Create retriever.py

retriever.py

@@ -0,0 +1,52 @@
+from smolagents import Tool
+from langchain_community.retrievers import BM25Retriever
+from langchain.docstore.document import Document
+import datasets
+
+
+class GuestInfoRetrieverTool(Tool):
+    name = "guest_info_retriever"
+    description = "Retrieves detailed information about gala guests based on their name or relation."
+    inputs = {
+        "query": {
+            "type": "string",
+            "description": "The name or relation of the guest you want information about."
+        }
+    }
+    output_type = "string"
+
+    def __init__(self, docs):
+        self.is_initialized = False
+        self.retriever = BM25Retriever.from_documents(docs)
+       
+
+    def forward(self, query: str):
+        results = self.retriever.get_relevant_documents(query)
+        if results:
+            return "\n\n".join([doc.page_content for doc in results[:3]])
+        else:
+            return "No matching guest information found."
+
+
+def load_guest_dataset():
+    # 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
+    ]
+
+    # Return the tool
+    return GuestInfoRetrieverTool(docs)
+
+