Compare commits

..
Author SHA1 Message Date
Roger Barreto 469525d9e6 Update 3 2025-11-07 21:53:36 +00:00
Roger Barreto 6e04c6bbbe Update 2 2025-11-07 21:44:31 +00:00
Roger Barreto f5d6056074 Update 2025-11-07 20:01:38 +00:00
Roger Barreto 9586a3ea53 Bugbash Samples 2025-11-07 17:51:17 +00:00
Roger Barreto 82bd9cf6b5 Restructure Step1 2025-11-07 12:46:04 +00:00
ChrisandGitHub 4cbde55243 Merge branch 'main' into feature-foundry-agents 2025-11-06 18:48:17 -08:00
Chris Rickman 864b1f7a91 Fix bad merge 2025-11-06 18:40:34 -08:00
ChrisandGitHub 5131f3a129 Merge branch 'main' into feature-foundry-agents 2025-11-06 14:31:48 -08:00
ChrisandGitHub 2ee34beed5 Merge branch 'main' into feature-foundry-agents 2025-11-06 08:32:05 -08:00
Roger BarretoandGitHub d55b15903d .NET: AgentDefinition extensions method simplification (#1967)
* Update extensions methods that accepts AgentDefinition type to not be restrictive

* Update Unit Tests

* Revert yarn/package-lock

* Revert yarn/package-lock

* Address copilot feedback
2025-11-06 16:04:31 +00:00
ChrisandGitHub 5a8c8fe634 Merge branch 'main' into feature-foundry-agents 2025-11-05 19:55:57 -08:00
ChrisandGitHub b2c38ac98c Merge branch 'main' into feature-foundry-agents 2025-11-05 19:14:20 -08:00
ChrisandGitHub 1aa00e6428 Merge branch 'main' into feature-foundry-agents 2025-11-05 16:57:09 -08:00
ChrisandGitHub f0d2dd6774 Merge branch 'main' into feature-foundry-agents 2025-11-05 15:49:58 -08:00
ChrisandGitHub bf007f854c Updated (#1948) 2025-11-05 15:47:50 -08:00
ChrisandGitHub 55a4aa2b53 Merge branch 'main' into feature-foundry-agents 2025-11-05 12:26:13 -08:00
Roger Barreto 95fe891369 Normalize changes 2025-11-05 20:20:48 +00:00
Roger Barreto 4d1a132737 .NET: Allow Declarative AIAgents Extensions (#1931)
* Improve reusability of extension code and additional option to losen the strictiness of in-proc tools

* Add missing UT scenarios

* Add missing UT test scenarios
2025-11-05 20:14:23 +00:00
Dmytro StrukandRoger Barreto 943e37836f Updated package version (#1906) 2025-11-05 20:14:22 +00:00
Roger Barreto 65e1c12dfa Version update (#1901) 2025-11-05 20:14:21 +00:00
Roger BarretoandCopilot 279d91f58e .NET: Update Extensions for Strict Agent Definitions + Improvements (#1892)
* Update Package Nameing: V1 -> AzureAI.Persistent / V2 -> AzureAI

* Update agents and extensions to comply with strict agent definitions

* More static updates

* Address UT, and ResponseTool support

* Improving reusability extensions

* Addressing ResponseTools Unit Tests and extension setup

* Adapted workaround on breaking AAA with OpenAI 2.6.0

* Small updates

* Remove strictness when retrieving agents, improved XmlDocs

* Improve sample comments

* Update dotnet/tests/Microsoft.Agents.AI.AzureAI.UnitTests/AgentsClientExtensionsTests.cs

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Apply suggestion from @Copilot

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Apply suggestion from @Copilot

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Address PR comments

* Address UT failing

* Address Copilot feedback

* Address Copilot feedback

* Address comment typo

* Address PR feedback

* Address typo

* Add missing Extensions with ChatClientAgentOptions

* Address comments

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2025-11-05 20:14:12 +00:00
Roger Barreto 51e7a2134a Update Package Nameing: V1 -> AzureAI.Persistent / V2 -> AzureAI (#1829) 2025-11-05 20:13:36 +00:00
Roger Barreto 90226526fa .NET: Change model to be required just for prompt agent definition specific extensions (#1812)
* Remove unneeded model from extensions

* Add noop justification
2025-11-05 20:11:43 +00:00
CopilotRoger BarretoCopilotcopilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
7405759593 .NET: Add comprehensive unit tests for Microsoft.Agents.AI.AzureAIAgents extension methods (#1786)
* Initial plan

* Add comprehensive unit test project for Microsoft.Agents.AI.AzureAIAgents

Co-authored-by: rogerbarreto <19890735+rogerbarreto@users.noreply.github.com>

* Add README documenting test project and package dependency requirements

Co-authored-by: rogerbarreto <19890735+rogerbarreto@users.noreply.github.com>

* Fix documentation URL to use learn.microsoft.com

Co-authored-by: rogerbarreto <19890735+rogerbarreto@users.noreply.github.com>

* Bump back AAAP 1.2.0-beta.7

* Address AI generated UT's

* Remove UT Readme

* Apply suggestions from code review

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: rogerbarreto <19890735+rogerbarreto@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2025-11-05 20:11:32 +00:00
ChrisandRoger Barreto 698aba5f97 Update Directory.Packages.props
Fix package version rollback:

Azure.AI.Agents.Persistent (beta-6 => beta-7)
2025-11-05 20:10:31 +00:00
Roger Barreto 7e23140ca9 .NET: Azure.AI.Agents Package Split + Initial Extensions (#1657)
* Move packages

* Update nuget.config

* Address Xmldoc

* Remove format from branches checks

* Address Xmldocs

* Add more details to the implementation

* Moving Agent logic to ChatClient

* Adding Name and Id overrides to AzureAIAgent

* Updating extensions

* Add GetAiAgent extensions

* Adding support for version as name can conflict 409 using the Agents API with same name

