A Python package for TRIZ (Theory of Inventive Problem Solving) tools and techniques.
Project description
PyTRIZ
A Python library for applying TRIZ (Theory of Inventive Problem Solving) — look up parameters, principles, and contradiction matrix results, or use LLM-powered agents to analyze engineering trade-offs.
Installation
pip install pytriz
Requires Python 3.12+. LLM features require an API key for your chosen provider (OpenAI, Anthropic, Mistral, or OpenRouter).
Quick start
Data lookups (no API key needed)
from pytriz import contradictions
# Find TRIZ principles for a contradiction
principles = contradictions.get_principles_from_matrix(
improving_parameters=[1, 3],
preserving_parameters=[17, 23],
)
# Search parameters and principles by description
params = contradictions.search_parameters("improves durability", top_k=5)
principles = contradictions.search_principles("segmentation", top_k=5)
LLM-powered analysis
import asyncio
from pytriz import contradictions
result = asyncio.run(
contradictions.analyze_contradiction(
"Increasing blade thickness improves durability but increases weight.",
provider="openai", # or "anthropic", "mistral", "openrouter"
model="gpt-4.1",
)
)
print(result.contradiction)
print(result.improving_parameter)
print(result.preserving_parameter)
Set your API key in a .env file or as an environment variable:
OPENAI_API_KEY=your-key-here
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