fabricatio


Namefabricatio JSON
Version 0.17.0 PyPI version JSON
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home_pageNone
SummaryA LLM multi-agent framework.
upload_time2025-07-11 09:33:51
maintainerNone
docs_urlNone
authorNone
requires_python<3.14,>=3.12
licenseNone
keywords ai agents multi-agent llm pyo3
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage
            <p align="center">   
<picture>
        <img src="./assets/band.png" width="80%" alt="Fabricatio Logo" loading="lazy">
</picture>
</p>



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    <img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="MIT License">
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  <a href="https://pypi.org/project/fabricatio/">
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    <img src="https://static.pepy.tech/badge/fabricatio/week" alt="PyPI Downloads (Week)">
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 <a href="https://fabricatio.readthedocs.io/en/latest/?badge=fabricatio">
    <img src="https://readthedocs.org/projects/fabricatio/badge/?version=latest" alt="Documentation Status">
  </a>
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    <img src="https://github.com/Whth/fabricatio/actions/workflows/build-package.yaml/badge.svg" alt="Build Package">
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</p>




---

## Overview

Fabricatio is a streamlined Python library for building LLM applications using an event-based agent structure. It
leverages Rust for performance-critical tasks, Handlebars for templating, and PyO3 for Python bindings.

## Features

- **Event-Driven Architecture**: Robust task management through an EventEmitter pattern.
- **LLM Integration & Templating**: Seamlessly interact with large language models and dynamic content generation.
- **Async & Extensible**: Fully asynchronous execution with easy extension via custom actions and workflows.

## Installation

```bash
# install fabricatio with full capabilities.
pip install fabricatio[full]

# or with uv

uv add fabricatio[full]


# install fabricatio with only rag and rule capabilities.
pip install fabricatio[rag,rule]

# or with uv

uv add fabricatio[rag,rule]

```


## Usage

### Basic Example

```python
"""Example of a simple hello world program using fabricatio."""

from typing import Any

from fabricatio import Action, Event, Role, Task, WorkFlow, logger


class Hello(Action):
    """Action that says hello."""

    output_key: str = "task_output"

    async def _execute(self, **_) -> Any:
        ret = "Hello fabricatio!"
        logger.info("executing talk action")
        return ret

    """Main function."""


(Role()
 .register_workflow(Event.quick_instantiate("talk"), WorkFlow(name="talk", steps=(Hello,)))
 .dispatch())

assert Task(name="say hello").delegate_blocking("talk") == "Hello fabricatio!"

```

### Examples

For various usage scenarios, refer to the following examples:

- Simple Chat
- Retrieval-Augmented Generation (RAG)
- Article Extraction
- Propose Task
- Code Review
- Write Outline

_(For full example details, please check our detailed documentation, see [Examples](./examples))_

## Configuration

Fabricatio supports flexible configuration through multiple sources, with the following priority order:
`./.env` > `Environment Variables` > `./fabricatio.toml` > `./pyproject.toml` > `<ROMANING>/fabricatio/fabricatio.toml` > `Defaults`.

Below is a unified view of the same configuration expressed in different formats:

### Format Examples: Unified Configuration Representation

#### Environment variables or dotenv file
```dotenv
FABRIK_LLM__API_ENDPOINT=https://api.openai.com
FABRIK_LLM__API_KEY=your_openai_api_key
FABRIK_LLM__TIMEOUT=300
FABRIK_LLM__MAX_RETRIES=3
FABRIK_LLM__MODEL=openai/gpt-3.5-turbo
FABRIK_LLM__TEMPERATURE=1.0
FABRIK_LLM__TOP_P=0.35
FABRIK_LLM__GENERATION_COUNT=1
FABRIK_LLM__STREAM=false
FABRIK_LLM__MAX_TOKENS=8192
FABRIK_DEBUG__LOG_LEVEL=INFO
```

#### `fabricatio.toml` file
```toml
[llm]
api_endpoint = "https://api.openai.com"
api_key = "your_openai_api_key"
timeout = 300
max_retries = 3
model = "openai/gpt-3.5-turbo"
temperature = 1.0
top_p = 0.35
generation_count = 1
stream = false
max_tokens = 8192

[debug]
log_level = "INFO"
```

#### `pyproject.toml` file
```toml
[tool.fabricatio.llm]
api_endpoint = "https://api.openai.com"
api_key = "your_openai_api_key"
timeout = 300
max_retries = 3
model = "openai/gpt-3.5-turbo"
temperature = 1.0
top_p = 0.35
generation_count = 1
stream = false
max_tokens = 8192

[tool.fabricatio.debug]
log_level = "INFO"
```

## Development Setup

1. **Clone the Repository**:
   ```bash
   git clone https://github.com/Whth/fabricatio.git
   cd fabricatio
   ```
2. **Install Dependencies**:
   ```bash
   make init
   ```
   
3. **Build the Package**:
   ```bash
   make dev
   ```
4. **Run Tests**:
   ```bash
   make tests
   ```
   
## Contributing

Contributions are welcome! Follow these steps:

1. Fork the repository.
2. Create your feature branch (`git checkout -b feat/new-feature`).
3. [Optional]Create a py/rs subpackage with `make rs` or `make py` 
4. Commit your changes (`git commit -am 'Add new feature'`).
5. Push to the branch (`git push origin feat/new-feature`).
6. Create a new Pull Request.

