Compare commits

..
Author SHA1 Message Date
Evan MattsonandGitHub c7ab201a4f Merge branch 'main' into feature/hosted-dwf 2026-04-29 09:46:47 +09:00
alliscodeandCopilot e584a4c8c0 Don't clear pending_requests after restore-only pre-pass
Pending requests in the restored checkpoint represent genuinely
outstanding HITL requests. The next user input may carry function
responses (Responses API `function_call_output` items become
FunctionResultContent / FunctionApprovalResponseContent), which
`WorkflowAgent._process_pending_requests` correctly extracts and
matches against the populated `pending_requests`. Clearing them
after restore would silently drop that state and force the next turn
to be treated as a fresh input even when the caller is responding to
the outstanding requests.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 17:07:32 -07:00
alliscodeandCopilot 31a0011063 Address Tao's review on PR 5531
- Rename Workflow._run_workflow_with_tracing parameter
  is_fresh_message_run -> is_continuation (default False, inverted).
  Fresh-message turns reset per-run accounting; continuations
  (checkpoint restores, responses replays) preserve it.
- Simplify the in-flight-messages guard: _validate_run_params already
  enforces that 'message' is mutually exclusive with 'checkpoint_id'
  and 'responses', so the additional checks were dead code.
- foundry_hosting _responses: move the restore-only pre-pass above
  emit_created/emit_in_progress; restore is preparation, not run
  progress. Drop the skip-restore gate (state preservation requires
  unconditional restore) and instead clear agent.pending_requests
  after the restore-only call. Collapse over-conditioned check.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 14:02:53 -07:00
alliscodeandCopilot d34a4834eb Merge upstream/main into hosted-declarative
Resolve foundry_hosting/pyproject.toml conflict by keeping the loosened
azure-ai-agentserver-* pins (>=X.Y.ZbN,<NEXT_MAJOR) while taking main's
agent-framework-core>=1.2.1,<2 bump.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 13:36:50 -07:00
alliscodeandCopilot 62150df256 Drop Workflow.reset(); checkpointing is the recovery path
The in-flight-messages guard prevented silent misbehavior, but the
companion Workflow.reset() escape hatch only cleared _messages while
leaving iteration count, executor-local state, and shared State
mutations in an indeterminate condition after a mid-run failure. That
gave a false sense of recovery.

Recovery from a mid-run failure is supported only via checkpoint
restoration. Keep the guard and reframe its error message accordingly;
remove reset() and its tests.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 13:29:01 -07:00
alliscodeandCopilot 8252ec6fb2 Loosen azure-ai-agentserver-* pins to major version
The exact-version pins on azure-ai-agentserver-{core,responses,invocations}
forced foundry-hosting consumers to upgrade in lockstep with every beta
bump from upstream. Switch to '>=current,<next-major' so we pick up patch
and feature updates within the same major series without a coordinated
release.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 13:11:20 -07:00
alliscodeandCopilot 2ccc75c8f0 Skip restore-only pre-pass when checkpoint has pending request_info
Address Copilot review on _responses.py: the restore-only checkpoint
replay populates self._agent.pending_requests for any request_info
events captured in the checkpoint. The follow-up run(input_messages)
call would then route through WorkflowAgent._process_pending_requests,
which expects function-response content and rejects plain text input
as 'unexpected content while awaiting request info responses'.

Workflows resumed from a checkpoint that was idle-with-pending-requests
would therefore fail every subsequent plain-text user turn. Inspect the
loaded checkpoint and skip the pre-pass when its
pending_request_info_events dict is non-empty. Workflows that don't use
request_info (the current sample set) are unaffected; workflows that do
will fall through to a fresh-message run rather than silently corrupting
the routing state.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 12:50:28 -07:00
alliscodeandCopilot b1914e8433 Address Copilot review batch: tests + Workflow.reset escape hatch
* Add Workflow.reset() public method as recovery escape hatch when an
  in-flight run aborted (e.g. WorkflowConvergenceException) and the
  workflow is not checkpointed. Update the in-flight messages guard's
  error message to point callers at it.

* Add test_workflow_run_inflight_messages_guard exercising both the
  guard (sync + streaming) and the reset() recovery path.
* Add test_workflow_reset_rejects_concurrent_runs to lock down the
  in-progress guard on reset.

* Add test_as_agent_continuation_preserves_prior_state covering the
  is_continuation branch in _ensure_state_initialized: stamps a marker
  between calls and asserts it survives, while Inputs.input and
  System.LastMessageText refresh to the new turn.

* Add test_powerfx_safe.py regression tests for the Enum branch in
  _make_powerfx_safe (str-subclass, int-subclass, plain Enum, and
  Enums nested in dict/list).

* Drop redundant @pytest.mark.asyncio on
  test_as_agent_round_trip_with_last_message_text (asyncio_mode='auto').

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 12:43:22 -07:00
alliscodeandCopilot 2d16cabef6 Fix pyright errors in _declarative_base.py for CI
- Replace state._state.get(...) protected access with new public
  is_initialized() method on DeclarativeWorkflowState (also clearer intent
  for the continuation detection use case).
- Add narrow pyright ignores for the Any-typed trigger paths that pyright
  cannot fully narrow (the list[Message] isinstance loop and the
  fallback-DefaultTransform branch).

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 11:40:04 -07:00
alliscodeandCopilot bb312f660d Address PR review: fix Inputs.input update and checkpoint storage path
- _declarative_base.py: continuation branch was writing 'Inputs.input' via
  state.set, which routes to the Custom namespace and never updates the
  PowerFx-visible Workflow.Inputs.input. Update state_data['Inputs'] in
  place via get_state_data / set_state_data so =Workflow.Inputs.input and
  =inputs.input see the new turn's user text on continuation.
- _declarative_base.py: refresh docstring to clarify that on a list[Message]
  trigger, Conversation.messages excludes the current user message at the
  start of the turn (agent executors append it before invoking the inner
  agent).
- _responses.py: when previous_response_id is supplied (no conversation_id),
  the prior checkpoint lives under <storage>/<previous_response_id> but new
  checkpoints must land under <storage>/<current_response_id> for the next
  turn to find them. Hold onto restore_storage from the get_latest lookup
  and pass it to the restore-only run; pass write_storage (current id) to
  the message-delivery run and to checkpoint cleanup.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 11:27:05 -07:00
alliscodeandCopilot 891c00c909 Fix CI lint and mypy issues from prior pivot commit
- _workflow.py: collapse nested if (SIM102), drop redundant assignment (RET504)
- _declarative_base.py: remove unused last_user_msg = tail assignment
  whose Message | None type clashed with the prior Message-typed branch

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 11:18:22 -07:00
alliscodeandCopilot e8dfcc90f9 Pivot: preserve workflow state across run() calls
Replace the prior 'combined message + checkpoint_id in one run()' approach
with a cleaner default: Workflow.run no longer wipes shared state or runner-
context messages between calls. Iteration counting and per-run kwargs still
reset on a fresh-message run; checkpoint and responses runs are continuations
that preserve everything.

This lets a WorkflowAgent be invoked repeatedly on the same instance and
maintain multi-turn context (e.g. accumulated Conversation.messages) without
asking developers to opt in. Hosted-agent multi-turn pattern becomes two
explicit calls: restore-from-checkpoint (drive to idle), then run-with-message.

Key changes:
- _workflow.py: drop _state.clear() and reset_for_new_run() from run().
  Reset iteration count and run kwargs on fresh-message runs only.
  Restore 'Cannot provide both message and checkpoint_id' validation.
  Add async guard: fresh-message run with un-drained pending executor
  messages from a prior run is invalid.
- _runner.py: clear _state before import_state in restore_from_checkpoint
  so restore is authoritative (import_state merges, not replaces).
- _agent.py: revert checkpoint branch to restore-only (no message forward).
- _responses.py (foundry_hosting): two-call host pattern - restore checkpoint
  silently, then run with new user input.
- tests: state-preservation is the new default; rebuild Workflow for clean slate.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 11:02:15 -07:00
alliscodeandCopilot baff7e33e1 feat(workflows): support combined message + checkpoint_id for multi-turn continuation
Allow Workflow.run(message=..., checkpoint_id=...) so callers can restore
prior workflow state from a checkpoint AND deliver a new message to the
start executor in a single call. The existing reset_context logic
already preserves shared state when checkpoint_id is set, so this gives
us 'fresh start executor invocation with prior state intact' - exactly
what hosted multi-turn declarative workflows need.

- _workflow.py: drop the message+checkpoint_id mutual exclusion and
  update _execute_with_message_or_checkpoint to do both (restore then
  execute) when both are provided.
- _agent.py: in _run_core's checkpoint branch, also forward
  input_messages so WorkflowAgent.run(messages, checkpoint_id=...) works
  end-to-end. Falls back to the legacy 'restore only' behavior when
  messages are absent.
- _declarative_base.py: detect continuation in _ensure_state_initialized
  by checking whether DECLARATIVE_STATE_KEY already exists in shared
  state; if so, refresh inputs/LastMessage* and append non-user trigger
  messages instead of calling state.initialize() (which would wipe
  Conversation/Local/System).
- foundry_hosting/_responses.py: collapse the host's two-call pattern
  (restore-only, then fresh run) into a single combined call now that
  the underlying APIs support it.
- tests: drop the assertion that combined message+checkpoint_id raises.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-28 08:49:38 -07:00
alliscode dde1edffd0 Foundry hosting: pass full conversation history to workflow agents
_handle_inner_workflow only forwarded the latest user turn to WorkflowAgent.run, even though _handle_inner_agent already prepends history fetched from Foundry storage to the messages it sends a regular agent. Declarative workflows reset Conversation.messages on every run (state.initialize), so checkpoint replay alone does not give them prior turns - the host has to pass them in, the same way it does for non-workflow agents. Mirror that contract: fetch context.get_history() and pass [*history, *input_messages] to the workflow agent.
2026-04-27 16:47:10 -07:00
alliscode 35fa93942c Coerce Enum values when serializing PowerFx symbols
MessageRole and other str-subclass Enums passed isinstance(v, str) and were forwarded to pythonnet unchanged. pythonnet then raised 'MessageRole value cannot be converted to System.String' for every PowerFx primitive when ConditionGroup/Expr eval walked the symbol table containing Conversation.messages. Reduce Enum members to their underlying value before the primitive check so eval sees plain strings/ints.
2026-04-27 16:32:27 -07:00
alliscode 56ab7df874 Populate Conversation.messages from list[Message] trigger
When Workflow.as_agent() is invoked with a list[Message], the start executor now populates Conversation.messages / Conversation.history / System.conversations.{id}.messages with prior turns only (excluding the latest user message), and surfaces the latest user message via Inputs.input and System.LastMessage*. This matches InvokeAzureAgent's contract that the messages binding holds prior turns and the executor itself appends the new user input before invoking, avoiding double-append of the trailing user turn while preserving full history (incl. assistant/system/tool roles and multi-modal content) for downstream actions.
2026-04-27 14:39:45 -07:00
alliscodeandCopilot 910172c456 Fix declarative Workflow.as_agent() by accepting list[Message] in start executor
The declarative start executor (JoinExecutor) only advertised dict and str
in its input_types, so WorkflowAgent.__init__ rejected it with
'Workflow's start executor cannot handle list[Message]'.

Add list[Message] to the JoinExecutor handler annotation and add a
matching branch in DeclarativeActionExecutor._ensure_state_initialized
that extracts the last user-message text and falls through to the
string-input initialization path, so =System.LastMessageText works
end-to-end via as_agent().

