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Add example to text chunking processor documentation #6794
Add example to text chunking processor documentation #6794
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Signed-off-by: yuye-aws <[email protected]>
Signed-off-by: yuye-aws <[email protected]>
Signed-off-by: Fanit Kolchina <[email protected]>
Signed-off-by: yuye-aws <[email protected]>
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@yuye-aws @kolchfa-aws Please see my comments and changes and let me know if you have any questions. Thanks!
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{% include copy-curl.html %} | ||
Once you have created an ingest pipeline, you need to create an index for ingestion and ingest documents into the index. To learn more, see [Text chunking]({{site.url}}{{site.baseurl}}/search-plugins/text-chunking/). |
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The text after the comma in the first sentence is a bit redundant. Can we simplify?
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Shall we also change the sentence from other files like text-image-embedding.md
?
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Creating an index is a separate step so I think separating the two makes sense, even though "ingest" appears in both parts of the sentence.
_search-plugins/text-chunking.md
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## Step 2: Create an index for ingestion | ||
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In order to use the ingest pipeline, you need to create a k-NN index. The `passage_chunk_embedding` field must be of a `nested` type. The `knn.dimension` field must contain the number of dimensions for your model: |
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"the" nested
type?
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Already changed
_search-plugins/text-chunking.md
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## Step 4: Search the index using neural search | ||
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You can use a `nested` query to perform vector search on your index. We recommend setting `score_mode` to `max`, where the document score is set to the maximum of the scores from all passage embeddings: |
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Is "maximum" the right word here, or do we mean "highest"?
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Either way. Changed to "highest".
Co-authored-by: Nathan Bower <[email protected]> Signed-off-by: Yuye Zhu <[email protected]>
Co-authored-by: Nathan Bower <[email protected]> Signed-off-by: Yuye Zhu <[email protected]>
Signed-off-by: yuye-aws <[email protected]>
Signed-off-by: Fanit Kolchina <[email protected]>
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LGTM. Thank you, @yuye-aws!
Description
Add example to text chunking processor documentation
Issues Resolved
Add example to text chunking processor documentation #6707
Checklist
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