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Author SHA1 Message Date
Eduard van Valkenburg 6751f9d819 Python: Updated plugins (#5827) 
### 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

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 2024-04-15 13:51:59 +00:00
Eduard van ValkenburgandEvan Mattson 629624cee3 Python: removed pipeline (#5779) 
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Remove the ability to run multiple functions in go in kernel.invoke.

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Co-authored-by: Evan Mattson <[email protected]>
 2024-04-04 15:54:19 +00:00
Evan Mattson c4c7464f07 Python: Introduce operations to handle OpenAI plugins, improve OpenAPI plugins, and allow for auth (#5695) 
### 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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 2024-04-01 15:01:08 +00:00
Eduard van Valkenburg 14a0881989 Python: mypy clears kernel.py (#5689) 
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Fixed all mypy errors for kernel.py
In preparation of extending that to all files in semantic_kernel
Also got the pre-commit hook working on a commit, with mypy checks

fixes #5630

### Description

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Moved pre-commit-config to base folder, can now be extended to have
specific hooks for other languages
fixed things in kernel.py to satisfy mypy
used assert for some things, so that they can be skipped when running in
-o mode.

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 2024-03-28 15:10:28 +00:00
Eduard van Valkenburg 75089cb711 Python: Enhance Chat Message Content creation and parsing (#5520) 
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Introduces a polymorphic approach to creating and rendering Chat Message
Contents and it's subclasses, leverages Pydantic Rootmodel for that.

Fixes #5496 

### Description

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Adds ChatMessageContentBase that can create all types of CMC's, based on
a type field (str)
Redoes some of the rendering and parsing
also retooled the hierarchy structure for Contents, including
introducing a StreamingContentMixin instead of the
StreamingKernelContent (which was never used), now all content classes
(TextContent, CMC, etc) determine the fields used, while the Mixin adds
one additional field and two additional methods for streaming messages,
especially __add__
everything else runs the same way.

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 2024-03-28 12:45:56 +00:00
Eduard van Valkenburg 1cf984cc99 Python: Enhanced pre commit and tasks (#5512) 
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To further make the SK python robust and make it easier to get
high-quality PRs, some work on the pre-commit-config.yaml and adding a
mypy settings ini.

### Description

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Added two steps to the pre-commit-config, the first for pypy, the second
for tests with coverage.
Over time we want to mandate these checks to run against a PR before it
goes to github, that will also reduce the number of ruff and black fix
commits, and non-passing unit tests.

Added a mypy.ini, currently all but the root folder is excluded, so that
we can gradually introduce mypy coverage, did the first pieces in
kernel.py, including switch to new style annotations (using from
`__future__ import annotations`) in Kernel.


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 2024-03-19 20:20:09 +00:00
Evan Mattson 5b127badbf Python: Add support for yaml prompt template (#5527) 
### Motivation and Context

SK Python doesn't have a way to create a prompt template config from a
yaml file. This is neeed to further achieve parity with dotnet and java.

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### Description

This PR introduces:
- some kernel methods to load yaml prompts from a directory as well as
create a kernel function from a string that contains yaml. Closes #4640
- Unit tests and a syntax example showing how to create a yaml prompt
and load it

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 2024-03-19 19:59:38 +00:00
Evan Mattson 0a1a7cabe8 Python: support Jinja2 templating (#5483) 
### 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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 2024-03-15 13:23:25 +00:00
Eduard van Valkenburg 59c3a9fc9a Python: planner love (#5477) 
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Based on #5474 went into the `using-the-planner` notebook and made sure
it works with the latest code.

### Description

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Moved all the planners to use '-' in line with the current work on new
templates and planners, once that is in several extension classes can be
changed.
Encountered several small bugs left over from changes over the last
months.
Got through the whole notebook with results.

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 2024-03-14 14:59:10 +00:00
Eduard van Valkenburg 3af69df7ea Python: Handlebars template support (#5466) 
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Introducing Handlebars templating to the Python Semantic Kernel!

