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Author SHA1 Message Date
Dmytro Struk 1a6ff77fcc Added AI Search example 2025-11-12 13:59:31 -08:00
Dmytro StrukandGitHub 562064cbde Merge branch 'main' into feature-python-foundry-agents 2025-11-12 12:59:17 -08:00
Dmytro Struk 5c74c3fd9c Addressed PR feedback 2025-11-12 12:48:23 -08:00
Dmytro StrukandGitHub 71358853fb Python: [Feature Branch] Resolve CI issues (#2143)
* Small documentation and code fixes

* Small fix in documentation
2025-11-12 11:54:40 -08:00
Dmytro StrukandGitHub 693d5c941d Updated azure-ai-projects package version and small fixes (#2139) 2025-11-12 10:40:35 -08:00
Dmytro Struk f309a2818b Merge branch 'main' into feature-python-foundry-agents 2025-11-12 07:53:38 -08:00
Dmytro Struk f55ac70178 Merge branch 'main' into feature-python-foundry-agents 2025-11-11 23:17:45 -08:00
+19
Dmytro StrukGitHubdependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>ChrisCopilotkzucopilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>Reuben BondPeter IbekweJeff HandleyDaniel RothVictor DibiaMark WallaceShawn HenryJavier Calvarro NelsonEvan MattsonEduard van ValkenburgKorolev Dmitrywesteydependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>Reuben BondTao ChenwuwengRoger BarretoSergeyMenshykhCopilotJacob AlberGiles OdigweDaniel Cazzulino
361c47f30f Python: [Feature Branch] Merge from main to Azure AI branch (#2111)
* Do not build DevUI assets during .NET project build (#2010)

* .NET: Add unit tests for declarative executor SetMultipleVariables (#2016)

* Add unit tests for create conversation executor

* Update indentation and comment typo.

* Added unit tests for declarative executor SetMultipleVariablesExecutor

* Updated comments and syntactic sugar

* Python: DevUI: Use metadata.entity_id instead of model field (#1984)

* DevUI: Use metadata.entity_id for agent/workflow name instead of model field

* OpenAI Responses: add explicit request validation

* Review feedback

* .NET: DevUI - Do not automatically add/map OpenAI services/endpoints (#2014)

* Don't add OpenAIResponses as part of Dev UI

You should be able to add and remove Dev UI without impacting your other production endpoints.

* Remove `AddDevUI()` and do not map OpenAI endpoints from `MapDevUI()`

* Fix comment wording

* Revise documentation

---------

Co-authored-by: Daniel Roth <daroth@microsoft.com>

* Python: DevUI: Add OpenAI Responses API proxy support  + HIL for Workflows (#1737)

* DevUI: Add OpenAI Responses API proxy support with enhanced UI features

This commit adds support for proxying requests to OpenAI's Responses API,
allowing DevUI to route conversations to OpenAI models when configured to enable testing.

Backend changes:
- Add OpenAI proxy executor with conversation routing logic
- Enhance event mapper to support OpenAI Responses API format
- Extend server endpoints to handle OpenAI proxy mode
- Update models with OpenAI-specific response types
- Remove emojis from logging and CLI output for cleaner text

Frontend changes:
- Add settings modal with OpenAI proxy configuration UI
- Enhance agent and workflow views with improved state management
- Add new UI components (separator, switch) for settings
- Update debug panel with better event filtering
- Improve message renderers for OpenAI content types
- Update types and API client for OpenAI integration

* update ui, settings modal and workflow input form, add register cleanup hooks.

* add workflow HIL support, user mode, other fixes

* feat(devui): add human-in-the-loop (HIL) support with dynamic response schemas

Implement  HIL workflow support allowing workflows to pause for user input
with dynamically generated JSON schemas based on response handler type hints.

Key Features:
- Automatic response schema extraction from @response_handler decorators
- Dynamic form generation in UI based on Pydantic/dataclass response types
- Checkpoint-based conversation storage for HIL requests/responses
- Resume workflow execution after user provides HIL response

Backend Changes:
- Add extract_response_type_from_executor() to introspect response handlers
- Enrich RequestInfoEvent with response_schema via _enrich_request_info_event_with_response_schema()
- Map RequestInfoEvent to response.input.requested OpenAI event format
- Store HIL responses in conversation history and restore checkpoints

Frontend Changes:
- Add HILInputModal component with SchemaFormRenderer for dynamic forms
- Support Pydantic BaseModel and dataclass response types
- Render enum fields as dropdowns, strings as text/textarea, numbers, booleans, arrays, objects
- Display original request context alongside response form

Testing:
- Add  tests for checkpoint storage (test_checkpoints.py)
- Add schema generation tests for all input types (test_schema_generation.py)
- Validate end-to-end HIL flow with spam workflow sample

This enables workflows to seamlessly pause execution and request structured user input
with type-safe, validated forms generated automatically from response type annotations.

* improve HIL support, improve workflow execution view

* ui updates

* ui updates

* improve HIL for workflows, add auth and view modes

* update workflow

* security improvements , ui fixes

* fix mypy error

* update loading spinner in ui

---------

Co-authored-by: Mark Wallace <127216156+markwallace-microsoft@users.noreply.github.com>

* .NET: Remove launchSettings.json from .gitignore in dotnet/samples (#2006)

* Remove launchSettings.json from .gitignore in dotnet/samples

* Update dotnet/samples/GettingStarted/DevUI/DevUI_Step01_BasicUsage/Properties/launchSettings.json

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

* Update dotnet/samples/AGUIClientServer/AGUIServer/Properties/launchSettings.json

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

---------

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

* DevUI: Serialize workflow input as string to maintain conformance with OpenAI Responses format (#2021)

Co-authored-by: Victor Dibia <chuvidi2003@gmail.com>

* Add Microsoft Agent Framework logo to assets (#2007)

* Updated package versions (#2027)

* DevUI: Prevent line breaks within words in the agent view (#2024)

Co-authored-by: Victor Dibia <chuvidi2003@gmail.com>

* .NET [AG-UI]: Adds support for shared state. (#1996)

* Product changes

* Tests

* Dojo project

* Cleanups

* Python: Fix underlying tool choice bug and all for return to previous Handoff subagent (#2037)

* Fix tool_choice override bug and add enable_return_to_previous support

* Add unit test for handoff checkpointing

* Handle tools when we have them

* added missing chatAgent params (#2044)

* .NET: fix ChatCompletions Tools serialization (#2043)

* fix serialization in chat completions on tools

* nit

* .NET: assign AgentCard's URL to mapped-endpoint if not defined explicitly (#2047)

* fix serialization in chat completions on tools

* nit

* write e2e test for agent card resolve + adjust behavior

* nit

* Version 1.0.0-preview.251110.1 (#2048)

* .NET: Remove moved OpenAPI sample and point to SK one. (#1997)

* Remove moved OpenAPI sample and point to SK one.

