Scribe is a collaborative project developed by a group of 6 students from Kalinga Institute of Industrial Technology (KIIT) as a minor project for their 6th semester. With Scribe, users can interact with their documents using advanced language models locally, powered by Ollama (mistral model), LangChain, and Chainlit.
To use Scribe, ensure that you have Python 3.9 or later installed on your system.
- Download Ollama: Begin by downloading Ollama from https://ollama.com/download
- Start the Ollama service:
sudo systemctl start ollama
- Pull Mistral: After downloading Ollama, you'll need to use a command to download the
specific LLM model you want to use, in this case, "mistral"
ollama pull mistral
- Clone the Repository: clone the Scribe repository to your local machine.
git clone https://github.com/prajuktadey/minor-project.git cd minor-project
Create a virtual environment for the project and activate it.
python3 -m venv .venv && source .venv/bin/activate
Install the required Python packages by running the following command:
pip install -r requirements.txt
Start the chat UI by running the appropriate command based on the example you want to replicate:
# Chatbot with Document Upload
chainlit run rag.py
Scribe offers a powerful yet simple solution for interacting with your documents using advanced language models. Developed by a team of students from Kalinga Institute of Industrial Technology (KIIT) as a minor project, Scribe leverages the capabilities of Ollama (mistral model), LangChain, and Chainlit to provide an educational tool for exploring the possibilities of natural language processing.
While Scribe is not intended for production use and may require additional configuration depending on your setup, it serves as a testament to the collaborative efforts of its developers and the potential of open-source resources in the field of AI and NLP.
Feel free to explore, modify, and adapt Scribe for your own use cases, keeping in mind that it is designed for educational purposes and should not be deployed in a production environment without proper testing and validation.