Closes: #5446
Prework for: #4641

### Description

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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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 2024-03-14 14:00:05 +00:00
Eduard van Valkenburg 2bc3de72da Python: Add extras and minor package updates (#5440) 
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Poetry groups are not the same as pip extras, so I removed the
individual groups per service, replaced with the ones needed for unit
tests and for integration tests (all).

Then added Extras, for each connector, as well as a `all` extra. Also
added a notebooks extra, this can be used instead of the first cell in
the notebooks as `pip install -U semantic-kernel[notebooks]` closing
#4713

Made all dependencies part of the main, tagged with optional.

Closes #5322

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 2024-03-12 15:25:24 +00:00
Eduard van Valkenburg 275db86fd1 Python: add py3.12 to unit tests (#5191) 
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Since Python 3.12 is now released we should test with it. In the fall
3.8 will be out of support so then we should remove support for that.

Since Numpy no longer support py 3.8 as of
[1.25](https://numpy.org/doc/stable/release/1.25.0-notes.html) we pin
that for py3.8, including other packages that depend on older version of
numpy for py3.8, and allow the new versions to work against newer
version of python.

Closes #5144 

### Description

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 2024-03-12 09:27:55 +00:00
Eduard van Valkenburg e884e81776 Python: update usearch to 2.9 (#5420) 
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Updates the usearch package to 2.9+, and fixes the tests for that.
Closes #2676 

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 2024-03-11 21:10:53 +00:00
Evan Mattson d7c1febc7b Python: Use the correct exception key for handling streaming exceptions in the kernel (#5417) 
### Motivation and Context

In a previous fix, the error -> exception key change was missed in a
line in the kernel. This fixes that.

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### Description

This PR:
- fixes the incorrect key (error) and now pulls the exception from the
metadata for streaming invoke for the key `exception`. Closes #5385
- Adds a unit test

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 2024-03-11 14:23:11 +00:00
Eduard van Valkenburg 555a7c8436 Python: fix for streaming openai responses, and first parts of fixes for Chat With Your Data (#5387) 
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 2024-03-08 21:10:43 +00:00
Evan Mattson bf5d21c69a Python: Properly handle exceptions in the kernel using the exception metadata (#5391) 
### Motivation and Context

Two things: 1) Add the exception to the on function invoked args if an
exception exists in the function result. 2) Set the stepwise planner's
goal to the plan's description, not the name.

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### Description

The PR addresses:
- Properly handling exceptions to raise them from the kernel if a
function result contains an exception in the metadata. Closes #5385
- In the stepwise planner, the goal was getting set as the plan's name,
instead of the description. Closes #5316

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 2024-03-08 20:21:19 +00:00
Eduard van Valkenburg 2493e293fb Python: Update kernel tests (#5341) 
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Adding a whole bunch of tests to better cover Kernel.py.
Also reviewed and updated the conftest and tweaked the scope, now runs
faster!

Skipped efforts for handlers since work is being done there. 

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 2024-03-07 07:38:04 +00:00
Evan Mattson d7820df9c2 Python: Add function name and plugin name to invoke prompt. Add unit tests. (#5318) 
### Motivation and Context

The kernel.invoke_prompt was missing the function name and plugin name
args and was failing.

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### Description

This PR:
- Adds the required arguments. Closes #5313 
- Adds unit tests. 

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- [X] All unit tests pass, and I have added new tests where possible
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 2024-03-06 08:38:47 +00:00
Evan MattsonandEduard van Valkenburg b93bab90ac Python: Support Auto tool calling for OpenAI models (#5267) 
### Motivation and Context

Auto tool calling hasn't been implemented in Python for OpenAI models.
This is a much needed feature, which helps open the possibilities and
extends being able to use the OpenAI models for just pure back and forth
chats.

