diff --git a/TikTok/TikTok_Get_liked_videos.ipynb b/TikTok/TikTok_Get_liked_videos.ipynb
new file mode 100644
index 0000000000..eb0369483f
--- /dev/null
+++ b/TikTok/TikTok_Get_liked_videos.ipynb
@@ -0,0 +1,407 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e04c2a66-0232-4311-8445-d69e43f287e7",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-01-07T21:15:57.009861Z",
+     "iopub.status.busy": "2022-01-07T21:15:57.009532Z",
+     "iopub.status.idle": "2022-01-07T21:15:57.013136Z",
+     "shell.execute_reply": "2022-01-07T21:15:57.012559Z",
+     "shell.execute_reply.started": "2022-01-07T21:15:57.009826Z"
+    },
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "<img width=\"8%\" alt=\"TikTok.png\" src=\"https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/.github/assets/logos/TikTok.png\" style=\"border-radius: 15%\">"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47c20033-2e43-4c30-9d89-6fd47bfa98e9",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "# TikTok - Get liked videos by profile\n",
+    "<a href=\"https://bit.ly/3JyWIk6\">Give Feedback</a> | <a href=\"https://github.com/jupyter-naas/awesome-notebooks/issues/new?assignees=&labels=bug&template=bug_report.md&title=TikTok+-+Get+videos+stats:+Error+short+description\">Bug report</a>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6ec59f5e-ac9e-4ab0-a0e9-51b01b38dcaa",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "**Tags:** #tiktok #videos #snippet #content"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c40e4f30-0b07-4a3b-b39b-7cb460053f74",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "**Author:** [Alex Nodeland](https://www.linkedin.com/in/alexnodeland/)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6861607a-c840-4f0e-b03c-346e3351972a",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "**Last update:** 2023-06-21 (Created: 2022-06-21)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "naas-description",
+   "metadata": {
+    "papermill": {},
+    "tags": [
+     "description"
+    ]
+   },
+   "source": [
+    "**Description:** This notebook provides a script to retrieve a list of the liked videos of a given user on the popular social media platform, TikTok."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "618b546f-943a-498c-9eb6-637a1e992f21",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "## Input"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91fc2ccf-9a27-40f4-bb62-df542a468bc6",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-01-08T05:48:50.458541Z",
+     "iopub.status.busy": "2022-01-08T05:48:50.458187Z",
+     "iopub.status.idle": "2022-01-08T05:48:50.465249Z",
+     "shell.execute_reply": "2022-01-08T05:48:50.464699Z",
+     "shell.execute_reply.started": "2022-01-08T05:48:50.458451Z"
+    },
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4f6774a6-ff96-4c39-87a7-69a1fd3777cc",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import time\n",
+    "import csv\n",
+    "import sys\n",
+    "import pandas as pd\n",
+    "try:\n",
+    "    from selenium import webdriver\n",
+    "    from selenium.webdriver.common.by import By\n",
+    "    from selenium.webdriver.support.ui import WebDriverWait\n",
+    "    from selenium.webdriver.support import expected_conditions as EC\n",
+    "except:\n",
+    "    %pip install selenium --user\n",
+    "    %pip install PyTikTokAPI --user\n",
+    "    from selenium import webdriver\n",
+    "    from selenium.webdriver.common.by import By\n",
+    "    from selenium.webdriver.support.ui import WebDriverWait\n",
+    "    from selenium.webdriver.support import expected_conditions as EC\n",
+    "try:\n",
+    "    from bs4 import BeautifulSoup\n",
+    "except:\n",
+    "    %pip install beautifulsoup4 --user\n",
+    "    from bs4 import BeautifulSoup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "958d3406-bf4c-48b9-b56b-ad4dad7caaae",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Setup variables\n",
+    "\n",
+    "**Mandatory**\n",
+    "- `USERNAME`: The username of the TikTok user whose liked videos you want to retrieve.\n",
+    "\n",
+    "**Optional**\n",
+    "- `LIMIT`: The maximum number of liked videos to retrieve. Default is None (no limit)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1a91eab8",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "#Mandatory\n",