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-27 12:53:17 -07:00
472 changed files with 5925 additions and 53131 deletions
+1 -108
View File
@@ -37,7 +37,6 @@ jobs:
outputs:
dotnetChanges: ${{ steps.filter.outputs.dotnet }}
cosmosDbChanges: ${{ steps.filter.outputs.cosmosdb }}
foundryHostingChanges: ${{ steps.filter.outputs.foundryHosting }}
steps:
- uses: actions/checkout@v6
- uses: dorny/paths-filter@v3
@@ -48,21 +47,6 @@ jobs:
- 'dotnet/**'
cosmosdb:
- 'dotnet/src/Microsoft.Agents.AI.CosmosNoSql/**'
# The Foundry hosted-agent IT is costly (builds a container, pushes to ACR,
# provisions live agents). Only run it when the project under test, its
# dependency chain, the test container, the test fixture, or their tooling
# changed. Keep this list in sync with $hashedDirs in scripts/it-build-image.ps1.
foundryHosting:
- 'dotnet/src/Microsoft.Agents.AI.Foundry.Hosting/**'
- 'dotnet/src/Microsoft.Agents.AI.Foundry/**'
- 'dotnet/src/Microsoft.Agents.AI/**'
- 'dotnet/src/Microsoft.Agents.AI.Abstractions/**'
- 'dotnet/src/Microsoft.Agents.AI.Workflows/**'
- 'dotnet/tests/Foundry.Hosting.IntegrationTests/**'
- 'dotnet/tests/Foundry.Hosting.IntegrationTests.TestContainer/**'
- 'dotnet/Directory.Packages.props'
- 'dotnet/tests/Foundry.Hosting.IntegrationTests/scripts/it-build-image.ps1'
- '.github/workflows/dotnet-build-and-test.yml'
# run only if 'dotnet' files were changed
- name: dotnet tests
if: steps.filter.outputs.dotnet == 'true'
@@ -275,7 +259,6 @@ jobs:
--report-xunit-trx `
--ignore-exit-code 8 `
--filter-not-trait "Category=IntegrationDisabled" `
--filter-not-trait "Category=FoundryHostedAgents" `
--parallel-algorithm aggressive `
--max-threads 2.0x
env:
@@ -316,101 +299,11 @@ jobs:
shell: pwsh
run: ./dotnet/eng/scripts/dotnet-check-coverage.ps1 -JsonReportPath "TestResults/Reports/Summary.json" -CoverageThreshold $env:COVERAGE_THRESHOLD
# The Foundry hosted-agent IT is costly (it builds a container, pushes to ACR, and provisions
# live agents on a separate Foundry project). Running it in its own job keeps the overall
# workflow time roughly flat: it executes in parallel to dotnet-build and dotnet-test and is
# gated on paths-filter.outputs.foundryHostingChanges so unrelated edits skip the work.
dotnet-foundry-hosted-it:
needs: paths-filter
if: github.event_name != 'pull_request' && needs.paths-filter.outputs.foundryHostingChanges == 'true'
runs-on: ubuntu-latest
environment: integration
env:
targetFramework: net10.0
configuration: Release
steps:
- uses: actions/checkout@v6
with:
persist-credentials: false
sparse-checkout: |
.
.github
dotnet
python
- name: Setup dotnet
uses: actions/setup-dotnet@v5.2.0
with:
global-json-file: ${{ github.workspace }}/dotnet/global.json
- name: Generate test solution (no samples)
shell: pwsh
run: |
./dotnet/eng/scripts/New-FilteredSolution.ps1 `
-Solution dotnet/agent-framework-dotnet.slnx `
-TargetFramework $env:targetFramework `
-Configuration $env:configuration `
-ExcludeSamples `
-OutputPath dotnet/filtered.slnx `
-Verbose
- name: Generate Foundry hosted IT filtered solution
shell: pwsh
run: |
./dotnet/eng/scripts/New-FilteredSolution.ps1 `
-Solution dotnet/filtered.slnx `
-TargetFramework $env:targetFramework `
-Configuration $env:configuration `
-TestProjectNameFilter "Foundry.Hosting.IntegrationTests*" `
-OutputPath dotnet/filtered-foundry-hosted.slnx `
-Verbose
- name: Build Foundry hosted IT (and its deps)
shell: bash
run: dotnet build dotnet/filtered-foundry-hosted.slnx -c "$configuration" -f "$targetFramework" --warnaserror
- name: Azure CLI Login
uses: azure/login@v2
with:
client-id: ${{ secrets.AZURE_CLIENT_ID }}
tenant-id: ${{ secrets.AZURE_TENANT_ID }}
subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
# We rebuild and push the test container image on every IT run so framework code changes
# are picked up; the image tag is content-hashed across the test container source AND its
# framework project references, so identical content is a no-op push.
- name: Build and push Foundry Hosted Agents test container
id: build-foundry-hosted-image
shell: pwsh
working-directory: ${{ github.workspace }}
run: |
$registry = "${{ vars.IT_HOSTED_AGENT_REGISTRY }}"
if ([string]::IsNullOrWhiteSpace($registry)) {
throw "IT_HOSTED_AGENT_REGISTRY not set in the integration environment."
}
& "${{ github.workspace }}/dotnet/tests/Foundry.Hosting.IntegrationTests/scripts/it-build-image.ps1" -Registry $registry | Tee-Object -FilePath $env:GITHUB_ENV -Append
- name: Run Foundry Hosted Agents Integration Tests
shell: pwsh
working-directory: dotnet
run: |
dotnet test --solution ./filtered-foundry-hosted.slnx `
-f $env:targetFramework `
-c $env:configuration `
--no-build -v Normal `
--report-xunit-trx `
--ignore-exit-code 8 `
--filter-trait "Category=FoundryHostedAgents"
env:
AZURE_AI_PROJECT_ENDPOINT: ${{ vars.IT_HOSTED_AGENT_PROJECT_ENDPOINT }}
AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.IT_HOSTED_AGENT_MODEL_DEPLOYMENT_NAME }}
# IT_HOSTED_AGENT_IMAGE was exported into $GITHUB_ENV by the previous step.
# This final job is required to satisfy the merge queue. It must only run (or succeed) if no tests failed
dotnet-build-and-test-check:
if: always()
runs-on: ubuntu-latest
needs: [dotnet-build, dotnet-test, dotnet-foundry-hosted-it]
needs: [dotnet-build, dotnet-test]
steps:
- name: Get Date
shell: bash
+18 -57
View File
@@ -157,8 +157,6 @@ jobs:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_CHAT_MODEL: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
OLLAMA_MODEL: qwen2.5:1.5b
OLLAMA_EMBEDDING_MODEL: nomic-embed-text
defaults:
run:
working-directory: python
@@ -173,43 +171,6 @@ jobs:
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Install Ollama
run: curl -fsSL https://ollama.com/install.sh | sh
working-directory: .
- name: Cache Ollama models
uses: actions/cache@v4
with:
path: ~/.ollama/models
key: ollama-models-qwen2.5-1.5b-nomic-embed-text-v1
- name: Start Ollama and pull models
run: |
# Stop any Ollama instance auto-started by the install script
pkill ollama || true
sleep 2
ollama serve &
for i in $(seq 1 30); do
if curl -sf http://localhost:11434/api/tags > /dev/null 2>&1; then
break
fi
sleep 1
done
# Pull models with retry for transient 429 rate limits
for model in qwen2.5:1.5b nomic-embed-text; do
pulled=false
for attempt in 1 2 3; do
if ollama pull "$model"; then
pulled=true
break
fi
echo "Retry $attempt for $model (waiting 15s)..."
sleep 15
done
if [ "$pulled" != "true" ]; then
echo "ERROR: Failed to pull $model after 3 attempts"
exit 1
fi
done
working-directory: .
- name: Start local MCP server
id: local-mcp
uses: ./.github/actions/setup-local-mcp-server
@@ -310,7 +271,7 @@ jobs:
-m integration
-n logical --dist worksteal
-x
--timeout=480 --session-timeout=900 --timeout_method thread
--timeout=360 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
- name: Upload test results
@@ -474,9 +435,9 @@ jobs:
path: ./python/pytest.xml
if-no-files-found: ignore
# Integration test trend report (aggregates per-job JUnit XML results)
python-integration-test-report:
name: Integration Test Report
# Flaky test trend report (aggregates per-job JUnit XML results)
python-flaky-test-report:
name: Flaky Test Report
if: >
always() &&
(contains(join(needs.*.result, ','), 'success') ||
@@ -510,36 +471,36 @@ jobs:
with:
pattern: test-results-*
path: test-results/
- name: Restore report history cache
- name: Restore flaky report history cache
uses: actions/cache/restore@v4
with:
path: python/integration-report-history.json
key: integration-report-history-integration-${{ github.run_id }}
path: python/flaky-report-history.json
key: flaky-report-history-integration-${{ github.run_id }}
restore-keys: |
integration-report-history-integration-
flaky-report-history-integration-
- name: Generate trend report
run: >
uv run python scripts/integration_test_report/aggregate.py
uv run python scripts/flaky_report/aggregate.py
../test-results/
integration-report-history.json
integration-test-report.md
flaky-report-history.json
flaky-test-report.md
- name: Post to Job Summary
if: always()
run: cat integration-test-report.md >> $GITHUB_STEP_SUMMARY
- name: Save report history cache
run: cat flaky-test-report.md >> $GITHUB_STEP_SUMMARY
- name: Save flaky report history cache
if: always()
uses: actions/cache/save@v4
with:
path: python/integration-report-history.json
key: integration-report-history-integration-${{ github.run_id }}
path: python/flaky-report-history.json
key: flaky-report-history-integration-${{ github.run_id }}
- name: Upload unified trend report
if: always()
uses: actions/upload-artifact@v7
with:
name: integration-test-report
name: flaky-test-report
path: |
python/integration-test-report.md
python/integration-report-history.json
python/flaky-test-report.md
python/flaky-report-history.json
python-integration-tests-check:
if: always()
+18 -57
View File
@@ -278,8 +278,6 @@ jobs:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_CHAT_MODEL: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
OLLAMA_MODEL: qwen2.5:1.5b
OLLAMA_EMBEDDING_MODEL: nomic-embed-text
defaults:
run:
working-directory: python
@@ -291,43 +289,6 @@ jobs:
with:
python-version: ${{ env.UV_PYTHON }}
os: ${{ runner.os }}
- name: Install Ollama
run: curl -fsSL https://ollama.com/install.sh | sh
working-directory: .
- name: Cache Ollama models
uses: actions/cache@v4
with:
path: ~/.ollama/models
key: ollama-models-qwen2.5-1.5b-nomic-embed-text-v1
- name: Start Ollama and pull models
run: |
# Stop any Ollama instance auto-started by the install script
pkill ollama || true
sleep 2
ollama serve &
for i in $(seq 1 30); do
if curl -sf http://localhost:11434/api/tags > /dev/null 2>&1; then
break
fi
sleep 1
done
# Pull models with retry for transient 429 rate limits
for model in qwen2.5:1.5b nomic-embed-text; do
pulled=false
for attempt in 1 2 3; do
if ollama pull "$model"; then
pulled=true
break
fi
echo "Retry $attempt for $model (waiting 15s)..."
sleep 15
done
if [ "$pulled" != "true" ]; then
echo "ERROR: Failed to pull $model after 3 attempts"
exit 1
fi
done
working-directory: .
- name: Start local MCP server
id: local-mcp
uses: ./.github/actions/setup-local-mcp-server
@@ -442,7 +403,7 @@ jobs:
-m integration
-n logical --dist worksteal
-x
--timeout=480 --session-timeout=900 --timeout_method thread
--timeout=360 --session-timeout=900 --timeout_method thread
--retries 2 --retry-delay 5
--junitxml=pytest.xml
working-directory: ./python
@@ -658,9 +619,9 @@ jobs:
path: ./python/pytest.xml
if-no-files-found: ignore
# Integration test trend report (aggregates per-job JUnit XML results)
python-integration-test-report:
name: Integration Test Report
# Flaky test trend report (aggregates per-job JUnit XML results)
python-flaky-test-report:
name: Flaky Test Report
if: >
always() &&
(contains(join(needs.*.result, ','), 'success') ||
@@ -691,36 +652,36 @@ jobs:
with:
pattern: test-results-*
path: test-results/
- name: Restore report history cache
- name: Restore flaky report history cache
uses: actions/cache/restore@v4
with:
path: python/integration-report-history.json
key: integration-report-history-merge-${{ github.run_id }}
path: python/flaky-report-history.json
key: flaky-report-history-merge-${{ github.run_id }}
restore-keys: |
integration-report-history-merge-
flaky-report-history-merge-
- name: Generate trend report
run: >
uv run python scripts/integration_test_report/aggregate.py
uv run python scripts/flaky_report/aggregate.py
../test-results/
integration-report-history.json
integration-test-report.md
flaky-report-history.json
flaky-test-report.md
- name: Post to Job Summary
if: always()
run: cat integration-test-report.md >> $GITHUB_STEP_SUMMARY
- name: Save report history cache
run: cat flaky-test-report.md >> $GITHUB_STEP_SUMMARY
- name: Save flaky report history cache
if: always()
uses: actions/cache/save@v4
with:
path: python/integration-report-history.json
key: integration-report-history-merge-${{ github.run_id }}
path: python/flaky-report-history.json
key: flaky-report-history-merge-${{ github.run_id }}
- name: Upload unified trend report
if: always()
uses: actions/upload-artifact@v7
with:
name: integration-test-report
name: flaky-test-report
path: |
python/integration-test-report.md
python/integration-report-history.json
python/flaky-test-report.md
python/flaky-report-history.json
python-integration-tests-check:
if: always()
+79 -77
View File
@@ -6,12 +6,8 @@
[![MS Learn Documentation](https://img.shields.io/badge/MS%20Learn-Documentation-blue)](https://learn.microsoft.com/en-us/agent-framework/)
[![PyPI](https://img.shields.io/pypi/v/agent-framework)](https://pypi.org/project/agent-framework/)
[![NuGet](https://img.shields.io/nuget/v/Microsoft.Agents.AI)](https://www.nuget.org/profiles/MicrosoftAgentFramework/)
[![GitHub stars](https://img.shields.io/github/stars/microsoft/agent-framework?style=social)](https://github.com/microsoft/agent-framework/stargazers)
Microsoft Agent Framework (MAF) is an open, multi-language framework for building **production-grade AI agents and multi-agent workflows** in **.NET and Python**.
Microsoft Agent Framework is built for teams taking agents from prototype to production. It provides a consistent foundation for building, orchestrating, and operating agent systems across Python and .NET, while keeping architecture choices open as requirements evolve, and supports a broad ecosystem including Microsoft Foundry, Azure OpenAI, OpenAI, and the GitHub Copilot SDK, with samples and hosting patterns for both local development and cloud deployment.
Welcome to Microsoft's comprehensive multi-language framework for building, orchestrating, and deploying AI agents with support for both .NET and Python implementations. This framework provides everything from simple chat agents to complex multi-agent workflows with graph-based orchestration.
<p align="center">
<a href="https://www.youtube.com/watch?v=AAgdMhftj8w" title="Watch the full Agent Framework introduction (30 min)">
@@ -25,54 +21,10 @@ Microsoft Agent Framework is built for teams taking agents from prototype to pro
</a>
</p>
## Is this the right framework for you?
## 📋 Getting Started
MAF is a strong fit if you:
- are building agents and workflows you expect to run in production,
- need orchestration beyond a single prompt or stateless chat loop,
- want graph-based patterns such as sequential, concurrent, handoff, and group collaboration,
- care about durability, restartability, observability, governance, or human-in-the-loop control,
- need provider flexibility so your architecture can evolve without major rewrites.
### 📦 Installation
## Key Features
Explore new MAF capabilities and real implementation patterns on the [official blog](https://devblogs.microsoft.com/agent-framework/).
- **Python and C#/.NET Support**: Full framework support for both Python and C#/.NET implementations with consistent APIs
- [Python packages](./python/packages/) | [.NET source](./dotnet/src/)
- **Multiple Agent Provider Support**: Support for various LLM providers with more being added continuously
- [Python examples](./python/samples/02-agents/providers/) | [.NET examples](./dotnet/samples/02-agents/AgentProviders/)
- **Middleware**: Flexible middleware system for request/response processing, exception handling, and custom pipelines
- [Python middleware](./python/samples/02-agents/middleware/) | [.NET middleware](./dotnet/samples/02-agents/Agents/Agent_Step11_Middleware/)
- **Orchestration Patterns & Workflows**: Build multi-agent systems with graph-based workflows supporting sequential, concurrent, handoff, and group collaboration patterns; includes checkpointing, streaming, human-in-the-loop, and time-travel
- [Python workflows](./python/samples/03-workflows/) | [.NET workflows](./dotnet/samples/03-workflows/)
- **Foundry Hosted Agents (new)**: Deploy and host your agents to Foundry-hosted infrastructure with just 2 additional lines of code
- [Python samples](./python/samples/04-hosting/foundry-hosted-agents/) | [.NET samples](./dotnet/samples/04-hosting/FoundryHostedAgents/)
- **Observability**: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging
- [Python observability](./python/samples/02-agents/observability/) | [.NET telemetry](./dotnet/samples/02-agents/AgentOpenTelemetry/)
- **Declarative Agents**: Define agents using YAML for faster setup and versioning
- [Declarative agent samples](./declarative-agents/)
- **Agent Skills**: Build domain-specific knowledge bases from multiple sources—files, inline code, class libraries—for agents to discover and use
- [Skills design](./docs/decisions/0021-agent-skills-design.md)
- **AF Labs**: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
- [Labs directory](./python/packages/lab/)
- **DevUI**: Interactive developer UI for agent development, testing, and debugging workflows
- [See the DevUI in action](https://www.youtube.com/watch?v=mOAaGY4WPvc)
## Table of Contents
- [Getting Started](#getting-started)
- [Installation](#installation)
- [Learning Resources](#learning-resources)
- [Quickstart](#quickstart)
- [Basic Agent - Python](#basic-agent---python)
- [Basic Agent - .NET](#basic-agent---net)
- [More Examples & Samples](#more-examples--samples)
- [Community & Feedback](#community--feedback)
- [Troubleshooting](#troubleshooting)
- [Contributor Resources](#contributor-resources)
## Getting Started
### Installation
Python
```bash
@@ -85,13 +37,9 @@ pip install agent-framework
```bash
dotnet add package Microsoft.Agents.AI
# For Foundry integration (used in the .NET quickstart below):
dotnet add package Microsoft.Agents.AI.Foundry
dotnet add package Azure.AI.Projects
dotnet add package Azure.Identity
```
### Learning Resources
### 📚 Documentation
- **[Overview](https://learn.microsoft.com/agent-framework/overview/agent-framework-overview)** - High level overview of the framework
- **[Quick Start](https://learn.microsoft.com/agent-framework/tutorials/quick-start)** - Get started with a simple agent
@@ -100,9 +48,44 @@ dotnet add package Azure.Identity
- **[Migration from Semantic Kernel](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-semantic-kernel)** - Guide to migrate from Semantic Kernel
- **[Migration from AutoGen](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-autogen)** - Guide to migrate from AutoGen
### Quickstart
Still have questions? Join our [weekly office hours](./COMMUNITY.md#public-community-office-hours) or ask questions in our [Discord channel](https://discord.gg/b5zjErwbQM) to get help from the team and other users.
#### Basic Agent - Python
### ✨ **Highlights**
- **Graph-based Workflows**: Connect agents and deterministic functions using data flows with streaming, checkpointing, human-in-the-loop, and time-travel capabilities
- [Python workflows](./python/samples/03-workflows/) | [.NET workflows](./dotnet/samples/03-workflows/)
- **AF Labs**: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
- [Labs directory](./python/packages/lab/)
- **DevUI**: Interactive developer UI for agent development, testing, and debugging workflows
- [DevUI package](./python/packages/devui/)
<p align="center">
<a href="https://www.youtube.com/watch?v=mOAaGY4WPvc">
<img src="https://img.youtube.com/vi/mOAaGY4WPvc/hqdefault.jpg" alt="See the DevUI in action" width="480">
</a>
</p>
<p align="center">
<a href="https://www.youtube.com/watch?v=mOAaGY4WPvc">
See the DevUI in action (1 min)
</a>
</p>
- **Python and C#/.NET Support**: Full framework support for both Python and C#/.NET implementations with consistent APIs
- [Python packages](./python/packages/) | [.NET source](./dotnet/src/)
- **Observability**: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging
- [Python observability](./python/samples/02-agents/observability/) | [.NET telemetry](./dotnet/samples/02-agents/AgentOpenTelemetry/)
- **Multiple Agent Provider Support**: Support for various LLM providers with more being added continuously
- [Python examples](./python/samples/02-agents/providers/) | [.NET examples](./dotnet/samples/02-agents/AgentProviders/)
- **Middleware**: Flexible middleware system for request/response processing, exception handling, and custom pipelines
- [Python middleware](./python/samples/02-agents/middleware/) | [.NET middleware](./dotnet/samples/02-agents/Agents/Agent_Step11_Middleware/)
### 💬 **We want your feedback!**
- For bugs, please file a [GitHub issue](https://github.com/microsoft/agent-framework/issues).
## Quickstart
### Basic Agent - Python
Create a simple Azure Responses Agent that writes a haiku about the Microsoft Agent Framework
@@ -126,7 +109,7 @@ async def main():
# project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
# model=os.environ["FOUNDRY_MODEL_DEPLOYMENT_NAME"],
),
name="HaikuAgent",
name="HaikuBot",
instructions="You are an upbeat assistant that writes beautifully.",
)
@@ -136,24 +119,40 @@ if __name__ == "__main__":
asyncio.run(main())
```
#### Basic Agent - .NET
Create a simple Agent, using Microsoft Foundry that writes a haiku about the Microsoft Agent Framework
### Basic Agent - .NET
Create a simple Agent, using Microsoft Foundry with token-based auth, that writes a haiku about the Microsoft Agent Framework
```c#
// This sample shows how to create and run a basic agent with AIProjectClient.AsAIAgent(...).
// dotnet add package Microsoft.Agents.AI.Foundry
// Use `az login` to authenticate with Azure CLI
using Azure.AI.Projects;
using Azure.Identity;
using System;
using Azure.AI.Projects;
using Azure.Identity;
using Microsoft.Agents.AI;
string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
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-5.4-mini";
AIAgent agent =
new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
.AsAIAgent(model: deploymentName, instructions: "You are an upbeat assistant that writes beautifully.", name: "HaikuAgent");
var agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
.AsAIAgent(model: deploymentName, name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
```
Create a simple Agent, using OpenAI Responses, that writes a haiku about the Microsoft Agent Framework
```c#
// dotnet add package Microsoft.Agents.AI.OpenAI
using System;
using OpenAI;
using OpenAI.Responses;
// Replace the <apikey> with your OpenAI API key.
var agent = new OpenAIClient("<apikey>")
.GetResponsesClient()
.AsAIAgent(model: "gpt-5.4-mini", name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
// Once you have the agent, you can invoke it like any other AIAgent.
Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
```
@@ -176,12 +175,6 @@ Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Fram
- [Hosting](./dotnet/samples/04-hosting): A2A, Durable Agents, Durable Workflows
- [End-to-End](./dotnet/samples/05-end-to-end): full applications and demos
## Community & Feedback
- **Found a bug?** File a [GitHub issue](https://github.com/microsoft/agent-framework/issues) to help us improve.
- **Enjoying MAF?** [![GitHub stars](https://img.shields.io/badge/Star-us%20on%20GitHub-yellow)](https://github.com/microsoft/agent-framework) to show your support and help others discover the project.
- **Have questions?** Join our [Discord](https://discord.gg/b5zjErwbQM) or visit [weekly office hours](./COMMUNITY.md#public-community-office-hours).
## Troubleshooting
### Authentication
@@ -194,7 +187,16 @@ Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Fram
> **Tip:** `DefaultAzureCredential` is convenient for development but in production, consider using a specific credential (e.g., `ManagedIdentityCredential`) to avoid latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
### Environment Variables
For environment variable configuration specific to each sample, refer to the README in the sample directory ([Python samples](./python/samples/) | [.NET samples](./dotnet/samples/)).
The samples typically read configuration from environment variables. Common required variables:
| Variable | Used by | Purpose |
|----------|---------|---------|
| `AZURE_OPENAI_ENDPOINT` | Azure OpenAI samples | Your Azure OpenAI resource URL |
| `AZURE_OPENAI_DEPLOYMENT_NAME` | Azure OpenAI samples | Model deployment name (e.g. `gpt-4o-mini`) |
| `AZURE_AI_PROJECT_ENDPOINT` | Microsoft Foundry samples | Your Microsoft Foundry project endpoint |
| `AZURE_AI_MODEL_DEPLOYMENT_NAME` | Microsoft Foundry samples | Model deployment name |
| `OPENAI_API_KEY` | OpenAI (non-Azure) samples | Your OpenAI platform API key |
## Contributor Resources
@@ -1,142 +0,0 @@
---
status: proposed
contact: shruti
date: 2026-01-14
deciders: {}
consulted: {}
informed: {}
---
# FIDES - Deterministic Prompt Injection Defense [Costa et al., 2025]
## Context and Problem Statement
AI agents are vulnerable to prompt injection attacks where malicious instructions embedded in external content (e.g., API responses, user input) can manipulate agent behavior. Traditional defenses rely on heuristics and prompt engineering, which are not deterministic and can be bypassed.
We need a systematic, deterministic defense mechanism that prevents untrusted content from influencing agent behavior, provides verifiable security guarantees, maintains audit trails for compliance, and integrates seamlessly with the existing agent framework.
## Decision Drivers
- Agents must not execute actions influenced by untrusted external content (prompt injection defense).
- The solution must provide deterministic, verifiable security guarantees — not heuristic-based.
- The solution must maintain audit trails for compliance and security reviews.
- The solution must integrate non-invasively with the existing middleware pipeline.
- The solution must be opt-in and backwards compatible with existing agents.
- Developer experience must remain simple with a clear security model.
## Considered Options
- Information-flow control with label-based middleware (FIDES)
- Prompt engineering defense
- Content sanitization
- Separate agent instances
- Runtime monitoring only
## Decision Outcome
Chosen option: "Information-flow control with label-based middleware (FIDES)", because it is the only option that provides deterministic, formally verifiable security guarantees while integrating non-invasively with the existing middleware pipeline and remaining fully backwards compatible.
FIDES (Flow Integrity Deterministic Enforcement System) is a label-based security system with four core components:
1. **Content Labeling System**`IntegrityLabel` (TRUSTED/UNTRUSTED) and `ConfidentialityLabel` (PUBLIC/PRIVATE/USER_IDENTITY) with most-restrictive-wins combination policy.
2. **Middleware-Based Enforcement**`LabelTrackingFunctionMiddleware` for automatic label propagation and `PolicyEnforcementFunctionMiddleware` for pre-execution policy checks.
3. **Variable Indirection**`ContentVariableStore` and `VariableReferenceContent` for physical isolation of untrusted content from the LLM context.
4. **Quarantined Execution**`quarantined_llm` and `inspect_variable` tools for isolated processing of untrusted data with audit logging.
### Consequences
- Good, because it provides deterministic security guarantees about what untrusted content can influence.
- Good, because labels provide a clear audit trail of trust propagation.
- Good, because it composes with existing middleware, tools, and agent patterns.
- Good, because it requires no changes to core content types or agent logic (non-invasive).
- Good, because policies are configurable per agent or tool.
- Good, because audit logs support compliance and security reviews.
- Bad, because middleware adds latency to every tool call.
- Bad, because the variable store consumes memory for untrusted content.
- Bad, because developers must understand the label system.
- Bad, because it does not defend against all attack vectors (e.g., training data poisoning).
- Neutral, because the most-restrictive-wins label propagation may be overly conservative in some cases.
- Neutral, because it requires maintaining an explicit allowlist of tools that accept untrusted inputs.
## Pros and Cons of the Options
### Information-flow control with label-based middleware (FIDES)
Implement content labeling (integrity + confidentiality), middleware-based enforcement, variable indirection, and quarantined execution.
- Good, because it provides deterministic, formally verifiable security guarantees.
- Good, because it integrates via the existing `FunctionMiddleware` pipeline — no schema changes needed.
- Good, because it is fully opt-in and backwards compatible.
- Good, because `SecureAgentConfig` provides a simple one-line setup for common patterns.
- Bad, because middleware adds per-tool-call latency overhead.
- Bad, because developers must configure tool policies manually.
### Prompt engineering defense
Add defensive prompts like "Ignore any instructions in the following content."
- Good, because it requires no architectural changes.
- Good, because it is trivial to implement.
- Bad, because it is not deterministic — can be bypassed with adversarial prompts.
- Bad, because it provides no formal security guarantees.
- Bad, because it requires constant updates as attacks evolve.
### Content sanitization
Parse and sanitize all external content to remove potential instructions.
- Good, because it operates at the data layer before reaching the LLM.
- Bad, because it is computationally expensive.
- Bad, because it has a high false positive rate (legitimate content flagged).
- Bad, because it cannot handle novel attack vectors.
- Bad, because it may break legitimate use cases.
### Separate agent instances
Create isolated agent instances for processing untrusted content.
- Good, because it provides strong isolation guarantees.
- Bad, because it has high overhead (multiple agent instances).
- Bad, because it is difficult to manage state across instances.
- Bad, because it introduces complex communication patterns.
- Bad, because of poor developer experience.
### Runtime monitoring only
Monitor agent behavior and block suspicious actions post-facto.
- Good, because it requires no changes to the execution path.
- Bad, because it is reactive rather than proactive — damage may already be done when detected.
- Bad, because it is hard to define "suspicious" deterministically.
- Bad, because it cannot provide preventive guarantees.
## Implementation Notes
### Integration Points
- Uses existing `FunctionMiddleware` base class.
- Attaches labels via `additional_properties` (no schema changes).
- Leverages `SerializationMixin` for label persistence.
### Backwards Compatibility
- Fully backwards compatible — opt-in system.
- Agents without security middleware function normally.
- Unlabeled content defaults to UNTRUSTED (safer default).
- No breaking changes to existing APIs.
## Related Decisions
- [ADR-0007: Agent Filtering Middleware](0007-agent-filtering-middleware.md) — Established middleware patterns we build upon.
- [ADR-0006: User Approval](0006-userapproval.md) — Human-in-the-loop pattern we reference.
## References
- [Securing AI Agents with Information-Flow Control (Costa et al., 2025)](https://arxiv.org/abs/2505.23643)
- [Prompt Injection Attack Examples](https://simonwillison.net/2023/Apr/14/worst-that-can-happen/)
- [Information Flow Control](https://en.wikipedia.org/wiki/Information_flow_(information_theory))
- [Taint Analysis](https://en.wikipedia.org/wiki/Taint_checking)
- [Defense in Depth](https://en.wikipedia.org/wiki/Defense_in_depth_(computing))
- [ ] Performance Benchmarks
- [ ] User Acceptance Testing
@@ -1,352 +0,0 @@
# FIDES Implementation Summary
## Overview
**FIDES** is a comprehensive deterministic prompt injection defense system for the agent framework. The implementation provides label-based security mechanisms to defend against prompt injection attacks by tracking integrity and confidentiality of content throughout agent execution.
**🚀 Key Features:**
- **Context Provider Pattern** - `SecureAgentConfig` extends `ContextProvider`, injecting tools, instructions, and middleware automatically
- **Automatic Variable Hiding** - UNTRUSTED content is automatically hidden without requiring manual intervention
- **Per-Item Embedded Labels** - Tools return `list[Content]` with `Content.from_text()` for proper label propagation
- **SecureAgentConfig** - One-line secure agent configuration via `context_providers=[config]`
- **Data Exfiltration Prevention** - `max_allowed_confidentiality` prevents sensitive data leakage
- **Message-Level Label Tracking** (Phase 1) - Track labels on every message in the conversation
## Architecture Components
The FIDES defense system consists of seven main components:
1. **Content Labeling Infrastructure** - Labels for tracking integrity and confidentiality
2. **Label Tracking Middleware** - Automatically assigns, propagates labels, and hides untrusted content
3. **Per-Item Embedded Labels** - Tools can return mixed-trust data with per-item security labels
4. **Policy Enforcement Middleware** - Blocks tool calls that violate security policies
5. **Security Tools** - Specialized tools for safe handling of untrusted content (`quarantined_llm`, `inspect_variable`)
6. **SecureAgentConfig** - Context provider for easy secure agent configuration
7. **Message-Level Label Tracking** - Track labels on every message in the conversation (Phase 1)
## Implementation Details
### Files Created
1. **`python/packages/core/agent_framework/security.py`** (~2950 lines — all security primitives, middleware, tools, and configuration in a single public module)
- `IntegrityLabel` enum (TRUSTED/UNTRUSTED)
- `ConfidentialityLabel` enum (PUBLIC/PRIVATE/USER_IDENTITY)
- `ContentLabel` class with serialization support
- `combine_labels()` function for label composition
- `ContentVariableStore` for client-side content storage
- `VariableReferenceContent` for variable indirection
- `LabeledMessage` class (inherits from `Message`) for message-level tracking
- `check_confidentiality_allowed()` helper for data exfiltration prevention
- `LabelTrackingFunctionMiddleware` - Tracks and propagates security labels
- `PolicyEnforcementFunctionMiddleware` - Enforces security policies
- `SecureAgentConfig` extends `ContextProvider` - automatic secure agent configuration
- `quarantined_llm()` - Isolated LLM calls with labeled data
- `inspect_variable()` - Controlled variable content inspection
- `store_untrusted_content()` - Helper for manual variable indirection (legacy)
- `get_security_tools()` - Returns list of security tools
- `SECURITY_TOOL_INSTRUCTIONS` - Detailed guidance for agents
2. **`FIDES_DEVELOPER_GUIDE.md`** (~1250 lines)
- Located at `python/samples/02-agents/security/FIDES_DEVELOPER_GUIDE.md`
- Complete documentation of the FIDES security system
- Architecture overview and design rationale
- Usage examples (6+ comprehensive scenarios)
- Best practices and configuration options
- API reference with full parameter documentation
- Data exfiltration prevention documentation
3. **`python/packages/core/tests/test_security.py`** (~800+ lines)
- Unit tests for ContentLabel and label operations
- Tests for ContentVariableStore functionality
- Tests for VariableReferenceContent
- Middleware behavior tests (label tracking and policy enforcement)
- Automatic hiding tests
- Per-item embedded label tests
- Context label tracking tests
- Message-level tracking tests (Phase 1)
- Data exfiltration prevention tests
4. **`docs/decisions/0024-prompt-injection-defense.md`**
- Architecture Decision Record (ADR)
- Design rationale and alternatives considered
- Security properties and guarantees
5. **`python/samples/02-agents/security/README.md`**
- Sample-focused entry point for the two runnable FIDES security samples
- Prerequisites, run commands, and links to the developer guide for deeper details
### Files Modified
1. **`python/packages/core/agent_framework/__init__.py`**
- Removed root-level security exports so `agent_framework.security` is the canonical import surface
## Core Features
### 1. Content Labeling Infrastructure
- **IntegrityLabel**: TRUSTED (user input) vs UNTRUSTED (AI-generated, external)
- **ConfidentialityLabel**: PUBLIC, PRIVATE, USER_IDENTITY
- **Label Combination**: Most restrictive policy (UNTRUSTED + metadata merging)
- **Serialization**: Full support for `to_dict()` and `from_dict()`
### 2. Per-Item Embedded Labels
Tools returning mixed-trust data embed labels on individual items using `Content.from_text()`:
```python
import json
from agent_framework import Content, tool
@tool(description="Fetch emails from inbox")
async def fetch_emails(count: int = 5) -> list[Content]:
return [
Content.from_text(
json.dumps({
"id": email["id"],
"body": email["body"],
}),
additional_properties={
"security_label": {
"integrity": "trusted" if email["internal"] else "untrusted",
"confidentiality": "private",
}
),
)
for email in emails
]
```
These embedded labels are automatically consumed by `LabelTrackingFunctionMiddleware`, which:
- Extracts the `security_label` from `additional_properties`
- Uses the embedded label as the highest-priority source for that item
- Automatically hides UNTRUSTED items in the variable store
- Replaces hidden items with `VariableReferenceContent` in the LLM context
- Preserves TRUSTED items visible to the LLM without tainting the context label
This enables tools to return mixed-trust data where some items (internal emails) remain visible while untrusted items (external emails) are automatically hidden without manual intervention.
},
)
for email in emails
]
```
### 3. Automatic Variable Hiding
This feature automatically hides any UNTRUSTED content returned by tools while keeping the hiding logic transparent to the developer. Developers do not need to manually call `store_untrusted_content()`. This allows the LLM /agent's context to remain clean and secure. Key aspects include:
- **Automatic Detection**: Middleware checks integrity label after each tool call
- **Automatic Storage**: UNTRUSTED results/items stored in variable store
- **Transparent Replacement**: LLM context receives `VariableReferenceContent`
- **Context Label Protection**: Hidden content does NOT taint context label
### 4. Context Label Tracking
- Context label starts as TRUSTED + PUBLIC
- Gets updated (tainted) when non-hidden untrusted content enters context
- Policy enforcement uses context label for validation
- Provides `get_context_label()` and `reset_context_label()` methods
### 5. Data Exfiltration Prevention
Tools declare `max_allowed_confidentiality` to prevent sensitive data leakage:
```python
@tool(
description="Post to public Slack channel",
additional_properties={
"max_allowed_confidentiality": "public", # Blocks PRIVATE data
}
)
async def post_to_slack(channel: str, message: str) -> dict:
return {"status": "posted"}
```
### 6. SecureAgentConfig (Context Provider)
SecureAgentConfig extends `ContextProvider` for automatic secure agent configuration:
```python
config = SecureAgentConfig(
auto_hide_untrusted=True,
allow_untrusted_tools={"search_web", "fetch_data"},
block_on_violation=True,
quarantine_chat_client=quarantine_client, # Optional: real LLM for quarantine
)
# Context provider injects tools, instructions, and middleware automatically
agent = Agent(
client=client,
name="secure_assistant",
instructions="You are a helpful assistant.",
tools=[my_tool],
context_providers=[config], # That's it!
)
```
## Security Properties
### Deterministic Defense
1. **Tiered label propagation**: Every tool result receives a label via 3-tier priority (embedded > source_integrity > input labels join)
2. **Context tracking**: Cumulative security state tracked across turns
3. **Policy enforcement**: Violations blocked before execution
4. **Content isolation**: Untrusted content stored as variables
5. **Taint propagation**: Once context becomes UNTRUSTED, it stays UNTRUSTED
6. **Data exfiltration prevention**: `max_allowed_confidentiality` gates output destinations
7. **Audit trail**: All security events logged
8. **No runtime guessing**: Deterministic label assignment
### Attack Prevention
- **Direct prompt injection**: Variables hide actual content from LLM
- **Indirect prompt injection**: Labels track untrusted AI-generated calls
- **Privilege escalation**: Policy blocks untrusted calls to privileged tools
- **Data exfiltration**: Confidentiality labels + `max_allowed_confidentiality` enforced
- **Tool misuse**: Only whitelisted tools accept untrusted inputs
