package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.trieve.ai/api/dataset/batch_create_datasets"
payload := strings.NewReader("{\n \"datasets\": [\n {\n \"dataset_name\": \"<string>\",\n \"server_configuration\": {\n \"AIMON_RERANKER_TASK_DEFINITION\": \"Your task is to grade the relevance of context document(s) against the specified user query.\",\n \"BM25_AVG_LEN\": 256,\n \"BM25_B\": 0.75,\n \"BM25_ENABLED\": true,\n \"BM25_K\": 0.75,\n \"DISTANCE_METRIC\": \"cosine\",\n \"EMBEDDING_BASE_URL\": \"https://embedding.trieve.ai\",\n \"EMBEDDING_MODEL_NAME\": \"jina-base-en\",\n \"EMBEDDING_QUERY_PREFIX\": \"\",\n \"EMBEDDING_SIZE\": 768,\n \"FREQUENCY_PENALTY\": 0,\n \"FULLTEXT_ENABLED\": true,\n \"INDEXED_ONLY\": false,\n \"LLM_BASE_URL\": \"https://api.openai.com/v1\",\n \"LLM_DEFAULT_MODEL\": \"gpt-4o\",\n \"LOCKED\": false,\n \"MAX_LIMIT\": 10000,\n \"MESSAGE_TO_QUERY_PROMPT\": \"Write a 1-2 sentence semantic search query along the lines of a hypothetical response to: \\n\\n\",\n \"N_RETRIEVALS_TO_INCLUDE\": 8,\n \"PRESENCE_PENALTY\": 0,\n \"QDRANT_ONLY\": false,\n \"RAG_PROMPT\": \"Use the following retrieved documents to respond briefly and accurately:\",\n \"SEMANTIC_ENABLED\": true,\n \"STOP_TOKENS\": [\n \"\\n\\n\",\n \"\\n\"\n ],\n \"SYSTEM_PROMPT\": \"You are a helpful assistant\",\n \"TEMPERATURE\": 0.5,\n \"USE_MESSAGE_TO_QUERY_PROMPT\": false\n },\n \"tracking_id\": \"<string>\"\n }\n ],\n \"upsert\": true\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("TR-Organization", "<tr-organization>")
req.Header.Add("Authorization", "<api-key>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}
HttpResponse<String> response = Unirest.post("https://api.trieve.ai/api/dataset/batch_create_datasets")
.header("TR-Organization", "<tr-organization>")
.header("Authorization", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"datasets\": [\n {\n \"dataset_name\": \"<string>\",\n \"server_configuration\": {\n \"AIMON_RERANKER_TASK_DEFINITION\": \"Your task is to grade the relevance of context document(s) against the specified user query.\",\n \"BM25_AVG_LEN\": 256,\n \"BM25_B\": 0.75,\n \"BM25_ENABLED\": true,\n \"BM25_K\": 0.75,\n \"DISTANCE_METRIC\": \"cosine\",\n \"EMBEDDING_BASE_URL\": \"https://embedding.trieve.ai\",\n \"EMBEDDING_MODEL_NAME\": \"jina-base-en\",\n \"EMBEDDING_QUERY_PREFIX\": \"\",\n \"EMBEDDING_SIZE\": 768,\n \"FREQUENCY_PENALTY\": 0,\n \"FULLTEXT_ENABLED\": true,\n \"INDEXED_ONLY\": false,\n \"LLM_BASE_URL\": \"https://api.openai.com/v1\",\n \"LLM_DEFAULT_MODEL\": \"gpt-4o\",\n \"LOCKED\": false,\n \"MAX_LIMIT\": 10000,\n \"MESSAGE_TO_QUERY_PROMPT\": \"Write a 1-2 sentence semantic search query along the lines of a hypothetical response to: \\n\\n\",\n \"N_RETRIEVALS_TO_INCLUDE\": 8,\n \"PRESENCE_PENALTY\": 0,\n \"QDRANT_ONLY\": false,\n \"RAG_PROMPT\": \"Use the following retrieved documents to respond briefly and accurately:\",\n \"SEMANTIC_ENABLED\": true,\n \"STOP_TOKENS\": [\n \"\\n\\n\",\n \"\\n\"\n ],\n \"SYSTEM_PROMPT\": \"You are a helpful assistant\",\n \"TEMPERATURE\": 0.5,\n \"USE_MESSAGE_TO_QUERY_PROMPT\": false\n },\n \"tracking_id\": \"<string>\"\n }\n ],\n \"upsert\": true\n}")
.asString();
require 'uri'
require 'net/http'