+    "USERNAME = '<username>'\n",
+    "\n",
+    "#Optional\n",
+    "LIMIT = 100"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "43fff853-fdf1-4949-a781-43b31e65cce9",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "## Model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da6d5ea2",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Web automations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f40d0a0b",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def click_liked_tab(driver):\n",
+    "    try:\n",
+    "        liked_tab = WebDriverWait(driver, 10).until(\n",
+    "            EC.element_to_be_clickable((By.CSS_SELECTOR, \"p[data-e2e='liked-tab']\"))\n",
+    "        )\n",
+    "        liked_tab.click()\n",
+    "        print(\"Clicked on Liked tab successfully\")\n",
+    "    except Exception as e:\n",
+    "        print(f\"Failed to click on Liked tab: {e}\")\n",
+    "\n",
+    "def scroll_to_load_all_videos(driver, max_scrolls=10):\n",
+    "    last_height = driver.execute_script(\"return document.body.scrollHeight\")\n",
+    "    scrolls = 0\n",
+    "    \n",
+    "    while scrolls < max_scrolls:\n",
+    "        driver.execute_script(\"window.scrollTo(0, document.body.scrollHeight);\")\n",
+    "        time.sleep(2)  # Wait for page to load\n",
+    "        \n",
+    "        new_height = driver.execute_script(\"return document.body.scrollHeight\")\n",
+    "        if new_height == last_height:\n",
+    "            break\n",
+    "        last_height = new_height\n",
+    "        scrolls += 1\n",
+    "        print(f\"Scroll {scrolls}/{max_scrolls} completed\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "43d26535",
+   "metadata": {},
+   "source": [
+    "### Scraping"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "60ff8ee3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_video_elements(soup):\n",
+    "    # Strategy 1: Look for the main container with data-e2e attribute\n",
+    "    main_container = soup.find('div', attrs={'data-e2e': 'user-liked-item-list'})\n",
+    "    if main_container:\n",
+    "        # Find all direct child divs that contain video items\n",
+    "        videos = main_container.find_all('div', attrs={'data-e2e': 'user-liked-item'}, recursive=False)\n",
+    "        if videos:\n",
+    "            return videos\n",
+    "\n",
+    "    # Strategy 2: If the main container isn't found, search for video items directly\n",
+    "    videos = soup.find_all('div', attrs={'data-e2e': 'user-liked-item'})\n",
+    "    if videos:\n",
+    "        return videos\n",
+    "\n",
+    "    # Strategy 3: Look for divs with specific class and role\n",
+    "    videos = soup.find_all('div', class_=lambda x: x and 'DivContainer' in x, attrs={'role': 'button', 'aria-label': 'Watch in full screen'})\n",
+    "    if videos:\n",
+    "        return videos\n",
+    "\n",
+    "    # Strategy 4: Fallback to a more general approach\n",
+    "    videos = soup.find_all('div', class_=lambda x: x and ('ItemContainer' in x or 'VideoFeed' in x))\n",
+    "    return videos\n",
+    "\n",
+    "def extract_video_info(video_element):\n",
+    "    try:\n",
+    "        video_link = video_element.find('a')['href']\n",
+    "        return {'url': video_link}\n",
+    "    except Exception as e:\n",
+    "        print(f\"Error extracting video info: {e}\")\n",
+    "        return None"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "be6a2481",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Script"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e9a0144c",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def main(username, limit=None):\n",
+    "    driver = webdriver.Chrome()\n",
+    "    \n",
+    "    # Navigate directly to the user's profile\n",
+    "    driver.get(f\"https://www.tiktok.com/@{username}\")\n",
+    "    print(f\"Navigated to https://www.tiktok.com/@{username}\")\n",
+    "\n",
+    "    # Click on the Liked tab\n",
+    "    click_liked_tab(driver)\n",
+    "\n",
+    "    # Scroll to load more videos\n",
+    "    scroll_to_load_all_videos(driver)\n",
+    "\n",
+    "    page_source = driver.page_source\n",
+    "    soup = BeautifulSoup(page_source, 'html.parser')\n",
