use std::collections::HashMap;

use qdrant_client::{
    Payload, Qdrant,
    qdrant::{Document, NamedVectors, PointStruct, UpsertPointsBuilder, Value},
};

pub async fn main() -> anyhow::Result<()> {
    let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide

    client
        .with_header("openai-api-key", "<YOUR_OPENAI_API_KEY>")
        .upsert_points(
            UpsertPointsBuilder::new(
                "{collection_name}",
                vec![PointStruct::new(
                    1,
                    NamedVectors::default()
                        .add_vector(
                            "large",
                            Document {
                                text: "Recipe for baking chocolate chip cookies".into(),
                                model: "openai/text-embedding-3-small".into(),
                                options: HashMap::new(),
                            },
                        )
                        .add_vector(
                            "small",
                            Document {
                                text: "Recipe for baking chocolate chip cookies".into(),
                                model: "openai/text-embedding-3-small".into(),
                                options: HashMap::<String, Value>::from_iter(vec![(
                                    "mrl".into(),
                                    Value::from(64),
                                )]),
                            },
                        ),
                    Payload::default(),
                )],
            )
            .wait(true),
        )
        .await?;

    Ok(())
}