InsightSummarizer is an AI-powered text summarization tool that condenses lengthy documents into concise, easy-to-digest summaries. Whether you're dealing with books, articles, or reports, InsightSummarizer helps you grasp the essential points quickly, saving you time and enhancing understanding.
- Chapter-wise Summarization: Generate summaries for individual chapters, focusing on specific sections of interest.
- Entire Document Summarization: Summarize the whole content when documents lack clear divisions.
- Advanced Natural Language Processing (NLP): Powered by cutting-edge NLP techniques to intelligently extract the most relevant information.
- User-Friendly Interface: An intuitive interface makes the summarization process seamless for users of all technical backgrounds.
- Email Notifications: Receive summarized content directly in your inbox for convenience.
InsightSummarizer leverages the T5-small pretrained model from HuggingFace Transformers to generate accurate and coherent summaries. The process involves:
- Text Segmentation: The document is divided into chunks, either by chapters or as a whole.
- Tokenization: Chunks are tokenized using T5Tokenizer for compatibility with the T5 model.
- Summary Generation: The tokenized text is processed by the T5ForConditionalGeneration model to produce summary token IDs.
- Decoding: Summary tokens are decoded back into human-readable text using the T5Tokenizer's
decode()
function.
- Python 3.x
- Required Python packages listed in
requirements.txt
-
Clone the Repository
git clone https://github.com/zjnbwxq/InsightSummarizer.git
-
Navigate to the Project Directory
cd InsightSummarizer
-
Install Dependencies
pip install -r requirements.txt
Run InsightSummarizer via CLI:
python3 summarizer_cli.py --path <path-to-your-document>
-
Configure Email Settings
Update
sender_address
andsender_pass
inmail.py
with your email credentials. -
Start the Flask Server
python3 app.py
-
Access the Web Application
Open your browser and navigate to
http://localhost:5000
.
Contributions are welcome! If you'd like to enhance InsightSummarizer, please submit a pull request or open an issue. Your feedback and support are greatly appreciated.
InsightSummarizer is released under the MIT License.
Made by Xiaoqi Weng from Birmingham with Love❤️