### Motivation and Context
It is confusing to have multiple skfunction invoke_* calls. This PR
combines invoke and invoke_with_vars to enable calls with the input
pattern: with SKContext, or with SKContextVariables.
### Description
- Removed `sk_function` methods `invoke_with_vars` and
`invoke_with_vars_async`
- Added the following optional paramters to `sk_function` methods
`invoke_` and `invoke_async`: `variables` and `memory`
- Added log warnings for when an both SKContext and variables/memory are
passed to `invoke` methods - this design ensures that the SDContext and
it's associated variables and memory are prioritized
- Updated tests and notebooks where applicable
### Motivation and Context
HttpSkill python version
### Description
- Porting the HttpSkill from C# to Python.
- Adding corresponding unit tests.
Co-authored-by: Abby Harrison <[email protected]>
### Motivation and Context
To make the Python SK more pythonic, combined all kernel.run_* methods
into a single method with optional parameters.
### Description
- Removed `kernel.run_on_vars_async()`
- Removed `kernel.run_on_str_async()`
- Added `SKContext`, `ContextVariables`, and string params to
`kernel.run_async()`
- Moved `run_on_vars_async()` logic to `run_async()` method
- Arranged method params so that required params come before optional
params.
- Updated tests and notebooks where applicable.
### Motivation and Context
It's better to avoid nested classes in Python, so in SKFunction, I move
RunThread out of the class. RunThread is needed because we need to wait
for the result of an async function that's being run in an existing
event loop, and subclassing Thread seems to be the best way to do that.
This also adds python-test.yml to the github workflows.
For python-test.yml:
- In this PR, the checks were run because python files were changed.
- In this test PR: https://github.com/mkarle/semantic-kernel/pull/2, the
python tests were skipped because files in the python directory were not
changed.
### Motivation and Context
This PR makes creating a kernel instance more pythonic. The builder
pattern is removed and the kernel is constructed using Kernel(...).
Work originally started with #137
### Description
- Removed kernel_builder.py.
- Instance creation pattern `kernel = sk.create_kernel() -> kernel =
sk.Kernel()`
- For notebook 6, there is no need to create a separate kernel for the
GitHub files. Changed to use a separate collection.
Co-authored-by: Devis Lucato <[email protected]>
* Add python getting started notebook
* Fix notebooks usage of Azure text completion
* Fix bug with skills definition
* Update READMEs
* New release version 0.2.2
READMEs and examples are out of date and showing incorrect code. There
are also a few bugs in the SKFunction blocking simpler syntax.
Extend SKFunction to allow synchronous calls and have simpler syntax
when async is not required.
* Update homepage README, moving all Python examples under python/README
* Make SKFunction callable as per v0
* Fix bugs in SKFunction
* Fix examples using realistic code
* Allow to use functions synchronously
AAD tokens offer greater authentication security and is used by several products.
Add support for Azure Active Directory auth for the `Azure*` backends.
### Motivation and Context
In an effort to make the Python port more idiomatic, let's remove the
`Verify` class and the `./diagnostics` sub-module. There are many more
follow-on tasks to do here, but this is a good start (and already a
large enough change).
### Description
This PR does the following:
1. Removes the `Verify` class, and re-writes all instances of `Verify.*`
2. Adds a `validation.py` in the `./utils` sub-module to hand some of
the more complex cases from `Verify` (checking that skills/functions/and
function params have valid names)
3. Removes the rest of the `./diagnostics` sub-module (w/ a longer-term
goal of removing all/most of our custom exception classes and, instead,
using appropriate built-in error classes)
### Motivation and Context
The `python-preview` branch is under active development and many
docs/tests/examples are getting a bit out of sync. There are also a few
small cleanup chores/refactors to make _usage_ easier (e.g., to make
examples cleaner). I've grouped these small fixes (plus a few bug fixes)
into this "cleanup" PR.
