This app allows you to chat with ChatGPT using a reverse-engineered API library called revChatGPT. Replies from the Chatbot are streamed back to the user in real-time, which gives the user an experience similar to how ChatGPT streams back its answers.

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To get started with the app, you'll need to create an account on OpenAI's ChatGPT and save your credentials. You can choose from three authentication methods: Email/Password, Session token, or Access token.

Once you have your credentials, you can select your authentication method in the sidebar and provide the required information. If you choose Email/Password, you'll need to provide your email and password. If you choose Session token, you'll need to provide your session token. If you choose Access token, you'll need to provide your access token.

revChatGPT is a reverse-engineered ChatGPT API that is not affiliated with OpenAI. It is intended for educational and research purposes only. Please use it responsibly and do not use it for any commercial or malicious purposes.

To install the required packages, please run the following command in your terminal:

pip install streamlit revChatGPT

To run the app, open your terminal, navigate to the directory where the code is saved, and run the following command:

streamlit run app.py

After running the app, you will see the AI Assistant: revChatGPT web page. In the sidebar, you can configure the authentication method for your ChatGPT account. You can choose between Email/Password, Session token, and Access token.

Note: You will need to create an account on OpenAI's ChatGPT and save your credentials before using the app.

After configuring your authentication method, you can start chatting with the AI assistant. Type your question or message in the "You:" field and click "Submit". The chatbot will respond with a message that will be displayed in the chat window.

This app was developed by Kaludii using the revChatGPT API library. Kaludii is an AI enthusiast who is passionate about developing and applying machine learning models to solve real-world problems.

This project is licensed under the MIT License.