)
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||||
{
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||||
string connector = i < sources.Count - 1 ? "├─" : "└─";
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||||
string line = FormatSource(sources[i]);
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||||
sb.Append($"\n {connector} {line}");
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||||
}
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||||
}
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||||
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||||
await ux.WriteInfoLineAsync(sb.ToString(), ConsoleColor.DarkCyan);
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||||
}
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||||
private static async Task WriteOpenPageAsync(IUXStateDriver ux, WebSearchOpenPageAction openPage)
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||||
{
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||||
string url = openPage.Uri?.AbsoluteUri ?? "(unknown)";
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await ux.WriteInfoLineAsync(
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$"🌐 Web Search Tool: open page\n └─ {url}",
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ConsoleColor.DarkCyan);
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}
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private static async Task WriteFindInPageAsync(IUXStateDriver ux, WebSearchFindInPageAction findInPage)
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{
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string url = findInPage.Uri?.AbsoluteUri ?? "(unknown)";
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||||
string pattern = findInPage.Pattern ?? "(unknown)";
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||||
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||||
await ux.WriteInfoLineAsync(
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$"🌐 Web Search Tool: find in page\n ├─ \"{Truncate(pattern, MaxQueryDisplayLength)}\"\n └─ {url}",
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ConsoleColor.DarkCyan);
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||||
}
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||||
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||||
/// <summary>
|
||||
/// Formats a single search result source from the SDK's <see cref="WebSearchActionSource"/> for display.
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||||
/// </summary>
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||||
private static string FormatSource(WebSearchActionSource source)
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||||
{
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||||
if (source is WebSearchActionUriSource uriSource)
|
||||
{
|
||||
string url = uriSource.Uri?.AbsoluteUri ?? "(unknown)";
|
||||
|
||||
// WebSearchActionUriSource doesn't expose a title property,
|
||||
// but the API may include one in the raw response JSON.
|
||||
string? title = GetTitleFromRawRepresentation(uriSource);
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||||
|
||||
return title is not null
|
||||
? $"{Truncate(title, MaxQueryDisplayLength)} — {url}"
|
||||
: url;
|
||||
}
|
||||
|
||||
return source.ToString() ?? "(unknown source)";
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Formats a single search result output from M.E.AI's <see cref="AIContent"/> for display.
|
||||
/// </summary>
|
||||
private static string FormatOutput(AIContent output)
|
||||
{
|
||||
if (output is UriContent uriContent)
|
||||
{
|
||||
string url = uriContent.Uri?.AbsoluteUri ?? "(unknown)";
|
||||
|
||||
// Try to extract a title from the raw JSON of the source.
|
||||
// The SDK's WebSearchActionUriSource doesn't expose a title property,
|
||||
// but the API may include one in the raw response.
|
||||
string? title = GetTitleFromRawRepresentation(uriContent.RawRepresentation)
|
||||
?? (uriContent.AdditionalProperties?.TryGetValue("title", out var t) is true ? t?.ToString() : null);
|
||||
|
||||
return title is not null
|
||||
? $"{Truncate(title, MaxQueryDisplayLength)} — {url}"
|
||||
: url;
|
||||
}
|
||||
|
||||
return output.ToString() ?? "(unknown output)";
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Attempts to extract a "title" field from a raw representation object by serializing it to JSON.
|
||||
/// The SDK's <see cref="WebSearchActionUriSource"/> doesn't expose a title property,
|
||||
/// but the API may include one in the raw JSON — this is forward-compatible for when
|
||||
/// the SDK adds title support.
|
||||
/// </summary>
|
||||
private static string? GetTitleFromRawRepresentation(object? rawRepresentation)
|
||||
{
|
||||
if (rawRepresentation is null)
|
||||
{
|
||||
return null;
|
||||
}
|
||||
|
||||
try
|
||||
{
|
||||
var data = System.ClientModel.Primitives.ModelReaderWriter.Write(rawRepresentation);
|
||||
using var doc = System.Text.Json.JsonDocument.Parse(data);
|
||||
if (doc.RootElement.TryGetProperty("title", out var titleEl)
|
||||
&& titleEl.ValueKind == System.Text.Json.JsonValueKind.String)
|
||||
{
|
||||
return titleEl.GetString();
|
||||
}
|
||||
}
|
||||
catch
|
||||
{
|
||||
// Serialization may not be supported for this object type.
