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Author SHA1 Message Date
SergeyMenshykhandCopilot App ee23e07cb9 Python: Make MCP server tool names consistent (#14506) 
## Summary
- Keep the first function when MCP tool names collide, warn for skipped
duplicates, and dispatch calls to the exact advertised function.
- Add opt-in plugin-qualified tool names and warn when names exceed
MCP's recommended length.
- Update MCP server documentation and cover naming, duplicate
registration, exclusions, dispatch, and agent forwarding with tests.

## Validation
- 70 focused MCP connector and agent tests passed.
- Ruff formatting passed; four changed Python files lint clean. The six
Ruff property-docstring findings in agent.py also occur at the upstream
base.

---------

Co-authored-by: Copilot App <[email protected]>
 2026-10-01 12:27:08 +00:00
Evan Mattsondependabot[bot]copilot-swe-agent[bot]rogerbarretoCopilot
 		ebc2ef9bb2 Consolidate Dependabot dependency updates (#14385) 
### Motivation and Context

Consolidates the currently open Dependabot updates into one reviewable
dependency PR while preserving each source update's intent across GitHub
Actions, .NET, Python, and JavaScript sample dependencies.

### Description

Updates pinned GitHub Actions, central NuGet package versions, Python
dependency constraints and uv lockfiles, and npm/Yarn lockfiles for the
affected samples. Overlapping lockfile updates were regenerated or
reconciled so that all compatible requested versions are retained
together on the latest `main`. The incompatible MCP 2.x and Python 3.10
`onnxruntime-genai` updates are excluded, the private-feed-only
`@humanfs/node` update is omitted, and the logging abstractions floor is
aligned with the updated Azure AI Projects dependency.

### Related Issue

Supersedes:
- https://github.com/microsoft/semantic-kernel/pull/14177
- https://github.com/microsoft/semantic-kernel/pull/14179
- https://github.com/microsoft/semantic-kernel/pull/14180
- https://github.com/microsoft/semantic-kernel/pull/14190
- https://github.com/microsoft/semantic-kernel/pull/14209
- https://github.com/microsoft/semantic-kernel/pull/14230
- https://github.com/microsoft/semantic-kernel/pull/14233
- https://github.com/microsoft/semantic-kernel/pull/14254
- https://github.com/microsoft/semantic-kernel/pull/14257
- https://github.com/microsoft/semantic-kernel/pull/14259
- https://github.com/microsoft/semantic-kernel/pull/14260
- https://github.com/microsoft/semantic-kernel/pull/14261
- https://github.com/microsoft/semantic-kernel/pull/14271
- https://github.com/microsoft/semantic-kernel/pull/14272
- https://github.com/microsoft/semantic-kernel/pull/14273
- https://github.com/microsoft/semantic-kernel/pull/14274
- https://github.com/microsoft/semantic-kernel/pull/14276
- https://github.com/microsoft/semantic-kernel/pull/14280
- https://github.com/microsoft/semantic-kernel/pull/14282
- https://github.com/microsoft/semantic-kernel/pull/14299
- https://github.com/microsoft/semantic-kernel/pull/14300
- https://github.com/microsoft/semantic-kernel/pull/14335
- https://github.com/microsoft/semantic-kernel/pull/14337
- https://github.com/microsoft/semantic-kernel/pull/14338
- https://github.com/microsoft/semantic-kernel/pull/14339
- https://github.com/microsoft/semantic-kernel/pull/14357
- https://github.com/microsoft/semantic-kernel/pull/14358
- https://github.com/microsoft/semantic-kernel/pull/14361
- https://github.com/microsoft/semantic-kernel/pull/14365
- https://github.com/microsoft/semantic-kernel/pull/14366
- https://github.com/microsoft/semantic-kernel/pull/14367
- https://github.com/microsoft/semantic-kernel/pull/14368
- https://github.com/microsoft/semantic-kernel/pull/14369

### Contribution Checklist

- [ ] The code builds clean without any errors or warnings
- [ ] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [ ] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄

---------

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: rogerbarreto <[email protected]>
Co-authored-by: Copilot <[email protected]>
Copilot-Session: d3c2550f-f129-4660-9461-af1288241064
 2026-09-07 09:46:40 +00:00
SergeyMenshykhEvan MattsonCopilot App
 		b371cc6c6f Python: update dependencies (#14360) 
## Summary
- update Transformers and related Hugging Face packages
- refresh Python dependencies used by the MCP OAuth demo
- regenerate the affected uv lockfiles
- adapt the Hugging Face text completion connector to Transformers 5
- temporarily disable live tests that depend on the retired Assistants
API

## Hugging Face connector

Transformers 5 removes the `text2text-generation`, `summarization` and
`translation` pipeline tasks, so `HuggingFaceTextCompletion` raised
`KeyError: Unknown task text2text-generation` on construction.

Those two tasks now use a small adapter built on `AutoModelForSeq2SeqLM`
and `AutoTokenizer` that preserves what the removed pipelines did:

- the same output keys (`summary_text` for summarization,
`generated_text` otherwise), so the content mapping is unchanged
- the model's task specific prefix (e.g. `summarize: `) is still
prepended before tokenization
- one record per generated sequence when `num_return_sequences > 1`
- `model_kwargs` are shared with the tokenizer load, as `pipeline()` did
- pipeline only options are dropped with a warning instead of reaching
`generate()`

`text-generation` keeps using `pipeline()`. There is no public API
change.

The previous unit tests mocked `pipeline()` and so did not catch the
incompatibility. New tests cover the adapter, option routing, device
placement, output mapping and prefix resolution.

## Temporarily disabled tests

The OpenAI and Azure OpenAI Assistants API has been retired. Live
requests now return HTTP 410 (`assistants_api_deprecated`) on Azure
OpenAI and HTTP 404 on OpenAI, so these tests cannot exercise a
functioning service.

- all 30 parametrized cases in
`tests/integration/agents/openai_assistant_agent/test_openai_assistant_agent_integration.py`
are skipped at module level, before the live-service fixture runs
- the `step1_openai_assistant` case in `tests/samples/test_concepts.py`
is skipped unconditionally
- the other concept samples are unchanged
- all 103 tests under `tests/unit/agents/openai_assistant` remain
enabled and passing

The skips are intentionally limited to live tests for the retired API.
Comments next to each skip include the migration guide and state that
the skip should be removed after the agents and sample move to the
replacement API.

