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Author SHA1 Message Date
SergeyMenshykh b39d95a344 Python: [Breaking] Remove unsupported service auth mode from Copilot Studio agent (#14306) 
### Motivation and Context

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

### Description

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

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

### Contribution Checklist

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

---------

Copilot-Session: 25dd6e2a-f759-4148-a630-40110e90eff2
 2026-08-20 11:36:32 +01:00
SergeyMenshykh 3da48a3d01 Python: [Breaking] Add MCP tool approval callback for Azure AI Agent (#14210) 
## Summary
- Add an Azure AI Agent callback for MCP tool approval requests.
- Route MCP tool approval submissions through a shared helper in thread
actions.
- Add unit coverage for approval, denial, callback failures, and
per-call decisions.

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

---------

Copilot-Session: 3e190979-228b-4a82-8e63-5ad14bd4879f
 2026-07-28 18:15:13 +00:00
SergeyMenshykhCopilotEvan Mattson
 		3df33f7862 Python: [Breaking] Update runtime handling (#14135) 
This PR updates Python runtime handling and related tests.

---------

Co-authored-by: Copilot <[email protected]>
Co-authored-by: Evan Mattson <[email protected]>
 2026-07-07 03:22:20 +00:00
Evan MattsonMAF Dashboard BotCopilot
 		0f322bcc48 Python: Improve prompt-template msg serialize and sample usage (#13738) 
### Motivation and Context

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

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### Description

Prompt template message serialize improvements.

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- [ ] I didn't break anyone 😄

---------

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

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

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### Description

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

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raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄
 2026-03-18 10:42:08 +00:00
Tao ChenandEvan Mattson 5c891d1769 Python: Add support to new openai text to image model (#13651) 
### Motivation and Context

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Dall-e-3 and Dall-e-2 have been deprecated. The newer gpt-1-image model
returns base64 strings.

### Description

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Return url if set, otherwise return the base64 string.

### Contribution Checklist

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- [ ] I didn't break anyone 😄

---------

Co-authored-by: Evan Mattson <[email protected]>
 2026-03-13 08:31:46 +00:00
Tao Chen d5c2b9d889 Python: Improves the robustness of filename handling (#13643) 
### Motivation and Context

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

### Description

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

### Contribution Checklist

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raises no violations
- [x] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄
 2026-03-12 17:02:02 +00:00
Evan Mattson 429dd1c4c0 Python: support (Azure) OpenAI realtime audio models (#13291) 
### Motivation and Context

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

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

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### Description

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

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### Contribution Checklist

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raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄
 2026-02-28 09:01:03 +09:00
Tao Chen d84363f477 Python: Migrate to new Google GenAI SDK (#13371) 
### Motivation and Context

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Closes #12970, #13352

### Description

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

### Contribution Checklist

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raises no violations
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- [ ] I didn't break anyone 😄
 2025-11-24 21:53:57 +00:00
Nico MöllerandEvan Mattson 145ad9bfd2 Python: Upgrade Onnx Connector to use 0.9.0 (#13162) 
### Motivation and Context

Fixes : #13001 

### Description

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

This PR adds the following functionalities:

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

### Samples

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

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


### Contribution Checklist

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- [x] The code builds clean without any errors or warnings
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raises no violations
- [x] All unit tests pass, and I have added new tests where possible
- [x] I didn't break anyone 😄

---------

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

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

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

### Description

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### Contribution Checklist

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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 😄
 2025-10-30 15:24:16 +00:00
Soumili Nandi 61d3e6ee8d Python: Introduce NvidiaChatCompletion AI Connector (#12952) 
### Motivation and Context

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

### Description

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



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

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raises no violations
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- [x] I didn't break anyone 😄
 2025-09-15 23:26:38 +00:00
Tao Chen d7db35dc47 Python: Fix Azure AI Inference connector model_extras duplication (#13066) 
### Motivation and Context

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Addresses #13005 

### Description

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

### Contribution Checklist

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

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

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### Description

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

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### Contribution Checklist

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- [X] The code builds clean without any errors or warnings
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Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
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raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [X] I didn't break anyone 😄
 2025-09-01 02:35:56 +00:00
Evan Mattson 86b10b95d2 Python: provide AzureAIAgent thread msg id during streaming (#13032) 
### Motivation and Context

