Vector Similarity Matching
最新の更新: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"
}'

        
このコードブロックは、フローティングウィンドウに表示されます

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
    }
  ]
}

        
このコードブロックは、フローティングウィンドウに表示されます

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