mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Restructure FoundryHostedAgents samples into invocations/ and responses/
Align dotnet hosted agent samples with the Python side (PR #5281) by reorganizing the directory structure: - Remove HostedAgentsV1 entirely (old API pattern) - Split HostedAgentsV2 into invocations/ and responses/ based on protocol - Move Using-Samples accordingly (SimpleAgent to responses, SimpleInvocationsAgent to invocations) - Update slnx with new project paths and add previously missing invocations projects - Update README cd paths from HostedAgentsV2 to invocations or responses - Rename .env.local to .env.example to match Python naming convention - Fix format violations in newly included invocations projects
This commit is contained in:
Roger Barreto
@@ -264,36 +264,34 @@
|
||||
<Project Path="samples/04-hosting/FoundryResponsesRepl/FoundryResponsesRepl.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/" />
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV1/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV1/AgentsInWorkflows/AgentsInWorkflows.csproj" />
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV1/AgentThreadAndHITL/AgentThreadAndHITL.csproj" />
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV1/AgentWithHostedMCP/AgentWithHostedMCP.csproj" />
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV1/AgentWithLocalTools/AgentWithLocalTools.csproj" />
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV1/AgentWithTextSearchRag/AgentWithTextSearchRag.csproj" />
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV1/FoundryMultiAgent/FoundryMultiAgent.csproj" />
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV1/FoundrySingleAgent/FoundrySingleAgent.csproj" />
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/invocations/" />
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/invocations/Hosted-Invocations-EchoAgent/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/invocations/Hosted-Invocations-EchoAgent/Hosted-Invocations-EchoAgent.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/" />
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-ChatClientAgent/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-ChatClientAgent/HostedChatClientAgent.csproj" />
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/invocations/Using-Samples/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/invocations/Using-Samples/SimpleInvocationsAgent/SimpleInvocationsAgent.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-FoundryAgent/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-FoundryAgent/HostedFoundryAgent.csproj" />
|
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<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/" />
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<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-ChatClientAgent/">
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||||
<Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-ChatClientAgent/HostedChatClientAgent.csproj" />
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</Folder>
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||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-TextRag/">
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||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-TextRag/HostedTextRag.csproj" />
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<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-FoundryAgent/">
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||||
<Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-FoundryAgent/HostedFoundryAgent.csproj" />
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</Folder>
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<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-LocalTools/">
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<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-LocalTools/HostedLocalTools.csproj" />
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||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-LocalTools/">
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||||
<Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-LocalTools/HostedLocalTools.csproj" />
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||||
</Folder>
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||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-Workflows/">
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||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-Workflows/HostedWorkflows.csproj" />
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<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-McpTools/">
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||||
<Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-McpTools/HostedMcpTools.csproj" />
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||||
</Folder>
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-McpTools/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-McpTools/HostedMcpTools.csproj" />
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||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-TextRag/">
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||||
<Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-TextRag/HostedTextRag.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Using-Samples/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Using-Samples/SimpleAgent/SimpleAgent.csproj" />
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-Workflows/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-Workflows/HostedWorkflows.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Using-Samples/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/responses/Using-Samples/SimpleAgent/SimpleAgent.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/04-hosting/FoundryResponsesHosting/">
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||||
<Project Path="samples/04-hosting/FoundryResponsesHosting/FoundryResponsesHosting.csproj" />
|
||||
|
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-69
@@ -1,69 +0,0 @@
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||||
<Project Sdk="Microsoft.NET.Sdk">
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||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<NoWarn>$(NoWarn);MEAI001</NoWarn>
|
||||
|
||||
<!--
|
||||
Disable central package management for this project.
|
||||
This project requires explicit package references with versions specified inline rather than
|
||||
inheriting them from Directory.Packages.props. This is necessary because a Docker image will
|
||||
be created from this project, and the Docker build process only has access to this folder
|
||||
and cannot access parent folders where Directory.Packages.props resides.
|
||||
-->
|
||||
<ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
|
||||
</PropertyGroup>
|
||||
|
||||
<!--
|
||||
Remove analyzer PackageReference items inherited from Directory.Packages.props.
|
||||
Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
|
||||
Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
|
||||
and the PackageReference items are always inherited through MSBuild imports regardless of the
|
||||
ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
|
||||
-->
|
||||
<ItemGroup>
|
||||
<PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
|
||||
<PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
|
||||
<PackageReference Remove="xunit.analyzers" />
|
||||
<PackageReference Remove="Moq.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Formatting.Analyzers" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.11" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc4" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Add analyzers with compatible versions -->
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
-20
@@ -1,20 +0,0 @@
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# Build the application
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||||
FROM mcr.microsoft.com/dotnet/sdk:10.0-alpine AS build
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WORKDIR /src
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||||
# Copy files from the current directory on the host to the working directory in the container
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COPY . .
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RUN dotnet restore
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RUN dotnet build -c Release --no-restore
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||||
RUN dotnet publish -c Release --no-build -o /app -f net10.0
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# Run the application
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FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
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WORKDIR /app
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# Copy everything needed to run the app from the "build" stage.
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COPY --from=build /app .
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||||
EXPOSE 8088
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ENTRYPOINT ["dotnet", "AgentThreadAndHITL.dll"]
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-41
@@ -1,41 +0,0 @@
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// Copyright (c) Microsoft. All rights reserved.
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||||
// This sample demonstrates Human-in-the-Loop (HITL) capabilities with thread persistence.
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||||
// The agent wraps function tools with ApprovalRequiredAIFunction to require user approval
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||||
// before invoking them. Users respond with 'approve' or 'reject' when prompted.
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||||
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||||
using System.ComponentModel;
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using Azure.AI.AgentServer.AgentFramework.Extensions;
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using Azure.AI.AgentServer.AgentFramework.Persistence;
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using Azure.AI.OpenAI;
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using Azure.Identity;
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||||
using Microsoft.Agents.AI;
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using Microsoft.Extensions.AI;
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using OpenAI.Chat;
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||||
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string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
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||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
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[Description("Get the weather for a given location.")]
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static string GetWeather([Description("The location to get the weather for.")] string location)
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=> $"The weather in {location} is cloudy with a high of 15°C.";
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||||
// Create the chat client and agent.
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||||
// Note: ApprovalRequiredAIFunction wraps the tool to require user approval before invocation.
|
||||
// User should reply with 'approve' or 'reject' when prompted.
|
||||
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
|
||||
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
|
||||
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
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||||
#pragma warning disable MEAI001 // Type is for evaluation purposes only
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||||
AIAgent agent = new AzureOpenAIClient(
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||||
new Uri(endpoint),
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||||
new DefaultAzureCredential())
|
||||
.GetChatClient(deploymentName)
|
||||
.AsAIAgent(
|
||||
instructions: "You are a helpful assistant",
|
||||
tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather))]
|
||||
);
|
||||
#pragma warning restore MEAI001
|
||||
|
||||
InMemoryAgentThreadRepository threadRepository = new(agent);
|
||||
await agent.RunAIAgentAsync(telemetrySourceName: "Agents", threadRepository: threadRepository);
|
||||
-46
@@ -1,46 +0,0 @@
|
||||
# What this sample demonstrates
|
||||
|
||||
This sample demonstrates Human-in-the-Loop (HITL) capabilities with thread persistence. The agent wraps function tools with `ApprovalRequiredAIFunction` so that every tool invocation requires explicit user approval before execution. Thread state is maintained across requests using `InMemoryAgentThreadRepository`.
|
||||
|
||||
Key features:
|
||||
- Requiring human approval before executing function calls
|
||||
- Persisting conversation threads across multiple requests
|
||||
- Approving or rejecting tool invocations at runtime
|
||||
|
||||
> For common prerequisites and setup instructions, see the [Hosted Agent Samples README](../README.md).
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before running this sample, ensure you have:
|
||||
|
||||
1. .NET 10 SDK installed
|
||||
2. An Azure OpenAI endpoint configured
|
||||
3. A deployment of a chat model (e.g., gpt-5.4-mini)
|
||||
4. Azure CLI installed and authenticated (`az login`)
|
||||
|
||||
## Environment Variables
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
# Replace with your Azure OpenAI endpoint
|
||||
$env:AZURE_OPENAI_ENDPOINT="https://your-openai-resource.openai.azure.com/"
|
||||
|
||||
# Optional, defaults to gpt-5.4-mini
|
||||
$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
|
||||
```
|
||||
|
||||
## How It Works
|
||||
|
||||
The sample uses `ApprovalRequiredAIFunction` to wrap standard AI function tools. When the model decides to call a tool, the wrapper intercepts the invocation and returns a HITL approval request to the caller instead of executing the function immediately.
|
||||
|
||||
1. The user sends a message (e.g., "What is the weather in Vancouver?")
|
||||
2. The model determines a function call is needed and selects the `GetWeather` tool
|
||||
3. `ApprovalRequiredAIFunction` intercepts the call and returns an approval request containing the function name and arguments
|
||||
4. The user responds with `approve` or `reject`
|
||||
5. If approved, the function executes and the model generates a response using the result
|
||||
6. If rejected, the model generates a response without the function result
|
||||
|
||||
Thread persistence is handled by `InMemoryAgentThreadRepository`, which stores conversation history keyed by `conversation.id`. This means the HITL flow works across multiple HTTP requests as long as each request includes the same `conversation.id`.
|
||||
|
||||
> **Note:** HITL requires a stable `conversation.id` in every request so the agent can correlate the approval response with the original function call. Use the `run-requests.http` file in this directory to test the full approval flow.
|
||||
-28
@@ -1,28 +0,0 @@
|
||||
name: AgentThreadAndHITL
|
||||
displayName: "Weather Assistant Agent"
|
||||
description: >
|
||||
A Weather Assistant Agent that provides weather information and forecasts. It
|
||||
demonstrates how to use Azure AI AgentServer with Human-in-the-Loop (HITL)
|
||||
capabilities to get human approval for functional calls.
|
||||
metadata:
|
||||
authors:
|
||||
- Microsoft Agent Framework Team
|
||||
tags:
|
||||
- Azure AI AgentServer
|
||||
- Microsoft Agent Framework
|
||||
- Human-in-the-Loop
|
||||
template:
|
||||
kind: hosted
|
||||
name: AgentThreadAndHITL
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: v1
|
||||
environment_variables:
|
||||
- name: AZURE_OPENAI_ENDPOINT
|
||||
value: ${AZURE_OPENAI_ENDPOINT}
|
||||
- name: AZURE_OPENAI_DEPLOYMENT_NAME
|
||||
value: gpt-5.4-mini
|
||||
resources:
|
||||
- name: "gpt-5.4-mini"
|
||||
kind: model
|
||||
id: gpt-5.4-mini
|
||||
-70
@@ -1,70 +0,0 @@
|
||||
@host = http://localhost:8088
|
||||
@endpoint = {{host}}/responses
|
||||
|
||||
### Health Check
|
||||
GET {{host}}/readiness
|
||||
|
||||
###
|
||||
# HITL (Human-in-the-Loop) Flow
|
||||
#
|
||||
# This sample requires a multi-turn conversation to demonstrate the approval flow:
|
||||
# 1. Send a request that triggers a tool call (e.g., asking about the weather)
|
||||
# 2. The agent responds with a function_call named "__hosted_agent_adapter_hitl__"
|
||||
# containing the call_id and the tool details
|
||||
# 3. Send a follow-up request with a function_call_output to approve or reject
|
||||
#
|
||||
# IMPORTANT: You must use the same conversation.id across all requests in a flow,
|
||||
# and update the call_id from step 2 into step 3.
|
||||
###
|
||||
|
||||
### Step 1: Send initial request (triggers HITL approval)
|
||||
# @name initialRequest
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": "What is the weather like in Vancouver?",
|
||||
"stream": false,
|
||||
"conversation": {
|
||||
"id": "conv_test0000000000000000000000000000000000000000000000"
|
||||
}
|
||||
}
|
||||
|
||||
### Step 2: Approve the function call
|
||||
# Copy the call_id from the Step 1 response output and replace below.
|
||||
# The response will contain: "name": "__hosted_agent_adapter_hitl__" with a "call_id" value.
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": [
|
||||
{
|
||||
"type": "function_call_output",
|
||||
"call_id": "REPLACE_WITH_CALL_ID_FROM_STEP_1",
|
||||
"output": "approve"
|
||||
}
|
||||
],
|
||||
"stream": false,
|
||||
"conversation": {
|
||||
"id": "conv_test0000000000000000000000000000000000000000000000"
|
||||
}
|
||||
}
|
||||
|
||||
### Step 3 (alternative): Reject the function call
|
||||
# Use this instead of Step 2 to deny the tool execution.
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": [
|
||||
{
|
||||
"type": "function_call_output",
|
||||
"call_id": "REPLACE_WITH_CALL_ID_FROM_STEP_1",
|
||||
"output": "reject"
|
||||
}
|
||||
],
|
||||
"stream": false,
|
||||
"conversation": {
|
||||
"id": "conv_test0000000000000000000000000000000000000000000000"
|
||||
}
|
||||
}
|
||||
-68
@@ -1,68 +0,0 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
<!--
|
||||
Disable central package management for this project.
