mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Adding LocalTools + Workflow samples
This commit is contained in:
Roger Barreto
@@ -283,6 +283,12 @@
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-TextRag/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-TextRag/HostedTextRag.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-LocalTools/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-LocalTools/HostedLocalTools.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-Workflows/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-Workflows/HostedWorkflows.csproj" />
|
||||
</Folder>
|
||||
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Using-Samples/">
|
||||
<Project Path="samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Using-Samples/SimpleAgent/SimpleAgent.csproj" />
|
||||
</Folder>
|
||||
|
||||
+4
@@ -0,0 +1,4 @@
|
||||
AZURE_AI_PROJECT_ENDPOINT=<your-azure-ai-project-endpoint>
|
||||
ASPNETCORE_URLS=http://+:8088
|
||||
ASPNETCORE_ENVIRONMENT=Development
|
||||
AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4o
|
||||
+17
@@ -0,0 +1,17 @@
|
||||
# Use the official .NET 10.0 ASP.NET runtime as a parent image
|
||||
FROM mcr.microsoft.com/dotnet/aspnet:10.0 AS base
|
||||
WORKDIR /app
|
||||
|
||||
FROM mcr.microsoft.com/dotnet/sdk:10.0 AS build
|
||||
WORKDIR /src
|
||||
COPY . .
|
||||
RUN dotnet restore
|
||||
RUN dotnet publish -c Release -o /app/publish
|
||||
|
||||
# Final stage
|
||||
FROM base AS final
|
||||
WORKDIR /app
|
||||
COPY --from=build /app/publish .
|
||||
EXPOSE 8088
|
||||
ENV ASPNETCORE_URLS=http://+:8088
|
||||
ENTRYPOINT ["dotnet", "HostedLocalTools.dll"]
|
||||
+19
@@ -0,0 +1,19 @@
|
||||
# Dockerfile for contributors building from the agent-framework repository source.
|
||||
#
|
||||
# This project uses ProjectReference to the local Microsoft.Agents.AI.Foundry source,
|
||||
# which means a standard multi-stage Docker build cannot resolve dependencies outside
|
||||
# this folder. Instead, pre-publish the app targeting the container runtime and copy
|
||||
# the output into the container:
|
||||
#
|
||||
# dotnet publish -c Debug -f net10.0 -r linux-musl-x64 --self-contained false -o out
|
||||
# docker build -f Dockerfile.contributor -t hosted-local-tools .
|
||||
# docker run --rm -p 8088:8088 -e AGENT_NAME=hosted-local-tools -e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN --env-file .env hosted-local-tools
|
||||
#
|
||||
# For end-users consuming the NuGet package (not ProjectReference), use the standard
|
||||
# Dockerfile which performs a full dotnet restore + publish inside the container.
|
||||
FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
|
||||
WORKDIR /app
|
||||
COPY out/ .
|
||||
EXPOSE 8088
|
||||
ENV ASPNETCORE_URLS=http://+:8088
|
||||
ENTRYPOINT ["dotnet", "HostedLocalTools.dll"]
|
||||
+30
@@ -0,0 +1,30 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk.Web">
|
||||
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<CentralPackageTransitivePinningEnabled>false</CentralPackageTransitivePinningEnabled>
|
||||
<RootNamespace>HostedLocalTools</RootNamespace>
|
||||
<AssemblyName>HostedLocalTools</AssemblyName>
|
||||
<NoWarn>$(NoWarn);</NoWarn>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="DotNetEnv" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- For contributors: uses ProjectReference to build against local source -->
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Foundry\Microsoft.Agents.AI.Foundry.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- For end-users: uncomment the PackageReference below and remove the ProjectReference above
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.Agents.AI.Foundry" Version="1.0.0" />
|
||||
</ItemGroup>
|
||||
-->
|
||||
|
||||
</Project>
|
||||
+164
@@ -0,0 +1,164 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// Seattle Hotel Agent - A hosted agent with local C# function tools.
|
||||
// Demonstrates how to define and wire local tools that the LLM can invoke,
|
||||
// a key advantage of code-based hosted agents over prompt agents.