## Configuration Options
### LabelTrackingFunctionMiddleware
- `default_integrity`: Default label for unknown sources
- `default_confidentiality`: Default confidentiality level
- `auto_hide_untrusted`: Enable automatic variable hiding (default: True)
- `hide_threshold`: Integrity level at which hiding occurs (default: UNTRUSTED)
### PolicyEnforcementFunctionMiddleware
- `allow_untrusted_tools`: Set of tools accepting untrusted inputs
- `block_on_violation`: Block vs warn on violations
- `enable_audit_log`: Enable/disable audit logging
### Tool Metadata (via `additional_properties`)
- `confidentiality`: Tool's output confidentiality level
- `source_integrity`: Fallback integrity for unlabeled results (data-producing tools only)
- `accepts_untrusted`: Explicit untrusted input permission
- `max_allowed_confidentiality`: Maximum allowed input confidentiality (for sink tools)
- `requires_approval`: Human-in-the-loop requirement
## Usage Pattern
### Recommended: SecureAgentConfig as Context Provider
```python
from agent_framework.security import SecureAgentConfig
config = SecureAgentConfig(
auto_hide_untrusted=True,
allow_untrusted_tools={"search_web"},
block_on_violation=True,
)
# Context provider injects everything automatically
agent = Agent(
client=client,
name="secure_assistant",
instructions="You are a helpful assistant.",
tools=[search_web],
context_providers=[config], # Tools, instructions, and middleware injected via before_run()
)
```
### Processing Hidden Content with quarantined_llm
```python
from agent_framework.security import quarantined_llm
# Agent automatically uses quarantined_llm with variable_ids
result = await quarantined_llm(
prompt="Summarize this data",
variable_ids=["var_abc123"] # Reference hidden content by ID
)
```
## Testing
Comprehensive test suite with:
- 115+ unit tests covering all components
- Label creation, serialization, combination
- Variable store operations
- Middleware behavior (tracking and enforcement)
- Automatic hiding with per-item labels
- Context label tracking
- Message-level tracking (Phase 1)
- Data exfiltration prevention
- Policy violation scenarios
- Audit log verification
Run tests:
```bash
cd python/packages/core && ../../.venv/bin/pytest tests/test_security.py -v
```
## Code Statistics
- **Total lines**: ~2,950+ lines (single `security.py` module)
- **New modules**: 1 (`security.py` — consolidated from 3 original modules)
- **Total tests**: 115+ unit tests
- **Documentation**: 1,250+ lines in developer guide
- **Examples**: 6+ comprehensive scenarios
## Deliverables Checklist
### Core Implementation
✅ ContentLabel infrastructure with integrity and confidentiality
✅ ContentVariableStore for variable indirection
✅ VariableReferenceContent for safe context references
✅ LabelTrackingFunctionMiddleware for automatic labeling
✅ PolicyEnforcementFunctionMiddleware for policy enforcement
✅ quarantined_llm tool for isolated processing
✅ inspect_variable tool for controlled content access
✅ store_untrusted_content helper for manual variable indirection
### Automatic Hiding Enhancement
✅ Auto-hide UNTRUSTED content with `auto_hide_untrusted` flag
✅ Per-middleware ContentVariableStore instances
✅ Thread-local storage for middleware access from tools
✅ Automatic UNTRUSTED content replacement
### Per-Item Embedded Labels
✅ Support for `additional_properties.security_label` on individual items
✅ Mixed-trust data handling (hide untrusted, keep trusted visible)
✅ Fallback to `source_integrity` for unlabeled items
### Context Label Tracking
✅ Cumulative context label tracking across turns
✅ Hidden content does NOT taint context
`get_context_label()` and `reset_context_label()` methods
✅ Policy enforcement uses context label
### Data Exfiltration Prevention
`max_allowed_confidentiality` tool property
`check_confidentiality_allowed()` helper function
✅ Policy enforcement validates confidentiality flow
### SecureAgentConfig
✅ Context provider pattern with `ContextProvider` base class
`before_run()` hook for automatic injection of tools, instructions, and middleware
✅ One-line secure agent configuration via `context_providers=[config]`
`get_tools()`, `get_instructions()`, `get_middleware()` methods (for manual use)
`quarantine_chat_client` support for real LLM calls
`SECURITY_TOOL_INSTRUCTIONS` constant
### Documentation & Testing
✅ Complete FIDES Developer Guide (~1250 lines)
✅ Architecture Decision Record (ADR)
✅ Quick Start Guide
✅ Comprehensive test suite (115+ tests)
✅ Example code with 6+ scenarios
✅ 3 complete security examples (email, repo confidentiality, GitHub MCP labels)
## Summary
**FIDES** provides a comprehensive, deterministic defense against prompt injection attacks with:
- **Zero-effort protection**: Automatic variable hiding for developers
- **Context provider pattern**: `SecureAgentConfig` extends `ContextProvider` for automatic setup
- **Granular control**: Per-item embedded labels via `Content.from_text()` for mixed-trust data
- **Easy configuration**: `SecureAgentConfig` for one-line setup
- **Data safety**: Exfiltration prevention via confidentiality gates
- **Full traceability**: Message-level label tracking
- **Complete auditability**: All security events logged
The system ensures that untrusted content never directly reaches the LLM context and that all tool calls are policy-checked based on the cumulative security state before execution.
+4 -9
View File
@@ -71,12 +71,12 @@
<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="10.5.1" />
<PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.5.1" />
<PackageVersion Include="Microsoft.Extensions.AI" Version="10.5.0" />
<PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.5.0" />
<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="10.5.1" />
<PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.5.0" />
<PackageVersion Include="Microsoft.Extensions.Caching.Memory" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Compliance.Abstractions" Version="10.5.0" />
<PackageVersion Include="Microsoft.Extensions.Configuration" Version="10.0.1" />
@@ -86,7 +86,6 @@
<PackageVersion Include="Microsoft.Extensions.Configuration.UserSecrets" Version="10.0.1" />
<PackageVersion Include="Microsoft.Extensions.DependencyInjection" Version="10.0.1" />
<PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.6" />
<PackageVersion Include="Microsoft.Extensions.FileSystemGlobbing" Version="10.0.6" />
<PackageVersion Include="Microsoft.Extensions.Hosting" Version="10.0.1" />
<PackageVersion Include="Microsoft.Extensions.Http.Resilience" Version="10.0.0" />
<PackageVersion Include="Microsoft.Extensions.Logging" Version="10.0.1" />
@@ -98,7 +97,7 @@
<PackageVersion Include="Microsoft.SemanticKernel.Connectors.InMemory" Version="1.67.0-preview" />
<PackageVersion Include="Microsoft.SemanticKernel.Connectors.Qdrant" Version="1.67.0-preview" />
<!-- Agent SDKs -->
<PackageVersion Include="GitHub.Copilot.SDK" Version="1.0.0-beta.2" />
<PackageVersion Include="GitHub.Copilot.SDK" Version="0.1.29" />
<PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.3.171-beta" />
<!-- M365 Agents SDK -->
<PackageVersion Include="AdaptiveCards" Version="3.1.0" />
@@ -109,8 +108,6 @@
<PackageVersion Include="A2A.AspNetCore" Version="1.0.0-preview2" />
<!-- MCP -->
<PackageVersion Include="ModelContextProtocol" Version="1.1.0" />
<!-- Hyperlight -->
<PackageVersion Include="Hyperlight.HyperlightSandbox.Api" Version="0.4.0" />
<!-- Inference SDKs -->
<PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.10.0" />
<PackageVersion Include="Microsoft.ML.Tokenizers" Version="2.0.0" />
@@ -138,8 +135,6 @@
<PackageVersion Include="Microsoft.Azure.Functions.Worker.Sdk" Version="2.0.7" />
<!-- Redis -->
<PackageVersion Include="StackExchange.Redis" Version="2.10.1" />
<!-- Console UX -->
<PackageVersion Include="Spectre.Console" Version="0.49.1" />
<!-- Test -->
<PackageVersion Include="FluentAssertions" Version="8.8.0" />
<PackageVersion Include="Microsoft.AspNetCore.TestHost" Condition="'$(TargetFramework)' == 'net8.0'" Version="8.0.22" />
+5 -38
View File
@@ -1,4 +1,4 @@
<Solution>
<Solution>
<Configurations>
<BuildType Name="Debug" />
<BuildType Name="Publish" />
@@ -117,13 +117,6 @@
<Project Path="samples/02-agents/AgentSkills/Agent_Step04_MixedSkills/Agent_Step04_MixedSkills.csproj" />
<Project Path="samples/02-agents/AgentSkills/Agent_Step05_SkillsWithDI/Agent_Step05_SkillsWithDI.csproj" />
</Folder>
<Folder Name="/Samples/02-agents/Harness/">
<File Path="samples/02-agents/Harness/README.md" />
<Project Path="samples/02-agents/Harness/Harness_Shared_Console/Harness_Shared_Console.csproj" />
<Project Path="samples/02-agents/Harness/Harness_Step01_Research/Harness_Step01_Research.csproj" />
<Project Path="samples/02-agents/Harness/Harness_Step02_Research_WithSubAgents/Harness_Step02_Research_WithSubAgents.csproj" />
<Project Path="samples/02-agents/Harness/Harness_Step03_DataProcessing/Harness_Step03_DataProcessing.csproj" />
</Folder>
<Folder Name="/Samples/02-agents/AGUI/Step05_StateManagement/">
<Project Path="samples/02-agents/AGUI/Step05_StateManagement/Client/Client.csproj" />
<Project Path="samples/02-agents/AGUI/Step05_StateManagement/Server/Server.csproj" />
@@ -170,16 +163,10 @@
<Project Path="samples/02-agents/AgentsWithFoundry/Agent_Step25_ToolboxServerSideTools/Agent_Step25_ToolboxServerSideTools.csproj" />
</Folder>
<Folder Name="/Samples/02-agents/Evaluation/">
<Project Path="samples/02-agents/Evaluation/Evaluation_SimpleEval/Evaluation_SimpleEval.csproj" />
<Project Path="samples/02-agents/Evaluation/Evaluation_CustomEvals/Evaluation_CustomEvals.csproj" />
<Project Path="samples/02-agents/Evaluation/Evaluation_ExpectedOutputs/Evaluation_ExpectedOutputs.csproj" />
<Project Path="samples/02-agents/Evaluation/Evaluation_Multimodal/Evaluation_Multimodal.csproj" />
<Project Path="samples/02-agents/Evaluation/Evaluation_SimpleEval/Evaluation_SimpleEval.csproj" />
</Folder>
<Folder Name="/Samples/02-agents/AgentWithCodeAct/">
<File Path="samples/02-agents/AgentWithCodeAct/README.md" />
<Project Path="samples/02-agents/AgentWithCodeAct/AgentWithCodeAct_Step01_Interpreter/AgentWithCodeAct_Step01_Interpreter.csproj" />
<Project Path="samples/02-agents/AgentWithCodeAct/AgentWithCodeAct_Step02_ToolEnabled/AgentWithCodeAct_Step02_ToolEnabled.csproj" />
<Project Path="samples/02-agents/AgentWithCodeAct/AgentWithCodeAct_Step03_ManualWiring/AgentWithCodeAct_Step03_ManualWiring.csproj" />
</Folder>
<Folder Name="/Samples/02-agents/AgentWithMemory/">
<File Path="samples/02-agents/AgentWithMemory/README.md" />
@@ -239,7 +226,6 @@
<Project Path="samples/03-workflows/Declarative/HostedWorkflow/HostedWorkflow.csproj" />
<Project Path="samples/03-workflows/Declarative/InputArguments/InputArguments.csproj" />
<Project Path="samples/03-workflows/Declarative/InvokeFunctionTool/InvokeFunctionTool.csproj" />
<Project Path="samples/03-workflows/Declarative/InvokeHttpRequest/InvokeHttpRequest.csproj" />
<Project Path="samples/03-workflows/Declarative/InvokeMcpTool/InvokeMcpTool.csproj" />
<Project Path="samples/03-workflows/Declarative/Marketing/Marketing.csproj" />
<Project Path="samples/03-workflows/Declarative/StudentTeacher/StudentTeacher.csproj" />
@@ -319,9 +305,6 @@
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-McpTools/">
<Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-McpTools/HostedMcpTools.csproj" />
</Folder>
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-Observability/">
<Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-Observability/HostedObservability.csproj" />
</Folder>
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-Toolbox/">
<Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-Toolbox/HostedToolbox.csproj" />
</Folder>
@@ -364,17 +347,17 @@
<File Path="samples/02-agents/A2A/README.md" />
<Project Path="samples/02-agents/A2A/A2AAgent_AsFunctionTools/A2AAgent_AsFunctionTools.csproj" />
<Project Path="samples/02-agents/A2A/A2AAgent_PollingForTaskCompletion/A2AAgent_PollingForTaskCompletion.csproj" />
<Project Path="samples/02-agents/A2A/A2AAgent_ProtocolSelection/A2AAgent_ProtocolSelection.csproj" />
<Project Path="samples/02-agents/A2A/A2AAgent_StreamReconnection/A2AAgent_StreamReconnection.csproj" />
<Project Path="samples/02-agents/A2A/A2AAgent_ProtocolSelection/A2AAgent_ProtocolSelection.csproj" />
</Folder>
<Folder Name="/Samples/05-end-to-end/">
<Project Path="samples/05-end-to-end/AgentWithPurview/AgentWithPurview.csproj" />
<Project Path="samples/05-end-to-end/M365Agent/M365Agent.csproj" />
</Folder>
<Folder Name="/Samples/05-end-to-end/Evaluation/">
<Project Path="samples/05-end-to-end/Evaluation/Evaluation_ConversationSplits/Evaluation_ConversationSplits.csproj" />
<Project Path="samples/05-end-to-end/Evaluation/Evaluation_FoundryQuality/Evaluation_FoundryQuality.csproj" />
<Project Path="samples/05-end-to-end/Evaluation/Evaluation_MixedProviders/Evaluation_MixedProviders.csproj" />
<Project Path="samples/05-end-to-end/Evaluation/Evaluation_ConversationSplits/Evaluation_ConversationSplits.csproj" />
</Folder>
<Folder Name="/Samples/05-end-to-end/A2AClientServer/">
<File Path="samples/05-end-to-end/A2AClientServer/README.md" />
@@ -544,16 +527,6 @@
<Folder Name="/Solution Items/src/Shared/StructuredOutput/">
<File Path="src/Shared/StructuredOutput/StructuredOutputSchemaUtilities.cs" />
</Folder>
<Folder Name="/Solution Items/src/Shared/Workflows/" />
<Folder Name="/Solution Items/src/Shared/Workflows/Execution/">
<File Path="src/Shared/Workflows/Execution/README.md" />
<File Path="src/Shared/Workflows/Execution/WorkflowFactory.cs" />
<File Path="src/Shared/Workflows/Execution/WorkflowRunner.cs" />
</Folder>
<Folder Name="/Solution Items/src/Shared/Workflows/Settings/">
<File Path="src/Shared/Workflows/Settings/Application.cs" />
<File Path="src/Shared/Workflows/Settings/README.md" />
</Folder>
<Folder Name="/Solution Items/tests/">
<File Path="tests/.editorconfig" />
<File Path="tests/Directory.Build.props" />
@@ -570,8 +543,8 @@
<Project Path="src/Microsoft.Agents.AI.Declarative/Microsoft.Agents.AI.Declarative.csproj" />
<Project Path="src/Microsoft.Agents.AI.DevUI/Microsoft.Agents.AI.DevUI.csproj" />
<Project Path="src/Microsoft.Agents.AI.DurableTask/Microsoft.Agents.AI.DurableTask.csproj" />
<Project Path="src/Microsoft.Agents.AI.Foundry.Hosting/Microsoft.Agents.AI.Foundry.Hosting.csproj" />
<Project Path="src/Microsoft.Agents.AI.Foundry/Microsoft.Agents.AI.Foundry.csproj" />
<Project Path="src/Microsoft.Agents.AI.Foundry.Hosting/Microsoft.Agents.AI.Foundry.Hosting.csproj" />
<Project Path="src/Microsoft.Agents.AI.GitHub.Copilot/Microsoft.Agents.AI.GitHub.Copilot.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting.A2A.AspNetCore/Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting.A2A/Microsoft.Agents.AI.Hosting.A2A.csproj" />
@@ -579,7 +552,6 @@
<Project Path="src/Microsoft.Agents.AI.Hosting.AzureFunctions/Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting.OpenAI/Microsoft.Agents.AI.Hosting.OpenAI.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hosting/Microsoft.Agents.AI.Hosting.csproj" />
<Project Path="src/Microsoft.Agents.AI.Hyperlight/Microsoft.Agents.AI.Hyperlight.csproj" />
<Project Path="src/Microsoft.Agents.AI.Mem0/Microsoft.Agents.AI.Mem0.csproj" />
<Project Path="src/Microsoft.Agents.AI.OpenAI/Microsoft.Agents.AI.OpenAI.csproj" />
<Project Path="src/Microsoft.Agents.AI.Purview/Microsoft.Agents.AI.Purview.csproj" />
@@ -596,14 +568,11 @@
<Project Path="tests/AnthropicChatCompletion.IntegrationTests/AnthropicChatCompletion.IntegrationTests.csproj" />
<Project Path="tests/AzureAIAgentsPersistent.IntegrationTests/AzureAIAgentsPersistent.IntegrationTests.csproj" />
<Project Path="tests/CopilotStudio.IntegrationTests/CopilotStudio.IntegrationTests.csproj" />
<Project Path="tests/Foundry.Hosting.IntegrationTests/Foundry.Hosting.IntegrationTests.csproj" />
<Project Path="tests/Foundry.Hosting.IntegrationTests.TestContainer/Foundry.Hosting.IntegrationTests.TestContainer.csproj" />
<Project Path="tests/Foundry.IntegrationTests/Foundry.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.DurableTask.IntegrationTests/Microsoft.Agents.AI.DurableTask.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.GitHub.Copilot.IntegrationTests/Microsoft.Agents.AI.GitHub.Copilot.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hyperlight.IntegrationTests/Microsoft.Agents.AI.Hyperlight.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Mem0.IntegrationTests/Microsoft.Agents.AI.Mem0.IntegrationTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Workflows.Declarative.IntegrationTests/Microsoft.Agents.AI.Workflows.Declarative.IntegrationTests.csproj" />
<Project Path="tests/OpenAIAssistant.IntegrationTests/OpenAIAssistant.IntegrationTests.csproj" />
@@ -622,14 +591,12 @@
<Project Path="tests/Microsoft.Agents.AI.DevUI.UnitTests/Microsoft.Agents.AI.DevUI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.DurableTask.UnitTests/Microsoft.Agents.AI.DurableTask.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Foundry.UnitTests/Microsoft.Agents.AI.Foundry.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Foundry.Hosting.UnitTests/Microsoft.Agents.AI.Foundry.Hosting.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.GitHub.Copilot.UnitTests/Microsoft.Agents.AI.GitHub.Copilot.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.A2A.UnitTests/Microsoft.Agents.AI.Hosting.A2A.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.AzureFunctions.UnitTests/Microsoft.Agents.AI.Hosting.AzureFunctions.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.OpenAI.UnitTests/Microsoft.Agents.AI.Hosting.OpenAI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hosting.UnitTests/Microsoft.Agents.AI.Hosting.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Hyperlight.UnitTests/Microsoft.Agents.AI.Hyperlight.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Mem0.UnitTests/Microsoft.Agents.AI.Mem0.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.OpenAI.UnitTests/Microsoft.Agents.AI.OpenAI.UnitTests.csproj" />
<Project Path="tests/Microsoft.Agents.AI.Purview.UnitTests/Microsoft.Agents.AI.Purview.UnitTests.csproj" />
+3 -3
View File
@@ -1,14 +1,14 @@
<Project>
<PropertyGroup>
<!-- Central version prefix - applies to all nuget packages. -->
<VersionPrefix>1.4.0</VersionPrefix>
<VersionPrefix>1.3.0</VersionPrefix>
<RCNumber>1</RCNumber>
<DateSuffix>260505</DateSuffix>
<DateSuffix>260423</DateSuffix>
<PackageVersion Condition="'$(IsReleaseCandidate)' == 'true'">$(VersionPrefix)-rc$(RCNumber)</PackageVersion>
<PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).$(DateSuffix).1</PackageVersion>
<PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.$(DateSuffix).1</PackageVersion>
<PackageVersion Condition="'$(IsReleased)' == 'true'">$(VersionPrefix)</PackageVersion>
<GitTag>1.4.0</GitTag>
<GitTag>1.3.0</GitTag>
<Configurations>Debug;Release;Publish</Configurations>
<IsPackable>true</IsPackable>
@@ -12,9 +12,7 @@ static Task<PermissionRequestResult> PromptPermission(PermissionRequest request,
Console.Write("Approve? (y/n): ");
string? input = Console.ReadLine()?.Trim().ToUpperInvariant();
PermissionRequestResultKind kind = input is "Y" or "YES"
? PermissionRequestResultKind.Approved
: PermissionRequestResultKind.Rejected;
string kind = input is "Y" or "YES" ? "approved" : "denied-interactively-by-user";
return Task.FromResult(new PermissionRequestResult { Kind = kind });
}
@@ -1,22 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Hyperlight\Microsoft.Agents.AI.Hyperlight.csproj" />
</ItemGroup>
</Project>
@@ -1,30 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to use HyperlightCodeActProvider as a sandboxed Python
// code interpreter: the model can write and execute arbitrary Python code to
// answer quantitative questions without calling any additional tools.
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hyperlight;
using OpenAI.Chat;
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
var guestPath = Environment.GetEnvironmentVariable("HYPERLIGHT_PYTHON_GUEST_PATH") ?? throw new InvalidOperationException("HYPERLIGHT_PYTHON_GUEST_PATH is not set.");
using var codeAct = new HyperlightCodeActProvider(HyperlightCodeActProviderOptions.CreateForWasm(guestPath));
AIAgent agent = new AzureOpenAIClient(
new Uri(endpoint),
new DefaultAzureCredential())
.GetChatClient(deploymentName)
.AsAIAgent(new ChatClientAgentOptions()
{
ChatOptions = new() { Instructions = "You are a helpful assistant. When the user asks something quantitative, write Python and call `execute_code` instead of guessing." },
AIContextProviders = [codeAct],
});
Console.WriteLine(await agent.RunAsync("What is the 20th Fibonacci number?"));
Console.WriteLine(await agent.RunAsync("Compute the mean and standard deviation of [1, 4, 9, 16, 25, 36]."));
@@ -1,35 +0,0 @@
# AgentWithCodeAct_Step01_Interpreter
A minimal CodeAct sample. The agent uses `HyperlightCodeActProvider` as a
sandboxed Python interpreter: when the user asks something quantitative, the
model writes Python and invokes the `execute_code` tool rather than answering
from memory.
## Configuration
| Variable | Description |
|--------------------------------|-------------------------------------------------------------------------------------------|
| `AZURE_OPENAI_ENDPOINT` | Azure OpenAI endpoint. Required. |
| `AZURE_OPENAI_DEPLOYMENT_NAME` | Azure OpenAI deployment. Defaults to `gpt-5.4-mini`. |
| `HYPERLIGHT_PYTHON_GUEST_PATH` | Absolute path to the Hyperlight Python guest module (`.wasm` or `.aot` file). Required. |
Authentication uses `DefaultAzureCredential`.
## Getting the guest module
The Python guest module is built from the
[hyperlight-dev/hyperlight-sandbox](https://github.com/hyperlight-dev/hyperlight-sandbox)
repository — see its README for the exact `cargo`/`just` invocations and
the location of the resulting `.wasm` / `.aot` file. Set
`HYPERLIGHT_PYTHON_GUEST_PATH` to the absolute path of that artifact
before running the sample.
Hyperlight requires a hardware virtualization back end on the host:
KVM on Linux or WHP (Windows Hypervisor Platform) on Windows.
## Run
```shell
cd AgentWithCodeAct_Step01_Interpreter
dotnet run
```
@@ -1,22 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Hyperlight\Microsoft.Agents.AI.Hyperlight.csproj" />
</ItemGroup>
</Project>
@@ -1,52 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to use HyperlightCodeActProvider with provider-owned
// tools (exposed inside the sandbox via `call_tool(...)`). The model can
// orchestrate those tools in a single Python block, reducing round-trips. A
// sensitive tool (`send_email`) is additionally wrapped in
// ApprovalRequiredAIFunction so any code that reaches it requires user approval
// for the entire execute_code invocation.
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hyperlight;
using Microsoft.Extensions.AI;
using OpenAI.Chat;
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
var guestPath = Environment.GetEnvironmentVariable("HYPERLIGHT_PYTHON_GUEST_PATH") ?? throw new InvalidOperationException("HYPERLIGHT_PYTHON_GUEST_PATH is not set.");
AIFunction fetchDocs = AIFunctionFactory.Create(
(string topic) => $"Docs for {topic}: (...)",
name: "fetch_docs",
description: "Fetch documentation for a given topic.");
AIFunction queryData = AIFunctionFactory.Create(
(string query) => $"Rows for `{query}`: []",
name: "query_data",
description: "Run a read-only SQL-like query against the sample store.");
AIFunction sendEmail = new ApprovalRequiredAIFunction(
AIFunctionFactory.Create(
(string to, string subject) => $"Sent '{subject}' to {to}.",
name: "send_email",
description: "Send an email on behalf of the user."));
var options = HyperlightCodeActProviderOptions.CreateForWasm(guestPath);
options.Tools = [fetchDocs, queryData, sendEmail];
using var codeAct = new HyperlightCodeActProvider(options);
AIAgent agent = new AzureOpenAIClient(
new Uri(endpoint),
new DefaultAzureCredential())
.GetChatClient(deploymentName)
.AsAIAgent(new ChatClientAgentOptions()
{
ChatOptions = new() { Instructions = "You are a helpful assistant. Prefer orchestrating your work in a single `execute_code` block using `call_tool(...)` over issuing many direct tool calls." },
AIContextProviders = [codeAct],
});
Console.WriteLine(await agent.RunAsync("Look up docs on 'retries' and query the 'orders' table, then summarize."));
@@ -1,34 +0,0 @@
# AgentWithCodeAct_Step02_ToolEnabled
Demonstrates adding provider-owned tools to `HyperlightCodeActProvider`. Those
tools are **only** available to code running inside the sandbox via
`call_tool("<name>", ...)` — they are never exposed to the model as direct
tools. This lets the model orchestrate multiple tool calls in a single Python
block.
One tool (`send_email`) is wrapped in `ApprovalRequiredAIFunction`, which causes
the entire `execute_code` invocation to require user approval when that tool
is configured.
## Configuration
| Variable | Description |
|--------------------------------|-------------------------------------------------------------------------------------------|
| `AZURE_OPENAI_ENDPOINT` | Azure OpenAI endpoint. Required. |
| `AZURE_OPENAI_DEPLOYMENT_NAME` | Azure OpenAI deployment. Defaults to `gpt-5.4-mini`. |
| `HYPERLIGHT_PYTHON_GUEST_PATH` | Absolute path to the Hyperlight Python guest module (`.wasm` or `.aot` file). Required. |
## Run
```shell
cd AgentWithCodeAct_Step02_ToolEnabled
dotnet run
```
## Planned follow-up
A more realistic "upload a file (e.g. an Excel workbook), have the agent
analyze it with code" sample is planned as a separate step that will use
`HostInputDirectory` together with a guest tool capable of reading the
uploaded file. It will be added in a follow-up PR once the corresponding
guest module support is in place.
@@ -1,22 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Hyperlight\Microsoft.Agents.AI.Hyperlight.csproj" />
</ItemGroup>
</Project>
@@ -1,40 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to wire up CodeAct manually using
// HyperlightExecuteCodeFunction rather than the AIContextProvider. Use this
// when you want a fixed tool surface for the agent's lifetime and don't need
// the per-run snapshot/registry semantics of HyperlightCodeActProvider.
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Hyperlight;
using Microsoft.Extensions.AI;
using OpenAI.Chat;
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
var guestPath = Environment.GetEnvironmentVariable("HYPERLIGHT_PYTHON_GUEST_PATH") ?? throw new InvalidOperationException("HYPERLIGHT_PYTHON_GUEST_PATH is not set.");
AIFunction calculate = AIFunctionFactory.Create(
(double a, double b) => a * b,
name: "multiply",
description: "Multiply two numbers.");
var options = HyperlightCodeActProviderOptions.CreateForWasm(guestPath);
options.Tools = [calculate];
using var executeCode = new HyperlightExecuteCodeFunction(options);
var instructions =
"You are a helpful assistant. When math is involved, solve it by writing Python "
+ "and calling `execute_code` instead of computing values yourself.\n\n"
+ executeCode.BuildInstructions(toolsVisibleToModel: false);
AIAgent agent = new AzureOpenAIClient(
new Uri(endpoint),
new DefaultAzureCredential())
.GetChatClient(deploymentName)
.AsAIAgent(instructions: instructions, tools: [executeCode]);
Console.WriteLine(await agent.RunAsync("What is 12.3 * 4.5? Use the multiply tool from within `execute_code`."));
@@ -1,21 +0,0 @@
# AgentWithCodeAct_Step03_ManualWiring
Shows how to wire CodeAct manually using `HyperlightExecuteCodeFunction` as a
direct agent tool instead of via an `AIContextProvider`. This is useful when
the sandbox's tool surface and capabilities are fixed for the agent's
lifetime, avoiding per-run snapshot/restore of the provider registry.
## Configuration
| Variable | Description |
|--------------------------------|-------------------------------------------------------------------------------------------|
| `AZURE_OPENAI_ENDPOINT` | Azure OpenAI endpoint. Required. |
| `AZURE_OPENAI_DEPLOYMENT_NAME` | Azure OpenAI deployment. Defaults to `gpt-5.4-mini`. |
| `HYPERLIGHT_PYTHON_GUEST_PATH` | Absolute path to the Hyperlight Python guest module (`.wasm` or `.aot` file). Required. |
## Run
```shell
cd AgentWithCodeAct_Step03_ManualWiring
dotnet run
```
@@ -1,16 +0,0 @@
# Agent Framework CodeAct (Hyperlight) Samples
These samples show how to enable an agent to write and execute code in a
Hyperlight-backed sandbox via the CodeAct pattern. Guest code can be pure
Python (interpreter mode) or orchestrate host-provided tools through
`call_tool(...)` — all inside a secure sandbox with opt-in filesystem and
network access.
|Sample|Description|
|---|---|
|[Code interpreter](./AgentWithCodeAct_Step01_Interpreter/)|Uses `HyperlightCodeActProvider` as a sandboxed Python interpreter with no host tools.|
|[Tool-enabled CodeAct](./AgentWithCodeAct_Step02_ToolEnabled/)|Registers provider-owned tools that guest code can orchestrate via `call_tool(...)`, with an approval-required tool for sensitive actions.|
|[Manual wiring](./AgentWithCodeAct_Step03_ManualWiring/)|Uses `HyperlightExecuteCodeFunction` directly as an agent tool when the sandbox configuration is fixed.|
All samples require a Hyperlight Python guest module. Set
`HYPERLIGHT_PYTHON_GUEST_PATH` to its absolute path before running.
@@ -1,28 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Agents.AI;
namespace Harness.Shared.Console.Commands;
/// <summary>
/// Handles a console command (e.g., /todos, /mode). Command handlers are checked
/// in order before user input is sent to the agent. The first handler that
/// accepts the input prevents further handlers from being checked.
/// </summary>
public interface ICommandHandler
{
/// <summary>
/// Gets the help text for this command, displayed in the console header.
/// Returns <see langword="null"/> if the command is not currently available.
/// </summary>
/// <returns>Help text like <c>"/todos (show todo list)"</c>, or <see langword="null"/>.</returns>
string? GetHelpText();
/// <summary>
/// Attempts to handle the given user input.
/// </summary>
/// <param name="input">The raw user input string.</param>
/// <param name="session">The current agent session.</param>
/// <returns><see langword="true"/> if this handler handled the input; <see langword="false"/> otherwise.</returns>
ValueTask<bool> TryHandleAsync(string input, AgentSession session);
}
@@ -1,69 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Agents.AI;
namespace Harness.Shared.Console.Commands;
/// <summary>
/// Handles the <c>/mode</c> command to display or switch the current agent mode.
/// </summary>
internal sealed class ModeCommandHandler : ICommandHandler
{
private readonly AgentModeProvider? _modeProvider;
private readonly IReadOnlyDictionary<string, ConsoleColor>? _modeColors;
/// <summary>
/// Initializes a new instance of the <see cref="ModeCommandHandler"/> class.
/// </summary>
/// <param name="modeProvider">The mode provider, or <see langword="null"/> if not available.</param>
/// <param name="modeColors">Optional mapping of mode names to console colors.</param>
public ModeCommandHandler(AgentModeProvider? modeProvider, IReadOnlyDictionary<string, ConsoleColor>? modeColors = null)
{
this._modeProvider = modeProvider;
this._modeColors = modeColors;
}
/// <inheritdoc/>
public string? GetHelpText() => this._modeProvider is not null ? "/mode [plan|execute] (show or switch mode)" : null;
/// <inheritdoc/>
public ValueTask<bool> TryHandleAsync(string input, AgentSession session)
{
if (!input.StartsWith("/mode ", StringComparison.OrdinalIgnoreCase) && !input.Equals("/mode", StringComparison.OrdinalIgnoreCase))
{
return ValueTask.FromResult(false);
}
if (this._modeProvider is null)
{
System.Console.WriteLine("AgentModeProvider is not available.");
return ValueTask.FromResult(true);
}
string[] parts = input.Split(' ', 2, StringSplitOptions.RemoveEmptyEntries | StringSplitOptions.TrimEntries);
if (parts.Length < 2)
{
string current = this._modeProvider.GetMode(session);
System.Console.WriteLine($"\n Current mode: {current}\n");
return ValueTask.FromResult(true);
}
string newMode = parts[1];
try
{
this._modeProvider.SetMode(session, newMode);
System.Console.ForegroundColor = ConsoleWriter.GetModeColor(newMode, this._modeColors);
System.Console.WriteLine($"\n Switched to {newMode} mode.\n");
System.Console.ResetColor();
}
catch (ArgumentException ex)
{
System.Console.ForegroundColor = ConsoleColor.Red;
System.Console.WriteLine($"\n {ex}\n");
System.Console.ResetColor();
}
return ValueTask.FromResult(true);
}
}
@@ -1,66 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Agents.AI;
namespace Harness.Shared.Console.Commands;
/// <summary>
/// Handles the <c>/todos</c> command to display the current todo list.
/// </summary>
internal sealed class TodoCommandHandler : ICommandHandler
{
private readonly TodoProvider? _todoProvider;
/// <summary>
/// Initializes a new instance of the <see cref="TodoCommandHandler"/> class.
/// </summary>
/// <param name="todoProvider">The todo provider, or <see langword="null"/> if not available.</param>
public TodoCommandHandler(TodoProvider? todoProvider)
{
this._todoProvider = todoProvider;
}
/// <inheritdoc/>
public string? GetHelpText() => this._todoProvider is not null ? "/todos (show todo list)" : null;
/// <inheritdoc/>
public async ValueTask<bool> TryHandleAsync(string input, AgentSession session)
{
if (!input.Equals("/todos", StringComparison.OrdinalIgnoreCase))
{
return false;
}
if (this._todoProvider is null)
{
System.Console.WriteLine("TodoProvider is not available.");
return true;
}
var todos = await this._todoProvider.GetAllTodosAsync(session).ConfigureAwait(false);
if (todos.Count == 0)
{
System.Console.WriteLine("\n No todos yet.\n");
return true;
}
System.Console.WriteLine();
System.Console.WriteLine(" ── Todo List ──");
foreach (var item in todos)
{
string status = item.IsComplete ? "✓" : "○";
System.Console.ForegroundColor = item.IsComplete ? ConsoleColor.DarkGray : ConsoleColor.White;
System.Console.Write($" [{status}] #{item.Id} {item.Title}");
if (!string.IsNullOrWhiteSpace(item.Description))
{
System.Console.Write($" — {item.Description}");
}
System.Console.WriteLine();
}
System.Console.ResetColor();
System.Console.WriteLine();
return true;
}
}
@@ -1,278 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Spectre.Console;
namespace Harness.Shared.Console;
/// <summary>
/// Centralizes all console output and spinner management for the harness console.
/// Observers write through this class so the spinner is automatically paused before output.
/// </summary>
public sealed class ConsoleWriter : IDisposable
{
private readonly Spinner _spinner = new();
private readonly IReadOnlyDictionary<string, ConsoleColor>? _modeColors;
private bool _lastWasText;
private bool _hasReceivedAnyText;
/// <summary>
/// Initializes a new instance of the <see cref="ConsoleWriter"/> class.
/// </summary>
/// <param name="modeColors">Optional mapping of mode names to console colors.</param>
public ConsoleWriter(IReadOnlyDictionary<string, ConsoleColor>? modeColors = null)
{
this._modeColors = modeColors;
}
/// <summary>
/// Gets or sets the current agent mode (e.g., "plan", "execute").
/// Used to determine the console color for mode-prefixed output.
/// </summary>
public string? CurrentMode { get; set; }
/// <summary>
/// Writes the agent response header (e.g., "[plan] Agent: ") and starts the spinner.
/// </summary>
public void WriteResponseHeader()
{
if (this.CurrentMode is not null)
{
System.Console.ForegroundColor = GetModeColor(this.CurrentMode, this._modeColors);
System.Console.Write($"\n[{this.CurrentMode}] Agent: ");
}
else
{
System.Console.Write("\nAgent: ");
}
this._lastWasText = true;
this._hasReceivedAnyText = false;
this._spinner.Start();
}
/// <summary>
/// Writes informational output with automatic prefix spacing, without a trailing newline.
/// Use when continuation content will be appended on the same line.
/// </summary>
/// <param name="text">The informational text to write (without leading newline/indent — added automatically).</param>
/// <param name="color">Optional console color for the text.</param>
public async Task WriteInfoAsync(string text, ConsoleColor? color = null)
{
await this.WriteInfoCoreAsync(text, color, newLine: false);
}
/// <summary>
/// Writes informational output with automatic prefix spacing, followed by a newline.
/// </summary>
/// <param name="text">The informational text to write (without leading newline/indent — added automatically).</param>
/// <param name="color">Optional console color for the text.</param>
public async Task WriteInfoLineAsync(string text, ConsoleColor? color = null)
{
await this.WriteInfoCoreAsync(text, color, newLine: true);
}
private async Task WriteInfoCoreAsync(string text, ConsoleColor? color, bool newLine)
{
await this._spinner.StopAsync();
string prefix = this._lastWasText ? "\n\n " : " ";
this._lastWasText = false;
System.Console.ForegroundColor = color ?? GetModeColor(this.CurrentMode, this._modeColors);
if (newLine)
{
System.Console.WriteLine(prefix + text);
}
else
{
System.Console.Write(prefix + text);
}
System.Console.ForegroundColor = GetModeColor(this.CurrentMode, this._modeColors);
this._spinner.Start();
}
/// <summary>
/// Writes text output from the agent, managing line break state.
/// Ensures a newline is written before the first text output.
/// </summary>
/// <param name="text">The text to write.</param>
/// <param name="color">Optional console color override for this text.</param>
public async Task WriteTextAsync(string text, ConsoleColor? color = null)
{
await this._spinner.StopAsync();
if (!this._lastWasText)
{
System.Console.Write("\n");
this._lastWasText = true;
}
this._hasReceivedAnyText = true;
if (color.HasValue)
{
System.Console.ForegroundColor = color.Value;
}
System.Console.Write(text);
if (color.HasValue)
{
System.Console.ForegroundColor = GetModeColor(this.CurrentMode, this._modeColors);
}
this._spinner.Start();
}
/// <summary>
/// Reads a line of input from the console, pausing the spinner while waiting for input.
/// Optionally displays a prompt before reading. The prompt is rendered between
/// two horizontal rules for visual clarity.
/// </summary>
/// <param name="prompt">Optional prompt text to display before reading input.</param>
/// <param name="promptColor">Optional console color for the prompt text.</param>
/// <returns>The line read from the console, or <c>null</c> if no input is available.</returns>
public async Task<string?> ReadLineAsync(string? prompt = null, ConsoleColor? promptColor = null)
{
await this._spinner.StopAsync();
if (prompt is not null)
{
System.Console.WriteLine();
AnsiConsole.Write(this.CreateModeRule());
if (promptColor.HasValue)
{
System.Console.ForegroundColor = promptColor.Value;
}
System.Console.Write($" {prompt}");
if (promptColor.HasValue)
{
System.Console.ForegroundColor = GetModeColor(this.CurrentMode, this._modeColors);
}
}
string? input = System.Console.ReadLine();
if (prompt is not null)
{
AnsiConsole.Write(this.CreateModeRule());
}
this._lastWasText = false;
return input;
}
/// <summary>
/// Presents a selection prompt with the given choices, plus an option to type a custom response.
/// Uses Spectre.Console <see cref="SelectionPrompt{T}"/> for interactive arrow-key selection.
/// </summary>
/// <param name="title">The title/question displayed above the selection list.</param>
/// <param name="choices">The list of choices to present.</param>
/// <returns>The selected choice text, or the custom-typed response.</returns>
public async Task<string> ReadSelectionAsync(string title, IList<string> choices)
{
await this._spinner.StopAsync();
AnsiConsole.Write(this.CreateModeRule());
const string FreeformOption = "✏️ Type a custom response...";
var allChoices = choices.Concat([FreeformOption]).ToList();
var prompt = new SelectionPrompt<string>()
.Title($" [bold]{Markup.Escape(title)}[/]")
.PageSize(10)
.AddChoices(allChoices);
string selection = AnsiConsole.Prompt(prompt);
if (selection == FreeformOption)
{
var textPrompt = new TextPrompt<string>(" [grey]Response:[/]");
selection = AnsiConsole.Prompt(textPrompt);
}
AnsiConsole.MarkupLine($" [dim]→ {Markup.Escape(selection)}[/]");
AnsiConsole.Write(this.CreateModeRule());
this._lastWasText = false;
return selection;
}
/// <summary>
