#[cfg(feature = "pinecone")]
use oris_runtime::{
embedding::openai::openai_embedder::OpenAiEmbedder, schemas::Document,
vectorstore::pinecone::StoreBuilder, vectorstore::VecStoreOptions, vectorstore::VectorStore,
};
#[cfg(feature = "pinecone")]
#[tokio::main]
async fn main() {
let api_key = std::env::var("PINECONE_API_KEY").expect("PINECONE_API_KEY");
let environment = std::env::var("PINECONE_ENV").unwrap_or_else(|_| "us-east1-gcp".into());
let index_name = std::env::var("PINECONE_INDEX").unwrap_or_else(|_| "oris".into());
let store = StoreBuilder::new()
.api_key(api_key)
.environment(environment)
.index_name(index_name)
.embedder(OpenAiEmbedder::default())
.build()
.await
.unwrap();
let doc1 = Document::new("oris is a programmable AI execution runtime in Rust.");
let doc2 = Document::new("oris is a programmable AI execution runtime in Rust.");
let doc3 = Document::new("Capital of USA is Washington D.C. Capital of France is Paris.");
let opt = VecStoreOptions::default();
let _ids = store
.add_documents(&[doc1, doc2, doc3], &opt)
.await
.unwrap();
let results = store
.similarity_search("capital of France", 2, &opt)
.await
.unwrap();
for r in &results {
println!(" {}", r.page_content);
}
}
#[cfg(not(feature = "pinecone"))]
fn main() {
println!("Run: cargo run --example vector_store_pinecone --features pinecone");
}