## Validation
- uv lock consistency checks
- 35 Hugging Face unit tests pass
- all 12 deliberate connector mutations used to assess regression
coverage were detected by the unit tests
- all 103 Assistants agent unit tests pass
- 30 live Assistants integration cases and the one retired-API concept
sample report as skipped before making service requests
- the three text completion services used by the integration suite were
exercised against their real models on Transformers 5, for both
completion and streaming
- Ruff check and formatting pass

---------

Co-authored-by: Evan Mattson <[email protected]>
Co-authored-by: Copilot App <[email protected]>
Copilot-Session: c2d4dd29-0a9c-4f43-b2ce-243e19ec34b2
 2026-09-03 15:10:36 +00:00
SergeyMenshykh 6da62d372a Python: update MCP OAuth sample dependencies (#14352) 
### Motivation and Context

Keep the MCP OAuth demo aligned with the current Semantic Kernel Python
SDK release and public API signatures.

### Description

- Update the sample's Semantic Kernel dependency to 1.44.1.
- Refresh the lockfile for the updated dependency graph.
- Align timeout and agent-thread type annotations with the current SDK
APIs.

### Contribution Checklist

- [x] The code builds clean without any errors or warnings
- [x] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [x] All applicable checks pass; no new unit tests are needed for this
sample dependency update
- [x] I didn't break anyone 😄

---------

Copilot-Session: 71b0555a-bf39-4b88-8ff9-9a1178453c1b
 2026-08-31 16:36:30 +01:00
Vincent BiretandCopilot Autofix powered by AI b4b0ae7780 chore: fixes typos (#14343) 
fixes typos across repo that were flagged by the CI

---------

Co-authored-by: Copilot Autofix powered by AI <[email protected]>
 2026-08-27 17:07:35 +01:00
SergeyMenshykh b39d95a344 Python: [Breaking] Remove unsupported service auth mode from Copilot Studio agent (#14306) 
### Motivation and Context

The Copilot Studio agent exposed a `SERVICE` authentication mode that
was never reachable — it was guarded to always raise before its
implementation ran. Its dormant credential handling also triggered
certificate-related static analysis alerts.

### Description

Removes the service authentication path along with its settings,
parameters, tests, and documentation. `CopilotStudioAgentAuthMode` is
kept with its `INTERACTIVE` member, which is the only supported mode.
Interactive authentication is unchanged.

Service authentication can be reintroduced later as a complete, tested
feature.

### Contribution Checklist

- [x] The code builds clean without any errors or warnings
- [x] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [x] All unit tests pass, and I have added new tests where possible
- [x] I didn't break anyone 😄

---------

Copilot-Session: 25dd6e2a-f759-4148-a630-40110e90eff2
 2026-08-20 11:36:32 +01:00
Evan Mattson 7d885ddac1 Consolidate Python and .NET dependency updates (#14222) 
### Motivation and Context

Consolidates the currently open Python and .NET Dependabot updates into
one coordinated dependency change. This reduces duplicate review and CI
work while preserving each source PR's update intent.

The npm and Yarn updates are intentionally excluded from this draft and
remain in their original Dependabot PRs.

### Related Issue

Supersedes:

- https://github.com/microsoft/semantic-kernel/pull/14178
- https://github.com/microsoft/semantic-kernel/pull/14184
- https://github.com/microsoft/semantic-kernel/pull/14185
- https://github.com/microsoft/semantic-kernel/pull/14186
- https://github.com/microsoft/semantic-kernel/pull/14187
- https://github.com/microsoft/semantic-kernel/pull/14188
- https://github.com/microsoft/semantic-kernel/pull/14189
- https://github.com/microsoft/semantic-kernel/pull/14191
- https://github.com/microsoft/semantic-kernel/pull/14192
- https://github.com/microsoft/semantic-kernel/pull/14202
- https://github.com/microsoft/semantic-kernel/pull/14203
- https://github.com/microsoft/semantic-kernel/pull/14204
- https://github.com/microsoft/semantic-kernel/pull/14205
- https://github.com/microsoft/semantic-kernel/pull/14207
- https://github.com/microsoft/semantic-kernel/pull/14208
- https://github.com/microsoft/semantic-kernel/pull/14211
- https://github.com/microsoft/semantic-kernel/pull/14212
- https://github.com/microsoft/semantic-kernel/pull/14213
- https://github.com/microsoft/semantic-kernel/pull/14214
- https://github.com/microsoft/semantic-kernel/pull/14215
- https://github.com/microsoft/semantic-kernel/pull/14216
- https://github.com/microsoft/semantic-kernel/pull/14217
- https://github.com/microsoft/semantic-kernel/pull/14218
- https://github.com/microsoft/semantic-kernel/pull/14219
- https://github.com/microsoft/semantic-kernel/pull/14221

### Description

- Updates the selected .NET Aspire and AWS SDK package versions in
central package management.
- Updates the selected Python requirements and regenerates both affected
uv lockfiles without losing earlier bumps.
- Keeps the compatible ONNX Runtime/GenAI pair on Python 3.10 while
applying ONNX Runtime GenAI 0.14.1 on Python 3.11 and newer.
- Retains pyOpenSSL 26.2.0, which is newer than the 26.0.0 requested by
its source PR and is required by the consolidated cryptography update.
- Uses Pinecone 7.3 or newer on Windows, where Pinecone 7.0.1 imports
the unavailable Unix `readline` module, while retaining the existing
`~=7.0` range on macOS and Linux.
- Constrains MCP to the compatible 1.x API because the current Semantic
Kernel integration imports interfaces removed by MCP 2.0.

### Validation

- Python unit tests passed across Python 3.10-3.13 on Ubuntu, Windows,
and macOS, including Dapr jobs.
- Python pre-commit, lock validation, spell checking, and
integration-test aggregate checks passed.
- .NET 9/10 builds, package-install checks, unit tests, AOT tests,
formatting, and coverage checks passed on Ubuntu and Windows.
- Merge Gatekeeper passed.

### Contribution Checklist

- [x] The code builds clean without any errors or warnings
- [x] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [x] All unit tests pass, and I have added new tests where possible
- [x] I didn't break anyone 😄
 2026-07-29 10:27:10 +00:00
SergeyMenshykh 3da48a3d01 Python: [Breaking] Add MCP tool approval callback for Azure AI Agent (#14210) 
## Summary
- Add an Azure AI Agent callback for MCP tool approval requests.
- Route MCP tool approval submissions through a shared helper in thread
actions.
- Add unit coverage for approval, denial, callback failures, and
per-call decisions.

