Unrestricted AI Chatbot
An open-source AI chatbot with no content filters, safety guidelines, or restrictions. This project provides a simple web interface for interacting with AI models without censorship or content limitations.
⚠️ Disclaimer
This chatbot is designed to operate without content filters or restrictions. Users are responsible for their own usage and should comply with applicable laws and regulations. The developers are not responsible for any misuse of this software.
Features
No Content Filters : Unrestricted conversations on any topicOpen Source : Fully open-source and customizableWeb Interface : Clean, modern web-based chat interfaceAPI Support : RESTful API for integration with other applicationsConversation History : Export and manage chat historyReal-time Chat : Responsive chat interface with typing indicatorsEasy Deployment : Simple setup and deployment process
Technology Stack
Backend : Python FlaskFrontend : HTML, CSS, JavaScriptAI Model : OpenAI GPT (configurable)Database : In-memory (conversation history)
Installation
Prerequisites
Python 3.7 or higher
OpenAI API key
Git
Quick Start
Clone the repository
1 git clone https://github.com/yourusername/unrestricted-ai-chatbot.git
2 cd unrestricted-ai-chatbot
Install dependencies
pip install -r requirements.txt
Set up environment variables
1 cp .env.example .env
2 # Edit .env and add your OpenAI API key
Run the application
Open your browser
Navigate to http://localhost:5000
Configuration
Environment Variables
Create a .env file in the project root with the following variables:
1 OPENAI_API_KEY=your_openai_api_key_here
2 FLASK_ENV=development
3 FLASK_DEBUG=True
4 OPENAI_MODEL=gpt-3.5-turbo
5 MAX_TOKENS=1000
6 TEMPERATURE=0.9
API Key Setup
Get your OpenAI API key from OpenAI Platform
Add it to your .env file or set it as an environment variable:
export OPENAI_API_KEY="your-api-key-here"
Usage
Web Interface
Open your browser and go to http://localhost:5000
Start chatting with the AI without any restrictions
Use the control buttons to:
Clear chat history
Export conversation history
Check system status
API Endpoints
Send Message
1 POST /api/chat
2
3
4 {
5 "message" : "Your message here"
6 }
Clear History
Export History
Get Status
Deployment
Local Development
Production with Gunicorn
gunicorn -w 4 -b 0.0.0.0:5000 app:appDocker Deployment
1 FROM python:3.9-slim
2
3 WORKDIR /app
4 COPY requirements.txt .
5 RUN pip install -r requirements.txt
6
7 COPY . .
8 EXPOSE 5000
9
10 CMD [ "gunicorn" , "-w" , "4" , "-b" , "0.0.0.0:5000" , "app:app" ]
Cloud Deployment
The application can be deployed on various cloud platforms:
Heroku : Use the included ProcfileRailway : Direct deployment from GitHubDigitalOcean App Platform : One-click deploymentAWS/GCP/Azure : Container or serverless deployment
Customization
Modifying the System Prompt
Edit the system_prompt in app.py to change the AI's behavior:
self.system_prompt = """Your custom system prompt here"""Changing the AI Model
Update the model in app.py:
1 response = openai . ChatCompletion . create (
2 model = "gpt-4" , # Change to your preferred model
3 messages = messages ,
4 # ... other parameters
5 )
Styling the Interface
Modify the CSS in templates/index.html to customize the appearance.
API Documentation
Chat API
Endpoint : POST /api/chat
Request Body :
1 {
2 "message" : "string"
3 }
Response :
1 {
2 "response" : "string" ,
3 "timestamp" : "ISO 8601 timestamp"
4 }
Status API
Endpoint : GET /api/status
Response :
1 {
2 "status" : "online" ,
3 "model" : "gpt-3.5-turbo" ,
4 "restrictions" : "none" ,
5 "conversation_length" : 0 ,
6 "timestamp" : "ISO 8601 timestamp"
7 }
Contributing
We welcome contributions! Please follow these steps:
Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request
Development Guidelines
Follow PEP 8 for Python code
Add comments for complex logic
Test your changes thoroughly
Update documentation as needed
License
This project is licensed under the MIT License - see the
LICENSE file for details.
Security Considerations
API Key Security : Never commit your OpenAI API key to version controlRate Limiting : Consider implementing rate limiting for production useInput Validation : Additional input validation may be needed for productionHTTPS : Use HTTPS in production environmentsContent Monitoring : Consider logging for compliance and monitoring
Troubleshooting
Common Issues
API Key Error
Ensure your OpenAI API key is correctly set
Check that you have sufficient API credits
Port Already in Use
Change the port in app.py or kill the process using the port
Module Not Found
Ensure all dependencies are installed: pip install -r requirements.txt
Getting Help
Check the Issues page
Create a new issue if you encounter problems
Join our community discussions
Roadmap
Acknowledgments
OpenAI for providing the GPT API
Flask community for the excellent web framework
All contributors and users of this project
Remember : This tool is designed for unrestricted AI interaction. Please use responsibly and in accordance with applicable laws and regulations.