* Update dotnet/samples/GettingStarted/Agents/README.md

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

---------

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

* Bump AWSSDK.Extensions.Bedrock.MEAI from 4.0.4.2 to 4.0.4.6 (#2031)

---
updated-dependencies:
- dependency-name: AWSSDK.Extensions.Bedrock.MEAI
  dependency-version: 4.0.4.6
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* .NET: Separate all memory and rag samples into their own folders (#2000)

* Separate all memory and rag samples into their own folders

* Fix broken link.

* Python: .Net: Dotnet devui compatibility fixes (#2026)

* DevUI: Add OpenAI Responses API proxy support with enhanced UI features

This commit adds support for proxying requests to OpenAI's Responses API,
allowing DevUI to route conversations to OpenAI models when configured to enable testing.

Backend changes:
- Add OpenAI proxy executor with conversation routing logic
- Enhance event mapper to support OpenAI Responses API format
- Extend server endpoints to handle OpenAI proxy mode
- Update models with OpenAI-specific response types
- Remove emojis from logging and CLI output for cleaner text

Frontend changes:
- Add settings modal with OpenAI proxy configuration UI
- Enhance agent and workflow views with improved state management
- Add new UI components (separator, switch) for settings
- Update debug panel with better event filtering
- Improve message renderers for OpenAI content types
- Update types and API client for OpenAI integration

* update ui, settings modal and workflow input form, add register cleanup hooks.

* add workflow HIL support, user mode, other fixes

* feat(devui): add human-in-the-loop (HIL) support with dynamic response schemas

Implement  HIL workflow support allowing workflows to pause for user input
with dynamically generated JSON schemas based on response handler type hints.

Key Features:
- Automatic response schema extraction from @response_handler decorators
- Dynamic form generation in UI based on Pydantic/dataclass response types
- Checkpoint-based conversation storage for HIL requests/responses
- Resume workflow execution after user provides HIL response

Backend Changes:
- Add extract_response_type_from_executor() to introspect response handlers
- Enrich RequestInfoEvent with response_schema via _enrich_request_info_event_with_response_schema()
- Map RequestInfoEvent to response.input.requested OpenAI event format
- Store HIL responses in conversation history and restore checkpoints

Frontend Changes:
- Add HILInputModal component with SchemaFormRenderer for dynamic forms
- Support Pydantic BaseModel and dataclass response types
- Render enum fields as dropdowns, strings as text/textarea, numbers, booleans, arrays, objects
- Display original request context alongside response form

Testing:
- Add  tests for checkpoint storage (test_checkpoints.py)
- Add schema generation tests for all input types (test_schema_generation.py)
- Validate end-to-end HIL flow with spam workflow sample

This enables workflows to seamlessly pause execution and request structured user input
with type-safe, validated forms generated automatically from response type annotations.

* improve HIL support, improve workflow execution view

* ui updates

* ui updates

* improve HIL for workflows, add auth and view modes

* update workflow

* security improvements , ui fixes

* fix mypy error

* update loading spinner in ui

* DevUI: Serialize workflow input as string to maintain conformance with OpenAI Responses format

* Phase 1: Add /meta endpoint and fix workflow event naming for .NET DevUI compatibility

* additional fixes for .NET DevUI workflow visualization item ID tracking

**Problem:**
.NET DevUI was generating different item IDs for ExecutorInvokedEvent and
ExecutorCompletedEvent, causing only the first executor to highlight in the
workflow graph. Long executor names and error messages also broke UI layout.

**Changes:**
- Add ExecutorActionItemResource to match Python DevUI implementation
- Track item IDs per executor using dictionary in AgentRunResponseUpdateExtensions
- Reuse same item ID across invoked/completed/failed events for proper pairing
- Add truncateText() utility to workflow-utils.ts
- Truncate executor names to 35 chars in execution timeline
- Truncate error messages to 150 chars in workflow graph nodes

** Details:**
- ExecutorActionItemResource registered with JSON source generation context
- Dictionary cleaned up after executor completion/failure to prevent memory leaks
- Frontend item tracking by unique item.id supports multiple executor runs
- All changes follow existing codebase patterns and conventions

Tested with review-workflow showing correct executor highlighting and state
transitions for sequential and concurrent executors.

* format fixes, remove cors tests

* remove unecessary attributes

---------

Co-authored-by: Mark Wallace <127216156+markwallace-microsoft@users.noreply.github.com>
Co-authored-by: Reuben Bond <reuben.bond@gmail.com>

* DevUI: support having both an agent and a workflow with the same id in discovery (#2023)

* Python: Fix Model ID attribute not showing up in `invoke_agent` span (#2061)

* Best effort to surface the model id to invoke agent span

* Fix tests

* Fix tests

* Version 1.0.0-preview.251107.2 (#2065)

* Version 1.0.0-preview.251110.2 (#2067)

* Update README.md to change Grafana links to Azure portal links for dashboard access (#1983)

* .NET - Enable build & test on branch `feature-foundry-agents` (#2068)

* Tests good, mkay

* Update .github/workflows/dotnet-build-and-test.yml

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

* Enable feature build pipelines

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com>

* Python: Add concrete AGUIChatClient (#2072)

* Add concrete AGUIChatClient

* Update logging docstrings and conventions

* PR feedback

* Updates to support client-side tool calls

* .NET: Move catalog samples to the HostedAgents folder (#2090)

* move catalog samples to the HostedAgents folder

* move the catalog samples' projects to the HostedAgents folder

* Bump OpenTelemetry.Instrumentation.Runtime from 1.12.0 to 1.13.0 (#1856)

---
updated-dependencies:
- dependency-name: OpenTelemetry.Instrumentation.Runtime
  dependency-version: 1.13.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

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Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* .NET: Bump Microsoft.SemanticKernel.Agents.Abstractions from 1.66.0 to 1.67.0 (#1962)

* Bump Microsoft.SemanticKernel.Agents.Abstractions from 1.66.0 to 1.67.0

---
updated-dependencies:
- dependency-name: Microsoft.SemanticKernel.Agents.Abstractions
  dependency-version: 1.67.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>

* .NET: Bump all Microsoft.SemanticKernel packages from 1.66.* to 1.67.* (#1969)

* Initial plan

* Update all Microsoft.SemanticKernel packages to 1.67.*

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

* Remove unrelated changes to package-lock.json and yarn.lock

Co-authored-by: markwallace-microsoft <127216156+markwallace-microsoft@users.noreply.github.com>

---------

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* .NET: fix: WorkflowAsAgent Sample (#1787)

* fix: WorkflowAsAgent Sample

* Also makes ChatForwardingExecutor public

* feat: Expand ChatForwardingExecutor handled types

Make ChatForwardingExecutor match the input types of ChatProtocolExecutor.

