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Router.Embeddings

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Create an Embedding

Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. 
from orq_ai_sdk import Orq
import os

with Orq(
    api_key=os.getenv("ORQ_API_KEY", ""),
) as orq:

    res = orq.router.embeddings.create(input=[
        "<value 1>",
        "<value 2>",
    ], model="V90", encoding_format="float", fallbacks=[
        {
            "model": "openai/text-embedding-3-small",
        },
    ], retry={
        "on_codes": [
            429,
            500,
            502,
            503,
            504,
        ],
    }, cache={
        "ttl": 3600,
        "type": "exact_match",
    }, load_balancer={
        "type": "weight_based",
        "models": [
            {
                "model": "openai/gpt-4o",
                "weight": 0.7,
            },
        ],
    }, timeout={
        "call_timeout": 30000,
    }, orq={
        "fallbacks": [
            {
                "model": "openai/gpt-4o-mini",
            },
        ],
        "cache": {
            "ttl": 3600,
            "type": "exact_match",
        },
        "retry": {
            "on_codes": [
                429,
                500,
                502,
                503,
                504,
            ],
        },
        "identity": {
            "id": "contact_01ARZ3NDEKTSV4RRFFQ69G5FAV",
            "display_name": "Jane Doe",
            "email": "jane.doe@example.com",
            "metadata": [
                {
                    "department": "Engineering",
                    "role": "Senior Developer",
                },
            ],
            "logo_url": "https://example.com/avatars/jane-doe.jpg",
            "tags": [
                "hr",
                "engineering",
            ],
        },
        "load_balancer": {
            "type": "weight_based",
            "models": [
                {
                    "model": "openai/gpt-4o",
                    "weight": 0.7,
                },
                {
                    "model": "anthropic/claude-3-5-sonnet",
                    "weight": 0.3,
                },
            ],
        },
        "timeout": {
            "call_timeout": 30000,
        },
    })

    # Handle response
    print(res)