|
||||
This project requires explicit package references with versions specified inline rather than
|
||||
inheriting them from Directory.Packages.props. This is necessary because a Docker image will
|
||||
be created from this project, and the Docker build process only has access to this folder
|
||||
and cannot access parent folders where Directory.Packages.props resides.
|
||||
-->
|
||||
<ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
|
||||
</PropertyGroup>
|
||||
|
||||
<!--
|
||||
Remove analyzer PackageReference items inherited from Directory.Packages.props.
|
||||
Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
|
||||
Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
|
||||
and the PackageReference items are always inherited through MSBuild imports regardless of the
|
||||
ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
|
||||
-->
|
||||
<ItemGroup>
|
||||
<PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
|
||||
<PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
|
||||
<PackageReference Remove="xunit.analyzers" />
|
||||
<PackageReference Remove="Moq.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Formatting.Analyzers" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.11" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc4" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Add analyzers with compatible versions -->
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
-20
@@ -1,20 +0,0 @@
|
||||
# Build the application
|
||||
FROM mcr.microsoft.com/dotnet/sdk:10.0-alpine AS build
|
||||
WORKDIR /src
|
||||
|
||||
# Copy files from the current directory on the host to the working directory in the container
|
||||
COPY . .
|
||||
|
||||
RUN dotnet restore
|
||||
RUN dotnet build -c Release --no-restore
|
||||
RUN dotnet publish -c Release --no-build -o /app -f net10.0
|
||||
|
||||
# Run the application
|
||||
FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
|
||||
WORKDIR /app
|
||||
|
||||
# Copy everything needed to run the app from the "build" stage.
|
||||
COPY --from=build /app .
|
||||
|
||||
EXPOSE 8088
|
||||
ENTRYPOINT ["dotnet", "AgentWithHostedMCP.dll"]
|
||||
-40
@@ -1,40 +0,0 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to create and use a simple AI agent with OpenAI Responses as the backend, that uses a Hosted MCP Tool.
|
||||
// In this case the OpenAI responses service will invoke any MCP tools as required. MCP tools are not invoked by the Agent Framework.
|
||||
// The sample demonstrates how to use MCP tools with auto approval by setting ApprovalMode to NeverRequire.
|
||||
|
||||
#pragma warning disable MEAI001 // HostedMcpServerTool, HostedMcpServerToolApprovalMode are experimental
|
||||
#pragma warning disable OPENAI001 // GetResponsesClient is experimental
|
||||
|
||||
using Azure.AI.AgentServer.AgentFramework.Extensions;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
using OpenAI.Responses;
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
|
||||
|
||||
// Create an MCP tool that can be called without approval.
|
||||
AITool mcpTool = new HostedMcpServerTool(serverName: "microsoft_learn", serverAddress: "https://learn.microsoft.com/api/mcp")
|
||||
{
|
||||
AllowedTools = ["microsoft_docs_search"],
|
||||
ApprovalMode = HostedMcpServerToolApprovalMode.NeverRequire
|
||||
};
|
||||
|
||||
// Create an agent with the MCP tool using Azure OpenAI Responses.
|
||||
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
|
||||
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
|
||||
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
|
||||
AIAgent agent = new AzureOpenAIClient(
|
||||
new Uri(endpoint),
|
||||
new DefaultAzureCredential())
|
||||
.GetResponsesClient(deploymentName)
|
||||
.AsAIAgent(
|
||||
instructions: "You answer questions by searching the Microsoft Learn content only.",
|
||||
name: "MicrosoftLearnAgent",
|
||||
tools: [mcpTool]);
|
||||
|
||||
await agent.RunAIAgentAsync();
|
||||
-45
@@ -1,45 +0,0 @@
|
||||
# What this sample demonstrates
|
||||
|
||||
This sample demonstrates how to use a Hosted Model Context Protocol (MCP) server with an AI agent.
|
||||
The agent connects to the Microsoft Learn MCP server to search documentation and answer questions using official Microsoft content.
|
||||
|
||||
Key features:
|
||||
- Configuring MCP tools with automatic approval (no user confirmation required)
|
||||
- Filtering available tools from an MCP server
|
||||
- Using Azure OpenAI Responses with MCP tools
|
||||
|
||||
> For common prerequisites and setup instructions, see the [Hosted Agent Samples README](../README.md).
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before running this sample, ensure you have:
|
||||
|
||||
1. An Azure OpenAI endpoint configured
|
||||
2. A deployment of a chat model (e.g., gpt-5.4-mini)
|
||||
3. Azure CLI installed and authenticated
|
||||
|
||||
**Note**: This sample uses `DefaultAzureCredential` for authentication, which probes multiple sources automatically. For local development, make sure you're logged in with `az login` and have access to the Azure OpenAI resource.
|
||||
|
||||
## Environment Variables
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
# Replace with your Azure OpenAI endpoint
|
||||
$env:AZURE_OPENAI_ENDPOINT="https://your-openai-resource.openai.azure.com/"
|
||||
|
||||
# Optional, defaults to gpt-5.4-mini
|
||||
$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
|
||||
```
|
||||
|
||||
## How It Works
|
||||
|
||||
The sample connects to the Microsoft Learn MCP server and uses its documentation search capabilities:
|
||||
|
||||
1. The agent is configured with a HostedMcpServerTool pointing to `https://learn.microsoft.com/api/mcp`
|
||||
2. Only the `microsoft_docs_search` tool is enabled from the available MCP tools
|
||||
3. Approval mode is set to `NeverRequire`, allowing automatic tool execution
|
||||
4. When you ask questions, Azure OpenAI Responses automatically invokes the MCP tool to search documentation
|
||||
5. The agent returns answers based on the Microsoft Learn content
|
||||
|
||||
In this configuration, the OpenAI Responses service manages tool invocation directly - the Agent Framework does not handle MCP tool calls.
|
||||
-31
@@ -1,31 +0,0 @@
|
||||
name: AgentWithHostedMCP
|
||||
displayName: "Microsoft Learn Response Agent with MCP"
|
||||
description: >
|
||||
An AI agent that uses Azure OpenAI Responses with a Hosted Model Context Protocol (MCP) server.
|
||||
The agent answers questions by searching Microsoft Learn documentation using MCP tools.
|
||||
This demonstrates how MCP tools can be integrated with Azure OpenAI Responses where the service
|
||||
itself handles tool invocation.
|
||||
metadata:
|
||||
authors:
|
||||
- Microsoft Agent Framework Team
|
||||
tags:
|
||||
- Azure AI AgentServer
|
||||
- Microsoft Agent Framework
|
||||
- Model Context Protocol
|
||||
- MCP
|
||||
- Tool Call Approval
|
||||
template:
|
||||
kind: hosted
|
||||
name: AgentWithHostedMCP
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: v1
|
||||
environment_variables:
|
||||
- name: AZURE_OPENAI_ENDPOINT
|
||||
value: ${AZURE_OPENAI_ENDPOINT}
|
||||
- name: AZURE_OPENAI_DEPLOYMENT_NAME
|
||||
value: gpt-5.4-mini
|
||||
resources:
|
||||
- name: "gpt-5.4-mini"
|
||||
kind: model
|
||||
id: gpt-5.4-mini
|
||||
-32
@@ -1,32 +0,0 @@
|
||||
@host = http://localhost:8088
|
||||
@endpoint = {{host}}/responses
|
||||
|
||||
### Health Check
|
||||
GET {{host}}/readiness
|
||||
|
||||
### Simple string input - Ask about MCP Tools
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": "Please summarize the Azure AI Agent documentation related to MCP Tool calling?"
|
||||
}
|
||||
|
||||
### Explicit input - Ask about Agent Framework
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": [
|
||||
{
|
||||
"type": "message",
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "input_text",
|
||||
"text": "What is the Microsoft Agent Framework?"
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
-24
@@ -1,24 +0,0 @@
|
||||
**/.dockerignore
|
||||
**/.env
|
||||
**/.git
|
||||
**/.gitignore
|
||||
**/.project
|
||||
**/.settings
|
||||
**/.toolstarget
|
||||
**/.vs
|
||||
**/.vscode
|
||||
**/*.*proj.user
|
||||
**/*.dbmdl
|
||||
**/*.jfm
|
||||
**/azds.yaml
|
||||
**/bin
|
||||
**/charts
|
||||
**/docker-compose*
|
||||
**/Dockerfile*
|
||||
**/node_modules
|
||||
**/npm-debug.log
|
||||
**/obj
|
||||
**/secrets.dev.yaml
|
||||
**/values.dev.yaml
|
||||
LICENSE
|
||||
README.md
|
||||
-70
@@ -1,70 +0,0 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<EnablePreviewFeatures>true</EnablePreviewFeatures>
|
||||
|
||||
<!--
|
||||
Disable central package management for this project.
|
||||
This project requires explicit package references with versions specified inline rather than
|
||||
inheriting them from Directory.Packages.props. This is necessary because a Docker image will
|
||||
be created from this project, and the Docker build process only has access to this folder
|
||||
and cannot access parent folders where Directory.Packages.props resides.
|
||||
-->
|
||||
<ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
|
||||
</PropertyGroup>
|
||||
|
||||
<!--
|
||||
Remove analyzer PackageReference items inherited from Directory.Packages.props.
|
||||
Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
|
||||
Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
|
||||
and the PackageReference items are always inherited through MSBuild imports regardless of the
|
||||
ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
|
||||
-->
|
||||
<ItemGroup>
|
||||
<PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
|
||||
<PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
|
||||
<PackageReference Remove="xunit.analyzers" />
|
||||
<PackageReference Remove="Moq.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Formatting.Analyzers" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.11" />
|
||||
<PackageReference Include="Azure.AI.Projects" Version="2.0.0-beta.1" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc4" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Add analyzers with compatible versions -->
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
-20
@@ -1,20 +0,0 @@
|
||||
# Build the application
|
||||
FROM mcr.microsoft.com/dotnet/sdk:10.0-alpine AS build
|
||||
WORKDIR /src
|
||||
|
||||
# Copy files from the current directory on the host to the working directory in the container
|
||||
COPY . .
|
||||
|
||||
RUN dotnet restore
|
||||
RUN dotnet build -c Release --no-restore
|
||||
RUN dotnet publish -c Release --no-build -o /app -f net10.0
|
||||
|
||||
# Run the application
|
||||
FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
|
||||
WORKDIR /app
|
||||
|
||||
# Copy everything needed to run the app from the "build" stage.
|
||||
COPY --from=build /app .
|
||||
|
||||
EXPOSE 8088
|
||||
ENTRYPOINT ["dotnet", "AgentWithLocalTools.dll"]
|
||||
-132
@@ -1,132 +0,0 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// Seattle Hotel Agent - A simple agent with a tool to find hotels in Seattle.
|
||||
// Uses Microsoft Agent Framework with Microsoft Foundry.
|
||||
// Ready for deployment to Foundry Hosted Agent service.
|
||||
|
||||
using System.ClientModel.Primitives;
|
||||
using System.ComponentModel;
|
||||
using System.Globalization;
|
||||
using System.Text;
|
||||
using Azure.AI.AgentServer.AgentFramework.Extensions;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
|
||||
Console.WriteLine($"Project Endpoint: {endpoint}");
|
||||
Console.WriteLine($"Model Deployment: {deploymentName}");
|
||||
|
||||
Hotel[] seattleHotels =
|
||||
[
|
||||
new Hotel("Contoso Suites", 189, 4.5, "Downtown"),
|
||||
new Hotel("Fabrikam Residences", 159, 4.2, "Pike Place Market"),
|
||||
new Hotel("Alpine Ski House", 249, 4.7, "Seattle Center"),
|
||||
new Hotel("Margie's Travel Lodge", 219, 4.4, "Waterfront"),
|
||||
new Hotel("Northwind Inn", 139, 4.0, "Capitol Hill"),
|
||||
new Hotel("Relecloud Hotel", 99, 3.8, "University District"),
|
||||
];
|
||||
|
||||
[Description("Get available hotels in Seattle for the specified dates. This simulates a call to a hotel availability API.")]