* fix: Update for the new AgentRunResponseUpdate merge logic

AIAgent always sends out List<ChatMessage> now.

* Updated (#2076)

* Bump vite in /python/samples/demos/chatkit-integration/frontend (#1918)

Bumps [vite](https://github.com/vitejs/vite/tree/HEAD/packages/vite) from 7.1.9 to 7.1.12.
- [Release notes](https://github.com/vitejs/vite/releases)
- [Changelog](https://github.com/vitejs/vite/blob/v7.1.12/packages/vite/CHANGELOG.md)
- [Commits](https://github.com/vitejs/vite/commits/v7.1.12/packages/vite)

---
updated-dependencies:
- dependency-name: vite
  dependency-version: 7.1.12
  dependency-type: direct:development
...

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* Bump Roslynator.Analyzers from 4.14.0 to 4.14.1 (#1857)

---
updated-dependencies:
- dependency-name: Roslynator.Analyzers
  dependency-version: 4.14.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Bump MishaKav/pytest-coverage-comment from 1.1.57 to 1.1.59 (#2034)

Bumps [MishaKav/pytest-coverage-comment](https://github.com/mishakav/pytest-coverage-comment) from 1.1.57 to 1.1.59.
- [Release notes](https://github.com/mishakav/pytest-coverage-comment/releases)
- [Changelog](https://github.com/MishaKav/pytest-coverage-comment/blob/main/CHANGELOG.md)
- [Commits](https://github.com/mishakav/pytest-coverage-comment/compare/v1.1.57...v1.1.59)

---
updated-dependencies:
- dependency-name: MishaKav/pytest-coverage-comment
  dependency-version: 1.1.59
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* Python: Handle agent user input request in AgentExecutor (#2022)

* Handle agent user input request in AgentExecutor

* fix test

* Address comments

* Fix tests

* Fix tests

* Address comments

* Address comments

* Python: OpenAI Responses Image Generation Stream Support, Sample and Unit Tests (#1853)

* support for image gen streaming

* small fixes

* fixes

* added comment

* Python: Fix MCP Tool Parameter Descriptions Not Propagated to LLMs (#1978)

* mcp tool description fix

* small fix

* .NET: Allow extending agent run options via additional properties (#1872)

* Allow extending agent run options via additional properties

This mirrors the M.E.AI model in ChatOptions.AdditionalProperties which is very useful when building functionality pipelines.

Fixes https://github.com/microsoft/agent-framework/issues/1815

* Expand XML documentation

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

* Add AdditionalProperties tests to AgentRunOptions

Co-authored-by: kzu <169707+kzu@users.noreply.github.com>

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
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* Python: Use the last entry in the task history to avoid empty responses (#2101)

* Use the last entry in the task history to avoid empty responses

* History only contains Messages

* Updated package versions (#2104)

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: Reuben Bond <203839+ReubenBond@users.noreply.github.com>
Co-authored-by: Peter Ibekwe <109177538+peibekwe@users.noreply.github.com>
Co-authored-by: Jeff Handley <jeffhandley@users.noreply.github.com>
Co-authored-by: Daniel Roth <daroth@microsoft.com>
Co-authored-by: Victor Dibia <chuvidi2003@gmail.com>
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Co-authored-by: Javier Calvarro Nelson <jacalvar@microsoft.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
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2025-11-11 23:12:09 -08:00
Dmytro Struk 85fcd230bf Revert "Merge from main"
This reverts commit b8206a85d7.
2025-11-11 18:44:25 -08:00
Dmytro Struk b8206a85d7 Merge from main 2025-11-11 18:28:38 -08:00
Dmytro StrukandGitHub 519bc9da0a Added handling for conversation_id (#2098) 2025-11-11 13:56:43 -08:00
26e73756c7 Python: [Feature Branch] Added more examples and fixes for Azure AI agent (#2077)
* Updated azure-ai-projects package version

* Added an example of hosted MCP with approval required

* Updated code interpreter example

* Added file search example

* Update python/samples/getting_started/agents/azure_ai/azure_ai_with_file_search.py

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* Update python/samples/getting_started/agents/azure_ai/azure_ai_with_file_search.py

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

* Small fix

---------

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2025-11-11 07:49:42 -08:00
Dmytro StrukandGitHub c3ef6475a2 Python: [Feature Branch] Fixed "store" parameter handling (#2069)
* Fixed store parameter handling

* Small fix
2025-11-10 18:24:32 -08:00
Dmytro StrukandGitHub 476fbbefc3 Added hosted MCP support (#2018) 2025-11-07 13:55:21 -08:00
ChrisandGitHub cfcfd713d2 Merge branch 'main' into feature-python-foundry-agents 2025-11-07 10:20:41 -08:00
Dmytro StrukandGitHub 50d3e652ec Removed optional ID from FunctionResultContent (#2011) 2025-11-07 10:17:10 -08:00
Dmytro StrukandGitHub 9423c1763c Python: [Feature Branch] Structured Outputs and more examples for AzureAIClient (#1987)
* Small updates

* Added support for structured outputs

* Added code interpreter example

* More examples and fixes

* Added more examples and README

* Small fix

* Addressed PR feedback
2025-11-07 00:17:20 -08:00
915c749e41 Python: [Feature Branch] Added use_latest_version parameter to AzureAIClient (#1959)
* Added use_latest_version parameter to AzureAIClient

* Added unit tests

* Update python/samples/getting_started/agents/azure_ai/azure_ai_use_latest_version.py

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* Update python/packages/azure-ai/agent_framework_azure_ai/_client.py

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>

---------

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Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
2025-11-06 07:42:34 -08:00
Dmytro Struk ce4b5fec33 Small fix 2025-11-05 19:37:16 -08:00
Dmytro Struk d8228d3a9d Merge branch 'main' into feature-python-foundry-agents 2025-11-05 19:32:00 -08:00
Dmytro Struk 599c5c2bc6 Merge branch 'main' into feature-python-foundry-agents 2025-11-05 09:21:26 -08:00
Dmytro StrukandGitHub f23070a448 Merge branch 'main' into feature-python-foundry-agents 2025-11-05 08:09:07 -08:00
Dmytro Struk 320a4c7438 Merge branch 'main' into feature-python-foundry-agents 2025-11-05 08:04:26 -08:00
8135a99f9e Python: [Feature Branch] Renamed Azure AI agent and small fixes (#1919)
* Renaming

