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| DELETE main | |
| PUT main/_doc/1 | |
| { | |
| "timestamp": "2025-10-12T00:00:00", | |
| "symbol": "ESTC", | |
| "price": 10.5 | |
| } | |
| PUT main/_doc/2 | |
| { | |
| "timestamp": "2025-10-13T00:00:00", |
xeraa
/ gist:8f0f4b2d09b583145de8b10bffb1be54
Created
September 2, 2025 17:58
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| GET / | |
| GET _analyze | |
| { | |
| "text": "These are <em>not</em> the droids you are looking for." | |
| } | |
| PUT starwars | |
| { | |
| "settings": { |
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| DELETE my-index | |
| PUT my-index | |
| { | |
| "mappings": { | |
| "properties": { | |
| "title": { | |
| "type": "text" | |
| }, | |
| "title_vector": { |
xeraa
/ beckrock-semantic_text.json
Created
February 2, 2025 01:56
Getting started with semantic_text on AWS Bedrock
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| GET / | |
| PUT starwars | |
| { | |
| "settings": { | |
| "analysis": { | |
| "analyzer": { | |
| "my_analyzer": { | |
| "char_filter": [ | |
| "html_strip" |
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| ollama run llama3.2:1b | |
| curl http://localhost:11434/v1/models --silent | jq | |
| curl http://localhost:11434/v1/embeddings --silent --json '{ "model": "llama3.2:1b", "input": ["You Know, for Search"] }' | jq | |
| curl -fsSL https://elastic.co/start-local | sh |
xeraa
/ nested-metadata.json
Last active
July 13, 2024 00:11
Include metadata with dense vector chunks in Elasticsearch
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| PUT audio | |
| { | |
| "mappings": { | |
| "properties": { | |
| "my_long_content": { | |
| "type": "nested", //because there can be multiple vectors per doc | |
| "properties": { | |
| "vector": { | |
| "type": "dense_vector" //the vector used for ranking | |
| }, |
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| GET / | |
| DELETE starwars | |
| DELETE semantic-starwars | |
| PUT starwars | |
| { | |
| "settings": { | |
| "analysis": { | |
| "analyzer": { |
xeraa
/ chunking-multi-vector.json
Last active
May 12, 2024 21:56
Elasticsearch example for chunked documents to multi-vectors and two different retrieval strategies
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| DELETE my-long-text-index | |
| PUT my-long-text-index | |
| { | |
| "mappings": { | |
| "properties": { | |
| "my_long_text_field": { | |
| "type": "nested", //because there can be multiple vectors per doc | |
| "properties": { | |
| "vector": { |
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| See https://xeraa.net/talks/elasticsearch-piped-query-language-esql/ for an updated version :) |
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| GET bytes-discuss-dense-search/_search | |
| { | |
| "query": { | |
| "multi_match": { | |
| "fields": [ "title" ], | |
| "query": "I don't know how to use ingest pipelines" | |
| } | |
| }, | |
| "size": 6, | |
| "fields": [ "title" ], |
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