## License

Fabricatio is licensed under the MIT License. See [LICENSE](LICENSE) for details.

## Acknowledgments

Special thanks to the contributors and maintainers of:

- [PyO3](https://github.com/PyO3/pyo3)
- [Maturin](https://github.com/PyO3/maturin)
- [Handlebars.rs](https://github.com/sunng87/handlebars-rust)
- [LiteLLM](https://github.com/BerriAI/litellm)


            

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    "description": "<p align=\"center\">   \n<picture>\n        <img src=\"./assets/band.png\" width=\"80%\" alt=\"Fabricatio Logo\" loading=\"lazy\">\n</picture>\n</p>\n\n\n\n<p align=\"center\">\n  <a href=\"LICENSE\">\n    <img src=\"https://img.shields.io/badge/license-MIT-blue.svg\" alt=\"MIT License\">\n  </a>\n  <a href=\"https://pypi.org/project/fabricatio/\">\n    <img src=\"https://img.shields.io/pypi/pyversions/fabricatio\" alt=\"Python Versions\">\n  </a>\n  <a href=\"https://pypi.org/project/fabricatio/\">\n    <img src=\"https://img.shields.io/pypi/v/fabricatio\" alt=\"PyPI Version\">\n  </a>\n  <a href=\"https://deepwiki.com/Whth/fabricatio\">\n    <img src=\"https://deepwiki.com/badge.svg\" alt=\"Ask DeepWiki\">\n  </a>\n  <a href=\"https://pepy.tech/projects/fabricatio\">\n    <img src=\"https://static.pepy.tech/badge/fabricatio/week\" alt=\"PyPI Downloads (Week)\">\n  </a>\n  <a href=\"https://pepy.tech/projects/fabricatio\">\n    <img src=\"https://static.pepy.tech/badge/fabricatio\" alt=\"PyPI Downloads\">\n  </a>\n  <a href=\"https://github.com/PyO3/pyo3\">\n    <img src=\"https://img.shields.io/badge/bindings-pyo3-green\" alt=\"Bindings: PyO3\">\n  </a>\n  <a href=\"https://github.com/BerriAI/litellm\">\n    <img src=\"https://img.shields.io/badge/Powered%20by-LiteLLM-blue\" alt=\"Powered by LiteLLM\">\n  </a>\n  <a href=\"https://github.com/astral-sh/uv\">\n    <img src=\"https://img.shields.io/badge/built%20with-uv%20%2B%20maturin-orange\" alt=\"Build Tool: uv + maturin\">\n  </a>\n\n</p>\n\n\n<p align=\"center\">\n\n <a href=\"https://fabricatio.readthedocs.io/en/latest/?badge=fabricatio\">\n    <img src=\"https://readthedocs.org/projects/fabricatio/badge/?version=latest\" alt=\"Documentation Status\">\n  </a>\n  <a href=\"https://github.com/Whth/fabricatio/actions/workflows/build-package.yaml\">\n    <img src=\"https://github.com/Whth/fabricatio/actions/workflows/build-package.yaml/badge.svg\" alt=\"Build Package\">\n  </a>\n  <a href=\"https://github.com/Whth/fabricatio/actions/workflows/ruff.yaml\">\n    <img src=\"https://github.com/Whth/fabricatio/actions/workflows/ruff.yaml/badge.svg\" alt=\"Ruff Lint\">\n  </a>\n  <a href=\"https://github.com/Whth/fabricatio/actions/workflows/tests.yaml\">\n    <img src=\"https://github.com/Whth/fabricatio/actions/workflows/tests.yaml/badge.svg\" alt=\"Tests\">\n  </a>\n  <a href=\"https://coveralls.io/github/Whth/fabricatio?branch=master\">\n    <img src=\"https://coveralls.io/repos/github/Whth/fabricatio/badge.svg?branch=master\" alt=\"Coverage Status\">\n  </a>\n  <a href=\"https://github.com/Whth/fabricatio/issues\">\n    <img src=\"https://img.shields.io/github/issues/Whth/fabricatio\" alt=\"GitHub Issues\">\n  </a>\n  <a href=\"https://github.com/Whth/fabricatio/pulls\">\n    <img src=\"https://img.shields.io/github/issues-pr/Whth/fabricatio\" alt=\"GitHub Pull Requests\">\n  </a>\n  <a href=\"https://github.com/Whth/fabricatio/stargazers\">\n    <img src=\"https://img.shields.io/github/stars/Whth/fabricatio\" alt=\"GitHub Stars\">\n  </a>\n</p>\n\n\n\n\n---\n\n## Overview\n\nFabricatio is a streamlined Python library for building LLM applications using an event-based agent structure. It\nleverages Rust for performance-critical tasks, Handlebars for templating, and PyO3 for Python bindings.