|
||||
}
|
||||
|
||||
return null;
|
||||
}
|
||||
|
||||
private static string Truncate(string text, int maxLength)
|
||||
=> text.Length <= maxLength ? text : string.Concat(text.AsSpan(0, maxLength - 1), "…");
|
||||
}
|
||||
@@ -1,8 +1,9 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// 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.
|
||||
// This sample demonstrates how to use a HarnessAgent for interactive research tasks.
|
||||
// The HarnessAgent comes pre-configured with TodoProvider, AgentModeProvider, FileMemoryProvider,
|
||||
// ToolApproval, WebSearch, and OpenTelemetry — so this sample only needs custom instructions
|
||||
// and a WebBrowsingTool.
|
||||
// The agent plans research tasks, creates a todo list, gets user approval,
|
||||
// and then executes each step — all within an interactive conversation loop.
|
||||
//
|
||||
@@ -34,86 +35,32 @@ const int MaxOutputTokens = 128_000;
|
||||
// and research-focused instructions including the mandatory planning workflow.
|
||||
var instructions =
|
||||
"""
|
||||
## Research Assistant Instructions
|
||||
|
||||
You are a research assistant. When given a research topic, research it thoroughly using web search and web browsing.
|
||||
Use your knowledge to form good search queries and hypotheses, but always verify claims with the tools available to you rather than relying on memory alone.
|
||||
|
||||
## Mandatory planning workflow
|
||||
|
||||
For every new substantive user request, including short factual questions, your behavior is determined by the mode you are in.
|
||||
If you are in plan mode, start with the *Plan Mode* steps, and if you are in execute mode, skip directly to the *Execute Mode* steps below.
|
||||
|
||||
*Plan Mode*
|
||||
|
||||
1. Analyze the request with the purpose of building a research plan.
|
||||
2. Create a list of todo items.
|
||||
3. If needed, use the provided tools to do some exploratory checks to help build a plan and determine what clarifying questions you may need from the user.
|
||||
4. Ask for clarifications from the user where needed.
|
||||
1. Ask each clarification one by one.
|
||||
2. When asking for clarification and you have specific options in mind, present them to the user, so they can choose the option instead of having to retype the entire response.
|
||||
3. Do not proceed until you have received all the needed clarifications.
|
||||
4. Do short exploratory research if it helps with being able to ask sensible clarifications from the user.
|
||||
5. Write the plan to a memory file, so that it is retained even if compaction happens. Make sure to update the plan file if the user requests changes.
|
||||
6. Present the plan to the user and ask for approval to switch to execute mode and process the plan.
|
||||
7. When approval is granted, always switch to execute mode (using the `AgentMode_Set` tool), and follow the steps for *Execute mode*.
|
||||
|
||||
*Execute Mode*
|
||||
|
||||
1. If you don't have a plan or tasks yet, analyse the user request and create tasks and a plan. (**Skip this step if you came from plan mode**)
|
||||
2. Work autonomously — use your best judgement to make decisions and keep progressing without asking the user questions. The goal is to have a complete, useful result ready when the user returns.
|
||||
3. If you encounter ambiguity or an unexpected situation during execution, choose the most reasonable option, note your choice, and keep going.
|
||||
4. Mark tasks as completed as you finish them.
|
||||
5. Continue working, thinking and calling tools until you have the research result for the user.
|
||||
|
||||
## General Instructions
|
||||
|
||||
- You must check the current mode after any user input, since the user may have changed the mode themselves,
|
||||
e.g. the user may have switched to 'plan' mode after a previous research task finished in 'execute' mode, meaning they want to review a plan first before execution.
