docs: text splitters improvements (#4490)

#docs: text splitters improvements

Changes are only in the Jupyter notebooks.
- added links to the source packages and a short description of these
packages
- removed " Text Splitters" suffixes from the TOC elements (they made
the list of the text splitters messy)
- moved text splitters, based on the length function into a separate
list. They can be mixed with any classes from the "Text Splitters", so
it is a different classification.

## Who can review?
        @hwchase17 - project lead
        @eyurtsev
        @vowelparrot

NOTE: please, check out the results of the `Python code` text splitter
example (text_splitters/examples/python.ipynb). It looks suboptimal.

docs/modules/indexes/text_splitters/examples/python.ipynb

@@ -5,19 +5,21 @@
    "id": "c350765d",
    "metadata": {},
    "source": [
-    "# Python Code Text Splitter\n",
+    "# Python Code\n",
     "\n",
-    "PythonCodeTextSplitter splits text along python class and method definitions. It's implemented as a simple subclass of RecursiveCharacterSplitter with Python-specific separators. See the source code to see the Python syntax expected by default.\n",
+    "`PythonCodeTextSplitter` splits text along python class and method definitions. It's implemented as a simple subclass of `RecursiveCharacterSplitter` with Python-specific separators. See the source code to see the Python syntax expected by default.\n",
     "\n",
-    "1. How the text is split: by list of python specific characters\n",
-    "2. How the chunk size is measured: by length function passed in (defaults to number of characters)"
+    "1. How the text is split: by list of python specific separators\n",
+    "2. How the chunk size is measured: by number of characters"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "id": "1703463f",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "from langchain.text_splitter import PythonCodeTextSplitter"
@@ -27,7 +29,9 @@
    "cell_type": "code",
    "execution_count": 2,
    "id": "f17a1854",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "python_text = \"\"\"\n",
@@ -77,6 +81,37 @@
    "source": [
     "docs"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "de625e08-c440-489d-beed-020b6c53bf69",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Foo:\\n\\n    def bar():', 'foo():\\n\\ndef testing_func():', 'bar():']"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "python_splitter.split_text(python_text)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "55aadd84-75ca-48ae-9b84-b39c368488ed",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -95,7 +130,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.10.6"
   },
   "vscode": {
    "interpreter": {