Create retriever.py

Creating retriever.py

retriever.py

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+# Step 1: Load and Prepare the Dataset
+# First, we need to transform our raw guest data into a format that’s optimized for retrieval.
+
+# We will use the Hugging Face datasets library to load the dataset and convert it into a list of Document objects from the langchain.docstore.document module.
+
+import datasets
+from langchain_core.documents import Document
+
+# Load the 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
+]