Julien's GPT4ALL Interface

Overview

This project integrates embeddings with an open-source Large Language Model (LLM) to answer questions about Julien GODFROY. It uses the langchain library in Python to handle embeddings and querying against a set of documents (e.g., CV of Julien GODFROY). The project includes a Streamlit web interface for easy interaction.

Screenshots

Features

• Query processing using langchain library.
• Integration with GPT4All for answering questions.
• Streamlit interface for user interaction.
• Specialized in answering queries related to Julien GODFROY's professional profile.

Installation

Before running the application, ensure that you have Python installed on your system, and that you're machine is powerfull enough to handle the LLM (at least 16GB RAM, a very good CPU). Then, follow these steps:

1. Clone the repository:

   git clone https://github.com/jugodfroy/GPT4ALL-langchain-embeddings.git

2. Navigate to the cloned repository:

   cd GPT4ALL-langchain-embeddings

3. Install required dependencies:

   pip install -r requirements.txt

4. Download the model mistral-7b-openorca.Q4_0.gguf (or equivalent) and store it in a models directory: Download model

Usage

To start the application, run the following command in the terminal:

streamlit run main.py

This will open the Streamlit interface in your default web browser. Here, you can type your questions about Julien GODFROY in the provided text area and submit them to receive answers.

References

• LangChain
• Streamlit
• FAISS