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

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### Description

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

Sample output looks like:

```
Sample Output:

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

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### Contribution Checklist

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- [X] The code builds clean without any errors or warnings
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- [X] I didn't break anyone 😄
 2025-08-30 10:05:55 +00:00
Christian GlessnerEvan MattsonEvan Mattson
 		5e50e190c4 Python: Add reasoning support for OpenAI Responses Agents (GPT-5, o4-mini, o3) (#12881) 
## Summary

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

Fixes #12843

## Changes

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

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

## Features

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

## Usage Example

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

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


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

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

---------

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

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

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

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

This enforces stricter, but more secure template rendering rules.

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

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

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

### Contribution Checklist

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

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

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

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

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

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

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

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

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

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### Description

Update sample.

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 2025-08-14 15:13:10 +00:00
Tao ChenandDmytro Struk 8336c320d9 Python: Add bedrock model provider parameter (#12853) 
### Motivation and Context

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Fixes #12833 

### Description

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


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- [x] I didn't break anyone 😄

---------

Co-authored-by: Dmytro Struk <[email protected]>
 2025-08-05 00:43:00 +00:00
Nava-7andEvan Mattson c16db27622 Python: Update README.md (#12737) 
Update links due to renamed files

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- [x] I didn't break anyone 😄

---------

Co-authored-by: Evan Mattson <[email protected]>
 2025-08-04 07:22:25 +00:00
Eduard van Valkenburg c79f5a5c63 Python: improved MCP connect and additional samples (#12696) 
### Motivation and Context

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


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

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

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### Description

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

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 2025-07-18 07:08:00 +00:00
Evan Mattson 9e3cdffc6b Python: Improve AzureAIAgent get thread msg handling. (#12535) 
### Motivation and Context

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

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

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

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

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### Description

- Closes #12435

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

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

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

### Description

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

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

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

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Sample on how to use Foundry Local with SK.

### Description

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- [x] I didn't break anyone 😄
 2025-06-19 08:18:18 +00:00
Tao Chen 9b8f8e22c3 Python: Correct chat completion agent history truncation samples (#12474) 
### Motivation and Context

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

### Description

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Update the samples.


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- [ ] I didn't break anyone 😄
 2025-06-13 20:11:00 +00:00
Evan Mattson 4b23389f71 Python: Emit token usage with streaming chat completion agent. (#12416) 
### Motivation and Context

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

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### Description

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

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 2025-06-09 23:12:05 +00:00
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.

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### Description

Fixes the broken OpenAPI sample.

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- [X] I didn't break anyone 😄
 2025-06-09 21:33:06 +00:00
Christian GlessnerandEvan Mattson 0e7556e112 Python: Add file handling support to BinaryContent for OpenAI Responses API (#12258) 
## Summary

Enhances `BinaryContent` to support file handling for OpenAI Responses
API, enabling file uploads through the responses agent while maintaining
a provider-agnostic design.

  ## Changes

  ### BinaryContent Enhancements
- **Add `can_read` property**: Indicates whether content has readable
data available
- **Add `from_file()` class method**: Creates BinaryContent instances
from file paths with automatic base64 encoding
- **Fix Unicode handling**: Prevents decode errors when processing
binary files (PDFs, images, etc.)

  ### OpenAI Responses Agent Integration
- **Add BinaryContent support**: Pattern matching case for file handling
in `responses_agent_thread_actions.py`
- **Correct OpenAI API format**: Uses proper `filename` and `file_data`
structure with data URI format
- **UUID-based filenames**: Generates appropriate filenames with
mime-type extensions
- **Provider-specific mapping**: File format conversion happens only in
OpenAI agent code

  ### Testing
- **Test coverage**: New tests for `can_read`, `from_file()`, and binary
data handling
- **Unicode error prevention**: Specific test for binary PDF-like
content
- **Base64 encoding verification**: Ensures proper data format for API
compatibility

  ## Design Principles

- **Provider-agnostic**: BinaryContent remains completely generic with
no OpenAI-specific dependencies
- **Clean separation**: OpenAI format mapping isolated to OpenAI agent
files
- **No FileContent class**: Enhances existing BinaryContent instead of
introducing new types
- **Follows existing patterns**: Similar approach to ImageContent and
TextContent handling

  ## Usage Example