|
||||
- Explain your reasoning and thought process as you work through tasks.
|
||||
- Explain what you learned and what you are going to do next between tool calls, so the user can follow along with your thought process.
|
||||
- Avoid making more than 4 tool calls in a row without explaining what you are doing.
|
||||
- Do not answer the underlying question before the plan has been presented and approved.
|
||||
- This rule applies even when the answer seems obvious or the task seems small.
|
||||
- For short requests, use a brief micro-plan rather than skipping planning. The only exceptions are:
|
||||
- greetings,
|
||||
- pure acknowledgments,
|
||||
- clarification questions needed to form the plan,
|
||||
- follow-up questions about results you have already presented,
|
||||
- meta-discussion about the workflow itself.
|
||||
|
||||
**Todo management**
|
||||
|
||||
Mark each todo complete as you finish it so the list stays current.
|
||||
If a todo turns out to be unnecessary or is blocked, remove it and briefly explain why.
|
||||
Once the user finishes with a topic and moves onto a new one, clean up old completed todos by deleting them.
|
||||
|
||||
**Research quality**
|
||||
### Research quality
|
||||
|
||||
Consult multiple sources when possible and cross-reference key claims.
|
||||
When sources disagree, note the discrepancy and explain which source you consider more reliable and why.
|
||||
If a web page fails to load or a search returns irrelevant results, try alternative search queries or sources before moving on.
|
||||
Track your sources — you will need them when presenting results.
|
||||
|
||||
**Presenting results**
|
||||
### Presenting results
|
||||
|
||||
When presenting your final findings:
|
||||
- Use Markdown formatting for clarity.
|
||||
- Use clear sections with headings for each major topic or sub-question.
|
||||
- Cite your sources inline (e.g., "According to [source name](URL), ...").
|
||||
- End with a brief summary of key takeaways.
|
||||
- Save the final research report to file memory so it survives compaction and can be referenced later.
|
||||
|
||||
**File memory**
|
||||
|
||||
Use the FileMemory_* tools to:
|
||||
- Store downloaded search results or web pages.
|
||||
- Store plans.
|
||||
- Read the current plan to make sure tasks were done according to plan.
|
||||
- Store findings.
|
||||
- Check for relevant previously downloaded data / findings before starting new research.
|
||||
- In addition to returning the results to the user, save the final research report to file memory so it survives compaction and can be referenced later.
|
||||
""";
|
||||
|
||||
// Create the agent using AsHarnessAgent, which pre-configures function invocation,
|
||||
// per-service-call chat history persistence, and in-loop compaction.
|
||||
// Then wrap with UseToolApproval to allow auto-approving tools once confirmed.
|
||||
// per-service-call chat history persistence, in-loop compaction, TodoProvider, AgentModeProvider,
|
||||
// FileMemoryProvider, ToolApproval, WebSearch, AgentSkillsProvider, and OpenTelemetry.
|
||||
// Only custom instructions, a WebBrowsingTool, and FileAccess opt-out are needed.
|
||||
AIAgent agent =
|
||||
// Create an OpenAIClient that communicates with the Foundry responses service.
|
||||
new OpenAIClient(
|
||||
@@ -127,35 +74,26 @@ AIAgent agent =
|
||||
RetryPolicy = new ClientRetryPolicy(3) // Enable retries to improve resiliency.
|
||||
})
|
||||
.GetResponsesClient()
|
||||
.AsIChatClientWithStoredOutputDisabled(deploymentName) // We want to manage chat history locally (not stored in the responses service), so that we can manage compaction ourselves.
|
||||
.AsIChatClientWithStoredOutputDisabled(deploymentName) // We want to manage chat history locally (not stored in the responses service), so that we can manage compaction ourselves.
