Python <3 Elasticsearch

A collection of Elasticsearch examples and use cases; use as a reference or cheat sheet for working with python + elastic

Starting out with Elasticsearch

Connect to the Elastic server, create an index, add documents, run a simple query. notebook

Loading data
Using parallel_bulk
Perform actions when ingesting data, for example an ingest pipeline adding a timestamp any time a document is updated. notebook

Build a simple classifier with the more like this query without any ML. notebook
Importing NLP third party models (LLMs) or ELSER and performing searches based on semantic data. notebook
Huggingface Examples
Langchain Examples
Observability & Tracking

Name		Name	Last commit message	Last commit date
Latest commit History 32 Commits
Elasticsearch-101		Elasticsearch-101
img		img
.gitignore		.gitignore
Classifier with MLT Query.ipynb		Classifier with MLT Query.ipynb
Elastic LLM Models and Semantic Search.ipynb		Elastic LLM Models and Semantic Search.ipynb
Huggingface examples.ipynb		Huggingface examples.ipynb
Ingest pipelines with timestamps.ipynb		Ingest pipelines with timestamps.ipynb
LICENSE		LICENSE
Langchain Chains Example.ipynb		Langchain Chains Example.ipynb
README.md		README.md
Scaling Inference ML.ipynb		Scaling Inference ML.ipynb
Simple Query.ipynb		Simple Query.ipynb
loading_data.py		loading_data.py
requirements.txt		requirements.txt
using_parallel_bulk.py		using_parallel_bulk.py