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https://github.com/devanshu-17/transcriptiq
TranscriptIQ is a project that enables users to transcribe YouTube videos and perform various NLP (Natural Language Processing) tasks, chat with youtube video and many more on the transcribed text.
https://github.com/devanshu-17/transcriptiq
clarifai-python cohere streamlit whisper
Last synced: about 20 hours ago
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TranscriptIQ is a project that enables users to transcribe YouTube videos and perform various NLP (Natural Language Processing) tasks, chat with youtube video and many more on the transcribed text.
- Host: GitHub
- URL: https://github.com/devanshu-17/transcriptiq
- Owner: Devanshu-17
- License: mit
- Created: 2023-09-14T15:28:01.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-05-13T10:32:46.000Z (7 months ago)
- Last Synced: 2024-12-19T14:11:38.837Z (4 days ago)
- Topics: clarifai-python, cohere, streamlit, whisper
- Language: Python
- Homepage: https://transcript-iq.streamlit.app/
- Size: 13.1 MB
- Stars: 9
- Watchers: 2
- Forks: 2
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# TranscriptIQ
TranscriptIQ is a project that enables users to transcribe YouTube videos and perform various NLP (Natural Language Processing) tasks, chat with youtube video and many more on the transcribed text.
## Deployed app link:
### https://transcript-iq.streamlit.app/
## Implementation video
https://github.com/Devanshu-17/TranscriptIQ/assets/42097653/c018a440-c613-4cfa-8440-edb5bc07bb26
## Directory Structure
```
./
├── LICENSE
├── README.md
├── app.py
├── images
│ ├── AI.jpg
│ ├── NER.png
│ ├── Robot_whisper1.jpg
│ ├── Robot_whisper2.jpg
│ ├── Robot_whisper3.jpg
│ ├── expander.png
│ ├── mp3_2_text.png
│ ├── resum.png
│ └── youtube2text.png
├── myfunctions
│ ├── __pycache__
│ ├── my_functions.py
│ └── my_summarization_functions.py
├── packages.txt
├── pages
│ ├── Chat.py
│ ├── Transcribe Youtube.py
│ └── static
└── requirements.txt
6 directories, 18 files
```
## Functionality
The main functionality of TranscriptIQ is provided by the `transcribe_youtube.py` script. It uses the Streamlit library to create a user interface for transcribing YouTube videos and performing NLP tasks. Here is a brief overview of the functionality provided by the script:
- Retrieve YouTube video information (title, author, views, duration, etc.)
- Download YouTube videos as MP4 format
- Convert MP4 videos to MP3 audio files
- Transcribe MP3 audio files to text using speech-to-text technology
- Perform text summarization using the Cohere API
- Perform Named Entity Recognition (NER) using the Spacy library
- Generate graphs based on NER results
- Perform sentiment analysis using the VADER library
- Display word clouds based on NER results
## Usage
To use TranscriptIQ, you can run the `app.py` script. This will start the Streamlit app and you can interact with it to transcribe YouTube videos and perform NLP tasks on the transcribed text.
Note: Before running the script, make sure you have installed all the required packages listed in `requirements.txt`.
```python
streamlit run app.py
```
## Credits
TranscriptIQ was developed as part of the Streamlit LLM Hackathon. The project was created by [Devanshu](https://github.com/Devanshu-17), [Somesh](https://github.com/someshfengde).
- [ ] demo running
- [ ] understand pricing points on customgpt.ai
- [ ] plan for a the link of videos. ( 20 videos downloaded as mp4 )
- [ ] build a demo according to the plan.