Insert
Inserts one or more entities into a collection.
POST
https://${MILVUS_URI}/v1/vector/insert
Example
Insert an entity to a collection named collection1
:
export MILVUS_URI="http://localhost:19530"
curl --request POST \
--url "${MILVUS_URI}/v1/vector/insert" \
--header "accept: application/json" \
--header "content-type: application/json" \
-d '{
"collectionName": "medium_articles",
"data": [{
"vector": [0.23254494, 0.01374953, 0.88497432, 0.05292784, 0.02204868, 0.21890409, 0.35428028, 0.97024438, 0.58635726, 0.67980838, 0.67202523, 0.16375636, 0.52829526, 0.80185865, 0.71167799, 0.98615784, 0.86350404, 0.64295726, 0.37624468, 0.99708253, 0.46243643, 0.32893164, 0.32094438, 0.47701896, 0.85275669, 0.13127097, 0.5889451, 0.97648346, 0.74876674, 0.66409428, 0.92279568, 0.59029588, 0.495616, 0.12791323, 0.90082737, 0.84513226, 0.47542935, 0.74928086, 0.44922073, 0.1020575, 0.37431645, 0.29738807, 0.71098564, 0.35390859, 0.87792487, 0.89928066, 0.4995833, 0.61043433, 0.55303136, 0.02036885, 0.02231103, 0.67648899, 0.72165575, 0.15671427, 0.00546115, 0.28756084, 0.15077446, 0.65105982, 0.44063386, 0.07762012, 0.59994796, 0.19935778, 0.58911788, 0.54601686, 0.47097711, 0.90082361, 0.05595469, 0.38546197, 0.91447695, 0.33456871, 0.12778749, 0.82224433, 0.3223666, 0.56243253, 0.72730363, 0.42176339, 0.02008885, 0.11265533, 0.71246733, 0.86685866, 0.5204902, 0.1653007, 0.80375364, 0.14031363, 0.76868394, 0.35325028, 0.1142984, 0.95218926, 0.37508951, 0.01396396, 0.16322817, 0.69052937, 0.30264489, 0.40555134, 0.06153988, 0.00101791, 0.18618961, 0.77599691, 0.3445008, 0.7106463, 0.13440427, 0.64690627, 0.40818622, 0.07025781, 0.89639434, 0.00494204, 0.10540909, 0.47865809, 0.47316137, 0.46836499, 0.93197388, 0.24012326, 0.49471039, 0.21283529, 0.47370547, 0.95777027, 0.50557255, 0.12809693, 0.79998351, 0.76532556, 0.3412945, 0.72270631, 0.3432966, 0.81465781, 0.6924483, 0.2885265, 0.84673871, 0.38711232, 0.18702427, 0.49496971, 0.65431764, 0.39590077, 0.31226873, 0.20910631, 0.86433119, 0.51681312, 0.77759473, 0.42447517, 0.05762998, 0.17887886, 0.41045186, 0.09120965, 0.6447974, 0.49632173, 0.72730052, 0.26646776, 0.48899696, 0.33221734, 0.98206029, 0.82591894, 0.28478645, 0.37324246, 0.35833242, 0.96558445, 0.5003729, 0.66676758, 0.7230707, 0.21599462, 0.70457393, 0.11649283, 0.03034646, 0.00318578, 0.57941155, 0.80640383, 0.30106438, 0.84618622, 0.02321722, 0.6453211, 0.31889303, 0.20069267, 0.19202631, 0.84127804, 0.06014367, 0.53307321, 0.78079442, 0.32043145, 0.30207626, 0.08691769, 0.07230655, 0.8059663, 0.03810803, 0.05415744, 0.44057945, 0.19306693, 0.75747746, 0.89299566, 0.82985846, 0.5958096, 0.89525864, 0.07336388, 0.38396764, 0.04846415, 0.56839423, 0.56106259, 0.14302027, 0.85109589, 0.6298057, 0.62168794, 0.24771729, 0.54924417, 0.9061572, 0.97241046, 0.33025088, 0.56675472, 0.72474551, 0.48314604, 0.26248324, 0.22614522, 0.13087051, 0.9292656, 0.80039537, 0.38300443, 0.78520422, 0.29857615, 0.19121419, 0.47509572, 0.35981825, 0.55131999, 0.04348036, 0.02168964, 0.80645188, 0.62876989, 0.70794394, 0.72093526, 0.85172951, 0.24799777, 0.97620833, 0.74877332, 0.92792629, 0.89200055, 0.74500415, 0.84596926, 0.97469625, 0.7171343, 0.30020491, 0.97313677, 0.241573, 0.15498676, 0.21273237, 0.58910547, 0.46249576, 0.01109894, 0.0180376, 0.80975073, 0.12900483, 0.96509751, 0.57304458, 0.73290638, 0.94211456, 0.35197941, 0.15532272, 0.76150926, 0.19317378, 0.72826792, 0.38820115, 0.94187109],
