Leverage TruLens with MongoDB & LlamaIndex for Customer Care

Building a Query and Feedback System for Customer Care with Modern Tech Stack

Hello everyone! I'm Sanchay Thalnerkar, an engineering student passionate about creating in-depth and engaging tutorials. In this article, we’ll build a Query and Feedback System for Customer Care to help businesses manage customer queries and feedback efficiently, ensuring a smoother and more responsive customer service experience. We will leverage a modern tech stack that includes TruLens, LlamaIndex, and MongoDB Atlas. Let’s dive into each component and their integration in our project.

1. Understanding the Tech Stack

1.1 TruLens

TruLens is a model interpretability library designed to provide insights into machine learning models. In this project, TruLens will help analyze how our model processes queries and feedback, thereby improving the decision-making process.

1.2 LlamaIndex

LlamaIndex is a high-performance vector search engine crucial for efficiently searching through large volumes of data based on vector similarities. For our customer care system, it enables quick response and query handling for customer relations.

1.3 MongoDB Atlas

MongoDB Atlas is a fully-managed cloud database that offers scalable storage solutions for modern applications. We will use it to store and manage customer queries and feedback, ensuring data accessibility and security.

2. Setting Up the Project

Before we get into coding, it’s essential to set up our project directory. This will provide a structured foundation for our application.

2.1 Creating the Project Directory

1. Open your terminal or command prompt.
2. Change your directory to the preferred location.
3. Create a new directory by entering: mkdir CustomerCareSystem
4. Navigate into your new directory using: cd CustomerCareSystem

2.2 Creating Project Files

We’ll focus on modularization and integrating TruLens into our feedback manager. A modular approach helps maintain, scale, and collaborate efficiently.

Key Files and Their Responsibilities:

• config.py: Central repository for configuration settings.
• query_manager.py: Handles all query-related operations.
• feedback_manager.py: Manages user feedback and integrates TruLens.
• setup.py: Manages dependencies and application packaging.
• data_manager.py: Interacts with MongoDB Atlas.
• Ecommerce_FAQ_Chatbot_dataset.json: Initial dataset for training.

3. Integrating TrueLens and Setting Up Environment

The FeedbackManager will utilize TruLens for analyzing response influences. Integration includes initialization, analysis based on feedback, and reporting.

3.1 Setting Up Virtual Environment and Dependencies

Setting up a virtual environment ensures isolation of project dependencies:

1. Navigate to the project directory.
2. Create a virtual environment using: python -m venv venv
3. Activate the virtual environment.
4. Install necessary libraries for the project.

3.2 Configuring the Application

Create a .env file to store sensitive information like API keys:

• Your OpenAI API keys can be stored here for secure access.
• Never share or expose the .env file publicly since it contains sensitive data.

4. Setting Up MongoDB Atlas

MongoDB Atlas will be our database service. Follow these steps to set it up:

1. Create or sign in to MongoDB Atlas.
2. Deploy a new cluster and ensure IP whitelisting for access.
3. Retrieve the MongoDB URI for connection.

5. Building the Application in app.py

The app.py script will facilitate user interactions with the system. It leverages the Streamlit library for a frontend interface.

• Streamlit initializes web application and takes user inputs.
• QueryManager and FeedbackManager work in sync to handle interactions.
• Utilizes TRU Dashboard for real-time performance insights.

6. Running the Application

To run your Streamlit application, use the command:

streamlit run app.py

Access your application at http://localhost:8501 in a web browser.

7. Key Features of the System

In wrapping up, let's reflect on the capabilities demonstrated by the Query and Feedback System:

• System initialization and configuration.
• Easy query submission interface.
• Effective response analysis using TruLens.
• Dashboard management features for real-time monitoring.
• Performance and evaluation record keeping for ongoing improvements.

Check your code resources and documentation on GitHub to expand or customize this system further. The technological adventure begins here, and you're well on your way to transforming your customer care into a bastion of efficiency and satisfaction!