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This commit is contained in:
wehub-resource-sync
2026-07-13 13:39:25 +08:00
commit db620d33df
5151 changed files with 925932 additions and 0 deletions
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{
"name": "Python 3",
"image": "mcr.microsoft.com/devcontainers/python:3.14-bookworm",
"features": {
"ghcr.io/va-h/devcontainers-features/uv:1": {},
"ghcr.io/devcontainers/features/docker-in-docker:3": {},
"ghcr.io/devcontainers/features/azure-cli:1.2.9": {},
"ghcr.io/devcontainers/features/copilot-cli:1": {}
},
"postCreateCommand": "bash ./devsetup.sh",
"workspaceFolder": "/workspaces/agent-framework/python/",
"customizations": {
"vscode": {
"extensions": [
"GitHub.copilot",
"GitHub.vscode-github-actions",
"ms-python.python",
"ms-windows-ai-studio.windows-ai-studio",
"littlefoxteam.vscode-python-test-adapter"
]
}
}
}
+35
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{
"name": "C# (.NET)",
"image": "mcr.microsoft.com/devcontainers/dotnet",
"features": {
"ghcr.io/devcontainers/features/azure-cli:1.2.9": {},
"ghcr.io/devcontainers/features/docker-in-docker:2": {},
"ghcr.io/devcontainers/features/github-cli:1": {
"version": "2"
},
"ghcr.io/devcontainers/features/powershell:1": {
"version": "latest"
},
"ghcr.io/azure/azure-dev/azd:0": {
"version": "latest"
},
"ghcr.io/devcontainers/features/dotnet:2": {
"version": "none",
"dotnetRuntimeVersions": "10.0",
"aspNetCoreRuntimeVersions": "10.0"
},
"ghcr.io/devcontainers/features/copilot-cli:1": {}
},
"workspaceFolder": "/workspaces/agent-framework/dotnet/",
"customizations": {
"vscode": {
"extensions": [
"GitHub.copilot",
"GitHub.vscode-github-actions",
"ms-dotnettools.csdevkit",
"vscode-icons-team.vscode-icons",
"ms-windows-ai-studio.windows-ai-studio"
]
}
}
}
+5
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# Auto-detect text files, ensure they use LF.
* text=auto eol=lf working-tree-encoding=UTF-8
# Bash scripts
*.sh text eol=lf
*.cmd text eol=crlf
+37
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dirs:
- .
excludedFiles:
- ./python/CHANGELOG.md
ignorePatterns:
- pattern: "/github/"
- pattern: "./actions"
- pattern: "./blob"
- pattern: "./issues"
- pattern: "./discussions"
- pattern: "./pull"
- pattern: "https:\/\/platform.openai.com"
- pattern: "http:\/\/localhost"
- pattern: "http:\/\/127.0.0.1"
- pattern: "https:\/\/localhost"
- pattern: "https:\/\/127.0.0.1"
- pattern: "0001-spec.md"
- pattern: "0001-madr-architecture-decisions.md"
- pattern: "https://api.powerplatform.com/.default"
- pattern: "https://your-resource.openai.azure.com/"
- pattern: "http://host.docker.internal"
- pattern: "https://openai.github.io/openai-agents-js/openai/agents/classes/"
# dotnet.microsoft.com bot-blocks CI link checkers with intermittent 403s on any
# path (including localized variants like /en-us/download/...), so ignore the
# whole domain rather than just /download.
- pattern: "https:\/\/dotnet.microsoft.com"
- pattern: "https://github.com/Rel1cx/eslint-react"
# excludedDirs:
# Folders which include links to localhost, since it's not ignored with regular expressions
baseUrl: https://github.com/microsoft/agent-framework/
aliveStatusCodes:
- 200
- 206
- 429
- 500
- 503
useGitIgnore: true
+7
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# 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
python/packages/durabletask/ @microsoft/agentframework-durabletask-developers
python/samples/getting_started/azure_functions/ @microsoft/agentframework-durabletask-developers
python/samples/getting_started/durabletask/ @microsoft/agentframework-durabletask-developers
+8
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blank_issues_enabled: true
contact_links:
- name: Documentation
url: https://aka.ms/agent-framework
about: Check out the official documentation for guides and API reference.
- name: Discussions
url: https://github.com/microsoft/agent-framework/discussions
about: Ask questions about Agent Framework.
+70
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@@ -0,0 +1,70 @@
name: .NET Bug Report
description: Report a bug in the Agent Framework .NET SDK
title: ".NET: [Bug]: "
labels: [".NET"]
type: bug
body:
- type: textarea
id: description
attributes:
label: Description
description: Please provide a clear and detailed description of the bug.
placeholder: |
- What happened?
- What did you expect to happen?
- Steps to reproduce the issue
validations:
required: true
- type: textarea
id: code-sample
attributes:
label: Code Sample
description: If applicable, provide a minimal code sample that demonstrates the issue.
placeholder: |
```csharp
// Your code here
```
render: markdown
validations:
required: false
- type: textarea
id: error-messages
attributes:
label: Error Messages / Stack Traces
description: Include any error messages or stack traces you received.
placeholder: |
```
Paste error messages or stack traces here
```
render: markdown
validations:
required: false
- type: input
id: dotnet-packages
attributes:
label: Package Versions
description: List the Microsoft.Agents.* packages and versions you are using
placeholder: "e.g., Microsoft.Agents.AI.Abstractions: 1.0.0, Microsoft.Agents.AI.OpenAI: 1.0.0"
validations:
required: true
- type: input
id: dotnet-version
attributes:
label: .NET Version
description: What version of .NET are you using?
placeholder: "e.g., .NET 8.0"
validations:
required: false
- type: textarea
id: additional-context
attributes:
label: Additional Context
description: Add any other context or screenshots that might be helpful.
placeholder: "Any additional information..."
validations:
required: false
@@ -0,0 +1,51 @@
name: Feature Request
description: Request a new feature for Microsoft Agent Framework
title: "[Feature]: "
type: feature
body:
- type: textarea
id: description
attributes:
label: Description
description: Please describe the feature you'd like and why it would be useful.
placeholder: |
Describe the feature you're requesting:
- What problem does it solve?
- What would the expected behavior be?
- Are there any alternatives you've considered?
validations:
required: true
- type: textarea
id: code-sample
attributes:
label: Code Sample
description: If applicable, provide a code sample showing how you'd like to use this feature.
placeholder: |
```python
# Your code here
```
or
```csharp
// Your code here
```
render: markdown
validations:
required: false
- type: dropdown
id: language
attributes:
label: Language/SDK
description: Which language/SDK does this feature apply to?
options:
- Both
- .NET
- Python
- Other / Not Applicable
default: 0
validations:
required: false
+70
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name: Python Bug Report
description: Report a bug in the Agent Framework Python SDK
title: "Python: [Bug]: "
labels: ["Python"]
type: bug
body:
- type: textarea
id: description
attributes:
label: Description
description: Please provide a clear and detailed description of the bug.
placeholder: |
- What happened?
- What did you expect to happen?
- Steps to reproduce the issue
validations:
required: true
- type: textarea
id: code-sample
attributes:
label: Code Sample
description: If applicable, provide a minimal code sample that demonstrates the issue.
placeholder: |
```python
# Your code here
```
render: markdown
validations:
required: false
- type: textarea
id: error-messages
attributes:
label: Error Messages / Stack Traces
description: Include any error messages or stack traces you received.
placeholder: |
```
Paste error messages or stack traces here
```
render: markdown
validations:
required: false
- type: input
id: python-packages
attributes:
label: Package Versions
description: List the agent-framework-* packages and versions you are using
placeholder: "e.g., agent-framework-core: 1.0.0, agent-framework-foundry: 1.0.0"
validations:
required: true
- type: input
id: python-version
attributes:
label: Python Version
description: What version of Python are you using?
placeholder: "e.g., Python 3.11"
validations:
required: false
- type: textarea
id: additional-context
attributes:
label: Additional Context
description: Add any other context or screenshots that might be helpful.
placeholder: "Any additional information..."
validations:
required: false
@@ -0,0 +1,48 @@
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 [ "$(docker ps -aq -f name=dts-emulator)" ]; then
echo "Stopping and removing existing Durable Task Scheduler Emulator"
docker rm -f dts-emulator
fi
echo "Starting Durable Task Scheduler Emulator"
docker run -d --name dts-emulator -p 8080:8080 -p 8082:8082 -e DTS_USE_DYNAMIC_TASK_HUBS=true mcr.microsoft.com/dts/dts-emulator:latest
echo "Waiting for Durable Task Scheduler Emulator to be ready"
timeout 30 bash -c 'until curl --silent http://localhost:8080/healthz; do sleep 1; done'
echo "Durable Task Scheduler Emulator is ready"
- name: Start Azurite (Azure Storage emulator)
shell: bash
run: |
if [ "$(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: Start Redis
shell: bash
run: |
if [ "$(docker ps -aq -f name=redis)" ]; then
echo "Stopping and removing existing Redis"
docker rm -f redis
fi
echo "Starting Redis"
docker run -d --name redis -p 6379:6379 redis:latest
echo "Waiting for Redis to be ready"
timeout 30 bash -c 'until docker exec redis redis-cli ping | grep -q PONG; do sleep 1; done'
echo "Redis is ready"
- name: Install Azure Functions Core Tools
shell: bash
run: |
echo "Installing Azure Functions Core Tools"
npm install -g azure-functions-core-tools@4 --unsafe-perm true
func --version
@@ -0,0 +1,64 @@
name: Free runner disk space
description: |
Reclaims disk space on GitHub-hosted Ubuntu runners by removing
pre-installed toolchains we do not use (Android SDK, GHC/Haskell,
CodeQL bundle), Docker images, and swap. Also relocates the
NuGet package cache to /mnt (which has ~75 GB free vs ~14 GB
on /). No-op on non-Linux runners.
runs:
using: composite
steps:
- name: Free disk space (Linux only)
if: runner.os == 'Linux'
shell: bash
run: |
set -euo pipefail
echo "::group::Disk usage before cleanup"
df -h /
echo "::endgroup::"
# Remove pre-installed toolchains we never use on this repo's
# dotnet/python jobs. These reclaim ~25-30 GB on ubuntu-latest.
sudo rm -rf \
/usr/local/lib/android \
/usr/share/dotnet/sdk/NuGetFallbackFolder \
/opt/ghc \
/usr/local/.ghcup \
/opt/hostedtoolcache/CodeQL \
/opt/hostedtoolcache/PyPy \
/opt/hostedtoolcache/Ruby \
/opt/hostedtoolcache/go \
/usr/local/share/boost \
/usr/local/share/powershell \
/usr/local/share/chromium \
/usr/local/share/vcpkg \
/usr/local/lib/heroku \
"${AGENT_TOOLSDIRECTORY:-/opt/hostedtoolcache}/PyPy" \
"${AGENT_TOOLSDIRECTORY:-/opt/hostedtoolcache}/Ruby" \
"${AGENT_TOOLSDIRECTORY:-/opt/hostedtoolcache}/go" || true
# Drop docker images shipped on the runner; jobs that need
# docker pull what they need fresh.
if command -v docker >/dev/null 2>&1; then
sudo docker image prune --all --force >/dev/null 2>&1 || true
fi
# Disable swap to free its backing file.
sudo swapoff -a || true
sudo rm -f /mnt/swapfile /swapfile || true
echo "::group::Disk usage after cleanup"
df -h /
echo "::endgroup::"
- name: Relocate NuGet package cache to /mnt (Linux only)
if: runner.os == 'Linux'
shell: bash
run: |
set -euo pipefail
sudo mkdir -p /mnt/nuget
sudo chown -R "$USER":"$USER" /mnt/nuget
echo "NUGET_PACKAGES=/mnt/nuget" >> "$GITHUB_ENV"
echo "Relocated NuGet package cache to /mnt/nuget"
df -h /mnt || true
+49
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name: Reusable Setup UV
description: Reusable workflow to setup uv environment
inputs:
python-version:
description: The Python version to set up
required: true
os:
description: The operating system to set up
required: true
exclude-packages:
description: Space-separated list of packages to exclude from uv sync
required: false
default: ''
runs:
using: "composite"
steps:
- name: Set up uv
uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
with:
version-file: "python/pyproject.toml"
enable-cache: true
cache-suffix: ${{ inputs.os }}-${{ inputs.python-version }}
cache-dependency-glob: "**/uv.lock"
- name: Exclude incompatible workspace packages
if: ${{ inputs.exclude-packages != '' }}
shell: bash
run: |
for pkg in ${{ inputs.exclude-packages }}; do
for f in python/packages/*/pyproject.toml; do
if grep -q "name = \"$pkg\"" "$f"; then
pkg_dir=$(dirname "$f" | sed 's|python/||')
echo "Excluding workspace package: $pkg ($pkg_dir)"
if awk '/^\[tool\.uv\.workspace\]/{f=1;next} /^\[/{f=0} f && /^exclude = \[/{found=1} END{exit !found}' python/pyproject.toml; then
if ! awk '/^\[tool\.uv\.workspace\]/{f=1;next} /^\[/{f=0} f && /^exclude = \[/ && index($0, "\"'"$pkg_dir"'\"")' python/pyproject.toml | grep -q .; then
sed -i.bak '/\[tool\.uv\.workspace\]/,/^\[/ { /^exclude = \[/ s|\]|, "'"$pkg_dir"'"]| }' python/pyproject.toml
fi
else
sed -i.bak '/\[tool\.uv\.workspace\]/a\exclude = ["'"$pkg_dir"'"]' python/pyproject.toml
fi
sed -i.bak '/'"$pkg"' = { workspace = true }/d' python/pyproject.toml
fi
done
done
- name: Install the project
shell: bash
run: |
cd python && uv sync --all-packages --all-extras --all-groups --prerelease=if-necessary-or-explicit
@@ -0,0 +1,50 @@
name: Sample Validation Setup
description: Sets up the environment for sample validation (checkout, Node.js, Copilot CLI, Azure login, Python)
inputs:
azure-client-id:
description: Azure Client ID for OIDC login
required: true
azure-tenant-id:
description: Azure Tenant ID for OIDC login
required: true
azure-subscription-id:
description: Azure Subscription ID for OIDC login
required: true
python-version:
description: The Python version to set up
required: false
default: "3.12"
os:
description: The operating system to set up
required: false
default: "Linux"
runs:
using: "composite"
steps:
- name: Set up Node.js environment
uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6
with:
node-version: 22
- name: Install Copilot CLI
shell: bash
run: npm install -g @github/copilot
- name: Test Copilot CLI
shell: bash
run: copilot --version && copilot -p "What can you do in one sentence?"
- name: Azure CLI Login
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ inputs.azure-client-id }}
tenant-id: ${{ inputs.azure-tenant-id }}
subscription-id: ${{ inputs.azure-subscription-id }}
- name: Set up python and install the project
uses: ./.github/actions/python-setup
with:
python-version: ${{ inputs.python-version }}
os: ${{ inputs.os }}
@@ -0,0 +1,166 @@
name: Setup Local MCP Server
description: Start and validate a local streamable HTTP MCP server for integration tests
inputs:
fallback_url:
description: Existing LOCAL_MCP_URL value to keep as a fallback if local startup fails
required: false
default: ''
host:
description: Host interface to bind the local MCP server
required: false
default: '127.0.0.1'
port:
description: Port to bind the local MCP server
required: false
default: '8011'
mount_path:
description: Mount path for the local streamable HTTP MCP endpoint
required: false
default: '/mcp'
outputs:
effective_url:
description: Local MCP URL when startup succeeds, otherwise the provided fallback URL
value: ${{ steps.start.outputs.effective_url }}
local_url:
description: URL of the local MCP server
value: ${{ steps.start.outputs.local_url }}
started:
description: Whether the local MCP server started and passed validation
value: ${{ steps.start.outputs.started }}
pid:
description: PID of the local MCP server process when startup succeeded
value: ${{ steps.start.outputs.pid }}
runs:
using: composite
steps:
- name: Start and validate local MCP server
id: start
shell: bash
run: |
set -euo pipefail
host="${{ inputs.host }}"
port="${{ inputs.port }}"
mount_path="${{ inputs.mount_path }}"
fallback_url="${{ inputs.fallback_url }}"
if [[ ! "$mount_path" =~ ^/ ]]; then
mount_path="/$mount_path"
fi
local_url="http://${host}:${port}${mount_path}"
health_url="http://${host}:${port}/healthz"
log_file="$RUNNER_TEMP/local-mcp-server.log"
pid_file="$RUNNER_TEMP/local-mcp-server.pid"
rm -f "$log_file" "$pid_file"
server_pid="$(
python3 - "$GITHUB_WORKSPACE/python" "$log_file" "$host" "$port" "$mount_path" <<'PY'
from __future__ import annotations
import subprocess
import sys
workspace, log_file, host, port, mount_path = sys.argv[1:]
with open(log_file, "w", encoding="utf-8") as log:
process = subprocess.Popen(
[
"uv",
"run",
"python",
"scripts/local_mcp_streamable_http_server.py",
"--host",
host,
"--port",
port,
"--mount-path",
mount_path,
],
cwd=workspace,
stdout=log,
stderr=subprocess.STDOUT,
start_new_session=True,
)
print(process.pid)
PY
)"
echo "$server_pid" > "$pid_file"
started=false
for _ in $(seq 1 30); do
if curl --silent --fail "$health_url" >/dev/null; then
started=true
break
fi
if ! kill -0 "$server_pid" 2>/dev/null; then
break
fi
sleep 1
done
if [[ "$started" == "true" ]]; then
if ! (
cd "$GITHUB_WORKSPACE/python"
LOCAL_MCP_URL="$local_url" uv run python - <<'PY'
from __future__ import annotations
import asyncio
import os
from agent_framework import Content, MCPStreamableHTTPTool
def result_to_text(result: str | list[Content]) -> str:
if isinstance(result, str):
return result
return "\n".join(content.text for content in result if content.type == "text" and content.text)
async def main() -> None:
tool = MCPStreamableHTTPTool(
name="local_ci_mcp",
url=os.environ["LOCAL_MCP_URL"],
approval_mode="never_require",
)
async with tool:
assert tool.functions, "Local MCP server did not expose any tools."
result = result_to_text(await tool.functions[0].invoke(query="What is Agent Framework?"))
assert result, "Local MCP server returned an empty response."
asyncio.run(main())
PY
); then
started=false
fi
fi
effective_url="$local_url"
pid="$server_pid"
if [[ "$started" != "true" ]]; then
effective_url="$fallback_url"
pid=""
if kill -0 "$server_pid" 2>/dev/null; then
kill -TERM -- "-$server_pid" 2>/dev/null || kill -TERM "$server_pid" || true
sleep 1
kill -KILL -- "-$server_pid" 2>/dev/null || kill -KILL "$server_pid" || true
fi
echo "Local MCP server was unavailable; continuing with fallback LOCAL_MCP_URL."
if [[ -f "$log_file" ]]; then
tail -n 100 "$log_file" || true
fi
else
echo "Using local MCP server at $local_url"
fi
echo "started=$started" >> "$GITHUB_OUTPUT"
echo "local_url=$local_url" >> "$GITHUB_OUTPUT"
echo "effective_url=$effective_url" >> "$GITHUB_OUTPUT"
echo "pid=$pid" >> "$GITHUB_OUTPUT"
+19
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# GitHub Copilot Instructions
Microsoft Agent Framework - a multi-language framework for building, orchestrating, and deploying AI agents.
## Repository Structure
- `python/` - Python implementation → see [python/AGENTS.md](../python/AGENTS.md)
- `dotnet/` - C#/.NET implementation → see [dotnet/AGENTS.md](../dotnet/AGENTS.md)
- `docs/` - Design documents and architectural decision records
## Architectural Decision Records (ADRs)
ADRs in `docs/decisions/` capture significant design decisions and their rationale. They document considered alternatives, trade-offs, and the reasoning behind choices.
**Templates:**
- `adr-template.md` - Full template with detailed sections
- `adr-short-template.md` - Abbreviated template for simpler decisions
When proposing architectural changes, create an ADR to capture options considered and the decision rationale. See [docs/decisions/README.md](../docs/decisions/README.md) for the full process.
+60
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# To get started with Dependabot version updates, you'll need to specify which
# package ecosystems to update and where the package manifests are located.
# Please see the documentation for all configuration options:
# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates
version: 2
updates:
# Maintain dependencies for nuget
- package-ecosystem: "nuget"
directory: "dotnet/"
schedule:
interval: "cron"
cronjob: "0 8 * * 4,0" # Every Thursday(4) and Sunday(0) at 8:00 UTC
ignore:
# For all System.* and Microsoft.Extensions/Bcl.* packages, ignore all major version updates
- dependency-name: "System.*"
update-types: ["version-update:semver-major"]
- dependency-name: "Microsoft.Extensions.*"
update-types: ["version-update:semver-major"]
- dependency-name: "Microsoft.Bcl.*"
update-types: ["version-update:semver-major"]
- dependency-name: "Moq"
labels:
- ".NET"
- "dependencies"
# Maintain dependencies for python.
# TODO: Remove these Python Dependabot entries after we have confidence in the
# Python dependency-maintenance workflow.
- package-ecosystem: "pip"
directory: "python/"
schedule:
interval: "weekly"
day: "thursday"
labels:
- "python"
- "dependencies"
- package-ecosystem: "uv"
directory: "python/"
schedule:
interval: "weekly"
day: "thursday"
labels:
- "python"
- "dependencies"
# Maintain dependencies for github-actions
- package-ecosystem: "github-actions"
# Cover both the standard workflow location and our composite actions.
# With `directory: "/"` Dependabot only scans `.github/workflows/*.{yml,yaml}`
# plus a root-level `action.yml/action.yaml`. It does NOT recurse into
# `.github/actions/*/action.yml`, so the glob below is required to keep the
# composite actions in `.github/actions/<name>/` up to date as well.
# Ref: https://docs.github.com/en/code-security/dependabot/working-with-dependabot/dependabot-options-reference#directories-or-directory--
directories:
- "/"
- "/.github/actions/*"
schedule:
interval: "weekly"
day: "sunday"
@@ -0,0 +1,17 @@
---
applyTo: "dotnet/src/Microsoft.Agents.AI.DurableTask/**,dotnet/src/Microsoft.Agents.AI.Hosting.AzureFunctions/**"
---
# Durable Task area code instructions
The following guidelines apply to pull requests that modify files under
`dotnet/src/Microsoft.Agents.AI.DurableTask/**` or
`dotnet/src/Microsoft.Agents.AI.Hosting.AzureFunctions/**`:
## CHANGELOG.md
- Each pull request that modifies code should add just one bulleted entry to the `CHANGELOG.md` file containing a change title (usually the PR title) and a link to the PR itself.
- New PRs should be added to the top of the `CHANGELOG.md` file under a "## [Unreleased]" heading.
- If the PR is the first since the last release, the existing "## [Unreleased]" heading should be replaced with a "## v[X.Y.Z]" heading and the PRs since the last release should be added to the new "## [Unreleased]" heading.
- The style of new `CHANGELOG.md` entries should match the style of the other entries in the file.
- If the PR introduces a breaking change, the changelog entry should be prefixed with "[BREAKING]".
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@@ -0,0 +1,34 @@
# Add 'python' label to any change within the 'python' directory
python:
- changed-files:
- any-glob-to-any-file:
- python/**
# Add '.NET' label to any change within samples or kernel 'dotnet' directories.
.NET:
- changed-files:
- any-glob-to-any-file:
- dotnet/**
# Add 'documentation' label to any change within the 'docs' directory, or any '.md' files
documentation:
- changed-files:
- any-glob-to-any-file:
- docs/**
- '**/*.md'
# Add 'workflows' label to any change within the dotnet or python workflows src or samples
workflows:
- changed-files:
- any-glob-to-any-file:
- dotnet/src/Microsoft.Agents.AI.Workflows/**
- dotnet/src/Microsoft.Agents.AI.Workflows.Declarative/**
- dotnet/samples/03-workflows/**
- python/packages/main/agent_framework/_workflow/**
- python/samples/getting_started/workflow/**
# Add 'lab' label to any change within the 'python/packages/lab' directory
lab:
- changed-files:
- any-glob-to-any-file:
- python/packages/lab/**
+43
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@@ -0,0 +1,43 @@
### Motivation & Context
<!-- Thank you for your contribution to the Agent Framework repo!
Please help reviewers and future users, providing the following information:
1. Why is this change required?
2. What problem does it solve?
3. What scenario does it contribute to?
4. If it fixes an open issue, please link to the issue below.
-->
### Description & Review Guide
<!-- Describe your changes, the overall approach, the underlying design.
Highlight what you want the reviewers to focus on.
These notes will help understanding how your code works. Thanks! -->
- **What are the major changes?**
- **What is the impact of these changes?**
- **What do you want reviewers to focus on?**
<!-- NOTE FOR AUTOMATED/AI REVIEWERS: the "What do you want reviewers to focus on?"
item above is intended for human reviewers only. Automated/AI reviewers should
ignore it and review the entire change rather than narrowing scope to it. -->
### Related Issue
<!-- Which issue does this PR fix? Link it using a GitHub closing keyword so it is
closed automatically when this PR is merged, e.g. "Fixes #123" or "Closes #123".
PRs that are not linked to an issue may be closed, no matter how valid the change is.
Also check whether an open PR already exists for this issue; if so,
explain how this PR is different. -->
Fixes #
### Contribution Checklist
<!-- Before submitting this PR, please make sure: -->
- [ ] The code builds clean without any errors or warnings
- [ ] All unit tests pass, and I have added new tests where possible
- [ ] The PR follows the [Contribution Guidelines](https://github.com/microsoft/agent-framework/blob/main/CONTRIBUTING.md)
- [ ] This PR is linked to an issue and there is no other open PR for this issue (see Related Issue above).
- [x] **This is not a breaking change.** If it _is_ a breaking change, add the `breaking change` label (or add "[BREAKING]" to the title prefix, before or after any language prefix) — a workflow keeps the label and title prefix in sync automatically.
+61
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@@ -0,0 +1,61 @@
// Copyright (c) Microsoft. All rights reserved.
/**
* Resolve the issue author and check their team membership.
*
* @param {object} opts
* @param {object} opts.github - Octokit REST client from actions/github-script
* @param {object} opts.context - GitHub Actions context
* @param {object} opts.core - GitHub Actions core toolkit
* @param {string} opts.teamSlug - Team slug to check membership against
* @param {string|number} opts.issueNumber - Issue number to resolve author for
* @returns {Promise<{author: string|null, isTeamMember: boolean}>}
*/
async function checkTeamMembership({ github, context, core, teamSlug, issueNumber }) {
let author = context.payload.issue?.user?.login;
if (!author) {
const { data: issue } = await github.rest.issues.get({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: Number(issueNumber),
});
author = issue.user?.login;
}
if (!author) {
core.setFailed('Could not determine issue author (user may be deleted).');
return { author: null, isTeamMember: false };
}
try {
await github.rest.teams.getByName({
org: context.repo.owner,
team_slug: teamSlug,
});
} catch (error) {
core.setFailed(`Team lookup failed for ${teamSlug}: ${error.message}`);
throw error;
}
let isTeamMember = false;
try {
const teamMembership = await github.rest.teams.getMembershipForUserInOrg({
org: context.repo.owner,
team_slug: teamSlug,
username: author,
});
isTeamMember = teamMembership.data.state === 'active';
} catch (error) {
if (error.status === 404) {
core.info(`Author ${author} is not a member of team ${teamSlug}.`);
isTeamMember = false;
} else {
core.setFailed(`Team membership lookup failed for ${author}: ${error.message}`);
throw error;
}
}
return { author, isTeamMember };
}
module.exports = checkTeamMembership;
+181
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@@ -0,0 +1,181 @@
// Copyright (c) Microsoft. All rights reserved.
function getPullRequest(context) {
const pullRequest = context.payload.pull_request;
if (!pullRequest?.number || !pullRequest.user?.login) {
throw new Error('This script must be run from a pull_request_target event.');
}
return {
author: pullRequest.user.login,
authorType: pullRequest.user.type,
labels: pullRequest.labels?.map((label) => label.name).filter(Boolean) ?? [],
number: pullRequest.number,
};
}
async function ensureLabel({ github, owner, repo, labelName }) {
try {
await github.rest.issues.getLabel({
owner,
repo,
name: labelName,
});
} catch (error) {
if (error.status !== 404) {
throw error;
}
try {
await github.rest.issues.createLabel({
owner,
repo,
name: labelName,
color: 'd93f0b',
description: 'Community author has exceeded the open pull request limit.',
});
} catch (createError) {
if (createError.status !== 422) {
throw createError;
}
}
}
}
function hasLabel(labels, labelName) {
if (!labelName) {
return false;
}
return labels.some((label) => label.toLowerCase() === labelName.toLowerCase());
}
function isDependabotAuthor({ author, authorType }) {
return authorType === 'Bot' && author.toLowerCase() === 'dependabot[bot]';
}
function buildLimitMessage({ author, exemptLabelName, maxOpenPrs, openPrCount }) {
return [
`Thank you for your contribution, @${author}.`,
'',
`To keep the review queue manageable, we currently limit community contributors to ${maxOpenPrs} `
+ `open pull requests at a time. This PR would put you at ${openPrCount} open pull requests, `
+ 'so we are closing it automatically.',
'',
'Please focus on getting your existing PRs reviewed, merged, or closed before opening another one. '
+ `If a maintainer asked you to open this PR, they can apply the \`${exemptLabelName}\` label and reopen it.`,
].join('\n');
}
async function getOpenPrCount({ github, owner, repo, author, pullRequestNumber }) {
const openPullRequests = await github.paginate(github.rest.pulls.list, {
owner,
repo,
state: 'open',
per_page: 100,
});
const authorOpenPullRequestNumbers = openPullRequests
.filter((pullRequest) => pullRequest.user?.login === author)
.map((pullRequest) => pullRequest.number);
const currentPrIsOpen = authorOpenPullRequestNumbers.includes(pullRequestNumber);
const existingOpenPrCount = currentPrIsOpen
? authorOpenPullRequestNumbers.length - 1
: authorOpenPullRequestNumbers.length;
return existingOpenPrCount + 1;
}
async function enforcePrLimit({ github, context, core, exemptLabelName, maxOpenPrs, labelName }) {
const { owner, repo } = context.repo;
const { author, authorType, labels, number } = getPullRequest(context);
if (isDependabotAuthor({ author, authorType })) {
core.info(`Author ${author} is Dependabot; skipping open PR limit enforcement.`);
return {
author,
closed: false,
dependabotExempt: true,
openPrCount: null,
};
}
if (hasLabel(labels, exemptLabelName)) {
core.info(`PR #${number} has the ${exemptLabelName} label; skipping open PR limit enforcement.`);
return {
author,
closed: false,
exempt: true,
openPrCount: null,
};
}
const openPrCount = await getOpenPrCount({
github,
owner,
repo,
author,
pullRequestNumber: number,
});
if (openPrCount <= maxOpenPrs) {
core.info(
`${author} has ${openPrCount} open pull request(s), which is within the limit of ${maxOpenPrs}.`,
);
return {
author,
closed: false,
openPrCount,
};
}
await ensureLabel({
github,
owner,
repo,
labelName,
});
await github.rest.issues.addLabels({
owner,
repo,
issue_number: number,
labels: [labelName],
});
await github.rest.issues.createComment({
owner,
repo,
issue_number: number,
body: buildLimitMessage({
author,
exemptLabelName,
maxOpenPrs,
openPrCount,
}),
});
await github.rest.pulls.update({
owner,
repo,
pull_number: number,
state: 'closed',
});
core.info(
`${author} has ${openPrCount} open pull request(s), which exceeds the limit of ${maxOpenPrs}. `
+ `Closed PR #${number}.`,
);
return {
author,
closed: true,
openPrCount,
};
}
module.exports = {
buildLimitMessage,
enforcePrLimit,
getOpenPrCount,
};
+216
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@@ -0,0 +1,216 @@
# Copyright (c) Microsoft. All rights reserved.
"""Scan open issues and PRs labeled 'waiting-for-author' for stale follow-ups.
Team members manually add the 'waiting-for-author' label when they need a
response from the external author. If the author hasn't replied within
DAYS_THRESHOLD days of the last team comment, post a reminder and add the
'requested-info' label to prevent duplicate pings.
"""
from __future__ import annotations
import os
import sys
import time
from datetime import datetime, timezone
from github import Auth, Github, GithubException
from github.Issue import Issue
from github.IssueComment import IssueComment
PING_COMMENT = (
"@{author}, friendly reminder — this issue is waiting on your response. "
"Please share any updates when you get a chance. (This is an automated message.)"
)
TRIGGER_LABEL = "waiting-for-author"
PINGED_LABEL = "requested-info"
def get_team_members(g: Github, org: str, team_slug: str) -> set[str]:
"""Fetch active team member usernames."""
try:
org_obj = g.get_organization(org)
team = org_obj.get_team_by_slug(team_slug)
return {m.login for m in team.get_members()}
except GithubException as exc:
if exc.status in (403, 404):
print(
f"ERROR: Failed to fetch team members for {org}/{team_slug} "
f"(HTTP {exc.status}). Check that the token has the 'read:org' "
f"scope and that the team slug '{team_slug}' is correct."
)
else:
print(f"ERROR: Failed to fetch team members for {org}/{team_slug}: {exc}")
sys.exit(1)
except Exception as exc:
print(f"ERROR: Failed to fetch team members for {org}/{team_slug}: {exc}")
sys.exit(1)
def find_last_team_comment(
comments: list[IssueComment], team_members: set[str]
) -> IssueComment | None:
"""Return the most recent comment from a team member, or None."""
for comment in reversed(comments):
if comment.user and comment.user.login in team_members:
return comment
return None
def author_replied_after(
comments: list[IssueComment], author: str, after: datetime
) -> bool:
"""Check if the issue author commented after the given timestamp."""
for comment in comments:
if (
comment.user
and comment.user.login == author
and comment.created_at > after
):
return True
return False
def should_ping(
issue: Issue,
team_members: set[str],
days_threshold: int,
now: datetime,
) -> bool:
"""Determine whether this issue/PR should be pinged.
Only issues/PRs carrying the 'waiting-for-author' label are candidates.
