https://github.com/anush008/chromadb-rs
Rust client library for ChromaDB
https://github.com/anush008/chromadb-rs
chromadb rust-lang similarity-search vector-database
Last synced: 6 months ago
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Rust client library for ChromaDB
- Host: GitHub
- URL: https://github.com/anush008/chromadb-rs
- Owner: Anush008
- License: mit
- Created: 2023-08-01T10:46:05.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2025-03-09T05:04:41.000Z (7 months ago)
- Last Synced: 2025-04-03T12:01:54.850Z (6 months ago)
- Topics: chromadb, rust-lang, similarity-search, vector-database
- Language: Rust
- Homepage: https://www.trychroma.com/
- Size: 167 KB
- Stars: 35
- Watchers: 2
- Forks: 10
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
## 💾 Installing the library
```shell
cargo add chromadb
```
## 📖 Documentation
The library reference can be found [here](https://docs.rs/chromadb).
## 🔍 Overview
#### The library provides 2 modules to interact with the ChromaDB server via API V1
* `client` - To interface with the ChromaDB server.
* `collection` - To interface with an associated ChromaDB collection.
#### You can connect to ChromaDB by instantiating a [ChromaClient](https://docs.rs/chromadb/latest/chromadb/v1/client/struct.ChromaClient.html)
```rust
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: "".to_string(),
header: ChromaTokenHeader::Authorization
};
let client: ChromaClient = ChromaClient::new(ChromaClientOptions {
url: Some("".into()),
database: "".into(),
auth
});
```
#### Now that a client is instantiated, we can interface with the ChromaDB server
```rust
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);
```
### With a collection instance, we can perform queries on the database
```rust
// 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);
```
Find more information about the available filters and options in the [get()](https://docs.rs/chromadb/latest/chromadb/v1/collection/struct.ChromaCollection.html#method.get) documentation.
### Performing a similarity search
```rust
//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);
```
### Support for Embedding providers
This crate has built-in support for OpenAI and SBERT embeddings.
To use [OpenAI](https://platform.openai.com/docs/guides/embeddings) embeddings, enable the `openai` feature in your Cargo.toml.
```rust
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?;
```
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