Job Title: AI RAG Chatbot implementation
Job Description:
We propose enhancing the functionality of our existing AI chatbot, which is currently implemented within our healthcare portal. While the chatbot performs basic tasks, it requires significant improvement to become more interactive, deliver personalized responses, and provide accurate and up-to-date information from all existing internal and external data sources.
At present, the chatbot operates primarily using Selenium, FastAPI, Retrieval-Augmented Generation (RAG), Groq LLM, and ChromaDB. However, it relies exclusively on website content as its data source, which limits its ability to deliver precise and contextually relevant responses.
To address this, we suggest expanding the chatbot’s capabilities to process and integrate data from multiple sources, including:
Website content: Utilizing existing site information for general interactions.
Two databases: PostgreSQL and MySQL containing critical information.
Email content: Incorporating relevant details from email data to provide more comprehensive responses.
By integrating these additional data sources, the chatbot will be better equipped to process user queries, extract meaningful insights, and deliver comprehensive and personalized interactions. Our goal is to transform the chatbot into a robust, intelligent solution capable of meeting user needs with increased precision and contextual relevance, while leveraging the latest advancements in AI and natural language processing.
This enhancement initiative will ensure the chatbot remains a comprehensive and reliable tool for users, significantly improving the overall user experience on the healthcare portal. |