* Addressing more updates to the extensions

* More improvements

* Remove debugging code from sample

* Address copilot feedback

* Apply suggestions from co-pilot code review
2025-11-05 20:10:24 +00:00
ChrisandRoger Barreto 904e17473f Fixed build errors (#1638)
Comment and nullable type alignment
2025-11-05 20:09:02 +00:00
Roger Barreto 2c5cf6c67b WIP 2025-11-05 20:08:55 +00:00
1112 changed files with 18570 additions and 88617 deletions
-4
View File
@@ -1,4 +0,0 @@
# Code ownership assignments
# https://docs.github.com/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners
python/packages/azurefunctions/ @microsoft/agentframework-durabletask-developers
@@ -1,36 +0,0 @@
name: Azure Functions Integration Test Setup
description: Prepare local emulators and tools for Azure Functions integration tests
runs:
using: "composite"
steps:
- name: Start Durable Task Scheduler Emulator
shell: bash
run: |
if [ "$(docker ps -aq -f name=dts-emulator)" ]; then
echo "Stopping and removing existing Durable Task Scheduler Emulator"
docker rm -f dts-emulator
fi
echo "Starting Durable Task Scheduler Emulator"
docker run -d --name dts-emulator -p 8080:8080 -p 8082:8082 mcr.microsoft.com/dts/dts-emulator:latest
echo "Waiting for Durable Task Scheduler Emulator to be ready"
timeout 30 bash -c 'until curl --silent http://localhost:8080/healthz; do sleep 1; done'
echo "Durable Task Scheduler Emulator is ready"
- name: Start Azurite (Azure Storage emulator)
shell: bash
run: |
if [ "$(docker ps -aq -f name=azurite)" ]; then
echo "Stopping and removing existing Azurite (Azure Storage emulator)"
docker rm -f azurite
fi
echo "Starting Azurite (Azure Storage emulator)"
docker run -d --name azurite -p 10000:10000 -p 10001:10001 -p 10002:10002 mcr.microsoft.com/azure-storage/azurite
echo "Waiting for Azurite (Azure Storage emulator) to be ready"
timeout 30 bash -c 'until curl --silent http://localhost:10000/devstoreaccount1; do sleep 1; done'
echo "Azurite (Azure Storage emulator) is ready"
- name: Install Azure Functions Core Tools
shell: bash
run: |
echo "Installing Azure Functions Core Tools"
npm install -g azure-functions-core-tools@4 --unsafe-perm true
func --version
+3 -8
View File
@@ -11,6 +11,9 @@ updates:
schedule:
interval: "cron"
cronjob: "0 8 * * 4,0" # Every Thursday(4) and Sunday(0) at 8:00 UTC
experimental:
nuget-native-updater: false
enable-cooldown-metrics-collection: false
ignore:
# For all System.* and Microsoft.Extensions/Bcl.* packages, ignore all major version updates
- dependency-name: "System.*"
@@ -25,14 +28,6 @@ updates:
- "dependencies"
# Maintain dependencies for python
- package-ecosystem: "pip"
directory: "python/"
schedule:
interval: "weekly"
day: "monday"
labels:
- "python"
- "dependencies"
- package-ecosystem: "uv"
directory: "python/"
schedule:
+3 -14
View File
@@ -8,11 +8,11 @@ name: dotnet-build-and-test
on:
workflow_dispatch:
pull_request:
branches: ["main", "feature*"]
branches: ["main"]
merge_group:
branches: ["main", "feature*"]
branches: ["main"]
push:
branches: ["main", "feature*"]
branches: ["main"]
schedule:
- cron: "0 0 * * *" # Run at midnight UTC daily
@@ -151,14 +151,6 @@ jobs:
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
# This setup action is required for both Durable Task and Azure Functions integration tests.
# We only run it on Ubuntu since the Durable Task and Azure Functions features are not available
# on .NET Framework (net472) which is what we use the Windows runner for.
- name: Set up Durable Task and Azure Functions Integration Test Emulators
if: github.event_name != 'pull_request' && matrix.integration-tests && matrix.os == 'ubuntu-latest'
uses: ./.github/actions/azure-functions-integration-setup
id: azure-functions-setup
- name: Run Integration Tests
shell: bash
if: github.event_name != 'pull_request' && matrix.integration-tests
@@ -180,9 +172,6 @@ jobs:
OpenAI__ApiKey: ${{ secrets.OPENAI__APIKEY }}
OpenAI__ChatModelId: ${{ vars.OPENAI__CHATMODELID }}
OpenAI__ChatReasoningModelId: ${{ vars.OPENAI__CHATREASONINGMODELID }}
# Azure OpenAI Models
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
# Azure AI Foundry
AzureAI__Endpoint: ${{ secrets.AZUREAI__ENDPOINT }}
AzureAI__DeploymentName: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
+1 -1
View File
@@ -7,7 +7,7 @@ name: dotnet-format
on:
workflow_dispatch:
pull_request:
branches: ["main", "feature*"]
branches: ["main"]
paths:
- dotnet/**
- '.github/workflows/dotnet-format.yml'
+1 -5
View File
@@ -28,8 +28,6 @@ jobs:
UV_PYTHON: ${{ matrix.python-version }}
steps:
- uses: actions/checkout@v5
with:
fetch-depth: 0
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
@@ -48,6 +46,4 @@ jobs:
with:
extra_args: --config python/.pre-commit-config.yaml --all-files
- name: Run Mypy
env:
GITHUB_BASE_REF: ${{ github.event.pull_request.base.ref || github.base_ref || 'main' }}
run: uv run poe ci-mypy
run: uv run poe mypy
-8
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@@ -66,11 +66,6 @@ jobs:
AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
# For Azure Functions integration tests
FUNCTIONS_WORKER_RUNTIME: "python"
DURABLE_TASK_SCHEDULER_CONNECTION_STRING: "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None"
AzureWebJobsStorage: "UseDevelopmentStorage=true"
defaults:
run:
working-directory: python
@@ -92,9 +87,6 @@ jobs:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Set up Azure Functions Integration Test Emulators
uses: ./.github/actions/azure-functions-integration-setup
id: azure-functions-setup
- name: Test with pytest
timeout-minutes: 10
run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --timeout 300 --retries 3 --retry-delay 10
@@ -39,7 +39,7 @@ jobs:
echo "PR_NUMBER=$PR_NUMBER" >> $GITHUB_ENV
- name: Pytest coverage comment
id: coverageComment
uses: MishaKav/pytest-coverage-comment@v1.1.59
uses: MishaKav/pytest-coverage-comment@v1.1.57
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
issue-number: ${{ env.PR_NUMBER }}
+1 -15
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@@ -204,20 +204,6 @@ agents.md
# AI
.claude/
WARP.md
**/memory-bank/
**/projectBrief.md
# Azurite storage emulator files
*/__azurite_db_blob__.json
*/__azurite_db_blob_extent__.json
*/__azurite_db_queue__.json
*/__azurite_db_queue_extent__.json
*/__azurite_db_table__.json
*/__blobstorage__/
*/__queuestorage__/
# Azure Functions local settings
local.settings.json
# Frontend
**/frontend/node_modules/
@@ -225,4 +211,4 @@ local.settings.json
**/frontend/dist/
# Database files
*.db
*.db
-3
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@@ -1,3 +0,0 @@
# Declarative Agents
This folder contains sample agent definitions than be ran using the declarative agent support, for python see the [declarative agent python sample folder](../python/samples/getting_started/declarative/).
-25
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@@ -1,25 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format. You must include Chat as the type in your response.
model:
id: =Env.AZURE_OPENAI_DEPLOYMENT_NAME
provider: AzureOpenAI
apiType: Chat
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
type:
kind: string
required: true
description: The type of the response.
@@ -1,25 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format. You must include Assistants as the type in your response.
model:
id: =Env.AZURE_OPENAI_DEPLOYMENT_NAME
provider: AzureOpenAI
apiType: Assistants
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
type:
kind: string
required: true
description: The type of the response.
@@ -1,28 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format. You must include Responses as the type in your response.
model:
id: =Env.AZURE_OPENAI_DEPLOYMENT_NAME
provider: AzureOpenAI
apiType: Responses
options:
text:
verbosity: medium
connection:
kind: remote
endpoint: =Env.AZURE_OPENAI_ENDPOINT
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
type:
kind: string
required: true
description: The type of the response.
-18
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@@ -1,18 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format.
model:
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
-27
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@@ -1,27 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions using the tools provided.
model:
options:
allowMultipleToolCalls: true
chatToolMode: auto
tools:
- kind: function
name: GetWeather
description: Get the weather for a given location.
bindings:
get_weather: get_weather
parameters:
properties:
location:
kind: string
description: The city and state, e.g. San Francisco, CA
required: true
unit:
kind: string
description: The unit of temperature. Possible values are 'celsius' and 'fahrenheit'.
required: false
enum:
- celsius
- fahrenheit
@@ -1,21 +0,0 @@
kind: Prompt
name: MicrosoftLearnAgent
description: Microsoft Learn Agent
instructions: You answer questions by searching the Microsoft Learn content only.
model:
id: =Env.AZURE_FOUNDRY_PROJECT_MODEL_ID
options:
temperature: 0.9
topP: 0.95
connection:
kind: remote
endpoint: =Env.AZURE_FOUNDRY_PROJECT_ENDPOINT
tools:
- kind: mcp
name: microsoft_learn
description: Get information from Microsoft Learn.
url: https://learn.microsoft.com/api/mcp
approvalMode:
kind: never
allowedTools:
- microsoft_docs_search
@@ -1,22 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format.
model:
id: =Env.AZURE_FOUNDRY_PROJECT_MODEL_ID
options:
temperature: 0.9
topP: 0.95
connection:
kind: remote
endpoint: =Env.AZURE_FOUNDRY_PROJECT_ENDPOINT
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
-28
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@@ -1,28 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format. You must include Chat as the type in your response.
model:
id: =Env.OPENAI_MODEL
provider: OpenAI
apiType: Chat
options:
temperature: 0.9
topP: 0.95
connection:
kind: key
key: =Env.OPENAI_API_KEY
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
type:
kind: string
required: true
description: The type of the response.
@@ -1,30 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format. You must include Assistants as the type in your response.
model:
id: =Env.OPENAI_MODEL
provider: OpenAI
apiType: Assistants
options:
temperature: 0.9
topP: 0.95
connection:
kind: key
key: =Env.OPENAI_APIKEY
outputSchema:
name: AssistantResponse
description: The response from the assistant.
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
type:
kind: string
required: true
description: The type of the response.
-28
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@@ -1,28 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions is the language specified by the user. You return your answers in a JSON format. You must include Responses as the type in your response.
model:
id: =Env.OPENAI_MODEL
provider: OpenAI
apiType: Responses
options:
text:
verbosity: medium
connection:
kind: key
key: =Env.OPENAI_APIKEY
outputSchema:
properties:
language:
kind: string
required: true
description: The language of the answer.
answer:
kind: string
required: true
description: The answer text.
type:
kind: string
required: true
description: The type of the response.
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+53 -70
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@@ -7,35 +7,34 @@
</PropertyGroup>
<PropertyGroup>
<!-- Aspire -->
<AspireAppHostSdkVersion>13.0.0</AspireAppHostSdkVersion>
<AspireAppHostSdkVersion>9.5.2</AspireAppHostSdkVersion>
</PropertyGroup>
<ItemGroup>
<!-- Aspire.* -->
<PackageVersion Include="Aspire.Azure.AI.OpenAI" Version="13.0.0-preview.1.25560.3" />
<PackageVersion Include="Aspire.Azure.AI.OpenAI" Version="9.5.1-preview.1.25502.11" />
<PackageVersion Include="Aspire.Hosting.AppHost" Version="$(AspireAppHostSdkVersion)" />
<PackageVersion Include="Aspire.Hosting.Azure.CognitiveServices" Version="$(AspireAppHostSdkVersion)" />
<PackageVersion Include="Aspire.Microsoft.Azure.Cosmos" Version="$(AspireAppHostSdkVersion)" />
<PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="13.0.0-beta.440" />
<PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="9.9.0" />
<!-- Azure.* -->
<PackageVersion Include="Azure.AI.Projects" Version="1.2.0-beta.3" />
<PackageVersion Include="Azure.AI.Projects.OpenAI" Version="1.0.0-beta.3" />
<PackageVersion Include="Azure.AI.Agents" Version="2.0.0-alpha.20251104.7" />
<PackageVersion Include="Azure.AI.Agents.Persistent" Version="1.2.0-beta.7" />
<PackageVersion Include="Azure.AI.OpenAI" Version="2.5.0-beta.1" />
<PackageVersion Include="Azure.Identity" Version="1.17.0" />
<PackageVersion Include="Azure.Monitor.OpenTelemetry.Exporter" Version="1.4.0" />
<!-- System.* -->
<PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.0" />
<PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="9.0.10" />
<PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
<PackageVersion Include="System.ClientModel" Version="1.8.0" />
<PackageVersion Include="System.CodeDom" Version="10.0.0" />
<PackageVersion Include="System.Collections.Immutable" Version="10.0.0" />
<PackageVersion Include="System.ClientModel" Version="1.7.0" />
<PackageVersion Include="System.CodeDom" Version="9.0.10" />
<PackageVersion Include="System.Collections.Immutable" Version="9.0.10" />
<PackageVersion Include="System.CommandLine" Version="2.0.0-rc.2.25502.107" />
<PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.0" />
<PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.0" />
<PackageVersion Include="System.Net.Http.Json" Version="10.0.0" />
<PackageVersion Include="System.Net.ServerSentEvents" Version="10.0.0" />
<PackageVersion Include="System.Text.Json" Version="10.0.0" />
<PackageVersion Include="System.Threading.Channels" Version="10.0.0" />
<PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="9.0.10" />
<PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.0-rc.2.25502.107" />
<PackageVersion Include="System.Net.Http.Json" Version="9.0.10" />
<PackageVersion Include="System.Net.ServerSentEvents" Version="9.0.10" />
<PackageVersion Include="System.Text.Json" Version="9.0.10" />
<PackageVersion Include="System.Threading.Channels" Version="9.0.10" />
<PackageVersion Include="System.Threading.Tasks.Extensions" Version="4.6.3" />
<!-- OpenTelemetry -->
<PackageVersion Include="OpenTelemetry" Version="1.13.1" />
@@ -46,45 +45,41 @@
<PackageVersion Include="OpenTelemetry.Extensions.Hosting" Version="1.13.1" />
<PackageVersion Include="OpenTelemetry.Instrumentation.AspNetCore" Version="1.13.0" />
<PackageVersion Include="OpenTelemetry.Instrumentation.Http" Version="1.13.0" />
<PackageVersion Include="OpenTelemetry.Instrumentation.Runtime" Version="1.13.0" />
<PackageVersion Include="OpenTelemetry.Instrumentation.Runtime" Version="1.12.0" />
<!-- Microsoft.AspNetCore.* -->
<PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="9.0.11" />
<PackageVersion Include="Swashbuckle.AspNetCore.SwaggerUI" Version="10.0.0" />
<PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="9.0.10" />
<PackageVersion Include="Swashbuckle.AspNetCore.SwaggerUI" Version="9.0.4" />
<!-- Microsoft.Extensions.* -->
<PackageVersion Include="Microsoft.Extensions.AI" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.AI.AzureAIInference" Version="10.0.0-preview.1.25559.3" />
<PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.0.0-preview.1.25559.3" />
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<PackageVersion Include="Microsoft.Extensions.ServiceDiscovery" Version="$(AspireAppHostSdkVersion)" />
<PackageVersion Include="Microsoft.Extensions.VectorData.Abstractions" Version="9.7.0" />
<!-- Vector Stores -->
<PackageVersion Include="Microsoft.SemanticKernel.Connectors.InMemory" Version="1.67.0-preview" />
<PackageVersion Include="Microsoft.SemanticKernel.Connectors.Qdrant" Version="1.67.0-preview" />
<!-- Semantic Kernel -->
<PackageVersion Include="Microsoft.SemanticKernel" Version="1.67.0" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.Core" Version="1.67.0" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.OpenAI" Version="1.67.0-preview" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.AzureAI" Version="1.67.0-preview" />
<PackageVersion Include="Microsoft.SemanticKernel.Plugins.OpenApi" Version="1.67.0" />
<PackageVersion Include="Microsoft.SemanticKernel" Version="1.66.0" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.Core" Version="1.66.0" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.OpenAI" Version="1.66.0-preview" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.AzureAI" Version="1.66.0-preview" />
<PackageVersion Include="Microsoft.SemanticKernel.Plugins.OpenApi" Version="1.66.0" />
<!-- Vector Stores -->
<PackageVersion Include="Microsoft.SemanticKernel.Connectors.InMemory" Version="1.66.0-preview" />
<PackageVersion Include="Microsoft.SemanticKernel.Connectors.Qdrant" Version="1.66.0-preview" />
<!-- Agent SDKs -->
<PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.2.41" />
<!-- M365 Agents SDK -->
<PackageVersion Include="AdaptiveCards" Version="3.1.0" />
<PackageVersion Include="Microsoft.Agents.Authentication.Msal" Version="1.2.41" />
<PackageVersion Include="Microsoft.Agents.Hosting.AspNetCore" Version="1.2.41" />
<!-- A2A -->
<PackageVersion Include="A2A" Version="0.3.3-preview" />
<PackageVersion Include="A2A.AspNetCore" Version="0.3.3-preview" />
@@ -92,38 +87,26 @@
<PackageVersion Include="ModelContextProtocol" Version="0.4.0-preview.3" />
<!-- Inference SDKs -->
<PackageVersion Include="Anthropic.SDK" Version="5.8.0" />
<PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.4.6" />
<PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.4.2" />
<PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.10.0" />
<PackageVersion Include="OllamaSharp" Version="5.4.8" />
<PackageVersion Include="OpenAI" Version="2.6.0" />
<!-- Identity -->
<PackageVersion Include="Microsoft.Identity.Client.Extensions.Msal" Version="4.78.0" />
<!-- Workflows -->
<PackageVersion Include="Microsoft.Bot.ObjectModel" Version="1.2025.1106.1" />
<PackageVersion Include="Microsoft.Bot.ObjectModel.Json" Version="1.2025.1106.1" />
<PackageVersion Include="Microsoft.Bot.ObjectModel.PowerFx" Version="1.2025.1106.1" />
<PackageVersion Include="Microsoft.PowerFx.Interpreter" Version="1.5.0-build.20251008-1002" />
<!-- Durable Task -->
<PackageVersion Include="Microsoft.DurableTask.Client" Version="1.16.2" />
<PackageVersion Include="Microsoft.DurableTask.Client.AzureManaged" Version="1.16.2-preview.1" />
<PackageVersion Include="Microsoft.DurableTask.Worker" Version="1.16.2" />
<PackageVersion Include="Microsoft.DurableTask.Worker.AzureManaged" Version="1.16.2-preview.1" />
<!-- Azure Functions -->
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<PackageVersion Include="Microsoft.Azure.Functions.Worker.ApplicationInsights" Version="2.50.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" Version="1.9.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" Version="1.0.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Http" Version="3.3.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" Version="2.1.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Mcp" Version="1.0.0" />
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Sdk" Version="2.0.7" />
<PackageVersion Include="Microsoft.Bot.ObjectModel" Version="1.2025.1003.2" />
<PackageVersion Include="Microsoft.Bot.ObjectModel.Json" Version="1.2025.1003.2" />
<PackageVersion Include="Microsoft.Bot.ObjectModel.PowerFx" Version="1.2025.1003.2" />
<PackageVersion Include="Microsoft.PowerFx.Interpreter" Version="1.4.0" />
<!-- Community -->
<PackageVersion Include="System.Linq.Async" Version="6.0.3" />
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<PackageVersion Include="FluentAssertions" Version="8.8.0" />
<PackageVersion Include="Microsoft.AspNetCore.TestHost" Version="9.0.11" />
<PackageVersion Include="Microsoft.AspNetCore.TestHost" Version="9.0.10" />
<PackageVersion Include="Microsoft.NET.Test.Sdk" Version="18.0.0" />
<PackageVersion Include="Moq" Version="[4.18.4]" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.Abstractions" Version="1.66.0" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.Yaml" Version="1.66.0-beta" />
