Compare commits

...

96 Commits

Author SHA1 Message Date
Evan Mattson 2d34deeb82 Reduce workflow credential exposure (#7270)
* Mask workflow authentication configuration

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: d9fa4e9c-c32d-42fb-8ee4-4772473e6479

* Use run-scoped Copilot authentication

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: d9fa4e9c-c32d-42fb-8ee4-4772473e6479

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: d9fa4e9c-c32d-42fb-8ee4-4772473e6479
2026-07-23 08:57:40 +09:00
Evan Mattson a2927c1c09 Python: Fix stateless replay of reasoning-paired tool calls (#7233)
* Python: Fix reasoning-paired client tool replay

* Python: Handle middleware-terminated reasoning tool loops

* Python: Replay encrypted reasoning function groups

Key decisions:
- Request encrypted reasoning on client-managed Responses calls while preserving caller include values.
- Store encrypted payloads in Content.protected_data and reconstruct one provider reasoning item per reasoning id.
- Replay active and completed function call/result groups; retain continuation-owned history behavior and the existing orphan-safe MCP path.

Files changed:
- python/packages/openai/agent_framework_openai/_chat_client.py
- python/packages/openai/tests/openai/test_openai_chat_client.py

Next iteration:
- Extend encrypted reasoning preservation to streaming and framework serialization boundaries.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Preserve encrypted reasoning through streaming

Key decisions:
- Capture encrypted reasoning from terminal streamed output items in Content.protected_data.
- Preserve summary and private reasoning as distinct framework contents while reconstructing one provider reasoning item per id.
- Prove replay after Message JSON and workflow checkpoint round trips, including encrypted-only and completed function groups.

Files changed:
- python/packages/core/agent_framework/_types.py
- python/packages/openai/agent_framework_openai/_chat_client.py
- python/packages/openai/tests/openai/test_openai_chat_client.py

Next iteration:
- Extend lossless stateless reasoning replay to hosted MCP call/output groups.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Replay hosted MCP reasoning groups

Key decisions:
- Preserve hosted MCP call/output groups in client-managed history instead of deleting them when reasoning cannot be reconstructed.
- Keep call/result coalescing and orphan-result exclusion intact, while retaining continuation-owned duplicate avoidance.
- Cover completed, active, and multi-call reasoning groups plus the public outgoing request boundary.

Files changed:
- python/packages/openai/agent_framework_openai/_chat_client.py
- python/packages/openai/tests/openai/test_openai_chat_client.py

Next iteration:
- Preserve middleware-terminated and parallel function groups atomically.
- Add preflight rejection for non-replayable reasoning groups in the dedicated validation slice.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Preserve terminated parallel reasoning groups

Key decisions:
- Return ordinary function results when middleware terminates a loop, removing the provider-specific durable marker.
- Preserve every parallel call and available sibling result as one encrypted reasoning group in stateless replay.
- Prove successful and policy-blocked batches through the public two-agent Foundry workflow and outgoing HTTP boundary.

Files changed:
- python/packages/core/agent_framework/_tools.py
- python/packages/core/tests/core/test_function_invocation_logic.py
- python/packages/openai/tests/openai/test_openai_chat_client.py
- python/packages/foundry/tests/foundry/test_foundry_agent.py

Next iteration:
- Add preflight rejection for non-replayable and partially compacted reasoning groups.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Reject unsafe stateless reasoning replay

Key decisions:
- Validate client-managed reasoning groups after compaction and report every affected reasoning and call identifier before transport.
- Permit service-owned continuation and fully excluded atomic groups while rejecting partial compaction projections.
- Surface encrypted-reasoning capability failures without lossy retries.

Files changed:
- python/packages/openai/agent_framework_openai/_chat_client.py
- python/packages/openai/tests/openai/test_openai_chat_client.py

Next iteration:
- Run the resource-specific Foundry proof and finish PR #7233; that live proof remains intentionally local and requires the configured developer resource.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Preserve reasoning metadata in Foundry hosting

* Python: Avoid duplicating reasoning text metadata

* Python: Gate encrypted reasoning for Foundry agents

* Python: Type stateless reasoning integration test

* Python: Narrow Foundry mock call arguments

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-07-22 23:51:22 +00:00
Ben Thomas c68c099347 .NET: Fix expensive logging (#7268)
* .NET: Guard workflow warning logging

Avoid unnecessary structured logging argument evaluation when warning logging is disabled, resolving CA1873 in release builds.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 0bc01e26-22ba-42ce-ac1e-6fe166500f4f

* .NET: Use generated workflow logging

Align the no-progress warning with the repository-standard LoggerMessage source generator pattern.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 0bc01e26-22ba-42ce-ac1e-6fe166500f4f

* Potential fix for pull request finding

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

---------

Co-authored-by: Ben Thomas <25218250+alliscode@users.noreply.github.com>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Copilot-Session: 0bc01e26-22ba-42ce-ac1e-6fe166500f4f
2026-07-22 23:03:32 +00:00
Yunus Emre Gültepe 61802723ff Python: Support prompt cache breakpoints for GPT-5.6 models in OpenAI clients (#7163)
* Python: Support prompt cache breakpoints for GPT-5.6 models in OpenAI clients

Add request-level prompt_cache_options to OpenAIChatOptions and
OpenAIChatCompletionOptions, and forward a per-part prompt_cache_breakpoint
from Content.additional_properties onto the content blocks each API supports.
Text parts that carry a breakpoint keep typed list content, since the
plain-string form cannot hold one; without a breakpoint the existing string
forms are unchanged.

* Clarify system-message content-shape comment

* Address review: SDK prompt cache types, private helper, add sample

Replace the custom PromptCacheOptions TypedDict with the openai SDK's own
types for each API, which raises the openai floor to 2.45.0 where those
types were introduced. Make the breakpoint helper private to the two chat
clients. Add a prompt caching sample with a README entry, and unquote the
helper's Content annotation so the pyupgrade hook passes.

* Guard the prompt cache options import for older openai versions

The SDK's PromptCacheOptions types only exist in openai 2.45.0 and
later, so each client falls back to a local mirror when the import
fails and the dependency floor stays at 2.25.0. A TYPE_CHECKING-only
import is not enough because the options classes are introspected with
get_type_hints() at runtime. Verified against openai 2.25.0: the
package imports, the fallback resolves, and part-level breakpoints
still work; sending the option itself requires 2.45.0, which the field
docstrings now note.

* Make the old-openai fallback for PromptCacheOptions deliberately empty

Assigning None instead, as suggested in review, trips pyright's
reportInvalidTypeForm on the field annotation (the symbol becomes
type | None after the try/except). An empty TypedDict gives the same
effect for users on older openai versions: any content they put in
prompt_cache_options is flagged by their type checker, since the
option cannot be sent on those versions anyway, while
get_type_hints() on the options classes keeps working at runtime.

* Guard prompt_cache_options at runtime instead of via an empty fallback type

The empty-TypedDict fallback flagged valid `prompt_cache_options` usage under
pyright on every openai version — including this PR's own
`client_prompt_caching.py` sample (`poe check -S`) — because pyright resolves the
try/except symbol to the fallback shape regardless of the installed openai, while
mypy/ty resolve the failed import to `Any` and never warn. So a type-only "warn on
old openai" signal is not achievable cleanly across type checkers.

Restore the faithful fallback (mirrors the SDK's `mode`/`ttl` shape) so the option
type-checks identically on every supported openai version, and add a runtime guard:
setting `prompt_cache_options` on openai < 2.45 now raises a clear
ChatClientInvalidRequestException instead of forwarding an unusable option to the
SDK. This keeps the option non-silent for all users regardless of type checker,
without forcing an openai upgrade. Adds tests covering the guard for both clients.

* Gate system/developer breakpoint shape on a real mapping value

The system/developer branch switched to list-form content whenever
prompt_cache_breakpoint was set to any non-None value, but the option is
only attached when the value is a mapping. A malformed value (e.g. a
string) therefore changed the message shape without adding a breakpoint.
Decide the shape from the built part instead, matching the user-role path.
2026-07-22 21:43:19 +00:00
Whit Waldo ddb0622f9c .NET: Added GettingStarted example demonstrating Dapr as an agent provider (#1615)
* Added example demonstrating creating an AIAgent using the Microsoft.AI.Extensions implementation of IChatClient using Dapr as the inference backend provider - in this example, using Ollama

Signed-off-by: Whit Waldo <whit.waldo@innovian.net>

* Update dotnet/samples/GettingStarted/AgentProviders/Agent_With_Dapr/README.md

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

* Added copyright statement at top of file

Signed-off-by: Whit Waldo <whit.waldo@innovian.net>

* Update dotnet/agent-framework-dotnet.slnx

That's odd the IDE added it a second time.

Co-authored-by: westey <164392973+westey-m@users.noreply.github.com>

* Address review nits: configurable Dapr gRPC endpoint and document VersionOverride

Make the Dapr sidecar gRPC endpoint configurable via the DAPR_GRPC_ENDPOINT environment variable
(defaulting to http://localhost:3501) and document it in the README. Add a comment explaining why the
Microsoft.Extensions.* VersionOverride entries are needed and when they can be removed.

---------

Signed-off-by: Whit Waldo <whit.waldo@innovian.net>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: westey <164392973+westey-m@users.noreply.github.com>
Co-authored-by: Roger Barreto <19890735+RogerBarreto@users.noreply.github.com>
2026-07-22 19:28:00 +00:00
Ben Thomas 12b23250f4 Updating dotnet version for release. (#7265)
Co-authored-by: Ben Thomas <25218250+alliscode@users.noreply.github.com>
2026-07-22 10:05:59 -07:00
Ben Thomas bfc73a5b14 .NET: Fix declarative autosend output (#7217)
* Fix declarative workflow auto-send output

Restore completed responses for workflow-conversation agents while preventing hosted workflow adapters from materializing streamed responses twice.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: c2d86826-ead0-40bc-b84b-a513ac4d325f

* Correlate streamed workflow responses by message

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: c2d86826-ead0-40bc-b84b-a513ac4d325f

* Handle empty streaming message IDs

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: c2d86826-ead0-40bc-b84b-a513ac4d325f

* Restore workflow conversation auto-send

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: c2d86826-ead0-40bc-b84b-a513ac4d325f

* Address workflow response review feedback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: c2d86826-ead0-40bc-b84b-a513ac4d325f

* Ignore whitespace workflow message IDs

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: c2d86826-ead0-40bc-b84b-a513ac4d325f

* Correlate all content-bearing agent updates

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: c2d86826-ead0-40bc-b84b-a513ac4d325f

---------

Co-authored-by: Ben Thomas <25218250+alliscode@users.noreply.github.com>
2026-07-22 15:11:59 +00:00
Roger Barreto 1f1da1bddb .NET: [BREAKING] Hosting OpenAI Responses protocol helpers and optional execution state (#7000)
* .NET: Add OpenAI Responses protocol helpers and optional execution state (ADR-0032)

* Fix netstandard2.0/net472 build; harden helpers and workflow checkpoint key per review

* .NET: Migrate hosting Responses samples to Azure.AI.Projects and fix workflow resume

Migrate HostingResponsesAgent and HostingResponsesWorkflow samples from
Azure.AI.OpenAI to Azure.AI.Projects (AIProjectClient.AsAIAgent), using the
FOUNDRY_PROJECT_ENDPOINT/FOUNDRY_MODEL convention.

Fix HostedWorkflowState.RunOrResumeAsync: on subsequent turns, restore the
session's latest checkpoint and run the workflow forward with the new turn's
input (mirroring the Python hosting host's restore-then-run semantics) instead
of resuming a halted run with no input, which waited on input indefinitely.
Add round-trip resume tests and update ADR-0032/spec-003 wording.

* .NET: Fix HostedWorkflowState resume hang on unserviced external requests

On resume, HostedWorkflowState.RunOrResumeAsync drained the workflow with the
blocking WatchStreamAsync overload, so a workflow that halts at an unserviced
RequestInfoEvent (human-in-the-loop / approval) blocked forever — asymmetric
with the first-turn RunAsync path, which returns at the same halt. Break the
drain when a superstep completes with HasPendingRequests, restoring symmetry
with turn 1. Add a HITL approval-gate workflow and a resume-does-not-block test.

* .NET: Warn when a HostedWorkflowState resume makes no progress

Add an optional ILoggerFactory to HostedWorkflowState and log a warning when a
resumed turn produces no events, mirroring the Python host's zero-event restore
warning (a stale checkpoint or an input that does not match the workflow's
expected type leaves session state unprogressed). Add a non-chat string workflow
helper, a capturing logger, and a red/green test.

* .NET: Resume HostedWorkflowState from durable checkpoint on cursor miss

Add CheckpointManager.GetLatestCheckpointAsync(sessionId) and have
HostedWorkflowState fall back to it when its in-memory head cursor misses, so a
durable CheckpointManager resumes a session across a process restart or a new
holder instead of restarting from the workflow's start executor. Mirrors the
Python host's per-turn get_latest read-through. Add a counting workflow that
proves resume-vs-fresh via accumulated state, plus a red/green test, and update
ADR-0032/spec-003 and the XML remarks.

* .NET: Serialize HostedWorkflowState turns through a workflow lock

A single workflow instance backs the holder and workflow instances do not
support concurrent runs (the runner throws "already owned by another runner"),
so concurrent turns could fault or race the head cursor. Serialize all turns
through one SemaphoreSlim (mirroring the Python host's workflow lock) and make
HostedWorkflowState IDisposable to own it. Add a gated workflow and a
deterministic concurrency red/green test.

* .NET: Cover non-chat resume and multi-turn checkpoint advance

Add tests for HostedWorkflowState resuming a non-chat-protocol workflow (no
TurnToken) and for a third turn continuing to advance the head checkpoint,
closing the coverage gaps the parity review flagged.

* .NET: Add streaming workflow resume path and stream the workflow sample

Add HostedWorkflowState.RunOrResumeStreamingAsync, which yields the turn's
WorkflowEvents as they occur (fresh run or checkpoint resume) under the same
serialization lock and records the head checkpoint after the stream drains,
keeping the blocking and streaming workflow paths in lockstep with the Python
host. Honor stream:true in the HostingResponsesWorkflow sample by projecting
AgentResponseUpdateEvent updates over the Responses SSE wire. Add a streaming
resume test and update the README/spec.

* .NET: Cover Responses input adaptation to a typed workflow start executor

Demonstrate that HostedWorkflowState's generic RunOrResumeAsync<TInput> is the
input-adaptation seam (parity with Python's ResponsesChannel run hook): the app
adapts the Responses input into the workflow start executor's own type at the
call site. Add a typed-brief workflow and a test, and note the seam in spec-003.

* .NET: Drain workflow resume non-blocking to prevent hang and truncation

The resume drain used a SuperStepCompletedEvent{HasPendingRequests} proxy over
the blocking public WatchStreamAsync. That proxy (a) truncated a resumed turn
when a superstep both emitted a request and queued downstream work, and (b)
could fail to fire at all — re-introducing the indefinite hang — when a resume
input drove no superstep (e.g. a rejected non-chat input).

Make StreamingRun.WatchStreamAsync(bool blockOnPendingRequest, CancellationToken)
public and drain both the blocking and streaming resume paths with
blockOnPendingRequest:false, exactly matching the first-turn RunAsync semantics
(Run.RunToNextHaltAsync). Add guard tests: resume with a rejected input does not
hang, and a resume superstep with a request plus downstream work is not
truncated (verified red against the old proxy).

* .NET: Return file-store checkpoint index in commit order

CheckpointManager.GetLatestCheckpointAsync takes the last entry of a store's
index as the head checkpoint. FileSystemJsonCheckpointStore backed its index
with a HashSet, whose enumeration order is not contractual: after a rollback
frees and reuses a slot, enumeration can diverge from commit order, so the
durable read-through could resume a stale checkpoint. Mirror the HashSet with an
insertion-ordered list and enumerate it from RetrieveIndexAsync so 'latest' is
reliable. Add a CheckpointManager.GetLatestCheckpointAsync contract test over the
file store.

Note: the HashSet disorder is only reachable via the internal rollback path, so
the test locks the ordering contract rather than reproducing the rare disorder.

* .NET: Advance cursor when a streaming resume is abandoned

RunOrResumeStreamingAsync recorded the head checkpoint only after the stream was
fully enumerated. If an SSE consumer disconnected mid-turn after supersteps had
committed, the in-memory cursor kept the previous turn's head; because the next
turn is then a cursor hit, durable read-through could not self-heal, so it
resumed pre-disconnect state. Record the run's last committed checkpoint in a
finally so an abandoned stream still advances the cursor. Add a red/green test.

* .NET: Stream only the final agent's updates in the workflow sample

ExtractUpdates streamed every agent's updates, so the sequential Writer->Reviewer
sample streamed the intermediate draft and the final answer over SSE, differing
from the non-streaming response (final message only). Filter the streamed updates
to the final agent so streaming and non-streaming produce the same response.
Live-verified against Foundry: one output item streamed instead of two.

* .NET: Isolate the holder lock in the concurrency test

The concurrency test asserted the second same-session turn did not enter the
workflow, which also passes via the engine's concurrent-run ownership guard
(which faults) rather than the holder lock (which waits). Assert instead that the
second turn is not completed while the first holds the lock: a fault would
complete the task, so a pending task isolates the holder lock from the engine
guard. Verified red with the lock removed.

* Fix IDE1006 naming in tests; address review feedback and add hosting/live tests

* Document commit-order contract for ICheckpointStore.RetrieveIndexAsync

* Restructure hosting samples under af-hosting with client/server split matching Python parity

* Clarify hosting sample README wording and drop Python comparisons

* Make AgentSessionStore.DeleteSessionAsync abstract and rename session id parameter to sessionStoreId

* Rename OpenAIResponses id helpers and parse the request once for id extraction

* Reclaim per-session locks in HostedAgentState and demonstrate session locking in the agent sample

* Internalize per-session locking in HostedAgentState (automatic, on by default) and remove mirroring-Python wording from code and spec

* Remove HostedAgentState; app-owned routes use AgentSessionStore directly

HostedAgentState only bundled an AIAgent with an AgentSessionStore and, after
the per-session lock was removed, its GetOrCreateSessionAsync/SaveSessionAsync/
DeleteSessionAsync were pass-throughs that just bound the agent argument.
Create-on-miss already lives in the store (unlike Python, whose get/set-only
SessionStore justifies its AgentState holder), so the type earned its place
only via the lock.

Each AgentSessionStore.GetSessionAsync now returns an independent session
instance per call, so concurrent gets fork the same stored state (e.g.
branching from previous_response_id or managing several conversation ids)
without sharing an instance. The store does no cross-call locking; serializing
concurrent runs against the same id is the application's concern.

- Delete HostedAgentState and its unit tests.
- Rewire the local_responses sample and the OpenAI hosting unit/integration
  tests to call AgentSessionStore (GetSessionAsync/SaveSessionAsync) directly.
- Update ADR-0032, spec-003, and the af-hosting sample READMEs.

* Isolate hosted session snapshots and distinguish conversation vs response continuation

Mirrors the Python hosted-session isolation work: a hosted session read must be
an independent copy, and the app-owned route must persist under the right
continuation key depending on how the caller continued the thread.

- AgentSessionStore.GetSessionAsync: document the isolation invariant (each
  call returns an independent AgentSession so concurrent branches from one
  previous_response_id do not observe each other's mutations or alter stored
  state); fix the stale "or null if not found" wording (in-box stores return a
  fresh created session on miss). The in-box stores already satisfy this via a
  serialize/deserialize snapshot round-trip.
- local_responses sample + hosting unit-test route: choose the save key by
  channel. A stable conversation id is a mutable head (write back under the
  same id; app owns single-writer coordination). A previous_response_id
  continuation or first turn is an immutable snapshot (save under the new
  response id so branches from the same prior response stay independent).
- Add regression tests: independent get returns a distinct instance
  (InMemoryAgentSessionStore); previous_response_id supports independent
  branches ([1,2,2,3,3]); conversation id advances the mutable head ([1,2]).
- Update the sample README and ADR-0032 wording.

* Add workflow-factory support to HostedWorkflowState for concurrent sessions

HostedWorkflowState backed every session with one shared Workflow instance and
serialized all turns through a lock, so independent sessions could not run
concurrently. Add a workflow-factory constructor and remove the run lock.

- New constructor HostedWorkflowState(Func<CancellationToken, ValueTask<Workflow>>
  workflowFactory, ..., bool cacheWorkflow = false):
  - cacheWorkflow: false (default) builds a fresh instance per run, so independent
    sessions run in parallel. A resume rehydrates a fresh instance from the
    session's checkpoint in the shared store.
  - cacheWorkflow: true builds the workflow once, lazily on first use, and reuses
    it (a deferred, cached target that, like a shared instance, cannot run
    concurrent turns).
- Remove the internal SemaphoreSlim run lock and IDisposable; the instance
  constructor is unchanged in behaviour (one shared instance still cannot run
  concurrent turns). Turns are no longer serialized by the holder; a single
  writer per session is the application's responsibility.
- Switch the local_responses_workflow sample to the factory constructor with an
  explicit cacheWorkflow: false, and document the option.
- Add tests: parallel independent sessions (factory), fresh-instance resume,
  cached factory builds once and reuses, uncached factory builds per run.
- Update ADR-0032, spec-003, and the sample README.

* Clarify in ADR-0032 how .NET covers AgentState factory and async-setup via DI

* Rebuild cached workflow after a faulted build and add checkpoint index dedup tests
2026-07-22 10:32:44 +00:00
Giles Odigwe 83ba938d1e Python: preserve Gemini 3 thought_signature across function-call replays (#7095)
* Python: preserve Gemini 3 thought_signature across function-call replays

Gemini 3 requires the opaque thought_signature attached to each functionCall
part to be echoed back on every replay of that call, or the request is rejected
with 400 INVALID_ARGUMENT. The signature previously survived only via
raw_representation, so any layer that reconstructs a FunctionCallContent (e.g.
harness tool approval) dropped it and broke the next step of the tool loop.

Capture the signature into additional_properties on parse and replay it when
building the Gemini Part, independent of raw_representation.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 33233834-bc6e-4ad2-a6f3-6f1d6e57b1d2

* Store Gemini thought_signature as base64 for JSON-safe persistence

Content.additional_properties is serialized via json.dumps(message.to_dict())
by history providers (e.g. RedisHistoryProvider), which fails on raw bytes.
Store the thought_signature as a base64 string on parse and decode it back to
bytes when building the Gemini Part. Also narrow call_id/name in the round-trip
test to satisfy the type checkers.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 33233834-bc6e-4ad2-a6f3-6f1d6e57b1d2

* Harden Gemini thought_signature decode against corrupted history

Guard the untyped additional_properties value with an isinstance(str) check and
decode with validate=True, degrading gracefully (warn + drop the signature) on
malformed data instead of raising binascii.Error mid tool loop. Matches the
defensive base64 handling already used for data URIs in this file.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 33233834-bc6e-4ad2-a6f3-6f1d6e57b1d2

* Carry Gemini thought_signature on reasoning content via protected_data

Represent the signature as a text_reasoning content's protected_data (base64)
immediately preceding the function call, instead of a bespoke additional_properties
key. This uses the framework's first-class opaque-signature field (as Anthropic
does), survives streaming accumulation, and stays intact when the harness
reconstructs the function call. Replay correlates the signature by adjacency.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 33233834-bc6e-4ad2-a6f3-6f1d6e57b1d2

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-07-22 07:10:45 +00:00
Evan Mattson d97c901301 Harden workflow credential selection (#7249)
* Harden workflow credential selection

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: d9fa4e9c-c32d-42fb-8ee4-4772473e6479

* Address workflow authentication review feedback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: d9fa4e9c-c32d-42fb-8ee4-4772473e6479

* Fail safely on membership lookup errors

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: d9fa4e9c-c32d-42fb-8ee4-4772473e6479

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-07-22 15:51:08 +09:00
Tao Chen d1d2610b28 Add MCPStreamableHTTPTool security guidance for custom http client (#7245) 2026-07-22 04:57:09 +00:00
Tao Chen 848443ac68 [BREAKING] Python: Ensure session isolation for FHA invocation impl (#7158)
* Ensure session isolation for FHA invocation impl

* Fix type check errors

* Add user isolation to sample
2026-07-21 19:33:01 +00:00
Giles Odigwe 1466d68cf1 Python: make FoundryToolbox.as_skills_provider() disable_caching effective (#7135)
* Python: make FoundryToolbox.as_skills_provider() disable_caching effective

as_skills_provider() forwarded disable_caching to SkillsProvider, which
ignores it for a caller-supplied SkillsSource, so it was a no-op and the
toolbox re-read skill://index.json on every agent run.

Compose caching in as_skills_provider() instead: wrap the context-independent
_FoundryToolboxSkillsSource in DeduplicatingSkillsSource(CachingSkillsSource(...)).
Add a cache_refresh_interval param, fix the docstring, and add tests covering
cached, disabled, and refresh-interval behavior.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 84150ec4-6f7c-4ef8-b9fb-12fa11652773

* Clarify caller-invariant skill-set wording in as_skills_provider docs

Emphasize that the toolbox advertises the same skill set to every caller (the
per-request call-id governs execution/authorization, not which skills are
listed) rather than leaning on 'ignores SkillsSourceContext'.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 84150ec4-6f7c-4ef8-b9fb-12fa11652773

* Make MCP skills reconnect-safe via session_provider

Cached MCPSkill objects captured the MCP ClientSession at construction, so
after a FoundryToolbox reconnect (which replaces its session) load_skill and
read_skill_resource would fail against the closed session. This regressed once
as_skills_provider() started caching discovery by default.

Add an optional session_provider callable to MCPSkillsSource and MCPSkill
(exactly one of client or session_provider). When supplied, the session is
resolved on every fetch, mirroring how MCPTool resolves self.session live at
call time. _FoundryToolboxSkillsSource now passes a provider that returns the
toolbox's current session, so cached skills always use the live session.

The fixed client= path is unchanged and backward-compatible. Update core tests,
foundry_hosting tests, and core AGENTS.md.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 84150ec4-6f7c-4ef8-b9fb-12fa11652773

* Fix ty error: type captured session_provider as Callable in test

ty could not call the provider narrowed from \object\ (Top callable). Type the
captured value as Callable[[], object] and drop the redundant callable() assert.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 84150ec4-6f7c-4ef8-b9fb-12fa11652773

* Simplify _resolve_mcp_session_provider per review

Address review feedback: replace the dense (client is None) == (session_provider
is None) guard with explicit branches, and drop the cast by binding the narrowed
client to a typed local. Keeps strict 'exactly one' semantics (raises on both and
on neither), matching the codebase convention (e.g. security.py mcp_tool/url).

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 84150ec4-6f7c-4ef8-b9fb-12fa11652773

* Add PR #7135 entries to the 1.12.0 changelog

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 84150ec4-6f7c-4ef8-b9fb-12fa11652773

* Drop redundant @pytest.mark.asyncio from MCP skills tests

asyncio_mode is 'auto', so the marker is unnecessary. Remove it from the whole
file for consistency with the async-by-default convention. Per review feedback.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 84150ec4-6f7c-4ef8-b9fb-12fa11652773

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-07-21 18:02:38 +00:00
Eduard van Valkenburg d08200d00e Python: Bump package versions for 1.12.0 release (#7238)
* Bump Python package versions for 1.12.0 release

Bump packages represented in the 1.12.0 changelog, promote Foundry Hosting, Azure Content Understanding, Gemini, Mistral, Monty, and Tools to beta, and apply the requested beta cohort date stamp. Root and core move to 1.12.0, released and RC packages use their selected increments, alpha packages including Hosting MCP use the 260721 stamp, and core floors are raised only for proven consumers.

Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf

* fix version in readme

* Add Responses conversation ID changes to release notes

Include the breaking Hosting Responses conversation ID helper changes from #7234 in the Python 1.12.0 changelog.

Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf
2026-07-21 15:45:00 +00:00
Binit Mohanty fb38b1d10a Python: Fix PropertySchema.to_json_schema() not recursing into nested array items / object properties (#7200)
* Python: Fix PropertySchema.to_json_schema() not recursing into nested schemas

Nested array 'items' and object 'properties' kept the declarative 'kind'
key and empty 'enum' placeholders, producing JSON Schema OpenAI rejects
('schema must have a type key'). Recursively apply the same conversion the
top-level properties loop performs, including the serialized named-list
properties shape and nested required arrays.

Fixes #7198

(cherry picked from commit c156ffd05924fb5a1884625f2fc3d9bdc3e152b1)

* Python: Validate nested properties list before mutating to avoid partial conversion

Review feedback: the list-shaped properties branch popped name/required from
each element and returned on the first unexpected one, leaving earlier
elements half-converted. Validate the whole list first so an unexpected
shape leaves the node fully untouched.

* Python: Type nested-properties normalization for strict Pyright and drop unreachable dict branch

ObjectProperty always stores nested properties as a named list, so the
elif-dict branch in _normalize_nested_schemas was unreachable; remove it
and flatten the list conversion behind an early return. Cast the narrowed
items/props values so strict Pyright no longer reports unknown types.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* Python: Emit additionalProperties: false on nested object nodes in PropertySchema.to_json_schema()

OpenAI strict structured outputs require additionalProperties: false on
every object node, but the chat clients only inject it at the schema
root, so declarative schemas with nested objects (e.g. array items)
failed with a schema-validation 400. Route the top-level properties loop
through _normalize_schema_node so all object nodes get the key, and add
a live OpenAI integration test covering the nested array-of-objects
response_format shape.

Verified live against the Responses API: the previous emission fails
with "In context=('properties', 'issues', 'items'),
'additionalProperties' is required to be supplied and to be false";
the new emission returns valid structured output.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

---------

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
2026-07-21 15:38:38 +00:00
Eduard van Valkenburg a70fe21298 [BREAKING] Python: add Responses conversation ID helper (#7234)
* Python: add Responses conversation ID helper

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf

* Python: make Responses session flag optional

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf

* Python: correlate Responses session return types

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf

* Python: clarify Responses conversation parameter

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf

* Python: clarify streaming conversation parameter

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf

* Python: include conversation in created event

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf

* Python: warn on nonstandard Responses IDs

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf
2026-07-21 15:17:14 +00:00
Roger Barreto f6a3c43e9a .NET: Add source-type-agnostic consent regression test for a2a_preview (#7229) 2026-07-21 15:08:06 +00:00
westey e6f7b3e9be Version bump for .net release (#7237) 2026-07-21 14:59:07 +00:00
Eduard van Valkenburg a1f3e536bc Python: Add MCP hosting helpers (#7209)
* Python: Add MCP hosting helpers

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 5d6987cd-1b67-4ba1-8b54-3c50da6e7607

* Python: Address MCP hosting review comments

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 5d6987cd-1b67-4ba1-8b54-3c50da6e7607

* renamed to AgentMCPTool
2026-07-21 14:46:46 +00:00
westey c033adb1f4 .NET: [BREAKING] Graduate HarnessAgent (#7119)
* Graduate HarnessAgent

* Switch harness project to released and remove unreleased shell dependency

* Address PR comments.
2026-07-21 14:24:19 +00:00
Roger Barreto 09473fa7ed .NET: [BREAKING] Bind tool-approval responses to surfaced approval requests (#7111)
* .NET: Bind tool-approval responses to surfaced approval requests

Harden the tool-approval flow so an approved tool call always matches the
request the framework surfaced for approval.

Add ApprovalResponseBindingChatClient as the outermost decorator above
FunctionInvokingChatClient. It records each model-originated
ToolApprovalRequestContent in the session state and, on the next request,
binds every ToolApprovalResponseContent to its recorded request: the
response tool call is rebound to the recorded call, matched entries are
consumed for one-time use, and only approvals tied to a framework-issued
request take effect.

Apply the same binding in the ToolApprovalAgent harness by tracking the
requests it surfaces and binding collected responses to them during a
queue cycle.

Add ChatClientAgentOptions.DisableApprovalResponseBinding (default off) and
a UseApprovalResponseBinding builder extension for custom chat client stacks.
Includes unit tests for the decorator and the harness.

* .NET: Bind approval responses once per turn and avoid re-enumeration

Address review feedback on the approval-response binding decorator:
consume a matched request from the per-turn lookup so a duplicate response
with the same request id in one turn is honored only once, and return the
materialized message list instead of the original enumerable so a single-use
sequence is not enumerated twice. Rename the local pending list to
pendingRequests for clarity. Adds a duplicate-response regression test.

* .NET: Snapshot recorded approval requests and consume duplicates in the harness

Address review feedback on ToolApprovalAgent:
store a snapshot of each surfaced/pending approval request (cloned tool call
with a copied arguments dictionary) so a later mutation of the caller-visible
instance cannot change the recorded call used to bind the response, and consume
a surfaced request on match so a duplicate response with the same request id in
one pass is honored only once. Apply both symmetrically in the harness and the
ApprovalResponseBindingChatClient decorator. Adds regression tests for the
snapshot and duplicate-response cases.

* .NET: Address review feedback on approval-response binding

- Harness: store surfaced approval requests in a dictionary and consume matches directly, drop the extra hashset and the redundant record-time dedup; replace clear-on-resolution with a debug assert.
- Harness pipeline: add UseApprovalResponseBinding() as the outermost decorator in HarnessAgent (it uses UseProvidedChatClientAsIs) behind a new DisableApprovalResponseBinding option, with tests.
- Decorator: avoid message/content allocations when nothing changes, keep the original content when a response already matches the recorded call, clear pending each inbound turn, and shorten helpers.

* .NET: Compare tool calls by fields instead of serializing

Replace the JSON-serialization comparison in the approval-response binding
decorator with a direct field comparison. Fast-path FunctionCallContent by
comparing CallId, Name, and arguments field by field; any other tool call
shape rebinds. The comparison only skips an allocation (the call is always
rebound to the recorded request otherwise), so a miss just triggers a safe
rebuild. Adds a test that a matching response is forwarded unchanged.

* .NET: Bind approval responses against requests present in history

Fix a merge-queue regression where AG-UI mixed server/client tool invocation
stopped executing the server tool. The binding decorator validated approval
responses only against its own recorded pending state, so a matched approval
request/response pair replayed from conversation history was treated as
unbound and dropped, and the auto-approved server tool never ran.

Treat known requests as the recorded pending state plus any approval requests
already present in the current messages, and stop dropping approval requests
(a request in history is the pairing authority). A response with no known
request anywhere is still dropped, so a forged approval cannot execute.

Also address review feedback: return the mutable contents buffer from a
helper instead of a null-forgiving operator, and use clearer naming
(PrepareMutableContentsBuffer / mutableContentsBuffer). Adds regression tests
for a request in history and a response bound to a history request with empty
pending state.
2026-07-21 14:23:48 +00:00
Robbie Walmsley a4f02aabf0 Python: Fix header_provider headers not reaching streamable HTTP transport requests (#7218)
* Python: fix header_provider headers not reaching streamable HTTP requests

MCPStreamableHTTPTool.call_tool stores header_provider output in a
ContextVar, but the streamable HTTP transport sends requests from tasks
spawned at connect time, whose contexts never observe values set later.
The request hook therefore always read an empty dict on real connections
and the per-call headers (e.g. Authorization) were silently dropped.

Keep the ContextVar for in-context reads and add an instance-level
snapshot of the active call's headers that the request hook falls back
to across tasks.

* Python: serialize header_provider tool calls to prevent cross-call header mixing

Parallel tool invocations run concurrently per function-invocation batch,
so two call_tool invocations on the same MCPStreamableHTTPTool could
overwrite each other's active-header snapshot while requests were still
in flight, attaching the wrong per-call credentials. Hold a per-instance
lock for the duration of a header-bearing call, add a regression test
that fails without the lock, and normalize captured header casing in the
transport-task test.
2026-07-21 13:20:27 +00:00
HaoFeng Zhao afdf8af400 Python: Prevent compaction from emitting empty projections (#7219)
* Python: preserve a non-empty compaction projection

* Python: annotate compaction regression input

* Python: document compaction retention floor
2026-07-21 13:16:43 +00:00
Scarab Systems 9e836f7b42 Python: Return MCP tool-use sampling results (#7189)
* Python: support MCP sampling tool-use results

* Python: align MCP sampling test tool schemas

* Python: centralize MCP sampling content type
2026-07-21 12:27:34 +00:00
安妮的心动录 9cf5143321 .NET: Populate AgentResponse metadata in CopilotStudioAgent (#6791)
* .NET: Populate AgentResponse metadata in CopilotStudioAgent

Map CreatedAt, FinishReason, RawRepresentation and AdditionalProperties onto
AgentResponse and AgentResponseUpdate, and map the activity timestamp and
properties onto ChatMessage, so Copilot Studio agents expose the same metadata
surface as other AIAgent implementations. Streaming sets the finish reason on
the terminal update while still emitting already-received content if the source
faults. Add unit tests covering the metadata mapping.