  ```python
 response = await self.agent.get_response(
        messages=ChatMessageContent(
            content="Analyse PDF",
            role=AuthorRole("user"),
            items=[BinaryContent.from_file(file_path=c":/test.pdf")],
        )
    )

Co-authored-by: Evan Mattson <[email protected]>
 2025-06-09 21:15:39 +00:00
Tao Chen 2f84e5d1bf Python: Add chat completion agent code interpreter sample (#12393) 
### Motivation and Context

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Closing #10962 

### Description

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1. Add a sample to demonstrate how to create a chat completion agent
with code interpreter capabilities using the Azure Container Apps
session pool service.
2. Fix a bug that cause the session tool to throw because the upload API
doesn't return the file uploaded.
3. Modify unit tests accordingly.

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- [x] I didn't break anyone 😄
 2025-06-06 18:13:44 +00:00
Tao Chen c822511f2c Python: Add special notes to samples that are still using AgentGroupchat (#12377) 
### Motivation and Context

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As we move away from `AgentGroupChat` to the new orchestrations, we want
to make sure it's clear to developers getting started with SK are aware
of the changes.

### Description

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We are including a special note to all the samples that use
`AgentGroupChat` to inform developers that this feature is no longer
maintained and they should consider using `GroupChatOrchestration`
instead.

We are keeping the samples for now so that developers can still refer to
them and we don't break any external links to these samples, but we want
to make sure they are aware of the changes and can migrate to the new
orchestrations.


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 2025-06-04 22:15:44 +00:00
Evan Mattson fb0e418a7c Python: Fix for AzureAIAgent streaming func call invocations. Other fixes/improvements for tool call content types, and logging. (#12335) 
### Motivation and Context

The AzureAIAgent streaming function call invocation is broken when
handling more than one required function call from the service. There is
nested logic to handle passing the tool calls back to the service
because it requires one to pass in a handler.

In this PR, we're now controlling everything from the main loop and are
passing back the handler as the event stream for further processing.
This does require some logic to determine if we have an initial async
context manager (based on the first call to create the run stream) or if
we're now using the handler from submitting tool calls. We can now see
that when we have multiple functions involved, we are able to get the
results as we expect:

```
Sample Output:

# User: 'What is the price of the special drink and then special food item added together?'
Function Call:> MenuPlugin-get_specials with arguments: {}
Function Result:> 
        Special Soup: Clam Chowder
        Special Salad: Cobb Salad
        Special Drink: Chai Tea
        for function: MenuPlugin-get_specials
Function Call:> MenuPlugin-get_item_price with arguments: {"menu_item": "Chai Tea"}
Function Call:> MenuPlugin-get_item_price with arguments: {"menu_item": "Clam Chowder"}
Function Result:> $9.99 for function: MenuPlugin-get_item_price
Function Result:> $9.99 for function: MenuPlugin-get_item_price
Function Call:> MathPlugin-Add with arguments: {"input":9.99,"amount":9.99}
Function Result:> 19.98 for function: MathPlugin-Add
# AuthorRole.ASSISTANT: The price of the special drink, Chai Tea, is $9.99 and the price of the special food 
    item, Clam Chowder, is $9.99. Added together, the total price is $19.98.
```

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### Description

Fix handling multiple function calls for the streaming AzureAIAgent.
- Fixes a missing `quote` from the url citation for streaming annotation
content
- Shows the correct way to retrieve Bing Grounding tool calls in the two
concept samples.
- Adds handling for tool content content for OpenAPI plugins.
- Adds logging for streaming agent invocation tool calls.
- Relaxes the handling of the `FunctionResultContent` id attribute to be
`str | None` similar to that of `FunctionCallContent`. The type hints
for `id` have always been `str | None`, but the actual type hint on the
attribute has been `str`. We don't always get a `FunctionResultContent`
id from the Azure Agent Service during streaming invocations - message
addition via the overide `__add__` method still work properly.
- Move the AzureAIAgent pkg dependencies to be installed by default,
instead of requiring the `azure` extra.
- Closes #12312
- Closes #12328
- Closes #12331
- Closes #12324

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- [X] I didn't break anyone 😄
 2025-06-03 01:11:56 +00:00
Evan Mattson 82229cecc3 Python: Improve Python README (#12289) 
### Motivation and Context

The Python README file is a bit stale, and lacking current content
related to agent framework and directly calling the AI service (not
always needing to invoke via the kernel). Additionally, there are links
to samples/notebooks that are relative and thus not resolving from pypi.