### Description
This PR does the following:
1. Updates the out-of-date example in `README.md`
2. Fixes all 5 of the notebooks we support right now (1,2,3,4, and 6;
notebook 5 is planner, I've blanked out most of the code there so we
don't confuse people, especially as the planner API is changing)
3. Fixes a bug w/ `stop_sequences` in `(Azure)OpenAITextCompletion`
4. Fixes a bug introduced in our upgrades to the embeddings cosine-sim
check (we should add more thorough tests here)
5. Cleans up tests
6. Ensures end-to-end tests are all runnable
7. Fixes up the `kernel_extensions` to work more naturally (so that end
users can use them directly on the `kernel` object and get good
type-hinting)
### Motivation and Context
Right now, there are lots of Config classes in SK. This doesn't feel
very "pythonic" and can be a bit confusing at times. To reduce the
amount of indirection, this PR removes several config classes from the
Python port.
NOTE: this PR is also critical preparation for a large change to re-sync
with how C# SK handles multi-modality. I have changes ready for adding a
`./connectors` dir and syncing with the Text/Chat/Image/Embedding
support, but there's a few "prep" PRs I need to get through first.
### Description
This PR makes the following changes:
1. We remove the `(Azure)OpenAIConfig` classes (simplifying the code
related to creating/managing backends)
2. We remove the `./configuration` sub-directory and move the
`KernelConfig` class to the module's root dir (this mirrors the C#
version)
3. We re-tool the `KernelConfig` class to behave similarly to the
current C# version (again, this is prep for later changes RE
multi-modality)
4. We make corresponding updates across the code/tests now that we've
removed some config classes
In future PRs, it'd be great to also simplify:
1. `(Chat|Completion)RequestSettings`
2. `(ReadOnly)SkillsCollection` and related classes
3. Take a hard look at `ContextVariables` and `SKContext` (maybe
`ContextVariables` is just a `dict` in SK python)
### Motivation and Context
This PR fixes#235 and adds a test for the functionality. This is ahead
of the planning skill.
### Description
1. Fix to fix the typo in the `from_dict()` method in
`prompt_template_config.py`
2. Add assignment back to skill config so results from JSON aren't
discarded in `import_semantic_skill_from_directory.py`
3. Add tests
### Motivation and Context
We recently merged an upgrade to the `PromptTemplateEngine`, let's make
the rest of the tests consistent with the directory structure used in
that PR.
### Description
This PR does three (small) things:
1. Makes the `./tests` directory have consistent structure
2. Re-names some of the "tests" that were at the top-level of the
`./tests` dir to `./tests/end-to-end` (which better describes their
purpose: things like `basics.py` and `memory.py` are end-to-end examples
of using SK and ways to verify nothing is horribly broken)
3. Applies `isort` (which we plan to add to our linting workflow here on
GitHub soon)
### Motivation and Context
The C# Semantic Kernel has recently undergone an upgrade to its
`PromptTemplateEngine`. This brings Python back in line with the
semantics of Prompt Templates in C#.
### Description
Here, unlike the original port, I've tried to make things more
pythonic/idiomatic (instead of trying to directly mirror the C#
codebase). I've also brought over the corresponding unit tests (and
added some of my own as I was building/validating).
### Motivation and Context
Port of the core TimeSkill
### Description
This PR adds the core TimeSkill with unit tests.
```
kernel = sk.create_kernel()
kernel.import_skill(TimeSkill(), "time")
```
```
sk_prompt = """
{{time.now}}
"""
```
This PR provides a path to using the ChatGPT API in the Python Preview
of Semantic Kernel. In addition, this provides `Azure*` versions of many
existing models (so Python users can leverage Azure OpenAI).
I think that, in general, it may be worth considering how best to work
with models that have different modalities: now we have text
completions, embeddings, chat completions (and I'd imagine images/etc.
may be nice to support someday too).
Regardless, this PR provides a fast path to using the exciting new Chat
APIs from OpenAI with SK!
See the new `python/tests/chat_gpt_api.py` for a usage example.
### Motivation and Context
Please help reviewers and future users, providing the following
information:
1. Why is this change required?
`SemanticTextMemory.save_reference_async` do nothing for its storage.
2. What problem does it solve? `save_reference_async` will work
appropriately
3. What scenario does it contribute to? embeddings
4. If it fixes an open issue, please link to the issue here.
https://github.com/microsoft/semantic-kernel/issues/165
### Description
I add missing codes with references of
`SemanticTextMemory.save_information_async` and C# version of
`SemanticTextMemory.save_reference_async`
### Motivation and Context
Porting the FileIOSkill to python.
