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Release 8.17.0
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‎docs/examples/00fea15cbca83be9d5f1a024ff2ec708.asciidoc

+1-1
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@@ -1,5 +1,5 @@
11
// This file is autogenerated, DO NOT EDIT
2-
// inference/service-elasticsearch.asciidoc:163
2+
// inference/service-elasticsearch.asciidoc:190
33

44
[source, python]
55
----

‎docs/examples/015e6e6132b6d6d44bddb06bc3b316ed.asciidoc

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// This file is autogenerated, DO NOT EDIT
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// search/search-your-data/retrievers-examples.asciidoc:789
3+
4+
[source, python]
5+
----
6+
resp = client.search(
7+
index="retrievers_example",
8+
retriever={
9+
"rrf": {
10+
"retrievers": [
11+
{
12+
"standard": {
13+
"query": {
14+
"range": {
15+
"year": {
16+
"gt": 2023
17+
}
18+
}
19+
}
20+
}
21+
},
22+
{
23+
"standard": {
24+
"query": {
25+
"term": {
26+
"topic": "elastic"
27+
}
28+
}
29+
}
30+
}
31+
],
32+
"rank_window_size": 10,
33+
"rank_constant": 1
34+
}
35+
},
36+
source=False,
37+
aggs={
38+
"topics": {
39+
"terms": {
40+
"field": "topic"
41+
}
42+
}
43+
},
44+
)
45+
print(resp)
46+
----

‎docs/examples/0165d22da5f2fc7678392b31d8eb5566.asciidoc

+18
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@@ -0,0 +1,18 @@
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// This file is autogenerated, DO NOT EDIT
2+
// search/search-your-data/retrievers-examples.asciidoc:1101
3+
4+
[source, python]
5+
----
6+
resp = client.inference.put(
7+
task_type="rerank",
8+
inference_id="my-rerank-model",
9+
inference_config={
10+
"service": "cohere",
11+
"service_settings": {
12+
"model_id": "rerank-english-v3.0",
13+
"api_key": "{{COHERE_API_KEY}}"
14+
}
15+
},
16+
)
17+
print(resp)
18+
----

‎docs/examples/0709a38613d2de90d418ce12b36af30e.asciidoc

+1-1
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@@ -1,5 +1,5 @@
11
// This file is autogenerated, DO NOT EDIT
2-
// troubleshooting/common-issues/red-yellow-cluster-status.asciidoc:109
2+
// troubleshooting/common-issues/red-yellow-cluster-status.asciidoc:113
33

44
[source, python]
55
----

‎docs/examples/0722b302b2b3275a988d858044f99d5d.asciidoc

+10
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@@ -0,0 +1,10 @@
1+
// This file is autogenerated, DO NOT EDIT
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// quickstart/aggs-tutorial.asciidoc:45
3+
4+
[source, python]
5+
----
6+
resp = client.indices.get_mapping(
7+
index="kibana_sample_data_ecommerce",
8+
)
9+
print(resp)
10+
----

‎docs/examples/083b92e8ea264e49bf9fd40fc6a3094b.asciidoc

+1-1
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@@ -1,5 +1,5 @@
11
// This file is autogenerated, DO NOT EDIT
2-
// inference/service-elasticsearch.asciidoc:223
2+
// inference/service-elasticsearch.asciidoc:250
33

44
[source, python]
55
----

‎docs/examples/0bc6155e0c88062a4d8490da49db3aa8.asciidoc

+57
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@@ -0,0 +1,57 @@
1+
// This file is autogenerated, DO NOT EDIT
2+
// search/search-your-data/retrievers-examples.asciidoc:550
3+
4+
[source, python]
5+
----
6+
resp = client.search(
7+
index="retrievers_example_nested",
8+
retriever={
9+
"rrf": {
10+
"retrievers": [
11+
{
12+
"standard": {
13+
"query": {
14+
"nested": {
15+
"path": "nested_field",
16+
"inner_hits": {
17+
"name": "nested_vector",
18+
"_source": False,
19+
"fields": [
20+
"nested_field.paragraph_id"
21+
]
22+
},
23+
"query": {
24+
"knn": {
25+
"field": "nested_field.nested_vector",
26+
"query_vector": [
27+
1,
28+
0,
29+
0.5
30+
],
31+
"k": 10
32+
}
33+
}
34+
}
35+
}
36+
}
37+
},
38+
{
39+
"standard": {
40+
"query": {
41+
"term": {
42+
"topic": "ai"
43+
}
44+
}
45+
}
46+
}
47+
],
48+
"rank_window_size": 10,
49+
"rank_constant": 1
50+
}
51+
},
52+
source=[
53+
"topic"
54+
],
55+
)
56+
print(resp)
57+
----