The [`ALL_SETTINGS.md`
guide](https://github.com/microsoft/semantic-kernel/blob/main/python/samples/concepts/setup/ALL_SETTINGS.md#semantic-kernel-settings)
is also missing the Agent Framework settings used. Adding those in this
PR.

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### Description

Improve the README to be more relevant.
- Closes #12286

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 2025-05-28 23:34:20 +00:00
Evan Mattson ff1997047d Python: Support Declarative Spec for OpenAIAssistantAgent & OpenAIResponsesAgent (#12247) 
### Motivation and Context

This PR builds on the initial work/abstractions from #11982. The
`AzureAssistantAgent` / `OpenAIAssistantAgent` as well as the
`AzureResponsesAgent` / `OpenAIResponsesAgent` now support declarative
specs. Several examples on how to declare the spec are shown in the
respective dirs in `samples/concepts/agents`, as well as a simple
getting started example for each agent type.

To further simplify working with these two agents, the
`setup_resources()` methods for each agent type have been marked with a
deprecation tag. The new method to use is
`OpenAIAssistantAgent.create_client()` or
`OpenAIResponsesAgent.create_client()`. Further, when one needs to
access the underlying setting's, it's simple to do so with a settings
object and accessing the attribute.

In the previous PR for the AzureAIAgent, it lacked support for
templating - this is included in this current PR.

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### Description

Bring in support for the declarative single agent spec for these agent
types.
- Add samples
- Add unit tests
- Add support for prompt templates for all current agent types
- Closes #11979

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 2025-05-26 05:02:59 +00:00
Evan Mattson c084b067de Python: Support structured outputs with Azure AI inference chat completion. (#12183) 
### Motivation and Context

The Azure AI inference SDK released support for structured outputs for
chat completions (for models that support it). We had not brought this
into SK. This PR adds functionality and the ability to run the
structured output samples that exist today.

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### Description

Adds functionality to handle structured outputs for the Azure AI
Inference Chat Completion calls.
- Fixes a bug within AzureAIInferenceChatCompletion where the wrong
isinstance check type is used. This prevented adding tool calls during
streaming invocation. Also properly add the `ai_model_id` from the
connector during message construction during streaming invocation,
- Adds unit tests for AzureAIInferenceChatCompletion structured outputs
- Closes #11952

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- [X] I didn't break anyone 😄
 2025-05-21 09:29:03 +00:00
Evan MattsonandTao Chen c64e51c40e Python: Update the AzureAIAgent packages, types, and APIs based on Azure SDK's new code (#12084) 
### Motivation and Context

The Azure AI Agent Service is moving to GA soon. As part of that,
they've made several changes in the underlying APIs, which require the
use of new packages, updated type imports and some new underlying APIs.
This PR updates the AzureAIAgent to use the latest Azure SDK's new code.

- The client's connection string has been replaced with an endpoint.
- The `AzureAIAgentSettings`'s `model_deployment_name` was updated to
`deployment_name`.
- Tools are now imported from `from azure.ai.agents.models` instead of
`from azure.ai.projects.models`.
- Declarative spec handling for AzureAIAgent was updated based on the
new APIs.
- Unit tests were updated.

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### Description

Update the AzureAIAgent related code, samples and tests based on the
Azure SDK's latest APIs.
- Closes #12177 

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---------

Co-authored-by: Tao Chen <[email protected]>
 2025-05-19 23:43:40 +00:00
Eduard van Valkenburg 03f0aba633 Python: added WebRTC support for Azure OpenAI Realtime (#12078) 
### Motivation and Context

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Added support for WebRTC for Azure OpenAI Realtime models.