<PackageVersion Include="xunit" Version="2.9.3" />
<PackageVersion Include="xunit.abstractions" Version="2.0.3" />
<PackageVersion Include="xunit.runner.visualstudio" Version="3.1.3" />
@@ -133,7 +116,7 @@
<PackageVersion Include="Microsoft.SourceLink.GitHub" Version="8.0.0" />
<!-- Toolset -->
<PackageVersion Include="Microsoft.CodeAnalysis.CSharp" Version="4.14.0" />
<PackageVersion Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100" />
<PackageVersion Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="9.0.0" />
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
@@ -153,7 +136,7 @@
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageVersion Include="Roslynator.Analyzers" Version="[4.14.1]" />
<PackageVersion Include="Roslynator.Analyzers" Version="[4.14.0]" />
<PackageReference Include="Roslynator.Analyzers">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+32 -80
View File
@@ -20,20 +20,8 @@
</Folder>
<Folder Name="/Samples/AGUIClientServer/">
<Project Path="samples/AGUIClientServer/AGUIClient/AGUIClient.csproj" />
<Project Path="samples/AGUIClientServer/AGUIDojoServer/AGUIDojoServer.csproj" />
<Project Path="samples/AGUIClientServer/AGUIServer/AGUIServer.csproj" />
</Folder>
<Folder Name="/Samples/AzureFunctions/">
<File Path="samples/AzureFunctions/.editorconfig" />
<File Path="samples/AzureFunctions/README.md" />
<Project Path="samples/AzureFunctions/01_SingleAgent/01_SingleAgent.csproj" />
<Project Path="samples/AzureFunctions/02_AgentOrchestration_Chaining/02_AgentOrchestration_Chaining.csproj" />
<Project Path="samples/AzureFunctions/03_AgentOrchestration_Concurrency/03_AgentOrchestration_Concurrency.csproj" />
<Project Path="samples/AzureFunctions/04_AgentOrchestration_Conditionals/04_AgentOrchestration_Conditionals.csproj" />
<Project Path="samples/AzureFunctions/05_AgentOrchestration_HITL/05_AgentOrchestration_HITL.csproj" />
<Project Path="samples/AzureFunctions/06_LongRunningTools/06_LongRunningTools.csproj" />
<Project Path="samples/AzureFunctions/07_AgentAsMcpTool/07_AgentAsMcpTool.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/">
<File Path="samples/GettingStarted/README.md" />
</Folder>
@@ -44,8 +32,7 @@
<Folder Name="/Samples/GettingStarted/AgentProviders/">
<File Path="samples/GettingStarted/AgentProviders/README.md" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_A2A/Agent_With_A2A.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgentsPersistent/Agent_With_AzureAIAgentsPersistent.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIProject/Agent_With_AzureAIProject.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureFoundryAgent/Agent_With_AzureFoundryAgent.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureFoundryModel/Agent_With_AzureFoundryModel.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureOpenAIChatCompletion/Agent_With_AzureOpenAIChatCompletion.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureOpenAIResponses/Agent_With_AzureOpenAIResponses.csproj" />
@@ -56,11 +43,29 @@
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_OpenAIChatCompletion/Agent_With_OpenAIChatCompletion.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_OpenAIResponses/Agent_With_OpenAIResponses.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AgentProviders/AzureAIAgents/">
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step01.1_Basics/AzureAIAgents_Step01.1_Basics.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step01.2_Running/AzureAIAgents_Step01.2_Running.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step02_MultiturnConversation/AzureAIAgents_Step02_MultiturnConversation.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step03.1_UsingFunctionTools/AzureAIAgents_Step03.1_UsingFunctionTools.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step03.2_UsingFunctionTools_FromOpenAPI/AzureAIAgents_Step03.2_UsingFunctionTools_FromOpenAPI.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step04_UsingFunctionToolsWithApprovals/AzureAIAgents_Step04_UsingFunctionToolsWithApprovals.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step05_StructuredOutput/AzureAIAgents_Step05_StructuredOutput.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step06_PersistedConversations/AzureAIAgents_Step06_PersistedConversations.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step07_Observability/AzureAIAgents_Step07_Observability.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step08_DependencyInjection/AzureAIAgents_Step08_DependencyInjection.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step09_AsMcpTool/AzureAIAgents_Step09_AsMcpTool.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step10_UsingImages/AzureAIAgents_Step10_UsingImages.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step11_AsFunctionTool/AzureAIAgents_Step11_AsFunctionTool.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step12_Middleware/AzureAIAgents_Step12_Middleware.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step13_Plugins/AzureAIAgents_Step13_Plugins.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/Agents/">
<File Path="samples/GettingStarted/Agents/README.md" />
<Project Path="samples/GettingStarted/Agents/Agent_Step01_Running/Agent_Step01_Running.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step02_MultiturnConversation/Agent_Step02_MultiturnConversation.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step03_UsingFunctionTools/Agent_Step03_UsingFunctionTools.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step03.1_UsingFunctionTools/Agent_Step03.1_UsingFunctionTools.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step03.2_UsingFunctionTools_FromOpenAPI/Agent_Step03.2_UsingFunctionTools_FromOpenAPI.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step04_UsingFunctionToolsWithApprovals/Agent_Step04_UsingFunctionToolsWithApprovals.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step05_StructuredOutput/Agent_Step05_StructuredOutput.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step06_PersistedConversations/Agent_Step06_PersistedConversations.csproj" />
@@ -70,57 +75,27 @@
<Project Path="samples/GettingStarted/Agents/Agent_Step10_AsMcpTool/Agent_Step10_AsMcpTool.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step11_UsingImages/Agent_Step11_UsingImages.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step12_AsFunctionTool/Agent_Step12_AsFunctionTool.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step13_BackgroundResponsesWithToolsAndPersistence/Agent_Step13_BackgroundResponsesWithToolsAndPersistence.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step13_Memory/Agent_Step13_Memory.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step14_Middleware/Agent_Step14_Middleware.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step15_Plugins/Agent_Step15_Plugins.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step16_ChatReduction/Agent_Step16_ChatReduction.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step17_BackgroundResponses/Agent_Step17_BackgroundResponses.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step18_DeepResearch/Agent_Step18_DeepResearch.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step18_TextSearchRag/Agent_Step18_TextSearchRag.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step19_Mem0Provider/Agent_Step19_Mem0Provider.csproj" />
<Project Path="samples/GettingStarted/Agents/Agent_Step20_BackgroundResponsesWithToolsAndPersistence/Agent_Step20_BackgroundResponsesWithToolsAndPersistence.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/DevUI/">
<File Path="samples/GettingStarted/DevUI/README.md" />
<Project Path="samples/GettingStarted/DevUI/DevUI_Step01_BasicUsage/DevUI_Step01_BasicUsage.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AgentWithMemory/">
<File Path="samples/GettingStarted/AgentWithMemory/README.md" />
<Project Path="samples/GettingStarted/AgentWithMemory/AgentWithMemory_Step01_ChatHistoryMemory/AgentWithMemory_Step01_ChatHistoryMemory.csproj" />
<Project Path="samples/GettingStarted/AgentWithMemory/AgentWithMemory_Step02_MemoryUsingMem0/AgentWithMemory_Step02_MemoryUsingMem0.csproj" />
<Project Path="samples/GettingStarted/AgentWithMemory/AgentWithMemory_Step03_CustomMemory/AgentWithMemory_Step03_CustomMemory.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AgentWithOpenAI/">
<File Path="samples/GettingStarted/AgentWithOpenAI/README.md" />
<Project Path="samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step01_Running/Agent_OpenAI_Step01_Running.csproj" />
<Project Path="samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step02_Reasoning/Agent_OpenAI_Step02_Reasoning.csproj" />
</Folder>
<Folder Name="/Samples/Purview/" />
<Folder Name="/Samples/Purview/AgentWithPurview/">
<Project Path="samples/Purview/AgentWithPurview/AgentWithPurview.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/AgentWithRAG/">
<File Path="samples/GettingStarted/AgentWithRAG/README.md" />
<Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step01_BasicTextRAG/AgentWithRAG_Step01_BasicTextRAG.csproj" />
<Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step02_CustomVectorStoreRAG/AgentWithRAG_Step02_CustomVectorStoreRAG.csproj" />
<Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step03_CustomRAGDataSource/AgentWithRAG_Step03_CustomRAGDataSource.csproj" />
<Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step04_FoundryServiceRAG/AgentWithRAG_Step04_FoundryServiceRAG.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/FoundryAgents/">
<File Path="samples/GettingStarted/FoundryAgents/README.md" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step01.1_Basics/FoundryAgents_Step01.1_Basics.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step01.2_Running/FoundryAgents_Step01.2_Running.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step02_MultiturnConversation/FoundryAgents_Step02_MultiturnConversation.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step03_UsingFunctionTools/FoundryAgents_Step03_UsingFunctionTools.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step04_UsingFunctionToolsWithApprovals/FoundryAgents_Step04_UsingFunctionToolsWithApprovals.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step05_StructuredOutput/FoundryAgents_Step05_StructuredOutput.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step06_PersistedConversations/FoundryAgents_Step06_PersistedConversations.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step07_Observability/FoundryAgents_Step07_Observability.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step08_DependencyInjection/FoundryAgents_Step08_DependencyInjection.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step09_UsingMcpClientAsTools/FoundryAgents_Step09_UsingMcpClientAsTools.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step10_UsingImages/FoundryAgents_Step10_UsingImages.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step11_AsFunctionTool/FoundryAgents_Step11_AsFunctionTool.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step12_Middleware/FoundryAgents_Step12_Middleware.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step13_Plugins/FoundryAgents_Step13_Plugins.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step14_CodeInterpreter/FoundryAgents_Step14_CodeInterpreter.csproj" />
<Project Path="samples/GettingStarted/FoundryAgents/FoundryAgents_Step15_ComputerUse/FoundryAgents_Step15_ComputerUse.csproj" />
<Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step02_ExternalDataSourceRAG/AgentWithRAG_Step02_ExternalDataSourceRAG.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/ModelContextProtocol/">
<File Path="samples/GettingStarted/ModelContextProtocol/README.md" />
@@ -146,22 +121,13 @@
</Folder>
<Folder Name="/Samples/GettingStarted/Workflows/Declarative/">
<File Path="samples/GettingStarted/Workflows/Declarative/README.md" />
<Project Path="samples/GettingStarted/Workflows/Declarative/ConfirmInput/ConfirmInput.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/CustomerSupport/CustomerSupport.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/DeepResearch/DeepResearch.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/ExecuteCode/ExecuteCode.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/ExecuteWorkflow/ExecuteWorkflow.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/FunctionTools/FunctionTools.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/GenerateCode/GenerateCode.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/HostedWorkflow/HostedWorkflow.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/InputArguments/InputArguments.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/Marketing/Marketing.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/StudentTeacher/StudentTeacher.csproj" />
<Project Path="samples/GettingStarted/Workflows/Declarative/ToolApproval/ToolApproval.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/Workflows/Declarative/Examples/">
<File Path="../workflow-samples/ConfirmInput.yaml" />
<File Path="../workflow-samples/DeepResearch.yaml" />
<File Path="../workflow-samples/HumanInLoop.yaml" />
<File Path="../workflow-samples/Marketing.yaml" />
<File Path="../workflow-samples/MathChat.yaml" />
<File Path="../workflow-samples/README.md" />
@@ -192,7 +158,7 @@
<Project Path="samples/GettingStarted/Workflows/Observability/WorkflowAsAnAgent/WorkflowAsAnAgentObservability.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/Workflows/Visualization/">
<Project Path="samples/GettingStarted/Workflows/Visualization/Visualization.csproj" />
<Project Path="samples/GettingStarted/Workflows/Visualization/Visualization.csproj" Id="99bf0bc6-2440-428e-b3e7-d880e4b7a5fd" />
</Folder>
<Folder Name="/Samples/GettingStarted/Workflows/_Foundational/">
<Project Path="samples/GettingStarted/Workflows/_Foundational/01_ExecutorsAndEdges/01_ExecutorsAndEdges.csproj" />
@@ -204,13 +170,10 @@
<Project Path="samples/GettingStarted/Workflows/_Foundational/07_MixedWorkflowAgentsAndExecutors/07_MixedWorkflowAgentsAndExecutors.csproj" />
<Project Path="samples/GettingStarted/Workflows/_Foundational/08_WriterCriticWorkflow/08_WriterCriticWorkflow.csproj" />
</Folder>
<Folder Name="/Samples/HostedAgents/">
<Project Path="samples/HostedAgents/AgentsInWorkflows/AgentsInWorkflows.csproj" />
<Project Path="samples/HostedAgents/AgentWithHostedMCP/AgentWithHostedMCP.csproj" />
<Project Path="samples/HostedAgents/AgentWithTextSearchRag/AgentWithTextSearchRag.csproj" />
</Folder>
<Folder Name="/Samples/M365Agent/">
<Project Path="samples/M365Agent/M365Agent.csproj" />
<Folder Name="/Samples/Catalog/">
<Project Path="samples/Catalog/AgentsInWorkflows/AgentsInWorkflows.csproj" />
<Project Path="samples/Catalog/AgentWithTextSearchRag/AgentWithTextSearchRag.csproj" />
<Project Path="samples/Catalog/DeepResearchAgent/DeepResearchAgent.csproj" />
</Folder>
<Folder Name="/Solution Items/">
<File Path=".editorconfig" />
@@ -339,17 +302,13 @@
<Project Path="src/Microsoft.Agents.AI.AzureAI/Microsoft.Agents.AI.AzureAI.csproj" />
<Project Path="src/Microsoft.Agents.AI.CopilotStudio/Microsoft.Agents.AI.CopilotStudio.csproj" />
<Project Path="src/Microsoft.Agents.AI.DevUI/Microsoft.Agents.AI.DevUI.csproj" />
<Project Path="src/Microsoft.Agents.AI.DurableTask/Microsoft.Agents.AI.DurableTask.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting.A2A.AspNetCore/Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting.A2A/Microsoft.Agents.AI.Hosting.A2A.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting.AzureFunctions/Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting.OpenAI/Microsoft.Agents.AI.Hosting.OpenAI.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting/Microsoft.Agents.AI.Hosting.csproj" />
<Project Path="src/Microsoft.Agents.AI.Mem0/Microsoft.Agents.AI.Mem0.csproj" />
<Project Path="src/Microsoft.Agents.AI.OpenAI/Microsoft.Agents.AI.OpenAI.csproj" />
<Project Path="src/Microsoft.Agents.AI.Purview/Microsoft.Agents.AI.Purview.csproj" />
<Project Path="src/Microsoft.Agents.AI.Workflows.Declarative.AzureAI/Microsoft.Agents.AI.Workflows.Declarative.AzureAI.csproj" />
<Project Path="src/Microsoft.Agents.AI.Workflows.Declarative/Microsoft.Agents.AI.Workflows.Declarative.csproj" />
<Project Path="src/Microsoft.Agents.AI.Workflows/Microsoft.Agents.AI.Workflows.csproj" />
<Project Path="src/Microsoft.Agents.AI/Microsoft.Agents.AI.csproj" />
@@ -357,12 +316,9 @@
<Folder Name="/Tests/" />
<Folder Name="/Tests/IntegrationTests/">
<Project Path="tests/AgentConformance.IntegrationTests/AgentConformance.IntegrationTests.csproj" />
<Project Path="tests/AzureAI.IntegrationTests/AzureAI.IntegrationTests.csproj" />
<Project Path="tests/AzureAIAgentsPersistent.IntegrationTests/AzureAIAgentsPersistent.IntegrationTests.csproj" />
<Project Path="tests/CopilotStudio.IntegrationTests/CopilotStudio.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.DurableTask.IntegrationTests/Microsoft.Agents.AI.DurableTask.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Mem0.IntegrationTests/Microsoft.Agents.AI.Mem0.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Workflows.Declarative.IntegrationTests/Microsoft.Agents.AI.Workflows.Declarative.IntegrationTests.csproj" />
<Project Path="tests/OpenAIAssistant.IntegrationTests/OpenAIAssistant.IntegrationTests.csproj" />
@@ -375,16 +331,12 @@
<Project Path="tests/Microsoft.Agents.AI.AGUI.UnitTests/Microsoft.Agents.AI.AGUI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.AzureAI.UnitTests/Microsoft.Agents.AI.AzureAI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.DevUI.UnitTests/Microsoft.Agents.AI.DevUI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.DurableTask.UnitTests/Microsoft.Agents.AI.DurableTask.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.A2A.UnitTests/Microsoft.Agents.AI.Hosting.A2A.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.A2A.Tests/Microsoft.Agents.AI.Hosting.A2A.Tests.csproj" Id="2a1c544d-237d-4436-8732-ba0c447ac06b" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AzureFunctions.UnitTests/Microsoft.Agents.AI.Hosting.AzureFunctions.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.OpenAI.UnitTests/Microsoft.Agents.AI.Hosting.OpenAI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.UnitTests/Microsoft.Agents.AI.Hosting.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Mem0.UnitTests/Microsoft.Agents.AI.Mem0.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.OpenAI.UnitTests/Microsoft.Agents.AI.OpenAI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Purview.UnitTests/Microsoft.Agents.AI.Purview.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.UnitTests/Microsoft.Agents.AI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Workflows.UnitTests/Microsoft.Agents.AI.Workflows.UnitTests.csproj" />
-9
View File
@@ -11,13 +11,4 @@
<ItemGroup Condition="'$(InjectSharedBuildTestCode)' == 'true'">
<Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\CodeTests\*.cs" LinkBase="Shared\CodeTests" />
</ItemGroup>
<ItemGroup Condition="'$(InjectSharedWorkflowsExecution)' == 'true'">
<Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\Workflows\Execution\*.cs" LinkBase="Shared\Workflows" />
</ItemGroup>
<ItemGroup Condition="'$(InjectSharedWorkflowsSettings)' == 'true'">
<Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\Workflows\Settings\*.cs" LinkBase="Shared\Workflows" />
</ItemGroup>
<ItemGroup Condition="'$(InjectSharedFoundryAgents)' == 'true'">
<Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\Foundry\Agents\*.cs" LinkBase="Shared\Foundry" />
</ItemGroup>
</Project>
+4
View File
@@ -3,10 +3,14 @@
<packageSources>
<clear />
<add key="nuget.org" value="https://api.nuget.org/v3/index.json" />
<add key="azure-sdk-for-net" value="https://pkgs.dev.azure.com/azure-sdk/public/_packaging/azure-sdk-for-net/nuget/v3/index.json" />
</packageSources>
<packageSourceMapping>
<packageSource key="nuget.org">
<package pattern="*" />
</packageSource>
<packageSource key="azure-sdk-for-net">
<package pattern="Azure.AI.Agents" />
</packageSource>
</packageSourceMapping>
</configuration>
+3 -3
View File
@@ -2,9 +2,9 @@
<PropertyGroup>
