huggingface / huggingface/cookbook

RAG: Question Answering using Gemma, Elasticsearch & langchain

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Dominant language
Jupyter Notebook
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Forks
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Merged PRs (30d)
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Description

This is Ashish from [Elastic](https://www.elastic.co/). I'm interested in sharing a notebook that showcases RAG implementation using Elasticsearch. The notebook will illustrate how we generate vectors using Elastic's ELSER model and retrieve semantic results. We'll be utilizing Gemma for contextual question answering.

Contributor guide

No contributing guide indexed for this repository

Research direction

Review the cookbook's existing notebook structure and identify where a RAG example using Elasticsearch, ELSER, and Gemma would fit. Confirm the expected setup and presentation conventions before adding the notebook. Done means a self-contained notebook demonstrates vector generation, semantic retrieval, and contextual question answering.

Written by the indexing model from the issue text.

Assessment

Tech stack
elasticsearch, jupyter-notebook
Domain
machine-learning, search
Issue type
Feature
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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