Verified Template

OpenAI GPT-4o Reminders WhatsApp bot

Test this app for free
2267
from typing import List
from db_utils import get_db_connection
from encryption_utils import decrypt
from db_utils import check_first_communication, insert_first_communication, insert_reminder, retrieve_reminders, delete_reminder, retrieve_all_reminders, update_timezone, retrieve_timezone, set_next_reminder_time
from time import sleep
import threading
from encryption_utils import encrypt
from timezone_finder import convert_timezone
from abilities import llm_prompt
from datetime import datetime, timedelta
from nlp_processing import process_reminder_input, process_timezone, process_action
from abilities import key_value_storage
import logging
import calendar
import requests
import json
import os
from twilio.twiml.messaging_response import MessagingResponse
from twilio.rest import Client
from flask import Flask, render_template, request
from gunicorn.app.base import BaseApplication
import random
import sqlite3
Get full code

Frequently Asked Questions

How can businesses benefit from using the GPT-4o Reminders WhatsApp bot?

The GPT-4o Reminders WhatsApp bot offers several benefits for businesses: - Improved customer engagement through a familiar platform (WhatsApp) - Automated reminder system that reduces missed appointments or deadlines - Natural language processing capabilities that make it easy for customers to set reminders - Customizable reminders for various business needs (e.g., appointment reminders, payment due dates, follow-ups) - Potential for increased customer satisfaction and loyalty through timely, personalized reminders

What are some potential applications of the GPT-4o Reminders WhatsApp bot across different industries?

The GPT-4o Reminders WhatsApp bot can be applied in various industries: - Healthcare: Appointment reminders, medication schedules - Finance: Bill payment reminders, investment deadlines - Education: Assignment due dates, exam schedules - Retail: Sale notifications, order status updates - Hospitality: Reservation reminders, check-in/check-out times - Personal services: Haircut appointments, gym class schedules The bot's flexibility allows it to be adapted to many different use cases across industries.

How does the GPT-4o Reminders WhatsApp bot handle data privacy and security?

The GPT-4o Reminders WhatsApp bot takes several measures to ensure data privacy and security: - Encryption: User data is encrypted using AES encryption before being stored in the database - Secure communication: The bot uses Twilio's secure WhatsApp Business API for messaging - Limited data storage: Only necessary information is stored (phone numbers, reminders, timezones) - Environment variables: Sensitive information like API keys are stored as environment variables - HTTPS: The web application uses HTTPS for secure communication These measures help protect user data and comply with privacy regulations.

How can I customize the reminder processing in the GPT-4o Reminders WhatsApp bot?

You can customize the reminder processing by modifying the process_reminder_input function in the nlp_processing.py file. Here's an example of how you might add custom logic for specific types of reminders:

```python def process_reminder_input(input_text, phoneNumber, timezone): current_datetime = datetime.now().strftime("%Y-%m-%d %H:%M") prompt = f"Given the current datetime {current_datetime}, create a list of reminders from: '{input_text}'. "

   # Add custom logic for specific reminder types
   if "birthday" in input_text.lower():
       prompt += "For birthdays, always set recurrent to True and recurrence_type to 'yearly'. "
   elif "weekly meeting" in input_text.lower():
       prompt += "For weekly meetings, set recurrent to True and recurrence_type to 'weekly'. "

   # Rest of the function remains the same
   response = client.chat.completions.create(
       model="gpt-4o",
       messages=[
           {"role": "user", "content": prompt},
       ],
       response_model=ReminderList,
   )
   return response

```

This customization allows the GPT-4o Reminders WhatsApp bot to handle specific types of reminders in a predefined way.

How can I extend the GPT-4o Reminders WhatsApp bot to support multiple languages?

To support multiple languages in the GPT-4o Reminders WhatsApp bot, you can modify the process_action function in nlp_processing.py. Here's an example of how you might implement this:

```python def process_action(input_text): prompt = f'''Based on the following user message in any language: "{input_text}", determine if the user wants to set a timezone/location, create a reminder, list reminders, or stop a reminder. Respond in the following JSON format: {{"action": "configure_timezone"}}, {{"action": "create"}}, {{"action": "list"}}, or {{"action": "stop"}}. If no action fits, use {{"action":"info"}}. Detect the language and include it in the response as "detected_language".'''

   response = client.chat.completions.create(
       model="gpt-4o",
       messages=[
           {"role": "user", "content": prompt},
       ],
       response_model=UserActionWithLanguage,
   )
   return response

```

You would also need to create a new UserActionWithLanguage model in reminder_structure.py:

```python class UserActionWithLanguage(BaseModel): action: str detected_language: str

   @validator('action')
   def validate_action(cls, v):
       valid_actions = ["configure_timezone", "create", "list", "stop", "info"]
       if v not in valid_actions:
           raise ValueError(f"Invalid action. Must be one of: {', '.join(valid_actions)}")
       return v

```

This modification allows the GPT-4o Reminders WhatsApp bot to detect the language of the input and potentially respond in the same language, making it more accessible to users worldwide.

