Streamlit Document QA and Text Summarization App

This Streamlit application empowers users to effortlessly perform Document Question-Answering (QA) and Text Summarization tasks in their preferred language, English or German, with just a few simple steps.

How to Use

Language Selection

1. Select your preferred language (English or German) from the sidebar.

Task Selection

2. Choose the task you want to perform - Document QA or Text Summarization.

Document QA

1. Upload Documents

• Click on the "Upload Files" section in the sidebar.
• Upload various types of documents including (PDFs, Markdown, plain text, and DOCX files).

2. OCR for Images

• Click on the "OCR for Images" section in the sidebar.
• Conveniently upload images (PNG, JPG, JPEG) for optical character recognition (OCR).

3. Upload Audio Files and Transcribe

• Click on the "Upload Audio Files and Transcribe" section in the sidebar.
• Effortlessly upload audio files (MP3, WAV) for automatic transcription.

4. Import HTML

• Click on the "Import HTML" section in the sidebar.
• Simply enter URLs to import HTML content from websites.

5. Transcribe YouTube Video

• Click on the "YouTube Video" section in the sidebar.
• Enter a YouTube video URL for transcription.

6. Create Vector Database

• Click on the "Create Vector Database" section in the sidebar to create a database from uploaded documents.

7. Remove All Files

• Click on the "Remove Files" section in the sidebar to remove all files in the data directory.

Chat with Chatbot

• Engage with a chatbot that can provide answers to questions based on the uploaded documents.

Text Summarization

• In the Text Summarization task, simply enter text in the provided text area.
• Click the "Summarize" button to generate a concise summarization of the input text.

Document QA Example:

Here's an example of the Document Question-Answering task in action:

Text Summarization Example:

And here's an example of the Text Summarization task in action:

Installation and Running Locally

To use this Streamlit application, follow these steps:

1. Clone the repository and navigate to the project directory:

   git clone https://github.com/saadkh1/DocQA-TextSummarization-App.git

   cd DocQA-TextSummarization-App

2. Install the required packages from the requirements.txt file:

   pip install -r requirements.txt

3. Download the necessary language models and embeddings by running the models.sh script:

   sh models.sh

4. Run the Streamlit app:

   streamlit run app.py

5. Open this URL in your browser: http://localhost:8501/

Using Docker

Alternatively, you can use Docker to run the application in a container. Make sure you have Docker installed on your system. Follow these steps:

1. Clone the repository and navigate to the project directory:

   git clone https://github.com/saadkh1/DocQA-TextSummarization-App.git

   cd DocQA-TextSummarization-App

2. Build the Docker image:

   docker build -t qa-summrize-app:1.0 .

3. Run the Docker container:

   docker run -p 8501:8501 qa-summrize-app:1.0

4. Open this URL in your browser: http://localhost:8501/

Using Google Colab

If you prefer to use Google Colab, you can run the app using the provided app.ipynb notebook:

1. Open the app.ipynb notebook in Google Colab:

2. Run all the cells in the notebook.

The notebook will start the Streamlit app and expose it using ngrok. Follow the instructions in the notebook to access the app URL.