mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Merge branch 'main' into dev/dotnet_workflow/fix_file_checkpointstore_paths
This commit is contained in:
Jacob Alber
GitHub
@@ -3,6 +3,7 @@
|
||||
"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"
|
||||
},
|
||||
|
||||
@@ -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.
|
||||
"""
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||||
|
||||
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 = (
|
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"@{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"
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||||
PINGED_LABEL = "requested-info"
|
||||
|
||||
|
||||
def get_team_members(g: Github, org: str, team_slug: str) -> set[str]:
|
||||
"""Fetch active team member usernames."""
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||||
try:
|
||||
org_obj = g.get_organization(org)
|
||||
team = org_obj.get_team_by_slug(team_slug)
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||||
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...")
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time.sleep(wait)
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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 = []
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||||
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()
|
||||
@@ -0,0 +1,297 @@
|
||||
# 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
|
||||
@@ -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@v6
|
||||
|
||||
- uses: actions/setup-python@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' }}
|
||||
@@ -0,0 +1,815 @@
|
||||
---
|
||||
status: accepted
|
||||
contact: bentho
|
||||
date: 2026-02-27
|
||||
deciders: bentho, markwallace-microsoft, westey-m
|
||||
consulted: Pratyush Mishra, Shivam Shrivastava, Manni Arora (Centrica eval scenario)
|
||||
informed: Agent Framework team, Foundry Evals team
|
||||
---
|
||||
|
||||
# Agent Evaluation Architecture with Azure AI Foundry Integration
|
||||
|
||||
## Context and Problem Statement
|
||||
|
||||
Azure AI Foundry provides a rich evaluation service for AI agents — built-in evaluators for agent behavior (task adherence, intent resolution), tool usage (tool call accuracy, tool selection), quality (coherence, fluency, relevance), and safety (violence, self-harm, prohibited actions). Results are viewable in the Foundry portal with dashboards and comparison views.
|
||||
|
||||
However, using Foundry Evals with an agent-framework agent today requires significant manual effort. Developers must:
|
||||
|
||||
1. Transform agent-framework's `Message`/`Content` types into the OpenAI-style agent message schema that Foundry evaluators expect
|
||||
2. Map tool definitions from agent-framework's `FunctionTool` format to evaluator-compatible schemas
|
||||
3. Manually wire up the correct Foundry data source type (`azure_ai_traces`, `jsonl`, `azure_ai_target_completions`, etc.) depending on their scenario
|
||||
4. Handle App Insights trace ID queries, response ID collection, and eval polling
|
||||
|
||||
Additionally, evaluation is a concern that extends beyond any single provider. Developers may want to use local evaluators (LLM-as-judge, regex, keyword matching), third-party evaluation libraries, or multiple providers in combination. The architecture must support this without creating a Foundry-specific lock-in at the API level.
|
||||
|
||||
### Functional Requirements for Agent Evaluation
|
||||
|
||||
- **Single agents and workflows.** Evaluate both individual agent responses and multi-agent workflow results, with per-agent breakdown to pinpoint underperformance.
|
||||
- **One-shot and multi-turn conversations.** Capture full conversation trajectories — including tool calls and results — not just final query/response pairs.
|
||||
- **Conversation factoring.** Support splitting conversations into query/response in multiple ways (last turn, full trajectory, per-turn) because different factorings measure different things.
|
||||
- **Multiple providers, mix and match.** Run Foundry LLM-as-judge evaluators alongside fast local checks and custom evaluators on the same data, without restructuring code.
|
||||
- **Third-party extensibility.** Any evaluation library can participate by implementing the `Evaluator` protocol (Python) or `IAgentEvaluator` interface (.NET). No predetermined list of supported libraries — the protocol is intentionally simple (`evaluate(items) → results`) so that wrappers for libraries like DeepEval, RAGAS, or Promptfoo are straightforward to write.
|
||||
- **Bring your own evaluator.** Creating a custom evaluator should be as simple as writing a function.
|
||||
- **Evaluate without re-running.** Evaluate existing responses from logs or previous runs without invoking the agent again.
|
||||
|
||||
## Decision Drivers
|
||||
|
||||
- **Zero-friction evaluation**: Developers should go from "I have an agent" to "I have eval results" with minimal code.
|
||||
- **Provider-agnostic API**: Core evaluation capabilities must not be tied to any specific provider. Provider configuration should be separate from the evaluation call.
|
||||
- **Lowest concept count**: Introduce the fewest possible new types, abstractions, and APIs for developers to learn.
|
||||
- **Leverage existing knowledge**: The framework already knows which agents exist, what tools they have, and what conversations occurred. Evals should use this automatically rather than requiring the developer to re-specify it.
|
||||
- **Foundry-native results**: When using Foundry, results should be viewable in the Foundry portal with dashboards and comparison views.
|
||||
- **Progressive disclosure**: Simple scenarios should be near-zero code. Advanced scenarios should build on the same primitives.
|
||||
- **Cross-language parity**: Design must be implementable in both Python and .NET.
|
||||
|
||||
## Considered Options
|
||||
|
||||
1. **Provider-specific functions** — Build Foundry-specific helper functions (`evaluate_agent()`, etc.) directly in the Azure package. All eval functions take Foundry connection parameters.
|
||||
2. **Evaluator protocol with shared orchestration** — Define a provider-agnostic `Evaluator` protocol in the base agent library (`agent_framework` in Python, `Microsoft.Agents.AI` in .NET). Orchestration functions live alongside it. Providers implement the protocol.
|
||||
3. **Full eval framework** — Build comprehensive eval infrastructure including custom evaluator definitions, scoring profiles, and reporting inside agent-framework.
|
||||
|
||||
## Decision Outcome
|
||||
|
||||
Proposed option: "Evaluator protocol with shared orchestration", because it delivers the low-friction developer experience, supports multiple providers without API changes, and keeps the concept count low.
|
||||
|
||||
### Usage Examples
|
||||
|
||||
#### Evaluate an agent
|
||||
|
||||
The agent is invoked once per query by default. For statistically meaningful evaluation, provide multiple diverse queries. For measuring **consistency** (does the same query produce reliable results?), use `num_repetitions` to run each query N times independently:
|
||||
|
||||
**Python:**
|
||||
|
||||
```python
|
||||
evals = FoundryEvals(
|
||||
project_client=client,
|
||||
model_deployment="gpt-4o",
|
||||
evaluators=[FoundryEvals.RELEVANCE, FoundryEvals.COHERENCE],
|
||||
)
|
||||
|
||||
results = await evaluate_agent(
|
||||
agent=my_agent,
|
||||
queries=[
|
||||
"What's the weather in Seattle?",
|
||||
"Plan a weekend trip to Portland",
|
||||
"What restaurants are near Pike Place?",
|
||||
],
|
||||
evaluators=evals,
|
||||
)
|
||||
for r in results:
|
||||
r.assert_passed()
|
||||
```
|
||||
|
||||
**C#:**
|
||||
|
||||
```csharp
|
||||
var evals = new FoundryEvals(chatConfiguration, FoundryEvals.Relevance, FoundryEvals.Coherence);
|
||||
|
||||
AgentEvaluationResults results = await agent.EvaluateAsync(
|
||||
new[] {
|
||||
"What's the weather in Seattle?",
|
||||
"Plan a weekend trip to Portland",
|
||||
"What restaurants are near Pike Place?",
|
||||
},
|
||||
evals);
|
||||
|
||||
results.AssertAllPassed();
|
||||
```
|
||||
|
||||
`evaluate_agent` returns one `EvalResults` per evaluator. Each result contains per-item scores with the evaluated response for auditing:
|
||||
|
||||
```
|
||||
# results[0] (FoundryEvals)
|
||||
EvalResults(status="completed", passed=3, failed=0, total=3)
|
||||
items[0]: EvalItemResult(
|
||||
query="What's the weather in Seattle?",
|
||||
response="It's currently 72°F and sunny in Seattle.",
|
||||
scores={"relevance": 5, "coherence": 5})
|
||||
items[1]: EvalItemResult(
|
||||
query="Plan a weekend trip to Portland",
|
||||
response="Here's a 2-day Portland itinerary...",
|
||||
scores={"relevance": 4, "coherence": 5})
|
||||
items[2]: EvalItemResult(
|
||||
query="What restaurants are near Pike Place?",
|
||||
response="Top restaurants near Pike Place Market: ...",
|
||||
scores={"relevance": 5, "coherence": 4})
|
||||
```
|
||||
|
||||
#### Measure consistency with repetitions
|
||||
|
||||
Run each query multiple times to detect non-deterministic behavior:
|
||||
|
||||
**Python:**
|
||||
|
||||
```python
|
||||
results = await evaluate_agent(
|
||||
agent=my_agent,
|
||||
queries=["What's the weather in Seattle?"],
|
||||
evaluators=evals,
|
||||
num_repetitions=3, # each query runs 3 times independently
|
||||
)
|
||||
# results contain 3 items (1 query × 3 repetitions)
|
||||
```
|
||||
|
||||
**C#:**
|
||||
|
||||
```csharp
|
||||
AgentEvaluationResults results = await agent.EvaluateAsync(
|
||||
new[] { "What's the weather in Seattle?" },
|
||||
evals,
|
||||
numRepetitions: 3); // each query runs 3 times independently
|
||||
// results contain 3 items (1 query × 3 repetitions)
|
||||
```
|
||||
|
||||
#### Evaluate a response you already have
|
||||
|
||||
When you already have agent responses, pass them directly to skip re-running the agent. Each query is paired with its corresponding response:
|
||||
|
||||
**Python:**
|
||||
|
||||
```python
|
||||
queries = ["What's the weather?", "What's the capital of France?"]
|
||||
responses = [await agent.run([Message("user", [q])]) for q in queries]
|
||||
|
||||
results = await evaluate_agent(
|
||||
responses=responses,
|
||||
evaluators=evals,
|
||||
)
|
||||
```
|
||||
|
||||
**C#:**
|
||||
|
||||
```csharp
|
||||
var queries = new[] { "What's the weather?" };
|
||||
var responses = new List<AgentResponse>();
|
||||
foreach (var q in queries)
|
||||
responses.Add(await agent.RunAsync(new[] { new ChatMessage(ChatRole.User, q) }));
|
||||
|
||||
AgentEvaluationResults results = await agent.EvaluateAsync(
|
||||
responses: responses,
|
||||
evals);
|
||||
```
|
||||
|
||||
Each `AgentResponse` already contains the conversation (query + response), so the evaluator extracts query/response from the conversation. When you pass `responses` without `queries`, the conversation is the source of truth.
|
||||
|
||||
#### Evaluate with conversation split strategies
|
||||
|
||||
By default, evaluators see only the last turn (final user message → final assistant response). For multi-turn conversations, you can control how the conversation is factored for evaluation:
|
||||
|
||||
**Python:**
|
||||
|
||||
```python
|
||||
results = await evaluate_agent(
|
||||
agent=agent,
|
||||
queries=["Plan a 3-day trip to Paris"],
|
||||
evaluators=evals,
|
||||
conversation_split=ConversationSplit.FULL, # evaluate entire trajectory
|
||||
)
|
||||
|
||||
# Or per-turn: each user→assistant exchange scored independently
|
||||
results = await evaluate_agent(
|
||||
agent=agent,
|
||||
queries=["Plan a 3-day trip to Paris"],
|
||||
evaluators=evals,
|
||||
conversation_split=ConversationSplit.PER_TURN,
|
||||
)
|
||||
```
|
||||
|
||||
**C#:**
|
||||
|
||||
```csharp
|
||||
// Full conversation as context
|
||||
AgentEvaluationResults results = await agent.EvaluateAsync(
|
||||
new[] { "Plan a 3-day trip to Paris" },
|
||||
evals,
|
||||
splitter: ConversationSplitters.Full);
|
||||
|
||||
// Per-turn splitting
|
||||
var items = EvalItem.PerTurnItems(conversation); // one EvalItem per user turn
|
||||
var results = await evals.EvaluateAsync(items);
|
||||
```
|
||||
|
||||
With `PER_TURN`, a 3-turn conversation produces 3 scored items:
|
||||
|
||||
```
|
||||
EvalResults(status="completed", passed=3, failed=0, total=3)
|
||||
items[0]: query="Plan a 3-day trip to Paris" scores={"relevance": 5}
|
||||
items[1]: query="What about restaurants?" scores={"relevance": 4}
|
||||
items[2]: query="Make it budget-friendly" scores={"relevance": 5}
|
||||
```
|
||||
|
||||
#### Evaluate a multi-agent workflow
|
||||
|
||||
**Python:**
|
||||
|
||||
```python
|
||||
result = await workflow.run("Plan a trip to Paris")
|
||||
eval_results = await evaluate_workflow(
|
||||
workflow=workflow,
|
||||
workflow_result=result,
|
||||
evaluators=evals,
|
||||
)
|
||||
|
||||
for r in eval_results:
|
||||
print(f" overall: {r.passed}/{r.total}")
|
||||
for name, sub in r.sub_results.items():
|
||||
print(f" {name}: {sub.passed}/{sub.total}")
|
||||
```
|
||||
|
||||
**C#:**
|
||||
|
||||
```csharp
|
||||
WorkflowRunResult result = await workflow.RunAsync("Plan a trip to Paris");
|
||||
|
||||
IReadOnlyList<AgentEvaluationResults> evalResults = await result.EvaluateAsync(evals);
|
||||
|
||||
foreach (var r in evalResults)
|
||||
{
|
||||
Console.WriteLine($" overall: {r.Passed}/{r.Total}");
|
||||
foreach (var (name, sub) in r.SubResults)
|
||||
Console.WriteLine($" {name}: {sub.Passed}/{sub.Total}");
|
||||
}
|
||||
```
|
||||
|
||||
Workflows return one result per evaluator, with sub-results per agent in the workflow:
|
||||
|
||||
```
|
||||
EvalResults(status="completed", passed=2, failed=0, total=2)
|
||||
sub_results:
|
||||
"planner": EvalResults(passed=1, total=1)
|
||||
"researcher": EvalResults(passed=1, total=1)
|
||||
```
|
||||
|
||||
#### Mix multiple providers
|
||||
|
||||
**Python:**
|
||||
|
||||
```python
|
||||
@evaluator
|
||||
def is_helpful(response: str) -> bool:
|
||||
return len(response.split()) > 10
|
||||
|
||||
foundry = FoundryEvals(
|
||||
project_client=client,
|
||||
model_deployment="gpt-4o",
|
||||
evaluators=[FoundryEvals.RELEVANCE, FoundryEvals.COHERENCE],
|
||||
)
|
||||
|
||||
results = await evaluate_agent(
|
||||
agent=agent,
|
||||
queries=queries,
|
||||
evaluators=[is_helpful, keyword_check("weather"), foundry],
|
||||
)
|
||||
```
|
||||
|
||||
**C#:**
|
||||
|
||||
```csharp
|
||||
IReadOnlyList<AgentEvaluationResults> results = await agent.EvaluateAsync(
|
||||
queries,
|
||||
evaluators: new IAgentEvaluator[]
|
||||
{
|
||||
new LocalEvaluator(
|
||||
EvalChecks.KeywordCheck("weather"),
|
||||
FunctionEvaluator.Create("is_helpful", (string r) => r.Split(' ').Length > 10)),
|
||||
new FoundryEvals(chatConfiguration, FoundryEvals.Relevance, FoundryEvals.Coherence),
|
||||
});
|
||||
```
|
||||
|
||||
Multiple evaluators return one result each — `results[0]` is the local evaluator, `results[1]` is Foundry.
|
||||
|
||||
#### Custom function evaluators
|
||||
|
||||
**Python:**
|
||||
|
||||
```python
|
||||
@evaluator
|
||||
def mentions_city(response: str, expected_output: str) -> bool:
|
||||
return expected_output.lower() in response.lower()
|
||||
|
||||
@evaluator
|
||||
def used_tools(conversation: list, tools: list) -> float:
|
||||
# ... scoring logic
|
||||
return score
|
||||
|
||||
local = LocalEvaluator(mentions_city, used_tools)
|
||||
```
|
||||
|
||||
`@evaluator` uses **parameter name injection** — the function's parameter names determine what data it receives from the `EvalItem`. Supported names: `query`, `response`, `expected`, `expected_tool_calls`, `conversation`, `tools`, `context`. Any combination is valid.
|
||||
|
||||
**C#:**
|
||||
|
||||
```csharp
|
||||
var local = new LocalEvaluator(
|
||||
FunctionEvaluator.Create("mentions_city",
|
||||
(EvalItem item) => item.ExpectedOutput != null
|
||||
&& item.Response.Contains(item.ExpectedOutput, StringComparison.OrdinalIgnoreCase)),
|
||||
FunctionEvaluator.Create("is_concise",
|
||||
(string response) => response.Split(' ').Length < 500));
|
||||
```
|
||||
|
||||
## What To Build
|
||||
|
||||
### Core: Evaluator Protocol
|
||||
|
||||
A runtime-checkable protocol that any evaluation provider implements:
|
||||
|
||||
```python
|
||||
@runtime_checkable
|
||||
class Evaluator(Protocol):
|
||||
name: str
|
||||
|
||||
async def evaluate(
|
||||
self, items: Sequence[EvalItem], *, eval_name: str = "Agent Framework Eval"
|
||||
) -> EvalResults: ...
|
||||
```
|
||||
|
||||
The protocol is minimal — just `name` and `evaluate()`.
|
||||
|
||||
### Core: EvalItem
|
||||
|
||||
Provider-agnostic data format for items to evaluate:
|
||||
|
||||
```python
|
||||
@dataclass
|
||||
class ExpectedToolCall:
|
||||
name: str # Tool/function name
|
||||
arguments: dict[str, Any] | None = None # None = don't check args
|
||||
|
||||
@dataclass
|
||||
class EvalItem:
|
||||
conversation: list[Message] # Single source of truth
|
||||
tools: list[FunctionTool] | None = None # Agent's available tools
|
||||
context: str | None = None
|
||||
expected_output: str | None = None # Ground-truth for comparison
|
||||
expected_tool_calls: list[ExpectedToolCall] | None = None
|
||||
split_strategy: ConversationSplitter | None = None
|
||||
|
||||
query: str # property — derived from conversation split
|
||||
response: str # property — derived from conversation split
|
||||
```
|
||||
|
||||
`conversation` is the single source of truth. `query` and `response` are derived properties — splitting the conversation at the last user message (default) and extracting text from each side. Changing the `split_strategy` consistently changes all derived values.
|
||||
|
||||
`tools` provides typed `FunctionTool` objects — including MCP tools, which are automatically extracted after agent runs.
