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// This file is autogenerated, DO NOT EDIT
// search/search-your-data/retrievers-examples.asciidoc:14
[source, python]
----
resp = client.indices.create(
index="retrievers_example",
settings={
"number_of_shards": 1
},
mappings={
"properties": {
"vector": {
"type": "dense_vector",
"dims": 3,
"similarity": "l2_norm",
"index": True,
"index_options": {
"type": "flat"
}
},
"text": {
"type": "text"
},
"year": {
"type": "integer"
},
"topic": {
"type": "keyword"
},
"timestamp": {
"type": "date"
}
}
},
)
print(resp)
resp1 = client.index(
index="retrievers_example",
id="1",
document={
"vector": [
0.23,
0.67,
0.89
],
"text": "Large language models are revolutionizing information retrieval by boosting search precision, deepening contextual understanding, and reshaping user experiences in data-rich environments.",
"year": 2024,
"topic": [
"llm",
"ai",
"information_retrieval"
],
"timestamp": "2021-01-01T12:10:30"
},
)
print(resp1)
resp2 = client.index(
index="retrievers_example",
id="2",
document={
"vector": [
0.12,
0.56,
0.78
],
"text": "Artificial intelligence is transforming medicine, from advancing diagnostics and tailoring treatment plans to empowering predictive patient care for improved health outcomes.",
"year": 2023,
"topic": [
"ai",
"medicine"
],
"timestamp": "2022-01-01T12:10:30"
},
)
print(resp2)
resp3 = client.index(
index="retrievers_example",
id="3",
document={
"vector": [
0.45,
0.32,
0.91
],
"text": "AI is redefining security by enabling advanced threat detection, proactive risk analysis, and dynamic defenses against increasingly sophisticated cyber threats.",
"year": 2024,
"topic": [
"ai",
"security"
],
"timestamp": "2023-01-01T12:10:30"
},
)
print(resp3)
resp4 = client.index(
index="retrievers_example",
id="4",
document={
"vector": [
0.34,
0.21,
0.98
],
"text": "Elastic introduces Elastic AI Assistant, the open, generative AI sidekick powered by ESRE to democratize cybersecurity and enable users of every skill level.",
"year": 2023,
"topic": [
"ai",
"elastic",
"assistant"
],
"timestamp": "2024-01-01T12:10:30"
},
)
print(resp4)
resp5 = client.index(
index="retrievers_example",
id="5",
document={
"vector": [
0.11,
0.65,
0.47
],
"text": "Learn how to spin up a deployment of our hosted Elasticsearch Service and use Elastic Observability to gain deeper insight into the behavior of your applications and systems.",
"year": 2024,
"topic": [
"documentation",
"observability",
"elastic"
],
"timestamp": "2025-01-01T12:10:30"
},
)
print(resp5)
resp6 = client.indices.refresh(
index="retrievers_example",
)
print(resp6)
----
|
