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7
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Eduard van Valkenburg
|
6751f9d819 |
Python: Updated plugins (#5827)
### 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?
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The loading of plugins and functions into Kernel was not fully
consistent and clear, this is now simplified.
Adding a plugin can now be done in two ways:
- multiple: `kernel.add_plugins[plugin1, plugin2]`
- single plugin: `kernel.add_plugin(plugin)`
- if the plugin here is a class, with methods that have the
kernel_function decorator then that is parsed into a plugin
Adding a function can now be done in three ways:
- multiple: `kernel.add_functions([func1, func2]` or
`kernel.add_function({'func1': func1})`
- single: `kernel.add_function('plugin_name', func1)`
- from a prompt: `kernel.add_function(function_name='func1',
prompt='test prompt', ...)`
In other words, all the different methods that were available have been
simplified, these methods also return the created plugin (or updated
plugin for the `add_functions` method. The `add_function` (singular)
method has a parameter `return_plugin` to control whether you get the
created or updated plugin, instead of the created function.
**An important callout:**
One big internal change that this introduces is that a function that
gets added to a plugin (new or existing) is automatically copied, the
metadata is deep-copied and the plugin_name in the metadata is updated,
so this sequence is valid now:
```python
@kernel_function(name='test')
def f(...):
etc
func = KernelFunctionFromMethod(method=f)
func2 = kernel.add_function('plugin', func)
assert func != func2
```
Also closes: #5855
### Description
<!-- Describe your changes, the overall approach, the underlying design.
These notes will help understanding how your code works. Thanks! -->
Removed KernelPluginCollection
Updated KernelPlugin
added from_... method to load from different sources
Updated KernelFunctionFromPrompt
added from_yaml and from_directory methods.
Added and updated tests to 99% coverage of KernelPlugin and
KernelFunctionFromPrompt
### 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 😄
|
||
|
Evan Mattson
|
3553d623b1 |
Python: Fix create func from prompt missing args (#5339)
### Motivation and Context There were missing function_name and plugin_name args from the create function from prompt method in several kernel examples. <!-- 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 Adding in the missing parameters. <!-- 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 😄 |
||
|
Evan Mattson
|
8b16af69c0 |
Python: Remove the memory tied to the kernel. Update kernel examples and notebooks. (#5143)
### Motivation and Context As we move toward v1, it is necessary to remove the single kernel memory attribute so that memory connectors can be handled via plugins. This change also refactors the `import_plugin` method name to be similar with dotnet as `import_plugin_from_object`, and introduces a simple `kernel.invoke_prompt` method. <!-- 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 Updates are: - The memory connector is now passed to the `SemanticTextMemory` class, along with the embedding generator. This allows the user to add memory to multiple plugins/services as needed. Closes #4632 - Kernel Examples and Notebooks were updated to reflect these changes. Now using Service Enum for all notebooks. Closes #4557 - There were planners using memory related to the kernel, to store the functions, and many of these planners are non-existent in dotnet's v1 SDK. Python has pending work to update the planner/remove deprecated planners before getting to v1. - A Kernel method called `invoke_prompt` was introduced to invoke a simple prompt, and return the `FunctionResult` when complete. - All unit/integration tests are passing. <!-- 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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|
5817c2b927 |
Python: major features for the Kernel Arguments, Function Result and new Prompt Templating (#5077)
### 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. --> Major work to replace the context with Kernel Arguments on the front-end and Function Results on the back. Updated the function decorator to a new approach, in line with dotnet. Revamps the way function are called, allowing native functions to be completely ignorant of SK, other then the decorator. This also moves things into the new folder structure in sync with dotnet. ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> Adds: - KernelArguments, a dict-like class that replaces the variables in KernelContext. Closes #4565 - FunctionResult, a class to hold the results of function executions, includes the function, the value and metadata, as well as two convenient function to get the value out of it (str and get_inner_content) the first is generic, the second specifically for KernelContent responses (from AI services). - AI Service Selector class, has a default, which is based on the order in the arguments followed by the order in the functions, can be overridden to implement your own strategy. Closes #4631 - Introduces ChatHistory and refactors the PromptTemplateConfig. Closes #4856, #4630 - Improves parsing of templates, will now all validate during creation and throw an error then, instead of some that do not check for validaty until used. - Introduces named_args block and thereby the ability to have multiple arguments for a function call in a template. Closes #5003 Updates: - kernel_function decorators, the parameter decorator was removed and instead we now use Annotated to add a description of a field and we get the type and required from the function definition. - core plugins, use the new approach to kernel_function decorators. - planners, template engines have all been updated to use the kernel and kernelarguments instead of Context. - Events have been updated, now use kernelarguments and function_result - Tokenizers support for named_args and improvements on parsing and checking. - Kernel examples and notebooks to use the latest code. - All unit and integration tests. There is more code coverage now than before. Removed: - kernelContext - kernel_function_parameter_decorator - delegate handling code for native functions - file_io_plugin and tests - SemanticFunctionConfig - ChatPromptTemplate ### 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]> Co-authored-by: Evan Mattson <[email protected]> Co-authored-by: Evan Mattson <[email protected]> |
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Evan Mattson
|
7170f0d6a1 |
Python: Remove sync function invoke. Update other code to use async invoke. (#4796)
### Motivation and Context Completes #4794. Most of SK Python is written with async code; however, there were some code paths that masked the underlying async code and made it look like a sync function invoke. In reality, asyncio spun up event loops and attempted to manage them properly. This becomes tricky when running a Jupyter notebook as they have their own event loop. <!-- 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 removes the ability to call a kernel function synchronously. Since the majority of the code base is written with async methods, and to match dotnet, which is async, we're removing the sync function invoke and its dependent code. Some Planners were also run synchronously -- these were updated to run asynchronously. Kernel examples, notebooks, docs, and tests were updated accordingly. <!-- 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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Julio Carlos MenendezandEvan Mattson
|
d97f9536c4 |
Python: Removes the _async suffix where is not needed (#4735)
### Motivation and Context Delete all *_async where *_sync doesn't exist to make the library more Pythonic. Fixes #4629 ### 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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Evan MattsonandEvan Mattson
|
674af5468d |
Python: Rename skills to plugins. Update prompt template config to use execution settings to align with dotnet. (#4595)
### Motivation and Context To better align with SK dotnet v1, Python skills have been renamed to plugins. This removes the root samples skills directory as dotnet supports the plugins and their configs. This the beginning of more work to consolidate other files/names, per the backlog. I've run several greps for files or file names containing "skill" (case insensitive), and no results appear. Do alert if you find anything else that includes "skill." Fixes #3319 <!-- 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 is a large, breaking change PR as the replacement of "skills" to "plugins" affects many files. It was difficult to break this up into smaller chunks without leaving the SK Python repo in a bad state for some time. Other updates include: - Prompt template has been updated to use `execution_settings`, which aligns with dotnet, from the previous `completion` that Python used. - AzureOpenAI/OpenAI function calling has been updated to match the current versions of tools/tool_choice. Parsing messages in the open_ai utils respects this as it now looks for tool_calls and it configures the function_call with the id (new), name, and argument). - File renames, where the filename used to contain "skill" will look like new code, but it's the same code, just with "plugin" in the name. - Kernel examples and notebooks have been tested and are working. Unit tests and integration tests are passing. <!-- 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 😄 --------- Co-authored-by: Evan Mattson <[email protected]> |