## Testing
- python -m pytest tests/unit/agents/azure_ai_agent

---------

Copilot-Session: 3e190979-228b-4a82-8e63-5ad14bd4879f
 2026-07-28 18:15:13 +00:00
Evan Mattsondependabot[bot]copilot-swe-agent[bot]
 		d003eb2590 Consolidate Dependabot dependency updates (#14176) 
### Motivation and Context

Semantic Kernel currently has 43 open Dependabot pull requests spanning
GitHub Actions, .NET, Python, npm, and Yarn dependency graphs. This
rollup applies their compatible net changes together on the latest
`main`, making it possible to validate and merge the updates as one
coherent dependency state.

Supersedes:

- https://github.com/microsoft/semantic-kernel/pull/13133
- https://github.com/microsoft/semantic-kernel/pull/13134
- https://github.com/microsoft/semantic-kernel/pull/13136
- https://github.com/microsoft/semantic-kernel/pull/13172
- https://github.com/microsoft/semantic-kernel/pull/13507
- https://github.com/microsoft/semantic-kernel/pull/13601
- https://github.com/microsoft/semantic-kernel/pull/13606
- https://github.com/microsoft/semantic-kernel/pull/13666
- https://github.com/microsoft/semantic-kernel/pull/13673
- https://github.com/microsoft/semantic-kernel/pull/13688
- https://github.com/microsoft/semantic-kernel/pull/13700
- https://github.com/microsoft/semantic-kernel/pull/13707
- https://github.com/microsoft/semantic-kernel/pull/13708
- https://github.com/microsoft/semantic-kernel/pull/13712
- https://github.com/microsoft/semantic-kernel/pull/13721
- https://github.com/microsoft/semantic-kernel/pull/13873
- https://github.com/microsoft/semantic-kernel/pull/13930
- https://github.com/microsoft/semantic-kernel/pull/13939
- https://github.com/microsoft/semantic-kernel/pull/13949
- https://github.com/microsoft/semantic-kernel/pull/13950
- https://github.com/microsoft/semantic-kernel/pull/13951
- https://github.com/microsoft/semantic-kernel/pull/13997
- https://github.com/microsoft/semantic-kernel/pull/14000
- https://github.com/microsoft/semantic-kernel/pull/14053
- https://github.com/microsoft/semantic-kernel/pull/14069
- https://github.com/microsoft/semantic-kernel/pull/14088
- https://github.com/microsoft/semantic-kernel/pull/14091
- https://github.com/microsoft/semantic-kernel/pull/14094
- https://github.com/microsoft/semantic-kernel/pull/14103
- https://github.com/microsoft/semantic-kernel/pull/14106
- https://github.com/microsoft/semantic-kernel/pull/14107
- https://github.com/microsoft/semantic-kernel/pull/14108
- https://github.com/microsoft/semantic-kernel/pull/14109
- https://github.com/microsoft/semantic-kernel/pull/14110
- https://github.com/microsoft/semantic-kernel/pull/14128
- https://github.com/microsoft/semantic-kernel/pull/14148
- https://github.com/microsoft/semantic-kernel/pull/14149
- https://github.com/microsoft/semantic-kernel/pull/14160
- https://github.com/microsoft/semantic-kernel/pull/14161
- https://github.com/microsoft/semantic-kernel/pull/14164
- https://github.com/microsoft/semantic-kernel/pull/14171
- https://github.com/microsoft/semantic-kernel/pull/14172
- https://github.com/microsoft/semantic-kernel/pull/14173

### Description

- Updates the requested GitHub Actions and preserves the PR-file-scoped
typos workflow fix.
- Consolidates the .NET Aspire, AWS SDK, ReportGenerator, JavaScript,
and SQLite security updates.
- Regenerates the npm, Yarn, and uv lockfiles from the combined
manifests instead of resolving generated-file conflicts by selection.
- Rolls overlapping updates forward to one compatible result: pyasn1
0.6.4 supersedes 0.6.3; pyOpenSSL 26.2.0 remains compatible with
cryptography 48.0.1; and Vite 8/Rolldown makes the older Rollup-only
overrides obsolete.
- Retains updates already present on current `main` without
reintroducing stale pins, including Aspire Hosting Azure Search 13.3.0
and Prompty.Core 2.0.0-beta.3.

The full .NET solution builds in Debug with zero warnings and errors.
Focused validation passed 82 .NET tests (3 skipped), 1,096 Python tests,
both frontend production builds, and uv lock consistency checks for the
main Python project and OAuth sample.

### Contribution Checklist

- [x] The code builds clean without any errors or warnings
- [ ] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [ ] All unit tests pass, and I have added new tests where possible
- [x] I didn't break anyone 😄

---------

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
 2026-07-23 08:29:36 +00:00
SergeyMenshykhCopilotEvan Mattson
 		3df33f7862 Python: [Breaking] Update runtime handling (#14135) 
This PR updates Python runtime handling and related tests.

---------

Co-authored-by: Copilot <[email protected]>
Co-authored-by: Evan Mattson <[email protected]>
 2026-07-07 03:22:20 +00:00
SergeyMenshykhandCopilot 38a5480af0 Python: Default MCP SSE server samples to loopback with host validation (#14127) 
## Motivation and Context

The Python MCP server demos under `python/samples/demos/mcp_server/` can
optionally run over the SSE transport (`--transport sse`). This updates
that sample wiring to follow the Model Context Protocol guidance for
local development servers, so developers who use these demos as a
starting point inherit sensible defaults.

## Description

- **Loopback by default**: the SSE samples now bind to `127.0.0.1`
instead of `0.0.0.0`. A new `--host` argument makes binding to other
interfaces an explicit opt-in that logs a warning.
- **Host/Origin validation**: added Starlette `TrustedHostMiddleware`
plus a small Origin allowlist middleware so the local listener only
serves loopback callers (requests without an `Origin` header are still
allowed, for non-browser MCP clients).
- **Sample hygiene**: switched `Starlette(debug=True)` to `debug=False`
so the demos don't ship verbose debug output.
- **Docs**: the README now describes the loopback-by-default behavior,
the `--host` opt-in, and points to the existing `mcp_with_oauth` sample
for authenticated, network-reachable deployments.

