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-0.3.24-cp313-cp313-win_amd64.whl (3.5 MB view details)

Uploaded CPython 3.13Windows x86-64

fabricatio_core-0.3.24-cp313-cp313-manylinux_2_34_x86_64.whl (3.8 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.34+ x86-64

fabricatio_core-0.3.24-cp313-cp313-manylinux_2_34_aarch64.whl (3.5 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.34+ ARM64

fabricatio_core-0.3.24-cp313-cp313-macosx_11_0_arm64.whl (3.5 MB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

fabricatio_core-0.3.24-cp312-cp312-win_amd64.whl (3.5 MB view details)

Uploaded CPython 3.12Windows x86-64

fabricatio_core-0.3.24-cp312-cp312-manylinux_2_34_x86_64.whl (3.8 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.34+ x86-64

fabricatio_core-0.3.24-cp312-cp312-manylinux_2_34_aarch64.whl (3.5 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.34+ ARM64

fabricatio_core-0.3.24-cp312-cp312-macosx_11_0_arm64.whl (3.5 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

File details

Details for the file fabricatio_core-0.3.24-cp313-cp313-win_amd64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.24-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 2d652148905bfe75f8d8469cd105054cd321f75c16b1ad0a1b615043df99a3a1
MD5 d2a2ea41379cc53da276498fcfeff7e2
BLAKE2b-256 4c0838e8b213902bf266e85bdb6092a4573eb514dccc1e9aa6a19a8b2aa7ce6d

See more details on using hashes here.

File details

Details for the file fabricatio_core-0.3.24-cp313-cp313-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.24-cp313-cp313-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 5057b127079f56b08cff95cc09c512b15176097886aa11c448b942b5bb35ea82
MD5 41c88b32ba96c8589de53001bda19531
BLAKE2b-256 ff745d0490349ea21bfd1ff7cbb81852782f69cf8c5c7792eabfc271d20450e7

See more details on using hashes here.

File details

Details for the file fabricatio_core-0.3.24-cp313-cp313-manylinux_2_34_aarch64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.24-cp313-cp313-manylinux_2_34_aarch64.whl
Algorithm Hash digest
SHA256 2374c92b757f71aef21feadeaa3dec1a36799c6deef25755ae0a2e05a1873b79
MD5 70bbc1d2bbeab8c43d2b51e36b73d17d
BLAKE2b-256 b4805c56d187a9e3e9720f3075c429540a4964e61f618a68d5c6449f87d36665

See more details on using hashes here.

File details

Details for the file fabricatio_core-0.3.24-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.24-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 652f67bc1b04ecc137c17a1aa15f4520f6120b6c1a54a0e83c6be0489b62cde4
MD5 de90f989fe232ca9a4896559a861a51d
BLAKE2b-256 8380904518d1fc803fdbd38cadc229a14f2a4ac9f9ecaeadd1593679ede792ff

See more details on using hashes here.

File details

Details for the file fabricatio_core-0.3.24-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.24-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 e2a26d14c9895560e4eba7039b494ae5195d103a117b93179277e156993111cb
MD5 3c32be380eba63ae0f2cd508eb35e93c
BLAKE2b-256 01c69e6eb43bc50ec68dc51bd2af8eed72b454a8fdb044a34125feb27a6d2e04

See more details on using hashes here.

File details

Details for the file fabricatio_core-0.3.24-cp312-cp312-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.24-cp312-cp312-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 85dde92274724ee976e31de9122231c0f2386f7e1468dfa7dc7422fcc7c604eb
MD5 d71b18129cb7609808c26b797b6da6b3
BLAKE2b-256 bc7d62c779b3bf797baefb4def0c896f652bb10c69d1233ce3fc019bf589a79f

See more details on using hashes here.

File details

Details for the file fabricatio_core-0.3.24-cp312-cp312-manylinux_2_34_aarch64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.24-cp312-cp312-manylinux_2_34_aarch64.whl
Algorithm Hash digest
SHA256 b3b64529c25573194e51c5d6d032bd71b5ef5230c257f4fac64986137e95ce3d
MD5 0077b54e2b4e092277b6fadc3f4c563c
BLAKE2b-256 bf94b0632fc28ff7b2733ec09767d1d2021233b78dd8503dc6e6d56186adb3f3

See more details on using hashes here.

File details

Details for the file fabricatio_core-0.3.24-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for fabricatio_core-0.3.24-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 59a62c603a60835baa47be813f55672db5572e76034241edc9e87a2088aa7eaa
MD5 ebfd3897f16b9309f769522803a32529
BLAKE2b-256 98f82f8b45338f44cc453b62579bfe0dce0fa46c08d52dd79ffdad4c0c379bfe

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