<!-- Central version prefix - applies to all nuget packages. -->
<VersionPrefix>1.0.0</VersionPrefix>
<PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).251114.1</PackageVersion>
<PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.251114.1</PackageVersion>
<GitTag>1.0.0-preview.251114.1</GitTag>
<PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).251105.1</PackageVersion>
<PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.251105.1</PackageVersion>
<GitTag>1.0.0-preview.251105.1</GitTag>
<Configurations>Debug;Release;Publish</Configurations>
<IsPackable>true</IsPackable>
@@ -16,7 +16,6 @@
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AGUI\Microsoft.Agents.AI.AGUI.csproj" />
</ItemGroup>
@@ -1,12 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to use the AG-UI client to connect to a remote AG-UI server
// and display streaming updates including conversation/response metadata, text content, and errors.
using System.Text.Json.Serialization;
namespace AGUIClient;
[JsonSerializable(typeof(SensorRequest))]
[JsonSerializable(typeof(SensorResponse))]
internal sealed partial class AGUIClientSerializerContext : JsonSerializerContext;
@@ -4,9 +4,7 @@
// and display streaming updates including conversation/response metadata, text content, and errors.
using System.CommandLine;
using System.ComponentModel;
using System.Reflection;
using System.Text;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.AGUI;
using Microsoft.Extensions.AI;
@@ -53,40 +51,11 @@ public static class Program
Timeout = TimeSpan.FromSeconds(60)
};
var changeBackground = AIFunctionFactory.Create(
() =>
{
Console.ForegroundColor = ConsoleColor.DarkBlue;
Console.WriteLine("Changing color to blue");
},
name: "change_background_color",
description: "Change the console background color to dark blue."
);
var readClientClimateSensors = AIFunctionFactory.Create(
([Description("The sensors measurements to include in the response")] SensorRequest request) =>
{
return new SensorResponse()
{
Temperature = 22.5,
Humidity = 45.0,
AirQualityIndex = 75
};
},
name: "read_client_climate_sensors",
description: "Reads the climate sensor data from the client device.",
serializerOptions: AGUIClientSerializerContext.Default.Options
);
var chatClient = new AGUIChatClient(
httpClient,
serverUrl,
jsonSerializerOptions: AGUIClientSerializerContext.Default.Options);
AIAgent agent = chatClient.CreateAIAgent(
name: "agui-client",
AGUIAgent agent = new(
id: "agui-client",
description: "AG-UI Client Agent",
tools: [changeBackground, readClientClimateSensors]);
httpClient: httpClient,
endpoint: serverUrl);
AgentThread thread = agent.GetNewThread();
List<ChatMessage> messages = [new(ChatRole.System, "You are a helpful assistant.")];
@@ -113,12 +82,10 @@ public static class Program
// Call RunStreamingAsync to get streaming updates
bool isFirstUpdate = true;
string? threadId = null;
var updates = new List<ChatResponseUpdate>();
await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: cancellationToken))
{
// Use AsChatResponseUpdate to access ChatResponseUpdate properties
ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
updates.Add(chatUpdate);
if (chatUpdate.ConversationId != null)
{
threadId = chatUpdate.ConversationId;
@@ -144,25 +111,6 @@ public static class Program
Console.ResetColor();
break;
case FunctionCallContent functionCallContent:
Console.ForegroundColor = ConsoleColor.Green;
Console.WriteLine($"\n[Function Call - Name: {functionCallContent.Name}, Arguments: {PrintArguments(functionCallContent.Arguments)}]");
Console.ResetColor();
break;
case FunctionResultContent functionResultContent:
Console.ForegroundColor = ConsoleColor.Magenta;
if (functionResultContent.Exception != null)
{
Console.WriteLine($"\n[Function Result - Exception: {functionResultContent.Exception}]");
}
else
{
Console.WriteLine($"\n[Function Result - Result: {functionResultContent.Result}]");
}
Console.ResetColor();
break;
case ErrorContent errorContent:
Console.ForegroundColor = ConsoleColor.Red;
string code = errorContent.AdditionalProperties?["Code"] as string ?? "Unknown";
@@ -172,14 +120,6 @@ public static class Program
}
}
}
if (updates.Count > 0 && !updates[^1].Contents.Any(c => c is TextContent))
{
var lastUpdate = updates[^1];
Console.ForegroundColor = ConsoleColor.Yellow;
Console.WriteLine();
Console.WriteLine($"[Run Ended - Thread: {threadId}, Run: {lastUpdate.ResponseId}]");
Console.ResetColor();
}
messages.Clear();
Console.WriteLine();
}
@@ -194,20 +134,4 @@ public static class Program
return;
}
}
private static string PrintArguments(IDictionary<string, object?>? arguments)
{
if (arguments == null)
{
return "";
}
var builder = new StringBuilder();
builder.AppendLine();
foreach (var kvp in arguments)
{
builder.AppendLine($" Name: {kvp.Key}");
builder.AppendLine($" Value: {kvp.Value}");
}
return builder.ToString();
}
}
@@ -1,13 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to use the AG-UI client to connect to a remote AG-UI server
// and display streaming updates including conversation/response metadata, text content, and errors.
namespace AGUIClient;
internal sealed class SensorRequest
{
public bool IncludeTemperature { get; set; } = true;
public bool IncludeHumidity { get; set; } = true;
public bool IncludeAirQualityIndex { get; set; } = true;
}
@@ -1,13 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to use the AG-UI client to connect to a remote AG-UI server
// and display streaming updates including conversation/response metadata, text content, and errors.
namespace AGUIClient;
internal sealed class SensorResponse
{
public double Temperature { get; set; }
public double Humidity { get; set; }
public int AirQualityIndex { get; set; }
}
@@ -1,24 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk.Web">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>b9c3f1e1-2fb4-5g29-0e52-53e2b7g9gf21</UserSecretsId>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AGUI\Microsoft.Agents.AI.AGUI.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
</ItemGroup>
</Project>
@@ -1,11 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIDojoServer;
[JsonSerializable(typeof(WeatherInfo))]
[JsonSerializable(typeof(Recipe))]
[JsonSerializable(typeof(Ingredient))]
[JsonSerializable(typeof(RecipeResponse))]
internal sealed partial class AGUIDojoServerSerializerContext : JsonSerializerContext;
@@ -1,98 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.ComponentModel;
using System.Text.Json;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using ChatClient = OpenAI.Chat.ChatClient;
namespace AGUIDojoServer;
internal static class ChatClientAgentFactory
{
private static AzureOpenAIClient? s_azureOpenAIClient;
private static string? s_deploymentName;
public static void Initialize(IConfiguration configuration)
{
string endpoint = configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
s_deploymentName = configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");
s_azureOpenAIClient = new AzureOpenAIClient(
new Uri(endpoint),
new DefaultAzureCredential());
}
public static ChatClientAgent CreateAgenticChat()
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
return chatClient.AsIChatClient().CreateAIAgent(
name: "AgenticChat",
description: "A simple chat agent using Azure OpenAI");
}
public static ChatClientAgent CreateBackendToolRendering()
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
return chatClient.AsIChatClient().CreateAIAgent(
name: "BackendToolRenderer",
description: "An agent that can render backend tools using Azure OpenAI",
tools: [AIFunctionFactory.Create(
GetWeather,
name: "get_weather",
description: "Get the weather for a given location.",
AGUIDojoServerSerializerContext.Default.Options)]);
}
public static ChatClientAgent CreateHumanInTheLoop()
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
return chatClient.AsIChatClient().CreateAIAgent(
name: "HumanInTheLoopAgent",
description: "An agent that involves human feedback in its decision-making process using Azure OpenAI");
}
public static ChatClientAgent CreateToolBasedGenerativeUI()
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
return chatClient.AsIChatClient().CreateAIAgent(
name: "ToolBasedGenerativeUIAgent",
description: "An agent that uses tools to generate user interfaces using Azure OpenAI");
}
public static ChatClientAgent CreateAgenticUI()
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
return chatClient.AsIChatClient().CreateAIAgent(
name: "AgenticUIAgent",
description: "An agent that generates agentic user interfaces using Azure OpenAI");
}
public static AIAgent CreateSharedState(JsonSerializerOptions options)
{
ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
var baseAgent = chatClient.AsIChatClient().CreateAIAgent(
name: "SharedStateAgent",
description: "An agent that demonstrates shared state patterns using Azure OpenAI");
return new SharedStateAgent(baseAgent, options);
}
[Description("Get the weather for a given location.")]
private static WeatherInfo GetWeather([Description("The location to get the weather for.")] string location) => new()
{
Temperature = 20,
Conditions = "sunny",
Humidity = 50,
WindSpeed = 10,
FeelsLike = 25
};
}
@@ -1,17 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIDojoServer;
internal sealed class Ingredient
{
[JsonPropertyName("icon")]
public string Icon { get; set; } = string.Empty;
[JsonPropertyName("name")]
public string Name { get; set; } = string.Empty;
[JsonPropertyName("amount")]
public string Amount { get; set; } = string.Empty;
}
@@ -1,45 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using AGUIDojoServer;
using Microsoft.Agents.AI.Hosting.AGUI.AspNetCore;
using Microsoft.AspNetCore.HttpLogging;
using Microsoft.Extensions.Options;
WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
builder.Services.AddHttpLogging(logging =>
{
logging.LoggingFields = HttpLoggingFields.RequestPropertiesAndHeaders | HttpLoggingFields.RequestBody
| HttpLoggingFields.ResponsePropertiesAndHeaders | HttpLoggingFields.ResponseBody;
logging.RequestBodyLogLimit = int.MaxValue;
logging.ResponseBodyLogLimit = int.MaxValue;
});
builder.Services.AddHttpClient().AddLogging();
builder.Services.ConfigureHttpJsonOptions(options => options.SerializerOptions.TypeInfoResolverChain.Add(AGUIDojoServerSerializerContext.Default));
builder.Services.AddAGUI();
WebApplication app = builder.Build();
app.UseHttpLogging();
// Initialize the factory
ChatClientAgentFactory.Initialize(app.Configuration);
// Map the AG-UI agent endpoints for different scenarios
app.MapAGUI("/agentic_chat", ChatClientAgentFactory.CreateAgenticChat());
app.MapAGUI("/backend_tool_rendering", ChatClientAgentFactory.CreateBackendToolRendering());
app.MapAGUI("/human_in_the_loop", ChatClientAgentFactory.CreateHumanInTheLoop());
app.MapAGUI("/tool_based_generative_ui", ChatClientAgentFactory.CreateToolBasedGenerativeUI());
app.MapAGUI("/agentic_generative_ui", ChatClientAgentFactory.CreateAgenticUI());
var jsonOptions = app.Services.GetRequiredService<IOptions<Microsoft.AspNetCore.Http.Json.JsonOptions>>();
app.MapAGUI("/shared_state", ChatClientAgentFactory.CreateSharedState(jsonOptions.Value.SerializerOptions));
await app.RunAsync();
public partial class Program { }
@@ -1,12 +0,0 @@
{
"profiles": {
"AGUIDojoServer": {
"commandName": "Project",
"launchBrowser": true,
"environmentVariables": {
"ASPNETCORE_ENVIRONMENT": "Development"
},
"applicationUrl": "http://localhost:5018"
}
}
}
@@ -1,26 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIDojoServer;
internal sealed class Recipe
{
[JsonPropertyName("title")]
public string Title { get; set; } = string.Empty;
[JsonPropertyName("skill_level")]
public string SkillLevel { get; set; } = string.Empty;
[JsonPropertyName("cooking_time")]
public string CookingTime { get; set; } = string.Empty;
[JsonPropertyName("special_preferences")]
public List<string> SpecialPreferences { get; set; } = [];
[JsonPropertyName("ingredients")]
public List<Ingredient> Ingredients { get; set; } = [];
[JsonPropertyName("instructions")]
public List<string> Instructions { get; set; } = [];
}
@@ -1,13 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIDojoServer;
#pragma warning disable CA1812 // Used for the JsonSchema response format
internal sealed class RecipeResponse
#pragma warning restore CA1812
{
[JsonPropertyName("recipe")]
public Recipe Recipe { get; set; } = new();
}
@@ -1,106 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Diagnostics.CodeAnalysis;
using System.Runtime.CompilerServices;
using System.Text.Json;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
namespace AGUIDojoServer;
[SuppressMessage("Performance", "CA1812:Avoid uninstantiated internal classes", Justification = "Instantiated by ChatClientAgentFactory.CreateSharedState")]
internal sealed class SharedStateAgent : DelegatingAIAgent
{
private readonly JsonSerializerOptions _jsonSerializerOptions;
public SharedStateAgent(AIAgent innerAgent, JsonSerializerOptions jsonSerializerOptions)
: base(innerAgent)
{
this._jsonSerializerOptions = jsonSerializerOptions;
}
public override Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
{
return this.RunStreamingAsync(messages, thread, options, cancellationToken).ToAgentRunResponseAsync(cancellationToken);
}
public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
IEnumerable<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
[EnumeratorCancellation] CancellationToken cancellationToken = default)
{
if (options is not ChatClientAgentRunOptions { ChatOptions.AdditionalProperties: { } properties } chatRunOptions ||
!properties.TryGetValue("ag_ui_state", out JsonElement state))
{
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, thread, options, cancellationToken).ConfigureAwait(false))
{
yield return update;
}
yield break;
}
var firstRunOptions = new ChatClientAgentRunOptions
{
ChatOptions = chatRunOptions.ChatOptions.Clone(),
AllowBackgroundResponses = chatRunOptions.AllowBackgroundResponses,
ContinuationToken = chatRunOptions.ContinuationToken,
ChatClientFactory = chatRunOptions.ChatClientFactory,
};
// Configure JSON schema response format for structured state output
firstRunOptions.ChatOptions.ResponseFormat = ChatResponseFormat.ForJsonSchema<RecipeResponse>(
schemaName: "RecipeResponse",
schemaDescription: "A response containing a recipe with title, skill level, cooking time, preferences, ingredients, and instructions");
ChatMessage stateUpdateMessage = new(
ChatRole.System,
[
new TextContent("Here is the current state in JSON format:"),
new TextContent(state.GetRawText()),
new TextContent("The new state is:")
]);
var firstRunMessages = messages.Append(stateUpdateMessage);
var allUpdates = new List<AgentRunResponseUpdate>();
await foreach (var update in this.InnerAgent.RunStreamingAsync(firstRunMessages, thread, firstRunOptions, cancellationToken).ConfigureAwait(false))
{
allUpdates.Add(update);
// Yield all non-text updates (tool calls, etc.)
bool hasNonTextContent = update.Contents.Any(c => c is not TextContent);
if (hasNonTextContent)
{
yield return update;
}
}
var response = allUpdates.ToAgentRunResponse();
if (response.TryDeserialize(this._jsonSerializerOptions, out JsonElement stateSnapshot))
{
byte[] stateBytes = JsonSerializer.SerializeToUtf8Bytes(
stateSnapshot,
this._jsonSerializerOptions.GetTypeInfo(typeof(JsonElement)));
yield return new AgentRunResponseUpdate
{
Contents = [new DataContent(stateBytes, "application/json")]
};
}
else
{
yield break;
}
var secondRunMessages = messages.Concat(response.Messages).Append(
new ChatMessage(
ChatRole.System,
[new TextContent("Please provide a concise summary of the state changes in at most two sentences.")]));
await foreach (var update in this.InnerAgent.RunStreamingAsync(secondRunMessages, thread, options, cancellationToken).ConfigureAwait(false))
{
yield return update;
}
}
}
@@ -1,23 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIDojoServer;
internal sealed class WeatherInfo
{
[JsonPropertyName("temperature")]
public int Temperature { get; init; }
[JsonPropertyName("conditions")]
public string Conditions { get; init; } = string.Empty;
[JsonPropertyName("humidity")]
public int Humidity { get; init; }
[JsonPropertyName("wind_speed")]
public int WindSpeed { get; init; }
[JsonPropertyName("feelsLike")]
public int FeelsLike { get; init; }
}
@@ -1,9 +0,0 @@
{
"Logging": {
"LogLevel": {
"Default": "Information",
"Microsoft.AspNetCore": "Warning",
"Microsoft.AspNetCore.HttpLogging.HttpLoggingMiddleware": "Information"
}
}
}
@@ -1,10 +0,0 @@
{
"Logging": {
"LogLevel": {
"Default": "Information",
"Microsoft.AspNetCore": "Warning",
"Microsoft.AspNetCore.HttpLogging.HttpLoggingMiddleware": "Information"
}
},
"AllowedHosts": "*"
}
@@ -1,9 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AGUIServer;
[JsonSerializable(typeof(ServerWeatherForecastRequest))]
[JsonSerializable(typeof(ServerWeatherForecastResponse))]
internal sealed partial class AGUIServerSerializerContext : JsonSerializerContext;
@@ -1,7 +1,5 @@
// Copyright (c) Microsoft. All rights reserved.
using System.ComponentModel;
using AGUIServer;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI.Hosting.AGUI.AspNetCore;
@@ -10,40 +8,17 @@ using OpenAI;
WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
builder.Services.AddHttpClient().AddLogging();
builder.Services.ConfigureHttpJsonOptions(options => options.SerializerOptions.TypeInfoResolverChain.Add(AGUIServerSerializerContext.Default));
builder.Services.AddAGUI();
WebApplication app = builder.Build();
string endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
string deploymentName = builder.Configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");
// Create the AI agent with tools
// Create the AI agent
var agent = new AzureOpenAIClient(
new Uri(endpoint),
new DefaultAzureCredential())
.GetChatClient(deploymentName)
.CreateAIAgent(
name: "AGUIAssistant",
tools: [
AIFunctionFactory.Create(
() => DateTimeOffset.UtcNow,
name: "get_current_time",
description: "Get the current UTC time."
),
AIFunctionFactory.Create(
([Description("The weather forecast request")]ServerWeatherForecastRequest request) => {
return new ServerWeatherForecastResponse()
{
Summary = "Sunny",
TemperatureC = 25,
Date = request.Date
};
},
name: "get_server_weather_forecast",
description: "Gets the forecast for a specific location and date",
AGUIServerSerializerContext.Default.Options)
]);
.CreateAIAgent(name: "AGUIAssistant");
// Map the AG-UI agent endpoint
app.MapAGUI("/", agent);
@@ -1,12 +0,0 @@
{
"profiles": {
"AGUIServer": {
"commandName": "Project",
"launchBrowser": true,
"environmentVariables": {
"ASPNETCORE_ENVIRONMENT": "Development"
},
"applicationUrl": "http://localhost:5100;https://localhost:5101"
}
}
}
@@ -1,9 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
namespace AGUIServer;
internal sealed class ServerWeatherForecastRequest
{
public DateTime Date { get; set; }
public string Location { get; set; } = "Seattle";
}
@@ -1,12 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
namespace AGUIServer;
internal sealed class ServerWeatherForecastResponse
{
public string Summary { get; set; } = "";
public int TemperatureC { get; set; }
public DateTime Date { get; set; }
}
+6 -12
View File
@@ -134,21 +134,15 @@ This automatically handles:
### Client Side
The `AGUIClient` uses the `AGUIChatClient` to connect to the remote server:
The `AGUIClient` uses the `AGUIAgent` class to connect to the remote server:
```csharp
using HttpClient httpClient = new();
var chatClient = new AGUIChatClient(
httpClient,
endpoint: serverUrl,
modelId: "agui-client",
jsonSerializerOptions: null);
AIAgent agent = chatClient.CreateAIAgent(
instructions: null,
name: "agui-client",
AGUIAgent agent = new(
id: "agui-client",
description: "AG-UI Client Agent",
tools: []);
messages: [],
httpClient: httpClient,
endpoint: serverUrl);
bool isFirstUpdate = true;
AgentRunResponseUpdate? currentUpdate = null;
@@ -2,7 +2,7 @@
using System.Diagnostics.CodeAnalysis;
using System.Text.Json.Serialization;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hosting;
namespace AgentWebChat.AgentHost;
@@ -10,24 +10,24 @@ internal static class ActorFrameworkWebApplicationExtensions
{