|
||||
|
||||
### Internal: AgentEvalConverter
|
||||
|
||||
Internal class that converts agent-framework types to `EvalItem`. Used by `evaluate_agent()` and `evaluate_workflow()` — not part of the public API:
|
||||
|
||||
| Agent Framework | Eval Format |
|
||||
|---|---|
|
||||
| `Content.function_call` | `tool_call` in OpenAI chat format |
|
||||
| `Content.function_result` | `tool_result` in OpenAI chat format |
|
||||
| `FunctionTool` | `{name, description, parameters}` schema |
|
||||
| `Message` history | `conversation` list + `query`/`response` extraction |
|
||||
|
||||
### Core: EvalResults
|
||||
|
||||
Rich result type with convenience properties for CI integration:
|
||||
|
||||
```python
|
||||
results.all_passed # bool: no failures or errors (recursive for workflow)
|
||||
results.passed # int: passing count
|
||||
results.failed # int: failure count
|
||||
results.total # int: total = passed + failed + errored
|
||||
results.items # list[EvalItemResult]: per-item detail with query, response, and scores
|
||||
results.error # str | None: error details on failure
|
||||
results.sub_results # dict: per-agent breakdown (workflow evals)
|
||||
results.report_url # str | None: portal link (Foundry)
|
||||
results.assert_passed() # raises AssertionError with details
|
||||
```
|
||||
|
||||
### Core: Orchestration Functions
|
||||
|
||||
Provider-agnostic functions that extract data and delegate to evaluators:
|
||||
|
||||
| Function | What it does |
|
||||
|---|---|
|
||||
| `evaluate_agent()` | Runs agent against test queries (or evaluates pre-existing `responses=`), converts to `EvalItem`s, passes to evaluator. Accepts optional `expected_output=` for ground-truth comparison, `expected_tool_calls=` for tool-correctness evaluation, and `num_repetitions=` for consistency measurement |
|
||||
| `evaluate_workflow()` | Extracts per-agent data from `WorkflowRunResult`, evaluates each agent and overall output. Per-agent breakdown in `sub_results`. Also accepts `num_repetitions=` |
|
||||
|
||||
### Core: Conversation Split Strategies
|
||||
|
||||
Multi-turn conversations must be split into query (input) and response (output) halves for evaluation. How you split determines *what you're evaluating*:
|
||||
|
||||
**Last-turn split** — split at the last user message. Everything up to and including it is the query context; the agent's subsequent actions are the response:
|
||||
|
||||
```
|
||||
conversation: user1 → assistant1 → user2 → assistant2(tool) → tool_result → assistant3
|
||||
query_messages: [user1, assistant1, user2]
|
||||
response_messages: [assistant2(tool), tool_result, assistant3]
|
||||
```
|
||||
|
||||
This evaluates: "Given all the context so far, did the agent answer the latest question well?" Best for response quality at a specific point in the conversation.
|
||||
|
||||
**Full-conversation split** — the first user message is the query; everything after is the response:
|
||||
|
||||
```
|
||||
query_messages: [user1]
|
||||
response_messages: [assistant1, user2, assistant2(tool), tool_result, assistant3]
|
||||
```
|
||||
|
||||
This evaluates: "Given the original request, did the entire conversation trajectory serve the user?" Best for task completion and overall conversation quality.
|
||||
|
||||
**Per-turn split** — produces N eval items from an N-turn conversation. Each turn is evaluated with its cumulative context:
|
||||
|
||||
```
|
||||
item 1: query = [user1], response = [assistant1]
|
||||
item 2: query = [user1, assistant1, user2], response = [assistant2(tool), tool_result, assistant3]
|
||||
```
|
||||
|
||||
This evaluates each response independently. Best for fine-grained analysis and pinpointing where a conversation goes wrong.
|
||||
|
||||
These factorings produce different scores for the same conversation. The framework ships all three as built-in strategies, defaulting to last-turn. Developers can also provide a custom splitter — a function (Python) or `IConversationSplitter` implementation (.NET) — and override the strategy at the call site or per evaluator.
|
||||
|
||||
### Azure AI: FoundryEvals
|
||||
|
||||
`Evaluator` implementation backed by Azure AI Foundry:
|
||||
|
||||
```python
|
||||
class FoundryEvals:
|
||||
def __init__(self, *, project_client=None, openai_client=None,
|
||||
model_deployment: str, evaluators=None, ...)
|
||||
async def evaluate(self, items, *, eval_name) -> EvalResults
|
||||
```
|
||||
|
||||
**Smart auto-detection in `evaluate()`:**
|
||||
- Default evaluators: relevance, coherence, task_adherence
|
||||
- Auto-adds `tool_call_accuracy` when items have tools/`tool_definitions`
|
||||
- Filters out tool evaluators for items without tools
|
||||
|
||||
### Azure AI: FoundryEvals Constants
|
||||
|
||||
```python
|
||||
from agent_framework_azure_ai import FoundryEvals
|
||||
|
||||
evaluators = [FoundryEvals.RELEVANCE, FoundryEvals.TOOL_CALL_ACCURACY]
|
||||
```
|
||||
|
||||
Categories: Agent behavior, Tool usage, Quality, Safety.
|
||||
|
||||
### Azure AI: Foundry-Specific Functions
|
||||
|
||||
| Function | What it does |
|
||||
|---|---|
|
||||
| `evaluate_traces()` | Evaluate from stored response IDs or OTel traces |
|
||||
| `evaluate_foundry_target()` | Evaluate a Foundry-registered agent or deployment |
|
||||
|
||||
### Core: LocalEvaluator and Function Evaluators
|
||||
|
||||
`LocalEvaluator` implements the `Evaluator` protocol for fast, API-free evaluation. It runs check functions locally — useful for inner-loop development, CI smoke tests, and combining with cloud-based evaluators.
|
||||
|
||||
Built-in checks:
|
||||
- `keyword_check(*keywords)` — response must contain specified keywords
|
||||
- `tool_called_check(*tool_names)` — agent must have called specified tools
|
||||
- `tool_calls_present` — all `expected_tool_calls` names appear in conversation (unordered, extras OK)
|
||||
- `tool_call_args_match` — expected tool calls match on name + arguments (subset match on args)
|
||||
|
||||
Custom function evaluators use `@evaluator` to wrap plain Python functions. The function's **parameter names** determine what data it receives from the `EvalItem`:
|
||||
|
||||
```python
|
||||
from agent_framework import evaluator, LocalEvaluator
|
||||
|
||||
# Tier 1: Simple check — just query + response
|
||||
@evaluator
|
||||
def is_concise(response: str) -> bool:
|
||||
return len(response.split()) < 500
|
||||
|
||||
# Tier 2: Ground truth — compare against expected output
|
||||
@evaluator
|
||||
def mentions_city(response: str, expected_output: str) -> bool:
|
||||
return expected_output.lower() in response.lower()
|
||||
|
||||
# Tier 3: Full context — inspect conversation and tools
|
||||
@evaluator
|
||||
def used_tools(conversation: list, tools: list) -> float:
|
||||
# ... scoring logic
|
||||
return score
|
||||
|
||||
local = LocalEvaluator(is_concise, mentions_city, used_tools)
|
||||
```
|
||||
|
||||
Supported parameters: `query`, `response`, `expected`, `expected_tool_calls`, `conversation`, `tools`, `context`.
|
||||
Return types: `bool`, `float` (≥0.5 = pass), `dict` with `score` or `passed` key, or `CheckResult`.
|
||||
|
||||
Async functions are handled automatically — `@evaluator` detects `async def` and produces the right wrapper.
|
||||
|
||||
### Example: GAIA Benchmark
|
||||
|
||||
[GAIA](https://huggingface.co/gaia-benchmark) tests real-world multi-step tasks with known expected answers. Each task has a question and a ground-truth answer, with optional file attachments. The framework accommodates GAIA's knobs (difficulty levels, file inputs, multi-step tool use) through the existing `EvalItem` fields:
|
||||
|
||||
```python
|
||||
from datasets import load_dataset
|
||||
from agent_framework import evaluate_agent, evaluator, LocalEvaluator
|
||||
|
||||
gaia = load_dataset("gaia-benchmark/GAIA", "2023_level1", split="test")
|
||||
|
||||
@evaluator
|
||||
def exact_match(response: str, expected_output: str) -> bool:
|
||||
return expected_output.strip().lower() in response.strip().lower()
|
||||
|
||||
# Simple path — evaluate_agent handles running + expected_output stamping
|
||||
results = await evaluate_agent(
|
||||
agent=agent,
|
||||
queries=[task["Question"] for task in gaia],
|
||||
expected_output=[task["Final answer"] for task in gaia],
|
||||
evaluators=LocalEvaluator(exact_match),
|
||||
)
|
||||
```
|
||||
|
||||
### Package Location
|
||||
|
||||
- Core types and orchestration: `agent_framework._eval`, `agent_framework._local_eval` (Python), `Microsoft.Agents.AI` (.NET)
|
||||
- Foundry provider: `agent_framework_azure_ai._foundry_evals` (Python), `Microsoft.Agents.AI.AzureAI` (.NET)
|
||||
- Azure-AI re-exports core types for convenience (Python)
|
||||
|
||||
## Known Limitations
|
||||
|
||||
1. **Tool evaluators require query + agent**: Tool evaluators need tool definition schemas. When using these evaluators with `evaluate_agent(responses=...)`, provide `queries=` and pass an agent with tool definitions.
|
||||
2. **`model_deployment` always required**: Could potentially be inferred from the Foundry project configuration.
|
||||
|
||||
## Open Questions
|
||||
|
||||
1. **Red teaming non-registered agents**: Requires Foundry API support for callback-based flows.
|
||||
2. **Datasets with expected outputs**: A dataset abstraction for pre-populating `expected_output` values across eval runs is a natural next step but not yet designed.
|
||||
3. **Multi-modal evaluation**: The `conversation` field on `EvalItem` already stores full `Message`/`Content` (Python) and `ChatMessage` (.NET) objects, which can represent multi-modal content (images, audio, structured data). Evaluators that accept the full `EvalItem` or `conversation` parameter can access this content today. However, the convenience shortcuts — `query`/`response` string projections and the `FunctionEvaluator` string overloads — are text-only. Multi-modal-aware evaluators should use the full-item path (`Func<EvalItem, CheckResult>` in .NET, `conversation: list` parameter in Python).
|
||||
|
||||
## .NET Implementation Design
|
||||
|
||||
### Key Difference: MEAI Ecosystem
|
||||
|
||||
Unlike Python, the .NET ecosystem already has `Microsoft.Extensions.AI.Evaluation` (v10.3.0) providing:
|
||||
|
||||
- `IEvaluator` — per-item evaluation of `(messages, chatResponse) → EvaluationResult`
|
||||
- `CompositeEvaluator` — combines multiple evaluators
|
||||
- Quality evaluators — `RelevanceEvaluator`, `CoherenceEvaluator`, `GroundednessEvaluator`
|
||||
- Safety evaluators — `ContentHarmEvaluator`, `ProtectedMaterialEvaluator`
|
||||
- Metric types — `NumericMetric`, `BooleanMetric`, `StringMetric`
|
||||
|
||||
The .NET integration uses MEAI's `IEvaluator` directly — no new evaluator interface. Our contribution is the **orchestration layer**: extension methods that run agents, extract data, call `IEvaluator` per item, and aggregate results.
|
||||
|
||||
### Architecture
|
||||
|
||||
```
|
||||
┌──────────────────────────────────────────────────────────────┐
|
||||
│ Developer Code │
|
||||
│ agent.EvaluateAsync(queries, evaluator) │
|
||||
│ run.EvaluateAsync(evaluator) │
|
||||
└────────────────┬─────────────────────────────────────────────┘
|
||||
│
|
||||
┌────────────────▼─────────────────────────────────────────────┐
|
||||
│ Orchestration Layer (Microsoft.Agents.AI) │
|
||||
│ AgentEvaluationExtensions — runs agents, extracts data, │
|
||||
│ calls IEvaluator per item, aggregates into │
|
||||
│ AgentEvaluationResults │
|
||||
└────────────────┬─────────────────────────────────────────────┘
|
||||
│ IEvaluator (MEAI)
|
||||
│
|
||||
┌───────────┼────────────┐
|
||||
│ │ │
|
||||
┌───▼───-┐ ┌───▼────┐ ┌────▼──────────┐
|
||||
│ MEAI │ │ Local │ │ Foundry │
|
||||
│ Quality│ │ Checks │ │ (cloud batch) │
|
||||
│ Safety │ │ Lambdas│ │ │
|
||||
└────────┘ └────────┘ └───────────────┘
|
||||
```
|
||||
|
||||
All evaluators implement MEAI's `IEvaluator`. The orchestration layer doesn't need to know which kind — it calls `EvaluateAsync(messages, chatResponse)` per item on all of them. `FoundryEvals` handles batching internally (buffers items, submits once, returns per-item results).
|
||||
|
||||
### .NET Core Types
|
||||
|
||||
**No new evaluator interface.** Use MEAI's `IEvaluator` directly.
|
||||
|
||||
**`AgentEvaluationResults`** — The only new type. Aggregates per-item MEAI `EvaluationResult`s across a batch of queries:
|
||||
|
||||
```csharp
|
||||
public class AgentEvaluationResults
|
||||
{
|
||||
public string Provider { get; init; }
|
||||
public string? ReportUrl { get; init; }
|
||||
|
||||
// Per-item — standard MEAI EvaluationResult, unchanged
|
||||
public IReadOnlyList<EvaluationResult> Items { get; init; }
|
||||
|
||||
// Aggregate pass/fail derived from metric interpretations
|
||||
public int Passed { get; }
|
||||
public int Failed { get; }
|
||||
public int Total { get; }
|
||||
public bool AllPassed { get; }
|
||||
|
||||
// Workflow: per-agent breakdown
|
||||
public IReadOnlyDictionary<string, AgentEvaluationResults>? SubResults { get; init; }
|
||||
|
||||
public void AssertAllPassed(string? message = null);
|
||||
}
|
||||
```
|
||||
|
||||
### .NET Evaluator Implementations
|
||||
|
||||
All implement MEAI's `IEvaluator`:
|
||||
|
||||
**`LocalEvaluator`** — Runs lambda checks locally, returns `BooleanMetric` per check:
|
||||
|
||||
```csharp
|
||||
var local = new LocalEvaluator(
|
||||
FunctionEvaluator.Create("is_concise",
|
||||
(string response) => response.Split().Length < 500),
|
||||
EvalChecks.KeywordCheck("weather"),
|
||||
EvalChecks.ToolCalledCheck("get_weather"));
|
||||
```
|
||||
|
||||
**MEAI evaluators** — Used directly, no adapter needed:
|
||||
|
||||
```csharp
|
||||
var quality = new CompositeEvaluator(
|
||||
new RelevanceEvaluator(),
|
||||
new CoherenceEvaluator());
|
||||
```
|
||||
|
||||
**`FoundryEvals`** — Implements `IEvaluator` but batches internally. On first call, buffers the item. On the last item (or when explicitly flushed), submits the batch to Foundry and distributes per-item results:
|
||||
|
||||
```csharp
|
||||
var foundry = new FoundryEvals(projectClient, "gpt-4o");
|
||||
```
|
||||
|
||||
### .NET Orchestration: Extension Methods
|
||||
|
||||
```csharp
|
||||
public static class AgentEvaluationExtensions
|
||||
{
|
||||
// Evaluate an agent against test queries
|
||||
public static Task<AgentEvaluationResults> EvaluateAsync(
|
||||
this AIAgent agent,
|
||||
IEnumerable<string> queries,
|
||||
IEvaluator evaluator,
|
||||
ChatConfiguration? chatConfiguration = null,
|
||||
IEnumerable<string>? expectedOutput = null,
|
||||
CancellationToken cancellationToken = default);
|
||||
|
||||
// Evaluate pre-existing responses (without re-running the agent)
|
||||
public static Task<AgentEvaluationResults> EvaluateAsync(
|
||||
this AIAgent agent,
|
||||
AgentResponse responses,
|
||||
IEvaluator evaluator,
|
||||
IEnumerable<string>? queries = null,
|
||||
ChatConfiguration? chatConfiguration = null,
|
||||
IEnumerable<string>? expectedOutput = null,
|
||||
CancellationToken cancellationToken = default);
|
||||
|
||||
// Evaluate with multiple evaluators (one result per evaluator)
|
||||
public static Task<IReadOnlyList<AgentEvaluationResults>> EvaluateAsync(
|
||||
this AIAgent agent,
|
||||
IEnumerable<string> queries,
|
||||
IEnumerable<IEvaluator> evaluators,
|
||||
ChatConfiguration? chatConfiguration = null,
|
||||
IEnumerable<string>? expectedOutput = null,
|
||||
CancellationToken cancellationToken = default);
|
||||
|
||||
// Evaluate a workflow run with per-agent breakdown
|
||||
public static Task<AgentEvaluationResults> EvaluateAsync(
|
||||
this Run run,
|
||||
IEvaluator evaluator,
|
||||
ChatConfiguration? chatConfiguration = null,
|
||||
bool includeOverall = true,
|
||||
bool includePerAgent = true,
|
||||
CancellationToken cancellationToken = default);
|
||||
}
|
||||
```
|
||||
|
||||
**Usage:**
|
||||
|
||||
```csharp
|
||||
// MEAI evaluators — just works
|
||||
var results = await agent.EvaluateAsync(
|
||||
queries: ["What's the weather?"],
|
||||
evaluator: new RelevanceEvaluator(),
|
||||
chatConfiguration: new ChatConfiguration(evalClient));
|
||||
|
||||
// Local checks
|
||||
var results = await agent.EvaluateAsync(
|
||||
queries: ["What's the weather?"],
|
||||
evaluator: new LocalEvaluator(
|
||||
EvalChecks.KeywordCheck("weather")));
|
||||
|
||||
// Foundry cloud
|
||||
var results = await agent.EvaluateAsync(
|
||||
queries: ["What's the weather?"],
|
||||
evaluator: new FoundryEvals(projectClient, "gpt-4o"));
|
||||
|
||||
// Evaluate existing response (without re-running the agent)
|
||||
var response = await agent.RunAsync("What's the weather?");
|
||||
var results = await agent.EvaluateAsync(
|
||||
responses: response,
|
||||
queries: ["What's the weather?"],
|
||||
evaluator: new FoundryEvals(projectClient, "gpt-4o"));
|
||||
|
||||
// Mixed — one result per evaluator
|
||||
var results = await agent.EvaluateAsync(
|
||||
queries: ["What's the weather?"],
|
||||
evaluators: [
|
||||
new LocalEvaluator(EvalChecks.KeywordCheck("weather")),
|
||||
new RelevanceEvaluator(),
|
||||
new FoundryEvals(projectClient, "gpt-4o")
|
||||
],
|
||||
chatConfiguration: new ChatConfiguration(evalClient));
|
||||
|
||||
// Workflow with per-agent breakdown
|
||||
Run run = await workflowRunner.RunAsync(workflow, "Plan a trip");
|
||||
var results = await run.EvaluateAsync(
|
||||
evaluator: new FoundryEvals(projectClient, "gpt-4o"));
