FrogBase simplifies the download-transcribe-embed-index workflow for multi-media content. It does so by linking content from various platforms with speech-to-text models, image & text encoders and embedding stores.
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).
⚠️ Warning: This is currently a pre-release version and is known to be very unstable. For stable releases, please use any 1.x versions.
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!
https://user-images.githubusercontent.com/6735526/216852681-53b6c3db-3e74-4c86-806f-6f6774a9003a.mp4
FrogBase currently provides functionality to:
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 FrogBase
sudo 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)
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
ffmpegto be installed on your system. You can install it usingsudo apt install ffmpegon Ubuntu.
Using pip
pip install frogbase streamlit
streamlit run ui/01_🏠_Home.py
[Coming soon] Instructions, environment for installation using Docker & Anaconda
FAQs
FrogBase simplifies the download-transcribe-embed-index workflow for multi-media content. It does so by linking content from various platforms with speech-to-text models, image & text encoders and embedding stores.
We found that frogbase demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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