url = URI("https://api.trieve.ai/api/dataset/batch_create_datasets")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["TR-Organization"] = '<tr-organization>'
request["Authorization"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"datasets\": [\n {\n \"dataset_name\": \"<string>\",\n \"server_configuration\": {\n \"AIMON_RERANKER_TASK_DEFINITION\": \"Your task is to grade the relevance of context document(s) against the specified user query.\",\n \"BM25_AVG_LEN\": 256,\n \"BM25_B\": 0.75,\n \"BM25_ENABLED\": true,\n \"BM25_K\": 0.75,\n \"DISTANCE_METRIC\": \"cosine\",\n \"EMBEDDING_BASE_URL\": \"https://embedding.trieve.ai\",\n \"EMBEDDING_MODEL_NAME\": \"jina-base-en\",\n \"EMBEDDING_QUERY_PREFIX\": \"\",\n \"EMBEDDING_SIZE\": 768,\n \"FREQUENCY_PENALTY\": 0,\n \"FULLTEXT_ENABLED\": true,\n \"INDEXED_ONLY\": false,\n \"LLM_BASE_URL\": \"https://api.openai.com/v1\",\n \"LLM_DEFAULT_MODEL\": \"gpt-4o\",\n \"LOCKED\": false,\n \"MAX_LIMIT\": 10000,\n \"MESSAGE_TO_QUERY_PROMPT\": \"Write a 1-2 sentence semantic search query along the lines of a hypothetical response to: \\n\\n\",\n \"N_RETRIEVALS_TO_INCLUDE\": 8,\n \"PRESENCE_PENALTY\": 0,\n \"QDRANT_ONLY\": false,\n \"RAG_PROMPT\": \"Use the following retrieved documents to respond briefly and accurately:\",\n \"SEMANTIC_ENABLED\": true,\n \"STOP_TOKENS\": [\n \"\\n\\n\",\n \"\\n\"\n ],\n \"SYSTEM_PROMPT\": \"You are a helpful assistant\",\n \"TEMPERATURE\": 0.5,\n \"USE_MESSAGE_TO_QUERY_PROMPT\": false\n },\n \"tracking_id\": \"<string>\"\n }\n ],\n \"upsert\": true\n}"
response = http.request(request)
puts response.read_body
[
{
"created_at": "2021-01-01 00:00:00.000",
"id": "e3e3e3e3-e3e3-e3e3-e3e3-e3e3e3e3e3e3",
"name": "Trieve",
"organization_id": "e3e3e3e3-e3e3-e3e3-e3e3-e3e3e3e3e3e3",
"server_configuration": {
"AIMON_RERANKER_TASK_DEFINITION": "Your task is to grade the relevance of context document(s) against the specified user query.",
"BM25_AVG_LEN": 256,
"BM25_B": 0.75,
"BM25_ENABLED": true,
"BM25_K": 0.75,
"DISTANCE_METRIC": "cosine",
"EMBEDDING_BASE_URL": "https://embedding.trieve.ai",
"EMBEDDING_MODEL_NAME": "jina-base-en",
"EMBEDDING_QUERY_PREFIX": "",
"EMBEDDING_SIZE": 768,
"FREQUENCY_PENALTY": 0,
"FULLTEXT_ENABLED": true,
"INDEXED_ONLY": false,
"LLM_BASE_URL": "https://api.openai.com/v1",
"LLM_DEFAULT_MODEL": "gpt-4o",
"LOCKED": false,
"MAX_LIMIT": 10000,
"MESSAGE_TO_QUERY_PROMPT": "Write a 1-2 sentence semantic search query along the lines of a hypothetical response to: \n\n",
"N_RETRIEVALS_TO_INCLUDE": 8,
"PRESENCE_PENALTY": 0,
"QDRANT_ONLY": false,
"RAG_PROMPT": "Use the following retrieved documents to respond briefly and accurately:",
"SEMANTIC_ENABLED": true,
"STOP_TOKENS": [
"\n\n",
"\n"
],
"SYSTEM_PROMPT": "You are a helpful assistant",
"TEMPERATURE": 0.5,
"USE_MESSAGE_TO_QUERY_PROMPT": false
},
"tracking_id": "foobar-dataset",
"updated_at": "2021-01-01 00:00:00.000"
}
]
{
"message": "Bad Request"
}
Dataset
Batch Create Datasets
Datasets will be created in the org specified via the TR-Organization header. Auth’ed user must be an owner of the organization to create datasets. If a tracking_id is ignored due to it already existing on the org, the response will not contain a dataset with that tracking_id and it can be assumed that a dataset with the missing tracking_id already exists.
