This is a personal chatbot project that allows you to create and interact with a customized AI companion named Iris. The project runs entirely on your local machine using an open-source large language model (Ollama), ensuring privacy and full control over your data.

• Local Processing: Runs locally on your computer using Ollama. No internet connection or API fees are required.
• Custom Persona: The AI's personality, communication style, and attitude are fully customizable within the application code.
• Contextual Memory: Maintains a short-term memory of the conversation context for a more natural and fluid interaction.
• Concise Responses: Tuned to provide short, complete, and engaging replies.
• Web Interface: A straightforward HTML and JavaScript interface allows for easy conversation through any modern web browser.

Before starting, ensure you have the following installed:

• Python: Version 3.8 or higher.
• Ollama: The application that runs the local language model.
• Mistral Model: Required language model, downloadable via Ollama.

1. Clone the repository:

   git clone https://github.com/Adarsh-Aravind/AI-GF-using-Ollama.git
   cd AI-GF-using-Ollama

2. Install the necessary Python libraries:

   pip install flask Flask-Cors requests

3. Download the language model using Ollama:

   ollama pull mistral

1. Start the server: Open your terminal in the project directory and run the Python application:

   python local_app.py

2. Open the interface: With the server running, open the index.html file in your preferred web browser to start chatting with Iris.

You can personalize the AI's behavior and traits by modifying the local_app.py file.

• Personality: Modify the SYSTEM_PROMPT variable to alter Iris's traits, rules, and fundamental behavior.
• Response Length: Adjust the num_predict value in the data dictionary to control the maximum length of the generated replies.
• Response Style: Adjust the temperature value (e.g., lower values like 0.1 for concise and deterministic replies, higher values like 0.8 for more creative and varied responses).

The project is structured into two main components:

• Backend (local_app.py): A Flask-based server that handles API requests from the frontend, maintains conversation history, and communicates with the local Ollama instance.
• Frontend (index.html): A simple browser interface for chatting, sending messages to the Flask backend via asynchronous JavaScript requests.