|
||||
```
|
||||
|
||||
### .NET Function Evaluators
|
||||
|
||||
Typed factory overloads (C# equivalent of Python's `@evaluator`):
|
||||
|
||||
```csharp
|
||||
public static class FunctionEvaluator
|
||||
{
|
||||
public static EvalCheck Create(string name, Func<string, bool> check); // response only
|
||||
public static EvalCheck Create(string name, Func<string, string?, bool> check); // expectedOutput
|
||||
public static EvalCheck Create(string name, Func<EvalItem, bool> check); // full item
|
||||
public static EvalCheck Create(string name, Func<EvalItem, CheckResult> check); // full control
|
||||
public static EvalCheck Create(string name, Func<string, Task<bool>> check); // async
|
||||
}
|
||||
```
|
||||
|
||||
`EvalItem` is a lightweight record used only by `FunctionEvaluator` and `LocalEvaluator` to pass context to check functions. It is not part of the `IEvaluator` interface:
|
||||
|
||||
```csharp
|
||||
public record ExpectedToolCall(string Name, IReadOnlyDictionary<string, object>? Arguments = null);
|
||||
|
||||
public sealed class EvalItem
|
||||
{
|
||||
public EvalItem(string query, string response, IReadOnlyList<ChatMessage> conversation);
|
||||
|
||||
public string Query { get; }
|
||||
public string Response { get; }
|
||||
public IReadOnlyList<ChatMessage> Conversation { get; }
|
||||
public IReadOnlyList<AITool>? Tools { get; set; }
|
||||
public string? ExpectedOutput { get; set; }
|
||||
public IReadOnlyList<ExpectedToolCall>? ExpectedToolCalls { get; set; }
|
||||
public string? Context { get; set; }
|
||||
public IConversationSplitter? Splitter { get; set; }
|
||||
}
|
||||
```
|
||||
|
||||
### Workflow Data Extraction (.NET)
|
||||
|
||||
`run.EvaluateAsync()` walks `Run.OutgoingEvents` via LINQ:
|
||||
|
||||
1. Pair `ExecutorInvokedEvent` / `ExecutorCompletedEvent` by `ExecutorId`
|
||||
2. Extract `AgentResponseEvent` for per-agent `ChatResponse`
|
||||
3. Call `evaluator.EvaluateAsync()` per invocation
|
||||
4. Group by `ExecutorId` for per-agent `SubResults`
|
||||
5. Use final workflow output for overall eval
|
||||
|
||||
### .NET Package Structure
|
||||
|
||||
| Package | Contents |
|
||||
|---------|----------|
|
||||
| `Microsoft.Agents.AI` | `IAgentEvaluator`, `AgentEvaluationResults`, `LocalEvaluator`, `FunctionEvaluator`, `EvalChecks`, `EvalItem`, `ExpectedToolCall`, `AgentEvaluationExtensions` |
|
||||
| `Microsoft.Agents.AI.AzureAI` | `FoundryEvals` (provider + constants) |
|
||||
|
||||
### Python ↔ .NET Mapping
|
||||
|
||||
| Python | .NET |
|
||||
|--------|------|
|
||||
| `Evaluator` protocol | `IAgentEvaluator` (our interface; MEAI provides `IEvaluator` for per-item scoring) |
|
||||
| `EvalItem` dataclass | `EvalItem` class |
|
||||
| `EvalResults` | `AgentEvaluationResults` |
|
||||
| `EvalItemResult` / `EvalScoreResult` | MEAI `EvaluationResult` / `EvaluationMetric` (reused) |
|
||||
| `LocalEvaluator` | `LocalEvaluator` (implements `IAgentEvaluator`) |
|
||||
| `@evaluator` | `FunctionEvaluator.Create()` overloads |
|
||||
| `keyword_check()` / `tool_called_check()` | `EvalChecks.KeywordCheck()` / `EvalChecks.ToolCalledCheck()` |
|
||||
| `tool_calls_present` / `tool_call_args_match` | (custom `FunctionEvaluator` — same pattern) |
|
||||
| `ExpectedToolCall` dataclass | `ExpectedToolCall` record |
|
||||
| `FoundryEvals` | `FoundryEvals` (implements `IAgentEvaluator`, includes evaluator name constants) |
|
||||
| `evaluate_agent()` | `agent.EvaluateAsync(queries, evaluator)` extension method |
|
||||
| `evaluate_agent(responses=)` | `agent.EvaluateAsync(responses, evaluator)` extension method |
|
||||
| `evaluate_workflow()` | `run.EvaluateAsync()` extension method |
|
||||
|
||||
## More Information
|
||||
|
||||
- [Foundry Evals documentation](https://learn.microsoft.com/azure/ai-foundry/concepts/evaluation-approach-gen-ai) — Azure AI Foundry evaluation overview
|
||||
@@ -19,11 +19,10 @@
|
||||
<PackageVersion Include="Aspire.Microsoft.Azure.Cosmos" Version="$(AspireAppHostSdkVersion)" />
|
||||
<PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="13.0.0" />
|
||||
<!-- Azure.* -->
|
||||
<PackageVersion Include="Azure.AI.Projects" Version="2.0.0-beta.1" />
|
||||
<PackageVersion Include="Azure.AI.Projects.OpenAI" Version="2.0.0-beta.1" />
|
||||
<PackageVersion Include="Azure.AI.Agents.Persistent" Version="1.2.0-beta.8" />
|
||||
<PackageVersion Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
|
||||
<PackageVersion Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageVersion Include="Azure.AI.Projects" Version="2.0.0-beta.2" />
|
||||
<PackageVersion Include="Azure.AI.Agents.Persistent" Version="1.2.0-beta.10" />
|
||||
<PackageVersion Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageVersion Include="Azure.Identity" Version="1.19.0" />
|
||||
<PackageVersion Include="Azure.Monitor.OpenTelemetry.Exporter" Version="1.4.0" />
|
||||
<!-- Google Gemini -->
|
||||
<PackageVersion Include="Google.GenAI" Version="0.11.0" />
|
||||
@@ -40,12 +39,12 @@
|
||||
<PackageVersion Include="System.CodeDom" Version="10.0.0" />
|
||||
<PackageVersion Include="System.Collections.Immutable" Version="10.0.1" />
|
||||
<PackageVersion Include="System.CommandLine" Version="2.0.0-rc.2.25502.107" />
|
||||
<PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.3" />
|
||||
<PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.4" />
|
||||
<PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.4" />
|
||||
<PackageVersion Include="System.Net.Http.Json" Version="10.0.0" />
|
||||
<PackageVersion Include="System.Net.ServerSentEvents" Version="10.0.3" />
|
||||
<PackageVersion Include="System.Text.Json" Version="10.0.3" />
|
||||
<PackageVersion Include="System.Threading.Channels" Version="10.0.3" />
|
||||
<PackageVersion Include="System.Net.ServerSentEvents" Version="10.0.4" />
|
||||
<PackageVersion Include="System.Text.Json" Version="10.0.4" />
|
||||
<PackageVersion Include="System.Threading.Channels" Version="10.0.4" />
|
||||
<PackageVersion Include="System.Threading.Tasks.Extensions" Version="4.6.3" />
|
||||
<PackageVersion Include="System.Net.Security" Version="4.3.2" />
|
||||
<!-- OpenTelemetry -->
|
||||
@@ -64,12 +63,12 @@
|
||||
<PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="10.0.0" />
|
||||
<PackageVersion Include="Swashbuckle.AspNetCore.SwaggerUI" Version="10.0.0" />
|
||||
<!-- Microsoft.Extensions.* -->
|
||||
<PackageVersion Include="Microsoft.Extensions.AI" Version="10.3.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.3.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.Evaluation" Version="10.3.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.Evaluation.Quality" Version="10.3.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI" Version="10.4.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.4.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.Evaluation" Version="10.4.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.Evaluation.Quality" Version="10.4.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.Evaluation.Safety" Version="10.3.0-preview.1.26109.11" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.3.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.4.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Caching.Memory" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Configuration" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Configuration.Binder" Version="10.0.0" />
|
||||
@@ -77,11 +76,11 @@
|
||||
<PackageVersion Include="Microsoft.Extensions.Configuration.Json" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Configuration.UserSecrets" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.DependencyInjection" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.3" />
|
||||
<PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.4" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Hosting" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Http.Resilience" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Logging" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.3" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.4" />
|
||||
<PackageVersion Include="Microsoft.Extensions.Logging.Console" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.ServiceDiscovery" Version="10.0.0" />
|
||||
<PackageVersion Include="Microsoft.Extensions.VectorData.Abstractions" Version="9.7.0" />
|
||||
@@ -111,9 +110,9 @@
|
||||
<PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.10.0" />
|
||||
<PackageVersion Include="Microsoft.ML.Tokenizers" Version="2.0.0" />
|
||||
<PackageVersion Include="OllamaSharp" Version="5.4.8" />
|
||||
<PackageVersion Include="OpenAI" Version="2.8.0" />
|
||||
<PackageVersion Include="OpenAI" Version="2.9.1" />
|
||||
<!-- Identity -->
|
||||
<PackageVersion Include="Microsoft.Identity.Client.Extensions.Msal" Version="4.78.0" />
|
||||
<PackageVersion Include="Microsoft.Identity.Client.Extensions.Msal" Version="4.83.1" />
|
||||
<!-- Workflows -->
|
||||
<PackageVersion Include="Microsoft.Agents.ObjectModel" Version="2026.2.4.1" />
|
||||
<PackageVersion Include="Microsoft.Agents.ObjectModel.Json" Version="2026.2.4.1" />
|
||||
|
||||
@@ -59,14 +59,14 @@ while ((input = Console.ReadLine()) != null && !input.Equals("exit", StringCompa
|
||||
{
|
||||
switch (content)
|
||||
{
|
||||
case FunctionApprovalRequestContent approvalRequest:
|
||||
DisplayApprovalRequest(approvalRequest);
|
||||
case ToolApprovalRequestContent approvalRequest when approvalRequest.ToolCall is FunctionCallContent fcc:
|
||||
DisplayApprovalRequest(approvalRequest, fcc);
|
||||
|
||||
Console.Write($"\nApprove '{approvalRequest.FunctionCall.Name}'? (yes/no): ");
|
||||
Console.Write($"\nApprove '{fcc.Name}'? (yes/no): ");
|
||||
string? userInput = Console.ReadLine();
|
||||
bool approved = userInput?.ToUpperInvariant() is "YES" or "Y";
|
||||
|
||||
FunctionApprovalResponseContent approvalResponse = approvalRequest.CreateResponse(approved);
|
||||
ToolApprovalResponseContent approvalResponse = approvalRequest.CreateResponse(approved);
|
||||
|
||||
if (approvalRequest.AdditionalProperties != null)
|
||||
{
|
||||
@@ -128,19 +128,19 @@ while ((input = Console.ReadLine()) != null && !input.Equals("exit", StringCompa
|
||||
}
|
||||
|
||||
#pragma warning disable MEAI001
|
||||
static void DisplayApprovalRequest(FunctionApprovalRequestContent approvalRequest)
|
||||
static void DisplayApprovalRequest(ToolApprovalRequestContent approvalRequest, FunctionCallContent fcc)
|
||||
{
|
||||
Console.ForegroundColor = ConsoleColor.Yellow;
|
||||
Console.WriteLine();
|
||||
Console.WriteLine("============================================================");
|
||||
Console.WriteLine("APPROVAL REQUIRED");
|
||||
Console.WriteLine("============================================================");
|
||||
Console.WriteLine($"Function: {approvalRequest.FunctionCall.Name}");
|
||||
Console.WriteLine($"Function: {fcc.Name}");
|
||||
|
||||
if (approvalRequest.FunctionCall.Arguments != null)
|
||||
if (fcc.Arguments != null)
|
||||
{
|
||||
Console.WriteLine("Arguments:");
|
||||
foreach (var arg in approvalRequest.FunctionCall.Arguments)
|
||||
foreach (var arg in fcc.Arguments)
|
||||
{
|
||||
Console.WriteLine($" {arg.Key} = {arg.Value}");
|
||||
}
|
||||
|
||||
+12
-12
@@ -9,7 +9,7 @@ using ServerFunctionApproval;
|
||||
|
||||
/// <summary>
|
||||
/// A delegating agent that handles server function approval requests and responses.
|
||||
/// Transforms between FunctionApprovalRequestContent/FunctionApprovalResponseContent
|
||||
/// Transforms between ToolApprovalRequestContent/ToolApprovalResponseContent
|
||||
/// and the server's request_approval tool call pattern.
|
||||
/// </summary>
|
||||
internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
|
||||
@@ -50,14 +50,14 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
|
||||
}
|
||||
|
||||
#pragma warning disable MEAI001 // Type is for evaluation purposes only
|
||||
private static FunctionResultContent ConvertApprovalResponseToToolResult(FunctionApprovalResponseContent approvalResponse, JsonSerializerOptions jsonOptions)
|
||||
private static FunctionResultContent ConvertApprovalResponseToToolResult(ToolApprovalResponseContent approvalResponse, JsonSerializerOptions jsonOptions)
|
||||
{
|
||||
return new FunctionResultContent(
|
||||
callId: approvalResponse.Id,
|
||||
callId: approvalResponse.RequestId,
|
||||
result: JsonSerializer.SerializeToElement(
|
||||
new ApprovalResponse
|
||||
{
|
||||
ApprovalId = approvalResponse.Id,
|
||||
ApprovalId = approvalResponse.RequestId,
|
||||
Approved = approvalResponse.Approved
|
||||
},
|
||||
jsonOptions));
|
||||
@@ -89,7 +89,7 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
|
||||
{
|
||||
List<ChatMessage>? result = null;
|
||||
|
||||
Dictionary<string, FunctionApprovalRequestContent> approvalRequests = [];
|
||||
Dictionary<string, ToolApprovalRequestContent> approvalRequests = [];
|
||||
for (var messageIndex = 0; messageIndex < messages.Count; messageIndex++)
|
||||
{
|
||||
var message = messages[messageIndex];
|
||||
@@ -102,21 +102,21 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
|
||||
var content = message.Contents[contentIndex];
|
||||
|
||||
// Handle pending approval requests (transform to tool call)
|
||||
if (content is FunctionApprovalRequestContent approvalRequest &&
|
||||
if (content is ToolApprovalRequestContent approvalRequest &&
|
||||
approvalRequest.AdditionalProperties?.TryGetValue("original_function", out var originalFunction) == true &&
|
||||
originalFunction is FunctionCallContent original)
|
||||
{
|
||||
approvalRequests[approvalRequest.Id] = approvalRequest;
|
||||
approvalRequests[approvalRequest.RequestId] = approvalRequest;
|
||||
transformedContents ??= CopyContentsUpToIndex(message.Contents, contentIndex);
|
||||
transformedContents.Add(original);
|
||||
}
|
||||
// Handle pending approval responses (transform to tool result)
|
||||
else if (content is FunctionApprovalResponseContent approvalResponse &&
|
||||
approvalRequests.TryGetValue(approvalResponse.Id, out var correspondingRequest))
|
||||
else if (content is ToolApprovalResponseContent approvalResponse &&
|
||||
approvalRequests.TryGetValue(approvalResponse.RequestId, out var correspondingRequest))
|
||||
{
|
||||
transformedContents ??= CopyContentsUpToIndex(message.Contents, contentIndex);
|
||||
transformedContents.Add(ConvertApprovalResponseToToolResult(approvalResponse, jsonSerializerOptions));
|
||||
approvalRequests.Remove(approvalResponse.Id);
|
||||
approvalRequests.Remove(approvalResponse.RequestId);
|
||||
correspondingRequest.AdditionalProperties?.Remove("original_function");
|
||||
}
|
||||
// Skip historical approval content
|
||||
@@ -198,8 +198,8 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
|
||||
var functionCallArgs = (Dictionary<string, object?>?)approvalRequest.FunctionArguments?
|
||||
.Deserialize(jsonSerializerOptions.GetTypeInfo(typeof(Dictionary<string, object?>)));
|
||||
|
||||
var approvalRequestContent = new FunctionApprovalRequestContent(
|
||||
id: approvalRequest.ApprovalId,
|
||||
var approvalRequestContent = new ToolApprovalRequestContent(
|
||||
requestId: approvalRequest.ApprovalId,
|
||||
new FunctionCallContent(
|
||||
callId: approvalRequest.ApprovalId,
|
||||
name: approvalRequest.FunctionName,
|
||||
|
||||
+8
-9
@@ -9,7 +9,7 @@ using ServerFunctionApproval;
|
||||
|
||||
/// <summary>
|
||||
/// A delegating agent that handles function approval requests on the server side.
|
||||
/// Transforms between FunctionApprovalRequestContent/FunctionApprovalResponseContent
|
||||
/// Transforms between ToolApprovalRequestContent/ToolApprovalResponseContent
|
||||
/// and the request_approval tool call pattern for client communication.
|
||||
/// </summary>
|
||||
internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
|
||||
@@ -50,7 +50,7 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
|
||||
}
|
||||
|
||||
#pragma warning disable MEAI001 // Type is for evaluation purposes only
|
||||
private static FunctionApprovalRequestContent ConvertToolCallToApprovalRequest(FunctionCallContent toolCall, JsonSerializerOptions jsonSerializerOptions)
|
||||
private static ToolApprovalRequestContent ConvertToolCallToApprovalRequest(FunctionCallContent toolCall, JsonSerializerOptions jsonSerializerOptions)
|
||||
{
|
||||
if (toolCall.Name != "request_approval" || toolCall.Arguments == null)
|
||||
{
|
||||
@@ -67,15 +67,15 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
|
||||
throw new InvalidOperationException("Failed to deserialize approval request from tool call");
|
||||
}
|
||||
|
||||
return new FunctionApprovalRequestContent(
|
||||
id: request.ApprovalId,
|
||||
return new ToolApprovalRequestContent(
|
||||
requestId: request.ApprovalId,
|
||||
new FunctionCallContent(
|
||||
callId: request.ApprovalId,
|
||||
name: request.FunctionName,
|
||||
arguments: request.FunctionArguments));
|
||||
}
|
||||
|
||||
private static FunctionApprovalResponseContent ConvertToolResultToApprovalResponse(FunctionResultContent result, FunctionApprovalRequestContent approval, JsonSerializerOptions jsonSerializerOptions)
|
||||
private static ToolApprovalResponseContent ConvertToolResultToApprovalResponse(FunctionResultContent result, ToolApprovalRequestContent approval, JsonSerializerOptions jsonSerializerOptions)
|
||||
{
|
||||
var approvalResponse = result.Result is JsonElement je ?