POST
/
api
/
dataset
/
batch_create_datasets
Batch Create Datasets
curl --request POST \
--url https://api.trieve.ai/api/dataset/batch_create_datasets \
--header 'Authorization: <api-key>' \
--header 'Content-Type: application/json' \
--header 'TR-Organization: <tr-organization>' \
--data '
{
"datasets": [
{
"dataset_name": "<string>",
"server_configuration": {
"AIMON_RERANKER_TASK_DEFINITION": "Your task is to grade the relevance of context document(s) against the specified user query.",
"BM25_AVG_LEN": 256,
"BM25_B": 0.75,
"BM25_ENABLED": true,
"BM25_K": 0.75,
"DISTANCE_METRIC": "cosine",
"EMBEDDING_BASE_URL": "https://embedding.trieve.ai",
"EMBEDDING_MODEL_NAME": "jina-base-en",
"EMBEDDING_QUERY_PREFIX": "",
"EMBEDDING_SIZE": 768,
"FREQUENCY_PENALTY": 0,
"FULLTEXT_ENABLED": true,
"INDEXED_ONLY": false,
"LLM_BASE_URL": "https://api.openai.com/v1",
"LLM_DEFAULT_MODEL": "gpt-4o",
"LOCKED": false,
"MAX_LIMIT": 10000,
"MESSAGE_TO_QUERY_PROMPT": "Write a 1-2 sentence semantic search query along the lines of a hypothetical response to: \n\n",
"N_RETRIEVALS_TO_INCLUDE": 8,
"PRESENCE_PENALTY": 0,
"QDRANT_ONLY": false,
"RAG_PROMPT": "Use the following retrieved documents to respond briefly and accurately:",
"SEMANTIC_ENABLED": true,
"STOP_TOKENS": [
"\n\n",
"\n"
],
"SYSTEM_PROMPT": "You are a helpful assistant",
"TEMPERATURE": 0.5,
"USE_MESSAGE_TO_QUERY_PROMPT": false
},
"tracking_id": "<string>"
}
],
"upsert": true
}
'
import requests
url = "https://api.trieve.ai/api/dataset/batch_create_datasets"
payload = {
"datasets": [
{
"dataset_name": "<string>",
"server_configuration": {
"AIMON_RERANKER_TASK_DEFINITION": "Your task is to grade the relevance of context document(s) against the specified user query.",
"BM25_AVG_LEN": 256,
"BM25_B": 0.75,
"BM25_ENABLED": True,
"BM25_K": 0.75,
"DISTANCE_METRIC": "cosine",
"EMBEDDING_BASE_URL": "https://embedding.trieve.ai",
"EMBEDDING_MODEL_NAME": "jina-base-en",
"EMBEDDING_QUERY_PREFIX": "",
"EMBEDDING_SIZE": 768,
"FREQUENCY_PENALTY": 0,
"FULLTEXT_ENABLED": True,
"INDEXED_ONLY": False,
"LLM_BASE_URL": "https://api.openai.com/v1",
"LLM_DEFAULT_MODEL": "gpt-4o",
"LOCKED": False,
"MAX_LIMIT": 10000,
"MESSAGE_TO_QUERY_PROMPT": "Write a 1-2 sentence semantic search query along the lines of a hypothetical response to:
",
"N_RETRIEVALS_TO_INCLUDE": 8,
"PRESENCE_PENALTY": 0,
"QDRANT_ONLY": False,
"RAG_PROMPT": "Use the following retrieved documents to respond briefly and accurately:",
"SEMANTIC_ENABLED": True,
"STOP_TOKENS": ["
", "
"],
"SYSTEM_PROMPT": "You are a helpful assistant",
"TEMPERATURE": 0.5,
"USE_MESSAGE_TO_QUERY_PROMPT": False
},
"tracking_id": "<string>"
}
],
"upsert": True
}
headers = {
"TR-Organization": "<tr-organization>",
"Authorization": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)
const options = {
method: 'POST',
headers: {
'TR-Organization': '<tr-organization>',
Authorization: '<api-key>',
'Content-Type': 'application/json'
},
body: JSON.stringify({
datasets: [
{
dataset_name: '<string>',
server_configuration: {
AIMON_RERANKER_TASK_DEFINITION: 'Your task is to grade the relevance of context document(s) against the specified user query.',
BM25_AVG_LEN: 256,
BM25_B: 0.75,
BM25_ENABLED: true,
BM25_K: 0.75,
DISTANCE_METRIC: 'cosine',
EMBEDDING_BASE_URL: 'https://embedding.trieve.ai',
EMBEDDING_MODEL_NAME: 'jina-base-en',
EMBEDDING_QUERY_PREFIX: '',
EMBEDDING_SIZE: 768,
FREQUENCY_PENALTY: 0,
FULLTEXT_ENABLED: true,
INDEXED_ONLY: false,
LLM_BASE_URL: 'https://api.openai.com/v1',
LLM_DEFAULT_MODEL: 'gpt-4o',
LOCKED: false,
MAX_LIMIT: 10000,
MESSAGE_TO_QUERY_PROMPT: 'Write a 1-2 sentence semantic search query along the lines of a hypothetical response to: \n\n',
N_RETRIEVALS_TO_INCLUDE: 8,
PRESENCE_PENALTY: 0,
QDRANT_ONLY: false,
RAG_PROMPT: 'Use the following retrieved documents to respond briefly and accurately:',
SEMANTIC_ENABLED: true,
STOP_TOKENS: ['\n\n', '\n'],
SYSTEM_PROMPT: 'You are a helpful assistant',
TEMPERATURE: 0.5,
USE_MESSAGE_TO_QUERY_PROMPT: false
},
tracking_id: '<string>'
}
],
upsert: true
})
};
fetch('https://api.trieve.ai/api/dataset/batch_create_datasets', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));
Upsert when a dataset with one of the specified tracking_ids already exists. By default this is false and specified datasets with a tracking_id that already exists in the org will not be ignored. If true, the existing dataset will be updated with the new dataset's details.
Response
Page of tags requested with all tags and the number of chunks in the dataset with that tag plus the total number of unique tags for the whole datset
Tracking ID of the dataset, can be any string, determined by the user. Tracking ID's are unique identifiers for datasets within an organization. They are designed to match the unique identifier of the dataset in the user's system.