* Small fixes

* Update python/packages/core/agent_framework/openai/_shared.py

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

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2025-11-05 07:53:55 -08:00
Dmytro StrukandGitHub 39d3111734 Added changes (#1909) 2025-11-04 13:13:21 -08:00
1336 changed files with 12595 additions and 82648 deletions
+2 -3
View File
@@ -1,11 +1,10 @@
{
"name": "C# (.NET)",
"image": "mcr.microsoft.com/devcontainers/dotnet:10.0",
"image": "mcr.microsoft.com/devcontainers/dotnet:9.0",
"features": {
"ghcr.io/devcontainers/features/dotnet:2.4.0": {},
"ghcr.io/devcontainers/features/powershell:1.5.1": {},
"ghcr.io/devcontainers/features/azure-cli:1.2.8": {},
"ghcr.io/devcontainers/features/docker-in-docker:2.12.4": {}
"ghcr.io/devcontainers/features/azure-cli:1.2.8": {}
},
"workspaceFolder": "/workspaces/agent-framework/dotnet/",
"customizations": {
-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:
@@ -1636,4 +1636,4 @@ The property mapping guide from a `AutoFunctionInvocationContext` to a `Function
| Result | Use `return` from the delegate |
| Terminate | Terminate |
| CancellationToken | provided via argument to middleware delegate |
| Arguments | Arguments |
| Arguments | Arguments |
+15 -51
View File
@@ -18,7 +18,6 @@ on:
env:
COVERAGE_THRESHOLD: 80
COVERAGE_FRAMEWORK: net10.0 # framework target for which we run/report code coverage
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
@@ -60,9 +59,9 @@ jobs:
fail-fast: false
matrix:
include:
- { targetFramework: "net10.0", os: "ubuntu-latest", configuration: Release, integration-tests: true, environment: "integration" }
- { targetFramework: "net9.0", os: "windows-latest", configuration: Debug }
- { targetFramework: "net8.0", os: "ubuntu-latest", configuration: Release }
- { targetFramework: "net9.0", os: "ubuntu-latest", configuration: Release, integration-tests: true, environment: "integration" }
- { targetFramework: "net9.0", os: "ubuntu-latest", configuration: Debug }
- { targetFramework: "net9.0", os: "windows-latest", configuration: Release }
- { targetFramework: "net472", os: "windows-latest", configuration: Release, integration-tests: true, environment: "integration" }
runs-on: ${{ matrix.os }}
@@ -70,16 +69,16 @@ jobs:
steps:
- uses: actions/checkout@v5
with:
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
workflow-samples
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
workflow-samples
- name: Setup dotnet
uses: actions/setup-dotnet@v5.0.1
uses: actions/setup-dotnet@v5.0.0
with:
global-json-file: ${{ github.workspace }}/dotnet/global.json
- name: Build dotnet solutions
@@ -124,17 +123,7 @@ jobs:
popd
rm -rf "$TEMP_DIR"
# Start Cosmos DB Emulator for Cosmos-based unit tests (only on Windows)
- name: Start Azure Cosmos DB Emulator
if: runner.os == 'Windows'
shell: pwsh
run: |
Write-Host "Launching Azure Cosmos DB Emulator"
Import-Module "$env:ProgramFiles\Azure Cosmos DB Emulator\PSModules\Microsoft.Azure.CosmosDB.Emulator"
Start-CosmosDbEmulator -NoUI -Key "C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw=="
echo "COSMOS_EMULATOR_AVAILABLE=true" >> $env:GITHUB_ENV
- name: Run Unit Tests
- name: Run Unit Tests Windows
shell: bash
run: |
export UT_PROJECTS=$(find ./dotnet -type f -name "*.UnitTests.csproj" | tr '\n' ' ')
@@ -144,20 +133,12 @@ jobs:
# Check if the project supports the target framework
if [[ "$target_frameworks" == *"${{ matrix.targetFramework }}"* ]]; then
if [[ "${{ matrix.targetFramework }}" == "${{ env.COVERAGE_FRAMEWORK }}" ]]; then
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx --collect:"XPlat Code Coverage" --results-directory:"TestResults/Coverage/" -- DataCollectionRunSettings.DataCollectors.DataCollector.Configuration.ExcludeByAttribute=GeneratedCodeAttribute,CompilerGeneratedAttribute,ExcludeFromCodeCoverageAttribute
else
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx
fi
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx --collect:"XPlat Code Coverage" --results-directory:"TestResults/Coverage/" -- DataCollectionRunSettings.DataCollectors.DataCollector.Configuration.ExcludeByAttribute=GeneratedCodeAttribute,CompilerGeneratedAttribute,ExcludeFromCodeCoverageAttribute
else
echo "Skipping $project - does not support target framework ${{ matrix.targetFramework }} (supports: $target_frameworks)"
fi
done
env:
# Cosmos DB Emulator connection settings
COSMOSDB_ENDPOINT: https://localhost:8081
COSMOSDB_KEY: C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==
- name: Log event name and matrix integration-tests
shell: bash
run: echo "github.event_name:${{ github.event_name }} matrix.integration-tests:${{ matrix.integration-tests }} github.event.action:${{ github.event.action }} github.event.pull_request.merged:${{ github.event.pull_request.merged }}"
@@ -170,14 +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
@@ -195,16 +168,10 @@ jobs:
fi
done
env:
# Cosmos DB Emulator connection settings
COSMOSDB_ENDPOINT: https://localhost:8081
COSMOSDB_KEY: C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==
# OpenAI Models
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: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
@@ -216,22 +183,19 @@ jobs:
# Generate test reports and check coverage
- name: Generate test reports
if: matrix.targetFramework == env.COVERAGE_FRAMEWORK
uses: danielpalme/ReportGenerator-GitHub-Action@5.5.0
uses: danielpalme/ReportGenerator-GitHub-Action@5.4.18
with:
reports: "./TestResults/Coverage/**/coverage.cobertura.xml"
targetdir: "./TestResults/Reports"
reporttypes: "HtmlInline;JsonSummary"
- name: Upload coverage report artifact
if: matrix.targetFramework == env.COVERAGE_FRAMEWORK
uses: actions/upload-artifact@v5
with:
name: CoverageReport-${{ matrix.os }}-${{ matrix.targetFramework }}-${{ matrix.configuration }} # Artifact name
path: ./TestResults/Reports # Directory containing files to upload
- name: Check coverage
if: matrix.targetFramework == env.COVERAGE_FRAMEWORK
shell: pwsh
run: .github/workflows/dotnet-check-coverage.ps1 -JsonReportPath "TestResults/Reports/Summary.json" -CoverageThreshold $env:COVERAGE_THRESHOLD
+1 -1
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@@ -22,7 +22,7 @@ jobs:
fail-fast: false
matrix:
include:
- { dotnet: "10.0", configuration: Release, os: ubuntu-latest }
- { dotnet: "9.0", configuration: Release, os: ubuntu-latest }
runs-on: ${{ matrix.os }}
env:
+1 -5
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@@ -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
+1 -15
View File
@@ -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
-2
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@@ -48,8 +48,6 @@ dotnet add package Microsoft.Agents.AI
- **[Migration from Semantic Kernel](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-semantic-kernel)** - Guide to migrate from Semantic Kernel
- **[Migration from AutoGen](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-autogen)** - Guide to migrate from AutoGen
Still have questions? Join our [weekly office hours](./COMMUNITY.md#public-community-office-hours) or ask questions in our [Discord channel](https://discord.gg/b5zjErwbQM) to get help from the team and other users.
