Fix use case sentence for bash util doc (#1295)

Thanks for all your hard work!

I noticed a small typo in the bash util doc so here's a quick update.
Additionally, my formatter caught some spacing in the `.md` as well.
Happy to revert that if it's an issue.

The main change is just
```
- A common use case this is for letting it interact with your local file system. 

+ A common use case for this is letting the LLM interact with your local file system.
```

## Testing

`make docs_build` succeeds locally and the changes show as expected ✌️ 
<img width="704" alt="image"
src="https://user-images.githubusercontent.com/17773666/221376160-e99e59a6-b318-49d1-a1d7-89f5c17cdab4.png">

docs/modules/utils/examples/bash.ipynb

@@ -1,85 +1,85 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "8f210ec3",
-   "metadata": {},
-   "source": [
-    "# Bash\n",
-    "It can often be useful to have an LLM generate bash commands, and then run them. A common use case this is for letting it interact with your local file system. We provide an easy util to execute bash commands."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "f7b3767b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain.utilities import BashProcess"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "cf1c92f0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bash = BashProcess()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "2fa952fc",
-   "metadata": {},
-   "outputs": [
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "id": "8f210ec3",
+      "metadata": {},
+      "source": [
+        "# Bash\n",
+        "It can often be useful to have an LLM generate bash commands, and then run them. A common use case for this is letting the LLM interact with your local file system. We provide an easy util to execute bash commands."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "id": "f7b3767b",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from langchain.utilities import BashProcess"
+      ]
+    },
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "bash.ipynb\n",
-      "google_search.ipynb\n",
-      "python.ipynb\n",
-      "requests.ipynb\n",
-      "serpapi.ipynb\n",
-      "\n"
-     ]
+      "cell_type": "code",
+      "execution_count": 2,
+      "id": "cf1c92f0",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "bash = BashProcess()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "id": "2fa952fc",
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "bash.ipynb\n",
+            "google_search.ipynb\n",
+            "python.ipynb\n",
+            "requests.ipynb\n",
+            "serpapi.ipynb\n",
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(bash.run(\"ls\"))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "851fee9f",
+      "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": "3.10.9"
     }
-   ],
-   "source": [
-    "print(bash.run(\"ls\"))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "851fee9f",
-   "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": "3.10.9"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
+  "nbformat": 4,
+  "nbformat_minor": 5
 }

docs/modules/utils/key_concepts.md

@@ -1,29 +1,35 @@
 # Key Concepts
 
 ## Python REPL
-Sometimes, for complex calculations, rather than have an LLM generate the answer directly, 
-it can be better to have the LLM generate code to calculate the answer, and then run that code to get the answer. 
+
+Sometimes, for complex calculations, rather than have an LLM generate the answer directly,
+it can be better to have the LLM generate code to calculate the answer, and then run that code to get the answer.
 In order to easily do that, we provide a simple Python REPL to execute commands in.
-This interface will only return things that are printed - 
+This interface will only return things that are printed -
 therefore, if you want to use it to calculate an answer, make sure to have it print out the answer.
 
 ## Bash
-It can often be useful to have an LLM generate bash commands, and then run them. 
-A common use case this is for letting it interact with your local file system. 
+
+It can often be useful to have an LLM generate bash commands, and then run them.
+A common use case for this is letting the LLM interact with your local file system.
 We provide an easy component to execute bash commands.
 
 ## Requests Wrapper
-The web contains a lot of information that LLMs do not have access to. 
-In order to easily let LLMs interact with that information, 
+
+The web contains a lot of information that LLMs do not have access to.
+In order to easily let LLMs interact with that information,
 we provide a wrapper around the Python Requests module that takes in a URL and fetches data from that URL.
 
 ## Google Search
+
 This uses the official Google Search API to look up information on the web.
 
 ## SerpAPI
+
 This uses SerpAPI, a third party search API engine, to interact with Google Search.
 
 ## Searx Search
+
 This uses the Searx (SearxNG fork) meta search engine API to lookup information
-on the web.  It supports 139 search engines and is easy to self-host
+on the web. It supports 139 search engines and is easy to self-host
 which makes it a good choice for privacy-conscious users.