|
||||
string GetAvailableHotels(
|
||||
[Description("Check-in date in YYYY-MM-DD format")] string checkInDate,
|
||||
[Description("Check-out date in YYYY-MM-DD format")] string checkOutDate,
|
||||
[Description("Maximum price per night in USD (optional, defaults to 500)")] int maxPrice = 500)
|
||||
{
|
||||
try
|
||||
{
|
||||
if (!DateTime.TryParseExact(checkInDate, "yyyy-MM-dd", CultureInfo.InvariantCulture, DateTimeStyles.None, out var checkIn))
|
||||
{
|
||||
return "Error parsing check-in date. Please use YYYY-MM-DD format.";
|
||||
}
|
||||
|
||||
if (!DateTime.TryParseExact(checkOutDate, "yyyy-MM-dd", CultureInfo.InvariantCulture, DateTimeStyles.None, out var checkOut))
|
||||
{
|
||||
return "Error parsing check-out date. Please use YYYY-MM-DD format.";
|
||||
}
|
||||
|
||||
if (checkOut <= checkIn)
|
||||
{
|
||||
return "Error: Check-out date must be after check-in date.";
|
||||
}
|
||||
|
||||
int nights = (checkOut - checkIn).Days;
|
||||
List<Hotel> availableHotels = seattleHotels.Where(h => h.PricePerNight <= maxPrice).ToList();
|
||||
|
||||
if (availableHotels.Count == 0)
|
||||
{
|
||||
return $"No hotels found in Seattle within your budget of ${maxPrice}/night.";
|
||||
}
|
||||
|
||||
StringBuilder result = new();
|
||||
result.AppendLine($"Available hotels in Seattle from {checkInDate} to {checkOutDate} ({nights} nights):");
|
||||
result.AppendLine();
|
||||
|
||||
foreach (Hotel hotel in availableHotels)
|
||||
{
|
||||
int totalCost = hotel.PricePerNight * nights;
|
||||
result.AppendLine($"**{hotel.Name}**");
|
||||
result.AppendLine($" Location: {hotel.Location}");
|
||||
result.AppendLine($" Rating: {hotel.Rating}/5");
|
||||
result.AppendLine($" ${hotel.PricePerNight}/night (Total: ${totalCost})");
|
||||
result.AppendLine();
|
||||
}
|
||||
|
||||
return result.ToString();
|
||||
}
|
||||
catch (Exception ex)
|
||||
{
|
||||
return $"Error processing request. Details: {ex.Message}";
|
||||
}
|
||||
}
|
||||
|
||||
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
|
||||
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
|
||||
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
|
||||
DefaultAzureCredential credential = new();
|
||||
AIProjectClient projectClient = new(new Uri(endpoint), credential);
|
||||
|
||||
ClientConnection connection = projectClient.GetConnection(typeof(AzureOpenAIClient).FullName!);
|
||||
|
||||
if (!connection.TryGetLocatorAsUri(out Uri? openAiEndpoint) || openAiEndpoint is null)
|
||||
{
|
||||
throw new InvalidOperationException("Failed to get OpenAI endpoint from project connection.");
|
||||
}
|
||||
openAiEndpoint = new Uri($"https://{openAiEndpoint.Host}");
|
||||
Console.WriteLine($"OpenAI Endpoint: {openAiEndpoint}");
|
||||
|
||||
IChatClient chatClient = new AzureOpenAIClient(openAiEndpoint, credential)
|
||||
.GetChatClient(deploymentName)
|
||||
.AsIChatClient()
|
||||
.AsBuilder()
|
||||
.UseOpenTelemetry(sourceName: "Agents", configure: cfg => cfg.EnableSensitiveData = false)
|
||||
.Build();
|
||||
|
||||
AIAgent agent = chatClient.AsAIAgent(
|
||||
name: "SeattleHotelAgent",
|
||||
instructions: """
|
||||
You are a helpful travel assistant specializing in finding hotels in Seattle, Washington.
|
||||
|
||||
When a user asks about hotels in Seattle:
|
||||
1. Ask for their check-in and check-out dates if not provided
|
||||
2. Ask about their budget preferences if not mentioned
|
||||
3. Use the GetAvailableHotels tool to find available options
|
||||
4. Present the results in a friendly, informative way
|
||||
5. Offer to help with additional questions about the hotels or Seattle
|
||||
|
||||
Be conversational and helpful. If users ask about things outside of Seattle hotels,
|
||||
politely let them know you specialize in Seattle hotel recommendations.
|
||||
""",
|
||||
tools: [AIFunctionFactory.Create(GetAvailableHotels)])
|
||||
.AsBuilder()
|
||||
.UseOpenTelemetry(sourceName: "Agents", configure: cfg => cfg.EnableSensitiveData = false)
|
||||
.Build();
|
||||
|
||||
Console.WriteLine("Seattle Hotel Agent Server running on http://localhost:8088");
|
||||
await agent.RunAIAgentAsync(telemetrySourceName: "Agents");
|
||||
|
||||
internal sealed record Hotel(string Name, int PricePerNight, double Rating, string Location);
|
||||
-39
@@ -1,39 +0,0 @@
|
||||
# What this sample demonstrates
|
||||
|
||||
This sample demonstrates how to build a hosted agent that uses local C# function tools — a key advantage of code-based hosted agents over prompt agents. The agent acts as a Seattle travel assistant with a `GetAvailableHotels` tool that simulates querying a hotel availability API.
|
||||
|
||||
Key features:
|
||||
- Defining local C# functions as agent tools using `AIFunctionFactory`
|
||||
- Using `AIProjectClient` to discover the OpenAI connection from the Microsoft Foundry project
|
||||
- Building a `ChatClientAgent` with custom instructions and tools
|
||||
- Deploying to the Foundry Hosted Agent service
|
||||
|
||||
> For common prerequisites and setup instructions, see the [Hosted Agent Samples README](../README.md).
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before running this sample, ensure you have:
|
||||
|
||||
1. .NET 10 SDK installed
|
||||
2. A Microsoft Foundry Project with a chat model deployed (e.g., gpt-5.4-mini)
|
||||
3. Azure CLI installed and authenticated (`az login`)
|
||||
|
||||
## Environment Variables
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
# Replace with your Microsoft Foundry project endpoint
|
||||
$env:AZURE_AI_PROJECT_ENDPOINT="https://your-project.services.ai.azure.com/api/projects/your-project-name"
|
||||
|
||||
# Optional, defaults to gpt-5.4-mini
|
||||
$env:MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
|
||||
```
|
||||
|
||||
## How It Works
|
||||
|
||||
1. The agent uses `AIProjectClient` to discover the Azure OpenAI connection from the project endpoint
|
||||
2. A local C# function `GetAvailableHotels` is registered as a tool using `AIFunctionFactory.Create`
|
||||
3. When users ask about hotels, the model invokes the local tool to search simulated hotel data
|
||||
4. The tool filters hotels by price and calculates total costs based on the requested dates
|
||||
5. Results are returned to the model, which presents them in a conversational format
|
||||
-29
@@ -1,29 +0,0 @@
|
||||
name: seattle-hotel-agent
|
||||
description: >
|
||||
A travel assistant agent that helps users find hotels in Seattle.
|
||||
Demonstrates local C# tool execution - a key advantage of code-based
|
||||
hosted agents over prompt agents.
|
||||
metadata:
|
||||
authors:
|
||||
- Microsoft
|
||||
tags:
|
||||
- Azure AI AgentServer
|
||||
- Microsoft Agent Framework
|
||||
- Local Tools
|
||||
- Travel Assistant
|
||||
- Hotel Search
|
||||
template:
|
||||
name: seattle-hotel-agent
|
||||
kind: hosted
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: v1
|
||||
environment_variables:
|
||||
- name: AZURE_AI_PROJECT_ENDPOINT
|
||||
value: ${AZURE_AI_PROJECT_ENDPOINT}
|
||||
- name: MODEL_DEPLOYMENT_NAME
|
||||
value: gpt-5.4-mini
|
||||
resources:
|
||||
- kind: model
|
||||
id: gpt-5.4-mini
|
||||
name: chat
|
||||
-52
@@ -1,52 +0,0 @@
|
||||
@host = http://localhost:8088
|
||||
@endpoint = {{host}}/responses
|
||||
|
||||
### Health Check
|
||||
GET {{host}}/readiness
|
||||
|
||||
### Simple hotel search - budget under $200
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": "I need a hotel in Seattle from 2025-03-15 to 2025-03-18, budget under $200 per night",
|
||||
"stream": false
|
||||
}
|
||||
|
||||
### Hotel search with higher budget
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": "Find me hotels in Seattle for March 20-23, 2025 under $250 per night",
|
||||
"stream": false
|
||||
}
|
||||
|
||||
### Ask for recommendations without dates (agent should ask for clarification)
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": "What hotels do you recommend in Seattle?",
|
||||
"stream": false
|
||||
}
|
||||
|
||||
### Explicit input format
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": [
|
||||
{
|
||||
"type": "message",
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "input_text",
|
||||
"text": "I'm looking for a hotel in Seattle from 2025-04-01 to 2025-04-05, my budget is $150 per night maximum"
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"stream": false
|
||||
}
|
||||
-68
@@ -1,68 +0,0 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
<!--
|
||||
Disable central package management for this project.
|
||||
This project requires explicit package references with versions specified inline rather than
|
||||
inheriting them from Directory.Packages.props. This is necessary because a Docker image will
|
||||
be created from this project, and the Docker build process only has access to this folder
|
||||
and cannot access parent folders where Directory.Packages.props resides.
|
||||
-->
|
||||
<ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
|
||||
</PropertyGroup>
|
||||
|
||||
<!--
|
||||
Remove analyzer PackageReference items inherited from Directory.Packages.props.
|
||||
Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
|
||||
Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
|
||||
and the PackageReference items are always inherited through MSBuild imports regardless of the
|
||||
ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
|
||||
-->
|
||||
<ItemGroup>
|
||||
<PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
|
||||
<PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
|
||||
<PackageReference Remove="xunit.analyzers" />
|
||||
<PackageReference Remove="Moq.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Formatting.Analyzers" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.11" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc4" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Add analyzers with compatible versions -->
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
-20
@@ -1,20 +0,0 @@
|
||||
# Build the application
|
||||
FROM mcr.microsoft.com/dotnet/sdk:10.0-alpine AS build
|
||||
WORKDIR /src
|
||||
|
||||
# Copy files from the current directory on the host to the working directory in the container
|
||||
COPY . .
|
||||
|
||||
RUN dotnet restore
|
||||
RUN dotnet build -c Release --no-restore
|
||||
RUN dotnet publish -c Release --no-build -o /app -f net10.0
|
||||
|
||||
# Run the application
|
||||
FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
|
||||
WORKDIR /app
|
||||
|
||||
# Copy everything needed to run the app from the "build" stage.
|
||||
COPY --from=build /app .
|
||||
|
||||
EXPOSE 8088
|
||||
ENTRYPOINT ["dotnet", "AgentWithTextSearchRag.dll"]
|
||||
-79
@@ -1,79 +0,0 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample shows how to use TextSearchProvider to add retrieval augmented generation (RAG)
|
||||
// capabilities to an AI agent. The provider runs a search against an external knowledge base
|
||||
// before each model invocation and injects the results into the model context.
|
||||
|
||||
using Azure.AI.AgentServer.AgentFramework.Extensions;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
using OpenAI.Chat;
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
|
||||
|
||||
TextSearchProviderOptions textSearchOptions = new()
|
||||
{
|
||||
// Run the search prior to every model invocation and keep a short rolling window of conversation context.