"title": "Top 10 In-Demand programming languages to learn in 2020",
"link": "https://towardsdatascience.com/top-10-in-demand-programming-languages-to-learn-in-2020-4462eb7d8d3e"
}]
}'
Insert multiple entities:
export MILVUS_URI="http://localhost:19530"
curl --request POST \
--url "${MILVUS_URI}/v1/vector/insert" \
--header "accept: application/json" \
--header "content-type: application/json" \
-d '{
"collectionName": "medium_articles",
"data": [{
"vector": [0.23254494, 0.01374953, 0.88497432, 0.05292784, 0.02204868, 0.21890409, 0.35428028, 0.97024438, 0.58635726, 0.67980838, 0.67202523, 0.16375636, 0.52829526, 0.80185865, 0.71167799, 0.98615784, 0.86350404, 0.64295726, 0.37624468, 0.99708253, 0.46243643, 0.32893164, 0.32094438, 0.47701896, 0.85275669, 0.13127097, 0.5889451, 0.97648346, 0.74876674, 0.66409428, 0.92279568, 0.59029588, 0.495616, 0.12791323, 0.90082737, 0.84513226, 0.47542935, 0.74928086, 0.44922073, 0.1020575, 0.37431645, 0.29738807, 0.71098564, 0.35390859, 0.87792487, 0.89928066, 0.4995833, 0.61043433, 0.55303136, 0.02036885, 0.02231103, 0.67648899, 0.72165575, 0.15671427, 0.00546115, 0.28756084, 0.15077446, 0.65105982, 0.44063386, 0.07762012, 0.59994796, 0.19935778, 0.58911788, 0.54601686, 0.47097711, 0.90082361, 0.05595469, 0.38546197, 0.91447695, 0.33456871, 0.12778749, 0.82224433, 0.3223666, 0.56243253, 0.72730363, 0.42176339, 0.02008885, 0.11265533, 0.71246733, 0.86685866, 0.5204902, 0.1653007, 0.80375364, 0.14031363, 0.76868394, 0.35325028, 0.1142984, 0.95218926, 0.37508951, 0.01396396, 0.16322817, 0.69052937, 0.30264489, 0.40555134, 0.06153988, 0.00101791, 0.18618961, 0.77599691, 0.3445008, 0.7106463, 0.13440427, 0.64690627, 0.40818622, 0.07025781, 0.89639434, 0.00494204, 0.10540909, 0.47865809, 0.47316137, 0.46836499, 0.93197388, 0.24012326, 0.49471039, 0.21283529, 0.47370547, 0.95777027, 0.50557255, 0.12809693, 0.79998351, 0.76532556, 0.3412945, 0.72270631, 0.3432966, 0.81465781, 0.6924483, 0.2885265, 0.84673871, 0.38711232, 0.18702427, 0.49496971, 0.65431764, 0.39590077, 0.31226873, 0.20910631, 0.86433119, 0.51681312, 0.77759473, 0.42447517, 0.05762998, 0.17887886, 0.41045186, 0.09120965, 0.6447974, 0.49632173, 0.72730052, 0.26646776, 0.48899696, 0.33221734, 0.98206029, 0.82591894, 0.28478645, 0.37324246, 0.35833242, 0.96558445, 0.5003729, 0.66676758, 0.7230707, 0.21599462, 0.70457393, 0.11649283, 0.03034646, 0.00318578, 0.57941155, 0.80640383, 0.30106438, 0.84618622, 0.02321722, 0.6453211, 0.31889303, 0.20069267, 0.19202631, 0.84127804, 0.06014367, 0.53307321, 0.78079442, 0.32043145, 0.30207626, 0.08691769, 0.07230655, 0.8059663, 0.03810803, 0.05415744, 0.44057945, 0.19306693, 