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This is my final year project. The project leveraging the following technologies: Backend: FastAPI, Python, OpenAI API, LangChain, ChromaDB, pymongo. Frontend: HTML, CSS, JavaScript, React.js, Gradio. Other Libraries: tiktoken, python-dotenv, pandas, tqdm, markdown, pypdf. Deployment: Uvicorn, Gunicorn

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AkramUllahKhan/llmentor-ai-driven_student_assistant

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University Chatbot Project

Introduction

Welcome to the University Chatbot Project! This project aims to create an AI-powered chatbot for our university's website, designed to provide users with quick and accurate information about our institution. Leveraging advanced Large Language Models, this chatbot is capable of engaging in human-like conversations, offering a more user-friendly and efficient way to access information.

The chatbot utilizes state-of-the-art language understanding techniques, allowing users to ask questions and receive precise, timely answers. This initiative represents a significant advancement towards enhancing the accessibility and interactivity of our university's digital presence, making the experience as seamless and fast as interacting with a person.

Aim and Objective of the Project

The primary aim of this project is to develop a conversational AI-powered chatbot for our university's website, enabling users to access precise information quickly and easily. The key objectives include:

  1. Human-like Conversations: Creating a chatbot that engages in natural, human-like conversations with users.
  2. Advanced NLP: Utilizing GPT (Generative Pre-trained Transformer) for accurate and contextually relevant responses.
  3. Streamlined Information Access: Providing comprehensive information across various aspects of the university, including academic programs, faculty, departments, admission requirements, campus facilities, student services, events, and more.
  4. User Engagement: Implementing features that enhance user interaction and engagement.
  5. Real-time Updates: Delivering real-time information and updates to users.
  6. Comprehensive Information Retrieval: Ensuring that users can access a wide range of information efficiently and conversationally.

These objectives collectively aim to provide an efficient, user-friendly means of accessing university information, significantly enhancing the user experience.

Requirements

To set up the project, you need to install the following dependencies:

langchain==0.1.0
langchain_openai==0.0.2
langchain-community==0.0.11
chromadb==0.5.0
openai==1.7.0
python-dotenv
tiktoken==0.5.2
pymongo==4.6.3
tqdm==4.66.1
gradio
fastapi
uvicorn
pandas
markdown
gunicorn
pypdf

Setting Up the Virtual Environment

To ensure a smooth setup process, we recommend using a virtual environment. Follow these steps:

  1. Clone the Repository:

    git clone https://github.com/AkramUllahKhan/llmentor-ai-driven_student_assistant.git
  2. Navigate to the Project Directory:

    cd university-chatbot
  3. Create a Virtual Environment:

    python -m venv venv
  4. Activate the Virtual Environment:

    • On Windows:
      venv\Scripts\activate
    • On Unix or MacOS:
      source venv/bin/activate
  5. Install the Requirements:

    pip install -r requirements.txt

Running the Application

Once the setup is complete, you can run the application using Uvicorn:

uvicorn main:app --reload

This command will start the server, and you can access the chatbot interface via your web browser.

Contributing

We welcome contributions to this project! Please feel free to fork the repository, create a branch, make your changes, and submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

Special thanks to the OpenAI, LangChain, and broader open-source community for providing the tools and libraries that made this project possible.

About

This is my final year project. The project leveraging the following technologies: Backend: FastAPI, Python, OpenAI API, LangChain, ChromaDB, pymongo. Frontend: HTML, CSS, JavaScript, React.js, Gradio. Other Libraries: tiktoken, python-dotenv, pandas, tqdm, markdown, pypdf. Deployment: Uvicorn, Gunicorn

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