Interactive Resume with Streamlit and Ollama

Overview

This project aims to create an interactive resume using Streamlit, a Python library for building web applications, and Ollama, a language model for conversational AI. The interactive resume allows users to engage in a conversation with an AI assistant to learn more about a person's qualifications, experience, and other relevant information typically found in a resume.

Features

• Streamlit Interface: Utilizes Streamlit to create a user-friendly interface for interaction.
• Ollama Integration: Incorporates Ollama, a language model, to generate conversational responses.
• Chat-Based Interaction: Enables users to ask questions and receive responses in a conversational format.
• Clear and Informative: Provides relevant links and information about the person whose resume is being presented.

Installation

Docker

Requirements:

1. Bash to set up variables
2. Python for setup script
3. Docker ;)

Instructions:

git clone https://github.com/serghidalg/interactive-resume && cd interactive-resume && python setup_variables.py

Run it:

With docker:

docker build -t interactive-resume .
docker run -d -p 8501:8501 interactive-resume

Linux

Requirements:

1. Python library accessible from terminal
2. Python venv
3. Python pip

Instructions:

git clone https://github.com/serghidalg/interactive-resume && cd interactive-resume && bash install.sh

Run it:

source venv/bin/activate
streamlit run main.py

Web access

Now everything should be accessible from 0.0.0.0:8501 on your web browser :D

Note: There is a streamlit_cv.service file which can be useful to some people in the files folder.

Usage

• Upon launching the application, you'll see a sidebar with relevant links and the conversation area.
• Users can input questions or prompts in the chat input area.
• The AI assistant (powered by Ollama) will respond to user queries, creating an interactive conversation.

Customization Guide:

Please note that certain sections of this project might need customization to suit individual preferences or information. Here are the sections you might want to review and potentially modify:

1. Install Ollama server: This project relies on you having a working ollama server working.

2. ollama_handler.py: Points to a specific IP for your Ollama server and model name. A second IP can be set as fallback. It also sets some rules for the assistant to follow.

3. session_logic.py: Contains specific information about the first prompt that the streamlit will show.

4. ui.py: Holds my personal info so the interviewers can know more about my work.