|
||||
|
||||
using System.ComponentModel;
|
||||
using System.Globalization;
|
||||
using System.Text;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Core;
|
||||
using Azure.Identity;
|
||||
using DotNetEnv;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.Foundry.Hosting;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
// Load .env file if present (for local development)
|
||||
Env.TraversePath().Load();
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o";
|
||||
|
||||
// Use a chained credential: try a temporary dev token first (for local Docker debugging),
|
||||
// then fall back to DefaultAzureCredential (for local dev via dotnet run / managed identity in production).
|
||||
TokenCredential credential = new ChainedTokenCredential(
|
||||
new DevTemporaryTokenCredential(),
|
||||
new DefaultAzureCredential());
|
||||
|
||||
// ── Hotel data ───────────────────────────────────────────────────────────────
|
||||
|
||||
Hotel[] seattleHotels =
|
||||
[
|
||||
new("Contoso Suites", 189, 4.5, "Downtown"),
|
||||
new("Fabrikam Residences", 159, 4.2, "Pike Place Market"),
|
||||
new("Alpine Ski House", 249, 4.7, "Seattle Center"),
|
||||
new("Margie's Travel Lodge", 219, 4.4, "Waterfront"),
|
||||
new("Northwind Inn", 139, 4.0, "Capitol Hill"),
|
||||
new("Relecloud Hotel", 99, 3.8, "University District"),
|
||||
];
|
||||
|
||||
// ── Tool: GetAvailableHotels ─────────────────────────────────────────────────
|
||||
|
||||
[Description("Get available hotels in Seattle for the specified dates.")]
|
||||
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)
|
||||
{
|
||||
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();
|
||||
}
|
||||
|
||||
// ── Create and host the agent ────────────────────────────────────────────────
|
||||
|
||||
AIAgent agent = new AIProjectClient(new Uri(endpoint), credential)
|
||||
.AsAIAgent(
|
||||
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.
|
||||
""",
|
||||
name: Environment.GetEnvironmentVariable("AGENT_NAME") ?? "hosted-local-tools",
|
||||
description: "Seattle hotel search agent with local function tools",
|
||||
tools: [AIFunctionFactory.Create(GetAvailableHotels)]);
|
||||
|
||||
var builder = WebApplication.CreateBuilder(args);
|
||||
builder.Services.AddFoundryResponses(agent);
|
||||
|
||||
var app = builder.Build();
|
||||
app.MapFoundryResponses();
|
||||
|
||||
if (app.Environment.IsDevelopment())
|
||||
{
|
||||
app.MapFoundryResponses("openai/v1");
|
||||
}
|
||||
|
||||
app.Run();
|
||||
|
||||
// ── Types ────────────────────────────────────────────────────────────────────
|
||||
|
||||
internal sealed record Hotel(string Name, int PricePerNight, double Rating, string Location);
|
||||
|
||||
/// <summary>
|
||||
/// A <see cref="TokenCredential"/> for local Docker debugging only.
|
||||
/// Reads a pre-fetched bearer token from the <c>AZURE_BEARER_TOKEN</c> environment variable
|
||||
/// once at startup. This should NOT be used in production.
|
||||
///
|
||||
/// Generate a token on your host and pass it to the container:
|
||||
/// export AZURE_BEARER_TOKEN=$(az account get-access-token --resource https://ai.azure.com --query accessToken -o tsv)
|
||||
/// docker run -e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN ...
