ConsumeWise - Gen AI Product Information
"ConsumeWise: Harnessing AI for Smarter, Healthier, and More Sustainable Consumer Choices."
Created on 25th September 2024
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ConsumeWise - Gen AI Product Information
"ConsumeWise: Harnessing AI for Smarter, Healthier, and More Sustainable Consumer Choices."
Describe your project
- In-Scope Features:
AI-Generated Product Descriptions:
The app leverages the Groq API to create customized descriptions for various products based on user input, enhancing the shopping experience with rich information.
State-Wise Consumption Analysis:
ConsumeWise analyzes consumption data for a range of products like almonds, apples, and avocados from a static dataset (foodStates.csv). This feature allows users to understand regional preferences and trends in product consumption.
Interactive Data Visualizations:
The application provides visually appealing representations of consumption data, including pie charts and bar graphs, making it easier for users to digest and compare information.
Chatbot Interaction:
An interactive AI chatbot is integrated to respond to user inquiries about products, offering quick, AI-generated answers that enhance user engagement.
Product Comparison Tool:
Users can compare two products side by side, generating relevant visualizations and AI descriptions for each item to help them make informed choices.
- Out of Scope:
Real-Time Data Updates:
The application does not support live tracking or real-time updates of consumption data; it relies on a static dataset for analysis.
Advanced Predictive Analytics:
While the app offers basic analysis, it does not include advanced statistical methods or machine learning algorithms for predicting future consumption trends.
Mobile Optimization:
Currently, the platform is designed exclusively for desktop use, lacking mobile-friendly features or responsive design.
User Authentication Features:
The app does not support user accounts or personalized settings beyond basic product queries, limiting customization.
Integration with External APIs:
There are no integrations with additional data sources or third-party APIs
Challenges I ran into
Integrating the Groq API:
One of the most significant challenges was integrating the Groq API to generate AI-powered product descriptions. Initially, the responses were inconsistent, with issues related to token limits and incomplete responses. I tackled this by optimizing token usage and refining the prompts to ensure the model generated more accurate and relevant information. Debugging and improving the error handling allowed for more robust and reliable responses from the AI.
Creating My Own Dataset:
Another challenge involved building a custom dataset for product insights, as existing datasets didn't cover the specific products or details I needed. Manually compiling the foodStates.csv file to represent product consumption across various states required careful data gathering and validation. The process was time-consuming, but it allowed for a more tailored dataset that provided relevant insights for the application. This custom approach ensured that the visualizations and AI descriptions accurately reflected real-world data.
Tracks Applied (1)