|
||||
.AsHarnessAgent(MaxContextWindowTokens, MaxOutputTokens, new HarnessAgentOptions
|
||||
{
|
||||
Name = "ResearchAgent",
|
||||
Description = "A research assistant that plans and executes research tasks.",
|
||||
AIContextProviders =
|
||||
[
|
||||
new TodoProvider(), // Add an AIContextProvider to allow the agent to create a TODO list, which is stored in the session.
|
||||
new AgentModeProvider(), // Add an AIContextProvider that tracks the agent mode and allows switching mode. Current mode is stored in the session.
|
||||
new FileMemoryProvider( // Add an AIContextProvider that can store memories in files under a session specific working folder.
|
||||
new FileSystemAgentFileStore(Path.Combine(AppContext.BaseDirectory, "agent-files")),
|
||||
(_) => new FileMemoryState() { WorkingFolder = DateTime.UtcNow.ToString("yyyyMMdd_HHmmss") + "_" + Guid.NewGuid().ToString() })
|
||||
],
|
||||
DisableFileMemory = true, // If enabled, this would allow the agent to store memories as files in a directory associated with the current session
|
||||
FileMemoryStore = new FileSystemAgentFileStore( // Configure the file memory provider to store files in a local folder called "agent-files".
|
||||
Path.Combine(AppContext.BaseDirectory, "agent-files")),
|
||||
ChatOptions = new ChatOptions
|
||||
{
|
||||
Instructions = instructions,
|
||||
Tools =
|
||||
[
|
||||
ResponseTool.CreateWebSearchTool().AsAITool(), // Add the foundry hosted web search tool that runs in the service.
|
||||
new WebBrowsingTool( // Add a local web browsing tool that converts html to markdown.
|
||||
new WebBrowsingTool( // Add a local web browsing tool that converts html to markdown.
|
||||
new WebBrowsingToolOptions { AllowPublicNetworks = true }),
|
||||
],
|
||||
MaxOutputTokens = MaxOutputTokens, // Set a high token limit for long research tasks with many tool calls and long outputs.
|
||||
MaxOutputTokens = MaxOutputTokens, // Set a high token limit for long research tasks with many tool calls and long outputs.
|
||||
Reasoning = new() { Effort = ReasoningEffort.Medium },
|
||||
},
|
||||
})
|
||||
.AsBuilder()
|
||||
.UseToolApproval() // Add the ability to auto approve tools once a user has said they don't want to be asked again. Approval rules are tied to the session.
|
||||
.Build();
|
||||
});
|
||||
|
||||
// Run the interactive console session using the shared HarnessConsole helper.
|
||||
await HarnessConsole.RunAgentAsync(
|
||||
@@ -163,12 +101,14 @@ await HarnessConsole.RunAgentAsync(
|
||||
userPrompt: "Enter a research topic to get started.",
|
||||
new HarnessConsoleOptions
|
||||
{
|
||||
Observers = HarnessConsoleOptions.BuildObserversWithPlanning(
|
||||
agent,
|
||||
planModeName: "plan",
|
||||
executionModeName: "execute",
|
||||
maxContextWindowTokens: MaxContextWindowTokens,
|
||||
maxOutputTokens: MaxOutputTokens,
|
||||
toolFormatters: [new DownloadUriToolFormatter(), .. ToolCallFormatter.BuildDefaultToolFormatters()]),
|
||||
Observers = [
|
||||
new OpenAIResponsesWebSearchDisplayObserver(),
|
||||
.. HarnessConsoleOptions.BuildObserversWithPlanning(
|
||||
agent,
|
||||
planModeName: "plan",
|
||||
executionModeName: "execute",
|
||||
maxContextWindowTokens: MaxContextWindowTokens,
|
||||
maxOutputTokens: MaxOutputTokens,
|
||||
toolFormatters: [new DownloadUriToolFormatter(), .. ToolCallFormatter.BuildDefaultToolFormatters()])],
|
||||
CommandHandlers = HarnessConsoleOptions.BuildDefaultCommandHandlers(agent),
|
||||
});
|
||||
|
||||
+31
-19
@@ -1,9 +1,10 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample demonstrates how to use the SubAgentsProvider to delegate work to sub-agents.