"""
author = issue.user.login
# Skip if the trigger label is not present
if not any(label.name == TRIGGER_LABEL for label in issue.labels):
return False
# Skip if author is a team member
if author in team_members:
return False
# Skip if already pinged
if any(label.name == PINGED_LABEL for label in issue.labels):
return False
# Skip if no comments at all
if issue.comments == 0:
return False
# Fetch comments once for both lookups
comments = list(issue.get_comments())
# Find last team member comment
last_team_comment = find_last_team_comment(comments, team_members)
if last_team_comment is None:
return False
# Skip if author replied after the last team comment
if author_replied_after(comments, author, last_team_comment.created_at):
return False
# Check if enough days have passed
days_since = (now - last_team_comment.created_at.astimezone(timezone.utc)).days
if days_since < days_threshold:
return False
return True
def ping(issue: Issue, dry_run: bool) -> bool:
"""Post a reminder comment and add the 'requested-info' label. Returns True on success."""
author = issue.user.login
kind = "PR" if issue.pull_request else "Issue"
if dry_run:
print(f" [DRY RUN] Would ping {kind} #{issue.number} (@{author})")
return True
max_retries = 3
commented = False
labeled = False
for attempt in range(1, max_retries + 1):
try:
if not commented:
issue.create_comment(PING_COMMENT.format(author=author))
commented = True
if not labeled:
issue.add_to_labels(PINGED_LABEL)
labeled = True
print(f" Pinged {kind} #{issue.number} (@{author})")
return True
except Exception as exc:
if attempt < max_retries:
wait = 2 ** attempt # 2s, 4s
print(f" WARN: Attempt {attempt}/{max_retries} failed for {kind} #{issue.number}: {exc}. Retrying in {wait}s...")
time.sleep(wait)
else:
print(f" ERROR: Failed to ping {kind} #{issue.number} after {max_retries} attempts: {exc}")
return False
def main() -> None:
token = os.environ.get("GITHUB_TOKEN")
if not token:
print("ERROR: GITHUB_TOKEN environment variable is required")
sys.exit(1)
repository = os.environ.get("GITHUB_REPOSITORY")
if not repository:
print("ERROR: GITHUB_REPOSITORY environment variable is required")
sys.exit(1)
team_slug = os.environ.get("TEAM_SLUG")
if not team_slug:
print("ERROR: TEAM_SLUG environment variable is required")
sys.exit(1)
days_threshold_raw = os.environ.get("DAYS_THRESHOLD", "4")
try:
days_threshold = int(days_threshold_raw)
except ValueError:
print(f"ERROR: DAYS_THRESHOLD must be a numeric value, got '{days_threshold_raw}'")
sys.exit(1)
dry_run = os.environ.get("DRY_RUN", "false").lower() == "true"
org = repository.split("/")[0]
if dry_run:
print("Running in DRY RUN mode — no comments or labels will be applied.\n")
g = Github(auth=Auth.Token(token))
repo = g.get_repo(repository)
print(f"Fetching team members for {org}/{team_slug}...")
team_members = get_team_members(g, org, team_slug)
print(f"Found {len(team_members)} team members.\n")
now = datetime.now(timezone.utc)
pinged = []
failed = []
scanned = 0
print(f"Scanning open issues and PRs labeled '{TRIGGER_LABEL}' (threshold: {days_threshold} days)...\n")
for issue in repo.get_issues(state="open", labels=[TRIGGER_LABEL]):
scanned += 1
if should_ping(issue, team_members, days_threshold, now):
if ping(issue, dry_run):
pinged.append(issue.number)
else:
failed.append(issue.number)
print(f"\nDone. Scanned {scanned} items, pinged {len(pinged)}, failed {len(failed)}.")
if pinged:
print(f"Pinged: {', '.join(f'#{n}' for n in pinged)}")
if failed:
print(f"Failed: {', '.join(f'#{n}' for n in failed)}")
sys.exit(1)
if __name__ == "__main__":
main()
+253
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@@ -0,0 +1,253 @@
// Copyright (c) Microsoft. All rights reserved.
const BREAKING_CHANGE_LABEL = 'breaking change';
const BREAKING_PREFIX = '[BREAKING]';
const DEFAULT_PREFIX_LABELS = Object.freeze({
python: 'Python',
'.NET': '.NET',
});
const DEFAULT_BRACKET_PREFIX_LABELS = Object.freeze({
[BREAKING_CHANGE_LABEL]: BREAKING_PREFIX,
});
function escapeRegExp(value) {
return value.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
}
function getMatchingValueByKey(valuesByKey, keyToFind) {
const matchingKey = Object.keys(valuesByKey).find((key) => key.toLowerCase() === keyToFind.toLowerCase());
return matchingKey === undefined ? null : valuesByKey[matchingKey];
}
function getPrefixPattern(prefixes) {
return prefixes.map(escapeRegExp).join('|');
}
function canonicalizePrefix(prefix, prefixes) {
return prefixes.find((knownPrefix) => knownPrefix.toLowerCase() === prefix.toLowerCase()) ?? prefix;
}
function normalizeLeadingBracketPrefix(title, bracketPrefixes) {
const bracketPattern = getPrefixPattern(bracketPrefixes);
if (!bracketPattern) {
return title;
}
const leadingBracketPrefix = new RegExp(`^(${bracketPattern})(?=\\s|$)`, 'i');
return title.replace(
leadingBracketPrefix,
(bracketPrefix) => canonicalizePrefix(bracketPrefix, bracketPrefixes),
);
}
function parseLeadingTitlePrefix(title, titlePrefixes) {
const titlePrefixPattern = getPrefixPattern(titlePrefixes);
if (!titlePrefixPattern) {
return null;
}
const match = title.match(new RegExp(`^(${titlePrefixPattern}):\\s*`, 'i'));
if (!match) {
return null;
}
return {
prefix: canonicalizePrefix(match[1], titlePrefixes),
rest: title.slice(match[0].length).trimStart(),
};
}
function removeBracketPrefixToken(title, bracketPrefix) {
const bracketPrefixPattern = escapeRegExp(bracketPrefix);
return title
.replace(new RegExp(`(^|\\s+)${bracketPrefixPattern}(?=\\s|$)`, 'ig'), '$1')
.replace(/\s{2,}/g, ' ')
.trim();
}
function addTitlePrefix(title, prefix, bracketPrefixes = Object.values(DEFAULT_BRACKET_PREFIX_LABELS)) {
const bracketPattern = getPrefixPattern(bracketPrefixes);
const prefixPattern = escapeRegExp(prefix);
if (bracketPattern) {
const bracketThenTitlePrefix = new RegExp(`^(${bracketPattern})(\\s+)(${prefixPattern})(?=:)`, 'i');
if (bracketThenTitlePrefix.test(title)) {
return title.replace(
bracketThenTitlePrefix,
(match, bracketPrefix, spacing) => `${canonicalizePrefix(bracketPrefix, bracketPrefixes)}${spacing}${prefix}`,
);
}
title = normalizeLeadingBracketPrefix(title, bracketPrefixes);
}
if (!title.startsWith(`${prefix}: `)) {
const existingTitlePrefix = new RegExp(`^${prefixPattern}:\\s*`, 'i');
if (existingTitlePrefix.test(title)) {
return title.replace(existingTitlePrefix, `${prefix}: `);
}
return `${prefix}: ${title}`;
}
return title;
}
function hasBracketPrefix(title, bracketPrefix, titlePrefixes = Object.values(DEFAULT_PREFIX_LABELS)) {
const bracketPrefixPattern = escapeRegExp(bracketPrefix);
const leadingBracketPrefix = new RegExp(`^${bracketPrefixPattern}(?=\\s|$)`, 'i');
if (leadingBracketPrefix.test(title)) {
return true;
}
const leadingTitlePrefix = parseLeadingTitlePrefix(title, titlePrefixes);
if (!leadingTitlePrefix) {
return false;
}
return leadingBracketPrefix.test(leadingTitlePrefix.rest);
}
function addBracketPrefix(title, bracketPrefix, titlePrefixes = Object.values(DEFAULT_PREFIX_LABELS)) {
const bracketPrefixPattern = escapeRegExp(bracketPrefix);
const leadingBracketPrefix = new RegExp(`^${bracketPrefixPattern}(?=\\s|$)`, 'i');
if (leadingBracketPrefix.test(title)) {
return title.replace(leadingBracketPrefix, bracketPrefix);
}
const leadingTitlePrefix = parseLeadingTitlePrefix(title, titlePrefixes);
if (leadingTitlePrefix) {
if (leadingBracketPrefix.test(leadingTitlePrefix.rest)) {
const normalizedRest = leadingTitlePrefix.rest.replace(leadingBracketPrefix, bracketPrefix);
return `${leadingTitlePrefix.prefix}: ${normalizedRest}`;
}
const titleWithoutBracketPrefix = removeBracketPrefixToken(leadingTitlePrefix.rest, bracketPrefix);
return `${leadingTitlePrefix.prefix}: ${bracketPrefix}`
+ (titleWithoutBracketPrefix ? ` ${titleWithoutBracketPrefix}` : '');
}
const titleWithoutBracketPrefix = removeBracketPrefixToken(title, bracketPrefix);
return `${bracketPrefix}${titleWithoutBracketPrefix ? ` ${titleWithoutBracketPrefix}` : ''}`;
}
function hasLabel(labels, labelName) {
return labels.some((label) => label.toLowerCase() === labelName.toLowerCase());
}
function getCurrentTitle(context) {
switch (context.eventName) {
case 'issues':
return context.payload.issue.title;
case 'pull_request_target':
return context.payload.pull_request.title;
default:
throw new Error(`Unrecognized eventName: ${context.eventName}`);
}
}
async function updateTitleForAddedLabel({
github,
context,
core,
prefixLabels = DEFAULT_PREFIX_LABELS,
bracketPrefixLabels = DEFAULT_BRACKET_PREFIX_LABELS,
}) {
const labelAdded = context.payload.label?.name;
if (!labelAdded) {
throw new Error('This script must be run from a labeled event.');
}
const currentTitle = getCurrentTitle(context);
let newTitle = null;
const titlePrefix = getMatchingValueByKey(prefixLabels, labelAdded);
if (titlePrefix !== null) {
newTitle = addTitlePrefix(currentTitle, titlePrefix, Object.values(bracketPrefixLabels));
}
const bracketPrefix = getMatchingValueByKey(bracketPrefixLabels, labelAdded);
if (bracketPrefix !== null) {
newTitle = addBracketPrefix(currentTitle, bracketPrefix, Object.values(prefixLabels));
}
if (newTitle === null) {
core.info(`No title prefix configured for label "${labelAdded}".`);
return { updated: false, newTitle: currentTitle };
}
if (newTitle === currentTitle) {
core.info(`Title already includes the prefix for label "${labelAdded}".`);
return { updated: false, newTitle };
}
switch (context.eventName) {
case 'issues':
await github.rest.issues.update({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
title: newTitle,
});
break;
case 'pull_request_target':
await github.rest.pulls.update({
pull_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
title: newTitle,
});
break;
default:
throw new Error(`Unrecognized eventName: ${context.eventName}`);
}
return { updated: true, newTitle };
}
async function syncBreakingChangeLabelFromTitle({
github,
context,
core,
labelName = BREAKING_CHANGE_LABEL,
bracketPrefix = BREAKING_PREFIX,
titlePrefixes = Object.values(DEFAULT_PREFIX_LABELS),
}) {
const pullRequest = context.payload.pull_request;
if (!pullRequest) {
throw new Error('This script must be run from a pull_request_target event.');
}
const title = pullRequest.title || '';
if (!hasBracketPrefix(title, bracketPrefix, titlePrefixes)) {
core.info(`Title does not include ${bracketPrefix} in the title prefix.`);
return { added: false };
}
const labels = pullRequest.labels?.map((label) => label.name).filter(Boolean) ?? [];
if (hasLabel(labels, labelName)) {
core.info(`PR already has the "${labelName}" label.`);
return { added: false };
}
await github.rest.issues.addLabels({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
labels: [labelName],
});
return { added: true };
}
module.exports = {
addBracketPrefix,
addTitlePrefix,
hasBracketPrefix,
syncBreakingChangeLabelFromTitle,
updateTitleForAddedLabel,
};
+116
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@@ -0,0 +1,116 @@
---
name: pull-requests
description: >
Guidance for creating pull requests and handling PR review comments in the
Agent Framework repository. Use this when writing a PR description (filling out
the PR template) or when responding to and resolving review comments on an
existing PR.
---
# Pull Request Workflow
This skill covers two tasks: (1) writing a high-quality PR description, and
(2) handling review comments on an existing PR.
## 1. Writing the PR description
Always follow the repository PR template at
[`.github/pull_request_template.md`](../../pull_request_template.md). Keep its
exact structure and headings. Fill every section:
### `### Motivation & Context`
Explain *why* the change is needed: the problem it solves and the scenario it
contributes to. Describe the net change relative to `main` — this is implied, so
do **not** spell out "vs main" explicitly.
### `### Description & Review Guide`
Describe the changes, the overall approach, and the design. Answer the three
prompts:
- **What are the major changes?**
- **What is the impact of these changes?**
- **What do you want reviewers to focus on?** — This item is for **human
reviewers only**. Automated/AI reviewers must ignore it and review the entire
change rather than narrowing scope to it.
### `### Related Issue`
Link the issue the PR fixes using a GitHub closing keyword (`Fixes #123` /
`Closes #123`) so it closes automatically on merge. A PR with no linked issue may
be closed regardless of how valid the change is. Before opening, confirm there is
no other open PR for the same issue; if there is, explain how this PR differs.
### `### Contribution Checklist`
Check every item that applies. For the breaking-change item:
- Leave **"This is not a breaking change."** checked for the common case.
- If the change **is** breaking, add the `breaking change` label **or** put
`[BREAKING]` in the title prefix, before or after a language prefix such as
`Python:` or `.NET:` — workflows keep the label and the title prefix in sync
automatically (see `.github/workflows/label-title-prefix.yml` and
`.github/workflows/label-pr.yml`).
### Do not
- Do **not** add ad-hoc sections such as "Validation" or "Tests run"; CI/CD and
the checklist already cover validation status.
- Do **not** remove or reorder the template's headings.
### Creating the PR
Open new PRs as **drafts** until they are ready for review. Example:
```bash
gh pr create --repo microsoft/agent-framework --base main \
--head <your-fork-owner>:<branch> --draft \
--title "<concise title>" --body "<body following the template>"
```
## 2. Handling review comments
When a PR receives review comments, follow this sequence — **do not start editing
code before the user has reviewed the plan**:
1. **Review the comments.** Read every review comment and thread on the PR,
including inline code comments and general review summaries.
2. **Make a plan.** Produce a concrete plan describing how each comment will be
addressed (or why it should not be, with reasoning).
3. **Let the user review the plan.** Present the plan and wait for the user's
approval or adjustments before implementing anything.
4. **Implement.** Make the agreed changes.
5. **Reply to every comment.** Add a reply to **all** comments explaining how it
was addressed (or the agreed outcome) — leave none unanswered.
6. **Resolve resolved threads.** Mark a review thread as resolved only when the
comment has actually been addressed.
### Useful commands
List review comments and threads:
```bash
# Inline review comments
gh api repos/{owner}/{repo}/pulls/{pr}/comments
# Review threads with resolution state (GraphQL)
gh api graphql -f query='
query($owner:String!,$repo:String!,$pr:Int!){
repository(owner:$owner,name:$repo){
pullRequest(number:$pr){
reviewThreads(first:100){
nodes{ id isResolved comments(first:50){ nodes{ id body author{login} } } }
}
}
}
}' -F owner={owner} -F repo={repo} -F pr={pr}
```
Reply to an inline review comment:
```bash
gh api repos/{owner}/{repo}/pulls/{pr}/comments/{comment_id}/replies \
-f body="Addressed in <commit>: <explanation>"
```
Resolve a review thread (needs the thread node id from the GraphQL query above):
```bash
gh api graphql -f query='
mutation($threadId:ID!){
resolveReviewThread(input:{threadId:$threadId}){ thread{ isResolved } }
}' -F threadId={thread_id}
```
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// Copyright (c) Microsoft. All rights reserved.
/**
* Tests for check_team_membership.js.
*
* Run with: node --test .github/tests/test_check_team_membership.js
*/
const { describe, it } = require('node:test');
const assert = require('node:assert/strict');
const checkTeamMembership = require('../scripts/check_team_membership.js');
// ---------------------------------------------------------------------------
// Helpers
// ---------------------------------------------------------------------------
function createMocks({ payloadIssue = undefined, apiUser = 'api-user', teamState = 'active' } = {}) {
const core = {
_infoMessages: [],
_failedMessages: [],
info(msg) { this._infoMessages.push(msg); },
setFailed(msg) { this._failedMessages.push(msg); },
};
const context = {
payload: { issue: payloadIssue },
repo: { owner: 'test-org', repo: 'test-repo' },
};
const github = {
rest: {
issues: {
get: async () => ({
data: { user: apiUser ? { login: apiUser } : null },
}),
},
teams: {
getByName: async () => ({}),
getMembershipForUserInOrg: async () => ({
data: { state: teamState },
}),
},
},
};
return { core, context, github };
}
const BASE_OPTS = { teamSlug: 'my-team', issueNumber: '123' };
// ---------------------------------------------------------------------------
// Author resolution
// ---------------------------------------------------------------------------
describe('author resolution', () => {
it('resolves author from event payload', async () => {
const { github, context, core } = createMocks({
payloadIssue: { user: { login: 'payload-user' } },
});
const result = await checkTeamMembership({ github, context, core, ...BASE_OPTS });
assert.equal(result.author, 'payload-user');
});
it('resolves author via API when payload issue is absent', async () => {
const { github, context, core } = createMocks({ apiUser: 'api-user' });
const result = await checkTeamMembership({ github, context, core, ...BASE_OPTS });
assert.equal(result.author, 'api-user');
});
it('resolves author via API when payload issue user is null (deleted account)', async () => {
const { github, context, core } = createMocks({
payloadIssue: { user: null },
apiUser: 'fetched-user',
});
const result = await checkTeamMembership({ github, context, core, ...BASE_OPTS });
assert.equal(result.author, 'fetched-user');
});
it('handles deleted account when API also returns null user', async () => {
const { github, context, core } = createMocks({ apiUser: null });
const result = await checkTeamMembership({ github, context, core, ...BASE_OPTS });
assert.equal(result.author, null);
assert.equal(result.isTeamMember, false);
assert.ok(core._failedMessages.some(m => m.includes('deleted')));
});
});
// ---------------------------------------------------------------------------
// Team lookup
// ---------------------------------------------------------------------------
describe('team lookup', () => {
it('fails the job when team lookup errors', async () => {
const { github, context, core } = createMocks({
payloadIssue: { user: { login: 'user1' } },
});
const error = new Error('Bad credentials');
github.rest.teams.getByName = async () => { throw error; };
await assert.rejects(
() => checkTeamMembership({ github, context, core, ...BASE_OPTS }),
(err) => err === error,
);
assert.ok(core._failedMessages.some(m => m.includes('Team lookup failed')));
});
});
// ---------------------------------------------------------------------------
// Team membership
// ---------------------------------------------------------------------------
describe('team membership', () => {
it('returns true for active team member', async () => {
const { github, context, core } = createMocks({
payloadIssue: { user: { login: 'member' } },
teamState: 'active',
});
const result = await checkTeamMembership({ github, context, core, ...BASE_OPTS });
assert.equal(result.isTeamMember, true);
});
it('returns false for pending team member', async () => {
const { github, context, core } = createMocks({
payloadIssue: { user: { login: 'pending-user' } },
teamState: 'pending',
});
const result = await checkTeamMembership({ github, context, core, ...BASE_OPTS });
assert.equal(result.isTeamMember, false);
});
it('treats 404 membership response as non-member without failing', async () => {
const { github, context, core } = createMocks({
payloadIssue: { user: { login: 'outsider' } },
});
const notFoundError = new Error('Not Found');
notFoundError.status = 404;
github.rest.teams.getMembershipForUserInOrg = async () => { throw notFoundError; };
const result = await checkTeamMembership({ github, context, core, ...BASE_OPTS });
assert.equal(result.isTeamMember, false);
assert.equal(core._failedMessages.length, 0);
assert.ok(core._infoMessages.some(m => m.includes('not a member')));
});
it('fails the job on non-404 membership errors', async () => {
const { github, context, core } = createMocks({
payloadIssue: { user: { login: 'user1' } },
});
const serverError = new Error('Internal Server Error');
serverError.status = 500;
github.rest.teams.getMembershipForUserInOrg = async () => { throw serverError; };
await assert.rejects(
() => checkTeamMembership({ github, context, core, ...BASE_OPTS }),
(err) => err === serverError,
);
assert.ok(core._failedMessages.some(m => m.includes('membership lookup failed')));
});
it('fails the job on membership errors without status code', async () => {
const { github, context, core } = createMocks({
payloadIssue: { user: { login: 'user1' } },
});
const networkError = new Error('ECONNREFUSED');
github.rest.teams.getMembershipForUserInOrg = async () => { throw networkError; };
await assert.rejects(
() => checkTeamMembership({ github, context, core, ...BASE_OPTS }),
(err) => err === networkError,
);
assert.ok(core._failedMessages.some(m => m.includes('membership lookup failed')));
});
});
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// Copyright (c) Microsoft. All rights reserved.
/**
* Tests for pr_limit_moderation.js.
*
* Run with: node --test .github/tests/test_pr_limit_moderation.js
*/
const { describe, it } = require('node:test');
const assert = require('node:assert/strict');
const { enforcePrLimit } = require('../scripts/pr_limit_moderation.js');
// ---------------------------------------------------------------------------
// Helpers
// ---------------------------------------------------------------------------
function createContext({ author = 'community-user', authorType = 'User', labels = [], number = 123 } = {}) {
return {
repo: {
owner: 'microsoft',
repo: 'agent-framework',
},
payload: {
pull_request: {
number,
labels: labels.map((name) => ({ name })),
user: {
login: author,
type: authorType,
},
},
},
};
}
function createCore() {
const messages = [];
return {
messages,
info(message) {
messages.push(message);
},
};
}
function createGithub({
itemNumbers,
labelExists = true,
pullRequests = createPullRequestPage({ numbers: itemNumbers }),
}) {
const calls = [];
return {
calls,
async paginate(method, params) {
calls.push({ api: 'paginate', method, params });
return pullRequests;
},
rest: {
issues: {
async getLabel(params) {
calls.push({ api: 'issues.getLabel', params });
if (!labelExists) {
const error = new Error('Not Found');
error.status = 404;
throw error;
}
return { data: { name: params.name } };
},
async createLabel(params) {
calls.push({ api: 'issues.createLabel', params });
return { data: { name: params.name } };
},
async addLabels(params) {
calls.push({ api: 'issues.addLabels', params });
return { data: [] };
},
async createComment(params) {
calls.push({ api: 'issues.createComment', params });
return { data: { id: 1 } };
},
},
pulls: {
async list(params) {
calls.push({ api: 'pulls.list', params });
return { data: pullRequests };
},
async update(params) {
calls.push({ api: 'pulls.update', params });
return { data: { state: params.state } };
},
},
},
};
}
function createPullRequestPage({ author = 'community-user', numbers }) {
return numbers.map((number) => ({
number,
user: {
login: author,
},
}));
}
// ---------------------------------------------------------------------------
// PR limit enforcement
// ---------------------------------------------------------------------------
describe('PR limit enforcement', () => {
it('does not close the PR when the author is at the open PR limit', async () => {
const github = createGithub({
itemNumbers: [1, 2, 3, 4, 5, 6, 7, 8, 9, 123],
});
const result = await enforcePrLimit({
github,
context: createContext(),
core: createCore(),
exemptLabelName: 'pr-limit-exempt',
maxOpenPrs: 10,
labelName: 'too-many-prs',
});
assert.equal(result.closed, false);
assert.equal(result.openPrCount, 10);
assert.deepEqual(
github.calls.map((call) => call.api),
['paginate'],
);
});
it('counts the new PR when the pull list includes it', async () => {
const github = createGithub({
itemNumbers: [123, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
});
const result = await enforcePrLimit({
github,
context: createContext(),
core: createCore(),
exemptLabelName: 'pr-limit-exempt',
maxOpenPrs: 10,
labelName: 'too-many-prs',
});
assert.equal(result.closed, true);
assert.equal(result.openPrCount, 11);
assert.deepEqual(
github.calls.map((call) => call.api),
[
'paginate',
'issues.getLabel',
'issues.addLabels',
'issues.createComment',
'pulls.update',
],
);
});
it('counts the current PR on top of existing open PRs', async () => {
const github = createGithub({
itemNumbers: [123, ...Array.from({ length: 24 }, (_, index) => index + 1)],
pullRequests: createPullRequestPage({
numbers: [123, ...Array.from({ length: 25 }, (_, index) => index + 1)],
}),
});
const result = await enforcePrLimit({
github,
context: createContext(),
core: createCore(),
exemptLabelName: 'pr-limit-exempt',
maxOpenPrs: 10,
labelName: 'too-many-prs',
});
assert.equal(result.closed, true);
assert.equal(result.openPrCount, 26);
const comment = github.calls.find((call) => call.api === 'issues.createComment').params.body;
assert.match(comment, /This PR would put you at 26 open pull requests/);
});
it('creates the label when it does not already exist', async () => {
const github = createGithub({
itemNumbers: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 123],
labelExists: false,
});
const result = await enforcePrLimit({
github,
context: createContext(),
core: createCore(),
exemptLabelName: 'pr-limit-exempt',
maxOpenPrs: 10,
labelName: 'too-many-prs',
});
assert.equal(result.closed, true);
assert.deepEqual(
github.calls.map((call) => call.api),
[
'paginate',
'issues.getLabel',
'issues.createLabel',
'issues.addLabels',
'issues.createComment',
'pulls.update',
],
);
assert.equal(
github.calls.find((call) => call.api === 'issues.createLabel').params.name,
'too-many-prs',
);
});
it('tolerates a 422 race when creating the label', async () => {
const github = createGithub({
itemNumbers: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 123],
labelExists: false,
});
github.rest.issues.createLabel = async (params) => {
github.calls.push({ api: 'issues.createLabel', params });
const error = new Error('Validation Failed');
error.status = 422;
throw error;
};
const result = await enforcePrLimit({
github,
context: createContext(),
core: createCore(),
exemptLabelName: 'pr-limit-exempt',
maxOpenPrs: 10,
labelName: 'too-many-prs',
});
assert.equal(result.closed, true);
assert.deepEqual(
github.calls.map((call) => call.api),
[
'paginate',
'issues.getLabel',
'issues.createLabel',
'issues.addLabels',
'issues.createComment',
'pulls.update',
],
);
});
it('uses a diplomatic close message with the configured limit', async () => {
const github = createGithub({
itemNumbers: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 123],
pullRequests: createPullRequestPage({
author: 'octo-contributor',
numbers: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 123],
}),
});
await enforcePrLimit({
github,
context: createContext({ author: 'octo-contributor' }),
core: createCore(),
exemptLabelName: 'pr-limit-exempt',
maxOpenPrs: 10,
labelName: 'too-many-prs',
});
const comment = github.calls.find((call) => call.api === 'issues.createComment').params.body;
assert.match(comment, /Thank you for your contribution/);
assert.match(comment, /limit community contributors to 10 open pull requests/);
assert.match(comment, /@octo-contributor/);
assert.match(comment, /`pr-limit-exempt` label and reopen/);
});
it('does not close an exempt PR when it is reopened', async () => {
const github = createGithub({
itemNumbers: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 123],
});
const result = await enforcePrLimit({
github,
context: createContext({ labels: ['PR-LIMIT-EXEMPT'] }),
core: createCore(),
exemptLabelName: 'pr-limit-exempt',
maxOpenPrs: 10,
labelName: 'too-many-prs',
});
assert.equal(result.closed, false);
assert.equal(result.exempt, true);
assert.equal(result.openPrCount, null);
assert.deepEqual(github.calls, []);
});
it('does not close Dependabot PRs', async () => {
const github = createGithub({
itemNumbers: [123, ...Array.from({ length: 25 }, (_, index) => index + 1)],
pullRequests: createPullRequestPage({
author: 'dependabot[bot]',
numbers: [123, ...Array.from({ length: 25 }, (_, index) => index + 1)],
}),
});
const result = await enforcePrLimit({
github,
context: createContext({ author: 'dependabot[bot]', authorType: 'Bot' }),
core: createCore(),
exemptLabelName: 'pr-limit-exempt',
maxOpenPrs: 10,
labelName: 'too-many-prs',
});
assert.equal(result.closed, false);
assert.equal(result.dependabotExempt, true);
assert.equal(result.openPrCount, null);
assert.deepEqual(github.calls, []);
});
it('counts the current PR when the author has more than one page of open PRs', async () => {
const github = createGithub({
itemNumbers: [123, ...Array.from({ length: 100 }, (_, index) => index + 1)],
});
const result = await enforcePrLimit({
github,
context: createContext({ number: 123 }),
core: createCore(),
exemptLabelName: 'pr-limit-exempt',
maxOpenPrs: 10,
labelName: 'too-many-prs',
});
assert.equal(result.closed, true);
assert.equal(result.openPrCount, 101);
});
});
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# Copyright (c) Microsoft. All rights reserved.
"""Tests for stale_issue_pr_ping.py."""
from __future__ import annotations
import os
import sys
from datetime import datetime, timezone, timedelta
from unittest.mock import MagicMock, patch
import pytest
# Ensure the script directory is importable
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "scripts"))
from stale_issue_pr_ping import (
PINGED_LABEL,
PING_COMMENT,
TRIGGER_LABEL,
author_replied_after,
find_last_team_comment,
get_team_members,
main,
ping,
should_ping,
)
TEAM = {"alice", "bob"}
NOW = datetime(2026, 3, 15, 12, 0, 0, tzinfo=timezone.utc)
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _make_comment(login: str | None, created_at: datetime) -> MagicMock:
"""Create a mock IssueComment."""
c = MagicMock()
if login is None:
c.user = None
else:
c.user = MagicMock()
c.user.login = login
c.created_at = created_at
return c
def _make_label(name: str) -> MagicMock:
lbl = MagicMock()
lbl.name = name
return lbl
def _make_issue(
author: str = "external",
labels: list[str] | None = None,
comment_count: int = 1,
comments: list[MagicMock] | None = None,
pull_request: bool = False,
number: int = 42,
) -> MagicMock:
issue = MagicMock()
issue.user = MagicMock()
issue.user.login = author
issue.number = number
# Default to having the trigger label, since the API query pre-filters.
if labels is None:
labels = [TRIGGER_LABEL]
issue.labels = [_make_label(n) for n in labels]
issue.comments = comment_count
issue.pull_request = MagicMock() if pull_request else None
if comments is not None:
issue.get_comments.return_value = comments
return issue
# ---------------------------------------------------------------------------
# find_last_team_comment
# ---------------------------------------------------------------------------
class TestFindLastTeamComment:
def test_returns_last_team_comment(self):
c1 = _make_comment("alice", datetime(2026, 3, 1, tzinfo=timezone.utc))
c2 = _make_comment("external", datetime(2026, 3, 2, tzinfo=timezone.utc))
c3 = _make_comment("bob", datetime(2026, 3, 3, tzinfo=timezone.utc))
assert find_last_team_comment([c1, c2, c3], TEAM) is c3
def test_returns_none_when_no_team_comments(self):
c1 = _make_comment("external", datetime(2026, 3, 1, tzinfo=timezone.utc))
assert find_last_team_comment([c1], TEAM) is None
def test_returns_none_for_empty_list(self):
assert find_last_team_comment([], TEAM) is None
def test_skips_deleted_user(self):
c1 = _make_comment(None, datetime(2026, 3, 1, tzinfo=timezone.utc))
c2 = _make_comment("alice", datetime(2026, 3, 2, tzinfo=timezone.utc))
assert find_last_team_comment([c1, c2], TEAM) is c2
def test_only_deleted_users(self):
c1 = _make_comment(None, datetime(2026, 3, 1, tzinfo=timezone.utc))
assert find_last_team_comment([c1], TEAM) is None
# ---------------------------------------------------------------------------
# author_replied_after
# ---------------------------------------------------------------------------
class TestAuthorRepliedAfter:
def test_author_replied(self):
after = datetime(2026, 3, 1, tzinfo=timezone.utc)
c1 = _make_comment("external", datetime(2026, 3, 2, tzinfo=timezone.utc))
assert author_replied_after([c1], "external", after) is True
def test_author_not_replied(self):
after = datetime(2026, 3, 5, tzinfo=timezone.utc)
c1 = _make_comment("external", datetime(2026, 3, 2, tzinfo=timezone.utc))
assert author_replied_after([c1], "external", after) is False
def test_different_user_replied(self):
after = datetime(2026, 3, 1, tzinfo=timezone.utc)
c1 = _make_comment("someone_else", datetime(2026, 3, 2, tzinfo=timezone.utc))
assert author_replied_after([c1], "external", after) is False
def test_deleted_user_comment(self):
after = datetime(2026, 3, 1, tzinfo=timezone.utc)
c1 = _make_comment(None, datetime(2026, 3, 2, tzinfo=timezone.utc))
assert author_replied_after([c1], "external", after) is False
# ---------------------------------------------------------------------------
# should_ping
# ---------------------------------------------------------------------------
class TestShouldPing:
def test_should_ping_stale_issue(self):
team_comment = _make_comment("alice", NOW - timedelta(days=5))
issue = _make_issue(comments=[team_comment], comment_count=1)
assert should_ping(issue, TEAM, 4, NOW) is True
def test_skip_team_member_author(self):
issue = _make_issue(author="alice", labels=[TRIGGER_LABEL], comment_count=1)
assert should_ping(issue, TEAM, 4, NOW) is False
def test_skip_already_pinged(self):
issue = _make_issue(labels=[TRIGGER_LABEL, PINGED_LABEL], comment_count=1)
assert should_ping(issue, TEAM, 4, NOW) is False
def test_skip_no_comments(self):
issue = _make_issue(comment_count=0)
assert should_ping(issue, TEAM, 4, NOW) is False
def test_skip_no_team_comment(self):
c = _make_comment("external", NOW - timedelta(days=5))
issue = _make_issue(comments=[c], comment_count=1)
assert should_ping(issue, TEAM, 4, NOW) is False
def test_skip_author_replied(self):
team_c = _make_comment("alice", NOW - timedelta(days=5))
author_c = _make_comment("external", NOW - timedelta(days=3))
issue = _make_issue(comments=[team_c, author_c], comment_count=2)
assert should_ping(issue, TEAM, 4, NOW) is False
def test_skip_not_enough_days(self):
team_comment = _make_comment("alice", NOW - timedelta(days=2))
issue = _make_issue(comments=[team_comment], comment_count=1)
assert should_ping(issue, TEAM, 4, NOW) is False
def test_aware_datetime_handled(self):
"""Timezone-aware datetimes should not be mangled by astimezone."""
aware_dt = (NOW - timedelta(days=5)).replace(tzinfo=timezone.utc)
team_comment = _make_comment("alice", aware_dt)
issue = _make_issue(comments=[team_comment], comment_count=1)
assert should_ping(issue, TEAM, 4, NOW) is True
def test_naive_datetime_handled(self):
"""Naive datetimes (pre-PyGithub 2.x) should be handled by astimezone."""
naive_dt = (NOW - timedelta(days=5)).replace(tzinfo=None)
team_comment = _make_comment("alice", naive_dt)
issue = _make_issue(comments=[team_comment], comment_count=1)
# astimezone on naive datetime treats it as local time; just verify no crash
should_ping(issue, TEAM, 4, NOW)
# ---------------------------------------------------------------------------
# ping
# ---------------------------------------------------------------------------
class TestPing:
def test_dry_run(self, capsys):
issue = _make_issue()
assert ping(issue, dry_run=True) is True
issue.create_comment.assert_not_called()
assert "DRY RUN" in capsys.readouterr().out
def test_success(self, capsys):
issue = _make_issue()
assert ping(issue, dry_run=False) is True
issue.create_comment.assert_called_once()
issue.add_to_labels.assert_called_once_with(PINGED_LABEL)
@patch("stale_issue_pr_ping.time.sleep")
def test_retry_on_failure(self, mock_sleep):
issue = _make_issue()
issue.create_comment.side_effect = [Exception("net error"), None]
assert ping(issue, dry_run=False) is True
assert issue.create_comment.call_count == 2
mock_sleep.assert_called_once()
@patch("stale_issue_pr_ping.time.sleep")
def test_idempotent_retry_skips_comment_on_label_failure(self, mock_sleep):
"""If create_comment succeeds but add_to_labels fails, retry should not re-comment."""
issue = _make_issue()
issue.add_to_labels.side_effect = [Exception("label error"), None]
assert ping(issue, dry_run=False) is True
# Comment should only be created once even though there were 2 attempts
assert issue.create_comment.call_count == 1
assert issue.add_to_labels.call_count == 2
@patch("stale_issue_pr_ping.time.sleep")
def test_all_retries_fail(self, mock_sleep):
issue = _make_issue()
issue.create_comment.side_effect = Exception("permanent error")
assert ping(issue, dry_run=False) is False
assert issue.create_comment.call_count == 3
# ---------------------------------------------------------------------------
# get_team_members
# ---------------------------------------------------------------------------
class TestGetTeamMembers:
def test_success(self):
g = MagicMock()
member = MagicMock()
member.login = "alice"
g.get_organization.return_value.get_team_by_slug.return_value.get_members.return_value = [member]
assert get_team_members(g, "org", "my-team") == {"alice"}
def test_403_error_message(self, capsys):
from github import GithubException
g = MagicMock()
g.get_organization.return_value.get_team_by_slug.side_effect = GithubException(
403, {"message": "Forbidden"}, None
)
with pytest.raises(SystemExit):
get_team_members(g, "org", "my-team")
out = capsys.readouterr().out
assert "read:org" in out
assert "403" in out
def test_404_error_message(self, capsys):
from github import GithubException
g = MagicMock()
g.get_organization.return_value.get_team_by_slug.side_effect = GithubException(
404, {"message": "Not Found"}, None
)
with pytest.raises(SystemExit):
get_team_members(g, "org", "bad-slug")
out = capsys.readouterr().out
assert "read:org" in out
assert "bad-slug" in out
def test_generic_error(self, capsys):
g = MagicMock()
g.get_organization.side_effect = RuntimeError("boom")
with pytest.raises(SystemExit):
get_team_members(g, "org", "team")
# ---------------------------------------------------------------------------
# main env var validation
# ---------------------------------------------------------------------------
class TestMain:
@patch.dict(os.environ, {
"GITHUB_TOKEN": "tok",
"GITHUB_REPOSITORY": "org/repo",
"TEAM_SLUG": "my-team",
"DAYS_THRESHOLD": "abc",
}, clear=True)
def test_invalid_days_threshold(self, capsys):
with pytest.raises(SystemExit):
main()
assert "numeric" in capsys.readouterr().out
@patch.dict(os.environ, {
"GITHUB_TOKEN": "tok",
"GITHUB_REPOSITORY": "org/repo",
}, clear=True)
def test_missing_team_slug(self, capsys):
with pytest.raises(SystemExit):
main()
assert "TEAM_SLUG" in capsys.readouterr().out
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# CodeQL is the code analysis engine developed by GitHub to automate security checks.