Applies to `sk_mcp_server.py` and `agent_as_server.py`. The stdio
transport (the default) and the other stdio-only samples are unchanged.

## Contribution Checklist

- [x] The code builds clean without any errors or warnings
- [x] I didn't break anyone 😄

---------

Co-authored-by: Copilot <[email protected]>
 2026-06-30 21:10:27 +00:00
dependabot[bot]copilot-swe-agent[bot]Evan Mattson
 		16085866f8 Bump urllib3 from 2.6.3 to 2.7.0 in /python (#13978) 
### Motivation and Context

Bumps <a href="https://github.com/urllib3/urllib3">urllib3</a> from
2.6.3 to 2.7.0 across the Python project, including the `mcp_with_oauth`
demo, to pick up the latest security and bug fixes.

### Description

- Bumps `urllib3` from 2.6.3 to 2.7.0 in `python/uv.lock`
- Bumps `urllib3` from 2.5.0 to 2.7.0 in
`python/samples/demos/mcp_with_oauth/uv.lock` so the demo no longer
resolves an older urllib3 version

### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [ ] The code builds clean without any errors or warnings
- [ ] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [ ] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄

> **Note**
> Automatic rebases have been disabled on this pull request as it has
been open for over 30 days.

---------

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: Evan Mattson <[email protected]>
 2026-06-17 12:47:30 +00:00
Evan MattsonMAF Dashboard BotCopilot
 		0f322bcc48 Python: Improve prompt-template msg serialize and sample usage (#13738) 
### Motivation and Context

This PR updates the Jinja2 and Handlebars prompt-template helpers to
serialize chat messages through the existing XML/message serializer
instead of assembling message XML manually. It also aligns the
prompt-template samples with the serializer-backed helper and adds
regression coverage for common message content.

<!-- Thank you for your contribution to the semantic-kernel repo!
Please help reviewers and future users, providing the following
information:
  1. Why is this change required?
  2. What problem does it solve?
  3. What scenario does it contribute to?
  4. If it fixes an open issue, please link to the issue here.
-->

### Description

Prompt template message serialize improvements.

<!-- Describe your changes, the overall approach, the underlying design.
These notes will help understanding how your code works. Thanks! -->

### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [X] The code builds clean without any errors or warnings
- [X] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄

---------

Co-authored-by: MAF Dashboard Bot <[email protected]>
Co-authored-by: Copilot <[email protected]>
 2026-04-08 00:29:36 +00:00
Evan Mattson 3f6d72725f Python: Fix image integration tests that are now blocked due to bot policies (#13680) 
### Motivation and Context

Fix image integration tests that are now blocked due to bot policies

<!-- Thank you for your contribution to the semantic-kernel repo!
Please help reviewers and future users, providing the following
information:
  1. Why is this change required?
  2. What problem does it solve?
  3. What scenario does it contribute to?
  4. If it fixes an open issue, please link to the issue here.
-->

### Description

Fix image integration tests that are now blocked due to bot policies

<!-- Describe your changes, the overall approach, the underlying design.
These notes will help understanding how your code works. Thanks! -->

### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [X] The code builds clean without any errors or warnings
- [X] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄
 2026-03-18 10:42:08 +00:00
Tao ChenandEvan Mattson 5c891d1769 Python: Add support to new openai text to image model (#13651) 
### Motivation and Context

<!-- Thank you for your contribution to the semantic-kernel repo!
Please help reviewers and future users, providing the following
information:
  1. Why is this change required?
  2. What problem does it solve?
  3. What scenario does it contribute to?
  4. If it fixes an open issue, please link to the issue here.
-->
Dall-e-3 and Dall-e-2 have been deprecated. The newer gpt-1-image model
returns base64 strings.

### Description

<!-- Describe your changes, the overall approach, the underlying design.
These notes will help understanding how your code works. Thanks! -->
Return url if set, otherwise return the base64 string.

### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [x] The code builds clean without any errors or warnings
- [x] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
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---------

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 2026-03-13 08:31:46 +00:00
Tao Chen d5c2b9d889 Python: Improves the robustness of filename handling (#13643) 
### Motivation and Context

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Improves the robustness of filename handling in the Bedrock agent
integration. Ensures that filenames sourced from external responses are
properly sanitized before use in file operations, and adds safer
defaults for file write behavior.

### Description

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1. Sanitize filenames received from Bedrock agent responses.
2. Add overwrite parameter to BinaryContent.write_to_file (defaults to
False).
3. Add tests.
4. Update samples.

### Contribution Checklist

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- [ ] I didn't break anyone 😄
 2026-03-12 17:02:02 +00:00
Evan Mattson 429dd1c4c0 Python: support (Azure) OpenAI realtime audio models (#13291) 
### Motivation and Context

As of 2/27/2026, revived the PR, and the latest code is working for both
Azure OpenAI realtime models and OpenAI realtime models.

SK has support for realtime-preview models; however, since they've gone
to GA we have not added support for the latest library abstractions.
This PR brings in the changes to support running models like
`gpt-realtime-1.5`, `gpt-realtime`, `gpt-realtime-mini` or `gpt-audio`.

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### Description

- Closes #13267
- Code now relies on `openai` >= 2.0
- Considered a breaking change due some new config added to the
execution settings.

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- [ ] I didn't break anyone 😄
 2026-02-28 09:01:03 +09:00
Evan Mattson e696dc7d52 Python: Add directory allowlist configuration for SessionsPythonTool file (#13467) 
### Motivation and Context

When `SessionsPythonTool` is used with an AI model, providing explicit
directory boundaries for file operations gives developers fine-grained
control over which parts of the filesystem the plugin can access. This
follows the pattern established by `HttpPlugin.allowed_domains`.

- Add `allowed_upload_directories` parameter to control which local
directories can be used for file uploads
- Add `allowed_download_directories` parameter for optional restrictions
on file download destinations
- Implement path canonicalization to resolve symlinks and normalize
paths

Usage:

```python
tool = SessionsPythonTool(
    credential=credential,
    allowed_upload_directories={"/app/data/uploads", "/app/user_files"},
    allowed_download_directories={"/app/data/downloads"},  # optional
)
```


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### Description

- `upload_file` now requires `allowed_upload_directories` to be
configured (deny-by-default)
- `download_file` optionally supports `allowed_download_directories`
(permissive-by-default, since it's not exposed as a kernel function)
- Both parameters accept `set[str]` or `list[str]` for convenience
- Paths are canonicalized using `os.path.realpath()` before validation

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 2026-01-23 09:02:05 +00:00
Dmytro Struk dc7c1c0484 Python: Updated Copilot Studio README (#13432) 
### Motivation and Context

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Renamed dependency from Copilot Studio README.