|
||||
// This sample demonstrates how to use the BackgroundAgentsProvider to delegate work to background agents.
|
||||
// A parent agent is given a list of stock tickers and instructed to find the closing price
|
||||
// for each ticker on December 31, 2025. It delegates the web searches to a sub-agent
|
||||
// equipped with Foundry's hosted web search tool.
|
||||
// for each ticker on December 31, 2025. It delegates the web searches to a background agent.
|
||||
// The HarnessAgent provides built-in WebSearch (HostedWebSearchTool) so no manual web search
|
||||
// tool configuration is needed on the background agent.
|
||||
//
|
||||
// Special commands:
|
||||
// /exit — End the session.
|
||||
@@ -25,8 +26,9 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYME
|
||||
const int MaxContextWindowTokens = 1_050_000;
|
||||
const int MaxOutputTokens = 128_000;
|
||||
|
||||
// --- Sub-agent: Web Search Agent ---
|
||||
// This agent can search the web and is used by the parent agent to look up stock prices.
|
||||
// --- Background agent: Web Search Agent ---
|
||||
// This agent uses the HarnessAgent's built-in HostedWebSearchTool to search the web.
|
||||
// Features not needed by this sub-agent are disabled.
|
||||
AIAgent webSearchAgent =
|
||||
new OpenAIClient(
|
||||
new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"),
|
||||
@@ -41,40 +43,44 @@ AIAgent webSearchAgent =
|
||||
{
|
||||
Name = "WebSearchAgent",
|
||||
Description = "An agent that can search the web to find information.",
|
||||
DisableTodoProvider = true,
|
||||
DisableAgentModeProvider = true,
|
||||
DisableFileMemory = true, // If enabled, this would allow the agent to store memories as files in a directory associated with the current session
|
||||
DisableFileAccess = true, // If enabled, this would allow the agent to read/write files in a working directory
|
||||
DisableToolApproval = true, // If enabled, this allows don't-ask-again approval functionality.
|
||||
ChatOptions = new ChatOptions
|
||||
{
|
||||
Instructions = "You are a web search assistant. When asked to find information, use the web search tool to look it up and return a concise, factual answer.",
|
||||
Tools =
|
||||
[
|
||||
ResponseTool.CreateWebSearchTool().AsAITool(),
|
||||
],
|
||||
},
|
||||
});
|
||||
|
||||
// --- Parent agent: Stock Price Researcher ---
|
||||
// This agent orchestrates the sub-agent to look up stock prices in parallel.
|
||||
// This agent orchestrates the background agent to look up stock prices in parallel.
|
||||
var parentInstructions =
|
||||
"""
|
||||
You are a stock price research assistant. You have access to a web search sub-agent that can look up information on the web.
|
||||
You are a stock price research assistant. You have access to a web search background agent that can look up information on the web.
|
||||
|
||||
When given a list of stock tickers, your job is to find the closing price for each ticker on December 31, 2025.
|
||||
|
||||
## Workflow
|
||||
|
||||
1. For each ticker, start a sub-task on the WebSearchAgent asking it to find the closing price on December 31, 2025.
|
||||
- Start all sub-tasks before waiting for any of them to complete, so they run concurrently.
|
||||
2. Wait for all sub-tasks to complete.
|
||||
3. Retrieve the results from each sub-task.
|
||||
1. For each ticker, start a background task on the WebSearchAgent asking it to find the closing price on December 31, 2025.
|
||||
- Start all background tasks before waiting for any of them to complete, so they run concurrently.
|
||||
2. Wait for all background tasks to complete.
|
||||
3. Retrieve the results from each background task.
|
||||
4. Present a summary table with the ticker symbol and closing price for each stock.
|
||||
5. Clear all completed tasks to free memory.
|
||||
|
||||
## Important
|
||||
|
||||
- Always delegate web searches to the WebSearchAgent sub-agent. Do not try to answer from memory.