|
||||
/// </summary>
|
||||
internal sealed class DevTemporaryTokenCredential : TokenCredential
|
||||
{
|
||||
private const string EnvironmentVariable = "AZURE_BEARER_TOKEN";
|
||||
private readonly string? _token;
|
||||
|
||||
public DevTemporaryTokenCredential()
|
||||
{
|
||||
_token = Environment.GetEnvironmentVariable(EnvironmentVariable);
|
||||
}
|
||||
|
||||
public override AccessToken GetToken(TokenRequestContext requestContext, CancellationToken cancellationToken)
|
||||
=> GetAccessToken();
|
||||
|
||||
public override ValueTask<AccessToken> GetTokenAsync(TokenRequestContext requestContext, CancellationToken cancellationToken)
|
||||
=> new(GetAccessToken());
|
||||
|
||||
private AccessToken GetAccessToken()
|
||||
{
|
||||
if (string.IsNullOrEmpty(_token))
|
||||
{
|
||||
throw new CredentialUnavailableException($"{EnvironmentVariable} environment variable is not set.");
|
||||
}
|
||||
|
||||
return new AccessToken(_token, DateTimeOffset.UtcNow.AddHours(1));
|
||||
}
|
||||
}
|
||||
+11
@@ -0,0 +1,11 @@
|
||||
{
|
||||
"profiles": {
|
||||
"HostedLocalTools": {
|
||||
"commandName": "Project",
|
||||
"environmentVariables": {
|
||||
"ASPNETCORE_ENVIRONMENT": "Development"
|
||||
},
|
||||
"applicationUrl": "http://localhost:8088"
|
||||
}
|
||||
}
|
||||
}
|
||||
+113
@@ -0,0 +1,113 @@
|
||||
# Hosted-LocalTools
|
||||
|
||||
A hosted agent with **local C# function tools** for hotel search. Demonstrates how to define and wire local tools that the LLM can invoke — a key advantage of code-based hosted agents over prompt agents.
|
||||
|
||||
The agent specializes in finding hotels in Seattle, with a `GetAvailableHotels` tool that searches a mock hotel database by dates and budget.
|
||||
|
||||
## Prerequisites
|
||||
|
||||
- [.NET 10 SDK](https://dotnet.microsoft.com/download/dotnet/10.0)
|
||||
- An Azure AI Foundry project with a deployed model (e.g., `gpt-4o`)
|
||||
- Azure CLI logged in (`az login`)
|
||||
|
||||
## Configuration
|
||||
|
||||
Copy the template and fill in your project endpoint:
|
||||
|
||||
```bash
|
||||
cp .env.local .env
|
||||
```
|
||||
|
||||
Edit `.env` and set your Azure AI Foundry project endpoint:
|
||||
|
||||
```env
|
||||
AZURE_AI_PROJECT_ENDPOINT=https://<your-account>.services.ai.azure.com/api/projects/<your-project>
|
||||
ASPNETCORE_URLS=http://+:8088
|
||||
ASPNETCORE_ENVIRONMENT=Development
|
||||
AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4o
|
||||
```
|
||||
|
||||
> **Note:** `.env` is gitignored. The `.env.local` 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
|
||||
AGENT_NAME=hosted-local-tools dotnet run
|
||||
```
|
||||
|
||||
The agent will start on `http://localhost:8088`.
|
||||
|
||||
### Test it
|
||||
|
||||
Using the Azure Developer CLI:
|
||||
|
||||
```bash
|
||||
azd ai agent invoke --local "Find me a hotel in Seattle for Dec 20-25 under $200/night"
|
||||
```
|
||||
|
||||
Or with curl:
|
||||
|
||||
```bash
|
||||
curl -X POST http://localhost:8088/responses \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"input": "Find me a hotel in Seattle for Dec 20-25 under $200/night", "model": "hosted-local-tools"}'
|
||||
```
|
||||
|
||||
## Running with Docker
|
||||
|
||||
Since this project uses `ProjectReference`, use `Dockerfile.contributor` which takes a pre-published output.
|
||||
|
||||
### 1. Publish for the container runtime (Linux Alpine)
|
||||
|
||||
```bash
|
||||
dotnet publish -c Debug -f net10.0 -r linux-musl-x64 --self-contained false -o out
|
||||
```
|
||||
|
||||
### 2. Build the Docker image
|
||||
|
||||
```bash
|
||||
docker build -f Dockerfile.contributor -t hosted-local-tools .
|
||||
```
|
||||
|
||||
### 3. Run the container
|
||||
|
||||
Generate a bearer token on your host and pass it to the container:
|
||||
|
||||
```bash
|
||||
# Generate token (expires in ~1 hour)
|
||||
export AZURE_BEARER_TOKEN=$(az account get-access-token --resource https://ai.azure.com --query accessToken -o tsv)
|
||||
|
||||
# Run with token
|
||||
docker run --rm -p 8088:8088 \
|
||||
-e AGENT_NAME=hosted-local-tools \
|
||||
-e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN \
|
||||
--env-file .env \
|
||||
hosted-local-tools
|
||||
```
|
||||
|
||||
### 4. Test it
|
||||
|
||||
Using the Azure Developer CLI:
|
||||
|
||||
```bash
|
||||
azd ai agent invoke --local "What hotels are available in Seattle for next weekend?"