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### Description

This PR:
- introduces auto tool calls for OpenAI models. If the prompt function
is of an OpenAI chat completion type, then we pass the kernel as an
argument to the OpenAI Chat Completion Base class. The kernel is used to
auto-invoke tools/functions seamlessly as part of the chat completion
request. Closes #4553
- splits the current chat completion/chat completion stream methods into
smaller, more readable/functional methods in the OpenAI Chat Completion
Base class.
- Adds an integration test to cover auto invoke tool calls
- Updates a kernel example to be able to work for a
streaming/non-streaming tool call. Other Kernel Examples that don't use
auto invoke tools still work as they did before.
- Removes old code in the utils file that was related to the manual form
of invoking function calls.

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### Contribution Checklist

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---------

Co-authored-by: Eduard van Valkenburg <[email protected]>
 2024-03-05 21:12:51 +00:00
Eduard van Valkenburg 3e67904d37 Python: small fix in create_function_from_prompt to match KernelFunctionFromPrompt (#5288) 
### Motivation and Context

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Small fix for the Kernel function that deal with Prompt function, they
were slightly out of sync with the KernelFunctionFromPrompt constructor.

### Description

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 2024-03-04 14:31:58 +00:00
Evan Mattson 2785c66622 Python: Migrate and update docs samples (#5235) 
### Motivation and Context

As of the latest code in main, and the push towards a beta package, the
Python sample code needed updates. We've migrated away from using the
semantic-kernel-docs repo and the Python sample code is now in the main
SK repo. The SK Python docs will be updated to reflect this latest code.

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### Description

This PR:
- Migrates the Python samples to the main SK repo
- The naming of the files is about 1:1 with dotnet, based on python
naming conventions/using underscores
- Updates the Python samples to work with the latest code in main.
Closes #5234
- Fixes some other small logging quirks related to parsing blocks and
printing plan steps.

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- [X] I didn't break anyone 😄
 2024-03-01 16:31:24 +00:00
Eduard van Valkenburg 739e7f0e2a Python: rebuilt exceptions structure; pythonic version (#5231) 
### Motivation and Context

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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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 2024-02-28 18:53:53 +00:00
Eduard van ValkenburgEvan MattsonEvan Mattson
 		a6f66ec098 Python: split kernelfunction into fromprompt and frommethod classes (#5159) 
### Motivation and Context

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Closes #4633 and brings this part of the python sdk in sync with dotnet,
also makes for a much more readable set of classes.

### Description

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Added:
- KernelFunctionFromPrompt class
- KernelFunctionFromMethod class
- tests for both.

Changed:
- removed parts of KernelFunction that are specific to one of the two
subtypes
- removed expose attribute of KernelParameterMetadata as that is no
longer needed

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---------

Co-authored-by: Evan Mattson <[email protected]>
Co-authored-by: Evan Mattson <[email protected]>
 2024-02-26 20:20:25 +00:00
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.
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### 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.

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 2024-02-26 17:50:23 +00:00
Eduard van ValkenburgEvan MattsonEvan MattsonEvan Mattson
 		5817c2b927 Python: major features for the Kernel Arguments, Function Result and new Prompt Templating (#5077) 
### 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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- [ ] 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]>
 2024-02-24 20:05:40 +00:00
Evan Mattson 1efeb69819 Python: Set the default plugins on the semantic function. Add a unit test. (#4897) 
### Motivation and Context

Fixes #4869. On a created semantic function, the plugins weren't getting
set for use for the function.

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### Description

Set the default plugins for the registered function, and add a unit
test.

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 2024-02-06 16:58:48 +00:00
Evan MattsonandEvan Mattson 7268d13ee8 Python: Pydantic-ify the KernelFunction class. Fix code paths related to tool_calls. (#4863) 
### Motivation and Context

Solves #4864

The KernelFunction was configured as a Python class without regards to
using Pydantic fields and its validations. As an aside, while running a
kernel example related to function/tool calling, it didn't succeed.

