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dependabot/github_actions/github/codeql-action/init-4.37.9
389
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
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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 |
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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 |
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SergeyMenshykh
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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 |
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Vincent BiretandCopilot Autofix powered by AI
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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]> |
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SergeyMenshykh
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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 |
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Evan Mattson
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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 😄 |
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SergeyMenshykh
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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 |
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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]> |
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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]> |
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SergeyMenshykhandCopilot
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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]> |
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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]> |
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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]> |
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Evan Mattson
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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 😄 |
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Tao ChenandEvan Mattson
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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 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: Evan Mattson <[email protected]> |
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Tao Chen
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d5c2b9d889 |
Python: Improves the robustness of filename handling (#13643)
### 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. --> 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 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> 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 <!-- 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 😄 |
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Evan Mattson
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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`. <!-- 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 - Closes #13267 - Code now relies on `openai` >= 2.0 - Considered a breaking change due some new config added to the execution settings. <!-- 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 😄 |
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Evan Mattson
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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
)
```
<!-- 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
- `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
<!-- 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 😄
|
||
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Dmytro Struk
|
dc7c1c0484 |
Python: Updated Copilot Studio README (#13432)
### 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. --> Renamed dependency from Copilot Studio README. ### 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 - [x] I didn't break anyone 😄 |
||
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Tao Chen
|
d84363f477 |
Python: Migrate to new Google GenAI SDK (#13371)
### 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. --> Closes #12970, #13352 ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> 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. ### 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 😄 |
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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" /> ### 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 - [x] I didn't break anyone 😄 --------- Co-authored-by: Evan Mattson <[email protected]> |
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Eduard van Valkenburg
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1c11258a32 |
Python: added af_tool bridge for kernel_functions (#13227)
### 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. --> 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 <!-- 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 - [x] I didn't break anyone 😄 |
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Taylor Rockey
|
e73446e86e |
Python: [Python] Updated Agents SDK version to latest for CopilotStudio connector (#13144)
### 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?
- 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
<!-- Describe your changes, the overall approach, the underlying design.
These notes will help understanding how your code works. Thanks! -->
- 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
### 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 😄
|
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Evan Mattson
|
28ea2f4df8 |
Python: Fix AzureAIAgent readme links (#13138)
### Motivation and Context Current getting started with agents README links for AzureAIAgent are broken. <!-- 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 - Fixes #13129 <!-- 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 - [X] I didn't break anyone 😄 |
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Soumili Nandi
|
61d3e6ee8d |
Python: Introduce NvidiaChatCompletion AI Connector (#12952)
### 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? Enables developers to use NVIDIA's chat models through Semantic Kernel with structured output support. 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. --> 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 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> - 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 <!-- 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 - [x] I didn't break anyone 😄 |
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Tao Chen
|
d7db35dc47 |
Python: Fix Azure AI Inference connector model_extras duplication (#13066)
### 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. --> Addresses #13005 ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> 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. ### 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 - [x] I didn't break anyone 😄 |
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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. <!-- 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 - 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 <!-- 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 - [X] I didn't break anyone 😄 |
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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. <!-- 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 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! ``` <!-- 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 - [X] I didn't break anyone 😄 |
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|
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]> |
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Dmytro Struk
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18d9a8e8b2 |
Python: .Net: Updated encoding logic in prompt templates (#12983)
### 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. --> 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 <!-- 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 😄 |
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Dmytro Struk
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2a47ba9b7d |
Python: Removed usage of DefaultAzureCredential (#12964)
