Add deps and minor cleaning to cookbooks (#11886)

cookbook/LLaMA2_sql_chat.ipynb

@@ -12,17 +12,19 @@
    "source": [
     "## LLaMA2 chat with SQL\n",
     "\n",
-    "LangChain makes it easy to build diverse chains from building blocks.\n",
+    "[LangChain Expression Langugae (LCEL)](https://python.langchain.com/docs/expression_language/) makes it easy to build diverse chains \"from scratch.\"\n",
+    "\n",
+    "This cookbook shows how to combine three ideas using LCEL:\n",
+    "\n",
+    "* We want to enable a chat application\n",
+    "* We want to apply chat to a SQL database\n",
+    "* We want to use an open source LLM (LLaMA2)\n",
     "\n",
     "![cake.png](attachment:02bd3e70-6db4-40e2-9f6b-c83127eb2339.png)\n",
     "\n",
-    "This cookbook shows how to combine three ideas:\n",
+    "We can do this on SQLite DB containing 2023-24 NBA rosters.\n",
     "\n",
-    "* Chat\n",
-    "* SQL\n",
-    "* An OSS model (LLaMA2)\n",
-    "\n",
-    "It demonstrates chat over a SQLite DB containing 2023-24 NBA rosters."
+    "## Packages"
    ]
   },
   {
@@ -44,12 +46,12 @@
     "\n",
     "Use Replicate API for `llama-2-13b-chat`.\n",
     "\n",
-    "Note there is also support for running LLaMA2 locally (see [here](https://python.langchain.com/docs/guides/local_llms)). "
+    "Note: there is also support for running `LLaMA2` locally (see [here](https://python.langchain.com/docs/guides/local_llms))."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 1,
    "id": "416ecce7-8aec-4145-b3f1-587a9b8a4fe9",
    "metadata": {},
    "outputs": [
@@ -69,9 +71,6 @@
     "\n",
     "# Replicate API\n",
     "llama2_13b_chat = \"meta/llama-2-13b-chat:f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d\"\n",
-    "\n",
-    "# Set the system_prompt so that LLaMA will generate only the SQL statement, instead of being wordy and adding something like\n",
-    "# \"Sure! Here's the SQL query for the given input question: \" before the SQL query; otherwise custom parsing will be needed.\n",
     "llm = Replicate(\n",
     "    model=llama2_13b_chat,\n",
     "    input={\"temperature\": 0.01, \n",
@@ -87,12 +86,14 @@
    "source": [
     "## DB\n",
     "\n",
-    "Connect to a SQLite DB."
+    "Connect to a SQLite DB.\n",
+    "\n",
+    "To create this particular DB, you can use the code and follow the steps shown [here](https://github.com/facebookresearch/llama-recipes/blob/main/demo_apps/StructuredLlama.ipynb)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 2,
    "id": "025bdd82-3bb1-4948-bc7c-c3ccd94fd05c",
    "metadata": {},
    "outputs": [],
@@ -119,7 +120,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 3,
    "id": "5a4933ea-d9c0-4b0a-8177-ba4490c6532b",
    "metadata": {},
    "outputs": [
@@ -129,7 +130,7 @@
        "\" SELECT * FROM nba_roster WHERE NAME = 'Klay Thompson';\""
       ]
      },
-     "execution_count": 72,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }