Telegram Chatbot

This is developed as one of Algoritma Academy Data Analytics Specialization Capstone Projects. The deliverable of this project is a Python script to create a Telegram chatbot using telebot package. I also deploy the chatbot to PythonAnywhere to run the program.

Note

You can test this Telegram chatbot live here. If the chatbot is unresponsive, it may be due to free-tier hosting limitations. Please check out the demo video (here) showcasing its full functionality. Alternatively, you can contact me and I'll be happy to activate it for you to test live!

Rubrics

The maximum score you will obtain from this project is 16 points:

• Setup (3 points)

  • Prepare virtual environment
    • Please provide requirements.txt on the project folder.
  • Create Telegram bot API via BotFather
    • Please provide your bot link when making a submission.
  • Using os.environ to secure token
    • Important: Make sure you do not push .env to your GitHub Repository.

• Chatbot functionalities

  • Basic function (3 points)
    • Command /start or /help: correctly respond to user trigger
    • Command /about: provide developer information
    • Function echo_all(): using emoji
  • Summary text report: /summary (3 points)
    • Perform necessary data wrangling steps to extract information
    • Perform the right mathematical calculation
    • Send summary message using Template
  • Visualization report: /plot (4 points)
    • Perform necessary data wrangling steps to extract information
    • Perform the right mathematical calculation
    • Send plot with caption
    • Tidy plot layout (title, label, color, size)

• Application deployment (3 points)

  • Using Flask to serve the chatbot as an application
  • Deploy to Railway
  • Deployed chatbot run smoothly without error

Project File Structure

telebot
├── 📁 assets
├── 📁 cache
├── 📁 data_input
├── 📁 template_text
├── .gitignore
├── </> app.py
├── </> bot_local.py
├── 📝 Notebook Guide.ipynb
├── 🚀 Procfile
├── 📝 requirements.txt
└── 📝 runtime.txt

• Folders (DO NOT CHANGE):

  • assets: Images used in notebook
  • cache: Pickled Python object
  • data_input: Dataset for analysis
  • template_text: Text files for chat template

• Application-related Files (TO BE COMPLETED BY STUDENT):

  • app.py: Main Flask application
  • bot_local.py: Telegram bot to be run locally
  • Notebook Guide.ipynb: Main guide for the project workflow

• Deployment-related Files (DO NOT CHANGE):

  • .gitignore: List of file extensions to be ignored when git push from local
  • Procfile: Commands for app's dynos on Railway
  • requirements.txt: List of package dependencies to be installed on Railway
  • runtime.txt: Python version to be installed on Railway

Requirements

• Python 3.10
• emoji==2.2.0
• Flask==2.2.2
• gunicorn==20.1.0
• matplotlib==3.6.2
• pandas==1.5.2
• pyTelegramBotAPI==4.8.0
• python-dotenv==0.21.0
• gTTS==2.3.0

For instructions on how to prepare the virtual environment and requirements, please read Notebook Guide.ipynb.

Expected Output

Telegram Bot Account

Create a bot that can provide report on Facebook daily ads for different marketing campaign. Here is an example: https://t.me/algo_capstone_telebot

Here are the chatbot functionalities:

1. Command /start or /help: send welcome message containing list of available commands.

2. Command /about: send information about the bot developer.

3. Command /summary: generate text report for selected campaign ID.

Reply from bot after campaign ID is selected:

4. Command /plot: generate visualization and voice message report per age group for selected campaign ID.

Reply from bot after campaign ID is selected:

Voice message: Sample audio for Campaign ID 916

This is your requested plot for Campaign ID 916. Age group with the highest total spent is 30-34, while the lowest is 40-44. Age group with the highest total approved conversion is 30-34, while the lowest is 45-49. Age group with the highest average CPC is 45-49, while the lowest is 40-44.

5. Default message: handle messages other than the previous commands.

Deployed Application

This bot is expected to run continuously on a server. Therefore we create a Flask application which deployed to Railway.