models/BAAI/Bge-Base-EN-V1.5

Bge-Base-EN-V1.5

embedding

BAAI general embedding (Base) model that transforms any given text into a 768-dimensional vector

slug · baai/bge-base-en-v1.5provider · BAAIfamily · BGEreleased · 2023-09-25

Quickstart

curl https://api.aigateway.sh/v1/embeddings \
  -H "Authorization: Bearer $AIGATEWAY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"baai/bge-base-en-v1.5","input":"hello"}'

Capabilities

CONTEXT
153,600 tok

Strengths

  • Semantic similarity
  • Vector search

Use cases

RAGSemantic searchRecommendation

Pricing

Input$0.067 / 1M tokens
You pay pass-through · 5% applied at credit top-up, not per-call.
Try in playground →CompareAPI referenceSee usage ranking →

Collections

More embedding models →More from BAAIFrontier models →Free-tier models →
API schema

Call Bge-Base-EN-V1.5 from any OpenAI SDK

POST https://api.aigateway.sh/v1/embeddings·Content-Type: application/json·Auth: Bearer sk-aig-...

Request body

json
{
  "model": "baai/bge-base-en-v1.5",
  "input": "Text to embed, or an array of strings for batch."
}

Response

json
{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [0.0123, -0.0456, 0.0789, /* ... */]
    }
  ],
  "model": "baai/bge-base-en-v1.5",
  "usage": { "prompt_tokens": 5, "total_tokens": 5 }
}

Quickstart

from openai import OpenAI
client = OpenAI(base_url="https://api.aigateway.sh/v1", api_key="sk-aig-...")

r = client.embeddings.create(model="baai/bge-base-en-v1.5", input="hello world")
print(r.data[0].embedding[:5])

Errors

401authentication_errorInvalid or missing API key
402insufficient_creditsWallet empty (PAYG only)
404not_foundUnknown model or endpoint
429rate_limit_errorOver per-minute limit — see Retry-After header
500server_errorUpstream provider failed (retryable)
503service_unavailableUpstream saturated (retryable)
Full docs →API reference →OpenAPI spec →llms.txt →