templates[patch]: Add cohere librarian template (#14601)

Adding the example I build for the Cohere hackathon.

It can:

use a vector database to reccommend books

<img width="840" alt="image"
src="https://github.com/langchain-ai/langchain/assets/144115527/96543a18-217b-4445-ab4b-950c7cced915">

Use a prompt template to provide information about the library

<img width="834" alt="image"
src="https://github.com/langchain-ai/langchain/assets/144115527/996c8e0f-cab0-4213-bcc9-9baf84f1494b">

Use Cohere RAG to provide grounded results

<img width="822" alt="image"
src="https://github.com/langchain-ai/langchain/assets/144115527/7bb4a883-5316-41a9-9d2e-19fd49a43dcb">

---------

Co-authored-by: Erick Friis <erick@langchain.dev>

templates/cohere-librarian/cohere_librarian/rag.py

@@ -0,0 +1,16 @@
+from langchain.chat_models import ChatCohere
+from langchain.retrievers import CohereRagRetriever
+
+rag = CohereRagRetriever(llm=ChatCohere())
+
+
+def get_docs_message(message):
+    docs = rag.get_relevant_documents(message)
+    message_doc = next(
+        (x for x in docs if x.metadata.get("type") == "model_response"), None
+    )
+    return message_doc.page_content
+
+
+def librarian_rag(x):
+    return get_docs_message(x["message"])