Create Embeddings

POST/v1/embeddings

Convert text input into vector embeddings.

Request Body

application/json

model:requiredstring

Model identifier used for this request.

input:requiredstring

Text, message, image, or file input supplied to the model.

encoding_format:optionalstring

Format used to encode the returned embeddings.

Allowedfloatbase64

dimensions:optionalinteger

Number of dimensions in the returned embedding vectors.

Response

200

A successful request returns a JSON response. The complete example is shown in the code panel.

Request ExamplePOST /v1/embeddings

1curl --request POST \2  --url 'https://api.unifyllm.top/v1/embeddings' \3  --header 'Authorization: Bearer <YOUR_API_KEY>' \4  --header 'Content-Type: application/json' \5  --data '{6  "model": "text-embedding-3-small",7  "input": "The quick brown fox jumps over the lazy dog.",8  "encoding_format": "float",9  "dimensions": 153610}'

1const response = await fetch("https://api.unifyllm.top/v1/embeddings", {2  method: "POST",3  headers: {4    "Authorization": "Bearer <YOUR_API_KEY>",5    "Content-Type": "application/json"6  },7  body: JSON.stringify({8    "model": "text-embedding-3-small",9    "input": "The quick brown fox jumps over the lazy dog.",10    "encoding_format": "float",11    "dimensions": 153612  }),13});14 15const data = await response.json();16console.log(data);

1import requests2 3response = requests.post(4    "https://api.unifyllm.top/v1/embeddings",5    headers={"Authorization": "Bearer <YOUR_API_KEY>"},6    json={7      "model": "text-embedding-3-small",8      "input": "The quick brown fox jumps over the lazy dog.",9      "encoding_format": "float",10      "dimensions": 153611    }12)13response.raise_for_status()14print(response.json())

Request Body

1{2  "model": "text-embedding-3-small",3  "input": "The quick brown fox jumps over the lazy dog.",4  "encoding_format": "float",5  "dimensions": 15366}

Response Example

200

1{2  "object": "list",3  "data": [4    {5      "object": "embedding",6      "index": 0,7      "embedding": [8        -0.015311058,9        -0.011375908,10        0.0048358003,11        -0.017444907,12        -0.0059027243,13        0.008549252,14        -0.007316053,15        -0.008036573,16        -0.0014254525,17        0.008320625,18        0.002068032,19        0.004077175,20        -0.009408333,21        0.0038035163,22        -0.0076208883,23        0.010821662,24        0.03940692,25        -0.0048808325,26        0.023624754,27        -0.026271282,28        -0.006283769,29        -0.009055001,30        -0.01190937,31        -0.006827623,32        -0.00985173,33        0.0018203531,34        0.015976153,35        -0.011597606,36        0.008639316,37        0.002154633,38        0.007988077,39        -0.027185788,40        -0.030123293,41        -0.020354701,42        -0.030289568,43        -0.014140212,44        -0.016391838,45        -0.015546612,46        0.0036407062,47      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