+    "\n",
+    "    videos = find_video_elements(soup)\n",
+    "    print(f\"Found {len(videos)} videos\")\n",
+    "\n",
+    "    # Create a DataFrame to store video information\n",
+    "    video_data = []\n",
+    "\n",
+    "    for video in videos:\n",
+    "        if limit and len(video_data) >= limit:\n",
+    "            break\n",
+    "        video_info = extract_video_info(video)\n",
+    "        if video_info:\n",
+    "            video_data.append(video_info)\n",
+    "\n",
+    "    df = pd.DataFrame(video_data)\n",
+    "    df.to_csv(f'{username}_liked_videos.csv', index=False, encoding='utf-8')\n",
+    "    print(f\"Data saved to {username}_liked_videos.csv\")\n",
+    "\n",
+    "    driver.quit()\n",
+    "\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5f6714c5",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "## Output"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4295fc59",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Get liked videos"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "08eaaac0",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "liked_videos = main(USERNAME, LIMIT)\n",
+    "liked_videos"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.11.5"
+  },
+  "naas": {
+   "notebook_id": "35f614b16e2f264d1d38670c7ca5c0fe010e4c1cd828f2812e8a58faaeaee557",
+   "notebook_path": "TikTok/TikTok_Get_videos_stats.ipynb"
+  },
+  "papermill": {
+   "default_parameters": {},
+   "environment_variables": {},
+   "parameters": {},
+   "version": "2.3.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/TikTok/TikTok_Get_liked_videos_transcripts.ipynb b/TikTok/TikTok_Get_liked_videos_transcripts.ipynb
new file mode 100644
index 0000000000..cfd3b35b5d
--- /dev/null
+++ b/TikTok/TikTok_Get_liked_videos_transcripts.ipynb
@@ -0,0 +1,567 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e04c2a66-0232-4311-8445-d69e43f287e7",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-01-07T21:15:57.009861Z",
+     "iopub.status.busy": "2022-01-07T21:15:57.009532Z",
+     "iopub.status.idle": "2022-01-07T21:15:57.013136Z",
+     "shell.execute_reply": "2022-01-07T21:15:57.012559Z",
+     "shell.execute_reply.started": "2022-01-07T21:15:57.009826Z"
+    },
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "<img width=\"8%\" alt=\"TikTok.png\" src=\"https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/.github/assets/logos/TikTok.png\" style=\"border-radius: 15%\">"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47c20033-2e43-4c30-9d89-6fd47bfa98e9",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "# TikTok - Get liked videos by profile\n",
+    "<a href=\"https://bit.ly/3JyWIk6\">Give Feedback</a> | <a href=\"https://github.com/jupyter-naas/awesome-notebooks/issues/new?assignees=&labels=bug&template=bug_report.md&title=TikTok+-+Get+videos+stats:+Error+short+description\">Bug report</a>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6ec59f5e-ac9e-4ab0-a0e9-51b01b38dcaa",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "**Tags:** #tiktok #videos #snippet #content"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c40e4f30-0b07-4a3b-b39b-7cb460053f74",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "**Author:** [Alex Nodeland](https://www.linkedin.com/in/alexnodeland/)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6861607a-c840-4f0e-b03c-346e3351972a",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "**Last update:** 2023-06-21 (Created: 2022-06-21)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "naas-description",
+   "metadata": {
+    "papermill": {},
+    "tags": [
+     "description"
+    ]
+   },
+   "source": [
+    "**Description:** This notebook provides a script to retrieve a list of the liked videos of a given user on the popular social media platform, TikTok."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "618b546f-943a-498c-9eb6-637a1e992f21",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "## Input"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91fc2ccf-9a27-40f4-bb62-df542a468bc6",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-01-08T05:48:50.458541Z",
+     "iopub.status.busy": "2022-01-08T05:48:50.458187Z",
+     "iopub.status.idle": "2022-01-08T05:48:50.465249Z",
