docs

app.py

@@ -4,9 +4,28 @@ import random
 from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint, HuggingFacePipeline
 from langchain.schema import AIMessage, HumanMessage
 import os
+import datasets
+from langchain.docstore.document import Document
 
 login(token=os.environ["HUGGINGFACEHUB_API_TOKEN"])
 
+# 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
+]
+
 llm = HuggingFaceEndpoint(
     repo_id="HuggingFaceH4/zephyr-7b-beta",
     task="text-generation",