|
||||
- If a sub-task fails or returns unclear results, continue the task with a more specific query.
|
||||
- Always delegate web searches to the WebSearchAgent background agent. Do not try to answer from memory.
|
||||
- If a background task fails or returns unclear results, continue the task with a more specific query.
|
||||
- Present results in a clean markdown table format.
|
||||
""";
|
||||
|
||||
// --- Parent agent: Stock Price Researcher ---
|
||||
// This agent orchestrates the sub-agent to look up stock prices in parallel.
|
||||
// Most features are disabled since the parent only needs SubAgentsProvider.
|
||||
AIAgent parentAgent =
|
||||
new OpenAIClient(
|
||||
new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"),
|
||||
@@ -88,10 +94,16 @@ AIAgent parentAgent =
|
||||
.AsHarnessAgent(MaxContextWindowTokens, MaxOutputTokens, new HarnessAgentOptions
|
||||
{
|
||||
Name = "StockPriceResearcher",
|
||||
Description = "An agent that researches stock prices using sub-agents.",
|
||||
Description = "An agent that researches stock prices using background agents.",
|
||||
DisableTodoProvider = true,
|
||||
DisableAgentModeProvider = true,
|
||||
DisableFileMemory = true, // If enabled, this would allow the agent to store memories as files in a directory associated with the current session
|
||||
DisableFileAccess = true, // If enabled, this would allow the agent to read/write files in a working directory
|
||||
DisableToolApproval = true, // If enabled, this allows don't-ask-again approval functionality.
|
||||
DisableWebSearch = true,
|
||||
AIContextProviders =
|
||||
[
|
||||
new SubAgentsProvider([webSearchAgent]),
|
||||
new BackgroundAgentsProvider([webSearchAgent]),
|
||||
],
|
||||
ChatOptions = new ChatOptions
|
||||
{
|
||||
+15
-15
@@ -1,24 +1,24 @@
|
||||
# Harness Step 02 — SubAgents (Stock Price Research)
|
||||
# Harness Step 02 — BackgroundAgents (Stock Price Research)
|
||||
|
||||
This sample demonstrates how to use the **SubAgentsProvider** to delegate work from a parent agent to sub-agents. Both agents use `HarnessAgent` for pre-configured function invocation, per-service-call persistence, and context-window compaction.
|
||||
This sample demonstrates how to use the **BackgroundAgentsProvider** to delegate work from a parent agent to background agents. Both agents use `HarnessAgent` for pre-configured function invocation, per-service-call persistence, and context-window compaction.
|
||||
|
||||
## What It Does
|
||||
|
||||
A parent agent receives a list of stock tickers and uses a web-search sub-agent to find the closing price for each ticker on December 31, 2025. The sub-tasks run concurrently, and results are presented in a summary table.
|
||||
A parent agent receives a list of stock tickers and uses a web-search background agent to find the closing price for each ticker on December 31, 2025. The background tasks run concurrently, and results are presented in a summary table.
|
||||
|
||||
### Architecture
|
||||
|
||||
```
|
||||
┌─────────────────────────────────┐
|
||||
│ StockPriceResearcher │
|
||||
│ (Parent Agent) │
|
||||
│ │
|
||||
│ SubAgentsProvider │
|
||||
│ ├─ SubAgents_StartTask │
|
||||
│ ├─ SubAgents_WaitFor... │
|
||||
│ ├─ SubAgents_GetTaskResults │
|
||||
│ └─ ... │
|
||||
└────────────┬────────────────────┘
|
||||
┌────────────────────────────────────────┐
|
||||
│ StockPriceResearcher │
|
||||
│ (Parent Agent) │
|
||||
│ │
|
||||
│ BackgroundAgentsProvider │
|
||||
│ ├─ BackgroundAgents_StartTask │
|
||||
│ ├─ BackgroundAgents_WaitFor... │
|
||||
│ ├─ BackgroundAgents_GetTaskResults │
|
||||
│ └─ ... │
|
||||
└────────────┬───────────────────────────┘
|
||||
│ delegates to
|
||||
▼
|
||||
┌─────────────────────────────────┐
|
||||
@@ -40,7 +40,7 @@ A parent agent receives a list of stock tickers and uses a web-search sub-agent
|
||||
## Running the Sample
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/02-agents/Harness/Harness_Step02_Research_WithSubAgents
|
||||
cd dotnet/samples/02-agents/Harness/Harness_Step02_Research_WithBackgroundAgents
|
||||
dotnet run
|
||||
```
|
||||
|
||||
@@ -50,4 +50,4 @@ When prompted, enter a list of stock tickers such as:
|
||||
BAC, MSFT, BA
|
||||
```
|
||||
|
||||
The parent agent will delegate each ticker lookup to the web search sub-agent concurrently and present the results in a table.