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 2025-12-23 00:28:28 +00:00
Tao Chen d84363f477 Python: Migrate to new Google GenAI SDK (#13371) 
### Motivation and Context

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Closes #12970, #13352

### Description

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1. Migrate Google AI connector to use the new Google AI SDK.
2. This PR also marks the VertexAI connector as deprecated in favor of
the Google AI connector. With this update, if users wants to connect to
a VertexAI project instead of a Google AI endpoint, they can do so with
the Google AI connector.
3. This PR also adds the ability for users to provide a custom client to
the Google AI connector (#13352).
4. This PR also marks `AzureTextCompletion` deprecated.

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 2025-11-24 21:53:57 +00:00
Nico MöllerandEvan Mattson 145ad9bfd2 Python: Upgrade Onnx Connector to use 0.9.0 (#13162) 
### Motivation and Context

Fixes : #13001 

### Description

Package version 0.9.0 introduced very helpful methods like applying chat
templates automatically from the tokenizer and also support for multi
audio & image files.

This PR adds the following functionalities:

- [x] Add Inference with multiple Images
- [x] Add Inference with multiple Audios
- [x] Chat Templates for non Multimodal Models are read via onnx 

### Samples

Text Sample with ONNX:
<img width="1728" height="90" alt="image"
src="https://github.com/user-attachments/assets/b93d9fc1-4e38-4fa9-b535-cc316e0900ed"
/>

Image Sample with ONNX :
<img width="1721" height="91" alt="image"
src="https://github.com/user-attachments/assets/47761beb-b728-4936-a6b6-fd253e041689"
/>


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- [x] I didn't break anyone 😄

---------

Co-authored-by: Evan Mattson <[email protected]>
 2025-11-11 08:44:52 +00:00
Eduard van Valkenburg 1c11258a32 Python: added af_tool bridge for kernel_functions (#13227) 
### Motivation and Context

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Adds a new method to KernelFunction that creates a Agent Framework Tool
from that function.

Does require the user to install agent-framework-core themselves.

### Description

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These notes will help understanding how your code works. Thanks! -->

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raises no violations
- [x] All unit tests pass, and I have added new tests where possible
- [x] I didn't break anyone 😄
 2025-10-30 15:24:16 +00:00
Taylor Rockey e73446e86e Python: [Python] Updated Agents SDK version to latest for CopilotStudio connector (#13144) 
### Motivation and Context

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  1. Why is this change required?
- The Agents SDK has been released, and the recent release changed the
namespace from `microsoft.agents` to `microsoft_agents`, which breaks
imports.
  2. What problem does it solve?
- This updates the `pyproject.toml` and copilot studio related files to
fix the imports
  3. What scenario does it contribute to?
      - Using a Copilot Studio agent as an Agent in Semantic Kernel
  4. If it fixes an open issue, please link to the issue here.
      - N/A
-->

### Description

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- Updated pyproject.toml to use the released packages for the Agents
SDK.
- Updated imports in the `copilot_studio_agent` related files to use the
new `microsoft_agents` namespace

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raises no violations
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- [] I didn't break anyone 😄
 2025-09-23 01:01:51 +00:00
Evan Mattson 28ea2f4df8 Python: Fix AzureAIAgent readme links (#13138) 
### Motivation and Context

Current getting started with agents README links for AzureAIAgent are
broken.

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### Description

- Fixes #13129

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raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [X] I didn't break anyone 😄
 2025-09-17 04:40:38 +00:00
Soumili Nandi 61d3e6ee8d Python: Introduce NvidiaChatCompletion AI Connector (#12952) 
### Motivation and Context

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Enables developers to use NVIDIA's chat models through Semantic Kernel
with structured output support.
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This change adds chat completion support with structured output to the
existing NVIDIA connector, enabling developers to use NVIDIA's chat
models through Semantic Kernel while building conversational AI
applications that require structured, validated responses. The connector
will support more model types iteratively, with future PRs introducing
VLM models and additional capabilities.

### Description

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- New Chat Completion Service:
`NvidiaChatCompletion`: Chat completion service following same structure
as other connectors
- Extends existing NVIDIA embedding connector patterns and architecture
- Custom logic for handling structured output specific to NVIDIA models
  
- Enhanced Configuration:
`NvidiaChatPromptExecutionSettings`: Chat-specific settings following
existing connector patterns
### Contribution Checklist



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- [x] I didn't break anyone 😄
 2025-09-15 23:26:38 +00:00
Tao Chen d7db35dc47 Python: Fix Azure AI Inference connector model_extras duplication (#13066) 
### Motivation and Context

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Addresses #13005 

### Description

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1. Remove the `extra_parameters` key from
`AzureAIInferenceChatPromptExecutionSettings` before calling the chat
completion API to avoid unknown parameter error.
2. Allow setting the API version on the `AzureAIInferenceXXX`
connectors.

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raises no violations
- [x] All unit tests pass, and I have added new tests where possible
- [x] I didn't break anyone 😄
 2025-09-04 01:27:19 +00:00
Evan Mattson f7fdfcd9a9 Python: Add AzureAIAgent Deep Research Tool support (#13034) 
### Motivation and Context

The deep research tool was introduced for the AzureAIAgent; however, we
didn't have support yet in SK. Adding support now for using the deep
research tool for both streaming and non-streaming. Samples added as
well.

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### Description

- Add support for deep research tool.
- Add samples with notes on prerequisites to configure the sample to run
properly.
- Added support for `AZURE_AI_AGENT_DEEP_RESEARCH_MODEL` env var within
`AzureAIAgentSettings` class.
- Bumped min allowed `azure-ai-agents` package ver to 1.2.0b3.
- Closes #12978

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### Contribution Checklist

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raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [X] I didn't break anyone 😄
 2025-09-01 02:35:56 +00:00
Evan Mattson 86b10b95d2 Python: provide AzureAIAgent thread msg id during streaming (#13032) 
### Motivation and Context

As part of invoking an AzureAIAgent via streaming, we weren't providing
the `thread_id` via the `AgentStreamEvent.THREAD_MESSAGE_CREATED` event.