* fix: add Async suffix to async test methods (IDE1006)
2026-07-20 21:38:24 +00:00
Giles Odigwe b6b16ddb75 Python: forward GitHubCopilotOptions verbatim to create_session (#7155)
* Python: forward GitHubCopilotOptions verbatim to create_session

Refactor the GitHub Copilot agent to forward the full options dict to the
Copilot SDK's create_session/resume_session instead of hand-mapping a fixed
subset. GitHubCopilotOptions stays as the curated, typed surface, but any
other create_session parameter (reasoning_effort, context_tier,
enable_citations, ...) is now passed through verbatim. Unknown keys surface
as TypeError from the SDK instead of being silently dropped.

De-duplicates the near-identical _create_session/_resume_session bodies into
a shared _build_session_kwargs helper.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: f9d016d5-4d8c-43f0-a8fb-f3cf3d1ad7eb

* Python: address review feedback on GHCP options passthrough

- Strip agent-internal/client-level keys (on_pre_tool_use, on_function_approval,
  timeout, cli_path, log_level, base_directory) from the forwarded kwargs so they
  cannot leak into create_session/resume_session and raise TypeError.
- Source caller tools from the merged options layer so tools supplied via
  default_options are honored instead of silently dropped.
- Honor a caller-supplied native 'hooks' dict in _build_session_hooks (composing
  with the on_pre_tool_use shortcut) instead of unconditionally overwriting it.
- Validate mock create_session/resume_session calls against the real SDK
  signatures in tests so invalid kwargs surface as TypeError, and add regression
  tests for the passthrough contract.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: f9d016d5-4d8c-43f0-a8fb-f3cf3d1ad7eb

* Python: avoid redundant re-read of model in _build_session_kwargs

model is popped from default_options into settings at init, so a per-run
model already lands in the merged kwargs. Keep that value when present and
only fall back to the resolved setting otherwise, instead of re-reading opts.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: f9d016d5-4d8c-43f0-a8fb-f3cf3d1ad7eb

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-07-20 18:08:55 +00:00
Evan Mattson c218067646 Python: Consolidate dependency updates (#7204)
* Bump uv from 0.11.28 to 0.11.29 in /python

Bumps [uv](https://github.com/astral-sh/uv) from 0.11.28 to 0.11.29.
- [Release notes](https://github.com/astral-sh/uv/releases)
- [Changelog](https://github.com/astral-sh/uv/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/uv/compare/0.11.28...0.11.29)

---
updated-dependencies:
- dependency-name: uv
  dependency-version: 0.11.29
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

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

* Bump zuban from 0.8.2 to 0.9.0 in /python

Bumps [zuban](https://github.com/zubanls/zubanls-python) from 0.8.2 to 0.9.0.
- [Release notes](https://github.com/zubanls/zubanls-python/releases)
- [Commits](https://github.com/zubanls/zubanls-python/compare/v0.8.2...v0.9.0)

---
updated-dependencies:
- dependency-name: zuban
  dependency-version: 0.9.0
  dependency-type: direct:development
  update-type: version-update:semver-minor
...

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

* PR #7146: Bump ty from 0.0.55 to 0.0.60 in /python

* Bump ruff from 0.15.20 to 0.15.22 in /python

Bumps [ruff](https://github.com/astral-sh/ruff) from 0.15.20 to 0.15.22.
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/0.15.20...0.15.22)

---
updated-dependencies:
- dependency-name: ruff
  dependency-version: 0.15.21
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

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

* Bump mypy from 2.2.0 to 2.3.0 in /python

Bumps [mypy](https://github.com/python/mypy) from 2.2.0 to 2.3.0.
- [Changelog](https://github.com/python/mypy/blob/master/CHANGELOG.md)
- [Commits](https://github.com/python/mypy/compare/v2.2.0...v2.3.0)

---
updated-dependencies:
- dependency-name: mypy
  dependency-version: 2.3.0
  dependency-type: direct:development
  update-type: version-update:semver-minor
...

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

* Bump prek from 0.4.8 to 0.4.10 in /python

Bumps [prek](https://github.com/j178/prek) from 0.4.8 to 0.4.10.
- [Release notes](https://github.com/j178/prek/releases)
- [Changelog](https://github.com/j178/prek/blob/master/CHANGELOG.md)
- [Commits](https://github.com/j178/prek/compare/v0.4.8...v0.4.10)

---
updated-dependencies:
- dependency-name: prek
  dependency-version: 0.4.10
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

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

* Bump azure-ai-projects from 2.2.0 to 2.3.0 in /python

Bumps azure-ai-projects from 2.2.0 to 2.3.0.

---
updated-dependencies:
- dependency-name: azure-ai-projects
  dependency-version: 2.3.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

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

* Bump types-python-dateutil in /python

Bumps [types-python-dateutil](https://github.com/python/typeshed) from 2.9.0.20260518 to 2.9.0.20260716.
- [Commits](https://github.com/python/typeshed/commits)

---
updated-dependencies:
- dependency-name: types-python-dateutil
  dependency-version: 2.9.0.20260716
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

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

* Bump mypy from 2.2.0 to 2.3.0 in /python

Bumps [mypy](https://github.com/python/mypy) from 2.2.0 to 2.3.0.
- [Changelog](https://github.com/python/mypy/blob/master/CHANGELOG.md)
- [Commits](https://github.com/python/mypy/compare/v2.2.0...v2.3.0)

---
updated-dependencies:
- dependency-name: mypy
  dependency-version: 2.3.0
  dependency-type: direct:development
  update-type: version-update:semver-minor
...

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

* Bump botocore from 1.43.45 to 1.43.49 in /python

Bumps [botocore](https://github.com/boto/botocore) from 1.43.45 to 1.43.49.
- [Commits](https://github.com/boto/botocore/compare/1.43.45...1.43.49)

---
updated-dependencies:
- dependency-name: botocore
  dependency-version: 1.43.49
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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

* PRs #7144/#7147: Align lab uv and ruff pins

* Regenerate lockfile for Python Dependabot PRs #7144-#7153

* Python: Support azure-ai-projects 2.3 session operations (#7150)

* Python: Apply Ruff 0.15.22 suppression updates (#7147)

* Python: Update tests for ty 0.0.60 (#7146)

* Python: Update Foundry samples for azure-ai-projects 2.3 (#7150)

* Python: Address dependency rollup review comments

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-07-20 18:01:24 +00:00
westey ac474100ce Python: [BREAKING] Graduate create_harness_agent out of experimental (#7120)
* Graduate harness agent

* Add agents.md update

* Fix build errors

* Address PR comments

* Fix build error
2026-07-20 18:00:28 +00:00
Theo van Kraay a057cd505c Python: Add agent-framework-azure-cosmos-memory context provider (#6719)
* Add agent-framework-azure-cosmos-memory context provider (draft)

Introduces CosmosMemoryContextProvider, a ContextProvider that wraps the azure-cosmos-agent-memory toolkit to give agents long-term, Cosmos DB-backed memory (fact/procedural recall + user summaries). Includes package scaffolding, unit tests (mocked client), live Azure integration tests (marked), samples, README, and AGENTS.md.

Draft: uv.lock is intentionally left unchanged. This package depends on azure-cosmos-agent-memory (requires Python >=3.11), which is unsatisfiable against the workspace's current >=3.10 floor, so adding it to the shared lock requires a workspace decision (raise floor to 3.11 or exclude from workspace). Test coverage to be expanded.

* ci: exclude azure-cosmos-memory from uv workspace resolution

The package depends on azure-cosmos-agent-memory which requires Python
>=3.11 and a prompty pre-release (>=2.0.0a9). Both are unsatisfiable
against the workspace's >=3.10 floor and pre-release policy, causing
uv sync to fail in every Python CI job. Exclude the package from the
shared workspace so it is resolved and tested as a standalone package.

* ci: fix code-quality failures for azure-cosmos-memory

- Strip trailing whitespace from package files (pre-commit trailing-whitespace hook)
- Exclude the package README from markdown-code-lint: the package is excluded
  from the uv workspace, so its README snippets import a module that is not
  installed in the workspace env and Pyright cannot resolve it

* Exclude azure-cosmos-memory README from markdown-code-lint task

* Address PR review comments on cosmos-memory context provider

- Wire credential into Cosmos and AI Foundry clients; let toolkit own
  DefaultAzureCredential when none supplied (remove dead import).
- Honor auto_extract=False by zeroing extraction/summary cadence thresholds.
- Skip whitespace-only conversation turns and store stripped content.
- Show confidence 0.0 and coerce confidence to float in _format_memories.
- Register both 'integration' and 'azure' pytest markers accurately.
- Fix duplicated install block in README.
- Update and extend unit tests for new credential wiring and fixes.

* Include azure-cosmos-memory in the uv workspace

Follow the github_copilot pattern for a package with a Python 3.11-only
dependency: lower requires-python to >=3.10 and gate azure-cosmos-agent-memory
behind a python_version >= '3.11' marker. Add a direct, gated prompty
pre-release dependency so the workspace's if-necessary-or-explicit prerelease
policy permits the toolkit's transitive prompty requirement. Guard the test
modules with pytest.importorskip so the 3.10 CI leg skips cleanly. Remove the
workspace exclude and the markdown-code-lint exclude, and regenerate uv.lock.

* Address review feedback on cosmos-memory provider

Rename provider parameters to match Agent Framework conventions:
foundry_endpoint (was ai_foundry_endpoint) and embedding_model/chat_model
(were *_deployment_name). Move DEFAULT_* to module-level constants, type
memory_types as a Literal, use DEFAULT_CONTEXT_PROMPT as the default value,
and add ProcessorConfig/CosmosMemorySettings TypedDicts. Resolve connection
settings via agent_framework load_settings with required-field validation,
replacing the manual getenv/raise blocks. Scope user_id/thread_id to the
provider state and drop the unpreventable first-turn warning.

Rewrite the samples around Agent (not raw SessionContext), provider-scoped
state, and session-id threading; use PEP 723 inline dependencies instead of a
samples dependency group; use a plain input() loop; remove the dead custom
processor stub. Update README/AGENTS for the renamed parameters and env vars.
Add a samples ruff per-file-ignores entry now that the package is linted in CI.

* Add emulator-backed vector search integration test

Bump azure-cosmos-agent-memory to >=0.2.0b2 (adds the embeddings/chat client
injection seam) and add tests/test_emulator.py: an integration (not azure)
suite that exercises real Cosmos vector search with a quantizedFlat index
against a local Cosmos DB emulator, using deterministic in-memory fakes for
embeddings and chat so no Azure AI Foundry account or LLM is required.

To run on a stock emulator the fixture strips the toolkit's full-text index
(the provider only does pure vector search) and requests provisioned autoscale
throughput instead of serverless. The suite skips cleanly when no emulator is
reachable.

* Fix CI typing and package checks for azure-cosmos-memory

The package recently joined the uv workspace, so its source and tests are now covered by the Test Typing Checks and Package Checks gates for the first time.

tests: rename stale constructor kwargs to the current provider API (foundry_endpoint/embedding_model/chat_model); use a typed _STUB_AGENT for the unused agent param so pyright/pyrefly/ty/zuban all accept it; make processor_config values ints; assert non-None memory_client in the emulator tests.

source: relax reportUnknown*/reportOptional* for this package only (the toolkit ships no py.typed; mirrors the hosting-telegram precedent); decouple the conditional toolkit import from the annotation type; use settings.get(); fix memory_types list invariance; drop a redundant None guard; read role via getattr.

* Apply pyupgrade: single-arg AsyncGenerator in test_integration

* Make Cosmos memory extraction drain transparently on provider exit

The provider now drains in-flight background memory extraction in __aexit__, so applications no longer need to call flush() in their own control flow; the client's close() would otherwise cancel pending extraction tasks. flush() is hardened against clients that expose no usable background-task registry.

sample: interactive_chat reads input via asyncio.to_thread so the event loop stays free and background extraction runs during the session; removes the manual flush now that the provider drains on exit.

tests: add explicit transparent-extraction integration tests (emulator: after_run schedules extraction and __aexit__ drains it; live Azure: a fact is extracted and recalled in a later session with no manual flush). Emulator tests reuse a single fixed database to avoid exhausting the emulator's partition budget across runs.

* Add custom extraction-prompt seam and sample to cosmos-memory provider

Adds a prompts_dir option to CosmosMemoryContextProvider that points the Agent Memory Toolkit pipeline at a caller-supplied directory of Prompty templates, so callers can override extract_memories.prompty to control what the extraction LLM produces. The toolkit exposes no public prompts-directory seam, so the provider contains the one internal touch (swapping the pipeline's template loader after the store connects); applies to both provider-built and supplied clients.

sample: interactive_chat_custom_extraction.py - the interactive chat wired with a custom coding-assistant extraction rubric. It derives a complete prompts directory at runtime (copies the bundled templates and augments extract_memories.prompty) so it stays schema-compatible with the installed toolkit.

tests: unit tests assert the provider redirects the pipeline loader only when prompts_dir is set; an emulator integration test proves end to end that a unique marker in a custom extract_memories.prompty reaches the extraction LLM call.

* docs: document prompts_dir custom-extraction seam in cosmos-memory README

Replaces the stale, non-functional CustomMemoryProcessor snippet with the working prompts_dir approach, lists the new interactive_chat_custom_extraction.py sample, and corrects the interactive-sample feature list.

* Address review: rename _new_session, drop defensive toolkit import guard

Sample (comment): rename _new_thread to _new_session in both interactive samples (a new session is the new thread).

Provider (comment): replace the _memory_toolkit_available flag + __init__ ImportError guard with a plain guarded import that re-raises a clear ImportError, matching the github_copilot package's pattern for its 3.11-only SDK. Kept requires-python >=3.10 (bumping this one workspace member to 3.11 would force the entire uv workspace lock floor to 3.11). Tests now run importorskip before importing the package, mirroring github_copilot.

* Pass cadence via cadence_thresholds instead of mutating os.environ

* Mark package alpha and drop private naming in samples

* Require Python 3.11 and inject user summary as untrusted context

* CI: exclude azure-cosmos-memory from uv sync on Python 3.10

* Re-trigger CI (flaky external link check)

* Require chat/embedding models instead of silent defaults

* Fix pyright: narrow resolved chat/embedding models to str

---------

Co-authored-by: Theo van Kraay <thvankra@microsoft.com>
2026-07-20 09:44:11 +00:00
Evan Mattson c66bb39ea2 Normalize durable workflow inputs (#7205) 2026-07-20 08:33:20 +00:00
Yufeng He 7c6b1e975f Python: fix compaction token count inflating non-ASCII text (#7124)
TokenBudgetComposedStrategy estimates tokens by feeding a JSON-serialized
message to the tokenizer, but _serialize_message() used ensure_ascii=True.
That escapes non-ASCII text into \uXXXX sequences, so CJK and other
non-Latin content is token-counted as the escape sequences rather than the
characters the model actually sees, inflating the estimate (~1.6x for mixed
Japanese, more for pure CJK) and skewing compaction/token-budget decisions.

Serialize with ensure_ascii=False, matching the ensure_ascii=False already
used elsewhere in this module. Only affects token estimation; the serialized
string is never stored or transmitted.

Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
2026-07-19 12:44:40 +00:00
Yufeng He 0d2925037d Python: preserve explicit null arguments in auto function calling (#7108)
* Python: preserve explicit null arguments in auto function calling

FunctionTool.invoke dumped validated arguments with model_dump(exclude_none=True),
which strips any argument the model set to null. A required nullable parameter
(e.g. unit: Literal["C","F"] | None) that the model deliberately sets to null was
therefore dropped, and the function failed to invoke on the missing argument.

Use exclude_unset instead: keep the arguments the model actually provided (null
included) and omit only the ones it left out, so the function's own defaults still
apply. Because the input model is generated from the function signature, its field
defaults match the signature defaults, so omitted optionals are unchanged.

Fixes #5934

Signed-off-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com>

* Python: extend null-arg fix to the auto function-calling path

The earlier change fixed FunctionTool.invoke, but _auto_invoke_function
(the path a model-emitted function_call actually takes) still ran
model_dump(exclude_none=True), so an explicit null for a required
nullable argument was still dropped and the call failed with a missing
argument. Switch it to exclude_unset to match invoke, and add a
regression test that drives _auto_invoke_function with an explicit null.

---------

Signed-off-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com>
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
2026-07-19 12:43:41 +00:00
Eduard van Valkenburg b5e635ed4d Python: isolate hosted session snapshots (#7141)
* Python: isolate hosted session snapshots

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 75d26ffd-7dc7-46b3-9966-9aaebb7b6bc3

* Python: avoid duplicate conversation snapshots

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 75d26ffd-7dc7-46b3-9966-9aaebb7b6bc3

* added some notes in the docstring
2026-07-18 11:59:24 +00:00
Eduard van Valkenburg 1036fa7438 Python: docs: add self-hosting sample snippets (#7104)
* docs: add self-hosting sample snippets

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 636b7fb2-381a-4d62-b5cf-d029efa3ad20

* docs: use stable hosting sample ranges

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 636b7fb2-381a-4d62-b5cf-d029efa3ad20

* docs: address hosting sample review feedback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 636b7fb2-381a-4d62-b5cf-d029efa3ad20

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-07-17 22:10:28 +00:00
Eduard van Valkenburg 62da382082 Python: Optimize shared serialization paths (#7165)
* Optimize core serialization paths

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: cda42f21-2500-4f78-a527-d6eeaeef922b

* Streamline AG-UI serialization

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: cda42f21-2500-4f78-a527-d6eeaeef922b

* Document shared serialization guidance

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: cda42f21-2500-4f78-a527-d6eeaeef922b

* Bound serialization protocol cache

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: cda42f21-2500-4f78-a527-d6eeaeef922b
2026-07-17 22:09:53 +00:00
Eduard van Valkenburg 3604ba70f6 Python: Normalize chat finish reasons (#7105)
* Python: Normalize chat finish reasons

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 45b65bfa-8e36-47b0-99d9-ec58ec60ace1

* Preserve Copilot finish reasons

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 45b65bfa-8e36-47b0-99d9-ec58ec60ace1

* fix claude finish reasons
2026-07-17 22:05:36 +00:00
Marco Minerva 3ab2630243 .NET: Refactor Workflows MessageMerger to preserve message order and structure (#6826)
* Refactor MessageMerger to preserve message order

Refactored MessageMerger to delegate update grouping and merging to M.E.AI, preserving the correct order and structure of assistant messages, especially for reasoning content without message IDs. Removed per-message bucketing and CreatedAt-based sorting. Added tests to verify message order and correct merging of reasoning and text updates.

* Set CreatedAt from merged responses preservation of original message timestamps during merging.

* Set merged message CreatedAt to current UTC time

Removed logic for tracking unique creation times and now always assign DateTimeOffset.UtcNow to the merged response's CreatedAt property. This simplifies timestamp handling during message merging.

* Refactor MessageMerger id-less folding logic

Refactored MessageMerger to fold identifierless reasoning segments into the following id'd message at the flattened-message level, ensuring correct merging across response buckets (fixes #6329). Updated ComputeMerged to merge id-less messages with the next message of the same role. Removed redundant per-bucket folding logic. Added unit tests to verify correct folding behavior and role matching.

* Remove unused property

 Removed the unused Role property from MessageMergeState for code cleanliness.

* Refactor MessageMerger to iterate backward for merging

Changed MessageMerger to iterate messages in reverse order, ensuring all consecutive messages without IDs preceding a message with an ID are merged correctly. Updated merging logic, index handling, and comments to reflect this new approach.

* Update code comment to better reflect its behavior.

---------

Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com>
2026-07-17 17:10:14 +00:00
Eduard van Valkenburg bc59c72170 Python: Add A2A hosting helpers (#7050)
* Python: Add A2A hosting helpers

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 5d6987cd-1b67-4ba1-8b54-3c50da6e7607

* Python: Preserve final A2A streaming output

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 5d6987cd-1b67-4ba1-8b54-3c50da6e7607

* Python: Clarify A2A conversion boundary

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 5d6987cd-1b67-4ba1-8b54-3c50da6e7607

* Python: Document A2A sample auth boundary

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 5d6987cd-1b67-4ba1-8b54-3c50da6e7607

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-07-17 16:58:39 +00:00
ssccinng d5f2c77b35 .NET: Honor terminal workflow outputs in Workflow.AsAIAgent responses (#6212)
* Fix workflow agent terminal output responses

* Address workflow agent response review feedback

---------

Co-authored-by: Peter Ibekwe <109177538+peibekwe@users.noreply.github.com>
2026-07-17 15:36:26 +00:00
VectorPeak 6afae2f9b4 Python: raise ValueError for malformed data URIs (#6916)
* Python: raise ValueError for malformed data URIs

* Address malformed data URI review feedback

---------

Co-authored-by: VectorPeak <VectorPeak@users.noreply.github.com>
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
2026-07-17 11:40:20 +00:00
Benke Qu cad81923e3 Python: fix: concurrent_agents sample incorrectly treats output as list[Message] (#6548)
* Python: fix: concurrent_agents sample treats output as list[Message] but it is AgentResponse

The default ConcurrentBuilder aggregator yields AgentResponse, not
list[Message]. The sample incorrectly cast the output to list[Message]
and iterated it directly. Fix by checking isinstance(output, AgentResponse)
and iterating output.messages instead.

* fix: remove warning print per review feedback

* fix: address review - remove unused Message import, update docs and sample output

- Remove unused Message import
- Update docstring: default aggregator yields AgentResponse objects, not list[Message]
- Fix sample output: remove user prompt entry (aggregator returns only assistant messages)
- Renumber sample output entries (researcher=01, marketer=02, legal=03)

---------

Co-authored-by: Benke Qu <bequ@microsoft.com>
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
2026-07-17 11:38:04 +00:00
Ahmed Muhsin 5ab8877ba5 Python: HITL respond-URL addressing from inside workflows (#7001)
* feat(durabletask): surface HITL respond-URL addressing to workflow executors

Let a workflow notify a human reviewer (e.g. email an approval link) from inside the
graph, without the caller threading the instanceId/requestId by hand.

- durabletask: the orchestrator injects host_context {instance_id, workflow_name,
  request_path_prefix} into each activity input; CapturingRunnerContext surfaces it as
  host_metadata. No new core API.
- azurefunctions: WorkflowHitlContext.from_context(ctx) builds the canonical
  respond/status URLs (returns None in-process so callers degrade gracefully).
  Re-exported through the agent_framework.azure lazy namespace.
- Nested sub-workflows: the address context (root instance + workflow name +
  accumulated {executor}~{ordinal}~ prefix) propagates down call_sub_orchestrator via a
  new SUBWORKFLOW_ADDRESS_KEY marker, so an executor at any depth builds a URL that
  targets the addressable top-level instance with a qualified request id. The per-child
  ordinal matches the read-side enumerate() index used by the status/respond endpoints.
  The marker is stripped from untrusted input alongside SUBWORKFLOW_INPUT_KEY
  (confused-deputy / info-leak guard).
- Samples 12 and 13 reworked into the retry-safe two-step notify pattern: the emitter
  generates an explicit request id and a downstream NotifyExecutor builds the URL and
  notifies, so failed upstream retries never produce a dead link.

Tests: unit coverage for the metadata round-trip, address/ordinal agreement (fan-out at
depth and nested prefix accumulation), marker stripping, and URL building; integration
tests assert the helper-built URL equals the server respondUrl and resumes the run, for
both the flat (12) and nested (13) samples.

* refactor(durabletask): read back request_info id instead of generating one in samples

Add WorkflowHitlContext.pending_request_id(ctx), an async helper that returns the
id request_info just generated (read from the runner context's pending request-info
events). This works on any host via the core RunnerContext protocol method, so it
needs no core change.

Samples 12 and 13 now call request_info() and read the id back to forward to the
NotifyExecutor, instead of minting a uuid by hand and passing request_id=. The
read-back happens in the same activity execution that generated the id, so the
pending request event and the notify message still commit together with the same id
(retry-safe; failed upstream retries notify no one).

* docs(azurefunctions): document request_info id read-back and notify safety

Tighten pending_request_id docstring to require calling it immediately after request_info, and explain why that is safe on the durable host (each executor runs in its own activity with its own runner context, so the pending set only holds this executor's requests and the newest is the one just emitted). Document the two-step notify pattern in the 12 and 13 sample READMEs, including the downstream-notifier retry safety and the nested address-prefix propagation.

* fix(python): resolve ty typing error and address PR review comments

- test_subworkflow_orchestration: replace the mypy-only type:ignore[arg-type] with a cast so the ty checker passes too (the other four checkers already honored the ignore).

- samples 12/13 README: guard the notify snippet against None before build_respond_url to match the documented graceful-degradation behavior.

- integration tests 12/13: reword comments that implied request_info now generates an explicit uuid4; it generates the id internally by default.

* fix(python): honor configurable Functions route prefix and address HITL PR review

- Resolve the route prefix from host.json (extensions.http.routePrefix, default api) in a new azurefunctions _routes module, used by both the server endpoints and WorkflowHitlContext, so a custom or empty routePrefix no longer 404s respond/status URLs (was hardcoded /api/ in four places).

- Extract respond/status URL construction into one shared builder called from _app.py and _hitl_context.py, removing the sync-by-test duplication.

- Broaden loopback detection (localhost, 127.0.0.0/8, 0.0.0.0, ::1, [::1]) via a _is_loopback helper so local links use http.

- Pin the host_context key names as shared constants in durabletask so producer and azurefunctions consumer cannot drift.

- Reword a stale base_url comment to reference WEBSITE_HOSTNAME.

- Add unit tests for the route module and loopback handling.

* refactor(azurefunctions): derive server-side HITL URLs from the request URL

The run and status endpoints now derive the base URL and route prefix from the incoming request URL (the value the host actually routed) via split_request_url, so the caller-visible respond/status URLs no longer depend on reading host.json on the server. The in-workflow helper keeps reading host.json since it has no request context. Replaces strip_route_prefix and updates its tests.

* test(durabletask): enforce sub-workflow ordinal and read-index agreement

Extract the read-side subworkflows grouping into a shared _index_subworkflows helper (used by the orchestrator) and add test_readside_index_matches_dispatch_ordinal, which round-trips a fan-out through that helper and asserts subworkflows[executor][ordinal] resolves to the child the dispatch stamped that ordinal onto. Turns the previously comment-only write-ordinal / read-index invariant into a shared, CI-enforced one.

* fix(azurefunctions): suppress bandit B104 on loopback host set
2026-07-16 22:06:25 +00:00
Jose Luis Latorre Millas f4e49958f3 samples: add AgentMemory (Neo4j-agent memory reimplemented in NET ) shopping assistant sample (#7096)
* samples: add Neo4j Shopping Assistant (standalone, published AgentMemory 1.0.1)

The .NET port of the official Neo4j Agent Memory "retail assistant" example
(neo4j-labs/agent-memory examples/microsoft_agent_retail_assistant, referenced
from the Learn integration page), which is currently Python-only.

Wires Neo4jMemoryContextProvider (AIContextProvider), MemoryToolFactory
memory tools, and a ProductCatalog of retail tools over a Neo4j :Product
graph, via the published AgentMemory + AgentMemory.AgentFramework 1.0.1
NuGet packages.

Lives at the repo root rather than under dotnet/samples/: that tree is
.NET 10 + Central Package Management + Microsoft.Agents.AI ~1.13 with
source ProjectReferences, while AgentMemory currently targets net9.0 +
Microsoft.Agents.AI 1.9.0. A repo-native version needs AgentMemory bumped
to track the newer Agents.AI/Extensions.AI line first. Cross-linked from
dotnet/samples/02-agents/AgentWithMemory/README.md as a "See also" entry,
same pattern already used for the cross-folder Custom Memory Implementation
link.

Verified: dotnet build succeeds (0 warnings, 0 errors) against the published
packages, proving the AgentMemory public surface is package-consumable.
Matches sibling AgentWithMemory samples' conventions (BOM + copyright file
header on .cs files, README sections: Features Demonstrated / Prerequisites
/ Environment Variables / Run the Sample / Expected Output).

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

* samples: move Neo4j shopping assistant into AgentWithMemory as Step06

Relocates the standalone shopping-assistant sample from the repo root into
dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step06_MemoryUsingAgentMemory,
following that folder's naming/README/solution conventions. Renames its identity
from "Neo4j" to "AgentMemory" (the library it actually demonstrates) since this
is a community .NET port, not an officially recognized Neo4j integration - Neo4j
is still referenced where it's a genuine technical detail (the graph backing
store, env vars, Cypher). Adds empty Directory.Build.props/targets markers so it
stays isolated from the repo's net10.0/CPM build, and registers it (skipped, like
the Mem0 sample) in the CI sample-verification list since it needs a live Neo4j
instance.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

* Update dotnet/samples/02-agents/AgentWithMemory/README.md

Co-authored-by: westey <164392973+westey-m@users.noreply.github.com>

* Update dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step06_MemoryUsingAgentMemory/AgentWithMemory_Step06_MemoryUsingAgentMemory.csproj

Co-authored-by: westey <164392973+westey-m@users.noreply.github.com>

* cleanup :)

* DefaultAzureCredential warning

* fixes - simplification userId

* minor doc fix

* NU1015 fix

* PR review fixes-improvements

* Bump AgentMemory to 1.2.0, let the context provider surface memory tools

WithMemoryOwnerScoping(sp) (1.1.0) already removed the need to manually
wrap agent.RunAsync in ownerContext.BeginOwnerScope(userId). This picks
up 1.2.0's ExposeMemoryToolsFromContextProvider option, so
Neo4jMemoryContextProvider now appends the memory tools to AIContext.Tools
itself on every model call — no more separate MemoryToolFactory wiring,
AIContextProviders = [memoryProvider] is enough.

Addresses westey-m's PR review suggestion.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

* improvements according to pr review comments

* Fix CI: use plural TargetFrameworks to actually restrict this sample to net10.0

Directory.Build.props sets a repo-wide TargetFrameworks (plural) list
before this project's own properties are evaluated, and the SDK decides
multi-targeting from that plural property at Sdk.props time. The prior
singular TargetFramework=net10.0 override didn't take effect early
enough, so restore still ran against net9.0/net8.0/netstandard2.0/net472
too - frameworks the published AgentMemory 1.2.0 packages don't support
(NU1202), plus surfaced an OpenTelemetry.Api advisory as an error
(NU1902) since TreatWarningsAsErrors is on repo-wide.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

* Fix CI: pin OpenTelemetry.Api to unblock NU1902 audit failure

The sample opts out of central package management, so it was pulling in
OpenTelemetry.Api 1.12.0 transitively (via Microsoft.Agents.AI), which has
a known moderate-severity vulnerability (GHSA-g94r-2vxg-569j). The repo
treats NuGet audit warnings as errors, so restore failed outright and took
down every dotnet-build matrix leg plus check-format.

Pinned OpenTelemetry.Api to 1.15.3, matching Directory.Packages.props.
With restore succeeding, previously-masked analyzer/format issues surfaced
and are fixed too: RCS1118 (const local for immutable Cypher queries),
CA1859 (List<IRecord> param instead of IReadOnlyList<IRecord>), and IDE1006
naming violations (s_seed field prefix, PascalCase Cypher/Shopper consts).

Verified locally with the same mcr.microsoft.com/dotnet/sdk:10.0 image CI
uses: dotnet build --warnaserror and dotnet format --verify-no-changes both
pass clean, and a full solution build completed ~24 min with zero errors.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

---------

Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>
Co-authored-by: westey <164392973+westey-m@users.noreply.github.com>
2026-07-16 15:39:23 +00:00
Eduard van Valkenburg 5282c158aa .NET: Fix LocalCodeAct validation and package checks (#7138)
* Fix LocalCodeAct validation and package checks

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: aecf332f-b940-41a7-ac3a-6fbbe9892141

* Address LocalCodeAct alias review feedback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: aecf332f-b940-41a7-ac3a-6fbbe9892141
2026-07-16 15:17:52 +00:00
feiyun0112 dde7635760 .NET: [Feature]: .NET Improve ChatClientAgentSession constructor (#7142)
* .NET: [Feature]: .NET Improve ChatClientAgentSession constructor

* Potential fix for pull request finding

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

* test: make deserialize test actually reproduce issue #7109

VerifyDeserializeWithWhenWritingNullOptions passed against both the old
and the fixed constructor, so it did not guard against the regression.

The bug only reproduces when required constructor parameters are respected
(the issue uses RespectRequiredConstructorParametersDefault=true). With
WhenWritingNull a null conversationId is omitted from the JSON, and STJ then
throws 'missing required properties including: conversationId' because the
constructor parameter had no default value.

Adding RespectRequiredConstructorParameters = true to the test options makes
the test red against the parameter-without-default constructor and green with
the default-valued constructor parameters, so it now protects the fix.

---------

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Roger Barreto <19890735+RogerBarreto@users.noreply.github.com>
2026-07-16 15:06:37 +00:00
King Star 85c00fc55b .NET: preserve HeadTailBuffer UTF-8 order (#7128)
Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com>
2026-07-16 10:03:43 +00:00
westey f19a129b55 Graduate FileMemoryProvider (#7114) 2026-07-16 09:38:59 +00:00
westey a376577263 Gradudate FileMemoryProvider (#7113) 2026-07-15 22:57:21 +00:00
Tao Chen b2549337ff Python: Best effort to serialize tool def to Json for observability (#7029)
* Best effort to serialize tool def to Json

* Fix formatting

* Fix tests

* Optimize json serialization

* Best effort: Add secret filtering

* Remove frozen set and only convert required fields

* Fix tests

* Address comments

* Fix typing
2026-07-15 20:43:36 +00:00
Peter Ibekwe 05834b56e3 Fix message ordering in workflow-hosted agents (#7123) 2026-07-15 19:40:47 +00:00
Roger Barreto 42ae534a07 CI: resolve PR author in community team check (#7129)
* CI: resolve PR author in community team check

pull_request_target events expose the author on payload.pull_request, not payload.issue. Read that field first and fall back to pulls.get so limit-community-prs no longer calls issues.get and fails with 401.

* Docs: clarify issueNumber accepts PR numbers
2026-07-15 18:14:02 +00:00
Evan Mattson a17102f9f5 Harden manual integration test trust boundary (#7081)
* Harden manual integration test workflow

Require two write-capable approvals for the exact PR head SHA, pin all targets to immutable commits, and narrow secret and OIDC access.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: b8c7d85f-7576-4fc7-a7b5-c77833344088

* Require integration workflow credentials

Declare credentials consumed by the reusable integration workflows as required while retaining the explicitly optional Foundry models key.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: b8c7d85f-7576-4fc7-a7b5-c77833344088

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-07-15 17:54:52 +00:00
westey b3f2e53923 .NET: [BREAKING] Graduate ToolApprovalAgent and add ToolAutoApprovalRuleContext (#7107)
* Graduate ToolApprovalAgent and introduce tool auto approval context

* Address PR comments
2026-07-15 09:21:12 +00:00
Chris Brown b5300fe0c0 Python: fix per-run additional_beta_flags leaking into Anthropic request kwargs (#7060)
* Python: fix per-run additional_beta_flags leaking into Anthropic request kwargs

_prepare_options copied every key from the caller-supplied options dict
into run_options except "instructions" and "response_format". A
per-run additional_beta_flags value is correctly folded into the betas
set by _prepare_betas, but the raw key was never excluded, so it
survived into run_options and was forwarded straight through to
AsyncMessages.create(), which rejects it with TypeError: got an
unexpected keyword argument 'additional_beta_flags'. Add it to the
exclusion set alongside the other framework-level keys.

Fixes #5764

* Exclude additional_beta_flags from filtered_kwargs too

Copilot's review on the original fix pointed out the exclusion only
covered the options-dict copy, not kwargs passed directly to
_prepare_options — so additional_beta_flags supplied as a raw kwarg
would still leak through and reproduce the same TypeError. Add the
same exclusion to filtered_kwargs for consistency, with a regression
test covering the kwarg path.

