Add ability in Token Counter to retrieve Open AI cached_tokens #17372

[sangwonku]

Description

This PR includes the implementation of the cached_tokens field in the TokenCountingEvent class and the corresponding updates in the TokenCountingHandler. It addresses issue #17372. The motivation behind this change is to accurately track cached tokens along with prompt and completion tokens, improving the token counting functionality.

Fixes #17372

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
• [ x] 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
• [x ] No

Type of Change

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• Bug fix (non-breaking change which fixes an issue)
• [x ] New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

How Has This Been Tested?

Your pull-request will likely not be merged unless it is covered by some form of impactful unit testing.

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

Suggested Checklist:

• [ x] I have performed a self-review of my own code
• [ x] 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.
• [ x] My changes generate no new warnings
• [ x] I have added tests that prove my fix is effective or that my feature works
• [ x] New and existing unit tests pass locally with my changes
• [ x] I ran make format; make lint to appease the lint gods

[logan-markewich]

this works for openai. But for llms that charge based on cache_read and cache_write (like anthropic), this approach doesn't translate well 🤔