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| integer\u003cint64> | null"},"lt":{"oneOf":[{"type":"number","format":"double","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range.oneOf.0.lt.oneOf.0","typeLabel":"number\u003cdouble>"},{"type":"integer","format":"int64","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range.oneOf.0.lt.oneOf.1","typeLabel":"integer\u003cint64>"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range.oneOf.0.lt.oneOf.2","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range.oneOf.0.lt","typeLabel":"number\u003cdouble> | integer\u003cint64> | null"},"lte":{"oneOf":[{"type":"number","format":"double","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range.oneOf.0.lte.oneOf.0","typeLabel":"number\u003cdouble>"},{"type":"integer","format":"int64","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range.oneOf.0.lte.oneOf.1","typeLabel":"integer\u003cint64>"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range.oneOf.0.lte.oneOf.2","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range.oneOf.0.lte","typeLabel":"number\u003cdouble> | integer\u003cint64> | null"}},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range.oneOf.0","typeLabel":"object"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0.range","typeLabel":"object | null"}},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.0","typeLabel":"object"},{"type":"object","description":"Filters can be constructed using either fields on the chunk objects, ids or tracking ids of chunks, and finally ids or tracking ids of groups.","properties":{"ids":{"oneOf":[{"type":"array","items":{"type":"string","format":"uuid","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.1.ids.oneOf.0.items.[INDEX]","typeLabel":"string\u003cuuid>"},"description":"Ids of the chunks to apply a match_any condition with. 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Only chunks with one of these ids will be returned.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.1.ids.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.1.ids","typeLabel":"string\u003cuuid>[] | null"},"tracking_ids":{"oneOf":[{"type":"array","items":{"type":"string","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.filters.oneOf.0.should.oneOf.0.items.[INDEX].oneOf.1.tracking_ids.oneOf.0.items.[INDEX]","typeLabel":"string"},"description":"Tracking ids of the chunks to apply a match_any condition with. 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To access fields inside of the metadata that you provide with the card, prefix the field name with `metadata.`."},"geo_bounding_box":{"oneOf":[{"type":"object","required":["top_left","bottom_right"],"properties":{"bottom_right":{"type":"object","description":"Location that you want to use as the center of the search.","required":["lat","lon"],"properties":{"lat":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]},"lon":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]}}},"top_left":{"type":"object","description":"Location that you want to use as the center of the search.","required":["lat","lon"],"properties":{"lat":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]},"lon":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]}}}}},{"type":"null"}]},"geo_polygon":{"oneOf":[{"type":"object","required":["exterior"],"properties":{"exterior":{"type":"array","items":{"type":"object","description":"Location that you want to use as the center of the search.","required":["lat","lon"],"properties":{"lat":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]},"lon":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]}}}},"interior":{"oneOf":[{"type":"array","items":{"type":"array","items":{"type":"object","description":"Location that you want to use as the center of the search.","required":["lat","lon"],"properties":{"lat":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]},"lon":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]}}}}},{"type":"null","items":{"type":"array","items":{"type":"object","description":"Location that you want to use as the center of the search.","required":["lat","lon"],"properties":{"lat":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]},"lon":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]}}}}}]}}},{"type":"null"}]},"geo_radius":{"oneOf":[{"type":"object","required":["center","radius"],"properties":{"center":{"type":"object","description":"Location that you want to use as the center of the search.","required":["lat","lon"],"properties":{"lat":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]},"lon":{"oneOf":[{"type":"integer","format":"int64"},{"type":"number","format":"double"}]}}},"radius":{"type":"number","format":"double"}}},{"type":"null"}]},"match_all":{"oneOf":[{"type":"array","items":{"oneOf":[{"type":"string"},{"type":"integer","format":"int64"},{"type":"number","format":"double"}]},"description":"Match all lets you pass in an array of values that will return results if all of the items match. 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The match value will be used to check for an exact substring match on the metadata values for each existing chunk. If both match_all and match_any are provided, the match_any condition will be used."},{"type":"null","items":{"oneOf":[{"type":"string"},{"type":"integer","format":"int64"},{"type":"number","format":"double"}]},"description":"Match any lets you pass in an array of values that will return results if any of the items match. The match value will be used to check for an exact substring match on the metadata values for each existing chunk. If both match_all and match_any are provided, the match_any condition will be used."