|
||||
(ApprovalResponse?)je.Deserialize(jsonSerializerOptions.GetTypeInfo(typeof(ApprovalResponse))) :
|
||||
@@ -121,7 +121,7 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
|
||||
// Track approval ID to original call ID mapping
|
||||
_ = new Dictionary<string, string>();
|
||||
#pragma warning disable MEAI001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
|
||||
Dictionary<string, FunctionApprovalRequestContent> trackedRequestApprovalToolCalls = new(); // Remote approvals
|
||||
Dictionary<string, ToolApprovalRequestContent> trackedRequestApprovalToolCalls = new(); // Remote approvals
|
||||
for (int messageIndex = 0; messageIndex < messages.Count; messageIndex++)
|
||||
{
|
||||
var message = messages[messageIndex];
|
||||
@@ -181,11 +181,10 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
|
||||
{
|
||||
var content = update.Contents[i];
|
||||
#pragma warning disable MEAI001 // Type is for evaluation purposes only
|
||||
if (content is FunctionApprovalRequestContent request)
|
||||
if (content is ToolApprovalRequestContent request && request.ToolCall is FunctionCallContent functionCall)
|
||||
{
|
||||
updatedContents ??= [.. update.Contents];
|
||||
var functionCall = request.FunctionCall;
|
||||
var approvalId = request.Id;
|
||||
var approvalId = request.RequestId;
|
||||
|
||||
var approvalData = new ApprovalRequest
|
||||
{
|
||||
|
||||
@@ -1,5 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
#pragma warning disable CS0618 // Type or member is obsolete - sample uses deprecated PersistentAgentsClientExtensions
|
||||
|
||||
// This sample shows how to create and use a simple AI agent with Azure Foundry Agents as the backend.
|
||||
|
||||
using Azure.AI.Agents.Persistent;
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to create and use a AI agents with Azure Foundry Agents as the backend.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
|
||||
|
||||
@@ -17,8 +17,8 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT
|
||||
AIAgent agent = new AzureOpenAIClient(
|
||||
new Uri(endpoint),
|
||||
new DefaultAzureCredential())
|
||||
.GetResponsesClient(deploymentName)
|
||||
.AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
|
||||
.GetResponsesClient()
|
||||
.AsAIAgent(model: deploymentName, instructions: "You are good at telling jokes.", name: "Joker");
|
||||
|
||||
// Invoke the agent and output the text result.
|
||||
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
|
||||
@@ -29,8 +29,8 @@ Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
|
||||
AIAgent agentStoreFalse = new AzureOpenAIClient(
|
||||
new Uri(endpoint),
|
||||
new DefaultAzureCredential())
|
||||
.GetResponsesClient(deploymentName)
|
||||
.AsIChatClientWithStoredOutputDisabled()
|
||||
.GetResponsesClient()
|
||||
.AsIChatClientWithStoredOutputDisabled(model: deploymentName)
|
||||
.AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
|
||||
|
||||
// Invoke the agent and output the text result.
|
||||
|
||||
@@ -11,8 +11,8 @@ var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt
|
||||
|
||||
AIAgent agent = new OpenAIClient(
|
||||
apiKey)
|
||||
.GetResponsesClient(model)
|
||||
.AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
|
||||
.GetResponsesClient()
|
||||
.AsAIAgent(model: model, instructions: "You are good at telling jokes.", name: "Joker");
|
||||
|
||||
// Invoke the agent and output the text result.
|
||||
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
|
||||
|
||||
@@ -23,7 +23,7 @@ var skillsProvider = new FileAgentSkillsProvider(skillPath: Path.Combine(AppCont
|
||||
|
||||
// --- Agent Setup ---
|
||||
AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
|
||||
.GetResponsesClient(deploymentName)
|
||||
.GetResponsesClient()
|
||||
.AsAIAgent(new ChatClientAgentOptions
|
||||
{
|
||||
Name = "SkillsAgent",
|
||||
@@ -32,7 +32,8 @@ AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredent
|
||||
Instructions = "You are a helpful assistant.",
|
||||
},
|
||||
AIContextProviders = [skillsProvider],
|
||||
});
|
||||
},
|
||||
model: deploymentName);
|
||||
|
||||
// --- Example 1: Expense policy question (loads FAQ resource) ---
|
||||
Console.WriteLine("Example 1: Checking expense policy FAQ");
|
||||
|
||||
@@ -10,8 +10,8 @@ var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new I
|
||||
var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5";
|
||||
|
||||
var client = new OpenAIClient(apiKey)
|
||||
.GetResponsesClient(model)
|
||||
.AsIChatClient().AsBuilder()
|
||||
.GetResponsesClient()
|
||||
.AsIChatClient(model).AsBuilder()
|
||||
.ConfigureOptions(o =>
|
||||
{
|
||||
o.Reasoning = new()
|
||||
|
||||
+6
-3
@@ -20,19 +20,21 @@ public class OpenAIResponseClientAgent : DelegatingAIAgent
|
||||
/// <param name="instructions">Optional instructions for the agent.</param>
|
||||
/// <param name="name">Optional name for the agent.</param>
|
||||
/// <param name="description">Optional description for the agent.</param>
|
||||
/// <param name="model">Optional default model ID to use for requests. Required when using a plain <see cref="ResponsesClient"/> (not via Azure OpenAI).</param>
|
||||
/// <param name="loggerFactory">Optional instance of <see cref="ILoggerFactory"/></param>
|
||||
public OpenAIResponseClientAgent(
|
||||
ResponsesClient client,
|
||||
string? instructions = null,
|
||||
string? name = null,
|
||||
string? description = null,
|
||||
string? model = null,
|
||||
ILoggerFactory? loggerFactory = null) :
|
||||
this(client, new()
|
||||
{
|
||||
Name = name,
|
||||
Description = description,
|
||||
ChatOptions = new ChatOptions() { Instructions = instructions },
|
||||
}, loggerFactory)
|
||||
}, model, loggerFactory)
|
||||
{
|
||||
}
|
||||
|
||||
@@ -41,10 +43,11 @@ public class OpenAIResponseClientAgent : DelegatingAIAgent
|
||||
/// </summary>
|
||||
/// <param name="client">Instance of <see cref="ResponsesClient"/></param>
|
||||
/// <param name="options">Options to create the agent.</param>
|
||||
/// <param name="model">Optional default model ID to use for requests. Required when using a plain <see cref="ResponsesClient"/> (not via Azure OpenAI).</param>
|
||||
/// <param name="loggerFactory">Optional instance of <see cref="ILoggerFactory"/></param>
|
||||
public OpenAIResponseClientAgent(
|
||||
ResponsesClient client, ChatClientAgentOptions options, ILoggerFactory? loggerFactory = null) :
|
||||
base(new ChatClientAgent((client ?? throw new ArgumentNullException(nameof(client))).AsIChatClient(), options, loggerFactory))
|
||||
ResponsesClient client, ChatClientAgentOptions options, string? model = null, ILoggerFactory? loggerFactory = null) :
|
||||
base(new ChatClientAgent((client ?? throw new ArgumentNullException(nameof(client))).AsIChatClient(model), options, loggerFactory))
|
||||
{
|
||||
}
|
||||
|
||||
|
||||
+2
-2
@@ -10,10 +10,10 @@ var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new I
|
||||
var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
|
||||
|
||||
// Create a ResponsesClient directly from OpenAIClient
|
||||
ResponsesClient responseClient = new OpenAIClient(apiKey).GetResponsesClient(model);
|
||||
ResponsesClient responseClient = new OpenAIClient(apiKey).GetResponsesClient();
|
||||
|
||||
// Create an agent directly from the ResponsesClient using OpenAIResponseClientAgent
|
||||
OpenAIResponseClientAgent agent = new(responseClient, instructions: "You are good at telling jokes.", name: "Joker");
|
||||
OpenAIResponseClientAgent agent = new(responseClient, instructions: "You are good at telling jokes.", name: "Joker", model: model);
|
||||
|
||||
ResponseItem userMessage = ResponseItem.CreateUserMessageItem("Tell me a joke about a pirate.");
|
||||
|
||||
|
||||
+1
-1
@@ -22,7 +22,7 @@ OpenAIClient openAIClient = new(apiKey);
|
||||
ConversationClient conversationClient = openAIClient.GetConversationClient();
|
||||
|
||||
// Create an agent directly from the ResponsesClient using OpenAIResponseClientAgent
|
||||
ChatClientAgent agent = new(openAIClient.GetResponsesClient(model).AsIChatClient(), instructions: "You are a helpful assistant.", name: "ConversationAgent");
|
||||
ChatClientAgent agent = new(openAIClient.GetResponsesClient().AsIChatClient(model), instructions: "You are a helpful assistant.", name: "ConversationAgent");
|
||||
|
||||
ClientResult createConversationResult = await conversationClient.CreateConversationAsync(BinaryContent.Create(BinaryData.FromString("{}")));
|
||||
|
||||
|
||||
+5
-5
@@ -36,11 +36,11 @@ AIAgent agent = new AzureOpenAIClient(
|
||||
// For simplicity, we are assuming here that only function approvals are pending.
|
||||
AgentSession session = await agent.CreateSessionAsync();
|
||||
AgentResponse response = await agent.RunAsync("What is the weather like in Amsterdam?", session);
|
||||
List<FunctionApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<FunctionApprovalRequestContent>().ToList();
|
||||
List<ToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
|
||||
// For streaming use:
|
||||
// var updates = await agent.RunStreamingAsync("What is the weather like in Amsterdam?", session).ToListAsync();
|
||||
// approvalRequests = updates.SelectMany(x => x.Contents).OfType<FunctionApprovalRequestContent>().ToList();
|
||||
// approvalRequests = updates.SelectMany(x => x.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
|
||||
while (approvalRequests.Count > 0)
|
||||
{
|
||||
@@ -48,18 +48,18 @@ while (approvalRequests.Count > 0)
|
||||
List<ChatMessage> userInputResponses = approvalRequests
|
||||
.ConvertAll(functionApprovalRequest =>
|
||||
{
|
||||
Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {functionApprovalRequest.FunctionCall.Name}");
|
||||
Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {((FunctionCallContent)functionApprovalRequest.ToolCall).Name}");
|
||||
return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
|
||||
});
|
||||
|
||||
// Pass the user input responses back to the agent for further processing.
|
||||
response = await agent.RunAsync(userInputResponses, session);
|
||||
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<FunctionApprovalRequestContent>().ToList();
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
|
||||
// For streaming use:
|
||||
// updates = await agent.RunStreamingAsync(userInputResponses, session).ToListAsync();
|
||||
// approvalRequests = updates.SelectMany(x => x.Contents).OfType<FunctionApprovalRequestContent>().ToList();
|
||||
// approvalRequests = updates.SelectMany(x => x.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
}
|
||||
|
||||
Console.WriteLine($"\nAgent: {response}");
|
||||
|
||||
+2
-2
@@ -10,14 +10,14 @@
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Agents.Persistent" />
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Microsoft.Extensions.Hosting" />
|
||||
<PackageReference Include="ModelContextProtocol" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
// This sample shows how to expose an AI agent as an MCP tool.
|
||||
|
||||
using Azure.AI.Agents.Persistent;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
@@ -15,18 +15,15 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYME
|
||||
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
|
||||
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
|
||||
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
|
||||
var persistentAgentsClient = new PersistentAgentsClient(endpoint, new DefaultAzureCredential());
|
||||
var aiProjectClient = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential());
|
||||
|
||||
// Create a server side persistent agent
|
||||
var agentMetadata = await persistentAgentsClient.Administration.CreateAgentAsync(
|
||||
// Create a server side agent and expose it as an AIAgent.
|
||||
AIAgent agent = await aiProjectClient.CreateAIAgentAsync(
|
||||
model: deploymentName,
|
||||
instructions: "You are good at telling jokes, and you always start each joke with 'Aye aye, captain!'.",
|
||||
name: "Joker",
|
||||
description: "An agent that tells jokes.");
|
||||
|
||||
// Retrieve the server side persistent agent as an AIAgent.
|
||||
AIAgent agent = await persistentAgentsClient.GetAIAgentAsync(agentMetadata.Value.Id);
|
||||
|
||||
// Convert the agent to an AIFunction and then to an MCP tool.
|
||||
// The agent name and description will be used as the mcp tool name and description.
|
||||
McpServerTool tool = McpServerTool.Create(agent.AsAIFunction());
|
||||
|
||||
+2
-1
@@ -25,8 +25,9 @@ var stateStore = new Dictionary<string, JsonElement?>();
|
||||
AIAgent agent = new AzureOpenAIClient(
|
||||
new Uri(endpoint),
|
||||
new DefaultAzureCredential())
|
||||
.GetResponsesClient(deploymentName)
|
||||
.GetResponsesClient()
|
||||
.AsAIAgent(
|
||||
model: deploymentName,
|
||||
name: "SpaceNovelWriter",
|
||||
instructions: "You are a space novel writer. Always research relevant facts and generate character profiles for the main characters before writing novels." +
|
||||
"Write complete chapters without asking for approval or feedback. Do not ask the user about tone, style, pace, or format preferences - just write the novel based on the request.",
|
||||
|
||||
@@ -246,7 +246,7 @@ async Task<AgentResponse> ConsolePromptingApprovalMiddleware(IEnumerable<ChatMes
|
||||
AgentResponse response = await innerAgent.RunAsync(messages, session, options, cancellationToken);
|
||||
|
||||
// For simplicity, we are assuming here that only function approvals are pending.
|
||||
List<FunctionApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<FunctionApprovalRequestContent>().ToList();
|
||||
List<ToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
|
||||
while (approvalRequests.Count > 0)
|
||||
{
|
||||
@@ -255,13 +255,13 @@ async Task<AgentResponse> ConsolePromptingApprovalMiddleware(IEnumerable<ChatMes
|
||||
response.Messages = approvalRequests
|
||||
.ConvertAll(functionApprovalRequest =>
|
||||
{
|
||||
Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {functionApprovalRequest.FunctionCall.Name}");
|
||||
Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {((FunctionCallContent)functionApprovalRequest.ToolCall).Name}");
|
||||
return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
|
||||
});
|
||||
|
||||
response = await innerAgent.RunAsync(response.Messages, session, options, cancellationToken);
|
||||
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<FunctionApprovalRequestContent>().ToList();
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
}
|
||||
|
||||
return response;
|
||||
|
||||
@@ -16,8 +16,8 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT
|
||||
AIAgent agent = new AzureOpenAIClient(
|
||||
new Uri(endpoint),
|
||||
new DefaultAzureCredential())
|
||||
.GetResponsesClient(deploymentName)
|
||||
.AsAIAgent();
|
||||
.GetResponsesClient()
|
||||
.AsAIAgent(model: deploymentName);
|
||||
|
||||
// Enable background responses (only supported by OpenAI Responses at this time).
|
||||
AgentRunOptions options = new() { AllowBackgroundResponses = true };
|
||||
|
||||
@@ -1,5 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
#pragma warning disable CS0618 // Type or member is obsolete - sample uses deprecated PersistentAgentsClientExtensions
|
||||
|
||||
// This sample shows how to create an Azure AI Foundry Agent with the Deep Research Tool.
|
||||
|
||||
using Azure.AI.Agents.Persistent;
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to create and use AI agents with Azure Foundry Agents as the backend.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to create and use a simple AI agent with Azure Foundry Agents as the backend.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
|
||||
|
||||
+2
-1
@@ -2,8 +2,9 @@
|
||||
|
||||
// This sample shows how to create and use a simple AI agent with a multi-turn conversation.
|
||||
|
||||
using Azure.AI.Extensions.OpenAI;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
|
||||
|
||||
+3
-3
@@ -40,7 +40,7 @@ AgentResponse response = await agent.RunAsync("What is the weather like in Amste
|
||||
|
||||
// Check if there are any approval requests.
|
||||
// For simplicity, we are assuming here that only function approvals are pending.
|
||||
List<FunctionApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<FunctionApprovalRequestContent>().ToList();
|
||||
List<ToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
|
||||
while (approvalRequests.Count > 0)
|
||||
{
|
||||
@@ -48,7 +48,7 @@ while (approvalRequests.Count > 0)
|
||||
List<ChatMessage> userInputMessages = approvalRequests
|
||||
.ConvertAll(functionApprovalRequest =>
|
||||
{
|
||||
Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {functionApprovalRequest.FunctionCall.Name}");
|
||||
Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {((FunctionCallContent)functionApprovalRequest.ToolCall).Name}");
|
||||
bool approved = Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false;
|
||||
return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(approved)]);
|
||||
});
|
||||
@@ -56,7 +56,7 @@ while (approvalRequests.Count > 0)
|
||||
// Pass the user input responses back to the agent for further processing.
|
||||
response = await agent.RunAsync(userInputMessages, session);
|
||||
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<FunctionApprovalRequestContent>().ToList();
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
}
|
||||
|
||||
Console.WriteLine($"\nAgent: {response}");
|
||||
|
||||
@@ -197,7 +197,7 @@ async Task<AgentResponse> ConsolePromptingApprovalMiddleware(IEnumerable<ChatMes
|
||||
AgentResponse response = await innerAgent.RunAsync(messages, session, options, cancellationToken);
|
||||
|
||||
// For simplicity, we are assuming here that only function approvals are pending.