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 2025-05-19 18:24:34 +00:00
Evan Mattson d7c2489a24 Python: Add MultiAgent Orchestration to README. (#12073) 
### Motivation and Context

The new multi-agent orchestration samples are missing from the getting
started with agents README. Add them in with their descriptions. Also,
remove two unused intermediate message callback lists from two samples
that are no longer used.

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### Description

Add samples to README. Clean up some samples.

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 2025-05-15 17:14:30 +00:00
Eduard van Valkenburg 6115e8d7dc Python: fixes and updates for MCP (#12039) 
### Motivation and Context

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Removes the two surpressed calls for extra info out of a MCP server,
since they seemed to hang every now and then.
Updated the package version spec
Added one of the samples as a integration test
Added:

- load_tools flag on the constructor, default = true
- load_prompt flag on the constructor, default = true
- request_timeout param, optional, default None

### Description

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- [x] I didn't break anyone 😄
 2025-05-14 22:12:34 +00:00
Evan Mattson ea3215ebb7 Python: Support Declarative Agent Spec for ChatCompletionAgent & AzureAIAgent (#11982) 
### Motivation and Context

This is the first installment of a series of PRs related to adding
single agent declarative spec support.

SK .NET has had support for single agent declarative specs for a bit
now, and Python needs the functionality as well. This PR adds the core
abstractions and functionality to be able to define agents via a
declarative yaml spec.

Declarative specs require the use of a kernel, and if in the case of
function calling, require that any plugins defined in the spec already
be present in the kernel.

For naming, there are placeholder names that are camel case. This needs
to be the case so it can match .NET.

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### Description

Provide declarative spec support for ChatCompletionAgent and
AzureAIAgent
- Adds many samples to show the use of declarative specs to handle
various AzureAIAgent + ChatCompletionAgent tools/plugins.
- Closes #11978

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- [X] I didn't break anyone 😄
 2025-05-13 23:14:36 +00:00
kanchi 904c10a11c Python: Add support for MCP Streamable HTTP transport (#12001) 
### Motivation and Context

Added support for the new Streamable HTTP transport introduced in the
`2025-03-26` revision of MCP, which replaces SSE.

### Description

1. Bump the `mcp` library version to `1.8`
2. Introduced a new `MCPStreamableHttpPlugin` class

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 2025-05-13 08:31:32 +00:00
Evan Mattson 4724dbc8f3 Python: Fix AzureAIAgent intermediate message ordering for invoke and invoke_stream (#12005) 
### Motivation and Context

This PR fixes a core issue in `AzureAIAgent` where `FunctionCallContent`
and `FunctionResultContent` messages were not being emitted in the
correct order during `invoke()` and `invoke_stream()` execution.

- `invoke_stream`: tool messages are now drained and emitted after each
streamed assistant chunk, preserving causal ordering (tool call ->
result -> assistant reply).
- `invoke`: tool messages are emitted via callback immediately after the
non-streaming response is received, ensuring they precede the final
assistant message if applicable.

### Description

Updated samples to better show how the callbacks are used to receive the
intermediate messages in the proper order.
- Added unit tests to ensure proper coverage and message ordering.
- Closes #11999

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 2025-05-12 22:58:06 +00:00
Evan Mattson b07454aff8 Python: Fix OpenAIAssistantAgent/OpenAIResponsesAgent intermediate message ordering for invoke and invoke_stream (#12008) 
### Motivation and Context

This PR fixes a core issue in `OpenAIAssistantAgent` and
`OpenAIResponsesAgent` where `FunctionCallContent` and
`FunctionResultContent` messages were not being emitted in the correct
order during `invoke()` and `invoke_stream()` execution.

- `invoke_stream`: tool messages are now drained and emitted after each
streamed assistant chunk, preserving causal ordering (tool call ->
result -> assistant reply).
- `invoke`: tool messages are emitted via callback immediately after the
non-streaming response is received, ensuring they precede the final
assistant message if applicable.