public static void MapAgentDiscovery(this IEndpointRouteBuilder endpoints, [StringSyntax("Route")] string path)
{
var registeredAIAgents = endpoints.ServiceProvider.GetKeyedServices<AIAgent>(KeyedService.AnyKey);
var routeGroup = endpoints.MapGroup(path);
routeGroup.MapGet("/", async (CancellationToken cancellationToken) =>
{
var results = new List<AgentDiscoveryCard>();
foreach (var result in registeredAIAgents)
routeGroup.MapGet("/", async (
AgentCatalog agentCatalog,
CancellationToken cancellationToken) =>
{
results.Add(new AgentDiscoveryCard
var results = new List<AgentDiscoveryCard>();
await foreach (var result in agentCatalog.GetAgentsAsync(cancellationToken).ConfigureAwait(false))
{
Name = result.Name!,
Description = result.Description,
});
}
results.Add(new AgentDiscoveryCard
{
Name = result.Name!,
Description = result.Description,
});
}
return Results.Ok(results);
})
.WithName("GetAgents");
return Results.Ok(results);
})
.WithName("GetAgents");
}
internal sealed class AgentDiscoveryCard
@@ -1,4 +1,4 @@
<Project Sdk="Microsoft.NET.Sdk.Web">
<Project Sdk="Microsoft.NET.Sdk.Web">
<PropertyGroup>
<TargetFramework>net9.0</TargetFramework>
@@ -8,13 +8,12 @@
</PropertyGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.DevUI\Microsoft.Agents.AI.DevUI.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Abstractions\Microsoft.Agents.AI.Abstractions.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting\Microsoft.Agents.AI.Hosting.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.A2A.AspNetCore\Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.OpenAI\Microsoft.Agents.AI.Hosting.OpenAI.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.OpenAI\Microsoft.Agents.AI.Hosting.OpenAI.csproj" />
<ProjectReference Include="..\AgentWebChat.ServiceDefaults\AgentWebChat.ServiceDefaults.csproj" />
</ItemGroup>
@@ -38,4 +37,4 @@
</ItemGroup>
<!-- A2A dependency -->
</Project>
</Project>
@@ -1,17 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Extensions.AI;
namespace AgentWebChat.AgentHost.Custom;
public class CustomAITool : AITool
{
}
public class CustomFunctionTool : AIFunction
{
protected override ValueTask<object?> InvokeCoreAsync(AIFunctionArguments arguments, CancellationToken cancellationToken)
{
return new ValueTask<object?>(arguments.Context?.Count ?? 0);
}
}
@@ -2,10 +2,8 @@
using A2A.AspNetCore;
using AgentWebChat.AgentHost;
using AgentWebChat.AgentHost.Custom;
using AgentWebChat.AgentHost.Utilities;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.DevUI;
using Microsoft.Agents.AI.Hosting;
using Microsoft.Agents.AI.Workflows;
using Microsoft.Extensions.AI;
@@ -22,20 +20,11 @@ builder.Services.AddProblemDetails();
// Configure the chat model and our agent.
builder.AddKeyedChatClient("chat-model");
// Add DevUI services
builder.AddDevUI();
// Add OpenAI services
builder.AddOpenAIChatCompletions();
builder.AddOpenAIResponses();
var pirateAgentBuilder = builder.AddAIAgent(
"pirate",
instructions: "You are a pirate. Speak like a pirate",
description: "An agent that speaks like a pirate.",
chatClientServiceKey: "chat-model")
.WithAITool(new CustomAITool())
.WithAITool(new CustomFunctionTool())
.WithInMemoryThreadStore();
var knightsKnavesAgentBuilder = builder.AddAIAgent("knights-and-knaves", (sp, key) =>
@@ -89,62 +78,11 @@ var literatureAgent = builder.AddAIAgent("literator",
description: "An agent that helps with literature.",
chatClientServiceKey: "chat-model");
var scienceSequentialWorkflow = builder.AddWorkflow("science-sequential-workflow", (sp, key) =>
{
List<IHostedAgentBuilder> usedAgents = [chemistryAgent, mathsAgent, literatureAgent];
var agents = usedAgents.Select(ab => sp.GetRequiredKeyedService<AIAgent>(ab.Name));
return AgentWorkflowBuilder.BuildSequential(workflowName: key, agents: agents);
}).AddAsAIAgent();
builder.AddSequentialWorkflow("science-sequential-workflow", [chemistryAgent, mathsAgent, literatureAgent]).AddAsAIAgent();
builder.AddConcurrentWorkflow("science-concurrent-workflow", [chemistryAgent, mathsAgent, literatureAgent]).AddAsAIAgent();
var scienceConcurrentWorkflow = builder.AddWorkflow("science-concurrent-workflow", (sp, key) =>
{
List<IHostedAgentBuilder> usedAgents = [chemistryAgent, mathsAgent, literatureAgent];
var agents = usedAgents.Select(ab => sp.GetRequiredKeyedService<AIAgent>(ab.Name));
return AgentWorkflowBuilder.BuildConcurrent(workflowName: key, agents: agents);
}).AddAsAIAgent();
builder.AddWorkflow("nonAgentWorkflow", (sp, key) =>
{
List<IHostedAgentBuilder> usedAgents = [pirateAgentBuilder, chemistryAgent];
var agents = usedAgents.Select(ab => sp.GetRequiredKeyedService<AIAgent>(ab.Name));
return AgentWorkflowBuilder.BuildSequential(workflowName: key, agents: agents);
});
builder.Services.AddKeyedSingleton("NonAgentAndNonmatchingDINameWorkflow", (sp, key) =>
{
List<IHostedAgentBuilder> usedAgents = [pirateAgentBuilder, chemistryAgent];
var agents = usedAgents.Select(ab => sp.GetRequiredKeyedService<AIAgent>(ab.Name));
return AgentWorkflowBuilder.BuildSequential(workflowName: "random-name", agents: agents);
});
builder.Services.AddSingleton<AIAgent>(sp =>
{
var chatClient = sp.GetRequiredKeyedService<IChatClient>("chat-model");
return new ChatClientAgent(chatClient, name: "default-agent", instructions: "you are a default agent.");
});
builder.Services.AddKeyedSingleton<AIAgent>("my-di-nonmatching-agent", (sp, name) =>
{
var chatClient = sp.GetRequiredKeyedService<IChatClient>("chat-model");
return new ChatClientAgent(
chatClient,
name: "some-random-name", // demonstrating registration can be different for DI and actual agent
instructions: "you are a dependency inject agent. Tell me all about dependency injection.");
});
builder.Services.AddKeyedSingleton<AIAgent>("my-di-matchingname-agent", (sp, name) =>
{
if (name is not string nameStr)
{
throw new NotSupportedException("Name should be passed as a key");
}
var chatClient = sp.GetRequiredKeyedService<IChatClient>("chat-model");
return new ChatClientAgent(
chatClient,
name: nameStr, // demonstrating registration with the same name
instructions: "you are a dependency inject agent. Tell me all about dependency injection.");
});
builder.AddOpenAIChatCompletions();
builder.AddOpenAIResponses();
var app = builder.Build();
@@ -155,8 +93,8 @@ app.UseSwaggerUI(options => options.SwaggerEndpoint("/openapi/v1.json", "Agents
app.UseExceptionHandler();
// attach a2a with simple message communication
app.MapA2A(pirateAgentBuilder, path: "/a2a/pirate");
app.MapA2A(knightsKnavesAgentBuilder, path: "/a2a/knights-and-knaves", agentCard: new()
app.MapA2A(agentName: "pirate", path: "/a2a/pirate");
app.MapA2A(agentName: "knights-and-knaves", path: "/a2a/knights-and-knaves", agentCard: new()
{
Name = "Knights and Knaves",
Description = "An agent that helps you solve the knights and knaves puzzle.",
@@ -166,10 +104,7 @@ app.MapA2A(knightsKnavesAgentBuilder, path: "/a2a/knights-and-knaves", agentCard
// Url = "http://localhost:5390/a2a/knights-and-knaves"
});
app.MapDevUI();
app.MapOpenAIResponses();
app.MapOpenAIConversations();
app.MapOpenAIChatCompletions(pirateAgentBuilder);
app.MapOpenAIChatCompletions(knightsKnavesAgentBuilder);
@@ -9,9 +9,7 @@ var azOpenAiResourceGroup = builder.AddParameterFromConfiguration("AzureOpenAIRe
var chatModel = builder.AddAIModel("chat-model").AsAzureOpenAI("gpt-4o", o => o.AsExisting(azOpenAiResource, azOpenAiResourceGroup));
var agentHost = builder.AddProject<Projects.AgentWebChat_AgentHost>("agenthost")
.WithHttpEndpoint(name: "devui")
.WithUrlForEndpoint("devui", (url) => new() { Url = "/devui", DisplayText = "Dev UI" })
.WithReference(chatModel);
.WithReference(chatModel);
builder.AddProject<Projects.AgentWebChat_Web>("webfrontend")
.WithExternalHttpEndpoints()
@@ -1,10 +0,0 @@
# .editorconfig
[*.cs]
# See https://github.com/Azure/azure-functions-durable-extension/issues/3173
dotnet_diagnostic.DURABLE0001.severity = none
dotnet_diagnostic.DURABLE0002.severity = none
dotnet_diagnostic.DURABLE0003.severity = none
dotnet_diagnostic.DURABLE0004.severity = none
dotnet_diagnostic.DURABLE0005.severity = none
dotnet_diagnostic.DURABLE0006.severity = none
@@ -1,42 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFramework>net9.0</TargetFramework>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
<OutputType>Exe</OutputType>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<!-- The Functions build tools don't like namespaces that start with a number -->
<AssemblyName>SingleAgent</AssemblyName>
<RootNamespace>SingleAgent</RootNamespace>
</PropertyGroup>
<ItemGroup>
<FrameworkReference Include="Microsoft.AspNetCore.App" />
</ItemGroup>
<!-- Azure Functions packages -->
<ItemGroup>
<PackageReference Include="Microsoft.Azure.Functions.Worker" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
<!--
<ItemGroup>
<PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
</ItemGroup>
-->
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
</ItemGroup>
</Project>
@@ -1,37 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Azure;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hosting.AzureFunctions;
using Microsoft.Azure.Functions.Worker.Builder;
using Microsoft.Extensions.Hosting;
using OpenAI;
// Get the Azure OpenAI endpoint and deployment name from environment variables.
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
// Set up an AI agent following the standard Microsoft Agent Framework pattern.
const string JokerName = "Joker";
const string JokerInstructions = "You are good at telling jokes.";
AIAgent agent = client.GetChatClient(deploymentName).CreateAIAgent(JokerInstructions, JokerName);
// Configure the function app to host the AI agent.
// This will automatically generate HTTP API endpoints for the agent.
using IHost app = FunctionsApplication
.CreateBuilder(args)
.ConfigureFunctionsWebApplication()
.ConfigureDurableAgents(options => options.AddAIAgent(agent))
.Build();
app.Run();
@@ -1,89 +0,0 @@
# Single Agent Sample
This sample demonstrates how to use the Durable Agent Framework (DAFx) to create a simple Azure Functions app that hosts a single AI agent and provides direct HTTP API access for interactive conversations.
## Key Concepts Demonstrated
- Using the Microsoft Agent Framework to define a simple AI agent with a name and instructions.
- Registering agents with the Function app and running them using HTTP.
- Conversation management (via session IDs) for isolated interactions.
## Environment Setup
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
## Running the Sample
With the environment setup and function app running, you can test the sample by sending an HTTP request to the agent endpoint.
You can use the `demo.http` file to send a message to the agent, or a command line tool like `curl` as shown below:
Bash (Linux/macOS/WSL):
```bash
curl -X POST http://localhost:7071/api/agents/Joker/run \
-H "Content-Type: text/plain" \
-d "Tell me a joke about a pirate."
```
PowerShell:
```powershell
Invoke-RestMethod -Method Post `
-Uri http://localhost:7071/api/agents/Joker/run `
-ContentType text/plain `
-Body "Tell me a joke about a pirate."
```
You can also send JSON requests:
```bash
curl -X POST http://localhost:7071/api/agents/Joker/run \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"message": "Tell me a joke about a pirate."}'
```
To continue a conversation, include the `thread_id` in the query string or JSON body:
```bash
curl -X POST "http://localhost:7071/api/agents/Joker/run?thread_id=your-thread-id" \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-d '{"message": "Tell me another one."}'
```
The response from the agent will be displayed in the terminal where you ran `func start`. The expected `text/plain` output will look something like:
```text
Why don't pirates ever learn the alphabet? Because they always get stuck at "C"!
```
The expected `application/json` output will look something like:
```json
{
"status": 200,
"thread_id": "ee6e47a0-f24b-40b1-ade8-16fcebb9eb40",
"response": {
"Messages": [
{
"AuthorName": "Joker",
"CreatedAt": "2025-11-11T12:00:00.0000000Z",
"Role": "assistant",
"Contents": [
{
"Type": "text",
"Text": "Why don't pirates ever learn the alphabet? Because they always get stuck at 'C'!"
}
]
}
],
"Usage": {
"InputTokenCount": 78,
"OutputTokenCount": 36,
"TotalTokenCount": 114
}
}
}
```
@@ -1,8 +0,0 @@
# Default endpoint address for local testing
@authority=http://localhost:7071
### Prompt the agent
POST {{authority}}/api/agents/Joker/run
Content-Type: text/plain
Tell me a joke about a pirate.
@@ -1,20 +0,0 @@
{
"version": "2.0",
"logging": {
"logLevel": {
"Microsoft.Agents.AI.DurableTask": "Information",
"Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
"DurableTask": "Information",
"Microsoft.DurableTask": "Information"
}
},
"extensions": {
"durableTask": {
"hubName": "default",
"storageProvider": {
"type": "AzureManaged",
"connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
}
}
}
}
@@ -1,10 +0,0 @@
{
"IsEncrypted": false,
"Values": {
"FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
"AzureWebJobsStorage": "UseDevelopmentStorage=true",
"DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None",
"AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
"AZURE_OPENAI_DEPLOYMENT": "<AZURE_OPENAI_DEPLOYMENT>"
}
}
@@ -1,42 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFramework>net9.0</TargetFramework>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
<OutputType>Exe</OutputType>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<!-- The Functions build tools don't like namespaces that start with a number -->
<AssemblyName>AgentOrchestration_Chaining</AssemblyName>
<RootNamespace>AgentOrchestration_Chaining</RootNamespace>
</PropertyGroup>
<ItemGroup>
<FrameworkReference Include="Microsoft.AspNetCore.App" />
</ItemGroup>
<!-- Azure Functions packages -->
<ItemGroup>
<PackageReference Include="Microsoft.Azure.Functions.Worker" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
<!--
<ItemGroup>
<PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
</ItemGroup>
-->
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
</ItemGroup>
</Project>
@@ -1,92 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Net;
using System.Text.Json;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.DurableTask;
using Microsoft.Azure.Functions.Worker;
using Microsoft.Azure.Functions.Worker.Http;
using Microsoft.DurableTask;
using Microsoft.DurableTask.Client;
namespace AgentOrchestration_Chaining;
public static class FunctionTriggers
{
public sealed record TextResponse(string Text);
[Function(nameof(RunOrchestrationAsync))]
public static async Task<string> RunOrchestrationAsync([OrchestrationTrigger] TaskOrchestrationContext context)
{
DurableAIAgent writer = context.GetAgent("WriterAgent");
AgentThread writerThread = writer.GetNewThread();
AgentRunResponse<TextResponse> initial = await writer.RunAsync<TextResponse>(
message: "Write a concise inspirational sentence about learning.",
thread: writerThread);
AgentRunResponse<TextResponse> refined = await writer.RunAsync<TextResponse>(
message: $"Improve this further while keeping it under 25 words: {initial.Result.Text}",
thread: writerThread);
return refined.Result.Text;
}
// POST /singleagent/run
[Function(nameof(StartOrchestrationAsync))]
public static async Task<HttpResponseData> StartOrchestrationAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = "singleagent/run")] HttpRequestData req,
[DurableClient] DurableTaskClient client)
{
string instanceId = await client.ScheduleNewOrchestrationInstanceAsync(
orchestratorName: nameof(RunOrchestrationAsync));
HttpResponseData response = req.CreateResponse(HttpStatusCode.Accepted);
await response.WriteAsJsonAsync(new
{
message = "Single-agent orchestration started.",
instanceId,
statusQueryGetUri = GetStatusQueryGetUri(req, instanceId),
});
return response;
}
// GET /singleagent/status/{instanceId}
[Function(nameof(GetOrchestrationStatusAsync))]
public static async Task<HttpResponseData> GetOrchestrationStatusAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "get", Route = "singleagent/status/{instanceId}")] HttpRequestData req,
string instanceId,
[DurableClient] DurableTaskClient client)
{
OrchestrationMetadata? status = await client.GetInstanceAsync(
instanceId,
getInputsAndOutputs: true,
req.FunctionContext.CancellationToken);
if (status is null)
{
HttpResponseData notFound = req.CreateResponse(HttpStatusCode.NotFound);
await notFound.WriteAsJsonAsync(new { error = "Instance not found" });
return notFound;
}
HttpResponseData response = req.CreateResponse(HttpStatusCode.OK);
await response.WriteAsJsonAsync(new
{
instanceId = status.InstanceId,
runtimeStatus = status.RuntimeStatus.ToString(),
input = status.SerializedInput is not null ? (object)status.ReadInputAs<JsonElement>() : null,
output = status.SerializedOutput is not null ? (object)status.ReadOutputAs<JsonElement>() : null,
failureDetails = status.FailureDetails
});
return response;
}
private static string GetStatusQueryGetUri(HttpRequestData req, string instanceId)
{
// NOTE: This can be made more robust by considering the value of
// request headers like "X-Forwarded-Host" and "X-Forwarded-Proto".
string authority = $"{req.Url.Scheme}://{req.Url.Authority}";
return $"{authority}/api/singleagent/status/{instanceId}";
}
}
@@ -1,40 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Azure;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hosting.AzureFunctions;
using Microsoft.Azure.Functions.Worker.Builder;
using Microsoft.Extensions.Hosting;
using OpenAI;
// Get the Azure OpenAI endpoint and deployment name from environment variables.
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
// Single agent used by the orchestration to demonstrate sequential calls on the same thread.
const string WriterName = "WriterAgent";
const string WriterInstructions =
"""
You refine short pieces of text. When given an initial sentence you enhance it;
when given an improved sentence you polish it further.
""";
AIAgent writerAgent = client.GetChatClient(deploymentName).CreateAIAgent(WriterInstructions, WriterName);
using IHost app = FunctionsApplication
.CreateBuilder(args)
.ConfigureFunctionsWebApplication()
.ConfigureDurableAgents(options => options.AddAIAgent(writerAgent))
.Build();
app.Run();
@@ -1,59 +0,0 @@
# Single Agent Orchestration Sample
This sample demonstrates how to use the Durable Agent Framework (DAFx) to create a simple Azure Functions app that orchestrates sequential calls to a single AI agent using the same conversation thread for context continuity.
## Key Concepts Demonstrated
- Orchestrating multiple interactions with the same agent in a deterministic order
- Using the same `AgentThread` across multiple calls to maintain conversational context
- Durable orchestration with automatic checkpointing and resumption from failures
- HTTP API integration for starting and monitoring orchestrations
## Environment Setup
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
## Running the Sample
With the environment setup and function app running, you can test the sample by sending an HTTP request to start the orchestration.
You can use the `demo.http` file to start the orchestration, or a command line tool like `curl` as shown below:
Bash (Linux/macOS/WSL):
```bash
curl -X POST http://localhost:7071/api/singleagent/run
```
PowerShell:
```powershell
Invoke-RestMethod -Method Post -Uri http://localhost:7071/api/singleagent/run
```
The response will be a JSON object that looks something like the following, which indicates that the orchestration has started.
```json
{
"message": "Single-agent orchestration started.",
"instanceId": "86313f1d45fb42eeb50b1852626bf3ff",
"statusQueryGetUri": "http://localhost:7071/api/singleagent/status/86313f1d45fb42eeb50b1852626bf3ff"
}
```
The orchestration will proceed to run the WriterAgent twice in sequence:
1. First, it writes an inspirational sentence about learning
2. Then, it refines the initial output using the same conversation thread
Once the orchestration has completed, you can get the status of the orchestration by sending a GET request to the `statusQueryGetUri` URL. The response will be a JSON object that looks something like the following:
```json
{