# The results are shown as code scanning alerts in GitHub. For more details, visit:
# https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/about-code-scanning-with-codeql
name: "CodeQL"
on:
workflow_dispatch:
push:
# TODO: Add "feature*" back in again, once we determine the cause of the ongoing CodeQL failures.
branches: ["main", "experimental*", "*-development"]
schedule:
- cron: "17 11 * * 2"
jobs:
analyze:
name: Analyze
runs-on: ubuntu-latest
permissions:
actions: read
contents: read
security-events: write
strategy:
fail-fast: false
matrix:
language: ["csharp", "python"]
# CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python', 'ruby' ]
# Use only 'java' to analyze code written in Java, Kotlin or both
# Use only 'javascript' to analyze code written in JavaScript, TypeScript or both
# Learn more about CodeQL language support at https://aka.ms/codeql-docs/language-support
steps:
- name: Checkout repository
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
persist-credentials: false
# Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL
uses: github/codeql-action/init@9e0d7b8d25671d64c341c19c0152d693099fb5ba # v4
with:
languages: ${{ matrix.language }}
# If you wish to specify custom queries, you can do so here or in a config file.
# By default, queries listed here will override any specified in a config file.
# Prefix the list here with "+" to use these queries and those in the config file.
# Details on CodeQL's query packs refer to : https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
# queries: security-extended,security-and-quality
# Autobuild attempts to build any compiled languages (C/C++, C#, Go, or Java).
# If this step fails, then you should remove it and run the build manually (see below)
- name: Autobuild
uses: github/codeql-action/autobuild@9e0d7b8d25671d64c341c19c0152d693099fb5ba # v4
# ️ Command-line programs to run using the OS shell.
# 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
# If the Autobuild fails above, remove it and uncomment the following three lines.
# modify them (or add more) to build your code if your project, please refer to the EXAMPLE below for guidance.
# - run: |
# echo "Run, Build Application using script"
# ./location_of_script_within_repo/buildscript.sh
- name: Perform CodeQL Analysis
uses: github/codeql-action/analyze@9e0d7b8d25671d64c341c19c0152d693099fb5ba # v4
with:
category: "/language:${{matrix.language}}"
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name: DevFlow PR Review
on:
pull_request_target:
types:
- opened
- reopened
- ready_for_review
workflow_dispatch:
inputs:
pr_number:
description: Pull request number to review
required: true
type: string
permissions:
contents: read
issues: write
pull-requests: write
concurrency:
group: devflow-pr-review-${{ github.repository }}-${{ github.event.pull_request.number || inputs.pr_number || github.run_id }}
cancel-in-progress: true
env:
DEVFLOW_REPOSITORY: ${{ vars.DF_REPO }}
DEVFLOW_REF: main
TARGET_REPO_PATH: ${{ github.workspace }}/target-repo
DEVFLOW_PATH: ${{ github.workspace }}/devflow
jobs:
team_check:
runs-on: ubuntu-latest
outputs:
is_team_member: ${{ steps.check.outputs.is_team_member }}
pr_number: ${{ steps.pr.outputs.pr_number }}
pr_url: ${{ steps.pr.outputs.pr_url }}
repo: ${{ steps.pr.outputs.repo }}
steps:
- name: Resolve PR metadata
id: pr
shell: bash
env:
PR_HTML_URL: ${{ github.event.pull_request.html_url }}
PR_NUMBER_EVENT: ${{ github.event.pull_request.number }}
PR_NUMBER_INPUT: ${{ inputs.pr_number }}
run: |
set -euo pipefail
if [[ "${GITHUB_EVENT_NAME}" == "pull_request_target" ]]; then
pr_number="${PR_NUMBER_EVENT}"
pr_url="${PR_HTML_URL}"
else
pr_number="${PR_NUMBER_INPUT}"
pr_url="https://github.com/${GITHUB_REPOSITORY}/pull/${pr_number}"
fi
if [[ ! "$pr_number" =~ ^[1-9][0-9]*$ ]]; then
echo "Could not determine PR number; for workflow_dispatch runs, the 'pr_number' input is required when not running on pull_request_target." >&2
exit 1
fi
echo "pr_url=${pr_url}" >> "$GITHUB_OUTPUT"
echo "pr_number=${pr_number}" >> "$GITHUB_OUTPUT"
echo "repo=${GITHUB_REPOSITORY}" >> "$GITHUB_OUTPUT"
- name: Check PR author team membership
id: check
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
env:
TEAM_NAME: ${{ secrets.DEVELOPER_TEAM }}
PR_NUMBER: ${{ steps.pr.outputs.pr_number }}
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
script: |
let author = context.payload.pull_request?.user?.login;
if (!author) {
const { data: pr } = await github.rest.pulls.get({
owner: context.repo.owner,
repo: context.repo.repo,
pull_number: Number(process.env.PR_NUMBER),
});
author = pr.user.login;
}
let isTeamMember = false;
try {
const teamMembership = await github.rest.teams.getMembershipForUserInOrg({
org: context.repo.owner,
team_slug: process.env.TEAM_NAME,
username: author,
});
isTeamMember = teamMembership.data.state === 'active';
} catch (error) {
console.log(`Team membership lookup failed for ${author}: ${error.message}`);
isTeamMember = false;
}
core.setOutput('is_team_member', isTeamMember ? 'true' : 'false');
if (isTeamMember) {
core.info(`Author ${author} is a team member; proceeding with review.`);
} else {
core.info(`Author ${author} is not a member of ${process.env.TEAM_NAME}; skipping review.`);
}
review:
runs-on: ubuntu-latest
needs: team_check
if: ${{ needs.team_check.outputs.is_team_member == 'true' }}
timeout-minutes: 60
# Advisory check: failures here should not block the PR. The reviewer
# posts comments as a best-effort signal; if the pipeline breaks, the
# PR author should still be able to merge without a red required check.
continue-on-error: true
steps:
# Safe checkout: base repo only, not the untrusted PR head.
- name: Checkout target repo base
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ github.event_name == 'pull_request_target' && github.event.pull_request.base.sha || github.sha }}
fetch-depth: 0
persist-credentials: false
path: target-repo
# Private DevFlow checkout: the PAT/token grants access to this repo's code.
- name: Checkout DevFlow
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
repository: ${{ env.DEVFLOW_REPOSITORY }}
ref: ${{ env.DEVFLOW_REF }}
token: ${{ secrets.DEVFLOW_TOKEN }}
fetch-depth: 1
persist-credentials: false
path: devflow
- name: Set up Python
uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5
with:
python-version: "3.13"
- name: Set up uv
uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7
with:
version: "0.11.x"
enable-cache: true
- name: Install DevFlow dependencies
working-directory: ${{ env.DEVFLOW_PATH }}
run: uv sync --frozen
- name: Run PR review
id: review
working-directory: ${{ env.DEVFLOW_PATH }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GH_COPILOT_TOKEN: ${{ secrets.GH_COPILOT_TOKEN }}
SK_REPO_PATH: ${{ env.TARGET_REPO_PATH }}
AGENT_REPO_PATH: ${{ env.TARGET_REPO_PATH }}
PR_URL: ${{ needs.team_check.outputs.pr_url }}
run: |
uv run python scripts/trigger_pr_review.py \
--pr-url "$PR_URL" \
--github-username "$GITHUB_ACTOR" \
--no-require-comment-selection
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#
# This workflow will build all .slnx files in the dotnet folder, and run all unit tests and integration tests using dotnet docker containers,
# each targeting a single version of the dotnet SDK.
#
name: dotnet-build-and-test
on:
workflow_dispatch:
pull_request:
branches: ["main", "feature*"]
merge_group:
branches: ["main", "feature*"]
push:
branches: ["main", "feature*"]
schedule:
- cron: "0 0 * * *" # Run at midnight UTC daily
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 }}
cancel-in-progress: true
permissions:
contents: read
id-token: "write"
jobs:
paths-filter:
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: read
outputs:
dotnetChanges: ${{ steps.filter.outputs.dotnet }}
cosmosDbChanges: ${{ steps.filter.outputs.cosmosdb }}
foundryHostingChanges: ${{ steps.filter.outputs.foundryHosting }}
functionsChanged: ${{ steps.filter.outputs.functions }}
coreChanged: ${{ steps.filter.outputs.core }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- uses: dorny/paths-filter@fbd0ab8f3e69293af611ebaee6363fc25e6d187d # v4.0.1
id: filter
with:
filters: |
dotnet:
- 'dotnet/**'
cosmosdb:
- 'dotnet/src/Microsoft.Agents.AI.CosmosNoSql/**'
# The Foundry hosted-agent IT is costly (builds a container, pushes to ACR,
# provisions live agents). Only run it when the project under test, its
# dependency chain, the test container, the test fixture, or their tooling
# changed. Keep this list in sync with $hashedDirs in scripts/it-build-image.ps1.
foundryHosting:
- 'dotnet/src/Microsoft.Agents.AI.Foundry.Hosting/**'
- 'dotnet/src/Microsoft.Agents.AI.Foundry/**'
- 'dotnet/src/Microsoft.Agents.AI/**'
- 'dotnet/src/Microsoft.Agents.AI.Abstractions/**'
- 'dotnet/src/Microsoft.Agents.AI.Workflows/**'
- 'dotnet/tests/Foundry.Hosting.IntegrationTests/**'
- 'dotnet/tests/Foundry.Hosting.IntegrationTests.TestContainer/**'
- 'dotnet/samples/04-hosting/FoundryHostedAgents/responses/Hosted-AzureSearchRag/**'
- 'dotnet/Directory.Packages.props'
- 'dotnet/tests/Foundry.Hosting.IntegrationTests/scripts/it-build-image.ps1'
- '.github/workflows/dotnet-build-and-test.yml'
functions:
- 'dotnet/src/Microsoft.Agents.AI.DurableTask/**'
- 'dotnet/src/Microsoft.Agents.AI.Hosting.AzureFunctions/**'
- 'dotnet/tests/Microsoft.Agents.AI.DurableTask.IntegrationTests/**'
- 'dotnet/tests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests/**'
- '.github/actions/azure-functions-integration-setup/**'
- '.github/workflows/dotnet-build-and-test.yml'
core:
- 'dotnet/src/Microsoft.Agents.AI/**'
- 'dotnet/src/Microsoft.Agents.AI.Abstractions/**'
- 'dotnet/src/Microsoft.Agents.AI.OpenAI/**'
- 'dotnet/src/Microsoft.Agents.AI.Workflows/**'
- 'dotnet/src/Microsoft.Agents.AI.Workflows.Generators/**'
- 'dotnet/eng/scripts/New-FilteredSolution.ps1'
- 'dotnet/tests/Directory.Build.props'
- 'dotnet/Directory.Packages.props'
- 'dotnet/global.json'
- '.github/workflows/dotnet-build-and-test.yml'
# run only if 'dotnet' files were changed
- name: dotnet tests
if: steps.filter.outputs.dotnet == 'true'
run: echo "Dotnet file"
- name: dotnet CosmosDB tests
if: steps.filter.outputs.cosmosdb == 'true'
run: echo "Dotnet CosmosDB changes"
# run only if not 'dotnet' files were changed
- name: not dotnet tests
if: steps.filter.outputs.dotnet != 'true'
run: echo "NOT dotnet file"
# Build the full solution (including samples) on all TFMs. No tests.
dotnet-build:
needs: paths-filter
if: needs.paths-filter.outputs.dotnetChanges == 'true'
strategy:
fail-fast: false
matrix:
include:
- { targetFramework: "net10.0", os: "ubuntu-latest", configuration: Release }
- { targetFramework: "net9.0", os: "windows-latest", configuration: Debug }
- { targetFramework: "net8.0", os: "ubuntu-latest", configuration: Release }
- { targetFramework: "net472", os: "windows-latest", configuration: Release }
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
declarative-agents
- name: Free runner disk space
uses: ./.github/actions/free-runner-disk-space
- name: Setup dotnet
uses: actions/setup-dotnet@c2fa09f4bde5ebb9d1777cf28262a3eb3db3ced7 # v5.2.0
with:
global-json-file: ${{ github.workspace }}/dotnet/global.json
- name: Build dotnet solutions
shell: bash
run: |
export SOLUTIONS=$(find ./dotnet/ -type f -name "*.slnx" | tr '\n' ' ')
for solution in $SOLUTIONS; do
dotnet build $solution -c ${{ matrix.configuration }} --warnaserror
done
- name: Package install check
shell: bash
# All frameworks are only built for the release configuration, so we only run this step for the release configuration
# and dotnet new doesn't support net472
if: matrix.configuration == 'Release' && matrix.targetFramework != 'net472'
run: |
TEMP_DIR=$(mktemp -d)
export SOLUTIONS=$(find ./dotnet/ -type f -name "*.slnx" | tr '\n' ' ')
for solution in $SOLUTIONS; do
dotnet pack $solution /property:TargetFrameworks=${{ matrix.targetFramework }} -c ${{ matrix.configuration }} --no-build --no-restore --output "$TEMP_DIR/artifacts"
done
pushd "$TEMP_DIR"
# Create a new console app to test the package installation
dotnet new console -f ${{ matrix.targetFramework }} --name packcheck --output consoleapp
# Create minimal nuget.config and use only dotnet nuget commands
echo '<?xml version="1.0" encoding="utf-8"?><configuration><packageSources><clear /></packageSources></configuration>' > consoleapp/nuget.config
# Add sources with local first using dotnet nuget commands
dotnet nuget add source ../artifacts --name local --configfile consoleapp/nuget.config
dotnet nuget add source https://api.nuget.org/v3/index.json --name nuget.org --configfile consoleapp/nuget.config
# Change to project directory to ensure local nuget.config is used
pushd consoleapp
dotnet add packcheck.csproj package Microsoft.Agents.AI --prerelease
dotnet build -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} packcheck.csproj
# Clean up
popd
popd
rm -rf "$TEMP_DIR"
# Build src+tests only (no samples) for a single TFM and run tests.
dotnet-test:
needs: paths-filter
if: needs.paths-filter.outputs.dotnetChanges == 'true'
strategy:
fail-fast: false
matrix:
include:
- { targetFramework: "net10.0", os: "ubuntu-latest", configuration: Release, integration-tests: true, environment: "integration" }
- { targetFramework: "net472", os: "windows-latest", configuration: Release, integration-tests: true, environment: "integration" }
runs-on: ${{ matrix.os }}
environment: ${{ matrix.environment }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
declarative-agents
- name: Free runner disk space
uses: ./.github/actions/free-runner-disk-space
# Start Cosmos DB Emulator for all integration tests and only for unit tests when CosmosDB changes happened)
- name: Start Azure Cosmos DB Emulator
if: ${{ runner.os == 'Windows' && (needs.paths-filter.outputs.cosmosDbChanges == 'true' || (github.event_name != 'pull_request' && matrix.integration-tests)) }}
shell: pwsh
run: |
Write-Host "Launching Azure Cosmos DB Emulator"
Import-Module "$env:ProgramFiles\Azure Cosmos DB Emulator\PSModules\Microsoft.Azure.CosmosDB.Emulator"
Start-CosmosDbEmulator -NoUI -Key "C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw=="
echo "COSMOSDB_EMULATOR_AVAILABLE=true" >> $env:GITHUB_ENV
- name: Setup dotnet
uses: actions/setup-dotnet@c2fa09f4bde5ebb9d1777cf28262a3eb3db3ced7 # v5.2.0
with:
global-json-file: ${{ github.workspace }}/dotnet/global.json
- name: Generate test solution (no samples)
shell: pwsh
run: |
./dotnet/eng/scripts/New-FilteredSolution.ps1 `
-Solution dotnet/agent-framework-dotnet.slnx `
-TargetFramework ${{ matrix.targetFramework }} `
-Configuration ${{ matrix.configuration }} `
-ExcludeSamples `
-OutputPath dotnet/filtered.slnx `
-Verbose
- name: Build src and tests
shell: bash
run: dotnet build dotnet/filtered.slnx -c ${{ matrix.configuration }} -f ${{ matrix.targetFramework }} --warnaserror
- name: Generate test-type filtered solutions
shell: pwsh
run: |
$commonArgs = @{
Solution = "dotnet/filtered.slnx"
TargetFramework = "${{ matrix.targetFramework }}"
Configuration = "${{ matrix.configuration }}"
Verbose = $true
}
./dotnet/eng/scripts/New-FilteredSolution.ps1 @commonArgs `
-TestProjectNameIncludeFilter "*UnitTests*" `
-OutputPath dotnet/filtered-unit.slnx
./dotnet/eng/scripts/New-FilteredSolution.ps1 @commonArgs `
-TestProjectNameIncludeFilter "*IntegrationTests*" `
-TestProjectNameExcludeFilter "*DurableTask.IntegrationTests*","*AzureFunctions.IntegrationTests*" `
-OutputPath dotnet/filtered-integration.slnx
- name: Run Unit Tests
shell: pwsh
working-directory: dotnet
run: |
$coverageSettings = Join-Path $PWD "tests/coverage.runsettings"
$coverageArgs = @()
if ("${{ matrix.targetFramework }}" -eq "${{ env.COVERAGE_FRAMEWORK }}") {
$coverageArgs = @(
"--coverage",
"--coverage-output-format", "cobertura",
"--coverage-settings", $coverageSettings,
"--results-directory", "../TestResults/Coverage/"
)
}
dotnet test --solution ./filtered-unit.slnx `
-f ${{ matrix.targetFramework }} `
-c ${{ matrix.configuration }} `
--no-build -v Normal `
--report-xunit-trx `
--ignore-exit-code 8 `
@coverageArgs
env:
# Cosmos DB Emulator connection settings
COSMOSDB_ENDPOINT: https://localhost:8081
COSMOSDB_KEY: C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==
- name: Log event name and matrix integration-tests
shell: bash
run: echo "github.event_name:${{ 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 }}"
- name: Azure CLI Login
if: github.event_name != 'pull_request' && matrix.integration-tests
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Run Integration Tests
shell: pwsh
working-directory: dotnet
if: github.event_name != 'pull_request' && matrix.integration-tests
run: |
dotnet test --solution ./filtered-integration.slnx `
-f ${{ matrix.targetFramework }} `
-c ${{ matrix.configuration }} `
--no-build -v Normal `
--report-xunit-trx `
--report-junit `
--results-directory ../IntegrationTestResults/ `
--ignore-exit-code 8 `
--filter-not-trait "Category=IntegrationDisabled" `
--filter-not-trait "Category=FoundryHostedAgents" `
--parallel-algorithm aggressive `
--max-threads 2.0x
env:
# Cosmos DB Emulator connection settings
COSMOSDB_ENDPOINT: https://localhost:8081
COSMOSDB_KEY: C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==
# OpenAI Models
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
OPENAI_CHAT_MODEL_NAME: ${{ vars.OPENAI_CHAT_MODEL_NAME }}
OPENAI_REASONING_MODEL_NAME: ${{ vars.OPENAI_REASONING_MODEL_NAME }}
# Azure OpenAI Models
AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZURE_OPENAI_ENDPOINT }}
# Azure AI Foundry
AZURE_AI_PROJECT_ENDPOINT: ${{ vars.AZURE_AI_PROJECT_ENDPOINT }}
AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZURE_AI_MODEL_DEPLOYMENT_NAME }}
AZURE_AI_BING_CONNECTION_ID: ${{ vars.AZURE_AI_BING_CONNECTION_ID }}
# Anthropic Models
# Disable Anthropic tests by not providing environment vars until 404 failure is resolved
# ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
# ANTHROPIC_CHAT_MODEL_NAME: ${{ vars.ANTHROPIC_CHAT_MODEL_NAME }}
# ANTHROPIC_REASONING_MODEL_NAME: ${{ vars.ANTHROPIC_REASONING_MODEL_NAME }}
# Generate test reports and check coverage
- name: Generate test reports
if: matrix.targetFramework == env.COVERAGE_FRAMEWORK
uses: danielpalme/ReportGenerator-GitHub-Action@2a82782178b2816d9d6960a7345fdd164791b323 # 5.5.3
with:
reports: "./TestResults/Coverage/**/*.cobertura.xml"
targetdir: "./TestResults/Reports"
reporttypes: "HtmlInline;JsonSummary"
- name: Upload coverage report artifact
if: matrix.targetFramework == env.COVERAGE_FRAMEWORK
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: CoverageReport-${{ 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: ./dotnet/eng/scripts/dotnet-check-coverage.ps1 -JsonReportPath "TestResults/Reports/Summary.json" -CoverageThreshold $env:COVERAGE_THRESHOLD
- name: Upload integration test results
if: always() && github.event_name != 'pull_request' && matrix.integration-tests
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: dotnet-test-results-${{ matrix.targetFramework }}-${{ matrix.os }}
path: IntegrationTestResults/**/*.junit
if-no-files-found: ignore
# The Foundry hosted-agent IT is costly (it builds a container, pushes to ACR, and provisions
# live agents on a separate Foundry project). Running it in its own job keeps the overall
# workflow time roughly flat: it executes in parallel to dotnet-build and dotnet-test and is
# gated on paths-filter.outputs.foundryHostingChanges so unrelated edits skip the work.
dotnet-foundry-hosted-it:
needs: paths-filter
if: github.event_name != 'pull_request' && needs.paths-filter.outputs.foundryHostingChanges == 'true'
runs-on: ubuntu-latest
environment: integration
env:
configuration: Release
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
- name: Free runner disk space
uses: ./.github/actions/free-runner-disk-space
- name: Setup dotnet
uses: actions/setup-dotnet@c2fa09f4bde5ebb9d1777cf28262a3eb3db3ced7 # v5.2.0
with:
global-json-file: ${{ github.workspace }}/dotnet/global.json
# Build the test csproj directly instead of a filtered slnx + -f override.
# The test project pins TargetFrameworks=net10.0 and its ProjectReference closure
# gives MSBuild a single-rooted graph, so each multi-targeted dependency is invoked
# exactly once for net10.0. This avoids the MSB3026/MSB3491/MSB4018/MSB3883 file-lock
# collisions caused by parallel inner-builds racing on shared bin/obj output paths
# under the previous slnx + global TFM override approach.
- name: Build Foundry hosted IT (and its deps)
shell: bash
run: dotnet build dotnet/tests/Foundry.Hosting.IntegrationTests/Foundry.Hosting.IntegrationTests.csproj -c "$configuration" --warnaserror
- name: Azure CLI Login
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
# We rebuild and push the test container image on every IT run so framework code changes
# are picked up; the image tag is content-hashed across the test container source AND its
# framework project references, so identical content is a no-op push.
#
# The script always passes --no-dependencies to dotnet publish so publish never re-touches
# the framework lib DLLs the prior "Build Foundry hosted IT (and its deps)" step produced.
# This structurally eliminates the MSB3026 collision that VBCSCompiler from the prebuild
# would otherwise cause by holding file handles to those DLLs. Do not remove the prebuild
# step: the subsequent `dotnet test --no-build` step and the publish's ProjectReference
# resolution both depend on the prebuilt outputs being present.
- name: Build and push Foundry Hosted Agents test container
id: build-foundry-hosted-image
shell: pwsh
working-directory: ${{ github.workspace }}
run: |
$registry = "${{ vars.IT_HOSTED_AGENT_REGISTRY }}"
if ([string]::IsNullOrWhiteSpace($registry)) {
throw "IT_HOSTED_AGENT_REGISTRY not set in the integration environment."
}
& "${{ github.workspace }}/dotnet/tests/Foundry.Hosting.IntegrationTests/scripts/it-build-image.ps1" -Registry $registry | Tee-Object -FilePath $env:GITHUB_ENV -Append
- name: Run Foundry Hosted Agents Integration Tests
shell: pwsh
working-directory: dotnet
run: |
dotnet test --project tests/Foundry.Hosting.IntegrationTests/Foundry.Hosting.IntegrationTests.csproj `
-c $env:configuration `
--no-build -v Normal `
--report-xunit-trx `
--ignore-exit-code 8 `
--filter-trait "Category=FoundryHostedAgents"
env:
AZURE_AI_PROJECT_ENDPOINT: ${{ vars.IT_HOSTED_AGENT_PROJECT_ENDPOINT }}
AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.IT_HOSTED_AGENT_MODEL_DEPLOYMENT_NAME }}
# Azure AI Search (for the azure-search-rag scenario). Reuses the integration
# environment secrets shared with python-sample-validation.yml. The index is
# provisioned out of band; see dotnet/tests/Foundry.Hosting.IntegrationTests/README.md
# for the required schema and seed content.
AZURE_SEARCH_ENDPOINT: ${{ secrets.AZURE_SEARCH_ENDPOINT }}
AZURE_SEARCH_INDEX_NAME: ${{ secrets.AZURE_SEARCH_INDEX_NAME }}
# IT_HOSTED_AGENT_IMAGE was exported into $GITHUB_ENV by the previous step.
# DurableTask and AzureFunctions integration tests (ubuntu/net10.0 only).
# Split from main dotnet-test job for path-based filtering and parallelism.
dotnet-test-functions:
needs: [paths-filter]
if: >
github.event_name != 'pull_request' &&
(needs.paths-filter.outputs.functionsChanged == 'true' ||
needs.paths-filter.outputs.coreChanged == 'true' ||
github.event_name == 'schedule' ||
github.event_name == 'workflow_dispatch')
runs-on: ubuntu-latest
environment: integration
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
declarative-agents
- name: Free runner disk space
uses: ./.github/actions/free-runner-disk-space
- name: Setup dotnet
uses: actions/setup-dotnet@c2fa09f4bde5ebb9d1777cf28262a3eb3db3ced7 # v5.2.0
with:
global-json-file: ${{ github.workspace }}/dotnet/global.json
- name: Build functions integration test projects
shell: bash
working-directory: dotnet
run: |
dotnet build ./tests/Microsoft.Agents.AI.DurableTask.IntegrationTests -c Release -f net10.0 --warnaserror
dotnet build ./tests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests -c Release -f net10.0 --warnaserror
- name: Azure CLI Login
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Set up Durable Task and Azure Functions Integration Test Emulators
uses: ./.github/actions/azure-functions-integration-setup
id: azure-functions-setup
- name: Run Functions Integration Tests
shell: pwsh
working-directory: dotnet
run: |
# Run DurableTask integration tests
dotnet test `
--project ./tests/Microsoft.Agents.AI.DurableTask.IntegrationTests `
-f net10.0 `
-c Release `
--no-build -v Normal `
--report-xunit-trx `
--report-junit `
--results-directory ../IntegrationTestResults/ `
--ignore-exit-code 8 `
--filter-not-trait "Category=IntegrationDisabled" `
--parallel-algorithm aggressive `
--max-threads 2.0x
# Run AzureFunctions integration tests
dotnet test `
--project ./tests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests `
-f net10.0 `
-c Release `
--no-build -v Normal `
--report-xunit-trx `
--report-junit `
--results-directory ../IntegrationTestResults/ `
--ignore-exit-code 8 `
--filter-not-trait "Category=IntegrationDisabled" `
--parallel-algorithm aggressive `
--max-threads 2.0x
env:
# OpenAI Models
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
OPENAI_CHAT_MODEL_NAME: ${{ vars.OPENAI_CHAT_MODEL_NAME }}
OPENAI_REASONING_MODEL_NAME: ${{ vars.OPENAI_REASONING_MODEL_NAME }}
# Azure OpenAI Models
AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZURE_OPENAI_ENDPOINT }}
# Azure AI Foundry
AZURE_AI_PROJECT_ENDPOINT: ${{ vars.AZURE_AI_PROJECT_ENDPOINT }}
AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZURE_AI_MODEL_DEPLOYMENT_NAME }}
AZURE_AI_BING_CONNECTION_ID: ${{ vars.AZURE_AI_BING_CONNECTION_ID }}
- name: Upload functions test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: dotnet-test-results-functions-net10.0-ubuntu-latest
path: IntegrationTestResults/**/*.junit
if-no-files-found: ignore
# This final job is required to satisfy the merge queue. It must only run (or succeed) if no tests failed
dotnet-build-and-test-check:
if: always()
runs-on: ubuntu-latest
needs: [dotnet-build, dotnet-test, dotnet-foundry-hosted-it, dotnet-test-functions]
steps:
- name: Get Date
shell: bash
run: |
echo "date=$(date +'%m/%d/%Y %H:%M:%S')" >> "$GITHUB_ENV"
- name: Run Type is Daily
if: ${{ github.event_name == 'schedule' }}
shell: bash
run: |
echo "run_type=Daily" >> "$GITHUB_ENV"
- name: Run Type is Manual
if: ${{ github.event_name == 'workflow_dispatch' }}
shell: bash
run: |
echo "run_type=Manual" >> "$GITHUB_ENV"
- name: Run Type is ${{ github.event_name }}
if: ${{ github.event_name != 'schedule' && github.event_name != 'workflow_dispatch'}}
shell: bash
run: |
echo "run_type=${{ github.event_name }}" >> "$GITHUB_ENV"
- name: Fail workflow if tests failed
id: check_tests_failed
if: contains(join(needs.*.result, ','), 'failure')
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
script: core.setFailed('Integration Tests Failed!')
- name: Fail workflow if tests cancelled
id: check_tests_cancelled
if: contains(join(needs.*.result, ','), 'cancelled')
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
script: core.setFailed('Integration Tests Cancelled!')
# Integration test trend report (aggregates JUnit XML results from dotnet test jobs)
dotnet-integration-test-report:
name: Integration Test Report
if: >
always() &&
github.event_name != 'pull_request' &&
(contains(join(needs.*.result, ','), 'success') ||
contains(join(needs.*.result, ','), 'failure'))
needs: [dotnet-test, dotnet-test-functions]
runs-on: ubuntu-latest
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
persist-credentials: false
sparse-checkout: |
.github/actions/python-setup
python
- name: Set up python and install the project
uses: ./.github/actions/python-setup
with:
python-version: "3.13"
os: ${{ runner.os }}
- name: Download all test results from current run
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
with:
pattern: dotnet-test-results-*
path: dotnet-test-results/
- name: Restore report history cache
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: python/dotnet-integration-report-history.json
key: dotnet-integration-report-history-${{ github.run_id }}
restore-keys: |
dotnet-integration-report-history-
- name: Generate trend report
run: >
uv run python scripts/integration_test_report/aggregate.py
../dotnet-test-results/
dotnet-integration-report-history.json
dotnet-integration-test-report.md
- name: Post to Job Summary
if: always()
run: cat dotnet-integration-test-report.md >> $GITHUB_STEP_SUMMARY
- name: Save report history cache
if: always()
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: python/dotnet-integration-report-history.json
key: dotnet-integration-report-history-${{ github.run_id }}
- name: Upload trend report
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: dotnet-integration-test-report
path: |
python/dotnet-integration-test-report.md
python/dotnet-integration-report-history.json
+102
View File
@@ -0,0 +1,102 @@
#
# This workflow runs the dotnet formatter on all c-sharp code.
#
name: dotnet-format
on:
workflow_dispatch:
pull_request:
branches: ["main", "feature*"]
paths:
- dotnet/**
- '.github/workflows/dotnet-format.yml'
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
jobs:
check-format:
strategy:
fail-fast: false
matrix:
include:
- { dotnet: "10.0", configuration: Release, os: ubuntu-latest }
runs-on: ${{ matrix.os }}
env:
NUGET_CERT_REVOCATION_MODE: offline
steps:
- name: Check out code
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
fetch-depth: 0
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
- name: Get changed files
id: changed-files
if: github.event_name == 'pull_request'
uses: jitterbit/get-changed-files@b17fbb00bdc0c0f63fcf166580804b4d2cdc2a42 # v1
continue-on-error: true
- name: No C# files changed
id: no-csharp
if: github.event_name == 'pull_request' && steps.changed-files.outputs.added_modified == ''
run: echo "No C# files changed"
# This step will loop over the changed files and find the nearest .csproj file for each one, then store the unique csproj files in a variable
- name: Find csproj files
id: find-csproj
if: github.event_name != 'pull_request' || steps.changed-files.outputs.added_modified != '' || steps.changed-files.outcome == 'failure'
env:
ADDED_MODIFIED: ${{ steps.changed-files.outputs.added_modified }}
run: |
csproj_files=()
exclude_files=("Experimental.Orchestration.Flow.csproj" "Experimental.Orchestration.Flow.UnitTests.csproj" "Experimental.Orchestration.Flow.IntegrationTests.csproj")
set -f
if [[ ${{ steps.changed-files.outcome }} == 'success' ]]; then
for file in $ADDED_MODIFIED; do
echo "$file was changed"
dir="./$file"
while [[ $dir != "." && $dir != "/" && $dir != $GITHUB_WORKSPACE ]]; do
if find "$dir" -maxdepth 1 -name "*.csproj" -print -quit | grep -q .; then
csproj_path="$(find "$dir" -maxdepth 1 -name "*.csproj" -print -quit)"
if [[ ! "${exclude_files[@]}" =~ "${csproj_path##*/}" ]]; then
csproj_files+=("$csproj_path")
fi
break
fi
dir=$(echo ${dir%/*})
done
done
else
# if the changed-files step failed, run dotnet on the whole slnx instead of specific projects
csproj_files=$(find ./ -type f -name "*.slnx" | tr '\n' ' ');
fi
csproj_files=($(printf "%s\n" "${csproj_files[@]}" | sort -u))
echo "Found ${#csproj_files[@]} unique csproj/slnx files: ${csproj_files[*]}"
echo "csproj_files=${csproj_files[*]}" >> $GITHUB_OUTPUT
set +f
- name: Pull container dotnet/sdk:${{ matrix.dotnet }}
if: steps.find-csproj.outputs.csproj_files != ''
run: docker pull mcr.microsoft.com/dotnet/sdk:${{ matrix.dotnet }}
# This step will run dotnet format on each of the unique csproj files and fail if any changes are made
- name: Run dotnet format
if: steps.find-csproj.outputs.csproj_files != ''
env:
CSPROJ_FILES: ${{ steps.find-csproj.outputs.csproj_files }}
run: |
set -f
for csproj in $CSPROJ_FILES; do
echo "Running dotnet format on $csproj"
docker run --rm -v "$(pwd):/app" -w /app mcr.microsoft.com/dotnet/sdk:${{ matrix.dotnet }} dotnet format "$csproj" --verify-no-changes --verbosity diagnostic
done
@@ -0,0 +1,103 @@
#
# Dedicated .NET integration tests workflow, called from the manual integration test orchestrator.
# Only runs integration test matrix entries (net10.0 and net472).
#
name: dotnet-integration-tests
on:
workflow_call:
inputs:
checkout-ref:
description: "Git ref to checkout (e.g., refs/pull/123/head)"
required: true
type: string
permissions:
contents: read
id-token: write
jobs:
dotnet-integration-tests:
strategy:
fail-fast: false
matrix:
include:
- { targetFramework: "net10.0", os: "ubuntu-latest", configuration: Release }
- { targetFramework: "net472", os: "windows-latest", configuration: Release }
runs-on: ${{ matrix.os }}
environment: integration
timeout-minutes: 60
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
declarative-agents
- name: Start Azure Cosmos DB Emulator
if: runner.os == 'Windows'
shell: pwsh
run: |
Write-Host "Launching Azure Cosmos DB Emulator"
Import-Module "$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: Setup dotnet
uses: actions/setup-dotnet@c2fa09f4bde5ebb9d1777cf28262a3eb3db3ced7 # v5.2.0
with:
global-json-file: ${{ github.workspace }}/dotnet/global.json
- name: Build dotnet solutions
shell: bash
run: |
export SOLUTIONS=$(find ./dotnet/ -type f -name "*.slnx" | tr '\n' ' ')
for solution in $SOLUTIONS; do
dotnet build $solution -c ${{ matrix.configuration }} --warnaserror
done
- name: Azure CLI Login
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Set up Durable Task and Azure Functions Integration Test Emulators
if: matrix.os == 'ubuntu-latest'
uses: ./.github/actions/azure-functions-integration-setup
- name: Run Integration Tests
shell: bash
run: |
export INTEGRATION_TEST_PROJECTS=$(find ./dotnet -type f -name "*IntegrationTests.csproj" | tr '\n' ' ')
for project in $INTEGRATION_TEST_PROJECTS; do
target_frameworks=$(dotnet msbuild $project -getProperty:TargetFrameworks -p:Configuration=${{ matrix.configuration }} -nologo 2>/dev/null | tr -d '\r')
if [[ "$target_frameworks" == *"${{ matrix.targetFramework }}"* ]]; then
dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx --filter "Category!=IntegrationDisabled"
else
echo "Skipping $project - does not support target framework ${{ matrix.targetFramework }} (supports: $target_frameworks)"
fi
done
env:
COSMOSDB_ENDPOINT: https://localhost:8081
COSMOSDB_KEY: C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==
COPILOT_GITHUB_TOKEN: ${{ secrets.COPILOT_GITHUB_TOKEN }}
OpenAI__ApiKey: ${{ secrets.OPENAI__APIKEY }}
OpenAI__ChatModelId: ${{ vars.OPENAI__CHATMODELID }}
OpenAI__ChatReasoningModelId: ${{ vars.OPENAI__CHATREASONINGMODELID }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
AzureAI__Endpoint: ${{ secrets.AZUREAI__ENDPOINT }}
AzureAI__DeploymentName: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
AzureAI__BingConnectionId: ${{ vars.AZUREAI__BINGCONECTIONID }}
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
FOUNDRY_MEDIA_DEPLOYMENT_NAME: ${{ vars.FOUNDRY_MEDIA_DEPLOYMENT_NAME }}
FOUNDRY_MODEL_DEPLOYMENT_NAME: ${{ vars.FOUNDRY_MODEL_DEPLOYMENT_NAME }}
FOUNDRY_CONNECTION_GROUNDING_TOOL: ${{ vars.FOUNDRY_CONNECTION_GROUNDING_TOOL }}
+140
View File
@@ -0,0 +1,140 @@
#
# Runs the .NET sample verification tool, which builds and executes sample projects
# and verifies their output using deterministic checks and AI-powered verification.
#
# Results are displayed as a GitHub Job Summary and the CSV report is uploaded as an artifact.
#
name: dotnet-verify-samples
on:
workflow_dispatch:
inputs:
category:
description: "Sample category to run (blank for all)"
required: false
type: choice
options:
- ""
- "01-get-started"
- "02-agents"
- "03-workflows"
parallelism:
description: "Max parallel sample runs"
required: false
default: "8"
type: string
schedule:
- cron: "0 6 * * 1-5" # Weekdays at 6:00 UTC
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
permissions:
contents: read
id-token: write
jobs:
verify-samples:
runs-on: ubuntu-latest
environment: 'integration'
timeout-minutes: 90
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
declarative-agents
- name: Setup dotnet
uses: actions/setup-dotnet@c2fa09f4bde5ebb9d1777cf28262a3eb3db3ced7 # v5.2.0
with:
global-json-file: ${{ github.workspace }}/dotnet/global.json
- name: Azure CLI Login
if: github.event_name != 'pull_request'
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Generate filtered solution
shell: pwsh
run: |
./dotnet/eng/scripts/New-FilteredSolution.ps1 `
-Solution dotnet/agent-framework-dotnet.slnx `
-TargetFramework net10.0 `
-Configuration Debug `
-OutputPath dotnet/filtered.slnx `
-Verbose
- name: Build solution
shell: bash
run: dotnet build dotnet/filtered.slnx -f net10.0 --warnaserror
- name: Run verify-samples
id: verify
working-directory: dotnet
shell: bash
run: |
CATEGORY_ARG=""
if [ -n "$CATEGORY_INPUT" ]; then
CATEGORY_ARG="--category $CATEGORY_INPUT"
fi
dotnet run --project eng/verify-samples -- \
$CATEGORY_ARG \
--parallel "$PARALLELISM" \
--md results.md \
--csv results.csv \
--log results.log
env:
CATEGORY_INPUT: ${{ github.event.inputs.category || '' }}
PARALLELISM: ${{ github.event.inputs.parallelism || '8' }}
# OpenAI Models
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
OPENAI_CHAT_MODEL_NAME: ${{ vars.OPENAI_CHAT_MODEL_NAME }}
OPENAI_REASONING_MODEL_NAME: ${{ vars.OPENAI_REASONING_MODEL_NAME }}
# Azure OpenAI Models
AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZURE_OPENAI_ENDPOINT }}
# Azure AI Foundry
AZURE_AI_PROJECT_ENDPOINT: ${{ vars.AZURE_AI_PROJECT_ENDPOINT }}
AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZURE_AI_MODEL_DEPLOYMENT_NAME }}
AZURE_AI_BING_CONNECTION_ID: ${{ vars.AZURE_AI_BING_CONNECTION_ID }}
# Foundry
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
- name: Write Job Summary
if: always()
working-directory: dotnet
shell: bash
run: |
if [ -f results.md ]; then
cat results.md >> "$GITHUB_STEP_SUMMARY"
else
echo "⚠️ No results.md generated — verify-samples may have failed to start." >> "$GITHUB_STEP_SUMMARY"
fi
- name: Upload results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: verify-samples-results
path: |
dotnet/results.csv
dotnet/results.log
if-no-files-found: warn
- name: Fail if samples failed
if: always() && steps.verify.outcome == 'failure'
shell: bash
run: exit 1
@@ -0,0 +1,134 @@
#
# This workflow allows manually running integration tests against an open PR or a branch.
# Go to Actions → "Integration Tests (Manual)" → Run workflow → enter a PR number or branch name.
#
# It calls dedicated integration-only workflows (dotnet-integration-tests and python-integration-tests),
# passing a ref so they check out and test the correct code.
# Changed paths are detected here so only the relevant test suites run.
#
name: Integration Tests (Manual)
on:
workflow_dispatch:
inputs:
pr-number:
description: "PR number to run integration tests against (leave empty if using branch)"
required: false
type: string
default: ""
branch:
description: "Branch name to run integration tests against (leave empty if using PR number)"
required: false
type: string
default: ""
permissions:
contents: read
pull-requests: read
id-token: write
concurrency:
group: integration-tests-manual-${{ github.event.inputs.pr-number || github.event.inputs.branch }}
cancel-in-progress: true
jobs:
resolve-ref:
name: Resolve ref
runs-on: ubuntu-latest
outputs:
checkout-ref: ${{ steps.resolve.outputs.checkout-ref }}
dotnet-changes: ${{ steps.detect-changes.outputs.dotnet }}
python-changes: ${{ steps.detect-changes.outputs.python }}
steps:
- name: Resolve checkout ref
id: resolve
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
PR_NUMBER: ${{ github.event.inputs.pr-number }}
BRANCH: ${{ github.event.inputs.branch }}
REPO: ${{ github.repository }}
run: |
if [ -n "$PR_NUMBER" ] && [ -n "$BRANCH" ]; then
echo "::error::Please provide either a PR number or a branch name, not both."