|
||||
SearchTime = TextSearchProviderOptions.TextSearchBehavior.BeforeAIInvoke,
|
||||
RecentMessageMemoryLimit = 6,
|
||||
};
|
||||
|
||||
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
|
||||
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
|
||||
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
|
||||
AIAgent agent = new AzureOpenAIClient(
|
||||
new Uri(endpoint),
|
||||
new DefaultAzureCredential())
|
||||
.GetChatClient(deploymentName)
|
||||
.AsAIAgent(new ChatClientAgentOptions
|
||||
{
|
||||
ChatOptions = new ChatOptions
|
||||
{
|
||||
Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available.",
|
||||
},
|
||||
AIContextProviders = [new TextSearchProvider(MockSearchAsync, textSearchOptions)]
|
||||
});
|
||||
|
||||
await agent.RunAIAgentAsync();
|
||||
|
||||
static Task<IEnumerable<TextSearchProvider.TextSearchResult>> MockSearchAsync(string query, CancellationToken cancellationToken)
|
||||
{
|
||||
// The mock search inspects the user's question and returns pre-defined snippets
|
||||
// that resemble documents stored in an external knowledge source.
|
||||
List<TextSearchProvider.TextSearchResult> results = [];
|
||||
|
||||
if (query.Contains("return", StringComparison.OrdinalIgnoreCase) || query.Contains("refund", StringComparison.OrdinalIgnoreCase))
|
||||
{
|
||||
results.Add(new()
|
||||
{
|
||||
SourceName = "Contoso Outdoors Return Policy",
|
||||
SourceLink = "https://contoso.com/policies/returns",
|
||||
Text = "Customers may return any item within 30 days of delivery. Items should be unused and include original packaging. Refunds are issued to the original payment method within 5 business days of inspection."
|
||||
});
|
||||
}
|
||||
|
||||
if (query.Contains("shipping", StringComparison.OrdinalIgnoreCase))
|
||||
{
|
||||
results.Add(new()
|
||||
{
|
||||
SourceName = "Contoso Outdoors Shipping Guide",
|
||||
SourceLink = "https://contoso.com/help/shipping",
|
||||
Text = "Standard shipping is free on orders over $50 and typically arrives in 3-5 business days within the continental United States. Expedited options are available at checkout."
|
||||
});
|
||||
}
|
||||
|
||||
if (query.Contains("tent", StringComparison.OrdinalIgnoreCase) || query.Contains("fabric", StringComparison.OrdinalIgnoreCase))
|
||||
{
|
||||
results.Add(new()
|
||||
{
|
||||
SourceName = "TrailRunner Tent Care Instructions",
|
||||
SourceLink = "https://contoso.com/manuals/trailrunner-tent",
|
||||
Text = "Clean the tent fabric with lukewarm water and a non-detergent soap. Allow it to air dry completely before storage and avoid prolonged UV exposure to extend the lifespan of the waterproof coating."
|
||||
});
|
||||
}
|
||||
|
||||
return Task.FromResult<IEnumerable<TextSearchProvider.TextSearchResult>>(results);
|
||||
}
|
||||
-43
@@ -1,43 +0,0 @@
|
||||
# What this sample demonstrates
|
||||
|
||||
This sample demonstrates how to use TextSearchProvider to add retrieval augmented generation (RAG) capabilities to an AI agent. The provider runs a search against an external knowledge base before each model invocation and injects the results into the model context.
|
||||
|
||||
Key features:
|
||||
- Configuring TextSearchProvider with custom search behavior
|
||||
- Running searches before AI invocations to provide relevant context
|
||||
- Managing conversation memory with a rolling window approach
|
||||
- Citing source documents in AI responses
|
||||
|
||||
> For common prerequisites and setup instructions, see the [Hosted Agent Samples README](../README.md).
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before running this sample, ensure you have:
|
||||
|
||||
1. An Azure OpenAI endpoint configured
|
||||
2. A deployment of a chat model (e.g., gpt-5.4-mini)
|
||||
3. Azure CLI installed and authenticated
|
||||
|
||||
## Environment Variables
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
# Replace with your Azure OpenAI endpoint
|
||||
$env:AZURE_OPENAI_ENDPOINT="https://your-openai-resource.openai.azure.com/"
|
||||
|
||||
# Optional, defaults to gpt-5.4-mini
|
||||
$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
|
||||
```
|
||||
|
||||
## How It Works
|
||||
|
||||
The sample uses a mock search function that demonstrates the RAG pattern:
|
||||
|
||||
1. When the user asks a question, the TextSearchProvider intercepts it
|
||||
2. The search function looks for relevant documents based on the query
|
||||
3. Retrieved documents are injected into the model's context
|
||||
4. The AI responds using both its training and the provided context
|
||||
5. The agent can cite specific source documents in its answers
|
||||
|
||||
The mock search function returns pre-defined snippets for demonstration purposes. In a production scenario, you would replace this with actual searches against your knowledge base (e.g., Azure AI Search, vector database, etc.).
|
||||
-31
@@ -1,31 +0,0 @@
|
||||
name: AgentWithTextSearchRag
|
||||
displayName: "Text Search RAG Agent"
|
||||
description: >
|
||||
An AI agent that uses TextSearchProvider for retrieval augmented generation (RAG) capabilities.
|
||||
The agent runs searches against an external knowledge base before each model invocation and
|
||||
injects the results into the model context. It can answer questions about Contoso Outdoors
|
||||
policies and products, including return policies, refunds, shipping options, and product care
|
||||
instructions such as tent maintenance.
|
||||
metadata:
|
||||
authors:
|
||||
- Microsoft Agent Framework Team
|
||||
tags:
|
||||
- Azure AI AgentServer
|
||||
- Microsoft Agent Framework
|
||||
- Retrieval-Augmented Generation
|
||||
- RAG
|
||||
template:
|
||||
kind: hosted
|
||||
name: AgentWithTextSearchRag
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: v1
|
||||
environment_variables:
|
||||
- name: AZURE_OPENAI_ENDPOINT
|
||||
value: ${AZURE_OPENAI_ENDPOINT}
|
||||
- name: AZURE_OPENAI_DEPLOYMENT_NAME
|
||||
value: gpt-5.4-mini
|
||||
resources:
|
||||
- name: "gpt-5.4-mini"
|
||||
kind: model
|
||||
id: gpt-5.4-mini
|
||||
-30
@@ -1,30 +0,0 @@
|
||||
@host = http://localhost:8088
|
||||
@endpoint = {{host}}/responses
|
||||
|
||||
### Health Check
|
||||
GET {{host}}/readiness
|
||||
|
||||
### Simple string input
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
{
|
||||
"input": "Hi! I need help understanding the return policy."
|
||||
}
|
||||
|
||||
### Explicit input
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
{
|
||||
"input": [
|
||||
{
|
||||
"type": "message",
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "input_text",
|
||||
"text": "How long does standard shipping usually take?"
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
-68
@@ -1,68 +0,0 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
<!--
|
||||
Disable central package management for this project.
|
||||
This project requires explicit package references with versions specified inline rather than
|
||||
inheriting them from Directory.Packages.props. This is necessary because a Docker image will
|
||||
be created from this project, and the Docker build process only has access to this folder
|
||||
and cannot access parent folders where Directory.Packages.props resides.
|
||||
-->
|
||||
<ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
|
||||
</PropertyGroup>
|
||||
|
||||
<!--
|
||||
Remove analyzer PackageReference items inherited from Directory.Packages.props.
|
||||
Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
|
||||
Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
|
||||
and the PackageReference items are always inherited through MSBuild imports regardless of the
|
||||
ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
|
||||
-->
|
||||
<ItemGroup>
|
||||
<PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
|
||||
<PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
|
||||
<PackageReference Remove="xunit.analyzers" />
|
||||
<PackageReference Remove="Moq.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Formatting.Analyzers" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.11" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc4" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Add analyzers with compatible versions -->
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
-20
@@ -1,20 +0,0 @@
|
||||
# Build the application
|
||||
FROM mcr.microsoft.com/dotnet/sdk:10.0-alpine AS build
|
||||
WORKDIR /src
|
||||
|
||||
# Copy files from the current directory on the host to the working directory in the container
|
||||
COPY . .
|
||||
|
||||
RUN dotnet restore
|
||||
RUN dotnet build -c Release --no-restore
|
||||
RUN dotnet publish -c Release --no-build -o /app -f net10.0
|
||||
|
||||
# Run the application
|
||||
FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
|
||||
WORKDIR /app
|
||||
|
||||
# Copy everything needed to run the app from the "build" stage.
|
||||
COPY --from=build /app .
|
||||
|
||||
EXPOSE 8088
|
||||
ENTRYPOINT ["dotnet", "AgentsInWorkflows.dll"]
|
||||
-40
@@ -1,40 +0,0 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample demonstrates how to integrate AI agents into a workflow pipeline.
|
||||
// Three translation agents are connected sequentially to create a translation chain:
|
||||
// English → French → Spanish → English, showing how agents can be composed as workflow executors.
|
||||
|
||||
using Azure.AI.AgentServer.AgentFramework.Extensions;
|
||||
using Azure.AI.OpenAI;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.Workflows;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
// Set up the Azure OpenAI client
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
|
||||
|
||||
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
|
||||
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
|
||||
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
|
||||
IChatClient chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
|
||||
.GetChatClient(deploymentName)
|
||||
.AsIChatClient();
|
||||
|
||||
// Create agents
|
||||
AIAgent frenchAgent = GetTranslationAgent("French", chatClient);
|
||||
AIAgent spanishAgent = GetTranslationAgent("Spanish", chatClient);
|
||||
AIAgent englishAgent = GetTranslationAgent("English", chatClient);
|
||||
|
||||
// Build the workflow and turn it into an agent
|
||||
AIAgent agent = new WorkflowBuilder(frenchAgent)
|
||||
.AddEdge(frenchAgent, spanishAgent)
|
||||
.AddEdge(spanishAgent, englishAgent)
|
||||
.Build()
|
||||
.AsAIAgent();
|
||||
|
||||
await agent.RunAIAgentAsync();
|
||||
|
||||
static AIAgent GetTranslationAgent(string targetLanguage, IChatClient chatClient) =>
|
||||
chatClient.AsAIAgent($"You are a translation assistant that translates the provided text to {targetLanguage}.");
|
||||
-28
@@ -1,28 +0,0 @@
|
||||
# What this sample demonstrates
|
||||
|
||||
This sample demonstrates the use of AI agents as executors within a workflow.
|
||||
|
||||
This workflow uses three translation agents:
|
||||
1. French Agent - translates input text to French
|
||||
2. Spanish Agent - translates French text to Spanish
|
||||
3. English Agent - translates Spanish text back to English
|
||||
|
||||
The agents are connected sequentially, creating a translation chain that demonstrates how AI-powered components can be seamlessly integrated into workflow pipelines.
|
||||
|
||||
> For common prerequisites and setup instructions, see the [Hosted Agent Samples README](../README.md).
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before you begin, ensure you have the following prerequisites:
|
||||
|
||||
- .NET 10 SDK or later
|
||||
- Azure OpenAI service endpoint and deployment configured
|
||||
- Azure CLI installed and authenticated (for Azure credential authentication)
|
||||
|
||||
**Note**: This demo uses `DefaultAzureCredential` for authentication, which probes multiple sources automatically. For local development, make sure you're logged in with `az login` and have access to the Azure OpenAI resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
```powershell
|
||||
$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
|
||||
$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini" # Optional, defaults to gpt-5.4-mini
|
||||
-28
@@ -1,28 +0,0 @@
|
||||
name: AgentsInWorkflows
|
||||
displayName: "Translation Chain Workflow Agent"
|
||||
description: >
|
||||
A workflow agent that performs sequential translation through multiple languages.
|
||||
The agent translates text from English to French, then to Spanish, and finally back
|
||||
to English, leveraging AI-powered translation capabilities in a pipeline workflow.
|
||||
metadata:
|
||||
authors:
|
||||
- Microsoft Agent Framework Team
|
||||
tags:
|
||||
- Azure AI AgentServer
|
||||
- Microsoft Agent Framework
|
||||
- Workflows
|
||||
template:
|
||||
kind: hosted
|
||||
name: AgentsInWorkflows
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: v1
|
||||
environment_variables:
|
||||
- name: AZURE_OPENAI_ENDPOINT
|
||||
value: ${AZURE_OPENAI_ENDPOINT}
|
||||
- name: AZURE_OPENAI_DEPLOYMENT_NAME
|
||||
value: gpt-5.4-mini
|
||||
resources:
|
||||
- name: "gpt-5.4-mini"
|
||||
kind: model
|
||||
id: gpt-5.4-mini
|
||||
-30
@@ -1,30 +0,0 @@
|
||||
@host = http://localhost:8088
|
||||
@endpoint = {{host}}/responses
|
||||
|
||||
### Health Check
|
||||
GET {{host}}/readiness
|
||||
|
||||
### Simple string input
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
{
|
||||
"input": "Hello, how are you today?"
|
||||
}
|
||||
|
||||
### Explicit input
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
{
|
||||
"input": [
|
||||
{
|
||||
"type": "message",
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "input_text",
|
||||
"text": "Hello, how are you today?"