|
||||
```
|
||||
|
||||
## How local tools work
|
||||
|
||||
The agent has a single tool `GetAvailableHotels` defined as a C# method with `[Description]` attributes. The LLM decides when to call it based on the user's request:
|
||||
|
||||
| Parameter | Type | Description |
|
||||
|-----------|------|-------------|
|
||||
| `checkInDate` | string | Check-in date (YYYY-MM-DD) |
|
||||
| `checkOutDate` | string | Check-out date (YYYY-MM-DD) |
|
||||
| `maxPrice` | int | Max price per night in USD (default: 500) |
|
||||
|
||||
The tool searches a mock database of 6 Seattle hotels and returns formatted results with name, location, rating, and pricing.
|
||||
|
||||
## NuGet package users
|
||||
|
||||
If you are consuming the Agent Framework as a NuGet package (not building from source), use the standard `Dockerfile` instead of `Dockerfile.contributor`. See the commented section in `HostedLocalTools.csproj` for the `PackageReference` alternative.
|
||||
+29
@@ -0,0 +1,29 @@
|
||||
# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/AgentManifest.yaml
|
||||
name: hosted-local-tools
|
||||
displayName: "Seattle Hotel 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:
|
||||
tags:
|
||||
- AI Agent Hosting
|
||||
- Azure AI AgentServer
|
||||
- Responses Protocol
|
||||
- Local Tools
|
||||
- Agent Framework
|
||||
|
||||
template:
|
||||
name: hosted-local-tools
|
||||
kind: hosted
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: 1.0.0
|
||||
resources:
|
||||
cpu: "0.25"
|
||||
memory: 0.5Gi
|
||||
parameters:
|
||||
properties: []
|
||||
resources: []
|
||||
+9
@@ -0,0 +1,9 @@
|
||||
# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/ContainerAgent.yaml
|
||||
kind: hosted
|
||||
name: hosted-local-tools
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: 1.0.0
|
||||
resources:
|
||||
cpu: "0.25"
|
||||
memory: 0.5Gi
|
||||
+4
@@ -0,0 +1,4 @@
|
||||
AZURE_AI_PROJECT_ENDPOINT=<your-azure-ai-project-endpoint>
|
||||
ASPNETCORE_URLS=http://+:8088
|
||||
ASPNETCORE_ENVIRONMENT=Development
|
||||
AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4o
|
||||
+17
@@ -0,0 +1,17 @@
|
||||
# Use the official .NET 10.0 ASP.NET runtime as a parent image
|
||||
FROM mcr.microsoft.com/dotnet/aspnet:10.0 AS base
|
||||
WORKDIR /app
|
||||
|
||||
FROM mcr.microsoft.com/dotnet/sdk:10.0 AS build
|
||||
WORKDIR /src
|
||||
COPY . .
|
||||
RUN dotnet restore
|
||||
RUN dotnet publish -c Release -o /app/publish
|
||||
|
||||
# Final stage
|
||||
FROM base AS final
|
||||
WORKDIR /app
|
||||
COPY --from=build /app/publish .
|
||||
EXPOSE 8088
|
||||
ENV ASPNETCORE_URLS=http://+:8088
|
||||
ENTRYPOINT ["dotnet", "HostedWorkflows.dll"]
|
||||
+18
@@ -0,0 +1,18 @@
|
||||
# Dockerfile for contributors building from the agent-framework repository source.
|
||||
#
|
||||
# This project uses ProjectReference to the local source, which means a standard
|
||||
# multi-stage Docker build cannot resolve dependencies outside this folder.
|
||||
# Pre-publish the app targeting the container runtime and copy the output:
|
||||
#
|
||||
# dotnet publish -c Debug -f net10.0 -r linux-musl-x64 --self-contained false -o out
|
||||
# docker build -f Dockerfile.contributor -t hosted-workflows .
|
||||
# docker run --rm -p 8088:8088 -e AGENT_NAME=hosted-workflows -e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN --env-file .env hosted-workflows
|
||||
#
|
||||
# For end-users consuming the NuGet package (not ProjectReference), use the standard
|
||||
# Dockerfile which performs a full dotnet restore + publish inside the container.
|
||||
FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
|
||||
WORKDIR /app
|
||||
COPY out/ .