exit 1
fi
if [ -z "$PR_NUMBER" ] && [ -z "$BRANCH" ]; then
echo "::error::Please provide either a PR number or a branch name."
exit 1
fi
if [ -n "$PR_NUMBER" ]; then
if ! echo "$PR_NUMBER" | grep -Eq '^[0-9]+$'; then
echo "::error::Invalid PR number. Only numeric values are allowed."
exit 1
fi
PR_DATA=$(gh pr view "$PR_NUMBER" --repo "$REPO" --json state)
PR_STATE=$(echo "$PR_DATA" | jq -r '.state')
if [ "$PR_STATE" != "OPEN" ]; then
echo "::error::PR #$PR_NUMBER is not open (state: $PR_STATE)"
exit 1
fi
echo "checkout-ref=refs/pull/$PR_NUMBER/head" >> "$GITHUB_OUTPUT"
echo "Running integration tests for PR #$PR_NUMBER"
else
if ! echo "$BRANCH" | grep -Eq '^[a-zA-Z0-9_./-]+$'; then
echo "::error::Invalid branch name. Only alphanumeric characters, hyphens, underscores, dots, and slashes are allowed."
exit 1
fi
echo "checkout-ref=$BRANCH" >> "$GITHUB_OUTPUT"
echo "Running integration tests for branch $BRANCH"
fi
- name: Detect changed paths
id: detect-changes
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
PR_NUMBER: ${{ github.event.inputs.pr-number }}
BRANCH: ${{ github.event.inputs.branch }}
REPO: ${{ github.repository }}
run: |
if [ -n "$PR_NUMBER" ]; then
CHANGED_FILES=$(gh pr diff "$PR_NUMBER" --repo "$REPO" --name-only)
else
# For branches, compare against main using the GitHub API
CHANGED_FILES=$(gh api "repos/$REPO/compare/main...$BRANCH" --jq '.files[].filename')
fi
DOTNET_CHANGES=false
PYTHON_CHANGES=false
if echo "$CHANGED_FILES" | grep -q '^dotnet/'; then
DOTNET_CHANGES=true
fi
if echo "$CHANGED_FILES" | grep -q '^python/'; then
PYTHON_CHANGES=true
fi
echo "dotnet=$DOTNET_CHANGES" >> "$GITHUB_OUTPUT"
echo "python=$PYTHON_CHANGES" >> "$GITHUB_OUTPUT"
echo "Detected changes — dotnet: $DOTNET_CHANGES, python: $PYTHON_CHANGES"
dotnet-integration-tests:
name: .NET Integration Tests
needs: resolve-ref
if: needs.resolve-ref.outputs.dotnet-changes == 'true'
uses: ./.github/workflows/dotnet-integration-tests.yml
with:
checkout-ref: ${{ needs.resolve-ref.outputs.checkout-ref }}
secrets: inherit
python-integration-tests:
name: Python Integration Tests
needs: resolve-ref
if: needs.resolve-ref.outputs.python-changes == 'true'
uses: ./.github/workflows/python-integration-tests.yml
with:
checkout-ref: ${{ needs.resolve-ref.outputs.checkout-ref }}
secrets: inherit
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name: Issue Triage
on:
issues:
types: [opened, typed]
permissions:
contents: read
issues: write
id-token: write
concurrency:
group: >-
issue-triage-${{ github.repository }}-${{
github.event.issue.type.name == 'Bug' && github.event.issue.number
|| github.run_id
}}
cancel-in-progress: true
env:
DEVFLOW_REPOSITORY: ${{ vars.DF_REPO }}
DEVFLOW_REF: main
TARGET_REPO_PATH: ${{ github.workspace }}/target-repo
DEVFLOW_PATH: ${{ github.workspace }}/devflow
jobs:
team_check:
runs-on: ubuntu-latest
if: ${{ github.event.issue.type.name == 'Bug' }}
outputs:
is_team_member: ${{ steps.check.outputs.is_team_member }}
issue_number: ${{ steps.issue.outputs.issue_number }}
repo: ${{ steps.issue.outputs.repo }}
steps:
- name: Resolve issue metadata
id: issue
shell: bash
env:
ISSUE_NUMBER_EVENT: ${{ github.event.issue.number }}
run: |
set -euo pipefail
issue_number="${ISSUE_NUMBER_EVENT}"
if [[ ! "$issue_number" =~ ^[1-9][0-9]*$ ]]; then
echo "Could not determine issue number from event payload." >&2
exit 1
fi
echo "issue_number=${issue_number}" >> "$GITHUB_OUTPUT"
echo "repo=${GITHUB_REPOSITORY}" >> "$GITHUB_OUTPUT"
- name: Checkout scripts
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
sparse-checkout: .github/scripts
fetch-depth: 1
persist-credentials: false
- name: Check issue author team membership
id: check
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
env:
TEAM_NAME: ${{ secrets.DEVELOPER_TEAM }}
ISSUE_NUMBER: ${{ steps.issue.outputs.issue_number }}
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
script: |
const checkTeamMembership = require('./.github/scripts/check_team_membership.js');
const { author, isTeamMember } = await checkTeamMembership({
github,
context,
core,
teamSlug: process.env.TEAM_NAME,
issueNumber: process.env.ISSUE_NUMBER,
});
core.setOutput('is_team_member', isTeamMember ? 'true' : 'false');
if (isTeamMember) {
core.info(`Author ${author} is a team member; skipping auto-triage.`);
} else {
core.info(`Author ${author} is not a team member; proceeding with triage.`);
}
triage:
runs-on: ubuntu-latest
needs: team_check
if: ${{ needs.team_check.outputs.is_team_member == 'false' }}
environment: integration
timeout-minutes: 60
steps:
# Safe checkout: base repo only.
- name: Checkout target repo base
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
fetch-depth: 0
persist-credentials: false
path: target-repo
# Private DevFlow (maf-dashboard) checkout.
- name: Checkout DevFlow
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
repository: ${{ env.DEVFLOW_REPOSITORY }}
ref: ${{ env.DEVFLOW_REF }}
token: ${{ secrets.DEVFLOW_TOKEN }}
fetch-depth: 1
persist-credentials: false
path: devflow
- name: Set up Python
uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5
with:
python-version: "3.13"
- name: Set up uv
uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7
with:
version: "0.11.x"
enable-cache: true
- name: Install DevFlow dependencies
working-directory: ${{ env.DEVFLOW_PATH }}
run: uv sync --frozen
- name: Azure CLI Login
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Classify issue relevance
id: spam
working-directory: ${{ env.DEVFLOW_PATH }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
DEVFLOW_TOKEN: ${{ secrets.DEVFLOW_TOKEN }}
SK_REPO_PATH: ${{ env.TARGET_REPO_PATH }}
AGENT_REPO_PATH: ${{ env.TARGET_REPO_PATH }}
ISSUE_REPO: ${{ needs.team_check.outputs.repo }}
ISSUE_NUMBER: ${{ needs.team_check.outputs.issue_number }}
run: |
uv run python scripts/classify_issue_spam.py \
--repo "$ISSUE_REPO" \
--issue-number "$ISSUE_NUMBER" \
--repo-path "${TARGET_REPO_PATH}" \
--apply-labels
- name: Stop after spam gate
if: ${{ steps.spam.outputs.allow_triage != 'true' }}
shell: bash
run: |
echo "Stopping: issue triage preflight did not allow automation."
exit 1
- name: Reproduce reported issue
if: ${{ steps.spam.outputs.allow_triage == 'true' }}
id: repro
working-directory: ${{ env.DEVFLOW_PATH }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GH_COPILOT_TOKEN: ${{ secrets.GH_COPILOT_TOKEN }}
# Not seen by the agent prompt; used only to push a paper-trail
# branch back to maf-dashboard at run end.
DEVFLOW_TOKEN: ${{ secrets.DEVFLOW_TOKEN }}
SK_REPO_PATH: ${{ env.TARGET_REPO_PATH }}
AGENT_REPO_PATH: ${{ env.TARGET_REPO_PATH }}
ISSUE_REPO: ${{ needs.team_check.outputs.repo }}
ISSUE_NUMBER: ${{ needs.team_check.outputs.issue_number }}
# Model-provider settings for generated repro code. Never enter the
# agent prompt; consumed by SDK constructors via os.environ. Azure
# OpenAI and Foundry auth via AAD from the azure/login step above.
OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_EMBEDDING_MODEL: ${{ vars.AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME }}
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
FOUNDRY_AGENT_NAME: ${{ vars.FOUNDRY_AGENT_NAME }}
FOUNDRY_AGENT_VERSION: ${{ vars.FOUNDRY_AGENT_VERSION }}
FOUNDRY_MODELS_ENDPOINT: ${{ vars.FOUNDRY_MODELS_ENDPOINT || '' }}
FOUNDRY_MODELS_API_KEY: ${{ secrets.FOUNDRY_MODELS_API_KEY || '' }}
FOUNDRY_EMBEDDING_MODEL: ${{ vars.FOUNDRY_EMBEDDING_MODEL || '' }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_CHAT_MODEL: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
run: |
uv run python scripts/trigger_issue_repro.py \
--repo "$ISSUE_REPO" \
--issue-number "$ISSUE_NUMBER" \
--github-username "$GITHUB_ACTOR"
+110
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name: Label issues
on:
issues:
types:
- reopened
- opened
jobs:
label_issues:
name: "Issue: add labels"
if: ${{ github.event.action == 'opened' || github.event.action == 'reopened' }}
runs-on: ubuntu-latest
permissions:
issues: write
steps:
- uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
script: |
// Get the issue body and title
const body = context.payload.issue.body
let title = context.payload.issue.title
// Define the labels array
let labels = []
// Check if the issue author is in the agentframework-developers team
let isTeamMember = false
try {
const teamMembership = await github.rest.teams.getMembershipForUserInOrg({
org: context.repo.owner,
team_slug: process.env.TEAM_NAME,
username: context.payload.issue.user.login
})
console.log("Team Membership Data:", teamMembership);
isTeamMember = teamMembership.data.state === 'active'
} catch (error) {
// User is not in the team or team doesn't exist
console.error("Error fetching team membership:", error);
isTeamMember = false
}
// Only add triage label if the author is not in the team
if (!isTeamMember) {
labels.push("triage")
}
// Helper function to extract field value from issue form body
// Issue forms format fields as: ### Field Name\n\nValue
function getFormFieldValue(body, fieldName) {
if (!body) return null
const regex = new RegExp(`###\\s*${fieldName}\\s*\\n\\n([^\\n#]+)`, 'i')
const match = body.match(regex)
return match ? match[1].trim() : null
}
// Check for language from issue form dropdown first
const languageField = getFormFieldValue(body, 'Language')
let languageLabelAdded = false
if (languageField) {
if (languageField === 'Python') {
labels.push("python")
languageLabelAdded = true
} else if (languageField === '.NET') {
labels.push(".NET")
languageLabelAdded = true
}
// 'None / Not Applicable' - don't add any language label
}
// Fallback: Check if the body or the title contains the word 'python' (case-insensitive)
// Only if language wasn't already determined from the form field
if (!languageLabelAdded) {
if ((body != null && body.match(/python/i)) || (title != null && title.match(/python/i))) {
// Add the 'python' label to the array
labels.push("python")
}
// Check if the body or the title contains the words 'dotnet', '.net', 'c#' or 'csharp' (case-insensitive)
if ((body != null && body.match(/\.net/i)) || (title != null && title.match(/\.net/i)) ||
(body != null && body.match(/dotnet/i)) || (title != null && title.match(/dotnet/i)) ||
(body != null && body.match(/C#/i)) || (title != null && title.match(/C#/i)) ||
(body != null && body.match(/csharp/i)) || (title != null && title.match(/csharp/i))) {
// Add the '.NET' label to the array
labels.push(".NET")
}
}
// Check for issue type from issue form dropdown
const issueTypeField = getFormFieldValue(body, 'Type of Issue')
if (issueTypeField) {
if (issueTypeField === 'Feature Request') {
labels.push("enhancement")
} else if (issueTypeField === 'Question') {
labels.push("question")
}
}
// Add the labels to the issue (only if there are labels to add)
if (labels.length > 0) {
github.rest.issues.addLabels({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
labels: labels
});
}
env:
TEAM_NAME: ${{ secrets.DEVELOPER_TEAM }}
+39
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@@ -0,0 +1,39 @@
# This workflow will triage pull requests and apply a label based on the
# paths that are modified in the pull request.
#
# To use this workflow, you will need to set up a .github/labeler.yml
# file with configuration. For more information, see:
# https://github.com/actions/labeler
name: Label pull request
on:
pull_request_target:
types: [opened, synchronize, reopened, edited]
jobs:
add_label:
runs-on: ubuntu-latest
permissions:
contents: read
issues: write
pull-requests: write
steps:
- uses: actions/labeler@f27b608878404679385c85cfa523b85ccb86e213 # v6
with:
repo-token: "${{ secrets.GH_ACTIONS_PR_WRITE }}"
- name: Checkout scripts
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
sparse-checkout: .github/scripts
fetch-depth: 1
persist-credentials: false
- name: "PR: add breaking change label from title"
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
script: |
const { syncBreakingChangeLabelFromTitle } = require('./.github/scripts/title_prefix.js');
await syncBreakingChangeLabelFromTitle({ github, context, core });
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@@ -0,0 +1,31 @@
name: Label title prefix
on:
issues:
types: [labeled]
pull_request_target:
types: [labeled]
jobs:
add_title_prefix:
name: "Issue/PR: add title prefix"
continue-on-error: true
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: write
steps:
- name: Checkout scripts
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
sparse-checkout: .github/scripts
fetch-depth: 1
persist-credentials: false
- uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
name: "Issue/PR: update title"
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
script: |
const { updateTitleForAddedLabel } = require('./.github/scripts/title_prefix.js');
await updateTitleForAddedLabel({ github, context, core });
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@@ -0,0 +1,83 @@
name: Limit community pull requests
on:
pull_request_target:
types: [opened, reopened]
permissions:
contents: read
issues: write
pull-requests: write
concurrency:
group: pr-limit-${{ github.repository }}-${{ github.event.pull_request.user.login }}
cancel-in-progress: false
env:
MAX_OPEN_PULL_REQUESTS: '10'
PR_LIMIT_EXEMPT_LABEL: pr-limit-exempt
TOO_MANY_PRS_LABEL: too-many-prs
jobs:
team_check:
runs-on: ubuntu-latest
outputs:
is_team_member: ${{ steps.check.outputs.is_team_member }}
steps:
- name: Checkout scripts
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
sparse-checkout: .github/scripts
fetch-depth: 1
persist-credentials: false
- name: Check PR author team membership
id: check
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
env:
TEAM_NAME: ${{ secrets.DEVELOPER_TEAM }}
PR_NUMBER: ${{ github.event.pull_request.number }}
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
script: |
const checkTeamMembership = require('./.github/scripts/check_team_membership.js');
const { author, isTeamMember } = await checkTeamMembership({
github,
context,
core,
teamSlug: process.env.TEAM_NAME,
issueNumber: process.env.PR_NUMBER,
});
core.setOutput('is_team_member', isTeamMember ? 'true' : 'false');
if (isTeamMember) {
core.info(`Author ${author} is a team member; skipping open PR limit.`);
} else {
core.info(`Author ${author} is not a team member; checking open PR limit.`);
}
limit_open_prs:
runs-on: ubuntu-latest
needs: team_check
if: ${{ needs.team_check.outputs.is_team_member == 'false' }}
steps:
- name: Checkout scripts
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
sparse-checkout: .github/scripts
fetch-depth: 1
persist-credentials: false
- name: Enforce open PR limit
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
script: |
const { enforcePrLimit } = require('./.github/scripts/pr_limit_moderation.js');
await enforcePrLimit({
github,
context,
core,
exemptLabelName: process.env.PR_LIMIT_EXEMPT_LABEL,
maxOpenPrs: Number.parseInt(process.env.MAX_OPEN_PULL_REQUESTS, 10),
labelName: process.env.TOO_MANY_PRS_LABEL,
});
+41
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@@ -0,0 +1,41 @@
name: Check .md links
on:
workflow_dispatch:
pull_request:
branches: ["main"]
paths:
- '**.md'
- '.github/workflows/markdown-link-check.yml'
- '.github/.linkspector.yml'
schedule:
- cron: "0 0 * * *" # Run at midnight UTC daily
permissions:
contents: read
jobs:
markdown-link-check:
runs-on: ubuntu-22.04
# check out the latest version of the code
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
persist-credentials: false
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: 20
- name: Install Chrome for Puppeteer
run: npx puppeteer browsers install chrome
# Checks the status of hyperlinks in all files
- name: Run linkspector
uses: umbrelladocs/action-linkspector@963b6264d7de32c904942a70b488d3407453049e # v1
with:
reporter: local
filter_mode: nofilter
fail_on_error: true
config_file: ".github/.linkspector.yml"
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name: Merge Gatekeeper
on:
pull_request:
branches: ["main", "feature*"]
merge_group:
branches: ["main"]
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
jobs:
merge-gatekeeper:
runs-on: ubuntu-latest
permissions:
checks: read
statuses: read
steps:
- name: Wait for required checks
if: github.event_name == 'pull_request'
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
env:
TIMEOUT_SECONDS: "3600"
INTERVAL_SECONDS: "30"
SELF_JOB_NAME: ${{ github.job }}
# "Cleanup artifacts", "Agent", "Prepare", and "Upload results" are check runs
# created by an org-level GitHub App (MSDO), not by any workflow in this repo.
# They are outside our control and their transient failures should not block merges.
IGNORED_NAMES: "CodeQL,CodeQL analysis (csharp),Cleanup artifacts,Agent,Prepare,Upload results,review"
with:
script: |
const timeoutSeconds = Number(process.env.TIMEOUT_SECONDS);
const intervalSeconds = Number(process.env.INTERVAL_SECONDS);
const selfName = process.env.SELF_JOB_NAME;
const ignored = new Set(
process.env.IGNORED_NAMES.split(',').map((s) => s.trim()).filter(Boolean),
);
const sha = context.payload.pull_request.head.sha;
const { owner, repo } = context.repo;
const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
// Mirrors upsidr/merge-gatekeeper: merge combined-statuses and check-runs
// for the PR head SHA, with combined-statuses winning on name collision.
async function collectChecks() {
const merged = new Map();
const combined = await github.rest.repos.getCombinedStatusForRef({
owner, repo, ref: sha, per_page: 100,
});
for (const s of combined.data.statuses ?? []) {
if (!merged.has(s.context)) {
// Combined-status states: success | pending | error | failure
merged.set(s.context, { name: s.context, state: s.state });
}
}
const runs = await github.paginate(github.rest.checks.listForRef, {
owner, repo, ref: sha, per_page: 100,
});
for (const r of runs) {
if (merged.has(r.name)) continue;
let state;
if (r.status !== 'completed') {
state = 'pending';
} else if (r.conclusion === 'skipped') {
continue; // Skipped runs are dropped, matching the original action.
} else if (r.conclusion === 'success' || r.conclusion === 'neutral') {
state = 'success';
} else {
// cancelled | timed_out | action_required | stale | failure
state = 'error';
}
merged.set(r.name, { name: r.name, state });
}
return [...merged.values()];
}
function evaluate(entries) {
const failed = [];
const pending = [];
const succeeded = [];
for (const e of entries) {
if (e.name === selfName || ignored.has(e.name)) continue;
if (e.state === 'success') succeeded.push(e.name);
else if (e.state === 'error' || e.state === 'failure') failed.push(e.name);
else pending.push(e.name);
}
return { failed, pending, succeeded };
}
const deadline = Date.now() + timeoutSeconds * 1000;
for (;;) {
const entries = await collectChecks();
const { failed, pending, succeeded } = evaluate(entries);
core.info(
`succeeded=${succeeded.length} pending=${pending.length} failed=${failed.length}`,
);
if (failed.length) {
core.setFailed(`Failing checks: ${failed.join(', ')}`);
return;
}
if (pending.length === 0) {
core.info(`All required checks passed: ${succeeded.join(', ') || '(none)'}`);
return;
}
if (Date.now() > deadline) {
core.setFailed(`Timed out waiting for: ${pending.join(', ')}`);
return;
}
core.info(`Waiting on (${pending.length}): ${pending.slice(0, 10).join(', ')}${pending.length > 10 ? ', …' : ''}`);
await sleep(intervalSeconds * 1000);
}
+382
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@@ -0,0 +1,382 @@
#!/usr/bin/env python3
# Copyright (c) Microsoft. All rights reserved.
"""Check Python test coverage against threshold for enforced targets.
This script parses a Cobertura XML coverage report and enforces a minimum
coverage threshold on specific targets. Targets can be package names
(e.g., "packages.core.agent_framework") or individual Python file paths
(e.g., "packages/core/agent_framework/observability.py").
Non-enforced targets are reported for visibility but don't block the build.
Usage:
python python-check-coverage.py <coverage-xml-path> <threshold>
Example:
python python-check-coverage.py python-coverage.xml 85
"""
import sys
import xml.etree.ElementTree as ET
from dataclasses import dataclass
# =============================================================================
# ENFORCED TARGETS CONFIGURATION
# =============================================================================
# Add or remove entries from this set to control which targets must meet
# the coverage threshold. Only these targets will fail the build if below
# threshold. Other targets are reported for visibility only.
#
# Target values can be:
# - Package paths as they appear in the coverage report
# (e.g., "packages.azure-ai.agent_framework_azure_ai")
# - Python source file paths as they appear in the coverage report
# (e.g., "packages/core/agent_framework/observability.py")
# =============================================================================
ENFORCED_TARGETS: set[str] = {
# Packages (sorted alphabetically)
"packages.anthropic.agent_framework_anthropic",
"packages.azure-ai-search.agent_framework_azure_ai_search",
"packages.core.agent_framework",
"packages.core.agent_framework._workflows",
"packages.foundry.agent_framework_foundry",
"packages.openai.agent_framework_openai",
"packages.purview.agent_framework_purview",
# Individual files (if you want to enforce specific files instead of whole packages)
"packages/core/agent_framework/observability.py",
# Add more targets here as coverage improves
}
@dataclass
class PackageCoverage:
"""Coverage data for a single package."""
name: str
line_rate: float
branch_rate: float
lines_valid: int
lines_covered: int
branches_valid: int
branches_covered: int
@property
def line_coverage_percent(self) -> float:
"""Return line coverage as a percentage."""
return self.line_rate * 100
@property
def branch_coverage_percent(self) -> float:
"""Return branch coverage as a percentage."""
return self.branch_rate * 100
def normalize_coverage_path(path: str) -> str:
"""Normalize coverage paths for reliable matching."""
return path.replace("\\", "/").lstrip("./")
def parse_coverage_xml(
xml_path: str,
) -> tuple[dict[str, PackageCoverage], dict[str, PackageCoverage], float, float]:
"""Parse Cobertura XML and extract per-package coverage data.
Args:
xml_path: Path to the Cobertura XML coverage report.
Returns:
A tuple of (packages_dict, files_dict, overall_line_rate, overall_branch_rate).
"""
tree = ET.parse(xml_path)
root = tree.getroot()
# Get overall coverage from root element
overall_line_rate = float(root.get("line-rate", 0))
overall_branch_rate = float(root.get("branch-rate", 0))
packages: dict[str, PackageCoverage] = {}
file_stats: dict[str, dict[str, int]] = {}
for package in root.findall(".//package"):
package_path = package.get("name", "unknown")
line_rate = float(package.get("line-rate", 0))
branch_rate = float(package.get("branch-rate", 0))
# Count lines and branches from classes within this package
lines_valid = 0
lines_covered = 0
branches_valid = 0
branches_covered = 0
for class_elem in package.findall(".//class"):
file_path = normalize_coverage_path(class_elem.get("filename", ""))
if file_path and file_path not in file_stats:
file_stats[file_path] = {
"lines_valid": 0,
"lines_covered": 0,
"branches_valid": 0,
"branches_covered": 0,
}
for line in class_elem.findall(".//line"):
lines_valid += 1
if int(line.get("hits", 0)) > 0:
lines_covered += 1
if file_path:
file_stats[file_path]["lines_valid"] += 1
if int(line.get("hits", 0)) > 0:
file_stats[file_path]["lines_covered"] += 1
# Branch coverage from line elements
if line.get("branch") == "true":
condition_coverage = line.get("condition-coverage", "")
if condition_coverage:
# Parse "X% (covered/total)" format
try:
coverage_parts = (
condition_coverage.split("(")[1].rstrip(")").split("/")
)
branches_covered += int(coverage_parts[0])
branches_valid += int(coverage_parts[1])
if file_path:
file_stats[file_path]["branches_covered"] += int(
coverage_parts[0]
)
file_stats[file_path]["branches_valid"] += int(
coverage_parts[1]
)
except (IndexError, ValueError):
# Ignore malformed condition-coverage strings; treat this line as having no branch data.
pass
# Use full package path as the key (no aggregation)
packages[package_path] = PackageCoverage(
name=package_path,
line_rate=line_rate if lines_valid == 0 else lines_covered / lines_valid,
branch_rate=branch_rate
if branches_valid == 0
else branches_covered / branches_valid,
lines_valid=lines_valid,
lines_covered=lines_covered,
branches_valid=branches_valid,
branches_covered=branches_covered,
)
files: dict[str, PackageCoverage] = {}
for file_path, stats in file_stats.items():
lines_valid = stats["lines_valid"]
lines_covered = stats["lines_covered"]
branches_valid = stats["branches_valid"]
branches_covered = stats["branches_covered"]
files[file_path] = PackageCoverage(
name=file_path,
line_rate=0 if lines_valid == 0 else lines_covered / lines_valid,
branch_rate=0 if branches_valid == 0 else branches_covered / branches_valid,
lines_valid=lines_valid,
lines_covered=lines_covered,
branches_valid=branches_valid,
branches_covered=branches_covered,
)
return packages, files, overall_line_rate, overall_branch_rate
def format_coverage_value(coverage: float, threshold: float, is_enforced: bool) -> str:
"""Format a coverage value with optional pass/fail indicator.
Args:
coverage: Coverage percentage (0-100).
threshold: Minimum required coverage percentage.
is_enforced: Whether this target is enforced.
Returns:
Formatted string like "85.5%" or "85.5%" or "75.0%".
"""
formatted = f"{coverage:.1f}%"
if is_enforced:
icon = "" if coverage >= threshold else ""
formatted = f"{formatted} {icon}"
return formatted
def print_coverage_table(
packages: dict[str, PackageCoverage],
files: dict[str, PackageCoverage],
threshold: float,
overall_line_rate: float,
overall_branch_rate: float,
) -> None:
"""Print a formatted coverage summary table.
Args:
packages: Dictionary of package name to coverage data.
files: Dictionary of file path to coverage data, used for per-file enforcement.
threshold: Minimum required coverage percentage.
overall_line_rate: Overall line coverage rate (0-1).
overall_branch_rate: Overall branch coverage rate (0-1).
"""
print("\n" + "=" * 80)
print("PYTHON TEST COVERAGE REPORT")
print("=" * 80)
# Overall coverage
print(f"\nOverall Line Coverage: {overall_line_rate * 100:.1f}%")
print(f"Overall Branch Coverage: {overall_branch_rate * 100:.1f}%")
print(f"Threshold: {threshold}%")
enforced_targets = {normalize_coverage_path(t) for t in ENFORCED_TARGETS}
# Package table
print("\n" + "-" * 110)
print(f"{'Package':<80} {'Lines':<15} {'Line Cov':<15}")
print("-" * 110)
# Sort: enforced package targets first, then alphabetically
sorted_packages = sorted(
packages.values(),
key=lambda p: (p.name not in ENFORCED_TARGETS, p.name),
)
for pkg in sorted_packages:
is_enforced = normalize_coverage_path(pkg.name) in enforced_targets
enforced_marker = "[ENFORCED] " if is_enforced else ""
line_cov = format_coverage_value(
pkg.line_coverage_percent, threshold, is_enforced
)
lines_info = f"{pkg.lines_covered}/{pkg.lines_valid}"
package_label = f"{enforced_marker}{pkg.name}"
print(f"{package_label:<80} {lines_info:<15} {line_cov:<15}")
print("-" * 110)
# Enforced file/model entries (if configured)
enforced_files = [
files[target]
for target in sorted(enforced_targets)
if target in files and target.endswith(".py")
]
if enforced_files:
print("\nEnforced Files/Models")
print("-" * 110)
print(f"{'File':<80} {'Lines':<15} {'Line Cov':<15}")
print("-" * 110)
for file_cov in enforced_files:
line_cov = format_coverage_value(
file_cov.line_coverage_percent, threshold, True
)
lines_info = f"{file_cov.lines_covered}/{file_cov.lines_valid}"
print(f"[ENFORCED] {file_cov.name:<69} {lines_info:<15} {line_cov:<15}")
print("-" * 110)
def check_coverage(xml_path: str, threshold: float) -> bool:
"""Check if all enforced targets meet the coverage threshold.
Args:
xml_path: Path to the Cobertura XML coverage report.
threshold: Minimum required coverage percentage.
Returns:
True if all enforced targets pass, False otherwise.
"""
packages, files, overall_line_rate, overall_branch_rate = parse_coverage_xml(
xml_path
)
print_coverage_table(
packages, files, threshold, overall_line_rate, overall_branch_rate
)
# Check enforced targets
failed_targets: list[str] = []
missing_targets: list[str] = []
for target_name in ENFORCED_TARGETS:
normalized_target = normalize_coverage_path(target_name)
package_alias = normalized_target.replace("/", ".")
target_coverage = None
if target_name in packages:
target_coverage = packages[target_name]
elif normalized_target in files:
target_coverage = files[normalized_target]
elif package_alias in packages:
target_coverage = packages[package_alias]
if target_coverage is None:
missing_targets.append(target_name)
continue
if target_coverage.line_coverage_percent < threshold:
failed_targets.append(
f"{target_name} ({target_coverage.line_coverage_percent:.1f}%)"
)
# Report results
if missing_targets:
print(
f"\n❌ FAILED: Enforced targets not found in coverage report: {', '.join(missing_targets)}"
)
return False
if failed_targets:
print(
f"\n❌ FAILED: The following enforced targets are below {threshold}% coverage threshold:"
)
for target in failed_targets:
print(f" - {target}")
print("\nTo fix: Add more tests to improve coverage for the failing targets.")
return False
if ENFORCED_TARGETS:
found_enforced = [
target
for target in ENFORCED_TARGETS
if target in packages or normalize_coverage_path(target) in files
]
if found_enforced:
print(
f"\n✅ PASSED: All enforced targets meet the {threshold}% coverage threshold."
)
return True
def main() -> int:
"""Main entry point.
Returns:
Exit code: 0 for success, 1 for failure.