### ✨ **Highlights**
- **Graph-based Workflows**: Connect agents and deterministic functions using data flows with streaming, checkpointing, human-in-the-loop, and time-travel capabilities
+2 -2
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@@ -42,9 +42,9 @@ Microsoft Agent Framework relies on existing LLMs. Using the framework retains c
**Framework-Specific Limitations**:
- **Platform Requirements**: Python 3.10+ required, specific .NET versions (.NET 8.0, 9.0, 10.0, netstandard2.0, net472)
- **Platform Requirements**: Python 3.10+ required, specific .NET versions (.NET 8.0, 9.0, netstandard2.0, net472)
- **API Dependencies**: Requires proper configuration of LLM provider keys and endpoints
- **Orchestration Features**: Advanced orchestration patterns including GroupChat, Sequential, and Concurrent workflows are now available in both Python and .NET implementations. See the respective language documentation for examples.
- **Orchestration Features**: Advanced orchestration patterns like GroupChat, Sequential, and Concurrent orchestrations are "coming soon" for Python implementation
- **Privacy and Data Protection**: The framework allows for human participation in conversations between agents. It is important to ensure that user data and conversations are protected and that developers use appropriate measures to safeguard privacy.
- **Accountability and Transparency**: The framework involves multiple agents conversing and collaborating, it is important to establish clear accountability and transparency mechanisms. Users should be able to understand and trace the decision-making process of the agents involved in order to ensure accountability and address any potential issues or biases.
- **Security & unintended consequences**: The use of multi-agent conversations and automation in complex tasks may have unintended consequences. Especially, allowing agents to make changes in external environments through tool calls or function execution could pose significant risks. Developers should carefully consider the potential risks and ensure that appropriate safeguards are in place to prevent harm or negative outcomes, including keeping a human in the loop for decision making.
-3
View File
@@ -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 in 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: gpt-4o-mini
provider: AzureOpenAI
apiType: Assistants
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: string
required: true
description: The type of the response.
-25
View File
@@ -1,25 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in 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: gpt-4o-mini
provider: AzureOpenAI
apiType: Chat
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: 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 in 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: gpt-4o-mini
provider: AzureOpenAI
apiType: Responses
options:
temperature: 0.9
topP: 0.95
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: string
required: true
description: The type of the response.
-18
View File
@@ -1,18 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in 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:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
-29
View File
@@ -1,29 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions using the tools provided.
model:
options:
temperature: 0.9
topP: 0.95
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
-22
View File
@@ -1,22 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format.
model:
id: gpt-4.1-mini
options:
temperature: 0.9
topP: 0.95
connection:
kind: Remote
endpoint: =Env.AZURE_FOUNDRY_PROJECT_ENDPOINT
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
@@ -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.
@@ -1,28 +0,0 @@
kind: Prompt
name: Assistant
description: Helpful assistant
instructions: You are a helpful assistant. You answer questions in 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: gpt-4.1-mini
provider: OpenAI
apiType: Assistants
options:
temperature: 0.9
topP: 0.95
connection:
kind: ApiKey
key: =Env.OPENAI_APIKEY
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: 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 in 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: gpt-4.1-mini
provider: OpenAI
apiType: Chat
options:
temperature: 0.9
topP: 0.95
connection:
kind: ApiKey
key: =Env.OPENAI_APIKEY
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: 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 in 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: gpt-4.1-mini
provider: OpenAI
apiType: Responses
options:
temperature: 0.9
topP: 0.95
connection:
kind: ApiKey
key: =Env.OPENAI_APIKEY
outputSchema:
properties:
language:
type: string
required: true
description: The language of the answer.
answer:
type: string
required: true
description: The answer text.
type:
type: string
required: true
description: The type of the response.
+6 -4
View File
@@ -6,12 +6,14 @@
<AnalysisMode>AllEnabledByDefault</AnalysisMode>
<AnalysisLevel>latest</AnalysisLevel>
<GenerateDocumentationFile>true</GenerateDocumentationFile>
<LangVersion>latest</LangVersion>
<LangVersion>13</LangVersion>
<Nullable>enable</Nullable>
<NoWarn>$(NoWarn);NU5128;CS8002</NoWarn>
<NoWarn>$(NoWarn);NU5128</NoWarn>
<TreatWarningsAsErrors>true</TreatWarningsAsErrors>
<TargetFrameworksCore>net10.0;net9.0;net8.0</TargetFrameworksCore>
<TargetFrameworks>$(TargetFrameworksCore);netstandard2.0;net472</TargetFrameworks>
<ProjectsCoreTargetFrameworks>net9.0;net8.0</ProjectsCoreTargetFrameworks>
<ProjectsDebugCoreTargetFrameworks>net9.0</ProjectsDebugCoreTargetFrameworks>
<ProjectsTargetFrameworks>net9.0;net8.0;netstandard2.0;net472</ProjectsTargetFrameworks>
<ProjectsDebugTargetFrameworks>net9.0;net472</ProjectsDebugTargetFrameworks>
<IsAotCompatible Condition="$([MSBuild]::IsTargetFrameworkCompatible('$(TargetFramework)', 'net7.0'))">true</IsAotCompatible>
<Configurations>Debug;Release;Publish</Configurations>
</PropertyGroup>
+1 -1
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@@ -5,7 +5,7 @@
<Sdk Name="Microsoft.Build.CentralPackageVersions" Version="2.1.3" />
<!-- Only run 'dotnet format' on dev machines, Release builds. Skip on GitHub Actions -->
<!-- as this runs in its own Actions job. -->
<Target Name="DotnetFormatOnBuild" BeforeTargets="Build" Condition=" '$(Configuration)' == 'Release' AND '$(GITHUB_ACTIONS)' == '' ">
<Target Name="DotnetFormatOnBuild" BeforeTargets="Build" Condition=" '$(Configuration)' == 'Release' AND '$(GITHUB_ACTIONS)' == '' AND '$(TargetFramework)' == '$(ProjectsDebugTargetFrameworks)'">
<Message Text="Running dotnet format" Importance="high" />
<Exec Command="dotnet format --no-restore -v diag $(ProjectFileName)" />
</Target>
+24 -52
View File
@@ -7,35 +7,24 @@
</PropertyGroup>
<PropertyGroup>
<!-- Aspire -->
<AspireAppHostSdkVersion>13.0.1</AspireAppHostSdkVersion>
<AspireAppHostSdkVersion>13.0.0</AspireAppHostSdkVersion>
</PropertyGroup>