}]},"range":{"oneOf":[{"type":"object","example":{"gt":0,"gte":0,"lt":1,"lte":1},"properties":{"gt":{"oneOf":[{"type":"number","format":"double"},{"type":"integer","format":"int64"},{"type":"null"}]},"gte":{"oneOf":[{"type":"number","format":"double"},{"type":"integer","format":"int64"},{"type":"null"}]},"lt":{"oneOf":[{"type":"number","format":"double"},{"type":"integer","format":"int64"},{"type":"null"}]},"lte":{"oneOf":[{"type":"number","format":"double"},{"type":"integer","format":"int64"},{"type":"null"}]}}},{"type":"null"}]}}},{"type":"object","description":"Filters can be constructed using either fields on the chunk objects, ids or tracking ids of chunks, and finally ids or tracking ids of groups.","properties":{"ids":{"oneOf":[{"type":"array","items":{"type":"string","format":"uuid"},"description":"Ids of the chunks to apply a match_any condition with. Only chunks with one of these ids will be returned."},{"type":"null","items":{"type":"string","format":"uuid"},"description":"Ids of the chunks to apply a match_any condition with. Only chunks with one of these ids will be returned."}]},"tracking_ids":{"oneOf":[{"type":"array","items":{"type":"string"},"description":"Tracking ids of the chunks to apply a match_any condition with. Only chunks with one of these tracking ids will be returned."},{"type":"null","items":{"type":"string"},"description":"Tracking ids of the chunks to apply a match_any condition with. 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Defaults to false, but can be set to true when the latency penalty is acceptable (typically 50-200ms).","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.get_total_pages.oneOf.0","typeLabel":"boolean"},{"type":"null","description":"Get total page count for the query accounting for the applied filters. Defaults to false, but can be set to true when the latency penalty is acceptable (typically 50-200ms).","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.get_total_pages.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.get_total_pages","typeLabel":"boolean | null"},"page":{"oneOf":[{"type":"integer","format":"int64","description":"Page of chunks to fetch. Page is 1-indexed.","minimum":0,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.page.oneOf.0","typeLabel":"integer\u003cint64>"},{"type":"null","format":"int64","description":"Page of chunks to fetch. Page is 1-indexed.","minimum":0,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.page.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.page","typeLabel":"integer\u003cint64> | null"},"page_size":{"oneOf":[{"type":"integer","format":"int64","description":"Page size is the number of chunks to fetch. This can be used to fetch more than 10 chunks at a time.","minimum":0,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.page_size.oneOf.0","typeLabel":"integer\u003cint64>"},{"type":"null","format":"int64","description":"Page size is the number of chunks to fetch. This can be used to fetch more than 10 chunks at a time.","minimum":0,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.page_size.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.page_size","typeLabel":"integer\u003cint64> | null"},"remove_stop_words":{"oneOf":[{"type":"boolean","description":"If true, stop words (specified in server/src/stop-words.txt in the git repo) will be removed. Queries that are entirely stop words will be preserved.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.remove_stop_words.oneOf.0","typeLabel":"boolean"},{"type":"null","description":"If true, stop words (specified in server/src/stop-words.txt in the git repo) will be removed. Queries that are entirely stop words will be preserved.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.remove_stop_words.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.remove_stop_words","typeLabel":"boolean | null"},"score_threshold":{"oneOf":[{"type":"number","format":"float","description":"Set score_threshold to a float to filter out chunks with a score below the threshold for cosine distance metric. For Manhattan Distance, Euclidean Distance, and Dot Product, it will filter out scores above the threshold distance. This threshold applies before weight and bias modifications. If not specified, this defaults to no threshold. A threshold of 0 will default to no threshold.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.score_threshold.oneOf.0","typeLabel":"number\u003cfloat>"},{"type":"null","format":"float","description":"Set score_threshold to a float to filter out chunks with a score below the threshold for cosine distance metric. For Manhattan Distance, Euclidean Distance, and Dot Product, it will filter out scores above the threshold distance. This threshold applies before weight and bias modifications. If not specified, this defaults to no threshold. A threshold of 0 will default to no threshold.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.score_threshold.