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retrieve.WatsonDiscoveryRM

Constructor​

The constructor initializes the WatsonDiscoveryRM class instance and sets up the request parameters for interacting with Watson Discovery service at IBM Cloud.

class WatsonDiscoveryRM:
    def __init__(
        self,
        apikey: str,
        url:str,
        version:str,
        project_id:str,
        collection_ids:list=[],
        k: int = 7,
    ):

Parameters:

  • apikey (str): apikey for authentication purposes,
  • url (str): endpoint URL that includes the service instance ID
  • version (str): Release date of the version of the API you want to use. Specify dates in YYYY-MM-DD format.
  • project_id (str): The Universally Unique Identifier (UUID) of the project.
  • collection_ids (list): An array containing the collections on which the search will be executed.
  • k (int, optional): The number of top passages to retrieve. Defaults to 7.

Methods​

forward(self, query_or_queries: Union[str, list[str]], k: Optional[int]= None) -> dspy.Prediction:​

Search the Watson Discovery collection for the top k passages matching the given query or queries.

Parameters:

  • query_or_queries (Union[str, list[str]]): The query or list of queries to search for.
  • k (Optional[int], optional): The number of results to retrieve. If not specified, defaults to the value set during initialization.

Returns:

  • dspy.Prediction: Contains the retrieved passages, each represented as a dotdict with schema [{"title":str, "long_text": str, "passage_score": float, "document_id": str, "collection_id": str, "start_offset": int, "end_offset": int, "field": str}]

Quickstart​

import dspy

retriever_model = WatsonDiscoveryRM(
    apikey = "Your API Key",
    url = "URL of the Watson Discovery Service",
    version = "2023-03-31",
    project_id = "Project Id",
    collection_ids = ["Collection ID"],
    k = 5
)

retrieval_response = retriever_model("Explore the significance of quantum computing",k=5)

for result in retrieval_response:
    print("Document:", result.long_text, "\n")