---------

Co-authored-by: Chris Brown <albatrossflyon1@gmail.com>
2026-07-14 23:02:55 +00:00
Evan Mattson c35a63ed8d Python: feat: cross-session origin attribution on context messages (#7041)
* Python: feat: cross-session origin attribution on context messages

Add an optional origin_session_id parameter to SessionContext.extend_messages
that propagates into the existing _attribution payload on
Message.additional_properties. Downstream context observers can use it to
detect when a provider injects content stored under a different session than
the requesting one.

Populate the field from the harness memory consolidation pipeline
(_harness/_memory.py) when injected topics include contributions from
sessions other than the current one. Add a self-contained sample observer
under samples/02-agents/context_providers/cross_session_observer.py
demonstrating how to subscribe to the signal.

Backward-compatible: omitting the parameter preserves the existing
attribution shape exactly. Tests added in test_sessions.py and
test_harness_memory.py cover the new parameter, the harness cross-session
case, and the same-session case.

Motivated by Dai et al., Stateful Agent Backdoor (arXiv:2605.06158, May
2026), which specifically surveys MAF in section 6.1 / Table 10.
See #5914 for design discussion.

Surfaced during independent audit conducted by @finnoybu (Ken Tannenbaum, AEGIS Initiative); [MEDIUM, python/packages/core].

* Address cross-session attribution review feedback

* Address follow-up review feedback

* Address follow-up review comments

* Address origin attribution review feedback

---------

Co-authored-by: finnoybu <21694570+finnoybu@users.noreply.github.com>
2026-07-14 17:34:52 +00:00
Rince Yuan 47cd0a508d docs/.NET: fix typos in XML doc comments, ADR docs, and test comments (#7085)
- Fix double period in AnthropicClientExtensions.cs XML param docs (lines 23, 77)
- Fix double period in IScopedContentProcessor.cs XML param doc (line 20)
- Fix 'similar the the' -> 'similar to the' in ADR 0009 (line 1092)
- Fix 'reponse' -> 'response' in ADR 0001 (line 142)
- Fix 'retreive' -> 'retrieve' in ChatClientAgentTests.cs (line 467)
- Remove leftover template placeholder from ADR 0001 and 0006 frontmatter

Co-authored-by: j-zhangyiyuan <j-zhangyiyuan@microsoft.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
Co-authored-by: Giles Odigwe <79032838+giles17@users.noreply.github.com>
2026-07-14 17:06:46 +00:00
Giles Odigwe 56e9a8f74c Python: Make foundry toolbox MCP skills sample self-contained (#7099)
* Python: Make foundry toolbox MCP skills sample self-contained

Rework sample 12 (foundry_toolbox_mcp_skills) so users can build it from
zero with azd, mirroring samples 04 and 09:

- Bundle two single-file SKILL.md skills (support-style, escalation-policy)
  and a skills-only toolbox.yaml (with one connectionless code_interpreter
  tool, required by `azd ai toolbox create`).
- Rewrite the README as an azd-native, from-zero guide (create skills ->
  create toolbox -> set TOOLBOX_ENDPOINT -> run) and fix the stale
  MCPSkillsSource API description to match main.py.
- Switch config from TOOLBOX_NAME to the versioned TOOLBOX_ENDPOINT
  (.env.example, agent.yaml, agent.manifest.yaml); add .azdignore.

Also enable the sample to run unattended behind ResponsesHostServer:

- Forward disable_load_skill_approval / disable_read_skill_resource_approval
  / disable_run_skill_script_approval from FoundryToolbox.as_skills_provider()
  to the underlying SkillsProvider, so load_skill needs no approval round-trip
  (the Responses host runs without an AgentSession, which the default approval
  flow requires). main.py now uses as_skills_provider(disable_load_skill_approval=True).
- Add unit tests covering the default and overridden approval behaviour.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 4f14f83d-1868-45c1-be1a-12f49a58ac36

* Python: Address PR review on toolbox MCP skills sample

- Remove the unused parameters section from agent.manifest.yaml (TOOLBOX_ENDPOINT
  is supplied via environment_variables, matching sample 04).
- README: state the sample is self-contained directly instead of contrasting
  with the C# sample.
- README: describe skill discovery behaviour without naming the internal
  MCPSkillsSource class.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 4f14f83d-1868-45c1-be1a-12f49a58ac36

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-07-14 17:03:26 +00:00
westey ba0ad2d1d2 Gradudate ToolApprovalMiddleware (#7106) 2026-07-14 11:16:10 +00:00
Evan Mattson b123480b65 Python: Fix AG-UI workflow handoff replay results (#7102)
* Fix AG-UI workflow handoff replay results

Decisions:
- Reconcile finalized function results only for call IDs exposed in the current run, and skip results already emitted or never exposed.
- Treat message-derived function results as workflow responses only when their IDs match pending interrupts.

Files:
- Updated _workflow_run.py reconciliation and resume filtering.
- Added runner and public two-turn handoff acceptance coverage.
- Expanded finalized-response call-ID, privacy, and deduplication tests.

Verification:
- uv run poe test -P ag-ui
- uv run poe syntax -P ag-ui -C
- uv run poe pyright -P ag-ui
- uv run poe test-typing -P ag-ui

Notes:
- No blockers. The handoff sample remains unchanged; local PRD and issue files are not included.

* Prevent duplicate AG-UI workflow tool results

* Preserve finalized AG-UI tool results

* Use AG-UI text emission controls
2026-07-14 09:29:46 +00:00
Evan Mattson 4c0d9ed43c Python: .NET: Consolidate Dependabot dependency updates (#7103)
* Bump Anthropic from 12.31.0 to 12.35.1

---
updated-dependencies:
- dependency-name: Anthropic
  dependency-version: 12.35.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

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

* #7070 Bump Anthropic.Foundry from 0.6.0 to 0.7.1

* Bump astral-sh/setup-uv from 7.6.0 to 8.3.2

Bumps [astral-sh/setup-uv](https://github.com/astral-sh/setup-uv) from 7.6.0 to 8.3.2.
- [Release notes](https://github.com/astral-sh/setup-uv/releases)
- [Commits](https://github.com/astral-sh/setup-uv/compare/37802adc94f370d6bfd71619e3f0bf239e1f3b78...11f9893b081a58869d3b5fccaea48c9e9e46f990)

---
updated-dependencies:
- dependency-name: astral-sh/setup-uv
  dependency-version: 8.3.2
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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

* Bump actions/cache/save from 5.0.5 to 6.1.0

Bumps [actions/cache/save](https://github.com/actions/cache) from 5.0.5 to 6.1.0.
- [Release notes](https://github.com/actions/cache/releases)
- [Changelog](https://github.com/actions/cache/blob/main/RELEASES.md)
- [Commits](https://github.com/actions/cache/compare/27d5ce7f107fe9357f9df03efb73ab90386fccae...55cc8345863c7cc4c66a329aec7e433d2d1c52a9)

---
updated-dependencies:
- dependency-name: actions/cache/save
  dependency-version: 6.1.0
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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

* Bump github/codeql-action/analyze from 4.35.5 to 4.37.0

Bumps [github/codeql-action/analyze](https://github.com/github/codeql-action) from 4.35.5 to 4.37.0.
- [Release notes](https://github.com/github/codeql-action/releases)
- [Changelog](https://github.com/github/codeql-action/blob/main/CHANGELOG.md)
- [Commits](https://github.com/github/codeql-action/compare/9e0d7b8d25671d64c341c19c0152d693099fb5ba...99df26d4f13ea111d4ec1a7dddef6063f76b97e9)

---
updated-dependencies:
- dependency-name: github/codeql-action/analyze
  dependency-version: 4.37.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

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

* Bump softprops/action-gh-release from 2.6.2 to 3.0.1

Bumps [softprops/action-gh-release](https://github.com/softprops/action-gh-release) from 2.6.2 to 3.0.1.
- [Release notes](https://github.com/softprops/action-gh-release/releases)
- [Changelog](https://github.com/softprops/action-gh-release/blob/master/CHANGELOG.md)
- [Commits](https://github.com/softprops/action-gh-release/compare/3bb12739c298aeb8a4eeaf626c5b8d85266b0e65...718ea10b132b3b2eba29c1007bb80653f286566b)

---
updated-dependencies:
- dependency-name: softprops/action-gh-release
  dependency-version: 3.0.1
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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

* Bump dorny/paths-filter from 4.0.1 to 4.0.2

Bumps [dorny/paths-filter](https://github.com/dorny/paths-filter) from 4.0.1 to 4.0.2.
- [Release notes](https://github.com/dorny/paths-filter/releases)
- [Changelog](https://github.com/dorny/paths-filter/blob/master/CHANGELOG.md)
- [Commits](https://github.com/dorny/paths-filter/compare/fbd0ab8f3e69293af611ebaee6363fc25e6d187d...7b450fff21473bca461d4b92ce414b9d0420d706)

---
updated-dependencies:
- dependency-name: dorny/paths-filter
  dependency-version: 4.0.2
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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

* Bump astral-sh/setup-uv in /.github/actions/python-setup

Bumps [astral-sh/setup-uv](https://github.com/astral-sh/setup-uv) from 6.8.0 to 8.3.2.
- [Release notes](https://github.com/astral-sh/setup-uv/releases)
- [Commits](https://github.com/astral-sh/setup-uv/compare/d0cc045d04ccac9d8b7881df0226f9e82c39688e...11f9893b081a58869d3b5fccaea48c9e9e46f990)

---
updated-dependencies:
- dependency-name: astral-sh/setup-uv
  dependency-version: 8.3.2
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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

* Align workflow action versions

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-07-14 09:18:27 +00:00
t-anjan 1c0082721c Python: Fix structured value parsing for split text chunks (#6990)
* Fix structured value parsing for split text chunks

* Potential fix for pull request finding

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

* Fix structured value parsing for split text chunks

---------

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
2026-07-14 08:39:11 +00:00
S3rj 6c0950adeb fix: clarify require_confirmation docstring to reflect confirm_changes HITL gating (#6884)
Co-authored-by: Sergey Borisov <sergey.borisov@dataimpact.io>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
2026-07-14 08:01:58 +00:00
Hasan Ghomi f1ba16e3fd Python: Fix Magentic manager duplicating conversation history (#6297)
* Python: Fix Magentic manager duplicating conversation history

_complete() reused one persistent AgentSession, so the default history provider
re-injected prior turns on top of the full prompt the manager already rebuilds
each call — duplicating task/facts/plan and compounding every round. Use a fresh
session per call; keep self._session only for
checkpointing. GroupChatOrchestrator is unaffected. Add a regression test and
update the session-propagation test.

* Python: Clean up Magentic manager per Copilot review (drop dead _session)

---------

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
2026-07-14 08:01:18 +00:00
Giles Odigwe cba77e3cd0 Python: quiet A2AExecutor logging for unmapped content types (#7034)
* Python: quiet A2AExecutor logging for unmapped content types

Tool-use responses include function_call/function_result content that the A2A executor does not surface, causing a WARNING per tool call. Log these at DEBUG and skip instead, matching the outbound content-conversion convention used across the Python chat clients.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: ee74cc55-44df-4fcf-b38f-1f79f2600dfc

* Address PR review: assert debug log args and drop redundant cast

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: ee74cc55-44df-4fcf-b38f-1f79f2600dfc
2026-07-14 07:44:31 +00:00
Eduard van Valkenburg 7ca8bb55b6 Python: Add Telegram hosting helpers and samples (#7047)
* Python: Add Telegram hosting helpers

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 5d6987cd-1b67-4ba1-8b54-3c50da6e7607

* Python: Exclude Telegram samples from aggregate typing

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 5d6987cd-1b67-4ba1-8b54-3c50da6e7607

* Python: Address Telegram helper review feedback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 5d6987cd-1b67-4ba1-8b54-3c50da6e7607

* Python: Serialize Telegram webhook sessions

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: d76a9c32-d170-426d-a64f-b70958b08b12
2026-07-14 07:40:12 +00:00
westey d93fc2dd74 .NET: [BREAKING] Harness: Switch FileAccess to opt-in (#7093)
* Switch FileAcessProvider on Harness to opt-in

* Address PR comment

---------

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
2026-07-14 07:08:33 +00:00
Nick Brady 54617557e6 Update Foundry branding (#6999)
Replace user-facing Azure AI Foundry branding with Microsoft Foundry across docs, samples, comments, and display text while preserving technical identifiers.

Co-authored-by: Copilot App <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
2026-07-14 06:44:26 +00:00
Syed Osama Ali Shah df198005fd Python: fix: preserve function-call name when merging streaming deltas (#6809)
* fix: preserve function-call name when merging streaming deltas

`Content._add_function_call_content` built the merged name with
`getattr(self, "name", getattr(other, "name", None))`. Because
`Content.__init__` always sets `self.name` (defaulting to `None`), the
attribute is never missing, so the `getattr` default is never consulted
and `other.name` is ignored. When two function_call contents are merged
and only the second carries the name -- e.g. a streaming delta where the
function name arrives after the first chunk -- the name was silently
dropped.

Use the same "either side" pattern already used for the sibling
`exception` field on the next line: `getattr(self, "name", None) or
getattr(other, "name", None)`. Extend the existing merge test to cover
the late-name and both-None cases.

* test: construct nameless function-call deltas via Content(...) directly

Per review (pyright `reportArgumentType`): `Content.from_function_call`
annotates `name: str`, so passing `name=None` to model a streaming delta
with no name yet tripped the typing gate. Build those nameless deltas
with the `Content("function_call", ...)` constructor instead (its `name`
param is `str | None`) — the factory just wraps that same constructor, so
the runtime objects and the merge assertions are unchanged.

---------

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
2026-07-14 06:36:57 +00:00
westey 0ceca9a76a Add name collision warnings for auto-approvals (#7090)
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
2026-07-14 06:35:38 +00:00
westey 23977a6045 .NET: Add name collision warnings for auto-approvals (#7089)
* Add name collision warnings for auto-approvals

* Address PR comments
2026-07-14 06:32:38 +00:00
Evan Mattson 18b03ea487 Python: adjust checkpoint encoding handling (#6579)
* Adjust checkpoint encoding handling

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Refine checkpoint encoding handling

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Adjust checkpoint dict encoding

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Clarify checkpoint unpickler blocked globals

* Preserve typed HITL requests in durable activities

* test: skip flaky durabletask multi-turn integration test

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-07-14 15:21:12 +09:00
Evan Mattson 56c4425db2 Python: bridge AG-UI request state and session continuity (#7084)
* Python: bridge AG-UI request state into sessions

Decisions:
- Project resolved AG-UI Shared State into the per-run AgentSession without typed restoration.
- Preserve existing local/service session identifiers and keep AG-UI state out of provider metadata.

Files changed:
- packages/ag-ui/agent_framework_ag_ui/_agent_run.py
- packages/ag-ui/tests/ag_ui/test_endpoint.py

Verification:
- uv run poe check -P ag-ui
- uv run poe test -P ag-ui (912 passed)

Notes:
- Scoped cross-run Session Continuation State remains for the next dependent issue.

* Python: persist scoped AG-UI session continuity

Decisions:
- Store private Session Continuation State atomically in scoped thread snapshots and restore it through the core AgentSession contract.
- Exclude Shared State keys, all HistoryProvider buckets, and tool approval state; request overlays evict colliding private values.
- Finalize interrupted response streams before snapshotting so provider after_run mutations are included.

Files changed:
- packages/ag-ui/agent_framework_ag_ui/_agent_run.py
- packages/ag-ui/agent_framework_ag_ui/_snapshots.py
- packages/ag-ui/tests/ag_ui/test_endpoint.py
- packages/ag-ui/tests/ag_ui/test_snapshots.py
- packages/ag-ui/AGENTS.md

Verification:
- uv run poe test -P ag-ui (921 passed)
- uv run poe check -P ag-ui
- uv run poe typing -P ag-ui

Notes:
- Lifecycle, isolation, and broader storage guidance remain for the next dependent issue.

* Python: document AG-UI session continuity lifecycle

Decisions:
- Keep scoped thread snapshots as the single reset and continuity boundary, with missing request Shared State preserving private continuation.
- Document trusted typed-restoration storage, State Authorities, custom-store round trips, and one-active-run last-writer-wins consistency.
- Verify failure, hydration privacy, scope/thread isolation, and reset mechanics through public endpoint and store seams.

Files changed:
- packages/ag-ui/README.md
- packages/ag-ui/tests/ag_ui/test_endpoint.py
- packages/ag-ui/tests/ag_ui/test_snapshots.py

Verification:
- uv run pytest -q <focused lifecycle tests> (6 passed)
- uv run poe test -P ag-ui
- uv run poe syntax -P ag-ui -C
- uv run poe typing -P ag-ui
- uv run poe check -P ag-ui
- uv run poe markdown-code-lint

Notes:
- No runtime capability probe, secondary state store, locking, or configuration flag was added.
- No blockers remain for this lifecycle and guidance slice.

* Python: harden AG-UI session continuity

* Python: isolate AG-UI request state
2026-07-14 04:55:46 +00:00
Evan Mattson 13066cdf96 Python: Refine DevUI request logging (#7083)
* Refine DevUI request logging

* Address DevUI logging review feedback
2026-07-14 03:40:18 +00:00
westey f11cfd9d76 Switch FileAcessProvider on Harness to opt-in (#7094) 2026-07-14 02:26:59 +00:00
Evan Mattson 774fc94bd2 Enable manual issue triage (#7098) 2026-07-14 11:04:38 +09:00
Peter Ibekwe 4bac2c2c05 Python: Promote python declarative workflows to stable version (#7065)
* Promote python declarative workflows to stable version

* Updated changelog with PR detail.

* Updated to address pr comments.

* Remove changelog update
2026-07-13 22:30:21 +00:00
pratik wayase 43568f1ef2 Fix: coalesce reasoning deltas into single block when content.id is None (#6804)
python/packages/ag-ui/tests/ag_ui/test_run_commoclear
:wq
2026-07-13 21:11:22 +00:00
VectorPeak 52005ff17d Python: accept AG-UI state data URI parameters (#6905)
* Python: Accept AG-UI state data URI parameters

* Python: Handle invalid AG-UI state base64

---------

Co-authored-by: VectorPeak <VectorPeak@users.noreply.github.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
2026-07-13 21:05:27 +00:00
pratik wayase a4e4a5a51c Python: Fix: Ollama parallel tool calls collide on same call_id (#6822)
* Fix: Ollama parallel tool calls collide on same call_id

* fix(ollama): use uuid4 for tool call IDs and support colons in tool names

---------

Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
2026-07-13 21:02:24 +00:00
Alireza Afzali c8fb491644 Python: docs: add env example files for durabletask samples (#5948)
* docs: add env example files for durabletask samples

* docs: clarify env example values and comments

* docs: set default Redis URL in streaming sample env example
2026-07-13 21:01:19 +00:00
westey e57f046d8a Graduate mode and todo providers (#7052) 2026-07-13 13:47:58 +00:00
westey c9b19e831f Gradudate mode and todo providers (#7053) 2026-07-13 13:47:53 +00:00
westey beb65b21a8 .NET: [BREAKING] Graduate message injection out of experimental (#7044)
* Remove experiemental flags for MessageInjection component

* Improve locking on message injection.
2026-07-13 11:26:01 +00:00
westey b3d523ee50 Python: [BREAKING] Fix harness before-strategy compaction under per-service-call persistence (#7055)
* Fix middleware ordering to ensure compaction runs

* Address PR comments

* Fix build issue
2026-07-13 09:51:00 +00:00
Copilot 6f38cb724d .NET: Enable Valkey NuGet package publishing (#7059)
* Initial plan

* Enable Valkey NuGet package publishing

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
2026-07-13 09:31:49 +00:00
Tao Chen 8e74360d52 Python: Add Microsoft OpenTelemetry Distro sample (#5632)
* Add Microsoft OpenTelemetry Distro sample

* Verify and add README

* Add dependency header

* Add maf dependency in PEP 723 block
2026-07-13 01:51:15 +00:00
ByteWise 7f4cc296fd Python: preserve tool span context for parallel calls (#6512)
* Python: preserve tool span context for parallel calls

* Python: address parallel tool span review feedback

* Python: fix parallel tool span test checks

---------

Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
2026-07-13 00:07:53 +00:00
Benke Qu f3057ef20c Python: fix: clear service_session_id in _agent_wrapper when propagate_session=True (#5875)
* fix: clear service_session_id in _agent_wrapper when propagate_session=True

When propagate_session=True, the child agent inherits the parent's
service_session_id. After the parent's first LLM call, MAF auto-populates
this from the Responses API conversation_id. The child sends it as
previous_response_id which the server rejects because the parent's
tool_call is still pending (400 error).

This fix saves and clears service_session_id before calling the child
agent and restores it in a finally block, preserving session.state
sharing while isolating the server-side conversation pointer.

Fixes #5874

* refactor: use child session copy instead of in-place mutation

Address Copilot review comments:
- Create a child AgentSession with shared state dict but isolated
  service_session_id, avoiding race conditions under concurrent
  asyncio.gather tool invocations.
- Update tests to verify child gets a separate session object and
  that child-set service_session_id does not leak to parent.

* fix: update test_chat_agent_as_tool_propagate_session_true for child session isolation

The existing test asserted captured_session is parent_session, but since
we now create a separate child AgentSession (to avoid racing under concurrent
asyncio.gather), the child is a different object. Updated assertions to verify:
- child is NOT the parent object (isolation)
- child shares the same session_id and state dict (by reference)
- child's service_session_id is None (isolated)

* fix: add type narrowing asserts for captured_session

Add 'assert captured_session is not None' before attribute access to
satisfy mypy/pyright type checking on Optional values.

* Python: Fix test typing checks

---------

Co-authored-by: Benke Qu <bequ@microsoft.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>
2026-07-12 23:37:53 +00:00
Eduard van Valkenburg 68136ee081 Python: Clean up dependency groups and compatibility (#7046)
* Python: Clean up dependency management

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 2f7b1c89-f3ff-418d-ab4e-4f014fda308f

* Python: Harden Mistral SDK import fallback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot-Session: 2f7b1c89-f3ff-418d-ab4e-4f014fda308f
2026-07-10 22:40:42 +00:00
Peter Ibekwe 875031ff56 Fix broken sample 2026-07-10 11:26:05 -07:00
Evan Mattson 87af313119 Python: [BREAKING]: Emit TOOL_CALL events for workflow participant tool calls in AG-UI (#7039)
* Python: emit participant tool calls in AG-UI workflows

Decisions:
- Pass function call, function result, and approval request content from streaming agent updates regardless of role.
- Preserve the assistant-role gate for text and reuse the shared AG-UI content emitters without dual custom-event emission.

Files changed:
- packages/ag-ui/agent_framework_ag_ui/_workflow_run.py
- packages/ag-ui/tests/ag_ui/test_workflow_run.py

Verification:
- uv run poe test -P ag-ui
- uv run poe pyright -P ag-ui
- uv run poe test-typing -P ag-ui
- uv run poe syntax -P ag-ui -C

Notes:
- Existing workflow golden scenarios do not exercise participant tool calls, so no snapshot changed.
- No blockers.

* Python: guard participant tool call duplication

Decisions:
- Assert the workflow stream emits one TOOL_CALL_START when a streamed call is also present in final conversation history.
- Keep production flow unchanged because latest-assistant final-response conversion prevents duplication.

Files changed:
- packages/ag-ui/tests/ag_ui/test_workflow_run.py

Verification:
- uv run pytest packages/ag-ui/tests/ag_ui/test_workflow_run.py -k 'participant_tool_call or repeat_tool_call' -q
- uv run poe test -P ag-ui
- uv run poe pyright -P ag-ui
- uv run poe test-typing -P ag-ui
- uv run poe syntax -P ag-ui -C
- git diff --check

Notes:
- No blockers; no call-id guard was required.

* Python: scope workflow tool content bypass to resumable tool calls

- Exclude approval request content from the role bypass. Workflow approvals
  resume through request_info pending state, so an approval interrupt emitted
  from streamed content would have no pending request to resume against.
- Admit mcp_server_tool_call and mcp_server_tool_result so provider-hosted MCP
  tool calls from workflow participants emit standard tool call events.
- Add unit tests for MCP passthrough, approval exclusion, and mixed
  text-plus-tool content in non-assistant updates.
2026-07-10 16:58:07 +00:00
Evan Mattson 9ac548ad15 Python: keep attachments close (#7038)
* Python: keep attachments close

* Python: close attachment edge cases
2026-07-10 16:57:29 +00:00
Peter Ibekwe 737042fc93 Fix workflow session bug (#7032) 2026-07-10 16:56:57 +00:00
Patrick Woo-Sam e677ccc3b1 .NET: Fix CompactionMessageIndex.IsSummaryMessage (#7042)
* Fix CompactionMessageIndex.IsSummaryMessage

