Python: Merge main into preb2 #11094
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### 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. --> This PR fixes links that were found unreachable by `linkspector`: https://github.com/microsoft/semantic-kernel/actions/runs/13954045797/job/39063140670?pr=11055 ### 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 😄
### Motivation and Context For quite a while the SYSLIB1222, are present in the solution. This PR suppress them and another new JSON001 warning. 
…ion (#10849) ### Motivation and Context Improve overall unit test coverage. ### Description - adding unit tests for ollama services utils - adding unit tests for dapr_actor_registration ### 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 😄 --------- Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
### Motivation and Context The current AzureAIAgent retrieval sample uses the old `assistant_id` kwarg to retrieve the agent. We need to fix this to use the new `agent_id` kwarg in AzureAIAgent retrieval sample <!-- 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 the kwarg to use `agent_id`. <!-- 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 😄
### 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: --> - [ ] 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 😄
### Motivation and Context In creating the `AzureRealtimeWebsocket` object, one can use an api key as part of `AzureOpenAISettings`. This api_key is not getting passed to the `AzureOpenAIConfigBase`. <!-- 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 the api key to the config base. - Closes #11003 <!-- 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 😄
### Motivation and Context When trying to do a model dump for `KernelFunction` models, they are failing with a message related to: ``` pydantic_core._pydantic_core.PydanticSerializationError: Unable to serialize unknown type: <class 'type'> ``` There are some class-level attributes that cannot be properly serialized. <!-- 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 Exclude dumping certain model attributes from the model dump, which allows the main KernelFunction metadata and its underlying parameters to be serialized. - Closes #11078 - Adds unit tests to ensure we have coverage and can dump Pydantic models. <!-- 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 😄
### 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. --> Removed some of the old search samples. ### 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 😄
### 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: --> - [ ] 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 😄
### Motivation and Context - Resolves #11071 Minor fixes: - Broken link fix
### Motivation and Context Removing AllowUnsafeBlocks from the project file as this is no more needed in the current code base. This change ensures the project is safer by disallowing the use of unsafe code blocks.
### Motivation and Context The given test was giving a false negative in environments where Bedrock Runtime was property configured and could be retrieved from the DI container. This change ensures this test only executes when the environment has no runtime configured to be recovered from the DI container.
) ### Motivation and Context Adds two new Python demos demonstrating integration with Microsoft Copilot Studio (MCS). ### Description - `copilot_studio_agent` features a new subclass of `Agent` connecting to a Microsoft Copilot Studio agent via DirectLine API - `copilot_studio_skill` showcases how to extend MCS to connect directly to a Semantic Kernel Agent, by defining a _skill_ ### 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 <35585003+moonbox3@users.noreply.github.com>
This PR introduces a new property to OpenAIPromptExecutionSettings to
enable OpenAI's web search feature. If specified, the property allows
web search to be utilized before generating responses in Semantic
Kernel. If set to null, it is ignored during serialization.
### Motivation and Context
1. Why is this change required?
OpenAI has released an update that enables web search functionality
before generating responses. We want to leverage this feature within
Semantic Kernel.
3. What problem does it solve?
By adding new property to OpenAIPromptExecutionSettings, the new
parameter for web search will be used when calling OpenAI API.
### Description
A new property has been added to OpenAIPromptExecutionSettings. I
decided to use `object?` instead of strong typed value so it will be
easier to adapt with new settings from OpenAI.
```
/// <summary>
/// Enables the web search feature when specified. If set to null, the option is ignored during serialization.
/// </summary>
[Experimental("SKEXP0010")]
[JsonPropertyName("web_search_options")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public object? WebSearchOptions
{
get => this._webSearchOptions;
set
{
this.ThrowIfFrozen();
this._webSearchOptions = value;
}
}
```
### Sample code
Based on OpenAI documentation:
https://platform.openai.com/docs/guides/tools-web-search?api-mode=chat
#### Default settings
```
var builder = Kernel.CreateBuilder()
.AddOpenAIChatCompletion(
modelId: "gpt-4o-mini-search-preview",
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY", EnvironmentVariableTarget.User)
);
var kernel = builder.Build();
var executionSettings = new OpenAIPromptExecutionSettings
{
WebSearchOptions = new { }
};
var chatClient = kernel.GetRequiredService<IChatCompletionService>();
var response = await chatClient.GetChatMessageContentAsync("What was a positive news story from today?", executionSettings, kernel);
```
#### Web search with user location
To refine search results based on geography, you can specify an
approximate user location using country, city, region, and/or timezone.
The *city* and *region* fields are free text strings, like Minneapolis
and Minnesota respectively.
The *country* field is a two-letter *[ISO country
code]*(https://en.wikipedia.org/wiki/ISO_3166-1), like US.
The *timezone* field is an [IANA
timezone](https://timeapi.io/documentation/iana-timezones) like
America/Chicago.
```
var executionSettings = new OpenAIPromptExecutionSettings
{
WebSearchOptions = new {
user_location = new {
type = "approximate",
approximate = new {
country = "GB",
city = "London",
region = "London",
}
},
}
};
var chatClient = kernel.GetRequiredService<IChatCompletionService>();
var response = await chatClient.GetChatMessageContentAsync("What are the best restaurants around Granary Square?", executionSettings, kernel);
```
#### Specify context size
When using this tool, the *search_context_size* parameter controls how
much context is retrieved from the web to help the tool formulate a
response. The tokens used by the search tool do not affect the context
window of the main model specified in the model parameter in your
response creation request. These tokens are also not carried over from
one turn to another — they're simply used to formulate the tool response
and then discarded.
*Choosing a context size impacts:*
Cost: Pricing of our search tool varies based on the value of this
parameter. Higher context sizes are more expensive. See tool pricing
[here](https://platform.openai.com/docs/pricing).
Quality: Higher search context sizes generally provide richer context,
resulting in more accurate, comprehensive answers.
Latency: Higher context sizes require processing more tokens, which can
slow down the tool's response time.
Available values:
- *high*: Most comprehensive context, highest cost, slower response.
- *medium* (default): Balanced context, cost, and latency.
- *low*: Least context, lowest cost, fastest response, but potentially
lower answer quality.
```
var executionSettings = new OpenAIPromptExecutionSettings
{
WebSearchOptions = new {
search_context_size = "low"
}
};
```
### 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 😄
---------
Co-authored-by: Dat Hoang Quoc <DAT@jsworldmedia.com>
Co-authored-by: Roger Barreto <19890735+RogerBarreto@users.noreply.github.com>
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Mar 20, 2025
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As agreed offline, let's merge #11095 instead |
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