Add a RAG via Elasticsearch, Hugging Face models cookbook #124
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I thought it would be useful to provide a cookbook for a RAG backed by Elasticsearch, Huggingface models, and Gemma. Users can easily toggle between vectorisation that is offloaded to ES and self-provided (pre)-vectorisation. This is based on the excellent MongoDB notebook and dataset. Signed-off-by: lloydmeta <[email protected]>
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lloydmeta
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lloydmeta
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
stevhliu
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Jun 24, 2024
Signed-off-by: lloydmeta <[email protected]>
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Thanks for your thorough review @stevhliu 🙇♂️ As noted above, the image change requires merging https://huggingface.co/datasets/huggingface/cookbook-images/discussions/20 |
lloydmeta
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stevhliu
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Jun 25, 2024
stevhliu
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Jun 25, 2024
Signed-off-by: lloydmeta <[email protected]>
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Thanks @stevhliu , really appreciate your patience in this review; it's my first Jupyter notebook PR and I'm not used to the UI (e.g. accidentally adding a blank cell 🤦🏻♂️) and the way diffs/suggestions are shown. |
merveenoyan
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Jun 26, 2024
merveenoyan
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Jun 26, 2024
Move the embedding and embedding model-related settings down. Add some links and info Signed-off-by: lloydmeta <[email protected]>
* Fix Eland version to avoid breaking changes * Switch to CPU usage by default Signed-off-by: lloydmeta <[email protected]>
Signed-off-by: lloydmeta <[email protected]>
Signed-off-by: lloydmeta <[email protected]>
Signed-off-by: lloydmeta <[email protected]>
stevhliu
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Jun 26, 2024
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What does this PR do?
I thought it would be useful to provide a cookbook for a RAG backed by Elasticsearch, Hugging Face models, and Gemma.
Users can easily toggle between vectorisation that is offloaded to ES and self-provided (pre)-vectorisation.
Who can review?
Feel free to tag members/contributors who may be interested in your PR.