* Add more robust JsonElement value checking and tests cases
2026-07-10 15:03:26 +00:00
Theo van Kraay d9c0c36379 Fix CosmosChatHistoryProvider: omit ttl when MessageTtlSeconds is null (#6992) (#7030) 2026-07-10 13:01:59 +00:00
HaoJun 32a547a1a7 Python: bind AG-UI tool arguments to call IDs (#6342)
Co-authored-by: White-Mouse <15983334+White-Mouse@users.noreply.github.com>
2026-07-10 06:54:53 +00:00
811 changed files with 32066 additions and 5857 deletions
+112
View File
@@ -0,0 +1,112 @@
name: Get GitHub automation token
description: Creates a GitHub App installation token with a temporary PAT fallback
inputs:
mode:
description: Authentication mode (app, app-with-fallback, or pat)
required: false
default: app-with-fallback
azure-client-id:
description: Client ID of the Azure workload identity
required: false
azure-tenant-id:
description: Azure tenant ID
required: false
azure-subscription-id:
description: Azure subscription containing the Key Vault
required: false
key-vault-name:
description: Azure Key Vault name
required: false
key-name:
description: Key Vault key used to sign the GitHub App JWT
required: false
github-app-client-id:
description: GitHub App client ID
required: false
github-app-installation-id:
description: GitHub App installation ID
required: false
repository:
description: Repository to include in the installation token
required: false
fallback-token:
description: PAT used temporarily when app authentication is unavailable
required: false
outputs:
token:
description: GitHub App installation token or fallback PAT
value: ${{ steps.select-token.outputs.token }}
source:
description: Selected authentication source
value: ${{ steps.select-token.outputs.source }}
runs:
using: composite
steps:
- name: Validate authentication mode
shell: bash
env:
AUTH_MODE: ${{ inputs.mode || 'app-with-fallback' }}
run: |
if [[ "$AUTH_MODE" != "app" && "$AUTH_MODE" != "app-with-fallback" && "$AUTH_MODE" != "pat" ]]; then
echo "::error::Unsupported GitHub authentication mode."
exit 1
fi
- name: Sign in to Azure
id: azure-login
if: ${{ (inputs.mode || 'app-with-fallback') != 'pat' }}
continue-on-error: true
uses: azure/login@a457da9ea143d694b1b9c7c869ebb04ebe844ef5 # v2
with:
client-id: ${{ inputs.azure-client-id }}
tenant-id: ${{ inputs.azure-tenant-id }}
subscription-id: ${{ inputs.azure-subscription-id }}
- name: Create GitHub App installation token
id: app-token
if: ${{ (inputs.mode || 'app-with-fallback') != 'pat' && steps.azure-login.outcome == 'success' }}
continue-on-error: true
shell: bash
env:
AZURE_SUBSCRIPTION_ID: ${{ inputs.azure-subscription-id }}
KEY_VAULT_NAME: ${{ inputs.key-vault-name }}
KEY_NAME: ${{ inputs.key-name }}
GITHUB_APP_CLIENT_ID: ${{ inputs.github-app-client-id }}
GITHUB_APP_INSTALLATION_ID: ${{ inputs.github-app-installation-id }}
TARGET_REPOSITORY: ${{ inputs.repository }}
run: |
token="$(node "$GITHUB_ACTION_PATH/create-token.js")"
echo "::add-mask::$token"
echo "token=$token" >> "$GITHUB_OUTPUT"
- name: Select authentication token
id: select-token
shell: bash
env:
AUTH_MODE: ${{ inputs.mode || 'app-with-fallback' }}
APP_TOKEN: ${{ steps.app-token.outputs.token }}
FALLBACK_TOKEN: ${{ inputs.fallback-token }}
run: |
if [[ "$AUTH_MODE" != "pat" && -n "$APP_TOKEN" ]]; then
token="$APP_TOKEN"
source="app"
echo "::notice::GitHub authentication source: app"
elif [[ "$AUTH_MODE" == "app-with-fallback" && -n "$FALLBACK_TOKEN" ]]; then
token="$FALLBACK_TOKEN"
source="pat-fallback"
echo "::warning::GitHub authentication source: PAT fallback"
elif [[ "$AUTH_MODE" == "pat" && -n "$FALLBACK_TOKEN" ]]; then
token="$FALLBACK_TOKEN"
source="pat-forced"
echo "::warning::GitHub authentication source: PAT (forced rollout mode)"
else
echo "::error::GitHub App authentication is unavailable and no fallback PAT was provided."
exit 1
fi
echo "::add-mask::$token"
echo "token=$token" >> "$GITHUB_OUTPUT"
echo "source=$source" >> "$GITHUB_OUTPUT"
@@ -0,0 +1,133 @@
// Copyright (c) Microsoft. All rights reserved.
const crypto = require('node:crypto');
const { execFileSync } = require('node:child_process');
function base64Url(value) {
return Buffer.from(value).toString('base64url');
}
function base64ToBase64Url(value) {
return Buffer.from(value, 'base64').toString('base64url');
}
function createJwtSigningInput(clientId, nowSeconds) {
const header = base64Url(JSON.stringify({ alg: 'RS256', typ: 'JWT' }));
const payload = base64Url(JSON.stringify({
iat: nowSeconds - 60,
exp: nowSeconds + 540,
iss: clientId,
}));
return `${header}.${payload}`;
}
function signJwt(signingInput, config, execute = execFileSync) {
const digest = crypto.createHash('sha256').update(signingInput).digest('base64');
const signature = execute(
'az',
[
'keyvault', 'key', 'sign',
'--subscription', config.azureSubscriptionId,
'--vault-name', config.keyVaultName,
'--name', config.keyName,
'--algorithm', 'RS256',
'--digest', digest,
'--query', 'signature',
'--output', 'tsv',
'--only-show-errors',
],
{ encoding: 'utf8' },
).trim();
if (!signature) {
throw new Error('Key Vault returned an empty signature.');
}
return `${signingInput}.${base64ToBase64Url(signature)}`;
}
async function createInstallationToken(config, dependencies = {}) {
const execute = dependencies.execute ?? execFileSync;
const request = dependencies.fetch ?? fetch;
const nowSeconds = dependencies.nowSeconds ?? Math.floor(Date.now() / 1000);
const repositoryParts = config.targetRepository.split('/');
if (repositoryParts.length !== 2 || repositoryParts.some((part) => part.length === 0)) {
throw new Error('TARGET_REPOSITORY must use the owner/repository format.');
}
const [, repository] = repositoryParts;
const signingInput = createJwtSigningInput(config.githubAppClientId, nowSeconds);
const jwt = signJwt(signingInput, config, execute);
const response = await request(
`https://api.github.com/app/installations/${config.githubAppInstallationId}/access_tokens`,
{
method: 'POST',
headers: {
Accept: 'application/vnd.github+json',
Authorization: `Bearer ${jwt}`,
'X-GitHub-Api-Version': '2022-11-28',
},
body: JSON.stringify({
repositories: [repository],
permissions: {
contents: 'read',
issues: 'write',
members: 'read',
pull_requests: 'write',
},
}),
},
);
if (!response.ok) {
throw new Error(`GitHub installation token request failed with HTTP ${response.status}.`);
}
const result = await response.json();
if (typeof result.token !== 'string' || result.token.length === 0) {
throw new Error('GitHub returned an empty installation token.');
}
return result.token;
}
function readConfig(environment) {
const config = {
azureSubscriptionId: environment.AZURE_SUBSCRIPTION_ID,
keyVaultName: environment.KEY_VAULT_NAME,
keyName: environment.KEY_NAME,
githubAppClientId: environment.GITHUB_APP_CLIENT_ID,
githubAppInstallationId: environment.GITHUB_APP_INSTALLATION_ID,
targetRepository: environment.TARGET_REPOSITORY,
};
if (Object.values(config).some((value) => !value)) {
throw new Error('Required GitHub App authentication configuration is missing.');
}
return config;
}
async function main() {
try {
const token = await createInstallationToken(readConfig(process.env));
process.stdout.write(token);
} catch {
console.error('GitHub App token generation failed.');
process.exitCode = 1;
}
}
if (require.main === module) {
void main();
}
module.exports = {
base64ToBase64Url,
createInstallationToken,
createJwtSigningInput,
readConfig,
signJwt,
};
+2 -2
View File
@@ -17,7 +17,7 @@ runs:
using: "composite"
steps:
- name: Set up uv
uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6
uses: astral-sh/setup-uv@11f9893b081a58869d3b5fccaea48c9e9e46f990 # v8.3.2
with:
version-file: "python/pyproject.toml"
enable-cache: true
@@ -46,4 +46,4 @@ runs:
- name: Install the project
shell: bash
run: |
cd python && uv sync --all-packages --all-extras --dev --prerelease=if-necessary-or-explicit
cd python && uv sync --all-packages --all-extras --all-groups --prerelease=if-necessary-or-explicit
+22 -9
View File
@@ -1,25 +1,38 @@
// Copyright (c) Microsoft. All rights reserved.
/**
* Resolve the issue author and check their team membership.
* Resolve the issue or pull request author and check their team membership.
*
* @param {object} opts
* @param {object} opts.github - Octokit REST client from actions/github-script
* @param {object} opts.context - GitHub Actions context
* @param {object} opts.core - GitHub Actions core toolkit
* @param {string} opts.teamSlug - Team slug to check membership against
* @param {string|number} opts.issueNumber - Issue number to resolve author for
* @param {string|number} opts.issueNumber - Issue or pull request number to resolve author for
* @returns {Promise<{author: string|null, isTeamMember: boolean}>}
*/
async function checkTeamMembership({ github, context, core, teamSlug, issueNumber }) {
let author = context.payload.issue?.user?.login;
let author =
context.payload.issue?.user?.login ??
context.payload.pull_request?.user?.login;
if (!author) {
const { data: issue } = await github.rest.issues.get({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: Number(issueNumber),
});
author = issue.user?.login;
const number = Number(issueNumber);
if (context.payload.pull_request) {
const { data: pr } = await github.rest.pulls.get({
owner: context.repo.owner,
repo: context.repo.repo,
pull_number: number,
});
author = pr.user?.login;
} else {
const { data: issue } = await github.rest.issues.get({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: number,
});
author = issue.user?.login;
}
}
if (!author) {
@@ -0,0 +1,170 @@
// Copyright (c) Microsoft. All rights reserved.
const DECISIVE_REVIEW_STATES = new Set(['APPROVED', 'CHANGES_REQUESTED', 'DISMISSED']);
const SHA_PATTERN = /^[0-9a-f]{40}$/;
const BRANCH_PATTERN = /^[a-zA-Z0-9_./-]+$/;
function assertValidSha(sha, description) {
if (!SHA_PATTERN.test(sha)) {
throw new Error(`GitHub returned an invalid ${description} SHA.`);
}
}
function hasWritePermission(permissionData) {
return permissionData.user?.permissions?.push === true
|| ['admin', 'maintain', 'write'].includes(permissionData.permission);
}
function latestDecisiveReviews(reviews) {
const latestByReviewer = new Map();
const sortedReviews = [...reviews].sort((left, right) => {
const submittedComparison = (left.submitted_at || '').localeCompare(right.submitted_at || '');
return submittedComparison || Number(left.id) - Number(right.id);
});
for (const review of sortedReviews) {
const state = review.state?.toUpperCase();
const reviewer = review.user?.login?.toLowerCase();
if (reviewer && DECISIVE_REVIEW_STATES.has(state)) {
latestByReviewer.set(reviewer, review);
}
}
return latestByReviewer;
}
async function resolvePullRequest({ github, context, core, prNumber, requiredApprovals }) {
if (!/^[0-9]+$/.test(prNumber)) {
throw new Error('Invalid PR number. Only numeric values are allowed.');
}
const pullNumber = Number(prNumber);
const { data: pullRequest } = await github.rest.pulls.get({
...context.repo,
pull_number: pullNumber,
});
if (pullRequest.state !== 'open') {
throw new Error(`PR #${pullNumber} is not open (state: ${pullRequest.state}).`);
}
const headSha = pullRequest.head.sha;
const baseSha = pullRequest.base.sha;
assertValidSha(headSha, 'PR head');
assertValidSha(baseSha, 'PR base');
const reviews = await github.paginate(github.rest.pulls.listReviews, {
...context.repo,
pull_number: pullNumber,
per_page: 100,
});
const latestReviews = latestDecisiveReviews(reviews);
const author = pullRequest.user?.login?.toLowerCase();
const approvalCandidates = [...latestReviews.entries()]
.filter(([, review]) => review.state.toUpperCase() === 'APPROVED')
.filter(([, review]) => review.commit_id === headSha)
.filter(([reviewer]) => reviewer !== author);
const approvedMaintainers = [];
for (const [reviewer] of approvalCandidates) {
const { data: permissionData } = await github.rest.repos.getCollaboratorPermissionLevel({
...context.repo,
username: reviewer,
});
if (hasWritePermission(permissionData)) {
approvedMaintainers.push(reviewer);
} else {
core.info(`Ignoring approval from ${reviewer}: reviewer does not have write permission.`);
}
}
if (approvedMaintainers.length < requiredApprovals) {
throw new Error(
`PR #${pullNumber} head ${headSha} requires ${requiredApprovals} approvals from unique `
+ `write-capable maintainers; found ${approvedMaintainers.length}.`,
);
}
core.info(
`PR #${pullNumber} head ${headSha} approved by: ${approvedMaintainers.join(', ')}.`,
);
return {
baseRef: baseSha,
checkoutRef: headSha,
description: `PR #${pullNumber}`,
};
}
async function resolveBranch({ github, context, core, branch }) {
if (!BRANCH_PATTERN.test(branch)) {
throw new Error(
'Invalid branch name. Only alphanumeric characters, hyphens, underscores, dots, and slashes '
+ 'are allowed.',
);
}
const [{ data: repository }, { data: targetBranch }] = await Promise.all([
github.rest.repos.get(context.repo),
github.rest.repos.getBranch({ ...context.repo, branch }),
]);
const { data: baseBranch } = await github.rest.repos.getBranch({
...context.repo,
branch: repository.default_branch,
});
const checkoutRef = targetBranch.commit.sha;
const baseRef = baseBranch.commit.sha;
assertValidSha(checkoutRef, 'branch head');
assertValidSha(baseRef, 'default branch');
core.info(`Branch ${branch} resolved to immutable commit ${checkoutRef}.`);
return {
baseRef,
checkoutRef,
description: `branch ${branch}`,
};
}
/**
* Resolve a manually requested integration-test target to an immutable commit.
*
* Pull requests must have fresh approvals from two unique write-capable
* maintainers for the exact head commit. Branches are limited to branches in
* the base repository and are pinned to their current commit.
*/
async function resolveIntegrationTestTarget({
github,
context,
core,
prNumber = '',
branch = '',
requiredApprovals = 2,
}) {
const normalizedPrNumber = prNumber.trim();
const normalizedBranch = branch.trim();
if (normalizedPrNumber && normalizedBranch) {
throw new Error('Please provide either a PR number or a branch name, not both.');
}
if (!normalizedPrNumber && !normalizedBranch) {
throw new Error('Please provide either a PR number or a branch name.');
}
if (normalizedPrNumber) {
return resolvePullRequest({
github,
context,
core,
prNumber: normalizedPrNumber,
requiredApprovals,
});
}
return resolveBranch({
github,
context,
core,
branch: normalizedBranch,
});
}
module.exports = resolveIntegrationTestTarget;
+51 -2
View File
@@ -16,7 +16,12 @@ const checkTeamMembership = require('../scripts/check_team_membership.js');
// Helpers
// ---------------------------------------------------------------------------
function createMocks({ payloadIssue = undefined, apiUser = 'api-user', teamState = 'active' } = {}) {
function createMocks({
payloadIssue = undefined,
payloadPullRequest = undefined,
apiUser = 'api-user',
teamState = 'active',
} = {}) {
const core = {
_infoMessages: [],
_failedMessages: [],
@@ -24,8 +29,16 @@ function createMocks({ payloadIssue = undefined, apiUser = 'api-user', teamState
setFailed(msg) { this._failedMessages.push(msg); },
};
const payload = {};
if (payloadIssue !== undefined) {
payload.issue = payloadIssue;
}
if (payloadPullRequest !== undefined) {
payload.pull_request = payloadPullRequest;
}
const context = {
payload: { issue: payloadIssue },
payload,
repo: { owner: 'test-org', repo: 'test-repo' },
};
@@ -36,6 +49,11 @@ function createMocks({ payloadIssue = undefined, apiUser = 'api-user', teamState
data: { user: apiUser ? { login: apiUser } : null },
}),
},
pulls: {
get: async () => ({
data: { user: apiUser ? { login: apiUser } : null },
}),
},
teams: {
getByName: async () => ({}),
getMembershipForUserInOrg: async () => ({
@@ -64,6 +82,37 @@ describe('author resolution', () => {
assert.equal(result.author, 'payload-user');
});
it('resolves author from pull_request event payload', async () => {
const { github, context, core } = createMocks({
payloadPullRequest: { user: { login: 'pr-author' } },
});
let issuesGetCalled = false;
github.rest.issues.get = async () => {
issuesGetCalled = true;
return { data: { user: { login: 'api-user' } } };
};
const result = await checkTeamMembership({ github, context, core, ...BASE_OPTS });
assert.equal(result.author, 'pr-author');
assert.equal(issuesGetCalled, false);
});
it('resolves author via pulls API when pull_request payload user is null', async () => {
const { github, context, core } = createMocks({
payloadPullRequest: { user: null },
apiUser: 'fetched-pr-author',
});
let pullsGetCalled = false;
github.rest.pulls.get = async () => {
pullsGetCalled = true;
return { data: { user: { login: 'fetched-pr-author' } } };
};
const result = await checkTeamMembership({ github, context, core, ...BASE_OPTS });
assert.equal(result.author, 'fetched-pr-author');
assert.equal(pullsGetCalled, true);
});
it('resolves author via API when payload issue is absent', async () => {
const { github, context, core } = createMocks({ apiUser: 'api-user' });
const result = await checkTeamMembership({ github, context, core, ...BASE_OPTS });
@@ -0,0 +1,125 @@
// Copyright (c) Microsoft. All rights reserved.
const { describe, it } = require('node:test');
const assert = require('node:assert/strict');
const {
base64ToBase64Url,
createInstallationToken,
createJwtSigningInput,
readConfig,
} = require('../actions/github-app-token/create-token.js');
const CONFIG = {
azureSubscriptionId: 'subscription-id',
keyVaultName: 'vault-name',
keyName: 'key-name',
githubAppClientId: 'client-id',
githubAppInstallationId: '12345',
targetRepository: 'microsoft/agent-framework',
};
describe('GitHub App token creation', () => {
it('creates a short-lived GitHub App JWT', () => {
const signingInput = createJwtSigningInput('client-id', 1_000);
const [encodedHeader, encodedPayload] = signingInput.split('.');
const header = JSON.parse(Buffer.from(encodedHeader, 'base64url').toString());
const payload = JSON.parse(Buffer.from(encodedPayload, 'base64url').toString());
assert.deepEqual(header, { alg: 'RS256', typ: 'JWT' });
assert.deepEqual(payload, { iat: 940, exp: 1_540, iss: 'client-id' });
});
it('converts Key Vault signatures to unpadded base64url', () => {
assert.equal(base64ToBase64Url('+/8='), '-_8');
});
it('requests a repository-scoped installation token', async () => {
let request;
const token = await createInstallationToken(CONFIG, {
nowSeconds: 1_000,
execute: (command, args) => {
assert.equal(command, 'az');
assert.ok(args.includes('RS256'));
return '+/8=\n';
},
fetch: async (url, options) => {
request = { url, options };
return {
ok: true,
json: async () => ({ token: 'installation-token' }),
};
},
});
assert.equal(token, 'installation-token');
assert.equal(request.url, 'https://api.github.com/app/installations/12345/access_tokens');
assert.match(request.options.headers.Authorization, /^Bearer [^.]+\.[^.]+\.-_8$/);
assert.deepEqual(JSON.parse(request.options.body), {
repositories: ['agent-framework'],
permissions: {
contents: 'read',
issues: 'write',
members: 'read',
pull_requests: 'write',
},
});
});
it('rejects incomplete configuration', () => {
assert.throws(
() => readConfig({}),
/Required GitHub App authentication configuration is missing/,
);
});
it('rejects repository values with extra path segments before signing', async () => {
let signed = false;
await assert.rejects(
createInstallationToken(
{ ...CONFIG, targetRepository: 'microsoft/agent-framework/extra' },
{
execute: () => {
signed = true;
return '+/8=\n';
},
},
),
/TARGET_REPOSITORY must use the owner\/repository format/,
);
assert.equal(signed, false);
});
it('rejects an empty Key Vault signature', async () => {
await assert.rejects(
createInstallationToken(CONFIG, {
execute: () => '\n',
}),
/Key Vault returned an empty signature/,
);
});
it('rejects a failed GitHub token request', async () => {
await assert.rejects(
createInstallationToken(CONFIG, {
execute: () => '+/8=\n',
fetch: async () => ({ ok: false, status: 403 }),
}),
/GitHub installation token request failed with HTTP 403/,
);
});
it('rejects an empty GitHub installation token', async () => {
await assert.rejects(
createInstallationToken(CONFIG, {
execute: () => '+/8=\n',
fetch: async () => ({
ok: true,
json: async () => ({ token: '' }),
}),
}),
/GitHub returned an empty installation token/,
);
});
});
@@ -0,0 +1,212 @@
// Copyright (c) Microsoft. All rights reserved.
/**
* Tests for resolve_integration_test_target.js.
*
* Run with: node --test .github/tests/test_resolve_integration_test_target.js
*/
const { describe, it } = require('node:test');
const assert = require('node:assert/strict');
const resolveIntegrationTestTarget = require('../scripts/resolve_integration_test_target.js');
const HEAD_SHA = 'a'.repeat(40);
const BASE_SHA = 'b'.repeat(40);
function review({
id,
login,
state = 'APPROVED',
commitId = HEAD_SHA,
submittedAt = `2026-07-13T00:00:${String(id).padStart(2, '0')}Z`,
}) {
return {
id,
state,
commit_id: commitId,
submitted_at: submittedAt,
user: { login },
};
}
function createMocks({
pullState = 'open',
pullAuthor = 'contributor',
reviews = [],
permissions = {},
} = {}) {
const core = {
infoMessages: [],
info(message) {
this.infoMessages.push(message);
},
};
const context = {
repo: { owner: 'microsoft', repo: 'agent-framework' },
};
const github = {
paginate: async () => reviews,
rest: {
pulls: {
get: async () => ({
data: {
state: pullState,
user: { login: pullAuthor },
head: { sha: HEAD_SHA },
base: { sha: BASE_SHA },
},
}),
listReviews: async () => {},
},
repos: {
get: async () => ({ data: { default_branch: 'main' } }),
getBranch: async ({ branch }) => ({
data: { commit: { sha: branch === 'main' ? BASE_SHA : HEAD_SHA } },
}),
getCollaboratorPermissionLevel: async ({ username }) => ({
data: permissions[username] || {
permission: 'read',
user: { permissions: { push: false } },
},
}),
},
},
};
return { core, context, github };
}
const WRITE_PERMISSION = {
permission: 'write',
user: { permissions: { push: true } },
};
describe('input validation', () => {
it('rejects missing and conflicting targets', async () => {
const mocks = createMocks();
await assert.rejects(
() => resolveIntegrationTestTarget(mocks),
/provide either a PR number or a branch name/,
);
await assert.rejects(
() => resolveIntegrationTestTarget({ ...mocks, prNumber: '1', branch: 'feature' }),
/not both/,
);
});
it('rejects invalid PR numbers and branch names', async () => {
const mocks = createMocks();
await assert.rejects(
() => resolveIntegrationTestTarget({ ...mocks, prNumber: '1;echo' }),
/Invalid PR number/,
);
await assert.rejects(
() => resolveIntegrationTestTarget({ ...mocks, branch: 'feature branch' }),
/Invalid branch name/,
);
});
});
describe('pull request resolution', () => {
it('pins an open PR with two fresh write-capable approvals', async () => {
const mocks = createMocks({
reviews: [
review({ id: 1, login: 'maintainer-one' }),
review({ id: 2, login: 'maintainer-two' }),
],
permissions: {
'maintainer-one': WRITE_PERMISSION,
'maintainer-two': WRITE_PERMISSION,
},
});
const result = await resolveIntegrationTestTarget({ ...mocks, prNumber: '123' });
assert.deepEqual(result, {
baseRef: BASE_SHA,
checkoutRef: HEAD_SHA,
description: 'PR #123',
});
});
it('rejects closed PRs', async () => {
const mocks = createMocks({ pullState: 'closed' });
await assert.rejects(
() => resolveIntegrationTestTarget({ ...mocks, prNumber: '123' }),
/is not open/,
);
});
it('ignores stale, self, and read-only approvals', async () => {
const mocks = createMocks({
reviews: [
review({ id: 1, login: 'stale', commitId: 'c'.repeat(40) }),
review({ id: 2, login: 'contributor' }),
review({ id: 3, login: 'reader' }),
review({ id: 4, login: 'maintainer' }),
],
permissions: {
contributor: WRITE_PERMISSION,
reader: { permission: 'read', user: { permissions: { push: false } } },
maintainer: WRITE_PERMISSION,
},
});
await assert.rejects(
() => resolveIntegrationTestTarget({ ...mocks, prNumber: '123' }),
/found 1/,
);
});
it('uses each reviewer latest decisive review and ignores later comments', async () => {
const mocks = createMocks({
reviews: [
review({ id: 1, login: 'changes-requested' }),
review({ id: 2, login: 'changes-requested', state: 'CHANGES_REQUESTED' }),
review({ id: 3, login: 'maintainer-one' }),
review({ id: 4, login: 'maintainer-one', state: 'COMMENTED' }),
review({ id: 5, login: 'maintainer-two' }),
],
permissions: {
'changes-requested': WRITE_PERMISSION,
'maintainer-one': WRITE_PERMISSION,
'maintainer-two': WRITE_PERMISSION,
},
});
const result = await resolveIntegrationTestTarget({ ...mocks, prNumber: '123' });
assert.equal(result.checkoutRef, HEAD_SHA);
});
it('does not count a dismissed approval', async () => {
const mocks = createMocks({
reviews: [
review({ id: 1, login: 'dismissed', state: 'DISMISSED' }),
review({ id: 2, login: 'maintainer' }),
],
permissions: {
dismissed: WRITE_PERMISSION,
maintainer: WRITE_PERMISSION,
},
});
await assert.rejects(
() => resolveIntegrationTestTarget({ ...mocks, prNumber: '123' }),
/found 1/,
);
});
});
describe('branch resolution', () => {
it('pins base-repository branches and their comparison base to SHAs', async () => {
const mocks = createMocks();
const result = await resolveIntegrationTestTarget({ ...mocks, branch: 'feature/test' });
assert.deepEqual(result, {
baseRef: BASE_SHA,
checkoutRef: HEAD_SHA,
description: 'branch feature/test',
});
});
});
@@ -23,16 +23,16 @@ For each project that needs to be migrated, you need to do the following:
- Identify the specific Semantic Kernel agent types being used:
- `ChatCompletionAgent``ChatClientAgent`
- `OpenAIAssistantAgent``assistantsClient.CreateAIAgent()` (via OpenAI Assistants client extension)
- `AzureAIAgent``persistentAgentsClient.CreateAIAgent()` (via Azure AI Foundry client extension)
- `AzureAIAgent``persistentAgentsClient.CreateAIAgent()` (via Microsoft Foundry client extension)
- `OpenAIResponseAgent``responsesClient.CreateAIAgent()` (via OpenAI Responses client extension)
- `A2AAgent``AIAgent` (via A2A card resolver)
- `BedrockAgent` → Custom implementation required (not supported)
- Determine if agents are being created new or retrieved from hosted services:
- **New agents**: Use `CreateAIAgent()` methods
- **Existing hosted agents**: Use `GetAIAgent(agentId)` methods for OpenAI Assistants and Azure AI Foundry
- **Existing hosted agents**: Use `GetAIAgent(agentId)` methods for OpenAI Assistants and Microsoft Foundry
</agent_type_identification>
- Determine the AI provider being used (OpenAI, Azure OpenAI, Azure AI Foundry, etc.)
- Determine the AI provider being used (OpenAI, Azure OpenAI, Microsoft Foundry, etc.)
- Analyze tool/function registration patterns
- Review thread management and invocation patterns
@@ -90,7 +90,7 @@ below in wrong order or skip any of them):
you generate report when migration complete. Report should contain:
- all project dependencies changes (mention what was changed, added or removed, including provider-specific packages)
- all code files that were changed (mention what was changed in the file, if it was not changed, just mention that the file was not changed)
- provider-specific migration patterns used (OpenAI, Azure OpenAI, Azure AI Foundry, A2A, ONNX, etc.)
- provider-specific migration patterns used (OpenAI, Azure OpenAI, Microsoft Foundry, A2A, ONNX, etc.)
- all cases where you could not convert the code because of unsupported features and you were unable to find a workaround
- unsupported providers that require custom implementation (Bedrock, CopilotStudio)
- breaking glass pattern migrations (InnerContent → RawRepresentation) and any CodeInterpreter or advanced tool usage
@@ -223,7 +223,7 @@ using Microsoft.Agents.AI;
// Provider-specific namespaces (add only if needed):
using OpenAI; // For OpenAI provider
using Azure.AI.OpenAI; // For Azure OpenAI provider
using Azure.AI.Agents.Persistent; // For Azure AI Foundry provider
using Azure.AI.Agents.Persistent; // For Microsoft Foundry provider
using Azure.Identity; // For Azure authentication
```
</configuration_changes>
@@ -499,7 +499,7 @@ For every thread created if there's intent to cleanup, the caller should track a
var assistantClient = new OpenAIClient(apiKey).GetAssistantClient();
await assistantClient.DeleteThreadAsync(thread.ConversationId);
// For Azure AI Foundry (when cleanup is needed):
// For Microsoft Foundry (when cleanup is needed):
var persistentClient = new PersistentAgentsClient(endpoint, credential);
await persistentClient.Threads.DeleteThreadAsync(thread.ConversationId);
@@ -514,7 +514,7 @@ await persistentClient.Threads.DeleteThreadAsync(thread.ConversationId);
1. Remove `thread.DeleteAsync()` calls
2. Use provider-specific client for cleanup when required
3. Access thread ID via `thread.ConversationId` property
4. Only implement cleanup for providers that require it (Assistants, Azure AI Foundry)
4. Only implement cleanup for providers that require it (Assistants, Microsoft Foundry)
</api_changes>
### Provider-Specific Creation Patterns
@@ -550,13 +550,13 @@ AIAgent agent = new AzureOpenAIClient(endpoint, credential)
.CreateAIAgent(instructions: instructions);
```
**Azure AI Foundry (New):**
**Microsoft Foundry (New):**
```csharp
AIAgent agent = new PersistentAgentsClient(endpoint, credential)
.CreateAIAgent(model: deploymentName, instructions: instructions);
```
**Azure AI Foundry (Existing):**
**Microsoft Foundry (Existing):**
```csharp
AIAgent agent = await new PersistentAgentsClient(endpoint, credential)
.GetAIAgentAsync(agentId);
@@ -1079,7 +1079,7 @@ AgentThread thread = agent.GetNewThread();
```
</api_changes>
### 4. Azure AI Foundry (AzureAIAgent) Migration
### 4. Microsoft Foundry (AzureAIAgent) Migration
<configuration_changes>
**Remove Semantic Kernel Packages:**
+3 -3
View File
@@ -38,7 +38,7 @@ jobs:
# Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL
uses: github/codeql-action/init@9e0d7b8d25671d64c341c19c0152d693099fb5ba # v4
uses: github/codeql-action/init@99df26d4f13ea111d4ec1a7dddef6063f76b97e9 # v4
with:
languages: ${{ matrix.language }}
# If you wish to specify custom queries, you can do so here or in a config file.
@@ -51,7 +51,7 @@ jobs:
# Autobuild attempts to build any compiled languages (C/C++, C#, Go, or Java).
# If this step fails, then you should remove it and run the build manually (see below)
- name: Autobuild
uses: github/codeql-action/autobuild@9e0d7b8d25671d64c341c19c0152d693099fb5ba # v4
uses: github/codeql-action/autobuild@99df26d4f13ea111d4ec1a7dddef6063f76b97e9 # v4
# ️ Command-line programs to run using the OS shell.
# 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
@@ -64,6 +64,6 @@ jobs:
# ./location_of_script_within_repo/buildscript.sh
- name: Perform CodeQL Analysis
uses: github/codeql-action/analyze@9e0d7b8d25671d64c341c19c0152d693099fb5ba # v4
uses: github/codeql-action/analyze@99df26d4f13ea111d4ec1a7dddef6063f76b97e9 # v4
with:
category: "/language:${{matrix.language}}"
+43 -26
View File
@@ -15,6 +15,7 @@ on:
permissions:
contents: read
id-token: write
issues: write
pull-requests: write
@@ -31,6 +32,7 @@ env:
jobs:
team_check:
runs-on: ubuntu-latest
environment: github-app-auth
outputs:
is_team_member: ${{ steps.check.outputs.is_team_member }}
pr_number: ${{ steps.pr.outputs.pr_number }}
@@ -64,6 +66,31 @@ jobs:
echo "pr_number=${pr_number}" >> "$GITHUB_OUTPUT"
echo "repo=${GITHUB_REPOSITORY}" >> "$GITHUB_OUTPUT"
- name: Checkout GitHub automation
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ github.event_name == 'pull_request_target' && github.event.pull_request.base.sha || github.sha }}
sparse-checkout: |
.github/actions/github-app-token
.github/scripts/check_team_membership.js
fetch-depth: 1
persist-credentials: false
- name: Get GitHub automation token
id: github-auth
uses: ./.github/actions/github-app-token
with:
mode: ${{ vars.GH_APP_AUTH_MODE }}
azure-client-id: ${{ secrets.GH_APP_AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.GH_APP_AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.GH_APP_AZURE_SUBSCRIPTION_ID }}
key-vault-name: ${{ secrets.GH_APP_KEY_VAULT_NAME }}
key-name: ${{ secrets.GH_APP_KEY_NAME }}
github-app-client-id: ${{ secrets.GH_APP_CLIENT_ID }}
github-app-installation-id: ${{ secrets.GH_APP_INSTALLATION_ID }}
repository: ${{ github.repository }}
fallback-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
- name: Check PR author team membership
id: check
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
@@ -71,31 +98,16 @@ jobs:
TEAM_NAME: ${{ secrets.DEVELOPER_TEAM }}
PR_NUMBER: ${{ steps.pr.outputs.pr_number }}
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
github-token: ${{ steps.github-auth.outputs.token }}
script: |
let author = context.payload.pull_request?.user?.login;
if (!author) {
const { data: pr } = await github.rest.pulls.get({
owner: context.repo.owner,
repo: context.repo.repo,
pull_number: Number(process.env.PR_NUMBER),
});
author = pr.user.login;
}
let isTeamMember = false;
try {
const teamMembership = await github.rest.teams.getMembershipForUserInOrg({
org: context.repo.owner,
team_slug: process.env.TEAM_NAME,
username: author,
});
isTeamMember = teamMembership.data.state === 'active';
} catch (error) {
console.log(`Team membership lookup failed for ${author}: ${error.message}`);
isTeamMember = false;
}
const checkTeamMembership = require('./.github/scripts/check_team_membership.js');
const { author, isTeamMember } = await checkTeamMembership({
github,
context,
core,
teamSlug: process.env.TEAM_NAME,
issueNumber: process.env.PR_NUMBER,
});
core.setOutput('is_team_member', isTeamMember ? 'true' : 'false');
if (isTeamMember) {
core.info(`Author ${author} is a team member; proceeding with review.`);
@@ -107,6 +119,11 @@ jobs:
runs-on: ubuntu-latest
needs: team_check
if: ${{ needs.team_check.outputs.is_team_member == 'true' }}
permissions:
contents: read
copilot-requests: write
issues: write
pull-requests: write
timeout-minutes: 60
# Advisory check: failures here should not block the PR. The reviewer
# posts comments as a best-effort signal; if the pipeline breaks, the
@@ -140,7 +157,7 @@ jobs:
python-version: "3.13"
- name: Set up uv
uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7
uses: astral-sh/setup-uv@11f9893b081a58869d3b5fccaea48c9e9e46f990 # v8.3.2
with:
version: "0.11.x"
enable-cache: true
@@ -154,7 +171,7 @@ jobs:
working-directory: ${{ env.DEVFLOW_PATH }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GH_COPILOT_TOKEN: ${{ secrets.GH_COPILOT_TOKEN }}
GH_COPILOT_TOKEN: ${{ github.token }}
SK_REPO_PATH: ${{ env.TARGET_REPO_PATH }}
AGENT_REPO_PATH: ${{ env.TARGET_REPO_PATH }}
PR_URL: ${{ needs.team_check.outputs.pr_url }}
+6 -5
View File
@@ -42,7 +42,7 @@ jobs:
coreChanged: ${{ steps.filter.outputs.core }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- uses: dorny/paths-filter@fbd0ab8f3e69293af611ebaee6363fc25e6d187d # v4.0.1
- uses: dorny/paths-filter@7b450fff21473bca461d4b92ce414b9d0420d706 # v4.0.2
id: filter
with:
filters: |
@@ -163,6 +163,7 @@ jobs:
# Change to project directory to ensure local nuget.config is used
pushd consoleapp
dotnet add packcheck.csproj package Microsoft.Agents.AI --prerelease
dotnet add packcheck.csproj package Microsoft.Agents.AI.LocalCodeAct --prerelease
dotnet build -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} packcheck.csproj
# Clean up
@@ -312,7 +313,7 @@ jobs:
AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZURE_OPENAI_ENDPOINT }}
# Azure AI Foundry
# Microsoft Foundry
AZURE_AI_PROJECT_ENDPOINT: ${{ vars.AZURE_AI_PROJECT_ENDPOINT }}
AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZURE_AI_MODEL_DEPLOYMENT_NAME }}
AZURE_AI_BING_CONNECTION_ID: ${{ vars.AZURE_AI_BING_CONNECTION_ID }}
@@ -528,7 +529,7 @@ jobs:
AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZURE_OPENAI_ENDPOINT }}
# Azure AI Foundry
# Microsoft Foundry
AZURE_AI_PROJECT_ENDPOINT: ${{ vars.AZURE_AI_PROJECT_ENDPOINT }}
AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZURE_AI_MODEL_DEPLOYMENT_NAME }}
AZURE_AI_BING_CONNECTION_ID: ${{ vars.AZURE_AI_BING_CONNECTION_ID }}
@@ -615,7 +616,7 @@ jobs:
pattern: dotnet-test-results-*
path: dotnet-test-results/
- name: Restore report history cache
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
uses: actions/cache/restore@55cc8345863c7cc4c66a329aec7e433d2d1c52a9 # v6.1.0
with:
path: python/dotnet-integration-report-history.json
key: dotnet-integration-report-history-${{ github.run_id }}
@@ -632,7 +633,7 @@ jobs:
run: cat dotnet-integration-test-report.md >> $GITHUB_STEP_SUMMARY
- name: Save report history cache
if: always()
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
uses: actions/cache/save@55cc8345863c7cc4c66a329aec7e433d2d1c52a9 # v6.1.0
with:
path: python/dotnet-integration-report-history.json
key: dotnet-integration-report-history-${{ github.run_id }}
+17 -2
View File
@@ -9,16 +9,31 @@ on:
workflow_call:
inputs:
checkout-ref:
description: "Git ref to checkout (e.g., refs/pull/123/head)"
description: "Immutable commit SHA to check out"
required: true
type: string
secrets:
AZURE_CLIENT_ID:
required: true
AZURE_TENANT_ID:
required: true
AZURE_SUBSCRIPTION_ID:
required: true
AZUREAI__ENDPOINT:
required: true
COPILOT_GITHUB_TOKEN:
required: true
OPENAI__APIKEY:
required: true
permissions:
contents: read
id-token: write
jobs:
dotnet-integration-tests:
permissions:
contents: read
id-token: write
strategy:
fail-fast: false
matrix:
+1 -1
View File
@@ -105,7 +105,7 @@ jobs:
AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZURE_OPENAI_DEPLOYMENT_NAME }}
AZURE_OPENAI_ENDPOINT: ${{ vars.AZURE_OPENAI_ENDPOINT }}
# Azure AI Foundry
# Microsoft Foundry
AZURE_AI_PROJECT_ENDPOINT: ${{ vars.AZURE_AI_PROJECT_ENDPOINT }}
AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZURE_AI_MODEL_DEPLOYMENT_NAME }}
AZURE_AI_BING_CONNECTION_ID: ${{ vars.AZURE_AI_BING_CONNECTION_ID }}
@@ -0,0 +1,33 @@
name: GitHub automation tests
on:
pull_request:
paths:
- ".github/actions/**"
- ".github/scripts/**"
- ".github/tests/**"
- ".github/workflows/github-automation-tests.yml"
push:
branches:
- main
paths:
- ".github/actions/**"
- ".github/scripts/**"
- ".github/tests/**"
- ".github/workflows/github-automation-tests.yml"
permissions:
contents: read
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6
with:
node-version: "22"
- name: Run tests
run: node --test .github/tests/*.js
+53 -52
View File
@@ -3,7 +3,7 @@
