Skip to main content

A foundational Python library providing core components for building LLM-driven applications using an event-based agent structure.

Project description

fabricatio-core

A foundational Python library providing core components for building LLM-driven applications using an event-based agent structure.

📦 Installation

This package is part of the fabricatio monorepo and is available as a single package:

pip install fabricatio

🔍 Overview

Provides essential tools for:

  • Event-based architecture patterns The event-based architecture patterns in this library enable a reactive programming model. Events are used to trigger actions and communicate between different components of the application. For example, when a certain condition is met, an event can be emitted, and other parts of the application can listen for this event and respond accordingly. This pattern helps in building scalable and modular applications.
  • Role-based agent execution framework The role-based agent execution framework allows for the definition of different roles for agents in the application. Each role has specific permissions and responsibilities, and agents can be assigned to these roles. For example, in a multi - user application, there could be roles like 'admin', 'user', and 'guest', each with different levels of access to resources and functionality.
  • Task scheduling and management The task scheduling and management feature is responsible for organizing and executing tasks in the application. It can handle task dependencies, prioritize tasks, and ensure that tasks are executed in the correct order. For example, in a data processing application, tasks like data ingestion, transformation, and analysis can be scheduled and managed using this framework.
  • File system operations and content detection This feature provides functionality for performing file system operations such as reading, writing, and deleting files. It also includes content detection capabilities, which can identify the type of content in a file, such as text, image, or binary data. For example, it can automatically detect the encoding of a text file or the format of an image file.
  • Logging and diagnostics The logging and diagnostics feature helps in monitoring the application's behavior and troubleshooting issues. It can record important events, errors, and warnings in a log file, which can be used for debugging and auditing purposes. For example, if an error occurs during the execution of a task, the log can provide detailed information about the error, including the stack trace and the values of relevant variables.
  • Template rendering and configuration handling The template rendering and configuration handling feature allows for the use of templates to generate dynamic content and manage application configuration. Templates can be used to generate HTML pages, emails, or other types of documents. Configuration handling ensures that the application can be easily configured with different settings, such as database connections and API keys.
  • Type-safe data models for common entities The type-safe data models for common entities ensure that the data used in the application has a well - defined structure. These models are based on Pydantic, which provides type validation and serialization capabilities. For example, in a user management application, a data model can be defined for the 'User' entity, with attributes like 'name', 'email', and 'password', and Pydantic can be used to validate the input data and ensure that it conforms to the defined model.
  • Asynchronous execution utilities The asynchronous execution utilities enable the application to perform tasks asynchronously, which can improve the performance and responsiveness of the application. For example, in a web application, asynchronous I/O operations can be used to handle multiple requests simultaneously without blocking the main thread. This feature uses Python's asyncio library to implement asynchronous programming.

Built on a hybrid Rust/Python foundation for performance-critical operations.

🧩 Key Features

  • Event System: Reactive architecture with event emitters and listeners The event system is the core of the event - based architecture. Event emitters are responsible for generating events, and event listeners are registered to listen for specific events. When an event is emitted, all the registered listeners are notified, and they can perform their respective actions. For example, in a game application, an event emitter can be used to emit an event when a player scores a goal, and event listeners can be used to update the scoreboard and play a sound effect.
  • Role Framework: Agent roles with workflow dispatching capabilities The role framework defines the different roles that agents can have in the application. Each role has a set of permissions and a workflow associated with it. When an agent is assigned a role, the workflow dispatching capabilities ensure that the agent follows the correct sequence of actions. For example, in a project management application, a 'project manager' role may have a workflow that includes tasks like creating a project plan, assigning tasks to team members, and monitoring progress.
  • Task Engine: Status-aware task management with dependencies The task engine is responsible for managing tasks in the application. It keeps track of the status of each task, such as 'pending', 'in progress', or 'completed'. It also handles task dependencies, ensuring that tasks are executed in the correct order. For example, in a software development project, a task to test a module may depend on the completion of the coding task for that module.
  • Toolbox System: Callable tool registry with rich metadata The toolbox system maintains a registry of callable tools in the application. Each tool has rich metadata associated with it, such as its name, description, input parameters, and output format. This metadata can be used to discover and use tools in a more efficient way. For example, in a data analysis application, a tool for calculating statistical measures can be registered in the toolbox, and other parts of the application can use this tool by providing the appropriate input parameters.
  • Type Models: Pydantic-based models for consistent data structures The type models are based on Pydantic, which provides a way to define and validate data structures. These models ensure that the data used in the application is consistent and conforms to the defined schema. For example, in a financial application, a type model can be used to define the structure of a transaction, including attributes like 'amount', 'date', and 'description', and Pydantic can be used to validate the input data and ensure that it is in the correct format.
  • File Utilities: Smart file operations with content type detection The file utilities provide a set of functions for performing file system operations. They include features like content type detection, which can automatically identify the type of content in a file. This can be useful for handling different types of files in a more intelligent way. For example, when reading a file, the file utilities can determine if it is a text file or a binary file and handle it accordingly.
  • Template Engine: Handlebars-based template rendering system The template engine uses the Handlebars library to render templates. Templates are used to generate dynamic content by replacing placeholders with actual values. For example, in a web application, a template can be used to generate HTML pages with dynamic content like user names and product information. The Handlebars syntax allows for easy customization and reuse of templates.
  • Language Tools: Language detection and text processing utilities The language tools provide capabilities for detecting the language of a text and performing text processing tasks. Language detection can be used to determine the language of a user - input text, which can be useful for providing language - specific services. Text processing utilities include functions for tasks like tokenization, stemming, and part - of - speech tagging, which can be used for natural language processing applications.

