### 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- Did not run notebooks because they are out of date with the current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
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]>
### Motivation and Context
The `python-preview` branch is under active development and many
docs/tests/examples are getting a bit out of sync. There are also a few
small cleanup chores/refactors to make _usage_ easier (e.g., to make
examples cleaner). I've grouped these small fixes (plus a few bug fixes)
into this "cleanup" PR.
### Description
This PR does the following:
1. Updates the out-of-date example in `README.md`
2. Fixes all 5 of the notebooks we support right now (1,2,3,4, and 6;
notebook 5 is planner, I've blanked out most of the code there so we
don't confuse people, especially as the planner API is changing)
3. Fixes a bug w/ `stop_sequences` in `(Azure)OpenAITextCompletion`
4. Fixes a bug introduced in our upgrades to the embeddings cosine-sim
check (we should add more thorough tests here)
5. Cleans up tests
6. Ensures end-to-end tests are all runnable
7. Fixes up the `kernel_extensions` to work more naturally (so that end
users can use them directly on the `kernel` object and get good
type-hinting)
### Motivation and Context
Right now, there are lots of Config classes in SK. This doesn't feel
very "pythonic" and can be a bit confusing at times. To reduce the
amount of indirection, this PR removes several config classes from the
Python port.
NOTE: this PR is also critical preparation for a large change to re-sync
with how C# SK handles multi-modality. I have changes ready for adding a
`./connectors` dir and syncing with the Text/Chat/Image/Embedding
support, but there's a few "prep" PRs I need to get through first.
### Description
This PR makes the following changes:
1. We remove the `(Azure)OpenAIConfig` classes (simplifying the code
related to creating/managing backends)
2. We remove the `./configuration` sub-directory and move the
`KernelConfig` class to the module's root dir (this mirrors the C#
version)
3. We re-tool the `KernelConfig` class to behave similarly to the
current C# version (again, this is prep for later changes RE
multi-modality)
4. We make corresponding updates across the code/tests now that we've
removed some config classes
In future PRs, it'd be great to also simplify:
1. `(Chat|Completion)RequestSettings`
2. `(ReadOnly)SkillsCollection` and related classes
3. Take a hard look at `ContextVariables` and `SKContext` (maybe
`ContextVariables` is just a `dict` in SK python)
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.
