Fixed some potential misspellings/errors.
### Motivation and Context
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---------
Co-authored-by: Roger Barreto <[email protected]>
clarified where to put the .env file
### Motivation and Context
As currently written, it's confusing as to where to put the .env file.
The proposed changes clarify where to put the .env file.
This improves onboarding experience and documentation.
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### Description
Minor changes to ReadMe to clarify where to put the .env file
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Co-authored-by: Evan Mattson <[email protected]>
prompt_template_config needs PromptTemplateConfig type but req_settings
is PromptExecutionSettings type which seems to be accepted better by
prompt_execution_settings
### Motivation and Context
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It throws an error otherwise
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AttributeError: 'AzureChatPromptExecutionSettings' object has no
attribute 'execution_settings'
4. What scenario does it contribute to?
5. If it fixes an open issue, please link to the issue here.
It's a README fix :)
### Description
prompt_template_config needs PromptTemplateConfig type but req_settings
is PromptExecutionSettings type which seems to be accepted better by
prompt_execution_settings
Changed to prompt_execution_settings=req_settings instead of
prompt_template_config=req_settings,
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### Motivation and Context
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The current link check action (github-action-markdown-link-check) is no
longer being maintained, because the developer created a new one, this
PR adds the new one side by side to test.
### Description
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Switches from poetry to uv
much faster and easier lock management
easier maintenance of pyproject.toml
fixes: #6584fixes: #8326
### Description
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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 😄
### Motivation and Context
SK Python is tightly coupled to the use of a `.env` file to read all
secrets, keys, endpoints, and more. This doesn't scale well for users
who wish to be able to use environment variables with their SK
Applications. By introducing Pydantic Settings, it is possible to use
both environment variables as well as have a fall-back to a `.env` file
(via a `env_file_path` parameter), if desired.
By introducing Pydantic Settings, we are removing the requirement to
have to create Text/Embedding/Chat completion objects with an `api_key`
or other previously required information (in the case of
AzureChatCompletion that means an `endpoint`, an `api_key`, a
`deployment_name`, and an `api_version`). When the AI connector is
created, the Pydantic settings are loaded either via env vars or the
fall-back `.env` file, and that means the user can create a chat
completion object like:
```python
chat_completion = OpenAIChatCompletion(service_id="test")
```
or, to optionally override the `ai_model_id` env var:
```python
chat_completion = OpenAIChatCompletion(service_id="test", ai_model_id="gpt-4-1106")
```
Note: we have left the ability to specific an `api_key`/`org_id` for
`OpenAIChatCompletion` or a `deployment_name`, `endpoint`, `base_url`,
and `api_version` for `AzureChatCompletion` as before, but if your
settings are configured to use env vars/.env file then there is no need
to pass this information.
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### Description
The PR introduces the use of Pydantic settings and removes the use of
the python-dotenv library.
- Closes#1779
- Updates notebooks, samples, code and tests to remove the explicit
config of api_key or other previous .env files values.
- Adds new unit test config using monkeypatch to simulate env variables
for testing
- All unit and integration tests passing
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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 😄
### Motivation and Context
All previous samples were either in kernel syntax or a separate
notebooks folder. The goal is to make the samples easier to understand
and have a better structure.
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### Description
The PR restructures the kernel syntax examples into new folders:
concepts (with subfolders for previous syntax examples), demos,
getting_started, and learn_resources.
- Closes#6119
- Adds a new concept/function example for understanding kernel
arguments.
- Updates the bookings plugin
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- [X] All unit tests pass, and I have added new tests where possible
- [X] I didn't break anyone 😄
### Motivation and Context
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`https://openai.com/product` is failing `Check .md links` workflow.
### Description
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Revise links.
https://github.com/microsoft/semantic-kernel/actions/workflows/markdown-link-check.yml
Whitespace edits peformed by VS Code
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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 😄
Kernel is already imported and there's no sk reference anymore since
it was removed last week in:
Python: fixing python readme
(https://github.com/microsoft/semantic-kernel/pull/5903)
### Motivation and Context
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The change https://github.com/microsoft/semantic-kernel/pull/5903
imported Kernel directly so the code
no longer works as written
2. What problem does it solve?
Code sample does not run
3. What scenario does it contribute to?
sample code in README.md working
4. If it fixes an open issue, please link to the issue here.
None
-->
### Description
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- [X] I didn't break anyone 😄
### Motivation and Context
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1. This change helps users by being able to copy the Azure OpenAI
endpoint directly
2. This solves the problem of getting a 404 Resource Not Found when
using `base_url`
3. Getting Started in Python scenario
### Description
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change `base_url` to `endpoint`
### Contribution Checklist
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- [x] I didn't break anyone 😄
Co-authored-by: Eduard van Valkenburg <[email protected]>
### Motivation and Context
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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
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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
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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 😄
This pull request primarily updates the `DEV_SETUP.md` and `README.md`
files in the `python` directory. The changes focus on improving the
setup instructions, updating the code snippets, and providing additional
information on running tests, code coverage, and keeping the local
repository up-to-date.
