LLM-Resume-Analyser-using-Unify

Demo

Streamlit App: https://ai-llm-resume-analyser.streamlit.app

LLM RESUME ANALYSER is an application that allows you to improve your CV using many Language Model analysis and suggestions

Tech Stack

Streamlit: Used for creating the web application interface that is intuitive and interactive.

Unify AI: Provides the backend LLMs that power the interactions within the application. Unify's API is utilized to send prompts to the LLMs and receive their responses in real-time.

Langchain: LangChain is a powerful framework designed for building applications that integrate with large language models (LLMs), enabling complex interactions and workflows by chaining together various components like prompts, LLMs, and data sources

Introduction

You find more model/provider information in the Unify benchmark interface.

Usage:

1. Visit the application: LLM Resume Analyser
2. Input your Unify API Key. If you don’t have one yet, log in to the Unify Console to get yours.
3. Select the model and provider of your choice
4. Upload your document(s) and click the Submit button
5. Enter your job description and job title
6. Gain insights on Resume match with the job offer and on how to improve your Resume

Repository and Deployment

The repository link: (https://github.com/OscarArroyoVega/LLM_Resume_Analyser_Unify) or (https://github.com/Sanjay8602/LLM-Resume-Analyser-using-Unify). To run the application locally, follow these steps:

1. Clone the repository to your local machine.

   git clone https://github.com/Sanjay8602/LLM-Resume-Analyser-using-Unify

2. Set up your virtual environment and install the dependencies from requirements.txt:

   python -m venv .venv    # create virtual environment 

   source .venv/bin/activate   # on Windows use .venv\Scripts\activate.bat

   pip install -r requirements.txt

3. Run app.py from Streamlit module

python -m streamlit run analyser.py

Contributors