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# LLM Bill Chat App | |
This project is a proof of concept for a chat application utilizing a Large Language Model (LLM) to assist users with their telecom billing inquiries. The application is built using Python and Streamlit, providing an interactive web interface for users to engage with. | |
## Features | |
- Maintain chat conversation context (history) | |
- Allow users to query their billing information | |
- Compare the last bills and provide insights | |
- Respond exclusively with the user's own billing information | |
- Augment the prompt instructions with user's text recognized entities - NER -> Dynamic prompting# Aplicaศia LLM Bill Chat | |
## Project Structure | |
hf-llm-bill-chat/ | |
โ | |
โโโ app.py | |
โโโ pages/ | |
โ โโโ One_model.py | |
โ โโโ Two_models.py | |
โ | |
โโโ data/ | |
โ โโโ user_data/ | |
โ โโโ user_data_724077190.json | |
โโโ logs/ | |
โโโ conversation_logs.json | |
## Code Implementation - Main Script | |
- Initialize Streamlit app | |
- Load user data and display existing bills | |
- Handle file uploads for new bills | |
- Maintain chat conversation context | |
- Leverage user text entities recognition (NER) for dynamic prompting | |
- Call OpenAI models (GPT-4o and GPT-4o-mini) for responses | |
- Display responses in two parallel columns | |
- Log conversation details | |
## Future Improvements | |
- Enhance Natural Language Processing (NLP) capabilities for better entity recognition | |
- Implement user authentication for secure access to billing information | |
- Add support for more telecom providers and bill formats | |
- Improve the user interface for better user experience | |
- Integrate with payment gateways for bill payments | |
## Conclusion | |
- The LLM Bill Chat App demonstrates the potential of using Large Language Models for telecom billing assistance. | |
- The app provides a user-friendly interface for querying billing information and getting insights. | |
- Future improvements can enhance the app's capabilities and user experience. | |