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### Description

This PR cleans up the KernelFunction by creating Pydantic fields. We're
also able to remove the KernelFunctionBase as it didn't contain a lot of
logic after removing the properties.

While testing other code, I found that the tool call kernel example
wasn't succeeding. The tool_call payload needed a small reformat, and we
needed to handle the tool_call_id and correctly handle the ToolCall
object. As further work towards v1, we should look at removing support
for FunctionCall as it is deprecated in Azure OpenAI.

We now see:

```
User:> What is 3+3?
Mosscap:> Ah, the timeless question of arithmetic! The sum of 3 and 3 is undoubtedly a splendid number. 
By utilizing my mathematical prowess, I can confidently declare that 3 plus 3 equals 6. 
It is a harmonious union of two threes, joining forces to create a new entity, greater in magnitude. 
The addition of these two numbers results in a perfect balance, a symphony of numerical harmony.
```

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---------

Co-authored-by: Evan Mattson <[email protected]>
 2024-02-05 16:46:58 +00:00
Evan MattsonEvan MattsonEduard van Valkenburg
 		9ae69a43fc Python: Make the Kernel class Pydantic. (#4850) 
### Motivation and Context

Completes work item: #4846. The Kernel class was not following the
Pydantic convention.

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### Description

This PR updates the Kernel class to use the KernelBaseModel and Pydantic
fields. All unit and integration tests passing.

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---------

Co-authored-by: Evan Mattson <[email protected]>
Co-authored-by: Eduard van Valkenburg <[email protected]>
 2024-02-02 12:46:45 +00:00
Evan MattsonandEvan Mattson 2b6bd03b03 Python: Add kernel plugin collection and remove old plugin collection classes (#4764) 
### Motivation and Context

This PR solves two works items: #4560 and #4667. The Python SDK had
different ways of handling plugins and collections. The work in the PR
helps align the SDK with dotnet nomenclature and structure.

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### Description

A `KernelPluginCollection` is introduced with an underlying
`DefaultKernelPlugin` and a `KernelPlugin` base class. Other code is
refactored to use this new `KernelPluginCollection` model which should
simplify how plugins are handled. Unit tests are added to test the new
functionality. Existing unit tests and integration tests, along with
kernel examples and notebooks were updated based on these changes.

Unlike before, we're requiring plugins to be defined with a name, which
removes the GLOBAL_PLUGIN constant name of "__GLOBAL_PLUGIN__". In some
senses, while creating a plugin or a function, a name may not be
provided and so a random name in the form of a plugin
(p_<random_ascii_chars>) or function (f_<random_ascii_chars>) is used.

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- [ ] I didn't break anyone 😄

---------

Co-authored-by: Evan Mattson <[email protected]>
 2024-02-01 18:57:00 +00:00
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.

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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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- [ ] I didn't break anyone 😄
 2024-01-31 20:29:22 +00:00
Julio Carlos Menendez 5303126c0d Python: Renames request settings to prompt execution settings (#4782) 
### Motivation and Context

Following the C# implementation, renames all classes and variables of
`*RequestSettings` to `*PromptExecutionSettings`.

Fixes #4676 

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 2024-01-31 15:58:09 +00:00
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 

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---------

Co-authored-by: Evan Mattson <[email protected]>
 2024-01-26 17:15:35 +00:00
Julio Carlos Menendez 08710373a4 Python: Renames SK prefix to Kernel (#4716) 
### Motivation and Context
The .NET SDK uses the `Kernel` prefix instead of `SK` for the context,
function, model, etc. classes. This PR aligns the Python package with
that policy.

