LLM call to be completed

• **Longer LLMs with Multiple call (chunking algortihm)
• **Overlapping chunks to ensure lossless transformations
• **Flask API and with HTML5 javasctip FRONT-END (templates/indext.html)
• **Interaction: Selection- Highlights Transribed Orginal Text from corresponding user FORM with mouse selection
• **Finds medical entities
• **Ingects medication to all calls to achieves a more accurate results.

Getting Started

How to Run

Before anything, run the bash keyyer.sh copy the Bearer Token and pased it at the beging og the app.py

Run:

http://192.168.0.104:8099/setup_n_generate_text

Set enviromnet:

use >this Envroment UIFORM

Crealte images and run container

Use >docker build -t my-flask-app . and >docker run -p 8090:8090 my-flask-app

To do:

Features

• Ehsan: Generate Text from Audio

  • This feature automatically converts audio input to text and connects it to a DOM element with the tag id user_input.

• Adding Medical Condition Entity Recognition

  • Implements entity recognition to identify and categorize medical conditions mentioned within the text.

• Developing UI Elements to Fit User (Clinician Needs)

  • Custom UI components designed specifically for clinician use, enhancing usability and accessibility.

• Interaction Design for Iterative Inferencing

  • A user interface design that supports iterative inferencing, allowing users to refine inputs and outputs through interaction.

• Ontology/Reasoner Options

  • Integration of ontology/reasoner tools to support advanced data interpretation and decision-making processes.
  • View Code