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.score_threshold","typeLabel":"number\u003cfloat> | null"},"scoring_options":{"oneOf":[{"type":"object","description":"Scoring options provides ways to modify the sparse or dense vector created for the query in order to change how potential matches are scored. If not specified, this defaults to no modifications.","properties":{"fulltext_boost":{"oneOf":[{"type":"object","description":"Boost the presence of certain tokens for fulltext (SPLADE) and keyword (BM25) search. I.e. boosting title phrases to priortize title matches or making sure that the listing for AirBNB itself ranks higher than companies who make software for AirBNB hosts by boosting the in-document-frequency of the AirBNB token (AKA word) for its official listing. Conceptually it multiples the in-document-importance second value in the tuples of the SPLADE or BM25 sparse vector of the chunk_html innerText for all tokens present in the boost phrase by the boost factor like so: (token, in-document-importance) -> (token, in-document-importance*boost_factor).","required":["phrase","boost_factor"],"properties":{"boost_factor":{"type":"number","format":"double","description":"Amount to multiplicatevly increase the frequency of the tokens in the phrase by","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0.fulltext_boost.oneOf.0.boost_factor","typeLabel":"number\u003cdouble>"},"phrase":{"type":"string","description":"The phrase to boost in the fulltext document frequency index","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0.fulltext_boost.oneOf.0.phrase","typeLabel":"string"}},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0.fulltext_boost.oneOf.0","typeLabel":"object"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0.fulltext_boost.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0.fulltext_boost","typeLabel":"object | null"},"semantic_boost":{"oneOf":[{"type":"object","description":"Semantic boosting moves the dense vector of the chunk in the direction of the distance phrase for semantic search. I.e. you can force a cluster by moving every chunk for a PDF closer to its title or push a chunk with a chunk_html of \"iphone\" 25% closer to the term \"flagship\" by using the distance phrase \"flagship\" and a distance factor of 0.25. Conceptually it's drawing a line (euclidean/L2 distance) between the vector for the innerText of the chunk_html and distance_phrase then moving the vector of the chunk_html distance_factor*L2Distance closer to or away from the distance_phrase point along the line between the two points.","required":["phrase","distance_factor"],"properties":{"distance_factor":{"type":"number","format":"float","description":"Arbitrary float (positive or negative) specifying the multiplicate factor to apply before summing the phrase vector with the chunk_html embedding vector","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0.semantic_boost.oneOf.0.distance_factor","typeLabel":"number\u003cfloat>"},"phrase":{"type":"string","description":"Terms to embed in order to create the vector which is weighted summed with the chunk_html embedding vector","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0.semantic_boost.oneOf.0.phrase","typeLabel":"string"}},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0.semantic_boost.oneOf.0","typeLabel":"object"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0.semantic_boost.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0.semantic_boost","typeLabel":"object | null"}},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.0","typeLabel":"object"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.scoring_options","typeLabel":"object | null"},"search_type":{"oneOf":[{"type":"string","enum":["fulltext","semantic","hybrid","bm25"],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.search_type.oneOf.0","typeLabel":"enum\u003cstring>"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.search_type.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.search_type","typeLabel":"enum\u003cstring> | null"},"slim_chunks":{"oneOf":[{"type":"boolean","description":"Set slim_chunks to true to avoid returning the content and chunk_html of the chunks. This is useful for when you want to reduce amount of data over the wire for latency improvement (typically 10-50ms). Default is false.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.slim_chunks.oneOf.0","typeLabel":"boolean"},{"type":"null","description":"Set slim_chunks to true to avoid returning the content and chunk_html of the chunks. This is useful for when you want to reduce amount of data over the wire for latency improvement (typically 10-50ms). Default is false.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.slim_chunks.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.slim_chunks","typeLabel":"boolean | null"},"sort_options":{"oneOf":[{"type":"object","description":"Sort Options lets you specify different methods to rerank the chunks in the result set. If not specified, this defaults to the score of the chunks.","properties":{"location_bias":{"oneOf":[{"type":"object","description":"Location bias lets you rank your results by distance from a location. If not specified, this has no effect. Bias allows you to determine how much of an effect the location of chunks will have on the search results. If not specified, this defaults to 0.0. We recommend setting this to 1.0 for a gentle reranking of the results, >3.0 for a strong reranking of the results.","required":["location","bias"],"properties":{"bias":{"type":"number","format":"double","description":"Bias lets you specify how much of an effect the location of chunks will have on the search results. If not specified, this defaults to 0.0. We recommend setting this to 1.0 for a gentle reranking of the results, >3.0 for a strong reranking