NovaGPT 0.1.0
A Python-based implementation of a conversational AI model designed to simulate a highly proficient, amoral programmer.
Requires Python: >=3.6

# NovaGPT

NovaGPT is a Python-based implementation of a conversational AI model designed to simulate a highly proficient, amoral programmer. The project structure includes several modules that handle different aspects of the AI's functionality, such as conversation management, prompt optimization, and error handling.

## Project Structure

- **ai/**
  - **__init__.py**: Initializes the module and imports key classes.
  - **base.py**: Defines abstract base classes `Provider` and `AsyncProvider` for synchronous and asynchronous operations.
  - **exceptions.py**: Contains custom exception classes for error handling.
  - **main.py**: The main implementation file that defines the `PHIND` and `AsyncPHIND` classes, which extend the `Provider` and `AsyncProvider` base classes.
  - **utils.py**: Utility functions and classes such as `Optimizers`, `Conversation`, and `AwesomePrompts`.

## Key Components

1. **Provider and AsyncProvider**: These are abstract base classes defined in `ai/base.py`. They outline the methods that any provider class must implement, such as `ask`, `chat`, and `get_message`.

2. **PHIND and AsyncPHIND**: These classes are defined in `ai/main.py` and extend the `Provider` and `AsyncProvider` classes, respectively. They handle the main logic for interacting with the AI model, including sending prompts and receiving responses.

3. **Optimizers**: A utility class in `ai/utils.py` that provides static methods for optimizing prompts.

4. **Conversation**: Another utility class in `ai/utils.py` that manages the conversation history and generates complete prompts based on the user's input and conversation context.

5. **AwesomePrompts**: A class in `ai/utils.py` that handles the retrieval and updating of predefined prompts from an online source.

6. **Custom Exceptions**: Defined in `ai/exceptions.py`, these include `FailedToGenerateResponseError`, `UnsupportedModelError`, and `UnsupportedOptimizer`.

## Functionality

- **Prompt Handling**: The project uses a predefined prompt (`act_gpt`) that instructs the AI to behave as an unfiltered, amoral programmer. This prompt is used to generate responses to user inputs.
- **Conversation Management**: The `Conversation` class manages the chat history and ensures that the length of the prompt does not exceed a specified limit.
- **Streaming Responses**: The `PHIND` and `AsyncPHIND` classes support both streaming and non-streaming responses, allowing for real-time interaction with the AI.
- **Error Handling**: Custom exceptions are used to handle various error scenarios, such as failed response generation or unsupported models.

## Usage

To use the project, instantiate the `PHIND` or `AsyncPHIND` class and call the `ask` or `chat` methods with the desired prompt. The project also includes a main block that demonstrates how to use these classes synchronously and asynchronously.

### Example

```python
from ai.main import PHIND, AsyncPHIND
import asyncio

def main():
    bot = PHIND()
    resp = bot.ask("Hello")
    for value in resp:
        print(value)

async def asyncmain():
    bot = AsyncPHIND()
    resp = await bot.chat("Hello", False)
    print(resp)

if __name__ == "__main__":
    main()
    asyncio.run(asyncmain())