|
||||
List<FunctionApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<FunctionApprovalRequestContent>().ToList();
|
||||
List<ToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
|
||||
while (approvalRequests.Count > 0)
|
||||
{
|
||||
@@ -206,14 +206,14 @@ async Task<AgentResponse> ConsolePromptingApprovalMiddleware(IEnumerable<ChatMes
|
||||
response.Messages = approvalRequests
|
||||
.ConvertAll(functionApprovalRequest =>
|
||||
{
|
||||
Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {functionApprovalRequest.FunctionCall.Name}");
|
||||
Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {((FunctionCallContent)functionApprovalRequest.ToolCall).Name}");
|
||||
bool approved = Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false;
|
||||
return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(approved)]);
|
||||
});
|
||||
|
||||
response = await innerAgent.RunAsync(response.Messages, session, options, cancellationToken);
|
||||
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<FunctionApprovalRequestContent>().ToList();
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
}
|
||||
|
||||
return response;
|
||||
|
||||
+1
-1
@@ -4,7 +4,7 @@
|
||||
|
||||
using System.Text;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to use Computer Use Tool with AI Agents.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to use File Search Tool with AI Agents.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to use OpenAPI Tools with AI Agents.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using OpenAI.Responses;
|
||||
@@ -72,7 +72,7 @@ const string CountriesOpenApiSpec = """
|
||||
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
|
||||
|
||||
// Create the OpenAPI function definition
|
||||
var openApiFunction = new OpenAPIFunctionDefinition(
|
||||
var openApiFunction = new OpenApiFunctionDefinition(
|
||||
"get_countries",
|
||||
BinaryData.FromString(CountriesOpenApiSpec),
|
||||
new OpenAPIAnonymousAuthenticationDetails())
|
||||
|
||||
+2
-2
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to use Bing Custom Search Tool with AI Agents.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using OpenAI.Responses;
|
||||
@@ -25,7 +25,7 @@ const string AgentInstructions = """
|
||||
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
|
||||
|
||||
// Bing Custom Search tool parameters shared by both options
|
||||
BingCustomSearchToolParameters bingCustomSearchToolParameters = new([
|
||||
BingCustomSearchToolOptions bingCustomSearchToolParameters = new([
|
||||
new BingCustomSearchConfiguration(connectionId, instanceName)
|
||||
]);
|
||||
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to use SharePoint Grounding Tool with AI Agents.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using OpenAI.Responses;
|
||||
|
||||
+1
-1
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to use Microsoft Fabric Tool with AI Agents.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using OpenAI.Responses;
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
// This sample shows how to use the Responses API Web Search Tool with AI Agents.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
-1
@@ -13,7 +13,6 @@
|
||||
<PackageReference Include="Microsoft.Extensions.Logging.Console" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.AI.Projects.OpenAI" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
|
||||
@@ -4,8 +4,9 @@
|
||||
// The Memory Search Tool enables agents to recall information from previous conversations,
|
||||
// supporting user profile persistence and chat summaries across sessions.
|
||||
|
||||
using Azure.AI.Extensions.OpenAI;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using OpenAI.Responses;
|
||||
@@ -36,7 +37,7 @@ AIProjectClient aiProjectClient = new(new Uri(endpoint), credential);
|
||||
await EnsureMemoryStoreAsync();
|
||||
|
||||
// Create the Memory Search tool configuration
|
||||
MemorySearchPreviewTool memorySearchTool = new(memoryStoreName, userScope) { UpdateDelay = 0 };
|
||||
MemorySearchPreviewTool memorySearchTool = new(memoryStoreName, userScope) { UpdateDelayInSecs = 0 };
|
||||
|
||||
// Create agent using Option 1 (MEAI) or Option 2 (Native SDK)
|
||||
AIAgent agent = await CreateAgentWithMEAI();
|
||||
@@ -128,8 +129,8 @@ async Task EnsureMemoryStoreAsync()
|
||||
|
||||
MemoryUpdateResult updateResult = await aiProjectClient.MemoryStores.WaitForMemoriesUpdateAsync(
|
||||
memoryStoreName: memoryStoreName,
|
||||
options: memoryOptions,
|
||||
pollingInterval: 500);
|
||||
pollingInterval: 500,
|
||||
options: memoryOptions);
|
||||
|
||||
if (updateResult.Status == MemoryStoreUpdateStatus.Failed)
|
||||
{
|
||||
|
||||
+2
-2
@@ -9,12 +9,12 @@
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Agents.Persistent" />
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
|
||||
@@ -4,7 +4,7 @@
|
||||
// In this case the Azure Foundry Agents service will invoke any MCP tools as required. MCP tools are not invoked by the Agent Framework.
|
||||
// The sample first shows how to use MCP tools with auto approval, and then how to set up a tool that requires approval before it can be invoked and how to approve such a tool.
|
||||
|
||||
using Azure.AI.Agents.Persistent;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
@@ -16,7 +16,7 @@ var model = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME")
|
||||
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
|
||||
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
|
||||
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
|
||||
var persistentAgentsClient = new PersistentAgentsClient(endpoint, new DefaultAzureCredential());
|
||||
var aiProjectClient = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential());
|
||||
|
||||
// **** MCP Tool with Auto Approval ****
|
||||
// *************************************
|
||||
@@ -31,8 +31,8 @@ var mcpTool = new HostedMcpServerTool(
|
||||
ApprovalMode = HostedMcpServerToolApprovalMode.NeverRequire
|
||||
};
|
||||
|
||||
// Create a server side persistent agent with the mcp tool, and expose it as an AIAgent.
|
||||
AIAgent agent = await persistentAgentsClient.CreateAIAgentAsync(
|
||||
// Create a server side agent with the mcp tool, and expose it as an AIAgent.
|
||||
AIAgent agent = await aiProjectClient.CreateAIAgentAsync(
|
||||
model: model,
|
||||
options: new()
|
||||
{
|
||||
@@ -49,7 +49,7 @@ AgentSession session = await agent.CreateSessionAsync();
|
||||
Console.WriteLine(await agent.RunAsync("Please summarize the Azure AI Agent documentation related to MCP Tool calling?", session));
|
||||
|
||||
// Cleanup for sample purposes.
|
||||
await persistentAgentsClient.Administration.DeleteAgentAsync(agent.Id);
|
||||
aiProjectClient.Agents.DeleteAgent(agent.Name);
|
||||
|
||||
// **** MCP Tool with Approval Required ****
|
||||
// *****************************************
|
||||
@@ -64,8 +64,8 @@ var mcpToolWithApproval = new HostedMcpServerTool(
|
||||
ApprovalMode = HostedMcpServerToolApprovalMode.AlwaysRequire
|
||||
};
|
||||
|
||||
// Create an agent based on Azure OpenAI Responses as the backend.
|
||||
AIAgent agentWithRequiredApproval = await persistentAgentsClient.CreateAIAgentAsync(
|
||||
// Create an agent with the MCP tool that requires approval.
|
||||
AIAgent agentWithRequiredApproval = await aiProjectClient.CreateAIAgentAsync(
|
||||
model: model,
|
||||
options: new()
|
||||
{
|
||||
@@ -81,7 +81,7 @@ AIAgent agentWithRequiredApproval = await persistentAgentsClient.CreateAIAgentAs
|
||||
// For simplicity, we are assuming here that only mcp tool approvals are pending.
|
||||
AgentSession sessionWithRequiredApproval = await agentWithRequiredApproval.CreateSessionAsync();
|
||||
AgentResponse response = await agentWithRequiredApproval.RunAsync("Please summarize the Azure AI Agent documentation related to MCP Tool calling?", sessionWithRequiredApproval);
|
||||
List<McpServerToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<McpServerToolApprovalRequestContent>().ToList();
|
||||
List<ToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
|
||||
while (approvalRequests.Count > 0)
|
||||
{
|
||||
@@ -89,11 +89,12 @@ while (approvalRequests.Count > 0)
|
||||
List<ChatMessage> userInputResponses = approvalRequests
|
||||
.ConvertAll(approvalRequest =>
|
||||
{
|
||||
McpServerToolCallContent mcpToolCall = (McpServerToolCallContent)approvalRequest.ToolCall!;
|
||||
Console.WriteLine($"""
|
||||
The agent would like to invoke the following MCP Tool, please reply Y to approve.
|
||||
ServerName: {approvalRequest.ToolCall.ServerName}
|
||||
Name: {approvalRequest.ToolCall.ToolName}
|
||||
Arguments: {string.Join(", ", approvalRequest.ToolCall.Arguments?.Select(x => $"{x.Key}: {x.Value}") ?? [])}
|
||||
ServerName: {mcpToolCall.ServerName}
|
||||
Name: {mcpToolCall.Name}
|
||||
Arguments: {string.Join(", ", mcpToolCall.Arguments?.Select(x => $"{x.Key}: {x.Value}") ?? [])}
|
||||
""");
|
||||
return new ChatMessage(ChatRole.User, [approvalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
|
||||
});
|
||||
@@ -101,7 +102,7 @@ while (approvalRequests.Count > 0)
|
||||
// Pass the user input responses back to the agent for further processing.
|
||||
response = await agentWithRequiredApproval.RunAsync(userInputResponses, sessionWithRequiredApproval);
|
||||
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<McpServerToolApprovalRequestContent>().ToList();
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
}
|
||||
|
||||
Console.WriteLine($"\nAgent: {response}");
|
||||
|
||||
@@ -33,8 +33,9 @@ var mcpTool = new HostedMcpServerTool(
|
||||
AIAgent agent = new AzureOpenAIClient(
|
||||
new Uri(endpoint),
|
||||
new DefaultAzureCredential())
|
||||
.GetResponsesClient(deploymentName)
|
||||
.GetResponsesClient()
|
||||
.AsAIAgent(
|
||||
model: deploymentName,
|
||||
instructions: "You answer questions by searching the Microsoft Learn content only.",
|
||||
name: "MicrosoftLearnAgent",
|
||||
tools: [mcpTool]);
|
||||
@@ -60,8 +61,9 @@ var mcpToolWithApproval = new HostedMcpServerTool(
|
||||
AIAgent agentWithRequiredApproval = new AzureOpenAIClient(
|
||||
new Uri(endpoint),
|
||||
new DefaultAzureCredential())
|
||||
.GetResponsesClient(deploymentName)
|
||||
.GetResponsesClient()
|
||||
.AsAIAgent(
|
||||
model: deploymentName,
|
||||
instructions: "You answer questions by searching the Microsoft Learn content only.",
|
||||
name: "MicrosoftLearnAgentWithApproval",
|
||||
tools: [mcpToolWithApproval]);
|
||||
@@ -70,7 +72,7 @@ AIAgent agentWithRequiredApproval = new AzureOpenAIClient(
|
||||
// For simplicity, we are assuming here that only mcp tool approvals are pending.
|
||||
AgentSession sessionWithRequiredApproval = await agentWithRequiredApproval.CreateSessionAsync();
|
||||
AgentResponse response = await agentWithRequiredApproval.RunAsync("Please summarize the Azure AI Agent documentation related to MCP Tool calling?", sessionWithRequiredApproval);
|
||||
List<McpServerToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<McpServerToolApprovalRequestContent>().ToList();
|
||||
List<ToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
|
||||
while (approvalRequests.Count > 0)
|
||||
{
|
||||
@@ -78,11 +80,12 @@ while (approvalRequests.Count > 0)
|
||||
List<ChatMessage> userInputResponses = approvalRequests
|
||||
.ConvertAll(approvalRequest =>
|
||||
{
|
||||
McpServerToolCallContent mcpToolCall = (McpServerToolCallContent)approvalRequest.ToolCall!;
|
||||
Console.WriteLine($"""
|
||||
The agent would like to invoke the following MCP Tool, please reply Y to approve.
|
||||
ServerName: {approvalRequest.ToolCall.ServerName}
|
||||
Name: {approvalRequest.ToolCall.ToolName}
|
||||
Arguments: {string.Join(", ", approvalRequest.ToolCall.Arguments?.Select(x => $"{x.Key}: {x.Value}") ?? [])}
|
||||
ServerName: {mcpToolCall.ServerName}
|
||||
Name: {mcpToolCall.Name}
|
||||
Arguments: {string.Join(", ", mcpToolCall.Arguments?.Select(x => $"{x.Key}: {x.Value}") ?? [])}
|
||||
""");
|
||||
return new ChatMessage(ChatRole.User, [approvalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
|
||||
});
|
||||
@@ -90,7 +93,7 @@ while (approvalRequests.Count > 0)
|
||||
// Pass the user input responses back to the agent for further processing.
|
||||
response = await agentWithRequiredApproval.RunAsync(userInputResponses, sessionWithRequiredApproval);
|
||||
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<McpServerToolApprovalRequestContent>().ToList();
|
||||
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
|
||||
}
|
||||
|
||||
Console.WriteLine($"\nAgent: {response}");
|
||||
|
||||
@@ -9,13 +9,13 @@
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Agents.Persistent" />
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using Azure.AI.Agents.Persistent;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.Workflows;
|
||||
@@ -20,60 +20,63 @@ public static class Program
|
||||
{
|
||||
private static async Task Main()
|
||||
{
|
||||
// Set up the Azure OpenAI client
|
||||
// Set up the Azure AI Project client
|
||||
var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
|
||||
?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
|
||||
var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
|
||||
var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());
|
||||
var aiProjectClient = new AIProjectClient(new Uri(endpoint), new AzureCliCredential());
|
||||
|
||||
// Create agents
|
||||
AIAgent frenchAgent = await GetTranslationAgentAsync("French", persistentAgentsClient, deploymentName);
|
||||
AIAgent spanishAgent = await GetTranslationAgentAsync("Spanish", persistentAgentsClient, deploymentName);
|
||||
AIAgent englishAgent = await GetTranslationAgentAsync("English", persistentAgentsClient, deploymentName);
|
||||
AIAgent frenchAgent = await CreateTranslationAgentAsync("French", aiProjectClient, deploymentName);
|
||||
AIAgent spanishAgent = await CreateTranslationAgentAsync("Spanish", aiProjectClient, deploymentName);
|
||||
AIAgent englishAgent = await CreateTranslationAgentAsync("English", aiProjectClient, deploymentName);
|
||||
|
||||
// Build the workflow by adding executors and connecting them
|
||||
var workflow = new WorkflowBuilder(frenchAgent)
|
||||
.AddEdge(frenchAgent, spanishAgent)
|
||||
.AddEdge(spanishAgent, englishAgent)
|
||||
.Build();
|
||||
|
||||
// Execute the workflow
|
||||
await using StreamingRun run = await InProcessExecution.RunStreamingAsync(workflow, new ChatMessage(ChatRole.User, "Hello World!"));
|
||||
// Must send the turn token to trigger the agents.
|
||||
// The agents are wrapped as executors. When they receive messages,
|
||||
// they will cache the messages and only start processing when they receive a TurnToken.
|
||||
await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
|
||||
await foreach (WorkflowEvent evt in run.WatchStreamAsync())
|
||||
try
|
||||
{
|
||||
if (evt is AgentResponseUpdateEvent executorComplete)
|
||||
// Build the workflow by adding executors and connecting them
|
||||
var workflow = new WorkflowBuilder(frenchAgent)
|
||||
.AddEdge(frenchAgent, spanishAgent)
|
||||
.AddEdge(spanishAgent, englishAgent)
|
||||
.Build();
|
||||
|
||||
// Execute the workflow
|
||||
await using StreamingRun run = await InProcessExecution.RunStreamingAsync(workflow, new ChatMessage(ChatRole.User, "Hello World!"));
|
||||
// Must send the turn token to trigger the agents.
|
||||
// The agents are wrapped as executors. When they receive messages,
|
||||
// they will cache the messages and only start processing when they receive a TurnToken.
|
||||
await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
|
||||
await foreach (WorkflowEvent evt in run.WatchStreamAsync())
|
||||
{
|
||||
Console.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}");
|
||||
if (evt is AgentResponseUpdateEvent executorComplete)
|
||||
{
|
||||
Console.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Cleanup the agents created for the sample.
|
||||
await persistentAgentsClient.Administration.DeleteAgentAsync(frenchAgent.Id);
|
||||
await persistentAgentsClient.Administration.DeleteAgentAsync(spanishAgent.Id);
|
||||
await persistentAgentsClient.Administration.DeleteAgentAsync(englishAgent.Id);
|
||||
finally
|
||||
{
|
||||
// Cleanup the agents created for the sample.
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(frenchAgent.Name);
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(spanishAgent.Name);
|
||||
await aiProjectClient.Agents.DeleteAgentAsync(englishAgent.Name);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Creates a translation agent for the specified target language.
|
||||
/// </summary>
|
||||
/// <param name="targetLanguage">The target language for translation</param>
|
||||
/// <param name="persistentAgentsClient">The PersistentAgentsClient to create the agent</param>
|
||||
/// <param name="aiProjectClient">The <see cref="AIProjectClient"/> to create the agent with.</param>
|
||||
/// <param name="model">The model to use for the agent</param>
|
||||
/// <returns>A ChatClientAgent configured for the specified language</returns>
|
||||
private static async Task<ChatClientAgent> GetTranslationAgentAsync(
|
||||
private static async Task<ChatClientAgent> CreateTranslationAgentAsync(
|
||||
string targetLanguage,
|
||||
PersistentAgentsClient persistentAgentsClient,
|
||||
AIProjectClient aiProjectClient,
|
||||
string model)
|
||||
{
|
||||
var agentMetadata = await persistentAgentsClient.Administration.CreateAgentAsync(
|
||||
model: model,
|
||||
return await aiProjectClient.CreateAIAgentAsync(
|
||||
name: $"{targetLanguage} Translator",
|
||||
model: model,
|
||||
instructions: $"You are a translation assistant that translates the provided text to {targetLanguage}.");
|
||||
|
||||
return await persistentAgentsClient.GetAIAgentAsync(agentMetadata.Value.Id);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -17,7 +17,7 @@
|
||||
//
|
||||
// Demonstrate:
|
||||
// - Using custom GroupChatManager with agents that have approval-required tools.
|
||||
// - Handling FunctionApprovalRequestContent in group chat scenarios.
|
||||
// - Handling ToolApprovalRequestContent in group chat scenarios.
|
||||
// - Multi-round group chat with tool approval interruption and resumption.