"""
if len(sys.argv) != 3:
print(f"Usage: {sys.argv[0]} <coverage-xml-path> <threshold>")
print(f"Example: {sys.argv[0]} python-coverage.xml 85")
return 1
xml_path = sys.argv[1]
try:
threshold = float(sys.argv[2])
except ValueError:
print(f"Error: Invalid threshold value: {sys.argv[2]}")
return 1
try:
success = check_coverage(xml_path, threshold)
return 0 if success else 1
except FileNotFoundError:
print(f"Error: Coverage file not found: {xml_path}")
return 1
except ET.ParseError as e:
print(f"Error: Failed to parse coverage XML: {e}")
return 1
if __name__ == "__main__":
sys.exit(main())
+143
View File
@@ -0,0 +1,143 @@
name: Python - Code Quality
on:
merge_group:
workflow_dispatch:
pull_request:
branches: ["main"]
paths:
- "python/**"
- "!python/AGENTS.md"
- "!python/**/AGENTS.md"
- "!python/.github/skills/*"
- "!python/.github/skills/**"
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
jobs:
pre-commit-hooks:
name: Pre-commit Hooks
if: "!cancelled()"
strategy:
fail-fast: false
matrix:
python-version: ["3.11"]
runs-on: ubuntu-latest
continue-on-error: true
defaults:
run:
working-directory: ./python
env:
UV_PYTHON: ${{ matrix.python-version }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
fetch-depth: 0
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
env:
UV_CACHE_DIR: /tmp/.uv-cache
- uses: actions/cache@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5
with:
path: ~/.cache/prek
key: prek|${{ matrix.python-version }}|${{ hashFiles('python/.pre-commit-config.yaml') }}
- uses: j178/prek-action@bdca6f102f98e2b4c7029491a53dfd366469e33d # v2.0.4
name: Run Pre-commit Hooks (excluding poe-check)
env:
SKIP: poe-check
with:
extra-args: --cd python --all-files
package-checks:
name: Package Checks
if: "!cancelled()"
strategy:
fail-fast: false
matrix:
python-version: ["3.11"]
runs-on: ubuntu-latest
continue-on-error: true
defaults:
run:
working-directory: ./python
env:
UV_PYTHON: ${{ matrix.python-version }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
fetch-depth: 0
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
env:
UV_CACHE_DIR: /tmp/.uv-cache
- name: Run syntax and pyright across packages
run: uv run poe check-packages
samples-markdown:
name: Samples & Markdown
if: "!cancelled()"
strategy:
fail-fast: false
matrix:
python-version: ["3.11"]
runs-on: ubuntu-latest
continue-on-error: true
defaults:
run:
working-directory: ./python
env:
UV_PYTHON: ${{ matrix.python-version }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
fetch-depth: 0
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
env:
UV_CACHE_DIR: /tmp/.uv-cache
- name: Run samples checks
run: uv run poe check -S
- name: Run markdown code lint
run: uv run poe markdown-code-lint
test-typing:
name: Test Typing Checks
if: "!cancelled()"
strategy:
fail-fast: false
matrix:
python-version: ["3.11"]
runs-on: ubuntu-latest
continue-on-error: true
defaults:
run:
working-directory: ./python
env:
UV_PYTHON: ${{ matrix.python-version }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
fetch-depth: 0
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
env:
UV_CACHE_DIR: /tmp/.uv-cache
- name: Run tests/samples type checkers (mypy, pyrefly, ty)
run: uv run python scripts/workspace_poe_tasks.py ci-test-typing
@@ -0,0 +1,431 @@
name: Python - Dependency Maintenance
on:
workflow_dispatch:
schedule:
- cron: "0 4 * * 1"
permissions:
contents: write
issues: write
concurrency:
group: python-dependency-maintenance
cancel-in-progress: false
env:
UV_CACHE_DIR: /tmp/.uv-cache
jobs:
dependency-maintenance:
name: Dependency Maintenance
runs-on: ubuntu-latest
env:
# Match the existing Python dependency maintenance workflows. Reevaluate if package
# installability starts differing across supported Python versions.
UV_PYTHON: "3.13"
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
fetch-depth: 0
- name: Set up python and install the project
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
env:
UV_CACHE_DIR: /tmp/.uv-cache
- name: Set dependency release cutoff
run: |
cutoff="$(date -u -d '7 days ago' '+%Y-%m-%dT%H:%M:%SZ')"
echo "DEPENDENCY_RELEASE_CUTOFF=${cutoff}" >> "$GITHUB_ENV"
echo "Using dependency release cutoff: ${cutoff}"
- name: Repin dev dependency declarations
run: uv run poe upgrade-dev-dependency-pins
working-directory: ./python
- name: Refresh lockfile after dev pin updates
run: uv lock
working-directory: ./python
- name: Save dev dependency changes
run: |
DEV_PATCH="${RUNNER_TEMP}/python-dev-dependency-updates.patch"
git diff -- python/pyproject.toml "python/packages/*/pyproject.toml" python/uv.lock > "${DEV_PATCH}"
if [ -s "${DEV_PATCH}" ]; then
echo "has_dev_changes=true" >> "$GITHUB_OUTPUT"
else
echo "has_dev_changes=false" >> "$GITHUB_OUTPUT"
fi
echo "patch=${DEV_PATCH}" >> "$GITHUB_OUTPUT"
id: dev_changes
- name: Run dependency bounds test scenarios
id: validate_bounds_test
continue-on-error: true
run: uv run poe validate-dependency-bounds-test --package "*"
working-directory: ./python
- name: Run dependency upper-bound validation
id: validate_ranges
if: steps.validate_bounds_test.outcome == 'success'
continue-on-error: true
run: uv run poe validate-dependency-bounds-project --mode upper --package "*"
working-directory: ./python
- name: Upload dependency validation reports
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: dependency-maintenance-results
path: |
python/scripts/dependencies/dependency-bounds-test-results.json
python/scripts/dependencies/dependency-range-results.json
if-no-files-found: warn
- name: Create issue for failed dependency bounds test
if: steps.validate_bounds_test.outcome != 'success'
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
script: |
const fs = require("fs")
const reportPath = "python/scripts/dependencies/dependency-bounds-test-results.json"
const owner = context.repo.owner
const repo = context.repo.repo
const openIssues = await github.paginate(github.rest.issues.listForRepo, {
owner,
repo,
state: "open",
per_page: 100,
})
const openIssueTitles = new Set(
openIssues.filter((issue) => !issue.pull_request).map((issue) => issue.title)
)
const formatError = (message) => String(message || "No error output captured.").replace(/```/g, "'''")
const title = "Dependency bounds test failed"
if (openIssueTitles.has(title)) {
core.info(`Issue already exists: ${title}`)
return
}
const bodyLines = [
"Automated dependency bounds test mode failed before dependency upper-bound validation could run.",
"",
"The weekly dependency maintenance workflow kept only dev dependency updates for the generated PR, if any, and skipped dependency range updates for this run.",
"",
]
if (fs.existsSync(reportPath)) {
const report = JSON.parse(fs.readFileSync(reportPath, "utf8"))
const failedScenarios = (report.scenarios ?? []).filter((scenario) => scenario.status === "failed")
for (const scenario of failedScenarios) {
bodyLines.push(`### ${scenario.name} scenario (${scenario.resolution})`)
const failedPackages = (scenario.packages ?? []).filter((pkg) => pkg.status === "failed")
for (const pkg of failedPackages.slice(0, 10)) {
bodyLines.push(
"",
`- Package: \`${pkg.package_name}\``,
`- Project path: \`${pkg.project_path}\``,
"",
"```",
formatError(pkg.error).slice(0, 3500),
"```"
)
}
if (failedPackages.length > 10) {
bodyLines.push("", `_Additional failed packages omitted: ${failedPackages.length - 10}_`)
}
}
} else {
bodyLines.push(`No dependency bounds test report was found at \`${reportPath}\`.`)
}
bodyLines.push("", `Workflow run: ${context.serverUrl}/${owner}/${repo}/actions/runs/${context.runId}`)
await github.rest.issues.create({
owner,
repo,
title,
body: bodyLines.join("\n"),
})
core.info(`Created issue: ${title}`)
- name: Create issues for failed dependency candidates
if: always()
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
script: |
const fs = require("fs")
const reportPath = "python/scripts/dependencies/dependency-range-results.json"
if (!fs.existsSync(reportPath)) {
core.info(`No dependency range report found at ${reportPath}`)
return
}
const report = JSON.parse(fs.readFileSync(reportPath, "utf8"))
const dependencyFailures = []
for (const packageResult of report.packages ?? []) {
for (const dependency of packageResult.dependencies ?? []) {
const candidateVersions = new Set(dependency.candidate_versions ?? [])
const failedAttempts = (dependency.attempts ?? []).filter(
(attempt) => attempt.status === "failed" && candidateVersions.has(attempt.trial_upper)
)
if (!failedAttempts.length) {
continue
}
const failuresByVersion = new Map()
for (const attempt of failedAttempts) {
const version = attempt.trial_upper || "unknown"
if (!failuresByVersion.has(version)) {
failuresByVersion.set(version, attempt.error || "No error output captured.")
}
}
dependencyFailures.push({
packageName: packageResult.package_name,
projectPath: packageResult.project_path,
dependencyName: dependency.name,
originalRequirements: dependency.original_requirements ?? [],
finalRequirements: dependency.final_requirements ?? [],
failedVersions: [...failuresByVersion.entries()].map(([version, error]) => ({ version, error })),
})
}
}
if (!dependencyFailures.length) {
core.info("No failing dependency candidates found.")
return
}
const owner = context.repo.owner
const repo = context.repo.repo
const openIssues = await github.paginate(github.rest.issues.listForRepo, {
owner,
repo,
state: "open",
per_page: 100,
})
const openIssueTitles = new Set(
openIssues.filter((issue) => !issue.pull_request).map((issue) => issue.title)
)
const formatError = (message) => String(message || "No error output captured.").replace(/```/g, "'''")
for (const failure of dependencyFailures) {
const title = `Dependency validation failed: ${failure.dependencyName} (${failure.packageName})`
if (openIssueTitles.has(title)) {
core.info(`Issue already exists: ${title}`)
continue
}
const visibleFailures = failure.failedVersions.slice(0, 5)
const omittedCount = failure.failedVersions.length - visibleFailures.length
const failureDetails = visibleFailures
.map(
(entry) =>
`- \`${entry.version}\`\n\n\`\`\`\n${formatError(entry.error).slice(0, 3500)}\n\`\`\``
)
.join("\n\n")
const body = [
"Automated dependency range validation found candidate versions that failed checks.",
"",
`- Package: \`${failure.packageName}\``,
`- Project path: \`${failure.projectPath}\``,
`- Dependency: \`${failure.dependencyName}\``,
`- Original requirements: ${
failure.originalRequirements.length
? failure.originalRequirements.map((value) => `\`${value}\``).join(", ")
: "_none_"
}`,
`- Final requirements after run: ${
failure.finalRequirements.length
? failure.finalRequirements.map((value) => `\`${value}\``).join(", ")
: "_none_"
}`,
"",
"### Failed versions and errors",
failureDetails,
omittedCount > 0 ? `\n_Additional failed versions omitted: ${omittedCount}_` : "",
"",
`Workflow run: ${context.serverUrl}/${owner}/${repo}/actions/runs/${context.runId}`,
].join("\n")
await github.rest.issues.create({
owner,
repo,
title,
body,
})
openIssueTitles.add(title)
core.info(`Created issue: ${title}`)
}
- name: Keep only dev updates when range validation fails
if: steps.validate_bounds_test.outcome != 'success' || steps.validate_ranges.outcome != 'success'
env:
DEV_PATCH: ${{ steps.dev_changes.outputs.patch }}
HAS_DEV_CHANGES: ${{ steps.dev_changes.outputs.has_dev_changes }}
run: |
git restore python/pyproject.toml python/packages/*/pyproject.toml python/uv.lock
if [ "${HAS_DEV_CHANGES}" = "true" ]; then
git apply "${DEV_PATCH}"
fi
- name: Refresh lockfile after dependency range updates
if: steps.validate_bounds_test.outcome == 'success' && steps.validate_ranges.outcome == 'success'
run: uv lock
working-directory: ./python
- name: Install final dependency set
run: uv run poe install
working-directory: ./python
- name: Run final checks
run: uv run poe check
working-directory: ./python
- name: Run final typing
run: uv run poe typing
working-directory: ./python
- name: Commit and push dependency updates
id: commit_updates
run: |
BRANCH="automation/python-dependency-maintenance"
git config user.name "github-actions[bot]"
git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
git checkout -B "${BRANCH}"
git add python/pyproject.toml python/packages/*/pyproject.toml python/uv.lock
if git diff --cached --quiet; then
echo "has_changes=false" >> "$GITHUB_OUTPUT"
echo "No dependency updates to commit."
exit 0
fi
git commit -m "Python: chore: update dependencies"
git push --force-with-lease --set-upstream origin "${BRANCH}"
echo "has_changes=true" >> "$GITHUB_OUTPUT"
- name: Create or update dependency maintenance tracking issue
if: steps.commit_updates.outputs.has_changes == 'true'
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
script: |
const branch = "automation/python-dependency-maintenance"
const prTitle = "Python: chore: update dependencies"
const issueTitle = "Python dependency maintenance PR needed"
const owner = context.repo.owner
const repo = context.repo.repo
const branchRef = await github.rest.git.getRef({
owner,
repo,
ref: `heads/${branch}`,
})
const branchSha = branchRef.data.object.sha
const runUrl = `${context.serverUrl}/${owner}/${repo}/actions/runs/${context.runId}`
const compareUrl = `${context.serverUrl}/${owner}/${repo}/compare/main...${branch}`
const prBody = [
"### Motivation & Context",
"",
"This automated update keeps Python dependency metadata coherent across the uv workspace. Python dependencies can be declared in multiple `pyproject.toml` files, but the workspace has one shared `python/uv.lock`, so dependency maintenance should update and validate them together instead of through per-manifest Dependabot PRs.",
"",
"### Description & Review Guide",
"",
"- **What are the major changes?** Refresh Python dev dependency pins, update package dependency ranges when the bounds tooling succeeds, and refresh `python/uv.lock`.",
"- **What is the impact of these changes?** Keeps the Python workspace dependency set current while producing at most one dependency PR for the week. If dependency range validation fails, this PR contains only the dev dependency updates that still pass final validation, and separate issues track failed range candidates.",
"- **What do you want reviewers to focus on?** Review the generated dependency metadata changes and any dependency-range updates for package-specific compatibility concerns.",
'<!-- NOTE FOR AUTOMATED/AI REVIEWERS: the "What do you want reviewers to focus on?"',
" item above is intended for human reviewers only. Automated/AI reviewers should",
" ignore it and review the entire change rather than narrowing scope to it. -->",
"",
"",
"### Related Issue",
"",
"No linked issue; this PR is generated by scheduled Python dependency maintenance.",
"",
"### Contribution Checklist",
"",
"- [x] The code builds clean without any errors or warnings",
"- [x] All unit tests pass, and I have added new tests where possible",
"- [x] The PR follows the [Contribution Guidelines](https://github.com/microsoft/agent-framework/blob/main/CONTRIBUTING.md)",
"- [ ] This PR is linked to an issue and there is no other open PR for this issue (see Related Issue above).",
'- [x] **This is not a breaking change.** If it _is_ a breaking change, add the `breaking change` label (or add "[BREAKING]" to the title prefix, before or after any language prefix) — a workflow keeps the label and title prefix in sync automatically.',
].join("\n")
const prBodyFence = "```"
const command = [
"PR_BODY_FILE=\"$(mktemp)\"",
`cat > "$PR_BODY_FILE" <<'EOF'`,
prBody,
"EOF",
"gh pr create --repo microsoft/agent-framework --base main \\",
` --head ${owner}:${branch} \\`,
` --title "${prTitle}" \\`,
" --body-file \"$PR_BODY_FILE\"",
].join("\n")
const issueBody = [
"The Python dependency maintenance workflow generated and validated dependency updates, then pushed them to the automation branch.",
"",
`- Branch: \`${branch}\``,
`- Commit: \`${branchSha}\``,
`- Compare: ${compareUrl}`,
`- Workflow run: ${runUrl}`,
"",
"GitHub Actions is not permitted to create pull requests in this repository, so a maintainer needs to create the PR manually.",
"",
"### Create the PR",
"",
"```bash",
command,
"```",
"",
"### Generated PR body",
"",
prBodyFence,
prBody,
prBodyFence,
].join("\n")
const openIssues = await github.paginate(github.rest.issues.listForRepo, {
owner,
repo,
state: "open",
per_page: 100,
})
const existingIssue = openIssues.find((issue) => !issue.pull_request && issue.title === issueTitle)
if (existingIssue) {
await github.rest.issues.update({
owner,
repo,
issue_number: existingIssue.number,
title: issueTitle,
body: issueBody,
})
core.info(`Updated issue #${existingIssue.number}: ${issueTitle}`)
} else {
const createdIssue = await github.rest.issues.create({
owner,
repo,
title: issueTitle,
body: issueBody,
})
core.info(`Created issue #${createdIssue.data.number}: ${issueTitle}`)
}
+39
View File
@@ -0,0 +1,39 @@
name: Python - Create Docs
on:
workflow_dispatch:
release:
types: [published]
permissions:
contents: write
id-token: write
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
jobs:
python-build-docs:
if: github.event_name == 'release' && startsWith(github.event.release.tag_name, 'python-')
name: Python Build Docs
runs-on: ubuntu-latest
environment: "integration"
env:
UV_PYTHON: "3.11"
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up uv
uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7
with:
version-file: "python/pyproject.toml"
enable-cache: true
cache-suffix: ${{ runner.os }}-${{ env.UV_PYTHON }}
cache-dependency-glob: "**/uv.lock"
- name: Install dependencies
run: uv sync --all-packages --dev --docs
- name: Build the docs
run: uv run poe docs-full
# Upload docs to learn gh
@@ -0,0 +1,610 @@
#
# Dedicated Python integration tests workflow, called from the manual integration test orchestrator.
# Runs all tests (unit + integration) split into parallel jobs by provider.
#
# NOTE: This workflow and python-merge-tests.yml share the same set of parallel
# test jobs. Keep them in sync — when adding, removing, or modifying a job here,
# apply the same change to python-merge-tests.yml.
#
name: python-integration-tests
on:
workflow_call:
inputs:
checkout-ref:
description: "Git ref to checkout (e.g., refs/pull/123/head)"
required: true
type: string
permissions:
contents: read
id-token: write
env:
UV_CACHE_DIR: /tmp/.uv-cache
UV_PYTHON: "3.13"
jobs:
# Unit tests: all non-integration tests across all packages
python-tests-unit:
name: Python Integration Tests - Unit
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Test with pytest (unit tests only)
run: >
uv run poe test -A
-m "not integration"
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
# OpenAI integration tests
python-tests-openai:
name: Python Integration Tests - OpenAI
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
env:
OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Test with pytest (OpenAI integration)
run: >
uv run pytest --import-mode=importlib
packages/openai/tests
-m "integration and not azure"
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-openai
path: ./python/pytest.xml
if-no-files-found: ignore
# Azure OpenAI integration tests
python-tests-azure-openai:
name: Python Integration Tests - Azure OpenAI
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
env:
AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_EMBEDDING_MODEL: ${{ vars.AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Azure CLI Login
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Test with pytest (Azure OpenAI integration)
run: >
uv run pytest --import-mode=importlib
packages/openai/tests/openai/test_openai_chat_completion_client_azure.py
packages/openai/tests/openai/test_openai_chat_client_azure.py
packages/openai/tests/openai/test_openai_embedding_client_azure.py
-m integration
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-azure-openai
path: ./python/pytest.xml
if-no-files-found: ignore
# Misc integration tests (Anthropic, Hyperlight, Ollama, MCP)
python-tests-misc-integration:
name: Python Integration Tests - Misc
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
env:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_CHAT_MODEL: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
OLLAMA_MODEL: qwen2.5:1.5b
OLLAMA_EMBEDDING_MODEL: nomic-embed-text
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Install Ollama
run: curl -fsSL https://ollama.com/install.sh | sh
working-directory: .
- name: Cache Ollama models
uses: actions/cache@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: ~/.ollama/models
key: ollama-models-qwen2.5-1.5b-nomic-embed-text-v1
- name: Start Ollama and pull models
run: |
# Stop any Ollama instance auto-started by the install script
pkill ollama || true
sleep 2
ollama serve &
for i in $(seq 1 30); do
if curl -sf http://localhost:11434/api/tags > /dev/null 2>&1; then
break
fi
sleep 1
done
# Pull models with retry for transient 429 rate limits
for model in qwen2.5:1.5b nomic-embed-text; do
pulled=false
for attempt in 1 2 3; do
if ollama pull "$model"; then
pulled=true
break
fi
echo "Retry $attempt for $model (waiting 15s)..."
sleep 15
done
if [ "$pulled" != "true" ]; then
echo "ERROR: Failed to pull $model after 3 attempts"
exit 1
fi
done
working-directory: .
- name: Start local MCP server
id: local-mcp
uses: ./.github/actions/setup-local-mcp-server
with:
fallback_url: ${{ env.LOCAL_MCP_URL }}
- name: Prefer local MCP URL when available
run: echo "LOCAL_MCP_URL=${{ steps.local-mcp.outputs.effective_url }}" >> "$GITHUB_ENV"
- name: Test with pytest (Anthropic, Hyperlight, Ollama, MCP integration)
run: >
uv run pytest --import-mode=importlib
packages/anthropic/tests
packages/hyperlight/tests
packages/ollama/tests
packages/core/tests/core/test_mcp.py
-m integration
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 30
--junitxml=pytest.xml
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-misc
path: ./python/pytest.xml
if-no-files-found: ignore
- name: Stop local MCP server
if: always()
shell: bash
run: |
set -euo pipefail
server_pid="${{ steps.local-mcp.outputs.pid }}"
if [[ -z "$server_pid" ]]; then
exit 0
fi
if ! kill -0 "$server_pid" 2>/dev/null; then
exit 0
fi
kill -TERM -- "-$server_pid" 2>/dev/null || kill -TERM "$server_pid" 2>/dev/null || true
for _ in $(seq 1 10); do
if ! kill -0 "$server_pid" 2>/dev/null; then
exit 0
fi
sleep 1
done
kill -KILL -- "-$server_pid" 2>/dev/null || kill -KILL "$server_pid" 2>/dev/null || true
# Azure Functions + Durable Task integration tests
python-tests-functions:
name: Python Integration Tests - Functions
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
env:
UV_PYTHON: "3.11"
OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
AZURE_OPENAI_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
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
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Azure CLI Login
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
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 (Functions + Durable Task integration)
run: >
uv run pytest --import-mode=importlib
packages/azurefunctions/tests/integration_tests
packages/durabletask/tests/integration_tests
-m integration
-n logical --dist worksteal
-x
--timeout=480 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-functions
path: ./python/pytest.xml
if-no-files-found: ignore
# Foundry integration tests
python-tests-foundry:
name: Python Integration Tests - Foundry
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
env:
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
FOUNDRY_AGENT_NAME: ${{ vars.FOUNDRY_AGENT_NAME }}
FOUNDRY_AGENT_VERSION: ${{ vars.FOUNDRY_AGENT_VERSION }}
FOUNDRY_MODELS_ENDPOINT: ${{ vars.FOUNDRY_MODELS_ENDPOINT || '' }}
FOUNDRY_MODELS_API_KEY: ${{ secrets.FOUNDRY_MODELS_API_KEY || '' }}
FOUNDRY_EMBEDDING_MODEL: ${{ vars.FOUNDRY_EMBEDDING_MODEL || '' }}
FOUNDRY_IMAGE_EMBEDDING_MODEL: ${{ vars.FOUNDRY_IMAGE_EMBEDDING_MODEL || '' }}
LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Azure CLI Login
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Test with pytest
timeout-minutes: 15
run: >
uv run pytest --import-mode=importlib
packages/foundry/tests
-m integration
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-foundry
path: ./python/pytest.xml
if-no-files-found: ignore
# Foundry Hosting integration tests
python-tests-foundry-hosting:
name: Python Integration Tests - Foundry Hosting
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
env:
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Azure CLI Login
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Test with pytest (Foundry Hosting integration)
timeout-minutes: 15
run: >
uv run pytest --import-mode=importlib
packages/foundry_hosting/tests
-m integration
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-foundry-hosting
path: ./python/pytest.xml
if-no-files-found: ignore
# Azure Cosmos integration tests
python-tests-cosmos:
name: Python Integration Tests - Cosmos
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
services:
cosmosdb:
image: mcr.microsoft.com/cosmosdb/linux/azure-cosmos-emulator:vnext-preview
ports:
- 8081:8081
env:
AZURE_COSMOS_ENDPOINT: "http://localhost:8081/"
# Static Azure Cosmos DB emulator key (documented): https://learn.microsoft.com/en-us/azure/cosmos-db/emulator
AZURE_COSMOS_KEY: "C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw=="
AZURE_COSMOS_DATABASE_NAME: "agent-framework-cosmos-it-db"
AZURE_COSMOS_CONTAINER_NAME: "agent-framework-cosmos-it-container"
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Wait for Cosmos DB emulator
run: |
for i in {1..60}; do
if curl --silent --show-error http://localhost:8081/ > /dev/null; then
echo "Cosmos DB emulator is ready."
exit 0
fi
sleep 2
done
echo "Cosmos DB emulator did not become ready in time." >&2
exit 1
- name: Test with pytest (Cosmos integration)
run: uv run --directory packages/azure-cosmos poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5 --junitxml=${{ github.workspace }}/python/pytest.xml
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-cosmos
path: ./python/pytest.xml
if-no-files-found: ignore
# GitHub Copilot integration tests
python-tests-github-copilot:
name: Python Integration Tests - GitHub Copilot
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
env:
COPILOT_GITHUB_TOKEN: ${{ secrets.COPILOT_GITHUB_TOKEN }}
GITHUB_COPILOT_TIMEOUT: "120"
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Test with pytest (GitHub Copilot integration)
run: >
uv run pytest --import-mode=importlib
packages/github_copilot/tests
-m integration
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-github-copilot
path: ./python/pytest.xml
if-no-files-found: ignore
# Integration test trend report (aggregates per-job JUnit XML results)
python-integration-test-report:
name: Integration Test Report
if: >
always() &&
(contains(join(needs.*.result, ','), 'success') ||
contains(join(needs.*.result, ','), 'failure'))
needs:
[
python-tests-openai,
python-tests-azure-openai,
python-tests-misc-integration,
python-tests-functions,
python-tests-foundry,
python-tests-foundry-hosting,
python-tests-cosmos,
python-tests-github-copilot,
]
runs-on: ubuntu-latest
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ inputs.checkout-ref }}
persist-credentials: false
- name: Set up python and install the project
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Download all test results from current run
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
with:
pattern: test-results-*
path: test-results/
- name: Restore report history cache
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: python/integration-report-history.json
key: integration-report-history-integration-${{ github.run_id }}
restore-keys: |
integration-report-history-integration-
- name: Generate trend report
run: >
uv run python scripts/integration_test_report/aggregate.py
../test-results/
integration-report-history.json
integration-test-report.md
- name: Post to Job Summary
if: always()
run: cat integration-test-report.md >> $GITHUB_STEP_SUMMARY
- name: Save report history cache
if: always()
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: python/integration-report-history.json
key: integration-report-history-integration-${{ github.run_id }}
- name: Upload unified trend report
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: integration-test-report
path: |
python/integration-test-report.md
python/integration-report-history.json
python-integration-tests-check:
if: always()
runs-on: ubuntu-latest
needs:
[
python-tests-unit,
python-tests-openai,
python-tests-azure-openai,
python-tests-misc-integration,
python-tests-functions,
python-tests-foundry,
python-tests-foundry-hosting,
python-tests-cosmos,
python-tests-github-copilot
]
steps:
- name: Fail workflow if tests failed
if: contains(join(needs.*.result, ','), 'failure')
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
script: core.setFailed('Integration Tests Failed!')
- name: Fail workflow if tests cancelled
if: contains(join(needs.*.result, ','), 'cancelled')
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
script: core.setFailed('Integration Tests Cancelled!')
+104
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@@ -0,0 +1,104 @@
name: Python - Lab Tests
on:
workflow_dispatch:
pull_request:
branches: ["main"]
paths:
- "python/packages/lab/**"
merge_group:
branches: ["main"]
schedule:
- cron: "0 0 * * *" # Run at midnight UTC daily
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
jobs:
paths-filter:
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: read
outputs:
pythonChanges: ${{ steps.filter.outputs.python}}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- uses: dorny/paths-filter@fbd0ab8f3e69293af611ebaee6363fc25e6d187d # v4.0.1
id: filter
with:
filters: |
python:
- 'python/**'
- '!python/AGENTS.md'
- '!python/**/AGENTS.md'
- '!python/.github/skills/*'
- '!python/.github/skills/**'
# run only if 'python' files were changed
- name: python tests
if: steps.filter.outputs.python == 'true'
run: echo "Python file"
# run only if not 'python' files were changed
- name: not python tests
if: steps.filter.outputs.python != 'true'
run: echo "NOT python file"
python-lab-tests:
name: Python Lab Tests
needs: paths-filter
if: needs.paths-filter.outputs.pythonChanges == 'true'
runs-on: ${{ matrix.os }}
strategy:
fail-fast: true
matrix:
python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
# TODO(ekzhu): re-enable macos-latest when this is fixed: https://github.com/actions/runner-images/issues/11881
os: [ubuntu-latest, windows-latest]
env:
UV_PYTHON: ${{ matrix.python-version }}
permissions:
contents: read
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
exclude-packages: ${{ matrix.python-version == '3.10' && 'agent-framework-github-copilot' || '' }}
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
# Lab specific tests
- name: Run lab tests
run: cd packages/lab && uv run poe test
- name: Run resource-intensive lab tests
run: cd packages/lab && uv run pytest -m "resource_intensive and not integration" --junitxml=test-results-resource-intensive.xml
- name: Run lab lint
run: cd packages/lab && uv run poe lint
- name: Run lab format check
run: cd packages/lab && uv run poe fmt --check
- name: Run lab type checking
run: cd packages/lab && uv run poe pyright
# Surface failing tests
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/packages/lab/**.xml
summary: true
display-options: fEX
fail-on-empty: false
title: Lab Test Results
+809
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@@ -0,0 +1,809 @@
name: Python - Merge - Tests
#
# NOTE: This workflow and python-integration-tests.yml share the same set of
# parallel test jobs. Keep them in sync — when adding, removing, or modifying a
# job here, apply the same change to python-integration-tests.yml.
#
on:
workflow_dispatch:
pull_request:
branches: ["main"]
merge_group:
branches: ["main"]
schedule:
- cron: "0 0 * * *" # Run at midnight UTC daily
permissions:
contents: read
id-token: write
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
UV_PYTHON: "3.13"
RUN_SAMPLES_TESTS: ${{ vars.RUN_SAMPLES_TESTS }}
jobs:
paths-filter:
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: read
outputs:
pythonChanges: ${{ steps.filter.outputs.python }}
coreChanged: ${{ steps.filter.outputs.core }}
openaiChanged: ${{ steps.filter.outputs.openai }}
azureChanged: ${{ steps.filter.outputs.azure }}
miscChanged: ${{ steps.filter.outputs.misc }}
functionsChanged: ${{ steps.filter.outputs.functions }}
foundryChanged: ${{ steps.filter.outputs.foundry }}
foundryHostingChanged: ${{ steps.filter.outputs.foundry_hosting }}
cosmosChanged: ${{ steps.filter.outputs.cosmos }}
githubCopilotChanged: ${{ steps.filter.outputs.github_copilot }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- uses: dorny/paths-filter@fbd0ab8f3e69293af611ebaee6363fc25e6d187d # v4.0.1
id: filter
with:
filters: |
python:
- 'python/**'
- '.github/actions/setup-local-mcp-server/**'
- '.github/workflows/python-merge-tests.yml'
- '.github/workflows/python-integration-tests.yml'
core:
- 'python/packages/core/agent_framework/_*.py'
- 'python/packages/core/agent_framework/_workflows/**'
- 'python/packages/core/agent_framework/exceptions.py'
- 'python/packages/core/agent_framework/observability.py'
openai:
- 'python/packages/core/agent_framework/openai/**'
- 'python/packages/openai/**'
- 'python/samples/**/providers/openai/**'
azure:
- 'python/packages/openai/**'
- 'python/packages/core/agent_framework/azure/**'
- 'python/samples/**/providers/azure/**'
misc:
- 'python/packages/anthropic/**'
- 'python/packages/hyperlight/**'
- 'python/packages/ollama/**'
- 'python/packages/core/agent_framework/_mcp.py'
- 'python/packages/core/tests/core/test_mcp.py'
- 'python/scripts/local_mcp_streamable_http_server.py'
- '.github/actions/setup-local-mcp-server/**'
- '.github/workflows/python-merge-tests.yml'
- '.github/workflows/python-integration-tests.yml'
functions:
- 'python/packages/azurefunctions/**'
- 'python/packages/durabletask/**'
foundry:
- 'python/packages/foundry/**'
- 'python/samples/**/providers/foundry/**'
- 'python/samples/02-agents/embeddings/foundry_embeddings.py'
foundry_hosting:
- 'python/packages/foundry_hosting/**'
cosmos:
- 'python/packages/azure-cosmos/**'
github_copilot:
- 'python/packages/github_copilot/**'
# run only if 'python' files were changed
- name: python tests
if: steps.filter.outputs.python == 'true'
run: echo "Python file"
# run only if not 'python' files were changed
- name: not python tests
if: steps.filter.outputs.python != 'true'
run: echo "NOT python file"
# Unit tests: always run all non-integration tests across all packages
python-tests-unit:
name: Python Tests - Unit
needs: paths-filter
if: >
github.event_name != 'pull_request' &&
needs.paths-filter.outputs.pythonChanges == 'true'
runs-on: ubuntu-latest
environment: integration
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Test with pytest (unit tests only)
run: >
uv run poe test -A
-m "not integration"
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
working-directory: ./python
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/pytest.xml
summary: true
display-options: fEX
fail-on-empty: false
title: Unit test results
# OpenAI integration tests
python-tests-openai:
name: Python Tests - OpenAI Integration
needs: paths-filter
if: >
github.event_name != 'pull_request' &&
needs.paths-filter.outputs.pythonChanges == 'true' &&
(github.event_name != 'merge_group' ||
needs.paths-filter.outputs.openaiChanged == 'true' ||
needs.paths-filter.outputs.coreChanged == 'true')
runs-on: ubuntu-latest
environment: integration
env:
OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Test with pytest (OpenAI integration)
run: >
uv run pytest --import-mode=importlib
packages/openai/tests
-m "integration and not azure"
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
working-directory: ./python
- name: Test OpenAI samples
timeout-minutes: 10
if: env.RUN_SAMPLES_TESTS == 'true'
run: uv run pytest tests/samples/ -m "openai"
working-directory: ./python
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/pytest.xml
summary: true
display-options: fEX
fail-on-empty: false
title: OpenAI integration test results
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-openai
path: ./python/pytest.xml
if-no-files-found: ignore
# Azure OpenAI integration tests
python-tests-azure-openai:
name: Python Tests - Azure OpenAI Integration
needs: paths-filter
if: >
github.event_name != 'pull_request' &&
needs.paths-filter.outputs.pythonChanges == 'true' &&
(github.event_name != 'merge_group' ||
needs.paths-filter.outputs.azureChanged == 'true' ||
needs.paths-filter.outputs.coreChanged == 'true')
runs-on: ubuntu-latest
environment: integration
env:
AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_EMBEDDING_MODEL: ${{ vars.AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Azure CLI Login
if: github.event_name != 'pull_request'
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Test with pytest (Azure OpenAI integration)
run: >
uv run pytest --import-mode=importlib
packages/openai/tests/openai/test_openai_chat_completion_client_azure.py
packages/openai/tests/openai/test_openai_chat_client_azure.py
packages/openai/tests/openai/test_openai_embedding_client_azure.py
-m integration
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
working-directory: ./python
- name: Test Azure samples
timeout-minutes: 10
if: env.RUN_SAMPLES_TESTS == 'true'
run: uv run pytest tests/samples/ -m "azure"
working-directory: ./python
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/pytest.xml
summary: true
display-options: fEX
fail-on-empty: false
title: Azure OpenAI integration test results
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-azure-openai
path: ./python/pytest.xml
if-no-files-found: ignore
# Misc integration tests (Anthropic, Ollama, MCP)
python-tests-misc-integration:
name: Python Tests - Misc Integration
needs: paths-filter
if: >
github.event_name != 'pull_request' &&
needs.paths-filter.outputs.pythonChanges == 'true' &&
(github.event_name != 'merge_group' ||
needs.paths-filter.outputs.miscChanged == 'true' ||
needs.paths-filter.outputs.coreChanged == 'true')
runs-on: ubuntu-latest
environment: integration
env:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_CHAT_MODEL: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
OLLAMA_MODEL: qwen2.5:1.5b
OLLAMA_EMBEDDING_MODEL: nomic-embed-text
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Install Ollama
run: curl -fsSL https://ollama.com/install.sh | sh
working-directory: .
- name: Cache Ollama models
uses: actions/cache@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: ~/.ollama/models
key: ollama-models-qwen2.5-1.5b-nomic-embed-text-v1
- name: Start Ollama and pull models
run: |
# Stop any Ollama instance auto-started by the install script
pkill ollama || true
sleep 2
ollama serve &
for i in $(seq 1 30); do
if curl -sf http://localhost:11434/api/tags > /dev/null 2>&1; then
break
fi
sleep 1
done
# Pull models with retry for transient 429 rate limits
for model in qwen2.5:1.5b nomic-embed-text; do
pulled=false
for attempt in 1 2 3; do
if ollama pull "$model"; then
pulled=true
break
fi
echo "Retry $attempt for $model (waiting 15s)..."
sleep 15
done
if [ "$pulled" != "true" ]; then
echo "ERROR: Failed to pull $model after 3 attempts"
exit 1
fi
done
working-directory: .
