Skip to content

Latest commit

 

History

History
57 lines (30 loc) · 1.66 KB

readme.md

File metadata and controls

57 lines (30 loc) · 1.66 KB
Raw

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