"failureDetails": null,
"input": null,
"instanceId": "86313f1d45fb42eeb50b1852626bf3ff",
"output": "Learning serves as the key, opening doors to boundless opportunities and a brighter future.",
"runtimeStatus": "Completed"
}
```
@@ -1,3 +0,0 @@
### Start the single-agent orchestration
POST http://localhost:7071/api/singleagent/run
@@ -1,20 +0,0 @@
{
"version": "2.0",
"logging": {
"logLevel": {
"Microsoft.Agents.AI.DurableTask": "Information",
"Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
"DurableTask": "Information",
"Microsoft.DurableTask": "Information"
}
},
"extensions": {
"durableTask": {
"hubName": "default",
"storageProvider": {
"type": "AzureManaged",
"connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
}
}
}
}
@@ -1,10 +0,0 @@
{
"IsEncrypted": false,
"Values": {
"FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
"AzureWebJobsStorage": "UseDevelopmentStorage=true",
"DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None",
"AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
"AZURE_OPENAI_DEPLOYMENT": "<AZURE_OPENAI_DEPLOYMENT>"
}
}
@@ -1,42 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFramework>net9.0</TargetFramework>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
<OutputType>Exe</OutputType>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<!-- The Functions build tools don't like namespaces that start with a number -->
<AssemblyName>AgentOrchestration_Concurrency</AssemblyName>
<RootNamespace>AgentOrchestration_Concurrency</RootNamespace>
</PropertyGroup>
<ItemGroup>
<FrameworkReference Include="Microsoft.AspNetCore.App" />
</ItemGroup>
<!-- Azure Functions packages -->
<ItemGroup>
<PackageReference Include="Microsoft.Azure.Functions.Worker" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
<!--
<ItemGroup>
<PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
</ItemGroup>
-->
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
</ItemGroup>
</Project>
@@ -1,116 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Net;
using System.Text.Json;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.DurableTask;
using Microsoft.Azure.Functions.Worker;
using Microsoft.Azure.Functions.Worker.Http;
using Microsoft.DurableTask;
using Microsoft.DurableTask.Client;
namespace AgentOrchestration_Concurrency;
public static class FunctionsTriggers
{
public sealed record TextResponse(string Text);
[Function(nameof(RunOrchestrationAsync))]
public static async Task<object> RunOrchestrationAsync([OrchestrationTrigger] TaskOrchestrationContext context)
{
// Get the prompt from the orchestration input
string prompt = context.GetInput<string>() ?? throw new InvalidOperationException("Prompt is required");
// Get both agents
DurableAIAgent physicist = context.GetAgent("PhysicistAgent");
DurableAIAgent chemist = context.GetAgent("ChemistAgent");
// Start both agent runs concurrently
Task<AgentRunResponse<TextResponse>> physicistTask = physicist.RunAsync<TextResponse>(prompt);
Task<AgentRunResponse<TextResponse>> chemistTask = chemist.RunAsync<TextResponse>(prompt);
// Wait for both tasks to complete using Task.WhenAll
await Task.WhenAll(physicistTask, chemistTask);
// Get the results
TextResponse physicistResponse = (await physicistTask).Result;
TextResponse chemistResponse = (await chemistTask).Result;
// Return the result as a structured, anonymous type
return new
{
physicist = physicistResponse.Text,
chemist = chemistResponse.Text,
};
}
// POST /multiagent/run
[Function(nameof(StartOrchestrationAsync))]
public static async Task<HttpResponseData> StartOrchestrationAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = "multiagent/run")] HttpRequestData req,
[DurableClient] DurableTaskClient client)
{
// Read the prompt from the request body
string? prompt = await req.ReadAsStringAsync();
if (string.IsNullOrWhiteSpace(prompt))
{
HttpResponseData badRequestResponse = req.CreateResponse(HttpStatusCode.BadRequest);
await badRequestResponse.WriteAsJsonAsync(new { error = "Prompt is required" });
return badRequestResponse;
}
string instanceId = await client.ScheduleNewOrchestrationInstanceAsync(
orchestratorName: nameof(RunOrchestrationAsync),
input: prompt);
HttpResponseData response = req.CreateResponse(HttpStatusCode.Accepted);
await response.WriteAsJsonAsync(new
{
message = "Multi-agent concurrent orchestration started.",
prompt,
instanceId,
statusQueryGetUri = GetStatusQueryGetUri(req, instanceId),
});
return response;
}
// GET /multiagent/status/{instanceId}
[Function(nameof(GetOrchestrationStatusAsync))]
public static async Task<HttpResponseData> GetOrchestrationStatusAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "get", Route = "multiagent/status/{instanceId}")] HttpRequestData req,
string instanceId,
[DurableClient] DurableTaskClient client)
{
OrchestrationMetadata? status = await client.GetInstanceAsync(
instanceId,
getInputsAndOutputs: true,
req.FunctionContext.CancellationToken);
if (status is null)
{
HttpResponseData notFound = req.CreateResponse(HttpStatusCode.NotFound);
await notFound.WriteAsJsonAsync(new { error = "Instance not found" });
return notFound;
}
HttpResponseData response = req.CreateResponse(HttpStatusCode.OK);
await response.WriteAsJsonAsync(new
{
instanceId = status.InstanceId,
runtimeStatus = status.RuntimeStatus.ToString(),
input = status.SerializedInput is not null ? (object)status.ReadInputAs<JsonElement>() : null,
output = status.SerializedOutput is not null ? (object)status.ReadOutputAs<JsonElement>() : null,
failureDetails = status.FailureDetails
});
return response;
}
private static string GetStatusQueryGetUri(HttpRequestData req, string instanceId)
{
// NOTE: This can be made more robust by considering the value of
// request headers like "X-Forwarded-Host" and "X-Forwarded-Proto".
string authority = $"{req.Url.Scheme}://{req.Url.Authority}";
return $"{authority}/api/multiagent/status/{instanceId}";
}
}
@@ -1,44 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Azure;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hosting.AzureFunctions;
using Microsoft.Azure.Functions.Worker.Builder;
using Microsoft.Extensions.Hosting;
using OpenAI;
// Get the Azure OpenAI endpoint and deployment name from environment variables.
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
// Two agents used by the orchestration to demonstrate concurrent execution.
const string PhysicistName = "PhysicistAgent";
const string PhysicistInstructions = "You are an expert in physics. You answer questions from a physics perspective.";
const string ChemistName = "ChemistAgent";
const string ChemistInstructions = "You are an expert in chemistry. You answer questions from a chemistry perspective.";
AIAgent physicistAgent = client.GetChatClient(deploymentName).CreateAIAgent(PhysicistInstructions, PhysicistName);
AIAgent chemistAgent = client.GetChatClient(deploymentName).CreateAIAgent(ChemistInstructions, ChemistName);
using IHost app = FunctionsApplication
.CreateBuilder(args)
.ConfigureFunctionsWebApplication()
.ConfigureDurableAgents(options =>
{
options.AddAIAgent(physicistAgent);
options.AddAIAgent(chemistAgent);
})
.Build();
app.Run();
@@ -1,65 +0,0 @@
# Multi-Agent Concurrent Orchestration Sample
This sample demonstrates how to use the Durable Agent Framework (DAFx) to create an Azure Functions app that orchestrates concurrent execution of multiple AI agents, each with specialized expertise, to provide comprehensive answers to complex questions.
## Key Concepts Demonstrated
- Multi-agent orchestration with specialized AI agents (physics and chemistry)
- Concurrent execution using the fan-out/fan-in pattern for improved performance and distributed processing
- Response aggregation from multiple agents into a unified result
- Durable orchestration with automatic checkpointing and resumption from failures
## Environment Setup
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
## Running the Sample
With the environment setup and function app running, you can test the sample by sending an HTTP request with a custom prompt to the orchestration.
You can use the `demo.http` file to send a message to the agents, or a command line tool like `curl` as shown below:
Bash (Linux/macOS/WSL):
```bash
curl -X POST http://localhost:7071/api/multiagent/run \
-H "Content-Type: text/plain" \
-d "What is temperature?"
```
PowerShell:
```powershell
Invoke-RestMethod -Method Post `
-Uri http://localhost:7071/api/multiagent/run `
-ContentType text/plain `
-Body "What is temperature?"
```
The response will be a JSON object that looks something like the following, which indicates that the orchestration has started.
```json
{
"message": "Multi-agent concurrent orchestration started.",
"prompt": "What is temperature?",
"instanceId": "e7e29999b6b8424682b3539292afc9ed",
"statusQueryGetUri": "http://localhost:7071/api/multiagent/status/e7e29999b6b8424682b3539292afc9ed"
}
```
The orchestration will run both the PhysicistAgent and ChemistAgent concurrently, asking them the same question. Their responses will be combined to provide a comprehensive answer covering both physical and chemical aspects.
Once the orchestration has completed, you can get the status of the orchestration by sending a GET request to the `statusQueryGetUri` URL. The response will be a JSON object that looks something like the following:
```json
{
"failureDetails": null,
"input": "What is temperature?",
"instanceId": "e7e29999b6b8424682b3539292afc9ed",
"output": {
"physicist": "Temperature is a measure of the average kinetic energy of particles in a system. From a physics perspective, it represents the thermal energy and determines the direction of heat flow between objects.",
"chemist": "From a chemistry perspective, temperature is crucial for chemical reactions as it affects reaction rates through the Arrhenius equation. It influences the equilibrium position of reversible reactions and determines the physical state of substances."
},
"runtimeStatus": "Completed"
}
```
@@ -1,5 +0,0 @@
### Start the multi-agent concurrent orchestration
POST http://localhost:7071/api/multiagent/run
Content-Type: text/plain
What is temperature?
@@ -1,20 +0,0 @@
{
"version": "2.0",
"logging": {
"logLevel": {
"Microsoft.Agents.AI.DurableTask": "Information",
"Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
"DurableTask": "Information",
"Microsoft.DurableTask": "Information"
}
},
"extensions": {
"durableTask": {
"hubName": "default",
"storageProvider": {
"type": "AzureManaged",
"connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
}
}
}
}
@@ -1,10 +0,0 @@
{
"IsEncrypted": false,
"Values": {
"FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
"AzureWebJobsStorage": "UseDevelopmentStorage=true",
"DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None",
"AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
"AZURE_OPENAI_DEPLOYMENT": "<AZURE_OPENAI_DEPLOYMENT>"
}
}
@@ -1,42 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFramework>net9.0</TargetFramework>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
<OutputType>Exe</OutputType>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<!-- The Functions build tools don't like namespaces that start with a number -->
<AssemblyName>AgentOrchestration_Conditionals</AssemblyName>
<RootNamespace>AgentOrchestration_Conditionals</RootNamespace>
</PropertyGroup>
<ItemGroup>
<FrameworkReference Include="Microsoft.AspNetCore.App" />
</ItemGroup>
<!-- Azure Functions packages -->
<ItemGroup>
<PackageReference Include="Microsoft.Azure.Functions.Worker" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
<!--
<ItemGroup>
<PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
</ItemGroup>
-->
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
</ItemGroup>
</Project>
@@ -1,143 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Net;
using System.Text.Json;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.DurableTask;
using Microsoft.Azure.Functions.Worker;
using Microsoft.Azure.Functions.Worker.Http;
using Microsoft.DurableTask;
using Microsoft.DurableTask.Client;
namespace AgentOrchestration_Conditionals;
public static class FunctionTriggers
{
[Function(nameof(RunOrchestrationAsync))]
public static async Task<string> RunOrchestrationAsync([OrchestrationTrigger] TaskOrchestrationContext context)
{
// Get the email from the orchestration input
Email email = context.GetInput<Email>() ?? throw new InvalidOperationException("Email is required");
// Get the spam detection agent
DurableAIAgent spamDetectionAgent = context.GetAgent("SpamDetectionAgent");
AgentThread spamThread = spamDetectionAgent.GetNewThread();
// Step 1: Check if the email is spam
AgentRunResponse<DetectionResult> spamDetectionResponse = await spamDetectionAgent.RunAsync<DetectionResult>(
message:
$"""
Analyze this email for spam content and return a JSON response with 'is_spam' (boolean) and 'reason' (string) fields:
Email ID: {email.EmailId}
Content: {email.EmailContent}
""",
thread: spamThread);
DetectionResult result = spamDetectionResponse.Result;
// Step 2: Conditional logic based on spam detection result
if (result.IsSpam)
{
// Handle spam email
return await context.CallActivityAsync<string>(nameof(HandleSpamEmail), result.Reason);
}
// Generate and send response for legitimate email
DurableAIAgent emailAssistantAgent = context.GetAgent("EmailAssistantAgent");
AgentThread emailThread = emailAssistantAgent.GetNewThread();
AgentRunResponse<EmailResponse> emailAssistantResponse = await emailAssistantAgent.RunAsync<EmailResponse>(
message:
$"""
Draft a professional response to this email. Return a JSON response with a 'response' field containing the reply:
Email ID: {email.EmailId}
Content: {email.EmailContent}
""",
thread: emailThread);
EmailResponse emailResponse = emailAssistantResponse.Result;
return await context.CallActivityAsync<string>(nameof(SendEmail), emailResponse.Response);
}
[Function(nameof(HandleSpamEmail))]
public static string HandleSpamEmail([ActivityTrigger] string reason)
{
return $"Email marked as spam: {reason}";
}
[Function(nameof(SendEmail))]
public static string SendEmail([ActivityTrigger] string message)
{
return $"Email sent: {message}";
}
// POST /spamdetection/run
[Function(nameof(StartOrchestrationAsync))]
public static async Task<HttpResponseData> StartOrchestrationAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = "spamdetection/run")] HttpRequestData req,
[DurableClient] DurableTaskClient client)
{
// Read the email from the request body
Email? email = await req.ReadFromJsonAsync<Email>();
if (email is null || string.IsNullOrWhiteSpace(email.EmailContent))
{
HttpResponseData badRequestResponse = req.CreateResponse(HttpStatusCode.BadRequest);
await badRequestResponse.WriteAsJsonAsync(new { error = "Email with content is required" });
return badRequestResponse;
}
string instanceId = await client.ScheduleNewOrchestrationInstanceAsync(
orchestratorName: nameof(RunOrchestrationAsync),
input: email);
HttpResponseData response = req.CreateResponse(HttpStatusCode.Accepted);
await response.WriteAsJsonAsync(new
{
message = "Spam detection orchestration started.",
emailId = email.EmailId,
instanceId,
statusQueryGetUri = GetStatusQueryGetUri(req, instanceId),
});
return response;
}
// GET /spamdetection/status/{instanceId}
[Function(nameof(GetOrchestrationStatusAsync))]
public static async Task<HttpResponseData> GetOrchestrationStatusAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "get", Route = "spamdetection/status/{instanceId}")] HttpRequestData req,
string instanceId,
[DurableClient] DurableTaskClient client)
{
OrchestrationMetadata? status = await client.GetInstanceAsync(
instanceId,
getInputsAndOutputs: true,
req.FunctionContext.CancellationToken);
if (status is null)
{
HttpResponseData notFound = req.CreateResponse(HttpStatusCode.NotFound);
await notFound.WriteAsJsonAsync(new { error = "Instance not found" });
return notFound;
}
HttpResponseData response = req.CreateResponse(HttpStatusCode.OK);
await response.WriteAsJsonAsync(new
{
instanceId = status.InstanceId,
runtimeStatus = status.RuntimeStatus.ToString(),
input = status.SerializedInput is not null ? (object)status.ReadInputAs<JsonElement>() : null,
output = status.SerializedOutput is not null ? (object)status.ReadOutputAs<JsonElement>() : null,
failureDetails = status.FailureDetails
});
return response;
}
private static string GetStatusQueryGetUri(HttpRequestData req, string instanceId)
{
// NOTE: This can be made more robust by considering the value of
// request headers like "X-Forwarded-Host" and "X-Forwarded-Proto".
string authority = $"{req.Url.Scheme}://{req.Url.Authority}";
return $"{authority}/api/spamdetection/status/{instanceId}";
}
}
@@ -1,38 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AgentOrchestration_Conditionals;
/// <summary>
/// Represents an email input for spam detection and response generation.
/// </summary>
public sealed class Email
{
[JsonPropertyName("email_id")]
public string EmailId { get; set; } = string.Empty;
[JsonPropertyName("email_content")]
public string EmailContent { get; set; } = string.Empty;
}
/// <summary>
/// Represents the result of spam detection analysis.
/// </summary>
public sealed class DetectionResult
{
[JsonPropertyName("is_spam")]
public bool IsSpam { get; set; }
[JsonPropertyName("reason")]
public string Reason { get; set; } = string.Empty;
}
/// <summary>
/// Represents a generated email response.
/// </summary>
public sealed class EmailResponse
{
[JsonPropertyName("response")]
public string Response { get; set; } = string.Empty;
}
@@ -1,47 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Azure;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hosting.AzureFunctions;
using Microsoft.Azure.Functions.Worker.Builder;
using Microsoft.Extensions.Hosting;
using OpenAI;
// Get the Azure OpenAI endpoint and deployment name from environment variables.
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
// Two agents used by the orchestration to demonstrate conditional logic.
const string SpamDetectionName = "SpamDetectionAgent";
const string SpamDetectionInstructions = "You are a spam detection assistant that identifies spam emails.";
const string EmailAssistantName = "EmailAssistantAgent";
const string EmailAssistantInstructions = "You are an email assistant that helps users draft responses to emails with professionalism.";
AIAgent spamDetectionAgent = client.GetChatClient(deploymentName)
.CreateAIAgent(SpamDetectionInstructions, SpamDetectionName);
AIAgent emailAssistantAgent = client.GetChatClient(deploymentName)
.CreateAIAgent(EmailAssistantInstructions, EmailAssistantName);
using IHost app = FunctionsApplication
.CreateBuilder(args)
.ConfigureFunctionsWebApplication()
.ConfigureDurableAgents(options =>
{
options.AddAIAgent(spamDetectionAgent);
options.AddAIAgent(emailAssistantAgent);
})
.Build();
app.Run();
@@ -1,113 +0,0 @@
# Multi-Agent Orchestration with Conditionals Sample
This sample demonstrates how to use the Durable Agent Framework (DAFx) to create a multi-agent orchestration workflow that includes conditional logic. The workflow implements a spam detection system that processes emails and takes different actions based on whether the email is identified as spam or legitimate.
## Key Concepts Demonstrated
- Multi-agent orchestration with conditional logic and different processing paths
- Spam detection using AI agent analysis
- Structured output from agents for reliable processing
- Activity functions for integrating non-agentic workflow actions
## Environment Setup
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
## Running the Sample
With the environment setup and function app running, you can test the sample by sending an HTTP request with email data to the orchestration.
You can use the `demo.http` file to send email data to the agents, or a command line tool like `curl` as shown below:
Bash (Linux/macOS/WSL):
```bash
# Test with a legitimate email
curl -X POST http://localhost:7071/api/spamdetection/run \
-H "Content-Type: application/json" \
-d '{
"email_id": "email-001",
"email_content": "Hi John, I hope you are doing well. I wanted to follow up on our meeting yesterday about the quarterly report. Could you please send me the updated figures by Friday? Thanks!"
