added retrivier tool

faq_retriever.py

@@ -0,0 +1,41 @@
+from langchain.docstore.document import Document
+from langchain_community.retrievers import BM25Retriever
+from smolagents import Tool
+from faq_data import faq_entries
+
+# Convert the FAQ data into LangChain Documents
+docs = [
+    Document(
+        page_content="\n".join([
+            f"Category: {faq['category']}",
+            f"Question: {faq['question']}",
+            f"Answer: {faq['answer']}"
+        ]),
+        metadata={"category": faq["category"]}
+    )
+    for faq in faq_entries
+]
+
+# Create the custom FAQ retriever tool
+class FAQRetrieverTool(Tool):
+    name = "faq_retriever"
+    description = "Retrieves relevant internal company FAQ entries based on a user query."
+    inputs = {
+        "query": {
+            "type": "string",
+            "description": "User's question about internal company processes or services."
+        }
+    }
+    output_type = "string"
+
+    def __init__(self, documents):
+        self.retriever = BM25Retriever.from_documents(documents)
+
+    def forward(self, query: str) -> str:
+        results = self.retriever.get_relevant_documents(query)
+        if not results:
+            return "No relevant FAQ entry found."
+        return "\n\n".join(doc.page_content for doc in results[:2])  # Return top 2
+
+# Initialize the retriever tool
+faq_tool = FAQRetrieverTool(docs)