my-ai-cv

Overview

my-ai-cv is a project implementing a Retrieve Augmented Generation pipeline using a quantized tiny LLM with GGUF, designed to work across any device. This enables the use of the model without directly pushing it to the repository, as it is available within the container.

An Hugging Face Space version 🤗 is available here.

Getting Started

Prerequisites

Before running the project, ensure you have Docker installed on your machine. If you do not have Docker, you can install it from Docker's official site.

Running the Project

There are two main ways to launch the chat interface:

Option 1: Using Docker

Run the following command to pull the image from the registry and start the service:

docker run -p 7860:7860 -d ghcr.io/ilanaliouchouche/my-cv

The model currently in the container is: microsoft/Phi-3-mini-4k-instruct-gguf

Option 2: Cloning and Running Locally

1. Clone the repository and install dependencies:

   git clone https://github.com/ilanaliouchouche/my-ai-cv.git
   cd my-ai-cv/assistant
   pip install -r requirements.txt

2. Ensure the assistant/models directory is created and populated as the model files are not pushed to the repository due to their size. Place the model files inside this directory.

3. Modify the .env file to match the model configurations, specifically the LLM_PATH should point to the model file within the assistant/models directory.

4. Run the application:

   python app.py

Configuration & Customization

Section	Description
Model	The project uses the microsoft/Phi-3-mini-4k-instruct-gguf model, specified in the .env file.
LLM_PATH	It is crucial to adjust the LLM_PATH variable in the .env file to point to the correct model file in the assistant/models directory.
Template	Inside assistant/ChatbotModel, it is strongly recommended to update the static TEMPLATE variable with instructions tailored to the model used.
Chroma	Replace the content of assistant/chromadb with your own vector database containing the information you want to share.

Customization

If you wish to adapt the project for your personal CV, please FORK the repo. You must ensure the LLM_PATH is correctly set in your .env file and update the ChatbotModel class as necessary to align with your model's specifications.