Embedding
Embedding & Reranker Quickstart
Embedding quickstart
Basic Request
import requests
response = requests.post(
"https://llm.onerouter.pro/v1/embeddings",
headers={
"Authorization": f"Bearer {{API_KEY_REF}}",
"Content-Type": "application/json",
},
json={
"model": "{{MODEL}}",
"input": "The quick brown fox jumps over the lazy dog"
}
)
data = response.json()
embedding = data["data"][0]["embedding"]
print(f"Embedding dimension: {len(embedding)}")const response = await fetch('https://llm.onerouter.pro/v1/embeddings', {
method: 'POST',
headers: {
'Authorization': 'Bearer {{API_KEY_REF}}',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: '{{MODEL}}',
input: 'The quick brown fox jumps over the lazy dog'
}),
});
const data = await response.json();
const embedding = data.data[0].embedding;
console.log(`Embedding dimension: ${embedding.length}`);Batch Processing
Semantic Search
Reranker quickstart
Example with Texts
Example with Structured Data:
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