# The length of the embedding contents

**URL:** <https://community.openai.com/t/the-length-of-the-embedding-contents/111471>\
**Category:** API\
**Created:** [March 21, 2023, 2:29pm UTC](https://community.openai.com/t/the-length-of-the-embedding-contents/111471 "2023-03-21T14:29:49Z")\
**Posts on this page:** 1\
**Showing post:** 12

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**Author:** ![AgusPG](https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/aguspg/32/41789_2.png) [@AgusPG](https://community.openai.com/u/AgusPG)\
**Post date:** [March 22, 2023, 7:43pm UTC](https://community.openai.com/t/the-length-of-the-embedding-contents/111471/12 "2023-03-22T19:43:06Z")

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What I don’t understand is point 3. What do you mean by “I use title and subtitle to index embedding, and I store the content as meta\_data to get to the content of the embed. I use the content as the text of the prompt context.“?

How is your actual call to the embedding endpoint? Can you share it with us?

If I were you, I’d def incorporate “title” and “subtitle” as global context of each chunk prior to embed it. I’d incorporate some other global metadata as well (timestamps? Author of each document? Short summary of the whole doc or at least key entities extracted via NER?)

The local context is a little bit more tricky, so I’d probably leave it for later 🙂.

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