### Motivation and Context
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It's shame sometimes it shines through that some of the earliest code in
the python code base was a direct port from C#, like with the .get
method on the context variables, made the change here to have the exact
some signature as the default python dict.
Also replaces contains_key with __contains__ so that 'in' keyword can be
used, just like a normal dict.
Fixes#2962
### Description
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Changed the .get method
Replaced the contains_key method with __contains__
Made changes in samples, tests and planner to deal with that.
### 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
- [ ] I didn't break anyone 😄
---------
Co-authored-by: Devis Lucato <[email protected]>
Co-authored-by: Devis Lucato <[email protected]>
### Motivation and Context
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I built support for function calling into SK!
Related to/fixes:
- #2315
- #2175
- #1450
### Description
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This implementation builds on top of all the existing pieces, but did
require some major work, so feel free to comment on where that is or is
not appropriate.
- Added a `ChatMessage` class to capture the relevant pieces of function
calling (name and content)
- Added a `complete_chat_with_functions_async` into
OpenAIChatCompletions class
- Added a `function_call` field to ChatRequestSettings class
- Added several helper functions and smaller changes
- Added a sample with updated core_skill that uses function calling to
demonstrate
- Added a second sample that shows how to use function_calling with
non-sk functions.
### Contribution Checklist
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- [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)
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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: Abby Harrison <[email protected]>
### Motivation and Context
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This solves [this
issue](https://github.com/microsoft/semantic-kernel/issues/1069) where
native functions are not returning the expected result. In python,
return typehints are optional. However, the semantic kernel requires a
return typehint to determine how to handle the function. For that
reason, we're now enforcing return typehints and raising an exception
when one is not provided. This may break existing void functions but
none in our repo are affected.
Fixes#1069
### 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
- [] I didn't break anyone 😄
## Summary
This pull request includes two sets of changes. First, it fixes the
return type annotations in three core skills: file_io_skill,
text_memory_skill, and wait_skill. Specifically, the write_async method
in file_io_skill and the save_async method in text_memory_skill now have
a return type of None, and the wait method in wait_skill now has a
return type of None. Additionally, the
import_native_skill_from_directory method in kernel.py has been
refactored to simplify the code. Second, this pull request adds error
handling for functions with no return type in the delegate inference
module. Previously, if a function did not specify a return type, the
DelegateType could not be inferred, leading to errors. This pull request
adds a check for functions with no return type and raises a
KernelException with an appropriate error message. Additionally, this
pull request includes some minor changes to unit tests for native
functions.
## Changes
- Fixed return type annotation for write_async method in file_io_skill
- Fixed return type annotation for save_async method in
text_memory_skill
- Fixed return type annotation for wait method in wait_skill
- Refactored import_native_skill_from_directory method in kernel.py
- Added error handling for functions with no return type in the delegate
inference module
- Added a check for functions with no return type and raised a
KernelException with an appropriate error message
- Made minor changes to unit tests for native functions
---
*Powered by [Microsoft Semantic
Kernel](https://github.com/microsoft/semantic-kernel)*
SKFunction has been excluded for now.
Handles issues arising due to many circular imports Update
DelegateInference to handle some cases where annotation is given as a
string to avoid circular imports like in FileIOSkill.
### Motivation and Context
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### Description
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### Contribution Checklist
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- [x] The code builds clean without any errors or warnings
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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: Abby Harrison <[email protected]>
Co-authored-by: Mark Karle <[email protected]>
Co-authored-by: Abby Harrison <[email protected]>
Co-authored-by: Lee Miller <[email protected]>
Co-authored-by: Devis Lucato <[email protected]>
### Motivation and Context
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solve #2473 and add unit test to prevent this from happening again.
### Description
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### Contribution Checklist
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- [ ] The code builds clean without any errors or warnings
- [ ] The PR follows the [SK Contribution
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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: Abby Harrison <[email protected]>
This is part 4 of the Serialization work for semantic kernel.
Corresponding issue:
https://github.com/microsoft/semantic-kernel/issues/131
### Motivation and Context
While there are no user facing changes, the ReadOnlySkillCollection has
been modified to remove
circular dependencies that were causing issues with serialization.