\n\n## Features\n\n- **Event-Driven Architecture**: Robust task management through an EventEmitter pattern.\n- **LLM Integration & Templating**: Seamlessly interact with large language models and dynamic content generation.\n- **Async & Extensible**: Fully asynchronous execution with easy extension via custom actions and workflows.\n\n## Installation\n\n```bash\n# install fabricatio with full capabilities.\npip install fabricatio[full]\n\n# or with uv\n\nuv add fabricatio[full]\n\n\n# install fabricatio with only rag and rule capabilities.\npip install fabricatio[rag,rule]\n\n# or with uv\n\nuv add fabricatio[rag,rule]\n\n```\n\n\n## Usage\n\n### Basic Example\n\n```python\n\"\"\"Example of a simple hello world program using fabricatio.\"\"\"\n\nfrom typing import Any\n\nfrom fabricatio import Action, Event, Role, Task, WorkFlow, logger\n\n\nclass Hello(Action):\n    \"\"\"Action that says hello.\"\"\"\n\n    output_key: str = \"task_output\"\n\n    async def _execute(self, **_) -> Any:\n        ret = \"Hello fabricatio!\"\n        logger.info(\"executing talk action\")\n        return ret\n\n    \"\"\"Main function.\"\"\"\n\n\n(Role()\n .register_workflow(Event.quick_instantiate(\"talk\"), WorkFlow(name=\"talk\", steps=(Hello,)))\n .dispatch())\n\nassert Task(name=\"say hello\").delegate_blocking(\"talk\") == \"Hello fabricatio!\"\n\n```\n\n### Examples\n\nFor various usage scenarios, refer to the following examples:\n\n- Simple Chat\n- Retrieval-Augmented Generation (RAG)\n- Article Extraction\n- Propose Task\n- Code Review\n- Write Outline\n\n_(For full example details, please check our detailed documentation, see [Examples](./examples))_\n\n## Configuration\n\nFabricatio supports flexible configuration through multiple sources, with the following priority order:\n`./.env` > `Environment Variables` > `./fabricatio.toml` > `./pyproject.toml` > `<ROMANING>/fabricatio/fabricatio.toml` > `Defaults`.\n\nBelow is a unified view of the same configuration expressed in different formats:\n\n### Format Examples: Unified Configuration Representation\n\n#### Environment variables or dotenv file\n```dotenv\nFABRIK_LLM__API_ENDPOINT=https://api.openai.com\nFABRIK_LLM__API_KEY=your_openai_api_key\nFABRIK_LLM__TIMEOUT=300\nFABRIK_LLM__MAX_RETRIES=3\nFABRIK_LLM__MODEL=openai/gpt-3.5-turbo\nFABRIK_LLM__TEMPERATURE=1.0\nFABRIK_LLM__TOP_P=0.35\nFABRIK_LLM__GENERATION_COUNT=1\nFABRIK_LLM__STREAM=false\nFABRIK_LLM__MAX_TOKENS=8192\nFABRIK_DEBUG__LOG_LEVEL=INFO\n```\n\n#### `fabricatio.toml` file\n```toml\n[llm]\napi_endpoint = \"https://api.openai.com\"\napi_key = \"your_openai_api_key\"\ntimeout = 300\nmax_retries = 3\nmodel = \"openai/gpt-3.5-turbo\"\ntemperature = 1.0\ntop_p = 0.35\ngeneration_count = 1\nstream = false\nmax_tokens = 8192\n\n[debug]\nlog_level = \"INFO\"\n```\n\n#### `pyproject.toml` file\n```toml\n[tool.fabricatio.llm]\napi_endpoint = \"https://api.openai.com\"\napi_key = \"your_openai_api_key\"\ntimeout = 300\nmax_retries = 3\nmodel = \"openai/gpt-3.5-turbo\"\ntemperature = 1.0\ntop_p = 0.35\ngeneration_count = 1\nstream = false\nmax_tokens = 8192\n\n[tool.fabricatio.debug]\nlog_level = \"INFO\"\n```\n\n## Development Setup\n\n1. **Clone the Repository**:\n   ```bash\n   git clone https://github.com/Whth/fabricatio.git\n   cd fabricatio\n   ```\n2. **Install Dependencies**:\n   ```bash\n   make init\n   ```\n   \n3. **Build the Package**:\n   ```bash\n   make dev\n   ```\n4. **Run Tests**:\n   ```bash\n   make tests\n   ```\n   \n## Contributing\n\nContributions are welcome! 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