‎docs/examples/0bee07a581c5776e068f6f4efad5a399.asciidoc

+8-3
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@@ -1,10 +1,15 @@
11
// This file is autogenerated, DO NOT EDIT
2-
// esql/esql-across-clusters.asciidoc:197
2+
// esql/esql-across-clusters.asciidoc:192
33

44
[source, python]
55
----
6-
resp = client.esql.async_query(
7-
format="json",
6+
resp = client.perform_request(
7+
"POST",
8+
"/_query/async",
9+
params={
10+
"format": "json"
11+
},
12+
headers={"Content-Type": "application/json"},
813
body={
914
"query": "\n FROM my-index-000001,cluster_one:my-index-000001,cluster_two:my-index*\n | STATS COUNT(http.response.status_code) BY user.id\n | LIMIT 2\n ",
1015
"include_ccs_metadata": True

‎docs/examples/160986f49758f4e8345d183a842f6351.asciidoc renamed to ‎docs/examples/0c52af573c9401a2a687e86a4beb182b.asciidoc

+2-2
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@@ -1,5 +1,5 @@
11
// This file is autogenerated, DO NOT EDIT
2-
// ingest/processors/attachment.asciidoc:165
2+
// ingest/processors/attachment.asciidoc:214
33

44
[source, python]
55
----
@@ -10,7 +10,7 @@ resp = client.ingest.put_pipeline(
1010
{
1111
"attachment": {
1212
"field": "data",
13-
"remove_binary": False
13+
"remove_binary": True
1414
}
1515
}
1616
],

‎docs/examples/0d689ac6e78be5d438f9b5d441be2b44.asciidoc

+60
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@@ -0,0 +1,60 @@
1+
// This file is autogenerated, DO NOT EDIT
2+
// search/search-your-data/retrievers-examples.asciidoc:929
3+
4+
[source, python]
5+
----
6+
resp = client.search(
7+
index="retrievers_example",
8+
retriever={
9+
"rrf": {
10+
"retrievers": [
11+
{
12+
"standard": {
13+
"query": {
14+
"term": {
15+
"topic": "elastic"
16+
}
17+
}
18+
}
19+
},
20+
{
21+
"rrf": {
22+
"retrievers": [
23+
{
24+
"standard": {
25+
"query": {
26+
"query_string": {
27+
"query": "(information retrieval) OR (artificial intelligence)",
28+
"default_field": "text"
29+
}
30+
}
31+
}
32+
},
33+
{
34+
"knn": {
35+
"field": "vector",
36+
"query_vector": [
37+
0.23,
38+
0.67,
39+
0.89
40+
],
41+
"k": 3,
42+
"num_candidates": 5
43+
}
44+
}
45+
],
46+
"rank_window_size": 10,
47+
"rank_constant": 1
48+
}
49+
}
50+
],
51+
"rank_window_size": 10,
52+
"rank_constant": 1
53+
}
54+
},
55+
source=False,
56+
size=1,
57+
explain=True,
58+
)
59+
print(resp)
60+
----

‎docs/examples/0da747e9d98bae157d3520ff1b489ad4.asciidoc

+1-1
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// This file is autogenerated, DO NOT EDIT
2-
// snapshot-restore/repository-s3.asciidoc:41
2+
// snapshot-restore/repository-s3.asciidoc:45
33

44
[source, python]
55
----

‎docs/examples/0dfde6a9d953822fd4b3aa0121ddd8fb.asciidoc

+4-2
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@@ -3,8 +3,10 @@
33

44
[source, python]
55
----
6-
resp = client.search_application.render_query(
7-
name="my-app",
6+
resp = client.perform_request(
7+
"POST",
8+
"/_application/search_application/my-app/_render_query",
9+
headers={"Content-Type": "application/json"},
810
body={
911
"params": {
1012
"query_string": "my first query",

‎docs/examples/11e8d6e14686efabb8634b6522c05cb5.asciidoc

+1-1
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11
// This file is autogenerated, DO NOT EDIT
2-
// search/search-your-data/highlighting.asciidoc:455
2+
// search/search-your-data/highlighting.asciidoc:453
33

44
[source, python]
55
----

‎docs/examples/15f769bbd7b5fddeb3353ae726b71b14.asciidoc

+1-1
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@@ -1,5 +1,5 @@
11
// This file is autogenerated, DO NOT EDIT
2-
// vectors/vector-functions.asciidoc:401
2+
// vectors/vector-functions.asciidoc:405
33

