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Credentials

Open the file named io_config.yaml at the root of your Mage project and enter chroma required fields: 
version: 0.1.1
default:
  CHROMA_COLLECTION: collection_name
  CHROMA_PATH: path of the chroma persisitant storage

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Dependencies

The dependency libraries are not installed in the docker image by default. You’ll need to add the libraries to project requirements.txt file manually and install them. 
chromadb>=0.4.17

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Using Python block

  1. Create a new pipeline or open an existing pipeline.
  2. Add a data loader or data exporter with Template. Under “Databases” category you can find the “Chroma” template.
  • Chroma data loader arguments:
    • n_results: Number of results to match.
    • collection: collection to use. Otherwise the collection defined in io_config.yml will be used.
    • query_texts: the texts or documents used to query.
    • query_embeddings: the embeddings used to query. Either query_texts or query_embeddings should be available.
  • Chroma data exporter arguments:
    • df: Dataframe contains the actual data.
    • collection: collection to use. Otherwise the collection defined in io_config.yml will be used.
    • document_column: specify the column in df dataframe that contains documents to be stored in Chroma.
    • id_column: specify the column in df dataframe that contains the id of the document
    • metadata_column: specify the column in df dataframe that contains the metadata of the document (metadata should be dictionary format)
  1. Add your customized code into the loader, exporter or add extra transformer blocks.
  2. Run the block.