Multi Agent based Medical Assistant for Edge Devices
Authors: name: Sakharam Gawade, name: Shivam Akhouri, name: Chinmay Kulkarni, name: Jagdish Samant, name: Pragya Sahu, name: Aastik, name: Jai Pahal, name: Saswat Meher

Large Action Models (LAMs) have revolutionized intelligent automation, but
their application in healthcare faces challenges due to privacy concerns,
latency, and dependency on internet access. This report introduces an ondevice,
multi-agent healthcare assistant that overcomes these limitations. The system
utilizes smaller, task-specific agents to optimize resources, ensure
scalability and high performance. Our proposed system acts as a one-stop
solution for health care needs with features like appointment booking, health
monitoring, medication reminders, and daily health reporting. Powered by the
Qwen Code Instruct 2.5 7B model, the Planner and Caller Agents achieve an
average RougeL score of 85.5 for planning and 96.5 for calling for our tasks
while being lightweight for on-device deployment. This innovative approach
combines the benefits of ondevice systems with multi-agent architectures,
paving the way for user-centric healthcare solutions.