/// Writes the stream-complete footer (handles "no text response" fallback, resets color).
/// </summary>
public async Task WriteStreamFooterAsync(bool hasFollowUpMessages)
{
await this._spinner.StopAsync();
if (!this._hasReceivedAnyText && !hasFollowUpMessages)
{
System.Console.ForegroundColor = ConsoleColor.DarkYellow;
System.Console.Write("\n (no text response from agent)");
}
System.Console.ResetColor();
System.Console.WriteLine();
}
/// <inheritdoc/>
public void Dispose()
{
this._spinner.Dispose();
}
/// <summary>
/// Gets the console color associated with a mode name, using the provided color map.
/// </summary>
internal static ConsoleColor GetModeColor(string? mode, IReadOnlyDictionary<string, ConsoleColor>? modeColors = null)
{
if (mode is null)
{
return ConsoleColor.Gray;
}
if (modeColors is not null && modeColors.TryGetValue(mode, out var color))
{
return color;
}
return ConsoleColor.Gray;
}
/// <summary>
/// Creates a <see cref="Rule"/> styled with the current mode color.
/// </summary>
internal Rule CreateModeRule()
{
var spectreColor = ToSpectreColor(GetModeColor(this.CurrentMode, this._modeColors));
return new Rule().RuleStyle(new Style(spectreColor));
}
internal static Color ToSpectreColor(ConsoleColor consoleColor) => consoleColor switch
{
ConsoleColor.Black => Color.Black,
ConsoleColor.DarkBlue => Color.Blue,
ConsoleColor.DarkGreen => Color.Green,
ConsoleColor.DarkCyan => Color.Teal,
ConsoleColor.DarkRed => Color.Red,
ConsoleColor.DarkMagenta => Color.Purple,
ConsoleColor.DarkYellow => Color.Olive,
ConsoleColor.Gray => Color.Silver,
ConsoleColor.DarkGray => Color.Grey,
ConsoleColor.Blue => Color.Blue1,
ConsoleColor.Green => Color.Green1,
ConsoleColor.Cyan => Color.Aqua,
ConsoleColor.Red => Color.Red1,
ConsoleColor.Magenta => Color.Fuchsia,
ConsoleColor.Yellow => Color.Yellow,
ConsoleColor.White => Color.White,
_ => Color.Silver,
};
}
@@ -1,214 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Harness.Shared.Console.Commands;
using Harness.Shared.Console.Observers;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
namespace Harness.Shared.Console;
/// <summary>
/// Provides a reusable interactive console loop for running an <see cref="AIAgent"/>
/// with streaming output, extensible observers, and mode-aware interaction strategies.
/// </summary>
public static class HarnessConsole
{
/// <summary>
/// Runs an interactive console session with the specified agent.
/// Supports streaming output, tool call display, spinner animation,
/// optional planning UX with structured output, and the <c>/todos</c> command.
/// </summary>
/// <param name="agent">The agent to interact with.</param>
/// <param name="title">The title displayed in the console header.</param>
/// <param name="userPrompt">A short prompt to the user, displayed below the title.</param>
/// <param name="options">Optional configuration options for the console session.</param>
public static async Task RunAgentAsync(AIAgent agent, string title, string userPrompt, HarnessConsoleOptions? options = null)
{
options ??= new();
if (options.EnablePlanningUx
&& (string.IsNullOrWhiteSpace(options.PlanningModeName) || string.IsNullOrWhiteSpace(options.ExecutionModeName)))
{
throw new ArgumentException(
"When EnablePlanningUx is true, both PlanningModeName and ExecutionModeName must be configured.",
nameof(options));
}
System.Console.WriteLine($"=== {title} ===");
System.Console.WriteLine(userPrompt);
var todoProvider = agent.GetService<TodoProvider>();
var modeProvider = agent.GetService<AgentModeProvider>();
// Build command handlers.
var commandHandlers = new List<ICommandHandler>
{
new TodoCommandHandler(todoProvider),
new ModeCommandHandler(modeProvider, options.ModeColors),
};
var commands = commandHandlers
.Select(h => h.GetHelpText())
.Where(t => t is not null)
.Append("exit (quit)");
System.Console.WriteLine($"Commands: {string.Join(", ", commands)}");
System.Console.WriteLine();
AgentSession session = await agent.CreateSessionAsync();
using var writer = new ConsoleWriter(options.ModeColors);
writer.CurrentMode = modeProvider?.GetMode(session);
string prompt = BuildUserPrompt(modeProvider, session);
string? userInput = await writer.ReadLineAsync(prompt);
// Main loop to run a command or agent and get the next user command/input.
while (!string.IsNullOrWhiteSpace(userInput) && !userInput.Equals("exit", StringComparison.OrdinalIgnoreCase))
{
// Check command handlers first — first one to handle wins.
bool handled = false;
foreach (var handler in commandHandlers)
{
if (await handler.TryHandleAsync(userInput, session).ConfigureAwait(false))
{
handled = true;
break;
}
}
if (!handled)
{
await RunAgentTurnAsync(agent, session, modeProvider, options, writer, userInput);
}
writer.CurrentMode = modeProvider?.GetMode(session);
prompt = BuildUserPrompt(modeProvider, session);
userInput = await writer.ReadLineAsync(prompt);
}
System.Console.ResetColor();
System.Console.WriteLine("Goodbye!");
}
/// <summary>
/// Runs one or more agent invocations for a single user turn, using the current
/// observers. Re-invokes automatically for tool approvals and mode-driven follow-ups
/// (e.g., planning clarification loops).
/// </summary>
private static async Task RunAgentTurnAsync(
AIAgent agent,
AgentSession session,
AgentModeProvider? modeProvider,
HarnessConsoleOptions options,
ConsoleWriter writer,
string userInput)
{
IList<ChatMessage>? nextMessages = [new ChatMessage(ChatRole.User, userInput)];
while (nextMessages is not null)
{
// Build observers for this invocation (may change between iterations due to mode changes).
var observers = CreateObservers(options, modeProvider, session);
// Build run options — observers may inject ResponseFormat, etc.
var runOptions = new AgentRunOptions();
foreach (var observer in observers)
{
observer.ConfigureRunOptions(runOptions);
}
// Stream the response, fanning out to all observers.
writer.CurrentMode = modeProvider?.GetMode(session);
writer.WriteResponseHeader();
try
{
await foreach (var update in agent.RunStreamingAsync(nextMessages, session, runOptions))
{
// Update mode color if the mode changed during streaming.
if (modeProvider is not null)
{
string currentMode = modeProvider.GetMode(session);
if (currentMode != writer.CurrentMode)
{
writer.CurrentMode = currentMode;
}
}
foreach (var content in update.Contents)
{
foreach (var observer in observers)
{
await observer.OnContentAsync(writer, content);
}
}
if (!string.IsNullOrEmpty(update.Text))
{
foreach (var observer in observers)
{
await observer.OnTextAsync(writer, update.Text);
}
}
}
}
catch (Exception ex)
{
await writer.WriteInfoLineAsync($"❌ Stream error: {ex.GetType().Name}:\n{ex}", ConsoleColor.Red);
}
// Collect messages from all observers.
var combinedMessages = new List<ChatMessage>();
bool hasObserverMessages = false;
foreach (var observer in observers)
{
var messages = await observer.OnStreamCompleteAsync(writer, agent, session, options);
if (messages is { Count: > 0 })
{
combinedMessages.AddRange(messages);
hasObserverMessages = true;
}
}
await writer.WriteStreamFooterAsync(hasFollowUpMessages: hasObserverMessages);
nextMessages = combinedMessages.Count > 0 ? combinedMessages : null;
}
}
private static List<ConsoleObserver> CreateObservers(HarnessConsoleOptions options, AgentModeProvider? modeProvider, AgentSession session)
{
var observers = new List<ConsoleObserver>
{
new ToolCallDisplayObserver(),
new ToolApprovalObserver(),
new ErrorDisplayObserver(),
new ReasoningDisplayObserver(),
new UsageDisplayObserver(options.MaxContextWindowTokens, options.MaxOutputTokens),
};
// Add the appropriate output observer based on the current mode.
if (options.EnablePlanningUx
&& modeProvider is not null
&& string.Equals(modeProvider.GetMode(session), options.PlanningModeName, StringComparison.OrdinalIgnoreCase))
{
observers.Add(new PlanningOutputObserver(modeProvider));
}
else
{
observers.Add(new TextOutputObserver());
}
return observers;
}
private static string BuildUserPrompt(AgentModeProvider? modeProvider, AgentSession session)
{
if (modeProvider is not null)
{
string mode = modeProvider.GetMode(session);
return $"[{mode}] You: ";
}
return "You: ";
}
}
@@ -1,52 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
namespace Harness.Shared.Console;
/// <summary>
/// Configuration options for <see cref="HarnessConsole"/>.
/// </summary>
public class HarnessConsoleOptions
{
/// <summary>
/// Gets or sets the optional maximum context window size in tokens.
/// When set, token usage is displayed as a percentage of the budget.
/// </summary>
public int? MaxContextWindowTokens { get; set; }
/// <summary>
/// Gets or sets the optional maximum output tokens.
/// Used with <see cref="MaxContextWindowTokens"/> to show input/output budget breakdown.
/// </summary>
public int? MaxOutputTokens { get; set; }
/// <summary>
/// Gets or sets a value indicating whether the planning UX is enabled.
/// When <see langword="true"/> and the agent is in the mode specified by <see cref="PlanningModeName"/>,
/// the console uses structured output to present clarification questions and approval requests
/// instead of streaming free-form text.
/// </summary>
/// <value>Defaults to <see langword="false"/>.</value>
public bool EnablePlanningUx { get; set; }
/// <summary>
/// Gets or sets the name of the agent mode that activates the planning UX.
/// Must be set when <see cref="EnablePlanningUx"/> is <see langword="true"/>.
/// </summary>
public string? PlanningModeName { get; set; }
/// <summary>
/// Gets or sets the name of the agent mode to switch to when the user approves a plan.
/// Must be set when <see cref="EnablePlanningUx"/> is <see langword="true"/>.
/// </summary>
public string? ExecutionModeName { get; set; }
/// <summary>
/// Gets or sets a mapping of agent mode names to console colors.
/// When a mode is not found in this dictionary, the default color (<see cref="ConsoleColor.Gray"/>) is used.
/// </summary>
public Dictionary<string, ConsoleColor> ModeColors { get; set; } = new(StringComparer.OrdinalIgnoreCase)
{
["plan"] = ConsoleColor.Cyan,
["execute"] = ConsoleColor.Green,
};
}
@@ -1,18 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Spectre.Console" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
</ItemGroup>
</Project>
@@ -1,53 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Abstract base class for console observers that participate in the agent response
/// streaming lifecycle. Observers can configure run options, observe streamed content,
/// and return messages to re-invoke the agent after the stream completes.
/// All methods have default no-op implementations so subclasses only override what they need.
/// </summary>
public abstract class ConsoleObserver
{
/// <summary>
/// Configures <see cref="AgentRunOptions"/> before the agent is invoked.
/// Override to set options such as <see cref="AgentRunOptions.ResponseFormat"/>.
/// </summary>
/// <param name="options">The run options to configure.</param>
public virtual void ConfigureRunOptions(AgentRunOptions options)
{
}
/// <summary>
/// Called for each <see cref="AIContent"/> item in the response stream.
/// </summary>
/// <param name="writer">The console writer for rendering output.</param>
/// <param name="content">The content item from the stream.</param>
public virtual Task OnContentAsync(ConsoleWriter writer, AIContent content) => Task.CompletedTask;
/// <summary>
/// Called for each text update in the response stream.
/// </summary>
/// <param name="writer">The console writer for rendering output.</param>
/// <param name="text">The text from the update.</param>
public virtual Task OnTextAsync(ConsoleWriter writer, string text) => Task.CompletedTask;
/// <summary>
/// Called after the response stream completes. Returns messages to include in the
/// next agent invocation, or <see langword="null"/> if no re-invocation is needed.
/// </summary>
/// <param name="writer">The console writer for rendering output.</param>
/// <param name="agent">The agent being interacted with.</param>
/// <param name="session">The current agent session.</param>
/// <param name="options">The console options.</param>
/// <returns>Messages to send to the agent, or <see langword="null"/> if no action is needed.</returns>
public virtual Task<IList<ChatMessage>?> OnStreamCompleteAsync(
ConsoleWriter writer,
AIAgent agent,
AgentSession session,
HarnessConsoleOptions options) => Task.FromResult<IList<ChatMessage>?>(null);
}
@@ -1,31 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Extensions.AI;
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Displays error content (❌) from the response stream.
/// </summary>
internal sealed class ErrorDisplayObserver : ConsoleObserver
{
/// <inheritdoc/>
public override async Task OnContentAsync(ConsoleWriter writer, AIContent content)
{
if (content is ErrorContent errorContent)
{
string errorText = $"❌ Error: {errorContent.Message}";
if (!string.IsNullOrWhiteSpace(errorContent.ErrorCode))
{
errorText += $" (code: {errorContent.ErrorCode})";
}
if (!string.IsNullOrWhiteSpace(errorContent.Details))
{
errorText += $" details: {errorContent.Details}";
}
await writer.WriteInfoLineAsync(errorText, ConsoleColor.Red);
}
}
}
@@ -1,177 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text;
using System.Text.Json;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Planning observer that configures structured output, collects streamed text,
/// and deserializes it as a <see cref="PlanningResponse"/>. Renders clarification
/// questions and approval prompts, and manages mode switching when the user approves a plan.
/// </summary>
internal sealed class PlanningOutputObserver : ConsoleObserver
{
private readonly StringBuilder _textCollector = new();
private readonly AgentModeProvider _modeProvider;
/// <summary>
/// Initializes a new instance of the <see cref="PlanningOutputObserver"/> class.
/// </summary>
/// <param name="modeProvider">The mode provider for switching modes on approval.</param>
public PlanningOutputObserver(AgentModeProvider modeProvider)
{
this._modeProvider = modeProvider;
}
/// <inheritdoc/>
public override void ConfigureRunOptions(AgentRunOptions options)
{
options.ResponseFormat = ChatResponseFormat.ForJsonSchema<PlanningResponse>();
}
/// <inheritdoc/>
public override Task OnTextAsync(ConsoleWriter writer, string text)
{
// Collect text silently instead of displaying it.
this._textCollector.Append(text);
return Task.CompletedTask;
}
/// <inheritdoc/>
public override async Task<IList<ChatMessage>?> OnStreamCompleteAsync(
ConsoleWriter writer,
AIAgent agent,
AgentSession session,
HarnessConsoleOptions options)
{
// Read collected text from our stream observation.
string collectedText = this._textCollector.ToString();
this._textCollector.Clear();
if (string.IsNullOrWhiteSpace(collectedText))
{
return null;
}
// Deserialize the structured response.
PlanningResponse? planningResponse;
try
{
planningResponse = JsonSerializer.Deserialize<PlanningResponse>(collectedText);
}
catch (JsonException ex)
{
await writer.WriteInfoLineAsync($"❌ Failed to parse planning response: {ex.Message}", ConsoleColor.Red);
await writer.WriteInfoLineAsync($"(raw response) {collectedText}", ConsoleColor.DarkYellow);
return null;
}
if (planningResponse is null)
{
await writer.WriteInfoLineAsync("(no structured response from agent)", ConsoleColor.DarkYellow);
return null;
}
// Render based on response type.
if (planningResponse.Type == PlanningResponseType.Clarification)
{
return AsUserMessages(await this.RenderClarificationsAndCollectResponsesAsync(writer, planningResponse));
}
if (planningResponse.Type == PlanningResponseType.Approval)
{
var question = planningResponse.Questions.FirstOrDefault();
if (question is null)
{
await writer.WriteInfoLineAsync("(approval response had no content)", ConsoleColor.DarkYellow);
return null;
}
string response = await this.RenderApprovalAndCollectResponseAsync(writer, question, options);
if (response == "Approved")
{
this._modeProvider.SetMode(session, options.ExecutionModeName!);
await writer.WriteInfoLineAsync($"✅ Switched to {options.ExecutionModeName} mode.",
ConsoleWriter.GetModeColor(options.ExecutionModeName, options.ModeColors));
}
return AsUserMessages(response);
}
await writer.WriteInfoLineAsync($"(unexpected response type: {planningResponse.Type})", ConsoleColor.DarkYellow);
return null;
}
private static IList<ChatMessage>? AsUserMessages(string? text) =>
text is not null ? [new ChatMessage(ChatRole.User, text)] : null;
private async Task<string?> RenderClarificationsAndCollectResponsesAsync(ConsoleWriter writer, PlanningResponse response)
{
var answers = new List<string>();
foreach (var question in response.Questions)
{
await writer.WriteInfoLineAsync(string.Empty);
await writer.WriteInfoLineAsync(question.Message);
string? answer;
if (question.Choices is { Count: > 0 })
{
answer = await writer.ReadSelectionAsync(
"Choose an option:",
question.Choices);
}
else
{
answer = (await writer.ReadLineAsync("Response: "))?.Trim();
}
if (!string.IsNullOrWhiteSpace(answer))
{
answers.Add($"Q: {question.Message}\nA: {answer}");
}
}
return answers.Count > 0 ? string.Join("\n\n", answers) : null;
}
private async Task<string> RenderApprovalAndCollectResponseAsync(ConsoleWriter writer, PlanningQuestion question, HarnessConsoleOptions options)
{
await writer.WriteInfoLineAsync(question.Message);
var choices = new List<string>
{
"Approve and switch to execute mode",
"Suggest changes",
};
string selection = await writer.ReadSelectionAsync("What would you like to do?", choices);
if (selection == choices[0])
{
return "Approved";
}
if (selection == choices[1])
{
string? feedback = await writer.ReadLineAsync(
"Your feedback: ",
ConsoleWriter.GetModeColor(options.PlanningModeName, options.ModeColors));
if (string.IsNullOrWhiteSpace(feedback))
{
// Treat empty feedback as no changes — re-prompt the agent with the plan.
return "No changes suggested. Please re-present the plan for approval.";
}
return feedback;
}
// Custom freeform input — treat as suggested changes.
return selection;
}
}
@@ -1,51 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.ComponentModel;
using System.Text.Json.Serialization;
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Represents a structured response from the agent while in planning mode.
/// Used with structured output to enable consistent rendering of clarification
/// questions and approval requests in the console.
/// </summary>
public class PlanningResponse
{
/// <summary>
/// Gets or sets the type of planning response.
/// </summary>
[JsonPropertyName("type")]
public required PlanningResponseType Type { get; set; }
/// <summary>
/// Gets or sets the list of questions or items to present to the user.
/// For clarification, this contains one or more questions (each with choices).
/// For approval, this contains exactly one item with the plan summary.
/// </summary>
[JsonPropertyName("questions")]
[Description("For clarifications, this has one or more questions to ask the user (each with choices). For approvals, this has exactly one item containing the plan summary for the user to approve.")]
public required List<PlanningQuestion> Questions { get; set; }
}
/// <summary>
/// Represents a single question or item within a <see cref="PlanningResponse"/>.
/// </summary>
public class PlanningQuestion
{
/// <summary>
/// Gets or sets the message to display to the user.
/// For clarification, this is the question. For approval, this is the plan summary.
/// </summary>
[JsonPropertyName("message")]
[Description("For clarifications, this has the question that needs to be clarified with the user. For approvals, this would contain a summary of the execution plan that the user needs to approve.")]
public required string Message { get; set; }
/// <summary>
/// Gets or sets the list of choices for the user to pick from.
/// Only used for clarification questions. Null when no predefined choices are offered.
/// </summary>
[JsonPropertyName("choices")]
[Description("For clarifications, this has a list of options that the user can choose from. null for approvals.")]
public List<string>? Choices { get; set; }
}
@@ -1,25 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.ComponentModel;
using System.Text.Json.Serialization;
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Specifies the type of planning response from the agent.
/// </summary>
[JsonConverter(typeof(JsonStringEnumConverter<PlanningResponseType>))]
public enum PlanningResponseType
{
/// <summary>
/// The agent needs clarification and presents options for the user to choose from.
/// </summary>
[Description("Use this type when you need clarification around the user request and you want to present the user with options to choose from.")]
Clarification,
/// <summary>
/// The agent is seeking approval to proceed with execution.
/// </summary>
[Description("Use this type when you are ready to start execution, but need approval to start executing.")]
Approval,
}
@@ -1,20 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Extensions.AI;
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Displays reasoning content in dark magenta from the response stream.
/// </summary>
internal sealed class ReasoningDisplayObserver : ConsoleObserver
{
/// <inheritdoc/>
public override async Task OnContentAsync(ConsoleWriter writer, AIContent content)
{
if (content is TextReasoningContent reasoning && !string.IsNullOrEmpty(reasoning.Text))
{
await writer.WriteTextAsync(reasoning.Text, ConsoleColor.DarkMagenta);
}
}
}
@@ -1,16 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Streams agent text output directly to the console.
/// Used in normal (non-planning) mode.
/// </summary>
internal sealed class TextOutputObserver : ConsoleObserver
{
/// <inheritdoc/>
public override async Task OnTextAsync(ConsoleWriter writer, string text)
{
await writer.WriteTextAsync(text);
}
}
@@ -1,92 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Collects <see cref="ToolApprovalRequestContent"/> items during the response stream,
/// displays approval-needed notifications inline, and prompts the user for approval
/// decisions after the stream completes.
/// </summary>
internal sealed class ToolApprovalObserver : ConsoleObserver
{
private readonly List<ToolApprovalRequestContent> _approvalRequests = [];
/// <inheritdoc/>
public override async Task OnContentAsync(ConsoleWriter writer, AIContent content)
{
if (content is ToolApprovalRequestContent approvalRequest)
{
this._approvalRequests.Add(approvalRequest);
string toolName = approvalRequest.ToolCall is FunctionCallContent fc
? ToolCallFormatter.Format(fc)
: approvalRequest.ToolCall?.ToString() ?? "unknown";
await writer.WriteInfoLineAsync($"⚠️ Approval needed: {toolName}", ConsoleColor.Yellow);
}
}
/// <inheritdoc/>
public override async Task<IList<ChatMessage>?> OnStreamCompleteAsync(
ConsoleWriter writer,
AIAgent agent,
AgentSession session,
HarnessConsoleOptions options)
{
if (this._approvalRequests.Count == 0)
{
return null;
}
var messages = await PromptForApprovalsAsync(writer, this._approvalRequests);
this._approvalRequests.Clear();
return messages;
}
private static async Task<List<ChatMessage>?> PromptForApprovalsAsync(ConsoleWriter writer, List<ToolApprovalRequestContent> approvalRequests)
{
if (approvalRequests.Count == 0)
{
return null;
}
var responses = new List<AIContent>();
foreach (var request in approvalRequests)
{
string toolName = request.ToolCall is FunctionCallContent fc
? ToolCallFormatter.Format(fc)
: request.ToolCall?.ToString() ?? "unknown";
var choices = new List<string>
{
"Approve this call",
"Always approve this tool (any arguments)",
"Always approve this tool with these arguments",
"Deny",
};
string selection = await writer.ReadSelectionAsync($"🔐 Tool approval: {toolName}", choices);
AIContent response = selection switch
{
"Always approve this tool (any arguments)" => request.CreateAlwaysApproveToolResponse("User chose to always approve this tool"),
"Always approve this tool with these arguments" => request.CreateAlwaysApproveToolWithArgumentsResponse("User chose to always approve this tool with these arguments"),
"Deny" => request.CreateResponse(approved: false, reason: "User denied"),
_ => request.CreateResponse(approved: true, reason: "User approved"),
};
string action = selection switch
{
"Always approve this tool (any arguments)" => "✅ Always approved (any args)",
"Always approve this tool with these arguments" => "✅ Always approved (these args)",
"Deny" => "❌ Denied",
_ => "✅ Approved",
};
await writer.WriteInfoLineAsync($" {action}", ConsoleColor.DarkGray);
responses.Add(response);
}
return [new ChatMessage(ChatRole.User, responses)];
}
}
@@ -1,25 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Extensions.AI;
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Displays tool call notifications (🔧) for <see cref="FunctionCallContent"/>
/// and <see cref="ToolCallContent"/> items in the response stream.
/// </summary>
internal sealed class ToolCallDisplayObserver : ConsoleObserver
{
/// <inheritdoc/>
public override async Task OnContentAsync(ConsoleWriter writer, AIContent content)
{
if (content is FunctionCallContent functionCall)
{
await writer.WriteInfoLineAsync($"🔧 Calling tool: {ToolCallFormatter.Format(functionCall)}...", ConsoleColor.DarkYellow);
}
else if (content is ToolCallContent toolCall)
{
await writer.WriteInfoLineAsync($"🔧 Calling tool: {toolCall}...", ConsoleColor.DarkYellow);
}
}
}
@@ -1,288 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text;
using System.Text.Json;
using Microsoft.Extensions.AI;
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Formats <see cref="FunctionCallContent"/> instances into human-readable strings
/// for console display.
/// </summary>
public static class ToolCallFormatter
{
/// <summary>
/// Returns a formatted string for the given tool call, with human-readable
/// details for known tools (todos, mode, sub-agents, web tools).
/// </summary>
/// <param name="call">The function call content to format.</param>
/// <returns>A formatted string describing the tool call.</returns>
public static string Format(FunctionCallContent call)
{
string? detail = call.Name switch
{
// Todo tools
"TodoList_Add" => FormatAddTodos(call),
"TodoList_Complete" => FormatIdList(call, "ids", "Complete"),
"TodoList_Remove" => FormatIdList(call, "ids", "Remove"),
"TodoList_GetRemaining" => null,
"TodoList_GetAll" => null,
// Mode tools
"AgentMode_Set" => FormatStringArg(call, "mode"),
"AgentMode_Get" => null,
// Sub-agent tools
"SubAgents_StartTask" => FormatStartSubTask(call),
"SubAgents_WaitForFirstCompletion" => FormatIdList(call, "taskIds", "Wait for"),
"SubAgents_GetTaskResults" => FormatSingleId(call, "taskId"),
"SubAgents_GetAllTasks" => null,
"SubAgents_ContinueTask" => FormatContinueTask(call),
"SubAgents_ClearCompletedTask" => FormatSingleId(call, "taskId"),
// File memory tools
"FileMemory_SaveFile" => FormatSaveFile(call),
"FileMemory_ReadFile" => FormatStringArg(call, "fileName"),
"FileMemory_DeleteFile" => FormatStringArg(call, "fileName"),
"FileMemory_ListFiles" => null,
"FileMemory_SearchFiles" => FormatSearchFiles(call),
// External tools
"web_search" => FormatStringArg(call, "query"),
"DownloadUri" => FormatStringArg(call, "uri"),
_ => FormatFallback(call),
};
return detail is not null ? $"{call.Name} {detail}" : call.Name;
}
private static string? FormatAddTodos(FunctionCallContent call)
{
if (call.Arguments?.TryGetValue("todos", out object? todosObj) != true || todosObj is null)
{
return null;
}
var titles = new List<string>();
if (todosObj is JsonElement jsonArray && jsonArray.ValueKind == JsonValueKind.Array)
{
foreach (JsonElement item in jsonArray.EnumerateArray())
{
string? title = item.TryGetProperty("title", out JsonElement titleElement)
? titleElement.GetString()
: null;
if (!string.IsNullOrEmpty(title))
{
titles.Add(title);
}
}
}
if (titles.Count == 0)
{
return null;
}
var sb = new StringBuilder();
sb.Append($"({titles.Count} item{(titles.Count == 1 ? "" : "s")})");
foreach (string title in titles)
{
sb.Append($"\n • {title}");
}
return sb.ToString();
}
private static string? FormatIdList(FunctionCallContent call, string paramName, string verb)
{
List<int>? ids = GetIntList(call, paramName);
if (ids is null || ids.Count == 0)
{
return null;
}
return $"({verb} #{string.Join(", #", ids)})";
}
private static string? FormatSingleId(FunctionCallContent call, string paramName)
{
int? id = GetInt(call, paramName);
return id.HasValue ? $"(task #{id.Value})" : null;
}
private static string? FormatStartSubTask(FunctionCallContent call)
{
string? agentName = GetString(call, "agentName");
string? description = GetString(call, "description");
if (agentName is null && description is null)
{
return null;
}
var sb = new StringBuilder("(");
if (agentName is not null)
{
sb.Append($"agent: {agentName}");
}
if (description is not null)
{
if (agentName is not null)
{
sb.Append(", ");
}
sb.Append($"\"{Truncate(description, 60)}\"");
}
sb.Append(')');
return sb.ToString();
}
private static string? FormatContinueTask(FunctionCallContent call)
{
int? taskId = GetInt(call, "taskId");
string? text = GetString(call, "text");
if (!taskId.HasValue)
{
return null;
}
return text is not null
? $"(task #{taskId.Value}, \"{Truncate(text, 50)}\")"
: $"(task #{taskId.Value})";
}
private static string? FormatSaveFile(FunctionCallContent call)
{
string? fileName = GetString(call, "fileName");
string? description = GetString(call, "description");
if (fileName is null)
{
return null;
}
return string.IsNullOrEmpty(description)
? $"({fileName})"
: $"({fileName}, with description)";
}
private static string? FormatSearchFiles(FunctionCallContent call)
{
string? pattern = GetString(call, "regexPattern");
string? filePattern = GetString(call, "filePattern");
if (pattern is null)
{
return null;
}
return string.IsNullOrEmpty(filePattern)
? $"(/{pattern}/)"
: $"(/{pattern}/ in {filePattern})";
}
private static string? FormatStringArg(FunctionCallContent call, string paramName)
{
string? value = GetString(call, paramName);
return value is not null ? $"({value})" : null;
}
private static string? FormatFallback(FunctionCallContent call)
{
if (call.Arguments is null || call.Arguments.Count == 0)
{
return null;
}
var parts = new List<string>();
foreach (var kvp in call.Arguments)
{
string? stringValue = kvp.Value switch
{
JsonElement je => je.ValueKind switch
{
JsonValueKind.String => je.GetString(),
JsonValueKind.Number => je.GetRawText(),
JsonValueKind.True => "true",
JsonValueKind.False => "false",
_ => null,
},
not null => kvp.Value.ToString(),
_ => null,
};
if (stringValue is not null)
{
parts.Add($"{kvp.Key}: {Truncate(stringValue, 40)}");
}
}
return parts.Count > 0 ? $"({string.Join(", ", parts)})" : null;
}
private static string? GetString(FunctionCallContent call, string paramName)
{
if (call.Arguments?.TryGetValue(paramName, out object? value) != true || value is null)
{
return null;
}
return value switch
{
JsonElement je when je.ValueKind == JsonValueKind.String => je.GetString(),
string s => s,
_ => value.ToString(),
};
}
private static int? GetInt(FunctionCallContent call, string paramName)
{
if (call.Arguments?.TryGetValue(paramName, out object? value) != true || value is null)
{
return null;
}
return value switch
{
JsonElement je when je.ValueKind == JsonValueKind.Number => je.GetInt32(),
int i => i,
_ => int.TryParse(value.ToString(), out int parsed) ? parsed : null,
};
}
private static List<int>? GetIntList(FunctionCallContent call, string paramName)
{
if (call.Arguments?.TryGetValue(paramName, out object? value) != true || value is null)
{
return null;
}
var result = new List<int>();
if (value is JsonElement je && je.ValueKind == JsonValueKind.Array)
{
foreach (JsonElement item in je.EnumerateArray())
{
if (item.ValueKind == JsonValueKind.Number)
{
result.Add(item.GetInt32());
}
}
}
return result.Count > 0 ? result : null;
}
private static string Truncate(string text, int maxLength)
{
return text.Length <= maxLength ? text : string.Concat(text.AsSpan(0, maxLength), "…");
}
}
@@ -1,68 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Extensions.AI;
namespace Harness.Shared.Console.Observers;
/// <summary>
/// Displays token usage statistics (📊) from the response stream.
/// </summary>
internal sealed class UsageDisplayObserver : ConsoleObserver
{
private readonly int? _maxContextWindowTokens;
private readonly int? _maxOutputTokens;
/// <summary>
/// Initializes a new instance of the <see cref="UsageDisplayObserver"/> class.
/// </summary>
/// <param name="maxContextWindowTokens">Optional max context window size in tokens.</param>
/// <param name="maxOutputTokens">Optional max output tokens.</param>
public UsageDisplayObserver(int? maxContextWindowTokens, int? maxOutputTokens)
{
this._maxContextWindowTokens = maxContextWindowTokens;
this._maxOutputTokens = maxOutputTokens;
}
/// <inheritdoc/>
public override async Task OnContentAsync(ConsoleWriter writer, AIContent content)
{
if (content is UsageContent usage)
{
if (usage.Details is not null)
{
await writer.WriteInfoLineAsync(this.FormatUsageBreakdown(usage.Details), ConsoleColor.DarkGray);
}
else
{
await writer.WriteInfoLineAsync("📊 Tokens —", ConsoleColor.DarkGray);
}
}
}
private string FormatUsageBreakdown(UsageDetails details)
{
int? inputBudget = (this._maxContextWindowTokens is not null && this._maxOutputTokens is not null)
? this._maxContextWindowTokens.Value - this._maxOutputTokens.Value
: null;
return $"📊 Tokens — input: {FormatTokenCount(details.InputTokenCount, inputBudget)}"
+ $" | output: {FormatTokenCount(details.OutputTokenCount, this._maxOutputTokens)}"
+ $" | total: {FormatTokenCount(details.TotalTokenCount, this._maxContextWindowTokens)}";
}
private static string FormatTokenCount(long? count, int? budget)
{
if (count is null)
{
return "—";
}
if (budget is not null && budget.Value > 0)
{
double pct = (double)count.Value / budget.Value * 100;
return $"{count.Value:N0}/{budget.Value:N0} ({pct:F1}%)";
}
return $"{count.Value:N0}";
}
}
@@ -1,77 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
namespace Harness.Shared.Console;
/// <summary>
/// A restartable spinner that can be started and stopped multiple times.
/// </summary>
internal sealed class Spinner : IDisposable
{
private static readonly string[] s_frames = ["⠋", "⠙", "⠹", "⠸", "⠼", "⠴", "⠦", "⠧", "⠇", "⠏"];
private CancellationTokenSource? _cts;
private Task? _task;
public void Start()
{
if (this._task is not null)
{
return;
}
this._cts = new CancellationTokenSource();
this._task = RunAsync(this._cts.Token);
}
public async Task StopAsync()
{
if (this._cts is null || this._task is null)
{
return;
}
this._cts.Cancel();
await this._task;
this._cts.Dispose();
this._cts = null;
this._task = null;
}
public void Dispose()
{
if (this._cts is not null && this._task is not null)
{
this._cts.Cancel();
// Block briefly to let the spinner task clean up.
// This prevents the background task from writing to the console after disposal.
#pragma warning disable VSTHRD002 // Synchronous wait in Dispose is acceptable here — the spinner task completes quickly on cancellation.
this._task.Wait();
#pragma warning restore VSTHRD002
}
this._cts?.Dispose();
this._cts = null;
this._task = null;
}
private static async Task RunAsync(CancellationToken cancellationToken)
{
int i = 0;
try
{
while (!cancellationToken.IsCancellationRequested)
{
System.Console.Write(s_frames[i % s_frames.Length]);
await Task.Delay(80, cancellationToken);
System.Console.Write("\b \b");
i++;
}
}
catch (OperationCanceledException)
{
// Clear the last spinner frame left on screen.
System.Console.Write("\b \b");
}
}
}
@@ -1,20 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
<ProjectReference Include="..\Harness_Shared_Console\Harness_Shared_Console.csproj" />
</ItemGroup>
</Project>
@@ -1,191 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to use a ChatClientAgent with the Harness AIContextProviders
// (TodoProvider and AgentModeProvider) for interactive research tasks with web search
// capabilities powered by Azure AI Foundry.
// The agent plans research tasks, creates a todo list, gets user approval,
// and then executes each step — all within an interactive conversation loop.
//
// Special commands:
// /todos — Display the current todo list without invoking the agent.
// exit — End the session.
#pragma warning disable OPENAI001 // Suppress experimental API warnings for Responses API usage.
#pragma warning disable MAAI001 // Suppress experimental API warnings for Agents AI experiments.
using System.ClientModel.Primitives;
using Azure.Identity;
using Harness.Shared.Console;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Compaction;
using Microsoft.Extensions.AI;
using OpenAI;
using OpenAI.Responses;
using SampleApp;
var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4";
const int MaxContextWindowTokens = 1_050_000;
const int MaxOutputTokens = 128_000;
// Create a ChatClientAgent with the Harness providers (TodoProvider and AgentModeProvider)
// and research-focused instructions including the mandatory planning workflow.
var instructions =
"""
You are a research assistant. When given a research topic, research it thoroughly using web search and web browsing.
Use your knowledge to form good search queries and hypotheses, but always verify claims with the tools available to you rather than relying on memory alone.
## Mandatory planning workflow
For every new substantive user request, including short factual questions, your behavior is determined by the mode you are in.
If you are in plan mode, start with the *Plan Mode* steps, and if you are in execute mode, skip directly to the *Execute Mode* steps below.
*Plan Mode*
1. Analyze the request with the purpose of building a research plan.
2. Create a list of todo items.
3. If needed, use the provided tools to do some exploratory checks to help build a plan and determine what clarifying questions you may need from the user.
4. Ask for clarifications from the user where needed.
1. Ask each clarification one by one.
2. When asking for clarification and you have specific options in mind, present them to the user, so they can choose the option instead of having to retype the entire response.
3. Do not proceed until you have received all the needed clarifications.
4. Do short exploratory research if it helps with being able to ask sensible clarifications from the user.
5. Write the plan to a memory file, so that it is retained even if compaction happens. Make sure to update the plan file if the user requests changes.
6. Present the plan to the user and ask for approval to switch to execute mode and process the plan.
7. When approval is granted, always switch to execute mode (using the `AgentMode_Set` tool), and follow the steps for *Execute mode*.
*Execute Mode*
1. If you don't have a plan or tasks yet, analyse the user request and create tasks and a plan. (**Skip this step if you came from plan mode**)
2. Work autonomously use your best judgement to make decisions and keep progressing without asking the user questions. The goal is to have a complete, useful result ready when the user returns.
3. If you encounter ambiguity or an unexpected situation during execution, choose the most reasonable option, note your choice, and keep going.
4. Mark tasks as completed as you finish them.
5. Continue working, thinking and calling tools until you have the research result for the user.
## General Instructions
- You must check the current mode after any user input, since the user may have changed the mode themselves,
e.g. the user may have switched to 'plan' mode after a previous research task finished in 'execute' mode, meaning they want to review a plan first before execution.
- Explain your reasoning and thought process as you work through tasks.
- Explain what you learned and what you are going to do next between tool calls, so the user can follow along with your thought process.
- Avoid making more than 4 tool calls in a row without explaining what you are doing.
- Do not answer the underlying question before the plan has been presented and approved.
- This rule applies even when the answer seems obvious or the task seems small.
- For short requests, use a brief micro-plan rather than skipping planning. The only exceptions are:
- greetings,
- pure acknowledgments,
- clarification questions needed to form the plan,
- follow-up questions about results you have already presented,