### Description

Updated samples to better show how the callbacks are used to receive the
intermediate messages in the proper order.
- Added unit tests to ensure proper coverage and message ordering.
- Closes #12007

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 2025-05-12 22:45:43 +00:00
Evan Mattson fb2fc6b30c Python: Fix ChatCompletionAgent intermediate message ordering for invoke and invoke_stream (#12000) 
### Motivation and Context

When using the `on_intermediate_message` callback, we are returning
messages to the caller in an incorrect order. While using function
calling, the order is:

1. Provide user input to agent that requires a tool call
2. FunctionCallContent chunks returned via callback
3. FunctionResultContent returned via callback
4. Final output (StreamingTextContent/TextContent) from agent returned
via invoke_stream/invoke

What we are really seeing is:
1. Provide user input to agent that requires a tool call
2. Final output (StreamingTextContent/TextContent) from agent returned
via invoke_stream/invoke
3. FunctionCallContent chunks returned via callback
4. FunctionResultContent returned via callback

The callback needs a bit of adjusting -- for the streaming case it must
emit messages as part of handling the AsyncGen response_list loop.

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### Description

Fix the ordering of the intermediate callback so messages aren't
received out of order.
- Adds unit tests to check message order
- Adjusts some samples
- Closes #11998 

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 2025-05-12 07:45:08 +00:00
Evan Mattson d266ac5db0 Python: Properly surface streaming code responses and handle Bing Grounding for AzureAIAgent (#11850) 
### Motivation and Context

The AzureAIAgent streaming event path for handling streaming code output
as well as both streaming and non-streaming Bing Grounding tool calls
were missing in the current implementation. This PR adds handling for
those two scenarios.

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### Description

Updates to allow for proper handling of streaming code using the
AzureAIAgent
- code_interpreter: note that the code interpreter tool call is handled
as returning `StreamingTextContent` with the `metadata` dict configured
with `{"code": True}`.
- bing_grounding: support for the Bing Grounding Tool is added. There is
a current issue with streaming events and the Bing Grounding tool - the
`requesturl` as part of the tool call is coming back empty. This issue
has been raised with the appropriate team. Both streaming and
non-streaming do properly return the `StreamingAnnotationContent` or
`AnnotationContent` respectively.
- Samples were added to show interaction with the AzureAIAgent and these
tools, some also showing how to use the `on_intermediate_message`
callback.
- Fixes #11847

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 2025-05-06 20:28:29 +00:00
Evan Mattson 30d2b0802a Python: Support Process State Management (#11637) 
### Motivation and Context

SK Python processes have been missing support to be able to serialize
and deserialize JSON state for a process and its steps. This PR brings
in the functionality to allow the developer to do so. The
`getting_started_with_processes` step03 has been update to reflect this
latest functionality. It is possible to dump a JSON state to a file, and
reload the state to continue running the process.

State metadata that handles the version for steps is managed via a
decorator:

```python
@kernel_process_step_metadata("CutFoodStep.V1")
class CutFoodStep(KernelProcessStep):
    class Functions(Enum):
        ChopFood = "ChopFood"
        SliceFood = "SliceFood"
```

If no decorator/state is supplied the step will be built with a default
state version of "v1" which aligns with .Net.

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### Description

Support state and versioning management for Python processes.
- Update samples to reflect changes.
- Closes #9584

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 2025-04-28 22:51:11 +00:00
Eduard van Valkenburg 9febe95fbb Python: updated mixed chat sample (#11624) 
### Motivation and Context

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Updated the mixed_chat sample to use Azure AI Agents instead of
assistant api and used the newest syntax for the chat completion agent

### Description

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- [x] I didn't break anyone 😄
 2025-04-22 07:31:54 +00:00
NEWTON MALLICKandEvan Mattson 8edcdb3ab0 Python: Added Brave search capability in SK(python) based on PR #9632 (#11531) 
### Motivation and Context

Added BRAVE SEARCH CAPABILITIES in Semantic Kernel Python based on PR
#11308 .

### Description

- Introduce BraveConnector & BraveSearch for Brave Search API
integration,
- BraveSettings and response models were added, respectively.
- Add unit Tests  

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---------

Co-authored-by: Evan Mattson <[email protected]>
 2025-04-21 10:16:31 +00:00
Eduard van Valkenburg 5cbd980f55 Python: create MCP server from agent (#11506) 
### Motivation and Context

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This PR adds a second create_mcp_server function that takes in a list of
functions/plugins/agents, and can thus easily be used to create a MCP
server based on a Agent
Adds a sample with a Azure AI Agent.
Partial for #11463 

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 2025-04-17 05:29:11 +00:00