+     "shell.execute_reply": "2022-01-08T05:48:50.464699Z",
+     "shell.execute_reply.started": "2022-01-08T05:48:50.458451Z"
+    },
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "4f6774a6-ff96-4c39-87a7-69a1fd3777cc",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import time\n",
+    "import os\n",
+    "import asyncio\n",
+    "import pandas as pd\n",
+    "import nest_asyncio\n",
+    "try:\n",
+    "    from openai import OpenAI\n",
+    "except:\n",
+    "    %pip install openai --user\n",
+    "    from openai import OpenAI\n",
+    "try:\n",
+    "    from selenium import webdriver\n",
+    "    from selenium.webdriver.common.by import By\n",
+    "    from selenium.webdriver.support.ui import WebDriverWait\n",
+    "    from selenium.webdriver.support import expected_conditions as EC\n",
+    "except:\n",
+    "    %pip install selenium --user\n",
+    "    %pip install PyTikTokAPI --user\n",
+    "    from selenium import webdriver\n",
+    "    from selenium.webdriver.common.by import By\n",
+    "    from selenium.webdriver.support.ui import WebDriverWait\n",
+    "    from selenium.webdriver.support import expected_conditions as EC\n",
+    "try:\n",
+    "    from bs4 import BeautifulSoup\n",
+    "except:\n",
+    "    %pip install beautifulsoup4 --user\n",
+    "    from bs4 import BeautifulSoup\n",
+    "try:\n",
+    "    from tiktokdl.download_post import get_post\n",
+    "except:\n",
+    "    %pip install tiktok-dlpy --user \n",
+    "    %%python -m playwright install --with-deps\n",
+    "    from tiktokdl.download_post import get_post\n",
+    "nest_asyncio.apply()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "958d3406-bf4c-48b9-b56b-ad4dad7caaae",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Setup variables\n",
+    "\n",
+    "**Mandatory**\n",
+    "- `USERNAME`: The username of the TikTok user whose liked videos you want to retrieve.\n",
+    "- `OPENAI_API_KEY`: Your OpenAI API key.\n",
+    "\n",
+    "**Optional**\n",
+    "- `LIMIT`: The maximum number of liked videos to retrieve. Default is None (no limit)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "1a91eab8",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "#Mandatory\n",
+    "USERNAME = '<username>'\n",
+    "OPENAI_API_KEY = '<openai_api_key>'\n",
+    "\n",
+    "#Optional\n",
+    "LIMIT = 3"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "43fff853-fdf1-4949-a781-43b31e65cce9",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "## Model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da6d5ea2",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Web automations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "f40d0a0b",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def click_liked_tab(driver):\n",
+    "    try:\n",
+    "        liked_tab = WebDriverWait(driver, 10).until(\n",
+    "            EC.element_to_be_clickable((By.CSS_SELECTOR, \"p[data-e2e='liked-tab']\"))\n",
+    "        )\n",
+    "        liked_tab.click()\n",
+    "        print(\"Clicked on Liked tab successfully\")\n",
+    "    except Exception as e:\n",
+    "        print(f\"Failed to click on Liked tab: {e}\")\n",
+    "\n",
+    "def scroll_to_load_all_videos(driver, max_scrolls=10):\n",
+    "    last_height = driver.execute_script(\"return document.body.scrollHeight\")\n",
+    "    scrolls = 0\n",
+    "    \n",
+    "    while scrolls < max_scrolls:\n",
+    "        driver.execute_script(\"window.scrollTo(0, document.body.scrollHeight);\")\n",
+    "        time.sleep(2)  # Wait for page to load\n",
+    "        \n",
+    "        new_height = driver.execute_script(\"return document.body.scrollHeight\")\n",
+    "        if new_height == last_height:\n",
+    "            break\n",
+    "        last_height = new_height\n",
+    "        scrolls += 1\n",
+    "        print(f\"Scroll {scrolls}/{max_scrolls} completed\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "43d26535",
+   "metadata": {},
+   "source": [
+    "### Scraping"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "60ff8ee3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_video_elements(soup):\n",
+    "    # Strategy 1: Look for the main container with data-e2e attribute\n",
+    "    main_container = soup.find('div', attrs={'data-e2e': 'user-liked-item-list'})\n",