Fixes #4561 
### Contribution Checklist

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 2024-01-24 15:51:56 +00:00
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 

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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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- [X] I didn't break anyone 😄

---------

Co-authored-by: Evan Mattson <[email protected]>
 2024-01-19 16:47:30 +00:00
Eduard van Valkenburg fa3e32bb16 Python: set line-length for black in sync with Ruff, run black. (#4396) 
### Motivation and Context

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As we are tightening the formatting and linting setups, this was
missing, now the line-length for black and ruff are the same, thereby no
longer running into black issues as often.

### Description

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raises no violations
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- [x] I didn't break anyone 😄
 2024-01-04 14:28:20 +00:00
Eduard van Valkenburg b91529a62e Python: Implement AI request settings (#4097) 
### Motivation and Context

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This PR implements the new approach to AI Request settings as described
here:
https://github.com/microsoft/semantic-kernel/blob/main/docs/decisions/0008-support-generic-llm-request-settings.md
and completes #3312

### Description

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Does this:
- Creates AI Request Settings with service_id (referring to the
registered AI services in a kernel) and extension_data, a dict that can
hold any number of settings
- has several methods:
- `from_ai_request_settings` -> constructor to create a new
request_settings object based on another, supports creating specific
ai_request_settings from generic ones.
- `update_from_ai_request_settings` -> updating the fields of a request
setting from another ones.
- `prepare_settings_dict` -> method that is used when actually creating
the dict that get's passed to the handler of the AI service.
- Created subclasses like OpenAIChatRequestSettings which has all the
required fields of a OpenAI Chat completion, same for OpenAIText,
AzureChat, GooglePalm, HuggingFace, etc.
- added `get_request_settings_class` to ai_services to return the class
used for the settings for that service.

The goal is that when running, this settings object get's updated and a
single operations (called `prepare_settings_dict`) is used to return a
dict that can be passed to the api call directly, thereby reducing the
need for custom logic everywhere, this will also negate the need for
things like `complete_chat_with_functions_async` and others. So also
removed complete_chat_..._async methods from openai and azure openai.

It has also changed the prompt_template_config with the generic type for
the AIRequestSettings or subclasses, and some other changes.

### 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 😄
 2024-01-03 19:57:27 +00:00
Julio Carlos MenendezandEduard van Valkenburg d3dd5c8e7e Python: Uses Python standard logging (#4115) 
### Motivation and Context

This replaces passing Logger instances as arguments around with the
preferred Python way of having each module define a module-wide `logger`
instance at the top of the module. Fixes #3711

### Description

Removes any `log` argument and argument documentation. Replaces usage of
those `log` arguments with the module-wide `logger` instance.

### Contribution Checklist

- [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: Eduard van Valkenburg <[email protected]>
 2023-12-16 18:41:41 +00:00
JoowonRoger BarretoDmytro Struk
 		194f2401eb Python: sync C# for Pre/Post RunAsync Handlers (#3063) 
### Motivation and Context

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#3038 

### Description

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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: Roger Barreto <[email protected]>
Co-authored-by: Dmytro Struk <[email protected]>
 2023-11-13 21:45:04 +00:00
Adarsh AcharyaandDmytro Struk 965c23d374 Python: Fixed type error in plan.run_next_step_async method (#3231) 
### Description

This PR fixes #3219 

### Contribution Checklist

- [X] The code builds clean without any errors or warnings
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- [X] I didn't break anyone 😄

---------

Co-authored-by: Dmytro Struk <[email protected]>
 2023-10-19 15:01:30 +00:00
Eduard van ValkenburgandAbby Harrison 85ee34b924 Python: Implement Function calling for Chat (#2356) 
### 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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These notes will help understanding how your code works. Thanks! -->
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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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]>
 2023-10-12 17:34:22 +00:00
Mark Karle 45f492aa89 Python: Enforcing return typehints on native functions (#2948) 
### 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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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)*
 2023-09-27 01:24:42 +00:00
Aditya GudimellaAbby HarrisonMark KarleAbby HarrisonLee MillerDevis Lucato
 		f251e654ec Python: Enable serialization for sk/orchestration (#2369) 
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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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]>
 2023-08-24 16:05:39 +00:00
JoowonAbby HarrisonAbby HarrisonLee Miller
 		4bc5ff716d Python: provide methods to register single native function to the kernel (#2390) 
### Motivation and Context

