This web application leverages advanced Natural Language Processing (NLP) techniques and integrates the OpenAI API to provide a range of features including text generation with context, multi-document summarization, multilingual sentiment analysis, and emotion recognition.
Follow the steps below to set up and run the application on your local machine.
Before you begin, make sure you have the following software installed:
- Python : ((https://www.python.org/downloads/))
- flask: Install flask
- Clone this repository to your local machine:
git clone <https://github.com/Kapil7982/Summarizer_App.git>
- Text Generation with Context This feature allows users to generate text based on a provided prompt while considering context and previous interactions. The application utilizes OpenAI's GPT-3.5 API for advanced text generation.
- Multi-Document Summarization Users can input multiple documents or articles, and receive a coherent summary. The application uses advanced NLP techniques, including the transformers library, to maintain context and relevance during summarization.
- Multilingual Sentiment Analysis and Emotion Recognition This feature provides advanced sentiment analysis supporting multiple languages and includes emotion recognition. Users can input text in various languages to receive sentiment and emotion analysis.
Text Generation with Context: Send a POST request to
http://localhost:5000/generate_text
with a JSON payload containing a prompt and context.
Multi-Document Summarization: Send a POST request to
http://localhost:5000/summarize
with a JSON payload containing a list of documents.
PDF Summarization: Upload a PDF file to