### 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
Porting the text partitioning module to python
(Reopening of PR #427 )
### Description
- This is adding the Text partitioning module in
`semantic_kernel/semantic_functions/semantic_text_partitioner.py`
and the function_extention in
`semantic_kernel/semantic_functions/function_extension.py`
- Compared to the C# version the files were added directly into the
`semantic_functions` directory instead of the
`semantic_functions/partitioning` to not have too many nested
directories.
Devis Lucato