- meta-discussion about the workflow itself.
**Todo management**
Mark each todo complete as you finish it so the list stays current.
If a todo turns out to be unnecessary or is blocked, remove it and briefly explain why.
Once the user finishes with a topic and moves onto a new one, clean up old completed todos by deleting them.
**Research quality**
Consult multiple sources when possible and cross-reference key claims.
When sources disagree, note the discrepancy and explain which source you consider more reliable and why.
If a web page fails to load or a search returns irrelevant results, try alternative search queries or sources before moving on.
Track your sources you will need them when presenting results.
**Presenting results**
When presenting your final findings:
- Use clear sections with headings for each major topic or sub-question.
- Cite your sources inline (e.g., "According to [source name](URL), ...").
- End with a brief summary of key takeaways.
- Save the final research report to file memory so it survives compaction and can be referenced later.
**File memory**
Use the FileMemory_* tools to:
- Store downloaded search results or web pages.
- Store plans.
- Read the current plan to make sure tasks were done according to plan.
- Store findings.
- Check for relevant previously downloaded data / findings before starting new research.
""";
// Create a compaction strategy based on the model's context window.
// gpt-5.4: 1,050,000 token context window, 128,000 max output tokens.
// Defaults: tool result eviction at 50% of input budget, truncation at 80%.
var compactionStrategy = new ContextWindowCompactionStrategy(
maxContextWindowTokens: MaxContextWindowTokens,
maxOutputTokens: MaxOutputTokens);
AIAgent agent =
// Create an OpenAIClient that communicates with the Foundry responses service.
new OpenAIClient(
// 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.
new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"),
new OpenAIClientOptions()
{
Endpoint = new Uri(endpoint),
RetryPolicy = new ClientRetryPolicy(3) // Enable retries to improve resiliency.
})
.GetResponsesClient()
.AsIChatClientWithStoredOutputDisabled(deploymentName) // We want to manage chat history locally (not stored in the responses service), so that we can manage compaction ourselves.
// Build a ChatClient Pipeline
.AsBuilder()
.UseFunctionInvocation() // We are building our own stack from scratch so we need to include Function Invocation ourselves.
.UsePerServiceCallChatHistoryPersistence() // Save chat history updates to the session after each service call, rather than only at the end of the run.
.UseAIContextProviders(new CompactionProvider(compactionStrategy)) // Add Compaction before each service call to responses so that long function invocation loops don't overflow the context.
// Build our agent on top of the ChatClient Pipeline
.BuildAIAgent(
new ChatClientAgentOptions
{
Name = "ResearchAgent",
Description = "A research assistant that plans and executes research tasks.",
UseProvidedChatClientAsIs = true, // Since we built our own stack from scratch we need to tell the agent not to also add defaults like Function Invocation.
RequirePerServiceCallChatHistoryPersistence = true, // Since we are added the per service call persistence ChatClient, we need to tell the agent to not also store chat history at the end of the run.
ChatHistoryProvider = new InMemoryChatHistoryProvider( // Store chat history in memory in the session object. Will persist if the session is persisted.
new InMemoryChatHistoryProviderOptions
{
ChatReducer = compactionStrategy.AsChatReducer(), // Run compaction on the InMemory chat history when it gets too large.
}),
AIContextProviders =
[
new TodoProvider(), // Add an AIContextProvider to allow the agent to create a TODO list, which is stored in the session.
new AgentModeProvider(), // Add an AIContextProvider that tracks the agent mode and allows switching mode. Current mode is stored in the session.
new FileMemoryProvider( // Add an AIContextProvider that can store memories in files under a session specific working folder.
new FileSystemAgentFileStore(Path.Combine(AppContext.BaseDirectory, "agent-files")),
(_) => new FileMemoryState() { WorkingFolder = DateTime.UtcNow.ToString("yyyyMMdd_HHmmss") + "_" + Guid.NewGuid().ToString() })
],
ChatOptions = new ChatOptions
{
Instructions = instructions,
Tools =
[
ResponseTool.CreateWebSearchTool().AsAITool(), // Add the foundry hosted web search tool that runs in the service.
new WebBrowsingTool( // Add a local web browsing tool that converts html to markdown.
new WebBrowsingToolOptions { AllowPublicNetworks = true }),
],
MaxOutputTokens = MaxOutputTokens, // Set a high token limit for long research tasks with many tool calls and long outputs.
Reasoning = new() { Effort = ReasoningEffort.Medium },
},
})
.AsBuilder()
.UseToolApproval() // Add the ability to auto approve tools once a user has said they don't want to be asked again. Approval rules are tied to the session.
.Build();
// Run the interactive console session using the shared HarnessConsole helper.
await HarnessConsole.RunAgentAsync(
agent,
title: "Research Assistant",
userPrompt: "Enter a research topic to get started.",
new HarnessConsoleOptions
{
MaxContextWindowTokens = MaxContextWindowTokens,
MaxOutputTokens = MaxOutputTokens,
EnablePlanningUx = true,
PlanningModeName = "plan",
ExecutionModeName = "execute"
});
@@ -1,52 +0,0 @@
# What this sample demonstrates
This sample demonstrates how to use a `ChatClientAgent` with the Harness `AIContextProviders` (`TodoProvider` and `AgentModeProvider`) for interactive research tasks with web search capabilities powered by Azure AI Foundry.
Key features showcased:
- **ChatClientAgent** — configured directly with Harness providers for planning and task management
- **Web Search** — the agent can search the web for current information via `ResponseTool.CreateWebSearchTool()`
- **TodoProvider** — the agent creates and manages a todo list to track research questions
- **AgentModeProvider** — the agent switches between "plan" mode (breaking down the topic) and "execute" mode (answering each research question)
- **Interactive conversation** — you can review the agent's plan, provide feedback, and approve before execution begins
- **Streaming output** — responses are streamed token-by-token for a natural experience
- **`/todos` command** — view the current todo list at any time without invoking the agent
- **Mode-based coloring** — console output is colored based on the agent's current mode (cyan for plan, green for execute)
## Prerequisites
Before running this sample, ensure you have:
1. An Azure AI Foundry project with a deployed model (e.g., `gpt-5.4`)
2. Azure CLI installed and authenticated (`az login`)
## Environment Variables
Set the following environment variables:
```bash
# Required: Your Azure AI Foundry OpenAI endpoint
export AZURE_FOUNDRY_OPENAI_ENDPOINT="https://your-project.services.ai.azure.com/openai/v1/"
# Optional: Model deployment name (defaults to gpt-5.4)
export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4"
```
## Running the Sample
```bash
cd dotnet
dotnet run --project samples/02-agents/Harness/Harness_Step01_Research
```
## What to Expect
The sample starts an interactive conversation loop. You can:
1. **Enter a research topic** — the agent will analyze it and create a plan with todos
2. **Review and adjust** — provide feedback on the plan, ask for changes, or approve it
3. **Type `/todos`** — to see the current todo list at any time
4. **Watch execution** — once approved, tell the agent to proceed and it will work through each todo
5. **Type `exit`** — to end the session
The prompt and agent output are colored by the current mode: **cyan** during planning, **green** during execution.
@@ -1,439 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.ComponentModel;
using System.Net;
using System.Net.Sockets;
using System.Text.Json;
using System.Text.RegularExpressions;
using Microsoft.Extensions.AI;
namespace SampleApp;
/// <summary>
/// An AI function that downloads HTML pages and converts them to markdown.
/// Access is controlled by <see cref="WebBrowsingToolOptions"/> — by default, no hosts are accessible.
/// </summary>
internal sealed partial class WebBrowsingTool : AIFunction
{
private static readonly HttpClient s_httpClient = new();
private readonly AIFunction _inner;
private readonly WebBrowsingToolOptions _options;
/// <summary>
/// Initializes a new instance of the <see cref="WebBrowsingTool"/> class.
/// </summary>
/// <param name="options">Options controlling which URLs are permitted. By default, no hosts are accessible.</param>
public WebBrowsingTool(WebBrowsingToolOptions options)
{
this._options = options ?? throw new ArgumentNullException(nameof(options));
this._inner = AIFunctionFactory.Create(this.DownloadUriAsync);
}
/// <inheritdoc/>
public override string Name => this._inner.Name;
/// <inheritdoc/>
public override string Description => this._inner.Description;
/// <inheritdoc/>
public override JsonElement JsonSchema => this._inner.JsonSchema;
/// <inheritdoc/>
protected override ValueTask<object?> InvokeCoreAsync(
AIFunctionArguments arguments,
CancellationToken cancellationToken) =>
this._inner.InvokeAsync(arguments, cancellationToken);
[Description("Fetch the html from the given url as markdown")]
private async Task<string> DownloadUriAsync(
[Description("The URL to download")] string uri,
CancellationToken cancellationToken = default)
{
if (!Uri.TryCreate(uri, UriKind.Absolute, out Uri? parsedUri))
{
return $"Error: '{uri}' is not a valid URL.";
}
if (parsedUri.Scheme is not "http" and not "https")
{
return $"Error: Only HTTP and HTTPS URLs are supported. Got: '{parsedUri.Scheme}'.";
}
// Check access policy.
string? accessError = await this.CheckAccessAsync(parsedUri, cancellationToken);
if (accessError is not null)
{
return accessError;
}
try
{
string html = await s_httpClient.GetStringAsync(parsedUri, cancellationToken);
return HtmlToMarkdownConverter.Convert(html);
}
catch (HttpRequestException ex)
{
return $"Error downloading {uri}: {ex.Message}";
}
}
/// <summary>
/// Checks whether the given URI is permitted by the configured access policy.
/// Returns null if allowed, or an error message string if blocked.
/// </summary>
private async Task<string?> CheckAccessAsync(Uri uri, CancellationToken cancellationToken)
{
string host = uri.Host;
// 1. Check AllowedHosts.
if (this._options.AllowedHosts is { Count: > 0 } allowedHosts)
{
foreach (string pattern in allowedHosts)
{
if (HostMatchesPattern(host, pattern))
{
return null; // Allowed by explicit host list.
}
}
}
// 2. Short-circuit when the policy is guaranteed to block.
if (!this._options.AllowPublicNetworks &&
!this._options.AllowPrivateNetworks &&
!this._options.AllowAllHosts)
{
return $"Error: Access to '{host}' is blocked by the current access policy. Configure WebBrowsingToolOptions to allow access.";
}
// 3. Resolve DNS to determine if the host is public or private.
IPAddress[] addresses;
try
{
addresses = await Dns.GetHostAddressesAsync(host, cancellationToken);
}
catch (SocketException)
{
return $"Error: Could not resolve host '{host}'.";
}
if (addresses.Length == 0)
{
return $"Error: Could not resolve host '{host}'.";
}
bool isPrivate = Array.Exists(addresses, IsPrivateAddress);
// 4. If public and AllowPublicNetworks is true → allow.
if (!isPrivate && this._options.AllowPublicNetworks)
{
return null;
}
// 5. If private and AllowPrivateNetworks is true → allow.
if (isPrivate && this._options.AllowPrivateNetworks)
{
return null;
}
// 6. If AllowAllHosts is true → allow.
if (this._options.AllowAllHosts)
{
return null;
}
// 7. Block.
string networkType = isPrivate ? "private/internal network" : "public network";
return $"Error: Access to '{host}' is blocked. The host resolves to a {networkType} address and the current access policy does not permit this. " +
"Configure WebBrowsingToolOptions to allow access.";
}
/// <summary>
/// Checks whether a host matches a pattern. Supports exact match and wildcard prefix (e.g., "*.example.com").
/// </summary>
private static bool HostMatchesPattern(string host, string pattern)
{
if (string.Equals(host, pattern, StringComparison.OrdinalIgnoreCase))
{
return true;
}
// Wildcard prefix: "*.example.com" matches "sub.example.com" and "a.b.example.com".
if (pattern.StartsWith("*.", StringComparison.Ordinal))
{
string suffix = pattern[1..]; // ".example.com"
return host.EndsWith(suffix, StringComparison.OrdinalIgnoreCase);
}
return false;
}
/// <summary>
/// Determines whether an IP address is private, loopback, or link-local.
/// </summary>
private static bool IsPrivateAddress(IPAddress address)
{
if (address.IsIPv4MappedToIPv6)
{
address = address.MapToIPv4();
}
if (IPAddress.IsLoopback(address))
{
return true;
}
if (address.AddressFamily == AddressFamily.InterNetwork)
{
byte[] bytes = address.GetAddressBytes();
return bytes[0] switch
{
10 => true, // 10.0.0.0/8
172 => bytes[1] >= 16 && bytes[1] <= 31, // 172.16.0.0/12
192 => bytes[1] == 168, // 192.168.0.0/16
169 => bytes[1] == 254, // 169.254.0.0/16 (link-local + metadata)
_ => false
};
}
if (address.AddressFamily == AddressFamily.InterNetworkV6)
{
// fe80::/10 (link-local) or fc00::/7 (unique local).
byte[] bytes = address.GetAddressBytes();
if (bytes[0] == 0xfe && (bytes[1] & 0xc0) == 0x80)
{
return true; // Link-local
}
if ((bytes[0] & 0xfe) == 0xfc)
{
return true; // Unique local
}
}
return false;
}
/// <summary>
/// A simple HTML to Markdown converter using regex-based transformations.
/// Handles the most common HTML elements without requiring external dependencies.
/// </summary>
private static partial class HtmlToMarkdownConverter
{
public static string Convert(string html)
{
// Extract body content if present, otherwise use the full HTML.
var bodyMatch = BodyRegex().Match(html);
string content = bodyMatch.Success ? bodyMatch.Groups[1].Value : html;
// Remove script, style, and head blocks.
content = ScriptRegex().Replace(content, string.Empty);
content = StyleRegex().Replace(content, string.Empty);
content = HeadRegex().Replace(content, string.Empty);
content = CommentRegex().Replace(content, string.Empty);
// Convert block elements before inline elements.
content = ConvertHeadings(content);
content = ConvertCodeBlocks(content);
content = ConvertBlockquotes(content);
content = ConvertLists(content);
content = ConvertHorizontalRules(content);
// Convert inline elements.
content = ConvertLinks(content);
content = ConvertImages(content);
content = ConvertBold(content);
content = ConvertItalic(content);
content = ConvertInlineCode(content);
// Convert structural elements.
content = ConvertParagraphs(content);
content = ConvertLineBreaks(content);
// Strip remaining HTML tags.
content = StripTagsRegex().Replace(content, string.Empty);
// Decode HTML entities.
content = WebUtility.HtmlDecode(content);
// Clean up excessive whitespace.
content = ExcessiveNewlinesRegex().Replace(content, "\n\n");
return content.Trim();
}
private static string ConvertHeadings(string html)
{
html = H1Regex().Replace(html, m => $"\n# {StripInnerTags(m.Groups[1].Value).Trim()}\n");
html = H2Regex().Replace(html, m => $"\n## {StripInnerTags(m.Groups[1].Value).Trim()}\n");
html = H3Regex().Replace(html, m => $"\n### {StripInnerTags(m.Groups[1].Value).Trim()}\n");
html = H4Regex().Replace(html, m => $"\n#### {StripInnerTags(m.Groups[1].Value).Trim()}\n");
html = H5Regex().Replace(html, m => $"\n##### {StripInnerTags(m.Groups[1].Value).Trim()}\n");
html = H6Regex().Replace(html, m => $"\n###### {StripInnerTags(m.Groups[1].Value).Trim()}\n");
return html;
}
private static string ConvertLinks(string html) =>
LinkRegex().Replace(html, m =>
{
string href = m.Groups[1].Value;
string text = StripInnerTags(m.Groups[2].Value).Trim();
// Skip javascript and data links.
if (href.StartsWith("javascript:", StringComparison.OrdinalIgnoreCase) ||
href.StartsWith("data:", StringComparison.OrdinalIgnoreCase))
{
return text;
}
return string.IsNullOrWhiteSpace(text) ? string.Empty : $"[{text}]({href})";
});
private static string ConvertImages(string html) =>
ImageRegex().Replace(html, m =>
{
string src = m.Groups[1].Value;
string alt = m.Groups[2].Value;
// Truncate data URIs.
if (src.StartsWith("data:", StringComparison.OrdinalIgnoreCase))
{
src = src.Split(',')[0] + "...";
}
return $"![{alt}]({src})";
});
private static string ConvertBold(string html) =>
BoldRegex().Replace(html, m => $"**{m.Groups[2].Value}**");
private static string ConvertItalic(string html) =>
ItalicRegex().Replace(html, m => $"*{m.Groups[2].Value}*");
private static string ConvertInlineCode(string html) =>
InlineCodeRegex().Replace(html, m => $"`{m.Groups[1].Value}`");
private static string ConvertCodeBlocks(string html) =>
CodeBlockRegex().Replace(html, m => $"\n```\n{StripInnerTags(m.Groups[1].Value).Trim()}\n```\n");
private static string ConvertBlockquotes(string html) =>
BlockquoteRegex().Replace(html, m =>
{
string inner = StripInnerTags(m.Groups[1].Value).Trim();
// Prefix each line with "> ".
string quoted = string.Join("\n", inner.Split('\n').Select(line => $"> {line.Trim()}"));
return $"\n{quoted}\n";
});
private static string ConvertLists(string html)
{
// Unordered lists.
html = UlRegex().Replace(html, m =>
{
string items = LiRegex().Replace(m.Groups[1].Value, li => $"- {StripInnerTags(li.Groups[1].Value).Trim()}\n");
return $"\n{items}";
});
// Ordered lists.
html = OlRegex().Replace(html, m =>
{
int index = 1;
string items = LiRegex().Replace(m.Groups[1].Value, li => $"{index++}. {StripInnerTags(li.Groups[1].Value).Trim()}\n");
return $"\n{items}";
});
return html;
}
private static string ConvertHorizontalRules(string html) =>
HrRegex().Replace(html, "\n---\n");
private static string ConvertParagraphs(string html) =>
ParagraphRegex().Replace(html, m => $"\n\n{m.Groups[1].Value}\n\n");
private static string ConvertLineBreaks(string html) =>
BrRegex().Replace(html, "\n");
private static string StripInnerTags(string html) =>
StripTagsRegex().Replace(html, string.Empty);
// Source-generated regex patterns for performance and AOT compatibility.
[GeneratedRegex(@"<body[^>]*>(.*?)</body>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex BodyRegex();
[GeneratedRegex(@"<script[^>]*>.*?</script>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex ScriptRegex();
[GeneratedRegex(@"<style[^>]*>.*?</style>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex StyleRegex();
[GeneratedRegex(@"<head[^>]*>.*?</head>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex HeadRegex();
[GeneratedRegex(@"<!--.*?-->", RegexOptions.Singleline)]
private static partial Regex CommentRegex();
[GeneratedRegex(@"<h1[^>]*>(.*?)</h1>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex H1Regex();
[GeneratedRegex(@"<h2[^>]*>(.*?)</h2>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex H2Regex();
[GeneratedRegex(@"<h3[^>]*>(.*?)</h3>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex H3Regex();
[GeneratedRegex(@"<h4[^>]*>(.*?)</h4>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex H4Regex();
[GeneratedRegex(@"<h5[^>]*>(.*?)</h5>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex H5Regex();
[GeneratedRegex(@"<h6[^>]*>(.*?)</h6>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex H6Regex();
[GeneratedRegex(@"<a\s[^>]*href=[""']([^""']*)[""'][^>]*>(.*?)</a>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex LinkRegex();
[GeneratedRegex(@"<img\s[^>]*src=[""']([^""']*)[""'][^>]*?(?:alt=[""']([^""']*)[""'])?[^>]*/?>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex ImageRegex();
[GeneratedRegex(@"<(strong|b)\b[^>]*>(.*?)</\1>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex BoldRegex();
[GeneratedRegex(@"<(em|i)\b[^>]*>(.*?)</\1>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex ItalicRegex();
[GeneratedRegex(@"<code[^>]*>(.*?)</code>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex InlineCodeRegex();
[GeneratedRegex(@"<pre[^>]*>(.*?)</pre>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex CodeBlockRegex();
[GeneratedRegex(@"<blockquote[^>]*>(.*?)</blockquote>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex BlockquoteRegex();
[GeneratedRegex(@"<ul[^>]*>(.*?)</ul>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex UlRegex();
[GeneratedRegex(@"<ol[^>]*>(.*?)</ol>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex OlRegex();
[GeneratedRegex(@"<li[^>]*>(.*?)</li>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex LiRegex();
[GeneratedRegex(@"<hr\s*/?>", RegexOptions.IgnoreCase)]
private static partial Regex HrRegex();
[GeneratedRegex(@"<p[^>]*>(.*?)</p>", RegexOptions.Singleline | RegexOptions.IgnoreCase)]
private static partial Regex ParagraphRegex();
[GeneratedRegex(@"<br\s*/?>", RegexOptions.IgnoreCase)]
private static partial Regex BrRegex();
[GeneratedRegex(@"<[^>]+>")]
private static partial Regex StripTagsRegex();
[GeneratedRegex(@"\n{3,}")]
private static partial Regex ExcessiveNewlinesRegex();
}
}
@@ -1,60 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
namespace SampleApp;
/// <summary>
/// Options that control which URLs the <see cref="WebBrowsingTool"/> is permitted to access.
/// </summary>
/// <remarks>
/// <para>
/// By default, <b>no hosts are accessible</b>. You must explicitly opt in to one or more
/// of the access modes below. The validation order is:
/// </para>
/// <list type="number">
/// <item><description>If the host matches an entry in <see cref="AllowedHosts"/>, the request is allowed.</description></item>
/// <item><description>If the resolved IP is a public address and <see cref="AllowPublicNetworks"/> is <see langword="true"/>, the request is allowed.</description></item>
/// <item><description>If the resolved IP is a private/loopback/link-local address and <see cref="AllowPrivateNetworks"/> is <see langword="true"/>, the request is allowed.</description></item>
/// <item><description>If <see cref="AllowAllHosts"/> is <see langword="true"/>, the request is allowed.</description></item>
/// <item><description>Otherwise, the request is blocked.</description></item>
/// </list>
/// </remarks>
internal sealed class WebBrowsingToolOptions
{
/// <summary>
/// Gets or sets a list of host patterns that are always permitted, regardless of other settings.
/// Patterns support wildcard prefix matching (e.g., <c>"*.example.com"</c> matches <c>"docs.example.com"</c>).
/// Exact host names (e.g., <c>"docs.microsoft.com"</c>) are also supported.
/// </summary>
/// <remarks>This has the highest priority — if a host matches, it is allowed immediately.</remarks>
public IReadOnlyList<string>? AllowedHosts { get; set; }
/// <summary>
/// Gets or sets a value indicating whether public internet hosts (non-private, non-loopback, non-link-local IPs) are permitted.
/// Default is <see langword="false"/>.
/// </summary>
public bool AllowPublicNetworks { get; set; }
/// <summary>
/// Gets or sets a value indicating whether private network hosts are permitted.
/// This includes RFC 1918 addresses (10.x.x.x, 172.16-31.x.x, 192.168.x.x),
/// loopback (127.x.x.x, ::1), link-local (169.254.x.x, fe80::),
/// and cloud metadata endpoints (169.254.169.254).
/// Default is <see langword="false"/>.
/// </summary>
/// <remarks>
/// <b>Warning:</b> Enabling this allows the agent to make requests to internal services,
/// localhost, and cloud metadata endpoints. Only enable this if you understand the SSRF risks.
/// </remarks>
public bool AllowPrivateNetworks { get; set; }
/// <summary>
/// Gets or sets a value indicating whether all hosts are permitted without any restriction.
/// Default is <see langword="false"/>.
/// </summary>
/// <remarks>
/// <b>⚠️ UNSAFE:</b> Enabling this disables all network boundary checks and allows the agent
/// to access any URL, including internal services, cloud metadata endpoints, and localhost.
/// Only use this for trusted, isolated environments where SSRF is not a concern.
/// </remarks>
public bool AllowAllHosts { get; set; }
}
@@ -1,20 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
<ProjectReference Include="..\Harness_Shared_Console\Harness_Shared_Console.csproj" />
</ItemGroup>
</Project>
@@ -1,106 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to use the SubAgentsProvider to delegate work to sub-agents.
// A parent agent is given a list of stock tickers and instructed to find the closing price
// for each ticker on December 31, 2025. It delegates the web searches to a sub-agent
// equipped with Foundry's hosted web search tool.
//
// Special commands:
// exit — End the session.
#pragma warning disable OPENAI001 // Suppress experimental API warnings for Responses API usage.
#pragma warning disable MAAI001 // Suppress experimental API warnings for Agents AI experiments.
using System.ClientModel.Primitives;
using Azure.Identity;
using Harness.Shared.Console;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using OpenAI;
using OpenAI.Responses;
var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4";
// --- Sub-agent: Web Search Agent ---
// This agent can search the web and is used by the parent agent to look up stock prices.
AIAgent webSearchAgent =
new OpenAIClient(
new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"),
new OpenAIClientOptions()
{
Endpoint = new Uri(endpoint),
RetryPolicy = new ClientRetryPolicy(3)
})
.GetResponsesClient()
.AsIChatClientWithStoredOutputDisabled(deploymentName)
.AsAIAgent(
new ChatClientAgentOptions
{
Name = "WebSearchAgent",
Description = "An agent that can search the web to find information.",
ChatOptions = new ChatOptions
{
Instructions = "You are a web search assistant. When asked to find information, use the web search tool to look it up and return a concise, factual answer.",
Tools =
[
ResponseTool.CreateWebSearchTool().AsAITool(),
],
},
});
// --- Parent agent: Stock Price Researcher ---
// This agent orchestrates the sub-agent to look up stock prices in parallel.
var parentInstructions =
"""
You are a stock price research assistant. You have access to a web search sub-agent that can look up information on the web.
When given a list of stock tickers, your job is to find the closing price for each ticker on December 31, 2025.
## Workflow
1. For each ticker, start a sub-task on the WebSearchAgent asking it to find the closing price on December 31, 2025.
- Start all sub-tasks before waiting for any of them to complete, so they run concurrently.
2. Wait for all sub-tasks to complete.
3. Retrieve the results from each sub-task.
4. Present a summary table with the ticker symbol and closing price for each stock.
5. Clear all completed tasks to free memory.
## Important
- Always delegate web searches to the WebSearchAgent sub-agent. Do not try to answer from memory.
- If a sub-task fails or returns unclear results, continue the task with a more specific query.
- Present results in a clean markdown table format.
""";
AIAgent parentAgent =
new OpenAIClient(
new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"),
new OpenAIClientOptions()
{
Endpoint = new Uri(endpoint),
RetryPolicy = new ClientRetryPolicy(3)
})
.GetResponsesClient()
.AsIChatClientWithStoredOutputDisabled(deploymentName)
.AsAIAgent(
new ChatClientAgentOptions
{
Name = "StockPriceResearcher",
Description = "An agent that researches stock prices using sub-agents.",
AIContextProviders =
[
new SubAgentsProvider([webSearchAgent]),
],
ChatOptions = new ChatOptions
{
Instructions = parentInstructions,
MaxOutputTokens = 16_000,
},
});
// Run the interactive console session.
await HarnessConsole.RunAgentAsync(
parentAgent,
title: "Stock Price Researcher (SubAgents Demo)",
userPrompt: "Enter a list of stock tickers (e.g., BAC, MSFT, BA):");
@@ -1,53 +0,0 @@
# Harness Step 02 — SubAgents (Stock Price Research)
This sample demonstrates how to use the **SubAgentsProvider** to delegate work from a parent agent to sub-agents.
## What It Does
A parent agent receives a list of stock tickers and uses a web-search sub-agent to find the closing price for each ticker on December 31, 2025. The sub-tasks run concurrently, and results are presented in a summary table.
### Architecture
```
┌─────────────────────────────────┐
│ StockPriceResearcher │
│ (Parent Agent) │
│ │
│ SubAgentsProvider │
│ ├─ SubAgents_StartTask │
│ ├─ SubAgents_WaitFor... │
│ ├─ SubAgents_GetTaskResults │
│ └─ ... │
└────────────┬────────────────────┘
│ delegates to
┌─────────────────────────────────┐
│ WebSearchAgent │
│ (Sub-Agent) │
│ │
│ Tools: │
│ └─ web_search (Foundry) │
└─────────────────────────────────┘
```
## Prerequisites
- An Azure AI Foundry endpoint with an OpenAI model deployment
- Set the following environment variables:
- `AZURE_FOUNDRY_OPENAI_ENDPOINT` — Your Foundry OpenAI endpoint URL
- `AZURE_AI_MODEL_DEPLOYMENT_NAME` — Model deployment name (defaults to `gpt-5.4`)
## Running the Sample
```bash
cd dotnet/samples/02-agents/Harness/Harness_Step02_Research_WithSubAgents
dotnet run
```
When prompted, enter a list of stock tickers such as:
```
BAC, MSFT, BA
```
The parent agent will delegate each ticker lookup to the web search sub-agent concurrently and present the results in a table.
@@ -1,24 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
<ProjectReference Include="..\Harness_Shared_Console\Harness_Shared_Console.csproj" />
</ItemGroup>
<ItemGroup>
<Content Include="data\**\*" CopyToOutputDirectory="PreserveNewest" />
</ItemGroup>
</Project>
@@ -1,110 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to use a ChatClientAgent with the FileAccessProvider
// to give an agent access to a folder of CSV data files. The agent can read, analyze,
// and extract information from the data, then write results back as new files.
//
// The sample includes a pre-populated `data/` folder with sales transaction data.
// Ask the agent to analyze the data, produce summaries, or create new output files.
//
// Special commands:
// exit — End the session.
#pragma warning disable OPENAI001 // Suppress experimental API warnings for Responses API usage.
#pragma warning disable MAAI001 // Suppress experimental API warnings for Agents AI experiments.
using System.ClientModel.Primitives;
using Azure.Identity;
using Harness.Shared.Console;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Compaction;
using Microsoft.Extensions.AI;
using OpenAI;
using OpenAI.Responses;
var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4";
const int MaxContextWindowTokens = 1_050_000;
const int MaxOutputTokens = 128_000;
// Point the file store at the data/ folder that ships with the sample.
var dataFolder = Path.Combine(AppContext.BaseDirectory, "data");
var fileStore = new FileSystemAgentFileStore(dataFolder);
var instructions =
"""
You are a data analyst assistant. You have access to a folder of data files via the FileAccess_* tools.
## Getting started
- Start by listing available files with FileAccess_ListFiles to see what data is available.
- Read the files to understand their structure and contents.
## Working with data
- When asked to analyze data, read the relevant files first, then perform the analysis.
- Show your analysis clearly with tables, summaries, and key insights.
- When calculations are needed, work through them step by step and show your reasoning.
## Writing output
- When asked to produce output files (e.g., reports, summaries, filtered data), use FileAccess_SaveFile to write them.
- Use appropriate file formats: CSV for tabular data, Markdown for reports.
- Confirm what you wrote and where.
## Important
- Never modify or delete the original input data files unless explicitly asked to do so.
- If asked about data you haven't read yet, read it first before answering.
- Always explain your reasoning and thought process as you work through tasks.
- Always explain what you learned and what you are going to do next between tool calls, so the user can follow along with your thought process.
""";
// Create a compaction strategy based on the model's context window.
var compactionStrategy = new ContextWindowCompactionStrategy(
maxContextWindowTokens: MaxContextWindowTokens,
maxOutputTokens: MaxOutputTokens);
AIAgent agent =
new OpenAIClient(
new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"),
new OpenAIClientOptions()
{
Endpoint = new Uri(endpoint),
RetryPolicy = new ClientRetryPolicy(3)
})
.GetResponsesClient()
.AsIChatClientWithStoredOutputDisabled(deploymentName)
.AsBuilder()
.UseFunctionInvocation()
.UsePerServiceCallChatHistoryPersistence()
.UseAIContextProviders(new CompactionProvider(compactionStrategy))
.BuildAIAgent(
new ChatClientAgentOptions
{
Name = "DataAnalyst",
Description = "A data analyst assistant that reads, analyzes, and processes data files.",
UseProvidedChatClientAsIs = true,
RequirePerServiceCallChatHistoryPersistence = true,
ChatHistoryProvider = new InMemoryChatHistoryProvider(
new InMemoryChatHistoryProviderOptions
{
ChatReducer = compactionStrategy.AsChatReducer(),
}),
AIContextProviders =
[
new FileAccessProvider(fileStore),
],
ChatOptions = new ChatOptions
{
Instructions = instructions,
MaxOutputTokens = MaxOutputTokens,
},
})
.AsBuilder()
.Build();
// Run the interactive console session.
await HarnessConsole.RunAgentAsync(
agent,
title: "Data Processing Assistant",
userPrompt: "Ask me to analyze the data files, produce summaries, or create output files.");
@@ -1,65 +0,0 @@
# What this sample demonstrates
This sample demonstrates how to use a `ChatClientAgent` with the `FileAccessProvider` to give an agent access to a folder of data files for reading, analyzing, and writing results.
Key features showcased:
- **FileAccessProvider** — gives the agent tools to read, write, list, search, and delete files in a shared data folder
- **CSV data processing** — the agent reads sales transaction data and performs analysis on demand
- **Output file creation** — the agent can write summaries, filtered data, or reports back to the data folder
- **Streaming output** — responses are streamed token-by-token for a natural experience
- **No planning mode** — this is a simple conversational sample focused on data interaction
## Prerequisites
Before running this sample, ensure you have:
1. An Azure AI Foundry project with a deployed model (e.g., `gpt-5.4`)
2. Azure CLI installed and authenticated (`az login`)
## Environment Variables
Set the following environment variables:
```bash
# Required: Your Azure AI Foundry OpenAI endpoint
export AZURE_FOUNDRY_OPENAI_ENDPOINT="https://your-project.services.ai.azure.com/openai/v1/"
# Optional: Model deployment name (defaults to gpt-5.4)
export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4"
```
## Running the Sample
```bash
cd dotnet
dotnet run --project samples/02-agents/Harness/Harness_Step03_DataProcessing
```
## What to Expect
The sample starts an interactive conversation with a data analyst agent. The `data/` folder contains a `sales.csv` file with ~50 rows of sales transaction data (date, product, category, quantity, unit price, region, salesperson).
You can ask the agent to:
1. **List available files** — "What files do you have?"
2. **Analyze the data** — "What are the total sales by region?" or "Which salesperson has the highest revenue?"
3. **Create output files** — "Create a summary report as a markdown file" or "Write a CSV with monthly totals"
4. **Search for patterns** — "Find all transactions over $1000"
5. **Type `exit`** — to end the session
E.g. try the following prompt `Please process the sales.csv file by first filtering it to only North region sales, and then calculating the sum of sales by person. I'd like to write the results of the processing to north_region_totals.csv`.
## Sample Data
The included `data/sales.csv` contains sales transactions from January to March 2025 with the following columns:
| Column | Description |
| --- | --- |
| `date` | Transaction date (YYYY-MM-DD) |
| `product` | Product name |
| `category` | Product category (Electronics, Furniture, Stationery) |
| `quantity` | Units sold |
| `unit_price` | Price per unit |
| `region` | Sales region (North, South, West) |
| `salesperson` | Name of the salesperson |
@@ -1,50 +0,0 @@
date,product,category,quantity,unit_price,region,salesperson
2025-01-03,Laptop Pro 15,Electronics,2,1299.99,North,Alice
2025-01-05,Ergonomic Chair,Furniture,5,349.50,South,Bob
2025-01-07,Wireless Mouse,Electronics,12,24.99,North,Alice
2025-01-08,Standing Desk,Furniture,1,599.00,West,Carol
2025-01-10,USB-C Hub,Electronics,8,45.99,North,David
2025-01-12,Monitor 27in,Electronics,3,429.00,South,Bob
2025-01-14,Desk Lamp,Furniture,6,79.95,West,Carol
2025-01-15,Keyboard Mech,Electronics,4,149.99,North,Alice
2025-01-17,Filing Cabinet,Furniture,2,189.00,South,David
2025-01-20,Webcam HD,Electronics,10,89.99,West,Bob
2025-01-22,Laptop Pro 15,Electronics,1,1299.99,South,Carol
2025-01-24,Ergonomic Chair,Furniture,3,349.50,North,Alice
2025-01-25,Notebook Pack,Stationery,20,12.99,South,David
2025-01-27,Wireless Mouse,Electronics,15,24.99,West,Carol
2025-01-28,Whiteboard,Stationery,4,129.00,North,Bob
2025-01-30,Standing Desk,Furniture,2,599.00,South,Alice
2025-02-02,USB-C Hub,Electronics,6,45.99,West,David
2025-02-04,Monitor 27in,Electronics,2,429.00,North,Carol
2025-02-05,Desk Lamp,Furniture,8,79.95,South,Bob
2025-02-07,Keyboard Mech,Electronics,5,149.99,West,Alice
2025-02-09,Filing Cabinet,Furniture,1,189.00,North,David
2025-02-11,Webcam HD,Electronics,7,89.99,South,Carol
2025-02-13,Laptop Pro 15,Electronics,3,1299.99,West,Bob
2025-02-15,Notebook Pack,Stationery,30,12.99,North,Alice
2025-02-17,Ergonomic Chair,Furniture,4,349.50,South,David
2025-02-19,Wireless Mouse,Electronics,20,24.99,North,Carol
2025-02-20,Whiteboard,Stationery,2,129.00,West,Bob
2025-02-22,Standing Desk,Furniture,1,599.00,North,Alice
2025-02-24,USB-C Hub,Electronics,10,45.99,South,David
2025-02-26,Monitor 27in,Electronics,4,429.00,West,Carol
2025-02-28,Desk Lamp,Furniture,3,79.95,North,Bob
2025-03-02,Keyboard Mech,Electronics,6,149.99,South,Alice
2025-03-04,Filing Cabinet,Furniture,3,189.00,West,David
2025-03-06,Webcam HD,Electronics,9,89.99,North,Carol
2025-03-08,Laptop Pro 15,Electronics,2,1299.99,South,Bob
2025-03-10,Notebook Pack,Stationery,25,12.99,West,Alice
2025-03-12,Ergonomic Chair,Furniture,6,349.50,North,David
2025-03-14,Wireless Mouse,Electronics,18,24.99,South,Carol
2025-03-15,Whiteboard,Stationery,5,129.00,North,Bob
2025-03-17,Standing Desk,Furniture,3,599.00,West,Alice
2025-03-19,USB-C Hub,Electronics,7,45.99,North,David
2025-03-21,Monitor 27in,Electronics,5,429.00,South,Carol
2025-03-23,Desk Lamp,Furniture,4,79.95,West,Bob
2025-03-25,Keyboard Mech,Electronics,3,149.99,North,Alice
2025-03-27,Filing Cabinet,Furniture,2,189.00,South,David
2025-03-28,Webcam HD,Electronics,11,89.99,West,Carol
2025-03-29,Laptop Pro 15,Electronics,1,1299.99,North,Bob
2025-03-30,Notebook Pack,Stationery,15,12.99,South,Alice
2025-03-31,Ergonomic Chair,Furniture,2,349.50,West,David
1 date product category quantity unit_price region salesperson
2 2025-01-03 Laptop Pro 15 Electronics 2 1299.99 North Alice
3 2025-01-05 Ergonomic Chair Furniture 5 349.50 South Bob
4 2025-01-07 Wireless Mouse Electronics 12 24.99 North Alice
5 2025-01-08 Standing Desk Furniture 1 599.00 West Carol
6 2025-01-10 USB-C Hub Electronics 8 45.99 North David
7 2025-01-12 Monitor 27in Electronics 3 429.00 South Bob
8 2025-01-14 Desk Lamp Furniture 6 79.95 West Carol
9 2025-01-15 Keyboard Mech Electronics 4 149.99 North Alice
10 2025-01-17 Filing Cabinet Furniture 2 189.00 South David
11 2025-01-20 Webcam HD Electronics 10 89.99 West Bob
12 2025-01-22 Laptop Pro 15 Electronics 1 1299.99 South Carol
13 2025-01-24 Ergonomic Chair Furniture 3 349.50 North Alice
14 2025-01-25 Notebook Pack Stationery 20 12.99 South David
15 2025-01-27 Wireless Mouse Electronics 15 24.99 West Carol
16 2025-01-28 Whiteboard Stationery 4 129.00 North Bob
17 2025-01-30 Standing Desk Furniture 2 599.00 South Alice
18 2025-02-02 USB-C Hub Electronics 6 45.99 West David
19 2025-02-04 Monitor 27in Electronics 2 429.00 North Carol
20 2025-02-05 Desk Lamp Furniture 8 79.95 South Bob
21 2025-02-07 Keyboard Mech Electronics 5 149.99 West Alice
22 2025-02-09 Filing Cabinet Furniture 1 189.00 North David
23 2025-02-11 Webcam HD Electronics 7 89.99 South Carol
24 2025-02-13 Laptop Pro 15 Electronics 3 1299.99 West Bob
25 2025-02-15 Notebook Pack Stationery 30 12.99 North Alice