44
[source, python]
55
----

‎docs/examples/16634cfa7916cf4e8048a1d70e6240f2.asciidoc

+1-1
Original file line numberDiff line numberDiff line change
@@ -12,7 +12,7 @@ resp = client.search_application.put(
1212
"template": {
1313
"script": {
1414
"lang": "mustache",
15-
"source": "\n {\n \"query\": {\n \"bool\": {\n \"must\": [\n {{#query}}\n \n {{/query}}\n ],\n \"filter\": {{#toJson}}_es_filters{{/toJson}}\n }\n },\n \"_source\": {\n \"includes\": [\"title\", \"plot\"]\n },\n \"highlight\": {\n \"fields\": {\n \"title\": { \"fragment_size\": 0 },\n \"plot\": { \"fragment_size\": 200 }\n }\n },\n \"aggs\": {{#toJson}}_es_aggs{{/toJson}},\n \"from\": {{from}},\n \"size\": {{size}},\n \"sort\": {{#toJson}}_es_sort_fields{{/toJson}}\n }\n ",
15+
"source": "\n {\n \"query\": {\n \"bool\": {\n \"must\": [\n {{#query}}\n {{/query}}\n ],\n \"filter\": {{#toJson}}_es_filters{{/toJson}}\n }\n },\n \"_source\": {\n \"includes\": [\"title\", \"plot\"]\n },\n \"highlight\": {\n \"fields\": {\n \"title\": { \"fragment_size\": 0 },\n \"plot\": { \"fragment_size\": 200 }\n }\n },\n \"aggs\": {{#toJson}}_es_aggs{{/toJson}},\n \"from\": {{from}},\n \"size\": {{size}},\n \"sort\": {{#toJson}}_es_sort_fields{{/toJson}}\n }\n ",
1616
"params": {
1717
"query": "",
1818
"_es_filters": {},

‎docs/examples/17a1e308761afd3282f13d44d7be008a.asciidoc

+1-1
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@@ -1,5 +1,5 @@
11
// This file is autogenerated, DO NOT EDIT
2-
// search/search-your-data/highlighting.asciidoc:687
2+
// search/search-your-data/highlighting.asciidoc:685
33

44
[source, python]
55
----

‎docs/examples/c02c2916b97b6fa7db82dbc7f0378310.asciidoc renamed to ‎docs/examples/17b1647c8509543f2388c886f2584a20.asciidoc

+2-2
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@@ -1,5 +1,5 @@
11
// This file is autogenerated, DO NOT EDIT
2-
// reranking/semantic-reranking.asciidoc:105
2+
// reranking/semantic-reranking.asciidoc:107
33

44
[source, python]
55
----
@@ -16,7 +16,7 @@ resp = client.search(
1616
}
1717
},
1818
"field": "text",
19-
"inference_id": "my-cohere-rerank-model",
19+
"inference_id": "elastic-rerank",
2020
"inference_text": "How often does the moon hide the sun?",
2121
"rank_window_size": 100,
2222
"min_score": 0.5

‎docs/examples/192fa1f6f51dfb640e9e15bb5cd7eebc.asciidoc

+1-1
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11
// This file is autogenerated, DO NOT EDIT
2-
// ilm/error-handling.asciidoc:147
2+
// ilm/error-handling.asciidoc:148
33

44
[source, python]
55
----

‎docs/examples/19c00c6b29bc7dbc5e92b3668da2da93.asciidoc

+4-1
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@@ -3,7 +3,10 @@
33

44
[source, python]
55
----
6-
resp = client.simulate.ingest(
6+
resp = client.perform_request(
7+
"POST",
8+
"/_ingest/_simulate",
9+
headers={"Content-Type": "application/json"},
710
body={
811
"docs": [
912
{

‎docs/examples/1aa91d3d48140d6367b6cabca8737b8f.asciidoc

+1-1
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@@ -1,5 +1,5 @@
11
// This file is autogenerated, DO NOT EDIT
2-
// docs/bulk.asciidoc:632
2+
// docs/bulk.asciidoc:636
33

44
[source, python]
55
----

‎docs/examples/1b37e2237c9e3aaf84d56cc5c0bdb9ec.asciidoc

+1-1
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,5 @@
11
// This file is autogenerated, DO NOT EDIT
2-
// ilm/error-handling.asciidoc:18
2+
// ilm/error-handling.asciidoc:19
33

44
[source, python]
55
----

‎docs/examples/22b176a184517cf1b5801f5eb4f17f97.asciidoc

+10
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@@ -0,0 +1,10 @@
1+
// This file is autogenerated, DO NOT EDIT
2+
// data-streams/downsampling-dsl.asciidoc:349
3+
4+
[source, python]
5+
----
6+
resp = client.indices.rollover(
7+
alias="datastream",
8+
)
9+
print(resp)
10+
----

‎docs/examples/2577acb462b95bd4394523cf2f8a661f.asciidoc

-33
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