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solve #2321 

### Description

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### Contribution Checklist

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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]>
Co-authored-by: Abby Harrison <[email protected]>
Co-authored-by: Lee Miller <[email protected]>
 2023-08-23 22:59:08 +00:00
JoowonandAbby Harrison 67dfb4c1f5 Python: add invoke_stream_async for SKFunction (#2200) 
### 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
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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]>
 2023-08-04 19:06:27 +00:00
Mark KarleandAbby Harrison 2733a5574f Python: Import OpenAPI documents into the semantic kernel (#2297) 
### Motivation and Context

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This allows us to import OpenAPI documents, including ChatGPT plugins,
into the Semantic Kernel.

### Description

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These notes will help understanding how your code works. Thanks! -->
- The interface reads the operationIds of the openapi spec into a skill:
```python
from semantic_kernel.connectors.openapi import register_openapi_skill
skill = register_openapi_skill(kernel=kernel, skill_name="test", openapi_document="url/or/path/to/openapi.yamlorjson")
skill['operationId'].invoke_async()
```
- Parse an OpenAPI document
- For each operation in the document, create a function that will
execute the operation
- Add all those operations to a skill in the kernel
- Modified `import_skill` to accept a dictionary of functions instead of
just class so that we can import dynamically created functions
- Created unit tests

TESTING:
I've been testing this with the following ChatGPT plugins:
- [Semantic Kernel Starter's Python Flask
plugin](https://github.com/microsoft/semantic-kernel-starters/tree/main/sk-python-flask)
- [ChatGPT's example retrieval
plugin](https://github.com/openai/chatgpt-retrieval-plugin/blob/main/docs/providers/azuresearch/setup.md)
- This one was annoying to setup. I didn't get the plugin functioning,
but I was able to send the right API requests
- Also, their openapi file was invalid. The "servers" attribute is
misindented
- [Google ChatGPT
plugin](https://github.com/Sogody/google-chatgpt-plugin)
- [Chat TODO plugin](https://github.com/lencx/chat-todo-plugin)
- This openapi file is also invalid. I checked with an online validator.
I had to remove"required" from the referenced request objects'
properties:
https://github.com/lencx/chat-todo-plugin/blob/main/openapi.yaml#L85

Then I used this python file to test the examples:

```python
import asyncio
import logging

import semantic_kernel as sk
from semantic_kernel import ContextVariables, Kernel
from semantic_kernel.connectors.ai.open_ai import AzureTextCompletion
from semantic_kernel.connectors.openapi.sk_openapi import register_openapi_skill

# Example usage
chatgpt_retrieval_plugin = {
    "openapi": # location of the plugin's openapi.yaml file,
    "payload": {
        "queries": [
            {
                "query": "string",
                "filter": {
                    "document_id": "string",
                    "source": "email",
                    "source_id": "string",
                    "author": "string",
                    "start_date": "string",
                    "end_date": "string",
                },
                "top_k": 3,
            }
        ]
    },
    "operation_id": "query_query_post",
}

sk_python_flask = {
    "openapi":  # location of the plugin's openapi.yaml file,
    "path_params": {"skill_name": "FunSkill", "function_name": "Joke"},
    "payload": {"input": "dinosaurs"},
    "operation_id": "executeFunction",
}
google_chatgpt_plugin = {
    "openapi":  # location of the plugin's openapi.yaml file,
    "query_params": {"q": "dinosaurs"},
    "operation_id": "searchGet",
}

todo_plugin_add = {
    "openapi":  # location of the plugin's openapi.yaml file,
    "path_params": {"username": "markkarle"},
    "payload": {"todo": "finish this"},
    "operation_id": "addTodo",
}

todo_plugin_get = {
    "openapi":  # location of the plugin's openapi.yaml file,
    "path_params": {"username": "markkarle"},
    "operation_id": "getTodos",
}

todo_plugin_delete = {
    "openapi":  # location of the plugin's openapi.yaml file,
    "path_params": {"username": "markkarle"},
    "payload": {"todo_idx": 0},
    "operation_id": "deleteTodo",
}


plugin = todo_plugin_get # set this to the plugin you want to try

logger = logging.getLogger(__name__)
logger.addHandler(logging.StreamHandler())
logger.setLevel(logging.DEBUG)

kernel = Kernel(log=logger)
deployment, api_key, endpoint = sk.azure_openai_settings_from_dot_env()
kernel.add_text_completion_service(
    "dv", AzureTextCompletion(deployment, endpoint, api_key)
)

skill = register_openapi_skill(
    kernel=kernel, skill_name="test", openapi_document=plugin["openapi"]
)
context_variables = ContextVariables(variables=plugin)
result = asyncio.run(
    skill[plugin["operation_id"]].invoke_async(variables=context_variables)
)
print(result)
```

