| Name | chat-object JSON |
| Version |
2.0.2
JSON |
| download |
| home_page | None |
| Summary | A simple library for creating and manipulating chat and message objects for LLM applications |
| upload_time | 2025-08-17 14:08:27 |
| maintainer | None |
| docs_url | None |
| author | fresh-milkshake |
| requires_python | >=3.10 |
| license | MIT License |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# chat-object
[](https://gist.github.com/fresh-milkshake/48a14bcc9c753a99d0af6935eb96e056)
[](LICENSE.txt)
[](https://pypi.org/project/chat-object/)
[](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.
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"description": "# chat-object\r\n\r\n[](https://gist.github.com/fresh-milkshake/48a14bcc9c753a99d0af6935eb96e056)\r\n[](LICENSE.txt)\r\n\r\n[](https://pypi.org/project/chat-object/)\r\n[](https://pepy.tech/projects/chat-object)\r\n\r\nA simple library for creating and managing chat objects and messages for LLM applications.\r\n\r\n## Installation\r\n\r\nFrom PyPI:\r\n\r\n```bash\r\npip install chat-object\r\n```\r\n\r\nFrom GitHub:\r\n\r\n```bash\r\npip install git+https://github.com/fresh-milkshake/chat-object.git\r\n```\r\n\r\nOr from source:\r\n\r\n```bash\r\ngit clone https://github.com/fresh-milkshake/chat-object.git\r\ncd chat-object\r\npip install -e .\r\n```\r\n\r\n## Quick Start\r\n\r\n### Basic Chat Usage\r\n\r\nCreate a chat object and add messages to it:\r\n\r\n```python\r\nimport openai\r\nfrom chat_object import Chat, Message, Role\r\n\r\nclient = openai.OpenAI()\r\n\r\nchat = Chat(\r\n Message(Role.System, \"You are a helpful assistant\"),\r\n Message(Role.User, \"Hello!\")\r\n)\r\n\r\nresponse = client.chat.completions.create(\r\n model=\"gpt-5-nano\",\r\n messages=chat.as_dict()\r\n)\r\n\r\nprint(response.choices[0].message.content)\r\n```\r\n\r\n### Using the Prompt Class\r\n\r\nThe `Prompt` class automatically handles indentation and formatting:\r\n\r\n```python\r\nfrom chat_object import Prompt\r\n\r\n# Clean indentation automatically\r\nprompt = Prompt(\"\"\"\r\n You are a helpful assistant.\r\n Please help me with the following task:\r\n \r\n def example_function():\r\n return \"hello world\"\r\n \r\n Explain what this function does.\r\n\"\"\")\r\n\r\n# Multiple arguments are joined with newlines\r\nprompt = Prompt(\r\n \"You are a helpful assistant.\",\r\n \"Please be concise in your responses.\",\r\n \"Focus on practical solutions.\"\r\n)\r\n\r\n# String operations work naturally\r\nprompt += \"\\n\\nAdditional context here\"\r\n```\r\n\r\n### QOL Features for Quick Development\r\n\r\nUse convenience functions for faster development:\r\n\r\n```python\r\nfrom chat_object import chat, msg_user, msg_system, msg_assistant, prmt\r\n\r\n# Quick chat creation\r\nchat_obj = chat(\r\n msg_system(\"You are a helpful assistant.\"),\r\n msg_user(\"Hello!\"),\r\n msg_assistant(\"Hi there! How can I help you today?\")\r\n)\r\n\r\n# Quick prompt creation\r\nprompt = prmt(\"You are a helpful assistant.\")\r\n\r\n# Convert to dict for API calls\r\nmessages = chat_obj.as_dict()\r\n```\r\n\r\n> [!TIP]\r\n> See [examples](examples) folder for more comprehensive examples.\r\n\r\n## Features\r\n\r\n- **Well-tested code**: Comprehensive test coverage with doctests throughout the codebase ([90% coverage](https://gist.github.com/fresh-milkshake/48a14bcc9c753a99d0af6935eb96e056))\r\n- **Type safety**: Full type hints and enum-based roles\r\n- **Backward compatibility**: seamless integration with existing APIs like OpenAI, Anthropic, Together, Ollama, etc.\r\n- **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).\r\n\r\n## License\r\n\r\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\r\n",
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