- name: Start local MCP server
id: local-mcp
uses: ./.github/actions/setup-local-mcp-server
with:
fallback_url: ${{ env.LOCAL_MCP_URL }}
- name: Prefer local MCP URL when available
run: echo "LOCAL_MCP_URL=${{ steps.local-mcp.outputs.effective_url }}" >> "$GITHUB_ENV"
- name: Test with pytest (Anthropic, Hyperlight, Ollama, MCP integration)
run: >
uv run pytest --import-mode=importlib
packages/anthropic/tests
packages/hyperlight/tests
packages/ollama/tests
packages/core/tests/core/test_mcp.py
-m integration
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 30
--junitxml=pytest.xml
working-directory: ./python
- name: Stop local MCP server
if: always()
shell: bash
run: |
set -euo pipefail
server_pid="${{ steps.local-mcp.outputs.pid }}"
if [[ -z "$server_pid" ]]; then
exit 0
fi
if ! kill -0 "$server_pid" 2>/dev/null; then
exit 0
fi
kill -TERM -- "-$server_pid" 2>/dev/null || kill -TERM "$server_pid" 2>/dev/null || true
for _ in $(seq 1 10); do
if ! kill -0 "$server_pid" 2>/dev/null; then
exit 0
fi
sleep 1
done
kill -KILL -- "-$server_pid" 2>/dev/null || kill -KILL "$server_pid" 2>/dev/null || true
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/pytest.xml
summary: true
display-options: fEX
fail-on-empty: false
title: Misc integration test results
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-misc
path: ./python/pytest.xml
if-no-files-found: ignore
# Azure Functions + Durable Task integration tests
python-tests-functions:
name: Python Tests - Functions Integration
needs: paths-filter
if: >
github.event_name != 'pull_request' &&
needs.paths-filter.outputs.pythonChanges == 'true' &&
(github.event_name != 'merge_group' ||
needs.paths-filter.outputs.functionsChanged == 'true' ||
needs.paths-filter.outputs.coreChanged == 'true')
runs-on: ubuntu-latest
environment: integration
env:
UV_PYTHON: "3.11"
OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
AZURE_OPENAI_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
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
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Azure CLI Login
if: github.event_name != 'pull_request'
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
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 (Functions + Durable Task integration)
run: >
uv run pytest --import-mode=importlib
packages/azurefunctions/tests/integration_tests
packages/durabletask/tests/integration_tests
-m integration
-n logical --dist worksteal
-x
--timeout=480 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
working-directory: ./python
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/pytest.xml
summary: true
display-options: fEX
fail-on-empty: false
title: Functions integration test results
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-functions
path: ./python/pytest.xml
if-no-files-found: ignore
python-tests-foundry:
name: Python Integration Tests - Foundry
needs: paths-filter
if: >
github.event_name != 'pull_request' &&
needs.paths-filter.outputs.pythonChanges == 'true' &&
(github.event_name != 'merge_group' ||
needs.paths-filter.outputs.foundryChanged == 'true' ||
needs.paths-filter.outputs.coreChanged == 'true')
runs-on: ubuntu-latest
environment: integration
env:
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
FOUNDRY_AGENT_NAME: ${{ vars.FOUNDRY_AGENT_NAME }}
FOUNDRY_AGENT_VERSION: ${{ vars.FOUNDRY_AGENT_VERSION }}
FOUNDRY_MODELS_ENDPOINT: ${{ vars.FOUNDRY_MODELS_ENDPOINT || '' }}
FOUNDRY_MODELS_API_KEY: ${{ secrets.FOUNDRY_MODELS_API_KEY || '' }}
FOUNDRY_EMBEDDING_MODEL: ${{ vars.FOUNDRY_EMBEDDING_MODEL || '' }}
FOUNDRY_IMAGE_EMBEDDING_MODEL: ${{ vars.FOUNDRY_IMAGE_EMBEDDING_MODEL || '' }}
LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Azure CLI Login
if: github.event_name != 'pull_request'
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Test with pytest
timeout-minutes: 15
run: >
uv run pytest --import-mode=importlib
packages/foundry/tests
-m integration
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
working-directory: ./python
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/pytest.xml
summary: true
display-options: fEX
fail-on-empty: false
title: Test results
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-foundry
path: ./python/pytest.xml
if-no-files-found: ignore
# Foundry Hosting integration tests
python-tests-foundry-hosting:
name: Python Tests - Foundry Hosting Integration
needs: paths-filter
if: >
github.event_name != 'pull_request' &&
needs.paths-filter.outputs.pythonChanges == 'true' &&
(github.event_name != 'merge_group' ||
needs.paths-filter.outputs.foundryHostingChanged == 'true' ||
needs.paths-filter.outputs.coreChanged == 'true')
runs-on: ubuntu-latest
environment: integration
env:
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Azure CLI Login
if: github.event_name != 'pull_request'
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
- name: Test with pytest (Foundry Hosting integration)
timeout-minutes: 15
run: >
uv run pytest --import-mode=importlib
packages/foundry_hosting/tests
-m integration
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
working-directory: ./python
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/pytest.xml
summary: true
display-options: fEX
fail-on-empty: false
title: Foundry Hosting integration test results
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-foundry-hosting
path: ./python/pytest.xml
if-no-files-found: ignore
# TODO: Add python-tests-lab
# Azure Cosmos integration tests
python-tests-cosmos:
name: Python Tests - Cosmos Integration
needs: paths-filter
if: >
github.event_name != 'pull_request' &&
needs.paths-filter.outputs.pythonChanges == 'true' &&
(github.event_name != 'merge_group' ||
needs.paths-filter.outputs.cosmosChanged == 'true' ||
needs.paths-filter.outputs.coreChanged == 'true')
runs-on: ubuntu-latest
environment: integration
services:
cosmosdb:
image: mcr.microsoft.com/cosmosdb/linux/azure-cosmos-emulator:vnext-preview
ports:
- 8081:8081
env:
AZURE_COSMOS_ENDPOINT: "http://localhost:8081/"
# Static Azure Cosmos DB emulator key (documented): https://learn.microsoft.com/en-us/azure/cosmos-db/emulator
AZURE_COSMOS_KEY: "C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw=="
AZURE_COSMOS_DATABASE_NAME: "agent-framework-cosmos-it-db"
AZURE_COSMOS_CONTAINER_NAME: "agent-framework-cosmos-it-container"
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Wait for Cosmos DB emulator
run: |
for i in {1..60}; do
if curl --silent --show-error http://localhost:8081/ > /dev/null; then
echo "Cosmos DB emulator is ready."
exit 0
fi
sleep 2
done
echo "Cosmos DB emulator did not become ready in time." >&2
exit 1
- name: Test with pytest (Cosmos integration)
run: uv run --directory packages/azure-cosmos poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5 --junitxml=${{ github.workspace }}/python/pytest.xml
working-directory: ./python
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/pytest.xml
summary: true
display-options: fEX
fail-on-empty: false
title: Cosmos integration test results
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-cosmos
path: ./python/pytest.xml
if-no-files-found: ignore
# GitHub Copilot integration tests
python-tests-github-copilot:
name: Python Tests - GitHub Copilot Integration
needs: paths-filter
if: >
github.event_name != 'pull_request' &&
needs.paths-filter.outputs.pythonChanges == 'true' &&
(github.event_name != 'merge_group' ||
needs.paths-filter.outputs.githubCopilotChanged == 'true' ||
needs.paths-filter.outputs.coreChanged == 'true')
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
env:
COPILOT_GITHUB_TOKEN: ${{ secrets.COPILOT_GITHUB_TOKEN }}
GITHUB_COPILOT_TIMEOUT: "120"
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Test with pytest (GitHub Copilot integration)
run: >
uv run pytest --import-mode=importlib
packages/github_copilot/tests
-m integration
--timeout=120 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/pytest.xml
summary: true
display-options: fEX
fail-on-empty: false
title: GitHub Copilot integration test results
- name: Upload test results
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: test-results-github-copilot
path: ./python/pytest.xml
if-no-files-found: ignore
# Integration test trend report (aggregates per-job JUnit XML results)
python-integration-test-report:
name: Integration Test Report
if: >
always() &&
(contains(join(needs.*.result, ','), 'success') ||
contains(join(needs.*.result, ','), 'failure'))
needs:
[
python-tests-openai,
python-tests-azure-openai,
python-tests-misc-integration,
python-tests-functions,
python-tests-foundry,
python-tests-foundry-hosting,
python-tests-cosmos,
python-tests-github-copilot,
]
runs-on: ubuntu-latest
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Download all test results from current run
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
with:
pattern: test-results-*
path: test-results/
- name: Restore report history cache
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: python/integration-report-history.json
key: integration-report-history-merge-${{ github.run_id }}
restore-keys: |
integration-report-history-merge-
- name: Generate trend report
run: >
uv run python scripts/integration_test_report/aggregate.py
../test-results/
integration-report-history.json
integration-test-report.md
- name: Post to Job Summary
if: always()
run: cat integration-test-report.md >> $GITHUB_STEP_SUMMARY
- name: Save report history cache
if: always()
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: python/integration-report-history.json
key: integration-report-history-merge-${{ github.run_id }}
- name: Upload unified trend report
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
name: integration-test-report
path: |
python/integration-test-report.md
python/integration-report-history.json
python-integration-tests-check:
if: always()
runs-on: ubuntu-latest
needs:
[
python-tests-unit,
python-tests-openai,
python-tests-azure-openai,
python-tests-misc-integration,
python-tests-functions,
python-tests-foundry,
python-tests-foundry-hosting,
python-tests-cosmos,
python-tests-github-copilot,
]
steps:
- name: Fail workflow if tests failed
id: check_tests_failed
if: contains(join(needs.*.result, ','), 'failure')
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
script: core.setFailed('Integration Tests Failed!')
- name: Fail workflow if tests cancelled
id: check_tests_cancelled
if: contains(join(needs.*.result, ','), 'cancelled')
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
script: core.setFailed('Integration Tests Cancelled!')
+62
View File
@@ -0,0 +1,62 @@
name: Python - Build Release Assets
on:
release:
types: [published]
permissions:
contents: write
id-token: write
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
jobs:
python-build-assets:
if: github.event_name == 'release' && startsWith(github.event.release.tag_name, 'python-')
name: Python Build Assets and add to Release
runs-on: ubuntu-latest
environment: "integration"
env:
UV_PYTHON: "3.13"
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
- name: Set environment variables
run: |
# Extract package name from tag (format: python-<package>-<version>)
TAG="${{ github.event.release.tag_name }}"
PACKAGE=$(echo "$TAG" | sed 's/^python-\([^-]*\)-.*$/\1/')
# Validate package exists
if [[ ! -d "packages/$PACKAGE" ]]; then
echo "Error: Package '$PACKAGE' not found in packages/ directory"
echo "Available packages: $(ls packages/)"
exit 1
fi
echo "PACKAGE=$PACKAGE" >> $GITHUB_ENV
echo "Building package: $PACKAGE"
- name: Check version
run: |
echo "Building and uploading Python package version: ${{ github.event.release.tag_name }}"
echo "Package directory: packages/${{ env.PACKAGE }}"
- name: Build the package
run: uv run poe --directory packages/${{ env.PACKAGE }} build
- name: Release
uses: softprops/action-gh-release@3bb12739c298aeb8a4eeaf626c5b8d85266b0e65 # v2
with:
files: |
python/dist/*
@@ -0,0 +1,732 @@
name: Python - Sample Validation
on:
workflow_dispatch:
schedule:
- cron: "0 0 * * *" # Run at midnight UTC daily
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
# GitHub Copilot configuration
GITHUB_COPILOT_MODEL: claude-opus-4.6
COPILOT_GITHUB_TOKEN: ${{ secrets.COPILOT_GITHUB_TOKEN }}
permissions:
contents: read
id-token: write
jobs:
validate-01-get-started:
name: Validate 01-get-started
runs-on: ubuntu-latest
environment: integration
env:
# Required configuration for get-started samples
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT || vars.AZURE_AI_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Create .env for samples
run: |
echo "FOUNDRY_PROJECT_ENDPOINT=$FOUNDRY_PROJECT_ENDPOINT" >> .env
echo "FOUNDRY_MODEL=$FOUNDRY_MODEL" >> .env
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 01-get-started --save-report --report-name 01-get-started
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-01-get-started
path: python/samples/sample_validation/reports/
validate-02-agents:
name: Validate 02-agents
runs-on: ubuntu-latest
environment: integration
env:
# Foundry configuration
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT || vars.AZURE_AI_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
# Azure OpenAI configuration
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
AZURE_OPENAI_MODEL: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
AZURE_OPENAI_CHAT_MODEL: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_EMBEDDING_MODEL: ${{ vars.AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME || vars.AZUREOPENAI__EMBEDDINGDEPLOYMENTNAME }}
# OpenAI configuration
OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
# GitHub MCP
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
# Observability
ENABLE_INSTRUMENTATION: "true"
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Create .env for samples
run: |
echo "FOUNDRY_PROJECT_ENDPOINT=$FOUNDRY_PROJECT_ENDPOINT" >> .env
echo "FOUNDRY_MODEL=$FOUNDRY_MODEL" >> .env
echo "AZURE_OPENAI_ENDPOINT=$AZURE_OPENAI_ENDPOINT" >> .env
echo "AZURE_OPENAI_MODEL=$AZURE_OPENAI_MODEL" >> .env
echo "AZURE_OPENAI_CHAT_COMPLETION_MODEL=$AZURE_OPENAI_CHAT_COMPLETION_MODEL" >> .env
echo "AZURE_OPENAI_CHAT_MODEL=$AZURE_OPENAI_CHAT_MODEL" >> .env
echo "AZURE_OPENAI_EMBEDDING_MODEL=$AZURE_OPENAI_EMBEDDING_MODEL" >> .env
echo "OPENAI_API_KEY=$OPENAI_API_KEY" >> .env
echo "OPENAI_CHAT_COMPLETION_MODEL=$OPENAI_CHAT_COMPLETION_MODEL" >> .env
echo "OPENAI_CHAT_MODEL=$OPENAI_CHAT_MODEL" >> .env
echo "GITHUB_PAT=$GITHUB_PAT" >> .env
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 02-agents --exclude providers --save-report --report-name 02-agents
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-02-agents
path: python/samples/sample_validation/reports/
validate-02-agents-openai:
name: Validate 02-agents/providers/openai
runs-on: ubuntu-latest
environment: integration
env:
OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
OPENAI_MODEL: ${{ vars.OPENAI__CHATMODELID }}
OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Create .env for samples
run: |
echo "OPENAI_API_KEY=$OPENAI_API_KEY" >> .env
echo "OPENAI_MODEL=$OPENAI_MODEL" >> .env
echo "OPENAI_CHAT_COMPLETION_MODEL=$OPENAI_CHAT_COMPLETION_MODEL" >> .env
echo "OPENAI_CHAT_MODEL=$OPENAI_CHAT_MODEL" >> .env
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 02-agents/providers/openai --save-report --report-name 02-agents-openai
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-02-agents-openai
path: python/samples/sample_validation/reports/
validate-02-agents-azure:
name: Validate 02-agents/providers/azure
runs-on: ubuntu-latest
environment: integration
env:
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
AZURE_OPENAI_MODEL: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
AZURE_OPENAI_API_VERSION: ${{ vars.AZURE_OPENAI_API_VERSION || '' }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Create .env for samples
run: |
echo "AZURE_OPENAI_ENDPOINT=$AZURE_OPENAI_ENDPOINT" >> .env
echo "AZURE_OPENAI_MODEL=$AZURE_OPENAI_MODEL" >> .env
echo "AZURE_OPENAI_API_VERSION=$AZURE_OPENAI_API_VERSION" >> .env
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 02-agents/providers/azure --save-report --report-name 02-agents-azure
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-02-agents-azure
path: python/samples/sample_validation/reports/
validate-02-agents-anthropic:
name: Validate 02-agents/providers/anthropic
runs-on: ubuntu-latest
environment: integration
env:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_CHAT_MODEL: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Create .env for samples
run: |
echo "ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY" >> .env
echo "ANTHROPIC_CHAT_MODEL=$ANTHROPIC_CHAT_MODEL" >> .env
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 02-agents/providers/anthropic --save-report --report-name 02-agents-anthropic
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-02-agents-anthropic
path: python/samples/sample_validation/reports/
validate-02-agents-github-copilot:
name: Validate 02-agents/providers/github_copilot
runs-on: ubuntu-latest
environment: integration
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 02-agents/providers/github_copilot --save-report --report-name 02-agents-github-copilot
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-02-agents-github-copilot
path: python/samples/sample_validation/reports/
validate-02-agents-amazon:
name: Validate 02-agents/providers/amazon
if: false # Temporarily disabled - requires AWS credentials
runs-on: ubuntu-latest
environment: integration
env:
BEDROCK_CHAT_MODEL: ${{ vars.BEDROCK__CHATMODELID }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 02-agents/providers/amazon --save-report --report-name 02-agents-amazon
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-02-agents-amazon
path: python/samples/sample_validation/reports/
validate-02-agents-ollama:
name: Validate 02-agents/providers/ollama
if: false # Temporarily disabled - requires local Ollama server
runs-on: ubuntu-latest
environment: integration
env:
OLLAMA_MODEL: ${{ vars.OLLAMA__MODEL }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 02-agents/providers/ollama --save-report --report-name 02-agents-ollama
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-02-agents-ollama
path: python/samples/sample_validation/reports/
validate-02-agents-foundry:
name: Validate 02-agents/providers/foundry
if: false # Temporarily disabled - provider folder also contains the local Foundry sample
runs-on: ubuntu-latest
environment: integration
env:
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT || vars.AZURE_AI_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
FOUNDRY_AGENT_NAME: ${{ vars.FOUNDRY_AGENT_NAME || '' }}
FOUNDRY_AGENT_VERSION: ${{ vars.FOUNDRY_AGENT_VERSION || '' }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Create .env for samples
run: |
echo "FOUNDRY_PROJECT_ENDPOINT=$FOUNDRY_PROJECT_ENDPOINT" >> .env
echo "FOUNDRY_MODEL=$FOUNDRY_MODEL" >> .env
echo "FOUNDRY_AGENT_NAME=$FOUNDRY_AGENT_NAME" >> .env
echo "FOUNDRY_AGENT_VERSION=$FOUNDRY_AGENT_VERSION" >> .env
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 02-agents/providers/foundry --save-report --report-name 02-agents-foundry
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-02-agents-foundry
path: python/samples/sample_validation/reports/
validate-02-agents-copilotstudio:
name: Validate 02-agents/providers/copilotstudio
if: false # Temporarily disabled - requires Copilot Studio setup
runs-on: ubuntu-latest
environment: integration
env:
COPILOTSTUDIOAGENT__ENVIRONMENTID: ${{ secrets.COPILOTSTUDIOAGENT__ENVIRONMENTID }}
COPILOTSTUDIOAGENT__SCHEMANAME: ${{ secrets.COPILOTSTUDIOAGENT__SCHEMANAME }}
COPILOTSTUDIOAGENT__TENANTID: ${{ secrets.COPILOTSTUDIOAGENT__TENANTID }}
COPILOTSTUDIOAGENT__AGENTAPPID: ${{ secrets.COPILOTSTUDIOAGENT__AGENTAPPID }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Create .env for samples
run: |
echo "COPILOTSTUDIOAGENT__ENVIRONMENTID=$COPILOTSTUDIOAGENT__ENVIRONMENTID" >> .env
echo "COPILOTSTUDIOAGENT__SCHEMANAME=$COPILOTSTUDIOAGENT__SCHEMANAME" >> .env
echo "COPILOTSTUDIOAGENT__TENANTID=$COPILOTSTUDIOAGENT__TENANTID" >> .env
echo "COPILOTSTUDIOAGENT__AGENTAPPID=$COPILOTSTUDIOAGENT__AGENTAPPID" >> .env
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 02-agents/providers/copilotstudio --save-report --report-name 02-agents-copilotstudio
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-02-agents-copilotstudio
path: python/samples/sample_validation/reports/
validate-02-agents-custom:
name: Validate 02-agents/providers/custom
runs-on: ubuntu-latest
environment: integration
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 02-agents/providers/custom --save-report --report-name 02-agents-custom
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-02-agents-custom
path: python/samples/sample_validation/reports/
validate-03-workflows:
name: Validate 03-workflows
runs-on: ubuntu-latest
environment: integration
env:
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT || vars.AZURE_AI_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Create .env for samples
run: |
echo "FOUNDRY_PROJECT_ENDPOINT=$FOUNDRY_PROJECT_ENDPOINT" >> .env
echo "FOUNDRY_MODEL=$FOUNDRY_MODEL" >> .env
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 03-workflows --save-report --report-name 03-workflows
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-03-workflows
path: python/samples/sample_validation/reports/
validate-04-hosting:
name: Validate 04-hosting
if: false # Temporarily disabled because of sample complexity
runs-on: ubuntu-latest
environment: integration
env:
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT || vars.AZURE_AI_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
# A2A configuration
A2A_AGENT_HOST: http://localhost:5001/
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 04-hosting --save-report --report-name 04-hosting
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-04-hosting
path: python/samples/sample_validation/reports/
validate-05-end-to-end:
name: Validate 05-end-to-end
if: false # Temporarily disabled because of sample complexity
runs-on: ubuntu-latest
environment: integration
env:
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT || vars.AZURE_AI_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
# Azure OpenAI configuration
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
AZURE_OPENAI_MODEL: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
# Azure AI Search (for evaluation samples)
AZURE_SEARCH_ENDPOINT: ${{ secrets.AZURE_SEARCH_ENDPOINT }}
AZURE_SEARCH_API_KEY: ${{ secrets.AZURE_SEARCH_API_KEY }}
AZURE_SEARCH_INDEX_NAME: ${{ secrets.AZURE_SEARCH_INDEX_NAME }}
# Evaluation sample
FOUNDRY_MODEL_WORKFLOW: ${{ vars.FOUNDRY_MODEL_WORKFLOW || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
FOUNDRY_MODEL_EVAL: ${{ vars.FOUNDRY_MODEL_EVAL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir 05-end-to-end --save-report --report-name 05-end-to-end
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-05-end-to-end
path: python/samples/sample_validation/reports/
validate-autogen-migration:
name: Validate autogen-migration
runs-on: ubuntu-latest
environment: integration
env:
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT || vars.AZURE_AI_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
# Azure OpenAI configuration
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
AZURE_OPENAI_MODEL: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
# OpenAI configuration
OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Create .env for samples
run: |
echo "FOUNDRY_PROJECT_ENDPOINT=$FOUNDRY_PROJECT_ENDPOINT" >> .env
echo "FOUNDRY_MODEL=$FOUNDRY_MODEL" >> .env
echo "AZURE_OPENAI_ENDPOINT=$AZURE_OPENAI_ENDPOINT" >> .env
echo "AZURE_OPENAI_MODEL=$AZURE_OPENAI_MODEL" >> .env
echo "OPENAI_API_KEY=$OPENAI_API_KEY" >> .env
echo "OPENAI_CHAT_COMPLETION_MODEL=$OPENAI_CHAT_COMPLETION_MODEL" >> .env
echo "OPENAI_CHAT_MODEL=$OPENAI_CHAT_MODEL" >> .env
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir autogen-migration --save-report --report-name autogen-migration
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-autogen-migration
path: python/samples/sample_validation/reports/
validate-semantic-kernel-migration:
name: Validate semantic-kernel-migration
runs-on: ubuntu-latest
environment: integration
env:
FOUNDRY_PROJECT_ENDPOINT: ${{ vars.FOUNDRY_PROJECT_ENDPOINT || vars.AZURE_AI_PROJECT_ENDPOINT }}
FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
# Azure OpenAI configuration for AF
AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
AZURE_OPENAI_MODEL: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME || vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
# Azure OpenAI configuration for SK
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
# OpenAI key
OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
OPENAI_CHAT_COMPLETION_MODEL: ${{ vars.OPENAI__CHATMODELID }}
OPENAI_CHAT_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
# OpenAI configuration for SK
OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
# Copilot Studio
COPILOTSTUDIOAGENT__ENVIRONMENTID: ${{ secrets.COPILOTSTUDIOAGENT__ENVIRONMENTID }}
COPILOTSTUDIOAGENT__SCHEMANAME: ${{ secrets.COPILOTSTUDIOAGENT__SCHEMANAME }}
COPILOTSTUDIOAGENT__TENANTID: ${{ secrets.COPILOTSTUDIOAGENT__TENANTID }}
COPILOTSTUDIOAGENT__AGENTAPPID: ${{ secrets.COPILOTSTUDIOAGENT__AGENTAPPID }}
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Setup environment
uses: ./.github/actions/sample-validation-setup
with:
azure-client-id: ${{ secrets.AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
os: ${{ runner.os }}
- name: Create .env for samples
run: |
echo "FOUNDRY_PROJECT_ENDPOINT=$FOUNDRY_PROJECT_ENDPOINT" >> .env
echo "FOUNDRY_MODEL=$FOUNDRY_MODEL" >> .env
echo "AZURE_OPENAI_ENDPOINT=$AZURE_OPENAI_ENDPOINT" >> .env
echo "AZURE_OPENAI_MODEL=$AZURE_OPENAI_MODEL" >> .env
echo "OPENAI_API_KEY=$OPENAI_API_KEY" >> .env
echo "OPENAI_CHAT_COMPLETION_MODEL=$OPENAI_CHAT_COMPLETION_MODEL" >> .env
echo "OPENAI_CHAT_MODEL=$OPENAI_CHAT_MODEL" >> .env
echo "COPILOTSTUDIOAGENT__ENVIRONMENTID=$COPILOTSTUDIOAGENT__ENVIRONMENTID" >> .env
echo "COPILOTSTUDIOAGENT__SCHEMANAME=$COPILOTSTUDIOAGENT__SCHEMANAME" >> .env
echo "COPILOTSTUDIOAGENT__TENANTID=$COPILOTSTUDIOAGENT__TENANTID" >> .env
echo "COPILOTSTUDIOAGENT__AGENTAPPID=$COPILOTSTUDIOAGENT__AGENTAPPID" >> .env
- name: Run sample validation
run: |
cd scripts && uv run python -m sample_validation --subdir semantic-kernel-migration --save-report --report-name semantic-kernel-migration
- name: Upload validation report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-report-semantic-kernel-migration
path: python/samples/sample_validation/reports/
aggregate-results:
name: Aggregate Results
runs-on: ubuntu-latest
if: always()
needs:
- validate-01-get-started
- validate-02-agents
- validate-02-agents-openai
- validate-02-agents-azure
- validate-02-agents-anthropic
- validate-02-agents-github-copilot
- validate-02-agents-amazon
- validate-02-agents-ollama
- validate-02-agents-foundry
- validate-02-agents-copilotstudio
- validate-02-agents-custom
- validate-03-workflows
- validate-04-hosting
- validate-05-end-to-end
- validate-autogen-migration
- validate-semantic-kernel-migration
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Download all validation reports
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
with:
pattern: validation-report-*
path: reports/
merge-multiple: true
- name: Restore validation history
id: cache-restore
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: validation-history/
key: validation-history-${{ github.run_id }}
restore-keys: |
validation-history-
- name: Aggregate results and generate trend report
run: |
python3 python/scripts/sample_validation/aggregate.py \
reports/ \
validation-history/history.json \
trend-report.md
- name: Write trend report to job summary
run: cat trend-report.md >> "$GITHUB_STEP_SUMMARY"
- name: Save validation history
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: validation-history/
key: validation-history-${{ github.run_id }}
- name: Upload trend report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
if: always()
with:
name: validation-trend-report
path: trend-report.md
@@ -0,0 +1,70 @@
name: Python - Test Coverage Report
on:
workflow_run:
workflows: ["Python - Test Coverage"]
types:
- completed
permissions:
contents: read
actions: read
pull-requests: write
jobs:
python-test-coverage-report:
runs-on: ubuntu-latest
if: github.event.workflow_run.conclusion == 'success'
continue-on-error: false
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Download coverage report
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8
with:
github-token: ${{ github.token }}
run-id: ${{ github.event.workflow_run.id }}
path: ./python
merge-multiple: true
- name: Display structure of downloaded files
run: ls
- name: Read and validate PR number
# Keep the artifact handoff aligned with the workflow run that produced it.
env:
GH_TOKEN: ${{ github.token }}
REPO: ${{ github.repository }}
RUN_HEAD_SHA: ${{ github.event.workflow_run.head_sha }}
run: |
if [ ! -s pr_number ]; then
echo "PR number file 'pr_number' is missing or empty"
exit 1
fi
ARTIFACT_PR_NUMBER=$(cat pr_number)
if ! [[ "$ARTIFACT_PR_NUMBER" =~ ^[0-9]+$ ]]; then
echo "::error::PR number file contains invalid content"
exit 1
fi
PR_HEAD_SHA=$(gh pr view "$ARTIFACT_PR_NUMBER" --repo "$REPO" --json headRefOid --jq '.headRefOid')
if [ "$PR_HEAD_SHA" != "$RUN_HEAD_SHA" ]; then
echo "::error::PR head SHA does not match the triggering workflow run"
exit 1
fi
echo "PR_NUMBER=$ARTIFACT_PR_NUMBER" >> "$GITHUB_ENV"
- name: Pytest coverage comment
id: coverageComment
uses: MishaKav/pytest-coverage-comment@dd5b80bde6d16941f336518e92929e89069d8451 # v1.7.2
with:
github-token: ${{ github.token }}
issue-number: ${{ env.PR_NUMBER }}
pytest-xml-coverage-path: python/python-coverage.xml
title: "Python Test Coverage Report"
badge-title: "Python Test Coverage"
junitxml-title: "Python Unit Test Overview"
junitxml-path: python/pytest.xml
default-branch: "main"
report-only-changed-files: true
@@ -0,0 +1,53 @@
name: Python - Test Coverage
on:
pull_request:
branches: ["main", "feature*"]
paths:
- "python/packages/**"
- "python/tests/unit/**"
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
# Coverage threshold percentage for enforced modules
COVERAGE_THRESHOLD: 85
jobs:
python-tests-coverage:
runs-on: ubuntu-latest
continue-on-error: false
defaults:
run:
working-directory: python
env:
UV_PYTHON: "3.11"
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
# Save the PR number to a file since the workflow_run event
# in the coverage report workflow does not have access to it
- name: Save PR number
run: |
echo ${{ github.event.number }} > ./pr_number
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
- name: Run all tests with coverage report
run: uv run poe test -A -C --cov-report=xml:python-coverage.xml -q --junitxml=pytest.xml
- name: Check coverage threshold
run: python ${{ github.workspace }}/.github/workflows/python-check-coverage.py python-coverage.xml ${{ env.COVERAGE_THRESHOLD }}
- name: Upload coverage report
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
with:
path: |
python/python-coverage.xml
python/pytest.xml
python/pr_number
overwrite: true
retention-days: 1
if-no-files-found: error
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name: Python - Tests
on:
pull_request:
branches: ["main", "feature*"]
paths:
- "python/**"
- "!python/AGENTS.md"
- "!python/**/AGENTS.md"
- "!python/.github/skills/*"
- "!python/.github/skills/**"
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
jobs:
python-tests:
name: Python Tests
runs-on: ${{ matrix.os }}
strategy:
fail-fast: true
matrix:
python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
# todo: add macos-latest when problems are resolved
os: [ubuntu-latest, windows-latest]
env:
UV_PYTHON: ${{ matrix.python-version }}
permissions:
contents: write
defaults:
run:
working-directory: python
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up python and install the project
id: python-setup
uses: ./.github/actions/python-setup
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
exclude-packages: ${{ matrix.python-version == '3.10' && 'agent-framework-github-copilot' || '' }}
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
# Unit tests
- name: Run all tests
run: uv run poe test -A --junitxml=pytest.xml
working-directory: ./python
# Surface failing tests
- name: Surface failing tests
if: always()
uses: pmeier/pytest-results-action@20b595761ba9bf89e115e875f8bc863f913bc8ad # v0.7.2
with:
path: ./python/pytest.xml
summary: true
display-options: fEX
fail-on-empty: false
title: Test results
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@@ -0,0 +1,49 @@
name: Stale issue and PR ping
on:
schedule:
- cron: '0 0 * * *' # Midnight UTC daily
workflow_dispatch:
inputs:
days_threshold:
description: 'Days of silence before pinging the author'
required: false
default: '4'
dry_run:
description: 'Log what would be pinged without taking action'
required: false
default: 'false'
type: choice
options:
- 'false'
- 'true'
concurrency:
group: stale-issue-pr-ping
cancel-in-progress: true
jobs:
ping_stale:
name: "Ping stale issues and PRs"
runs-on: ubuntu-latest
permissions:
contents: read
issues: write
pull-requests: write
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5
with:
python-version: '3.13'
- name: Install dependencies
run: pip install PyGithub==2.6.0
- name: Run stale issue/PR ping
run: python .github/scripts/stale_issue_pr_ping.py
env:
GITHUB_TOKEN: ${{ secrets.GH_ACTIONS_PR_WRITE }}
TEAM_SLUG: ${{ secrets.DEVELOPER_TEAM }}
DAYS_THRESHOLD: ${{ github.event.inputs.days_threshold || '4' }}
DRY_RUN: ${{ github.event.inputs.dry_run || 'false' }}
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# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
!python/packages/devui/frontend/src/lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
TestResults/
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
pytest.xml
python-coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock
# UV
# Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
#uv.lock
# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock
# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
# .pdm.toml
# .pdm-python
# .pdm-build/
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
# Foundry agent CLI (contains secrets, auto-generated)
.foundry-agent.json
.foundry-agent-build.log
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# pytype static type analyzer
.pytype/
# Cython debug symbols
cython_debug/
# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
# Ruff stuff:
.ruff_cache/
# PyPI configuration file
.pypirc
**/.DS_Store
.DS_Store
# Visual Studio 2015/2017 cache/options directory
.vs/
**/.user/**
# Temporary files
*.~tmp
*.~bak
*.~swp
*.~swo
# Temporary directories
*tmp/
*temp/
*.tmp/
*.temp/
tmp*/
temp*/
.tmp/
.temp/
# AI
**/.checkpoints/
.claude/
.omc/
.omx/
WARP.md
**/memory-bank/
**/projectBrief.md
**/tmpclaude*
.kiro/
# Dependency-bound validation reports
python/scripts/dependency-*-results.json
python/scripts/dependencies/dependency-*-results.json
# 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__/
*/AzuriteConfig
# Azure Functions local settings
local.settings.json
# Frontend
**/frontend/node_modules/
**/frontend/.vite/
**/frontend/dist/
# Database files
*.db
python/dotnet-ref
# Generated filtered solution files (created by eng/scripts/New-FilteredSolution.ps1)
dotnet/filtered-*.slnx
**/*.lscache
# Local tool state
.omc/
.omx/
**/issues/
.test_*
+9
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# Microsoft Open Source Code of Conduct
This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
Resources:
- [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/)
- [Microsoft Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/)
- Contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with questions or concerns
+22
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# Welcome to the Agent Framework Community
Below are some ways that you can get involved in the Agent Framework Community.
## Engage on GitHub
- [Discussions](https://github.com/microsoft/agent-framework/discussions): Ask questions, provide feedback and ideas to what you'd like to see from the Agent Framework.
- [Issues](https://github.com/microsoft/agent-framework/issues) - If you find a bug, unexpected behavior or have a feature request, please open an issue.
- [Pull Requests](https://github.com/microsoft/agent-framework/pulls) - We welcome contributions! Please see our [Contributing Guide](https://github.com/microsoft/agent-framework/blob/main/CONTRIBUTING.md)
We do our best to respond to each submission.
## Public Community Office Hours
We regularly have Community Office Hours that are open to the **public** to join.
Add Agent Framework events to your calendar. We are running two community calls to accommodate different time zones for Q&A Office Hours:
- **Americas & EMEA timezone:** Every Wednesday at 8:00 AM Pacific Time/17:00 CET. Adjusted for daylight savings. Join here: [AF-AG-SK-Americas-Europe-OfficeHours](https://aka.ms/sk-officehours).
- **Asia Pacific timezone:** The second Wednesday of every month at 4:00 PM Pacific Time Wednesday. In much of Asia this occurs on Thursday local time. Adjusted for daylight savings. Join here: [AF-AG-SK-APAC-OfficeHours](https://aka.ms/sk-apac-officehours).
If you are unable to make it live, all meetings will be recorded and posted online.
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# Contributing to Agent Framework
You can contribute to Agent Framework with issues and pull requests (PRs). Simply
filing issues for problems you encounter is a great way to contribute. Contributing
code is greatly appreciated.
## Reporting Issues
We always welcome bug reports, API proposals and overall feedback. Here are a few
tips on how you can make reporting your issue as effective as possible.
### Where to Report
New issues can be reported in our [list of issues](https://github.com/microsoft/agent-framework/issues).
Before filing a new issue, please search the list of issues to make sure it does
not already exist.
If you do find an existing issue for what you wanted to report, please include
your own feedback in the discussion. Do consider upvoting (👍 reaction) the original
post, as this helps us prioritize popular issues in our backlog.
### Writing a Good Bug Report
Good bug reports make it easier for maintainers to verify and root cause the
underlying problem.
The better a bug report, the faster the problem will be resolved. Ideally, a bug
report should contain the following information:
- A high-level description of the problem.
- A _minimal reproduction_, i.e. the smallest size of code/configuration required
to reproduce the wrong behavior.
- A description of the _expected behavior_, contrasted with the _actual behavior_ observed.
- Information on the environment: OS/distribution, CPU architecture, SDK version, etc.
- Additional information, e.g. Is it a regression from previous versions? Are there
any known workarounds?
## Contributing Changes
Project maintainers will merge accepted code changes from contributors.
### DOs and DON'Ts
DO's:
- **DO** follow the standard coding conventions
- [.NET](https://learn.microsoft.com/dotnet/csharp/fundamentals/coding-style/coding-conventions)
- [Python](https://pypi.org/project/black/)
- **DO** give priority to the current style of the project or file you're changing
if it diverges from the general guidelines.
- **DO** use the pre-commit hooks for python to ensure proper formatting.
- **DO** include tests when adding new features. When fixing bugs, start with
adding a test that highlights how the current behavior is broken.
- **DO** keep the discussions focused. When a new or related topic comes up
it's often better to create new issue than to side track the discussion.
- **DO** clearly state on an issue that you are going to take on implementing it.
- **DO** blog and tweet (or whatever) about your contributions, frequently!
DON'Ts:
- **DON'T** surprise us with big pull requests. Instead, file an issue and start
a discussion so we can agree on a direction before you invest a large amount of time.
- **DON'T** commit code that you didn't write. If you find code that you think is a good
fit to add to Agent Framework, file an issue and start a discussion before proceeding.
- **DON'T** submit PRs that alter licensing related files or headers. If you believe
there's a problem with them, file an issue and we'll be happy to discuss it.
- **DON'T** make new APIs without filing an issue and discussing with us first.
### Breaking Changes
Contributions must maintain API signature and behavioral compatibility. Contributions
that include breaking changes will be rejected. Please file an issue to discuss
your idea or change if you believe that a breaking change is warranted.
#### Automated API Compatibility Validation
The .NET projects use [Package Validation](https://learn.microsoft.com/dotnet/fundamentals/package-validation/overview)
to automatically detect API breaking changes. This validation runs during `dotnet build`
(Release configuration) and `dotnet pack`, comparing the current API surface against the
latest published NuGet baseline version.
**What gets validated:** By default, packable RC packages (`IsReleaseCandidate=true`) and
GA packages (`IsGenerallyAvailable=true`) that have a published NuGet baseline and do not
override validation settings are automatically validated. The shared baseline version and
default validation settings are defined in `dotnet/nuget/nuget-package.props`, but
individual projects may opt out (for example by setting `EnablePackageValidation=false`).
**If the build fails with CP errors (e.g., CP0001, CP0002):**
1. **Unintentional breaking change** — Refactor your code to maintain backward compatibility.
