Getting Started

🐸 FrogBase lets you create & navigate knowledge from multi-media content.

from frogbase import FrogBase

fb = FrogBase()

sources = [
   "https://www.youtube.com/watch?v=HBxn56l9WcU",
   "https://www.youtube.com/@hayabhay"
]

fb.add(sources)

fb.search("squeaky frog")

Find FrogBase on Discord

Features

FrogBase currently provides functionality to:

• Download media files from a wide range of platforms (YouTube, TikTok, Vimeo, etc.) using yt_dlp
• Transcribe audio streams for downloaded & local files using OpenAI's Whisper
• Embed transcribed text from corresponding video segments using Sentence Transformers
• Index & search the embedded content using hnswlib

FrogBase also includes a Streamlit UI to provide a simple GUI for the above functionality enabling a locally hosted, interactive experience.

Non-technical Users

This section is for non-technical users who want to use FrogBase primarily through the accompanying Streamlit UI.

1. Download the latest release of FrogBase from here and unzip it. Or, you can also clone the repository console git clone https://github.com/hayabhay/frogbase.git

2. Install FrogBase dependencies manually and run the UI.

Note: This also requires ffmpeg to be installed on your system. You can install it using sudo apt install ffmpeg on Ubuntu.

1. Using pip

   pip install frogbase streamlit
   streamlit run ui/01_🏠_Home.py
   

[Coming soon] Instructions, environment for installation using Docker & Anaconda