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🎭 Custom Local AI Role-Play Framework

A lightweight, high-performance Python framework for running isolated local AI role-play sessions using Ollama and the Microsoft Phi-3 model.

This repository is built with an elite focus on clean Object-Oriented Programming (OOP), explicit state isolation, and secure, non-blocking UI animations.

✨ Key Architectural Features

• 🚀 Generator-Driven Streaming: Utilises Python yield logic to process text data on the fly. This decouples data ingestion from terminal display formatting.
• 🛡️ Built-in Anti-Jailbreak Protection: Automatically strips dangerous system commands, markdown headers, and injection prompts to prevent the AI from breaking character boundaries.
• 🧮 Memory Sliding Window: Hardcoded history bounding (max_history = 6) automatically prunes legacy message arrays to optimize model context windows.
• 🔒 Direct Local Routing: Configured to query Ollama via direct IPv4 socket bindings (127.0.0.1), entirely bypassing Windows proxy routing drops.
• 🧪 Integrated Debugger: Connects seamlessly to an internal handler subsystem to cleanly monitor prompt data payloads without cluttering production loops.

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🛠️ Step-by-Step Installation Guide

1. Prerequisites

This framework requires Python 3.12+, Git, and the Ollama Desktop Application.

1. Install the Ollama App: Download and run the client engine from ollama.com.
2. Download the Model: Open your system terminal and download the default lightweight Microsoft Phi-3 model into the background application engine:

   ollama run phi3

3. Keep it Active: Ensure the Ollama background process is running in your system tray before executing the Python framework.

2. Download the Repository

Clone this codebase using Git and navigate into the workspace directory:

git clone https://github.com
cd ai-roleplay-framework

3. Install Dependencies

Install the required keyboard event hooks and official Python API client packages:

pip install -r requirements.txt

(Note: Core modules like inspect, datetime, and sys are part of Python's standard library and do not require manual installation).

4. Running the Framework

Execute the central script loop to begin chatting in the terminal workspace:

python main.py

💡 Tip: Press the Esc key at any point during your session to safely close the terminal loop.

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📖 Basic Developer Usage Example

Other developers can import your class into their own custom systems instantly:

from chatbot import ChatBot

# Instantiate a unique character session with its own memory boundary
character = ChatBot(
    name="Detective", 
    desc="A gritty noir investigator", 
    task="Question the suspect"
)

# Launch the interactive session loop
character.chat()

📄 Licensing

Distributed under the MIT License. See the LICENSE file for more details.