### Description
This is the port of the FileIOSkill to python with unit tests.
```
kernel = sk.create_kernel()
kernel.import_skill(FileIOSkill(), "file")
context = kernel.create_new_context()
context["path"] = "test_file_io_skill.txt"
context["content"] = "Hello, world!"
```
Using the same function names than the C# version
```
{{file.readAsync $path}}
{{file.writeAsync}}
```
modification to the depencies :
- Adding the package : aiofiles
- Adding the dev package : pytest-asyncio
### Motivation and Context
1. Why is this change required? `pytest .` raises error
2. What problem does it solve? pass all test
3. What scenario does it contribute to? `infer_delegate_type` will not
raise error
4. If it fixes an open issue, please link to the issue here.
https://github.com/microsoft/semantic-kernel/issues/168
### Description
static function has no attribute __wrapped__ and this raises error.
use __func__ for this.
I think `wrapped = getattr(value, "__wrapped__", getattr(value,
"__func__", None))` is reasonable for this issue.
```@staticmethod
def infer_delegate_type(function) -> DelegateTypes:
# Get the function signature
function_signature = signature(function)
awaitable = iscoroutinefunction(function)
for name, value in DelegateInference.__dict__.items():
if name.startswith("infer_") and hasattr(
> value.__wrapped__, "_delegate_type"
):
E AttributeError: 'staticmethod' object has no attribute '__wrapped__'
../semantic_kernel/orchestration/delegate_inference.py:240: AttributeError
======================================================================================= short test summary info =======================================================================================
FAILED test_text_skill.py::test_can_be_imported - AttributeError: 'staticmethod' object has no attribute '__wrapped__'
FAILED test_text_skill.py::test_can_be_imported_with_name - AttributeError: 'staticmethod' object has no attribute '__wrapped__'
===================================================================================== 2 failed, 9 passed in 0.23s =====================================================================================
```
### Motivation and Context
1. Why is this change required? compatibility for python 3.9
2. What problem does it solve? if user use PromptTemplateEngine with
skills inside, it does not work.
3. What scenario does it contribute to? PromptTemplateEngine will work
4. If it fixes an open issue, please link to the issue here.
#182
### Description
detailed in #182
similar concept with #169
### Contribution Checklist
<!-- Before submitting this PR, please make sure: -->
- [x] The code builds clean without any errors or warnings
- [x] The PR follows SK Contribution Guidelines
(https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
- [x] The code follows the .NET coding conventions
(https://learn.microsoft.com/dotnet/csharp/fundamentals/coding-style/coding-conventions)
verified with `dotnet format`
- [x] All unit tests pass, and I have added new tests where possible
- [x] I didn't break anyone 😄
<!-- Thank you for your contribution to the semantic-kernel repo! -->
### Motivation and Context
This PR adds a Lint Github workflow so that code style rules can be
enforced for PRs.
1. This forms a baseline workflow that can be used as a template for
future workflows that will be added.
2. It helps enforce code style rules. Currently it only checks
PyCodeStyle and PyFlakes. Others will be added in the future.
3. Contributes to automated testing
4. Does not fix any open issue.
### Description
Added Ruff as a dev dependency. Added Github workflow which runs Ruff.
---------
Co-authored-by: Aditya Gudimella <[email protected]>
Co-authored-by: Devis Lucato <[email protected]>
### Motivation and Context
This PR simplifies `@sk_*` decorators while porting the core TextSkill
### Description
This PR is a first step at adapting the python codebase to be more
*pythonic*, it contains the following modifications :
1. Merged the decorators `@sk_function_context_parameter`,
`@sk_function_input` , `@sk_function_name` with `@sk_function`.
The decorators were replaced with new kwargs on `sk_function` : `name`,
`input_description`, `input_default_value`
2. The `name` kwarg is optional, the name of the method will be used if
none is provided.
3. Ported core skill - TextSkill
4. Added some pytest unit test for SK decorators and TextSkill
5. Changed how skills are imported in the kernel by using instance of
the class, not relying on static method anymore for the discovery.
e.g.
```
kernel.import_skill(TextSkill())
```
Abby Harrison
