Welcome to the Transcript Summarizer! 🚀
Transcript Summarizer is a powerful tool designed to simplify the process of summarizing transcripts. With this user-friendly backend application, you can effortlessly generate concise summaries from lengthy transcripts, making it easier to extract key information.
Tired of sifting through long transcripts to find the important details? Transcript Summarizer automates this process for you using openAI's APIs. Whether you're analyzing interviews, meetings, lectures, or any other type of audio or text-based conversation, this application will help you distill the essence of the content into succinct summaries.
- Efficiency: Save time and effort by letting Transcript Summarizer do the heavy lifting for you.
- Accuracy: OpenAI's advanced algorithms ensure that the summaries are accurate and relevant.
- Customizability: Tailor the summarization process to your specific needs with customizable file upload options.
- 🤖 Automatic Summarization: Generate summaries automatically with just a click of a button.
- 🚀 Multi-format Support: Summarize transcripts in various formats including text, audio, and video.
- 💡 Integration: Seamlessly integrate Transcript Summarizer into your existing workflow with our easy-to-use API.
- 🌐 Scalable Architecture: Built on robust infrastructure, our application scales effortlessly to meet your growing needs.
Transcript Summarizer consists of the following two components:
Refer to the corresponding README files of these components for more information, setup, and usage instructions.
We welcome contributions from the community! If you're interested in contributing to the Transcript Summarizer, please take a moment to review our Contribution Guidelines.
Your contributions help make our app even better. Whether you're a developer, designer, or just enthusiastic about enhancing user experiences, we'd love to have you on board.
Before you get started, please familiarize yourself with our guidelines to ensure a smooth collaboration process.
This project is licensed under the MIT License - see the LICENSE file for details.
We appreciate the time and effort contributed by everyone to improve this project!