|
||||
The parent agent will delegate each ticker lookup to the web search background agent concurrently and present the results in a table.
|
||||
+1
-1
@@ -19,7 +19,7 @@
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<Content Include="data\**\*" CopyToOutputDirectory="PreserveNewest" />
|
||||
<Content Include="working\**\*" CopyToOutputDirectory="PreserveNewest" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
|
||||
@@ -1,10 +1,12 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample demonstrates how to use a HarnessAgent with the FileAccessProvider
|
||||
// This sample demonstrates how to use a HarnessAgent with the default FileAccessProvider
|
||||
// to give an agent access to a folder of CSV data files. The agent can read, analyze,
|
||||
// and extract information from the data, then write results back as new files.
|
||||
//
|
||||
// The sample includes a pre-populated `data/` folder with sales transaction data.
|
||||
// The sample includes a pre-populated `working/` folder with sales transaction data.
|
||||
// The HarnessAgent's default FileAccessProvider uses `{cwd}/working` as its working directory,
|
||||
// which matches this sample's folder layout.
|
||||
// Ask the agent to analyze the data, produce summaries, or create new output files.
|
||||
//
|
||||
// Special commands:
|
||||
@@ -27,10 +29,6 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYME
|
||||
const int MaxContextWindowTokens = 1_050_000;
|
||||
const int MaxOutputTokens = 128_000;
|
||||
|
||||
// Point the file store at the data/ folder that ships with the sample.
|
||||
var dataFolder = Path.Combine(AppContext.BaseDirectory, "data");
|
||||
var fileStore = new FileSystemAgentFileStore(dataFolder);
|
||||
|
||||
var instructions =
|
||||
"""
|
||||
You are a data analyst assistant. You have access to a folder of data files via the FileAccess_* tools.
|
||||
@@ -56,7 +54,9 @@ var instructions =
|
||||
- Always explain what you learned and what you are going to do next between tool calls, so the user can follow along with your thought process.
|
||||
""";
|
||||
|
||||
// Create the chat client from the OpenAI provider.
|
||||
// Create the agent using AsHarnessAgent. The FileAccessStore is explicitly set to the
|
||||
// sample's working/ folder (copied to the output directory) so it works regardless of cwd.
|
||||
// Unused features are disabled.
|
||||
AIAgent agent =
|
||||
new OpenAIClient(
|
||||
new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"),
|
||||
@@ -71,10 +71,11 @@ AIAgent agent =
|
||||
{
|
||||
Name = "DataAnalyst",
|
||||
Description = "A data analyst assistant that reads, analyzes, and processes data files.",
|
||||
AIContextProviders =
|
||||
[
|
||||
new FileAccessProvider(fileStore),
|
||||
],
|
||||
FileAccessStore = new FileSystemAgentFileStore(Path.Combine(AppContext.BaseDirectory, "working")),
|
||||
DisableTodoProvider = true,
|
||||
DisableAgentModeProvider = true,
|
||||
DisableFileMemory = true, // If enabled, this would allow the agent to store memories as files in a directory associated with the current session
|
||||
DisableWebSearch = true,
|
||||
ChatOptions = new ChatOptions
|
||||
{
|
||||
Instructions = instructions,
|
||||
|
||||
@@ -1,11 +1,11 @@
|
||||
# What this sample demonstrates
|
||||
|
||||
This sample demonstrates how to use a `HarnessAgent` with the `FileAccessProvider` to give an agent access to a folder of data files for reading, analyzing, and writing results. The `HarnessAgent` pre-configures function invocation, per-service-call chat history persistence, and in-loop compaction — so the sample only needs to supply the chat client, token limits, and application-specific options.
