Add example: Multimodal RAG on xlsx file with ColQwen2

[IntelligentCow]

An example notebook of integrating ColQwen2 in RAG pipeline to improve its performance in processing complex files.

Description

Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.

Fixes # (issue)

New Package?

Did I fill in the tool.llamahub section in the pyproject.toml and provide a detailed README.md for my new integration or package?

• Yes
• No

Version Bump?

Did I bump the version in the pyproject.toml file of the package I am updating? (Except for the llama-index-core package)

• Yes
• No

Type of Change

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• Add example

How Has This Been Tested?

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• I added new unit tests to cover this change
• I believe this change is already covered by existing unit tests

Suggested Checklist:

• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• I have added Google Colab support for the newly added notebooks.
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes
• I ran make format; make lint to appease the lint gods

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[logan-markewich]

This is cool, but it largely doesn't use llama-index for... anything?

Using the llm at the end is cool, but

• no llama-index data loaders are used
• no llama-index retirevers are used
• no llama-index embeddings are used