# Go to Actions → "Integration Tests (Manual)" → Run workflow → enter a PR number or branch name.
#
# It calls dedicated integration-only workflows (dotnet-integration-tests and python-integration-tests),
# passing a ref so they check out and test the correct code.
# passing an immutable commit SHA so they check out and test the approved code.
# Changed paths are detected here so only the relevant test suites run.
#
@@ -26,7 +26,6 @@ on:
permissions:
contents: read
pull-requests: read
id-token: write
concurrency:
group: integration-tests-manual-${{ github.event.inputs.pr-number || github.event.inputs.branch }}
@@ -38,67 +37,50 @@ jobs:
runs-on: ubuntu-latest
outputs:
checkout-ref: ${{ steps.resolve.outputs.checkout-ref }}
base-ref: ${{ steps.resolve.outputs.base-ref }}
dotnet-changes: ${{ steps.detect-changes.outputs.dotnet }}
python-changes: ${{ steps.detect-changes.outputs.python }}
steps:
- name: Resolve checkout ref
- name: Check out trusted workflow helpers
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
ref: ${{ github.sha }}
persist-credentials: false
sparse-checkout: .github/scripts
- name: Resolve and authorize checkout ref
id: resolve
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
script: |
const resolveIntegrationTestTarget = require(
'./.github/scripts/resolve_integration_test_target.js'
);
const target = await resolveIntegrationTestTarget({
github,
context,
core,
prNumber: process.env.PR_NUMBER,
branch: process.env.BRANCH,
});
core.setOutput('checkout-ref', target.checkoutRef);
core.setOutput('base-ref', target.baseRef);
core.info(`Running integration tests for ${target.description} at ${target.checkoutRef}.`);
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
PR_NUMBER: ${{ github.event.inputs.pr-number }}
BRANCH: ${{ github.event.inputs.branch }}
REPO: ${{ github.repository }}
run: |
if [ -n "$PR_NUMBER" ] && [ -n "$BRANCH" ]; then
echo "::error::Please provide either a PR number or a branch name, not both."
exit 1
fi
if [ -z "$PR_NUMBER" ] && [ -z "$BRANCH" ]; then
echo "::error::Please provide either a PR number or a branch name."
exit 1
fi
if [ -n "$PR_NUMBER" ]; then
if ! echo "$PR_NUMBER" | grep -Eq '^[0-9]+$'; then
echo "::error::Invalid PR number. Only numeric values are allowed."
exit 1
fi
PR_DATA=$(gh pr view "$PR_NUMBER" --repo "$REPO" --json state)
PR_STATE=$(echo "$PR_DATA" | jq -r '.state')
if [ "$PR_STATE" != "OPEN" ]; then
echo "::error::PR #$PR_NUMBER is not open (state: $PR_STATE)"
exit 1
fi
echo "checkout-ref=refs/pull/$PR_NUMBER/head" >> "$GITHUB_OUTPUT"
echo "Running integration tests for PR #$PR_NUMBER"
else
if ! echo "$BRANCH" | grep -Eq '^[a-zA-Z0-9_./-]+$'; then
echo "::error::Invalid branch name. Only alphanumeric characters, hyphens, underscores, dots, and slashes are allowed."
exit 1
fi
echo "checkout-ref=$BRANCH" >> "$GITHUB_OUTPUT"
echo "Running integration tests for branch $BRANCH"
fi
- name: Detect changed paths
id: detect-changes
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
PR_NUMBER: ${{ github.event.inputs.pr-number }}
BRANCH: ${{ github.event.inputs.branch }}
BASE_REF: ${{ steps.resolve.outputs.base-ref }}
CHECKOUT_REF: ${{ steps.resolve.outputs.checkout-ref }}
REPO: ${{ github.repository }}
run: |
if [ -n "$PR_NUMBER" ]; then
CHANGED_FILES=$(gh pr diff "$PR_NUMBER" --repo "$REPO" --name-only)
else
# For branches, compare against main using the GitHub API
CHANGED_FILES=$(gh api "repos/$REPO/compare/main...$BRANCH" --jq '.files[].filename')
fi
CHANGED_FILES=$(gh api "repos/$REPO/compare/$BASE_REF...$CHECKOUT_REF" \
--jq '.files[].filename')
DOTNET_CHANGES=false
PYTHON_CHANGES=false
@@ -113,22 +95,41 @@ jobs:
echo "dotnet=$DOTNET_CHANGES" >> "$GITHUB_OUTPUT"
echo "python=$PYTHON_CHANGES" >> "$GITHUB_OUTPUT"
echo "Detected changes dotnet: $DOTNET_CHANGES, python: $PYTHON_CHANGES"
echo "Detected changes; dotnet: $DOTNET_CHANGES, python: $PYTHON_CHANGES"
dotnet-integration-tests:
name: .NET Integration Tests
needs: resolve-ref
if: needs.resolve-ref.outputs.dotnet-changes == 'true'
permissions:
contents: read
id-token: write
uses: ./.github/workflows/dotnet-integration-tests.yml
with:
checkout-ref: ${{ needs.resolve-ref.outputs.checkout-ref }}
secrets: inherit
secrets:
AZURE_CLIENT_ID: ${{ secrets.AZURE_CLIENT_ID }}
AZURE_TENANT_ID: ${{ secrets.AZURE_TENANT_ID }}
AZURE_SUBSCRIPTION_ID: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
AZUREAI__ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
COPILOT_GITHUB_TOKEN: ${{ secrets.COPILOT_GITHUB_TOKEN }}
OPENAI__APIKEY: ${{ secrets.OPENAI__APIKEY }}
python-integration-tests:
name: Python Integration Tests
needs: resolve-ref
if: needs.resolve-ref.outputs.python-changes == 'true'
permissions:
contents: read
id-token: write
uses: ./.github/workflows/python-integration-tests.yml
with:
checkout-ref: ${{ needs.resolve-ref.outputs.checkout-ref }}
secrets: inherit
secrets:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
AZURE_CLIENT_ID: ${{ secrets.AZURE_CLIENT_ID }}
AZURE_TENANT_ID: ${{ secrets.AZURE_TENANT_ID }}
AZURE_SUBSCRIPTION_ID: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
COPILOT_GITHUB_TOKEN: ${{ secrets.COPILOT_GITHUB_TOKEN }}
FOUNDRY_MODELS_API_KEY: ${{ secrets.FOUNDRY_MODELS_API_KEY }}
OPENAI__APIKEY: ${{ secrets.OPENAI__APIKEY }}
+53 -10
View File
@@ -3,6 +3,12 @@ name: Issue Triage
on:
issues:
types: [opened, typed]
workflow_dispatch:
inputs:
issue_number:
description: Issue number to triage
required: true
type: string
permissions:
contents: read
@@ -12,7 +18,8 @@ permissions:
concurrency:
group: >-
issue-triage-${{ github.repository }}-${{
github.event.issue.type.name == 'Bug' && github.event.issue.number
github.event_name == 'workflow_dispatch' && inputs.issue_number
|| github.event.issue.type.name == 'Bug' && github.event.issue.number
|| github.run_id
}}
cancel-in-progress: true
@@ -26,7 +33,12 @@ env:
jobs:
team_check:
runs-on: ubuntu-latest
if: ${{ github.event.issue.type.name == 'Bug' }}
environment: github-app-auth
if: >-
${{
github.event_name == 'workflow_dispatch'
|| github.event.issue.type.name == 'Bug'
}}
outputs:
is_team_member: ${{ steps.check.outputs.is_team_member }}
issue_number: ${{ steps.issue.outputs.issue_number }}
@@ -36,14 +48,18 @@ jobs:
id: issue
shell: bash
env:
ISSUE_NUMBER_EVENT: ${{ github.event.issue.number }}
ISSUE_NUMBER: >-
${{
github.event_name == 'workflow_dispatch' && inputs.issue_number
|| github.event.issue.number
}}
run: |
set -euo pipefail
issue_number="${ISSUE_NUMBER_EVENT}"
issue_number="${ISSUE_NUMBER}"
if [[ ! "$issue_number" =~ ^[1-9][0-9]*$ ]]; then
echo "Could not determine issue number from event payload." >&2
echo "Could not determine issue number from event payload or manual input." >&2
exit 1
fi
@@ -53,18 +69,36 @@ jobs:
- name: Checkout scripts
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
sparse-checkout: .github/scripts
sparse-checkout: |
.github/actions/github-app-token
.github/scripts
fetch-depth: 1
persist-credentials: false
- name: Get GitHub automation token
id: github-auth
uses: ./.github/actions/github-app-token
with:
mode: ${{ vars.GH_APP_AUTH_MODE }}
azure-client-id: ${{ secrets.GH_APP_AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.GH_APP_AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.GH_APP_AZURE_SUBSCRIPTION_ID }}
key-vault-name: ${{ secrets.GH_APP_KEY_VAULT_NAME }}
key-name: ${{ secrets.GH_APP_KEY_NAME }}
github-app-client-id: ${{ secrets.GH_APP_CLIENT_ID }}
github-app-installation-id: ${{ secrets.GH_APP_INSTALLATION_ID }}
repository: ${{ github.repository }}
fallback-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
- name: Check issue author team membership
if: ${{ github.event_name != 'workflow_dispatch' }}
id: check
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
env:
TEAM_NAME: ${{ secrets.DEVELOPER_TEAM }}
ISSUE_NUMBER: ${{ steps.issue.outputs.issue_number }}
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
github-token: ${{ steps.github-auth.outputs.token }}
script: |
const checkTeamMembership = require('./.github/scripts/check_team_membership.js');
const { author, isTeamMember } = await checkTeamMembership({
@@ -84,8 +118,17 @@ jobs:
triage:
runs-on: ubuntu-latest
needs: team_check
if: ${{ needs.team_check.outputs.is_team_member == 'false' }}
if: >-
${{
github.event_name == 'workflow_dispatch'
|| needs.team_check.outputs.is_team_member == 'false'
}}
environment: integration
permissions:
contents: read
copilot-requests: write
id-token: write
issues: write
timeout-minutes: 60
steps:
@@ -114,7 +157,7 @@ jobs:
python-version: "3.13"
- name: Set up uv
uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7
uses: astral-sh/setup-uv@11f9893b081a58869d3b5fccaea48c9e9e46f990 # v8.3.2
with:
version: "0.11.x"
enable-cache: true
@@ -160,7 +203,7 @@ jobs:
working-directory: ${{ env.DEVFLOW_PATH }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GH_COPILOT_TOKEN: ${{ secrets.GH_COPILOT_TOKEN }}
GH_COPILOT_TOKEN: ${{ github.token }}
# Not seen by the agent prompt; used only to push a paper-trail
# branch back to maf-dashboard at run end.
DEVFLOW_TOKEN: ${{ secrets.DEVFLOW_TOKEN }}
+36 -16
View File
@@ -10,12 +10,39 @@ jobs:
name: "Issue: add labels"
if: ${{ github.event.action == 'opened' || github.event.action == 'reopened' }}
runs-on: ubuntu-latest
environment: github-app-auth
permissions:
contents: read
id-token: write
issues: write
steps:
- name: Checkout GitHub automation
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
sparse-checkout: |
.github/actions/github-app-token
.github/scripts/check_team_membership.js
fetch-depth: 1
persist-credentials: false
- name: Get GitHub automation token
id: github-auth
uses: ./.github/actions/github-app-token
with:
mode: ${{ vars.GH_APP_AUTH_MODE }}
azure-client-id: ${{ secrets.GH_APP_AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.GH_APP_AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.GH_APP_AZURE_SUBSCRIPTION_ID }}
key-vault-name: ${{ secrets.GH_APP_KEY_VAULT_NAME }}
key-name: ${{ secrets.GH_APP_KEY_NAME }}
github-app-client-id: ${{ secrets.GH_APP_CLIENT_ID }}
github-app-installation-id: ${{ secrets.GH_APP_INSTALLATION_ID }}
repository: ${{ github.repository }}
fallback-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
- uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
github-token: ${{ steps.github-auth.outputs.token }}
script: |
// Get the issue body and title
const body = context.payload.issue.body
@@ -24,21 +51,14 @@ jobs:
// Define the labels array
let labels = []
// Check if the issue author is in the agentframework-developers team
let isTeamMember = false
try {
const teamMembership = await github.rest.teams.getMembershipForUserInOrg({
org: context.repo.owner,
team_slug: process.env.TEAM_NAME,
username: context.payload.issue.user.login
})
console.log("Team Membership Data:", teamMembership);
isTeamMember = teamMembership.data.state === 'active'
} catch (error) {
// User is not in the team or team doesn't exist
console.error("Error fetching team membership:", error);
isTeamMember = false
}
const checkTeamMembership = require('./.github/scripts/check_team_membership.js')
const { isTeamMember } = await checkTeamMembership({
github,
context,
core,
teamSlug: process.env.TEAM_NAME,
issueNumber: context.issue.number,
})
// Only add triage label if the author is not in the team
if (!isTeamMember) {
+26 -6
View File
@@ -13,27 +13,47 @@ on:
jobs:
add_label:
runs-on: ubuntu-latest
environment: github-app-auth
permissions:
contents: read
id-token: write
issues: write
pull-requests: write
steps:
- uses: actions/labeler@f27b608878404679385c85cfa523b85ccb86e213 # v6
with:
repo-token: "${{ secrets.GH_ACTIONS_PR_WRITE }}"
- name: Checkout scripts
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
sparse-checkout: .github/scripts
ref: ${{ github.event.pull_request.base.sha }}
sparse-checkout: |
.github/actions/github-app-token
.github/scripts
fetch-depth: 1
persist-credentials: false
- name: Get GitHub automation token
id: github-auth
uses: ./.github/actions/github-app-token
with:
mode: ${{ vars.GH_APP_AUTH_MODE }}
azure-client-id: ${{ secrets.GH_APP_AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.GH_APP_AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.GH_APP_AZURE_SUBSCRIPTION_ID }}
key-vault-name: ${{ secrets.GH_APP_KEY_VAULT_NAME }}
key-name: ${{ secrets.GH_APP_KEY_NAME }}
github-app-client-id: ${{ secrets.GH_APP_CLIENT_ID }}
github-app-installation-id: ${{ secrets.GH_APP_INSTALLATION_ID }}
repository: ${{ github.repository }}
fallback-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
- uses: actions/labeler@f27b608878404679385c85cfa523b85ccb86e213 # v6
with:
repo-token: ${{ steps.github-auth.outputs.token }}
- name: "PR: add breaking change label from title"
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
github-token: ${{ steps.github-auth.outputs.token }}
script: |
const { syncBreakingChangeLabelFromTitle } = require('./.github/scripts/title_prefix.js');
await syncBreakingChangeLabelFromTitle({ github, context, core });
+43 -4
View File
@@ -6,6 +6,7 @@ on:
permissions:
contents: read
id-token: write
issues: write
pull-requests: write
@@ -21,16 +22,35 @@ env:
jobs:
team_check:
runs-on: ubuntu-latest
environment: github-app-auth
outputs:
is_team_member: ${{ steps.check.outputs.is_team_member }}
steps:
- name: Checkout scripts
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
sparse-checkout: .github/scripts
ref: ${{ github.event.pull_request.base.sha }}
sparse-checkout: |
.github/actions/github-app-token
.github/scripts
fetch-depth: 1
persist-credentials: false
- name: Get GitHub automation token
id: github-auth
uses: ./.github/actions/github-app-token
with:
mode: ${{ vars.GH_APP_AUTH_MODE }}
azure-client-id: ${{ secrets.GH_APP_AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.GH_APP_AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.GH_APP_AZURE_SUBSCRIPTION_ID }}
key-vault-name: ${{ secrets.GH_APP_KEY_VAULT_NAME }}
key-name: ${{ secrets.GH_APP_KEY_NAME }}
github-app-client-id: ${{ secrets.GH_APP_CLIENT_ID }}
github-app-installation-id: ${{ secrets.GH_APP_INSTALLATION_ID }}
repository: ${{ github.repository }}
fallback-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
- name: Check PR author team membership
id: check
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
@@ -38,7 +58,7 @@ jobs:
TEAM_NAME: ${{ secrets.DEVELOPER_TEAM }}
PR_NUMBER: ${{ github.event.pull_request.number }}
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
github-token: ${{ steps.github-auth.outputs.token }}
script: |
const checkTeamMembership = require('./.github/scripts/check_team_membership.js');
const { author, isTeamMember } = await checkTeamMembership({
@@ -57,20 +77,39 @@ jobs:
limit_open_prs:
runs-on: ubuntu-latest
environment: github-app-auth
needs: team_check
if: ${{ needs.team_check.outputs.is_team_member == 'false' }}
steps:
- name: Checkout scripts
uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
with:
sparse-checkout: .github/scripts
ref: ${{ github.event.pull_request.base.sha }}
sparse-checkout: |
.github/actions/github-app-token
.github/scripts
fetch-depth: 1
persist-credentials: false
- name: Get GitHub automation token
id: github-auth
uses: ./.github/actions/github-app-token
with:
mode: ${{ vars.GH_APP_AUTH_MODE }}
azure-client-id: ${{ secrets.GH_APP_AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.GH_APP_AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.GH_APP_AZURE_SUBSCRIPTION_ID }}
key-vault-name: ${{ secrets.GH_APP_KEY_VAULT_NAME }}
key-name: ${{ secrets.GH_APP_KEY_NAME }}
github-app-client-id: ${{ secrets.GH_APP_CLIENT_ID }}
github-app-installation-id: ${{ secrets.GH_APP_INSTALLATION_ID }}
repository: ${{ github.repository }}
fallback-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
- name: Enforce open PR limit
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
with:
github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
github-token: ${{ steps.github-auth.outputs.token }}
script: |
const { enforcePrLimit } = require('./.github/scripts/pr_limit_moderation.js');
await enforcePrLimit({
+1 -1
View File
@@ -26,7 +26,7 @@ jobs:
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Set up uv
uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7
uses: astral-sh/setup-uv@11f9893b081a58869d3b5fccaea48c9e9e46f990 # v8.3.2
with:
version-file: "python/pyproject.toml"
enable-cache: true
+31 -4
View File
@@ -13,13 +13,27 @@ on:
workflow_call:
inputs:
checkout-ref:
description: "Git ref to checkout (e.g., refs/pull/123/head)"
description: "Immutable commit SHA to check out"
required: true
type: string
secrets:
ANTHROPIC_API_KEY:
required: true
AZURE_CLIENT_ID:
required: true
AZURE_TENANT_ID:
required: true
AZURE_SUBSCRIPTION_ID:
required: true
COPILOT_GITHUB_TOKEN:
required: true
FOUNDRY_MODELS_API_KEY:
required: false
OPENAI__APIKEY:
required: true
permissions:
contents: read
id-token: write
env:
UV_CACHE_DIR: /tmp/.uv-cache
@@ -99,6 +113,9 @@ jobs:
# Azure OpenAI integration tests
python-tests-azure-openai:
name: Python Integration Tests - Azure OpenAI
permissions:
contents: read
id-token: write
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
@@ -224,6 +241,7 @@ jobs:
packages/hyperlight/tests
packages/ollama/tests
packages/core/tests/core/test_mcp.py
packages/hosting-mcp/tests
-m integration
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
@@ -260,6 +278,9 @@ jobs:
# Azure Functions + Durable Task integration tests
python-tests-functions:
name: Python Integration Tests - Functions
permissions:
contents: read
id-token: write
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
@@ -324,6 +345,9 @@ jobs:
# Foundry integration tests
python-tests-foundry:
name: Python Integration Tests - Foundry
permissions:
contents: read
id-token: write
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
@@ -378,6 +402,9 @@ jobs:
# Foundry Hosting integration tests
python-tests-foundry-hosting:
name: Python Integration Tests - Foundry Hosting
permissions:
contents: read
id-token: write
runs-on: ubuntu-latest
environment: integration
timeout-minutes: 60
@@ -551,7 +578,7 @@ jobs:
pattern: test-results-*
path: test-results/
- name: Restore report history cache
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
uses: actions/cache/restore@55cc8345863c7cc4c66a329aec7e433d2d1c52a9 # v6.1.0
with:
path: python/integration-report-history.json
key: integration-report-history-integration-${{ github.run_id }}
@@ -568,7 +595,7 @@ jobs:
run: cat integration-test-report.md >> $GITHUB_STEP_SUMMARY
- name: Save report history cache
if: always()
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
uses: actions/cache/save@55cc8345863c7cc4c66a329aec7e433d2d1c52a9 # v6.1.0
with:
path: python/integration-report-history.json
key: integration-report-history-integration-${{ github.run_id }}
+2 -2
View File
@@ -25,7 +25,7 @@ jobs:
pythonChanges: ${{ steps.filter.outputs.python}}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- uses: dorny/paths-filter@fbd0ab8f3e69293af611ebaee6363fc25e6d187d # v4.0.1
- uses: dorny/paths-filter@7b450fff21473bca461d4b92ce414b9d0420d706 # v4.0.2
id: filter
with:
filters: |
@@ -71,7 +71,7 @@ jobs:
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
exclude-packages: ${{ matrix.python-version == '3.10' && 'agent-framework-github-copilot' || '' }}
exclude-packages: ${{ matrix.python-version == '3.10' && 'agent-framework-github-copilot agent-framework-azure-cosmos-memory' || '' }}
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
+5 -3
View File
@@ -43,7 +43,7 @@ jobs:
githubCopilotChanged: ${{ steps.filter.outputs.github_copilot }}
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- uses: dorny/paths-filter@fbd0ab8f3e69293af611ebaee6363fc25e6d187d # v4.0.1
- uses: dorny/paths-filter@7b450fff21473bca461d4b92ce414b9d0420d706 # v4.0.2
id: filter
with:
filters: |
@@ -71,6 +71,7 @@ jobs:
- 'python/packages/ollama/**'
- 'python/packages/core/agent_framework/_mcp.py'
- 'python/packages/core/tests/core/test_mcp.py'
- 'python/packages/hosting-mcp/**'
- 'python/scripts/local_mcp_streamable_http_server.py'
- '.github/actions/setup-local-mcp-server/**'
- '.github/workflows/python-merge-tests.yml'
@@ -345,6 +346,7 @@ jobs:
packages/hyperlight/tests
packages/ollama/tests
packages/core/tests/core/test_mcp.py
packages/hosting-mcp/tests
-m integration
-n logical --dist worksteal
--timeout=120 --session-timeout=900 --timeout_method thread
@@ -748,7 +750,7 @@ jobs:
pattern: test-results-*
path: test-results/
- name: Restore report history cache
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
uses: actions/cache/restore@55cc8345863c7cc4c66a329aec7e433d2d1c52a9 # v6.1.0
with:
path: python/integration-report-history.json
key: integration-report-history-merge-${{ github.run_id }}
@@ -765,7 +767,7 @@ jobs:
run: cat integration-test-report.md >> $GITHUB_STEP_SUMMARY
- name: Save report history cache
if: always()
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
uses: actions/cache/save@55cc8345863c7cc4c66a329aec7e433d2d1c52a9 # v6.1.0
with:
path: python/integration-report-history.json
key: integration-report-history-merge-${{ github.run_id }}
+1 -1
View File
@@ -56,7 +56,7 @@ jobs:
- name: Build the package
run: uv run poe --directory packages/${{ env.PACKAGE }} build
- name: Release
uses: softprops/action-gh-release@3bb12739c298aeb8a4eeaf626c5b8d85266b0e65 # v2
uses: softprops/action-gh-release@718ea10b132b3b2eba29c1007bb80653f286566b # v3.0.1
with:
files: |
python/dist/*
@@ -701,7 +701,7 @@ jobs:
- name: Restore validation history
id: cache-restore
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
uses: actions/cache/restore@55cc8345863c7cc4c66a329aec7e433d2d1c52a9 # v6.1.0
with:
path: validation-history/
key: validation-history-${{ github.run_id }}
@@ -719,7 +719,7 @@ jobs:
run: cat trend-report.md >> "$GITHUB_STEP_SUMMARY"
- name: Save validation history
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
uses: actions/cache/save@55cc8345863c7cc4c66a329aec7e433d2d1c52a9 # v6.1.0
with:
path: validation-history/
key: validation-history-${{ github.run_id }}
+1 -1
View File
@@ -38,7 +38,7 @@ jobs:
with:
python-version: ${{ matrix.python-version }}
os: ${{ runner.os }}
exclude-packages: ${{ matrix.python-version == '3.10' && 'agent-framework-github-copilot' || '' }}
exclude-packages: ${{ matrix.python-version == '3.10' && 'agent-framework-github-copilot agent-framework-azure-cosmos-memory' || '' }}
env:
# Configure a constant location for the uv cache
UV_CACHE_DIR: /tmp/.uv-cache
+18 -1
View File
@@ -26,13 +26,30 @@ jobs:
ping_stale:
name: "Ping stale issues and PRs"
runs-on: ubuntu-latest
environment: github-app-auth
permissions:
contents: read
id-token: write
issues: write
pull-requests: write
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
- name: Get GitHub automation token
id: github-auth
uses: ./.github/actions/github-app-token
with:
mode: ${{ vars.GH_APP_AUTH_MODE }}
azure-client-id: ${{ secrets.GH_APP_AZURE_CLIENT_ID }}
azure-tenant-id: ${{ secrets.GH_APP_AZURE_TENANT_ID }}
azure-subscription-id: ${{ secrets.GH_APP_AZURE_SUBSCRIPTION_ID }}
key-vault-name: ${{ secrets.GH_APP_KEY_VAULT_NAME }}
key-name: ${{ secrets.GH_APP_KEY_NAME }}
github-app-client-id: ${{ secrets.GH_APP_CLIENT_ID }}
github-app-installation-id: ${{ secrets.GH_APP_INSTALLATION_ID }}
repository: ${{ github.repository }}
fallback-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
- uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5
with:
python-version: '3.13'
@@ -43,7 +60,7 @@ jobs:
- name: Run stale issue/PR ping
run: python .github/scripts/stale_issue_pr_ping.py
env:
GITHUB_TOKEN: ${{ secrets.GH_ACTIONS_PR_WRITE }}
GITHUB_TOKEN: ${{ steps.github-auth.outputs.token }}
TEAM_SLUG: ${{ secrets.DEVELOPER_TEAM }}
DAYS_THRESHOLD: ${{ github.event.inputs.days_threshold || '4' }}
DRY_RUN: ${{ github.event.inputs.dry_run || 'false' }}
+2 -2
View File
@@ -2,7 +2,7 @@
**What is Microsoft Agent Framework?**
Microsoft Agent Framework is a comprehensive multi-language (C#/.NET and Python) framework for building, orchestrating, and deploying AI agents and multi-agent workflows. The system takes user instructions and conversation inputs and produces intelligent responses through AI agents that can integrate with various LLM providers (OpenAI, Azure OpenAI, Azure AI Foundry). It provides both simple chat agents and complex multi-agent workflows with graph-based orchestration.
Microsoft Agent Framework is a comprehensive multi-language (C#/.NET and Python) framework for building, orchestrating, and deploying AI agents and multi-agent workflows. The system takes user instructions and conversation inputs and produces intelligent responses through AI agents that can integrate with various LLM providers (OpenAI, Azure OpenAI, Microsoft Foundry). It provides both simple chat agents and complex multi-agent workflows with graph-based orchestration.
**What can Microsoft Agent Framework do?**
@@ -12,7 +12,7 @@ The framework offers:
- **Multi-Agent Orchestration**: Group chat, sequential, concurrent, and handoff patterns
- **Graph-based Workflows**: Connect agents and deterministic functions using data flows with streaming, checkpointing, time-travel, and Human-in-the-loop
- **Extensibility Framework**: Extend with native functions, A2A, Model Context Protocol (MCP)
- **LLM Integration**: Support for OpenAI, Azure OpenAI, Azure AI Foundry, and other providers
- **LLM Integration**: Support for OpenAI, Azure OpenAI, Microsoft Foundry, and other providers
- **Runtime Support**: Both in-process and distributed agent execution
**What is/are Microsoft Agent Framework's intended use(s)?**
+2 -2
View File
@@ -2,7 +2,7 @@
# These are optional elements. Feel free to remove any of them.
status: accepted
contact: westey-m
date: 2025-07-10 {YYYY-MM-DD when the decision was last updated}
date: 2025-07-10
deciders: sergeymenshykh, markwallace, rbarreto, dmytrostruk, westey-m, eavanvalkenburg, stephentoub
consulted:
informed:
@@ -139,7 +139,7 @@ Therefore something like `AgentResponse.Text` which also aggregates all `TextCon
#### Option 1.2 Presence of Secondary Content is determined by a runtime parameter
We can allow callers to choose whether to include secondary content in the list of reponse messages.
We can allow callers to choose whether to include secondary content in the list of response messages.
Open Question: Do we allow secondary content to use `TextContent` types?
```csharp
+8 -8
View File
@@ -113,7 +113,7 @@ Implement a hybrid strategy where common tools use generic `AITool`-derived abst
### AI Agent Tool Types Availability
Tool Type | Azure AI Foundry Agent Service | OpenAI Assistant API | OpenAI ChatCompletion API | OpenAI Responses API | Amazon Bedrock Agents | Google | Anthropic | Description
Tool Type | Microsoft Foundry Agent Service | OpenAI Assistant API | OpenAI ChatCompletion API | OpenAI Responses API | Amazon Bedrock Agents | Google | Anthropic | Description
-- | -- | -- | -- | -- | -- | -- | -- | --
Function Calling | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | Enables custom, stateless functions to define specific agent behaviors.
Code Interpreter | ✅ | ✅ | ❌ | ✅ | ✅ | ✅ | ✅ | Allows agents to execute code for tasks like data analysis or problem-solving.
@@ -132,7 +132,7 @@ Image Generation | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | Generates or edits
#### Function Calling
<details>
<summary>Azure AI Foundry Agent Service</summary>
<summary>Microsoft Foundry Agent Service</summary>
Source: <a href="https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/function-calling?pivots=rest">https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/function-calling?pivots=rest</a>
Message Request:
@@ -401,7 +401,7 @@ Image Generation | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | Generates or edits
#### Code Interpreter
<details>
<summary>Azure AI Foundry Agent Service</summary>
<summary>Microsoft Foundry Agent Service</summary>
<p>Source: <a href="https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/code-interpreter-samples?pivots=rest-api">https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/code-interpreter-samples?pivots=rest-api</a></p>
<p>.NET Support: ✅</p>
@@ -709,7 +709,7 @@ Image Generation | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | Generates or edits
#### Search and Retrieval
<details>
<summary>Azure AI Foundry Agent Service</summary>
<summary>Microsoft Foundry Agent Service</summary>
Source: <a href="https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/file-search-upload-files?pivots=rest">https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/file-search-upload-files?pivots=rest</a>
File Search Request:
@@ -1083,7 +1083,7 @@ Image Generation | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | Generates or edits
#### Web Search
<details>
<summary>Azure AI Foundry Agent Service</summary>
<summary>Microsoft Foundry Agent Service</summary>
Source: <a href="https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/bing-code-samples?pivots=rest">https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/bing-code-samples?pivots=rest</a>
Bing Search Message Request:
@@ -1630,7 +1630,7 @@ Image Generation | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | Generates or edits
#### OpenAPI Spec Tool
<details>
<summary>Azure AI Foundry Agent Service</summary>
<summary>Microsoft Foundry Agent Service</summary>
Source: <a href="https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/openapi-spec-samples?pivots=rest-api">https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/openapi-spec-samples?pivots=rest-api</a><br>
Source: <a href="https://learn.microsoft.com/en-us/rest/api/aifoundry/aiagents/run-steps/get-run-step?view=rest-aifoundry-aiagents-v1&tabs=HTTP#runstepopenapitoolcall">https://learn.microsoft.com/en-us/rest/api/aifoundry/aiagents/run-steps/get-run-step?view=rest-aifoundry-aiagents-v1&tabs=HTTP#runstepopenapitoolcall</a>
@@ -1712,7 +1712,7 @@ Image Generation | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | Generates or edits
#### Stateful Functions
<details>
<summary>Azure AI Foundry Agent Service</summary>
<summary>Microsoft Foundry Agent Service</summary>
Source: <a href="https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/azure-functions-samples?pivots=rest">https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/azure-functions-samples?pivots=rest</a>
Message Request:
@@ -1832,7 +1832,7 @@ Image Generation | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | Generates or edits
#### Microsoft Fabric
<details>
<summary>Azure AI Foundry Agent Service</summary>
<summary>Microsoft Foundry Agent Service</summary>
Source: <a href="https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/fabric?pivots=rest">https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/fabric?pivots=rest</a>
Message Request:
+2 -2
View File
@@ -2,7 +2,7 @@
# These are optional elements. Feel free to remove any of them.
status: accepted
contact: westey-m
date: 2025-09-12 {YYYY-MM-DD when the decision was last updated}
date: 2025-09-12
deciders: sergeymenshykh, markwallace-microsoft, rogerbarreto, dmytrostruk, westey-m, eavanvalkenburg, stephentoub, peterychang
consulted:
informed:
@@ -25,7 +25,7 @@ See various features that would need to be supported via this type of mechanism,
- Also see [the openai human-in-the-loop guide](https://openai.github.io/openai-agents-js/guides/human-in-the-loop/#approval-requests).
- Also see [the openai MCP guide](https://openai.github.io/openai-agents-js/guides/mcp/#optional-approval-flow).
- Also see [MCP Approval Requests from OpenAI](https://platform.openai.com/docs/guides/tools-remote-mcp#approvals).
- Also see [Azure AI Foundry MCP Approvals](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/model-context-protocol-samples?pivots=rest#submit-your-approval).
- Also see [Microsoft Foundry MCP Approvals](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/model-context-protocol-samples?pivots=rest#submit-your-approval).
- Also see [MCP Elicitation requests](https://modelcontextprotocol.io/specification/draft/client/elicitation)
## Decision Drivers
@@ -57,7 +57,7 @@ This section describes different options for various aspects required to add lon
### 1. Methods for Working with Long-Running Operations
Based on the analysis of existing APIs that support long-running operations (such as OpenAI Responses, Azure AI Foundry Agents, and A2A),
Based on the analysis of existing APIs that support long-running operations (such as OpenAI Responses, Microsoft Foundry Agents, and A2A),
the following operations are used for working with long-running operations:
- Common operations:
- **Start Long-Running Execution**: Initiates a long-running operation and returns its Id.
@@ -757,7 +757,7 @@ Some of them natively support resuming streaming from a specific point in the st
| API | Can Resume Streaming | Model |
|-------------------------|--------------------------------------|------------------------------------------------------------------------------------------------------------|
| OpenAI Responses | Yes | StreamingResponseUpdate.**SequenceNumber** + GetResponseStreamingAsync(responseId, **startingAfter**, ct) |
| Azure AI Foundry Agents | Emulated<sup>2</sup> | RunStep.**Id** + custom pseudo code: client.Runs.GetRunStepsAsync(...).AllStepsAfter(**stepId**) |
| Microsoft Foundry Agents | Emulated<sup>2</sup> | RunStep.**Id** + custom pseudo code: client.Runs.GetRunStepsAsync(...).AllStepsAfter(**stepId**) |
| A2A | Implementation dependent<sup>1</sup> | |
<sup>1</sup> The [A2A specification](https://github.com/a2aproject/A2A/blob/main/docs/topics/streaming-and-async.md#1-streaming-with-server-sent-events-sse)
@@ -765,7 +765,7 @@ allows an A2A agent implementation to decide how to handle streaming resumption:
a task is still active (and the server hasn't sent a final: true event for that phase), the client can attempt to reconnect to the stream using the tasks/resubscribe RPC method.
The server's behavior regarding missed events during the disconnection period (e.g., whether it backfills or only sends new updates) is implementation-dependent._
<sup>2</sup> The Azure AI Foundry Agents API has an API to start a streaming run but does not have an API to resume streaming from a specific point in the stream.
<sup>2</sup> The Microsoft Foundry Agents API has an API to start a streaming run but does not have an API to resume streaming from a specific point in the stream.
However, it has non-streaming APIs to access already started runs, which can be used to emulate streaming resumption by accessing a run and its steps and streaming all the steps after a specific step.
#### Required Changes
@@ -828,7 +828,7 @@ Sequence of updates from OpenAI Responses API to answer the question "What time
| resp_2 | 10 | resp.output_item.done | - | InProgress | |
| resp_2 | 11 | resp.completed | Completed | Completed | |
Sequence of updates from Azure AI Foundry Agents API to answer the question "What time is it?" using a function call:
Sequence of updates from Microsoft Foundry Agents API to answer the question "What time is it?" using a function call:
| Id | SN | UpdateKind | Run.Status | Step.Status | Message.Status | ChatResponseUpdate.Status | Description |
|--------|---------|-------------------|----------------|-------------|-----------------|---------------------------|---------------------------------------------------|
| run_1 | - | RunCreated | Queued | - | - | Queued | |
@@ -852,7 +852,7 @@ Sequence of updates from Azure AI Foundry Agents API to answer the question "Wha
To support long-running operations, the following values need to be returned by the GetResponseAsync and GetStreamingResponseAsync methods:
- `ResponseId` - identifier of the long-running operation or an entity representing it, such as a task.
- `ConversationId` - identifier of the conversation or thread the long-running operation is part of. Some APIs, like Azure AI Foundry Agents, use
- `ConversationId` - identifier of the conversation or thread the long-running operation is part of. Some APIs, like Microsoft Foundry Agents, use
this identifier together with the ResponseId to identify a run.
- `SequenceNumber` - identifier of an update within a stream of updates. This is required to support streaming resumption by the GetStreamingResponseAsync method only.
- `Status` - status of the long-running operation: whether it is queued, running, failed, cancelled, completed, etc.
@@ -1089,7 +1089,7 @@ public class ChatOptions
##### 6.1.5 Continuation Token of a Custom Type
The option is similar the the "6.1.3 Continuation Token of System.ClientModel.ContinuationToken Type" option but suggests using a
The option is similar to the "6.1.3 Continuation Token of System.ClientModel.ContinuationToken Type" option but suggests using a
custom type for the continuation token instead of the `System.ClientModel.ContinuationToken` type.
**Pros**
@@ -1203,7 +1203,7 @@ response = await agent.CancelRunAsync(response.ResponseId, new AgentCancelRunOpt
In case an agent supports either or both cancellation and deletion of long-running operations, it will override the corresponding methods.
Otherwise, it won't override them, and the base implementations will return null by default.
Some agents, for example Azure AI Foundry Agents, require the thread identifier to cancel a run. To accommodate this requirement, the `CancelRunAsync` method
Some agents, for example Microsoft Foundry Agents, require the thread identifier to cancel a run. To accommodate this requirement, the `CancelRunAsync` method
accepts an optional `AgentCancelRunOptions` parameter that allows callers to specify the thread associated with the run they want to cancel.
```csharp
@@ -1574,7 +1574,7 @@ the thread is provided with background operations consistently for all runs.
</details>
<details>
<summary>Azure AI Foundry Agents</summary>
<summary>Microsoft Foundry Agents</summary>
- Create a thread and run the agent against it and wait for it to complete using polling:
```csharp
@@ -34,11 +34,11 @@ Key changes:
1. **New `agent-framework-openai` package** with dependencies on `agent-framework-core`, `openai`, and `packaging` only.
