CompletedPythonStreamlit
ClipQuoter
Python app that transcribes video clips and generates shareable quote cards using Gemini AI and Streamlit
Timeline
2 weeks
Role
Full Stack
Team
Solo
Status
CompletedTechnology Stack
Python
Streamlit
Key Challenges
- Video-to-audio conversion
- Speech recognition accuracy
- AI quote extraction
- Acuurate Timestamps generation
- Large Video Processing
Key Learnings
- Google Gemini API integration
- Streamlit app development
- Transcript generation using Youtube Transcript API
- JSON structuring of the Quotes
- Streamlit state management
ClipQuoter: Video to Meangingfull Quotes
Overview
ClipQuoter is a Streamlit-based web application that extracts transcripts from YouTube videos and leverages Google Gemini AI to generate meaningful, timestamped quotes. It is designed for creators, researchers, and analysts who need structured insights and shareable highlights from long-form video content.
Key Features
- Video Transcription: Extracts transcripts from YouTube videos using youtube-transcript-api with support for multiple URLs.
- AI Quote Extraction: Uses Google Gemini AI to generate meaningful, concise quotes with precise start and end timestamps.
- Quotes Generation: Saves Quotes in structured JSON format for reuse and analysis.
- Streamlit Interface: Interactive Streamlit interface with secure API key input and real-time processing.
- End-to-End Pipeline: Built-in error handling for invalid URLs, unavailable transcripts, and API issues.
Why I Built This
I often found valuable insights hidden inside long YouTube lectures, podcasts, and interviews but extracting them manually was inefficient. I built ClipQuoter to automate transcript retrieval and intelligently surface impactful, timestamped quotes — making video content easier to analyze, repurpose, and share.
Future Plans
- Custom quote card templates and themes
- Batch processing for longer videos
- Direct social media sharing integration
- Support for multiple languages