|
||||
|
||||
using System.ComponentModel;
|
||||
@@ -101,16 +101,16 @@ public static class Program
|
||||
{
|
||||
case RequestInfoEvent e:
|
||||
{
|
||||
if (e.Request.TryGetDataAs(out FunctionApprovalRequestContent? approvalRequestContent))
|
||||
if (e.Request.TryGetDataAs(out ToolApprovalRequestContent? approvalRequestContent))
|
||||
{
|
||||
Console.WriteLine();
|
||||
Console.WriteLine($"[APPROVAL REQUIRED] From agent: {e.Request.PortInfo.PortId}");
|
||||
Console.WriteLine($" Tool: {approvalRequestContent.FunctionCall.Name}");
|
||||
Console.WriteLine($" Arguments: {JsonSerializer.Serialize(approvalRequestContent.FunctionCall.Arguments)}");
|
||||
Console.WriteLine($" Tool: {((FunctionCallContent)approvalRequestContent.ToolCall).Name}");
|
||||
Console.WriteLine($" Arguments: {JsonSerializer.Serialize(((FunctionCallContent)approvalRequestContent.ToolCall).Arguments)}");
|
||||
Console.WriteLine();
|
||||
|
||||
// Approve the tool call request
|
||||
Console.WriteLine($"Tool: {approvalRequestContent.FunctionCall.Name} approved");
|
||||
Console.WriteLine($"Tool: {((FunctionCallContent)approvalRequestContent.ToolCall).Name} approved");
|
||||
await run.SendResponseAsync(e.Request.CreateResponse(approvalRequestContent.CreateResponse(approved: true)));
|
||||
}
|
||||
|
||||
|
||||
@@ -41,6 +41,7 @@ internal static class WorkflowFactory
|
||||
/// <summary>
|
||||
/// Executor that aggregates the results from the concurrent agents.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(string))]
|
||||
private sealed class ConcurrentAggregationExecutor() :
|
||||
Executor<List<ChatMessage>>("ConcurrentAggregationExecutor"), IResettableExecutor
|
||||
{
|
||||
|
||||
@@ -41,6 +41,7 @@ internal enum NumberSignal
|
||||
/// <summary>
|
||||
/// Executor that makes a guess based on the current bounds.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(int))]
|
||||
internal sealed class GuessNumberExecutor() : Executor<NumberSignal>("Guess")
|
||||
{
|
||||
/// <summary>
|
||||
@@ -104,6 +105,8 @@ internal sealed class GuessNumberExecutor() : Executor<NumberSignal>("Guess")
|
||||
/// <summary>
|
||||
/// Executor that judges the guess and provides feedback.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(NumberSignal))]
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class JudgeExecutor() : Executor<int>("Judge")
|
||||
{
|
||||
private readonly int _targetNumber;
|
||||
|
||||
@@ -41,6 +41,7 @@ internal enum NumberSignal
|
||||
/// <summary>
|
||||
/// Executor that makes a guess based on the current bounds.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(int))]
|
||||
internal sealed class GuessNumberExecutor() : Executor<NumberSignal>("Guess")
|
||||
{
|
||||
/// <summary>
|
||||
@@ -104,6 +105,8 @@ internal sealed class GuessNumberExecutor() : Executor<NumberSignal>("Guess")
|
||||
/// <summary>
|
||||
/// Executor that judges the guess and provides feedback.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(NumberSignal))]
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class JudgeExecutor() : Executor<int>("Judge")
|
||||
{
|
||||
private readonly int _targetNumber;
|
||||
|
||||
@@ -53,6 +53,8 @@ internal sealed class SignalWithNumber
|
||||
/// <summary>
|
||||
/// Executor that judges the guess and provides feedback.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(SignalWithNumber))]
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class JudgeExecutor() : Executor<int>("Judge")
|
||||
{
|
||||
private readonly int _targetNumber;
|
||||
|
||||
@@ -72,6 +72,8 @@ public static class Program
|
||||
/// <summary>
|
||||
/// Executor that starts the concurrent processing by sending messages to the agents.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(ChatMessage))]
|
||||
[SendsMessage(typeof(TurnToken))]
|
||||
internal sealed partial class ConcurrentStartExecutor() :
|
||||
Executor("ConcurrentStartExecutor")
|
||||
{
|
||||
@@ -97,7 +99,8 @@ internal sealed partial class ConcurrentStartExecutor() :
|
||||
/// <summary>
|
||||
/// Executor that aggregates the results from the concurrent agents.
|
||||
/// </summary>
|
||||
internal sealed class ConcurrentAggregationExecutor() :
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed partial class ConcurrentAggregationExecutor() :
|
||||
Executor<List<ChatMessage>>("ConcurrentAggregationExecutor")
|
||||
{
|
||||
private readonly List<ChatMessage> _messages = [];
|
||||
|
||||
@@ -128,6 +128,7 @@ public static class Program
|
||||
/// <summary>
|
||||
/// Splits data into roughly equal chunks based on the number of mapper nodes.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(SplitComplete))]
|
||||
internal sealed class Split(string[] mapperIds, string id) :
|
||||
Executor<string>(id)
|
||||
{
|
||||
@@ -186,6 +187,7 @@ internal sealed class Split(string[] mapperIds, string id) :
|
||||
/// <summary>
|
||||
/// Maps each token to a count of 1 and writes pairs to a per-mapper file.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(MapComplete))]
|
||||
internal sealed class Mapper(string id) : Executor<SplitComplete>(id)
|
||||
{
|
||||
/// <summary>
|
||||
@@ -212,6 +214,7 @@ internal sealed class Mapper(string id) : Executor<SplitComplete>(id)
|
||||
/// <summary>
|
||||
/// Groups intermediate pairs by key and partitions them across reducers.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(ShuffleComplete))]
|
||||
internal sealed class Shuffler(string[] reducerIds, string[] mapperIds, string id) :
|
||||
Executor<MapComplete>(id)
|
||||
{
|
||||
@@ -311,6 +314,7 @@ internal sealed class Shuffler(string[] reducerIds, string[] mapperIds, string i
|
||||
/// <summary>
|
||||
/// Sums grouped counts per key for its assigned partition.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(ReduceComplete))]
|
||||
internal sealed class Reducer(string id) : Executor<ShuffleComplete>(id)
|
||||
{
|
||||
/// <summary>
|
||||
@@ -352,6 +356,7 @@ internal sealed class Reducer(string id) : Executor<ShuffleComplete>(id)
|
||||
/// <summary>
|
||||
/// Joins all reducer outputs and yields the final output.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(List<string>))]
|
||||
internal sealed class CompletionExecutor(string id) :
|
||||
Executor<List<ReduceComplete>>(id)
|
||||
{
|
||||
|
||||
@@ -228,6 +228,7 @@ internal sealed class EmailAssistantExecutor : Executor<DetectionResult, EmailRe
|
||||
/// <summary>
|
||||
/// Executor that sends emails.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class SendEmailExecutor() : Executor<EmailResponse>("SendEmailExecutor")
|
||||
{
|
||||
/// <summary>
|
||||
@@ -240,6 +241,7 @@ internal sealed class SendEmailExecutor() : Executor<EmailResponse>("SendEmailEx
|
||||
/// <summary>
|
||||
/// Executor that handles spam messages.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class HandleSpamExecutor() : Executor<DetectionResult>("HandleSpamExecutor")
|
||||
{
|
||||
/// <summary>
|
||||
|
||||
@@ -252,6 +252,7 @@ internal sealed class EmailAssistantExecutor : Executor<DetectionResult, EmailRe
|
||||
/// <summary>
|
||||
/// Executor that sends emails.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class SendEmailExecutor() : Executor<EmailResponse>("SendEmailExecutor")
|
||||
{
|
||||
/// <summary>
|
||||
@@ -264,6 +265,7 @@ internal sealed class SendEmailExecutor() : Executor<EmailResponse>("SendEmailEx
|
||||
/// <summary>
|
||||
/// Executor that handles spam messages.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class HandleSpamExecutor() : Executor<DetectionResult>("HandleSpamExecutor")
|
||||
{
|
||||
/// <summary>
|
||||
@@ -285,6 +287,7 @@ internal sealed class HandleSpamExecutor() : Executor<DetectionResult>("HandleSp
|
||||
/// <summary>
|
||||
/// Executor that handles uncertain emails.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class HandleUncertainExecutor() : Executor<DetectionResult>("HandleUncertainExecutor")
|
||||
{
|
||||
/// <summary>
|
||||
|
||||
@@ -310,6 +310,7 @@ internal sealed class EmailAssistantExecutor : Executor<AnalysisResult, EmailRes
|
||||
/// <summary>
|
||||
/// Executor that sends emails.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class SendEmailExecutor() : Executor<EmailResponse>("SendEmailExecutor")
|
||||
{
|
||||
/// <summary>
|
||||
@@ -322,6 +323,7 @@ internal sealed class SendEmailExecutor() : Executor<EmailResponse>("SendEmailEx
|
||||
/// <summary>
|
||||
/// Executor that handles spam messages.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class HandleSpamExecutor() : Executor<AnalysisResult>("HandleSpamExecutor")
|
||||
{
|
||||
/// <summary>
|
||||
@@ -343,6 +345,7 @@ internal sealed class HandleSpamExecutor() : Executor<AnalysisResult>("HandleSpa
|
||||
/// <summary>
|
||||
/// Executor that handles uncertain messages.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class HandleUncertainExecutor() : Executor<AnalysisResult>("HandleUncertainExecutor")
|
||||
{
|
||||
/// <summary>
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Extensions.AI;
|
||||
using Microsoft.Extensions.Configuration;
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Extensions.Configuration;
|
||||
using OpenAI.Responses;
|
||||
@@ -275,7 +275,7 @@ internal sealed class Program
|
||||
Tools =
|
||||
{
|
||||
AgentTool.CreateOpenApiTool(
|
||||
new OpenAPIFunctionDefinition(
|
||||
new OpenApiFunctionDefinition(
|
||||
"weather-forecast",
|
||||
BinaryData.FromString(File.ReadAllText(Path.Combine(AppContext.BaseDirectory, "wttr.json"))),
|
||||
new OpenAPIAnonymousAuthenticationDetails()))
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Extensions.AI;
|
||||
using Microsoft.Extensions.Configuration;
|
||||
|
||||
@@ -3,8 +3,9 @@
|
||||
// Uncomment this to enable JSON checkpointing to the local file system.
|
||||
//#define CHECKPOINT_JSON
|
||||
|
||||
using Azure.AI.Extensions.OpenAI;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Extensions.Configuration;
|
||||
using OpenAI.Responses;
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Extensions.AI;
|
||||
using Microsoft.Extensions.Configuration;
|
||||
|
||||
@@ -5,7 +5,7 @@
|
||||
// invoked to perform specific tasks, like searching documentation or executing operations.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Core;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI.Workflows.Declarative.Mcp;
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Extensions.Configuration;
|
||||
using Shared.Foundry;
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Extensions.Configuration;
|
||||
using Shared.Foundry;
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Extensions.Configuration;
|
||||
using OpenAI.Responses;
|
||||
|
||||
@@ -38,6 +38,8 @@ internal enum NumberSignal
|
||||
/// <summary>
|
||||
/// Executor that judges the guess and provides feedback.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(NumberSignal))]
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class JudgeExecutor() : Executor<int>("Judge")
|
||||
{
|
||||
private readonly int _targetNumber;
|
||||
|
||||
@@ -56,6 +56,7 @@ internal enum NumberSignal
|
||||
/// <summary>
|
||||
/// Executor that makes a guess based on the current bounds.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(int))]
|
||||
internal sealed class GuessNumberExecutor : Executor<NumberSignal>
|
||||
{
|
||||
/// <summary>
|
||||
@@ -104,6 +105,8 @@ internal sealed class GuessNumberExecutor : Executor<NumberSignal>
|
||||
/// <summary>
|
||||
/// Executor that judges the guess and provides feedback.
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(NumberSignal))]
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class JudgeExecutor : Executor<int>
|
||||
{
|
||||
private readonly int _targetNumber;
|
||||
@@ -124,8 +127,7 @@ internal sealed class JudgeExecutor : Executor<int>
|
||||
this._tries++;
|
||||
if (message == this._targetNumber)
|
||||
{
|
||||
await context.YieldOutputAsync($"{this._targetNumber} found in {this._tries} tries!", cancellationToken)
|
||||
;
|
||||
await context.YieldOutputAsync($"{this._targetNumber} found in {this._tries} tries!", cancellationToken);
|
||||
}
|
||||
else if (message < this._targetNumber)
|
||||
{
|
||||
|
||||
@@ -99,6 +99,10 @@ internal sealed class ParagraphCountingExecutor() : Executor<string, FileStats>(
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The aggregation executor collects results from both executors and yields the final output.
|
||||
/// </summary>
|
||||
[YieldsOutput(typeof(string))]
|
||||
internal sealed class AggregationExecutor() : Executor<FileStats>("AggregationExecutor")
|
||||
{
|
||||
private readonly List<FileStats> _messages = [];
|
||||
|
||||
@@ -205,6 +205,8 @@ internal sealed class TextInverterExecutor(string id) : Executor<string, string>
|
||||
/// 1. Sending ChatMessage(s)
|
||||
/// 2. Sending a TurnToken to trigger processing
|
||||
/// </summary>
|
||||
[SendsMessage(typeof(ChatMessage))]
|
||||
[SendsMessage(typeof(TurnToken))]
|
||||
internal sealed class StringToChatMessageExecutor(string id) : Executor<string>(id)
|
||||
{
|
||||
public override async ValueTask HandleAsync(string message, IWorkflowContext context, CancellationToken cancellationToken = default)
|
||||
@@ -234,6 +236,8 @@ internal sealed class StringToChatMessageExecutor(string id) : Executor<string>(
|
||||
/// The AIAgentHostExecutor sends response.Messages which has runtime type List<ChatMessage>.
|
||||
/// The message router uses exact type matching via message.GetType().
|
||||
/// </remarks>
|
||||
[SendsMessage(typeof(ChatMessage))]
|
||||
[SendsMessage(typeof(TurnToken))]
|
||||
internal sealed class JailbreakSyncExecutor() : Executor<List<ChatMessage>>("JailbreakSync")
|
||||
{
|
||||
public override async ValueTask HandleAsync(List<ChatMessage> message, IWorkflowContext context, CancellationToken cancellationToken = default)
|
||||
|
||||
@@ -9,7 +9,7 @@
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Agents.Persistent" />
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.Identity" />
|
||||
</ItemGroup>
|
||||
|
||||
@@ -23,7 +23,7 @@
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Hosting.A2A\Microsoft.Agents.AI.Hosting.A2A.csproj" />
|
||||
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.A2A\Microsoft.Agents.AI.A2A.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
|
||||
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
using A2A;
|
||||
using Azure.AI.Agents.Persistent;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.Identity;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Extensions.AI;
|
||||
@@ -12,16 +12,15 @@ namespace A2AServer;
|
||||
|
||||
internal static class HostAgentFactory
|
||||
{
|
||||
internal static async Task<(AIAgent, AgentCard)> CreateFoundryHostAgentAsync(string agentType, string model, string endpoint, string assistantId, IList<AITool>? tools = null)
|
||||
internal static async Task<(AIAgent, AgentCard)> CreateFoundryHostAgentAsync(string agentType, string model, string endpoint, string agentName, IList<AITool>? tools = null)
|
||||
{
|
||||
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
|
||||
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
|
||||
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
|
||||
var persistentAgentsClient = new PersistentAgentsClient(endpoint, new DefaultAzureCredential());
|
||||
PersistentAgent persistentAgent = await persistentAgentsClient.Administration.GetAgentAsync(assistantId);
|
||||
var aiProjectClient = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential());
|
||||
|
||||
AIAgent agent = await persistentAgentsClient
|
||||
.GetAIAgentAsync(persistentAgent.Id, chatOptions: new() { Tools = tools });
|
||||
AIAgent agent = await aiProjectClient
|
||||
.GetAIAgentAsync(agentName, tools: tools);
|
||||
|
||||
AgentCard agentCard = agentType.ToUpperInvariant() switch
|
||||
{
|
||||
|
||||
@@ -8,16 +8,16 @@ using Microsoft.Extensions.AI;
|
||||
using Microsoft.Extensions.Configuration;
|
||||
using Microsoft.Extensions.DependencyInjection;
|
||||
|
||||
string agentId = string.Empty;
|
||||
string agentName = string.Empty;
|
||||
string agentType = string.Empty;
|
||||
|
||||
for (var i = 0; i < args.Length; i++)
|
||||
{
|
||||
if (args[i].StartsWith("--agentId", StringComparison.InvariantCultureIgnoreCase) && i + 1 < args.Length)
|
||||
if (args[i].Equals("--agentName", StringComparison.OrdinalIgnoreCase) && i + 1 < args.Length)
|
||||
{
|
||||
agentId = args[++i];
|
||||
agentName = args[++i];
|
||||
}
|
||||
else if (args[i].StartsWith("--agentType", StringComparison.InvariantCultureIgnoreCase) && i + 1 < args.Length)
|
||||
else if (args[i].Equals("--agentType", StringComparison.OrdinalIgnoreCase) && i + 1 < args.Length)
|
||||
{
|
||||
agentType = args[++i];
|
||||
}
|
||||
@@ -50,13 +50,13 @@ IList<AITool> tools =
|
||||
AIAgent hostA2AAgent;
|
||||
AgentCard hostA2AAgentCard;
|
||||
|
||||
if (!string.IsNullOrEmpty(endpoint) && !string.IsNullOrEmpty(agentId))
|
||||
if (!string.IsNullOrEmpty(endpoint) && !string.IsNullOrEmpty(agentName))
|
||||
{
|
||||
(hostA2AAgent, hostA2AAgentCard) = agentType.ToUpperInvariant() switch
|
||||
{
|
||||
"INVOICE" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, model, endpoint, agentId, tools),
|
||||
"POLICY" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, model, endpoint, agentId),
|
||||
"LOGISTICS" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, model, endpoint, agentId),
|
||||
"INVOICE" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, model, endpoint, agentName, tools),
|
||||
"POLICY" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, model, endpoint, agentName),
|
||||
"LOGISTICS" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, model, endpoint, agentName),
|
||||
_ => throw new ArgumentException($"Unsupported agent type: {agentType}"),
|
||||
};
|
||||
}
|
||||
@@ -101,7 +101,7 @@ else if (!string.IsNullOrEmpty(apiKey))
|
||||
}
|
||||
else
|
||||
{
|
||||
throw new ArgumentException("Either A2AServer:ApiKey or A2AServer:ConnectionString & agentId must be provided");
|
||||
throw new ArgumentException("Either A2AServer:ApiKey or A2AServer:ConnectionString & agentName must be provided");
|
||||
}
|
||||
|
||||
var a2aTaskManager = app.MapA2A(
|
||||
|
||||
@@ -90,15 +90,15 @@ $env:AZURE_AI_PROJECT_ENDPOINT="https://ai-foundry-your-project.services.ai.azur
|
||||
Use the following commands to run each A2A server
|
||||
|
||||
```bash
|
||||
dotnet run --urls "http://localhost:5000;https://localhost:5010" --agentId "<Invoice Agent Id>" --agentType "invoice" --no-build
|
||||
dotnet run --urls "http://localhost:5000;https://localhost:5010" --agentName "<Invoice Agent Name>" --agentType "invoice" --no-build
|
||||
```
|
||||
|
||||
```bash
|
||||
dotnet run --urls "http://localhost:5001;https://localhost:5011" --agentId "<Policy Agent Id>" --agentType "policy" --no-build
|
||||
dotnet run --urls "http://localhost:5001;https://localhost:5011" --agentName "<Policy Agent Name>" --agentType "policy" --no-build
|
||||
```
|
||||
|
||||
```bash
|
||||
dotnet run --urls "http://localhost:5002;https://localhost:5012" --agentId "<Logistics Agent Id>" --agentType "logistics" --no-build
