• Jansirani S
• Kurapati Pavankumar
• Mannargudi Sidduvinay
• Bora Mohan Rao, Mekala Bharath
• Saravanan M

In an era where quick access to health information is essential, AI-driven solutions like medical chatbots can bridge the gap by providing preliminary insights based on user symptoms. Our AI-powered medical chatbot utilizes LlaMA 3.3 70B for conversational interactions and LlaMA 3.2 Vision for medical image analysis, integrating advanced NLP techniques with Hugging Face Transformers for efficient text processing and BERT for summarizing medical information. To enhance accessibility, Google’s Deep Translator enables multilingual support, while Google Speech-to-Text API and gTTS allow seamless voice-based interaction. Additionally, the chatbot processes medical reports using ReportLab, extracting key information from PDFs for better analysis. A Scikit-learn-based recommendation system personalizes health tips based on user inputs, offering data-driven insights. The user-friendly interface, built with Streamlit, HTML, and CSS, ensures an interactive experience, making AI-powered health assistance more accessible to a wider audience.

LlaMA 3.3 70B, LlaMA 3.2 Vision, Hugging Face Transformers, BERT, Google Deep Translator, Google Speech-to-Text API, gTTS, ReportLab, Scikit-learn, Streamlit, HTML, CSS.

"AI-POWERED MEDICAL CHATBOT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.d12-d17, March-2025, Available :http://www.jetir.org/papers/JETIR2503303.pdf

"AI-POWERED MEDICAL CHATBOT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppd12-d17, March-2025, Available at : http://www.jetir.org/papers/JETIR2503303.pdf