|
||||
EXPOSE 8088
|
||||
ENV ASPNETCORE_URLS=http://+:8088
|
||||
ENTRYPOINT ["dotnet", "HostedWorkflows.dll"]
|
||||
+34
@@ -0,0 +1,34 @@
|
||||
<Project Sdk="Microsoft.NET.Sdk.Web">
|
||||
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>net10.0</TargetFrameworks>
|
||||
<Nullable>enable</Nullable>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<CentralPackageTransitivePinningEnabled>false</CentralPackageTransitivePinningEnabled>
|
||||
<RootNamespace>HostedWorkflows</RootNamespace>
|
||||
<AssemblyName>HostedWorkflows</AssemblyName>
|
||||
<NoWarn>$(NoWarn);</NoWarn>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="DotNetEnv" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- For contributors: uses ProjectReference to build against local source -->
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Foundry\Microsoft.Agents.AI.Foundry.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- For end-users: uncomment the PackageReference below and remove the ProjectReferences above
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Microsoft.Agents.AI.Foundry" Version="1.0.0" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.Workflows" Version="1.0.0" />
|
||||
</ItemGroup>
|
||||
-->
|
||||
|
||||
</Project>
|
||||
+97
@@ -0,0 +1,97 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
// Translation Chain Workflow Agent — demonstrates how to compose multiple AI agents
|
||||
// into a sequential workflow pipeline. Three translation agents are connected:
|
||||
// English → French → Spanish → English, showing how agents can be orchestrated
|
||||
// as workflow executors in a hosted agent.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Core;
|
||||
using Azure.Identity;
|
||||
using DotNetEnv;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.Foundry.Hosting;
|
||||
using Microsoft.Agents.AI.Workflows;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
// Load .env file if present (for local development)
|
||||
Env.TraversePath().Load();
|
||||
|
||||
string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
|
||||
string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o";
|
||||
|
||||
// Use a chained credential: try a temporary dev token first (for local Docker debugging),
|
||||
// then fall back to DefaultAzureCredential (for local dev via dotnet run / managed identity in production).
|
||||
TokenCredential credential = new ChainedTokenCredential(
|
||||
new DevTemporaryTokenCredential(),
|
||||
new DefaultAzureCredential());
|
||||
|
||||
// Create a chat client from the Foundry project
|
||||
IChatClient chatClient = new AIProjectClient(new Uri(endpoint), credential)
|
||||
.GetProjectOpenAIClient()
|
||||
.GetChatClient(deploymentName)
|
||||
.AsIChatClient();
|
||||
|
||||
// Create translation agents
|
||||
AIAgent frenchAgent = chatClient.AsAIAgent("You are a translation assistant that translates the provided text to French.");
|
||||
AIAgent spanishAgent = chatClient.AsAIAgent("You are a translation assistant that translates the provided text to Spanish.");
|
||||
AIAgent englishAgent = chatClient.AsAIAgent("You are a translation assistant that translates the provided text to English.");
|
||||
|
||||
// Build the sequential workflow: French → Spanish → English
|
||||
AIAgent agent = new WorkflowBuilder(frenchAgent)
|
||||
.AddEdge(frenchAgent, spanishAgent)
|
||||
.AddEdge(spanishAgent, englishAgent)
|
||||
.Build()
|
||||
.AsAIAgent(
|
||||
name: Environment.GetEnvironmentVariable("AGENT_NAME") ?? "hosted-workflows");
|
||||
|
||||
// Host the workflow agent as a Foundry Hosted Agent using the Responses API.