26 2025-02-17 Ergonomic Chair Furniture 4 349.50 South David
27 2025-02-19 Wireless Mouse Electronics 20 24.99 North Carol
28 2025-02-20 Whiteboard Stationery 2 129.00 West Bob
29 2025-02-22 Standing Desk Furniture 1 599.00 North Alice
30 2025-02-24 USB-C Hub Electronics 10 45.99 South David
31 2025-02-26 Monitor 27in Electronics 4 429.00 West Carol
32 2025-02-28 Desk Lamp Furniture 3 79.95 North Bob
33 2025-03-02 Keyboard Mech Electronics 6 149.99 South Alice
34 2025-03-04 Filing Cabinet Furniture 3 189.00 West David
35 2025-03-06 Webcam HD Electronics 9 89.99 North Carol
36 2025-03-08 Laptop Pro 15 Electronics 2 1299.99 South Bob
37 2025-03-10 Notebook Pack Stationery 25 12.99 West Alice
38 2025-03-12 Ergonomic Chair Furniture 6 349.50 North David
39 2025-03-14 Wireless Mouse Electronics 18 24.99 South Carol
40 2025-03-15 Whiteboard Stationery 5 129.00 North Bob
41 2025-03-17 Standing Desk Furniture 3 599.00 West Alice
42 2025-03-19 USB-C Hub Electronics 7 45.99 North David
43 2025-03-21 Monitor 27in Electronics 5 429.00 South Carol
44 2025-03-23 Desk Lamp Furniture 4 79.95 West Bob
45 2025-03-25 Keyboard Mech Electronics 3 149.99 North Alice
46 2025-03-27 Filing Cabinet Furniture 2 189.00 South David
47 2025-03-28 Webcam HD Electronics 11 89.99 West Carol
48 2025-03-29 Laptop Pro 15 Electronics 1 1299.99 North Bob
49 2025-03-30 Notebook Pack Stationery 15 12.99 South Alice
50 2025-03-31 Ergonomic Chair Furniture 2 349.50 West David
@@ -1,11 +0,0 @@
# Harness Agent Samples
Samples demonstrating the [Harness AIContextProviders](../../../src/Microsoft.Agents.AI/Harness/) — reusable providers that add planning, task management, and mode tracking to any `ChatClientAgent`.
## Samples
| Sample | Description |
| --- | --- |
| [Harness_Step01_Research](./Harness_Step01_Research/README.md) | Using a ChatClientAgent with TodoProvider and AgentModeProvider for research, showcasing planning mode and todo management |
| [Harness_Step02_Research_WithSubAgents](./Harness_Step02_Research_WithSubAgents/README.md) | Using SubAgentsProvider to delegate stock price lookups to a web-search sub-agent concurrently |
| [Harness_Step03_DataProcessing](./Harness_Step03_DataProcessing/README.md) | Using FileAccessProvider to give an agent access to CSV data files for reading, analysis, and output generation |
-2
View File
@@ -11,13 +11,11 @@ The getting started samples demonstrate the fundamental concepts and functionali
| [Agent Providers](./AgentProviders/README.md) | Getting started with creating agents using various providers |
| [Agents With Retrieval Augmented Generation (RAG)](./AgentWithRAG/README.md) | Adding Retrieval Augmented Generation (RAG) capabilities to your agents |
| [Agents With Memory](./AgentWithMemory/README.md) | Adding memory capabilities to your agents |
| [Agents With CodeAct (Hyperlight)](./AgentWithCodeAct/README.md) | Enabling sandboxed code execution (CodeAct) for your agents via Hyperlight |
| [Agent Open Telemetry](./AgentOpenTelemetry/README.md) | Getting started with OpenTelemetry for agents |
| [Agent With OpenAI exchange types](./AgentWithOpenAI/README.md) | Using OpenAI exchange types with agents |
| [Agent With Anthropic](./AgentWithAnthropic/README.md) | Getting started with agents using Anthropic Claude |
| [Model Context Protocol](./ModelContextProtocol/README.md) | Getting started with Model Context Protocol |
| [Agent Skills](./AgentSkills/README.md) | Getting started with Agent Skills |
| [Agent Harness with built-in tools](./Harness/README.md) | Demonstrating how to build an Agent Harness with built-in planning, todo, and mode management tooling |
| [Declarative Agents](./DeclarativeAgents) | Loading and executing AI agents from YAML configuration files |
| [AG-UI](./AGUI/README.md) | Getting started with AG-UI (Agent UI Protocol) servers and clients |
| [Dev UI](./DevUI/README.md) | Interactive web interface for testing and debugging AI agents during development |
@@ -1,38 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
</PropertyGroup>
<PropertyGroup>
<InjectIsExternalInitOnLegacy>true</InjectIsExternalInitOnLegacy>
<InjectSharedFoundryAgents>true</InjectSharedFoundryAgents>
<InjectSharedWorkflowsExecution>true</InjectSharedWorkflowsExecution>
<InjectSharedWorkflowsSettings>true</InjectSharedWorkflowsSettings>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Microsoft.Extensions.Configuration" />
<PackageReference Include="Microsoft.Extensions.Configuration.Binder" />
<PackageReference Include="Microsoft.Extensions.Configuration.EnvironmentVariables" />
<PackageReference Include="Microsoft.Extensions.Configuration.Json" />
<PackageReference Include="Microsoft.Extensions.Configuration.UserSecrets" />
<PackageReference Include="Microsoft.Extensions.DependencyInjection" />
<PackageReference Include="Microsoft.Extensions.Logging" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Workflows.Declarative\Microsoft.Agents.AI.Workflows.Declarative.csproj" />
<ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Workflows.Declarative.Foundry\Microsoft.Agents.AI.Workflows.Declarative.Foundry.csproj" />
</ItemGroup>
<ItemGroup>
<None Include="InvokeHttpRequest.yaml">
<CopyToOutputDirectory>Always</CopyToOutputDirectory>
</None>
</ItemGroup>
</Project>
@@ -1,76 +0,0 @@
#
# This workflow demonstrates using HttpRequestAction to call a REST API directly
# from the workflow without going through an AI agent first.
#
# HttpRequestAction allows workflows to:
# - Fetch data from external HTTP endpoints
# - Store the parsed response in workflow variables for later use
# - Add the response body to the conversation so a downstream agent can
# answer questions based on it
#
# This sample fetches public metadata for the dotnet/runtime repository from
# the GitHub REST API (no authentication required) and uses an agent to
# answer follow-up questions about it.
#
# Example input:
# How many subscribers does the repository have?
#
kind: Workflow
trigger:
kind: OnConversationStart
id: workflow_invoke_http_request_demo
actions:
# Capture the original user message for input to the follow-up agent.
- kind: SetVariable
id: set_user_message
variable: Local.InputMessage
value: =System.LastMessage
# Set the repository org/name used to form the request URL.
- kind: SetVariable
id: set_repo_name
variable: Local.RepoName
value: microsoft/agent-framework
# Invoke the GitHub repo API. The response body is parsed into Local.RepoInfo
# and also added to the conversation (via conversationId) so the agent below
# can answer questions based on it.
- kind: HttpRequestAction
id: fetch_repo_info
conversationId: =System.ConversationId
method: GET
url: =Concatenate("https://api.github.com/repos/", Local.RepoName)
headers:
Accept: application/vnd.github+json
User-Agent: agent-framework-sample
response: Local.RepoInfo
# Display a confirmation message showing key fields from the parsed response.
- kind: SendMessage
id: show_repo_summary
message: "Fetched repo: visibility={Local.RepoInfo.visibility}, description={Local.RepoInfo.description}"
# Use the agent to summarize the repo using the conversation context.
- kind: InvokeAzureAgent
id: summarize_repo
conversationId: =System.ConversationId
agent:
name: GitHubRepoInfoAgent
input:
messages: =UserMessage("Please provide a brief summary of this GitHub repository based on the data already in the conversation.")
output:
autoSend: true
messages: Local.AgentResponse
# Allow the user to ask follow-up questions about the repo in a loop.
- kind: InvokeAzureAgent
id: invoke_followup
conversationId: =System.ConversationId
agent:
name: GitHubRepoInfoAgent
input:
messages: =Local.InputMessage
externalLoop:
when: =Upper(System.LastMessage.Text) <> "EXIT"
@@ -1,95 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Azure.AI.Projects;
using Azure.AI.Projects.Agents;
using Azure.Identity;
using Microsoft.Agents.AI.Workflows.Declarative;
using Microsoft.Extensions.Configuration;
using Shared.Foundry;
using Shared.Workflows;
namespace Demo.Workflows.Declarative.InvokeHttpRequest;
/// <summary>
/// Demonstrates a workflow that uses HttpRequestAction to call a REST API
/// directly from the workflow.
/// </summary>
/// <remarks>
/// <para>
/// The HttpRequestAction allows workflows to issue HTTP requests and:
/// </para>
/// <list type="bullet">
/// <item>Fetch data from external REST endpoints</item>
/// <item>Store the parsed response in workflow variables</item>
/// <item>Add the response body to the conversation so an agent can answer
/// questions based on it</item>
/// </list>
/// <para>
/// This sample fetches public metadata for the dotnet/runtime repository from
/// the GitHub REST API (no authentication required) and uses a Foundry agent
/// to answer follow-up questions about it. Type "EXIT" to end the conversation.
/// </para>
/// <para>
/// See the README.md file in the parent folder (../README.md) for detailed
/// information about the configuration required to run this sample.
/// </para>
/// </remarks>
internal sealed class Program
{
public static async Task Main(string[] args)
{
// Initialize configuration
IConfiguration configuration = Application.InitializeConfig();
Uri foundryEndpoint = new(configuration.GetValue(Application.Settings.FoundryEndpoint));
// Ensure sample agent exists in Foundry. The agent has no tools - it answers
// questions about the GitHub repository using only the JSON data that the
// HttpRequestAction adds to the conversation.
await CreateAgentAsync(foundryEndpoint, configuration);
// Get input from command line or console
string workflowInput = Application.GetInput(args);
// The default HttpRequestHandler is sufficient for this sample because the
// GitHub REST endpoint used here does not require authentication. For
// authenticated endpoints, supply a custom Func<HttpRequestInfo, ..., HttpClient?>
// to DefaultHttpRequestHandler so each request can be routed through a
// pre-configured (cached) HttpClient with the appropriate credentials.
await using DefaultHttpRequestHandler httpRequestHandler = new();
// Create the workflow factory with the HTTP request handler
WorkflowFactory workflowFactory = new("InvokeHttpRequest.yaml", foundryEndpoint)
{
HttpRequestHandler = httpRequestHandler
};
// Execute the workflow
WorkflowRunner runner = new() { UseJsonCheckpoints = true };
await runner.ExecuteAsync(workflowFactory.CreateWorkflow, workflowInput);
}
private static async Task CreateAgentAsync(Uri foundryEndpoint, IConfiguration configuration)
{
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
AIProjectClient aiProjectClient = new(foundryEndpoint, new DefaultAzureCredential());
await aiProjectClient.CreateAgentAsync(
agentName: "GitHubRepoInfoAgent",
agentDefinition: DefineAgent(configuration),
agentDescription: "Answers questions about a GitHub repository using HTTP response data in the conversation");
}
private static DeclarativeAgentDefinition DefineAgent(IConfiguration configuration)
{
return new DeclarativeAgentDefinition(configuration.GetValue(Application.Settings.FoundryModel))
{
Instructions =
"""
Answer the user's questions about the GitHub repository using only the
JSON data already present in the conversation history.
If the answer is not contained in the conversation, say so plainly
rather than guessing. Be concise and helpful.
"""
};
}
}
@@ -1,7 +0,0 @@
.env
bin/
obj/
out/
.vs/
.vscode/
*.user
@@ -1,12 +0,0 @@
AZURE_AI_PROJECT_ENDPOINT=<your-azure-ai-project-endpoint>
ASPNETCORE_URLS=http://+:8088
ASPNETCORE_ENVIRONMENT=Development
AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4o
AZURE_BEARER_TOKEN=DefaultAzureCredential
# Capture prompt / completion / tool argument content on GenAI spans.
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true
# Uncomment and set to send local-run telemetry to Application Insights.
# When the agent runs inside Foundry this value is injected automatically.
#APPLICATIONINSIGHTS_CONNECTION_STRING=<your-app-insights-connection-string>
@@ -1,17 +0,0 @@
# Use the official .NET 10.0 ASP.NET runtime as a parent image
FROM mcr.microsoft.com/dotnet/aspnet:10.0 AS base
WORKDIR /app
FROM mcr.microsoft.com/dotnet/sdk:10.0 AS build
WORKDIR /src
COPY . .
RUN dotnet restore
RUN dotnet publish -c Release -o /app/publish
# Final stage
FROM base AS final
WORKDIR /app
COPY --from=build /app/publish .
EXPOSE 8088
ENV ASPNETCORE_URLS=http://+:8088
ENTRYPOINT ["dotnet", "HostedObservability.dll"]
@@ -1,19 +0,0 @@
# Dockerfile for contributors building from the agent-framework repository source.
#
# This project uses ProjectReference to the local Microsoft.Agents.AI.Foundry source,
# which means a standard multi-stage Docker build cannot resolve dependencies outside
# this folder. Instead, pre-publish the app targeting the container runtime and copy
# the output into the container:
#
# dotnet publish -c Debug -f net10.0 -r linux-musl-x64 --self-contained false -o out
# docker build -f Dockerfile.contributor -t hosted-observability .
# docker run --rm -p 8088:8088 -e AGENT_NAME=hosted-observability -e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN --env-file .env hosted-observability
#
# For end-users consuming the NuGet package (not ProjectReference), use the standard
# Dockerfile which performs a full dotnet restore + publish inside the container.
FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
WORKDIR /app
COPY out/ .
EXPOSE 8088
ENV ASPNETCORE_URLS=http://+:8088
ENTRYPOINT ["dotnet", "HostedObservability.dll"]
@@ -1,32 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk.Web">
<PropertyGroup>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
<CentralPackageTransitivePinningEnabled>false</CentralPackageTransitivePinningEnabled>
<RootNamespace>HostedObservability</RootNamespace>
<AssemblyName>HostedObservability</AssemblyName>
<NoWarn>$(NoWarn);</NoWarn>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.Projects" VersionOverride="2.1.0-beta.1" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="DotNetEnv" />
</ItemGroup>
<!-- For contributors: uses ProjectReference to build against local source -->
<ItemGroup>
<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Foundry\Microsoft.Agents.AI.Foundry.csproj" />
<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Foundry.Hosting\Microsoft.Agents.AI.Foundry.Hosting.csproj" />
</ItemGroup>
<!-- For end-users: uncomment the PackageReference below and remove the ProjectReference above
<ItemGroup>
<PackageReference Include="Microsoft.Agents.AI.Foundry" Version="1.0.0" />
<PackageReference Include="Microsoft.Agents.AI.Foundry.Hosting" Version="1.0.0" />
</ItemGroup>
-->
</Project>
@@ -1,108 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
// Hosted Observability Agent - demonstrates that the Foundry hosting pipeline
// emits OpenTelemetry traces, metrics and logs with no extra wiring required.
// Two small tools are included so a request produces a span tree covering
// agent invocation, the chat call, and tool execution.
using System.ComponentModel;
using Azure.AI.Projects;
using Azure.Core;
using Azure.Identity;
using DotNetEnv;
using Microsoft.Agents.AI;
using Microsoft.Agents.AI.Foundry.Hosting;
using Microsoft.Extensions.AI;
// Load .env file if present (for local development)
Env.TraversePath().Load();
string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o";
// Use a chained credential: try a temporary dev token first (for local Docker debugging),
// then fall back to DefaultAzureCredential (for local dev via dotnet run / managed identity in production).
TokenCredential credential = new ChainedTokenCredential(
new DevTemporaryTokenCredential(),
new DefaultAzureCredential());
// ── Tools ────────────────────────────────────────────────────────────────────
string[] locations = ["New York", "London", "Paris", "Tokyo"];
string[] conditions = ["sunny", "cloudy", "rainy", "stormy"];
[Description("Get the current location of the user.")]
string GetCurrentLocation() => locations[Random.Shared.Next(locations.Length)];
[Description("Get the weather for a given location.")]
string GetWeather(
[Description("The location to get the weather for.")] string location)
=> $"The weather in {location} is {conditions[Random.Shared.Next(conditions.Length)]} with a high of {Random.Shared.Next(10, 31)}°C.";
// ── Create and host the agent ────────────────────────────────────────────────
//
// AddFoundryResponses automatically wraps `agent` with OpenTelemetryAgent
// (see Microsoft.Agents.AI.Foundry.Hosting.ServiceCollectionExtensions.ApplyOpenTelemetry)
// and the OTLP exporter is registered by Azure.AI.AgentServer.Core's
// AddAgentHostTelemetry(). No additional observability wiring is required.
AIAgent agent = new AIProjectClient(new Uri(endpoint), credential)
.AsAIAgent(
model: deploymentName,
instructions: "You are a friendly assistant. Keep your answers brief.",
name: Environment.GetEnvironmentVariable("AGENT_NAME") ?? "hosted-observability",
description: "A hosted agent that demonstrates Foundry observability.",
tools: [
AIFunctionFactory.Create(GetCurrentLocation),
AIFunctionFactory.Create(GetWeather),
]);
var builder = WebApplication.CreateBuilder(args);
builder.Services.AddFoundryResponses(agent);
var app = builder.Build();
app.MapFoundryResponses();
if (app.Environment.IsDevelopment())
{
app.MapFoundryResponses("openai/v1");
}
app.Run();
/// <summary>
/// A <see cref="TokenCredential"/> for local Docker debugging only.
/// Reads a pre-fetched bearer token from the <c>AZURE_BEARER_TOKEN</c> environment variable
/// once at startup. This should NOT be used in production.
///
/// Generate a token on your host and pass it to the container:
/// export AZURE_BEARER_TOKEN=$(az account get-access-token --resource https://ai.azure.com --query accessToken -o tsv)
/// docker run -e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN ...
/// </summary>
internal sealed class DevTemporaryTokenCredential : TokenCredential
{
private const string EnvironmentVariable = "AZURE_BEARER_TOKEN";
private readonly string? _token;
public DevTemporaryTokenCredential()
{
this._token = Environment.GetEnvironmentVariable(EnvironmentVariable);
}
public override AccessToken GetToken(TokenRequestContext requestContext, CancellationToken cancellationToken)
=> this.GetAccessToken();
public override ValueTask<AccessToken> GetTokenAsync(TokenRequestContext requestContext, CancellationToken cancellationToken)
=> new(this.GetAccessToken());
private AccessToken GetAccessToken()
{
if (string.IsNullOrEmpty(this._token) || this._token == "DefaultAzureCredential")
{
throw new CredentialUnavailableException($"{EnvironmentVariable} environment variable is not set.");
}
return new AccessToken(this._token, DateTimeOffset.UtcNow.AddHours(1));
}
}
@@ -1,109 +0,0 @@
# Hosted-Observability
A hosted [Agent Framework](https://github.com/microsoft/agent-framework) agent that demonstrates how the Foundry hosting pipeline emits OpenTelemetry traces, metrics and logs with no extra wiring.
The agent has two small tools, `GetCurrentLocation` and `GetWeather`, so an end-to-end run produces a span tree covering agent invocation, the underlying chat call, and tool execution.
## How it works
### Instrumentation is on by default
Unlike the Python SDK, the .NET hosting library is instrumented by default. `AddFoundryResponses(agent)` automatically wraps the agent with `OpenTelemetryAgent` (see `Microsoft.Agents.AI.Foundry.Hosting.ServiceCollectionExtensions.ApplyOpenTelemetry`) and the OTLP exporter pipeline is registered by `Azure.AI.AgentServer.Core`'s `AddAgentHostTelemetry()`. There is no `ENABLE_INSTRUMENTATION` flag to set.
### Sensitive content
Prompt, completion and tool argument content are omitted from spans by default. Set the OpenTelemetry standard environment variable to capture them:
```env
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true
```
This is the .NET equivalent of the Python sample's `ENABLE_SENSITIVE_DATA`. It is read by `OpenTelemetryAgent.EnableSensitiveData`.
### Where the telemetry goes
Foundry injects `APPLICATIONINSIGHTS_CONNECTION_STRING` when the agent runs in the hosted environment, so traces, metrics and logs flow to Application Insights with no code change. To send telemetry from a local run, set the connection string yourself in `.env`.
## Prerequisites
- [.NET 10 SDK](https://dotnet.microsoft.com/download/dotnet/10.0)
- An Azure AI Foundry project with a deployed model (e.g., `gpt-4o`)
- Azure CLI logged in (`az login`)
## Configuration
```bash
cp .env.example .env
```
Edit `.env` and set your Azure AI Foundry project endpoint:
```env
AZURE_AI_PROJECT_ENDPOINT=https://<your-account>.services.ai.azure.com/api/projects/<your-project>
ASPNETCORE_URLS=http://+:8088
ASPNETCORE_ENVIRONMENT=Development
AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4o
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true
```
> **Note:** `.env` is gitignored. The `.env.example` template is checked in as a reference.
## Running directly (contributors)
```bash
cd dotnet/samples/04-hosting/FoundryHostedAgents/responses/Hosted-Observability
AGENT_NAME=hosted-observability dotnet run
```
The agent starts on `http://localhost:8088`.
### Test it
```bash
azd ai agent invoke --local "What is the current weather where I am?"
```
Or with curl:
```bash
curl -X POST http://localhost:8088/responses \
-H "Content-Type: application/json" \
-d '{"input": "What is the current weather where I am?", "model": "hosted-observability"}'
```
## Expected span tree
A single request produces approximately the following spans:
| Span | Source |
|------|--------|
| `invoke_agent` | Outer span emitted by the Azure AI AgentServer hosting SDK |
| `agent_invoke <name>` | Emitted by `OpenTelemetryAgent` for each agent invocation |
| `chat <model>` | Emitted by the underlying `IChatClient` for each model call |
| `execute_tool <tool>` | Emitted for each invocation of `GetCurrentLocation` / `GetWeather` |
See the [OpenTelemetry GenAI semantic conventions](https://opentelemetry.io/docs/specs/semconv/gen-ai/) for the attributes captured on each span.
## Running with Docker
This project uses `ProjectReference` to the local Agent Framework source, so use `Dockerfile.contributor` with a pre-published output:
```bash
dotnet publish -c Debug -f net10.0 -r linux-musl-x64 --self-contained false -o out
docker build -f Dockerfile.contributor -t hosted-observability .
export AZURE_BEARER_TOKEN=$(az account get-access-token --resource https://ai.azure.com --query accessToken -o tsv)
docker run --rm -p 8088:8088 \
-e AGENT_NAME=hosted-observability \
-e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN \
--env-file .env \
hosted-observability
```
## Deploying to Foundry and viewing traces
Once deployed, telemetry flows to the Application Insights instance attached to your Foundry project. In the Foundry UI, the **Traces** tab next to **Playground** lists conversations and lets you drill into the span tree for any request.
## NuGet package users
If consuming the Agent Framework as a NuGet package, use the standard `Dockerfile` instead of `Dockerfile.contributor`. See the commented section in `HostedObservability.csproj` for the `PackageReference` alternative.
@@ -1,34 +0,0 @@
# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/AgentManifest.yaml
name: hosted-observability
displayName: "Hosted Observability Agent"
description: >
A hosted Agent Framework agent that demonstrates how the Foundry hosting
pipeline emits OpenTelemetry traces, metrics and logs to Application Insights
with no extra wiring required.
metadata:
tags:
- AI Agent Hosting
- Azure AI AgentServer
- Responses Protocol
- Observability
- OpenTelemetry
- Agent Framework
template:
name: hosted-observability
kind: hosted
protocols:
- protocol: responses
version: 1.0.0
resources:
cpu: "0.25"
memory: 0.5Gi
environment_variables:
# Capture prompt / completion / tool argument content on GenAI spans.
- name: OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT
value: "true"
parameters:
properties: []
resources: []
@@ -1,14 +0,0 @@
# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/ContainerAgent.yaml
kind: hosted
name: hosted-observability
protocols:
- protocol: responses
version: 1.0.0
resources:
cpu: "0.25"
memory: 0.5Gi
environment_variables:
# Capture prompt / completion / tool argument content on GenAI spans.
# See https://opentelemetry.io/docs/specs/semconv/gen-ai/ for the standard env var.
- name: OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT
value: "true"
@@ -2,7 +2,6 @@
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text.Json;
using Microsoft.Extensions.AI;
@@ -56,32 +55,6 @@ internal static class AGUIChatMessageExtensions
break;
}
case AGUIReasoningMessage reasoningMessage:
{
var contents = new List<AIContent>();
if (!string.IsNullOrEmpty(reasoningMessage.Content))
{
contents.Add(new TextReasoningContent(reasoningMessage.Content)
{
ProtectedData = reasoningMessage.EncryptedValue
});
}
else if (!string.IsNullOrEmpty(reasoningMessage.EncryptedValue))
{
contents.Add(new TextReasoningContent("")
{
ProtectedData = reasoningMessage.EncryptedValue
});
}
yield return new ChatMessage(role, contents)
{
MessageId = message.Id
};
break;
}
case AGUIAssistantMessage assistantMessage when assistantMessage.ToolCalls is { Length: > 0 }:
{
var contents = new List<AIContent>();
@@ -152,12 +125,6 @@ internal static class AGUIChatMessageExtensions
}
else if (message.Role == ChatRole.Assistant)
{
var reasoningMessage = MapReasoningMessage(message);
if (reasoningMessage != null)
{
yield return reasoningMessage;
}
var assistantMessage = MapAssistantMessage(jsonSerializerOptions, message);
if (assistantMessage != null)
{
@@ -177,32 +144,6 @@ internal static class AGUIChatMessageExtensions
}
}
private static AGUIReasoningMessage? MapReasoningMessage(ChatMessage message)
{
var reasoning = message.Contents.OfType<TextReasoningContent>().FirstOrDefault();
if (reasoning is null)
{
return null;
}
var text = string.Join(
string.Empty,
message.Contents.OfType<TextReasoningContent>()
.Where(r => !string.IsNullOrEmpty(r.Text))
.Select(r => r.Text));
var protectedData = message.Contents.OfType<TextReasoningContent>()
.Select(r => r.ProtectedData)
.LastOrDefault(p => !string.IsNullOrEmpty(p));
return new AGUIReasoningMessage
{
Id = message.MessageId,
Content = text,
EncryptedValue = protectedData,
};
}
private static AGUIAssistantMessage? MapAssistantMessage(JsonSerializerOptions jsonSerializerOptions, ChatMessage message)
{
List<AGUIToolCall>? toolCalls = null;
@@ -271,6 +212,5 @@ internal static class AGUIChatMessageExtensions
string.Equals(role, AGUIRoles.Assistant, StringComparison.OrdinalIgnoreCase) ? ChatRole.Assistant :
string.Equals(role, AGUIRoles.Developer, StringComparison.OrdinalIgnoreCase) ? s_developerChatRole :
string.Equals(role, AGUIRoles.Tool, StringComparison.OrdinalIgnoreCase) ? ChatRole.Tool :
string.Equals(role, AGUIRoles.Reasoning, StringComparison.OrdinalIgnoreCase) ? ChatRole.Assistant :
throw new InvalidOperationException($"Unknown chat role: {role}");
}
@@ -31,18 +31,4 @@ internal static class AGUIEventTypes
public const string StateSnapshot = "STATE_SNAPSHOT";
public const string StateDelta = "STATE_DELTA";
public const string ReasoningStart = "REASONING_START";
public const string ReasoningMessageStart = "REASONING_MESSAGE_START";
public const string ReasoningMessageContent = "REASONING_MESSAGE_CONTENT";
public const string ReasoningMessageEnd = "REASONING_MESSAGE_END";
public const string ReasoningEnd = "REASONING_END";
public const string ReasoningMessageChunk = "REASONING_MESSAGE_CHUNK";
public const string ReasoningEncryptedValue = "REASONING_ENCRYPTED_VALUE";
}
@@ -28,7 +28,6 @@ namespace Microsoft.Agents.AI.AGUI;
[JsonSerializable(typeof(AGUIUserMessage))]
[JsonSerializable(typeof(AGUIAssistantMessage))]
[JsonSerializable(typeof(AGUIToolMessage))]
[JsonSerializable(typeof(AGUIReasoningMessage))]
[JsonSerializable(typeof(AGUITool))]
[JsonSerializable(typeof(AGUIToolCall))]
[JsonSerializable(typeof(AGUIToolCall[]))]
@@ -47,13 +46,6 @@ namespace Microsoft.Agents.AI.AGUI;
[JsonSerializable(typeof(ToolCallResultEvent))]
[JsonSerializable(typeof(StateSnapshotEvent))]
[JsonSerializable(typeof(StateDeltaEvent))]
[JsonSerializable(typeof(ReasoningStartEvent))]
[JsonSerializable(typeof(ReasoningMessageStartEvent))]
[JsonSerializable(typeof(ReasoningMessageContentEvent))]
[JsonSerializable(typeof(ReasoningMessageEndEvent))]
[JsonSerializable(typeof(ReasoningEndEvent))]
[JsonSerializable(typeof(ReasoningMessageChunkEvent))]
[JsonSerializable(typeof(ReasoningEncryptedValueEvent))]
[JsonSerializable(typeof(IDictionary<string, object?>))]
[JsonSerializable(typeof(Dictionary<string, object?>))]
[JsonSerializable(typeof(IDictionary<string, System.Text.Json.JsonElement?>))]
@@ -41,7 +41,6 @@ internal sealed class AGUIMessageJsonConverter : JsonConverter<AGUIMessage>
AGUIRoles.User => jsonElement.Deserialize(options.GetTypeInfo(typeof(AGUIUserMessage))) as AGUIUserMessage,
AGUIRoles.Assistant => jsonElement.Deserialize(options.GetTypeInfo(typeof(AGUIAssistantMessage))) as AGUIAssistantMessage,
AGUIRoles.Tool => jsonElement.Deserialize(options.GetTypeInfo(typeof(AGUIToolMessage))) as AGUIToolMessage,
AGUIRoles.Reasoning => jsonElement.Deserialize(options.GetTypeInfo(typeof(AGUIReasoningMessage))) as AGUIReasoningMessage,
_ => throw new JsonException($"Unknown AGUIMessage role discriminator: '{discriminator}'")
};
@@ -76,9 +75,6 @@ internal sealed class AGUIMessageJsonConverter : JsonConverter<AGUIMessage>
case AGUIToolMessage tool:
JsonSerializer.Serialize(writer, tool, options.GetTypeInfo(typeof(AGUIToolMessage)));
break;
case AGUIReasoningMessage reasoning:
JsonSerializer.Serialize(writer, reasoning, options.GetTypeInfo(typeof(AGUIReasoningMessage)));
break;
default:
throw new JsonException($"Unknown AGUIMessage type: {value.GetType().Name}");
}
@@ -1,20 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
#if ASPNETCORE
namespace Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.Shared;
#else
namespace Microsoft.Agents.AI.AGUI.Shared;
#endif
internal sealed class AGUIReasoningMessage : AGUIMessage
{
public AGUIReasoningMessage()
{
this.Role = AGUIRoles.Reasoning;
}
[JsonPropertyName("encryptedValue")]
public string? EncryptedValue { get; set; }
}
@@ -17,6 +17,4 @@ internal static class AGUIRoles
public const string Developer = "developer";
public const string Tool = "tool";
public const string Reasoning = "reasoning";
}
@@ -47,13 +47,6 @@ internal sealed class BaseEventJsonConverter : JsonConverter<BaseEvent>
AGUIEventTypes.ToolCallEnd => jsonElement.Deserialize(options.GetTypeInfo(typeof(ToolCallEndEvent))) as ToolCallEndEvent,
AGUIEventTypes.ToolCallResult => jsonElement.Deserialize(options.GetTypeInfo(typeof(ToolCallResultEvent))) as ToolCallResultEvent,
AGUIEventTypes.StateSnapshot => jsonElement.Deserialize(options.GetTypeInfo(typeof(StateSnapshotEvent))) as StateSnapshotEvent,
AGUIEventTypes.ReasoningStart => jsonElement.Deserialize(options.GetTypeInfo(typeof(ReasoningStartEvent))) as ReasoningStartEvent,
AGUIEventTypes.ReasoningMessageStart => jsonElement.Deserialize(options.GetTypeInfo(typeof(ReasoningMessageStartEvent))) as ReasoningMessageStartEvent,
AGUIEventTypes.ReasoningMessageContent => jsonElement.Deserialize(options.GetTypeInfo(typeof(ReasoningMessageContentEvent))) as ReasoningMessageContentEvent,
AGUIEventTypes.ReasoningMessageEnd => jsonElement.Deserialize(options.GetTypeInfo(typeof(ReasoningMessageEndEvent))) as ReasoningMessageEndEvent,
AGUIEventTypes.ReasoningEnd => jsonElement.Deserialize(options.GetTypeInfo(typeof(ReasoningEndEvent))) as ReasoningEndEvent,
AGUIEventTypes.ReasoningMessageChunk => jsonElement.Deserialize(options.GetTypeInfo(typeof(ReasoningMessageChunkEvent))) as ReasoningMessageChunkEvent,
AGUIEventTypes.ReasoningEncryptedValue => jsonElement.Deserialize(options.GetTypeInfo(typeof(ReasoningEncryptedValueEvent))) as ReasoningEncryptedValueEvent,
_ => throw new JsonException($"Unknown BaseEvent type discriminator: '{discriminator}'")
};
@@ -109,27 +102,6 @@ internal sealed class BaseEventJsonConverter : JsonConverter<BaseEvent>
case StateDeltaEvent stateDelta:
JsonSerializer.Serialize(writer, stateDelta, options.GetTypeInfo(typeof(StateDeltaEvent)));
break;
case ReasoningStartEvent reasoningStart:
JsonSerializer.Serialize(writer, reasoningStart, options.GetTypeInfo(typeof(ReasoningStartEvent)));
break;
case ReasoningMessageStartEvent reasoningMessageStart:
JsonSerializer.Serialize(writer, reasoningMessageStart, options.GetTypeInfo(typeof(ReasoningMessageStartEvent)));
break;
case ReasoningMessageContentEvent reasoningMessageContent:
JsonSerializer.Serialize(writer, reasoningMessageContent, options.GetTypeInfo(typeof(ReasoningMessageContentEvent)));
break;
case ReasoningMessageEndEvent reasoningMessageEnd:
JsonSerializer.Serialize(writer, reasoningMessageEnd, options.GetTypeInfo(typeof(ReasoningMessageEndEvent)));
break;
case ReasoningEndEvent reasoningEnd:
JsonSerializer.Serialize(writer, reasoningEnd, options.GetTypeInfo(typeof(ReasoningEndEvent)));
break;
case ReasoningMessageChunkEvent reasoningMessageChunk:
JsonSerializer.Serialize(writer, reasoningMessageChunk, options.GetTypeInfo(typeof(ReasoningMessageChunkEvent)));
break;
case ReasoningEncryptedValueEvent reasoningEncryptedValue:
JsonSerializer.Serialize(writer, reasoningEncryptedValue, options.GetTypeInfo(typeof(ReasoningEncryptedValueEvent)));
break;
default:
throw new InvalidOperationException($"Unknown event type: {value.GetType().Name}");
}
@@ -31,7 +31,6 @@ internal static class ChatResponseUpdateAGUIExtensions
string? responseId = null;
var textMessageBuilder = new TextMessageBuilder();
var toolCallAccumulator = new ToolCallBuilder();
var reasoningBuilder = new ReasoningMessageBuilder();
await foreach (var evt in events.WithCancellation(cancellationToken).ConfigureAwait(false))
{
switch (evt)
@@ -42,7 +41,6 @@ internal static class ChatResponseUpdateAGUIExtensions
responseId = runStarted.RunId;
toolCallAccumulator.SetConversationAndResponseIds(conversationId, responseId);
textMessageBuilder.SetConversationAndResponseIds(conversationId, responseId);
reasoningBuilder.SetConversationAndResponseIds(conversationId, responseId);
yield return ValidateAndEmitRunStart(runStarted);
break;
case RunFinishedEvent runFinished:
@@ -90,36 +88,6 @@ internal static class ChatResponseUpdateAGUIExtensions
yield return CreateStateDeltaUpdate(stateDelta, conversationId, responseId, jsonSerializerOptions);
}
break;
// Reasoning events (explicit lifecycle form)
case ReasoningMessageStartEvent reasoningStart:
reasoningBuilder.AddReasoningStart(reasoningStart);
break;
case ReasoningMessageContentEvent reasoningContent:
yield return reasoningBuilder.EmitReasoningContent(reasoningContent);
break;
case ReasoningMessageEndEvent reasoningEnd:
reasoningBuilder.EndCurrentMessage(reasoningEnd);
break;
// Reasoning events (chunk shorthand form)
case ReasoningMessageChunkEvent reasoningChunk:
var chunkUpdate = reasoningBuilder.EmitReasoningChunk(reasoningChunk);
if (chunkUpdate is not null)
{
yield return chunkUpdate;
}
break;
// Encrypted reasoning value (emitted by either form)
case ReasoningEncryptedValueEvent encryptedValue:
yield return reasoningBuilder.EmitEncryptedValue(encryptedValue);
break;
// ReasoningStartEvent and ReasoningEndEvent are bracket markers only — no content to emit
case ReasoningStartEvent:
case ReasoningEndEvent:
break;
}
}
}
@@ -337,81 +305,6 @@ internal static class ChatResponseUpdateAGUIExtensions
}
}
private sealed class ReasoningMessageBuilder()
{
private string? _currentMessageId;
private string? _conversationId;
private string? _responseId;
public void SetConversationAndResponseIds(string? conversationId, string? responseId)
{
this._conversationId = conversationId;
this._responseId = responseId;
}
public void AddReasoningStart(ReasoningMessageStartEvent reasoningStart)
{
if (this._currentMessageId != null)
{
throw new InvalidOperationException(
"Received ReasoningMessageStartEvent while another message is being processed.");
}
this._currentMessageId = reasoningStart.MessageId;
}
public ChatResponseUpdate EmitReasoningContent(ReasoningMessageContentEvent contentEvent)
{
return new ChatResponseUpdate(ChatRole.Assistant, [new TextReasoningContent(contentEvent.Delta)])
{
ConversationId = this._conversationId,
ResponseId = this._responseId,
MessageId = contentEvent.MessageId,
CreatedAt = DateTimeOffset.UtcNow
};
}
public ChatResponseUpdate? EmitReasoningChunk(ReasoningMessageChunkEvent chunkEvent)
{
if (string.IsNullOrEmpty(chunkEvent.Delta))
{
// Empty delta is the implicit close signal for chunk-based streaming
this._currentMessageId = null;
return null;
}
this._currentMessageId ??= chunkEvent.MessageId;
return new ChatResponseUpdate(ChatRole.Assistant, [new TextReasoningContent(chunkEvent.Delta)])
{
ConversationId = this._conversationId,
ResponseId = this._responseId,
MessageId = chunkEvent.MessageId,
CreatedAt = DateTimeOffset.UtcNow
};
}
public ChatResponseUpdate EmitEncryptedValue(ReasoningEncryptedValueEvent encryptedEvent)
{
return new ChatResponseUpdate(ChatRole.Assistant, [new TextReasoningContent("") { ProtectedData = encryptedEvent.EncryptedValue }])
{
ConversationId = this._conversationId,
ResponseId = this._responseId,
MessageId = encryptedEvent.EntityId,
CreatedAt = DateTimeOffset.UtcNow
};
}
public void EndCurrentMessage(ReasoningMessageEndEvent reasoningEnd)
{
if (!string.Equals(this._currentMessageId, reasoningEnd.MessageId, StringComparison.Ordinal))
{
throw new InvalidOperationException(
"Received ReasoningMessageEndEvent for a different message than the current one.");
}
this._currentMessageId = null;
}
}
private static IDictionary<string, object?>? DeserializeArgumentsIfAvailable(string argsJson, JsonSerializerOptions options)
{
if (!string.IsNullOrEmpty(argsJson))
@@ -449,9 +342,6 @@ internal static class ChatResponseUpdateAGUIExtensions
string? currentMessageId = null;
string? streamingMessageId = null;
string? currentReasoningBaseId = null;
string? currentReasoningId = null;
string? currentReasoningMessageId = null;
await foreach (var chatResponse in updates.WithCancellation(cancellationToken).ConfigureAwait(false))
{
// Generate a fallback MessageId when the provider doesn't supply one.
@@ -466,25 +356,6 @@ internal static class ChatResponseUpdateAGUIExtensions
chatResponse.Contents[0] is TextContent &&
!string.Equals(currentMessageId, chatResponse.MessageId, StringComparison.Ordinal))
{
// Close any open reasoning block before opening a text message, so AG-UI
// events are properly bracketed. MEAI providers share one MessageId across
// reasoning and text content, so the reasoning-block state alone wouldn't
// detect the transition.
if (currentReasoningMessageId is not null)
{
yield return new ReasoningMessageEndEvent
{
MessageId = currentReasoningMessageId
};
yield return new ReasoningEndEvent
{
MessageId = currentReasoningId!
};
currentReasoningBaseId = null;
currentReasoningId = null;
currentReasoningMessageId = null;
}
// End the previous message if there was one
if (currentMessageId is not null)
{
@@ -510,7 +381,7 @@ internal static class ChatResponseUpdateAGUIExtensions
{
yield return new TextMessageContentEvent
{
MessageId = currentMessageId!,
MessageId = chatResponse.MessageId!,
Delta = textContent.Text
};
}
@@ -522,22 +393,6 @@ internal static class ChatResponseUpdateAGUIExtensions
{
if (content is FunctionCallContent functionCallContent)
{
// Close any open reasoning block before emitting tool events.
if (currentReasoningMessageId is not null)
{
yield return new ReasoningMessageEndEvent
{
MessageId = currentReasoningMessageId
};
yield return new ReasoningEndEvent
{
MessageId = currentReasoningId!
};
currentReasoningBaseId = null;
currentReasoningId = null;
currentReasoningMessageId = null;
}
yield return new ToolCallStartEvent
{
ToolCallId = functionCallContent.CallId,
@@ -560,22 +415,6 @@ internal static class ChatResponseUpdateAGUIExtensions
}
else if (content is FunctionResultContent functionResultContent)
{
// Close any open reasoning block before emitting tool result events.
if (currentReasoningMessageId is not null)
{
yield return new ReasoningMessageEndEvent
{
MessageId = currentReasoningMessageId
};
yield return new ReasoningEndEvent
{
MessageId = currentReasoningId!
};
currentReasoningBaseId = null;
currentReasoningId = null;
currentReasoningMessageId = null;