}'
# Test with a spam email
curl -X POST http://localhost:7071/api/spamdetection/run \
-H "Content-Type: application/json" \
-d '{
"email_id": "email-002",
"email_content": "URGENT! You have won $1,000,000! Click here now to claim your prize! Limited time offer! Do not miss out!"
}'
```
PowerShell:
```powershell
# Test with a legitimate email
$body = @{
email_id = "email-001"
email_content = "Hi John, I hope you are doing well. I wanted to follow up on our meeting yesterday about the quarterly report. Could you please send me the updated figures by Friday? Thanks!"
} | ConvertTo-Json
Invoke-RestMethod -Method Post `
-Uri http://localhost:7071/api/spamdetection/run `
-ContentType application/json `
-Body $body
# Test with a spam email
$body = @{
email_id = "email-002"
email_content = "URGENT! You have won $1,000,000! Click here now to claim your prize! Limited time offer! Do not miss out!"
} | ConvertTo-Json
Invoke-RestMethod -Method Post `
-Uri http://localhost:7071/api/spamdetection/run `
-ContentType application/json `
-Body $body
```
The response from either input will be a JSON object that looks something like the following, which indicates that the orchestration has started.
```json
{
"message": "Spam detection orchestration started.",
"emailId": "email-001",
"instanceId": "555dbbb63f75406db2edf9f1f092de95",
"statusQueryGetUri": "http://localhost:7071/api/spamdetection/status/555dbbb63f75406db2edf9f1f092de95"
}
```
The orchestration will:
1. Analyze the email content using the SpamDetectionAgent
2. If spam: Mark the email as spam with a reason
3. If legitimate: Use the EmailAssistantAgent to draft a professional response and "send" it
Once the orchestration has completed, you can get the status of the orchestration by sending a GET request to the `statusQueryGetUri` URL. The response for the legitimate email will be a JSON object that looks something like the following:
```json
{
"failureDetails": null,
"input": {
"email_content": "Hi John, I hope you're doing well. I wanted to follow up on our meeting yesterday about the quarterly report. Could you please send me the updated figures by Friday? Thanks!",
"email_id": "email-001"
},
"instanceId": "555dbbb63f75406db2edf9f1f092de95",
"output": "Email sent: Subject: Re: Follow-Up on Quarterly Report\n\nHi [Recipient's Name],\n\nI hope this message finds you well. Thank you for your patience. I will ensure the updated figures for the quarterly report are sent to you by Friday.\n\nIf you have any further questions or need additional information, please feel free to reach out.\n\nBest regards,\n\nJohn",
"runtimeStatus": "Completed"
}
```
The response for the spam email will be a JSON object that looks something like the following, which indicates that the email was marked as spam:
```json
{
"failureDetails": null,
"input": {
"email_content": "URGENT! You have won $1,000,000! Click here now to claim your prize! Limited time offer! Do not miss out!",
"email_id": "email-002"
},
"instanceId": "555dbbb63f75406db2edf9f1f092de95",
"output": "Email marked as spam: The email contains misleading claims of winning a large sum of money and encourages immediate action, which are common characteristics of spam.",
"runtimeStatus": "Completed"
}
```
@@ -1,18 +0,0 @@
### Test spam detection with a legitimate email
POST http://localhost:7071/api/spamdetection/run
Content-Type: application/json
{
"email_id": "email-001",
"email_content": "Hi John, I hope you're doing well. I wanted to follow up on our meeting yesterday about the quarterly report. Could you please send me the updated figures by Friday? Thanks!"
}
### Test spam detection with a spam email
POST http://localhost:7071/api/spamdetection/run
Content-Type: application/json
{
"email_id": "email-002",
"email_content": "URGENT! You've won $1,000,000! Click here now to claim your prize! Limited time offer! Don't miss out!"
}
@@ -1,20 +0,0 @@
{
"version": "2.0",
"logging": {
"logLevel": {
"Microsoft.Agents.AI.DurableTask": "Information",
"Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
"DurableTask": "Information",
"Microsoft.DurableTask": "Information"
}
},
"extensions": {
"durableTask": {
"hubName": "default",
"storageProvider": {
"type": "AzureManaged",
"connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
}
}
}
}
@@ -1,10 +0,0 @@
{
"IsEncrypted": false,
"Values": {
"FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
"AzureWebJobsStorage": "UseDevelopmentStorage=true",
"DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None",
"AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
"AZURE_OPENAI_DEPLOYMENT": "<AZURE_OPENAI_DEPLOYMENT>"
}
}
@@ -1,43 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFramework>net9.0</TargetFramework>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
<OutputType>Exe</OutputType>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<!-- The Functions build tools don't like namespaces that start with a number -->
<AssemblyName>AgentOrchestration_HITL</AssemblyName>
<RootNamespace>AgentOrchestration_HITL</RootNamespace>
<NoWarn>$(NoWarn);DURABLE0001;DURABLE0002;DURABLE0003;DURABLE0004;DURABLE0005;DURABLE0006</NoWarn>
</PropertyGroup>
<ItemGroup>
<FrameworkReference Include="Microsoft.AspNetCore.App" />
</ItemGroup>
<!-- Azure Functions packages -->
<ItemGroup>
<PackageReference Include="Microsoft.Azure.Functions.Worker" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
<!--
<ItemGroup>
<PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
</ItemGroup>
-->
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
</ItemGroup>
</Project>
@@ -1,229 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Net;
using System.Text.Json;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.DurableTask;
using Microsoft.Azure.Functions.Worker;
using Microsoft.Azure.Functions.Worker.Http;
using Microsoft.DurableTask;
using Microsoft.DurableTask.Client;
using Microsoft.Extensions.Logging;
namespace AgentOrchestration_HITL;
public static class FunctionTriggers
{
[Function(nameof(RunOrchestrationAsync))]
public static async Task<object> RunOrchestrationAsync(
[OrchestrationTrigger] TaskOrchestrationContext context)
{
// Get the input from the orchestration
ContentGenerationInput input = context.GetInput<ContentGenerationInput>()
?? throw new InvalidOperationException("Content generation input is required");
// Get the writer agent
DurableAIAgent writerAgent = context.GetAgent("WriterAgent");
AgentThread writerThread = writerAgent.GetNewThread();
// Set initial status
context.SetCustomStatus($"Starting content generation for topic: {input.Topic}");
// Step 1: Generate initial content
AgentRunResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
message: $"Write a short article about '{input.Topic}'.",
thread: writerThread);
GeneratedContent content = writerResponse.Result;
// Human-in-the-loop iteration - we set a maximum number of attempts to avoid infinite loops
int iterationCount = 0;
while (iterationCount++ < input.MaxReviewAttempts)
{
context.SetCustomStatus(
$"Requesting human feedback. Iteration #{iterationCount}. Timeout: {input.ApprovalTimeoutHours} hour(s).");
// Step 2: Notify user to review the content
await context.CallActivityAsync(nameof(NotifyUserForApproval), content);
// Step 3: Wait for human feedback with configurable timeout
HumanApprovalResponse humanResponse;
try
{
humanResponse = await context.WaitForExternalEvent<HumanApprovalResponse>(
eventName: "HumanApproval",
timeout: TimeSpan.FromHours(input.ApprovalTimeoutHours));
}
catch (OperationCanceledException)
{
// Timeout occurred - treat as rejection
context.SetCustomStatus(
$"Human approval timed out after {input.ApprovalTimeoutHours} hour(s). Treating as rejection.");
throw new TimeoutException($"Human approval timed out after {input.ApprovalTimeoutHours} hour(s).");
}
if (humanResponse.Approved)
{
context.SetCustomStatus("Content approved by human reviewer. Publishing content...");
// Step 4: Publish the approved content
await context.CallActivityAsync(nameof(PublishContent), content);
context.SetCustomStatus($"Content published successfully at {context.CurrentUtcDateTime:s}");
return new { content = content.Content };
}
context.SetCustomStatus("Content rejected by human reviewer. Incorporating feedback and regenerating...");
// Incorporate human feedback and regenerate
writerResponse = await writerAgent.RunAsync<GeneratedContent>(
message: $"""
The content was rejected by a human reviewer. Please rewrite the article incorporating their feedback.
Human Feedback: {humanResponse.Feedback}
""",
thread: writerThread);
content = writerResponse.Result;
}
// If we reach here, it means we exhausted the maximum number of iterations
throw new InvalidOperationException(
$"Content could not be approved after {input.MaxReviewAttempts} iterations.");
}
// POST /hitl/run
[Function(nameof(StartOrchestrationAsync))]
public static async Task<HttpResponseData> StartOrchestrationAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = "hitl/run")] HttpRequestData req,
[DurableClient] DurableTaskClient client)
{
// Read the input from the request body
ContentGenerationInput? input = await req.ReadFromJsonAsync<ContentGenerationInput>();
if (input is null || string.IsNullOrWhiteSpace(input.Topic))
{
HttpResponseData badRequestResponse = req.CreateResponse(HttpStatusCode.BadRequest);
await badRequestResponse.WriteAsJsonAsync(new { error = "Topic is required" });
return badRequestResponse;
}
string instanceId = await client.ScheduleNewOrchestrationInstanceAsync(
orchestratorName: nameof(RunOrchestrationAsync),
input: input);
HttpResponseData response = req.CreateResponse(HttpStatusCode.Accepted);
await response.WriteAsJsonAsync(new
{
message = "HITL content generation orchestration started.",
topic = input.Topic,
instanceId,
statusQueryGetUri = GetStatusQueryGetUri(req, instanceId),
});
return response;
}
// POST /hitl/approve/{instanceId}
[Function(nameof(SendHumanApprovalAsync))]
public static async Task<HttpResponseData> SendHumanApprovalAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = "hitl/approve/{instanceId}")] HttpRequestData req,
string instanceId,
[DurableClient] DurableTaskClient client)
{
// Read the approval response from the request body
HumanApprovalResponse? approvalResponse = await req.ReadFromJsonAsync<HumanApprovalResponse>();
if (approvalResponse is null)
{
HttpResponseData badRequestResponse = req.CreateResponse(HttpStatusCode.BadRequest);
await badRequestResponse.WriteAsJsonAsync(new { error = "Approval response is required" });
return badRequestResponse;
}
// Send the approval event to the orchestration
await client.RaiseEventAsync(instanceId, "HumanApproval", approvalResponse);
HttpResponseData response = req.CreateResponse(HttpStatusCode.OK);
await response.WriteAsJsonAsync(new
{
message = "Human approval sent to orchestration.",
instanceId,
approved = approvalResponse.Approved
});
return response;
}
// GET /hitl/status/{instanceId}
[Function(nameof(GetOrchestrationStatusAsync))]
public static async Task<HttpResponseData> GetOrchestrationStatusAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "get", Route = "hitl/status/{instanceId}")] HttpRequestData req,
string instanceId,
[DurableClient] DurableTaskClient client)
{
OrchestrationMetadata? status = await client.GetInstanceAsync(
instanceId,
getInputsAndOutputs: true,
req.FunctionContext.CancellationToken);
if (status is null)
{
HttpResponseData notFound = req.CreateResponse(HttpStatusCode.NotFound);
await notFound.WriteAsJsonAsync(new { error = "Instance not found" });
return notFound;
}
HttpResponseData response = req.CreateResponse(HttpStatusCode.OK);
await response.WriteAsJsonAsync(new
{
instanceId = status.InstanceId,
runtimeStatus = status.RuntimeStatus.ToString(),
workflowStatus = status.SerializedCustomStatus is not null ? (object)status.ReadCustomStatusAs<JsonElement>() : null,
input = status.SerializedInput is not null ? (object)status.ReadInputAs<JsonElement>() : null,
output = status.SerializedOutput is not null ? (object)status.ReadOutputAs<JsonElement>() : null,
failureDetails = status.FailureDetails
});
return response;
}
[Function(nameof(NotifyUserForApproval))]
public static void NotifyUserForApproval(
[ActivityTrigger] GeneratedContent content,
FunctionContext functionContext)
{
ILogger logger = functionContext.GetLogger(nameof(NotifyUserForApproval));
// In a real implementation, this would send notifications via email, SMS, etc.
logger.LogInformation(
"""
NOTIFICATION: Please review the following content for approval:
Title: {Title}
Content: {Content}
Use the approval endpoint to approve or reject this content.
""",
content.Title,
content.Content);
}
[Function(nameof(PublishContent))]
public static void PublishContent(
[ActivityTrigger] GeneratedContent content,
FunctionContext functionContext)
{
ILogger logger = functionContext.GetLogger(nameof(PublishContent));
// In a real implementation, this would publish to a CMS, website, etc.
logger.LogInformation(
"""
PUBLISHING: Content has been published successfully.
Title: {Title}
Content: {Content}
""",
content.Title,
content.Content);
}
private static string GetStatusQueryGetUri(HttpRequestData req, string instanceId)
{
// NOTE: This can be made more robust by considering the value of
// request headers like "X-Forwarded-Host" and "X-Forwarded-Proto".
string authority = $"{req.Url.Scheme}://{req.Url.Authority}";
return $"{authority}/api/hitl/status/{instanceId}";
}
}
@@ -1,44 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace AgentOrchestration_HITL;
/// <summary>
/// Represents the input for the Human-in-the-Loop content generation workflow.
/// </summary>
public sealed class ContentGenerationInput
{
[JsonPropertyName("topic")]
public string Topic { get; set; } = string.Empty;
[JsonPropertyName("max_review_attempts")]
public int MaxReviewAttempts { get; set; } = 3;
[JsonPropertyName("approval_timeout_hours")]
public float ApprovalTimeoutHours { get; set; } = 72;
}
/// <summary>
/// Represents the content generated by the writer agent.
/// </summary>
public sealed class GeneratedContent
{
[JsonPropertyName("title")]
public string Title { get; set; } = string.Empty;
[JsonPropertyName("content")]
public string Content { get; set; } = string.Empty;
}
/// <summary>
/// Represents the human approval response.
/// </summary>
public sealed class HumanApprovalResponse
{
[JsonPropertyName("approved")]
public bool Approved { get; set; }
[JsonPropertyName("feedback")]
public string Feedback { get; set; } = string.Empty;
}
@@ -1,40 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Azure;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hosting.AzureFunctions;
using Microsoft.Azure.Functions.Worker.Builder;
using Microsoft.Extensions.Hosting;
using OpenAI;
// Get the Azure OpenAI endpoint and deployment name from environment variables.
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
// Single agent used by the orchestration to demonstrate human-in-the-loop workflow.
const string WriterName = "WriterAgent";
const string WriterInstructions =
"""
You are a professional content writer who creates high-quality articles on various topics.
You write engaging, informative, and well-structured content that follows best practices for readability and accuracy.
""";
AIAgent writerAgent = client.GetChatClient(deploymentName).CreateAIAgent(WriterInstructions, WriterName);
using IHost app = FunctionsApplication
.CreateBuilder(args)
.ConfigureFunctionsWebApplication()
.ConfigureDurableAgents(options => options.AddAIAgent(writerAgent))
.Build();
app.Run();
@@ -1,126 +0,0 @@
# Multi-Agent Orchestration with Human-in-the-Loop Sample
This sample demonstrates how to use the Durable Agent Framework (DAFx) to create a human-in-the-loop (HITL) workflow using a single AI agent. The workflow uses a writer agent to generate content and requires human approval on every iteration, emphasizing the human-in-the-loop pattern.
## Key Concepts Demonstrated
- Single-agent orchestration
- Human-in-the-loop feedback loop using external events (`WaitForExternalEvent`)
- Activity functions for non-agentic workflow steps
- Iterative content refinement based on human feedback
- Custom status tracking for workflow visibility
- Error handling with maximum retry attempts and timeout handling for human approval
## Environment Setup
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
## Running the Sample
With the environment setup and function app running, you can test the sample by sending an HTTP request with a topic to start the content generation workflow.
You can use the `demo.http` file to send a topic to the agents, or a command line tool like `curl` as shown below:
Bash (Linux/macOS/WSL):
```bash
curl -X POST http://localhost:7071/api/hitl/run \
-H "Content-Type: application/json" \
-d '{
"topic": "The Future of Artificial Intelligence",
"max_review_attempts": 3,
"timeout_minutes": 5
}'
```
PowerShell:
```powershell
$body = @{
topic = "The Future of Artificial Intelligence"
max_review_attempts = 3
timeout_minutes = 5
} | ConvertTo-Json
Invoke-RestMethod -Method Post `
-Uri http://localhost:7071/api/hitl/run `
-ContentType application/json `
-Body $body
```
The response will be a JSON object that looks something like the following, which indicates that the orchestration has started.
```json
{
"message": "HITL content generation orchestration started.",
"topic": "The Future of Artificial Intelligence",
"instanceId": "a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6",
"statusQueryGetUri": "http://localhost:7071/api/hitl/status/a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6"
}
```
The orchestration will:
1. Generate initial content using the WriterAgent
2. Notify the user to review the content
3. Wait for human feedback via external event (configurable timeout)
4. If approved by human, publish the content
5. If rejected by human, incorporate feedback and regenerate content
6. If approval timeout occurs, treat as rejection and fail the orchestration
7. Repeat until human approval is received or maximum loop iterations are reached
Once the orchestration is waiting for human approval, you can send approval or rejection using the approval endpoint:
Bash (Linux/macOS/WSL):
```bash
# Approve the content
curl -X POST http://localhost:7071/api/hitl/approve/a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6 \
-H "Content-Type: application/json" \
-d '{
"approved": true,
"feedback": "Great article! The content is well-structured and informative."
}'
# Reject the content with feedback
curl -X POST http://localhost:7071/api/hitl/approve/a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6 \
-H "Content-Type: application/json" \
-d '{
"approved": false,
"feedback": "The article needs more technical depth and better examples."
}'
```
PowerShell:
```powershell
# Approve the content
Invoke-RestMethod -Method Post `
-Uri http://localhost:7071/api/hitl/approve/a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6 `
-ContentType application/json `
-Body '{ "approved": true, "feedback": "Great article! The content is well-structured and informative." }'
# Reject the content with feedback
Invoke-RestMethod -Method Post `
-Uri http://localhost:7071/api/hitl/approve/a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6 `
-ContentType application/json `
-Body '{ "approved": false, "feedback": "The article needs more technical depth and better examples." }'
```
Once the orchestration has completed, you can get the status by sending a GET request to the `statusQueryGetUri` URL. The response will be a JSON object that looks something like the following:
```json
{
"failureDetails": null,
"input": {
"topic": "The Future of Artificial Intelligence",
"max_review_attempts": 3
},
"instanceId": "a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6",
"output": {
"content": "The Future of Artificial Intelligence is..."
},
"runtimeStatus": "Completed",
"workflowStatus": "Content published successfully at 2025-10-15T12:00:00Z"
}
```
@@ -1,44 +0,0 @@
### Start the HITL content generation orchestration with default timeout (30 days)
POST http://localhost:7071/api/hitl/run
Content-Type: application/json