|
||||
var builder = WebApplication.CreateBuilder(args);
|
||||
builder.Services.AddFoundryResponses(agent);
|
||||
|
||||
var app = builder.Build();
|
||||
app.MapFoundryResponses();
|
||||
|
||||
if (app.Environment.IsDevelopment())
|
||||
{
|
||||
app.MapFoundryResponses("openai/v1");
|
||||
}
|
||||
|
||||
app.Run();
|
||||
|
||||
/// <summary>
|
||||
/// A <see cref="TokenCredential"/> for local Docker debugging only.
|
||||
/// Reads a pre-fetched bearer token from the <c>AZURE_BEARER_TOKEN</c> environment variable
|
||||
/// once at startup. This should NOT be used in production.
|
||||
///
|
||||
/// Generate a token on your host and pass it to the container:
|
||||
/// export AZURE_BEARER_TOKEN=$(az account get-access-token --resource https://ai.azure.com --query accessToken -o tsv)
|
||||
/// docker run -e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN ...
|
||||
/// </summary>
|
||||
internal sealed class DevTemporaryTokenCredential : TokenCredential
|
||||
{
|
||||
private const string EnvironmentVariable = "AZURE_BEARER_TOKEN";
|
||||
private readonly string? _token;
|
||||
|
||||
public DevTemporaryTokenCredential()
|
||||
{
|
||||
_token = Environment.GetEnvironmentVariable(EnvironmentVariable);
|
||||
}
|
||||
|
||||
public override AccessToken GetToken(TokenRequestContext requestContext, CancellationToken cancellationToken)
|
||||
=> GetAccessToken();
|
||||
|
||||
public override ValueTask<AccessToken> GetTokenAsync(TokenRequestContext requestContext, CancellationToken cancellationToken)
|
||||
=> new(GetAccessToken());
|
||||
|
||||
private AccessToken GetAccessToken()
|
||||
{
|
||||
if (string.IsNullOrEmpty(_token))
|
||||
{
|
||||
throw new CredentialUnavailableException($"{EnvironmentVariable} environment variable is not set.");
|
||||
}
|
||||
|
||||
return new AccessToken(_token, DateTimeOffset.UtcNow.AddHours(1));
|
||||
}
|
||||
}
|
||||
+11
@@ -0,0 +1,11 @@
|
||||
{
|
||||
"profiles": {
|
||||
"HostedWorkflows": {
|
||||
"commandName": "Project",
|
||||
"environmentVariables": {
|
||||
"ASPNETCORE_ENVIRONMENT": "Development"
|
||||
},
|
||||
"applicationUrl": "http://localhost:8088"
|
||||
}
|
||||
}
|
||||
}
|
||||
+109
@@ -0,0 +1,109 @@
|
||||
# Hosted-Workflows
|
||||
|
||||
A hosted agent that demonstrates **multi-agent workflow orchestration**. Three translation agents are composed into a sequential pipeline: English → French → Spanish → English, showing how agents can be chained as workflow executors using `WorkflowBuilder`.
|
||||
|
||||
## Prerequisites
|
||||
|
||||
- [.NET 10 SDK](https://dotnet.microsoft.com/download/dotnet/10.0)
|
||||
- An Azure AI Foundry project with a deployed model (e.g., `gpt-4o`)
|
||||
- Azure CLI logged in (`az login`)
|
||||
|
||||
## Configuration
|
||||
|
||||
Copy the template and fill in your project endpoint:
|
||||
|
||||
```bash
|
||||
cp .env.local .env
|
||||
```
|
||||
|
||||
Edit `.env` and set your Azure AI Foundry project endpoint:
|
||||
|
||||
```env
|
||||
AZURE_AI_PROJECT_ENDPOINT=https://<your-account>.services.ai.azure.com/api/projects/<your-project>
|
||||
ASPNETCORE_URLS=http://+:8088
|
||||
ASPNETCORE_ENVIRONMENT=Development
|
||||
AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4o
|
||||
```
|
||||
|
||||
> **Note:** `.env` is gitignored. The `.env.local` template is checked in as a reference.
|
||||
|
||||
## Running directly (contributors)
|
||||
|
||||
```bash
|
||||
cd dotnet/samples/04-hosting/FoundryHostedAgents/HostedAgentsV2/Hosted-Workflows
|
||||
AGENT_NAME=hosted-workflows dotnet run
|
||||
```
|
||||
|
||||
The agent will start on `http://localhost:8088`.