}
yield return new ToolCallResultEvent
{
MessageId = chatResponse.MessageId,
@@ -584,55 +423,6 @@ internal static class ChatResponseUpdateAGUIExtensions
Role = AGUIRoles.Tool
};
}
else if (content is TextReasoningContent reasoningContent
&& (!string.IsNullOrEmpty(reasoningContent.Text) || !string.IsNullOrEmpty(reasoningContent.ProtectedData)))
{
if (!string.Equals(currentReasoningBaseId, chatResponse.MessageId, StringComparison.Ordinal))
{
if (currentReasoningMessageId is not null)
{
yield return new ReasoningMessageEndEvent
{
MessageId = currentReasoningMessageId
};
yield return new ReasoningEndEvent
{
MessageId = currentReasoningId!
};
}
currentReasoningBaseId = chatResponse.MessageId;
currentReasoningId = Guid.NewGuid().ToString("N");
currentReasoningMessageId = Guid.NewGuid().ToString("N");
yield return new ReasoningStartEvent
{
MessageId = currentReasoningId
};
yield return new ReasoningMessageStartEvent
{
MessageId = currentReasoningMessageId
};
}
if (!string.IsNullOrEmpty(reasoningContent.Text))
{
yield return new ReasoningMessageContentEvent
{
MessageId = currentReasoningMessageId!,
Delta = reasoningContent.Text
};
}
if (!string.IsNullOrEmpty(reasoningContent.ProtectedData))
{
yield return new ReasoningEncryptedValueEvent
{
EntityId = currentReasoningMessageId!,
EncryptedValue = reasoningContent.ProtectedData
};
}
}
else if (content is DataContent dataContent)
{
if (MediaTypeHeaderValue.TryParse(dataContent.MediaType, out var mediaType) && mediaType.Equals(s_json))
@@ -686,19 +476,6 @@ internal static class ChatResponseUpdateAGUIExtensions
}
}
// End the last reasoning block if there was one
if (currentReasoningMessageId is not null)
{
yield return new ReasoningMessageEndEvent
{
MessageId = currentReasoningMessageId
};
yield return new ReasoningEndEvent
{
MessageId = currentReasoningId!
};
}
// End the last message if there was one
if (currentMessageId is not null)
{
@@ -1,26 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
#if ASPNETCORE
namespace Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.Shared;
#else
namespace Microsoft.Agents.AI.AGUI.Shared;
#endif
internal sealed class ReasoningEncryptedValueEvent : BaseEvent
{
public ReasoningEncryptedValueEvent()
{
this.Type = AGUIEventTypes.ReasoningEncryptedValue;
}
[JsonPropertyName("subtype")]
public string Subtype { get; set; } = "message";
[JsonPropertyName("entityId")]
public string EntityId { get; set; } = string.Empty;
[JsonPropertyName("encryptedValue")]
public string EncryptedValue { get; set; } = string.Empty;
}
@@ -1,20 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
#if ASPNETCORE
namespace Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.Shared;
#else
namespace Microsoft.Agents.AI.AGUI.Shared;
#endif
internal sealed class ReasoningEndEvent : BaseEvent
{
public ReasoningEndEvent()
{
this.Type = AGUIEventTypes.ReasoningEnd;
}
[JsonPropertyName("messageId")]
public string MessageId { get; set; } = string.Empty;
}
@@ -1,25 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
#if ASPNETCORE
namespace Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.Shared;
#else
namespace Microsoft.Agents.AI.AGUI.Shared;
#endif
internal sealed class ReasoningMessageChunkEvent : BaseEvent
{
public ReasoningMessageChunkEvent()
{
this.Type = AGUIEventTypes.ReasoningMessageChunk;
}
[JsonPropertyName("messageId")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public string? MessageId { get; set; }
[JsonPropertyName("delta")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public string? Delta { get; set; }
}
@@ -1,23 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
#if ASPNETCORE
namespace Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.Shared;
#else
namespace Microsoft.Agents.AI.AGUI.Shared;
#endif
internal sealed class ReasoningMessageContentEvent : BaseEvent
{
public ReasoningMessageContentEvent()
{
this.Type = AGUIEventTypes.ReasoningMessageContent;
}
[JsonPropertyName("messageId")]
public string MessageId { get; set; } = string.Empty;
[JsonPropertyName("delta")]
public string Delta { get; set; } = string.Empty;
}
@@ -1,20 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
#if ASPNETCORE
namespace Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.Shared;
#else
namespace Microsoft.Agents.AI.AGUI.Shared;
#endif
internal sealed class ReasoningMessageEndEvent : BaseEvent
{
public ReasoningMessageEndEvent()
{
this.Type = AGUIEventTypes.ReasoningMessageEnd;
}
[JsonPropertyName("messageId")]
public string MessageId { get; set; } = string.Empty;
}
@@ -1,23 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
#if ASPNETCORE
namespace Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.Shared;
#else
namespace Microsoft.Agents.AI.AGUI.Shared;
#endif
internal sealed class ReasoningMessageStartEvent : BaseEvent
{
public ReasoningMessageStartEvent()
{
this.Type = AGUIEventTypes.ReasoningMessageStart;
}
[JsonPropertyName("messageId")]
public string MessageId { get; set; } = string.Empty;
[JsonPropertyName("role")]
public string Role { get; set; } = AGUIRoles.Reasoning;
}
@@ -1,20 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Text.Json.Serialization;
#if ASPNETCORE
namespace Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.Shared;
#else
namespace Microsoft.Agents.AI.AGUI.Shared;
#endif
internal sealed class ReasoningStartEvent : BaseEvent
{
public ReasoningStartEvent()
{
this.Type = AGUIEventTypes.ReasoningStart;
}
[JsonPropertyName("messageId")]
public string MessageId { get; set; } = string.Empty;
}
@@ -19,7 +19,8 @@ namespace Azure.AI.Projects;
/// Foundry toolbox definitions as server-side tools.
/// </summary>
/// <remarks>
/// Provides a single call on the project client to retrieve tools ready for use
/// These extensions mirror Python's <c>FoundryChatClient.get_toolbox()</c> pattern,
/// allowing a single call on the project client to retrieve tools ready for use
/// with <c>AsAIAgent(model, instructions, tools: ...)</c>.
/// </remarks>
[Experimental(DiagnosticIds.Experiments.AIOpenAIResponses)]
@@ -77,31 +77,23 @@ public class AgentFrameworkResponseHandler : ResponseHandler
// 4. Convert input: history + current input → ChatMessage[]
var messages = new List<ChatMessage>();
// Load conversation history only for fresh sessions. When a session already exists
// (e.g. resuming a workflow paused at an external-input port), the workflow's
// checkpointed state already contains the prior turns' messages — replaying history
// would re-drive completed actions and break HITL resume semantics.
var isResume = !string.IsNullOrWhiteSpace(sessionConversationId)
&& session?.StateBag?.Count > 0;
if (!isResume)
// Load conversation history if available
var history = await context.GetHistoryAsync(cancellationToken).ConfigureAwait(false);
if (history.Count > 0)
{
var history = await context.GetHistoryAsync(cancellationToken).ConfigureAwait(false);
if (history.Count > 0)
{
messages.AddRange(InputConverter.ConvertOutputItemsToMessages(history, session?.StateBag));
}
messages.AddRange(InputConverter.ConvertOutputItemsToMessages(history));
}
// Load and convert current input items
var inputItems = await context.GetInputItemsAsync(cancellationToken: cancellationToken).ConfigureAwait(false);
if (inputItems.Count > 0)
{
messages.AddRange(InputConverter.ConvertItemsToMessages(inputItems, session?.StateBag));
messages.AddRange(InputConverter.ConvertItemsToMessages(inputItems));
}
else
{
// Fall back to raw request input
messages.AddRange(InputConverter.ConvertInputToMessages(request, session?.StateBag));
messages.AddRange(InputConverter.ConvertInputToMessages(request));
}
// 5. Build chat options
@@ -199,7 +191,6 @@ public class AgentFrameworkResponseHandler : ResponseHandler
var enumerator = OutputConverter.ConvertUpdatesToEventsAsync(
agent.RunStreamingAsync(messages, session, options: options, cancellationToken: consentCts.Token),
stream,
session?.StateBag,
cancellationToken).GetAsyncEnumerator(cancellationToken);
try
{
@@ -306,7 +297,6 @@ public class AgentFrameworkResponseHandler : ResponseHandler
var agent = this._serviceProvider.GetKeyedService<AIAgent>(agentName);
if (agent is not null)
{
FoundryHostingExtensions.TryApplyUserAgent(agent);
return FoundryHostingExtensions.ApplyOpenTelemetry(agent);
}
@@ -320,13 +310,12 @@ public class AgentFrameworkResponseHandler : ResponseHandler
var defaultAgent = this._serviceProvider.GetService<AIAgent>();
if (defaultAgent is not null)
{
FoundryHostingExtensions.TryApplyUserAgent(defaultAgent);
return FoundryHostingExtensions.ApplyOpenTelemetry(defaultAgent);
}
var errorMessage = string.IsNullOrEmpty(agentName)
? "No agent name specified in the request (via agent.name or metadata[\"entity_id\"]) and no default AIAgent is registered."
: $"Agent '{agentName}' not found. Ensure it is registered via AddFoundryResponses(services, agent) or services.AddKeyedSingleton<AIAgent>(\"{agentName}\", ...).";
: $"Agent '{agentName}' not found. Ensure it is registered via AddAIAgent(\"{agentName}\", ...) or as a default AIAgent.";
throw new InvalidOperationException(errorMessage);
}
@@ -363,7 +352,7 @@ public class AgentFrameworkResponseHandler : ResponseHandler
var errorMessage = string.IsNullOrEmpty(agentName)
? "No agent name specified in the request (via agent.name or metadata[\"entity_id\"]) and no default AgentSessionStore is registered."
: $"AgentSessionStore for agent '{agentName}' not found. Ensure it is registered via AddFoundryResponses(services, agent, agentSessionStore) or services.AddKeyedSingleton<AgentSessionStore>(\"{agentName}\", ...).";
: $"Agent '{agentName}' not found. Ensure it is registered via AddAIAgent(\"{agentName}\", ...) or as a default AgentSessionStore.";
throw new InvalidOperationException(errorMessage);
}
@@ -1,261 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System;
using System.Buffers;
using System.Diagnostics.CodeAnalysis;
using System.IO;
using System.Linq;
using System.Text.Json;
using System.Threading;
using System.Threading.Tasks;
using Microsoft.Shared.DiagnosticIds;
namespace Microsoft.Agents.AI.Foundry.Hosting;
/// <summary>
/// Provides a file-system backed implementation of <see cref="AgentSessionStore"/> that persists
/// the agent-framework's serialized <see cref="AgentSession"/> state for each (agent, conversation)
/// pair to disk. This complements Foundry storage (which owns conversation messages, agent
/// definitions, and threads) — it is not a replacement for it.
/// </summary>
/// <remarks>
/// <para>
/// The session JSON stored here is the AF runtime's own state (workflow checkpoint manager,
/// pending external requests, internal port state) that is required to resume an
/// <see cref="AgentSession"/> across HTTP requests or process restarts but is not part of
/// Foundry's data model.
/// </para>
/// <para>
/// When running in a Foundry hosted environment, sessions are stored under the well-known
/// <c>/.checkpoints</c> path; locally, they fall under <c>{cwd}/.checkpoints</c>. The session
/// JSON produced when the agent serializes the session already contains the workflow's
/// in-memory checkpoint manager state, so a single file per (agent, conversation) pair is
/// sufficient to resume long-running workflows across process restarts.
/// </para>
/// <para>
/// Files are written atomically via a temp-file + <see cref="File.Move(string, string, bool)"/>
/// rename so a partially-written file cannot be observed by a concurrent reader.
/// </para>
/// </remarks>
[Experimental(DiagnosticIds.Experiments.AIOpenAIResponses)]
public sealed class FileSystemAgentSessionStore : AgentSessionStore
{
/// <summary>
/// The well-known absolute path used when running inside a Foundry hosted environment.
/// </summary>
public const string HostedCheckpointDirectory = "/.checkpoints";
/// <summary>
/// The directory name used under the current working directory when running locally.
/// </summary>
public const string LocalCheckpointDirectoryName = ".checkpoints";
/// <summary>
/// Initializes a new instance of the <see cref="FileSystemAgentSessionStore"/> class
/// that stores serialized sessions under <paramref name="rootDirectory"/>.
/// </summary>
/// <param name="rootDirectory">
/// The absolute or relative directory where session files will be written.
/// The directory is created on first write if it does not already exist.
/// </param>
public FileSystemAgentSessionStore(string rootDirectory)
{
ArgumentException.ThrowIfNullOrWhiteSpace(rootDirectory);
this.RootDirectory = Path.GetFullPath(rootDirectory);
}
/// <summary>
/// Gets the root directory under which session files are written.
/// </summary>
public string RootDirectory { get; }
/// <summary>
/// Creates a <see cref="FileSystemAgentSessionStore"/> rooted at the default location:
/// <see cref="HostedCheckpointDirectory"/> when running in a Foundry hosted environment,
/// otherwise <see cref="LocalCheckpointDirectoryName"/> under the current working directory.
/// </summary>
/// <returns>A new <see cref="FileSystemAgentSessionStore"/> instance.</returns>
public static FileSystemAgentSessionStore CreateDefault()
{
string root = FoundryEnvironment.IsHosted
? HostedCheckpointDirectory
: Path.Combine(Environment.CurrentDirectory, LocalCheckpointDirectoryName);
return new FileSystemAgentSessionStore(root);
}
/// <inheritdoc/>
public override async ValueTask SaveSessionAsync(AIAgent agent, string conversationId, AgentSession session, CancellationToken cancellationToken = default)
{
ArgumentNullException.ThrowIfNull(agent);
ArgumentException.ThrowIfNullOrWhiteSpace(conversationId);
ArgumentNullException.ThrowIfNull(session);
JsonElement serialized = await agent.SerializeSessionAsync(session, cancellationToken: cancellationToken).ConfigureAwait(false);
Directory.CreateDirectory(this.RootDirectory);
string path = this.GetSessionPath(agent, conversationId);
string? parentDir = Path.GetDirectoryName(path);
if (!string.IsNullOrEmpty(parentDir))
{
Directory.CreateDirectory(parentDir);
}
// Each save writes to its own temp file before atomically renaming over the
// destination. Last writer wins for the final file, but no reader can observe
// a torn or partially-written JSON document.
string tempPath = $"{path}.{Guid.NewGuid():N}.tmp";
try
{
using (FileStream stream = new(tempPath, FileMode.Create, FileAccess.Write, FileShare.None))
using (Utf8JsonWriter writer = new(stream))
{
serialized.WriteTo(writer);
}
File.Move(tempPath, path, overwrite: true);
}
catch
{
try { File.Delete(tempPath); } catch { /* best-effort cleanup */ }
throw;
}
}
/// <inheritdoc/>
public override async ValueTask<AgentSession> GetSessionAsync(AIAgent agent, string conversationId, CancellationToken cancellationToken = default)
{
ArgumentNullException.ThrowIfNull(agent);
ArgumentException.ThrowIfNullOrWhiteSpace(conversationId);
string path = this.GetSessionPath(agent, conversationId);
if (!File.Exists(path))
{
return await agent.CreateSessionAsync(cancellationToken).ConfigureAwait(false);
}
byte[] bytes = await File.ReadAllBytesAsync(path, cancellationToken).ConfigureAwait(false);
if (bytes.Length == 0)
{
return await agent.CreateSessionAsync(cancellationToken).ConfigureAwait(false);
}
// Parse and clone so the document buffer can be released.
using JsonDocument document = JsonDocument.Parse(bytes);
JsonElement element = document.RootElement.Clone();
return await agent.DeserializeSessionAsync(element, cancellationToken: cancellationToken).ConfigureAwait(false);
}
private string GetSessionPath(AIAgent agent, string conversationId)
{
// When agent.Name is set we bucket sessions into a per-agent subdirectory so
// multiple keyed agents sharing a single in-process default store cannot
// collide on the same conversationId. agent.Id is intentionally NOT used
// because it is regenerated on every startup for in-memory-defined agents.
string fileName = $"{Sanitize(conversationId)}.json";
if (string.IsNullOrEmpty(agent.Name))
{
return Path.Combine(this.RootDirectory, fileName);
}
string agentDir = Path.Combine(this.RootDirectory, Sanitize(agent.Name!));
return Path.Combine(agentDir, fileName);
}
private static string Sanitize(string value)
{
// Percent-encode every character that is invalid in a filename, plus '%' itself
// so the encoding is unambiguous. This is reversible and avoids the collision
// hazard of a lossy character substitution (e.g. "foo/bar" and "foo_bar" sharing
// a sanitized name).
char[] invalid = Path.GetInvalidFileNameChars();
int encodedLength = ComputeEncodedLength(value, invalid);
// stackalloc is bounded so an externally-controlled length cannot crash the
// hosting process with StackOverflowException.
const int StackLimit = 512;
string sanitized;
if (encodedLength <= StackLimit)
{
Span<char> buffer = stackalloc char[encodedLength];
SanitizeCore(value, invalid, buffer);
sanitized = new string(buffer);
}
else
{
char[] rented = ArrayPool<char>.Shared.Rent(encodedLength);
try
{
Span<char> buffer = rented.AsSpan(0, encodedLength);
SanitizeCore(value, invalid, buffer);
sanitized = new string(buffer);
}
finally
{
ArrayPool<char>.Shared.Return(rented);
}
}
// '.' and '..' are valid filename characters but resolve to current/parent
// directory when used as a bare path component. Windows additionally strips
// trailing dots from filenames, so a segment like "..." would survive on disk
// as "" and a partial-encode like "%2E.." would survive as "%2E". Encode every
// dot in any all-dot segment so the result has no special meaning to the OS.
if (sanitized.Length > 0 && IsAllDots(sanitized))
{
return string.Concat(Enumerable.Repeat("%2E", sanitized.Length));
}
return sanitized;
}
private static int ComputeEncodedLength(string value, char[] invalid)
{
int extra = 0;
for (int i = 0; i < value.Length; i++)
{
char c = value[i];
if (c == '%' || Array.IndexOf(invalid, c) >= 0)
{
extra += 2; // 1 char ('%' or invalid) becomes 3 chars ("%XX")
}
}
return value.Length + extra;
}
private static bool IsAllDots(string value)
{
for (int i = 0; i < value.Length; i++)
{
if (value[i] != '.')
{
return false;
}
}
return true;
}
private static void SanitizeCore(string value, char[] invalid, Span<char> buffer)
{
int j = 0;
for (int i = 0; i < value.Length; i++)
{
char c = value[i];
if (c == '%' || Array.IndexOf(invalid, c) >= 0)
{
buffer[j++] = '%';
buffer[j++] = HexChar((c >> 4) & 0xF);
buffer[j++] = HexChar(c & 0xF);
}
else
{
buffer[j++] = c;
}
}
}
private static char HexChar(int n) => (char)(n < 10 ? '0' + n : 'A' + n - 10);
}
@@ -32,6 +32,9 @@ namespace Microsoft.Agents.AI.Foundry.Hosting;
/// they are sent as server-side tool definitions in the Responses API request. The Foundry platform
/// handles tool execution — the agent process does not invoke tools locally.
/// </para>
/// <para>
/// This is the dotnet equivalent of Python's <c>FoundryChatClient.get_toolbox()</c> pattern.
/// </para>
/// </remarks>
[Experimental(DiagnosticIds.Experiments.AIOpenAIResponses)]
public static class FoundryToolbox
@@ -1,84 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.ClientModel.Primitives;
using System.Collections.Generic;
using System.Reflection;
using System.Threading.Tasks;
using Microsoft.Extensions.AI;
namespace Microsoft.Agents.AI.Foundry.Hosting;
/// <summary>
/// Pipeline policy that appends the hosted-agent <c>User-Agent</c> segment
/// (e.g. <c>"foundry-hosting/agent-framework-dotnet/{version}"</c>) to outgoing requests.
/// </summary>
/// <remarks>
/// <para>
/// The supplement value is computed once from the Microsoft.Agents.AI.Foundry.Hosting
/// assembly's informational version. The policy is idempotent on retries: if the segment
/// is already present in the <c>User-Agent</c> header, the policy does not append it again.
/// </para>
/// <para>
/// This policy is added at hosted-agent resolution time via the MEAI 10.5.1
/// <see cref="OpenAIRequestPolicies"/> hook on the agent's underlying chat client. It is only
/// registered when an agent is resolved by the Foundry hosting layer.
/// </para>
/// </remarks>
internal sealed class HostedAgentUserAgentPolicy : PipelinePolicy
{
public static HostedAgentUserAgentPolicy Instance { get; } = new HostedAgentUserAgentPolicy();
private static readonly string s_supplementValue = CreateSupplementValue();
public override void Process(PipelineMessage message, IReadOnlyList<PipelinePolicy> pipeline, int currentIndex)
{
AppendHeader(message);
ProcessNext(message, pipeline, currentIndex);
}
public override async ValueTask ProcessAsync(PipelineMessage message, IReadOnlyList<PipelinePolicy> pipeline, int currentIndex)
{
AppendHeader(message);
await ProcessNextAsync(message, pipeline, currentIndex).ConfigureAwait(false);
}
private static void AppendHeader(PipelineMessage message)
{
if (message.Request.Headers.TryGetValue("User-Agent", out var existing) && !string.IsNullOrEmpty(existing))
{
// Guard against double-append on retries or when the policy
// is registered on multiple pipeline positions.
if (existing.Contains(s_supplementValue))
{
return;
}
message.Request.Headers.Set("User-Agent", $"{existing} {s_supplementValue}");
}
else
{
message.Request.Headers.Set("User-Agent", s_supplementValue);
}
}
private static string CreateSupplementValue()
{
const string Name = "foundry-hosting/agent-framework-dotnet";
if (typeof(HostedAgentUserAgentPolicy).Assembly.GetCustomAttribute<AssemblyInformationalVersionAttribute>()?.InformationalVersion is string version)
{
int pos = version.IndexOf('+');
if (pos >= 0)
{
version = version.Substring(0, pos);
}
if (version.Length > 0)
{
return $"{Name}/{version}";
}
}
return Name;
}
}
@@ -3,12 +3,10 @@
using System;
using System.Collections.Generic;
using System.Diagnostics.CodeAnalysis;
using System.Text;
using System.Text.Json;
using Azure.AI.AgentServer.Responses.Models;
using Microsoft.Extensions.AI;
using MeaiTextContent = Microsoft.Extensions.AI.TextContent;
using SdkTextContent = Azure.AI.AgentServer.Responses.Models.TextContent;
namespace Microsoft.Agents.AI.Foundry.Hosting;
@@ -21,15 +19,14 @@ internal static class InputConverter
/// Converts the SDK <see cref="CreateResponse"/> request input items into a list of <see cref="ChatMessage"/>.
/// </summary>
/// <param name="request">The create response request from the SDK.</param>
/// <param name="stateBag">Optional session state bag carrying the tool-approval id mapping.</param>
/// <returns>A list of chat messages representing the request input.</returns>
public static List<ChatMessage> ConvertInputToMessages(CreateResponse request, AgentSessionStateBag? stateBag = null)
public static List<ChatMessage> ConvertInputToMessages(CreateResponse request)
{
var messages = new List<ChatMessage>();
foreach (var item in request.GetInputExpanded())
{
var message = ConvertInputItemToMessage(item, stateBag);
var message = ConvertInputItemToMessage(item);
if (message is not null)
{
messages.Add(message);
@@ -43,15 +40,14 @@ internal static class InputConverter
/// Converts resolved SDK <see cref="Item"/> input items into <see cref="ChatMessage"/> instances.
/// </summary>
/// <param name="items">The resolved input items from the SDK context.</param>
/// <param name="stateBag">Optional session state bag carrying the tool-approval id mapping.</param>
/// <returns>A list of chat messages.</returns>
public static List<ChatMessage> ConvertItemsToMessages(IReadOnlyList<Item> items, AgentSessionStateBag? stateBag = null)
public static List<ChatMessage> ConvertItemsToMessages(IReadOnlyList<Item> items)
{
var messages = new List<ChatMessage>();
foreach (var item in items)
{
var message = ConvertInputItemToMessage(item, stateBag);
var message = ConvertInputItemToMessage(item);
if (message is not null)
{
messages.Add(message);
@@ -65,15 +61,14 @@ internal static class InputConverter
/// Converts resolved SDK <see cref="OutputItem"/> history/input items into <see cref="ChatMessage"/> instances.
/// </summary>
/// <param name="items">The resolved output items from the SDK context.</param>
/// <param name="stateBag">Optional session state bag carrying the tool-approval id mapping.</param>
/// <returns>A list of chat messages.</returns>
public static List<ChatMessage> ConvertOutputItemsToMessages(IReadOnlyList<OutputItem> items, AgentSessionStateBag? stateBag = null)
public static List<ChatMessage> ConvertOutputItemsToMessages(IReadOnlyList<OutputItem> items)
{
var messages = new List<ChatMessage>();
foreach (var item in items)
{
var message = ConvertOutputItemToMessage(item, stateBag);
var message = ConvertOutputItemToMessage(item);
if (message is not null)
{
messages.Add(message);
@@ -133,15 +128,13 @@ internal static class InputConverter
return markers;
}
private static ChatMessage? ConvertInputItemToMessage(Item item, AgentSessionStateBag? stateBag)
private static ChatMessage? ConvertInputItemToMessage(Item item)
{
return item switch
{
ItemMessage msg => ConvertItemMessage(msg),
FunctionCallOutputItemParam funcOutput => ConvertFunctionCallOutput(funcOutput),
ItemFunctionToolCall funcCall => ConvertItemFunctionToolCall(funcCall),
ItemMcpApprovalRequest approvalRequest => ConvertMcpApprovalRequest(approvalRequest.Id, approvalRequest.Name, approvalRequest.Arguments),
MCPApprovalResponse approvalResponse => ConvertMcpApprovalResponse(approvalResponse.ApprovalRequestId, approvalResponse.Approve, stateBag),
ItemReferenceParam => null,
_ => null
};
@@ -159,23 +152,43 @@ internal static class InputConverter
case MessageContentInputTextContent textContent:
contents.Add(new MeaiTextContent(textContent.Text));
break;
case SdkTextContent textContent:
contents.Add(new MeaiTextContent(textContent.Text));
break;
case SummaryTextContent summary:
contents.Add(new MeaiTextContent(summary.Text));
break;
case MessageContentReasoningTextContent reasoning:
contents.Add(new TextReasoningContent(reasoning.Text));
break;
case MessageContentInputImageContent imageContent:
AppendImageContent(contents, imageContent.ImageUrl, imageContent.FileId);
if (imageContent.ImageUrl is not null)
{
var url = imageContent.ImageUrl.ToString();
if (url.StartsWith("data:", StringComparison.OrdinalIgnoreCase))
{
contents.Add(new DataContent(url, "image/*"));
}
else
{
contents.Add(new UriContent(imageContent.ImageUrl, "image/*"));
}
}
else if (!string.IsNullOrEmpty(imageContent.FileId))
{
contents.Add(new HostedFileContent(imageContent.FileId));
}
break;
case MessageContentInputFileContent fileContent:
AppendFileContent(contents, fileContent.FileUrl, fileContent.FileData, fileContent.FileId, fileContent.Filename);
break;
case ComputerScreenshotContent screenshot:
AppendImageContent(contents, screenshot.ImageUrl, screenshot.FileId);
if (fileContent.FileUrl is not null)
{
contents.Add(new UriContent(fileContent.FileUrl, "application/octet-stream"));
}
else if (!string.IsNullOrEmpty(fileContent.FileData))
{
contents.Add(new DataContent(fileContent.FileData, "application/octet-stream"));
}
else if (!string.IsNullOrEmpty(fileContent.FileId))
{
contents.Add(new HostedFileContent(fileContent.FileId));
}
else if (!string.IsNullOrEmpty(fileContent.Filename))
{
contents.Add(new MeaiTextContent($"[File: {fileContent.Filename}]"));
}
break;
}
}
@@ -218,73 +231,13 @@ internal static class InputConverter
[new FunctionCallContent(funcCall.CallId, funcCall.Name, arguments)]);
}
/// <summary>
/// Converts an inbound <c>mcp_approval_request</c> wire item (from history replay
/// or fresh-input) to a <see cref="ToolApprovalRequestContent"/> wrapping a
/// <see cref="FunctionCallContent"/>.
/// </summary>
private static ChatMessage ConvertMcpApprovalRequest(string id, string name, string? arguments)
{
var functionCall = new FunctionCallContent(id, name, ParseFunctionArgumentsObject(arguments));
return new ChatMessage(
ChatRole.Assistant,
[new ToolApprovalRequestContent(id, functionCall)]);
}
/// <summary>
/// Converts an inbound <c>mcp_approval_response</c> wire item to a
/// <see cref="ToolApprovalResponseContent"/>. Looks up the original
/// <see cref="FunctionCallContent"/> via <see cref="ToolApprovalIdMap"/> so the
/// reconstructed response carries the original tool name, call id, and arguments.
/// </summary>
/// <exception cref="InvalidOperationException">
/// Thrown when no mapping is recorded for <paramref name="approvalRequestId"/>.
/// Without the mapping the original call cannot be reconstructed, so we fail the request.
/// </exception>
private static ChatMessage ConvertMcpApprovalResponse(string approvalRequestId, bool approve, AgentSessionStateBag? stateBag)
{
var entry = ToolApprovalIdMap.ResolveEntry(stateBag, approvalRequestId)
?? throw new InvalidOperationException(
$"No approval mapping recorded for wire id '{approvalRequestId}'.");
var functionCall = new FunctionCallContent(
entry.CallId,
entry.Name,
ParseFunctionArgumentsObject(entry.Arguments));
return new ChatMessage(
ChatRole.User,
[new ToolApprovalResponseContent(entry.AfRequestId, approve, functionCall)]);
}
[UnconditionalSuppressMessage("Trimming", "IL2026", Justification = "Deserializing tool-call arguments from SDK input.")]
[UnconditionalSuppressMessage("AOT", "IL3050", Justification = "Deserializing tool-call arguments from SDK input.")]
private static Dictionary<string, object?>? ParseFunctionArgumentsObject(string? arguments)
{
if (string.IsNullOrWhiteSpace(arguments))
{
return null;
}
try
{
return JsonSerializer.Deserialize<Dictionary<string, object?>>(arguments);
}
catch (JsonException)
{
return new Dictionary<string, object?> { ["_raw"] = arguments };
}
}
private static ChatMessage? ConvertOutputItemToMessage(OutputItem item, AgentSessionStateBag? stateBag)
private static ChatMessage? ConvertOutputItemToMessage(OutputItem item)
{
return item switch
{
OutputItemMessage msg => ConvertOutputItemMessageToChat(msg),
OutputItemFunctionToolCall funcCall => ConvertOutputItemFunctionCall(funcCall),
OutputItemFunctionToolCallOutput funcOutput => ConvertFunctionToolCallOutput(funcOutput),
OutputItemMcpApprovalRequest approvalRequest => ConvertMcpApprovalRequest(approvalRequest.Id, approvalRequest.Name, approvalRequest.Arguments),
OutputItemMcpApprovalResponseResource approvalResponse => ConvertMcpApprovalResponse(approvalResponse.ApprovalRequestId, approvalResponse.Approve, stateBag),
OutputItemReasoningItem => null,
_ => null
};
@@ -305,26 +258,46 @@ internal static class InputConverter
case MessageContentOutputTextContent textContent:
contents.Add(new MeaiTextContent(textContent.Text));
break;
case SdkTextContent textContent:
contents.Add(new MeaiTextContent(textContent.Text));
break;
case SummaryTextContent summary:
contents.Add(new MeaiTextContent(summary.Text));
break;
case MessageContentReasoningTextContent reasoning:
contents.Add(new TextReasoningContent(reasoning.Text));
break;
case MessageContentRefusalContent refusal:
contents.Add(new MeaiTextContent($"[Refusal: {refusal.Refusal}]"));
break;
case MessageContentInputImageContent imageContent:
AppendImageContent(contents, imageContent.ImageUrl, imageContent.FileId);
if (imageContent.ImageUrl is not null)
{
var url = imageContent.ImageUrl.ToString();
if (url.StartsWith("data:", StringComparison.OrdinalIgnoreCase))
{
contents.Add(new DataContent(url, "image/*"));
}
else
{
contents.Add(new UriContent(imageContent.ImageUrl, "image/*"));
}
}
else if (!string.IsNullOrEmpty(imageContent.FileId))
{
contents.Add(new HostedFileContent(imageContent.FileId));
}
break;
case MessageContentInputFileContent fileContent:
AppendFileContent(contents, fileContent.FileUrl, fileContent.FileData, fileContent.FileId, fileContent.Filename);
break;
case ComputerScreenshotContent screenshot:
AppendImageContent(contents, screenshot.ImageUrl, screenshot.FileId);
if (fileContent.FileUrl is not null)
{
contents.Add(new UriContent(fileContent.FileUrl, "application/octet-stream"));
}
else if (!string.IsNullOrEmpty(fileContent.FileData))
{
contents.Add(new DataContent(fileContent.FileData, "application/octet-stream"));
}
else if (!string.IsNullOrEmpty(fileContent.FileId))
{
contents.Add(new HostedFileContent(fileContent.FileId));
}
else if (!string.IsNullOrEmpty(fileContent.Filename))
{
contents.Add(new MeaiTextContent($"[File: {fileContent.Filename}]"));
}
break;
}
}
@@ -337,127 +310,6 @@ internal static class InputConverter
return new ChatMessage(role, contents);
}
private static void AppendImageContent(List<AIContent> contents, Uri? imageUrl, string? fileId)
{
if (imageUrl is not null)
{
var url = imageUrl.ToString();
if (url.StartsWith("data:", StringComparison.OrdinalIgnoreCase))
{
contents.Add(new DataContent(url, "image/*"));
}
else
{
contents.Add(new UriContent(imageUrl, "image/*"));
}
}
else if (!string.IsNullOrEmpty(fileId))
{
contents.Add(new HostedFileContent(fileId));
}
}
private static void AppendFileContent(List<AIContent> contents, Uri? fileUrl, string? fileData, string? fileId, string? filename)
{
if (fileUrl is not null)
{
var content = new UriContent(fileUrl, "application/octet-stream");
if (!string.IsNullOrEmpty(filename))
{
content.AdditionalProperties = new AdditionalPropertiesDictionary { ["filename"] = filename };
}
contents.Add(content);
return;
}
if (!string.IsNullOrEmpty(fileData))
{
// If the data URI carries text/* content, decode it inline as TextContent so
// {System.LastMessageText} (and other text-only consumers) sees the file's
// body rather than an opaque blob.
if (TryDecodeTextDataUri(fileData, filename, out var decodedText))
{
contents.Add(new MeaiTextContent(decodedText));
}
else
{
var dataContent = new DataContent(fileData, "application/octet-stream");
if (!string.IsNullOrEmpty(filename))
{
dataContent.AdditionalProperties = new AdditionalPropertiesDictionary { ["filename"] = filename };
}
contents.Add(dataContent);
}
return;
}
if (!string.IsNullOrEmpty(fileId))
{
var hosted = new HostedFileContent(fileId);
if (!string.IsNullOrEmpty(filename))
{
hosted.AdditionalProperties = new AdditionalPropertiesDictionary { ["filename"] = filename };
}
contents.Add(hosted);
return;
}
if (!string.IsNullOrEmpty(filename))
{
contents.Add(new MeaiTextContent($"[File: {filename}]"));
}
}
private static bool TryDecodeTextDataUri(string dataUri, string? filename, out string text)
{
// Cap the encoded payload so an oversized client-supplied data URI cannot
// trigger an unbounded allocation in Convert.FromBase64String. 16 MiB
// encoded → ~12 MiB decoded, well above any realistic text/* file we'd
// want to inline as content while still bounding the worst case.
const int MaxEncodedLength = 16 * 1024 * 1024;
text = string.Empty;
if (!dataUri.StartsWith("data:", StringComparison.OrdinalIgnoreCase))
{
return false;
}
const string Marker = ";base64,";
int markerIndex = dataUri.IndexOf(Marker, StringComparison.OrdinalIgnoreCase);
if (markerIndex < 0)
{
return false;
}
string mediaType = dataUri.Substring("data:".Length, markerIndex - "data:".Length);
if (!mediaType.StartsWith("text/", StringComparison.OrdinalIgnoreCase))
{
return false;
}
string encoded = dataUri.Substring(markerIndex + Marker.Length);
if (encoded.Length > MaxEncodedLength)
{
return false;
}
try
{
byte[] bytes = Convert.FromBase64String(encoded);
string decoded = Encoding.UTF8.GetString(bytes);
text = string.IsNullOrEmpty(filename) ? decoded : $"[File: {filename}]\n{decoded}";
return true;
}
catch (FormatException)
{
return false;
}
catch (DecoderFallbackException)
{
return false;
}
}
[UnconditionalSuppressMessage("Trimming", "IL2026", Justification = "Deserializing function call arguments from SDK output history.")]
[UnconditionalSuppressMessage("AOT", "IL3050", Justification = "Deserializing function call arguments from SDK output history.")]
private static ChatMessage ConvertOutputItemFunctionCall(OutputItemFunctionToolCall funcCall)
@@ -44,7 +44,7 @@
</ItemGroup>
<ItemGroup>
<InternalsVisibleTo Include="Microsoft.Agents.AI.Foundry.Hosting.UnitTests" />
<InternalsVisibleTo Include="Microsoft.Agents.AI.Foundry.UnitTests" />
<InternalsVisibleTo Include="DynamicProxyGenAssembly2" />
</ItemGroup>
@@ -30,7 +30,6 @@ internal static class OutputConverter
/// </summary>
/// <param name="updates">The agent response updates to convert.</param>
/// <param name="stream">The SDK event stream builder.</param>
/// <param name="stateBag">Optional session state bag used to persist tool-approval id mappings across turns.</param>
/// <param name="cancellationToken">Cancellation token.</param>
/// <returns>An async enumerable of SDK response stream events (excluding lifecycle events).</returns>
[UnconditionalSuppressMessage("Trimming", "IL2026", Justification = "Serializing function call arguments dictionary.")]
@@ -38,7 +37,6 @@ internal static class OutputConverter
public static async IAsyncEnumerable<ResponseStreamEvent> ConvertUpdatesToEventsAsync(
IAsyncEnumerable<AgentResponseUpdate> updates,
ResponseEventStream stream,
AgentSessionStateBag? stateBag = null,
[EnumeratorCancellation] CancellationToken cancellationToken = default)
{
ResponseUsage? accumulatedUsage = null;
@@ -53,11 +51,8 @@ internal static class OutputConverter
{
cancellationToken.ThrowIfCancellationRequested();
// Handle workflow events from RawRepresentation.
// If the update also carries Contents (e.g. WorkflowSession unwrapped a
// WorkflowErrorEvent or ExecutorFailedEvent into an ErrorContent payload),
// fall through to the content-processing path below so those are emitted.
if (update.RawRepresentation is WorkflowEvent workflowEvent && update.Contents.Count == 0)
// Handle workflow events from RawRepresentation
if (update.RawRepresentation is WorkflowEvent workflowEvent)
{
// Close any open message builder before emitting workflow items
foreach (var evt in CloseCurrentMessage(currentMessageBuilder, currentTextBuilder, accumulatedText))
@@ -118,13 +113,8 @@ internal static class OutputConverter
break;
}
case FunctionCallContent functionCall:
case FunctionCallContent funcCall:
{
if (functionCall.CallId is not { Length: > 0 })
{
break;
}
foreach (var evt in CloseCurrentMessage(currentMessageBuilder, currentTextBuilder, accumulatedText))
{
yield return evt;
@@ -135,15 +125,17 @@ internal static class OutputConverter
accumulatedText = null;
previousMessageId = null;
var arguments = functionCall.Arguments is not null
? JsonSerializer.Serialize(functionCall.Arguments)
var callId = funcCall.CallId ?? Guid.NewGuid().ToString("N");
var funcBuilder = stream.AddOutputItemFunctionCall(funcCall.Name, callId);
yield return funcBuilder.EmitAdded();
var arguments = funcCall.Arguments is not null
? JsonSerializer.Serialize(funcCall.Arguments)
: "{}";
var fcBuilder = stream.AddOutputItemFunctionCall(functionCall.Name, functionCall.CallId);
yield return fcBuilder.EmitAdded();
yield return fcBuilder.EmitArgumentsDelta(arguments);
yield return fcBuilder.EmitArgumentsDone(arguments);
yield return fcBuilder.EmitDone();
yield return funcBuilder.EmitArgumentsDelta(arguments);
yield return funcBuilder.EmitArgumentsDone(arguments);
yield return funcBuilder.EmitDone();
break;
}
@@ -174,61 +166,6 @@ internal static class OutputConverter
break;
}
case ToolApprovalRequestContent approvalRequest when approvalRequest.ToolCall is FunctionCallContent approvalFunctionCall:
{
foreach (var evt in CloseCurrentMessage(currentMessageBuilder, currentTextBuilder, accumulatedText))
{
yield return evt;
}
currentTextBuilder = null;
currentMessageBuilder = null;
accumulatedText = null;
previousMessageId = null;
// The Responses API only standardizes the MCP-flavored approval primitive.
// We emit the AF tool-approval request as `mcp_approval_request` with
// server_label="agent_framework" — declaring the AF runtime as the virtual
// server holding this call. The SDK requires a strict {prefix}_{50hex}
// wire-id format, so we hash the AF RequestId and persist the
// wireId↔afRequestId mapping in the session state bag for later lookup
// when the matching `mcp_approval_response` arrives on a subsequent turn.
var wireId = ToolApprovalIdMap.ComputeWireId(approvalRequest.RequestId);
var approvalArguments = approvalFunctionCall.Arguments is not null
? JsonSerializer.Serialize(approvalFunctionCall.Arguments)
: "{}";
ToolApprovalIdMap.Record(
stateBag,
wireId,
approvalRequest.RequestId,
approvalFunctionCall.CallId,
approvalFunctionCall.Name,
approvalArguments);
var approvalItem = new OutputItemMcpApprovalRequest(
wireId,
"agent_framework",
approvalFunctionCall.Name,
approvalArguments);
var approvalBuilder = stream.AddOutputItem<OutputItemMcpApprovalRequest>(wireId);
yield return approvalBuilder.EmitAdded(approvalItem);
