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from langchain_community.retrievers import BM25Retriever
import datasets
from langchain.docstore.document import Document
class GuestInfoRetriever:
"""A class to retrieve information about gala guests."""
def __init__(self, docs):
self.docs = docs
self.dataset = BM25Retriever.from_documents(docs)
def retrieve(self, query: str):
"""Retrieves detailed information about gala guests based on their name or relation."""
results = self.dataset.invoke(query)
if results:
return "\n\n".join([doc.page_content for doc in results[:3]])
else:
return "No matching guest information found."
# Load the dataset
def load_guest_dataset():
guest_dataset = datasets.load_dataset("agents-course/unit3-invitees", split="train")
# Convert dataset entries into Document objects
docs = [
Document(
page_content="\n".join([
f"Name: {guest['name']}",
f"Relation: {guest['relation']}",
f"Description: {guest['description']}",
f"Email: {guest['email']}"
]),
metadata={"name": guest["name"]}
)
for guest in guest_dataset
]
return GuestInfoRetriever(docs)
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