chat-object 2.0.2
A simple library for creating and manipulating chat and message objects for LLM applications
License: MIT License
Requires Python: >=3.10

# chat-object

[![doctest coverage](https://img.shields.io/badge/doctest-90%25_coverage-00796b)](https://gist.github.com/fresh-milkshake/48a14bcc9c753a99d0af6935eb96e056)
[![license](https://img.shields.io/badge/license-MIT-blue)](LICENSE.txt)
![python](https://img.shields.io/badge/python-3.10%2B-306998)
[![version](https://img.shields.io/pypi/v/chat-object?color=white&label=version)](https://pypi.org/project/chat-object/)
[![PyPI Downloads](https://static.pepy.tech/badge/chat-object?color=6c757d)](https://pepy.tech/projects/chat-object)

A simple library for creating and managing chat objects and messages for LLM applications.

## Installation

From PyPI:

```bash
pip install chat-object
```

From GitHub:

```bash
pip install git+https://github.com/fresh-milkshake/chat-object.git
```

Or from source:

```bash
git clone https://github.com/fresh-milkshake/chat-object.git
cd chat-object
pip install -e .
```

## Quick Start

### Basic Chat Usage

Create a chat object and add messages to it:

```python
import openai
from chat_object import Chat, Message, Role

client = openai.OpenAI()

chat = Chat(
    Message(Role.System, "You are a helpful assistant"),
    Message(Role.User, "Hello!")
)

response = client.chat.completions.create(
    model="gpt-5-nano",
    messages=chat.as_dict()
)

print(response.choices[0].message.content)
```

### Using the Prompt Class

The `Prompt` class automatically handles indentation and formatting:

```python
from chat_object import Prompt

# Clean indentation automatically
prompt = Prompt("""
    You are a helpful assistant.
    Please help me with the following task:
    
    def example_function():
        return "hello world"
    
    Explain what this function does.
""")

# Multiple arguments are joined with newlines
prompt = Prompt(
    "You are a helpful assistant.",
    "Please be concise in your responses.",
    "Focus on practical solutions."
)

# String operations work naturally
prompt += "\n\nAdditional context here"
```

### QOL Features for Quick Development

Use convenience functions for faster development:

```python
from chat_object import chat, msg_user, msg_system, msg_assistant, prmt

# Quick chat creation
chat_obj = chat(
    msg_system("You are a helpful assistant."),
    msg_user("Hello!"),
    msg_assistant("Hi there! How can I help you today?")
)

# Quick prompt creation
prompt = prmt("You are a helpful assistant.")

# Convert to dict for API calls
messages = chat_obj.as_dict()
```

> [!TIP]
> See [examples](examples) folder for more comprehensive examples.

## Features

- **Well-tested code**: Comprehensive test coverage with doctests throughout the codebase ([90% coverage](https://gist.github.com/fresh-milkshake/48a14bcc9c753a99d0af6935eb96e056))
- **Type safety**: Full type hints and enum-based roles
- **Backward compatibility**: seamless integration with existing APIs like OpenAI, Anthropic, Together, Ollama, etc.
- **QOL features**: Quick and easy message creation with `msg_user`, `msg_assistant`, `msg_system`, `prmt`, `msgs`, `chat` (Recommended, but not required). Pretty rich example usage of qol features is in [examples/openai_use_case.py](examples/openai_use_case.py).

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.