import SambaNova from 'sambanova';const client = new SambaNova({ apiKey: process.env['SAMBANOVA_API_KEY'], // This is the default and can be omitted});const embeddingsResponse = await client.embeddings.create({ input: ['text to embed number 1', 'text to embed number 2'], model: 'E5-Mistral-7B-Instruct',});console.log(embeddingsResponse.data);
import os
from sambanova import SambaNova
client = SambaNova(
api_key=os.environ.get("SAMBANOVA_API_KEY"), # This is the default and can be omitted
)
embeddings_response = client.embeddings.create(
input=["text to embed number 1", "text to embed number 2"],
model="E5-Mistral-7B-Instruct",
)
print(embeddings_response.data)
curl --request POST \
--url https://api.sambanova.ai/v1/embeddings \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"input": [
"text to embed number 1",
"text to embed number 2"
],
"model": "E5-Mistral-7B-Instruct"
}
'
import SambaNova from 'sambanova';const client = new SambaNova({ apiKey: process.env['SAMBANOVA_API_KEY'], // This is the default and can be omitted});const embeddingsResponse = await client.embeddings.create({ input: ['text to embed number 1', 'text to embed number 2'], model: 'E5-Mistral-7B-Instruct',});console.log(embeddingsResponse.data);
import os
from sambanova import SambaNova
client = SambaNova(
api_key=os.environ.get("SAMBANOVA_API_KEY"), # This is the default and can be omitted
)
embeddings_response = client.embeddings.create(
input=["text to embed number 1", "text to embed number 2"],
model="E5-Mistral-7B-Instruct",
)
print(embeddings_response.data)
curl --request POST \
--url https://api.sambanova.ai/v1/embeddings \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"input": [
"text to embed number 1",
"text to embed number 2"
],
"model": "E5-Mistral-7B-Instruct"
}
'
SambaNova API key, sent as a bearer token in the Authorization header (Authorization: Bearer <key>). Default authentication scheme used by the SambaNova SDK across every OpenAI compatible endpoint.
Body
application/json
Texts to embed and parameters
embeddings request object. Unknown fields are rejected with a 400 (unknown_parameter) error.
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