|
||||
|
||||
### Test it
|
||||
|
||||
Using the Azure Developer CLI:
|
||||
|
||||
```bash
|
||||
azd ai agent invoke --local "The quick brown fox jumps over the lazy dog"
|
||||
```
|
||||
|
||||
Or with curl:
|
||||
|
||||
```bash
|
||||
curl -X POST http://localhost:8088/responses \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"input": "The quick brown fox jumps over the lazy dog", "model": "hosted-workflows"}'
|
||||
```
|
||||
|
||||
The text will be translated through the chain: English → French → Spanish → English.
|
||||
|
||||
## Running with Docker
|
||||
|
||||
### 1. Publish for the container runtime
|
||||
|
||||
```bash
|
||||
dotnet publish -c Debug -f net10.0 -r linux-musl-x64 --self-contained false -o out
|
||||
```
|
||||
|
||||
### 2. Build the Docker image
|
||||
|
||||
```bash
|
||||
docker build -f Dockerfile.contributor -t hosted-workflows .
|
||||
```
|
||||
|
||||
### 3. Run the container
|
||||
|
||||
```bash
|
||||
export AZURE_BEARER_TOKEN=$(az account get-access-token --resource https://ai.azure.com --query accessToken -o tsv)
|
||||
|
||||
docker run --rm -p 8088:8088 \
|
||||
-e AGENT_NAME=hosted-workflows \
|
||||
-e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN \
|
||||
--env-file .env \
|
||||
hosted-workflows
|
||||
```
|
||||
|
||||
### 4. Test it
|
||||
|
||||
```bash
|
||||
azd ai agent invoke --local "Hello, how are you today?"
|
||||
```
|
||||
|
||||
## How the workflow works
|
||||
|
||||
```
|
||||
Input text
|
||||
│
|
||||
▼
|
||||
┌─────────────┐ ┌──────────────┐ ┌──────────────┐
|
||||
│ French Agent │ → │ Spanish Agent │ → │ English Agent │
|
||||
│ (translate) │ │ (translate) │ │ (translate) │
|
||||
└─────────────┘ └──────────────┘ └──────────────┘
|
||||
│
|
||||
▼
|
||||
Final output
|
||||
(back in English)
|
||||
```
|
||||
|
||||
Each agent in the chain receives the output of the previous agent. The final result demonstrates how meaning is preserved (or subtly shifted) through multiple translation hops.
|
||||
|
||||
## NuGet package users
|
||||
|
||||
Use the standard `Dockerfile` instead of `Dockerfile.contributor`. See the commented section in `HostedWorkflows.csproj` for the `PackageReference` alternative.
|
||||
+29
@@ -0,0 +1,29 @@
|
||||
# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/AgentManifest.yaml
|
||||
name: hosted-workflows
|
||||
displayName: "Translation Chain Workflow Agent"
|
||||
|
||||
description: >
|
||||
A workflow agent that performs sequential translation through multiple languages.
|
||||
Translates text from English to French, then to Spanish, and finally back to English,
|
||||
demonstrating how AI agents can be composed as workflow executors.
|
||||
|
||||
metadata:
|
||||
tags:
|
||||
- AI Agent Hosting
|
||||
- Azure AI AgentServer
|
||||
- Responses Protocol
|
||||
- Workflows
|
||||
- Agent Framework
|
||||
|
||||
template:
|
||||
name: hosted-workflows
|
||||
kind: hosted
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: 1.0.0
|
||||
resources:
|
||||
cpu: "0.25"
|
||||
memory: 0.5Gi
|
||||
parameters:
|
||||
properties: []
|
||||
resources: []
|
||||
+9
@@ -0,0 +1,9 @@
|
||||
# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/ContainerAgent.yaml
|
||||
kind: hosted
|
||||
name: hosted-workflows
|
||||
protocols:
|
||||
- protocol: responses
|
||||
version: 1.0.0
|
||||
resources:
|
||||
cpu: "0.25"
|
||||
memory: 0.5Gi
|
||||
Reference in New Issue
Block a user