Setup

Let's get you started with
the all-new Sttabot console.

Start building, capturing and annotating your datasets to powerlifting your LLM models.

YoLoBot Preview

This section is to test, preview and deploy your Telegram bot.

You can first play around with your bot. Then, we will deploy it on  cloud servers.

Scale your AI applications and bots into an enterprise plan.

Why scale to enterprise?

Your applications should not rely on shared servers and public APIs if you want your users to efficiently use it all the time. 

Shared servers and public APIs are awesome for testing purpose or if you have a very small audience to actually use the application. However, if you have a good numbers of users who would be using this application more frequently, do scale to the enterprise edition.

Who should choose to scale their apps?

Other benefits of enterprise plan?

Other benefits.

Why choose Sttabot enterprise?

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Tutorial Videos to Make Your Dev Journey Easy..

More support videos coming soon..

See your AI application backend code

import telebot import requests import json TELEGRAM_API_KEY = ‘6130414057:AAH9yDANb3kTBoYKIFw46XhYj1Eobah8BFk’ STTABOT_API_KEY = ‘eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOjU3OTMsIm5hbWUiOiJoZWxsb2RlbW9AZGVtby5jb20iLCJpYXQiOjE2OTYyMjYyMDIsImV4cCI6MTg1MzkwNjIwMn0.khP3o3khrjzEMoIBtCHikUkAlpgF9rIADQK9t26SpaI’ # Initialize the bot bot = telebot.TeleBot(TELEGRAM_API_KEY) # Define a function to greet users when they start a chat with the bot @bot.message_handler(commands=[‘start’]) def greet_user(message): bot.send_message(message.chat.id, “Hello there! I am YoLoBot – I am here to help you!”) # Define a function to provide help information @bot.message_handler(commands=[‘help’]) def help_command(message): help_text = “You can use the following commands:n” help_text += “/start – Start a conversation with the bot.n” help_text += “/help – Get help and information about using the bot.n” help_text += “/support – Contact customer support.n” help_text += “/startchat – Start a chat with Sttabot.n” bot.send_message(message.chat.id, help_text) # Define a function to handle user messages and interact with Sttabot API @bot.message_handler(func=lambda message: True) def handle_message(message): user_message = message.text # Add instruction or context to the prompt context_instruction = “Instructions : A virtual assistant.. Please help me with the following:” # Combine context_instruction and user_message into the prompt prompt = f”{context_instruction}n{user_message}” # Make a request to the Sttabot API sttabot_url = “https://api.sttabot.io/json/Sttabot/v1/InitiateNewQuery” headers = { “Content-Type”: “application/json”, “Authorization”: f”Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOjU3OTMsIm5hbWUiOiJoZWxsb2RlbW9AZGVtby5jb20iLCJpYXQiOjE2OTYyMjYyMDIsImV4cCI6MTg1MzkwNjIwMn0.khP3o3khrjzEMoIBtCHikUkAlpgF9rIADQK9t26SpaI” } payload = { “prompt”: prompt, “botId”: “default”, “clientId”: “1” } response = requests.post(sttabot_url, headers=headers, data=json.dumps(payload)) if response.status_code == 200: try: data = response.json() success = data.get(“success”, False) bot_response = data.get(“data”, “Sorry, I couldn’t get a response from Sttabot.”) if success: bot.send_message(message.chat.id, bot_response) else: bot.send_message(message.chat.id, “Sttabot API returned an error.”) except Exception as e: print(f”Error parsing Sttabot response: {str(e)}”) bot.send_message(message.chat.id, “Sorry, there was an error processing your request.”) else: print(f”Sttabot API Error – Status Code: {response.status_code}”) bot.send_message(message.chat.id, “Sorry, there was an error processing your request with Sttabot API.”) # Start the bot bot.polling()