From f75f0dbad6030012470a275bf00f84506cd3469f Mon Sep 17 00:00:00 2001
From: Michael Landis <michael@momentohq.com>
Date: Fri, 26 May 2023 10:34:11 -0700
Subject: [PATCH] docs: improve flow of llm caching notebook (#5309)

# docs: improve flow of llm caching notebook

The notebook `llm_caching` demos various caching providers. In the
previous version, there was setup common to all examples but under the
`In Memory Caching` heading.

If a user comes and only wants to try a particular example, they will
run the common setup, then the cells for the specific provider they are
interested in. Then they will get import and variable reference errors.
This commit moves the common setup to the top to avoid this.

## Who can review?

Community members can review the PR once tests pass. Tag
maintainers/contributors who might be interested:

@dev2049
---
 .../models/llms/examples/llm_caching.ipynb    | 19 ++++++-------------
 1 file changed, 6 insertions(+), 13 deletions(-)

diff --git a/docs/modules/models/llms/examples/llm_caching.ipynb b/docs/modules/models/llms/examples/llm_caching.ipynb
index 149d7969..1f51e3bf 100644
--- a/docs/modules/models/llms/examples/llm_caching.ipynb
+++ b/docs/modules/models/llms/examples/llm_caching.ipynb
@@ -16,10 +16,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.llms import OpenAI"
+    "import langchain\n",
+    "from langchain.llms import OpenAI\n",
+    "\n",
+    "# To make the caching really obvious, lets use a slower model.\n",
+    "llm = OpenAI(model_name=\"text-davinci-002\", n=2, best_of=2)"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "id": "b50f0598",
    "metadata": {},
@@ -34,22 +39,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import langchain\n",
     "from langchain.cache import InMemoryCache\n",
     "langchain.llm_cache = InMemoryCache()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "f69f6283",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# To make the caching really obvious, lets use a slower model.\n",
-    "llm = OpenAI(model_name=\"text-davinci-002\", n=2, best_of=2)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 4,