<ItemGroup>
<!-- Aspire.* -->
<PackageVersion Include="Anthropic" Version="11.0.0" />
<PackageVersion Include="Anthropic.Foundry" Version="0.1.0" />
<PackageVersion Include="Aspire.Azure.AI.OpenAI" Version="13.0.0-preview.1.25560.3" />
<PackageVersion Include="Aspire.Hosting.AppHost" Version="$(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="13.0.0-beta.435" />
<!-- Azure.* -->
<PackageVersion Include="Azure.AI.Projects" Version="1.2.0-beta.3" />
<PackageVersion Include="Azure.AI.Projects.OpenAI" Version="1.0.0-beta.4" />
<PackageVersion Include="Azure.AI.Agents.Persistent" Version="1.2.0-beta.8" />
<PackageVersion Include="Azure.AI.OpenAI" Version="2.7.0-beta.1" />
<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" />
<!-- Google Gemini -->
<PackageVersion Include="Google.GenAI" Version="0.6.0" />
<PackageVersion Include="Mscc.GenerativeAI.Microsoft" Version="2.9.3" />
<!-- Microsoft.Azure.* -->
<PackageVersion Include="Microsoft.Azure.Cosmos" Version="3.54.0" />
<!-- Newtonsoft.Json -->
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<!-- System.* -->
<PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.0" />
<PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
<PackageVersion Include="System.ClientModel" Version="1.8.1" />
<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.CommandLine" Version="2.0.0-rc.2.25502.107" />
@@ -46,7 +35,6 @@
<PackageVersion Include="System.Text.Json" Version="10.0.0" />
<PackageVersion Include="System.Threading.Channels" Version="10.0.0" />
<PackageVersion Include="System.Threading.Tasks.Extensions" Version="4.6.3" />
<PackageVersion Include="System.Net.Security" Version="4.3.2" />
<!-- OpenTelemetry -->
<PackageVersion Include="OpenTelemetry" Version="1.13.1" />
<PackageVersion Include="OpenTelemetry.Api" Version="1.13.1" />
@@ -58,13 +46,13 @@
<PackageVersion Include="OpenTelemetry.Instrumentation.Http" Version="1.13.0" />
<PackageVersion Include="OpenTelemetry.Instrumentation.Runtime" Version="1.13.0" />
<!-- Microsoft.AspNetCore.* -->
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<PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="9.0.11" />
<PackageVersion Include="Swashbuckle.AspNetCore.SwaggerUI" Version="10.0.0" />
<!-- Microsoft.Extensions.* -->
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<PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.0.1" />
<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="10.0.1-preview.1.25571.5" />
<PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.0.0-preview.1.25559.3" />
<PackageVersion Include="Microsoft.Extensions.Caching.Memory" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Configuration" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Configuration.Binder" Version="10.0.0" />
@@ -90,53 +78,37 @@
<PackageVersion Include="Microsoft.SemanticKernel.Agents.AzureAI" Version="1.67.0-preview" />
<PackageVersion Include="Microsoft.SemanticKernel.Plugins.OpenApi" Version="1.67.0" />
<!-- Agent SDKs -->
<PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.3.171-beta" />
<!-- M365 Agents SDK -->
<PackageVersion Include="AdaptiveCards" Version="3.1.0" />
<PackageVersion Include="Microsoft.Agents.Authentication.Msal" Version="1.3.171-beta" />
<PackageVersion Include="Microsoft.Agents.Hosting.AspNetCore" Version="1.3.171-beta" />
<PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.2.41" />
<!-- A2A -->
<PackageVersion Include="A2A" Version="0.3.3-preview" />
<PackageVersion Include="A2A.AspNetCore" Version="0.3.3-preview" />
<!-- MCP -->
<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="Microsoft.ML.OnnxRuntimeGenAI" Version="0.10.0" />
<PackageVersion Include="OllamaSharp" Version="5.4.8" />
<PackageVersion Include="OpenAI" Version="2.7.0" />
<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 -->
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<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" />
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<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 -->
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<!-- Test -->
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<PackageVersion Include="Microsoft.AspNetCore.TestHost" Condition="'$(TargetFramework)' == 'net8.0'" Version="8.0.22" />
<PackageVersion Include="Microsoft.AspNetCore.TestHost" Condition="'$(TargetFramework)' == 'net9.0'" Version="9.0.11" />
<PackageVersion Include="Microsoft.AspNetCore.TestHost" Condition="'$(TargetFramework)' == 'net10.0'" Version="10.0.0" />
<PackageVersion Include="Microsoft.AspNetCore.TestHost" Version="9.0.11" />
<PackageVersion Include="Microsoft.NET.Test.Sdk" Version="18.0.0" />
<PackageVersion Include="Moq" Version="[4.18.4]" />
<PackageVersion Include="Microsoft.SemanticKernel.Agents.Abstractions" Version="1.67.0" />
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<PackageVersion Include="xretry" Version="1.9.0" />
<PackageVersion Include="coverlet.collector" Version="6.0.4" />
<!-- Symbols -->
@@ -163,17 +135,17 @@
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<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
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<PackageVersion Include="Roslynator.Analyzers" Version="[4.14.1]" />
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<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
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<PackageReference Include="Roslynator.Formatting.Analyzers">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+5 -87
View File
@@ -23,36 +23,21 @@
<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>
<Folder Name="/Samples/GettingStarted/A2A/">
<File Path="samples/GettingStarted/A2A/README.md" />
<Project Path="samples/GettingStarted/A2A/A2AAgent_AsFunctionTools/A2AAgent_AsFunctionTools.csproj" />
<Project Path="samples/GettingStarted/A2A/A2AAgent_PollingForTaskCompletion/A2AAgent_PollingForTaskCompletion.csproj" />
</Folder>
<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_Anthropic/Agent_With_Anthropic.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" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Agent_With_CustomImplementation.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_GoogleGemini/Agent_With_GoogleGemini.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_Ollama/Agent_With_Ollama.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_ONNX/Agent_With_ONNX.csproj" />
<Project Path="samples/GettingStarted/AgentProviders/Agent_With_OpenAIAssistants/Agent_With_OpenAIAssistants.csproj" />
@@ -79,21 +64,11 @@
<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_Step19_Declarative/Agent_Step19_Declarative.csproj" />
</Folder>
<Folder Name="/Samples/GettingStarted/DeclarativeAgents/">
<Project Path="samples/GettingStarted/DeclarativeAgents/ChatClient/DeclarativeChatClientAgents.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/AgentWithAnthropic/">
<File Path="samples/GettingStarted/AgentWithAnthropic/README.md" />
<Project Path="samples/GettingStarted/AgentWithAnthropic/Agent_Anthropic_Step01_Running/Agent_Anthropic_Step01_Running.csproj" />
