Food Commerce GPT
The Food Commerce GPT project centers around creating a chatbot that simulates human-like interaction for businesses in the food industry, particularly through the WhatsApp platform. This chatbot uses the GPT model developed by OpenAI and was crafted as part of the content for Dev Samurai's Master Class #013.
How Does It Work?
The chatbot utilizes OpenAI's GPT model to autonomously generate answers to user inquiries, mimicking human customer service interactions. This service is delivered via WhatsApp using the Venom library, which handles the connection and message exchange. To ensure the bot adheres to intended conversation flows, a predefined prompt is used, which can be customized for different businesses or niches, such as medical clinics, by modifying a specific file in the project.
A visual demonstration of how the bot operates can be found in the demo section of the project documentation.
Running the Bot
To get started with Food Commerce GPT, several key installations and configurations are required:
- Essentials: Ensure you have Node.js and Docker installed on your machine, and you'll need an active WhatsApp account.
- APIs: Sign up for an account with OpenAI and obtain an API Key.
- Environment Setup: Create a
.envfile in the project root and include necessary configurations like your OpenAI API Key and Redis connection settings.
OPENAI_API_KEY=your_openai_api_key
REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_DB=0
- Dependencies Installation: Once the environment is set up, install all project dependencies using npm.
npm install
- Start the Bot: With everything configured, you can start the bot using:
npm run dev
To interact with the bot, scan the QR code generated in the terminal with your WhatsApp application. Note that using an unauthorized API may lead to number bans, testing should be done with disposable numbers as a precaution.
Step-by-Step Implementation
The project follows several structured steps to create a robust backend:
Step 1: Node.js Backend with TypeScript
This initial setup creates the backend infrastructure using Node.js with TypeScript, ensuring that the application is both scalable and error-free.
Step 2: Venom Library Integration
With the backend ready, the Venom library is installed to create a client capable of interacting with WhatsApp, allowing for real-time message handling.
Step 3: OpenAI Integration
Next, the project integrates the OpenAI library, enabling the chatbot to generate human-like responses using predefined prompts.
Step 4: Developing the Bot's Script
A coherent script is crucial for meaningful interaction, ensuring the bot can handle various conversation paths effectively.
Step 5: User State Management
Utilizing Redis, the bot stores user states, allowing it to maintain context and carry forward ongoing interactions seamlessly.
Step 6: Order Processing
Finally, the bot completes the order process and saves this information, providing a full service cycle from inquiry to order confirmation.
Conclusion
The Food Commerce GPT project provides a detailed guide and a functional template for businesses looking to implement AI-driven customer service solutions in the food industry. Its modular and customizable approach means it's adaptable to a wide range of business needs, making it a powerful tool in modern commerce.