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

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πŸ“œ 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!

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πŸš€ 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.

πŸ› οΈ 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

πŸ“š 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.

πŸ“ 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.

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

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