<Project Path="samples/GettingStarted/AgentWithAnthropic/Agent_Anthropic_Step02_Reasoning/Agent_Anthropic_Step02_Reasoning.csproj" />
<Project Path="samples/GettingStarted/AgentWithAnthropic/Agent_Anthropic_Step03_UsingFunctionTools/Agent_Anthropic_Step03_UsingFunctionTools.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" />
@@ -105,35 +80,11 @@
<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" />
</Folder>
<Folder Name="/Samples/GettingStarted/ModelContextProtocol/">
<File Path="samples/GettingStarted/ModelContextProtocol/README.md" />
@@ -159,22 +110,13 @@
</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" />
@@ -205,7 +147,7 @@
<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" />
@@ -219,11 +161,8 @@
</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" />
<Project Path="samples/HostedAgents/AgentWithHostedMCP/AgentWithHostedMCP.csproj" />
</Folder>
<Folder Name="/Solution Items/">
<File Path=".editorconfig" />
@@ -324,7 +263,6 @@
<File Path="src/Shared/Demos/SampleEnvironment.cs" />
</Folder>
<Folder Name="/Solution Items/src/Shared/IntegrationTests/">
<File Path="src/Shared/IntegrationTests/AnthropicConfiguration.cs" />
<File Path="src/Shared/IntegrationTests/AzureAIConfiguration.cs" />
<File Path="src/Shared/IntegrationTests/Mem0Configuration.cs" />
<File Path="src/Shared/IntegrationTests/OpenAIConfiguration.cs" />
@@ -349,24 +287,16 @@
<Project Path="src/Microsoft.Agents.AI.A2A/Microsoft.Agents.AI.A2A.csproj" />
<Project Path="src/Microsoft.Agents.AI.Abstractions/Microsoft.Agents.AI.Abstractions.csproj" />
<Project Path="src/Microsoft.Agents.AI.AGUI/Microsoft.Agents.AI.AGUI.csproj" />
<Project Path="src/Microsoft.Agents.AI.Anthropic/Microsoft.Agents.AI.Anthropic.csproj" />
<Project Path="src/Microsoft.Agents.AI.AzureAI.Persistent/Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
<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.CosmosNoSql/Microsoft.Agents.AI.CosmosNoSql.csproj" />
<Project Path="src/Microsoft.Agents.AI.Declarative/Microsoft.Agents.AI.Declarative.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" />
@@ -374,13 +304,9 @@
<Folder Name="/Tests/" />
<Folder Name="/Tests/IntegrationTests/">
<Project Path="tests/AgentConformance.IntegrationTests/AgentConformance.IntegrationTests.csproj" />
<Project Path="tests/AnthropicChatCompletion.IntegrationTests/AnthropicChatCompletion.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" />
@@ -391,23 +317,15 @@
<Project Path="tests/Microsoft.Agents.AI.A2A.UnitTests/Microsoft.Agents.AI.A2A.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Abstractions.UnitTests/Microsoft.Agents.AI.Abstractions.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.AGUI.UnitTests/Microsoft.Agents.AI.AGUI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Anthropic.UnitTests/Microsoft.Agents.AI.Anthropic.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.CosmosNoSql.UnitTests/Microsoft.Agents.AI.CosmosNoSql.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Declarative.UnitTests/Microsoft.Agents.AI.Declarative.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.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" />
</Folder>
</Solution>
</Solution>
-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="$(MSBuildThisFileDirectory)\..\..\src\Shared\Foundry\Agents\*.cs" LinkBase="Shared\Foundry" />
</ItemGroup>
</Project>
+2 -2
View File
@@ -1,7 +1,7 @@
{
"sdk": {
"version": "10.0.100",
"rollForward": "minor",
"version": "9.0.300",
"rollForward": "latestMajor",
"allowPrerelease": false
}
}
+3 -3
View File
@@ -2,9 +2,9 @@
<PropertyGroup>
<!-- Central version prefix - applies to all nuget packages. -->
<VersionPrefix>1.0.0</VersionPrefix>
<PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).251125.1</PackageVersion>
<PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.251125.1</PackageVersion>
<GitTag>1.0.0-preview.251125.1</GitTag>
<PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).251110.2</PackageVersion>
<PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.251110.2</PackageVersion>
<GitTag>1.0.0-preview.251110.2</GitTag>
<Configurations>Debug;Release;Publish</Configurations>
<IsPackable>true</IsPackable>
@@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>5ee045b0-aea3-4f08-8d31-32d1a6f8fed0</UserSecretsId>
@@ -12,6 +12,8 @@
<PackageReference Include="A2A" />
<PackageReference Include="System.CommandLine" />
<PackageReference Include="Microsoft.Extensions.Hosting" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<ItemGroup>
@@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>5ee045b0-aea3-4f08-8d31-32d1a6f8fed0</UserSecretsId>
@@ -11,11 +11,8 @@
<ItemGroup>
<PackageReference Include="Azure.AI.Agents.Persistent" />
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<ItemGroup Condition="!$([MSBuild]::IsTargetFrameworkCompatible($(TargetFramework), 'net10.0'))">
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" />
<PackageReference Include="System.Linq.AsyncEnumerable" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<ItemGroup>
+1 -1
View File
@@ -103,7 +103,7 @@ dotnet run --urls "http://localhost:5002;https://localhost:5012" --agentId "<Log
### Testing the Agents using the Rest Client
This sample contains a [.http file](https://learn.microsoft.com/aspnet/core/test/http-files?view=aspnetcore-10.0) which can be used to test the agent.
This sample contains a [.http file](https://learn.microsoft.com/aspnet/core/test/http-files?view=aspnetcore-9.0) which can be used to test the agent.
1. In Visual Studio open [./A2AServer/A2AServer.http](./A2AServer/A2AServer.http)
1. There are two sent requests for each agent, e.g., for the invoice agent:
@@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>a8b2e9f0-1ea3-4f18-9d41-42d1a6f8fe10</UserSecretsId>
@@ -11,6 +11,8 @@
<ItemGroup>
<PackageReference Include="System.CommandLine" />
<PackageReference Include="Microsoft.Extensions.Hosting" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<ItemGroup>
@@ -201,12 +201,12 @@ public static class Program
{
return "";
}
var builder = new StringBuilder().AppendLine();
var builder = new StringBuilder();
builder.AppendLine();
foreach (var kvp in arguments)
{
builder
.AppendLine($" Name: {kvp.Key}")
.AppendLine($" Value: {kvp.Value}");
builder.AppendLine($" Name: {kvp.Key}");
builder.AppendLine($" Value: {kvp.Value}");
}
return builder.ToString();
}
@@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>b9c3f1e1-2fb4-5g29-0e52-53e2b7g9gf21</UserSecretsId>
@@ -11,6 +11,8 @@
<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>
@@ -42,4 +42,4 @@ app.MapAGUI("/shared_state", ChatClientAgentFactory.CreateSharedState(jsonOption
await app.RunAsync();
public partial class Program;
public partial class Program { }
@@ -2,7 +2,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<UserSecretsId>a8b2e9f0-1ea3-4f18-9d41-42d1a6f8fe10</UserSecretsId>
@@ -11,6 +11,8 @@
<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>
@@ -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
@@ -1,14 +1,13 @@
<Project Sdk="Microsoft.NET.Sdk.Web">