+    "    if main_container:\n",
+    "        # Find all direct child divs that contain video items\n",
+    "        videos = main_container.find_all('div', attrs={'data-e2e': 'user-liked-item'}, recursive=False)\n",
+    "        if videos:\n",
+    "            return videos\n",
+    "\n",
+    "    # Strategy 2: If the main container isn't found, search for video items directly\n",
+    "    videos = soup.find_all('div', attrs={'data-e2e': 'user-liked-item'})\n",
+    "    if videos:\n",
+    "        return videos\n",
+    "\n",
+    "    # Strategy 3: Look for divs with specific class and role\n",
+    "    videos = soup.find_all('div', class_=lambda x: x and 'DivContainer' in x, attrs={'role': 'button', 'aria-label': 'Watch in full screen'})\n",
+    "    if videos:\n",
+    "        return videos\n",
+    "\n",
+    "    # Strategy 4: Fallback to a more general approach\n",
+    "    videos = soup.find_all('div', class_=lambda x: x and ('ItemContainer' in x or 'VideoFeed' in x))\n",
+    "    return videos\n",
+    "\n",
+    "def extract_video_info(video_element):\n",
+    "    try:\n",
+    "        video_link = video_element.find('a')['href']\n",
+    "        return {'url': video_link}\n",
+    "    except Exception as e:\n",
+    "        print(f\"Error extracting video info: {e}\")\n",
+    "        return None\n",
+    "    \n",
+    "async def download_tiktok_video(url, output_filename):\n",
+    "    try:\n",
+    "        video = await get_post(url)\n",
+    "        print(f\"Downloading {url} to {output_filename}\")\n",
+    "        if video.file_path:\n",
+    "            if os.path.abspath(video.file_path) != os.path.abspath(output_filename):\n",
+    "                os.rename(video.file_path, output_filename)\n",
+    "            print(f\"Downloaded {url} to {output_filename}\")\n",
+    "            return True\n",
+    "        else:\n",
+    "            print(f\"Error: No file path found for {url}\")\n",
+    "            return False\n",
+    "    except Exception as e:\n",
+    "        print(f\"Error downloading {url}: {e}\")\n",
+    "        return False"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b43aad2e",
+   "metadata": {},
+   "source": [
+    "### Transcription"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "12b372c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def transcribe_audio(file_path, client):\n",
+    "    try:\n",
+    "        with open(file_path, \"rb\") as audio_file:\n",
+    "            response = client.audio.transcriptions.create(\n",
+    "                model=\"whisper-1\",\n",
+    "                file=audio_file\n",
+    "            )\n",
+    "        return response.text\n",
+    "    except Exception as e:\n",
+    "        print(f\"Error transcribing {file_path}: {e}\")\n",
+    "        return \"Error\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "be6a2481",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Script"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "e9a0144c",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "async def main(username, limit=None):\n",
+    "    driver = webdriver.Chrome()\n",
+    "    \n",
+    "    # Navigate directly to the user's profile\n",
+    "    driver.get(f\"https://www.tiktok.com/@{username}\")\n",
+    "    print(f\"Navigated to https://www.tiktok.com/@{username}\")\n",
+    "\n",
+    "    # Click on the Liked tab\n",
+    "    click_liked_tab(driver)\n",
+    "\n",
+    "    # Scroll to load more videos\n",
+    "    scroll_to_load_all_videos(driver)\n",
+    "\n",
+    "    page_source = driver.page_source\n",
+    "    soup = BeautifulSoup(page_source, 'html.parser')\n",
+    "\n",
+    "    videos = find_video_elements(soup)\n",
+    "    print(f\"Found {len(videos)} videos\")\n",
+    "\n",
+    "    # Create a DataFrame to store video information\n",
+    "    video_data = []\n",
+    "\n",
+    "    # Set up OpenAI client\n",
+    "    client = OpenAI(api_key=OPENAI_API_KEY)\n",
+    "\n",
+    "    for video in videos:\n",
+    "        if limit and len(video_data) >= limit:\n",
+    "            break\n",
+    "        video_info = extract_video_info(video)\n",
+    "        if video_info:\n",
+    "            url = video_info['url']\n",