Created: | Last Updated:

This bot uses GPT-4o to give Whatsapp-based reminders to people just by chatting. In the encryption key environment secret, you need to get a 128 bit AES hex key from a website such as https://asecuritysite.com/encryption/plain

Introduction to the GPT-4o Reminders WhatsApp Bot Template

The GPT-4o Reminders WhatsApp Bot is an innovative template that allows builders to create a WhatsApp bot capable of setting and managing reminders through chat. This bot leverages the power of GPT-4o to understand natural language inputs, making it easy for users to interact with and set reminders just by sending a message. Whether it's a one-time reminder or a recurring notification, this bot can handle it all seamlessly.

Getting Started with the Template

To begin building your own WhatsApp reminder bot, click
on the Lazy platform. This will pre-populate the code in the Lazy Builder interface, so you won't need to copy or paste any code manually.

Initial Setup: Adding Environment Secrets

Before testing your bot, you'll need to set up some environment secrets within the Lazy Builder. These are crucial for the bot to interact with the Twilio API and to encrypt sensitive data.

Remember, these credentials are sensitive and should be kept secure.

Test: Deploying the App

Once you've set up the necessary environment secrets, you can deploy your app by clicking the
button. This will launch the Lazy CLI, and the deployment process will begin.

Entering Input: Providing User Input

If the bot requires any user input, the Lazy CLI will prompt you to provide it after pressing the
button. Follow the instructions in the CLI to enter the necessary information.

Using the App

After deployment, the Lazy platform will provide you with a dedicated server link. This link is where you can interact with your WhatsApp bot. Send a message to your WhatsApp number connected with Twilio, and the bot will respond accordingly, allowing you to set and manage reminders.

Integrating the App

To integrate the WhatsApp bot into your service, you may need to add the server link provided by Lazy to your Twilio WhatsApp sandbox or configure it in your Twilio settings. Follow these steps to complete the integration:

This will ensure that when users send a message to your WhatsApp number, Twilio will forward the message to your bot, and the bot will handle the reminders accordingly.

Sample API Request and Response

If you wish to interact with the bot's API directly, you can use the server link to send HTTP POST requests. Here's a sample request to set a reminder:

POST /wa HTTP/1.1 Host: [Your Server Link] Content-Type: application/x-www-form-urlencoded Body: From=whatsapp%3A%2B[YourPhoneNumber]&Body=Remind+me+to+call+John+tomorrow+at+9+AM

A successful response from the bot will confirm that the reminder has been set.

For further guidance and documentation on the Twilio API, you can refer to the official
.

By following these steps, you can create a fully functional WhatsApp reminder bot that helps users manage their tasks efficiently. Enjoy building with Lazy!



Here are the top 5 business benefits or applications of this GPT-4o Reminders WhatsApp bot template:

Template Benefits

  1. Enhanced Customer Engagement: This WhatsApp bot provides a convenient and familiar platform for users to set reminders, improving customer engagement and satisfaction.

  2. Increased Productivity: By automating the reminder process, businesses can help their clients or employees stay on top of important tasks and deadlines, boosting overall productivity.

  3. Scalable Customer Service: The bot can handle multiple users simultaneously, providing 24/7 reminder services without the need for human intervention, thus reducing operational costs.

  4. Personalized User Experience: Leveraging GPT-4o's natural language processing capabilities, the bot can understand and respond to user requests in a more human-like manner, creating a personalized experience.

  5. Data-Driven Insights: By analyzing the types of reminders set and user interactions, businesses can gain valuable insights into customer behavior and preferences, informing future product or service improvements.

Technologies

Maximize OpenAI Potential with Lazy AI: Automate Integrations, Enhance Customer Support and More  Maximize OpenAI Potential with Lazy AI: Automate Integrations, Enhance Customer Support and More
Streamline WhatsApp Workflows with Lazy AI: Automate Messaging, Notifications, API Integrations and More Streamline WhatsApp Workflows with Lazy AI: Automate Messaging, Notifications, API Integrations and More

Similar templates

FastAPI endpoint for Text Classification using OpenAI GPT 4

This API will classify incoming text items into categories using the Open AI's GPT 4 model. If the model is unsure about the category of a text item, it will respond with an empty string. The categories are parameters that the API endpoint accepts. The GPT 4 model will classify the items on its own with a prompt like this: "Classify the following item {item} into one of these categories {categories}". There is no maximum number of categories a text item can belong to in the multiple categories classification. The API will use the llm_prompt ability to ask the LLM to classify the item and respond with the category. The API will take the LLM's response as is and will not handle situations where the model identifies multiple categories for a text item in the single category classification. If the model is unsure about the category of a text item in the multiple categories classification, it will respond with an empty string for that item. The API will use Python's concurrent.futures module to parallelize the classification of text items. The API will handle timeouts and exceptions by leaving the items unclassified. The API will parse the LLM's response for the multiple categories classification and match it to the list of categories provided in the API parameters. The API will convert the LLM's response and the categories to lowercase before matching them. The API will split the LLM's response on both ':' and ',' to remove the "Category" word from the response. The temperature of the GPT model is set to a minimal value to make the output more deterministic. The API will return all matching categories for a text item in the multiple categories classification. The API will strip any leading or trailing whitespace from the categories in the LLM's response before matching them to the list of categories provided in the API parameters. The API will accept lists as answers from the LLM. If the LLM responds with a string that's formatted like a list, the API will parse it and match it to the list of categories provided in the API parameters.

Icon 1 Icon 1
218

We found some blogs you might like...