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
-20
@@ -1,20 +0,0 @@
|
||||
# Build the application
|
||||
FROM mcr.microsoft.com/dotnet/sdk:10.0-alpine AS build
|
||||
WORKDIR /src
|
||||
|
||||
# Copy files from the current directory on the host to the working directory in the container
|
||||
COPY . .
|
||||
|
||||
RUN dotnet restore
|
||||
RUN dotnet build -c Release --no-restore
|
||||
RUN dotnet publish -c Release --no-build -o /app -f net10.0
|
||||
|
||||
# Run the application
|
||||
FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
|
||||
WORKDIR /app
|
||||
|
||||
# Copy everything needed to run the app from the "build" stage.
|
||||
COPY --from=build /app .
|
||||
|
||||
EXPOSE 8088
|
||||
ENTRYPOINT ["dotnet", "FoundryMultiAgent.dll"]
|
||||
-76
@@ -1,76 +0,0 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<Nullable>enable</Nullable>
|
||||
|
||||
<!--
|
||||
Disable central package management for this project.
|
||||
This project requires explicit package references with versions specified inline rather than
|
||||
inheriting them from Directory.Packages.props. This is necessary because a Docker image will
|
||||
be created from this project, and the Docker build process only has access to this folder
|
||||
and cannot access parent folders where Directory.Packages.props resides.
|
||||
-->
|
||||
<ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
|
||||
</PropertyGroup>
|
||||
|
||||
<!--
|
||||
Remove analyzer PackageReference items inherited from Directory.Packages.props.
|
||||
Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
|
||||
Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
|
||||
and the PackageReference items are always inherited through MSBuild imports regardless of the
|
||||
ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
|
||||
-->
|
||||
<ItemGroup>
|
||||
<PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
|
||||
<PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
|
||||
<PackageReference Remove="xunit.analyzers" />
|
||||
<PackageReference Remove="Moq.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Formatting.Analyzers" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.11" />
|
||||
<PackageReference Include="Azure.AI.Projects" Version="2.0.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI" Version="1.0.0-rc4" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.AzureAI" Version="1.0.0-rc4" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.Workflows" Version="1.0.0-rc4" />
|
||||
<PackageReference Include="OpenTelemetry" Version="1.12.0" />
|
||||
<PackageReference Include="OpenTelemetry.Exporter.OpenTelemetryProtocol" Version="1.12.0" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Add analyzers with compatible versions -->
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<None Update="appsettings.Development.json">
|
||||
<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
|
||||
</None>
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
-51
@@ -1,51 +0,0 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// This sample demonstrates a multi-agent workflow with Writer and Reviewer agents
|
||||
// using Microsoft Foundry AIProjectClient and the Agent Framework WorkflowBuilder.
|
||||
|
||||
#pragma warning disable CA2252 // AIProjectClient and Agents API require opting into preview features
|
||||
|
||||
using Azure.AI.AgentServer.AgentFramework.Extensions;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.Workflows;
|
||||
|
||||
var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
|
||||
var deploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
|
||||
|
||||
Console.WriteLine($"Using Azure AI endpoint: {endpoint}");
|
||||
Console.WriteLine($"Using model deployment: {deploymentName}");
|
||||
|
||||
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
|
||||
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
|
||||
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
|
||||
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
|
||||
|
||||
// Create Foundry agents
|
||||
AIAgent writerAgent = await aiProjectClient.CreateAIAgentAsync(
|
||||
name: "Writer",
|
||||
model: deploymentName,
|
||||
instructions: "You are an excellent content writer. You create new content and edit contents based on the feedback.");
|
||||
|
||||
AIAgent reviewerAgent = await aiProjectClient.CreateAIAgentAsync(
|
||||
name: "Reviewer",
|
||||
model: deploymentName,
|
||||
instructions: "You are an excellent content reviewer. Provide actionable feedback to the writer about the provided content. Provide the feedback in the most concise manner possible.");
|
||||
|
||||
try
|
||||
{
|
||||
var workflow = new WorkflowBuilder(writerAgent)
|
||||
.AddEdge(writerAgent, reviewerAgent)
|
||||
.Build();
|
||||
|
||||
Console.WriteLine("Starting Writer-Reviewer Workflow Agent Server on http://localhost:8088");
|
||||
await workflow.AsAIAgent().RunAIAgentAsync();
|
||||
}
|
||||
finally
|
||||
{
|
||||
// Cleanup server-side agents
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(writerAgent.Name);
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(reviewerAgent.Name);
|
||||
}
|
||||
-168
@@ -1,168 +0,0 @@
|
||||
**IMPORTANT!** All samples and other resources made available in this GitHub repository ("samples") are designed to assist in accelerating development of agents, solutions, and agent workflows for various scenarios. Review all provided resources and carefully test output behavior in the context of your use case. AI responses may be inaccurate and AI actions should be monitored with human oversight. Learn more in the transparency documents for [Agent Service](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/agents/transparency-note) and [Agent Framework](https://github.com/microsoft/agent-framework/blob/main/TRANSPARENCY_FAQ.md).
|
||||
|
||||
Agents, solutions, or other output you create may be subject to legal and regulatory requirements, may require licenses, or may not be suitable for all industries, scenarios, or use cases. By using any sample, you are acknowledging that any output created using those samples are solely your responsibility, and that you will comply with all applicable laws, regulations, and relevant safety standards, terms of service, and codes of conduct.
|
||||
|
||||
Third-party samples contained in this folder are subject to their own designated terms, and they have not been tested or verified by Microsoft or its affiliates.
|
||||
|
||||
Microsoft has no responsibility to you or others with respect to any of these samples or any resulting output.
|
||||
|
||||
# What this sample demonstrates
|
||||
|
||||
This sample demonstrates a **key advantage of code-based hosted agents**:
|
||||
|
||||
- **Multi-agent workflows** - Orchestrate multiple agents working together
|
||||
|
||||
Code-based agents can execute **any C# code** you write. This sample includes a Writer-Reviewer workflow where two agents collaborate: a Writer creates content and a Reviewer provides feedback.
|
||||
|
||||
The agent is hosted using the [Azure AI AgentServer SDK](https://www.nuget.org/packages/Azure.AI.AgentServer.AgentFramework/) and can be deployed to Microsoft Foundry.
|
||||
|
||||
## How It Works
|
||||
|
||||
### Multi-Agent Workflow
|
||||
|
||||
In [Program.cs](Program.cs), the sample creates two agents using `AIProjectClient.CreateAIAgentAsync()` from the [Microsoft.Agents.AI.AzureAI](https://www.nuget.org/packages/Microsoft.Agents.AI.AzureAI/) package:
|
||||
|
||||
- **Writer** - An agent that creates and edits content based on feedback
|
||||
- **Reviewer** - An agent that provides actionable feedback on the content
|
||||
|
||||
The `WorkflowBuilder` from the [Microsoft.Agents.AI.Workflows](https://www.nuget.org/packages/Microsoft.Agents.AI.Workflows/) package connects these agents in a sequential flow:
|
||||
|
||||
1. The Writer receives the initial request and generates content
|
||||
2. The Reviewer evaluates the content and provides feedback
|
||||
3. Both agent responses are output to the user
|
||||
|
||||
### Agent Hosting
|
||||
|
||||
The agent is hosted using the [Azure AI AgentServer SDK](https://www.nuget.org/packages/Azure.AI.AgentServer.AgentFramework/),
|
||||
which provisions a REST API endpoint compatible with the OpenAI Responses protocol.
|
||||
|
||||
## Running the Agent Locally
|
||||
|
||||
### Prerequisites
|
||||
|
||||
Before running this sample, ensure you have:
|
||||
|
||||
1. **Microsoft Foundry Project**
|
||||
- Project created.
|
||||
- Chat model deployed (e.g., `gpt-5.4-mini`)
|
||||
- Note your project endpoint URL and model deployment name
|
||||
> **Note**: You can right-click the project in the Microsoft Foundry VS Code extension and select `Copy Project Endpoint URL` to get the endpoint.
|
||||
|
||||
2. **Azure CLI**
|
||||
- Installed and authenticated
|
||||
- Run `az login` and verify with `az account show`
|
||||
- Your identity needs the **Azure AI Developer** role on the Foundry resource (for `agents/write` data action required by `CreateAIAgentAsync`)
|
||||
|
||||
3. **.NET 10.0 SDK or later**
|
||||
- Verify your version: `dotnet --version`
|
||||
- Download from [https://dotnet.microsoft.com/download](https://dotnet.microsoft.com/download)
|
||||
|
||||
### Environment Variables
|
||||
|
||||
Set the following environment variables:
|
||||
|
||||
**PowerShell:**
|
||||
|
||||
```powershell
|
||||
# Replace with your actual values
|
||||
$env:AZURE_AI_PROJECT_ENDPOINT="https://<your-resource>.services.ai.azure.com/api/projects/<your-project>"
|
||||
$env:MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
|
||||
```
|
||||
|
||||
**Bash:**
|
||||
|
||||
```bash
|
||||
export AZURE_AI_PROJECT_ENDPOINT="https://<your-resource>.services.ai.azure.com/api/projects/<your-project>"
|
||||
export MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
|
||||
```
|
||||
|
||||
### Running the Sample
|
||||
|
||||
To run the agent, execute the following command in your terminal:
|
||||
|
||||
```bash
|
||||
dotnet restore
|
||||
dotnet build
|
||||
dotnet run
|
||||
```
|
||||
|
||||
This will start the hosted agent locally on `http://localhost:8088/`.
|
||||
|
||||
### Interacting with the Agent
|
||||
|
||||
**VS Code:**
|
||||
|
||||
1. Open the Visual Studio Code Command Palette and execute the `Microsoft Foundry: Open Container Agent Playground Locally` command.
|
||||
2. Execute the following commands to start the containerized hosted agent.
|
||||
```bash
|
||||
dotnet restore
|
||||
dotnet build
|
||||
dotnet run
|
||||
```
|
||||
3. Submit a request to the agent through the playground interface. For example, you may enter a prompt such as: "Create a slogan for a new electric SUV that is affordable and fun to drive."
|
||||
4. Review the agent's response in the playground interface.
|
||||
|
||||
> **Note**: Open the local playground before starting the container agent to ensure the visualization functions correctly.
|
||||
|
||||
**PowerShell (Windows):**
|
||||
|
||||
```powershell
|
||||
$body = @{
|
||||
input = "Create a slogan for a new electric SUV that is affordable and fun to drive"
|
||||
stream = $false
|
||||
} | ConvertTo-Json
|
||||
|
||||
Invoke-RestMethod -Uri http://localhost:8088/responses -Method Post -Body $body -ContentType "application/json"
|
||||
```
|
||||
|
||||
**Bash/curl (Linux/macOS):**
|
||||
|
||||
```bash
|
||||
curl -sS -H "Content-Type: application/json" -X POST http://localhost:8088/responses \
|
||||
-d '{"input": "Create a slogan for a new electric SUV that is affordable and fun to drive","stream":false}'
|
||||
```
|
||||
|
||||
You can also use the `run-requests.http` file in this directory with the VS Code REST Client extension.
|
||||
|
||||
The Writer agent will generate content based on your prompt, and the Reviewer agent will provide feedback on the output.
|
||||
|
||||
## Deploying the Agent to Microsoft Foundry
|
||||
|
||||
**Preparation (required)**
|
||||
|
||||
Please check the environment_variables section in [agent.yaml](agent.yaml) and ensure the variables there are set in your target Microsoft Foundry Project.
|
||||
|
||||
To deploy the hosted agent:
|
||||
|
||||
1. Open the VS Code Command Palette and run the `Microsoft Foundry: Deploy Hosted Agent` command.
|
||||
|
||||
2. Follow the interactive deployment prompts. The extension will help you select or create the container files it needs.
|
||||
|
||||
3. After deployment completes, the hosted agent appears under the `Hosted Agents (Preview)` section of the extension tree. You can select the agent there to view details and test it using the integrated playground.
