Skip to main content

Arcee Retriever

This notebook demonstrates how to use the ArceeRetriever class to retrieve relevant document(s) for Arcee’s Domain Adapted Language Models (DALMs).

Setup​

Before using ArceeRetriever, make sure the Arcee API key is set as ARCEE_API_KEY environment variable. You can also pass the api key as a named parameter.

from langchain.retrievers import ArceeRetriever

retriever = ArceeRetriever(
    model="DALM-PubMed",
    # arcee_api_key="ARCEE-API-KEY" # if not already set in the environment
)

Additional Configuration​

You can also configure ArceeRetriever’s parameters such as arcee_api_url, arcee_app_url, and model_kwargs as needed. Setting the model_kwargs at the object initialization uses the filters and size as default for all the subsequent retrievals.

retriever = ArceeRetriever(
    model="DALM-PubMed",
    # arcee_api_key="ARCEE-API-KEY", # if not already set in the environment
    arcee_api_url="https://custom-api.arcee.ai",  # default is https://api.arcee.ai
    arcee_app_url="https://custom-app.arcee.ai",  # default is https://app.arcee.ai
    model_kwargs={
        "size": 5,
        "filters": [
            {
                "field_name": "document",
                "filter_type": "fuzzy_search",
                "value": "Einstein",
            }
        ],
    },
)

Retrieving documents​

You can retrieve relevant documents from uploaded contexts by providing a query. Here’s an example:

query = "Can AI-driven music therapy contribute to the rehabilitation of patients with disorders of consciousness?"
documents = retriever.get_relevant_documents(query=query)

Additional parameters​

Arcee allows you to apply filters and set the size (in terms of count) of retrieved document(s). Filters help narrow down the results. Here’s how to use these parameters:

# Define filters
filters = [
    {"field_name": "document", "filter_type": "fuzzy_search", "value": "Music"},
    {"field_name": "year", "filter_type": "strict_search", "value": "1905"},
]

# Retrieve documents with filters and size params
documents = retriever.get_relevant_documents(query=query, size=5, filters=filters)