add save and load tfidf vectorizer and docs for TFIDFRetriever (#8112)

This is to add save_local and load_local to tfidf_vectorizer and docs in
tfidf_retriever to make the vectorizer reusable.

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- Description: add save_local and load_local to tfidf_vectorizer and
docs in tfidf_retriever
  - Issue: None
  - Dependencies: None
  - Tag maintainer: @rlancemartin, @eyurtsev
  - Twitter handle: @MlopsJ

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  2. an example notebook showing its use.

Maintainer responsibilities:
  - General / Misc / if you don't know who to tag: @baskaryan
  - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev
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---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>

docs/extras/integrations/retrievers/tf_idf.ipynb

@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "id": "a801b57c",
    "metadata": {},
    "outputs": [],
@@ -26,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "393ac030",
    "metadata": {
     "tags": []
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "98b1c017",
    "metadata": {
     "tags": []
@@ -133,6 +133,68 @@
    "source": [
     "result"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "363f3c04",
+   "metadata": {},
+   "source": [
+    "## Save and load\n",
+    "\n",
+    "You can easily save and load this retriever, making it handy for local development!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "10c90d03",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "retriever.save_local(\"testing.pkl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "fb3b153c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "retriever_copy = TFIDFRetriever.load_local(\"testing.pkl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "c03ff3c7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Document(page_content='foo', metadata={}),\n",
+       " Document(page_content='foo bar', metadata={}),\n",
+       " Document(page_content='hello', metadata={}),\n",
+       " Document(page_content='world', metadata={})]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "retriever_copy.get_relevant_documents(\"foo\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2d7c5728",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -151,7 +213,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.10.1"
   }
  },
  "nbformat": 4,