### 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]>
 2023-08-04 17:48:21 +00:00
JoowonShawn CallegariAbby HarrisonAbby Harrison
 		ff2ba072a4 Python: temporal kernel run stream async (#1691) 
### Motivation and Context
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Temporal solution for #1606 

### Description
<!-- 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: -->
- [ ] The code builds clean without any errors or warnings
- [ ] The PR follows SK Contribution Guidelines
(https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
- [ ] The code follows the .NET coding conventions
(https://learn.microsoft.com/dotnet/csharp/fundamentals/coding-style/coding-conventions)
verified with `dotnet format`
- [ ] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄

---------

Co-authored-by: Shawn Callegari <[email protected]>
Co-authored-by: Abby Harrison <[email protected]>
Co-authored-by: Abby Harrison <[email protected]>
 2023-07-17 18:05:39 +00:00
Abby Harrison b2e1548379 Python: Multiple results per prompt (incl. streaming) (#1316) 
### Motivation and Context
To take advantage of APIs offered by most LLMs and to be in sync with
.NET SK, this PR introduces the ability to generate multiple text
completions or chat completions from a single prompt.


![MultiChatCompletionStreamMulti](https://github.com/microsoft/semantic-kernel/assets/54643756/7bec03ec-0be2-40b0-b938-6ff71beac209)


### Description
- Return type hint for `complete_async` and `complete_chat_async`
changed from `str -> Union[str, List[str]]`. The use of `Union` is the
proper way to indicate multiple return types prior to Python 3.10+. 3.10
supports the use of the `|` symbol, but since the Python SK is supported
on 3.8 and 3.9, I did not adopt the newer standard.
- `complete_async`, `complete_stream_async`, `complete_chat_async`, and
`complete_chat_stream_async` now support settings field
`number_of_responses` greater than 1. Previously only a value of 1 was
supported.
- **Note: hf_text_completion does not support streaming multiple
responses due to a limitation of TextIteratorStreamer. This feature
requires the ability to parse distinct responses from
TextIteratorStreamer.**
- Fixed a bug where `complete_async` was streaming single responses as
1D arrays, content now is simply a string.

### Example Usage
#### Setup
```
    kernel = sk.Kernel()

    # Configure OpenAI service
    api_key, org_id = sk.openai_settings_from_dot_env()
    oai_text_service = OpenAITextCompletion("text-davinci-003", api_key, org_id)
    oai_chat_service = OpenAIChatCompletion("gpt-3.5-turbo", api_key, org_id)

    # Configure Hugging Face service
    hf_text_service = HuggingFaceTextCompletion("gpt2", task="text-generation")
  
    # Configure Prompt
    prompt = "what is the purpose of a rubber duck?"

    # Configure Request Settings
    text_request_settings_multi = CompleteRequestSettings(
        max_tokens=100,
        temperature=0.7,
        top_p=1,
        frequency_penalty=0.5,
        presence_penalty=0.8,
        number_of_responses=4
    )

    chat_request_settings_multi = ChatRequestSettings(
        max_tokens=100,
        temperature=0.7,
        top_p=1,
        frequency_penalty=0.5,
        presence_penalty=0.8,
        number_of_responses=4
    )
```