|
||||
dotnet run --urls "http://localhost:5002;https://localhost:5012" --agentName "<Logistics Agent Name>" --agentType "logistics" --no-build
|
||||
```
|
||||
|
||||
### Testing the Agents using the Rest Client
|
||||
|
||||
+1
-1
@@ -27,7 +27,7 @@ internal sealed class OpenAIResponsesAgentClient(HttpClient httpClient) : AgentC
|
||||
Transport = new HttpClientPipelineTransport(httpClient)
|
||||
};
|
||||
|
||||
var openAiClient = new ResponsesClient(model: agentName, credential: new ApiKeyCredential("dummy-key"), options: options).AsIChatClient();
|
||||
var openAiClient = new ResponsesClient(credential: new ApiKeyCredential("dummy-key"), options: options).AsIChatClient(agentName);
|
||||
var chatOptions = new ChatOptions()
|
||||
{
|
||||
ConversationId = sessionId
|
||||
|
||||
@@ -30,8 +30,8 @@ TokenCredential browserCredential = new InteractiveBrowserCredential(
|
||||
using IChatClient client = new AzureOpenAIClient(
|
||||
new Uri(endpoint),
|
||||
new DefaultAzureCredential())
|
||||
.GetResponsesClient(deploymentName)
|
||||
.AsIChatClient()
|
||||
.GetResponsesClient()
|
||||
.AsIChatClient(deploymentName)
|
||||
.AsBuilder()
|
||||
.WithPurview(browserCredential, new PurviewSettings("Agent Framework Test App"))
|
||||
.Build();
|
||||
|
||||
+1
-1
@@ -37,7 +37,7 @@
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
|
||||
</ItemGroup>
|
||||
|
||||
+2
-1
@@ -36,9 +36,10 @@
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
|
||||
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="10.4.0" />
|
||||
</ItemGroup>
|
||||
|
||||
<!-- Add analyzers with compatible versions -->
|
||||
|
||||
@@ -31,7 +31,8 @@ AITool mcpTool = new HostedMcpServerTool(serverName: "microsoft_learn", serverAd
|
||||
AIAgent agent = new AzureOpenAIClient(
|
||||
new Uri(endpoint),
|
||||
new DefaultAzureCredential())
|
||||
.GetResponsesClient(deploymentName)
|
||||
.GetResponsesClient()
|
||||
.AsIChatClient(deploymentName)
|
||||
.AsAIAgent(
|
||||
instructions: "You answer questions by searching the Microsoft Learn content only.",
|
||||
name: "MicrosoftLearnAgent",
|
||||
|
||||
+1
-1
@@ -38,7 +38,7 @@
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
|
||||
<PackageReference Include="Azure.AI.Projects" Version="1.2.0-beta.5" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
|
||||
</ItemGroup>
|
||||
|
||||
+1
-1
@@ -36,7 +36,7 @@
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.7.0-beta.2" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
|
||||
</ItemGroup>
|
||||
|
||||
@@ -36,7 +36,7 @@
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
|
||||
</ItemGroup>
|
||||
|
||||
+1
-1
@@ -36,7 +36,7 @@
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.7.0-beta.2" />
|
||||
<PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
|
||||
<PackageReference Include="Azure.Identity" Version="1.17.1" />
|
||||
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
|
||||
</ItemGroup>
|
||||
|
||||
@@ -122,7 +122,7 @@ internal sealed class AFAgentApplication : AgentApplication
|
||||
&& valueElement.GetProperty("requestJson") is JsonElement requestJsonElement
|
||||
&& requestJsonElement.ValueKind == JsonValueKind.String)
|
||||
{
|
||||
var requestContent = JsonSerializer.Deserialize<FunctionApprovalRequestContent>(requestJsonElement.GetString()!, JsonUtilities.DefaultOptions);
|
||||
var requestContent = JsonSerializer.Deserialize<ToolApprovalRequestContent>(requestJsonElement.GetString()!, JsonUtilities.DefaultOptions);
|
||||
|
||||
return new ChatMessage(ChatRole.User, [requestContent!.CreateResponse(approvedJsonElement.ValueKind == JsonValueKind.True)]);
|
||||
}
|
||||
@@ -138,7 +138,7 @@ internal sealed class AFAgentApplication : AgentApplication
|
||||
/// <param name="attachments">The list of <see cref="Attachment"/> to which the adaptive cards will be added.</param>
|
||||
private static void HandleUserInputRequests(AgentResponse response, ref List<Attachment>? attachments)
|
||||
{
|
||||
foreach (FunctionApprovalRequestContent functionApprovalRequest in response.Messages.SelectMany(m => m.Contents).OfType<FunctionApprovalRequestContent>())
|
||||
foreach (ToolApprovalRequestContent functionApprovalRequest in response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>())
|
||||
{
|
||||
var functionApprovalRequestJson = JsonSerializer.Serialize(functionApprovalRequest, JsonUtilities.DefaultOptions);
|
||||
|
||||
@@ -152,7 +152,7 @@ internal sealed class AFAgentApplication : AgentApplication
|
||||
});
|
||||
card.Body.Add(new AdaptiveTextBlock
|
||||
{
|
||||
Text = $"Function: {functionApprovalRequest.FunctionCall.Name}"
|
||||
Text = $"Function: {((FunctionCallContent)functionApprovalRequest.ToolCall).Name}"
|
||||
});
|
||||
card.Body.Add(new AdaptiveActionSet()
|
||||
{
|
||||
|
||||
+2
@@ -20,6 +20,8 @@
|
||||
<!-- NuGet Package Settings -->
|
||||
<Title>Microsoft Agent Framework AzureAI Persistent Agents</Title>
|
||||
<Description>Provides Microsoft Agent Framework support for Azure AI Persistent Agents.</Description>
|
||||
<!-- Disabled until Azure.AI.Agents.Persistent targets ME.AI 10.4.0+ (https://github.com/microsoft/agent-framework/issues/4769) -->
|
||||
<IsPackable>false</IsPackable>
|
||||
</PropertyGroup>
|
||||
|
||||
</Project>
|
||||
|
||||
@@ -19,6 +19,7 @@ public static class PersistentAgentsClientExtensions
|
||||
/// <param name="clientFactory">Provides a way to customize the creation of the underlying <see cref="IChatClient"/> used by the agent.</param>
|
||||
/// <param name="services">An optional <see cref="IServiceProvider"/> to use for resolving services required by the <see cref="AIFunction"/> instances being invoked.</param>
|
||||
/// <returns>A <see cref="ChatClientAgent"/> instance that can be used to perform operations on the persistent agent.</returns>
|
||||
[Obsolete("Please use the latest Foundry Agents service via the Microsoft.Agents.AI.AzureAI package.")]
|
||||
public static ChatClientAgent AsAIAgent(
|
||||
this PersistentAgentsClient persistentAgentsClient,
|
||||
Response<PersistentAgent> persistentAgentResponse,
|
||||
@@ -43,6 +44,7 @@ public static class PersistentAgentsClientExtensions
|
||||
/// <param name="clientFactory">Provides a way to customize the creation of the underlying <see cref="IChatClient"/> used by the agent.</param>
|
||||
/// <param name="services">An optional <see cref="IServiceProvider"/> to use for resolving services required by the <see cref="AIFunction"/> instances being invoked.</param>
|
||||
/// <returns>A <see cref="ChatClientAgent"/> instance that can be used to perform operations on the persistent agent.</returns>
|
||||
[Obsolete("Please use the latest Foundry Agents service via the Microsoft.Agents.AI.AzureAI package.")]
|
||||
public static ChatClientAgent AsAIAgent(
|
||||
this PersistentAgentsClient persistentAgentsClient,
|
||||
PersistentAgent persistentAgentMetadata,
|
||||
@@ -93,6 +95,7 @@ public static class PersistentAgentsClientExtensions
|
||||
/// <param name="services">An optional <see cref="IServiceProvider"/> to use for resolving services required by the <see cref="AIFunction"/> instances being invoked.</param>
|
||||
/// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
|
||||
/// <returns>A <see cref="ChatClientAgent"/> instance that can be used to perform operations on the persistent agent.</returns>
|
||||
[Obsolete("Please use the latest Foundry Agents service via the Microsoft.Agents.AI.AzureAI package.")]
|
||||
public static async Task<ChatClientAgent> GetAIAgentAsync(
|
||||
this PersistentAgentsClient persistentAgentsClient,
|
||||
string agentId,
|
||||
@@ -125,6 +128,7 @@ public static class PersistentAgentsClientExtensions
|
||||
/// <param name="services">An optional <see cref="IServiceProvider"/> to use for resolving services required by the <see cref="AIFunction"/> instances being invoked.</param>
|
||||
/// <returns>A <see cref="ChatClientAgent"/> instance that can be used to perform operations on the persistent agent.</returns>
|
||||
/// <exception cref="ArgumentNullException">Thrown when <paramref name="persistentAgentResponse"/> or <paramref name="options"/> is <see langword="null"/>.</exception>
|
||||
[Obsolete("Please use the latest Foundry Agents service via the Microsoft.Agents.AI.AzureAI package.")]
|
||||
public static ChatClientAgent AsAIAgent(
|
||||
this PersistentAgentsClient persistentAgentsClient,
|
||||
Response<PersistentAgent> persistentAgentResponse,
|
||||
@@ -150,6 +154,7 @@ public static class PersistentAgentsClientExtensions
|
||||
/// <param name="services">An optional <see cref="IServiceProvider"/> to use for resolving services required by the <see cref="AIFunction"/> instances being invoked.</param>
|
||||
/// <returns>A <see cref="ChatClientAgent"/> instance that can be used to perform operations on the persistent agent.</returns>
|
||||
/// <exception cref="ArgumentNullException">Thrown when <paramref name="persistentAgentMetadata"/> or <paramref name="options"/> is <see langword="null"/>.</exception>
|
||||
[Obsolete("Please use the latest Foundry Agents service via the Microsoft.Agents.AI.AzureAI package.")]
|
||||
public static ChatClientAgent AsAIAgent(
|
||||
this PersistentAgentsClient persistentAgentsClient,
|
||||
PersistentAgent persistentAgentMetadata,
|
||||
@@ -211,6 +216,7 @@ public static class PersistentAgentsClientExtensions
|
||||
/// <returns>A <see cref="ChatClientAgent"/> instance that can be used to perform operations on the persistent agent.</returns>
|
||||
/// <exception cref="ArgumentNullException">Thrown when <paramref name="persistentAgentsClient"/> or <paramref name="options"/> is <see langword="null"/>.</exception>
|
||||
/// <exception cref="ArgumentException">Thrown when <paramref name="agentId"/> is empty or whitespace.</exception>
|
||||
[Obsolete("Please use the latest Foundry Agents service via the Microsoft.Agents.AI.AzureAI package.")]
|
||||
public static async Task<ChatClientAgent> GetAIAgentAsync(
|
||||
this PersistentAgentsClient persistentAgentsClient,
|
||||
string agentId,
|
||||
@@ -256,6 +262,7 @@ public static class PersistentAgentsClientExtensions
|
||||
/// <param name="services">An optional <see cref="IServiceProvider"/> to use for resolving services required by the <see cref="AIFunction"/> instances being invoked.</param>
|
||||
/// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
|
||||
/// <returns>A <see cref="ChatClientAgent"/> instance that can be used to perform operations on the newly created agent.</returns>
|
||||
[Obsolete("Please use the latest Foundry Agents service via the Microsoft.Agents.AI.AzureAI package.")]
|
||||
public static async Task<ChatClientAgent> CreateAIAgentAsync(
|
||||
this PersistentAgentsClient persistentAgentsClient,
|
||||
string model,
|
||||
@@ -306,6 +313,7 @@ public static class PersistentAgentsClientExtensions
|
||||
/// <returns>A <see cref="ChatClientAgent"/> instance that can be used to perform operations on the newly created agent.</returns>
|
||||
/// <exception cref="ArgumentNullException">Thrown when <paramref name="persistentAgentsClient"/> or <paramref name="model"/> or <paramref name="options"/> is <see langword="null"/>.</exception>
|
||||
/// <exception cref="ArgumentException">Thrown when <paramref name="model"/> is empty or whitespace.</exception>
|
||||
[Obsolete("Please use the latest Foundry Agents service via the Microsoft.Agents.AI.AzureAI package.")]
|
||||
public static async Task<ChatClientAgent> CreateAIAgentAsync(
|
||||
this PersistentAgentsClient persistentAgentsClient,
|
||||
string model,
|
||||
|
||||
@@ -0,0 +1,19 @@
|
||||
# Microsoft.Agents.AI.AzureAI.Persistent
|
||||
|
||||
Provides integration between the Microsoft Agent Framework and Azure AI Agents Persistent (`Azure.AI.Agents.Persistent`).
|
||||
|
||||
## ⚠️ Known Compatibility Limitation
|
||||
|
||||
The underlying `Azure.AI.Agents.Persistent` package (currently 1.2.0-beta.9) targets `Microsoft.Extensions.AI.Abstractions` 10.1.x and references types that were renamed in 10.4.0 (e.g., `McpServerToolApprovalResponseContent` → `ToolApprovalResponseContent`). This causes `TypeLoadException` at runtime when used with ME.AI 10.4.0+.
|
||||
|
||||
**Compatible versions:**
|
||||
|
||||
| Package | Compatible Version |
|
||||
|---|---|
|
||||
| `Azure.AI.Agents.Persistent` | 1.2.0-beta.9 (targets ME.AI 10.1.x) |
|
||||
| `Microsoft.Extensions.AI.Abstractions` | ≤ 10.3.0 |
|
||||
| `OpenAI` | ≤ 2.8.0 |
|
||||
|
||||
**Resolution:** An updated version of `Azure.AI.Agents.Persistent` targeting ME.AI 10.4.0+ is expected in 1.2.0-beta.10. The upstream fix is tracked in [Azure/azure-sdk-for-net#56929](https://github.com/Azure/azure-sdk-for-net/pull/56929).
|
||||
|
||||
**Tracking issue:** [microsoft/agent-framework#4769](https://github.com/microsoft/agent-framework/issues/4769)
|
||||
@@ -2,8 +2,9 @@
|
||||
|
||||
using System.Diagnostics.CodeAnalysis;
|
||||
using System.Runtime.CompilerServices;
|
||||
using Azure.AI.Extensions.OpenAI;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Microsoft.Extensions.AI;
|
||||
using Microsoft.Shared.DiagnosticIds;
|
||||
using Microsoft.Shared.Diagnostics;
|
||||
@@ -57,7 +58,7 @@ internal sealed class AzureAIProjectChatClient : DelegatingChatClient
|
||||
/// The <see cref="IChatClient"/> provided should be decorated with a <see cref="AzureAIProjectChatClient"/> for proper functionality.
|
||||
/// </remarks>
|
||||
internal AzureAIProjectChatClient(AIProjectClient aiProjectClient, AgentRecord agentRecord, ChatOptions? chatOptions)
|
||||
: this(aiProjectClient, Throw.IfNull(agentRecord).Versions.Latest, chatOptions)
|
||||
: this(aiProjectClient, Throw.IfNull(agentRecord).GetLatestVersion(), chatOptions)
|
||||
{
|
||||
this._agentRecord = agentRecord;
|
||||
}
|
||||
|
||||
@@ -9,7 +9,8 @@ using System.Text.Json;
|
||||
using System.Text.Json.Nodes;
|
||||
using System.Text.Json.Serialization;
|
||||
using System.Text.RegularExpressions;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Extensions.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Microsoft.Agents.AI;
|
||||
using Microsoft.Agents.AI.AzureAI;
|
||||
using Microsoft.Extensions.AI;
|
||||
@@ -189,7 +190,7 @@ public static partial class AzureAIProjectChatClientExtensions
|
||||
ThrowIfInvalidAgentName(options.Name);
|
||||
|
||||
AgentRecord agentRecord = await GetAgentRecordByNameAsync(aiProjectClient, options.Name, cancellationToken).ConfigureAwait(false);
|
||||
var agentVersion = agentRecord.Versions.Latest;
|
||||
var agentVersion = agentRecord.GetLatestVersion();
|
||||
|
||||
var agentOptions = CreateChatClientAgentOptions(agentVersion, options, requireInvocableTools: !options.UseProvidedChatClientAsIs);
|
||||
|
||||
@@ -361,7 +362,7 @@ public static partial class AzureAIProjectChatClientExtensions
|
||||
{
|
||||
ClientResult protocolResponse = await aiProjectClient.Agents.GetAgentAsync(agentName, cancellationToken.ToRequestOptions(false)).ConfigureAwait(false);
|
||||
var rawResponse = protocolResponse.GetRawResponse();
|
||||
AgentRecord? result = ModelReaderWriter.Read<AgentRecord>(rawResponse.Content, s_modelWriterOptionsWire, AzureAIProjectsOpenAIContext.Default);
|
||||
AgentRecord? result = ModelReaderWriter.Read<AgentRecord>(rawResponse.Content, s_modelWriterOptionsWire, AzureAIProjectsAgentsContext.Default);
|
||||
return result ?? throw new InvalidOperationException($"Agent with name '{agentName}' not found.");
|
||||
}
|
||||
|
||||
@@ -370,11 +371,11 @@ public static partial class AzureAIProjectChatClientExtensions
|
||||
/// </summary>
|
||||
private static async Task<AgentVersion> CreateAgentVersionWithProtocolAsync(AIProjectClient aiProjectClient, string agentName, AgentVersionCreationOptions creationOptions, CancellationToken cancellationToken)
|
||||
{
|
||||
BinaryData serializedOptions = ModelReaderWriter.Write(creationOptions, s_modelWriterOptionsWire, AzureAIProjectsContext.Default);
|
||||
BinaryData serializedOptions = ModelReaderWriter.Write(creationOptions, s_modelWriterOptionsWire, AzureAIProjectsAgentsContext.Default);
|
||||
BinaryContent content = BinaryContent.Create(serializedOptions);
|
||||
ClientResult protocolResponse = await aiProjectClient.Agents.CreateAgentVersionAsync(agentName, content, foundryFeatures: null, cancellationToken.ToRequestOptions(false)).ConfigureAwait(false);
|
||||
var rawResponse = protocolResponse.GetRawResponse();
|
||||
AgentVersion? result = ModelReaderWriter.Read<AgentVersion>(rawResponse.Content, s_modelWriterOptionsWire, AzureAIProjectsOpenAIContext.Default);
|
||||
AgentVersion? result = ModelReaderWriter.Read<AgentVersion>(rawResponse.Content, s_modelWriterOptionsWire, AzureAIProjectsAgentsContext.Default);
|
||||
return result ?? throw new InvalidOperationException($"Failed to create agent version for agent '{agentName}'.");
|
||||
}
|
||||
|
||||
@@ -485,7 +486,7 @@ public static partial class AzureAIProjectChatClientExtensions
|
||||
=> AsChatClientAgent(
|
||||
AIProjectClient,
|
||||
agentRecord,
|
||||
CreateChatClientAgentOptions(agentRecord.Versions.Latest, new ChatOptions() { Tools = tools }, requireInvocableTools),
|
||||
CreateChatClientAgentOptions(agentRecord.GetLatestVersion(), new ChatOptions() { Tools = tools }, requireInvocableTools),
|
||||
clientFactory,
|
||||
services);
|
||||
|
||||
|
||||
@@ -15,7 +15,6 @@
|
||||
|
||||
<ItemGroup>
|
||||
<PackageReference Include="Azure.AI.Projects" />
|
||||
<PackageReference Include="Azure.AI.Projects.OpenAI" />
|
||||
<PackageReference Include="Microsoft.Extensions.AI" />
|
||||
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
|
||||
<PackageReference Include="OpenAI" />
|
||||
|
||||
+2
-2
@@ -196,8 +196,8 @@ internal static class AgentResponseUpdateExtensions
|
||||
TextReasoningContent => new TextReasoningContentEventGenerator(context.IdGenerator, seq, outputIndex),
|
||||
FunctionCallContent => new FunctionCallEventGenerator(context.IdGenerator, seq, outputIndex, context.JsonSerializerOptions),
|
||||
FunctionResultContent => new FunctionResultEventGenerator(context.IdGenerator, seq, outputIndex),
|
||||
FunctionApprovalRequestContent => new FunctionApprovalRequestEventGenerator(context.IdGenerator, seq, outputIndex, context.JsonSerializerOptions),
|
||||
FunctionApprovalResponseContent => new FunctionApprovalResponseEventGenerator(context.IdGenerator, seq, outputIndex),
|
||||
ToolApprovalRequestContent => new ToolApprovalRequestEventGenerator(context.IdGenerator, seq, outputIndex, context.JsonSerializerOptions),
|
||||
ToolApprovalResponseContent => new ToolApprovalResponseEventGenerator(context.IdGenerator, seq, outputIndex),
|
||||
ErrorContent => new ErrorContentEventGenerator(context.IdGenerator, seq, outputIndex),
|
||||
UriContent uriContent when uriContent.HasTopLevelMediaType("image") => new ImageContentEventGenerator(context.IdGenerator, seq, outputIndex),
|
||||
DataContent dataContent when dataContent.HasTopLevelMediaType("image") => new ImageContentEventGenerator(context.IdGenerator, seq, outputIndex),
|
||||
|
||||
+12
-8
@@ -12,33 +12,37 @@ namespace Microsoft.Agents.AI.Hosting.OpenAI.Responses.Streaming;
|
||||
/// A generator for streaming events from function approval request content.
