ChromaDB

The AI-native embedding database

Exposing Publicly

This ChromaDB is by default exposed under the [Private Network](https://docs.railway.app/guides/private-networking). To use it under the public network you'll need to expose it under the public network and then replace `--host ::` with `--host 0.0.0.0` in the service's Start Command.

Documentation

All the documentation is covered [here](https://docs.trychroma.com)!

Examples

Javascript

```js // install the JS client and the (optional) default embedding function npm install --save chromadb chromadb-default-embed // set "type": "module" in your package.json import { ChromaClient } from 'chromadb' async function chromaExample() { const client = new ChromaClient(); const collection = await client.createCollection({name: "sample_collection"}); await collection.add({ documents: ["This is a document", "This is another document"], // we embed for you, or bring your own metadatas: [{ source: "my_source" }, { source: "my_source" }], // filter on arbitrary metadata! ids: ["id1", "id2"] // must be unique for each doc }); const results = await collection.query({ queryTexts: ["This is a query document"], nResults: 2, // where: {"metadata_field": "is_equal_to_this"}, // optional filter // whereDocument: {"$contains":"search_string"} // optional filter }); } chromaExample(); ```

Python

```py # python can also run in-memory with no server running: chromadb.PersistentClient() import chromadb client = chromadb.HttpClient() collection = client.create_collection("sample_collection") # Add docs to the collection. Can also update and delete. Row-based API coming soon! collection.add( documents=["This is document1", "This is document2"], # we embed for you, or bring your own metadatas=[{"source": "notion"}, {"source": "google-docs"}], # filter on arbitrary metadata! ids=["doc1", "doc2"], # must be unique for each doc ) results = collection.query( query_texts=["This is a query document"], n_results=2, # where={"metadata_field": "is_equal_to_this"}, # optional filter # where_document={"$contains":"search_string"} # optional filter ) ```