AI Complaint Analyzer

Getting Started

This is a complaint analyzer using AI summarization and categorization. Currently storing data to firestore database.
Future Improvements include editing the complaint status, include RAG pipeline etc.

Demo Img

Home Screen

Analysis of the text message if it is a complaint!

Not a complaint!

Features

1. Use Llama Model and OpenRouter API for config.
2. Firebase Firestore Database for data storage.

Dependencies

1. openai
2. firebase
3. mui
4. uuid
5. roboto font from mui

FootNote:

• Backend: A Ruby on Rails server that handles API requests, processes consumer complaints, and interfaces with the AI model.
• Database: PostgreSQL to store complaint data and category tags, with a separate vector database for RAG pipeline.
• AI Integration: Use an LLM API to categorize complaints and generate summaries.
• RAG Pipeline: Implement a pipeline that stores complaint vectors in a vector database, enabling quick retrieval of related complaints.
• Deployment: Basic setup with a focus on AI functionality, ensuring the system can handle increased data loads for more complex use cases.