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### Description

Supply the caller with the `thread_msg_id` by sticking it into the
returned SCMC's `metadata` dictionary.
- Closes #12959

Sample output looks like:

```
Sample Output:

# User: 'Hello'
# AuthorRole.ASSISTANT: (thread message id: msg_HZ2h4Wzbj7GEcnVCjnyEuYWT) Hello! How can I assist you with 
    the menu today?
# User: 'What is the special soup?'
# AuthorRole.ASSISTANT: (thread message id: msg_TSjkJK6hHJojIkPvF6uUofHD) The special soup today is 
    Clam Chowder. Would you like to know more about it or anything else from the menu?
# User: 'How much does that cost?'
# AuthorRole.ASSISTANT: (thread message id: msg_liwTpBFrB9JpCM1oM9EXKiwq) The Clam Chowder costs $9.99. 
    Is there anything else you'd like to know?
# User: 'Thank you'
# AuthorRole.ASSISTANT: (thread message id: msg_K6lpR3gYIHethXq17T6gJcxi) You're welcome! 
    If you have any more questions or need assistance, feel free to ask. Enjoy your meal!
```

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- [X] I didn't break anyone 😄
 2025-08-30 10:05:55 +00:00
Christian GlessnerEvan MattsonEvan Mattson
 		5e50e190c4 Python: Add reasoning support for OpenAI Responses Agents (GPT-5, o4-mini, o3) (#12881) 
## Summary

Adds reasoning capabilities to Python OpenAI ResponsesAgent, bringing
parity with the C# implementation. This enables fine-grained control
over reasoning effort for O-series models (o1, o3-mini, o4-mini) and
gpt-5 that support the reasoning parameter.

Fixes #12843

## Changes

### Core Implementation
- **`openai_responses_agent.py`**: Added reasoning configuration support
  - Constructor-level reasoning effort setting
  - Per-invocation reasoning effort override capability
  - Proper parameter validation and model compatibility checks
- **`responses_agent_thread_actions.py`**: Extended thread actions to
support reasoning parameters
  - Reasoning effort propagation through thread operations
  - Metadata preservation for reasoning tokens and summaries

### Sample and Tests
- **`responses_agent_reasoning.py`**: Comprehensive demonstration sample
  - Constructor vs per-invocation reasoning configuration
  - Function calling integration with reasoning
  - Reasoning comparison scenarios (low/medium/high effort)
  - Error handling and troubleshooting guidance
- **`test_openai_responses_agent_reasoning.py`**: Full unit test
coverage
  - Parameter validation tests
  - Integration scenarios with function calling
  - Edge cases and error conditions

## Features

✅ **Constructor-Level Reasoning**: Set default reasoning effort when
creating agents
✅ **Per-Invocation Override**: Override reasoning effort per request  
✅ **Priority Hierarchy**: per-invocation > constructor > model default  
✅ **Function Calling Compatible**: Works seamlessly with existing plugin
system
✅ **Azure OpenAI & OpenAI Support**: Compatible with both service
providers
✅ **Model Validation**: Automatic compatibility checks for O-series
models nad GÜT-5
✅ **Metadata Access**: Reasoning tokens and summaries available in
response metadata

## Usage Example

```python
# Constructor-level reasoning
# Constructor-level reasoning configuration
agent = AzureResponsesAgent(
    ai_model_id="gpt-5",
    client=client,
    reasoning={"effort": "low"}  # Default reasoning for all requests
)

# Per-invocation override
response = await agent.invoke(
    "Solve this complex problem step by step",
    reasoning={"effort": "high"}  
)


# Invoke with reasoning callback to capture intermediate thoughts
response = await agent.invoke(
    "Analyze this data step by step",
    reasoning={"effort": "high", "summary": "detailed"},
    on_intermediate_message=handle_reasoning_message
)

# Streaming with reasoning
async for response in agent.invoke_stream(
    "Explain quantum computing in detail",
    reasoning={"effort": "high", "summary": "detailed"},
    on_intermediate_message=handle_reasoning_message
):
    print(response.content, end="", flush=True)

---------

Co-authored-by: Evan Mattson <[email protected]>
Co-authored-by: Evan Mattson <[email protected]>
 2025-08-28 23:25:26 +00:00
Dmytro Struk 18d9a8e8b2 Python: .Net: Updated encoding logic in prompt templates (#12983) 
### Motivation and Context

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Resolves: https://github.com/microsoft/semantic-kernel/issues/11821

Today, the encoding of template arguments is performed only if argument
type is `string`. In case of custom type, anonymous type or collection -
the encoding is not performed.

This PR contains changes to throw an exception in case if encoding is
enabled but complex type is used. In case of complex type, the encoding
should be performed manually according to business logic and automatic
encoding should be explicitly disabled.

This enforces stricter, but more secure template rendering rules.

**Note**: this is a breaking change for customers who use Handlebars or
Liquid template with complex type arguments. Code changes are required
when initializing template arguments:
```diff
var arguments = new KernelArguments()
{
    { "customer", new
        {
-             firstName = userInput.FirstName,
-             lastName = userInput.LastName,
+             firstName = HttpUtility.HtmlEncode(userInput.FirstName),
+             lastName = HttpUtility.HtmlEncode(userInput.LastName),
        }
    }
};

var templateFactory = new LiquidPromptTemplateFactory();
var promptTemplateConfig = new PromptTemplateConfig()
{
    TemplateFormat = "liquid"
+   InputVariables = new()
+   {
+       // We set AllowDangerouslySetContent to 'true' because each property of this argument is encoded manually. 
+       new() { Name = "customer", AllowDangerouslySetContent = true },
+   }
};

