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"
}'

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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
    }
  ]
}

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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