📁 Structure

fabricatio-core/
├── capabilities/     - Core capability definitions
├── decorators.py     - Common function decorators
├── emitter.py        - Event emission and handling
├── fs/               - File system operations
├── journal.py        - Logging infrastructure
├── models/           - Core data models
│   ├── action.py     - Action base classes
│   ├── generic.py    - Base traits (Named, Described, etc.)
│   ├── role.py       - Role definitions
│   ├── task.py       - Task abstractions
│   └── tool.py       - Tool interfaces
├── parser.py         - Text parsing utilities
├── rust.pyi          - Rust extension interfaces
├── utils.py          - General utility functions
└── __init__.py       - Package entry point

📄 License

MIT – see LICENSE

GitHub: github.com/Whth/fabricatio

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

fabricatio_core-0.3.1-cp313-cp313-win_amd64.whl (2.4 MB view details)

Uploaded CPython 3.13Windows x86-64

fabricatio_core-0.3.1-cp313-cp313-manylinux_2_34_x86_64.whl (15.7 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.34+ x86-64

fabricatio_core-0.3.1-cp312-cp312-win_amd64.whl (2.4 MB view details)

Uploaded CPython 3.12Windows x86-64

fabricatio_core-0.3.1-cp312-cp312-manylinux_2_34_x86_64.whl (15.7 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.34+ x86-64

File details

Details for the file fabricatio_core-0.3.1-cp313-cp313-win_amd64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.1-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 e4366befc92a1dddd1a0dc2ee1ba3b0ca962a96e157f2c42c7f9911660e8bd90
MD5 aa302cca96573be260e2334571ca4441
BLAKE2b-256 450efb65654a67e02b790c06ee0ec01eb17b26ab5d79ebabbab155f35b2ac9ce

See more details on using hashes here.

File details

Details for the file fabricatio_core-0.3.1-cp313-cp313-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.1-cp313-cp313-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 46e7bb8d415fa35a1e3f642d31ee4a1c7ba11e30cd7902c547e1f8bcb079d155
MD5 b92fa938d4805c9b7e8089ea860394af
BLAKE2b-256 c5ab87cbfeb8c698adcac86fd275b856ae3ee7a10fc0739d0882d6d509a4021f

See more details on using hashes here.

File details

Details for the file fabricatio_core-0.3.1-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.1-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 b0ca8771a51f0139a8e45859cb0fb857122c776c1e3ec8128ba40e6e205daa53
MD5 43be700e91755ace66347649648f34a7
BLAKE2b-256 5c88a60e22f93db5eca2ddd6b952b81599720e776f2d1e47e01b9bd3c27ef57d

See more details on using hashes here.

File details

Details for the file fabricatio_core-0.3.1-cp312-cp312-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.1-cp312-cp312-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 7408f908d86f2f2fc8f0e2646ce88936b2dd05763d3734abe3029feaca60021d
MD5 78faf77dd502fa22e4288ca2dd3f609c
BLAKE2b-256 f3f3589cd062c2ac2d1996631c43a091521d701922ba1ddeff205e522f4485cd

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page