Bilbot – Ollama Chatbot

Bilbot is a chatbot built using Python and Ollama. It is designed to answer questions related to binary search and linear search algorithms.

The project includes a custom model configuration, chatbot knowledge data, Python logic, and a simple HTML-based user interface.

Project Overview

Bilbot was created as an educational chatbot that helps users understand searching algorithms.

The chatbot focuses on:

• Binary search
• Linear search
• Differences between search algorithms
• Basic algorithm concepts
• Search-related questions and explanations

Features

• Answers questions about binary search
• Answers questions about linear search
• Uses a custom Ollama model
• Uses a text file as the chatbot's knowledge source
• Includes a Python-based chatbot program
• Provides a simple web interface
• Designed for educational purposes

Technologies Used

• Python
• Ollama
• HTML
• CSS
• Large Language Models
• Visual Studio Code
• Git
• GitHub

Project Files

Ollama-Chatbot-Bilbot/
├── Bilbot-Data.txt
├── Bilbot.py
├── Modelfile
├── index.html
└── README.md

````markdown
# Bilbot – Ollama Chatbot

Bilbot is a chatbot built using **Python** and **Ollama**. It is designed to answer questions related to **binary search** and **linear search algorithms**.

The project includes a custom model configuration, chatbot knowledge data, Python logic, and a simple HTML-based user interface.

## Project Overview

Bilbot was created as an educational chatbot that helps users understand searching algorithms.

The chatbot focuses on:

- Binary search
- Linear search
- Differences between search algorithms
- Basic algorithm concepts
- Search-related questions and explanations

## Features

- Answers questions about binary search
- Answers questions about linear search
- Uses a custom Ollama model
- Uses a text file as the chatbot's knowledge source
- Includes a Python-based chatbot program
- Provides a simple web interface
- Designed for educational purposes

## Technologies Used

- Python
- Ollama
- HTML
- CSS
- Large Language Models
- Visual Studio Code
- Git
- GitHub

## Project Files

```text
Ollama-Chatbot-Bilbot/
├── Bilbot-Data.txt
├── Bilbot.py
├── Modelfile
├── index.html
└── README.md

Bilbot-Data.txt

Contains the keywords, information, and training content used by the chatbot.

Bilbot.py

Contains the main Python code responsible for running the chatbot and communicating with the Ollama model.

Modelfile

Contains the configuration and instructions used to create the custom Bilbot model in Ollama.

index.html

Contains the structure and design of the chatbot's web interface.

README.md

Contains the documentation and instructions for the project.

Prerequisites

Before running the project, make sure the following are installed:

• Python
• Ollama
• A code editor such as Visual Studio Code

Ollama must also be running on your computer before starting the chatbot.

How to Run the Project

1. Clone the Repository

git clone https://github.com/your-username/Ollama-Chatbot-Bilbot.git

2. Open the Project Folder

cd Ollama-Chatbot-Bilbot

3. Create the Bilbot Model

Run the following command inside the project folder:

ollama create bilbot -f Modelfile

This command creates the custom Ollama model using the configuration inside the Modelfile.

4. Verify the Model

ollama list

Check that the bilbot model appears in the list of available Ollama models.

5. Install the Required Python Packages

Install the packages required by Bilbot.py.

pip install ollama

Additional packages may be required depending on the imports used in the Python file.

6. Run the Python Program

python Bilbot.py

7. Open the Web Interface

Open the following file in a browser:

index.html

You may also use the Live Server extension in Visual Studio Code:

1. Open the repository in Visual Studio Code.
2. Right-click index.html.
3. Select Open with Live Server.

Example Questions

Users may ask Bilbot questions such as:

• What is binary search?
• What is linear search?
• What is the difference between binary and linear search?
• When should binary search be used?
• What is the time complexity of linear search?
• Does binary search require sorted data?
• Which search algorithm is faster?

Purpose of the Project

The purpose of this project is to demonstrate how a locally hosted large language model can be customized to create an educational chatbot.

It also demonstrates the integration of:

• Python programming
• Ollama models
• Custom chatbot data
• Prompt configuration
• A basic web interface

Limitations

• Bilbot mainly focuses on binary and linear search algorithms.
• The quality of its responses depends on the information provided in the chatbot data and model instructions.
• Ollama must be installed and running locally.
• The chatbot may not answer questions outside its intended topic accurately.
• The project is intended as a basic educational prototype.

Future Improvements

Possible future improvements include:

• Adding more searching algorithms
• Adding sorting algorithms
• Improving the chatbot interface
• Adding conversation history
• Adding error handling
• Improving response accuracy
• Adding voice input
• Adding mobile responsiveness
• Connecting the HTML interface directly to the Python backend
• Adding more examples and visual explanations

Author

Lerrica Jeremy S. Torreno

Academic Purpose

This project was created for academic and educational purposes to demonstrate the use of Python, Ollama, and custom language models in building a specialized chatbot.

Disclaimer

Bilbot is an educational chatbot. Its responses should be reviewed and verified before being used as a primary academic or technical reference.

**Suggested GitHub repository description:**

> An educational chatbot built with Python and Ollama that specializes in binary and linear search algorithms.