Metadata-Version: 2.4
Name: literun
Version: 0.3.0
Summary: A Minimal agent runtime built on OpenAI Responses API
Project-URL: Homepage, https://github.com/kaustubh-tr/literun
Project-URL: Source, https://github.com/kaustubh-tr/literun
Project-URL: Issues, https://github.com/kaustubh-tr/literun/issues
Project-URL: Readme, https://github.com/kaustubh-tr/literun#readme
Project-URL: Documentation, https://github.com/kaustubh-tr/literun/blob/main/DOCS.md
Author-email: Kaustubh Trivedi <trivedikaustubh01@gmail.com>
License: MIT License
        
        Copyright (c) 2026 Kaustubh Trivedi
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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        SOFTWARE.
License-File: LICENSE
Requires-Python: <4.0.0,>=3.10.0
Requires-Dist: openai<3.0.0,>=2.11.0
Requires-Dist: pydantic<3.0.0,>=2.12.0
Provides-Extra: dev
Requires-Dist: pytest<10.0.0,>=9.0.0; extra == 'dev'
Description-Content-Type: text/markdown

# LiteRun 🚀

[![PyPI - Version](https://img.shields.io/pypi/v/literun)](https://pypi.org/project/literun/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/literun)](https://pypi.org/project/literun/)
[![PyPI - License](https://img.shields.io/pypi/l/literun)](https://opensource.org/licenses/MIT)
[![Documentation](https://img.shields.io/badge/docs-DOCS-blue)](https://github.com/kaustubh-tr/literun/blob/main/DOCS.md)

A lightweight, production-grade Python framework for building predictable, multi-turn AI agents. LiteRun standardizes the chaotic mechanics of modern LLM APIs (like tool-loop continuation, JSON stream assembly, and token accounting) while giving you absolute control over execution and state.

*Currently supports **OpenAI Responses API**.*

## Key Features

- **Standardized Execution**: A symmetric API for `run()`, `arun()`, `stream()`, and `astream()` with normalized result/event schemas for supported provider behavior.
- **Structured Tooling Runtime**: Pydantic-powered schema generation, execution routing, and output validation.
- **Secure Context Injection**: Safely pass ephemeral app state (like DB connections or Tenant IDs) into tools via `ToolRuntime` without exposing it to the LLM.
- **OpenAI-Focused Token Accounting**: Exposes explicit `cached_read`, `reasoning`, and standard token buckets when usage data is available.
- **Canonical Prompting**: A strictly typed `PromptTemplate` builder that enforces message invariants before network execution.

## Requirements

- Python 3.10+

> **Note**: Core dependencies like `openai` and `pydantic` are automatically installed when you install `literun`.

## Installation

Install `literun` directly from PyPI. 

```bash
pip install literun
```

Set your API key in your environment:

```bash
export OPENAI_API_KEY="sk-proj-..."
```

## Quick Start

Here is a simple example demonstrating how to initialize an Agent, register a Tool using Pydantic schemas, and execute a synchronous run.

```python
from literun import Agent, ChatOpenAI, Tool
from pydantic import BaseModel, Field

# 1. Define the tool's input schema for strict validation
class WeatherInput(BaseModel):
    location: str = Field(description="The city and state, e.g. San Francisco, CA")
    unit: str = Field(default="celsius", description="The unit of temperature")

# 2. Define the Python logic
def get_weather(location: str, unit: str = "celsius") -> str:
    return f"The weather in {location} is 22 degrees {unit}."

# 3. Wrap it in a LiteRun Tool
weather_tool = Tool(
    func=get_weather,
    name="get_weather",
    description="Get the current weather for a specific location.",
    input_schema=WeatherInput,
    strict=True # Enforces stricter OpenAI schema adherence (model/provider dependent)
)

# 4. Initialize the Agent Orchestrator
agent = Agent(
    llm=ChatOpenAI(model="gpt-5-nano"),
    system_instruction="You are a helpful and concise weather assistant.",
    tools=[weather_tool],
)

# 5. Execute the Run
result = agent.run("What is the weather in Tokyo?")

print(f"Response: {result.output}")
print(f"Usage: {result.token_usage}")
print(f"Execution Time: {result.timing.duration:.2f}s")

```

### Advanced Usage & Examples

LiteRun supports sync/async execution in both non-streaming and streaming modes, plus runtime context injection and direct LLM client usage.

👉 Check out the [Documentation](https://github.com/kaustubh-tr/literun/blob/main/DOCS.md) and [Examples](https://github.com/kaustubh-tr/literun/blob/main/examples/) for more details.

## Testing

This project uses `pytest` as the primary test runner, but supports `unittest` as well.

```bash
# Run all tests
python -m pytest
```

or using unittest:

```bash
python -m unittest discover tests
```

> **Note**: Some integration tests may require the `OPENAI_API_KEY` environment variable. They are automatically skipped if it is missing.

## License

Copyright (c) 2026 Kaustubh Trivedi.

Distributed under the terms of the [MIT](https://github.com/kaustubh-tr/literun/blob/main/LICENSE) license, LiteRun is free and open source software.