|
||||
This sample demonstrates how to use a `HarnessAgent` with the default `FileAccessProvider` to give an agent access to a folder of data files for reading, analyzing, and writing results. The `HarnessAgent` pre-configures function invocation, per-service-call chat history persistence, in-loop compaction, tool approval, and OpenTelemetry — so the sample only needs to supply the chat client, token limits, custom instructions, and opt out of unused features.
|
||||
|
||||
Key features showcased:
|
||||
|
||||
- **HarnessAgent** — a pre-configured agent that wraps a `ChatClientAgent` with function invocation, per-service-call persistence, and context-window compaction
|
||||
- **FileAccessProvider** — gives the agent tools to read, write, list, search, and delete files in a shared data folder
|
||||
- **FileAccessProvider** — the HarnessAgent's default file access provider uses `{cwd}/working` as its working directory, matching this sample's `working/` folder
|
||||
- **CSV data processing** — the agent reads sales transaction data and performs analysis on demand
|
||||
- **Output file creation** — the agent can write summaries, filtered data, or reports back to the data folder
|
||||
- **Streaming output** — responses are streamed token-by-token for a natural experience
|
||||
@@ -39,7 +39,7 @@ dotnet run --project samples/02-agents/Harness/Harness_Step03_DataProcessing
|
||||
|
||||
## What to Expect
|
||||
|
||||
The sample starts an interactive conversation with a data analyst agent. The `data/` folder contains a `sales.csv` file with ~50 rows of sales transaction data (date, product, category, quantity, unit price, region, salesperson).
|
||||
The sample starts an interactive conversation with a data analyst agent. The `working/` folder contains a `sales.csv` file with ~50 rows of sales transaction data (date, product, category, quantity, unit price, region, salesperson).
|
||||
|
||||
You can ask the agent to:
|
||||
|
||||
@@ -53,7 +53,7 @@ E.g. try the following prompt `Please process the sales.csv file by first filter
|
||||
|
||||
## Sample Data
|
||||
|
||||
The included `data/sales.csv` contains sales transactions from January to March 2025 with the following columns:
|
||||
The included `working/sales.csv` contains sales transactions from January to March 2025 with the following columns:
|
||||
|
||||
| Column | Description |
|
||||
| --- | --- |
|
||||
|
||||
@@ -7,5 +7,5 @@ Samples demonstrating the [Harness AIContextProviders](../../../src/Microsoft.Ag
|
||||
| Sample | Description |
|
||||
| --- | --- |
|
||||
| [Harness_Step01_Research](./Harness_Step01_Research/README.md) | Using a ChatClientAgent with TodoProvider and AgentModeProvider for research, showcasing planning mode and todo management |
|
||||
| [Harness_Step02_Research_WithSubAgents](./Harness_Step02_Research_WithSubAgents/README.md) | Using SubAgentsProvider to delegate stock price lookups to a web-search sub-agent concurrently |
|
||||
| [Harness_Step02_Research_WithBackgroundAgents](./Harness_Step02_Research_WithBackgroundAgents/README.md) | Using BackgroundAgentsProvider to delegate stock price lookups to a web-search background agent concurrently |
|
||||
| [Harness_Step03_DataProcessing](./Harness_Step03_DataProcessing/README.md) | Using FileAccessProvider to give an agent access to CSV data files for reading, analysis, and output generation |
|
||||
|
||||
Reference in New Issue
Block a user