|
||||
|
||||
**What the deploy flow does for you:**
|
||||
|
||||
- Creates or obtains an Azure Container Registry for the target project.
|
||||
- Builds and pushes a container image from your workspace (the build packages the workspace respecting `.dockerignore`).
|
||||
- Creates an agent version in Microsoft Foundry using the built image. If a `.env` file exists at the workspace root, the extension will parse it and include its key/value pairs as the hosted agent's environment variables in the create request (these variables will be available to the agent runtime).
|
||||
- Starts the agent container on the project's capability host. If the capability host is not provisioned, the extension will prompt you to enable it and will guide you through creating it.
|
||||
|
||||
## MSI Configuration in the Azure Portal
|
||||
|
||||
This sample requires the Microsoft Foundry Project to authenticate using a Managed Identity when running remotely in Azure. Grant the project's managed identity the required permissions by assigning the built-in [Azure AI User](https://aka.ms/foundry-ext-project-role) role.
|
||||
|
||||
To configure the Managed Identity:
|
||||
|
||||
1. In the Azure Portal, open the Foundry Project.
|
||||
2. Select "Access control (IAM)" from the left-hand menu.
|
||||
3. Click "Add" and choose "Add role assignment".
|
||||
4. In the role selection, search for and select "Azure AI User", then click "Next".
|
||||
5. For "Assign access to", choose "Managed identity".
|
||||
6. Click "Select members", locate the managed identity associated with your Foundry Project (you can search by the project name), then click "Select".
|
||||
7. Click "Review + assign" to complete the assignment.
|
||||
8. Allow a few minutes for the role assignment to propagate before running the application.
|
||||
|
||||
## Additional Resources
|
||||
|
||||
- [Microsoft Agents Framework](https://learn.microsoft.com/en-us/agent-framework/overview/agent-framework-overview)
|
||||
- [Managed Identities for Azure Resources](https://learn.microsoft.com/en-us/entra/identity/managed-identities-azure-resources/)
|
||||
-31
@@ -1,31 +0,0 @@
|
||||
# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/ContainerAgent.yaml
|
||||
|
||||
name: FoundryMultiAgent
|
||||
displayName: "Foundry Multi-Agent Workflow"
|
||||
description: >
|
||||
A multi-agent workflow featuring a Writer and Reviewer that collaborate
|
||||
to create and refine content using Microsoft Foundry PersistentAgentsClient.
|
||||
metadata:
|
||||
authors:
|
||||
- Microsoft Agent Framework Team
|
||||
tags:
|
||||
- Azure AI AgentServer
|
||||
- Microsoft Agent Framework
|
||||
- Multi-Agent Workflow
|
||||
- Writer-Reviewer
|
||||
- Content Creation
|
||||
template:
|
||||
kind: hosted
|
||||
name: FoundryMultiAgent
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: v1
|
||||
environment_variables:
|
||||
- name: AZURE_AI_PROJECT_ENDPOINT
|
||||
value: ${AZURE_AI_PROJECT_ENDPOINT}
|
||||
- name: MODEL_DEPLOYMENT_NAME
|
||||
value: gpt-5.4-mini
|
||||
resources:
|
||||
- name: "gpt-5.4-mini"
|
||||
kind: model
|
||||
id: gpt-5.4-mini
|
||||
-4
@@ -1,4 +0,0 @@
|
||||
{
|
||||
"AZURE_AI_PROJECT_ENDPOINT": "https://<your-resource>.services.ai.azure.com/api/projects/<your-project>",
|
||||
"MODEL_DEPLOYMENT_NAME": "gpt-5.4-mini"
|
||||
}
|
||||
-34
@@ -1,34 +0,0 @@
|
||||
@host = http://localhost:8088
|
||||
@endpoint = {{host}}/responses
|
||||
|
||||
### Health Check
|
||||
GET {{host}}/readiness
|
||||
|
||||
### Simple string input - Content creation request
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": "Create a slogan for a new electric SUV that is affordable and fun to drive",
|
||||
"stream": false
|
||||
}
|
||||
|
||||
### Explicit input format
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": [
|
||||
{
|
||||
"type": "message",
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "input_text",
|
||||
"text": "Write a short product description for a smart water bottle that tracks hydration"
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"stream": false
|
||||
}
|
||||
-20
@@ -1,20 +0,0 @@
|
||||
# Build the application
|
||||
FROM mcr.microsoft.com/dotnet/sdk:10.0-alpine AS build
|
||||
WORKDIR /src
|
||||
|
||||
# Copy files from the current directory on the host to the working directory in the container
|
||||
COPY . .
|
||||
|
||||
RUN dotnet restore
|
||||
RUN dotnet build -c Release --no-restore
|
||||
RUN dotnet publish -c Release --no-build -o /app -f net10.0
|
||||
|
||||
# Run the application
|
||||
FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
|
||||
WORKDIR /app
|
||||
|
||||
# Copy everything needed to run the app from the "build" stage.
|
||||
COPY --from=build /app .
|
||||
|
||||
EXPOSE 8088
|
||||
ENTRYPOINT ["dotnet", "FoundrySingleAgent.dll"]
|
||||
-67
@@ -1,67 +0,0 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<PropertyGroup>
|
||||
<OutputType>Exe</OutputType>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
|
||||
<!--
|
||||
Disable central package management for this project.
|
||||
This project requires explicit package references with versions specified inline rather than
|
||||
inheriting them from Directory.Packages.props. This is necessary because a Docker image will
|
||||
be created from this project, and the Docker build process only has access to this folder
|
||||
and cannot access parent folders where Directory.Packages.props resides.
|
||||
-->
|
||||
<ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
|
||||
</PropertyGroup>
|
||||
|
||||
<!--
|
||||
Remove analyzer PackageReference items inherited from Directory.Packages.props.
|
||||
Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
|
||||
Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
|
||||
and the PackageReference items are always inherited through MSBuild imports regardless of the
|
||||
ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
|
||||
-->
|
||||
<ItemGroup>
|
||||
<PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
|
||||
<PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
|
||||
<PackageReference Remove="xunit.analyzers" />
|
||||
<PackageReference Remove="Moq.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
|
||||
<PackageReference Remove="Roslynator.Formatting.Analyzers" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.11" />
|
||||
<PackageReference Include="Azure.AI.Projects" Version="2.0.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI" Version="1.0.0-rc4" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.AzureAI" Version="1.0.0-rc4" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Add analyzers with compatible versions -->
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
<PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.14.1">
|
||||
<PrivateAssets>all</PrivateAssets>
|
||||
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
|
||||
</PackageReference>
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
-132
@@ -1,132 +0,0 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// Seattle Hotel Agent - A simple agent with a tool to find hotels in Seattle.
|
||||
// Uses Microsoft Agent Framework with Microsoft Foundry.
|
||||
// Ready for deployment to Foundry Hosted Agent service.
|
||||
|
||||
#pragma warning disable CA2252 // AIProjectClient and Agents API require opting into preview features
|
||||
|
||||
using System.ComponentModel;
|
||||
using System.Globalization;
|
||||
using System.Text;
|
||||
|
||||
using Azure.AI.AgentServer.AgentFramework.Extensions;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
// Get configuration from environment variables
|
||||
var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
|
||||
var deploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
|
||||
Console.WriteLine($"Project Endpoint: {endpoint}");
|
||||
Console.WriteLine($"Model Deployment: {deploymentName}");
|
||||
// Simulated hotel data for Seattle
|
||||
var seattleHotels = new[]
|
||||
{
|
||||
new Hotel("Contoso Suites", 189, 4.5, "Downtown"),
|
||||
new Hotel("Fabrikam Residences", 159, 4.2, "Pike Place Market"),
|
||||
new Hotel("Alpine Ski House", 249, 4.7, "Seattle Center"),
|
||||
new Hotel("Margie's Travel Lodge", 219, 4.4, "Waterfront"),
|
||||
new Hotel("Northwind Inn", 139, 4.0, "Capitol Hill"),
|
||||
new Hotel("Relecloud Hotel", 99, 3.8, "University District"),
|
||||
};
|
||||
|
||||
[Description("Get available hotels in Seattle for the specified dates. This simulates a call to a hotel availability API.")]
|
||||
string GetAvailableHotels(
|
||||
[Description("Check-in date in YYYY-MM-DD format")] string checkInDate,
|
||||
[Description("Check-out date in YYYY-MM-DD format")] string checkOutDate,
|
||||
[Description("Maximum price per night in USD (optional, defaults to 500)")] int maxPrice = 500)
|
||||
{
|
||||
try
|
||||
{
|
||||
// Parse dates
|
||||
if (!DateTime.TryParseExact(checkInDate, "yyyy-MM-dd", CultureInfo.InvariantCulture, DateTimeStyles.None, out var checkIn))
|
||||
{
|
||||
return "Error parsing check-in date. Please use YYYY-MM-DD format.";
|
||||
}
|
||||
|
||||
if (!DateTime.TryParseExact(checkOutDate, "yyyy-MM-dd", CultureInfo.InvariantCulture, DateTimeStyles.None, out var checkOut))
|
||||
{
|
||||
return "Error parsing check-out date. Please use YYYY-MM-DD format.";
|
||||
}
|
||||
|
||||
// Validate dates
|
||||
if (checkOut <= checkIn)
|
||||
{
|
||||
return "Error: Check-out date must be after check-in date.";
|
||||
}
|
||||
|
||||
var nights = (checkOut - checkIn).Days;
|
||||
|
||||
// Filter hotels by price
|
||||
var availableHotels = seattleHotels.Where(h => h.PricePerNight <= maxPrice).ToList();
|
||||
|
||||
if (availableHotels.Count == 0)
|
||||
{
|
||||
return $"No hotels found in Seattle within your budget of ${maxPrice}/night.";
|
||||
}
|
||||
|
||||
// Build response
|
||||
var result = new StringBuilder();
|
||||
result
|
||||
.AppendLine($"Available hotels in Seattle from {checkInDate} to {checkOutDate} ({nights} nights):")
|
||||
.AppendLine();
|
||||
|
||||
foreach (var hotel in availableHotels)
|
||||
{
|
||||
var totalCost = hotel.PricePerNight * nights;
|
||||
result
|
||||
.AppendLine($"**{hotel.Name}**")
|
||||
.AppendLine($" Location: {hotel.Location}")
|
||||
.AppendLine($" Rating: {hotel.Rating}/5")
|
||||
.AppendLine($" ${hotel.PricePerNight}/night (Total: ${totalCost})")
|
||||
.AppendLine();
|
||||
}
|
||||
|
||||
return result.ToString();
|
||||
}
|
||||
catch (Exception ex)
|
||||
{
|
||||
return $"Error processing request. Details: {ex.Message}";
|
||||
}
|
||||
}
|
||||
|
||||
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
|
||||
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
|
||||
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
|
||||
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
|
||||
|
||||
// Create Foundry agent with hotel search tool
|
||||
AIAgent agent = await aiProjectClient.CreateAIAgentAsync(
|
||||
name: "SeattleHotelAgent",
|
||||
model: deploymentName,
|
||||
instructions: """
|
||||
You are a helpful travel assistant specializing in finding hotels in Seattle, Washington.
|
||||
|
||||
When a user asks about hotels in Seattle:
|
||||
1. Ask for their check-in and check-out dates if not provided
|
||||
2. Ask about their budget preferences if not mentioned
|
||||
3. Use the GetAvailableHotels tool to find available options
|
||||
4. Present the results in a friendly, informative way
|
||||
5. Offer to help with additional questions about the hotels or Seattle
|
||||
|
||||
Be conversational and helpful. If users ask about things outside of Seattle hotels,
|
||||
politely let them know you specialize in Seattle hotel recommendations.