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### Description
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### Contribution Checklist
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- [x] The code builds clean without any errors or warnings
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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 😄
---------
Co-authored-by: Abby Harrison <[email protected]>
Co-authored-by: Abby Harrison <[email protected]>
### Motivation and Context
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while implementing #1691, there was an idea that adding
`invoke_stream_async` on `SKFunction` is reasonable.
<img width="870" alt="image"
src="https://github.com/microsoft/semantic-kernel/assets/69464062/44278d30-66b2-41d2-8c9f-c1daea50b331">
### Description
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moved temporal streaming logic from `Kernel` to `SKFunction`
I didn't want to add new `DelegateTypes` like `InStringOutStreaming` for
minimal changes.
in most cases, `SKFunction` is initiated from `from_semantic_config` or
`from_native_method`.
Now, both functions will handle the 'delegate_stream_function' argument,
which will be used in `invoke_stream_async`
### Contribution Checklist
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- [ ] 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: Abby Harrison <[email protected]>
### Motivation and Context
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solve #2233
### Description
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### Contribution Checklist
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- [ ] The code builds clean without any errors or warnings
- [ ] The PR follows the [SK Contribution
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raises no violations
- [ ] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄
Co-authored-by: Abby Harrison <[email protected]>
### Motivation and Context
To fix a runtime error on windows for python version 3.10, 3.11 and
above
On windows, python version above 3.10.1, there will be a runtime error
caused by asyncio event loop. add adapting code for windows when python
version is above 3.10.1 to avoid the error.
### Description
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These notes will help understanding how your code works. Thanks! -->
Refer link:
https://docs.python.org/3/library/asyncio-policy.html
"Note In Python versions 3.10.9, 3.11.1 and 3.12 the
[get_event_loop()](https://docs.python.org/3/library/asyncio-eventloop.html#asyncio.get_event_loop)
method of the default asyncio policy emits a
[DeprecationWarning](https://docs.python.org/3/library/exceptions.html#DeprecationWarning)
if there is no running event loop and no current loop is set. In some
future Python release this will become an error."
Note: per testing, this error also occurred on python 3.10 below 3.10.9
Co-authored-by: Mark Karle <[email protected]>
Co-authored-by: Lee Miller <[email protected]>
### Motivation and Context
#691#1053
### Description
1. Added an argument to prevent TypeError when inferring an unknown
type.
2. Fixed a bug in the process of checking parameters when inferring the
InStringAndContext type.
### Motivation and Context
This PR significantly reduces the complexity of implementing a new
memory store. Previously, memory stores needed to implement
EmbeddingIndexBase, DataStoreBase, and MemoryStoreBase. Now, memory
stores only need to implement MemoryStoreBase. This PR also brings
MemoryStoreBase to parity with the .NET IMemoryStore interface.
### Description
- Removed `data_entry.py`, `data_store_base.py`,
`volatile_data_store.py`, and `embedding_index_base.py`
- Added `with_embedding` parameter to all get/search methods. Passing
the embedding between the application and storage is not optional and
defaults to False
- `MemoryStoreBase` (Python SK) == `IMemoryStore` (.NET SK)
- Updated `volatile_memory_store` to implement `MemoryStoreBase`
- Removed `ABC` from `MemoryStoreBase`
- Added documentation to memory files
Closes https://github.com/microsoft/semantic-kernel/issues/670
### Motivation and Context
This PR introduces native python support for Hugging Face models that
can: complete text, generate new text, summarize, and that generate
embeddings. Currently only supports downloading the models locally from
the HF model hub. Future plans include supporting the HF inference API
as well.
### Description
- Added 2 services: `hf_text_completion` and `hf_text_embedding`
- `hf_text_completion` supports the following tasks: _text-generation_,
_text2text-generation_, and _summarization_
- `hf_text_embedding` supports any model supported by the
sentence-transformers pip package
- Added dependencies: pytorch, transformers, sentence-transformers to
`requirements.txt` and `poetry.lock`
- fixed typo: `get_embedding_service_service_id` ->
`get_embedding_service_id`
- Added a number of integration tests for supported HF models
### Motivation and Context
This PR is a consistency update between the Python and .NET Semantic
Kernels.
**This PR does not contain any feature enhancements or improvements!**
### Description
- Replace terminology 'backend' with 'service'
- Move semantic_kernel.ai (semantic_kernel/ai) to
semantic_kernel.connectors.ai (semantic_kernel/connectors/ai)
### 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
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.
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
### 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 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).
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
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
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- [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 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())
```