### 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. --> 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()) ``` ### 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 😄 |
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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. <!-- 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 Update sample. <!-- 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 - [X] I didn't break anyone 😄 |
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Tao Chen
|
6416c58b90 |
Python: Add arguments and results attributes to execute tool span (#12940)
### 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. --> 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 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> The following two attributes are added to the `execute_tool` span: 1. `gen_ai.tool.call.arguments` 2. `gen_ai.tool.call.result` ### 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 - [x] I didn't break anyone 😄 |
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Tao ChenandDmytro Struk
|
8336c320d9 |
Python: Add bedrock model provider parameter (#12853)
### 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. --> Fixes #12833 ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> 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. ### 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 - [x] I didn't break anyone 😄 --------- Co-authored-by: Dmytro Struk <[email protected]> |
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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. <!-- 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 This PR adds handling for the incomplete details reason, if it exists, so it can be passed back via the error message. - Closes #12752 <!-- 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 - [X] I didn't break anyone 😄 |
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Tao ChenandEvan Mattson
|
b7bb2832aa |
Python: Input & output attributes in invoke_agent span (#12834)
### 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. --> 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 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> 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" /> ### 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 - [x] I didn't break anyone 😄 --------- Co-authored-by: Evan Mattson <[email protected]> |
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Nava-7andEvan Mattson
|
c16db27622 |
Python: Update README.md (#12737)
Update links due to renamed files ### 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. --> ### Description <!-- 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 - [ ] 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 😄 --------- Co-authored-by: Evan Mattson <[email protected]> |
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Evan Mattson
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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. <!-- 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 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 <!-- 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 - [X] I didn't break anyone 😄 |
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Tao Chen
|
b723fbd5e1 |
Python: Add mix agent orchestration sample (#12749)
### 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. --> 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 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> 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. ### 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 - [x] I didn't break anyone 😄 |
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Eduard van Valkenburg
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c79f5a5c63 |
Python: improved MCP connect and additional samples (#12696)
### 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. --> 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 <!-- 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 - [x] I didn't break anyone 😄 |
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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. <!-- 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 Adds MCP support for the Python AzureAI Agent. - Upgrades dependent packages to be able to use the mcp tool from the Azure SDK. <!-- 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 - [X] I didn't break anyone 😄 |
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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! ``` <!-- 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 - Closes #12435 <!-- 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 - [X] I didn't break anyone 😄 |
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Eduard van Valkenburg
|
003cc4c010 |
Python: Feature python vector stores preb (#12271)
### 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. --> 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 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> 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. ### 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 😄 |
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Eduard van Valkenburg
|
bd4168316d |
Python: add Foundry local sample (#12214)
### 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. --> Sample on how to use Foundry Local with SK. ### Description <!-- 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 - [x] I didn't break anyone 😄 |
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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` ### 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 - [x] I didn't break anyone 😄 --------- Co-authored-by: Chris <[email protected]> Co-authored-by: Evan Mattson <[email protected]> |
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Tao Chen
|
44f1253460 |
Python: Agent response callbacks to provide full context (#12501)
### 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. --> 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 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> 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. ### 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 - [x] I didn't break anyone 😄 |
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Tao Chen
|
9b8f8e22c3 |
Python: Correct chat completion agent history truncation samples (#12474)
### 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. --> 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 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> Update the samples. ### 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 😄 |
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Tao Chen
|
dfbc993d8f |
Python: Remove orchestration persona adaptation messages (#12446)
### 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. --> 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 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> 1. Remove the persona adaptation messages. 2. Unit tests. 3. Replace `OpenAIChatCompletion` with `AzureChatCompletion` in some of the samples. ### 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 - [x] I didn't break anyone 😄 |
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Evan Mattson
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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.
<!-- 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
- 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
<!-- 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
- [X] I didn't break anyone 😄
|
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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. <!-- 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 - Removing planner-related code. - Closes #12400 <!-- 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 😄 |
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Evan Mattson
|
e0221e58ce |
Python: Fix OpenAPI concept sample (#12418)
### Motivation and Context An OpenAPI concept sample that we have is broken. This PR fixes it to run properly based on the current OpenAPI plugin handling. <!-- 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 Fixes the broken OpenAPI sample. <!-- 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 - [X] I didn't break anyone 😄 |