Vector Similarity Matching
Last updated:2023-11-02
Vector Similarity Matching
Convert keywords to vectors and match to document IDs, perform vector retrieval and return top K results ranked by keyword similarity.
Request Method
POST
Request URL
https://api.gptbots.ai/v1/bot/detail
Request Authentication
See Overview for authentication details.
Request
Request Example
curl -X POST https://api.gptbots.ai/v1/vector/match \
-H 'Authorization: Bearer your_apikey' \
-H 'Content-Type: application/json' \
-d '{
"embedding_rate": "1",
"prompt": "Please introduce Aurora.",
"data_ids": [
"1234567890",
"1230987654"
],
"top_k": "5"
}'
curl -X POST https://api.gptbots.ai/v1/vector/match \
-H 'Authorization: Bearer your_apikey' \
-H 'Content-Type: application/json' \
-d '{
"embedding_rate": "1",
"prompt": "Please introduce Aurora.",
"data_ids": [
"1234567890",
"1230987654"
],
"top_k": "5"
}'
This code block in the floating window
Request Headers
Field | Type | Description |
---|---|---|
Authorization | Bearer ${token} | Use Authorization: Bearer ${token} for authentication. Get the key from the API Keys page as token. |
Content-Type | application/json | Data type, set to application/json. |
Request Body
ld | Type | Required | Description |
---|---|---|---|
embedding_rate | float | No | Knowledge vector retrieval, vector retrieval proportion, default 1, value range: [0,1] |
prompt | string | Yes | Keywords for vector similarity matching against documents in the bot. |
data_ids | array | No | Document IDs to match the keyword vectors against. Can specify multiple knowledge document IDs from bots. Defaults to all docs if empty. |
top_k | int | Yes | Number of top similar results to return after matching keywords to document IDs. Only 1-10 allowed. |
Response
Response Example
{
"total": 2,
"list": [
{
"content": "Test data",
"data_id": "aS1CNvPK4XCckDKQNj7azC9a",
"score": 0.75
},
{
"content": "Test data",
"data_id": "aS1CNvPK4XCckDKQNj7azC9a",
"score": 0.75
}
]
}
{
"total": 2,
"list": [
{
"content": "Test data",
"data_id": "aS1CNvPK4XCckDKQNj7azC9a",
"score": 0.75
},
{
"content": "Test data",
"data_id": "aS1CNvPK4XCckDKQNj7azC9a",
"score": 0.75
}
]
}
This code block in the floating window
Success Response
Field | Type | Description |
---|---|---|
total | int | The total number of returned fragments. |
list | JSON Array | Fragment list. |
content | string | Snippet content. |
data_id | string | Source document ID. |
score | float | Similarity score. |
Failure Response
Field | Type | Description |
---|---|---|
code | int | Error code. |
message | string | Error details. |
Error Codes
Code | Message |
---|---|
40000 | Invalid parameter |
40127 | Developer authentication failed |
20059 | Bot deleted |
40332 | Documents queried cannot exceed 10 |