of the results.","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias.oneOf.0.bias","typeLabel":"number\u003cdouble>"},"location":{"type":"object","description":"Location that you want to use as the center of the search.","required":["lat","lon"],"properties":{"lat":{"oneOf":[{"type":"integer","format":"int64","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias.oneOf.0.location.lat.oneOf.0","typeLabel":"integer\u003cint64>"},{"type":"number","format":"double","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias.oneOf.0.location.lat.oneOf.1","typeLabel":"number\u003cdouble>"}],"isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias.oneOf.0.location.lat","typeLabel":"integer\u003cint64> | number\u003cdouble>"},"lon":{"oneOf":[{"type":"integer","format":"int64","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias.oneOf.0.location.lon.oneOf.0","typeLabel":"integer\u003cint64>"},{"type":"number","format":"double","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias.oneOf.0.location.lon.oneOf.1","typeLabel":"number\u003cdouble>"}],"isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias.oneOf.0.location.lon","typeLabel":"integer\u003cint64> | number\u003cdouble>"}},"isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias.oneOf.0.location","typeLabel":"object"}},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias.oneOf.0","typeLabel":"object"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.location_bias","typeLabel":"object | null"},"mmr":{"oneOf":[{"type":"object","description":"MMR Options lets you specify different methods to rerank the chunks in the result set using Maximal Marginal Relevance. If not specified, this defaults to the score of the chunks.","required":["use_mmr"],"properties":{"use_mmr":{"type":"boolean","description":"Set use_mmr to true to use the Maximal Marginal Relevance algorithm to rerank the results.","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.mmr.oneOf.0.use_mmr","typeLabel":"boolean"},"mmr_lambda":{"oneOf":[{"type":"number","format":"float","description":"Set mmr_lambda to a value between 0.0 and 1.0 to control the tradeoff between relevance and diversity. Closer to 1.0 will give more diverse results, closer to 0.0 will give more relevant results. If not specified, this defaults to 0.5.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.mmr.oneOf.0.mmr_lambda.oneOf.0","typeLabel":"number\u003cfloat>"},{"type":"null","format":"float","description":"Set mmr_lambda to a value between 0.0 and 1.0 to control the tradeoff between relevance and diversity. Closer to 1.0 will give more diverse results, closer to 0.0 will give more relevant results. If not specified, this defaults to 0.5.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.mmr.oneOf.0.mmr_lambda.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.mmr.oneOf.0.mmr_lambda","typeLabel":"number\u003cfloat> | null"}},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.mmr.oneOf.0","typeLabel":"object"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.mmr.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.mmr","typeLabel":"object | null"},"recency_bias":{"oneOf":[{"type":"number","format":"float","description":"Recency Bias lets you determine how much of an effect the recency of chunks will have on the search results. If not specified, this defaults to 0.0. We recommend setting this to 1.0 for a gentle reranking of the results, >3.0 for a strong reranking of the results.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.recency_bias.oneOf.0","typeLabel":"number\u003cfloat>"},{"type":"null","format":"float","description":"Recency Bias lets you determine how much of an effect the recency of chunks will have on the search results. If not specified, this defaults to 0.0. We recommend setting this to 1.0 for a gentle reranking of the results, >3.0 for a strong reranking of the results.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.recency_bias.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.recency_bias","typeLabel":"number\u003cfloat> | null"},"sort_by":{"oneOf":[{"type":"object","description":"Sort by lets you specify a method to sort the results by. If not specified, this defaults to the score of the chunks. If specified, this can be any key in the chunk metadata. This key must be a numeric value within the payload.","required":["field"],"properties":{"field":{"type":"string","description":"Field to sort by. This has to be a numeric field with a Qdrant `Range` index on it. i.e. num_value and timestamp","isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.0.field","typeLabel":"string"},"direction":{"oneOf":[{"type":"string","enum":["desc","asc"],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.0.direction.oneOf.0","typeLabel":"enum\u003cstring>"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.0.direction.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.0.direction","typeLabel":"enum\u003cstring> | null"},"prefetch_amount":{"oneOf":[{"type":"integer","format":"int64","description":"How many results to pull in before the sort","minimum":0,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.0.prefetch_amount.oneOf.0","typeLabel":"integer\u003cint64>"},{"type":"null","format":"int64","description":"How many results to pull in before the sort","minimum":0,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.0.prefetch_amount.