{"id":21239201,"url":"https://github.com/cutupdev/real-time-data-chatbot","last_synced_at":"2025-03-15T03:40:30.016Z","repository":{"id":222874061,"uuid":"758630589","full_name":"cutupdev/real-time-data-chatbot","owner":"cutupdev","description":"This chatbot process real time data. It's dynamic and built with Django REST framework, supporting to collect data from from PDFs, documents, websites, and YouTube videos. 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It uses a user system with social authentication through Google, and the Django REST framework for its backend. The chatbot leverages OpenAI's GPT-3.5 language model to conduct conversations and is designed for scalability and ease of use.\n\n## Features\n- Train chatbot from multiple sources (PDFs, documents, websites, YouTube videos)\n- User system with social authentication through Google\n- Connect with OpenAI GPT-3.5 language model for conversation\n- Use Pinecone and FAISS for vector indexing\n- Employ OpenAI's text-embedding-ada-002 for text embedding\n- Python Langchain library for file processing and text conversion\n- Scalable architecture with separate settings for local, staging, and production environments\n- Dynamic site settings for title and prompt updates\n- Multilingual support\n- PostgreSQL database support\n- Celery task scheduler with Redis and AWS SQS options\n- AWS S3 bucket support for scalable hosting\n- Easy deployment on Heroku or AWS\n\n## Technologies\n- Language: Python\n- Framework: Django REST Framework\n- Database: PostgreSQL\n\n### Major Libraries:\n- Celery\n- Langchain \n- OpenAI\n- Pinecone\n- FAISS\n## Requirements\n- Python 3.8 or above\n- Django 4.1 or above\n- Pinecone API Key\n- API key from OpenAI\n- Redis or AWS SQS\n- PostgreSQL database\n\n## Future Scope\n- Integration with more third-party services for authentication\n- Support for additional file formats and media types for chatbot training\n- Improved context-awareness in conversations\n- Enhanced multilingual support with automatic language detection\n- Integration with popular messaging platforms and chat applications\n\n## How to run\n- Clone the repository. `git clone https://github.com/catlover75926/real-time-data-chatbot`\n- Install the required packages by running `pip install -r requirements.txt`\n- Run celery `celery -A config worker --loglevel=info`\n- Run the command `python manage.py runserver`\n- Open `http://127.0.0.1:8000/` in your browser\n\nIn linux and mac need to install 'sudo apt install python3-dev -y`\n1. Make sure that you have the development libraries for libcurl installed on your system. You can install them by running the following command: `sudo apt-get install libcurl4-openssl-dev gcc libssl-dev -y`\n2. Make sure that you have the latest version of pip and setuptools installed by running the following command: `pip install --upgrade pip setuptools`\n3. `pip install pycurl`","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcutupdev%2Freal-time-data-chatbot","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcutupdev%2Freal-time-data-chatbot","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcutupdev%2Freal-time-data-chatbot/lists"}