#### Text Completion (Standard)
```
    texts = await oai_text_service.complete_async(prompt, text_request_settings_multi)
    i = 0
    for text in texts:
        print("Option " + str(i) + ": " + text)
        i += 1
```

#### Streaming Text Completion
```
    multi_stream = oai_text_service.complete_stream_async(prompt, text_request_settings_multi)
    texts = [''] * text_request_settings_multi.number_of_responses
    async for text in multi_stream:
        i = 0
        os.system('cls' if os.name == 'nt' else 'clear') # clear the screen for a better experience
        print("PROMPT: " + prompt)
        for option in text:
            texts[i] = texts[i] + option
            print("{0}: {1}".format(i, texts[i]))
            i += 1
```

#### Chat Completion (Standard)
```
    texts = await oai_chat_service.complete_chat_async([("user",prompt)], chat_request_settings_multi)
    i = 0
    for text in texts:
        print("Option " + str(i) + ": " + text)
        i += 1
```

#### Streaming Chat Completion
```
    multi_stream = oai_chat_service.complete_chat_stream_async([("user",prompt)], chat_request_settings_multi)
    texts = [''] * chat_request_settings_multi.number_of_responses
    async for text in multi_stream:
        i = 0
        os.system('cls' if os.name == 'nt' else 'clear') # clear the screen for a better experience
        print("PROMPT: " + prompt)
        for option in text:
            texts[i] = texts[i] + option
            print("{0}: {1}".format(i, texts[i]))
            i += 1
```

#### HuggingFace Standard Completion
```
    texts = await hf_text_service.complete_async(prompt, request_settings_multi)
    i = 0
    for text in texts:
        print("-----------------------------------")
        print("Option " + str(i) + ": " + text)
        i += 1
```
 2023-06-09 14:13:45 -07:00
Abby Harrison 7a884d4e57 Python: make abstraction usage consistent (#1052) 
### Motivation and Context
Use of abstraction was not consistent in the python SK. This PR makes
the import and use of ABC consistent and removes unused file kernel.py.

### Description
- MemoryStoreBase derives from ABC - this properly sets its metaclass.
MemoryStoreBase itself should never be instantiated, only derived.
- RetryMechanism derives ABC, so should be named 'Base' like all other
derivatives of ABC in this repo.
- removed kernel_base.py, was made obsolete by
https://github.com/microsoft/semantic-kernel/pull/1015
 2023-05-19 11:42:26 -07:00
Abby Harrison 493dfc1b61 Python: Merge Kernel, KernelBase, KernelExtensions (#1015) 
### Motivation and Context
The separation of Kernel, KernelBase, and KernelExtensions is several
layers of unnecessary abstraction. This PR does not change any API or
kernel behavior - it just reduces the number of files and namespaces to
accomplish the same functionality.


### Description
- Removed the `semantic_kernel/kernel_extensions` namespace. Methods
that existed in this namespace now exist in kernel.py.
- Removed KernelBase - this abstract class implies that there are
multiple ways to instantiate SK. For Python, we expect only a single
type of Kernel to instantiated for all instances.
- Updated tests and imports to accommodate the above changes.
 2023-05-17 15:38:02 -07:00
Devis Lucato de3436d02f Python: fixes and release (#855) 
* Fix lint errors
* Bump version number
* Add retry loop to integration tests
* Enable all integration tests: some tests will fail if OpenAI/Azure are
throttling.
 2023-05-08 15:52:48 -07:00