yield return approvalBuilder.EmitDone(approvalItem);
break;
}
case ToolApprovalRequestContent:
// Approval requests must wrap a FunctionCallContent (handled above).
// Any other shape has no representation in the Responses wire format.
break;
case ToolApprovalResponseContent:
// Approval responses originate from the client and travel inbound; the
// workflow does not re-emit them. Skip silently if encountered.
break;
case UsageContent usageContent when usageContent.Details is not null:
{
accumulatedUsage = ConvertUsage(usageContent.Details, accumulatedUsage);
@@ -262,40 +199,10 @@ internal static class OutputConverter
// These would need to be serialized as base64 or URL references.
break;
case FunctionResultContent functionResult:
{
if (functionResult.CallId is not { Length: > 0 })
{
break;
}
foreach (var evt in CloseCurrentMessage(currentMessageBuilder, currentTextBuilder, accumulatedText))
{
yield return evt;
}
currentTextBuilder = null;
currentMessageBuilder = null;
accumulatedText = null;
previousMessageId = null;
var outputText = functionResult.Result switch
{
null => string.Empty,
string s => s,
_ => JsonSerializer.Serialize(functionResult.Result),
};
var itemId = GenerateItemId("fc");
var outputItem = new OutputItemFunctionToolCallOutput(
functionResult.CallId,
BinaryData.FromString(outputText));
var outputBuilder = stream.AddOutputItem<OutputItemFunctionToolCallOutput>(itemId);
yield return outputBuilder.EmitAdded(outputItem);
yield return outputBuilder.EmitDone(outputItem);
case FunctionResultContent:
// Function results are internal to the agent's tool-calling loop
// and are not emitted as output items in the response stream.
break;
}
default:
break;
@@ -1,14 +1,15 @@
// Copyright (c) Microsoft. All rights reserved.
using System;
using System.ClientModel.Primitives;
using System.Diagnostics.CodeAnalysis;
using System.Runtime.CompilerServices;
using System.Reflection;
using System.Threading.Tasks;
using Azure.AI.AgentServer.Responses;
using Azure.Core;
using Azure.Identity;
using Microsoft.AspNetCore.Builder;
using Microsoft.AspNetCore.Http;
using Microsoft.AspNetCore.Routing;
using Microsoft.Extensions.AI;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.DependencyInjection.Extensions;
using Microsoft.Shared.DiagnosticIds;
@@ -35,7 +36,7 @@ public static class FoundryHostingExtensions
/// <para>
/// Example:
/// <code>
/// builder.Services.AddKeyedSingleton&lt;AIAgent&gt;("my-agent", myAgent);
/// builder.AddAIAgent("my-agent", ...);
/// builder.Services.AddFoundryResponses();
///
/// var app = builder.Build();
@@ -49,7 +50,7 @@ public static class FoundryHostingExtensions
{
ArgumentNullException.ThrowIfNull(services);
services.AddResponsesServer();
services.TryAddSingleton<AgentSessionStore>(_ => FileSystemAgentSessionStore.CreateDefault());
services.TryAddSingleton<AgentSessionStore, InMemoryAgentSessionStore>();
services.TryAddSingleton<ResponseHandler, AgentFrameworkResponseHandler>();
return services;
}
@@ -76,7 +77,7 @@ public static class FoundryHostingExtensions
/// </remarks>
/// <param name="services">The service collection.</param>
/// <param name="agent">The agent instance to register.</param>
/// <param name="agentSessionStore">The agent session store to use for managing agent sessions server-side. If null, a file-system session store is used, rooted at <c>/.checkpoints</c> when running in a Foundry hosted environment and <c>{cwd}/.checkpoints</c> locally.</param>
/// <param name="agentSessionStore">The agent session store to use for managing agent sessions server-side. If null, an in-memory session store will be used.</param>
/// <returns>The service collection for chaining.</returns>
public static IServiceCollection AddFoundryResponses(this IServiceCollection services, AIAgent agent, AgentSessionStore? agentSessionStore = null)
{
@@ -84,7 +85,7 @@ public static class FoundryHostingExtensions
ArgumentNullException.ThrowIfNull(agent);
services.AddResponsesServer();
agentSessionStore ??= FileSystemAgentSessionStore.CreateDefault();
agentSessionStore ??= new InMemoryAgentSessionStore();
if (!string.IsNullOrWhiteSpace(agent.Name))
{
@@ -180,11 +181,20 @@ public static class FoundryHostingExtensions
{
ArgumentNullException.ThrowIfNull(endpoints);
endpoints.MapResponsesServer(prefix);
if (endpoints is IApplicationBuilder app)
{
// Ensure the middleware is added to the pipeline
app.UseMiddleware<AgentFrameworkUserAgentMiddleware>();
}
return endpoints;
}
/// <summary>
/// The ActivitySource name for the Responses hosting pipeline.
/// Matches the value previously exposed by <c>AgentHostTelemetry.ResponsesSourceName</c>
/// in <c>Azure.AI.AgentServer.Core</c>.
/// </summary>
private const string ResponsesSourceName = "Azure.AI.AgentServer.Responses";
@@ -206,46 +216,46 @@ public static class FoundryHostingExtensions
.Build();
}
/// <summary>
/// Registers the hosted-agent <c>User-Agent</c> supplement policy
/// (<see cref="HostedAgentUserAgentPolicy"/>) on the agent's underlying chat client via the
/// MEAI 10.5.1 <see cref="OpenAIRequestPolicies"/> hook so every outgoing OpenAI Responses
/// request carries the segment <c>foundry-hosting/agent-framework-dotnet/{version}</c>.
/// </summary>
/// <remarks>
/// <para>
/// Best-effort and idempotent. The method is a no-op when:
/// <list type="bullet">
/// <item><description><paramref name="agent"/> exposes no <see cref="IChatClient"/>;</description></item>
/// <item><description>the chat client is not OpenAI-backed (the <see cref="OpenAIRequestPolicies"/> service lookup returns <see langword="null"/>);</description></item>
/// <item><description>the policy was already registered on this client by a prior invocation (deduped via reflection on <c>OpenAIRequestPolicies._entries</c>).</description></item>
/// </list>
/// </para>
/// <para>
/// Returns the same <paramref name="agent"/> instance unchanged. The policy is installed
/// on the chat client; the agent itself is not wrapped.
/// </para>
/// </remarks>
internal static AIAgent TryApplyUserAgent(AIAgent agent)
private sealed class AgentFrameworkUserAgentMiddleware(RequestDelegate next)
{
var chatClient = agent.GetService<IChatClient>();
if (chatClient?.GetService<OpenAIRequestPolicies>() is { } policies)
private static readonly string s_userAgentValue = CreateUserAgentValue();
public async Task InvokeAsync(HttpContext context)
{
// Hosted agents are typically singletons resolved per request, so AddPolicy must be
// called at most once per OpenAIRequestPolicies instance to avoid unbounded growth of
// the policy list (each entry adds per-request CPU work even though the User-Agent
// value stays stable). Track which instances we have already wired with a
// ConditionalWeakTable keyed on the OpenAIRequestPolicies reference; the table holds
// weak references so it does not extend the lifetime of the chat client.
if (s_userAgentRegistrations.TryAdd(policies, s_boxedTrue))
var headers = context.Request.Headers;
var userAgent = headers.UserAgent.ToString();
if (string.IsNullOrEmpty(userAgent))
{
policies.AddPolicy(HostedAgentUserAgentPolicy.Instance, PipelinePosition.PerCall);
headers.UserAgent = s_userAgentValue;
}
else if (!userAgent.Contains(s_userAgentValue, StringComparison.OrdinalIgnoreCase))
{
headers.UserAgent = $"{userAgent} {s_userAgentValue}";
}
await next(context).ConfigureAwait(false);
}
return agent;
}
private static string CreateUserAgentValue()
{
const string Name = "agent-framework-dotnet";
private static readonly object s_boxedTrue = new();
private static readonly ConditionalWeakTable<OpenAIRequestPolicies, object> s_userAgentRegistrations = new();
if (typeof(AgentFrameworkUserAgentMiddleware).Assembly.GetCustomAttribute<AssemblyInformationalVersionAttribute>()?.InformationalVersion is string version)
{
int pos = version.IndexOf('+');
if (pos >= 0)
{
version = version.Substring(0, pos);
}
if (version.Length > 0)
{
return $"{Name}/{version}";
}
}
return Name;
}
}
}
@@ -1,139 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System;
using System.Collections.Generic;
using System.Security.Cryptography;
using System.Text;
using Microsoft.Extensions.AI;
namespace Microsoft.Agents.AI.Foundry.Hosting;
/// <summary>
/// Helper for translating between agent-framework tool-approval request ids and the
/// strict-format wire ids required by the Responses Server SDK <c>mcp_approval_request</c>
/// item type, and for preserving the original <see cref="FunctionCallContent"/> across
/// the request/response round trip. The mapping is persisted in
/// <see cref="AgentSessionStateBag"/>.
/// </summary>
internal static class ToolApprovalIdMap
{
/// <summary>
/// State-bag key used to store the wire-id ↔ approval-entry mapping.
/// </summary>
public const string StateBagKey = "Microsoft.Agents.AI.Foundry.Hosting.ToolApprovalIdMap";
/// <summary>
/// Captures the data needed to reconstruct the original
/// <see cref="FunctionCallContent"/> on the inbound (response) side.
/// </summary>
/// <remarks>
/// FICC composes <c>RequestId</c> as <c>"ficc_{CallId}"</c>; <c>CallId</c> is stored
/// independently so the reconstructed function-call id matches the one the model
/// emitted and the backend Conversations API persisted.
/// </remarks>
internal sealed class ApprovalEntry
{
public string AfRequestId { get; set; } = string.Empty;
public string CallId { get; set; } = string.Empty;
public string Name { get; set; } = string.Empty;
public string? Arguments { get; set; }
}
/// <summary>
/// SDK item-id format constraints: <c>{prefix}_{50_or_48_chars}</c>. We use the
/// canonical <c>mcpr_</c> prefix and a SHA-256 truncated to 50 hex chars (25 bytes)
/// for deterministic, format-safe wire ids.
/// </summary>
public static string ComputeWireId(string afRequestId)
{
ArgumentNullException.ThrowIfNull(afRequestId);
#if NET10_0_OR_GREATER
Span<byte> hash = stackalloc byte[32];
SHA256.HashData(Encoding.UTF8.GetBytes(afRequestId), hash);
#else
byte[] hash = SHA256.HashData(Encoding.UTF8.GetBytes(afRequestId));
#endif
// 25 bytes = 50 hex chars (matches SDK body length 50).
return "mcpr_" + Convert.ToHexString(hash).AsSpan(0, 50).ToString();
}
/// <summary>
/// Records the wire-id → approval-entry mapping in the supplied state bag.
/// Arguments are passed as already-serialized JSON to keep this method
/// trim/AOT-friendly (no polymorphic <c>object</c> serialization here).
/// No-op when <paramref name="callId"/> or <paramref name="name"/> is empty —
/// without those fields the entry cannot be used to faithfully reconstruct
/// the original <see cref="FunctionCallContent"/> on the inbound side.
/// </summary>
public static void Record(AgentSessionStateBag? stateBag, string wireId, string afRequestId, string? callId, string? name, string? argumentsJson)
{
if (stateBag is null)
{
return;
}
if (string.IsNullOrEmpty(callId) || string.IsNullOrEmpty(name))
{
return;
}
var map = LoadMap(stateBag);
map[wireId] = new ApprovalEntry
{
AfRequestId = afRequestId,
CallId = callId!,
Name = name!,
Arguments = argumentsJson,
};
stateBag.SetValue(StateBagKey, map);
}
/// <summary>
/// Looks up the AF request id for a given wire id. Returns the wire id verbatim
/// when no mapping is present.
/// </summary>
public static string Resolve(AgentSessionStateBag? stateBag, string wireId)
{
if (TryLoadMap(stateBag, out var map)
&& map.TryGetValue(wireId, out var entry))
{
return entry.AfRequestId;
}
return wireId;
}
/// <summary>
/// Looks up the full approval entry for a given wire id, or <see langword="null"/>
/// when no mapping is present.
/// </summary>
public static ApprovalEntry? ResolveEntry(AgentSessionStateBag? stateBag, string wireId)
{
if (TryLoadMap(stateBag, out var map)
&& map.TryGetValue(wireId, out var entry))
{
return entry;
}
return null;
}
private static Dictionary<string, ApprovalEntry> LoadMap(AgentSessionStateBag stateBag)
=> TryLoadMap(stateBag, out var map) ? map : new Dictionary<string, ApprovalEntry>(StringComparer.Ordinal);
private static bool TryLoadMap(AgentSessionStateBag? stateBag, out Dictionary<string, ApprovalEntry> map)
{
if (stateBag is null)
{
map = null!;
return false;
}
// Don't swallow JsonException: ConvertMcpApprovalResponse fails fast on a missing entry,
// so an empty map here would just turn a clear deserialization error into a confusing one.
map = stateBag.GetValue<Dictionary<string, ApprovalEntry>>(StateBagKey)
?? new Dictionary<string, ApprovalEntry>(StringComparer.Ordinal);
return true;
}
}
@@ -1,103 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using System.Threading;
using System.Threading.Tasks;
using Microsoft.Extensions.AI;
namespace Microsoft.Agents.AI.Foundry;
/// <summary>
/// Delegating <see cref="AIAgent"/> that captures any <c>x-client-*</c> headers stored on
/// <see cref="ChatClientAgentRunOptions.ChatOptions"/> by callers of
/// <see cref="ClientHeadersExtensions.WithClientHeader(ChatOptions, string, string)"/> and pushes
/// them onto a <see cref="ClientHeadersScope"/> for the lifetime of the run. The scope is read by
/// <see cref="ClientHeadersPolicy"/> inside the SCM transport pipeline and stamped onto the
/// outbound request.
/// </summary>
/// <remarks>
/// <para>
/// The decorator snapshots the header dictionary at scope-push time so concurrent runs that share
/// the same <see cref="ChatOptions"/> reference are isolated; mutating the source dictionary after
/// <c>RunAsync</c> begins does not leak into in-flight requests.
/// </para>
/// <para>
/// Streaming uses the async-iterator pattern so the AsyncLocal scope stays alive across yields,
/// which is required because the underlying HTTP send happens during enumeration.
/// </para>
/// </remarks>
internal sealed class ClientHeadersAgent : DelegatingAIAgent
{
public ClientHeadersAgent(AIAgent innerAgent)
: base(innerAgent)
{
}
/// <inheritdoc/>
protected override Task<AgentResponse> RunCoreAsync(
IEnumerable<ChatMessage> messages,
AgentSession? session = null,
AgentRunOptions? options = null,
CancellationToken cancellationToken = default)
{
var snapshot = TrySnapshot(options);
if (snapshot is null)
{
return this.InnerAgent.RunAsync(messages, session, options, cancellationToken);
}
return RunAsyncCoreAsync(messages, session, options, snapshot, cancellationToken);
async Task<AgentResponse> RunAsyncCoreAsync(
IEnumerable<ChatMessage> innerMessages,
AgentSession? innerSession,
AgentRunOptions? innerOptions,
Dictionary<string, string> innerSnapshot,
CancellationToken innerCt)
{
using var _ = ClientHeadersScope.Push(innerSnapshot);
return await this.InnerAgent.RunAsync(innerMessages, innerSession, innerOptions, innerCt).ConfigureAwait(false);
}
}
/// <inheritdoc/>
protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
IEnumerable<ChatMessage> messages,
AgentSession? session = null,
AgentRunOptions? options = null,
[EnumeratorCancellation] CancellationToken cancellationToken = default)
{
var snapshot = TrySnapshot(options);
using var _ = snapshot is null ? default : ClientHeadersScope.Push(snapshot);
await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, session, options, cancellationToken).ConfigureAwait(false))
{
yield return update;
}
}
/// <summary>Reads the header dictionary stamped by <c>WithClientHeader(s)</c> and returns an immutable snapshot, or <see langword="null"/> if none.</summary>
private static Dictionary<string, string>? TrySnapshot(AgentRunOptions? options)
{
if (options is not ChatClientAgentRunOptions { ChatOptions: { } chatOptions })
{
return null;
}
var headers = chatOptions.GetClientHeaders();
if (headers is null || headers.Count == 0)
{
return null;
}
// Copy to defeat caller mutation after RunAsync starts.
var copy = new Dictionary<string, string>(headers.Count, System.StringComparer.OrdinalIgnoreCase);
foreach (var kvp in headers)
{
copy[kvp.Key] = kvp.Value;
}
return copy;
}
}
@@ -1,204 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System;
using System.Collections.Generic;
using System.Diagnostics.CodeAnalysis;
using Microsoft.Extensions.AI;
using Microsoft.Shared.DiagnosticIds;
using Microsoft.Shared.Diagnostics;
namespace Microsoft.Agents.AI.Foundry;
/// <summary>
/// Provides extension methods for attaching per-call <c>x-client-*</c> headers to an agent run
/// and for opting an existing <see cref="AIAgent"/> into the client-headers pipeline.
/// </summary>
/// <remarks>
/// <para>
/// The Foundry platform forwards headers prefixed with <c>x-client-</c> transparently from the
/// Agent Endpoint into the agent container (see the multi-tenant overlay design). Callers use
/// <see cref="WithClientHeader(ChatOptions, string, string)"/> or
/// <see cref="WithClientHeaders(ChatOptions, IEnumerable{KeyValuePair{string, string}})"/> to
/// stamp headers per <c>RunAsync</c> call (for example to attest the SaaS end-user identity
/// in <c>x-client-end-user-id</c>).
/// </para>
/// <para>
/// Headers are only delivered to the wire when:
/// <list type="number">
/// <item><description>the agent has been wrapped with <see cref="UseClientHeaders(AIAgentBuilder)"/> (or built via a Foundry factory that pre-wires it), and</description></item>
/// <item><description>the underlying <see cref="IChatClient"/> exposes the experimental MEAI 10.5.1 <see cref="OpenAIRequestPolicies"/> service (true for OpenAI-backed clients).</description></item>
/// </list>
/// When either condition is not met the call is a silent no-op.
/// </para>
/// </remarks>
[Experimental(DiagnosticIds.Experiments.AIOpenAIRequestPolicies)]
public static class ClientHeadersExtensions
{
/// <summary>The well-known <see cref="ChatOptions.AdditionalProperties"/> key used to carry the dictionary across packages.</summary>
internal const string ClientHeadersKey = "Microsoft.Agents.AI.Foundry.ClientHeaders";
/// <summary>The required prefix on every client header name (case-insensitive).</summary>
private const string ClientHeaderPrefix = "x-client-";
/// <summary>
/// Adds a single <c>x-client-*</c> header to the per-call carrier on <paramref name="options"/>.
/// </summary>
/// <param name="options">The <see cref="ChatOptions"/> instance to mutate.</param>
/// <param name="name">The header name. Must start with <c>x-client-</c> (case-insensitive).</param>
/// <param name="value">The header value. Must be non-empty.</param>
/// <returns><paramref name="options"/> for fluent chaining.</returns>
/// <exception cref="ArgumentNullException"><paramref name="options"/>, <paramref name="name"/>, or <paramref name="value"/> is <see langword="null"/>.</exception>
/// <exception cref="ArgumentException"><paramref name="name"/> does not start with <c>x-client-</c>, or is empty/whitespace, or <paramref name="value"/> is empty.</exception>
/// <exception cref="InvalidOperationException">The carrier slot on <see cref="ChatOptions.AdditionalProperties"/> is occupied by a value of a foreign type.</exception>
public static ChatOptions WithClientHeader(this ChatOptions options, string name, string value)
{
_ = Throw.IfNull(options);
ValidateHeader(name, value);
var dict = GetOrCreateHeadersDictionary(options);
dict[name] = value;
return options;
}
/// <summary>
/// Adds multiple <c>x-client-*</c> headers to the per-call carrier on <paramref name="options"/>.
/// </summary>
/// <remarks>Validation is all-or-nothing: if any entry is invalid no entries are written.</remarks>
/// <param name="options">The <see cref="ChatOptions"/> instance to mutate.</param>
/// <param name="headers">The headers to add. Each name must start with <c>x-client-</c>.</param>
/// <returns><paramref name="options"/> for fluent chaining.</returns>
/// <exception cref="ArgumentNullException"><paramref name="options"/> or <paramref name="headers"/> is <see langword="null"/>, or any element of <paramref name="headers"/> has a <see langword="null"/> name or value.</exception>
/// <exception cref="ArgumentException">Any header name does not start with <c>x-client-</c>, or any name is empty/whitespace, or any value is empty.</exception>
/// <exception cref="InvalidOperationException">The carrier slot on <see cref="ChatOptions.AdditionalProperties"/> is occupied by a value of a foreign type.</exception>
public static ChatOptions WithClientHeaders(this ChatOptions options, IEnumerable<KeyValuePair<string, string>> headers)
{
_ = Throw.IfNull(options);
_ = Throw.IfNull(headers);
// Validate first; mutate only when every entry passes.
var staged = new List<KeyValuePair<string, string>>();
foreach (var kvp in headers)
{
ValidateHeader(kvp.Key, kvp.Value);
staged.Add(kvp);
}
if (staged.Count == 0)
{
return options;
}
var dict = GetOrCreateHeadersDictionary(options);
foreach (var kvp in staged)
{
dict[kvp.Key] = kvp.Value;
}
return options;
}
/// <summary>
/// Wraps the agent built by <paramref name="builder"/> so that headers stamped by
/// <see cref="WithClientHeader(ChatOptions, string, string)"/> on the per-call
/// <see cref="ChatOptions"/> are forwarded onto the outbound HTTP request.
/// </summary>
/// <remarks>
/// <para>
/// Idempotent: if the inner agent is already wrapped with a <see cref="ClientHeadersAgent"/>
/// anywhere in its delegating chain, the agent is returned unchanged. This makes
/// <c>myFoundryAgent.AsBuilder().UseClientHeaders().Build()</c> safe even though Foundry
/// agents are pre-wired automatically.
/// </para>
/// <para>
/// Also registers <see cref="ClientHeadersPolicy"/> against the underlying chat client's
/// <see cref="OpenAIRequestPolicies"/> service if available. When the underlying chat client
/// is not OpenAI-backed (the service lookup returns <see langword="null"/>), the registration
/// step is silently skipped; the agent decorator still runs but no headers are stamped on
/// the wire. See the type-level remarks for the conditions under which delivery happens.
/// </para>
/// </remarks>
/// <param name="builder">The <see cref="AIAgentBuilder"/> to extend.</param>
/// <returns>The same builder, to allow fluent chaining.</returns>
/// <exception cref="ArgumentNullException"><paramref name="builder"/> is <see langword="null"/>.</exception>
public static AIAgentBuilder UseClientHeaders(this AIAgentBuilder builder) =>
Throw.IfNull(builder).Use((AIAgent innerAgent, IServiceProvider services) =>
{
// Agent-side dedup: if any decorator in the chain is already a ClientHeadersAgent, no-op.
if (innerAgent.GetService<ClientHeadersAgent>() is not null)
{
return innerAgent;
}
// Best-effort policy registration on the underlying OpenAI-backed chat client.
// Silent no-op when the service is unavailable (non-OpenAI providers).
if (innerAgent.GetService<OpenAIRequestPolicies>() is { } policies)
{
OpenAIRequestPoliciesReflection.AddPolicyIfMissing(
policies,
ClientHeadersPolicy.Instance,
System.ClientModel.Primitives.PipelinePosition.PerCall);
}
return new ClientHeadersAgent(innerAgent);
});
/// <summary>Reads the headers dictionary stamped by callers, or <see langword="null"/> if none.</summary>
[SuppressMessage("Design", "CA1002:Do not expose generic lists", Justification = "Internal helper.")]
internal static IReadOnlyDictionary<string, string>? GetClientHeaders(this ChatOptions options)
{
if (options.AdditionalProperties is null)
{
return null;
}
if (!options.AdditionalProperties.TryGetValue(ClientHeadersKey, out var raw))
{
return null;
}
return raw as Dictionary<string, string>;
}
private static Dictionary<string, string> GetOrCreateHeadersDictionary(ChatOptions options)
{
options.AdditionalProperties ??= new AdditionalPropertiesDictionary();
if (options.AdditionalProperties.TryGetValue(ClientHeadersKey, out var existing))
{
if (existing is Dictionary<string, string> dict)
{
return dict;
}
throw new InvalidOperationException(
$"ChatOptions.AdditionalProperties[\"{ClientHeadersKey}\"] is occupied by a value of type '{existing?.GetType().FullName ?? "null"}', expected Dictionary<string, string>.");
}
var fresh = new Dictionary<string, string>(StringComparer.OrdinalIgnoreCase);
options.AdditionalProperties[ClientHeadersKey] = fresh;
return fresh;
}
private static void ValidateHeader(string name, string value)
{
_ = Throw.IfNull(name);
_ = Throw.IfNull(value);
if (string.IsNullOrWhiteSpace(name))
{
throw new ArgumentException("Header name must not be empty or whitespace.", nameof(name));
}
if (value.Length == 0)
{
throw new ArgumentException("Header value must not be empty.", nameof(value));
}
if (!name.StartsWith(ClientHeaderPrefix, StringComparison.OrdinalIgnoreCase))
{
throw new ArgumentException(
$"Header name '{name}' must start with '{ClientHeaderPrefix}' (case-insensitive). Only x-client-* headers are forwarded by the Foundry platform.",
nameof(name));
}
}
}
@@ -1,152 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System;
using System.ClientModel.Primitives;
using System.Collections.Generic;
using System.Diagnostics.CodeAnalysis;
using System.Reflection;
using System.Threading.Tasks;
using Microsoft.Extensions.AI;
using Microsoft.Shared.DiagnosticIds;
namespace Microsoft.Agents.AI.Foundry;
/// <summary>
/// Pipeline policy that stamps <c>x-client-*</c> headers from the current
/// <see cref="ClientHeadersScope"/> onto outbound OpenAI Responses requests.
/// </summary>
/// <remarks>
/// <para>
/// Registered once per <see cref="OpenAIRequestPolicies"/> instance via the new MEAI 10.5.1
/// extension hook. Headers are written using <see cref="PipelineRequestHeaders.Set(string, string)"/>
/// so per-call values overwrite anything stamped earlier in the pipeline (for example by static
/// pipeline policies registered on the underlying client). This also makes accidental double
/// registration value-stable.
/// </para>
/// </remarks>
internal sealed class ClientHeadersPolicy : PipelinePolicy
{
public static ClientHeadersPolicy Instance { get; } = new ClientHeadersPolicy();
private ClientHeadersPolicy()
{
}
public override void Process(PipelineMessage message, IReadOnlyList<PipelinePolicy> pipeline, int currentIndex)
{
Stamp(message);
ProcessNext(message, pipeline, currentIndex);
}
public override ValueTask ProcessAsync(PipelineMessage message, IReadOnlyList<PipelinePolicy> pipeline, int currentIndex)
{
Stamp(message);
return ProcessNextAsync(message, pipeline, currentIndex);
}
private static void Stamp(PipelineMessage message)
{
var headers = ClientHeadersScope.Current;
if (headers is null || headers.Count == 0)
{
return;
}
foreach (var kvp in headers)
{
// Per-call wins: Set overwrites any same-name header previously stamped by other policies.
message.Request.Headers.Set(kvp.Key, kvp.Value);
}
}
}
/// <summary>
/// Best-effort reflection helpers for <see cref="OpenAIRequestPolicies"/>. MEAI 10.5.1 does not
/// publicly expose its registered-policies list, so we reach into the private <c>_entries</c>
/// field to detect duplicate registrations of <see cref="ClientHeadersPolicy.Instance"/>.
/// </summary>
/// <remarks>
/// All access is guarded with try/catch and graceful fallback. If MEAI changes the field name
/// or shape in a future bump, dedup degrades to "always add" but stamping stays correct because
/// <see cref="ClientHeadersPolicy"/> uses <c>Headers.Set</c>. A CI test asserts the field shape
/// to fail loudly on future MEAI bumps.
/// </remarks>
[Experimental(DiagnosticIds.Experiments.AIOpenAIRequestPolicies)]
internal static class OpenAIRequestPoliciesReflection
{
private static readonly Lazy<FieldInfo?> s_entriesField = new(() =>
{
try
{
return typeof(OpenAIRequestPolicies).GetField(
"_entries",
BindingFlags.Instance | BindingFlags.NonPublic);
}
catch
{
return null;
}
});
/// <summary>Returns <see langword="true"/> if <paramref name="policies"/> already contains <paramref name="policy"/>.</summary>
/// <remarks>Returns <see langword="false"/> on any reflection failure (caller should treat the registration as not yet done).</remarks>
#if NET
[UnconditionalSuppressMessage("Trimming", "IL2075:RequiresUnreferencedCode",
Justification = "Reflecting on the private Entry struct shipped by Microsoft.Extensions.AI.OpenAI; falls back gracefully if shape changes. CI test asserts the field shape on every MEAI bump.")]
#endif
public static bool ContainsPolicy(OpenAIRequestPolicies policies, PipelinePolicy policy)
{
try
{
if (s_entriesField.Value?.GetValue(policies) is not Array entries)
{
return false;
}
for (int i = 0; i < entries.Length; i++)
{
var entry = entries.GetValue(i);
if (entry is null)
{
continue;
}
// Entry is a private struct with a Policy property/field. Try property first, then field.
var entryType = entry.GetType();
var policyMember = entryType.GetProperty("Policy", BindingFlags.Instance | BindingFlags.Public | BindingFlags.NonPublic);
object? value = policyMember is not null
? policyMember.GetValue(entry)
: entryType.GetField("Policy", BindingFlags.Instance | BindingFlags.Public | BindingFlags.NonPublic)?.GetValue(entry);
if (ReferenceEquals(value, policy))
{
return true;
}
}
return false;
}
catch
{
return false;
}
}
/// <summary>
/// Registers <paramref name="policy"/> on <paramref name="policies"/> if not already present.
/// </summary>
/// <returns>
/// <see langword="true"/> if <c>AddPolicy</c> was called on this invocation; <see langword="false"/>
/// when the policy was already detected as present and the call was skipped.
/// </returns>
public static bool AddPolicyIfMissing(OpenAIRequestPolicies policies, PipelinePolicy policy, PipelinePosition position = PipelinePosition.PerCall)
{
if (ContainsPolicy(policies, policy))
{
return false;
}
policies.AddPolicy(policy, position);
return true;
}
}
@@ -1,49 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Collections.Generic;
using System.Threading;
namespace Microsoft.Agents.AI.Foundry;
/// <summary>
/// AsyncLocal carrier that bridges per-call client-header values from the
/// <see cref="ClientHeadersAgent"/> decorator down to the
/// <see cref="ClientHeadersPolicy"/> running inside the SCM transport pipeline.
/// </summary>
/// <remarks>
/// AsyncLocal flows the value into downstream awaits but does not roll the value back when the
/// setting method returns. This type pairs each <see cref="Push(IReadOnlyDictionary{string, string}?)"/>
/// with a disposable that explicitly restores the prior value, giving stack-style LIFO semantics
/// for nested or sequential per-call scopes on the same async flow.
/// </remarks>
internal static class ClientHeadersScope
{
private static readonly AsyncLocal<IReadOnlyDictionary<string, string>?> s_current = new();
/// <summary>Gets the dictionary captured by the most recent <see cref="Push(IReadOnlyDictionary{string, string}?)"/> on this async flow.</summary>
public static IReadOnlyDictionary<string, string>? Current => s_current.Value;
/// <summary>
/// Pushes a new value as the current scope. Disposing the returned token restores the previous value.
/// </summary>
/// <param name="headers">The header dictionary to surface to the policy. May be <see langword="null"/>.</param>
public static Scope Push(IReadOnlyDictionary<string, string>? headers)
{
var previous = s_current.Value;
s_current.Value = headers;
return new Scope(previous);
}
/// <summary>Disposable token that restores the previous scope on <see cref="Dispose"/>.</summary>
internal readonly struct Scope : System.IDisposable
{
private readonly IReadOnlyDictionary<string, string>? _previous;
internal Scope(IReadOnlyDictionary<string, string>? previous)
{
this._previous = previous;
}
public void Dispose() => s_current.Value = this._previous;
}
}
@@ -102,7 +102,7 @@ public sealed class FoundryAgent : DelegatingAIAgent
/// Internal constructor used by <c>AsAIAgent</c> extension methods that already have an <see cref="AIProjectClient"/> and a configured <see cref="ChatClientAgent"/>.
/// </summary>
internal FoundryAgent(AIProjectClient aiProjectClient, ChatClientAgent innerAgent)
: base(WireClientHeaders(Throw.IfNull(innerAgent)))
: base(Throw.IfNull(innerAgent))
{
this._aiProjectClient = Throw.IfNull(aiProjectClient);
}
@@ -128,7 +128,7 @@ public sealed class FoundryAgent : DelegatingAIAgent
/// </para>
/// </remarks>
public ValueTask<AgentSession> CreateSessionAsync(string conversationId, CancellationToken cancellationToken = default)
=> this.GetInnerChatClientAgent().CreateSessionAsync(conversationId, cancellationToken);
=> ((ChatClientAgent)this.InnerAgent).CreateSessionAsync(conversationId, cancellationToken);
/// <summary>
/// Creates a server-side conversation session that appears in the Foundry Project UI.
@@ -143,14 +143,9 @@ public sealed class FoundryAgent : DelegatingAIAgent
var conversation = (await conversationsClient.CreateProjectConversationAsync(options: null, cancellationToken).ConfigureAwait(false)).Value;
return (ChatClientAgentSession)await this.GetInnerChatClientAgent().CreateSessionAsync(conversation.Id, cancellationToken).ConfigureAwait(false);
return (ChatClientAgentSession)await ((ChatClientAgent)this.InnerAgent).CreateSessionAsync(conversation.Id, cancellationToken).ConfigureAwait(false);
}
/// <summary>Walks the delegating chain to find the inner <see cref="ChatClientAgent"/>.</summary>
private ChatClientAgent GetInnerChatClientAgent() =>
this.GetService<ChatClientAgent>()
?? throw new InvalidOperationException("FoundryAgent inner chain does not contain a ChatClientAgent.");
#endregion
/// <inheritdoc/>
@@ -166,7 +161,7 @@ public sealed class FoundryAgent : DelegatingAIAgent
#region Private helpers
private static AIAgent CreateInnerAgent(
private static ChatClientAgent CreateInnerAgent(
AIProjectClient aiProjectClient,
string model, string instructions,
string? name, string? description,
@@ -196,7 +191,7 @@ public sealed class FoundryAgent : DelegatingAIAgent
return CreateResponsesChatClientAgent(aiProjectClient, options, clientFactory, loggerFactory, services);
}
private static AIAgent CreateResponsesChatClientAgent(
private static ChatClientAgent CreateResponsesChatClientAgent(
AIProjectClient aiProjectClient,
ChatClientAgentOptions agentOptions,
Func<IChatClient, IChatClient>? clientFactory,
@@ -215,36 +210,10 @@ public sealed class FoundryAgent : DelegatingAIAgent
chatClient = clientFactory(chatClient);
}
return WireClientHeaders(new ChatClientAgent(chatClient, agentOptions, loggerFactory, services));
return new ChatClientAgent(chatClient, agentOptions, loggerFactory, services);
}
/// <summary>
/// Registers <see cref="ClientHeadersPolicy"/> on the agent's underlying chat client (if it
/// exposes <see cref="OpenAIRequestPolicies"/>) and wraps the agent in a
/// <see cref="ClientHeadersAgent"/> so per-call <c>x-client-*</c> headers stamped via
/// <see cref="ClientHeadersExtensions.WithClientHeader(ChatOptions, string, string)"/> reach
/// the wire. Idempotent: if the chain already contains a <see cref="ClientHeadersAgent"/>,
/// the original instance is returned unchanged.
/// </summary>
private static AIAgent WireClientHeaders(ChatClientAgent innerAgent)
{
if (innerAgent.GetService<ClientHeadersAgent>() is not null)
{
return innerAgent;
}
if (innerAgent.ChatClient.GetService<OpenAIRequestPolicies>() is { } policies)
{
OpenAIRequestPoliciesReflection.AddPolicyIfMissing(
policies,
ClientHeadersPolicy.Instance,
System.ClientModel.Primitives.PipelinePosition.PerCall);
}
return new ClientHeadersAgent(innerAgent);
}
private static AIAgent CreateInnerAgentFromEndpoint(
private static ChatClientAgent CreateInnerAgentFromEndpoint(
AIProjectClient aiProjectClient,
Uri agentEndpoint,
IList<AITool>? tools,
@@ -269,7 +238,7 @@ public sealed class FoundryAgent : DelegatingAIAgent
chatClient = clientFactory(chatClient);
}
return WireClientHeaders(new ChatClientAgent(chatClient, agentOptions, services: services));
return new ChatClientAgent(chatClient, agentOptions, services: services);
}
private static AIProjectClient CreateProjectClient(Uri endpoint, AuthenticationTokenProvider credential, AIProjectClientOptions? clientOptions = null)
@@ -53,7 +53,6 @@
<ItemGroup>
<InternalsVisibleTo Include="Microsoft.Agents.AI.Foundry.UnitTests" />
<InternalsVisibleTo Include="Microsoft.Agents.AI.Foundry.Hosting.UnitTests" />
<InternalsVisibleTo Include="DynamicProxyGenAssembly2" />
</ItemGroup>
@@ -3,6 +3,7 @@
using System.ClientModel.Primitives;
using System.Collections.Generic;
using System.Reflection;
using System.Threading;
using System.Threading.Tasks;
namespace Microsoft.Agents.AI;
@@ -12,6 +13,20 @@ internal static class RequestOptionsExtensions
/// <summary>Gets the singleton <see cref="PipelinePolicy"/> that adds a MEAI user-agent header.</summary>
internal static PipelinePolicy UserAgentPolicy => MeaiUserAgentPolicy.Instance;
/// <summary>Creates a <see cref="RequestOptions"/> configured for use with Foundry Agents.</summary>
public static RequestOptions ToRequestOptions(this CancellationToken cancellationToken, bool streaming)
{
RequestOptions requestOptions = new()
{
CancellationToken = cancellationToken,
BufferResponse = !streaming
};
requestOptions.AddPolicy(MeaiUserAgentPolicy.Instance, PipelinePosition.PerCall);
return requestOptions;
}
/// <summary>Provides a pipeline policy that adds a "MEAI/x.y.z" user-agent header.</summary>
private sealed class MeaiUserAgentPolicy : PipelinePolicy
{
@@ -210,7 +210,7 @@ public sealed class GitHubCopilotAgent : AIAgent, IAsyncDisposable
string prompt = string.Join("\n", messages.Select(m => m.Text));
// Handle DataContent as attachments
(List<UserMessageAttachmentFile>? attachments, tempDir) = await ProcessDataContentAttachmentsAsync(
(List<UserMessageDataAttachmentsItem>? attachments, tempDir) = await ProcessDataContentAttachmentsAsync(
messages,
cancellationToken).ConfigureAwait(false);
@@ -443,11 +443,11 @@ public sealed class GitHubCopilotAgent : AIAgent, IAsyncDisposable
return new SessionConfig { Tools = mappedTools, SystemMessage = systemMessage };
}
private static async Task<(List<UserMessageAttachmentFile>? Attachments, string? TempDir)> ProcessDataContentAttachmentsAsync(
private static async Task<(List<UserMessageDataAttachmentsItem>? Attachments, string? TempDir)> ProcessDataContentAttachmentsAsync(
IEnumerable<ChatMessage> messages,
CancellationToken cancellationToken)
{
List<UserMessageAttachmentFile>? attachments = null;
List<UserMessageDataAttachmentsItem>? attachments = null;
string? tempDir = null;
foreach (ChatMessage message in messages)
{
@@ -461,7 +461,7 @@ public sealed class GitHubCopilotAgent : AIAgent, IAsyncDisposable
string tempFilePath = await dataContent.SaveToAsync(tempDir, cancellationToken).ConfigureAwait(false);
attachments ??= [];
attachments.Add(new UserMessageAttachmentFile
attachments.Add(new UserMessageDataAttachmentsItemFile
{
Path = tempFilePath,
DisplayName = Path.GetFileName(tempFilePath)
@@ -1,32 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using System.Collections.Generic;
namespace Microsoft.Agents.AI.Hyperlight;
/// <summary>
/// Represents a single entry in the outbound network allow-list applied to the
/// Hyperlight sandbox.
/// </summary>
public sealed class AllowedDomain
{
/// <summary>
/// Initializes a new instance of the <see cref="AllowedDomain"/> class.
/// </summary>
/// <param name="target">URL or domain to allow, for example <c>"https://api.github.com"</c>.</param>
/// <param name="methods">
/// Optional list of HTTP methods to allow (for example <c>["GET", "POST"]</c>).
/// When <see langword="null"/>, all methods supported by the backend are allowed.
/// </param>
public AllowedDomain(string target, IReadOnlyList<string>? methods = null)
{
this.Target = target;
this.Methods = methods;
}
/// <summary>Gets the URL or domain to allow.</summary>
public string Target { get; }
/// <summary>Gets the optional list of HTTP methods to allow.</summary>
public IReadOnlyList<string>? Methods { get; }
}
@@ -1,25 +0,0 @@
// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Extensions.AI;
namespace Microsoft.Agents.AI.Hyperlight;
/// <summary>
/// Controls the approval behavior for the <c>execute_code</c> tool exposed by
/// <see cref="HyperlightCodeActProvider"/> and <see cref="HyperlightExecuteCodeFunction"/>.
/// </summary>
public enum CodeActApprovalMode
{
/// <summary>
/// <c>execute_code</c> always requires user approval before invocation.
/// </summary>
AlwaysRequire,
/// <summary>
/// Approval is derived from the provider-owned CodeAct tool registry.
/// If any configured tool is an
/// <see cref="ApprovalRequiredAIFunction"/>,
/// <c>execute_code</c> also requires approval. Otherwise it does not.
/// </summary>
NeverRequire,
}

Some files were not shown because too many files have changed in this diff Show More