2. **Class renames**: `OpenAIResponsesClient``OpenAIChatClient` (Responses API), `OpenAIChatClient``OpenAIChatCompletionClient` (Chat Completions API). Old names remain as deprecated aliases.
3. **Deprecated classes**: `OpenAIAssistantsClient`, all `AzureOpenAI*Client` classes, `AzureAIClient`, `AzureAIAgentClient`, and `AzureAIProjectAgentProvider` are marked deprecated.
4. **New `FoundryChatClient`** in azure-ai for Azure AI Foundry Responses API access, built on `RawFoundryChatClient(RawOpenAIChatClient)`.
4. **New `FoundryChatClient`** in azure-ai for Microsoft Foundry Responses API access, built on `RawFoundryChatClient(RawOpenAIChatClient)`.
5. **All deprecated `AzureOpenAI*` classes** consolidated into a single file (`_deprecated_azure_openai.py`) in the azure-ai package for clean future deletion.
6. **Core's `agent_framework.openai` and `agent_framework.azure` namespaces** become lazy-loading gateways, preserving backward-compatible import paths while removing hard dependencies.
7. **Unified `model` parameter** replaces `model_id` (OpenAI), `deployment_name` (Azure OpenAI), and `model_deployment_name` (Azure AI) across all client constructors. The term `model` is intentionally generic: it naturally maps to an OpenAI model name *and* to an Azure OpenAI deployment name, making it straightforward to use `OpenAIChatClient` with either OpenAI or Azure OpenAI backends (via `AsyncAzureOpenAI`). Environment variables are similarly unified (e.g., `OPENAI_MODEL` instead of separate `OPENAI_CHAT_MODEL_ID` / `OPENAI_CHAT_COMPLETION_MODEL_ID`).
8. **`FoundryAgent`** replaces the pattern of `Agent(client=AzureAIClient(...))` for connecting to pre-configured agents in Azure AI Foundry (PromptAgents and HostedAgents). The underlying `RawFoundryAgentChatClient` is an implementation detail — most users interact only with `FoundryAgent`. `AzureAIAgentClient` is separately deprecated as it refers to the V1 Agents Service API. See below for design rationale.
8. **`FoundryAgent`** replaces the pattern of `Agent(client=AzureAIClient(...))` for connecting to pre-configured agents in Microsoft Foundry (PromptAgents and HostedAgents). The underlying `RawFoundryAgentChatClient` is an implementation detail — most users interact only with `FoundryAgent`. `AzureAIAgentClient` is separately deprecated as it refers to the V1 Agents Service API. See below for design rationale.
### Foundry Agent Design: `FoundryAgentClient` vs `FoundryAgent`
@@ -7,11 +7,11 @@ consulted: Pratyush Mishra, Shivam Shrivastava, Manni Arora (Centrica eval scena
informed: Agent Framework team, Foundry Evals team
---
# Agent Evaluation Architecture with Azure AI Foundry Integration
# Agent Evaluation Architecture with Microsoft Foundry Integration
## Context and Problem Statement
Azure AI Foundry provides a rich evaluation service for AI agents — built-in evaluators for agent behavior (task adherence, intent resolution), tool usage (tool call accuracy, tool selection), quality (coherence, fluency, relevance), and safety (violence, self-harm, prohibited actions). Results are viewable in the Foundry portal with dashboards and comparison views.
Microsoft Foundry provides a rich evaluation service for AI agents — built-in evaluators for agent behavior (task adherence, intent resolution), tool usage (tool call accuracy, tool selection), quality (coherence, fluency, relevance), and safety (violence, self-harm, prohibited actions). Results are viewable in the Foundry portal with dashboards and comparison views.
However, using Foundry Evals with an agent-framework agent today requires significant manual effort. Developers must:
@@ -445,7 +445,7 @@ These factorings produce different scores for the same conversation. The framewo
### Azure AI: FoundryEvals
`Evaluator` implementation backed by Azure AI Foundry:
`Evaluator` implementation backed by Microsoft Foundry:
```python
class FoundryEvals:
@@ -812,4 +812,4 @@ public sealed class EvalItem
## More Information
- [Foundry Evals documentation](https://learn.microsoft.com/azure/ai-foundry/concepts/evaluation-approach-gen-ai) — Azure AI Foundry evaluation overview
- [Foundry Evals documentation](https://learn.microsoft.com/azure/ai-foundry/concepts/evaluation-approach-gen-ai) — Microsoft Foundry evaluation overview
@@ -9,7 +9,7 @@ deciders: evmattso
## What is the goal of this feature?
Enable Agent Framework users to consume Foundry **toolboxes** — named, versioned bundles of tool definitions stored server-side in an Azure AI Foundry project — directly from `FoundryChatClient`, without dropping to the raw `azure-ai-projects` SDK.
Enable Agent Framework users to consume Foundry **toolboxes** — named, versioned bundles of tool definitions stored server-side in a Microsoft Foundry project — directly from `FoundryChatClient`, without dropping to the raw `azure-ai-projects` SDK.
A user who has configured a toolbox in the Foundry portal (or via the raw SDK) should be able to load it into an agent with a single call:
+9 -3
View File
@@ -181,8 +181,8 @@ The app chooses which helper to call for that route and deployment. For example:
- `responses_session_id(body)` from `agent-framework-hosting-responses`, which can return either a `resp_*` previous
response id or a `conv_*` conversation id when present;
- `telegram_session_id(update)` from `agent-framework-hosting-telegram`, which can choose the chat, user, thread, or
other Telegram-native partitioning logic for that helper;
- `telegram_session_id(update, bot_id=...)` from `agent-framework-hosting-telegram`, which uses the bot and sender for
private chats and the bot and chat for shared group sessions;
- `activity_session_id(activity)`, `discord_session_id(interaction_or_message)`, or
`a2a_session_id(request_context)` from their respective protocol packages;
- `foundry_user_isolation_key()` or `foundry_chat_isolation_key()` from `agent-framework-foundry-hosting`.
@@ -204,7 +204,8 @@ safe to use:
transient execution.
A `SessionStore` stores `session_id -> AgentSession`, but it does not create sessions. `AgentState` resolves the agent
target and creates the session on first use:
target and creates the session on first use. Reads return independent working copies so running from one continuation
point does not mutate the stored snapshot or another simultaneous branch:
For agent targets:
@@ -227,6 +228,11 @@ await state.set_session(response_id, session)
`agent.run(...)` may update the session object (for example, with service continuation state), so the explicit store call
belongs after the run, not before it.
Response ids are immutable continuation points, so simultaneous callers can branch from one `previous_response_id` and
store their completed sessions under different new response ids. A stable `conversation_id` is a mutable head: the app
must explicitly update it after the run and provide single-writer coordination. The hosting state helper does not lock
an entire run or resolve concurrent updates to that stable key.
The session id is a partition key, not proof of identity. App or platform code must authenticate and authorize any
externally supplied key before using it.
@@ -0,0 +1,177 @@
---
status: accepted
contact: rogerbarreto
date: 2026-07-08
deciders: rogerbarreto
consulted: eavanvalkenburg
informed: []
---
# .NET hosting: OpenAI Responses protocol helpers for app-owned routing
Realizes the helper-first direction of [ADR-0027](0027-hosting-channels.md) for .NET.
## Context and Problem Statement
[ADR-0027](0027-hosting-channels.md) refocused the (Python) hosting design away from a channel
framework toward **protocol conversion helpers plus optional execution state**: Agent Framework owns
protocol-native <-> run conversion, while the application owns HTTP routing, authentication,
middleware, storage, and native SDK calls.
.NET already ships `Microsoft.Agents.AI.Hosting.OpenAI`, a route-owning server that **exposes an
`AIAgent` (or workflow) as the OpenAI Responses API** (`MapOpenAIResponses` + `IResponsesService`). It
owns the routes, an in-memory response/conversation store, streaming, and lifecycle. The question is
what, if anything, .NET must add to satisfy the ADR-0027 boundary.
## Decision Drivers
- Do not reinvent conversion logic that already exists and is battle-tested in `Hosting.OpenAI`.
- Give applications a way to own their own route/auth/middleware/storage while reusing Agent Framework
conversion (the ADR-0027 boundary).
- Keep the released public surface small.
- Stay consistent with the existing .NET hosting stack, which deliberately does **not** use the OpenAI
SDK Responses types server-side (it hand-rolled its own wire model).
## Considered Options
1. Self-contained new package that reimplements conversion using the OpenAI SDK Responses types
(mirrors the Python `agent-framework-hosting-responses` lineage).
2. New package that reuses `Hosting.OpenAI`'s internal converters (via `InternalsVisibleTo` or by
moving the conversion core out).
3. Thin public helper facade **inside** `Hosting.OpenAI` over the existing internal converters, plus
protocol-neutral execution-state holders in `Microsoft.Agents.AI.Hosting`.
### First-principles gap analysis
A capability comparison of the ADR-0027 / PR #6891 helper surface against the existing .NET stack:
| Python helper capability | .NET today | Status |
| --- | --- | --- |
| `responses_to_run` | `ResponseInput.GetInputMessages` + `InputMessage.ToChatMessage` + `OpenAIResponsesMapOptions.RunOptionsFactory` | exists, internal |
| `responses_from_run` | `AgentResponseExtensions.ToResponse` | exists, internal |
| `responses_from_streaming_run` | `AgentResponseUpdateExtensions.ToStreamingResponseAsync` + `SseJsonResult` (also renders workflow events) | exists, internal, richer |
| `responses_session_id` | continuity resolved inside `InMemoryResponsesService` | exists, internal, not standalone |
| `create_response_id` | `IdGenerator` | exists, internal |
| `AgentState` (target + store, get-or-create, callable/awaitable target) | `AgentSessionStore` (get-or-create + save + serialize + isolation) + DI container (target lifetime + async setup) | create-on-miss lives in the store; per-run instance and deferred/async target come from DI, so no separate holder is needed |
| `SessionStore` (get/set/delete) | `AgentSessionStore` + `InMemoryAgentSessionStore` | richer; `Delete` added |
| `WorkflowState` + checkpoint resume | `WorkflowCatalog`/`HostedWorkflowBuilder`; workflow events already render over Responses; `CheckpointManager` is session-keyed | partial; no per-session checkpoint cursor |
| App owns routing/auth/middleware/storage | `MapOpenAIResponses`/`IResponsesService` own routing + storage | **the one real gap** |
.NET already covers ~90% of the capability, and more richly (its streaming renderer even emits workflow
events; its session store serializes and supports per-principal isolation, neither of which Python's
in-memory `SessionStore` does). The single genuine gap is the **ownership model**: every conversion
primitive is bundled behind the route-owning server, so an application cannot own its own route and
call just the conversion.
Note on lineage: Python's Responses offering was introduced *as a channel* (PR #6580) and always used
the `openai` SDK Responses types. .NET's `Hosting.OpenAI` predates and is independent of channels and
hand-rolled its own server-side wire DTOs (the SDK's Responses types are client-shaped and awkward
server-side). So Option 1 would both reinvent a working asset and contradict the .NET codebase's own
precedent.
## Decision Outcome
Chosen option: **3. Thin public helper facade inside `Hosting.OpenAI` plus neutral state holders**,
because the only real gap is the ownership model, so the work is to *un-bundle* the existing
converters, not to rebuild them or add a package.
### Public surface
`Microsoft.Agents.AI.Hosting.OpenAI` gains a single public static facade, `OpenAIResponses`, whose
boundary is `System.Text.Json` (`JsonElement`/streamed events), matching Python's dict boundary and
keeping the hand-rolled wire DTOs internal:
- `OpenAIResponses.ToAgentRunRequest(JsonElement body)` -> messages + `AgentRunOptions?`.
- `OpenAIResponses.WriteResponse(AgentRunResponse response, string responseId, string? sessionId = null)`
-> a Responses-shaped `JsonElement`.
- `OpenAIResponses.WriteResponseStreamAsync(IAsyncEnumerable<AgentRunResponseUpdate> updates, string responseId, ...)`
-> Responses SSE `data:` frames.
- `OpenAIResponses.GetSessionId(JsonElement body)` -> `previous_response_id` or `conversation` id, or
`null`. Kept **separate** from `ToAgentRunRequest` so the trust boundary is visible: choosing to use
a request-derived key is an explicit application decision.
- `OpenAIResponses.CreateResponseId()` -> a `resp_*` id.
All helpers are side-effect-free and delegate to the existing internal converters. `MapOpenAIResponses`
public behavior is unchanged; it and the facade share one internal conversion core (an internal
`ToResponse` overload with an optional originating request is added so the facade can render without a
request object).
### Optional execution state (neutral package)
`Microsoft.Agents.AI.Hosting` gains:
- `AgentSessionStore.DeleteSessionAsync(...)` (+ `InMemoryAgentSessionStore` implementation and
isolation-decorator passthrough): the one missing store operation.
- No agent-side holder. Applications use `AgentSessionStore` directly: `GetSessionAsync(agent, id)`
already creates on miss and returns an independent session instance per call (so concurrent calls fork
the same stored state rather than sharing an instance), `SaveSessionAsync(agent, id, session)` persists
post-run (including under a newly minted id), and `DeleteSessionAsync(agent, id)` removes it. An earlier
draft added a `HostedAgentState` holder, but once create-on-miss lives in the store and the store does no
cross-call locking, the holder would only bind the `agent` argument, which is not enough to justify a
public type. Any coordination for concurrent runs against the same id is the application's concern.
(Unlike Python, whose `SessionStore` is get/set-only and whose `AgentState` therefore owns
create-on-miss, .NET's store already owns it.)
Python's `AgentState` carries two further responsibilities beyond create-on-miss: it accepts a callable
or awaitable target so the host can (1) obtain a fresh agent instance per run and (2) defer expensive or
asynchronous agent setup while keeping server construction synchronous. In .NET these two concerns are
owned by the dependency-injection container, not by a hosting type. Per-run lifetime is expressed by the
registration lifetime (`AddScoped`/`AddTransient` yields a fresh `AIAgent` per request or scope, resolved
by the framework), and deferred or asynchronous construction is expressed by an async factory registration
(for example an `async` factory delegate, `ActivatorUtilities`, or resolving the agent inside the request
after any async warm-up), so the route handler resolves an already-built agent from the container. An
`AIAgent` is also safe to invoke concurrently (per-turn state lives in `AgentSession`, not the agent), so
the "fresh instance per run" motivation does not apply to it the way it does to a workflow. This is the
deliberate asymmetry with `HostedWorkflowState` below: a `Workflow` instance is a stateful run engine that
cannot be driven by two runners at once, so the factory/`cacheWorkflow` affordance is load-bearing there
for correctness, whereas for agents the container already provides both per-run instances and async setup.
- `HostedWorkflowState`: a thin holder bundling a workflow target with a `CheckpointManager` and an
internal `sessionId -> CheckpointInfo` head cursor, exposing `RunOrResumeAsync`. .NET's checkpoint
store is already `sessionId`-keyed (unlike Python's workflow-name keying), but `CheckpointInfo` has
no ordering, so the holder remembers the head checkpoint per session to resume. On subsequent turns it
restores that checkpoint and runs the workflow forward with the new turn's input (mirroring the Python
host's restore-then-run semantics), rather than continuing a halted run with no input. When the
in-memory cursor misses (new holder / process restart) it reads the session's latest checkpoint from the
`CheckpointManager`, so a durable manager resumes across restarts. It accepts either a single workflow
instance (which cannot be run by two runners at once, so its turns are processed one at a time) or a
workflow factory (`Func<CancellationToken, ValueTask<Workflow>>`). By default the factory builds a fresh
instance per run so independent sessions run in parallel; with `cacheWorkflow: true` the factory is invoked
once lazily and its result is cached and reused (a deferred, cached target that, like the instance, cannot
run concurrent turns). A resume rehydrates an instance from the session's checkpoint in the shared store, so
per-run instances still continue the same run; concurrent turns against the same session id remain the
application's coordination responsibility.
### Scope
Responses only for v1; the facade is named so a parallel `OpenAIChatCompletions` facade can follow.
No new package, no OpenAI-SDK-typed reimplementation, no change to `MapOpenAIResponses` public
behavior.
### Security responsibilities
Consistent with ADR-0027, the application owns the trust boundary. `GetSessionId(...)` returns an
untrusted candidate key; the application must authenticate the caller and authorize/bind the id before
using it as an `AgentSessionStore` key or workflow checkpoint session id. Multi-user hosts must scope
the session store per principal (`IsolationKeyScopedAgentSessionStore`). Helpers stay side-effect-free;
persistence happens only after the run completes.
## Consequences
Positive:
- Smallest possible surface: the released addition is one facade type plus one thin workflow state
holder and one new store method (agents use `AgentSessionStore` directly, no holder).
- No duplicated conversion; the app-owned-routing path and the route-owning server share one core.
- `MapOpenAIResponses` users are unaffected.
Negative:
- The facade's `JsonElement` boundary is less strongly typed than the internal DTOs (accepted to keep
the wire model internal and mirror Python's dict boundary).
- Workflow resume relies on an in-memory head cursor by default; durable multi-replica hosts must
supply their own cursor persistence.
## More Information
- Parent ADR: [ADR-0027](0027-hosting-channels.md).
- Spec: `docs/specs/003-dotnet-hosting-protocol-helpers.md`.
+151 -1
View File
@@ -66,8 +66,11 @@ must be aligned with the helper-first model before implementation. Old vocabular
| Package | Import surface | v1 helper-first contents |
|---|---|---|
| `agent-framework-hosting` | `agent_framework_hosting` | `AgentState`, `WorkflowState`, `SessionStore`, and run-argument `TypedDict`s. |
| `agent-framework-hosting-a2a` | `agent_framework_hosting_a2a` | A2A `Message` to run conversion and Agent Framework output to A2A `Part` conversion. |
| `agent-framework-hosting-mcp` | `agent_framework_hosting_mcp` | Agent and workflow MCP tool adapters, MCP tool arguments to run conversion, and Agent Framework output to MCP `ContentBlock` conversion. |
| `agent-framework-hosting-responses` | `agent_framework_hosting_responses` | Responses helpers: request parsing, session id extraction, response id creation, response rendering, streaming rendering. |
| Future protocol packages | e.g. `agent_framework_hosting_telegram` | Protocol-specific helpers such as `telegram_to_run(...)`, `telegram_from_run(...)`, `telegram_session_id(...)`, and command/media helpers when useful. |
| `agent-framework-hosting-telegram` | `agent_framework_hosting_telegram` | Telegram Bot API helpers: update parsing, chat/session/command/media extraction, final rendering, and streaming edit rendering. |
| Future protocol packages | e.g. `agent_framework_hosting_activity_protocol` | Protocol-specific helpers such as `activity_to_run(...)`, `activity_from_run(...)`, `activity_session_id(...)`, and command/media helpers when useful. |
The core hosting package must not depend on protocol SDKs. Protocol packages may depend on their native protocol SDKs if
needed, but helper functions should stay usable from plain app code and tests.
@@ -90,6 +93,7 @@ Examples:
- `responses_to_run(...)`, `responses_from_run(...)`, `responses_from_streaming_run(...)`,
`responses_session_id(...)`;
- `a2a_to_run(...)`, `a2a_from_run(...)`;
- `telegram_to_run(...)`, `telegram_from_run(...)`, `telegram_from_streaming_run(...)`,
`telegram_session_id(...)`, `telegram_command(...)`;
- `activity_to_run(...)`, `activity_from_run(...)`, `activity_session_id(...)`, `activity_command(...)`;
@@ -177,6 +181,9 @@ The target may be:
- `await get_target()`;
- synchronous `target` only after a target is already available/resolved.
A workflow instance permits one active run. Concurrent hosts use a factory or
builder with `cache_target=False` to resolve a fresh instance per run.
Workflow checkpointing uses Agent Framework's existing `CheckpointStorage` abstraction directly. Apps that need
per-session workflow resume should keep an app-owned cursor such as `session_id -> checkpoint_id`. When the app uses
file-backed cursor storage, the file-based checkpoint storage should share the same app storage root and should be
@@ -244,6 +251,146 @@ text deltas, and a completed event. The final completed payload is produced thro
also preserves the model id observed on streaming updates when the finalized `AgentResponse` no longer carries raw model
metadata.
## `agent-framework-hosting-a2a`
The A2A package provides only the conversion seam between the native A2A SDK
and Agent Framework:
- `a2a_to_run(message, *, stream=False) -> AgentRunArgs`
- `a2a_from_run(result) -> list[a2a.types.Part]`
`a2a_to_run(...)` accepts a native A2A `Message` and converts its text, URL,
raw-byte, and structured-data parts into one Agent Framework user message.
`a2a_from_run(...)` accepts an `AgentResponse`, `Message`, or
`AgentResponseUpdate` and converts supported text, URI, and data content into
native A2A `Part` values. This one helper is usable for both completed and
streaming runs.
The package does not provide an A2A `AgentExecutor`, application, route,
request handler, task store, event queue, `TaskUpdater`, task-state policy,
artifact-id policy, or session-key policy. Application code composes the two
helpers with those native A2A SDK constructs and may use any server framework
supported by the SDK.
## `agent-framework-hosting-mcp`
The MCP package provides only the conversion seam between native MCP SDK values
and Agent Framework:
- `MCPAgentTool(target, ...)`
- `MCPWorkflowTool(target, ...)`
- `mcp_to_run(arguments, *, argument_name="task", chat_option_arguments=()) -> AgentRunArgs`
- `mcp_from_run(result) -> list[mcp.types.ContentBlock]`
`MCPAgentTool` represents one Agent Framework agent as one native MCP tool. It
derives the default tool name and description from the agent, accepts
overrides for those values and the main text parameter, includes app-owned
additional parameter schemas, and explicitly maps selected parameter schemas
to ChatOptions. Its asynchronous `list_tools()` returns the native `Tool` list,
and `call_tool(...)` performs conversion, agent execution, and final result
conversion.
The adapter accepts either an agent or an existing `AgentState`. With a
configured `session_id_parameter`, it loads and stores the corresponding
`AgentSession`. The application remains responsible for deriving and
authorizing the session id and preventing concurrent updates to the same
session.
`MCPWorkflowTool` represents one Agent Framework workflow as one native MCP
tool. It derives the tool name and description from the workflow and derives
the input schema from the start executor's single declared input type.
Object-shaped dataclass and Pydantic inputs become top-level MCP arguments;
primitive inputs are wrapped in one configurable argument. The adapter
validates the arguments against that type, runs the workflow, and converts
terminal outputs to MCP content blocks.
Workflow instances preserve state and reject concurrent runs. Applications
that need independent calls should provide a `WorkflowState` factory with
`cache_target=False`. Checkpoint restoration, human-in-the-loop responses, and
continuation identifiers remain application-owned contracts. If a workflow
stops to request external input, the adapter raises rather than returning an
empty successful tool result.
`mcp_to_run(...)` accepts the argument mapping from a native MCP `call_tool`
handler. The application owns the tool schema and may select which required
string argument contains the user request. The application should define that
argument name once and use the same value in the native tool schema and the
`argument_name` parameter so those two sides of the contract remain aligned.
Applications may also expose selected ChatOptions fields in their native tool
schema and pass those names through `chat_option_arguments`. Only explicitly
selected names are copied to run options; the helper does not forward all MCP
arguments or own their JSON Schema validation.
MCP `tools/call` arguments are JSON-only and do not have a native multimodal
content-block union. The package does not impose a non-standard JSON
representation for multimodal tool arguments.
`mcp_from_run(...)` accepts an `AgentResponse` or `Message`. It converts text,
URI, image data, audio data, and other binary data into native MCP content
blocks.
Its output is specifically the content union accepted by `CallToolResult`.
Sampling-only values such as `ToolUseContent` belong to the separate MCP
sampling response path and are not emitted by this hosting helper.
MCP `tools/call` returns one final `CallToolResult`. Streamable HTTP can carry
multiple MCP messages and progress notifications can report operation status,
but the protocol does not define partial tool-result content chunks.
Experimental MCP tasks defer retrieval of the same final result. Therefore the
conversion helpers do not expose Agent Framework streaming updates.
The package does not provide an MCP `Server`, handler registration, transport, route,
session policy, authentication, authorization, or deployment wrapper.
Application code composes the adapters and conversion helpers with native MCP SDK constructs and
may use stdio, streamable HTTP, or another transport supported by the SDK.
## `agent-framework-hosting-telegram`
The Telegram package provides side-effect-free helpers around Telegram Bot API
update and method payloads. It does not provide a Bot API client, polling loop,
webhook route, command registry, retry policy, or rate limiter.
### Update helpers
- `telegram_to_run(update, *, resolve_file_url=None, stream=False) -> AgentRunArgs`
- `telegram_chat_id(update) -> int | None`
- `telegram_session_id(update, *, bot_id) -> str | None`
- `telegram_command(update) -> str | None`
- `telegram_callback_query_id(update) -> str | None`
- `telegram_media_file_id(update_or_message) -> tuple[str, str] | None`
`telegram_to_run(...)` handles `message`, `edited_message`, and
`callback_query` updates. Text and captions become AF text content. When the
app supplies an async `resolve_file_url` callback, supported Telegram media
file ids can become AF URI content. The package does not call Telegram's
`getFile` method itself.
`telegram_session_id(..., bot_id=...)` includes the bot identity in every key.
Private chats return `telegram:<bot_id>:<user_id>`; other chats return
`telegram:<bot_id>:<chat_id>`, giving groups a shared session by default. This
matches Telegram's native isolation boundaries while preventing two bots from
sharing state accidentally. Apps that want per-user sessions inside a group
can construct a key that includes both chat and sender ids. The app must
authorize those Telegram identities before loading session state.
`telegram_command(...)` parses Telegram's `/name` and `/name@bot` syntax. It
does not register commands or invoke handlers.
### Response helpers
- `telegram_from_run(result, *, chat_id, parse_mode=None)`
- `telegram_from_streaming_run(stream, *, chat_id, message_id, initial_text=None, parse_mode=None)`
The helpers produce Telegram method/payload values for app-owned Bot API
calls. Final rendering supports text and image URI output and applies
Telegram's text-length boundary. Streaming rendering produces cumulative
`editMessageText` payloads for a placeholder message id supplied by the app,
omitting edits that match an optional `initial_text`, then renders the final
rich output. Image-only responses remove the placeholder with `deleteMessage`
before sending the image. The app owns the initial placeholder send, Bot API
calls, edit throttling, retries, and failure policy.
## Security responsibilities
Protocol helper packages parse and render. They do not authenticate callers, authorize access to state, or decide which
@@ -346,3 +493,6 @@ Implementation validation must cover:
- Responses streaming SSE rendering;
- HTTP round-trip tests showing a native FastAPI route using `AgentState` and Responses helpers;
- sample type checking for the local Responses sample.
- Telegram update parsing, chat/session/command/media extraction, final
rendering, and streaming edit rendering;
- sample type checking for the local Telegram polling and webhook entry points.
@@ -0,0 +1,246 @@
---
status: accepted
contact: rogerbarreto
date: 2026-07-08
deciders: rogerbarreto
consulted: eavanvalkenburg
informed: []
---
# .NET hosting: OpenAI Responses protocol helpers and optional execution state
Implements [ADR-0032](../decisions/0032-dotnet-hosting-protocol-helpers.md), which realizes the
helper-first direction of [ADR-0027](../decisions/0027-hosting-channels.md) for .NET.
## What is the goal of this feature?
Let application developers expose an `AIAgent` or workflow over the OpenAI Responses protocol **while
owning their own ASP.NET Core route, authentication, middleware, and storage**, by calling small,
side-effect-free Agent Framework conversion helpers instead of adopting the batteries-included,
route-owning `MapOpenAIResponses` server.
Success: an application can implement a working `POST /responses` endpoint (sync + streaming) in its
own minimal-API handler using only the public helpers plus its own auth/storage, with no dependency on
`MapOpenAIResponses` or `IResponsesService`.
## What is the problem being solved?
.NET already exposes agents as the OpenAI Responses API, but only through the route-owning
`MapOpenAIResponses`/`IResponsesService`, which also owns routing, response/conversation storage,
streaming, and lifecycle. An application that wants its own routing (custom auth, middleware, status
codes, durable storage, or a different framework surface) currently has no supported way to reuse the
framework's Responses<->agent conversion. Every conversion primitive that would make this possible
already exists in `Microsoft.Agents.AI.Hosting.OpenAI` but is `internal`.
This feature un-bundles that conversion into a public, app-callable surface, and adds the minimal
execution-state helpers an app needs for session continuity and workflow checkpoint resume.
## API Changes
### `Microsoft.Agents.AI.Hosting.OpenAI` (new public static facade `OpenAIResponses`)
Boundary is `System.Text.Json`; the wire DTOs stay internal. All members are side-effect-free.
```csharp
namespace Microsoft.Agents.AI.Hosting.OpenAI;
public static class OpenAIResponses
{
// Wire -> Agent Framework run input.
public static OpenAIResponsesRunRequest ToAgentRunRequest(
JsonElement body,
OpenAIResponsesMapOptions? mapOptions = null);
// Agent Framework result -> Responses payload (no originating request required).
public static JsonElement WriteResponse(
AgentResponse response,
string responseId,
string? sessionId = null);
// Agent Framework stream -> Responses SSE `data:` frames.
public static IAsyncEnumerable<string> WriteResponseStreamAsync(
IAsyncEnumerable<AgentResponseUpdate> updates,
string responseId,
string? sessionId = null,
CancellationToken cancellationToken = default);
// Untrusted candidate continuation key: previous_response_id or conversation id (or null).
// Kept SEPARATE from ToAgentRunRequest so using a request-derived key is an explicit decision.
public static string? GetSessionId(JsonElement body);
// Mint a `resp_*` id.
public static string CreateResponseId();
}
// Result of ToAgentRunRequest.
public sealed class OpenAIResponsesRunRequest
{
public IList<ChatMessage> Messages { get; }
public AgentRunOptions? Options { get; }
}
```
`ToAgentRunRequest` honors `OpenAIResponsesMapOptions.RunOptionsFactory` exactly as the route model
does (by default no request setting is mapped onto the run; unsupported settings surface as a
`NotSupportedException`). `WriteResponse`/`WriteResponseStreamAsync` reuse the existing internal
`AgentResponseExtensions.ToResponse` / `AgentResponseUpdateExtensions.ToStreamingResponseAsync`
converters (an internal `ToResponse` overload with an optional originating request is added so the
facade can render without one). The streaming renderer's existing workflow-event support is preserved.
### `Microsoft.Agents.AI.Hosting` (execution state, protocol-neutral)
```csharp
namespace Microsoft.Agents.AI.Hosting;
public abstract class AgentSessionStore
{
// ... existing members ...
// New: the one missing store operation. Virtual (not abstract) with a default that throws
// NotSupportedException, so existing external stores (e.g. the Foundry hosting stores) keep
// compiling; the in-box Hosting stores override it. In-box overrides treat deleting a missing
// session as a no-op.
public virtual ValueTask DeleteSessionAsync(
AIAgent agent, string conversationId, CancellationToken cancellationToken = default);
}
// Thin holder: pairs a workflow target with checkpointing + a per-session head cursor.
public sealed class HostedWorkflowState
{
// Shared-instance mode: one instance cannot be run by two runners at once, so turns run one at a time.
public HostedWorkflowState(Workflow workflow, CheckpointManager? checkpointManager = null);
// Factory mode: by default a fresh instance is built per run, so independent sessions run in parallel.
// With cacheWorkflow: true the factory is invoked once lazily and the built instance is cached and reused.
public HostedWorkflowState(Func<CancellationToken, ValueTask<Workflow>> workflowFactory, CheckpointManager? checkpointManager = null, bool cacheWorkflow = false);
// First turn runs forward from the start; subsequent turns restore the session's latest
// checkpoint and run forward with the new turn's input, then record the new head checkpoint.
public ValueTask<HostedWorkflowRunResult> RunOrResumeAsync(
string sessionId, object input, CancellationToken ct = default);
}
```
For agents, the application uses `AgentSessionStore` directly: `GetSessionAsync(agent, id)` creates a
session on miss and returns an independent instance per call (so concurrent calls can fork the same
stored state — for example branching from a `previous_response_id` or managing several `conversation`
ids side by side — without one branch observing another's in-flight mutations). The store performs no
cross-call locking; an application that needs concurrent runs against the same id to be serialized owns
that coordination. `SaveSessionAsync(agent, id, session)` persists post-run, including under a newly
minted `resp_*` id when the protocol mints a new continuation id. `DeleteSessionAsync` uses the new
store method. No agent-side holder is needed: create-on-miss already lives in the store, so a
pass-through wrapper would only bind the `agent` argument.
`HostedWorkflowState` defaults to `CheckpointManager.CreateInMemory()` and an in-memory
`sessionId -> CheckpointInfo` cursor. Because the checkpoint store is already `sessionId`-keyed but
`CheckpointInfo` carries no ordering, the holder remembers the head checkpoint per session so
`RunOrResumeAsync` can resume the correct one. On subsequent turns it restores that checkpoint to
rehydrate accumulated workflow state and then runs the workflow forward with the new turn's input,
rather than continuing a halted run with no input (which would wait for input
indefinitely). For agent (chat-protocol) workflows the new input is accompanied by a `TurnToken` so the
turn is driven. When the in-memory cursor misses (a new holder or a process restart), the holder falls
back to `CheckpointManager.GetLatestCheckpointAsync(sessionId)`, so a durable `CheckpointManager` resumes
correctly across restarts (the default in-memory manager does not persist, so a restart starts fresh). A
resume that produces no events is logged as a warning (possible stale checkpoint or mismatched input).
Concurrency depends on how the holder is constructed. With a single shared workflow instance, concurrent runs
are not supported, because a workflow instance cannot be run by two runners at once; process turns one at a
time. With a workflow factory
(`Func<CancellationToken, ValueTask<Workflow>>`) it builds a fresh instance per run by default, so independent
sessions run in parallel; a resume rehydrates a fresh instance
from the session's checkpoint in the shared store, and concurrent turns against the same session id remain the
application's coordination responsibility. Passing `cacheWorkflow: true` instead builds the workflow once,
lazily on first use, and reuses it (a deferred, cached target that — like the instance — cannot run concurrent
turns). A
streaming counterpart, `RunOrResumeStreamingAsync`, yields the turn's `WorkflowEvent`s as they occur (for
example to render agent updates over the Responses SSE wire) and records the head checkpoint once the
stream is fully enumerated, keeping the blocking and streaming workflow paths in lockstep.
Because `RunOrResumeAsync`/`RunOrResumeStreamingAsync` are generic over the input type, the application
adapts the Responses input into the workflow's start-executor input type at the call site (for example
parsing a structured payload into a typed record), without coupling the holder to a specific wire type.
## Non-goals for v1
- ChatCompletions / Conversations helper surfaces (the facade is named so `OpenAIChatCompletions` can