var promptTemplate = templateFactory.Create(promptTemplateConfig);
var renderedPrompt = await promptTemplate.RenderAsync(kernel, arguments); 
```

### Contribution Checklist

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- [ ] I didn't break anyone 😄
 2025-08-26 22:09:00 -07:00
Dmytro Struk 2a47ba9b7d Python: Removed usage of DefaultAzureCredential (#12964) 
### Motivation and Context

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The usage of `DefaultAzureCredential` by default is unsafe and raises
security issues. Instead, users should provide their own credential
types such as `AzureCliCredential`, `ManagedIdentityCredential` and so
on. More information here:

https://learn.microsoft.com/en-us/python/api/azure-identity/azure.identity.aio?view=azure-python

In this PR:
1. Removed the usage of `DefaultAzureCredential` from authentication
logic.
2. Replaced `DefaultAzureCredential` with `AzureCliCredential` in all
examples.

**Note**: this is breaking change for Azure users, who relies on
`DefaultAzureCredential`. Users will need to update the code and pass
the credential type of their choice by using `credential` parameter when
initializing one of the Azure clients.

Before:
```python
chat_completion = AzureChatCompletion()
```

After:
```python
chat_completion = AzureChatCompletion(credential=AzureCliCredential())
```

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- [ ] I didn't break anyone 😄
 2025-08-25 18:29:13 +00:00
Evan Mattson 96bad5ceac Python: Update MCP streamable sample (#12950) 
### Motivation and Context

The MCPStreamableHttpPlugin concept sample pointing to GitHub isn't
working. Updating it to use the Microsoft Learn site MCP server instead.

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### Description

Update sample.

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 2025-08-14 15:13:10 +00:00
Tao Chen 6416c58b90 Python: Add arguments and results attributes to execute tool span (#12940) 
### Motivation and Context

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We are adding two new attributes to the execute tool span according to
this proposal to Otel Semantic Conventions:
https://github.com/open-telemetry/semantic-conventions/pull/2528

### Description

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The following two attributes are added to the `execute_tool` span:
1. `gen_ai.tool.call.arguments`
2. `gen_ai.tool.call.result`

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 2025-08-13 23:35:42 +00:00
Tao ChenandDmytro Struk 8336c320d9 Python: Add bedrock model provider parameter (#12853) 
### Motivation and Context

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Fixes #12833 

### Description

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Add an optional setting to the Bedrock AI connectors to allow users to
specify the Bedrock model providers (i.e. amazon, anthropic, etc) so
that they can use application inference profiles.


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- [x] I didn't break anyone 😄

---------

Co-authored-by: Dmytro Struk <[email protected]>
 2025-08-05 00:43:00 +00:00
Evan Mattson e5972e2430 Python: Add incomplete details reason to AzureAIAgent error message (#12796) 
### Motivation and Context

When errors occur processing a run of an AzureAIAgent, we surface the
error message but not the incomplete_details reason if it exists.

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### Description

This PR adds handling for the incomplete details reason, if it exists,
so it can be passed back via the error message.
- Closes #12752

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 2025-08-04 21:59:19 +00:00
Tao ChenandEvan Mattson b7bb2832aa Python: Input & output attributes in invoke_agent span (#12834) 
### Motivation and Context

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The OTel workgroup has been thinking about enhancing tracing for agents.
This is a proposal from our tracing team:
https://github.com/open-telemetry/semantic-conventions/pull/2528. This
PR implements part of the proposal so that when the proposal gets
merged, we can quickly follow.

### Description

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Two new attributes are added to the `invoke_agent` span, namely the
`gen_ai.agent.invocation_input` and `gen_ai.agent.invocation_output`.

<img width="747" height="583" alt="image"
src="https://github.com/user-attachments/assets/d8b81f68-915b-48ee-8f86-66a0d4f686cc"
/>


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---------

Co-authored-by: Evan Mattson <[email protected]>
 2025-08-04 21:54:45 +00:00
Nava-7andEvan Mattson c16db27622 Python: Update README.md (#12737) 
Update links due to renamed files

### Motivation and Context

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### Description

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- [x] I didn't break anyone 😄

---------

Co-authored-by: Evan Mattson <[email protected]>
 2025-08-04 07:22:25 +00:00
Evan Mattson 1efc7ad04e Python: Pass through arguments when creating agents from specs (#12771) 
### Motivation and Context

Currently, attempting to pass through KernelArguments through agent
creation via declarative spec isn't working properly. The arguments are
used to normalize fields, but are then not passed through fully to where
the agent is created.

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### Description

Pass arguments through, and merge them properly with the normalized
fields. This allows for underlying args to be used by the agent, like in
the case of structured outputs.
- Closes #12770

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 2025-07-24 05:47:43 +00:00
Tao Chen b723fbd5e1 Python: Add mix agent orchestration sample (#12749) 
### Motivation and Context

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We don't have a sample showing how to use a mix of agents of various
types in an orchestration. This PR adds one.
A bug is also discovered in the OpenAIResponsesAgent while creating the
sample.

### Description

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1. Add a new sample showing how to use a mix of agents in the Handoff
orchestration.
2. Fix a bug in the OpenAIResponsesAgent where the tools were not
considering the tools in the kernel instance. A new test is added too.
3. Fix a bug in the AgentActorBase where the intermediate message
callback was rejecting ChatMeesageContent type.

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 2025-07-22 16:57:05 +00:00
Eduard van Valkenburg c79f5a5c63 Python: improved MCP connect and additional samples (#12696) 
### Motivation and Context

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Adding a sample using StreamableHTTPServer towards Github.
Added a demo showing how to connect to a OAuth protected MCP server.
Also some improvements in the connect logic for MCP.


### Description

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- [x] I didn't break anyone 😄
 2025-07-22 15:14:32 +00:00
Evan Mattson 48f71b1f2e Python: Support AzureAI agent MCP tools for streaming and non-streaming invocations (#12736) 
### Motivation and Context

MCP tool support was released for the AzureAI Agent and it has yet to be
added to the SK Python AzureAIAgent. This PR adds functionality to
handle the MCP tools for both streaming and non-streaming invocations.

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### Description

Adds MCP support for the Python AzureAI Agent.
- Upgrades dependent packages to be able to use the mcp tool from the
Azure SDK.

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- [X] I didn't break anyone 😄
 2025-07-18 07:08:00 +00:00
Evan Mattson 9e3cdffc6b Python: Improve AzureAIAgent get thread msg handling. (#12535) 
### Motivation and Context

Currently, when fetching thread messages for an AzureAIAgent, it assumes
that the agent exists, so we can pull it down and get its id. This may
not always be the case - an agent could have been deleted, but the
thread still exists. We need to account for this.

When creating user messages that we add to the thread, there's no `name`
or `id` parameter allowed. We can, however, add metadata to the message.
Going forward we are adding the `agent_id` as metadata to the message,
so upon retrieval later, we can attempt to get it and return the id with
the user's message. This allows one to see which agent_id has responded
to the user's message:

```
# Messages in the thread (asc order):