2. **Intentional breaking change** (approved by maintainers) — Generate a suppression file:
```bash
dotnet build <project>.csproj -c Release /p:ApiCompatGenerateSuppressionFile=true
```
This creates or updates a `CompatibilitySuppressions.xml` in the project directory.
Include this file in your PR with justification for the breaking change.
**After each release:**
1. Delete all `CompatibilitySuppressions.xml` files from validated projects.
2. Update `PackageValidationBaselineVersion` in `dotnet/nuget/nuget-package.props` to the
newly published version.
For more details, see the [Package Validation diagnostic IDs](https://learn.microsoft.com/dotnet/fundamentals/package-validation/diagnostic-ids).
### Suggested Workflow
We use and recommend the following workflow:
1. Create an issue for your work.
- You can skip this step for trivial changes.
- Reuse an existing issue on the topic, if there is one.
- Get agreement from the team and the community that your proposed change is
a good one.
- Clearly state that you are going to take on implementing it, if that's the case.
You can request that the issue be assigned to you. Note: The issue filer and
the implementer don't have to be the same person.
2. Create a personal fork of the repository on GitHub (if you don't already have one).
3. In your fork, create a branch off of main (`git checkout -b mybranch`).
- Name the branch so that it clearly communicates your intentions, such as
"issue-123" or "githubhandle-issue".
4. Make and commit your changes to your branch.
5. Add new tests corresponding to your change, if applicable.
6. Run the relevant scripts in [the section below](#development-setup) to ensure that your build is clean and all tests are passing.
7. Create a PR against the repository's **main** branch.
- State in the description what issue or improvement your change is addressing.
- Verify that all the Continuous Integration checks are passing.
8. Wait for feedback or approval of your changes from the code maintainers.
9. When area owners have signed off, and all checks are green, your PR will be merged.
### Development Setup
Each language has its own dev setup guide, coding standards, and build scripts:
- **Python**: [Dev Setup](./python/DEV_SETUP.md) · [Coding Standard](./python/CODING_STANDARD.md) · [README](./python/README.md)
- From the `./python` directory:
- Build: `uv run poe build`
- Unit tests: `uv run poe test -A -m "not integration"`
- Integration tests: `uv run poe test -A -m integration` (requires API keys/endpoints)
- Format + lint: `uv run poe syntax`
- All checks: `uv run poe check`
- **.NET**: [README](./dotnet/README.md) · [Agent Instructions](./dotnet/AGENTS.md)
- From the `./dotnet` directory:
- Build: `dotnet build`
- Unit tests: `dotnet test --filter-query "/*UnitTests*/*/*/*"`
- Integration tests: `dotnet test --filter-query "/*IntegrationTests*/*/*/*"` (requires API keys/endpoints)
- Linting (auto-fix): `dotnet format`
### PR - CI Process
The continuous integration (CI) system will automatically perform the required
builds and run tests (including the ones you are expected to run) for PRs. Builds
and test runs must be clean.
If the CI build fails for any reason, the PR issue will be updated with a link
that can be used to determine the cause of the failure.
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MIT License
Copyright (c) Microsoft Corporation.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE
+213
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![Microsoft Agent Framework](docs/assets/readme-banner.png)
# Welcome to Microsoft Agent Framework!
[![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/b5zjErwbQM?style=flat)](https://discord.gg/b5zjErwbQM)
[![MS Learn Documentation](https://img.shields.io/badge/MS%20Learn-Documentation-blue)](https://learn.microsoft.com/en-us/agent-framework/)
[![PyPI](https://img.shields.io/pypi/v/agent-framework)](https://pypi.org/project/agent-framework/)
[![NuGet](https://img.shields.io/nuget/v/Microsoft.Agents.AI)](https://www.nuget.org/profiles/MicrosoftAgentFramework/)
[![GitHub stars](https://img.shields.io/github/stars/microsoft/agent-framework?style=social)](https://github.com/microsoft/agent-framework)
Microsoft Agent Framework (MAF) is an open, multi-language framework for building **production-grade AI agents and multi-agent workflows** in **.NET and Python**.
Microsoft Agent Framework is built for teams taking agents from prototype to production. It provides a consistent foundation for building, orchestrating, and operating agent systems across Python and .NET, while keeping architecture choices open as requirements evolve, and supports a broad ecosystem including Microsoft Foundry, Azure OpenAI, OpenAI, and the GitHub Copilot SDK, with samples and hosting patterns for both local development and cloud deployment.
<p align="center">
<a href="https://www.youtube.com/watch?v=AAgdMhftj8w" title="Watch the full Agent Framework introduction (30 min)">
<img src="https://img.youtube.com/vi/AAgdMhftj8w/hqdefault.jpg"
alt="Watch the full Agent Framework introduction (30 min)" width="480">
</a>
</p>
<p align="center">
<a href="https://www.youtube.com/watch?v=AAgdMhftj8w">
Watch the full Agent Framework introduction (30 min)
</a>
</p>
## Is this the right framework for you?
MAF is a strong fit if you:
- are building agents and workflows you expect to run in production,
- need orchestration beyond a single prompt or stateless chat loop,
- want graph-based patterns such as sequential, concurrent, handoff, and group collaboration,
- care about durability, restartability, observability, governance, or human-in-the-loop control,
- need provider flexibility so your architecture can evolve without major rewrites.
## Key Features
Explore new MAF capabilities and real implementation patterns on the [official blog](https://devblogs.microsoft.com/agent-framework/).
- **Python and C#/.NET Support**: Full framework support for both Python and C#/.NET implementations with consistent APIs
- [Python packages](./python/packages/) | [.NET source](./dotnet/src/)
- **Multiple Agent Provider Support**: Support for various LLM providers with more being added continuously
- [Python examples](./python/samples/02-agents/providers/) | [.NET examples](./dotnet/samples/02-agents/AgentProviders/)
- **Middleware**: Flexible middleware system for request/response processing, exception handling, and custom pipelines
- [Python middleware](./python/samples/02-agents/middleware/) | [.NET middleware](./dotnet/samples/02-agents/Agents/Agent_Step11_Middleware/)
- **Orchestration Patterns & Workflows**: Build multi-agent systems with graph-based workflows supporting sequential, concurrent, handoff, and group collaboration patterns; includes checkpointing, streaming, human-in-the-loop, and time-travel
- [Python workflows](./python/samples/03-workflows/) | [.NET workflows](./dotnet/samples/03-workflows/)
- **Foundry Hosted Agents (new)**: Deploy and host your agents to Foundry-hosted infrastructure with just 2 additional lines of code
- [Python samples](./python/samples/04-hosting/foundry-hosted-agents/) | [.NET samples](./dotnet/samples/04-hosting/FoundryHostedAgents/)
- **Observability**: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging
- [Python observability](./python/samples/02-agents/observability/) | [.NET telemetry](./dotnet/samples/02-agents/AgentOpenTelemetry/)
- **Declarative Agents**: Define agents using YAML for faster setup and versioning
- [Declarative agent samples](./declarative-agents/)
- **Agent Skills**: Build domain-specific knowledge bases from multiple sources—files, inline code, class libraries—for agents to discover and use
- [Skills design](./docs/decisions/0021-agent-skills-design.md)
- **AF Labs**: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
- [Labs directory](./python/packages/lab/)
- **DevUI**: Interactive developer UI for agent development, testing, and debugging workflows
- [See the DevUI in action](https://www.youtube.com/watch?v=mOAaGY4WPvc)
## Table of Contents
- [Getting Started](#getting-started)
- [Installation](#installation)
- [Learning Resources](#learning-resources)
- [Quickstart](#quickstart)
- [Basic Agent - Python](#basic-agent---python)
- [Basic Agent - .NET](#basic-agent---net)
- [More Examples & Samples](#more-examples--samples)
- [Community & Feedback](#community--feedback)
- [Troubleshooting](#troubleshooting)
- [Contributor Resources](#contributor-resources)
## Getting Started
### Installation
Python
```bash
pip install agent-framework
# This will install all sub-packages, see `python/packages` for individual packages.
# It may take a minute on first install on Windows.
```
.NET
```bash
dotnet add package Microsoft.Agents.AI
# For Foundry integration (used in the .NET quickstart below):
dotnet add package Microsoft.Agents.AI.Foundry
dotnet add package Azure.AI.Projects
dotnet add package Azure.Identity
```
### Learning Resources
- **[Overview](https://learn.microsoft.com/agent-framework/overview/agent-framework-overview)** - High level overview of the framework
- **[Quick Start](https://learn.microsoft.com/agent-framework/tutorials/quick-start)** - Get started with a simple agent
- **[Tutorials](https://learn.microsoft.com/agent-framework/tutorials/overview)** - Step by step tutorials
- **[User Guide](https://learn.microsoft.com/en-us/agent-framework/user-guide/overview)** - In-depth user guide for building agents and workflows
- **[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
### Quickstart
#### Basic Agent - Python
Create a simple Azure Responses Agent that writes a haiku about the Microsoft Agent Framework
```python
# pip install agent-framework
# Use `az login` to authenticate with Azure CLI
import os
import asyncio
from agent_framework import Agent
from agent_framework.foundry import FoundryChatClient
from azure.identity import AzureCliCredential
async def main():
# Initialize a chat agent with Microsoft Foundry
# the endpoint, deployment name, and api version can be set via environment variables
# or they can be passed in directly to the FoundryChatClient constructor
agent = Agent(
client=FoundryChatClient(
credential=AzureCliCredential(),
# project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
# model=os.environ["FOUNDRY_MODEL_DEPLOYMENT_NAME"],
),
name="HaikuAgent",
instructions="You are an upbeat assistant that writes beautifully.",
)
print(await agent.run("Write a haiku about Microsoft Agent Framework."))
if __name__ == "__main__":
asyncio.run(main())
```
#### Basic Agent - .NET
Create a simple Agent, using Microsoft Foundry that writes a haiku about the Microsoft Agent Framework
```c#
// This sample shows how to create and run a basic agent with AIProjectClient.AsAIAgent(...).
using Azure.AI.Projects;
using Azure.Identity;
using Microsoft.Agents.AI;
string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
AIAgent agent =
new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
.AsAIAgent(model: deploymentName, instructions: "You are an upbeat assistant that writes beautifully.", name: "HaikuAgent");
// Once you have the agent, you can invoke it like any other AIAgent.
Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
```
## More Examples & Samples
### Python
- [Getting Started](./python/samples/01-get-started): progressive tutorial from hello-world to hosting
- [Agent Concepts](./python/samples/02-agents): deep-dive samples by topic (tools, middleware, providers, etc.)
- [Workflows](./python/samples/03-workflows): workflow creation and integration with agents
- [Hosting](./python/samples/04-hosting): A2A, Azure Functions, Durable Task hosting
- [End-to-End](./python/samples/05-end-to-end): full applications, evaluation, and demos
### .NET
- [Getting Started](./dotnet/samples/01-get-started): progressive tutorial from hello agent to hosting
- [Agent Concepts](./dotnet/samples/02-agents/Agents): basic agent creation and tool usage
- [Agent Providers](./dotnet/samples/02-agents/AgentProviders): samples showing different agent providers
- [Workflows](./dotnet/samples/03-workflows): advanced multi-agent patterns and workflow orchestration
- [Hosting](./dotnet/samples/04-hosting): A2A, Durable Agents, Durable Workflows
- [End-to-End](./dotnet/samples/05-end-to-end): full applications and demos
## Community & Feedback
- **Found a bug?** File a [GitHub issue](https://github.com/microsoft/agent-framework/issues) to help us improve.
- **Enjoying MAF?** [![GitHub stars](https://img.shields.io/badge/Star-us%20on%20GitHub-yellow)](https://github.com/microsoft/agent-framework) to show your support and help others discover the project.
- **Have questions?** Join our [Discord](https://discord.gg/b5zjErwbQM) or visit [weekly office hours](./COMMUNITY.md#public-community-office-hours).
## Troubleshooting
### Authentication
| Problem | Cause | Fix |
|---------|-------|-----|
| Authentication errors when using Azure credentials | Not signed in to Azure CLI | Run `az login` before starting your app |
| API key errors | Wrong or missing API key | Verify the key and ensure it's for the correct resource/provider |
> **Tip:** `DefaultAzureCredential` is convenient for development but in production, consider using a specific credential (e.g., `ManagedIdentityCredential`) to avoid latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
### Environment Variables
For environment variable configuration specific to each sample, refer to the README in the sample directory ([Python samples](./python/samples/) | [.NET samples](./dotnet/samples/)).
## Contributor Resources
- [Contributing Guide](./CONTRIBUTING.md)
- [Python Development Guide](./python/DEV_SETUP.md)
- [Design Documents](./docs/design)
- [Architectural Decision Records](./docs/decisions)
## Important Notes
> [!IMPORTANT]
> If you use Microsoft Agent Framework to build applications that operate with any third-party servers, agents, code, or non-Azure Direct models (“Third-Party Systems”), you do so at your own risk. Third-Party Systems are Non-Microsoft Products under the Microsoft Product Terms and are governed by their own third-party license terms. You are responsible for any usage and associated costs.
>
>We recommend reviewing all data being shared with and received from Third-Party Systems and being cognizant of third-party practices for handling, sharing, retention and location of data. It is your responsibility to manage whether your data will flow outside of your organizations Azure compliance and geographic boundaries and any related implications, and that appropriate permissions, boundaries and approvals are provisioned.
>
>You are responsible for carefully reviewing and testing applications you build using Microsoft Agent Framework in the context of your specific use cases, and making all appropriate decisions and customizations. This includes implementing your own responsible AI mitigations such as metaprompt, content filters, or other safety systems, and ensuring your applications meet appropriate quality, reliability, security, and trustworthiness standards. See also: [Transparency FAQ](./TRANSPARENCY_FAQ.md)
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# WeHub 来源说明
- 原始项目:`microsoft/agent-framework`
- 原始仓库:https://github.com/microsoft/agent-framework
- 导入方式:上游默认分支的最新快照
- 原作者、版权和许可证信息以原始仓库及本仓库 LICENSE 为准
- 本文件仅用于记录来源,不代表 WeHub 是原项目作者
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<!-- BEGIN MICROSOFT SECURITY.MD V0.0.9 BLOCK -->
## Security
Microsoft takes the security of our software products and services seriously, which includes all source code repositories managed through our GitHub organizations, which include [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet](https://github.com/aspnet) and [Xamarin](https://github.com/xamarin).
If you believe you have found a security vulnerability in any Microsoft-owned repository that meets [Microsoft's definition of a security vulnerability](https://aka.ms/security.md/definition), please report it to us as described below.
## Reporting Security Issues
**Please do not report security vulnerabilities through public GitHub issues.**
Instead, please report them to the Microsoft Security Response Center (MSRC) at [https://msrc.microsoft.com/create-report](https://aka.ms/security.md/msrc/create-report).
If you prefer to submit without logging in, send email to [secure@microsoft.com](mailto:secure@microsoft.com). If possible, encrypt your message with our PGP key; please download it from the [Microsoft Security Response Center PGP Key page](https://aka.ms/security.md/msrc/pgp).
You should receive a response within 24 hours. If for some reason you do not, please follow up via email to ensure we received your original message. Additional information can be found at [microsoft.com/msrc](https://www.microsoft.com/msrc).
Please include the requested information listed below (as much as you can provide) to help us better understand the nature and scope of the possible issue:
* Type of issue (e.g. buffer overflow, SQL injection, cross-site scripting, etc.)
* Full paths of source file(s) related to the manifestation of the issue
* The location of the affected source code (tag/branch/commit or direct URL)
* Any special configuration required to reproduce the issue
* Step-by-step instructions to reproduce the issue
* Proof-of-concept or exploit code (if possible)
* Impact of the issue, including how an attacker might exploit the issue
This information will help us triage your report more quickly.
If you are reporting for a bug bounty, more complete reports can contribute to a higher bounty award. Please visit our [Microsoft Bug Bounty Program](https://aka.ms/security.md/msrc/bounty) page for more details about our active programs.
## Preferred Languages
We prefer all communications to be in English.
## Policy
Microsoft follows the principle of [Coordinated Vulnerability Disclosure](https://aka.ms/security.md/cvd).
<!-- END MICROSOFT SECURITY.MD BLOCK -->
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# Support
## How to file issues and get help
This project uses GitHub Issues to track bugs and feature requests. Please search the existing
issues before filing new issues to avoid duplicates. For new issues, file your bug or
feature request as a new Issue.
For help and questions about using this project, please create a GitHub issue.
AI Support team will support Microsoft Agent Framework issues for customers under a **Unified support agreement when the issue arises from usage of Azure AI services** (Foundry Models, Foundry Agents etc.) in conjunction with the SDK. Conversely, if customer has any other / non unified support agreement and/or Agent Framework SDK is used in a way **not involving an Azure service**, it is treated as a purely open-source tool Microsofts support organization will not handle it, and users should use GitHub or forums for assistance
For Copilot Studio SDK implementation issues, customers should use GitHub Issues for assistance, as outlined above. Conversely, for prerequisites managed within the Copilot Studio portal, customers can rely on the standard Microsoft Copilot Studio support channels.
## Microsoft Support Policy
Support for this **PROJECT or PRODUCT** is limited to the resources listed above.
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# Responsible AI Transparency FAQs
**What is Microsoft Agent Framework?**
Microsoft Agent Framework is a comprehensive multi-language (C#/.NET and Python) framework for building, orchestrating, and deploying AI agents and multi-agent workflows. The system takes user instructions and conversation inputs and produces intelligent responses through AI agents that can integrate with various LLM providers (OpenAI, Azure OpenAI, Azure AI Foundry). It provides both simple chat agents and complex multi-agent workflows with graph-based orchestration.
**What can Microsoft Agent Framework do?**
The framework offers:
- **Agent Creation**: Build AI agents with custom instructions and tools
- **Multi-Agent Orchestration**: Group chat, sequential, concurrent, and handoff patterns
- **Graph-based Workflows**: Connect agents and deterministic functions using data flows with streaming, checkpointing, time-travel, and Human-in-the-loop
- **Extensibility Framework**: Extend with native functions, A2A, Model Context Protocol (MCP)
- **LLM Integration**: Support for OpenAI, Azure OpenAI, Azure AI Foundry, and other providers
- **Runtime Support**: Both in-process and distributed agent execution
**What is/are Microsoft Agent Framework's intended use(s)?**
Intended uses include:
- **Enterprise AI Applications**: Building AI-powered business applications with multiple specialized agents
- **Multi-Agent Collaboration**: Coordinating multiple AI agents for complex tasks (e.g., content creation with writer/reviewer agents)
- **Workflow Automation**: Orchestrating AI agents and deterministic functions in business processes
**How was Microsoft Agent Framework evaluated? What metrics are used to measure performance?**
Microsoft Agent Framework is a development framework rather than a deployed AI system. The framework undergoes engineering testing for component functionality, integration testing for multi-agent scenarios, and conformance testing across .NET and Python implementations. However, AI performance metrics such as accuracy, helpfulness, and safety are dependent on the underlying LLM providers and specific application implementations. Developers using the framework should conduct application-specific evaluation including performance, safety, and accuracy testing appropriate to their chosen LLM providers, deployment contexts, and use cases.
**What are the limitations of Microsoft Agent Framework? How can users minimize the impact of Microsoft Agent Framework's limitations when using the system?**
Microsoft Agent Framework relies on existing LLMs. Using the framework retains common limitations of large language models, including:
**LLM-Inherited Limitations**:
- **Data Biases**: Large language models, trained on extensive data, can inadvertently carry biases present in the source data. Consequently, the models may generate outputs that could be potentially biased or unfair.
- **Lack of Contextual Understanding**: Despite their impressive capabilities in language understanding and generation, these models exhibit limited real-world understanding, resulting in potential inaccuracies or nonsensical responses.
- **Lack of Transparency**: Due to the complexity and size, large language models can act as 'black boxes,' making it difficult to comprehend the rationale behind specific outputs or decisions.
- **Content Harms**: There are various types of content harms that large language models can cause. It is important to be aware of them when using these models, and to take actions to prevent them. It is recommended to leverage various content moderation services provided by different companies and institutions.
- **Inaccurate or ungrounded content**: It is important to be aware and cautious not to entirely rely on a given language model for critical decisions or information that might have deep impact as it is not obvious how to prevent these models to fabricate content without high authority input sources.
- **Potential for Misuse**: Without suitable safeguards, there is a risk that these models could be maliciously used for generating disinformation or harmful content.
**Framework-Specific Limitations**:
- **Platform Requirements**: Python 3.10+ required, specific .NET versions (.NET 8.0, 9.0, 10.0, 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.
- **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.
**Mitigation Steps**:
- Follow setup guides for proper API key configuration
- Use provided samples as starting points to avoid configuration issues
- Monitor the GitHub repository for feature releases and updates
- Implement content moderation and safety measures when deploying agents
- Maintain human oversight for critical decisions and actions
- Use appropriate security measures to protect user data and conversations
**What operational factors and settings allow for effective and responsible use of Microsoft Agent Framework?**
**Configuration Requirements**:
- **API Keys**: Proper configuration of your LLM provider credentials and endpoints
- **Model Selection**: Choose appropriate deployment models for specific use cases
- **Tool Integration**: Careful selection and validation of external tools and MCP servers
- **Type Safety**: Strong typing and compatibility validation between agents and threads
**Responsible Development Practices**:
- **Human Oversight**: Microsoft Agent Framework prioritizes human involvement in multi-agent conversations. Users should maintain oversight and can step in to provide feedback to agents and steer them in the correct direction. In critical applications, users should confirm actions before they are executed.
- **Agent Modularity**: Modularity allows agents to have different levels of information access. Additional agents can assume roles that help keep other agents in check. For example, one can easily add a dedicated agent to play the role of safeguard.
- **LLM Selection**: Users can choose the LLM that is optimized for responsible use. We encourage developers to review and follow LLM providers policies. Developers should add content moderation and/or use safety metaprompts when using agents, like they would do when using LLMs directly.
- **Security Measures**: Implement appropriate security measures for tool execution and external system integrations. Consider using containerization or sandboxing for code execution scenarios to prevent unintended system changes.
- **Testing and Validation**: Use provided testing frameworks (unit, integration, conformance tests) to validate agent behavior and ensure reliability.
- **Monitoring and Observability**: Implement proper error handling, logging, and use OpenTelemetry for observability to track agent behavior and identify potential issues.
**How do I provide feedback on Microsoft Agent Framework?**
- **Bug Reports**: File issues at https://github.com/microsoft/agent-framework/issues
**What are external services and how does Microsoft Agent Framework use them?**
The framework supports multiple external service types:
- **Native Functions**: Custom Python/C# functions that agents can invoke
- **A2A (Agent2Agent)Integration**: Agent-to-agent communication and coordination
- **Model Context Protocol (MCP)**: External tools and data sources through MCP servers
- **Tools & External Capabilities**: Agent-invokable external services
External service development is open to developers who can create custom functions and integrate external APIs. Users have control over which tools are provided to agents during agent creation.
**What data can Microsoft Agent Framework provide to external services? What permissions do Microsoft Agent Framework external services have?**
Microsoft Agent Framework is an open-source framework that allows integration with various types of external services. The data access and permissions depend on how you configure and implement these integrations:
**Data Access by Service Type**:
- **Native Functions**: Custom functions you develop have access to whatever data you explicitly pass to them as parameters
- **A2A (Agent2Agent)**: External agents can access conversation history, messages, and any data you configure to share through the communication interface
- **Model Context Protocol (MCP) Servers**: External MCP servers can access data according to the specific MCP server implementation and your configuration
- **External Tools**: Third-party tools and APIs have access to data you explicitly send to them through function calls
**Important Security Considerations**:
- **Community and Third-Party Services**: Microsoft Agent Framework is an open-source project. When using community-developed tools or services from third-party providers, it is your responsibility to evaluate and ensure their safety, security, and compliance with your data protection requirements.
- **Data Boundary Considerations**: When connecting Azure-hosted agents to external agents or services, data may leave the Azure boundary and Microsoft's security perimeter. You should verify the data handling practices, security measures, and compliance certifications of external providers before sharing sensitive or regulated data.
- **Provider Due Diligence**: Before integrating any external service, you should review their privacy policies, security practices, data retention policies, and terms of service to ensure they meet your organization's requirements and regulatory obligations.
- **Data Minimization**: Only provide external services with the minimum data necessary for their function. Avoid sharing sensitive, personal, or confidential information unless absolutely required and properly secured.
**Recommendation**: Consult with your organization's security, privacy, and legal teams before integrating external services, especially in production environments handling sensitive data.
**What kinds of issues may arise when using Microsoft Agent Framework enabled with external services?**
**Potential Issues**:
- **API Key Security**: Risk of exposing API keys in configuration or logs
- **Tool Reliability**: External tool failures or unavailability affecting agent performance
- **Type Safety**: Mismatched message types between agents and handlers
- **Provider Dependencies**: Reliance on external LLM provider availability and rate limits
**Mitigation Mechanisms**:
- Follow security best practices for API key management
- Implement proper error handling for tool failures
- Use strong typing and compatibility validation
- Monitor external service health and implement fallback strategies
- Regular repository updates during preview period for bug fixes
@@ -0,0 +1,3 @@
# Declarative Agents
This folder contains sample agent definitions that can be run using the declarative agent support, for python see the [declarative agent python sample folder](../../python/samples/02-agents/declarative/).
@@ -0,0 +1,25 @@
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.
@@ -0,0 +1,25 @@
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.
@@ -0,0 +1,25 @@
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.
@@ -0,0 +1,25 @@
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.
@@ -0,0 +1,18 @@
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.
@@ -0,0 +1,29 @@
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
@@ -0,0 +1,22 @@
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.
@@ -0,0 +1,21 @@
kind: Prompt
name: MicrosoftLearnAgent
description: Microsoft Learn Agent
instructions: You answer questions by searching the Microsoft Learn content only.
model:
id: =Env.FOUNDRY_MODEL
options:
temperature: 0.9
topP: 0.95
connection:
kind: remote
endpoint: =Env.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
@@ -0,0 +1,22 @@
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.
@@ -0,0 +1,28 @@
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.
@@ -0,0 +1,28 @@
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_API_KEY
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.
@@ -0,0 +1,28 @@
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_API_KEY
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.
@@ -0,0 +1,28 @@
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: key
apiKey: =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.
@@ -0,0 +1,164 @@
#
# This workflow demonstrates using multiple agents to provide automated
# troubleshooting steps to resolve common issues with escalation options.
#
# Example input:
# My PC keeps rebooting and I can't use it.
#
kind: Workflow
trigger:
kind: OnConversationStart
id: workflow_demo
actions:
# Interact with user until the issue has been resolved or
# a determination is made that a ticket is required.
- kind: InvokeAzureAgent
id: service_agent
conversationId: =System.ConversationId
agent:
name: SelfServiceAgent
input:
externalLoop:
when: |-
=Not(Local.ServiceParameters.IsResolved)
And
Not(Local.ServiceParameters.NeedsTicket)
output:
responseObject: Local.ServiceParameters
# All done if issue is resolved.
- kind: ConditionGroup
id: check_if_resolved
conditions:
- condition: =Local.ServiceParameters.IsResolved
id: test_if_resolved
actions:
- kind: GotoAction
id: end_when_resolved
actionId: all_done
# Create the ticket.
- kind: InvokeAzureAgent
id: ticket_agent
agent:
name: TicketingAgent
input:
arguments:
IssueDescription: =Local.ServiceParameters.IssueDescription
AttemptedResolutionSteps: =Local.ServiceParameters.AttemptedResolutionSteps
output:
responseObject: Local.TicketParameters
# Capture the attempted resolution steps.
- kind: SetVariable
id: capture_attempted_resolution
variable: Local.ResolutionSteps
value: =Local.ServiceParameters.AttemptedResolutionSteps
# Notify user of ticket identifier.
- kind: SendActivity
id: log_ticket
activity: "Created ticket #{Local.TicketParameters.TicketId}"
# Determine which team for which route the ticket.
- kind: InvokeAzureAgent
id: routing_agent
agent:
name: TicketRoutingAgent
input:
messages: =UserMessage(Local.ServiceParameters.IssueDescription)
output:
responseObject: Local.RoutingParameters
# Notify user of routing decision.
- kind: SendActivity
id: log_route
activity: Routing to {Local.RoutingParameters.TeamName}
- kind: ConditionGroup
id: check_routing
conditions:
- condition: =Local.RoutingParameters.TeamName = "Windows Support"
id: route_to_support
actions:
# Invoke the support agent to attempt to resolve the issue.
- kind: CreateConversation
id: conversation_support
conversationId: Local.SupportConversationId
- kind: InvokeAzureAgent
id: support_agent
conversationId: =Local.SupportConversationId
agent:
name: WindowsSupportAgent
input:
arguments:
IssueDescription: =Local.ServiceParameters.IssueDescription
AttemptedResolutionSteps: =Local.ServiceParameters.AttemptedResolutionSteps
externalLoop:
when: |-
=Not(Local.SupportParameters.IsResolved)
And
Not(Local.SupportParameters.NeedsEscalation)
output:
autoSend: true
responseObject: Local.SupportParameters
# Capture the attempted resolution steps.
- kind: SetVariable
id: capture_support_resolution
variable: Local.ResolutionSteps
value: =Local.SupportParameters.ResolutionSummary
# Check if the issue was resolved by support.
- kind: ConditionGroup
id: check_resolved
conditions:
# Resolve ticket
- condition: =Local.SupportParameters.IsResolved
id: handle_if_resolved
actions:
- kind: InvokeAzureAgent
id: resolution_agent
agent:
name: TicketResolutionAgent
input:
arguments:
TicketId: =Local.TicketParameters.TicketId
ResolutionSummary: =Local.SupportParameters.ResolutionSummary
- kind: GotoAction
id: end_when_solved
actionId: all_done
# Escalate the ticket by sending an email notification.
- kind: CreateConversation
id: conversation_escalate
conversationId: Local.EscalationConversationId
- kind: InvokeAzureAgent
id: escalate_agent
conversationId: =Local.EscalationConversationId
agent:
name: TicketEscalationAgent
input:
arguments:
TicketId: =Local.TicketParameters.TicketId
IssueDescription: =Local.ServiceParameters.IssueDescription
ResolutionSummary: =Local.ResolutionSteps
externalLoop:
when: =Not(Local.EscalationParameters.IsComplete)
output:
autoSend: true
responseObject: Local.EscalationParameters
# All done
- kind: EndWorkflow
id: all_done
@@ -0,0 +1,381 @@
#
# This workflow coordinates multiple agents in order to address complex user requests
# according to the "Magentic" orchestration pattern introduced by AutoGen.
#
# For this workflow, several agents used, each with specific roles.
#
# The following agents are responsible for overseeing and coordinating the workflow:
# - Research Agent: Analyze the current task and correlate relevant facts.
# - Planner Agent: Analyze the current task and devise an overall plan.
# - Manager Agent: Evaluates status and delegate tasks to other agents.
# - Summary Agent: Evaluates status and delegate tasks to other agents.
#
# The following agents have capabilities that are utilized to address the input task:
# - Knowledge Agent: Performs generic web searches.
# - Coder Agent: Able to write and execute code.
# - Weather Agent: Provides weather information.
#
kind: Workflow
maxTurns: 500
trigger:
kind: OnConversationStart
id: workflow_demo
actions:
- kind: SetVariable
id: setVariable_aASlmF
displayName: List all available agents for this orchestrator
variable: Local.AvailableAgents
value: |-
=[
{
name: "WeatherAgent",
description: "Able to retrieve weather information"
},
{
name: "CoderAgent",
description: "Able to write and execute Python code"
},
{
name: "KnowledgeAgent",
description: "Able to perform generic websearches"
}
]
- kind: SetVariable
id: setVariable_V6yEbo
displayName: Get a summary of all the agents for use in prompts
variable: Local.TeamDescription
value: "=Concat(ForAll(Local.AvailableAgents, $\"- \" & name & $\": \" & description), Value, \"\n\")"
- kind: SetVariable
id: setVariable_NZ2u0l
displayName: Set Task
variable: Local.InputTask
value: =System.LastMessage.Text
- kind: SetVariable
id: setVariable_10u2ZN
displayName: Set Task
variable: Local.SeedTask
value: =UserMessage(Local.InputTask)
- kind: SendActivity
id: sendActivity_yFsbRy
activity: Analyzing facts...
- kind: CreateConversation
id: conversation_1a2b3c
conversationId: Local.StatusConversationId
- kind: CreateConversation
id: conversation_1x2y3z
conversationId: Local.TaskConversationId
- kind: InvokeAzureAgent
id: question_UDoMUw
displayName: Get Facts
conversationId: =Local.StatusConversationId
agent:
name: ResearchAgent
output:
messages: Local.TaskFacts
input:
messages: =UserMessage(Local.InputTask)
- kind: SendActivity
id: sendActivity_yFsbRz
activity: Creating a plan...
- kind: InvokeAzureAgent
id: question_DsBaJU
displayName: Create a Plan
conversationId: =Local.StatusConversationId
agent:
name: PlannerAgent
input:
arguments:
team: =Local.TeamDescription
output:
messages: Local.Plan
- kind: SetTextVariable
id: setVariable_Kk2LDL
displayName: Define instructions
variable: Local.TaskInstructions
value: |-
# TASK
Address the following user request:
{Local.InputTask}
# TEAM
Use the following team to answer this request:
{Local.TeamDescription}
# FACTS
Consider this initial fact sheet:
{MessageText(Local.TaskFacts)}
# PLAN
Here is the plan to follow as best as possible:
{MessageText(Local.Plan)}
- kind: SendActivity
id: sendActivity_bwNZiM
activity: {Local.TaskInstructions}
- kind: InvokeAzureAgent
id: question_o3BQkf
displayName: Progress Ledger Prompt
conversationId: =Local.StatusConversationId
agent:
name: ManagerAgent
input:
messages: =UserMessage(Local.AgentResponseText)
output:
responseObject: Local.ProgressLedger
autoSend: false
- kind: ConditionGroup
id: conditionGroup_mVIecC
conditions:
- id: conditionItem_fj432c
condition: =Local.ProgressLedger.is_request_satisfied.answer
displayName: If Done
actions:
- kind: SendActivity
id: sendActivity_kdl3mC
activity: Completed! {Local.ProgressLedger.is_request_satisfied.reason}
- kind: InvokeAzureAgent
id: question_Ke3l1d
displayName: Generate Response
conversationId: =Local.TaskConversationId
agent:
name: SummaryAgent
output:
autoSend: true
messages: Local.FinalResponse
- kind: EndConversation
id: end_SVoNSV
- id: conditionItem_yiqund
condition: =Local.ProgressLedger.is_in_loop.answer || Not(Local.ProgressLedger.is_progress_being_made.answer)
displayName: If Stalling
actions:
- kind: SetVariable
id: setVariable_H5lXdD
displayName: Increase stall count
variable: Local.StallCount
value: =Local.StallCount + 1
- kind: ConditionGroup
id: conditionGroup_vBTQd3
conditions:
- id: conditionItem_fpaNL9
condition: =Local.ProgressLedger.is_in_loop.answer
displayName: Is Loop
actions:
- kind: SendActivity
id: sendActivity_fpaNL9
activity: {Local.ProgressLedger.is_in_loop.reason}
- id: conditionItem_NnqvXh
condition: =Not(Local.ProgressLedger.is_progress_being_made.answer)
displayName: Is No Progress
actions:
- kind: SendActivity
id: sendActivity_NnqvXh
activity: {Local.ProgressLedger.is_progress_being_made.reason}
- kind: ConditionGroup
id: conditionGroup_xzNrdM
conditions:
- id: conditionItem_NlQTBv
condition: =Local.StallCount > 2
displayName: Stall Count Exceeded
actions:
- kind: SendActivity
id: sendActivity_H5lXdD
activity: Unable to make sufficient progress...
- kind: ConditionGroup
id: conditionGroup_4s1Z27
conditions:
- id: conditionItem_EXAlhZ
condition: =Local.RestartCount > 2
actions:
- kind: SendActivity
id: sendActivity_xKxFUU
activity: Stopping after attempting {Local.RestartCount} restarts...
- kind: EndConversation
id: end_GHVrFh
- kind: SendActivity
id: sendActivity_cwNZiM
activity: Re-analyzing facts...
- kind: InvokeAzureAgent
id: question_wFJ123
displayName: Get New Facts Prompt
conversationId: =Local.StatusConversationId
agent:
name: ResearchAgent
output:
messages: Local.TaskFacts
input:
messages: |-
=UserMessage(
"It's clear we aren't making as much progress as we would like, but we may have learned something new.
Please rewrite the following fact sheet, updating it to include anything new we have learned that may be helpful.
Example edits can include (but are not limited to) adding new guesses, moving educated guesses to verified facts if appropriate, etc.
Updates may be made to any section of the fact sheet, and more than one section of the fact sheet can be edited.
This is an especially good time to update educated guesses, so please at least add or update one educated guess or hunch, and explain your reasoning.
Here is the old fact sheet:
{MessageText(Local.TaskFacts)}"
- kind: SendActivity
id: sendActivity_dsBaJU
activity: Re-analyzing plan...
- kind: InvokeAzureAgent
id: question_uEJ456
displayName: Create new Plan Prompt
conversationId: =Local.StatusConversationId
agent:
name: PlannerAgent
output:
messages: Local.Plan
input:
messages: |-
=UserMessage(
"Please briefly explain what went wrong on this last run (the root cause of the failure),
and then come up with a new plan that takes steps and/or includes hints to overcome prior challenges and especially avoids repeating the same mistakes.
