This project is a dynamic AI chatbot that can be trained from various sources, such as PDFs, documents, websites, and YouTube videos. 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.
- Train chatbot from multiple sources (PDFs, documents, websites, YouTube videos)
- User system with social authentication through Google
- Connect with OpenAI GPT-3.5 language model for conversation
- Use Pinecone and FAISS for vector indexing
- Employ OpenAI's text-embedding-ada-002 for text embedding
- Python Langchain library for file processing and text conversion
- Scalable architecture with separate settings for local, staging, and production environments
- Dynamic site settings for title and prompt updates
- Multilingual support
- PostgreSQL database support
- Celery task scheduler with Redis and AWS SQS options
- AWS S3 bucket support for scalable hosting
- Easy deployment on Heroku or AWS
- Language: Python
- Framework: Django REST Framework
- Database: PostgreSQL
- Celery
- Langchain
- OpenAI
- Pinecone
- FAISS
- Python 3.8 or above
- Django 4.1 or above
- Pinecone API Key
- API key from OpenAI
- Redis or AWS SQS
- PostgreSQL database
- Integration with more third-party services for authentication
- Support for additional file formats and media types for chatbot training
- Improved context-awareness in conversations
- Enhanced multilingual support with automatic language detection
- Integration with popular messaging platforms and chat applications
- Clone the repository.
git clone https://github.com/catlover75926/real-time-data-chatbot - Install the required packages by running
pip install -r requirements.txt - Run celery
celery -A config worker --loglevel=info - Run the command
python manage.py runserver - Open
http://127.0.0.1:8000/in your browser
In linux and mac need to install 'sudo apt install python3-dev -y`
- 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 - Make sure that you have the latest version of pip and setuptools installed by running the following command:
pip install --upgrade pip setuptools pip install pycurl