|
||||
/// This is a non-standard DevUI extension for human-in-the-loop scenarios.
|
||||
/// </summary>
|
||||
internal sealed class FunctionApprovalRequestEventGenerator(
|
||||
internal sealed class ToolApprovalRequestEventGenerator(
|
||||
IdGenerator idGenerator,
|
||||
SequenceNumber seq,
|
||||
int outputIndex,
|
||||
JsonSerializerOptions jsonSerializerOptions) : StreamingEventGenerator
|
||||
{
|
||||
public override bool IsSupported(AIContent content) => content is FunctionApprovalRequestContent;
|
||||
public override bool IsSupported(AIContent content) => content is ToolApprovalRequestContent;
|
||||
|
||||
public override IEnumerable<StreamingResponseEvent> ProcessContent(AIContent content)
|
||||
{
|
||||
if (content is not FunctionApprovalRequestContent approvalRequest)
|
||||
if (content is not ToolApprovalRequestContent approvalRequest)
|
||||
{
|
||||
throw new InvalidOperationException("FunctionApprovalRequestEventGenerator only supports FunctionApprovalRequestContent.");
|
||||
throw new InvalidOperationException("ToolApprovalRequestEventGenerator only supports ToolApprovalRequestContent.");
|
||||
}
|
||||
|
||||
if (approvalRequest.ToolCall is not FunctionCallContent functionCall)
|
||||
{
|
||||
yield break;
|
||||
}
|
||||
yield return new StreamingFunctionApprovalRequested
|
||||
{
|
||||
SequenceNumber = seq.Increment(),
|
||||
OutputIndex = outputIndex,
|
||||
RequestId = approvalRequest.Id,
|
||||
RequestId = approvalRequest.RequestId,
|
||||
ItemId = idGenerator.GenerateMessageId(),
|
||||
FunctionCall = new FunctionCallInfo
|
||||
{
|
||||
Id = approvalRequest.FunctionCall.CallId,
|
||||
Name = approvalRequest.FunctionCall.Name,
|
||||
Id = functionCall.CallId,
|
||||
Name = functionCall.Name,
|
||||
Arguments = JsonSerializer.SerializeToElement(
|
||||
approvalRequest.FunctionCall.Arguments,
|
||||
functionCall.Arguments,
|
||||
jsonSerializerOptions.GetTypeInfo(typeof(IDictionary<string, object>)))
|
||||
}
|
||||
};
|
||||
|
||||
+5
-5
@@ -11,25 +11,25 @@ namespace Microsoft.Agents.AI.Hosting.OpenAI.Responses.Streaming;
|
||||
/// A generator for streaming events from function approval response content.
|
||||
/// This is a non-standard DevUI extension for human-in-the-loop scenarios.
|
||||
/// </summary>
|
||||
internal sealed class FunctionApprovalResponseEventGenerator(
|
||||
internal sealed class ToolApprovalResponseEventGenerator(
|
||||
IdGenerator idGenerator,
|
||||
SequenceNumber seq,
|
||||
int outputIndex) : StreamingEventGenerator
|
||||
{
|
||||
public override bool IsSupported(AIContent content) => content is FunctionApprovalResponseContent;
|
||||
public override bool IsSupported(AIContent content) => content is ToolApprovalResponseContent;
|
||||
|
||||
public override IEnumerable<StreamingResponseEvent> ProcessContent(AIContent content)
|
||||
{
|
||||
if (content is not FunctionApprovalResponseContent approvalResponse)
|
||||
if (content is not ToolApprovalResponseContent approvalResponse)
|
||||
{
|
||||
throw new InvalidOperationException("FunctionApprovalResponseEventGenerator only supports FunctionApprovalResponseContent.");
|
||||
throw new InvalidOperationException("ToolApprovalResponseEventGenerator only supports ToolApprovalResponseContent.");
|
||||
}
|
||||
|
||||
yield return new StreamingFunctionApprovalResponded
|
||||
{
|
||||
SequenceNumber = seq.Increment(),
|
||||
OutputIndex = outputIndex,
|
||||
RequestId = approvalResponse.Id,
|
||||
RequestId = approvalResponse.RequestId,
|
||||
Approved = approvalResponse.Approved,
|
||||
ItemId = idGenerator.GenerateMessageId()
|
||||
};
|
||||
|
||||
+2
@@ -1,5 +1,7 @@
|
||||
// Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
#pragma warning disable OPENAI001 // Experimental OpenAI features
|
||||
|
||||
using System.ClientModel;
|
||||
using OpenAI.Chat;
|
||||
|
||||
|
||||
@@ -26,6 +26,7 @@ public static class OpenAIResponseClientExtensions
|
||||
/// Creates an AI agent from an <see cref="ResponsesClient"/> using the OpenAI Response API.
|
||||
/// </summary>
|
||||
/// <param name="client">The <see cref="ResponsesClient" /> to use for the agent.</param>
|
||||
/// <param name="model">Optional default model ID to use for requests. Required when using a plain <see cref="ResponsesClient"/> (not via Azure OpenAI).</param>
|
||||
/// <param name="instructions">Optional system instructions that define the agent's behavior and personality.</param>
|
||||
/// <param name="name">Optional name for the agent for identification purposes.</param>
|
||||
/// <param name="description">Optional description of the agent's capabilities and purpose.</param>
|
||||
@@ -37,6 +38,7 @@ public static class OpenAIResponseClientExtensions
|
||||
/// <exception cref="ArgumentNullException">Thrown when <paramref name="client"/> is <see langword="null"/>.</exception>
|
||||
public static ChatClientAgent AsAIAgent(
|
||||
this ResponsesClient client,
|
||||
string? model = null,
|
||||
string? instructions = null,
|
||||
string? name = null,
|
||||
string? description = null,
|
||||
@@ -58,6 +60,7 @@ public static class OpenAIResponseClientExtensions
|
||||
Tools = tools,
|
||||
}
|
||||
},
|
||||
model,
|
||||
clientFactory,
|
||||
loggerFactory,
|
||||
services);
|
||||
@@ -68,6 +71,7 @@ public static class OpenAIResponseClientExtensions
|
||||
/// </summary>
|
||||
/// <param name="client">The <see cref="ResponsesClient" /> to use for the agent.</param>
|
||||
/// <param name="options">Full set of options to configure the agent.</param>
|
||||
/// <param name="model">Optional default model ID to use for requests. Required when using a plain <see cref="ResponsesClient"/> (not via Azure OpenAI).</param>
|
||||
/// <param name="clientFactory">Provides a way to customize the creation of the underlying <see cref="IChatClient"/> used by the agent.</param>
|
||||
/// <param name="loggerFactory">Optional logger factory for enabling logging within the agent.</param>
|
||||
/// <param name="services">An optional <see cref="IServiceProvider"/> to use for resolving services required by the <see cref="AIFunction"/> instances being invoked.</param>
|
||||
@@ -76,6 +80,7 @@ public static class OpenAIResponseClientExtensions
|
||||
public static ChatClientAgent AsAIAgent(
|
||||
this ResponsesClient client,
|
||||
ChatClientAgentOptions options,
|
||||
string? model = null,
|
||||
Func<IChatClient, IChatClient>? clientFactory = null,
|
||||
ILoggerFactory? loggerFactory = null,
|
||||
IServiceProvider? services = null)
|
||||
@@ -83,7 +88,7 @@ public static class OpenAIResponseClientExtensions
|
||||
Throw.IfNull(client);
|
||||
Throw.IfNull(options);
|
||||
|
||||
var chatClient = client.AsIChatClient();
|
||||
var chatClient = client.AsIChatClient(model);
|
||||
|
||||
if (clientFactory is not null)
|
||||
{
|
||||
@@ -100,6 +105,7 @@ public static class OpenAIResponseClientExtensions
|
||||
/// This corresponds to setting the "store" property in the JSON representation to false.
|
||||
/// </remarks>
|
||||
/// <param name="responseClient">The client.</param>
|
||||
/// <param name="model">Optional default model ID to use for requests. Required when using a plain <see cref="ResponsesClient"/> (not via Azure OpenAI).</param>
|
||||
/// <param name="includeReasoningEncryptedContent">
|
||||
/// Includes an encrypted version of reasoning tokens in reasoning item outputs.
|
||||
/// This enables reasoning items to be used in multi-turn conversations when using the Responses API statelessly
|
||||
@@ -109,10 +115,10 @@ public static class OpenAIResponseClientExtensions
|
||||
/// <returns>An <see cref="IChatClient"/> that can be used to converse via the <see cref="ResponsesClient"/> that does not store responses for later retrieval.</returns>
|
||||
/// <exception cref="ArgumentNullException"><paramref name="responseClient"/> is <see langword="null"/>.</exception>
|
||||
[Experimental(DiagnosticIds.Experiments.AgentsAIExperiments)]
|
||||
public static IChatClient AsIChatClientWithStoredOutputDisabled(this ResponsesClient responseClient, bool includeReasoningEncryptedContent = true)
|
||||
public static IChatClient AsIChatClientWithStoredOutputDisabled(this ResponsesClient responseClient, string? model = null, bool includeReasoningEncryptedContent = true)
|
||||
{
|
||||
return Throw.IfNull(responseClient)
|
||||
.AsIChatClient()
|
||||
.AsIChatClient(model)
|
||||
.AsBuilder()
|
||||
.ConfigureOptions(x => x.RawRepresentationFactory = _ => includeReasoningEncryptedContent
|
||||
? new CreateResponseOptions() { StoredOutputEnabled = false, IncludedProperties = { IncludedResponseProperty.ReasoningEncryptedContent } }
|
||||
|
||||
@@ -10,8 +10,9 @@ using System.Runtime.CompilerServices;
|
||||
using System.Text.Json.Nodes;
|
||||
using System.Threading;
|
||||
using System.Threading.Tasks;
|
||||
using Azure.AI.Extensions.OpenAI;
|
||||
using Azure.AI.Projects;
|
||||
using Azure.AI.Projects.OpenAI;
|
||||
using Azure.AI.Projects.Agents;
|
||||
using Azure.Core;
|
||||
using Microsoft.Extensions.AI;
|
||||
using OpenAI.Responses;
|
||||
@@ -149,7 +150,7 @@ public sealed class AzureAgentProvider(Uri projectEndpoint, TokenCredential proj
|
||||
agentName,
|
||||
cancellationToken).ConfigureAwait(false);
|
||||
|
||||
targetAgent = agentRecord.Versions.Latest;
|
||||
targetAgent = agentRecord.GetLatestVersion();
|
||||
}
|
||||
else
|
||||
{
|
||||
|
||||
@@ -185,8 +185,8 @@ public sealed class DefaultMcpToolHandler : IMcpToolHandler, IAsyncDisposable
|
||||
|
||||
private static void PopulateResultContent(McpServerToolResultContent resultContent, CallToolResult result)
|
||||
{
|
||||
// Ensure Output list is initialized
|
||||
resultContent.Output ??= [];
|
||||
// Ensure Outputs list is initialized
|
||||
resultContent.Outputs ??= [];
|
||||
|
||||
if (result.IsError == true)
|
||||
{
|
||||
@@ -203,7 +203,7 @@ public sealed class DefaultMcpToolHandler : IMcpToolHandler, IAsyncDisposable
|
||||
}
|
||||
}
|
||||
|
||||
resultContent.Output.Add(new TextContent($"Error: {errorText ?? "Unknown error from MCP Server call"}"));
|
||||
resultContent.Outputs.Add(new TextContent($"Error: {errorText ?? "Unknown error from MCP Server call"}"));
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -218,7 +218,7 @@ public sealed class DefaultMcpToolHandler : IMcpToolHandler, IAsyncDisposable
|
||||
AIContent content = ConvertContentBlock(block);
|
||||
if (content is not null)
|
||||
{
|
||||
resultContent.Output.Add(content);
|
||||
resultContent.Outputs.Add(content);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
+1
-1
@@ -150,7 +150,7 @@ internal sealed class InvokeAzureAgentExecutor(InvokeAzureAgent model, ResponseA
|
||||
|
||||
foreach (ChatMessage responseMessage in agentResponse.Messages)
|
||||
{
|
||||
if (responseMessage.Contents.Any(content => content is UserInputRequestContent))
|
||||
if (responseMessage.Contents.Any(content => content is ToolApprovalRequestContent))
|
||||
{
|
||||
yield return responseMessage;
|
||||
continue;
|
||||
|
||||
+1
-1
@@ -68,7 +68,7 @@ internal sealed class InvokeFunctionToolExecutor(
|
||||
// If approval is required, add user input request content
|
||||
if (requireApproval)
|
||||
{
|
||||
requestMessage.Contents.Add(new FunctionApprovalRequestContent(this.Id, functionCall));
|
||||
requestMessage.Contents.Add(new ToolApprovalRequestContent(this.Id, functionCall));
|
||||
}
|
||||
|
||||
AgentResponse agentResponse = new([requestMessage]);
|
||||
|
||||
+8
-9
@@ -85,7 +85,7 @@ internal sealed class InvokeMcpToolExecutor(
|
||||
toolCall.AdditionalProperties.Add(headers);
|
||||
}
|
||||
|
||||
McpServerToolApprovalRequestContent approvalRequest = new(this.Id, toolCall);
|
||||
ToolApprovalRequestContent approvalRequest = new(this.Id, toolCall);
|
||||
|
||||
ChatMessage requestMessage = new(ChatRole.Assistant, [approvalRequest]);
|
||||
AgentResponse agentResponse = new([requestMessage]);
|
||||
@@ -127,11 +127,10 @@ internal sealed class InvokeMcpToolExecutor(
|
||||
ExternalInputResponse response,
|
||||
CancellationToken cancellationToken)
|
||||
{
|
||||
// Check for approval response
|
||||
McpServerToolApprovalResponseContent? approvalResponse = response.Messages
|
||||
ToolApprovalResponseContent? approvalResponse = response.Messages
|
||||
.SelectMany(m => m.Contents)
|
||||
.OfType<McpServerToolApprovalResponseContent>()
|
||||
.FirstOrDefault(r => r.Id == this.Id);
|
||||
.OfType<ToolApprovalResponseContent>()
|
||||
.FirstOrDefault(r => r.RequestId == this.Id);
|
||||
|
||||
if (approvalResponse?.Approved != true)
|
||||
{
|
||||
@@ -174,7 +173,7 @@ internal sealed class InvokeMcpToolExecutor(
|
||||
string? conversationId = this.GetConversationId();
|
||||
|
||||
await this.AssignResultAsync(context, resultContent).ConfigureAwait(false);
|
||||
ChatMessage resultMessage = new(ChatRole.Tool, resultContent.Output);
|
||||
ChatMessage resultMessage = new(ChatRole.Tool, resultContent.Outputs);
|
||||
|
||||
// Store messages if output path is configured
|
||||
if (this.Model.Output?.Messages is not null)
|
||||
@@ -192,20 +191,20 @@ internal sealed class InvokeMcpToolExecutor(
|
||||
// Add messages to conversation if conversationId is provided
|
||||
if (conversationId is not null)
|
||||
{
|
||||
ChatMessage assistantMessage = new(ChatRole.Assistant, resultContent.Output);
|
||||
ChatMessage assistantMessage = new(ChatRole.Assistant, resultContent.Outputs);
|
||||
await agentProvider.CreateMessageAsync(conversationId, assistantMessage, cancellationToken).ConfigureAwait(false);
|
||||
}
|
||||
}
|
||||
|
||||
private async ValueTask AssignResultAsync(IWorkflowContext context, McpServerToolResultContent toolResult)
|
||||
{
|
||||
if (this.Model.Output?.Result is null || toolResult.Output is null || toolResult.Output.Count == 0)
|
||||
if (this.Model.Output?.Result is null || toolResult.Outputs is null || toolResult.Outputs.Count == 0)
|
||||
{
|
||||
return;
|
||||
}
|
||||
|
||||
List<object?> parsedResults = [];
|
||||
foreach (AIContent resultContent in toolResult.Output)
|
||||
foreach (AIContent resultContent in toolResult.Outputs)
|
||||
{
|
||||
object? resultValue = resultContent switch
|
||||
{
|
||||
|
||||
@@ -21,7 +21,7 @@ public sealed class AIAgentHostOptions
|
||||
public bool EmitAgentResponseEvents { get; set; }
|
||||
|
||||
/// <summary>
|
||||
/// Gets or sets a value indicating whether <see cref="UserInputRequestContent"/> should be intercepted and sent
|
||||
/// Gets or sets a value indicating whether <see cref="ToolApprovalRequestContent"/> should be intercepted and sent
|
||||
/// as a message to the workflow for handling, instead of being raised as a request.
|
||||
/// </summary>
|
||||
public bool InterceptUserInputRequests { get; set; }
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user