Create navigable knowledge from multi-media content
FrogBase (previously whisper-ui) simplifies the download-transcribe-embed-index
workflow for multi-media content.
It does so by linking content from various platforms
(yt_dlp)
with speech-to-text models (OpenAI's Whisper),
image & text encoders (SentenceTransformers),
and embedding stores (hnswlib).
from frogbase import FrogBase
fb = FrogBase()
fb.demo()
fb.search("What is the name of the squeaky frog?")
Full Documentation (WIP).
FrogBase also comes with a ready-to-use UI for non-technical users!
whisper-ui-update-demo.mp4
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.
This section is for software developers who want to use FrogBase as a python package.
-
Install
ffmpeg
and FrogBasesudo apt install ffmpeg pip install frogbase
-
Import FrogBase and use it as follows -
from frogbase import FrogBase fb = FrogBase() sources = [ "https://www.youtube.com/watch?v=HBxn56l9WcU", "https://www.youtube.com/@hayabhay" ] fb.add(sources)\ .transcribe()\ .embed()\ .index() fb.search("What is the name of the squeaky frog?")
This section is for non-technical users who want to use FrogBase primarily through the accompanying Streamlit UI.
-
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
-
Install FrogBase dependencies manually and run the UI.
Note: This also requires
ffmpeg
to be installed on your system. You can install it usingsudo apt install ffmpeg
on Ubuntu.-
Using pip
pip install frogbase streamlit streamlit run ui/01_🏠_Home.py
-
[Coming soon] Instructions, environment for installation using Docker & Anaconda