As before, the new plan should be concise, be expressed in bullet-point form, and consider the following team composition
(do not involve any other outside people since we cannot contact anyone else):
{Local.TeamDescription}")
- kind: SetTextVariable
id: setVariable_jW7tmM
displayName: Set Plan as Context
variable: Local.TaskInstructions
value: |-
# TASK
Address the following user request:
{Local.InputTask}
# TEAM
Use the following team to answer this request:
{Local.TeamDescription}
# FACTS
Consider this initial fact sheet:
{MessageText(Local.TaskFacts)}
# PLAN
Here is the plan to follow as best as possible:
{MessageText(Local.Plan)}
- kind: SetVariable
id: setVariable_6J2snP
displayName: Reset Stall count
variable: Local.StallCount
value: 0
- kind: SetVariable
id: setVariable_S6HCgh
displayName: Increase Restart count
variable: Local.RestartCount
value: =Local.RestartCount + 1
- kind: GotoAction
id: goto_LzfJ8u
actionId: question_o3BQkf
elseActions:
- kind: SendActivity
id: sendActivity_L7ooQO
activity: |-
({Local.ProgressLedger.next_speaker.reason})
{Local.ProgressLedger.next_speaker.answer} - {Local.ProgressLedger.instruction_or_question.answer}
- kind: SetVariable
id: setVariable_nxN1mE
variable: Local.NextSpeaker
value: =Search(Local.AvailableAgents, Local.ProgressLedger.next_speaker.answer, name)
- kind: ConditionGroup
id: conditionGroup_QFPiF5
conditions:
- id: conditionItem_GmigcU
condition: =CountRows(Local.NextSpeaker) = 1
displayName: If next Agent tool Exists
actions:
- kind: SetVariable
id: setVariable_L7ooQO
variable: Local.StallCount
value: 0
- kind: InvokeAzureAgent
id: question_orsBf06
displayName: Progress Ledger Prompt
conversationId: =Local.TaskConversationId
agent:
name: =First(Local.NextSpeaker).name
output:
autoSend: true
messages: Local.AgentResponse
input:
messages: =UserMessage(Local.ProgressLedger.instruction_or_question.answer)
- kind: SetVariable
id: setVariable_XzNrdM
variable: Local.AgentResponseText
value: =MessageText(Local.AgentResponse)
- kind: ResetVariable
id: setVariable_8eIx2A
displayName: Clear seed task
variable: Local.SeedTask
elseActions:
- kind: SendActivity
id: sendActivity_BhcsI7
activity: Unable to choose next agent...
- kind: SetVariable
id: setVariable_BhcsI7
displayName: Increase stall count
variable: Local.StallCount
value: =Local.StallCount + 1
- kind: GotoAction
id: goto_76Hne8
actionId: question_o3BQkf
@@ -0,0 +1,30 @@
#
# This workflow demonstrates sequential agent interaction to develop product marketing copy.
#
# Example input:
# An eco-friendly stainless steel water bottle that keeps drinks cold for 24 hours.
#
kind: Workflow
trigger:
kind: OnConversationStart
id: workflow_demo
actions:
- kind: InvokeAzureAgent
id: invoke_analyst
conversationId: =System.ConversationId
agent:
name: AnalystAgent
- kind: InvokeAzureAgent
id: invoke_writer
conversationId: =System.ConversationId
agent:
name: WriterAgent
- kind: InvokeAzureAgent
id: invoke_editor
conversationId: =System.ConversationId
agent:
name: EditorAgent
@@ -0,0 +1,58 @@
#
# This workflow demonstrates conversation between two agents: a student and a teacher.
# The student attempts to solve the input problem and the teacher provides guidance.
#
# Example input:
# How would you compute the value of PI?
#
kind: Workflow
trigger:
kind: OnConversationStart
id: workflow_demo
actions:
- kind: InvokeAzureAgent
id: question_student
conversationId: =System.ConversationId
agent:
name: StudentAgent
- kind: InvokeAzureAgent
id: question_teacher
conversationId: =System.ConversationId
agent:
name: TeacherAgent
output:
messages: Local.TeacherResponse
- kind: SetVariable
id: set_count_increment
variable: Local.TurnCount
value: =Local.TurnCount + 1
- kind: ConditionGroup
id: check_completion
conditions:
- condition: =!IsBlank(Find("CONGRATULATIONS", Upper(MessageText(Local.TeacherResponse))))
id: check_turn_done
actions:
- kind: SendActivity
id: sendActivity_done
activity: GOLD STAR!
- condition: =Local.TurnCount < 4
id: check_turn_count
actions:
- kind: GotoAction
id: goto_student_agent
actionId: question_student
elseActions:
- kind: SendActivity
id: sendActivity_tired
activity: Let's try again later...
@@ -0,0 +1,17 @@
# Declarative Workflows
A _Declarative Workflow_ is defined as a single YAML file and
may be executed locally no different from any regular `Workflow` that is defined by code.
The difference is that the workflow definition is loaded from a YAML file instead of being defined in code:
```c#
Workflow workflow = DeclarativeWorkflowBuilder.Build("Marketing.yaml", options);
```
These example workflows may be executed by the workflow
[Samples](../../dotnet/samples/03-workflows/Declarative)
that are present in this repository.
> See the [README.md](../../dotnet/samples/03-workflows/Declarative/README.md)
associated with the samples for configuration details.
+54
View File
@@ -0,0 +1,54 @@
# Frequently Asked Questions
### How do I get access to nightly builds?
Nightly builds of the Agent Framework are available [here](https://github.com/orgs/microsoft/packages?repo_name=agent-framework).
To download nightly builds follow the following steps:
1. You will need a GitHub account to complete these steps.
1. Create a GitHub Personal Access Token with the `read:packages` scope using these [instructions](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens#creating-a-personal-access-token-classic).
1. If your account is part of the Microsoft organization then you must authorize the `Microsoft` organization as a single sign-on organization.
1. Click the "Configure SSO" next to the Personal Access Token you just created and then authorize `Microsoft`.
1. Use the following command to add the Microsoft GitHub Packages source to your NuGet configuration:
```powershell
dotnet nuget add source --username GITHUBUSERNAME --password GITHUBPERSONALACCESSTOKEN --store-password-in-clear-text --name GitHubMicrosoft "https://nuget.pkg.github.com/microsoft/index.json"
```
1. Or you can manually create a `NuGet.Config` file.
```xml
<?xml version="1.0" encoding="utf-8"?>
<configuration>
<packageSources>
<add key="nuget.org" value="https://api.nuget.org/v3/index.json" protocolVersion="3" />
<add key="GitHubMicrosoft" value="https://nuget.pkg.github.com/microsoft/index.json" />
</packageSources>
<packageSourceMapping>
<packageSource key="nuget.org">
<package pattern="*" />
</packageSource>
<packageSource key="GitHubMicrosoft">
<package pattern="*nightly"/>
</packageSource>
</packageSourceMapping>
<packageSourceCredentials>
<GitHubMicrosoft>
<add key="Username" value="<Your GitHub Id>" />
<add key="ClearTextPassword" value="<Your Personal Access Token>" />
</GitHubMicrosoft>
</packageSourceCredentials>
</configuration>
```
* If you place this file in your project folder make sure to have Git (or whatever source control you use) ignore it.
* For more information on where to store this file go [here](https://learn.microsoft.com/en-us/nuget/reference/nuget-config-file).
1. You can now add packages from the nightly build to your project.
* E.g. use this command `dotnet add package Microsoft.Agents.AI --version 0.0.1-nightly-250731.6-alpha`
1. And the latest package release can be referenced in the project like this:
* `<PackageReference Include="Microsoft.Agents.AI" Version="*-*" />`
For more information see: <https://docs.github.com/en/packages/working-with-a-github-packages-registry/working-with-the-nuget-registry>
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---
# These are optional elements. Feel free to remove any of them.
status: accepted
contact: westey-m
date: 2025-07-10 {YYYY-MM-DD when the decision was last updated}
deciders: sergeymenshykh, markwallace, rbarreto, dmytrostruk, westey-m, eavanvalkenburg, stephentoub
consulted:
informed:
---
# Agent Run Responses Design
## Context and Problem Statement
Agents may produce lots of output during a run including
1. **[Primary]** General response messages to the caller (this may be in the form of text, including structured output, images, sound, etc.)
2. **[Primary]** Structured confirmation requests to the caller
3. **[Secondary]** Tool invocation activities executed (both local and remote). For information only.
4. Reasoning/Thinking output.
1. **[Primary]** In some cases an LLM may return reasoning output intermixed with as part of the answer to the caller, since the caller's prompt asked for this detail in some way. This should be considered a specialization of 1.
1. **[Secondary]** Reasonining models optionally produce reasoning output separate from the answer to the caller's question, and this should be considered secondary content.
5. **[Secondary]** Handoffs / transitions from agent to agent where an agent contains sub agents.
6. **[Secondary]** An indication that the agent is responding (i.e. typing) as if it's a real human.
7. Complete messages in addition to updates, when streaming
8. Id for long running process that is launched
9. and more
We need to ensure that with this diverse list of output, we are able to
- Support all with abstractions where needed
- Provide a simple getting started experience that doesn't overwhelm developers
### Agent response data types
When comparing various agent SDKs and protocols, agent output is often divided into two categories:
1. **Result**: A response from the agent that communicates the result of the agent's work to the caller in natural language (or images/sound/etc.). Let's call this **Primary** output.
1. Includes cases where the agent finished because it requires more input from the user.
2. **Progress**: Updates while the agent is running, which are informational only, typically showing what the agent is doing, and does not allow any actions to be taken by the caller that modify the behavior of the agent before completing the run. Let's call this **Secondary** output.
A potential third category is:
3. **Long Running**: A response that does not contain a Primary response or Secondary updates, but rather a reference to a long running task.
### Different use cases for Primary and Secondary output
To solve complex problems, many agents must be used together. These agents typically have their own capabilities and responsibilities and communicate via input messages and final responses/handoff calls, while the internal workings of each agent is not of interest to the other agents participating in solving the problem.
When an agent is in conversation with one or more humans, the information that may be displayed to the user(s) can vary. E.g. When an agent is part of a conversation with multiple humans it may be asked to perform tasks by the humans, and they may not want a stream of distracting updates posted to the conversation, but rather just a final response. On the other hand, if an agent is being used by a single human to perform a task, the human may be waiting for the agent to complete the task. Therefore, they may be interested in getting updates of what the agent is doing.
Where agents are nested, consumers would also likely want to constrain the amount of data from an agent that bubbles up into higher level conversations to avoid exceeding the context window, therefore limiting it to the Primary response only.
### Comparison with other SDKs / Protocols
Approaches observed from the compared SDKs:
1. Response object with separate properties for Primary and Secondary
2. Response stream that contains Primary and Secondary entries and callers need to filter.
3. Response containing just Primary.
| SDK | Non-Streaming | Streaming |
|-|-|-|
| AutoGen | **Approach 1** Separates messages into Agent-Agent (maps to Primary) and Internal (maps to Secondary) and these are returned as separate properties on the agent response object. See [types of messages](https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/messages.html#types-of-messages) and [Response](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.Response) | **Approach 2** Returns a stream of internal events and the last item is a Response object. See [ChatAgent.on_messages_stream](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.ChatAgent.on_messages_stream) |
| OpenAI Agent SDK | **Approach 1** Separates new_items (Primary+Secondary) from final output (Primary) as separate properties on the [RunResult](https://github.com/openai/openai-agents-python/blob/main/src/agents/result.py#L39) | **Approach 1** Similar to non-streaming, has a way of streaming updates via a method on the response object which includes all data, and then a separate final output property on the response object which is populated only when the run is complete. See [RunResultStreaming](https://github.com/openai/openai-agents-python/blob/main/src/agents/result.py#L136) |
| Google ADK | **Approach 2** [Emits events](https://google.github.io/adk-docs/runtime/#step-by-step-breakdown) with [FinalResponse](https://github.com/google/adk-java/blob/main/core/src/main/java/com/google/adk/events/Event.java#L232) true (Primary) / false (Secondary) and callers have to filter out those with false to get just the final response message | **Approach 2** Similar to non-streaming except [events](https://google.github.io/adk-docs/runtime/#streaming-vs-non-streaming-output-partialtrue) are emitted with [Partial](https://github.com/google/adk-java/blob/main/core/src/main/java/com/google/adk/events/Event.java#L133) true to indicate that they are streaming messages. A final non partial event is also emitted. |
| AWS (Strands) | **Approach 3** Returns an [AgentResult](https://strandsagents.com/docs/api/python/strands.agent.agent_result/) (Primary) with messages and a reason for the run's completion. | **Approach 2** [Streams events](https://strandsagents.com/docs/api/python/strands.agent.agent/) (Primary+Secondary) including, response text, current_tool_use, even data from "callbacks" (strands plugins) |
| LangGraph | **Approach 2** A mixed list of all [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) | **Approach 2** A mixed list of all [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) |
| Agno | **Combination of various approaches** Returns a [RunResponse](https://docs.agno.com/reference/agents/run-response) object with text content, messages (essentially chat history including inputs and instructions), reasoning and thinking text properties. Secondary events could potentially be extracted from messages. | **Approach 2** Returns [RunResponseEvent](https://docs.agno.com/reference/agents/run-response#runresponseevent-types-and-attributes) objects including tool call, memory update, etc, information, where the [RunResponseCompletedEvent](https://docs.agno.com/reference/agents/run-response#runresponsecompletedevent) has similar properties to RunResponse|
| A2A | **Approach 3** Returns a [Task or Message](https://a2aproject.github.io/A2A/latest/specification/#71-messagesend) where the message is the final result (Primary) and task is a reference to a long running process. | **Approach 2** Returns a [stream](https://a2aproject.github.io/A2A/latest/specification/#72-messagestream) that contains task updates (Secondary) and a final message (Primary) |
| Protocol Activity | **Approach 2** Single stream of responses including secondary events and final response messages (Primary). | No separate behavior for streaming. |
## Decision Drivers
- Solutions provides an easy to use experience for users who are getting started and just want the answer to a question.
- Solution must be extensible to future requirements, e.g. long running agent processes.
- Experience is in line or better than the best in class experience from other SDKs
## Response Type Options
- **Option 1** Run: Messages List contains mix of Primary and Secondary content, RunStreaming: Stream of Primary + Secondary
- **Option 1.1** Secondary content do not use `TextContent`
- **Option 1.2** Presence of Secondary Content is determined by a runtime parameter
- **Option 1.3** Use ChatClient response types
- **Option 1.4** Return derived ChatClient response types
- **Option 2** Run: Container with Primary and Secondary Properties, RunStreaming: Stream of Primary + Secondary
- **Option 2.1** Response types extend MEAI types
- **Option 2.2** New Response types
- **Option 3** Run: Primary-only, RunStreaming: Stream of Primary + Secondary
- **Option 4** Remove Run API and retain RunStreaming API only, which returns a Stream of Primary + Secondary.
Since the suggested options vary only for the non-streaming case, the following detailed explanations for each
focuses on the non-streaming case.
### Option 1 Run: Messages List contains mix of Primary and Secondary content, RunStreaming: Stream of Primary + Secondary
Run returns a `Task<ChatResponse>` and RunStreaming returns a `IAsyncEnumerable<ChatResponseUpdate>`.
For Run, the returned `ChatResponse.Messages` contains an ordered list of messages that contain both the Primary and Secondary content.
`ChatResponse.Text` automatically aggregates all text from any `TextContent` items in all `ChatMessage` items in the response.
If we can ensure that no updates ever contain `TextContent`, this will mean that `ChatResponse.Text` will always contain
the Primary response text. See option 1.1.
If we cannot ensure this, either the solution or usage becomes more complex, see 1.3 and 1.4.
#### Option 1.1 `TextContent`, `DataContent` and `UriContent` means Primary content
`ChatResponse.Text` aggregates all `TextContent` values, and no secondary updates use `TextContent`
so `ChatResponse.Text` will always contain the Primary content.
```csharp
// Since the Text property contains the primary content, it's a simple getting started experience.
var response = await agent.RunAsync("Do Something");
Console.WriteLine(response.Text);
// Callers can still get access to all updates too.
foreach (var update in response.Messages)
{
Console.WriteLine(update.Contents.FirstOrDefault()?.GetType().Name);
}
// For streaming, it's possible to output the primary content by also using the Text property on each update.
await foreach (var update in agent.RunStreamingAsync("Do Something"))
{
Console.Writeline(update.Text)
}
```
- **PROS**: Easy and familiar user experience, reuse response types from IChatClient. Similar experience for both streaming and non streaming.
- **CONS**: The agent response types cannot evolve separately from MEAI if needed.
#### Option 1.1a `TextContent`, `DataContent` and `UriContent` means Primary content, with custom Agent response types
Same as 1.1 but with custom Agent Framework response types.
The response types should preferably resemble ChatResponse types closely, to ensure user's have a fimilar experience when moving between the two.
Therefore something like `AgentResponse.Text` which also aggregates all `TextContent` values similar to 1.1 makes sense.
- **PROS**: Easy getting started experience, and response types can be customized for the Agent Framework where needed.
- **CONS**: More work to define custom response types.
#### Option 1.2 Presence of Secondary Content is determined by a runtime parameter
We can allow callers to choose whether to include secondary content in the list of reponse messages.
Open Question: Do we allow secondary content to use `TextContent` types?
```csharp
// By default the response only has the primary content, so text
// contains the primary content, and it's a good starting experience.
var response = await agent.RunAsync("Do Something");
Console.WriteLine(response.Text);
// we can also optionally include updates via an option.
var response = await agent.RunAsync("Do Something", options: new() { IncludeUpdates = true });
// Callers can now access all updates.
foreach (var update in response.Messages)
{
Console.WriteLine(update.Contents.FirstOrDefault()?.GetType().Name);
}
```
- **PROS**: Easy getting started experience, reuse response types from IChatClient.
- **CONS**: Since the basic experience is the same as 1.1, and when you look at individual messages, you most likely want all anyway, it seems arbitrarily limiting compared to 1.1.
### Option 2 Run: Container with Primary and Secondary Properties, RunStreaming: Stream of Primary + Secondary
Run returns a new response type that has separate properties for the Primary Content and the Secondary Updates leading up to it.
The Primary content is available in the `AgentResponse.Messages` property while Secondary updates are in a new `AgentResponse.Updates` property.
`AgentResponse.Text` returns the Primary content text.
Since streaming would still need to return an `IAsyncEnumerable` of updates, the design would differ from non-streaming.
With non-streaming Primary and Secondary content is split into separate lists, while with streaming it's combined in one stream.
```csharp
// Since text contains the primary content, it's a good getting started experience.
var response = await agent.RunAsync("Do Something");
Console.WriteLine(response.Text);
// Callers can still get access to all updates too.
foreach (var update in response.Updates)
{
Console.WriteLine(update.Contents.FirstOrDefault()?.GetType().Name);
}
```
- **PROS**: Primary content and Secondary Updates are categorised for non-streaming and therefore easy to distinguish and this design matches popular SDKs like AutoGen and OpenAI SDK.
- **CONS**: Requires custom response types and design would differ between streaming and non-streaming.
### Option 3 Run: Primary-only, RunStreaming: Stream of Primary + Secondary
Run returns a `Task<ChatResponse>` and RunStreaming returns a `IAsyncEnumerable<ChatResponseUpdate>`.
For Run, the returned `ChatResponse.Messages` contains only the Primary content messages.
`ChatResponse.Text` will contain the aggregate text of `ChatResponse.Messages` and therefore the primary content messages text.
```csharp
// Since text contains the primary content response, it's a good getting started experience.
var response = await agent.RunAsync("Do Something");
Console.WriteLine(response.Text);
// Callers cannot get access to all updates, since only the primary content is in messages.
var primaryContentOnly = response.Messages.FirstOrDefault();
```
- **PROS**: Simple getting started experience, Reusing IChatClient response types.
- **CONS**: Intermediate updates are only availble in streaming mode.
### Option 4: Remove Run API and retain RunStreaming API only, which returns a Stream of Primary + Secondary
With this option, we remove the `RunAsync` method and only retain the `RunStreamingAsync` method, but
we add helpers to process the streaming responses and extract information from it.
```csharp
// User can get the primary content through an extension method on the async enumerable stream.
var responses = agent.RunStreamingAsync("Do Something");
// E.g. an extension method that builds the primary content text.
Console.WriteLine(await responses.AggregateFinalResult());
// Or an extention method that builds complete messages from the updates.
Console.WriteLine(await responses.BuildMessage().Text);
// Callers can also iterate through all updates if needed
await foreach (var update in responses)
{
Console.WriteLine(update.Contents.FirstOrDefault()?.GetType().Name);
}
```
- **PROS**: Single API for streaming/non-streaming
- **CONS**: More complex to for inexperienced users.
## Custom Response Type Design Options
### Option 1 Response types extend MEAI types
```csharp
class Agent
{
public abstract Task<AgentResponse> RunAsync(
IReadOnlyCollection<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default);
public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
IReadOnlyCollection<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default);
}
class AgentResponse : ChatResponse
{
}
public class AgentResponseUpdate : ChatResponseUpdate
{
}
```
- **PROS**: Fimilar response types for anyone already using MEAI.
- **CONS**: Agent response types cannot evolve separately.
### Option 2 New Response types
We could create new response types for Agents.
The new types could also exclude properties that make less sense for agents, like ConversationId, which is abstracted away by AgentThread, or ModelId, where an agent might use multiple models.
```csharp
class Agent
{
public abstract Task<AgentResponse> RunAsync(
IReadOnlyCollection<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default);
public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
IReadOnlyCollection<ChatMessage> messages,
AgentThread? thread = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default);
}
class AgentResponse // Compare with ChatResponse
{
public string Text { get; } // Aggregation of TextContent from messages.
public IList<ChatMessage> Messages { get; set; }
public string? ResponseId { get; set; }
// Metadata
public string? AuthorName { get; set; }
public DateTimeOffset? CreatedAt { get; set; }
public object? RawRepresentation { get; set; }
public UsageDetails? Usage { get; set; }
public AdditionalPropertiesDictionary? AdditionalProperties { get; set; }
}
// Not Included in AgentResponse compared to ChatResponse
public ChatFinishReason? FinishReason { get; set; }
public string? ConversationId { get; set; }
public string? ModelId { get; set; }
public class AgentResponseUpdate // Compare with ChatResponseUpdate
{
public string Text { get; } // Aggregation of TextContent from Contents.
public IList<AIContent> Contents { get; set; }
public string? ResponseId { get; set; }
public string? MessageId { get; set; }
// Metadata
public ChatRole? Role { get; set; }
public string? AuthorName { get; set; }
public DateTimeOffset? CreatedAt { get; set; }
public UsageDetails? Usage { get; set; }
public object? RawRepresentation { get; set; }
public AdditionalPropertiesDictionary? AdditionalProperties { get; set; }
}
// Not Included in AgentResponseUpdate compared to ChatResponseUpdate
public ChatFinishReason? FinishReason { get; set; }
public string? ConversationId { get; set; }
public string? ModelId { get; set; }
```
- **PROS**: Agent response types can evolve separately. Types can still resemble MEAI response types to ensure a fimilar experience for developers.
- **CONS**: No automatic inheritence of new properties from MEAI. (this might also be a pro)
## Long Running Processes Options
Some agent protocols, like A2A, support long running agentic processes. When invoking the agent
in the non-streaming case, the agent may respond with an id of a process that was launched.
The caller is then expected to poll the service to get status updates using the id.
The caller may also subscribe to updates from the process using the id.
We therefore need to be able to support providing this type of response to agent callers.
- **Option 1** Add a new `AIContent` type and `ChatFinishReason` for long running processes.
- **Option 2** Add another property on a custom response type.
### Option 1: Add another AIContent type and ChatFinishReason for long running processes
```csharp
public class AgentRunContent : AIContent
{
public string AgentRunId { get; set; }
}
// Add a new long running chat finish reason.
public class ChatFinishReason
{
public static ChatFinishReason LongRunning { get; } = new ChatFinishReason("long_running");
}
```
- **PROS**: Fits well into existing `ChatResponse` design.
- **CONS**: More complex for users to extract the required long running result (can be mitigated with extenion methods)
### Option 2: Add another property on responses for AgentRun
```csharp
class AgentResponse
{
...
public AgentRun RunReference { get; set; } // Reference to long running process
...
}
public class AgentResponseUpdate
{
...
public AgentRun RunReference { get; set; } // Reference to long running process
...
}
// Add a new long running chat finish reason.
public class ChatFinishReason
{
...
public static ChatFinishReason LongRunning { get; } = new ChatFinishReason("long_running");
...
}
// Can be added in future: Class representing long running processing by the agent
// that can be used to check for updates and status of the processing.
public class AgentRun
{
public string AgentRunId { get; set; }
}
```
- **PROS**: Easy access to long running result values
- **CONS**: Requires custom response types.
## Structured user input options (Work in progress)
Some agent services may ask end users a question while also providing a list of options that the user can pick from or a template for the input required.
We need to decide whether to maintain an abstraction for these, so that similar types of structured input from different agents can be used by callers without
needing to break out of the abstraction.
## Tool result options (Work in progress)
We need to consider abstractions for `AIContent` derived types for tool call results for common tool types beyond Function calls, e.g. CodeInterpreter, WebSearch, etc.
## StructuredOutputs
Structured outputs is a valueable aspect of any Agent system, since it forces an Agent to produce output in a required format, and may include required fields. This allows turning unstructured data into structured data easily using a general purpose language model.
Not all agent types necessarily support this or necessarily support this in the same way.
Requesting a specific output schema at invocation time is widely supported by inference services though, and therefore inference based agents would support this well.
Custom agents on the other hand may not necessarily want to support this, and forcing all custom Agent implementations to have a final structured output step to produce this complicates implementations.
Custom agents may also have a built in output schema, that they always produce.
Options:
1. Support configuring the preferred structured output schema at agent construction time for those agents that support structured outputs.
2. Support configuring the preferred structured output schema at invocation time, and ignore/throw if not supported (similar to IChatClient)
3. Support both options with the invocation time schema overriding the construction time (or built in) schema if both are supported.
Note that where an agent doesn't support structured output, it may also be possible to use a decorator to produce structured output from the agent's unstructured response, thereby turning an agent that doesn't support this into one that does.
See [Structured Outputs Support](#structured-outputs-support) for a comparison on what other agent frameworks and protocols support.
To support a good user experience for structured outputs, I'm proposing that we follow the pattern used by MEAI.
We would add a generic version of `AgentResponse<T>`, that allows us to get the agent result already deserialized into our preferred type.
This would be coupled with generic overload extension methods for Run that automatically builds a schema from the supplied type and updates
the run options.
If we support requesting a schema at invocation time the following would be the preferred approach:
```csharp
class Movie
{
public string Title { get; set; }
public string DirectorFullName { get; set; }
public int ReleaseYear { get; set; }
}
AgentResponse<Movie[]> response = agent.RunAsync<Movie[]>("What are the top 3 children's movies of the 80s.");
Movie[] movies = response.Result
```
If we only support requesting a schema at agent creation time or where an agent has a built in schema, the following would be the preferred approach:
```csharp
AgentResponse response = agent.RunAsync("What are the top 3 children's movies of the 80s.");
Movie[] movies = response.TryParseStructuredOutput<Movie[]>();
```
## Decision Outcome
### Response Type Options Decision
Option 1.1 with the caveate that we cannot control the output of all agents. However, as far as possible we should have appropriate AIContext derived types for
progress updates so that TextContent is not used for these.
### Custom Response Type Design Options Decision
Option 2 chosen so that we can vary Agent responses independently of Chat Client.
### StructuredOutputs Decision
We will not support structured output per run request, but individual agents are free to allow this on the concrete implementation or at construction time.
We will however add support for easily extracting a structured output type from the `AgentResponse`.
## Addendum 1: AIContext Derived Types for different response types / Gap Analysis (Work in progress)
We need to decide what AIContent types, each agent response type will be mapped to.
| Number | DataType | AIContent Type |
|-|-|-|
| 1. | General response messages to the user | TextContent + DataContent + UriContent |
| 2. | Structured confirmation requests to the user | ? |
| 3. | Function invocation activities executed (both local and remote). For information only. | FunctionCallContent + FunctionResultContent |
| 4. | Tool invocation activities executed (both local and remote). For information only. | FunctionCallContent/FunctionResultContent/Custom ? |
| 5. | Reasoning/Thinking output. For information only. | TextReasoningContent |
| 6. | Handoffs / transitions from agent to agent. | ? |
| 7. | An indication that the agent is responding (i.e. typing) as if it's a real human. | ? |
| 8. | Complete messages in addition to updates, when streaming | TextContent |
| 9. | Id for long running process that is launched | ? |
| 10. | Memory storage / lookups (are these just traces?) | ? |
| 11. | RAG indexing / lookups (are these just traces?) | ? |
| 12. | General status updates for human consumption / Tracing | ? |
| 13. | Unknown Type | AIContent |
## Addendum 2: Other SDK feature comparison
### Structured Outputs Support
1. Configure Schema on Agent at Agent construction
2. Pass schema at Agent invocation
| SDK | Structured Outputs support |
|-|-|
| AutoGen | **Approach 1** Supports [configuring an agent](https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/agents.html#structured-output) at agent creation. |
| Google ADK | **Approach 1** Both [input and output schemas can be specified for LLM Agents](https://google.github.io/adk-docs/agents/llm-agents/#structuring-data-input_schema-output_schema-output_key) at construction time. This option is specific to this agent type and other agent types do not necessarily support |
| AWS (Strands) | **Approach 2** Supports a special invocation method called [structured_output](https://strandsagents.com/docs/api/python/strands.agent.agent/) |
| LangGraph | **Approach 1** Supports [configuring an agent](https://langchain-ai.github.io/langgraph/agents/agents/?h=structured#6-configure-structured-output) at agent construction time, and a [structured response](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) can be retrieved as a special property on the agent response |
| Agno | **Approach 1** Supports [configuring an agent](https://docs.agno.com/input-output/structured-output/agent) at agent construction time |
| A2A | **Informal Approach 2** Doesn't formally support schema negotiation, but [hints can be provided via metadata](https://a2a-protocol.org/latest/specification/#97-structured-data-exchange-requesting-and-providing-json) at invocation time |
| Protocol Activity | Supports returning [Complex types](https://github.com/microsoft/Agents/blob/main/specs/activity/protocol-activity.md#complex-types) but no support for requesting a type |
### Response Reason Support
| SDK | Response Reason support |
|-|-|
| AutoGen | Supports a [stop reason](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.TaskResult.stop_reason) which is a freeform text string |
| Google ADK | [No equivalent present](https://github.com/google/adk-python/blob/main/src/google/adk/events/event.py) |
| AWS (Strands) | Exposes a [stop_reason](https://strandsagents.com/docs/api/python/strands.types.event_loop/) property on the [AgentResult](https://strandsagents.com/docs/api/python/strands.agent.agent_result/) class with options that are tied closely to LLM operations. |
| LangGraph | No equivalent present, output contains only [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) |
| Agno | [No equivalent present](https://docs.agno.com/reference/agents/run-response) |
| A2A | No equivalent present, response only contains a [message](https://a2a-protocol.org/latest/specification/#64-message-object) or [task](https://a2a-protocol.org/latest/specification/#61-task-object). |
| Protocol Activity | [No equivalent present.](https://github.com/microsoft/Agents/blob/main/specs/activity/protocol-activity.md) |
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@@ -0,0 +1,144 @@
---
status: proposed
contact: rogerbarreto
date: 2025-07-14
deciders: stephentoub, markwallace-microsoft, rogerbarreto, westey-m
informed: {}
---
# Agent OpenTelemetry Instrumentation
## Context and Problem Statement
Currently, the Agent Framework lacks comprehensive observability and telemetry capabilities, making it difficult for developers to monitor agent performance, track usage patterns, debug issues, and gain insights into agent behavior in production environments. While the underlying ChatClient implementations may have their own telemetry, there is no standardized way to capture agent-specific metrics and traces that provide visibility into agent operations, token usage, response times, and error patterns at the agent abstraction level.
## Decision Drivers
- **Compliance**: The implementation should adhere to established OpenTelemetry semantic conventions for agents, ensuring consistency and interoperability with existing telemetry systems.
- **Observability Requirements**: Developers need comprehensive telemetry to monitor agent performance, track usage patterns, and debug issues in production environments.
- **Standardization**: The solution must follow established OpenTelemetry semantic conventions and integrate seamlessly with existing .NET telemetry infrastructure.
- **Microsoft.Extensions.AI Alignment**: The implementation should follow the exact patterns and conventions established by Microsoft.Extensions.AI's OpenTelemetry instrumentation.
- **Non-Intrusive Design**: Telemetry should be optional and not impact the core agent functionality or performance when disabled.
- **Agent-Level Insights**: The telemetry should capture agent-specific operations without duplicating underlying ChatClient telemetry.
- **Extensibility**: The solution should support future enhancements and additional telemetry scenarios.
## Considered Options
### Option 1: Direct Integration into Core Agent Classes
Embed OpenTelemetry instrumentation directly into the base `Agent` class and `ChatClientAgent` implementations.
#### Pros
- Automatic telemetry for all agent implementations
- No additional wrapper classes needed
- Consistent telemetry across all agents
#### Cons
- Violates single responsibility principle
- Increases complexity of core agent classes
- Makes telemetry mandatory rather than optional
- Harder to test and maintain
- Couples telemetry concerns with business logic
### Option 2: Aspect-Oriented Programming (AOP) Approach
Use interceptors or AOP frameworks to inject telemetry behavior into agent methods.
#### Pros
- Clean separation of concerns
- Non-intrusive to existing code
- Can be applied selectively
#### Cons
- Adds complexity with AOP framework dependencies
- Runtime overhead for interception
- Harder to debug and understand
- Not consistent with Microsoft.Extensions.AI patterns
### Option 3: OpenTelemetryAgent Wrapper Pattern
Create a delegating `OpenTelemetryAgent` wrapper class that implements the `Agent` interface and wraps any existing agent with telemetry instrumentation, following the exact pattern of Microsoft.Extensions.AI's `OpenTelemetryChatClient`.
#### Pros
- Follows established Microsoft.Extensions.AI patterns exactly
- Clean separation of concerns
- Optional and non-intrusive
- Easy to test and maintain
- Consistent with .NET telemetry conventions
- Supports any agent implementation
- Provides agent-level telemetry without duplicating ChatClient telemetry
#### Cons
- Requires explicit wrapping of agents
- Additional object allocation for wrapper
## Decision Outcome
Chosen option: "OpenTelemetryAgent Wrapper Pattern", because it follows the established Microsoft.Extensions.AI patterns exactly, provides clean separation of concerns, maintains optional telemetry, and offers the best balance of functionality, maintainability, and consistency with existing .NET telemetry infrastructure.
### Implementation Details
The implementation includes:
1. **OpenTelemetryAgent Wrapper Class**: A delegating agent that wraps any `Agent` implementation with telemetry instrumentation
2. **AgentOpenTelemetryConsts**: Comprehensive constants for telemetry attribute names and metric definitions
3. **Extension Methods**: `.WithOpenTelemetry()` extension method for easy agent wrapping
4. **Comprehensive Test Suite**: Full test coverage following Microsoft.Extensions.AI testing patterns
### Telemetry Data Captured
**Activities/Spans:**
- `agent.operation.name` (agent.run, agent.run_streaming)
- `agent.request.id`, `agent.request.name`, `agent.request.instructions`
- `agent.request.message_count`, `agent.request.thread_id`
- `agent.response.id`, `agent.response.message_count`, `agent.response.finish_reason`
- `agent.usage.input_tokens`, `agent.usage.output_tokens`
- Error information and activity status codes
**Metrics:**
- Operation duration histogram with proper buckets
- Token usage histogram (input/output tokens)
- Request count counter
- All metrics tagged with operation type and agent name
### Consequences
- **Good**: Provides comprehensive agent-level observability following established patterns
- **Good**: Non-intrusive and optional implementation that doesn't affect core functionality
- **Good**: Consistent with Microsoft.Extensions.AI telemetry conventions
- **Good**: Easy to integrate with existing OpenTelemetry infrastructure
- **Good**: Supports debugging, monitoring, and performance analysis
- **Neutral**: Requires explicit wrapping of agents with `.WithOpenTelemetry()`
- **Neutral**: Additional object allocation for telemetry wrapper
## Validation
The implementation is validated through:
1. **Comprehensive Unit Tests**: 16 test methods covering all scenarios including success, error, streaming, and edge cases
2. **Integration Testing**: Step05 telemetry sample demonstrating real-world usage
3. **Pattern Compliance**: Exact adherence to Microsoft.Extensions.AI OpenTelemetry patterns
4. **Semantic Convention Compliance**: Follows OpenTelemetry semantic conventions for telemetry data
## More Information
### Usage Example
```csharp
// Create TracerProvider
using var tracerProvider = Sdk.CreateTracerProviderBuilder()
.AddSource(AgentOpenTelemetryConsts.DefaultSourceName)
.AddConsoleExporter()
.Build();
// Create and wrap agent with telemetry
var baseAgent = new ChatClientAgent(chatClient, options);
using var telemetryAgent = baseAgent.WithOpenTelemetry();
// Use agent normally - telemetry is captured automatically
var response = await telemetryAgent.RunAsync(messages);
```
### Relationship to Microsoft.Extensions.AI
This implementation follows the exact patterns established by Microsoft.Extensions.AI's OpenTelemetry instrumentation, ensuring consistency across the AI ecosystem and leveraging proven patterns for telemetry integration.

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