Changes to setup instructions:
*
[`python/DEV_SETUP.md`](diffhunk://#diff-22a026622159be328328c5bb6fef874e8aa799efb6ab8844d0c94ad051b08f3cR75-R90):
Added instructions on how to use Python 3.11 with Poetry, how to install
pre-commit hooks, and how to run tests using VSCode Tasks.
[[1]](diffhunk://#diff-22a026622159be328328c5bb6fef874e8aa799efb6ab8844d0c94ad051b08f3cR75-R90)
[[2]](diffhunk://#diff-22a026622159be328328c5bb6fef874e8aa799efb6ab8844d0c94ad051b08f3cR112-R114)
[[3]](diffhunk://#diff-22a026622159be328328c5bb6fef874e8aa799efb6ab8844d0c94ad051b08f3cR131-R133)
[[4]](diffhunk://#diff-22a026622159be328328c5bb6fef874e8aa799efb6ab8844d0c94ad051b08f3cL287-R252)
Code snippets updates:
*
[`python/DEV_SETUP.md`](diffhunk://#diff-22a026622159be328328c5bb6fef874e8aa799efb6ab8844d0c94ad051b08f3cL140-L227):
Updated the code snippets to reflect the latest changes in the codebase.
This includes changes in the use of Pydantic and the use of
KernelBaseModel.
[[1]](diffhunk://#diff-22a026622159be328328c5bb6fef874e8aa799efb6ab8844d0c94ad051b08f3cL140-L227)
[[2]](diffhunk://#diff-22a026622159be328328c5bb6fef874e8aa799efb6ab8844d0c94ad051b08f3cL244-R177)
*
[`python/README.md`](diffhunk://#diff-217ed82f87b78b399e304b07a159b27dff327c0f83adf4a2fc30b03bcbf84b01L58-R66):
Updated the code snippet to reflect the change in getting request
settings from a service ID.
Additional information:
*
[`python/DEV_SETUP.md`](diffhunk://#diff-22a026622159be328328c5bb6fef874e8aa799efb6ab8844d0c94ad051b08f3cL287-R252):
Added information on how to run code coverage, how to keep the local
repository up-to-date, and how to resolve conflicts after a rebase.
*
[`python/README.md`](diffhunk://#diff-217ed82f87b78b399e304b07a159b27dff327c0f83adf4a2fc30b03bcbf84b01R7-R14):
Added instructions on how to install optional dependencies.
### Motivation and Context
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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
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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
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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)
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]>
### 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.
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### 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.
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### 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)
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 😄
### 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
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### 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.
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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: Evan Mattson <[email protected]>
### Motivation and Context
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typo in docs
### Description
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Just fix the error import
### 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: Abby Harrison <[email protected]>
### Motivation and Context
text-davinci-003 is being retired by Azure OpenAI and is no longer
supported for new deployments
Resolves - https://github.com/microsoft/semantic-kernel/issues/2309
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### Description
Update examples and notebooks to use gpt-35-turbo / gpt-3.5-turbo
instead
<!-- Describe your changes, the overall approach, the underlying design.
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### Contribution Checklist
<!-- Before submitting this PR, please make sure: -->
- [ ] The code builds clean without any errors or warnings
- [ ] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [ ] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄
Signed-off-by: karthikmurali60 <[email protected]>
Co-authored-by: Lee Miller <[email protected]>
Co-authored-by: Gil LaHaye <[email protected]>
Update the README for Python to include latest notebooks and add a link
to Learn Documentation site for the feature matrix
---------
Co-authored-by: Alex Chao <achao@achao>
### Motivation and Context
* Removing the requirements.txt and just pinning each notebook to a pip
package that should work.
Doing this allows users to run notebooks without error even if the code
in the core repo updates.
When a new pip package is released, we will bump the version number in
each notebook.
* Fix usage of context variables. Apps should avoid using anonymous
context variables and prefer using the context, to retain access to the
kernel internals during the orchestration.
---------
Co-authored-by: Alex Chao <[email protected]>
Co-authored-by: Devis Lucato <[email protected]>
### Motivation and Context
KernelConfig isn't needed as it's less pythonic and is not used
independently from Kernel. This moves all its methods and members into
Kernel.
### Description
- Removed KernelConfig
- Put KernelConfig's methods and variables into Kernel
- Ran unit and end-to-end tests
- Did not run notebooks because they are out of date with the current
repo.
---------
Co-authored-by: Shawn Callegari <[email protected]>
### Motivation and Context
New release version 0.2.6
Fix bug in 0.2.5.dev0 pip package
Update notebooks to the latest pip package (0.2.6)
### Description of Changes
- fixed a param name error in the creation of a reference memory_record
- renamed text_service -> text_completion_service (consistency with .NET)
- renamed text_embedding_service -> text_embedding_generation_service
(consistency with .NET)
- Updated notebooks accordingly
- bumped pip versions to 0.2.6.dev0
### 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
1. Why is this change required? prompts are not semantic functions with
input <-> other way round
2. What problem does it solve? clearer understanding
3. What scenario does it contribute to? documentation
### Description
- corrected wording
- added a table for Q&A
### Contribution Checklist
- [x] I didn't break anyone 😄
---------
Co-authored-by: Devis Lucato <[email protected]>
Co-authored-by: Devis Lucato <[email protected]>
### 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
### 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)
