mhijazi16/briefly

📜 Briefly utilizes open-source LLM's with text embeddings and vectorstores to chat with your documents

📜 Briefly

Briefly is an innovative application that allows you to chat with your documents using open-source Large Language Models (LLMs). Upload your PDFs, ask questions, and receive relevant answers in no time!

🚀 Features

• Interactive Chat: Engage in a conversation with your documents.
• Easy Upload: Upload multiple PDF files effortlessly.
• Efficient Processing: Fast and accurate document processing.
• Open-Source LLMs: Powered by open-source language models.

🛠️ Installation

To get started with Briefly, follow these steps:

make sure Ollama and llama3 is installed

1. Clone the repository:

   git clone https://github.com/Mhijazi16/Briefly.git
   cd Briefly

2. Install the required dependencies:

   pip install -r requirements.txt

3. Run the application:

   streamlit run Briefly.py

📚 Usage

1. Upload Documents: Use the sidebar to upload your PDF documents.
2. Ask Questions: Enter your questions in the text input field.
3. Get Answers: Receive relevant answers extracted from your documents.

📝 Code Overview

Here's a brief overview of the main components of the code:

• Document Reading: Uses PyPDF2 to read and extract text from PDF documents.
• Text Splitting: Utilizes RecursiveCharacterTextSplitter from Langchain to split text into manageable chunks.
• Embedding and Retrieval: Implements OllamaEmbeddingWrapper to embed documents and FAISS for efficient retrieval.
• Interactive Interface: Built with Streamlit to provide a user-friendly interface.