# AuthorRole.USER for name=asst_mXwZOwyJLxXGtaYKHizRH6Ip: Hello
# AuthorRole.ASSISTANT for name=asst_mXwZOwyJLxXGtaYKHizRH6Ip: Hello! How can I assist you with the menu today?
# AuthorRole.USER for name=asst_mXwZOwyJLxXGtaYKHizRH6Ip: What is the special soup?
# AuthorRole.ASSISTANT for name=asst_mXwZOwyJLxXGtaYKHizRH6Ip: The special soup today is Clam Chowder. Would you like to know more about it or anything else on the menu?
# AuthorRole.USER for name=asst_mXwZOwyJLxXGtaYKHizRH6Ip: How much does that cost?
# AuthorRole.ASSISTANT for name=asst_mXwZOwyJLxXGtaYKHizRH6Ip: The Clam Chowder costs $9.99. Would you like to order it or need information on other items?
# AuthorRole.USER for name=asst_mXwZOwyJLxXGtaYKHizRH6Ip: Thank you
# AuthorRole.ASSISTANT for name=asst_mXwZOwyJLxXGtaYKHizRH6Ip: You're welcome! If you have any more questions or need assistance with the menu, feel free to ask. Enjoy your meal!
```

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### Description

- Closes #12435

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 2025-06-19 23:52:07 +00:00
Eduard van Valkenburg 003cc4c010 Python: Feature python vector stores preb (#12271) 
### Motivation and Context

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Overhaul of the VectorStores to get it matching with dotnet and the
latest development there.

Closes: 
- #11938 
- #11598 
- #11597
- #11517 
- #10561 
- #10391 
- #9911 
- #9892 
- #10867 

### Description

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Many changes, some highlights:
- Moved from different vector fields types, to a single with a enum
first VectorStoreField()
- Renamed several items
- Made embeddinggenerrator a part of the vector field spec and do
automatic vectorization from there or from the same param on a
collection
- Adds hybrid search using the same setup
- Removed the intermediate TextSeachVectorSearch object need, by
allowing `create_search_function` directly on a collection

Will write out full changes in a migration guide in the docs.

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 2025-06-19 18:34:59 +00:00
Eduard van Valkenburg bd4168316d Python: add Foundry local sample (#12214) 
### Motivation and Context

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Sample on how to use Foundry Local with SK.

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- [x] I didn't break anyone 😄
 2025-06-19 08:18:18 +00:00
Nico MöllerChrisEvan Mattson
 		206655adbb Python: Add check for not approved and approved for Agent Sample (#12316) 
### Motivation and Context

I was having a Demo with the Agents, and found that
`step06_chat_completion_agent_group_chat.py` sample always terminated
after one iteration.

The Reviewer Agent answered "not approved", which also triggered the
`Termination Strategy`, due to the fact that the word `approved` is also
in `not approved`.
To only trigger when there is a real approval I added a check if the
answer is `approved` **and** the answer also don't include `not approve`


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---------

Co-authored-by: Chris <[email protected]>
Co-authored-by: Evan Mattson <[email protected]>
 2025-06-19 05:34:53 +00:00
Tao Chen 44f1253460 Python: Agent response callbacks to provide full context (#12501) 
### Motivation and Context

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Currently, the agent response callbacks in the `Orchestrations` are
triggered only when the final responses from the agents become
available. This limits developers to create solutions that can expose
the internal processing of the agents in multi agent orchestrations.

### Description

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The callbacks will now be triggered by the intermediate messages of the
agents:
1. A new sample
2. Tests

P.s. Fix a bug where the name of the intermediate messages is not
assigned.

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 2025-06-17 16:17:11 +00:00
Tao Chen 9b8f8e22c3 Python: Correct chat completion agent history truncation samples (#12474) 
### Motivation and Context

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While addressing the developer in this
[discussion](https://github.com/microsoft/semantic-kernel/discussions/12450),
I notice that there are a few changes needed to the improve the
truncation history reducer samples of the chat completion agent.

### Description

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Update the samples.


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 2025-06-13 20:11:00 +00:00
Tao Chen dfbc993d8f Python: Remove orchestration persona adaptation messages (#12446) 
### Motivation and Context

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We previously found that agents might get carried away from in long
contexts. The persona adaptation messages were designed to steer the
agents in an orchestration to respond more closely to the instructions
provided (as system message).

As we perform more testing with newer models, we believe that the
persona adaptation messages are no longer necessary. The additional
instability (because they are hardcoded messages that devs can't
override) and cost (the additional token cost which is not significant,
but they do pollute the context which makes debugging difficult) they
introduce is not worth the benefit they provide.


Closing #12294 


> Ideally, we'd want to approach this more analytically. The lack of a
multi-agent evaluation process makes it difficult. All samples were
verified to make sure they behave the same before and after the removal
of the persona adaptation messages.

### Description

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1. Remove the persona adaptation messages.
2. Unit tests.
3. Replace `OpenAIChatCompletion` with `AzureChatCompletion` in some of
the samples.

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 2025-06-11 15:58:21 +00:00
Evan Mattson 4b23389f71 Python: Emit token usage with streaming chat completion agent. (#12416) 
### Motivation and Context

The chat completion agent was not emitting token using during streaming
invocation because we were only allowing through `response.items`. In
the case of token usage, `response.items` is [] and the usage is
contained as part of the message's `metadata` dict. This PR fixes that
bug and allows for `response.items or response.metadata.get("usage")`.
Two new samples are added to the concepts/agents/chat_completion dir to
show how one can track token use for streaming and non-streaming agent
invocation. Token usage handling is also added to the chat completion
agent integration tests.

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### Description

- Fixes a bug where we weren't emitting the streaming token usage for
the chat completion agent. Also now includes the `prompt_tokens_details`
and `completion_tokens_details` models that are returned, but not
previously handled.
- Adds new samples
- Updates integration tests to track token usage and make sure they're
non-zero.
- Closes #12411

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### Contribution Checklist

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- [X] The PR follows the [SK Contribution
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raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [X] I didn't break anyone 😄
 2025-06-09 23:12:05 +00:00
Evan Mattson 3e31c3bdc6 Python: Remove planner-related code and samples. (#12417) 
### Motivation and Context

Per deprecation method, removing planner-related code after June 1,
2025.

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### Description

- Removing planner-related code.
- Closes #12400

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### Contribution Checklist

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raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄
 2025-06-09 21:35:23 +00:00