Vector
Create Index
This endpoint creates an index.
POST
/
v2
/
vector
/
index
curl --request POST \
--url https://api.upstash.com/v2/vector/index \
--header 'Authorization: Basic <encoded-value>' \
--header 'Content-Type: application/json' \
--data '{
"name": "<string>",
"region": "eu-west-1",
"similarity_function": "COSINE",
"dimension_count": 123,
"type": "payg",
"embedding_model": "BGE_SMALL_EN_V1_5"
}'
{
"customer_id": "<string>",
"id": "<string>",
"name": "<string>",
"similarity_function": "<string>",
"dimension_count": 123,
"endpoint": "<string>",
"token": "<string>",
"read_only_token": "<string>",
"type": "<string>",
"region": "<string>",
"max_vector_count": 123,
"max_daily_updates": 123,
"max_daily_queries": 123,
"max_monthly_bandwidth": 123,
"max_writes_per_second": 123,
"max_query_per_second": 123,
"max_reads_per_request": 123,
"max_writes_per_request": 123,
"max_total_metadata_size": 123,
"reserved_price": 123,
"creation_time": 123,
"embedding_model": "<string>"
}
Authorizations
Basic authentication using email and API key
Body
application/json
Response
200 - application/json
Index created successfully
The response is of type object
.
Was this page helpful?
curl --request POST \
--url https://api.upstash.com/v2/vector/index \
--header 'Authorization: Basic <encoded-value>' \
--header 'Content-Type: application/json' \
--data '{
"name": "<string>",
"region": "eu-west-1",
"similarity_function": "COSINE",
"dimension_count": 123,
"type": "payg",
"embedding_model": "BGE_SMALL_EN_V1_5"
}'
{
"customer_id": "<string>",
"id": "<string>",
"name": "<string>",
"similarity_function": "<string>",
"dimension_count": 123,
"endpoint": "<string>",
"token": "<string>",
"read_only_token": "<string>",
"type": "<string>",
"region": "<string>",
"max_vector_count": 123,
"max_daily_updates": 123,
"max_daily_queries": 123,
"max_monthly_bandwidth": 123,
"max_writes_per_second": 123,
"max_query_per_second": 123,
"max_reads_per_request": 123,
"max_writes_per_request": 123,
"max_total_metadata_size": 123,
"reserved_price": 123,
"creation_time": 123,
"embedding_model": "<string>"
}