|
||||
""",
|
||||
tools: [AIFunctionFactory.Create(GetAvailableHotels)]);
|
||||
|
||||
try
|
||||
{
|
||||
Console.WriteLine("Seattle Hotel Agent Server running on http://localhost:8088");
|
||||
await agent.RunAIAgentAsync(telemetrySourceName: "Agents");
|
||||
}
|
||||
finally
|
||||
{
|
||||
// Cleanup server-side agent
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(agent.Name);
|
||||
}
|
||||
|
||||
// Hotel record for simulated data
|
||||
internal sealed record Hotel(string Name, int PricePerNight, double Rating, string Location);
|
||||
-167
@@ -1,167 +0,0 @@
|
||||
**IMPORTANT!** All samples and other resources made available in this GitHub repository ("samples") are designed to assist in accelerating development of agents, solutions, and agent workflows for various scenarios. Review all provided resources and carefully test output behavior in the context of your use case. AI responses may be inaccurate and AI actions should be monitored with human oversight. Learn more in the transparency documents for [Agent Service](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/agents/transparency-note) and [Agent Framework](https://github.com/microsoft/agent-framework/blob/main/TRANSPARENCY_FAQ.md).
|
||||
|
||||
Agents, solutions, or other output you create may be subject to legal and regulatory requirements, may require licenses, or may not be suitable for all industries, scenarios, or use cases. By using any sample, you are acknowledging that any output created using those samples are solely your responsibility, and that you will comply with all applicable laws, regulations, and relevant safety standards, terms of service, and codes of conduct.
|
||||
|
||||
Third-party samples contained in this folder are subject to their own designated terms, and they have not been tested or verified by Microsoft or its affiliates.
|
||||
|
||||
Microsoft has no responsibility to you or others with respect to any of these samples or any resulting output.
|
||||
|
||||
# What this sample demonstrates
|
||||
|
||||
This sample demonstrates a **key advantage of code-based hosted agents**:
|
||||
|
||||
- **Local C# tool execution** - Run custom C# methods as agent tools
|
||||
|
||||
Code-based agents can execute **any C# code** you write. This sample includes a Seattle Hotel Agent with a `GetAvailableHotels` tool that searches for available hotels based on check-in/check-out dates and budget preferences.
|
||||
|
||||
The agent is hosted using the [Azure AI AgentServer SDK](https://learn.microsoft.com/en-us/dotnet/api/overview/azure/ai.agentserver.agentframework-readme) and can be deployed to Microsoft Foundry.
|
||||
|
||||
## How It Works
|
||||
|
||||
### Local Tools Integration
|
||||
|
||||
In [Program.cs](Program.cs), the agent uses `AIProjectClient.CreateAIAgentAsync()` from the [Microsoft.Agents.AI.AzureAI](https://www.nuget.org/packages/Microsoft.Agents.AI.AzureAI/) package to create a Foundry agent with a local C# method (`GetAvailableHotels`) that simulates a hotel availability API. This demonstrates how code-based agents can execute custom server-side logic that prompt agents cannot access.
|
||||
|
||||
The tool accepts:
|
||||
|
||||
- **checkInDate** - Check-in date in YYYY-MM-DD format
|
||||
- **checkOutDate** - Check-out date in YYYY-MM-DD format
|
||||
- **maxPrice** - Maximum price per night in USD (optional, defaults to $500)
|
||||
|
||||
### Agent Hosting
|
||||
|
||||
The agent is hosted using the [Azure AI AgentServer SDK](https://learn.microsoft.com/en-us/dotnet/api/overview/azure/ai.agentserver.agentframework-readme),
|
||||
which provisions a REST API endpoint compatible with the OpenAI Responses protocol.
|
||||
|
||||
## Running the Agent Locally
|
||||
|
||||
### Prerequisites
|
||||
|
||||
Before running this sample, ensure you have:
|
||||
|
||||
1. **Microsoft Foundry Project**
|
||||
- Project created.
|
||||
- Chat model deployed (e.g., `gpt-5.4-mini`)
|
||||
- Note your project endpoint URL and model deployment name
|
||||
|
||||
2. **Azure CLI**
|
||||
- Installed and authenticated
|
||||
- Run `az login` and verify with `az account show`
|
||||
- Your identity needs the **Azure AI Developer** role on the Foundry resource (for `agents/write` data action required by `CreateAIAgentAsync`)
|
||||
|
||||
3. **.NET 10.0 SDK or later**
|
||||
- Verify your version: `dotnet --version`
|
||||
- Download from [https://dotnet.microsoft.com/download](https://dotnet.microsoft.com/download)
|
||||
|
||||
### Environment Variables
|
||||
|
||||
Set the following environment variables (matching `agent.yaml`):
|
||||
|
||||
- `AZURE_AI_PROJECT_ENDPOINT` - Your Microsoft Foundry project endpoint URL (required)
|
||||
- `MODEL_DEPLOYMENT_NAME` - The deployment name for your chat model (defaults to `gpt-5.4-mini`)
|
||||
|
||||
**PowerShell:**
|
||||
|
||||
```powershell
|
||||
# Replace with your actual values
|
||||
$env:AZURE_AI_PROJECT_ENDPOINT="https://<your-resource>.services.ai.azure.com/api/projects/<your-project>"
|
||||
$env:MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
|
||||
```
|
||||
|
||||
**Bash:**
|
||||
|
||||
```bash
|
||||
export AZURE_AI_PROJECT_ENDPOINT="https://<your-resource>.services.ai.azure.com/api/projects/<your-project>"
|
||||
export MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
|
||||
```
|
||||
|
||||
### Running the Sample
|
||||
|
||||
To run the agent, execute the following command in your terminal:
|
||||
|
||||
```bash
|
||||
dotnet restore
|
||||
dotnet build
|
||||
dotnet run
|
||||
```
|
||||
|
||||
This will start the hosted agent locally on `http://localhost:8088/`.
|
||||
|
||||
### Interacting with the Agent
|
||||
|
||||
**VS Code:**
|
||||
|
||||
1. Open the Visual Studio Code Command Palette and execute the `Microsoft Foundry: Open Container Agent Playground Locally` command.
|
||||
2. Execute the following commands to start the containerized hosted agent.
|
||||
|
||||
```bash
|
||||
dotnet restore
|
||||
dotnet build
|
||||
dotnet run
|
||||
```
|
||||
|
||||
3. Submit a request to the agent through the playground interface. For example, you may enter a prompt such as: "I need a hotel in Seattle from 2025-03-15 to 2025-03-18, budget under $200 per night."
|
||||
4. The agent will use the GetAvailableHotels tool to search for available hotels matching your criteria.
|
||||
|
||||
> **Note**: Open the local playground before starting the container agent to ensure the visualization functions correctly.
|
||||
|
||||
**PowerShell (Windows):**
|
||||
|
||||
```powershell
|
||||
$body = @{
|
||||
input = "I need a hotel in Seattle from 2025-03-15 to 2025-03-18, budget under `$200 per night"
|
||||
stream = $false
|
||||
} | ConvertTo-Json
|
||||
|
||||
Invoke-RestMethod -Uri http://localhost:8088/responses -Method Post -Body $body -ContentType "application/json"
|
||||
```
|
||||
|
||||
**Bash/curl (Linux/macOS):**
|
||||
|
||||
```bash
|
||||
curl -sS -H "Content-Type: application/json" -X POST http://localhost:8088/responses \
|
||||
-d '{"input": "Find me hotels in Seattle for March 20-23, 2025 under $200 per night","stream":false}'
|
||||
```
|
||||
|
||||
You can also use the `run-requests.http` file in this directory with the VS Code REST Client extension.
|
||||
|
||||
The agent will use the `GetAvailableHotels` tool to search for available hotels matching your criteria.
|
||||
|
||||
## Deploying the Agent to Microsoft Foundry
|
||||
|
||||
**Preparation (required)**
|
||||
|
||||
Please check the environment_variables section in [agent.yaml](agent.yaml) and ensure the variables there are set in your target Microsoft Foundry Project.
|
||||
|
||||
To deploy the hosted agent:
|
||||
|
||||
1. Open the VS Code Command Palette and run the `Microsoft Foundry: Deploy Hosted Agent` command.
|
||||
2. Follow the interactive deployment prompts. The extension will help you select or create the container files it needs.
|
||||
3. After deployment completes, the hosted agent appears under the `Hosted Agents (Preview)` section of the extension tree. You can select the agent there to view details and test it using the integrated playground.
|
||||
|
||||
**What the deploy flow does for you:**
|
||||
|
||||
- Creates or obtains an Azure Container Registry for the target project.
|
||||
- Builds and pushes a container image from your workspace (the build packages the workspace respecting `.dockerignore`).
|
||||
- Creates an agent version in Microsoft Foundry using the built image. If a `.env` file exists at the workspace root, the extension will parse it and include its key/value pairs as the hosted agent's environment variables in the create request (these variables will be available to the agent runtime).
|
||||
- Starts the agent container on the project's capability host. If the capability host is not provisioned, the extension will prompt you to enable it and will guide you through creating it.
|
||||
|
||||
## MSI Configuration in the Azure Portal
|
||||
|
||||
This sample requires the Microsoft Foundry Project to authenticate using a Managed Identity when running remotely in Azure. Grant the project's managed identity the required permissions by assigning the built-in [Azure AI User](https://aka.ms/foundry-ext-project-role) role.
|
||||
|
||||
To configure the Managed Identity:
|
||||
|
||||
1. In the Azure Portal, open the Foundry Project.
|
||||
2. Select "Access control (IAM)" from the left-hand menu.
|
||||
3. Click "Add" and choose "Add role assignment".
|
||||
4. In the role selection, search for and select "Azure AI User", then click "Next".
|
||||
5. For "Assign access to", choose "Managed identity".
|
||||
6. Click "Select members", locate the managed identity associated with your Foundry Project (you can search by the project name), then click "Select".
|
||||
7. Click "Review + assign" to complete the assignment.
|
||||
8. Allow a few minutes for the role assignment to propagate before running the application.
|
||||
|
||||
## Additional Resources
|
||||
|
||||
- [Microsoft Agents Framework](https://learn.microsoft.com/en-us/agent-framework/overview/agent-framework-overview)
|
||||
- [Managed Identities for Azure Resources](https://learn.microsoft.com/en-us/entra/identity/managed-identities-azure-resources/)
|
||||
-32
@@ -1,32 +0,0 @@
|
||||
# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/ContainerAgent.yaml
|
||||
|
||||
name: FoundrySingleAgent
|
||||
displayName: "Foundry Single Agent with Local Tools"
|
||||
description: >
|
||||
A travel assistant agent that helps users find hotels in Seattle.
|
||||
Demonstrates local C# tool execution - a key advantage of code-based
|
||||
hosted agents over prompt agents.
|
||||
metadata:
|
||||
authors:
|
||||
- Microsoft Agent Framework Team
|
||||
tags:
|
||||
- Azure AI AgentServer
|
||||
- Microsoft Agent Framework
|
||||
- Local Tools
|
||||
- Travel Assistant
|
||||
- Hotel Search
|
||||
template:
|
||||
kind: hosted
|
||||
name: FoundrySingleAgent
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: v1
|
||||
environment_variables:
|
||||
- name: AZURE_AI_PROJECT_ENDPOINT
|
||||
value: ${AZURE_AI_PROJECT_ENDPOINT}
|
||||
- name: MODEL_DEPLOYMENT_NAME
|
||||
value: gpt-5.4-mini
|
||||
resources:
|
||||
- name: "gpt-5.4-mini"
|
||||
kind: model
|
||||
id: gpt-5.4-mini
|
||||
-52
@@ -1,52 +0,0 @@
|
||||
@host = http://localhost:8088
|
||||
@endpoint = {{host}}/responses
|
||||
|
||||
### Health Check
|
||||
GET {{host}}/readiness
|
||||
|
||||
### Simple hotel search - budget under $200
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": "I need a hotel in Seattle from 2025-03-15 to 2025-03-18, budget under $200 per night",
|
||||
"stream": false
|
||||
}
|
||||
|
||||
### Hotel search with higher budget
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": "Find me hotels in Seattle for March 20-23, 2025 under $250 per night",
|
||||
"stream": false
|
||||
}
|
||||
|
||||
### Ask for recommendations without dates (agent should ask for clarification)
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": "What hotels do you recommend in Seattle?",
|
||||
"stream": false
|
||||
}
|
||||
|
||||
### Explicit input format
|
||||
POST {{endpoint}}
|
||||
Content-Type: application/json
|
||||
|
||||
{
|
||||
"input": [
|
||||
{
|
||||
"type": "message",
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "input_text",
|
||||
"text": "I'm looking for a hotel in Seattle from 2025-04-01 to 2025-04-05, my budget is $150 per night maximum"
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"stream": false
|
||||
}
|
||||
@@ -1,100 +0,0 @@
|
||||
# Hosted Agent Samples
|
||||
|
||||
These samples demonstrate how to build and host AI agents using the [Azure AI AgentServer SDK](https://learn.microsoft.com/en-us/dotnet/api/overview/azure/ai.agentserver.agentframework-readme). Each sample can be run locally and deployed to Microsoft Foundry as a hosted agent.