follow).
- Changing `MapOpenAIResponses` public behavior.
- A new package or an OpenAI-SDK-typed reimplementation.
- Durable/pluggable workflow checkpoint-cursor storage (in-memory default only for v1).
## Security responsibilities (application-owned)
- Authenticate the caller before using any `GetSessionId(...)` result.
- Authorize and bind the candidate id to the authenticated principal/tenant before using it as an
`AgentSessionStore` key or a workflow checkpoint session id.
- For multi-user hosts, wrap the store with `IsolationKeyScopedAgentSessionStore` (for example via
`UseClaimsBasedSessionIsolation(...)`), so the session namespace is scoped per principal.
- Persist session/checkpoint state only after the run or stream has completed.
## E2E Code Samples
### Agent over Responses, app-owned route (non-streaming + SSE)
```csharp
var agent = /* an AIAgent */;
AgentSessionStore sessionStore = new InMemoryAgentSessionStore(); // in-memory session store
app.MapPost("/responses", async (HttpContext http, CancellationToken ct) =>
{
using var doc = await JsonDocument.ParseAsync(http.Request.Body, cancellationToken: ct);
JsonElement body = doc.RootElement;
// App owns auth + id trust decisions.
string? candidate = OpenAIResponses.GetSessionId(body);
string sessionId = Authorize(http.User, candidate) ?? OpenAIResponses.CreateResponseId();
var run = OpenAIResponses.ToAgentRunRequest(body);
var session = await sessionStore.GetSessionAsync(agent, sessionId, ct);
string responseId = OpenAIResponses.CreateResponseId();
if (body.TryGetProperty("stream", out var s) && s.GetBoolean())
{
http.Response.ContentType = "text/event-stream";
var updates = agent.RunStreamingAsync(run.Messages, session, run.Options, ct);
await foreach (var frame in OpenAIResponses.WriteResponseStreamAsync(updates, responseId, sessionId, ct))
{
await http.Response.WriteAsync(frame, ct);
await http.Response.Body.FlushAsync(ct);
}
await sessionStore.SaveSessionAsync(agent, responseId, session, ct);
return Results.Empty;
}
var result = await agent.RunAsync(run.Messages, session, run.Options, ct);
await sessionStore.SaveSessionAsync(agent, responseId, session, ct);
return Results.Json(OpenAIResponses.WriteResponse(result, responseId, sessionId));
});
```
### Workflow over Responses with checkpoint resume
Workflow checkpoint resume requires a **stable** session key across turns. `previous_response_id` changes
every turn, so it is not a valid checkpoint key; use the `conversation` id (constant for the conversation).
Because `GetSessionId(...)` prefers `previous_response_id`, a workflow route reads the conversation id
directly rather than calling `GetSessionId(...)`.
```csharp
var state = new HostedWorkflowState(workflow); // in-memory checkpoints + cursor
app.MapPost("/responses", async (HttpContext http, CancellationToken ct) =>
{
using var doc = await JsonDocument.ParseAsync(http.Request.Body, cancellationToken: ct);
JsonElement body = doc.RootElement;
// Stable, authorized checkpoint key. GetConversationId(...) reads the conversation id (string or object).
string sessionId = Authorize(http.User, GetConversationId(body))
?? OpenAIResponses.CreateResponseId();
var run = OpenAIResponses.ToAgentRunRequest(body);
// Runs forward on first call, resumes from the session's head checkpoint thereafter.
var result = await state.RunOrResumeAsync(sessionId, run.Messages, ct);
return Results.Json(OpenAIResponses.WriteResponse(result.AsAgentResponse(),
OpenAIResponses.CreateResponseId(), sessionId));
});
```
+3 -2
View File
@@ -11,8 +11,8 @@
</PropertyGroup>
<ItemGroup>
<!-- Aspire.* -->
<PackageVersion Include="Anthropic" Version="12.31.0" />
<PackageVersion Include="Anthropic.Foundry" Version="0.6.0" />
<PackageVersion Include="Anthropic" Version="12.35.1" />
<PackageVersion Include="Anthropic.Foundry" Version="0.7.1" />
<PackageVersion Include="Aspire.Hosting" Version="$(AspireAppHostSdkVersion)" />
<PackageVersion Include="Aspire.Azure.AI.OpenAI" Version="13.0.0-preview.1.25560.3" />
<PackageVersion Include="Aspire.Azure.AI.Inference" Version="13.1.0-preview.1.25616.3" />
@@ -122,6 +122,7 @@
<PackageVersion Include="Hyperlight.HyperlightSandbox.Api" Version="0.4.0" />
<PackageVersion Include="Hyperlight.HyperlightSandbox.Guest.Python" Version="0.4.0" />
<!-- Inference SDKs -->
<PackageVersion Include="Dapr.AI.Microsoft.Extensions" Version="1.18.4" />
<PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.10.0" />
<PackageVersion Include="Microsoft.ML.Tokenizers" Version="2.0.0" />
<PackageVersion Include="OllamaSharp" Version="5.4.8" />
+18 -2
View File
@@ -29,6 +29,7 @@
<Project Path="samples/02-agents/AgentProviders/azure/Agent_With_AzureOpenAIChatCompletion/Agent_With_AzureOpenAIChatCompletion.csproj" />
<Project Path="samples/02-agents/AgentProviders/azure/Agent_With_AzureOpenAIResponses/Agent_With_AzureOpenAIResponses.csproj" />
<Project Path="samples/02-agents/AgentProviders/custom/Agent_With_CustomImplementation/Agent_With_CustomImplementation.csproj" />
<Project Path="samples/02-agents/AgentProviders/dapr/Agent_With_Dapr/Agent_With_Dapr.csproj" />
<Project Path="samples/02-agents/AgentProviders/github-copilot/Agent_With_GitHubCopilot/Agent_With_GitHubCopilot.csproj" />
<Project Path="samples/02-agents/AgentProviders/google-gemini/Agent_With_GoogleGemini/Agent_With_GoogleGemini.csproj" />
<Project Path="samples/02-agents/AgentProviders/ollama/Agent_With_Ollama/Agent_With_Ollama.csproj" />
@@ -200,6 +201,7 @@
<Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step03_MemoryUsingValkey_Bedrock/AgentWithMemory_Step03_MemoryUsingValkey_Bedrock.csproj" />
<Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step04_MemoryUsingFoundry/AgentWithMemory_Step04_MemoryUsingFoundry.csproj" />
<Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step05_BoundedChatHistory/AgentWithMemory_Step05_BoundedChatHistory.csproj" />
<Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step06_MemoryUsingAgentMemory/AgentWithMemory_Step06_MemoryUsingAgentMemory.csproj" />
</Folder>
<Folder Name="/Samples/02-agents/AgentProviders/openai/">
<File Path="samples/02-agents/AgentProviders/openai/README.md" />
@@ -313,7 +315,19 @@
<Project Path="samples/03-workflows/Evaluation/Evaluation_WorkflowEval/Evaluation_WorkflowEval.csproj" />
<Project Path="samples/03-workflows/Evaluation/Evaluation_WorkflowExpectedOutputs/Evaluation_WorkflowExpectedOutputs.csproj" />
</Folder>
<Folder Name="/Samples/04-hosting/">
<Folder Name="/Samples/04-hosting/" />
<Folder Name="/Samples/04-hosting/af-hosting/">
<File Path="samples/04-hosting/af-hosting/README.md" />
</Folder>
<Folder Name="/Samples/04-hosting/af-hosting/local_responses/">
<File Path="samples/04-hosting/af-hosting/local_responses/README.md" />
<Project Path="samples/04-hosting/af-hosting/local_responses/Server/Server.csproj" />
<Project Path="samples/04-hosting/af-hosting/local_responses/Client/Client.csproj" />
</Folder>
<Folder Name="/Samples/04-hosting/af-hosting/local_responses_workflow/">
<File Path="samples/04-hosting/af-hosting/local_responses_workflow/README.md" />
<Project Path="samples/04-hosting/af-hosting/local_responses_workflow/Server/Server.csproj" />
<Project Path="samples/04-hosting/af-hosting/local_responses_workflow/Client/Client.csproj" />
</Folder>
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/" />
<Folder Name="/Samples/04-hosting/FoundryHostedAgents/invocations/" />
@@ -639,7 +653,9 @@
<Project Path="src/Microsoft.Agents.AI.Workflows/Microsoft.Agents.AI.Workflows.csproj" />
<Project Path="src/Microsoft.Agents.AI/Microsoft.Agents.AI.csproj" />
</Folder>
<Folder Name="/Tests/" />
<Folder Name="/Tests/">
<Project Path="tests/Microsoft.Agents.AI.Hosting.OpenAI.IntegrationTests/Microsoft.Agents.AI.Hosting.OpenAI.IntegrationTests.csproj" />
</Folder>
<Folder Name="/Tests/IntegrationTests/">
<Project Path="tests/AgentConformance.IntegrationTests/AgentConformance.IntegrationTests.csproj" />
<Project Path="tests/AnthropicChatCompletion.IntegrationTests/AnthropicChatCompletion.IntegrationTests.csproj" />
+1
View File
@@ -28,6 +28,7 @@
"src\\Microsoft.Agents.AI.OpenAI\\Microsoft.Agents.AI.OpenAI.csproj",
"src\\Microsoft.Agents.AI.Purview\\Microsoft.Agents.AI.Purview.csproj",
"src\\Microsoft.Agents.AI.Tools.Shell\\Microsoft.Agents.AI.Tools.Shell.csproj",
"src\\Microsoft.Agents.AI.Valkey\\Microsoft.Agents.AI.Valkey.csproj",
"src\\Microsoft.Agents.AI.Workflows.Declarative.Foundry\\Microsoft.Agents.AI.Workflows.Declarative.Foundry.csproj",
"src\\Microsoft.Agents.AI.Workflows.Declarative.Mcp\\Microsoft.Agents.AI.Workflows.Declarative.Mcp.csproj",
"src\\Microsoft.Agents.AI.Workflows.Declarative\\Microsoft.Agents.AI.Workflows.Declarative.csproj",
+10 -1
View File
@@ -427,6 +427,15 @@ internal static class AgentsSamples
],
},
new SampleDefinition
{
Name = "AgentWithMemory_Step06_MemoryUsingAgentMemory",
ProjectPath = "samples/02-agents/AgentWithMemory/AgentWithMemory_Step06_MemoryUsingAgentMemory",
RequiredEnvironmentVariables = ["AZURE_OPENAI_ENDPOINT"],
OptionalEnvironmentVariables = ["AZURE_OPENAI_API_KEY", "FOUNDRY_MODEL", "FOUNDRY_EMBEDDING_MODEL", "NEO4J_URI", "NEO4J_USER", "NEO4J_PASSWORD"],
SkipReason = "Requires a running Neo4j instance; standalone sample outside the repo's CPM build.",
},
// ── AgentWithRAG ────────────────────────────────────────────────────
new SampleDefinition
@@ -837,7 +846,7 @@ internal static class AgentsSamples
ProjectPath = "samples/02-agents/Agents/Agent_Step15_DeepResearch",
RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT", "AZURE_AI_MODEL_DEPLOYMENT_NAME", "AZURE_AI_BING_CONNECTION_ID"],
OptionalEnvironmentVariables = ["AZURE_AI_REASONING_DEPLOYMENT_NAME"],
SkipReason = "Requires Azure AI Foundry project with Bing search connection.",
SkipReason = "Requires Microsoft Foundry project with Bing search connection.",
},
new SampleDefinition
+1 -1
View File
@@ -19,7 +19,7 @@
// Pre-build the solution before running, or pass --build to avoid missing build output failures.
//
// Required environment variables (for AI-powered verification):
// FOUNDRY_PROJECT_ENDPOINT — Your Azure AI Foundry project endpoint
// FOUNDRY_PROJECT_ENDPOINT — Your Microsoft Foundry project endpoint
// FOUNDRY_MODEL — Model deployment name (optional, defaults to gpt-5.4-mini)
using System.Diagnostics;
+1 -1
View File
@@ -130,7 +130,7 @@ internal static class WorkflowSamples
ProjectPath = "samples/03-workflows/Agents/FoundryAgent",
RequiredEnvironmentVariables = ["FOUNDRY_PROJECT_ENDPOINT"],
OptionalEnvironmentVariables = ["FOUNDRY_MODEL"],
SkipReason = "Requires Azure AI Foundry project endpoint.",
SkipReason = "Requires Microsoft Foundry project endpoint.",
},
new SampleDefinition
+3 -3
View File
@@ -1,14 +1,14 @@
<Project>
<PropertyGroup>
<!-- Central version prefix - applies to all nuget packages. -->
<VersionPrefix>1.13.0</VersionPrefix>
<VersionPrefix>1.15.0</VersionPrefix>
<RCNumber>1</RCNumber>
<DateSuffix>260703</DateSuffix>
<DateSuffix>260722</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>1.13.0</GitTag>
<GitTag>1.15.0</GitTag>
<Configurations>Debug;Release;Publish</Configurations>
<IsPackable>true</IsPackable>
@@ -44,6 +44,12 @@ See the README.md for each sample for the prerequisites for that sample.
| --- | --- |
| [Custom Implementation](./custom/Agent_With_CustomImplementation/) | Create an AIAgent with a custom implementation |
### [Dapr](./dapr/)
| Sample | Description |
| --- | --- |
| [Agent with Dapr](./dapr/Agent_With_Dapr/) | Create an AIAgent using Dapr's Conversation building block as the inference backend |
### [Foundry](./foundry/)
See [foundry/README.md](./foundry/README.md) for the full list of Foundry agent samples,
@@ -0,0 +1,29 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
<CentralPackageTransitivePinningEnabled>false</CentralPackageTransitivePinningEnabled>
<NoWarn>$(NoWarn);DAPR_CONVERSATION</NoWarn>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Dapr.AI.Microsoft.Extensions" />
<!--
Dapr.AI.Microsoft.Extensions depends on Microsoft.Extensions.* 10.0.8, which is higher than the
versions pinned centrally in Directory.Packages.props. Central transitive pinning is disabled above
for this sample and these two direct references are overridden to that minimum. Remove the overrides
(and the CentralPackageTransitivePinningEnabled setting) once the central versions are >= 10.0.8.
-->
<PackageReference Include="Microsoft.Extensions.DependencyInjection" VersionOverride="10.0.8" />
<PackageReference Include="Microsoft.Extensions.Hosting" VersionOverride="10.0.8" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
</ItemGroup>
</Project>
@@ -0,0 +1,11 @@
apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
name: ollama
spec:
type: conversation.ollama
metadata:
- name: model
value: llama3.2
- name: cacheTTL
value: 10m
@@ -0,0 +1,36 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to create and use a simple AI agent with Dapr as the backend.
// Dapr's Conversation building block is used here to route inference to Ollama.
using Dapr.AI.Conversation.Extensions;
using Dapr.AI.Microsoft.Extensions;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Hosting;
// The Dapr sidecar's gRPC endpoint. This must match the --dapr-grpc-port used when starting
// the sidecar (see this sample's README). Override it with the DAPR_GRPC_ENDPOINT environment
// variable if you run the sidecar on a different port.
var daprGrpcEndpoint = Environment.GetEnvironmentVariable("DAPR_GRPC_ENDPOINT") ?? "http://localhost:3501";
// Register the Dapr Conversation client with dependency injection.
var app = Host.CreateDefaultBuilder()
.ConfigureServices(services =>
{
// Configure the gRPC endpoint for the Dapr sidecar.
services.AddDaprConversationClient((_, builder) => builder.UseGrpcEndpoint(daprGrpcEndpoint));
// Provide the name of the Conversation component loaded in the sidecar to use.
services.AddDaprChatClient(opt => opt.ConversationComponentName = "ollama");
}).Build();
// Get an instance of the Dapr chat client from the dependency injection container.
using var scope = app.Services.CreateScope();
var daprChatClient = scope.ServiceProvider.GetRequiredService<IChatClient>();
// Use this chat client to construct an AIAgent.
AIAgent agent = daprChatClient.AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
// Invoke the agent and output the text result.
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
@@ -0,0 +1,37 @@
# Prerequisites
Before you begin, ensure you have the following prerequisites:
- .NET 10 SDK or later
- Docker installed and running on your machine
- Ollama installed
- Dapr CLI installed ([instructions](https://docs.dapr.io/getting-started/install-dapr-cli/))
You'll need to download a model from [Ollama's library](https://ollama.com/library) to get started. Open
a terminal and run the following, replacing `<model_name>` with the name of the model you want to use from
Ollama's library (e.g., `llama3.2`).
```powershell
ollama run <model_name>
```
Once it has downloaded and started running, update the component bundled with this example
in `./Components/conversation-ollama.yaml` to reflect the name of the model you just installed, modifying the value of
the `model` metadata property, then save your changes and close the file.
Next, start your Dapr sidecar and tell it where it can look for your components. If launching from this project's directory,
run the following; otherwise, replace `./Components` with the path to your components directory.
```powershell
dapr run --app-id agents --resources-path ./Components --dapr-grpc-port 3501
```
The sample connects to the sidecar at `http://localhost:3501` by default. If you start the sidecar on a
different gRPC port, set the `DAPR_GRPC_ENDPOINT` environment variable to match before running the sample.
Because the Dapr sidecar needs to continue running while your application is running, please open another terminal
window and run the following command from this project's directory to start the demo.
```powershell
dotnet run
```
@@ -66,6 +66,18 @@ When using multiple providers (e.g., skills + file access), combine their rules
})
```
## ⚠️ Security: avoid tool-name collisions
Built-in auto-approval rules match tool calls **solely by tool name**. A rule cannot tell the
provider's own tool apart from any other registered tool that happens to share the same name. If a
different tool — especially one with a caller-configurable name, such as the Harness shell tool
(`HarnessAgentOptions.ShellToolName`) — is registered under a name that one of these rules approves
(e.g. `load_skill`, `read_skill_resource`, `run_skill_script`, or the `file_access_*` names), that
tool will be **silently auto-approved**, bypassing the human approval boundary.
When using auto-approval rules, ensure no other tool's name collides with the reserved names the
rules approve, and never assign a configurable tool name that matches one of them.
## Skills Included
### unit-converter
@@ -0,0 +1,78 @@
<Project Sdk="Microsoft.NET.Sdk">
<!--
This project is part of the repo's solution and targets .NET 10 like the rest of the repo, but it
intentionally opts out of Central Package Management and source-referencing Microsoft.Agents.AI:
it consumes the *published* AgentMemory NuGet packages (which target Microsoft.Agents.AI 1.9.0)
instead. Run it with `dotnet run` from this folder.
ManagePackageVersionsCentrally is off, but dotnet/Directory.Packages.props still unconditionally
merges its repo-wide analyzer PackageReference items (no Version, resolved via CPM) into every
project that imports it — including this one. With CPM off here those versions can't resolve
(NU1015), so each is removed and re-added with an explicit version below (matching
AgentWithRAG_Step05_Neo4jGraphRAG, which hits the same issue). xunit.analyzers/Moq.Analyzers are
dropped rather than re-added since this project has no test code.
-->
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFrameworks>net10.0</TargetFrameworks>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
<RootNamespace>AgentMemoryShoppingAssistant</RootNamespace>
<!-- OPENAI001: the OpenAIClient(AuthenticationPolicy, options) ctor used for keyless Azure auth is
marked experimental in the OpenAI SDK (the MAF Foundry samples use the same pattern). -->
<NoWarn>$(NoWarn);OPENAI001</NoWarn>
</PropertyGroup>
<ItemGroup>
<PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
<PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
<PackageReference Remove="xunit.analyzers" />
<PackageReference Remove="Moq.Analyzers" />
<PackageReference Remove="Roslynator.Analyzers" />
<PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
<PackageReference Remove="Roslynator.Formatting.Analyzers" />
</ItemGroup>
<ItemGroup>
<!-- AgentMemory (published) — an unofficial .NET port of the Neo4j Labs agent-memory library + its
Microsoft Agent Framework adapter. -->
<PackageReference Include="AgentMemory" Version="1.2.0" />
<PackageReference Include="AgentMemory.AgentFramework" Version="1.2.0" />
<!-- Microsoft Agent Framework (matches AgentMemory's target) + the OpenAI/Foundry chat & embedding clients. -->
<PackageReference Include="Microsoft.Agents.AI" Version="1.9.0" />
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="10.5.1" />
<PackageReference Include="Azure.Identity" Version="1.21.0" />
<PackageReference Include="Microsoft.Extensions.Hosting" Version="9.0.17" />
<!-- Transitive dependency of Microsoft.Agents.AI; pinned explicitly (CPM is off here) because the
version it would otherwise resolve to, 1.12.0, has a known moderate severity vulnerability
(GHSA-g94r-2vxg-569j) that fails the repo's NuGet audit (NU1902 as error). Matches the version
pinned in dotnet/Directory.Packages.props. -->
<PackageReference Include="OpenTelemetry.Api" Version="1.15.3" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageReference Include="Roslynator.Analyzers" Version="4.14.1">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.14.1">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
</ItemGroup>
</Project>
@@ -0,0 +1,195 @@
// Copyright (c) Microsoft. All rights reserved.
using System.ComponentModel;
using System.Text;
using AgentMemory.Neo4j.Infrastructure;
using Microsoft.Extensions.AI;
using Neo4j.Driver;
namespace AgentMemoryShoppingAssistant;
/// <summary>
/// A small retail product graph plus the shopping tools that query it — the .NET counterpart of the
/// Python retail-assistant's <c>get_product_tools</c>. Products live in Neo4j as <c>:Product</c> nodes
/// linked to <c>:ProductCategory</c> / <c>:ProductBrand</c> nodes, so recommendations and "related
/// products" come from graph traversals. Cypher runs through the public <see cref="INeo4jTransactionRunner"/>
/// seam. Exposed as <see cref="AIFunction"/>s so a real chat model can call them during a run — the same
/// way <c>Neo4jMemoryContextProvider</c> surfaces the memory tools through <c>AIContext.Tools</c> when
/// <c>ExposeMemoryToolsFromContextProvider</c> is enabled.
/// </summary>
public sealed class ProductCatalog(INeo4jTransactionRunner runner)
{
private readonly INeo4jTransactionRunner _runner = runner;
private static readonly (string Name, string Category, string Brand, double Price, bool InStock, int Inventory, string Description, int Popularity)[] s_seed =
[
("Nike Air Zoom Pegasus 40", "shoes", "Nike", 130, true, 40, "Everyday running shoe with responsive cushioning.", 95),
("Nike Revolution 7", "shoes", "Nike", 70, true, 60, "Lightweight, budget-friendly running shoe.", 80),
("Adidas Ultraboost Light", "shoes", "Adidas", 190, true, 25, "Premium running shoe with Boost cushioning.", 90),
("Asics Gel-Kayano 31", "shoes", "Asics", 165, false, 0, "Stability running shoe for overpronation.", 70),
("Sony WH-1000XM5", "electronics", "Sony", 350, true, 18, "Industry-leading noise-cancelling headphones.", 92),
("Bose QuietComfort Ultra", "electronics", "Bose", 330, true, 12, "Premium noise-cancelling over-ear headphones.", 85),
("Apple AirPods Pro 2", "electronics", "Apple", 250, true, 50, "Wireless earbuds with active noise cancellation.", 88),
("Garmin Forerunner 265", "electronics", "Garmin", 450, true, 9, "GPS running watch with training metrics.", 78),
("Nike Dri-FIT Running Tee", "apparel", "Nike", 35, true, 120, "Breathable, moisture-wicking running shirt.", 65),
("Adidas Own the Run Jacket","apparel", "Adidas", 80, true, 33, "Lightweight, water-repellent running jacket.", 60),
];
/// <summary>Seeds the sample product graph (idempotent — safe to run every start).</summary>
public Task SeedAsync(CancellationToken ct = default) => this._runner.WriteAsync(async r =>
{
await r.RunAsync(
"""
UNWIND $products AS row
MERGE (p:Product {name: row.name})
SET p.category = row.category, p.brand = row.brand, p.price = row.price,
p.in_stock = row.in_stock, p.inventory = row.inventory,
p.description = row.description, p.popularity = row.popularity
MERGE (c:ProductCategory {name: row.category})
MERGE (b:ProductBrand {name: row.brand})
MERGE (p)-[:IN_CATEGORY]->(c)
MERGE (p)-[:MADE_BY]->(b)
""",
new
{
products = s_seed.Select(p => (object)new Dictionary<string, object>
{
["name"] = p.Name, ["category"] = p.Category, ["brand"] = p.Brand, ["price"] = p.Price,
["in_stock"] = p.InStock, ["inventory"] = p.Inventory, ["description"] = p.Description,
["popularity"] = p.Popularity,
}).ToList(),
});
}, ct);
// ── Tools (also usable directly in the scripted demo) ────────────────────────────────────────
[Description("Search the product catalog for items matching a query, with optional category, brand, and max-price filters.")]
public Task<string> SearchProductsAsync(
[Description("What the customer is looking for, e.g. 'running shoes'.")] string query,
[Description("Optional category filter: shoes, electronics, apparel.")] string? category = null,
[Description("Optional brand filter, e.g. 'Nike'.")] string? brand = null,
[Description("Optional maximum price.")] double? maxPrice = null,
CancellationToken ct = default) => this._runner.ReadAsync(async r =>
{
const string Cypher =
"""
MATCH (p:Product)
WHERE ANY(w IN split(toLower($query), ' ') WHERE
toLower(p.name) CONTAINS w OR toLower(p.description) CONTAINS w OR toLower(p.category) CONTAINS w)
AND ($category IS NULL OR p.category = $category)
AND ($brand IS NULL OR p.brand = $brand)
AND ($maxPrice IS NULL OR p.price <= $maxPrice)
RETURN p.name AS name, p.brand AS brand, p.category AS category,
p.price AS price, p.in_stock AS inStock
ORDER BY p.popularity DESC
LIMIT 10
""";
var cursor = await r.RunAsync(Cypher, new { query, category, brand, maxPrice });
return Render("Matches", await cursor.ToListAsync());
}, ct);
[Description("Get personalized product recommendations, optionally biased toward a preferred brand and/or category.")]
public Task<string> GetRecommendationsAsync(
[Description("The customer's preferred brand (from their saved preferences), if known.")] string? preferredBrand = null,
[Description("Optional category to recommend within.")] string? category = null,
[Description("How many recommendations to return.")] int limit = 5,
CancellationToken ct = default) => this._runner.ReadAsync(async r =>
{
const string Cypher =
"""
MATCH (p:Product)
WHERE p.in_stock = true
AND ($category IS NULL OR p.category = $category)
WITH p, (CASE WHEN $preferredBrand IS NOT NULL AND p.brand = $preferredBrand THEN 1 ELSE 0 END) AS onBrand
RETURN p.name AS name, p.brand AS brand, p.category AS category, p.price AS price, p.in_stock AS inStock
ORDER BY onBrand DESC, p.popularity DESC
LIMIT $limit
""";
var cursor = await r.RunAsync(Cypher, new { preferredBrand, category, limit });
var header = preferredBrand is null ? "Recommended for you" : $"Recommended for you (favoring {preferredBrand})";
return Render(header, await cursor.ToListAsync());
}, ct);
[Description("Find products related to a given product — same category or same brand — via graph traversal.")]
public Task<string> GetRelatedProductsAsync(
[Description("The exact product name to find related items for.")] string productName,
CancellationToken ct = default) => this._runner.ReadAsync(async r =>
{
const string Cypher =
"""
MATCH (p:Product {name: $productName})
CALL (p) {
MATCH (p)-[:IN_CATEGORY]->(c)<-[:IN_CATEGORY]-(rel:Product) WHERE rel <> p
RETURN rel, 'same category' AS reason
UNION
MATCH (p)-[:MADE_BY]->(b)<-[:MADE_BY]-(rel:Product) WHERE rel <> p
RETURN rel, 'same brand' AS reason
}
WITH rel, collect(DISTINCT reason) AS reasons
RETURN rel.name AS name, rel.brand AS brand, rel.category AS category,
rel.price AS price, rel.in_stock AS inStock, rel.popularity AS popularity,
reduce(s = '', x IN reasons | CASE WHEN s = '' THEN x ELSE s + ', ' + x END) AS reason
ORDER BY popularity DESC
LIMIT 5
""";
var cursor = await r.RunAsync(Cypher, new { productName });
return Render($"Related to {productName}", await cursor.ToListAsync());
}, ct);
[Description("Check whether a product is in stock and how many units are available.")]
public Task<string> CheckInventoryAsync(
[Description("The exact product name to check.")] string productName,
CancellationToken ct = default) => this._runner.ReadAsync(async r =>
{
var cursor = await r.RunAsync(
"MATCH (p:Product {name: $productName}) RETURN p.name AS name, p.in_stock AS inStock, p.inventory AS inventory",
new { productName });
var rows = await cursor.ToListAsync();
if (rows.Count == 0)
{
return $"'{productName}' was not found in the catalog.";
}
var rec = rows[0];
var inStock = rec["inStock"].As<bool>();
return inStock
? $"{rec["name"].As<string>()}: In stock ({rec["inventory"].As<long>()} available)."
: $"{rec["name"].As<string>()}: Out of stock.";
}, ct);
/// <summary>The retail tools as MAF/MEAI <see cref="AIFunction"/>s (attach to the agent's ChatOptions.Tools).</summary>
public IReadOnlyList<AIFunction> CreateAIFunctions() =>
[
AIFunctionFactory.Create(this.SearchProductsAsync, "search_products",
"Search the product catalog with optional category/brand/price filters."),
AIFunctionFactory.Create(this.GetRecommendationsAsync, "get_recommendations",
"Get personalized recommendations, optionally favoring a preferred brand/category."),
AIFunctionFactory.Create(this.GetRelatedProductsAsync, "get_related_products",
"Find products related to a given product via the graph."),
AIFunctionFactory.Create(this.CheckInventoryAsync, "check_inventory",
"Check stock/availability for a product."),
];
private static string Render(string header, List<IRecord> rows)
{
if (rows.Count == 0)
{
return $"{header}: (no matches)";
}
var sb = new StringBuilder().Append(header).Append(':').AppendLine();
foreach (var rec in rows)
{
var stock = rec["inStock"].As<bool>() ? "in stock" : "out of stock";
var reason = rec.Keys.Contains("reason") ? $" [{rec["reason"].As<string>()}]" : string.Empty;
sb.Append(" • ")
.Append(rec["name"].As<string>())
.Append(" — ").Append(rec["brand"].As<string>())
.Append(", ").Append(rec["category"].As<string>())
.Append(", $").Append(rec["price"].As<double>().ToString("0"))
.Append(", ").Append(stock).Append(reason)
.AppendLine();
}
return sb.ToString().TrimEnd();
}
}
@@ -0,0 +1,156 @@
// Copyright (c) Microsoft. All rights reserved.
// Agent Memory — Shopping Assistant (Microsoft Agent Framework, .NET)
//
// A .NET port of the Neo4j Labs "agent-memory" retail-assistant example
// (https://github.com/neo4j-labs/agent-memory/tree/main/examples/microsoft_agent_retail_assistant,
// referenced from https://learn.microsoft.com/en-us/agent-framework/integrations/neo4j-memory).
//
// A shopping assistant that LEARNS a customer's preferences and RECOMMENDS products via graph
// traversal, backed by DURABLE memory in Neo4j. It uses the AgentMemory library — a .NET port of the
// Python memory provider, not an officially recognized Neo4j integration — and its Microsoft Agent
// Framework adapter:
// • Neo4jMemoryContextProvider (an AIContextProvider) — recalls memory before each run, persists
// after, and (via ExposeMemoryToolsFromContextProvider) surfaces the memory tools (search/remember/
// recall) itself through AIContext.Tools
// • ProductCatalog.CreateAIFunctions() — retail tools over a Neo4j :Product graph
//
// Configuration (environment variables, matching the other Foundry samples):
// AZURE_OPENAI_ENDPOINT (required) — your Azure OpenAI / Foundry endpoint
// AZURE_OPENAI_API_KEY (optional) — API key; if unset, DefaultAzureCredential (az login) is used
// FOUNDRY_MODEL (default: gpt-4o-mini) — chat model deployment
// FOUNDRY_EMBEDDING_MODEL (default: text-embedding-3-small) — embedding model deployment (1536 dims)
// NEO4J_URI (default: bolt://localhost:7687)
// NEO4J_USER (default: neo4j)
// NEO4J_PASSWORD (default: password)
using System.ClientModel;
using System.ClientModel.Primitives;
using AgentMemory.Abstractions.Services;
using AgentMemory.AgentFramework;
using AgentMemory.Core;
using AgentMemory.Core.Stubs;
using AgentMemory.Neo4j.Infrastructure;
using AgentMemoryShoppingAssistant;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.DependencyInjection.Extensions;
using Microsoft.Extensions.Hosting;
using Microsoft.Extensions.Logging;
using OpenAI;
// ── Model + credentials (Azure OpenAI / Foundry, via env vars) ───────────────────────────────────
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var apiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_API_KEY");
var chatModel = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-4o-mini";
var embeddingModel = Environment.GetEnvironmentVariable("FOUNDRY_EMBEDDING_MODEL") ?? "text-embedding-3-small";
var clientOptions = new OpenAIClientOptions { Endpoint = new Uri(endpoint) };
// API key if provided, otherwise Azure credential (dev: `az login`).
// 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.
OpenAIClient openAI = string.IsNullOrWhiteSpace(apiKey)
? new OpenAIClient(new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"), clientOptions)
: new OpenAIClient(new ApiKeyCredential(apiKey), clientOptions);
IChatClient chatClient = openAI.GetChatClient(chatModel).AsIChatClient();
IEmbeddingGenerator<string, Embedding<float>> embeddingGenerator =
openAI.GetEmbeddingClient(embeddingModel).AsIEmbeddingGenerator();
// ── AgentMemory (Neo4j) DI ───────────────────────────────────────────────────────────────────────
var builder = Host.CreateApplicationBuilder(args);
builder.Logging.SetMinimumLevel(LogLevel.Warning);
builder.Services.AddNeo4jAgentMemory(options =>
{
options.Uri = Environment.GetEnvironmentVariable("NEO4J_URI") ?? "bolt://localhost:7687";
options.Username = Environment.GetEnvironmentVariable("NEO4J_USER") ?? "neo4j";
options.Password = Environment.GetEnvironmentVariable("NEO4J_PASSWORD") ?? "password";
});
builder.Services.AddAgentMemoryCore(_ => { });
builder.Services.AddSingleton<IClock, SystemClock>();
builder.Services.AddSingleton<IIdGenerator, GuidIdGenerator>();
builder.Services.TryAddSingleton(chatClient);
builder.Services.TryAddSingleton(embeddingGenerator);
builder.Services.AddAgentMemoryFramework(options =>
{
options.AutoExtractOnPersist = true;
options.ContextFormat.IncludeEntities = true;
options.ContextFormat.IncludeFacts = true;
options.ContextFormat.IncludePreferences = true;
options.ExposeMemoryToolsFromContextProvider = true;
});
var host = builder.Build();
await using var hostDisposal = (IAsyncDisposable)host;
await using var scope = host.Services.CreateAsyncScope();
var sp = scope.ServiceProvider;
// ── Setup: schema + sample product graph ─────────────────────────────────────────────────────────
var catalog = new ProductCatalog(sp.GetRequiredService<INeo4jTransactionRunner>());
await sp.GetRequiredService<ISchemaBootstrapper>().BootstrapAsync();
await catalog.SeedAsync();
Console.WriteLine("Neo4j schema ready; sample products loaded.\n");
// ── The shopping assistant: context provider (recall + memory tools) + product tools ─────────────
var memoryProvider = sp.GetRequiredService<Neo4jMemoryContextProvider>();
var productTools = catalog.CreateAIFunctions();
// WithMemoryOwnerScoping(sp) scopes the whole invocation (recall, tool calls, persistence) to the
// owner set via WithMemoryIdentity below — no manual BeginOwnerScope wrapping needed per turn.
AIAgent agent = chatClient.AsAIAgent(new ChatClientAgentOptions
{
Name = "ShoppingAssistant",
ChatOptions = new ChatOptions
{
ModelId = chatModel,
Instructions =
"You are a helpful shopping assistant for an online store. Learn and remember the customer's "
+ "preferences (brands, budget, categories) using the memory tools, and recommend products that "
+ "fit using the product tools. Explain why each recommendation matches, and suggest alternatives "
+ "when something is out of stock.",
// memoryProvider appends the six memory tools (search_memory, remember_fact, ...) to this list
// on every model call via AIContext.Tools — see ExposeMemoryToolsFromContextProvider above.
Tools = [.. productTools],
},
AIContextProviders = [memoryProvider],
}).WithMemoryOwnerScoping(sp);
const string Shopper = "shopper-amelia";
// ── Session A — the customer shops; the model calls the tools and remembers preferences ──────────
Console.WriteLine(">> Session A\n");
var sessionA = (await agent.CreateSessionAsync())
.WithMemoryIdentity(userId: Shopper, sessionId: "cart-a", applicationId: "retail-demo");
foreach (var turn in new[]
{
"Hi! I'm looking for running shoes. I love Nike and want to stay under $150.",
"Nice — what would you recommend for me, and is anything I might like out of stock?",
})
{
await SayAsync(agent, sessionA, turn);
}
// ── Session B — a NEW session for the same shopper still recalls her preferences ─────────────────
Console.WriteLine(">> Session B — a brand-new session; memory is durable\n");
var sessionB = (await agent.CreateSessionAsync())
.WithMemoryIdentity(userId: Shopper, sessionId: "cart-b", applicationId: "retail-demo");
await SayAsync(agent, sessionB, "I'm back — remind me what I like and suggest something new.");
Console.WriteLine("=== Done. Preferences + messages persist in Neo4j across sessions. ===");
// One conversational turn. Owner scoping (recall, tool calls, and persistence) is guaranteed
// automatically by the WithMemoryOwnerScoping-wrapped agent — no manual BeginOwnerScope needed here.
static async Task SayAsync(AIAgent agent, AgentSession session, string message)
{
Console.WriteLine($"USER : {message}");
var response = await agent.RunAsync(message, session);
Console.WriteLine($"ASSISTANT : {response.Text}\n");
}
@@ -0,0 +1,75 @@
# Agent with Memory Using AgentMemory — Shopping Assistant
A **.NET port of the Neo4j Labs "agent-memory" retail assistant** example
([`microsoft_agent_retail_assistant`](https://github.com/neo4j-labs/agent-memory/tree/main/examples/microsoft_agent_retail_assistant),
referenced from the [Learn integration page](https://learn.microsoft.com/en-us/agent-framework/integrations/neo4j-memory)).
A shopping assistant that **learns a customer's preferences** and **recommends products via graph
traversal**, backed by durable memory in Neo4j.
It uses the [`AgentMemory`](https://www.nuget.org/packages/AgentMemory) library — a .NET port of the
(Python-only) Neo4j Labs memory provider, **not an officially recognized Neo4j integration** — through
its Microsoft Agent Framework adapter.
## Features Demonstrated
- **`Neo4jMemoryContextProvider`** (an `AIContextProvider`) — recalls relevant memory before each run,
persists new memory after (the same bidirectional pattern as the official provider), and — via
`ExposeMemoryToolsFromContextProvider = true` — surfaces the memory tools (search / remember / recall)
itself through `AIContext.Tools`.
- **`ProductCatalog.CreateAIFunctions()`** — retail tools over a Neo4j `:Product` graph (search /
recommend / related / inventory).
- Preference learning that persists across a brand-new `AgentSession` for the same shopper.
- Graph-based product recommendations and "related products" via traversal.
## Prerequisites
- [.NET 10 SDK](https://dotnet.microsoft.com/download/dotnet/10.0)
- A **Neo4j 5.x** instance (the sample bootstraps the schema and seeds sample products)
- An **Azure OpenAI / Foundry** deployment (a chat model + an embedding model)
## Configuration
Set the following environment variables:
