Redis langserve template (#12443)

Add Redis langserve template! Eventually will add semantic caching to
this too. But I was struggling to get that to work for some reason with
the LCEL implementation here.

- **Description:** Introduces the Redis LangServe template. A simple RAG
based app built on top of Redis that allows you to chat with company's
public financial data (Edgar 10k filings)
  - **Issue:** None
- **Dependencies:** The template contains the poetry project
requirements to run this template
  - **Tag maintainer:** @baskaryan @Spartee 
  - **Twitter handle:** @tchutch94

**Note**: this requires the commit here that deletes the
`_aget_relevant_documents()` method from the Redis retriever class that
wasn't implemented. That was breaking the langserve app.

---------

Co-authored-by: Sam Partee <sam.partee@redis.com>

templates/rag-redis/rag_redis.ipynb

@@ -0,0 +1,88 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "681a5d1e",
+   "metadata": {},
+   "source": [
+    "## Connect to RAG App\n",
+    "\n",
+    "Assuming you are already running this server:\n",
+    "```bash\n",
+    "langserve start\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "d774be2a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Nike's revenue in 2023 was $51.2 billion. \n",
+      "\n",
+      "Source: 'data/nke-10k-2023.pdf', Start Index: '146100'\n"
+     ]
+    }
+   ],
+   "source": [
+    "from langserve.client import RemoteRunnable\n",
+    "\n",
+    "rag_redis = RemoteRunnable('http://localhost:8000/rag-redis')\n",
+    "\n",
+    "print(rag_redis.invoke(\"What was Nike's revenue in 2023?\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "07ae0005",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "As of May 31, 2023, Nike had approximately 83,700 employees worldwide. This information can be found in the first piece of context provided. (source: data/nke-10k-2023.pdf, start_index: 32532)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(rag_redis.invoke(\"How many employees work at Nike?\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4a6b9f00",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}