|
||||
|
||||
## Samples
|
||||
|
||||
| Sample | Description |
|
||||
|--------|-------------|
|
||||
| [`AgentWithLocalTools`](./AgentWithLocalTools/) | Local C# function tool execution (Seattle hotel search) |
|
||||
| [`AgentThreadAndHITL`](./AgentThreadAndHITL/) | Human-in-the-loop with `ApprovalRequiredAIFunction` and thread persistence |
|
||||
| [`AgentWithHostedMCP`](./AgentWithHostedMCP/) | Hosted MCP server tool (Microsoft Learn search) |
|
||||
| [`AgentWithTextSearchRag`](./AgentWithTextSearchRag/) | RAG with `TextSearchProvider` (Contoso Outdoors) |
|
||||
| [`AgentsInWorkflows`](./AgentsInWorkflows/) | Sequential workflow pipeline (translation chain) |
|
||||
| [`FoundryMultiAgent`](./FoundryMultiAgent/) | Multi-agent Writer-Reviewer workflow using `AIProjectClient.CreateAIAgentAsync()` from [Microsoft.Agents.AI.AzureAI](https://www.nuget.org/packages/Microsoft.Agents.AI.AzureAI/) |
|
||||
| [`FoundrySingleAgent`](./FoundrySingleAgent/) | Single agent with local C# tool execution (hotel search) using `AIProjectClient.CreateAIAgentAsync()` from [Microsoft.Agents.AI.AzureAI](https://www.nuget.org/packages/Microsoft.Agents.AI.AzureAI/) |
|
||||
|
||||
## Common Prerequisites
|
||||
|
||||
Before running any sample, ensure you have:
|
||||
|
||||
1. **.NET 10 SDK** or later — [Download](https://dotnet.microsoft.com/download/dotnet/10.0)
|
||||
2. **Azure CLI** installed — [Install guide](https://learn.microsoft.com/cli/azure/install-azure-cli)
|
||||
3. **Azure OpenAI** or **Microsoft Foundry project** with a chat model deployed (e.g., `gpt-5.4-mini`)
|
||||
|
||||
### Authenticate with Azure CLI
|
||||
|
||||
All samples use `DefaultAzureCredential` for authentication, which automatically probes multiple credential sources (environment variables, managed identity, Azure CLI, etc.). For local development, the simplest approach is to authenticate via Azure CLI:
|
||||
|
||||
```powershell
|
||||
az login
|
||||
az account show # Verify the correct subscription
|
||||
```
|
||||
|
||||
### Common Environment Variables
|
||||
|
||||
Most samples require one or more of these environment variables:
|
||||
|
||||
| Variable | Used By | Description |
|
||||
|----------|---------|-------------|
|
||||
| `AZURE_OPENAI_ENDPOINT` | Most samples | Your Azure OpenAI resource endpoint URL |
|
||||
| `AZURE_OPENAI_DEPLOYMENT_NAME` | Most samples | Chat model deployment name (defaults to `gpt-5.4-mini`) |
|
||||
| `AZURE_AI_PROJECT_ENDPOINT` | AgentWithLocalTools, FoundryMultiAgent, FoundrySingleAgent | Microsoft Foundry project endpoint |
|
||||
| `MODEL_DEPLOYMENT_NAME` | AgentWithLocalTools, FoundryMultiAgent, FoundrySingleAgent | Chat model deployment name (defaults to `gpt-5.4-mini`) |
|
||||
|
||||
See each sample's README for the specific variables required.
|
||||
|
||||
## Microsoft Foundry Setup (for samples that use Foundry)
|
||||
|
||||
Some samples (`AgentWithLocalTools`, `FoundrySingleAgent`, `FoundryMultiAgent`) connect to a Microsoft Foundry project. If you're using these samples, you'll need additional setup.
|
||||
|
||||
### Azure AI Developer Role
|
||||
|
||||
Some Foundry operations require the **Azure AI Developer** role on the Cognitive Services resource. Even if you created the project, you may not have this role by default.
|
||||
|
||||
```powershell
|
||||
az role assignment create `
|
||||
--role "Azure AI Developer" `
|
||||
--assignee "your-email@microsoft.com" `
|
||||
--scope "/subscriptions/{subscription-id}/resourceGroups/{resource-group}/providers/Microsoft.CognitiveServices/accounts/{account-name}"
|
||||
```
|
||||
|
||||
> **Note**: You need **Owner** or **User Access Administrator** permissions on the resource to assign roles. If you don't have this, you may need to request JIT (Just-In-Time) elevated access via [Azure PIM](https://portal.azure.com/#view/Microsoft_Azure_PIMCommon/ActivationMenuBlade/~/aadmigratedresource).
|
||||
|
||||
For more details on permissions, see [Microsoft Foundry Permissions](https://aka.ms/FoundryPermissions).
|
||||
|
||||
## Running a Sample
|
||||
|
||||
Each sample runs as a standalone hosted agent on `http://localhost:8088/`:
|
||||
|
||||
```powershell
|
||||
cd <sample-directory>
|
||||
dotnet run
|
||||
```
|
||||
|
||||
### Interacting with the Agent
|
||||
|
||||
Each sample includes a `run-requests.http` file for testing with the [VS Code REST Client](https://marketplace.visualstudio.com/items?itemName=humao.rest-client) extension, or you can use PowerShell:
|
||||
|
||||
```powershell
|
||||
$body = @{ input = "Your question here" } | ConvertTo-Json
|
||||
Invoke-RestMethod -Uri "http://localhost:8088/responses" -Method Post -Body $body -ContentType "application/json"
|
||||
```
|
||||
|
||||
## Deploying to Microsoft Foundry
|
||||
|
||||
Each sample includes a `Dockerfile` and `agent.yaml` for deployment. To deploy your agent to Microsoft Foundry, follow the [hosted agents deployment guide](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/concepts/hosted-agents).
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### `PermissionDenied` — lacks `agents/write` data action
|
||||
|
||||
Assign the **Azure AI Developer** role to your user. See [Azure AI Developer Role](#azure-ai-developer-role) above.
|
||||
|
||||
### Multi-framework error when running `dotnet run`
|
||||
|
||||
If you see "Your project targets multiple frameworks", specify the framework:
|
||||
|
||||
```powershell
|
||||
dotnet run --framework net10.0
|
||||
```
|
||||
-1
@@ -2,7 +2,6 @@
|
||||
|
||||
using Azure.AI.AgentServer.Invocations;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.AspNetCore.Http;
|
||||
|
||||
namespace HostedInvocationsEchoAgent;
|
||||
|
||||
+1
-1
@@ -11,7 +11,7 @@ A minimal echo agent hosted as a Foundry Hosted Agent using the **Invocations pr
|
||||
This project uses `ProjectReference` to build against the local Agent Framework source.
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-Invocations-EchoAgent
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/invocations/Hosted-Invocations-EchoAgent
|
||||
dotnet run
|
||||
```
|
||||
|
||||
+2
-2
@@ -59,7 +59,7 @@ public sealed class InvocationsAIAgent : AIAgent
|
||||
CancellationToken cancellationToken = default)
|
||||
{
|
||||
var inputText = GetLastUserText(messages);
|
||||
var responseText = await SendInvocationAsync(inputText, cancellationToken).ConfigureAwait(false);
|
||||
var responseText = await this.SendInvocationAsync(inputText, cancellationToken).ConfigureAwait(false);
|
||||
return new AgentResponse(new ChatMessage(ChatRole.Assistant, responseText));
|
||||
}
|
||||
|
||||
@@ -73,7 +73,7 @@ public sealed class InvocationsAIAgent : AIAgent
|
||||
// The Invocations protocol returns a complete response (no SSE streaming),
|
||||
// so we yield a single update with the full text.
|
||||
var inputText = GetLastUserText(messages);
|
||||
var responseText = await SendInvocationAsync(inputText, cancellationToken).ConfigureAwait(false);
|
||||
var responseText = await this.SendInvocationAsync(inputText, cancellationToken).ConfigureAwait(false);
|
||||
|
||||
yield return new AgentResponseUpdate
|
||||
{
|
||||
+3
-3
@@ -13,7 +13,7 @@ A simple general-purpose AI assistant hosted as a Foundry Hosted Agent using the
|
||||
Copy the template and fill in your project endpoint:
|
||||
|
||||
```bash
|
||||
cp .env.local .env
|
||||
cp .env.example .env
|
||||
```
|
||||
|
||||
Edit `.env` and set your Azure AI Foundry project endpoint:
|
||||
@@ -25,14 +25,14 @@ ASPNETCORE_ENVIRONMENT=Development
|
||||
AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4o
|
||||
```
|
||||
|
||||
> **Note:** `.env` is gitignored. The `.env.local` template is checked in as a reference.
|
||||
> **Note:** `.env` is gitignored. The `.env.example` template is checked in as a reference.
|
||||
|
||||
## Running directly (contributors)
|
||||
|
||||
This project uses `ProjectReference` to build against the local Agent Framework source.
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-ChatClientAgent
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/responses/Hosted-ChatClientAgent
|
||||
dotnet run
|
||||
```
|
||||
|
||||
+3
-3
@@ -15,7 +15,7 @@ This is the **Foundry hosting** pattern — the agent's behavior is configured i
|
||||
Copy the template and fill in your project endpoint:
|
||||
|
||||
```bash
|
||||
cp .env.local .env
|
||||
cp .env.example .env
|
||||
```
|
||||
|
||||
Edit `.env` and set your Azure AI Foundry project endpoint:
|
||||
@@ -26,7 +26,7 @@ ASPNETCORE_URLS=http://+:8088
|
||||
ASPNETCORE_ENVIRONMENT=Development
|
||||
```
|
||||
|
||||
> **Note:** `.env` is gitignored. The `.env.local` template is checked in as a reference.
|
||||
> **Note:** `.env` is gitignored. The `.env.example` template is checked in as a reference.
|
||||
|
||||
You also need to set `AGENT_NAME` — the name of the Foundry-managed agent to host. This is injected automatically by the Foundry platform when deployed. For local development, pass it as an environment variable.
|
||||
|
||||
@@ -35,7 +35,7 @@ You also need to set `AGENT_NAME` — the name of the Foundry-managed agent to h
|
||||
This project uses `ProjectReference` to build against the local Agent Framework source.
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-FoundryAgent
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/responses/Hosted-FoundryAgent
|
||||
AGENT_NAME=<your-agent-name> dotnet run
|
||||
```
|
||||
|
||||
+3
-3
@@ -15,7 +15,7 @@ The agent specializes in finding hotels in Seattle, with a `GetAvailableHotels`
|
||||
Copy the template and fill in your project endpoint:
|
||||
|
||||
```bash
|
||||
cp .env.local .env
|
||||
cp .env.example .env
|
||||
```
|
||||
|
||||
Edit `.env` and set your Azure AI Foundry project endpoint:
|
||||
@@ -27,14 +27,14 @@ ASPNETCORE_ENVIRONMENT=Development
|
||||
AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4o
|
||||
```
|
||||
|
||||
> **Note:** `.env` is gitignored. The `.env.local` template is checked in as a reference.
|
||||
> **Note:** `.env` is gitignored. The `.env.example` template is checked in as a reference.
|
||||
|
||||
## Running directly (contributors)
|
||||
|
||||
This project uses `ProjectReference` to build against the local Agent Framework source.
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-LocalTools
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/responses/Hosted-LocalTools
|
||||
AGENT_NAME=hosted-local-tools dotnet run
|
||||
```
|
||||
|
||||
+2
-2
@@ -28,7 +28,7 @@ A hosted agent demonstrating **two layers of MCP (Model Context Protocol) tool i
|
||||
Copy the template and fill in your values:
|
||||
|
||||
```bash
|
||||
cp .env.local .env
|
||||
cp .env.example .env
|
||||
```
|
||||
|
||||
Edit `.env`:
|
||||
@@ -42,7 +42,7 @@ GITHUB_PAT=ghp_your_token_here
|
||||
## Running directly (contributors)
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-McpTools
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/responses/Hosted-McpTools
|
||||
dotnet run
|
||||
```
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user