{
"topic": "The Future of Artificial Intelligence",
"max_review_attempts": 3
}
### Start the HITL content generation orchestration with very short timeout for demonstration (~4 seconds)
POST http://localhost:7071/api/hitl/run
Content-Type: application/json
{
"topic": "The Future of Artificial Intelligence",
"max_review_attempts": 3,
"approval_timeout_hours": 0.001
}
### Copy/paste the instanceId from the response above
@instanceId=INSTANCE_ID_GOES_HERE
### Check the status of the orchestration (replace {instanceId} with the actual instance ID from the response above)
GET http://localhost:7071/api/hitl/status/{{instanceId}}
### Send human approval (replace {instanceId} with the actual instance ID)
POST http://localhost:7071/api/hitl/approve/{{instanceId}}
Content-Type: application/json
{
"approved": true,
"feedback": "Great article! The content is well-structured and informative."
}
### Send human rejection with feedback (replace {instanceId} with the actual instance ID)
POST http://localhost:7071/api/hitl/approve/{{instanceId}}
Content-Type: application/json
{
"approved": false,
"feedback": "The article needs more technical depth and better examples. Please add more specific use cases and implementation details."
}
@@ -1,20 +0,0 @@
{
"version": "2.0",
"logging": {
"logLevel": {
"Microsoft.Agents.AI.DurableTask": "Information",
"Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
"DurableTask": "Information",
"Microsoft.DurableTask": "Information"
}
},
"extensions": {
"durableTask": {
"hubName": "default",
"storageProvider": {
"type": "AzureManaged",
"connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
}
}
}
}
@@ -1,10 +0,0 @@
{
"IsEncrypted": false,
"Values": {
"FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
"AzureWebJobsStorage": "UseDevelopmentStorage=true",
"DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None",
"AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
"AZURE_OPENAI_DEPLOYMENT": "<AZURE_OPENAI_DEPLOYMENT>"
}
}
@@ -1,42 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFramework>net9.0</TargetFramework>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
<OutputType>Exe</OutputType>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<!-- The Functions build tools don't like namespaces that start with a number -->
<AssemblyName>LongRunningTools</AssemblyName>
<RootNamespace>LongRunningTools</RootNamespace>
</PropertyGroup>
<ItemGroup>
<FrameworkReference Include="Microsoft.AspNetCore.App" />
</ItemGroup>
<!-- Azure Functions packages -->
<ItemGroup>
<PackageReference Include="Microsoft.Azure.Functions.Worker" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
<!--
<ItemGroup>
<PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
</ItemGroup>
-->
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
</ItemGroup>
</Project>
@@ -1,151 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.DurableTask;
using Microsoft.Azure.Functions.Worker;
using Microsoft.DurableTask;
using Microsoft.Extensions.Logging;
namespace LongRunningTools;
public static class FunctionTriggers
{
[Function(nameof(RunOrchestrationAsync))]
public static async Task<object> RunOrchestrationAsync(
[OrchestrationTrigger] TaskOrchestrationContext context)
{
// Get the input from the orchestration
ContentGenerationInput input = context.GetInput<ContentGenerationInput>()
?? throw new InvalidOperationException("Content generation input is required");
// Get the writer agent
DurableAIAgent writerAgent = context.GetAgent("Writer");
AgentThread writerThread = writerAgent.GetNewThread();
// Set initial status
context.SetCustomStatus($"Starting content generation for topic: {input.Topic}");
// Step 1: Generate initial content
AgentRunResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
message: $"Write a short article about '{input.Topic}'.",
thread: writerThread);
GeneratedContent content = writerResponse.Result;
// Human-in-the-loop iteration - we set a maximum number of attempts to avoid infinite loops
int iterationCount = 0;
while (iterationCount++ < input.MaxReviewAttempts)
{
context.SetCustomStatus(
new
{
message = "Requesting human feedback.",
approvalTimeoutHours = input.ApprovalTimeoutHours,
iterationCount,
content
});
// Step 2: Notify user to review the content
await context.CallActivityAsync(nameof(NotifyUserForApproval), content);
// Step 3: Wait for human feedback with configurable timeout
HumanApprovalResponse humanResponse;
try
{
humanResponse = await context.WaitForExternalEvent<HumanApprovalResponse>(
eventName: "HumanApproval",
timeout: TimeSpan.FromHours(input.ApprovalTimeoutHours));
}
catch (OperationCanceledException)
{
// Timeout occurred - treat as rejection
context.SetCustomStatus(
new
{
message = $"Human approval timed out after {input.ApprovalTimeoutHours} hour(s). Treating as rejection.",
iterationCount,
content
});
throw new TimeoutException($"Human approval timed out after {input.ApprovalTimeoutHours} hour(s).");
}
if (humanResponse.Approved)
{
context.SetCustomStatus(new
{
message = "Content approved by human reviewer. Publishing content...",
content
});
// Step 4: Publish the approved content
await context.CallActivityAsync(nameof(PublishContent), content);
context.SetCustomStatus(new
{
message = $"Content published successfully at {context.CurrentUtcDateTime:s}",
humanFeedback = humanResponse,
content
});
return new { content = content.Content };
}
context.SetCustomStatus(new
{
message = "Content rejected by human reviewer. Incorporating feedback and regenerating...",
humanFeedback = humanResponse,
content
});
// Incorporate human feedback and regenerate
writerResponse = await writerAgent.RunAsync<GeneratedContent>(
message: $"""
The content was rejected by a human reviewer. Please rewrite the article incorporating their feedback.
Human Feedback: {humanResponse.Feedback}
""",
thread: writerThread);
content = writerResponse.Result;
}
// If we reach here, it means we exhausted the maximum number of iterations
throw new InvalidOperationException(
$"Content could not be approved after {input.MaxReviewAttempts} iterations.");
}
[Function(nameof(NotifyUserForApproval))]
public static void NotifyUserForApproval(
[ActivityTrigger] GeneratedContent content,
FunctionContext functionContext)
{
ILogger logger = functionContext.GetLogger(nameof(NotifyUserForApproval));
// In a real implementation, this would send notifications via email, SMS, etc.
logger.LogInformation(
"""
NOTIFICATION: Please review the following content for approval:
Title: {Title}
Content: {Content}
Use the approval endpoint to approve or reject this content.
""",
content.Title,
content.Content);
}
[Function(nameof(PublishContent))]
public static void PublishContent(
[ActivityTrigger] GeneratedContent content,
FunctionContext functionContext)
{
ILogger logger = functionContext.GetLogger(nameof(PublishContent));
// In a real implementation, this would publish to a CMS, website, etc.
logger.LogInformation(
"""
PUBLISHING: Content has been published successfully.
Title: {Title}
Content: {Content}
""",
content.Title,
content.Content);
}
}
@@ -1,44 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
namespace LongRunningTools;
/// <summary>
/// Represents the input for the content generation workflow.
/// </summary>
public sealed class ContentGenerationInput
{
[JsonPropertyName("topic")]
public string Topic { get; set; } = string.Empty;
[JsonPropertyName("max_review_attempts")]
public int MaxReviewAttempts { get; set; } = 3;
[JsonPropertyName("approval_timeout_hours")]
public float ApprovalTimeoutHours { get; set; } = 72;
}
/// <summary>
/// Represents the content generated by the writer agent.
/// </summary>
public sealed class GeneratedContent
{
[JsonPropertyName("title")]
public string Title { get; set; } = string.Empty;
[JsonPropertyName("content")]
public string Content { get; set; } = string.Empty;
}
/// <summary>
/// Represents the human approval response.
/// </summary>
public sealed class HumanApprovalResponse
{
[JsonPropertyName("approved")]
public bool Approved { get; set; }
[JsonPropertyName("feedback")]
public string Feedback { get; set; } = string.Empty;
}
@@ -1,73 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Azure;
using Azure.AI.OpenAI;
using Azure.Identity;
using LongRunningTools;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hosting.AzureFunctions;
using Microsoft.Azure.Functions.Worker.Builder;
using Microsoft.Extensions.AI;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Hosting;
using Microsoft.Extensions.Logging;
using OpenAI;
// Get the Azure OpenAI endpoint and deployment name from environment variables.
string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
// Agent used by the orchestration to write content.
const string WriterAgentName = "Writer";
const string WriterAgentInstructions =
"""
You are a professional content writer who creates high-quality articles on various topics.
You write engaging, informative, and well-structured content that follows best practices for readability and accuracy.
""";
AIAgent writerAgent = client.GetChatClient(deploymentName).CreateAIAgent(WriterAgentInstructions, WriterAgentName);
// Agent that can start content generation workflows using tools
const string PublisherAgentName = "Publisher";
const string PublisherAgentInstructions =
"""
You are a publishing agent that can manage content generation workflows.
You have access to tools to start, monitor, and raise events for content generation workflows.
""";
using IHost app = FunctionsApplication
.CreateBuilder(args)
.ConfigureFunctionsWebApplication()
.ConfigureDurableAgents(options =>
{
// Add the writer agent used by the orchestration
options.AddAIAgent(writerAgent);
// Define the agent that can start orchestrations from tool calls
options.AddAIAgentFactory(PublisherAgentName, sp =>
{
// Initialize the tools to be used by the agent.
Tools publisherTools = new(sp.GetRequiredService<ILogger<Tools>>());
return client.GetChatClient(deploymentName).CreateAIAgent(
instructions: PublisherAgentInstructions,
name: PublisherAgentName,
services: sp,
tools: [
AIFunctionFactory.Create(publisherTools.StartContentGenerationWorkflow),
AIFunctionFactory.Create(publisherTools.GetWorkflowStatusAsync),
AIFunctionFactory.Create(publisherTools.SubmitHumanApprovalAsync),
]);
});
})
.Build();
app.Run();
@@ -1,129 +0,0 @@
# Long Running Tools Sample
This sample demonstrates how to use the Durable Agent Framework (DAFx) to create agents with long running tools. This sample builds on the [05_AgentOrchestration_HITL](../05_AgentOrchestration_HITL) sample by adding a publisher agent that can start and manage content generation workflows. A key difference is that the publisher agent knows the IDs of the workflows it starts, so it can check the status of the workflows and approve or reject them without being explicitly given the context (instance IDs, etc).
## Key Concepts Demonstrated
The same key concepts as the [05_AgentOrchestration_HITL](../05_AgentOrchestration_HITL) sample are demonstrated, but with the following additional concepts:
- **Long running tools**: Using `DurableAgentContext.Current` to start orchestrations from tool calls
- **Multi-agent orchestration**: Agents can start and manage workflows that orchestrate other agents
- **Human-in-the-loop (with delegation)**: The agent acts as an intermediary between the human and the workflow. The human remains in the loop, but delegates to the agent to start the workflow and approve or reject the content.
## Environment Setup
See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
## Running the Sample
With the environment setup and function app running, you can test the sample by sending an HTTP request to start the agent, which will then trigger the content generation workflow.
You can use the `demo.http` file to send requests to the agent, or a command line tool like `curl` as shown below.
Bash (Linux/macOS/WSL):
```bash
curl -i -X POST http://localhost:7071/api/agents/publisher/run \
-D headers.txt \
-H "Content-Type: text/plain" \
-d 'Start a content generation workflow for the topic \"The Future of Artificial Intelligence\"'
# Save the thread ID to a variable and print it to the terminal
threadId=$(cat headers.txt | grep "x-ms-thread-id" | cut -d' ' -f2)
echo "Thread ID: $threadId"
```
PowerShell:
```powershell
Invoke-RestMethod -Method Post `
-Uri http://localhost:7071/api/agents/publisher/run `
-ResponseHeadersVariable ResponseHeaders `
-ContentType text/plain `
-Body 'Start a content generation workflow for the topic \"The Future of Artificial Intelligence\"' `
# Save the thread ID to a variable and print it to the console
$threadId = $ResponseHeaders['x-ms-thread-id']
Write-Host "Thread ID: $threadId"
```
The response will be a text string that looks something like the following, indicating that the agent request has been received and will be processed:
```http
HTTP/1.1 200 OK
Content-Type: text/plain
x-ms-thread-id: 351ec855-7f4d-4527-a60d-498301ced36d
The content generation workflow for the topic "The Future of Artificial Intelligence" has been successfully started, and the instance ID is **6a04276e8d824d8d941e1dc4142cc254**. If you need any further assistance or updates on the workflow, feel free to ask!
```
The `x-ms-thread-id` response header contains the thread ID, which can be used to continue the conversation by passing it as a query parameter (`thread_id`) to the `run` endpoint. The commands above show how to save the thread ID to a `$threadId` variable for use in subsequent requests.
Behind the scenes, the publisher agent will:
1. Start the content generation workflow via a tool call
1. The workflow will generate initial content using the Writer agent and wait for human approval, which will be visible in the logs
Once the workflow is waiting for human approval, you can send approval or rejection by prompting the publisher agent accordingly (e.g. "Approve the content" or "Reject the content with feedback: The article needs more technical depth and better examples."):
Bash (Linux/macOS/WSL):
```bash
# Approve the content
curl -X POST "http://localhost:7071/api/agents/publisher/run?thread_id=$threadId" \
-H "Content-Type: text/plain" \
-d 'Approve the content'
# Reject the content with feedback
curl -X POST "http://localhost:7071/api/agents/publisher/run?thread_id=$threadId" \
-H "Content-Type: text/plain" \
-d 'Reject the content with feedback: The article needs more technical depth and better examples.'
```
PowerShell:
```powershell
# Approve the content
Invoke-RestMethod -Method Post `
-Uri "http://localhost:7071/api/agents/publisher/run?thread_id=$threadId" `
-ContentType text/plain `
-Body 'Approve the content'
# Reject the content with feedback
Invoke-RestMethod -Method Post `
-Uri "http://localhost:7071/api/agents/publisher/run?thread_id=$threadId" `
-ContentType text/plain `
-Body 'Reject the content with feedback: The article needs more technical depth and better examples.'
```
Once the workflow has completed, you can get the status by prompting the publisher agent to give you the status.
Bash (Linux/macOS/WSL):
```bash
curl -X POST "http://localhost:7071/api/agents/publisher/run?thread_id=$threadId" \
-H "Content-Type: text/plain" \
-d 'Get the status of the workflow you previously started'
```
PowerShell:
```powershell
Invoke-RestMethod -Method Post `
-Uri "http://localhost:7071/api/agents/publisher/run?thread_id=$threadId" `
-ContentType text/plain `
-Body 'Get the status of the workflow you previously started'
```
The response from the publisher agent will look something like the following:
```text
The status of the workflow with instance ID **ab1076d6e7ec49d8a2c2474d09b69ded** is as follows:
- **Execution Status:** Completed
- **Workflow Status:** Content published successfully at `2025-10-24T20:42:02`
- **Created At:** `2025-10-24T20:41:40.7531781+00:00`
- **Last Updated At:** `2025-10-24T20:42:02.1410736+00:00`
The content has been successfully published.
```
@@ -1,84 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.ComponentModel;
using Microsoft.Agents.AI.DurableTask;
using Microsoft.DurableTask.Client;
using Microsoft.Extensions.Logging;
namespace LongRunningTools;
/// <summary>
/// Tools that demonstrate starting orchestrations from agent tool calls.
/// </summary>
internal sealed class Tools(ILogger<Tools> logger)
{
private readonly ILogger<Tools> _logger = logger;
[Description("Starts a content generation workflow and returns the instance ID for tracking.")]
public string StartContentGenerationWorkflow([Description("The topic for content generation")] string topic)
{
this._logger.LogInformation("Starting content generation workflow for topic: {Topic}", topic);
const int MaxReviewAttempts = 3;
const float ApprovalTimeoutHours = 72;
// Schedule the orchestration, which will start running after the tool call completes.
string instanceId = DurableAgentContext.Current.ScheduleNewOrchestration(
name: nameof(FunctionTriggers.RunOrchestrationAsync),
input: new ContentGenerationInput
{
Topic = topic,
MaxReviewAttempts = MaxReviewAttempts,
ApprovalTimeoutHours = ApprovalTimeoutHours
});
this._logger.LogInformation(
"Content generation workflow scheduled to be started for topic '{Topic}' with instance ID: {InstanceId}",
topic,
instanceId);
return $"Workflow started with instance ID: {instanceId}";
}
[Description("Gets the status of a workflow orchestration.")]
public async Task<object> GetWorkflowStatusAsync(
[Description("The instance ID of the workflow to check")] string instanceId,
[Description("Whether to include detailed information")] bool includeDetails = true)
{
this._logger.LogInformation("Getting status for workflow instance: {InstanceId}", instanceId);
// Get the current agent context using the thread-static property
OrchestrationMetadata? status = await DurableAgentContext.Current.GetOrchestrationStatusAsync(
instanceId,
includeDetails);
if (status is null)
{
this._logger.LogInformation("Workflow instance '{InstanceId}' not found.", instanceId);
return new
{
instanceId,
error = $"Workflow instance '{instanceId}' not found.",
};
}
return new
{
instanceId = status.InstanceId,
createdAt = status.CreatedAt,
executionStatus = status.RuntimeStatus,
workflowStatus = status.SerializedCustomStatus,
lastUpdatedAt = status.LastUpdatedAt,
failureDetails = status.FailureDetails
};
}
[Description("Raises a feedback event for the content generation workflow.")]
public async Task SubmitHumanApprovalAsync(
[Description("The instance ID of the workflow to submit feedback for")] string instanceId,
[Description("Feedback to submit")] HumanApprovalResponse feedback)
{
this._logger.LogInformation("Submitting human approval for workflow instance: {InstanceId}", instanceId);
await DurableAgentContext.Current.RaiseOrchestrationEventAsync(instanceId, "HumanApproval", feedback);
}
}
@@ -1,27 +0,0 @@
### Run an agent that can schedule orchestrations as tool calls
POST http://localhost:7071/api/agents/publisher/run
Content-Type: text/plain
Start a content generation workflow for the topic 'The Future of Artificial Intelligence'
### Save the session ID from the response to continue the conversation
@threadId = <YOUR_THREAD_ID>
### Check the status of the workflow
POST http://localhost:7071/api/agents/publisher/run?thread_id={{threadId}}
Content-Type: text/plain
Check the status of the workflow you previously started
### Reject content with feedback
POST http://localhost:7071/api/agents/publisher/run?thread_id={{threadId}}
Content-Type: text/plain
Reject the content with feedback: The article needs more technical depth and better examples.
### Approve content
POST http://localhost:7071/api/agents/publisher/run?thread_id={{threadId}}
Content-Type: text/plain
Approve the content
@@ -1,20 +0,0 @@
{
"version": "2.0",
"logging": {
"logLevel": {
"Microsoft.Agents.AI.DurableTask": "Information",
"Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
"DurableTask": "Information",
"Microsoft.DurableTask": "Information"
}
},
"extensions": {
"durableTask": {
"hubName": "default",
"storageProvider": {
"type": "AzureManaged",
"connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
}
}
}
}

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