0.75747746, 0.89299566, 0.82985846, 0.5958096, 0.89525864, 0.07336388, 0.38396764, 0.04846415, 0.56839423, 0.56106259, 0.14302027, 0.85109589, 0.6298057, 0.62168794, 0.24771729, 0.54924417, 0.9061572, 0.97241046, 0.33025088, 0.56675472, 0.72474551, 0.48314604, 0.26248324, 0.22614522, 0.13087051, 0.9292656, 0.80039537, 0.38300443, 0.78520422, 0.29857615, 0.19121419, 0.47509572, 0.35981825, 0.55131999, 0.04348036, 0.02168964, 0.80645188, 0.62876989, 0.70794394, 0.72093526, 0.85172951, 0.24799777, 0.97620833, 0.74877332, 0.92792629, 0.89200055, 0.74500415, 0.84596926, 0.97469625, 0.7171343, 0.30020491, 0.97313677, 0.241573, 0.15498676, 0.21273237, 0.58910547, 0.46249576, 0.01109894, 0.0180376, 0.80975073, 0.12900483, 0.96509751, 0.57304458, 0.73290638, 0.94211456, 0.35197941, 0.15532272, 0.76150926, 0.19317378, 0.72826792, 0.38820115, 0.94187109],
"title": "Top 10 In-Demand programming languages to learn in 2020",
"link": "https://towardsdatascience.com/top-10-in-demand-programming-languages-to-learn-in-2020-4462eb7d8d3e"
},{
"vector": [0.4882628, 0.85768371, 0.48556888, 0.9681036, 0.94807827, 0.80656861, 0.72123286, 0.81810534, 0.83713905, 0.73258409, 0.97732714, 0.09869599, 0.83189308, 0.33537219, 0.88647192, 0.66132137, 0.703723, 0.34379603, 0.74785059, 0.84559156, 0.65074354, 0.61864253, 0.73546132, 0.84872955, 0.6006182, 0.04830389, 0.37780669, 0.96101751, 0.22319285, 0.88504273, 0.44813016, 0.69746754, 0.5707871, 0.37386075, 0.25382573, 0.42397712, 0.89749552, 0.39729882, 0.38485115, 0.12583234, 0.47243267, 0.74576701, 0.45814588, 0.88024839, 0.72812605, 0.6622232, 0.31803479, 0.74101011, 0.76141925, 0.5024863, 0.47431501, 0.40002184, 0.45752955, 0.54383915, 0.67569667, 0.52164475, 0.33647519, 0.93068322, 0.65766685, 0.95959175, 0.83665213, 0.1753687, 0.27341319, 0.34550907, 0.79669369, 0.95065082, 0.30838918, 0.79784458, 0.37323557, 0.97728813, 0.11170225, 0.87876854, 0.85212036, 0.88599461, 0.76916602, 0.6094099, 0.4427332, 0.87373443, 0.18576099, 0.81970137, 0.74932009, 0.92106027, 0.76417889, 0.35671825, 0.09990157, 0.14570871, 0.43084067, 0.30551776, 0.63985873, 0.45777184, 0.16172334, 0.32226743, 0.27613814, 0.18182943, 0.7019827, 0.45446168, 0.31359211, 0.17426952, 0.19392872, 0.59816543, 0.31679765, 0.60059089, 0.92800561, 0.95165562, 0.55177484, 0.49510178, 0.60250447, 0.1519485, 0.33565446, 0.92865767, 0.86723503, 0.85392181, 0.85337828, 0.01631286, 0.25257909, 0.00124323, 0.59344951, 0.78468014, 0.61854741, 0.61980932, 0.87467147, 0.44361724, 0.97777631, 0.42543721, 0.5290862, 0.12384163, 0.45287003, 0.30333621, 0.10408064, 0.71930918, 0.90741917, 0.09838064, 0.66319033, 0.08133113, 0.30527365, 0.40877414, 0.11552966, 0.76451148, 0.00529968, 0.76741598, 0.90358724, 0.05710312, 0.32659557, 0.66143926, 0.3258203, 0.62721598, 0.18690116, 0.00184847, 0.11355109, 0.33962499, 0.64671448, 0.67297271, 0.02416349, 0.3173442, 0.54041374, 0.33752188, 0.75654937, 0.08236666, 0.40054276, 0.1021504, 0.20874325, 0.75615835, 0.54953906, 0.44659766, 0.16064502, 0.58682242, 0.15547067, 0.57503622, 