use chromadb::client::{ChromaAuthMethod, ChromaClient, ChromaClientOptions, ChromaTokenHeader}; use chromadb::collection::{ChromaCollection, GetOptions, GetResult, CollectionEntries}; // With default ChromaClientOptions // Defaults to http://localhost:8000 let client: ChromaClient = ChromaClient::new(Default::default()); // With custom ChromaClientOptions let auth = ChromaAuthMethod::TokenAuth { token: "<TOKEN>".to_string(), header: ChromaTokenHeader::Authorization }; let client: ChromaClient = ChromaClient::new(ChromaClientOptions { url: Some("<CHROMADB_URL>".into()), database: "<DATABASE>".into(), auth });

use serde_json::json; // Get or create a collection with the given name and no metadata. let collection: ChromaCollection = client.get_or_create_collection("my_collection", None).await?; // Get the UUID of the collection let collection_uuid = collection.id(); println!("Collection UUID: {}", collection_uuid);

// Upsert some embeddings with documents and no metadata. let collection_entries = CollectionEntries { ids: vec!["demo-id-1".into(), "demo-id-2".into()], embeddings: Some(vec![vec![0.0_f32; 768], vec![0.0_f32; 768]]), metadatas: None, documents: Some(vec![ "Some document about 9 octopus recipies".into(), "Some other document about DCEU Superman Vs CW Superman".into() ]) }; let result: bool = collection.upsert(collection_entries, None).await?; // Create a filter object to filter by document content. let where_document = json!({ "$contains": "Superman" }); // Get embeddings from a collection with filters and limit set to 1.  // An empty IDs vec will return all embeddings. let get_query = GetOptions { ids: vec![], where_metadata: None, limit: Some(1), offset: None, where_document: Some(where_document), include: Some(vec!["documents".into(),"embeddings".into()]) }; let get_result: GetResult = collection.get(get_query).await?; println!("Get result: {:?}", get_result);

//Instantiate QueryOptions to perform a similarity search on the collection //Alternatively, an embedding_function can also be provided with query_texts to perform the search let query = QueryOptions { query_texts: None, query_embeddings: Some(vec![vec![0.0_f32; 768], vec![0.0_f32; 768]]), where_metadata: None, where_document: None, n_results: Some(5), include: None, }; let query_result: QueryResult = collection.query(query, None).await?; println!("Query result: {:?}", query_result);

let collection: ChromaCollection = client.get_or_create_collection("openai_collection", None).await?; let collection_entries = CollectionEntries { ids: vec!["demo-id-1", "demo-id-2"], embeddings: None, metadatas: None, documents: Some(vec![ "Some document about 9 octopus recipies", "Some other document about DCEU Superman Vs CW Superman"]) }; // Use OpenAI embeddings let openai_embeddings = OpenAIEmbeddings::new(Default::default()); collection.upsert(collection_entries, Some(Box::new(openai_embeddings))).await?;