<PropertyGroup>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<GenerateDocumentationFile>true</GenerateDocumentationFile>
</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" />
@@ -31,4 +30,11 @@
<PackageReference Include="Swashbuckle.AspNetCore.SwaggerUI" />
</ItemGroup>
<!-- A2A dependency -->
<ItemGroup>
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<!-- A2A dependency -->
</Project>
@@ -4,7 +4,9 @@ using Microsoft.Extensions.AI;
namespace AgentWebChat.AgentHost.Custom;
public class CustomAITool : AITool;
public class CustomAITool : AITool
{
}
public class CustomFunctionTool : AIFunction
{
@@ -5,7 +5,6 @@ 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;
@@ -22,13 +21,6 @@ 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",
@@ -103,48 +95,8 @@ var scienceConcurrentWorkflow = builder.AddWorkflow("science-concurrent-workflow
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();
@@ -166,10 +118,7 @@ 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);
@@ -4,7 +4,7 @@
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<IsAspireHost>true</IsAspireHost>
@@ -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()
@@ -1,7 +1,7 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<IsAspireSharedProject>true</IsAspireSharedProject>
@@ -25,7 +25,7 @@ internal sealed class A2AAgentClient : AgentClientBase
this._uri = baseUri;
}
public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
public async override IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
string agentName,
IList<ChatMessage> messages,
string? threadId = null,
@@ -122,7 +122,7 @@ internal sealed class A2AAgentClient : AgentClientBase
}
}
public override async Task<AgentCard?> GetAgentCardAsync(string agentName, CancellationToken cancellationToken = default)
public async override Task<AgentCard?> GetAgentCardAsync(string agentName, CancellationToken cancellationToken = default)
{
this._logger.LogInformation("Retrieving agent card for {Agent}", agentName);
@@ -1,7 +1,7 @@
<Project Sdk="Microsoft.NET.Sdk.Web">
<PropertyGroup>
<TargetFrameworks>net10.0</TargetFrameworks>
<TargetFramework>net9.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<NoWarn>$(NoWarn);CA1812</NoWarn>
@@ -15,4 +15,11 @@
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Abstractions\Microsoft.Agents.AI.Abstractions.csproj" />
</ItemGroup>
<!-- A2A dependency -->
<ItemGroup>
<PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
<PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
</ItemGroup>
<!-- A2A dependency -->
</Project>
@@ -16,7 +16,7 @@ namespace AgentWebChat.Web;
/// </summary>
internal sealed class OpenAIChatCompletionsAgentClient(HttpClient httpClient) : AgentClientBase
{
public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
public async override IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
string agentName,
IList<ChatMessage> messages,
string? threadId = null,
@@ -15,7 +15,7 @@ namespace AgentWebChat.Web;
/// </summary>
internal sealed class OpenAIResponsesAgentClient(HttpClient httpClient) : AgentClientBase
{
public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
public async override IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
string agentName,
IList<ChatMessage> messages,
string? threadId = null,
@@ -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>
<TargetFrameworks>net10.0</TargetFrameworks>
<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>
<TargetFrameworks>net10.0</TargetFrameworks>
<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>
<TargetFrameworks>net10.0</TargetFrameworks>
<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}";
}
}
@@ -1,45 +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)
.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>
<TargetFrameworks>net10.0</TargetFrameworks>
<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;
}
@@ -1,48 +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)
.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 $1,000,000! Click here now to claim your prize! Limited time offer! Don't miss out!"
}
@@ -1,20 +0,0 @@
{
"version": "2.0",
"logging": {
"logLevel": {
"Microsoft.Agents.AI.DurableTask": "Information",
"Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
"DurableTask": "Information",
"Microsoft.DurableTask": "Information"
}
},
"extensions": {
"durableTask": {
"hubName": "default",
"storageProvider": {
"type": "AzureManaged",
"connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
}
}
}
}
@@ -1,10 +0,0 @@
{
"IsEncrypted": false,
"Values": {
"FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
"AzureWebJobsStorage": "UseDevelopmentStorage=true",
"DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None",
"AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
"AZURE_OPENAI_DEPLOYMENT": "<AZURE_OPENAI_DEPLOYMENT>"
}
}
@@ -1,43 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFrameworks>net10.0</TargetFrameworks>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
<OutputType>Exe</OutputType>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<!-- The Functions build tools don't like namespaces that start with a number -->
<AssemblyName>AgentOrchestration_HITL</AssemblyName>
<RootNamespace>AgentOrchestration_HITL</RootNamespace>
<NoWarn>$(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>
<TargetFrameworks>net10.0</TargetFrameworks>
<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"
}
}
}
}
@@ -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>
<TargetFrameworks>net10.0</TargetFrameworks>
<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>AgentAsMcpTool</AssemblyName>
<RootNamespace>AgentAsMcpTool</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>
@@ -1,53 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to configure AI agents to be accessible as MCP tools.
// When using AddAIAgent and enabling MCP tool triggers, the Functions host will automatically
// generate a remote MCP endpoint for the app at /runtime/webhooks/mcp with a agent-specific
// query tool name.
using Azure;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.DurableTask;
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());
// Define three AI agents we are going to use in this application.
AIAgent agent1 = client.GetChatClient(deploymentName).CreateAIAgent("You are good at telling jokes.", "Joker");
AIAgent agent2 = client.GetChatClient(deploymentName)
.CreateAIAgent("Check stock prices.", "StockAdvisor");
AIAgent agent3 = client.GetChatClient(deploymentName)
.CreateAIAgent("Recommend plants.", "PlantAdvisor", description: "Get plant recommendations.");
using IHost app = FunctionsApplication
.CreateBuilder(args)
.ConfigureFunctionsWebApplication()
.ConfigureDurableAgents(options =>
{
options
.AddAIAgent(agent1) // Enables HTTP trigger by default.
.AddAIAgent(agent2, enableHttpTrigger: false, enableMcpToolTrigger: true) // Disable HTTP trigger, enable MCP Tool trigger.
.AddAIAgent(agent3, agentOptions =>
{
agentOptions.McpToolTrigger.IsEnabled = true; // Enable MCP Tool trigger.
});
})
.Build();
app.Run();

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