feat: Adding Docling RAG demo

[franciscojavierarceo]

What this PR does / why we need it:

This PR introduces enhancements to the RAG (Retrieval-Augmented Generation) demo, adds support for PDF transformation with Docling, and updates various components for better feature handling and testing.

• examples/rag-docling/*

  • Updated the quickstart guide to include Docling and Milvus usage for transforming PDFs and storing/retrieving embeddings.
  • Added a new notebook (docling-demo.ipynb) demonstrating the use of Docling for text extraction from PDFs.
  • Added a new notebook (docling-quickstart.ipynb) showing how to use Feast to ingest and retrieve text data from the online store.
  • Introduced new functions for embedding text and generating chunk IDs.
  • Added support for Docling and Milvus in feature definitions and transformations.
  • Enhanced feature view configurations for PDF handling.
  • Updated the configuration to use Milvus as the online store with vector search capabilities.

• sdk/python/feast/feature_store.py

  • Enhanced _get_feature_view_and_df_for_online_write to handle feature view transformations differently for singleton and non-singleton cases.

• sdk/python/tests/unit/online_store/test_online_retrieval.py

  • Uncommented a previously skipped test for local Milvus to ensure it runs in CI.

• sdk/python/tests/unit/online_store/test_online_writes.py

  • Added a new test class TestOnlineWritesWithTransform to validate PDF handling and feature transformations during online writes.

• sdk/python/tests/unit/test_on_demand_python_transformation.py

  • Updated the test for docling_transform_docs to handle multiple inputs and validate the transformation logic.

Which issue(s) this PR fixes:

N/A

Misc:

N/A