Spaces:
Sleeping
A newer version of the Gradio SDK is available:
5.33.0
title: SFOSR
emoji: 🏃
colorFrom: yellow
colorTo: gray
sdk: gradio
sdk_version: 5.24.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: SFOSR System
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
SFOSR: Система Формальной Оценки Смысла и Верификации
This project implements core components of the SFOSR theory, including semantic analysis, contract verification, and proof construction using both input data and a knowledge base.
Project Structure
sfosr_core/
: Contains the main system logic (integrated_sfosr.py
,sfosr_database.py
).tests/
: Contains unit tests (test_*.py
).docs/
: Contains documentation and theoretical papers related to SFOSR.archive/
: Contains archived materials (e.g., old databases).sfosr.db
: The main SQLite database containing concepts, vectors, rules, etc.requirements.txt
: Project dependencies.README.md
: This file.
Installation
(Currently, no external dependencies are required beyond standard Python libraries.)
# It's recommended to use a virtual environment
python -m venv venv
source venv/bin/activate # On Windows use `venv\\Scripts\\activate`
# Install dependencies (if any added later)
pip install -r requirements.txt
Running Tests
To run all tests, execute the following command from the project root directory:
python -m unittest discover tests -v
Current Capabilities
- Analyzes SFOSR structures for syntactic validity.
- Verifies vectors against database concepts and predefined contracts.
- Constructs proofs based on input vectors, prioritizing them first.
- Integrates knowledge from the
sfosr.db
database into the proof process if input vectors are insufficient. - Supports inference rules:
chain_rule
,causality_transfer
,implication_causality_chain
,part_of_transitivity
. - Correctly handles cyclic dependencies in proof paths.
Known Limitations / Future Work
Запуск python integrated_sfosr.py
демонстрирует обработку примера с построением доказательства и выводом оценок достоверности.
Вклад в проект
Приглашаем заинтересованных исследователей и разработчиков присоединиться к развитию SFOSR.
Лицензия
Проект SFOSR распространяется под лицензией MIT.