| Variable | Required | Default | Purpose |
|---|---|---|---|
| `AZURE_OPENAI_ENDPOINT` | ✅ | — | Azure OpenAI / Foundry endpoint |
| `AZURE_OPENAI_API_KEY` | — | — | API key; if unset, `DefaultAzureCredential` (`az login`) is used |
| `FOUNDRY_MODEL` | — | `gpt-4o-mini` | chat model deployment |
| `FOUNDRY_EMBEDDING_MODEL` | — | `text-embedding-3-small` | embedding model deployment (1536 dims) |
| `NEO4J_URI` | — | `bolt://localhost:7687` | Neo4j bolt URI |
| `NEO4J_USER` | — | `neo4j` | Neo4j user |
| `NEO4J_PASSWORD` | — | `password` | Neo4j password |
> Ensure the embedding model's dimensions match the Neo4j vector-index dimensions AgentMemory bootstraps
> (default 1536, which matches `text-embedding-3-small`).
## Run the Sample
```bash
docker run -d --name neo4j -p 7474:7474 -p 7687:7687 -e NEO4J_AUTH=neo4j/password neo4j:5.26
export AZURE_OPENAI_ENDPOINT="https://<your-resource>.openai.azure.com"
export AZURE_OPENAI_API_KEY="<your-key>" # or omit and `az login`
export FOUNDRY_MODEL="gpt-4o-mini"
dotnet run
```
## Expected Output
1. The sample bootstraps the Neo4j schema and seeds a small product graph (`:Product`,
`:ProductCategory`, `:ProductBrand` nodes).
2. **Session A** — the shopper says she wants running shoes, loves Nike, and has a $150 budget; the
agent calls the memory tools to remember this and the product tools to recommend matching items.
3. **Session B** — a brand-new session for the same shopper (`shopper-amelia`) still recalls her
preferences and can suggest something new, because memory persists in Neo4j across sessions.
## Note on packaging
This sample is part of the repo's solution and targets .NET 10 like every other sample, but it
deliberately opts out of **Central Package Management** and does **not** reference `Microsoft.Agents.AI`
via the repo's in-source project — it consumes the **published** `AgentMemory` NuGet packages instead
(which target `Microsoft.Agents.AI` 1.9.0). A version that references the repo's current
`Microsoft.Agents.AI` source would require AgentMemory to be rebuilt against that version first.
@@ -9,6 +9,7 @@ These samples show how to create an agent with the Agent Framework that uses Mem
|[Custom Memory Implementation](../../01-get-started/04_memory/)|This sample demonstrates how to create a custom memory component and attach it to an agent.|
|[Memory with Microsoft Foundry](./AgentWithMemory_Step04_MemoryUsingFoundry/)|This sample demonstrates how to create and run an agent that uses Microsoft Foundry's managed memory service to extract and retrieve individual memories.|
|[Bounded Chat History with Overflow](./AgentWithMemory_Step05_BoundedChatHistory/)|This sample demonstrates how to create a bounded chat history provider that overflows older messages to a vector store and recalls them as memories.|
|[Memory Using AgentMemory](./AgentWithMemory_Step06_MemoryUsingAgentMemory/)|This sample demonstrates a retail shopping assistant built with [`AgentMemory`](https://www.nuget.org/packages/AgentMemory), an unofficial .NET port of the Neo4j Labs graph-memory provider, to learn customer preferences and recommend products via graph traversal.|
> **See also**: [Memory Search with Foundry Agents](../AgentProviders/foundry/Agent_Step22_MemorySearch/) - demonstrates using the built-in Memory Search tool with Microsoft Foundry agents.
@@ -24,7 +24,7 @@ AIProjectClient aiProjectClient = new(
new Uri(endpoint),
new DefaultAzureCredential());
// Create an In-Memory vector store that uses the Azure AI Foundry embedding model to generate embeddings.
// Create an In-Memory vector store that uses the Microsoft Foundry embedding model to generate embeddings.
VectorStore vectorStore = new InMemoryVectorStore(new()
{
EmbeddingGenerator = aiProjectClient.GetProjectOpenAIClient().GetEmbeddingClient(embeddingDeploymentName).AsIEmbeddingGenerator()
@@ -25,7 +25,7 @@ AIProjectClient aiProjectClient = new(
new Uri(endpoint),
new DefaultAzureCredential());
// Create a Qdrant vector store that uses the Azure AI Foundry embedding model to generate embeddings.
// Create a Qdrant vector store that uses the Microsoft Foundry embedding model to generate embeddings.
QdrantClient client = new("localhost");
VectorStore vectorStore = new QdrantVectorStore(client, ownsClient: true, new()
{
@@ -3,7 +3,7 @@
// Structured Output — Configure agents to return typed JSON
//
// This sample shows how to configure a ChatClientAgent to produce
// structured output using JSON schema constraints with Azure AI Foundry.
// structured output using JSON schema constraints with Microsoft Foundry.
using System.ComponentModel;
using System.Text.Json;
@@ -1,6 +1,6 @@
// Copyright (c) Microsoft. All rights reserved.
// Agent Observability — OpenTelemetry tracing with Azure AI Foundry
// Agent Observability — OpenTelemetry tracing with Microsoft Foundry
//
// This sample shows how to instrument an AI agent with OpenTelemetry
// for distributed tracing and telemetry logging.
@@ -19,7 +19,7 @@ var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt
// Create a host builder that we will register services with and then run.
HostApplicationBuilder builder = Host.CreateApplicationBuilder(args);
// Create the AI agent from the Azure AI Foundry project client.
// Create the AI agent from the Microsoft Foundry project client.
// 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.
@@ -2,7 +2,7 @@
// Middleware — Chain multiple middleware layers on an agent
//
// This sample shows multiple middleware layers working together with Azure AI Foundry:
// This sample shows multiple middleware layers working together with Microsoft Foundry:
// chat client (global/per-request), agent run (PII filtering and guardrails),
// function invocation (logging and result overrides), human-in-the-loop
// approval workflows for sensitive function calls, and MessageAIContextProvider
@@ -15,7 +15,7 @@ using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
// Get Azure AI Foundry configuration from environment variables
// Get Microsoft Foundry configuration from environment variables
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
@@ -3,7 +3,7 @@
// Background Responses — Asynchronous agent execution with polling
//
// This sample shows how to use background responses with ChatClientAgent
// and Azure AI Foundry for non-blocking agent execution.
// and Microsoft Foundry for non-blocking agent execution.
using Azure.AI.Projects;
using Azure.Identity;
@@ -67,7 +67,7 @@ static string GetTime([Description("The city name.")] string city) =>
// asking for alternative destinations. The model will process this injected message on the next
// service call — even though the parent FunctionInvokingChatClient loop would otherwise stop.
[Description("Check current travel advisories for a city.")]
static string CheckTravelAdvisory([Description("The city name.")] string city)
static async Task<string> CheckTravelAdvisory([Description("The city name.")] string city)
{
// Simulated travel advisory data.
var advisory = city.ToUpperInvariant() switch
@@ -85,9 +85,13 @@ static string CheckTravelAdvisory([Description("The city name.")] string city)
// When an advisory is found, inject a follow-up question so the model automatically
// suggests alternatives without the user needing to ask.
var runContext = AIAgent.CurrentRunContext!;
runContext.Agent.GetService<MessageInjectingChatClient>()?.EnqueueMessages(
runContext.Session!,
[new ChatMessage(ChatRole.User, $"Given the travel advisory for {city}, what alternative cities would you recommend instead?")]);
var injector = runContext.Agent.GetService<MessageInjectingChatClient>();
if (injector is not null)
{
await injector.EnqueueMessagesAsync(
runContext.Session!,
[new ChatMessage(ChatRole.User, $"Given the travel advisory for {city}, what alternative cities would you recommend instead?")]);
}
return advisory;
}
+1 -1
View File
@@ -18,7 +18,7 @@ Before you begin, ensure you have the following prerequisites:
- Azure CLI installed and authenticated (for Azure credential authentication)
- User has the required role to invoke models in the Foundry project.
**Note**: These samples use models hosted through Microsoft Foundry. For more information, see [Azure AI Foundry documentation](https://learn.microsoft.com/en-us/azure/ai-foundry/).
**Note**: These samples use models hosted through Microsoft Foundry. For more information, see [Microsoft Foundry documentation](https://learn.microsoft.com/en-us/azure/ai-foundry/).
**Note**: These samples use Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Foundry project. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
@@ -12,7 +12,7 @@ The simplest agent evaluation: create a Foundry agent, run it against test quest
- .NET 10 SDK or later
- Azure authentication available to `DefaultAzureCredential` (for local development, run `az login`)
- A deployed model in your Azure AI Foundry project
- A deployed model in your Microsoft Foundry project
Set the following environment variables:
@@ -14,6 +14,12 @@ It builds on Post 1's personal finance assistant and teaches it to work with *yo
saving and deleting still pause for approval. The `place_trade` tool is also wrapped in an
`ApprovalRequiredAIFunction` (see `TradingTools.cs`), so the harness surfaces an approval prompt
before any trade runs. The trade itself is simulated — no real order is placed.
> ⚠️ **Security — avoid tool-name collisions:** auto-approval rules such as
> `FileAccessProvider.ReadOnlyToolsAutoApprovalRule` match tool calls **solely by tool name**. Any
> other registered tool that shares one of the approved names (`file_access_read`, `file_access_ls`,
> `file_access_grep`) would be silently auto-approved, bypassing the human
> approval boundary. Ensure no other tool's name collides with the reserved names a rule approves.
- **Durable memory, two ways:**
- **File memory** (coarse-grained, explicit) — the agent reads/writes files such as
`watchlist.md`. File memory is on by default; its files live on disk under
@@ -133,7 +133,7 @@ AIAgent researchAgent = ResearchAgent.Create(chatClient);
// A sandboxed shell, confined to the trade-confirmation vault. ConfineWorkingDirectory re-anchors
// every command to the vault, and the deny-list policy pre-filters obviously destructive commands.
// (Patterns are a UX guardrail, not a security boundary — for hard isolation use DockerShellExecutor.)
await using var shell = new LocalShellExecutor(new LocalShellExecutorOptions
await using var shellExecutor = new LocalShellExecutor(new LocalShellExecutorOptions
{
WorkingDirectory = vaultDir,
ConfineWorkingDirectory = true,
@@ -160,7 +160,9 @@ using var codeAct = new HyperlightCodeActProvider(HyperlightCodeActProviderOptio
// Turn the chat client into a HarnessAgent. On top of Post 2's file access and approvals we add the
// four "scaling" capabilities: skills (our own provider), background agents, a confined shell, and
// CodeAct.
List<AIContextProvider> contextProviders = [skillsProvider, codeAct];
// The shell is wired up in two parts: the ShellEnvironmentProvider injects OS/shell/CWD info into the
// system prompt, and the shell tool is registered below in ChatOptions.
List<AIContextProvider> contextProviders = [skillsProvider, codeAct, new ShellEnvironmentProvider(shellExecutor)];
AIAgent agent = chatClient.AsHarnessAgent(new HarnessAgentOptions
{
@@ -170,8 +172,6 @@ AIAgent agent = chatClient.AsHarnessAgent(new HarnessAgentOptions
DisableAgentSkillsProvider = true,
// Fan-out research is delegated to this background agent.
BackgroundAgents = [researchAgent],
// The confined shell, exposed as the approval-gated run_shell tool.
ShellExecutor = shell,
// Keep reading the portfolio frictionless while writes, trades, and shell commands still prompt.
ToolApprovalAgentOptions = new ToolApprovalAgentOptions
{
@@ -179,7 +179,7 @@ AIAgent agent = chatClient.AsHarnessAgent(new HarnessAgentOptions
},
// Start in "execute" mode for quick lookups and actions; switch any time with /mode plan.
AgentModeProviderOptions = new AgentModeProviderOptions { DefaultMode = "execute" },
// Our skills provider plus CodeAct.
// Our skills provider, CodeAct, and the shell environment provider.
AIContextProviders = contextProviders,
ChatOptions = new ChatOptions
{
@@ -188,6 +188,8 @@ AIAgent agent = chatClient.AsHarnessAgent(new HarnessAgentOptions
[
StockTools.CreateGetStockPriceTool(),
TradingTools.CreatePlaceTradeTool(),
// The confined shell, exposed as the approval-gated run_shell tool.
shellExecutor.AsAIFunction(requireApproval: true),
],
Reasoning = new() { Effort = ReasoningEffort.Medium },
},
@@ -43,7 +43,7 @@ public sealed class ModeCommandHandler : CommandHandler
string[] parts = input.Split(' ', 2, StringSplitOptions.RemoveEmptyEntries | StringSplitOptions.TrimEntries);
if (parts.Length < 2)
{
string current = this._modeProvider.GetMode(session);
string current = await this._modeProvider.GetModeAsync(session).ConfigureAwait(false);
await ux.WriteInfoLineAsync($"Current mode: {current}").ConfigureAwait(false);
return true;
}
@@ -52,7 +52,7 @@ public sealed class ModeCommandHandler : CommandHandler
try
{
this._modeProvider.SetMode(session, newMode);
await this._modeProvider.SetModeAsync(session, newMode).ConfigureAwait(false);
ux.CurrentMode = newMode;
await ux.WriteInfoLineAsync($"Switched to {newMode} mode.", ModeColors.Get(newMode, this._modeColors)).ConfigureAwait(false);
}
@@ -93,7 +93,7 @@ public sealed class HarnessAgentRunner : IDisposable
{
if (await handler.TryHandleAsync(text, this._session, this._ux).ConfigureAwait(false))
{
this._ux.CurrentMode = this._modeProvider?.GetMode(this._session);
this._ux.CurrentMode = this._modeProvider is null ? null : await this._modeProvider.GetModeAsync(this._session).ConfigureAwait(false);
return;
}
}
@@ -111,16 +111,15 @@ public sealed class HarnessAgentRunner : IDisposable
/// enqueued via the <see cref="MessageInjectingChatClient"/> so it can be picked up
/// by the agent on its next opportunity.
/// </summary>
internal Task OnStreamingInputAsync(string text)
internal async Task OnStreamingInputAsync(string text)
{
if (this._messageInjector is null)
{
return Task.CompletedTask;
return;
}
this._messageInjector.EnqueueMessages(this._session, [new ChatMessage(ChatRole.User, text)]);
this._ux.SetQueuedMessages(this._messageInjector.GetPendingMessages(this._session));
return Task.CompletedTask;
await this._messageInjector.EnqueueMessagesAsync(this._session, [new ChatMessage(ChatRole.User, text)]).ConfigureAwait(false);
this._ux.SetQueuedMessages(await this._messageInjector.GetPendingMessagesAsync(this._session).ConfigureAwait(false));
}
/// <summary>
@@ -136,7 +135,7 @@ public sealed class HarnessAgentRunner : IDisposable
{
if (messages.Count == 0)
{
this.CompleteTurn();
await this.CompleteTurnAsync().ConfigureAwait(false);
return;
}
@@ -151,17 +150,19 @@ public sealed class HarnessAgentRunner : IDisposable
private async Task RunAgentLoopAsync(IList<ChatMessage> messages)
{
IList<ChatMessage>? nextMessages = messages;
IReadOnlyList<ChatMessage> lastPendingMessages = this._messageInjector?.GetPendingMessages(this._session) ?? [];
IReadOnlyList<ChatMessage> lastPendingMessages = this._messageInjector is not null
? await this._messageInjector.GetPendingMessagesAsync(this._session).ConfigureAwait(false)
: [];
while (nextMessages is not null)
{
var runOptions = new AgentRunOptions();
foreach (var observer in this._observers)
{
observer.ConfigureRunOptions(runOptions, this._agent, this._session);
await observer.ConfigureRunOptionsAsync(runOptions, this._agent, this._session).ConfigureAwait(false);
}
this._ux.CurrentMode = this._modeProvider?.GetMode(this._session);
this._ux.CurrentMode = this._modeProvider is null ? null : await this._modeProvider.GetModeAsync(this._session).ConfigureAwait(false);
this._ux.BeginStreaming();
this._ux.BeginStreamingOutput();
@@ -171,7 +172,7 @@ public sealed class HarnessAgentRunner : IDisposable
{
if (this._modeProvider is not null)
{
string currentMode = this._modeProvider.GetMode(this._session);
string currentMode = await this._modeProvider.GetModeAsync(this._session).ConfigureAwait(false);
if (currentMode != this._ux.CurrentMode)
{
this._ux.CurrentMode = currentMode;
@@ -199,7 +200,7 @@ public sealed class HarnessAgentRunner : IDisposable
}
}
this.SyncQueuedMessageDisplay(ref lastPendingMessages);
lastPendingMessages = await this.SyncQueuedMessageDisplayAsync(lastPendingMessages).ConfigureAwait(false);
}
}
catch (Exception ex)
@@ -208,7 +209,7 @@ public sealed class HarnessAgentRunner : IDisposable
}
// Final sync after streaming.
this.SyncQueuedMessageDisplay(ref lastPendingMessages);
lastPendingMessages = await this.SyncQueuedMessageDisplayAsync(lastPendingMessages).ConfigureAwait(false);
this._ux.StopSpinner();
await this._ux.EndStreamingOutputAsync().ConfigureAwait(false);
@@ -261,13 +262,13 @@ public sealed class HarnessAgentRunner : IDisposable
nextMessages = drained.Count > 0 ? [.. drained] : null;
}
this.CompleteTurn();
await this.CompleteTurnAsync().ConfigureAwait(false);
}
private void CompleteTurn()
private async Task CompleteTurnAsync()
{
this._ux.EndStreaming();
this._ux.CurrentMode = this._modeProvider?.GetMode(this._session);
this._ux.CurrentMode = this._modeProvider is null ? null : await this._modeProvider.GetModeAsync(this._session).ConfigureAwait(false);
}
/// <summary>
@@ -275,14 +276,15 @@ public sealed class HarnessAgentRunner : IDisposable
/// Messages that have been consumed (drained by the service) are echoed to the output
/// area as regular user-input entries.
/// </summary>
private void SyncQueuedMessageDisplay(ref IReadOnlyList<ChatMessage> lastPendingMessages)
/// <returns>The updated snapshot of pending messages.</returns>
private async Task<IReadOnlyList<ChatMessage>> SyncQueuedMessageDisplayAsync(IReadOnlyList<ChatMessage> lastPendingMessages)
{
if (this._messageInjector is null)
{
return;
return lastPendingMessages;
}
var pending = this._messageInjector.GetPendingMessages(this._session);
var pending = await this._messageInjector.GetPendingMessagesAsync(this._session).ConfigureAwait(false);
int consumedCount = lastPendingMessages.Count - pending.Count;
for (int i = 0; i < consumedCount && i < lastPendingMessages.Count; i++)
@@ -291,7 +293,7 @@ public sealed class HarnessAgentRunner : IDisposable
this._ux.WriteUserInputEcho(text);
}
lastPendingMessages = pending;
this._ux.SetQueuedMessages(pending);
return pending;
}
}
@@ -40,9 +40,11 @@ public static class HarnessConsole
? await options.SessionFactory(agent)
: await agent.CreateSessionAsync();
string? initialMode = modeProvider is null ? null : await modeProvider.GetModeAsync(session);
using var component = new HarnessAppComponent(
placeholder: userPrompt,
initialMode: modeProvider?.GetMode(session),
initialMode: initialMode,
inputEnabled: messageInjector is not null,
runnerFactory: ux => new HarnessAgentRunner(
agent: agent,
@@ -20,9 +20,7 @@ public abstract class ConsoleObserver
/// <param name="options">The run options to configure.</param>
/// <param name="agent">The agent being interacted with.</param>
/// <param name="session">The current agent session.</param>
public virtual void ConfigureRunOptions(AgentRunOptions options, AIAgent agent, AgentSession session)
{
}
public virtual ValueTask ConfigureRunOptionsAsync(AgentRunOptions options, AIAgent agent, AgentSession session) => default;
/// <summary>
/// Called for each <see cref="AgentResponseUpdate"/> in the response stream, regardless of
@@ -40,9 +40,9 @@ public sealed class PlanningOutputObserver : ConsoleObserver
}
/// <inheritdoc/>
public override void ConfigureRunOptions(AgentRunOptions options, AIAgent agent, AgentSession session)
public override async ValueTask ConfigureRunOptionsAsync(AgentRunOptions options, AIAgent agent, AgentSession session)
{
if (this.IsPlanningMode(this._modeProvider.GetMode(session)))
if (this.IsPlanningMode(await this._modeProvider.GetModeAsync(session).ConfigureAwait(false)))
{
options.ResponseFormat = ChatResponseFormat.ForJsonSchema<PlanningResponse>();
}
@@ -205,7 +205,7 @@ public sealed class PlanningOutputObserver : ConsoleObserver
if (selection == ApproveOption)
{
this._modeProvider.SetMode(session, this._executionModeName);
await this._modeProvider.SetModeAsync(session, this._executionModeName).ConfigureAwait(false);
await ux.WriteInfoLineAsync(
$"✅ Switched to {this._executionModeName} mode.",
ModeColors.Get(this._executionModeName, this._modeColors)).ConfigureAwait(false);
@@ -85,7 +85,6 @@ AIAgent agent =
MaxOutputTokens = MaxOutputTokens,
Name = "ResearchAgent",
Description = "A research assistant that plans and executes research tasks.",
DisableFileAccess = true, // If enabled, this would allow the agent to read/write files in a working directory
OpenTelemetrySourceName = TracingSourceName, // Use our custom source name so spans are captured by the TracerProvider above.
FileMemoryStore = new FileSystemAgentFileStore( // Configure the file memory provider to store files in a local folder called "agent-files".
Path.Combine(AppContext.BaseDirectory, "agent-files")),
@@ -1,6 +1,6 @@
# What this sample demonstrates
This sample demonstrates how to use a `HarnessAgent` with the Harness `AIContextProviders` (`TodoProvider` and `AgentModeProvider`) for interactive research tasks with web search capabilities powered by Azure AI Foundry. The `HarnessAgent` pre-configures function invocation, per-service-call chat history persistence, and context-window compaction.
This sample demonstrates how to use a `HarnessAgent` with the Harness `AIContextProviders` (`TodoProvider` and `AgentModeProvider`) for interactive research tasks with web search capabilities powered by Microsoft Foundry. The `HarnessAgent` pre-configures function invocation, per-service-call chat history persistence, and context-window compaction.
Key features showcased:
@@ -19,7 +19,7 @@ Key features showcased:
Before running this sample, ensure you have:
1. An Azure AI Foundry project with a deployed model (e.g., `gpt-5.4`)
1. A Microsoft Foundry project with a deployed model (e.g., `gpt-5.4`)
2. Azure CLI installed and authenticated (`az login`)
## Environment Variables
@@ -27,7 +27,7 @@ Before running this sample, ensure you have:
Set the following environment variables:
```bash
# Required: Your Azure AI Foundry OpenAI endpoint
# Required: Your Microsoft 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)
@@ -57,7 +57,6 @@ AIAgent webSearchAgent =
DisableTodoProvider = true,
DisableAgentModeProvider = true,
DisableFileMemory = true, // If enabled, this would allow the agent to store memories as files in a directory associated with the current session
DisableFileAccess = true, // If enabled, this would allow the agent to read/write files in a working directory
DisableToolAutoApproval = true, // If true, this disables the don't-ask-again approval functionality.
ChatOptions = new ChatOptions
{
@@ -107,7 +106,6 @@ AIAgent parentAgent =
DisableTodoProvider = true,
DisableAgentModeProvider = true,
DisableFileMemory = true, // If enabled, this would allow the agent to store memories as files in a directory associated with the current session
DisableFileAccess = true, // If enabled, this would allow the agent to read/write files in a working directory
DisableToolAutoApproval = true, // If true, this disables the don't-ask-again approval functionality.
DisableWebSearch = true,
BackgroundAgents = [webSearchAgent],
@@ -32,7 +32,7 @@ A parent agent receives a list of stock tickers and uses a web-search background
## Prerequisites
- An Azure AI Foundry endpoint with an OpenAI model deployment
- A Microsoft Foundry endpoint with an OpenAI model deployment
- Set the following environment variables:
- `AZURE_FOUNDRY_OPENAI_ENDPOINT` — Your Foundry OpenAI endpoint URL
- `FOUNDRY_MODEL` — Model deployment name (defaults to `gpt-5.4`)
@@ -1,12 +1,12 @@
// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to use a HarnessAgent with the default FileAccessProvider
// This sample demonstrates how to use a HarnessAgent 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 `working/` folder with sales transaction data.
// The HarnessAgent's default FileAccessProvider uses `{cwd}/working` as its working directory,
// which matches this sample's folder layout.
// File access is opt-in: setting HarnessAgentOptions.FileAccessStore enables the
// FileAccessProvider, and this sample points it at the `working/` folder below the location of the executable.
// Ask the agent to analyze the data, produce summaries, or create new output files.
//
// Special commands:
@@ -1,11 +1,11 @@
# What this sample demonstrates
This sample demonstrates how to use a `HarnessAgent` with the default `FileAccessProvider` to give an agent access to a folder of data files for reading, analyzing, and writing results. The `HarnessAgent` pre-configures function invocation, per-service-call chat history persistence, in-loop compaction, tool approval, and OpenTelemetry — so the sample only needs to supply the chat client, token limits, custom instructions, and opt out of unused features.
This sample demonstrates how to use a `HarnessAgent` with the `FileAccessProvider` to give an agent access to a folder of data files for reading, analyzing, and writing results. The `HarnessAgent` pre-configures function invocation, per-service-call chat history persistence, in-loop compaction, tool approval, and OpenTelemetry — so the sample only needs to supply the chat client, token limits, custom instructions, a `FileAccessStore`, and opt out of unused features.
Key features showcased:
- **HarnessAgent** — a pre-configured agent that wraps a `ChatClientAgent` with function invocation, per-service-call persistence, and context-window compaction
- **FileAccessProvider** — the HarnessAgent's default file access provider uses `{cwd}/working` as its working directory, matching this sample's `working/` folder
- **FileAccessProvider** — file access is opt-in; setting `HarnessAgentOptions.FileAccessStore` to the sample's `working/` folder enables the provider's read/write tools
- **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
@@ -15,7 +15,7 @@ Key features showcased:
Before running this sample, ensure you have:
1. An Azure AI Foundry project with a deployed model (e.g., `gpt-5.4`)
1. A Microsoft Foundry project with a deployed model (e.g., `gpt-5.4`)
2. Azure CLI installed and authenticated (`az login`)
## Environment Variables
@@ -23,7 +23,7 @@ Before running this sample, ensure you have:
Set the following environment variables:
```bash
# Required: Your Azure AI Foundry OpenAI endpoint
# Required: Your Microsoft 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)
@@ -51,6 +51,15 @@ You can ask the agent to:
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`.
## ⚠️ Security: avoid tool-name collisions
This sample uses `FileAccessProvider.ReadOnlyToolsAutoApprovalRule` to auto-approve read-only file
access tools. Built-in auto-approval rules match tool calls **solely by tool name**, so any other
registered tool that shares one of the approved names (`file_access_read`, `file_access_ls`,
`file_access_grep`) would be **silently auto-approved**, bypassing the
human approval boundary. Ensure no other tool's name collides with the reserved names an
auto-approval rule approves.
## Sample Data
The included `working/sales.csv` contains sales transactions from January to March 2025 with the following columns:
@@ -82,8 +82,9 @@ var instructions =
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
// Create the agent with ALL HarnessAgent features enabled plus Hyperlight CodeAct.
// No Disable* flags are set — TodoProvider, AgentModeProvider, FileMemory, FileAccess,
// ToolApproval, WebSearch, and AgentSkillsProvider are all active.
// TodoProvider, AgentModeProvider, FileMemory, ToolApproval, WebSearch, and
// AgentSkillsProvider are on by default. File access is opt-in, so it is enabled here by
// supplying a FileAccessStore.
AIAgent agent =
new AIProjectClient(
new Uri(endpoint),
@@ -101,6 +102,8 @@ AIAgent agent =
OpenTelemetrySourceName = TracingSourceName,
// Point the file memory at a local folder for persistent memory across sessions.
FileMemoryStore = new FileSystemAgentFileStore(Path.Combine(AppContext.BaseDirectory, "agent-files")),
// Enable file access (opt-in) by rooting the file access tools at a local working folder.
FileAccessStore = new FileSystemAgentFileStore(Path.Combine(AppContext.BaseDirectory, "working")),
// Add the HyperlightCodeActProvider so the agent can execute Python code in a sandbox.
AIContextProviders = [codeAct],
ChatOptions = new ChatOptions
@@ -10,14 +10,14 @@ The agent can plan tasks, manage modes, store memories, read/write files, search
## Prerequisites
- .NET 10 SDK
- An Azure AI Foundry project endpoint
- A Microsoft Foundry project endpoint
- KVM-capable host (the Hyperlight sandbox runs code in micro-VMs)
## Environment Variables
| Variable | Description |
|----------|-------------|
| `FOUNDRY_PROJECT_ENDPOINT` | Your Azure AI Foundry project endpoint |
| `FOUNDRY_PROJECT_ENDPOINT` | Your Microsoft Foundry project endpoint |
| `FOUNDRY_MODEL` | Model deployment name (default: `gpt-5.4`) |
## Running
@@ -174,9 +174,9 @@ async Task ApprovalLoopAsync()
{
AutoApprovalRules =
[
functionCall =>
context =>
{
Console.WriteLine($" Auto-approving: {functionCall.Name}");
Console.WriteLine($" Auto-approving: {context.FunctionCallContent.Name}");
return ValueTask.FromResult(true);
},
],
@@ -252,7 +252,6 @@ AIAgent CreateLeanHarnessAgent(
DisableAgentModeProvider = true,
DisableTodoProvider = disableTodoProvider,
DisableFileMemory = true,
DisableFileAccess = true,
DisableWebSearch = true,
ToolApprovalAgentOptions = toolApprovalAgentOptions,
ChatOptions = new ChatOptions
@@ -32,7 +32,7 @@ The Python sample in [microsoft/agent-framework#6174](https://github.com/microso
Before running this sample, ensure you have:
1. An Azure AI Foundry project with a deployed model (e.g., `gpt-5.4`)
1. A Microsoft Foundry project with a deployed model (e.g., `gpt-5.4`)
2. Azure CLI installed and authenticated (`az login`)
## Environment Variables
@@ -40,7 +40,7 @@ Before running this sample, ensure you have:
Set the following environment variables:
```bash
# Required: Your Azure AI Foundry project endpoint
# Required: Your Microsoft Foundry project endpoint
export AZURE_AI_PROJECT_ENDPOINT="https://your-project.services.ai.azure.com/api/projects/your-project"
# Optional: Model deployment name (defaults to gpt-5.4)
@@ -31,7 +31,7 @@ public static class Program
{
private static async Task Main()
{
// Set up the Azure AI Foundry client
// Set up the Microsoft Foundry client
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
@@ -92,7 +92,7 @@ public static class Program
string model)
{
ProjectsAgentVersion agentVersion = await aiProjectClient.AgentAdministrationClient.CreateAgentVersionAsync(
$"{targetLanguage} Translator",
$"{targetLanguage}Translator",
new ProjectsAgentVersionCreationOptions(
new DeclarativeAgentDefinition(model: model)
{
@@ -37,7 +37,7 @@ public static class Program
{
private static async Task Main()
{
// Set up the Azure AI Foundry client
// Set up the Microsoft Foundry client
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
@@ -34,7 +34,7 @@ public static class Program
{
private static async Task Main()
{
// Set up the Azure AI Foundry client
// Set up the Microsoft Foundry client
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
@@ -35,7 +35,7 @@ public static class Program
{
private static async Task Main()
{
// Set up the Azure AI Foundry client
// Set up the Microsoft Foundry client
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
@@ -37,7 +37,7 @@ public static class Program
private static async Task Main()
{
// Set up the Azure AI Foundry client
// Set up the Microsoft Foundry client
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
@@ -70,7 +70,7 @@ public static class Program
using var traceProvider = traceProviderBuilder.Build();
// Set up the Azure AI Foundry client
// Set up the Microsoft Foundry client
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
@@ -18,7 +18,7 @@ namespace WorkflowMagenticOrchestrationSample;
/// </summary>
/// <remarks>
/// Pre-requisites:
/// - An Azure AI Foundry project endpoint and model deployment must be configured.
/// - A Microsoft Foundry project endpoint and model deployment must be configured.
/// - Run <c>az login</c> before executing the sample.
/// </remarks>
public static class Program
@@ -15,7 +15,7 @@ This sample showcases the Magentic Orchestration Pattern in .NET, setting up a t
## Prerequisites
- `FOUNDRY_PROJECT_ENDPOINT` set to your Azure AI Foundry project endpoint
- `FOUNDRY_PROJECT_ENDPOINT` set to your Microsoft Foundry project endpoint
- `FOUNDRY_MODEL` set to your model deployment name (defaults to `gpt-5.4-mini`)
- `az login` completed before running the sample
@@ -21,13 +21,13 @@ namespace WorkflowAgentsInWorkflowsSample;
/// </summary>
/// <remarks>
/// Pre-requisites:
/// - An Azure AI Foundry project endpoint and model must be configured.
/// - A Microsoft Foundry project endpoint and model must be configured.
/// </remarks>
public static class Program
{
private static async Task Main()
{
// Set up the Azure AI Foundry client
// Set up the Microsoft Foundry client
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
@@ -16,13 +16,13 @@ namespace WorkflowAgentsInWorkflowsSample;
/// </summary>
/// <remarks>
/// Pre-requisites:
/// - An Azure AI Foundry project endpoint and model must be configured.
/// - A Microsoft Foundry project endpoint and model must be configured.
/// </remarks>
public static class Program
{
private static async Task Main()
{
// Set up the Azure AI Foundry client.
// Set up the Microsoft Foundry client.
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
@@ -31,7 +31,7 @@ namespace MixedWorkflowWithAgentsAndExecutors;
/// <remarks>
/// Pre-requisites:
/// - Previous foundational samples should be completed first.
/// - An Azure AI Foundry project endpoint and model must be configured.
/// - A Microsoft Foundry project endpoint and model must be configured.
/// </remarks>
public static class Program
{
@@ -40,7 +40,7 @@ public static class Program
{
Console.WriteLine("\n=== Mixed Workflow: Agents and Executors ===\n");
// Set up the Azure AI Foundry client
// Set up the Microsoft Foundry client
var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
@@ -47,7 +47,7 @@ public static class Program
Console.WriteLine("\n=== Writer-Critic Iteration Workflow ===\n");
Console.WriteLine($"Writer and Critic will iterate up to {MaxIterations} times until approval.\n");
// Set up the Azure AI Foundry client
// Set up the Microsoft Foundry client
string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
@@ -119,7 +119,7 @@ internal static class Pages
</div>
<div id="chat"></div>
<form id="form">
<input id="input" placeholder="Try: 'What time is it?' or 'Search docs for Azure AI Foundry'" autocomplete="off" autofocus />
<input id="input" placeholder="Try: 'What time is it?' or 'Search docs for Microsoft Foundry'" autocomplete="off" autofocus />
<button type="submit">Send</button>
</form>
<div id="status"></div>
@@ -0,0 +1,53 @@
# Agent Framework hosting samples (bring your own route)
These samples show how to expose an Agent Framework agent or workflow over the OpenAI Responses HTTP
protocol from an ASP.NET Core app that you write, where your app owns the HTTP route, authentication, and
where conversations are stored.
## Two ways to expose an agent over the Responses protocol
Agent Framework gives you two options:
1. **`MapOpenAIResponses` (batteries included).** A single call maps a ready-made `/responses` endpoint that
handles the protocol, routing, and session storage for you. Pick this when you want a working endpoint
quickly and the built-in behavior fits. See [AgentWebChat](../../05-end-to-end/AgentWebChat) for a sample
that uses it.
2. **Call the conversion helpers from your own route (these samples).** You write the ASP.NET Core route and
call the `OpenAIResponses` helper methods to translate between the Responses HTTP payloads and the agent.
The framework only does the protocol translation, so you keep full control of routing, authentication,
and where conversations are stored. Pick this when you need hosting behavior the built-in endpoint does
not provide.
## Samples
| Sample | What it shows |
|---|---|
| [`local_responses/`](./local_responses) | An agent behind an ASP.NET Core route you write, using the `OpenAIResponses` helper methods plus `AgentSessionStore` for conversation continuity. The simplest sample to start with. |
| [`local_responses_workflow/`](./local_responses_workflow) | A workflow behind an ASP.NET Core route you write, using the `OpenAIResponses` helper methods, `HostedWorkflowState`, an explicit `CheckpointManager`, and a checkpoint cursor your app keeps so a run resumes across turns. |
Each sample is a **client/server pair** split into two projects:
```
local_responses/
├── Server/ # exposes POST /responses using the OpenAIResponses helper methods
└── Client/ # consumes it two ways: a chat client and an agent
```
The `Client` shows the two ways to consume the endpoint from .NET, both against the same server:
- A plain `Microsoft.Extensions.AI.IChatClient` (the lower-level chat-client path).
- A Microsoft Agent Framework `AIAgent` (the higher-level agent path).
## Relationship to `../FoundryHostedAgents/`
The sibling [`../FoundryHostedAgents/`](../FoundryHostedAgents) directory contains samples for agents that
run inside the Foundry Hosted Agents platform, which hosts the agent and exposes the protocol for you. Use
those when you want the Foundry-managed hosting surface; use these when you want to host the agent in your
own ASP.NET Core app.
| Aspect | `af-hosting/` (this directory) | `FoundryHostedAgents/` |
|---|---|---|
| Server stack | An ASP.NET Core app you write plus the hosting protocol helpers | Foundry Hosted Agents runtime |
| Who exposes the route | Your app | The platform |
| When to pick this | You need custom hosting code | You want the Foundry-managed hosting surface |

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