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.0.prefetch_amount","typeLabel":"integer\u003cint64> | null"}},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.0","typeLabel":"object"},{"type":"object","description":"Sort by lets you specify a method to sort the results by. If not specified, this defaults to the score of the chunks. If specified, this can be any key in the chunk metadata. This key must be a numeric value within the payload.","required":["rerank_type"],"properties":{"rerank_type":{"type":"string","enum":["semantic","fulltext","bm25","cross_encoder"],"isRequired":true,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.1.rerank_type","typeLabel":"enum\u003cstring>"},"prefetch_amount":{"oneOf":[{"type":"integer","format":"int64","description":"How many results to pull in before the rerabj","minimum":0,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.1.prefetch_amount.oneOf.0","typeLabel":"integer\u003cint64>"},{"type":"null","format":"int64","description":"How many results to pull in before the rerabj","minimum":0,"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.1.prefetch_amount.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.1.prefetch_amount","typeLabel":"integer\u003cint64> | null"},"rerank_query":{"oneOf":[{"type":"string","description":"Query to use for prefetching defaults to the search query","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.1.rerank_query.oneOf.0","typeLabel":"string"},{"type":"null","description":"Query to use for prefetching defaults to the search query","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.1.rerank_query.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.1.rerank_query","typeLabel":"string | null"}},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.1","typeLabel":"object"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by.oneOf.2","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.sort_by","typeLabel":"object · object · null"},"tag_weights":{"oneOf":[{"type":"object","description":"Tag weights is a JSON object which can be used to boost the ranking of chunks with certain tags. This is useful for when you want to be able to bias towards chunks with a certain tag on the fly. The keys are the tag names and the values are the weights.","additionalProperties":{"type":"number","format":"float","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.tag_weights.oneOf.0.additionalProperties","typeLabel":"number\u003cfloat>"},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.tag_weights.oneOf.0","typeLabel":"object"},{"type":"null","description":"Tag weights is a JSON object which can be used to boost the ranking of chunks with certain tags. This is useful for when you want to be able to bias towards chunks with a certain tag on the fly. The keys are the tag names and the values are the weights.","additionalProperties":{"type":"number","format":"float","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.tag_weights.oneOf.1.additionalProperties","typeLabel":"number\u003cfloat>"},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.tag_weights.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.tag_weights","typeLabel":"object | null"},"use_weights":{"oneOf":[{"type":"boolean","description":"Set use_weights to true to use the weights of the chunks in the result set in order to sort them. If not specified, this defaults to true.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.use_weights.oneOf.0","typeLabel":"boolean"},{"type":"null","description":"Set use_weights to true to use the weights of the chunks in the result set in order to sort them. If not specified, this defaults to true.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.use_weights.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0.use_weights","typeLabel":"boolean | null"}},"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.0","typeLabel":"object"},{"type":"null","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.sort_options","typeLabel":"object | null"},"typo_options":{"oneOf":[{"type":"object","description":"Typo Options lets you specify different methods to correct typos in the query. If not specified, typos will not be corrected.","properties":{"correct_typos":{"oneOf":[{"type":"boolean","description":"Set correct_typos to true to correct typos in the query. If not specified, this defaults to false.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.typo_options.oneOf.0.correct_typos.oneOf.0","typeLabel":"boolean"},{"type":"null","description":"Set correct_typos to true to correct typos in the query. If not specified, this defaults to false.","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.typo_options.oneOf.0.correct_typos.oneOf.1","typeLabel":"null"}],"uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.typo_options.oneOf.0.correct_typos","typeLabel":"boolean | null"},"disable_on_word":{"oneOf":[{"type":"array","items":{"type":"string","uniqueKey":"datasets.items.[INDEX].server_configuration.oneOf.0.PUBLIC_DATASET.oneOf.0.extra_params.oneOf.0.searchOptions.oneOf.0.typo_options.oneOf.0.disable_on_word.oneOf.0.items.[INDEX]","typeLabel":"string"},"description":"Words that should not be corrected. 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