### Motivation and Context
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Added a section on documentation to the DEV_SETUP
Added a check for the copyright row to pre-commit
Closes#5629
### Description
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- Added static code checking to pre-commit (check-ast and
nbqa-check-ast)
- Added Bandit security checking to pre-commit
- Added pre-commit step to python-lint workflow, if it works, can delete
seperate mypy, ruff and black tests
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### Motivation and Context
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This pull request includes significant changes across multiple files,
mainly related to the addition of hooks and the modification of function
invocations in the `semantic_kernel` module. The changes also include
the addition of a new sample and a YAML file, and modifications to the
`__init__.py` files.
Removals:
*
[`python/semantic_kernel/events`](diffhunk://#diff-ebda9504832b19ab83239a92c9a6d5f8c744deff9fef86071c13956ec92bb010L1-L11):
Removed the previously used events.
New Exceptions:
*
[`python/semantic_kernel/exceptions/kernel_exceptions.py`](diffhunk://#diff-450aaa5595a8b22cd6ee212eb79b7d6b0d4e9c1072063ef32018a3e7d3fdf21dR41-R48):
Added new exception classes `OperationCancelledException` and
`HookInvalidSignatureError`.
[[1]](diffhunk://#diff-450aaa5595a8b22cd6ee212eb79b7d6b0d4e9c1072063ef32018a3e7d3fdf21dR41-R48)
[[2]](diffhunk://#diff-450aaa5595a8b22cd6ee212eb79b7d6b0d4e9c1072063ef32018a3e7d3fdf21dR57-R58)
Fixes: #3038Fixes: #6276
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### 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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- [ ] I didn't break anyone 😄
### Motivation and Context
Python had the ability to handle operations for OpenAPI plugins, but at
a basic level. It did not have the ability to handle OpenAI plugins, nor
did it allow the user to configure an authentication callback. This PR
brings in that functionality.
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### Description
This PR:
- Allows a user to handle OpenAI plugins with/without auth. Closes#5355
- Improves the functionality around handling OpenAPI specs.
- Introduces an auth callback mechanism to allow for REST API calls to
use auth
- Introduces OpenAI/OpenAPI function execution settings.
- Provides two new kernel examples that show how to handle a simple
OpenAI plugin (Klarna) as well as a more complex plugin (Azure Key
Vault) that requires auth.
- Updates unit tests.
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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 😄
### Motivation and Context
Jinja2 is a heavily supported Python templating language and we're
introducing it to SK Python.
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### Description
This PR brings in the ability to specify Jinja2 templates for use within
SK Python:
- Closes#5343
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Introducing Handlebars templating to the Python Semantic Kernel!
Closes: #5446
Prework for: #4641
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Adds HandlebarsPromptTemplate as a subclass of PromptTemplateBase
Adds second literal to the PromptTemplateConfig definition
Adds helpers for Handlebars (system_helpers) and
`create_helper_from_function` function
Moves fully_qualified_name into KernelFunctionMetadata instead of in
different extensions.
Defaults are still 'semantic-kernel' templates, and without making
explicit changes that still is the norm.
Adds a azure_chat_gpt_handlebars.py sample
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- [x] I didn't break anyone 😄
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The existing Exceptions structure was very much inspired by dotnet, this
is now replaced with a pythonic implementations.
This means all Exceptions derive from KernelException and then
specialise for different purposes.
Closes#2194
### Description
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Added folder for all exception types, all can be imported through `from
semantic_kernel.exceptions import ...` no need for a user to know which
file the relevant one is in, but keeps things tidy for developers.
Removed old KernelException, added back subtypes for the errorcodes.
Went through everything to make sure the `raise ... from exc` pattern is
used as much as possible as that returns a better stacktrace.
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- [x] I didn't break anyone 😄