+    "            video_id = url.split('/')[-1]\n",
+    "            video_filename = f'{video_id}.mp4'\n",
+    "            \n",
+    "            try:\n",
+    "                # Download the TikTok video\n",
+    "                if await download_tiktok_video(url, video_filename):\n",
+    "                    # Transcribe the video\n",
+    "                    transcription = transcribe_audio(video_filename, client)\n",
+    "                    video_info['transcript'] = transcription\n",
+    "                else:\n",
+    "                    video_info['transcript'] = 'Error'\n",
+    "            finally:\n",
+    "                # Always try to remove the video file, even if an error occurred\n",
+    "                if os.path.exists(video_filename):\n",
+    "                    os.remove(video_filename)\n",
+    "            \n",
+    "            video_data.append(video_info)\n",
+    "\n",
+    "    driver.quit()\n",
+    "\n",
+    "    df = pd.DataFrame(video_data)\n",
+    "    df.to_csv(f'{username}_liked_videos_transcripts.csv', index=False, encoding='utf-8')\n",
+    "    print(f\"Data saved to {username}_liked_videos_transcripts.csv\")\n",
+    "\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5f6714c5",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "## Output"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4295fc59",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Get liked videos"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "08eaaac0",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Navigated to https://www.tiktok.com/@jeremyravenel\n",
+      "Failed to click on Liked tab: Message: element click intercepted: Element <p aria-selected=\"false\" role=\"tab\" data-e2e=\"liked-tab\" tabindex=\"0\" class=\"css-r7ao4-PLike e1jjp0pq4\">...</p> is not clickable at point (409, 330). Other element would receive the click: <div class=\"sc-fjdhpX klIBjd\">...</div>\n",
+      "  (Session info: chrome=126.0.6478.127)\n",
+      "Stacktrace:\n",
+      "\tGetHandleVerifier [0x00007FF7116EEEA2+31554]\n",
+      "\t(No symbol) [0x00007FF711667ED9]\n",
+      "\t(No symbol) [0x00007FF71152872A]\n",
+      "\t(No symbol) [0x00007FF71158012E]\n",
+      "\t(No symbol) [0x00007FF71157DAF2]\n",
+      "\t(No symbol) [0x00007FF71157AF8B]\n",
+      "\t(No symbol) [0x00007FF71157A156]\n",
+      "\t(No symbol) [0x00007FF71156C151]\n",
+      "\t(No symbol) [0x00007FF71159D02A]\n",
+      "\t(No symbol) [0x00007FF71156BA76]\n",
+      "\t(No symbol) [0x00007FF71159D240]\n",
+      "\t(No symbol) [0x00007FF7115BC977]\n",
+      "\t(No symbol) [0x00007FF71159CDD3]\n",
+      "\t(No symbol) [0x00007FF71156A33B]\n",
+      "\t(No symbol) [0x00007FF71156AED1]\n",
+      "\tGetHandleVerifier [0x00007FF7119F8B1D+3217341]\n",
+      "\tGetHandleVerifier [0x00007FF711A45AE3+3532675]\n",
+      "\tGetHandleVerifier [0x00007FF711A3B0E0+3489152]\n",
+      "\tGetHandleVerifier [0x00007FF71179E776+750614]\n",
+      "\t(No symbol) [0x00007FF71167375F]\n",
+      "\t(No symbol) [0x00007FF71166EB14]\n",
+      "\t(No symbol) [0x00007FF71166ECA2]\n",
+      "\t(No symbol) [0x00007FF71165E16F]\n",
+      "\tBaseThreadInitThunk [0x00007FFB2C66257D+29]\n",
+      "\tRtlUserThreadStart [0x00007FFB2E62AF28+40]\n",
+      "\n",
+      "Found 4 videos\n",
+      "Error extracting video info: 'NoneType' object is not subscriptable\n",
+      "Error extracting video info: 'NoneType' object is not subscriptable\n",
+      "Error extracting video info: 'NoneType' object is not subscriptable\n",
+      "Error extracting video info: 'NoneType' object is not subscriptable\n",
+      "Data saved to jeremyravenel_liked_videos_transcripts.csv\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: []\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "liked_videos_transcripts = asyncio.run(main(USERNAME, LIMIT))\n",
+    "liked_videos_transcripts"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.11.5"
+  },
+  "naas": {
+   "notebook_id": "35f614b16e2f264d1d38670c7ca5c0fe010e4c1cd828f2812e8a58faaeaee557",
+   "notebook_path": "TikTok/TikTok_Get_videos_stats.ipynb"
+  },
+  "papermill": {
+   "default_parameters": {},
+   "environment_variables": {},
+   "parameters": {},
+   "version": "2.3.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}