0.07797247, 0.1559962, 0.94815864, 0.12474807, 0.0999395, 0.85504252, 0.55633022, 0.56959553, 0.75966109, 0.70444125, 0.66884798, 0.81692129, 0.06837097, 0.9714623, 0.86751075, 0.42125912, 0.44367403, 0.49978621, 0.32267559, 0.67220653, 0.56167557, 0.25248436, 0.94191099, 0.71508807, 0.64564731, 0.56824345, 0.29187781, 0.93961505, 0.28196959, 0.92713673, 0.7256734, 0.51042292, 0.81504509, 0.55849401, 0.19380059, 0.46767559, 0.52275063, 0.66075204, 0.97290358, 0.57524932, 0.7219121, 0.85188581, 0.26220385, 0.75686621, 0.51934907, 0.185452, 0.49708297, 0.95783663, 0.61397962, 0.45956795, 0.49311061, 0.49464425, 0.43094667, 0.76768303, 0.29252745, 0.57964633, 0.72950803, 0.94616381, 0.60436868, 0.47828997, 0.90345857, 0.92971537, 0.64784105, 0.18095567, 0.94852017, 0.05224637, 0.50829763, 0.89020778, 0.008269, 0.9500583, 0.20305412, 0.21179052, 0.28443536, 0.39540241, 0.20286982, 0.30968133, 0.2141927, 0.4390286, 0.12686093, 0.59583271, 0.88270185, 0.28187656, 0.90096987, 0.29104497, 0.38480562, 0.40069773, 0.52293091, 0.37621525],
"title": "Dashboards in Python: 3 Advanced Examples for Dash Beginners and Everyone Else",
"link": "https://medium.com/swlh/dashboards-in-python-3-advanced-examples-for-dash-beginners-and-everyone-else"
}]
}'
Request
Parameters
No query parameters required
No path parameters required
Request Body
{
"collectionName": "string",
"dbName": "string"
}
Parameter | Description |
---|---|
dbName | string The name of the database. |
collectionName | string(required) The name of the collection to which entities will be inserted. |
data | object(required) An entity object. Note that the keys in the entity should match the collection schema. |
{
"collectionName": "string",
"data": [],
"dbName": "string"
}
Parameter | Description |
---|---|
dbName | string The name of the database. |
collectionName | string(required) The name of the collection to which entities will be inserted. |
data | array(required) An array of entity objects. Note that the keys in an entity object should match the collection schema |
Response
Returns the number of inserted entities and an array of their IDs.
Response Bodies
- Response body if we process your request successfully
{
"code": 200,
"data": {
"insertCount": "integer"
}
}
- Response body if we failed to process your request
{
"code": integer,
"message": string
}
Properties
The properties in the returned response are listed in the following table.
Property | Description |
---|---|
code | integer Indicates whether the request succeeds.
|
data | object A data object. |
data.insertCount | integer The number of inserted entities. |
data.insertIds | array An array of the IDs of inserted entities. |
message | string Indicates the possible reason for the reported error. |
Possible Errors
Error Code | Description |
---|---|
800 | database not found |
1800 | user hasn’t authenticate |
1801 | can only accept json format request |
1802 | missing required parameters |
1804 | fail to deal the insert data |
1806 | please check the primary key and its’ type can only in [int |