The fastest vector
retrieval engine for
AI workloads

import os
from openai import AsyncOpenAI
from kyrodb import AsyncClient

client = AsyncOpenAI(
    api_key=os.environ["OPENAI_API_KEY"]
)
kyro = AsyncClient(
    api_key=os.environ["KYRODB_API_KEY"]
)
# Keep secrets in environment variables, never inline in code.

async def retrieve_context(user_query: str) -> str:
    # 1. Generate a fresh query embedding
    result = await client.embeddings.create(
        model="text-embedding-3-small",
        input=user_query,
    )
    vector = result.data[0].embedding

    # 2. Sub-millisecond ANN search via KyroDB
    results = await kyro.collection("enterprise_knowledge").search(
        vector=vector,
        limit=5,
        filters={"access_level": {"$gte": 2}}
    )

    return"\n".join(doc.text for doc in results)