pickpod 1.0.5

Description:

pickpod 1.0.5

Pickpod



Integrated tools to transfer internet audio to text, extract unpopular views, and pick up podcasts for you.
Pickpod helps to build your private wiki efficiently.
This repository contains:


A Python package that can easily call specified tasks.


A Streamlit app that provides a web UI to manage your podcast library.


Several package usage examples of complete tasks for target audio.


Welcome to our commercial deployment: Pickpod, implementation with Java and microservice architecture.
Compared to the personal open-source prototype in this repository, the commercial version provides powerful performance and stable services.
Table of Contents


Background


Install


Usage


Examples


Related Efforts


Maintainers


Contributing


License


Background
The goals for Pickpod are:


High-quality integration with yt-dlp, faster-whisper, and pyannote-audio, so that users can quickly obtain the text result of the corresponding audio transcription by simply inputting a link or a local file.


The convenient use of LISTEN NOTES Podcast API and Claude API. After completing the necessary settings and making a task, Pickpod can get the list of podcasts the users are interested in regularly according to the specified release period. Thus, the transcription task can be completed in batch. Then, Pickpod can pick up podcasts based on the evaluation through the extracted keywords, summaries, views, or only the LLM. Users can reference and modify the recommendation according to the sorting results of podcasts.


Rapid deployment for local environments, so that when the user launches the project, all features are easily accessible in the browser.


Install
Since ffmpeg and ffprobe are strongly recommended by yt-dlp, it is necessary to install the ffmpeg binary within the system before installing Pickpod.
You can refer to the installation method provided by pydub, or go to the ffmpeg download page and ffmpeg compilation guide for more.
Moreover, please see the note about hugging face access token fetching in pyannote-audio for more information on using speaker-diarization.
If you need to filter the list of podcasts to be batch transcribed based on customized rules or use LLM to analyze the transcribed text, please refer to the API documentation provided by Listen Notes and Anthropic to obtain the necessary Access Keys, respectively.
❗️Warning
Due to Pickpod strictly restricting the version of used Python packages, some packages may automatically solve conflicts and remove some of the packages that you have installed before. To avoid unnecessary conflicts or damage to your environment, we strongly recommend installing Pickpod in a brand new Python environment or a Python virtual environment.
Python
You don't need this source code if you just want to use the package. Just run:
$ pip install --upgrade pickpod

If you want to modify the package, install from source with:
$ pip install ./pickpod

If you want to run the Streamlit app that provides a web UI, install from source with:
$ pip install -r ./pickpod/app/requirements.txt
$ # For Linux or Unix
$ streamlit run ./pickpod/app/Home.py --server.port 8051
$ # For Windows
$ python -m streamlit run ./pickpod/app/Home.py --server.port 8051

Then visit http://127.0.0.1:8051 in your local browser.
Installation in a typical environment
We chose nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04 as a typical system environment to try to install Pickpod. The docker image has the following base configuration:
$ python3 -V

Python 3.10.12


$ nvidia-smi

Tue Aug 15 08:06:56 2023
+-----------------------------------------------------------------------------+
NVIDIA-SMI 525.105.17 Driver Version: 525.105.17 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | MIG M. |
|===============================+======================+======================|
0 NVIDIA GeForce ... On | 00000000:65:00.0 Off | N/A |
0% 43C P8 23W / 370W | 1481MiB / 24576MiB | 0% Default |
| | N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
Processes: |
GPU GI CI PID Type Process name GPU Memory |
ID ID Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+

First, we need to install ffmpeg, python3-pip, and other essential tools, then upgrade the software packages.
$ sudo apt-get -y install cmake libsndfile1 ffmpeg python3-pip
$ sudo apt update && apt upgrade -y

We can verify if ffmpeg is installed successfully in the following way:
$ ffmpeg -version

ffmpeg version 4.4.2-0ubuntu0.22.04.1 Copyright (c) 2000-2021 the FFmpeg developers
built with gcc 11 (Ubuntu 11.2.0-19ubuntu1)
configuration: --prefix=/usr --extra-version=0ubuntu0.22.04.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librabbitmq --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libsrt --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-pocketsphinx --enable-librsvg --enable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared
libavutil 56. 70.100 / 56. 70.100
libavcodec 58.134.100 / 58.134.100
libavformat 58. 76.100 / 58. 76.100
libavdevice 58. 13.100 / 58. 13.100
libavfilter 7.110.100 / 7.110.100
libswscale 5. 9.100 / 5. 9.100
libswresample 3. 9.100 / 3. 9.100
libpostproc 55. 9.100 / 55. 9.100

After downloading the source code and running setup.py, we can import Pickpod in Python.
$ git clone https://github.com/shixiangcap/pickpod.git
$ pip install ./pickpod

Usage
Do internet Pickpod task
from pickpod.config import TaskConfig
from pickpod.draft import AudioDraft
from pickpod.task import PickpodTask

HUGGING_FACE_KEY = "YOUR_HUGGING_FACE_KEY"

# For example: https://www.youtube.com/watch?v=xxxxxxxxxxx
audio_url = "YOUR_AUDIO_URL_ON_INTERNET"

# Set audio information
audio_draft = AudioDraft(audio_url=audio_url)
# Config pickpod task
task_config = TaskConfig(key_hugging_face=HUGGING_FACE_KEY, pipeline=True)
# Initial pickpod task
pickpod_task = PickpodTask(audio_draft, task_config)
# Start pickpod task
pickpod_task.pickpod_with_url()
# Print the result of pickpod task
print(pickpod_task.__dict__)

Do local Pickpod task
from pickpod.config import TaskConfig
from pickpod.draft import AudioDraft
from pickpod.task import PickpodTask

HUGGING_FACE_KEY = "YOUR_HUGGING_FACE_KEY"

# For example: xxxxxxxxxxx.m4a
audio_path = "YOUR_LOCAL_FILE_PATH"

# Set audio information
audio_draft = AudioDraft(audio_path=audio_path)
# Config pickpod task
task_config = TaskConfig(key_hugging_face=HUGGING_FACE_KEY, pipeline=False)
# Initial pickpod task
pickpod_task = PickpodTask(audio_draft, task_config)
# Start pickpod task
pickpod_task.pickpod_with_local()
# Save the result of pickpod task
pickpod_task.save_to_txt()

Examples
A complete transcription result of an audio file
If the target YouTube video is Introducing GPT-4, the Pickpod can get the JSON file afeb5810-25ee-426d-aa88-7b58484d4c6f.json
If the target 小宇宙 podcast is EP 35. ICML现场对话AI研究员符尧：亲历AI诸神之战，解读LLM前沿研究，Llama 2，AI Agents, the Pickpod can get the JSON file 93aa3140-300d-4af6-9d9c-2c41e9095821.json
Related Efforts


yt-dlp - A youtube-dl fork with additional features and fixes.


faster-whisper - Faster Whisper transcription with CTranslate2.


pyannote-audio - Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding.


Maintainers
@shixiangcap
Contributing
Feel free to dive in! Open an issue or submit PRs.
License
MIT © shixiangcap