Skip to main content

A dialectical framework for augmented intelligence. AI reasoning powered with dialectics supports humans in: system optimization (psychology, engineering, business, politics, etc.); dispute resolution (mediation, conflicts, negotiations, etc.); decision-making (dilemmas, challenging situations, win-win, etc.).

Project description

Dialectical Framework

Turn stories, strategies, or systems into insight. Auto-generate Dialectical Wheels (DWs) from any text to reveal blind spots, surface polarities, and trace dynamic paths toward synthesis. DWs are semantic maps that expose tension, transformation, and coherence within a system—whether narrative, ethical, organizational, or technological.

What It Does:

  • Converts natural language into Dialectical Wheels (DWs)
  • Highlights thesis–antithesis tensions and feedback loops
  • Reveals overlooked leverage points and systemic blind-spots
  • Maps decisions, ethics, or mindsets across dialectical structures

Built for:

  • Systems optimization
  • Wisdom mining & decision diagnostics
  • Augmented intelligence / narrative AI
  • Ethical modeling & polarity navigation

Useful for:

  • Consultants, coaches, facilitators, and system designers
  • Storytellers, educators, and regenerative thinkers
  • Strategists, SDD/BIMA practitioners, values-driven innovators

Learn more:

Development

Contributors Welcome!

We invite developers, philosophers, cognitive scientists, and regenerative ecosystem builders to co-create with us.

Setup

Behind the scenes we heavily rely on Mirascope

Environment Variables

Variable Name Description Example Value
DIALEXITY_DEFAULT_MODEL Default model name for the framework gpt-4
DIALEXITY_DEFAULT_MODEL_PROVIDER Model provider (required) openai

You can store these in a .env file or export them in your environment.

These will specify the default "brain" for your reasoning.

Architecture

At the core of the dialectical framework is a dialectical wheel. It is a fancy semantic graph where nodes are statements or concepts and edges are relationships such as "opposite of," "complementary to," etc. To make the graph more readable, it's depicted as a 2D wheel.

Simple More Complicated
Dialectical Wheel Diagram Dialectical Wheel Diagram

The main architectural parts are:

  • Wheel
  • Wheel Segment
  • Wisdom Unit
  • Dialectical Component
  • Transition

Wheel is composed of segments. Think of a dialectical wheel as a pizza, a segment is a slice of pizza. In the simplest case it represents some thesis (a statement, a concept, an action, a thought, an idea, etc.). A thesis can have positive and negative things related to it. Hence, a segment of a wheel is composed of these dialectical components: a thesis (T), positive side of that thesis (T+) and a negative side of that thesis (T-). In more detailed wheels, a segment could have more than 3 layers.

If we take two opposite segments, we get the basic (and the most important) structure: Wisdom Unit (half-wheel, verified by diagonal constraints: control statements). It's composed of:

Dialectical Component Description
T- Negative side of the main thesis
T The thesis
T+ Positive side of the main thesis
A+ Positive side of the antithesis
A The antithesis
A- Negative side of the antithesis

In a Wheel, segments next to each other are related. We wrap that relationship into a Transition. Practically, a Transition is a recipe for how to go from one segment to another in a way that we approach synthesis. Essentially, it shows how the negative side of a given thesis (Tn-) converts into the positive side of the following thesis (T(n+1)+). If we were to look at a wheel as a sliced pizza, the lines that separate the slices would be Transitions.

If we derive Transitions in a Wheel with only 2 segments (aka half-wheel), they are symmetrical and represent a special kind of Wisdom Unit, we call it Action (Ac) and Reflection (Re). As any Wisdom Unit, Action and Reflection must be verified by diagonal constraints as well.

Prototyping & App Ideas

Simple Win-Win Finder

Win-Win Finder

Eye-Opener

Working beta product Eye Opener. It's a tool that analyzes text and generates a visual map of its underlying structure and hidden assumptions. The core feature is a graph-like interface we call the Dialectical Wheel, that shows the delayed dialectical responses ("blind spots").

Argument Inspector

Working beta product Argument Inspector. Useful for analysts and mediators/facilitators to deeper understand the case.

Atlas of Feelings

The Atlas of Feelings is the Plutchik's wheel converted into the „vortex“ model, whereby the most gentle emotions are inside of the wheel, whereas the rudest are outside. As everything is interconnected with dialectical rules, we can understand human nature better.

"Spiral" Lila game

In this blog post we explain how the ancient Lila (Leela) game has been elevated to a new level.

Project details


Download files

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

Source Distribution

dialectical_framework-0.6.2.tar.gz (69.5 kB view details)

Uploaded Source

Built Distribution

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

dialectical_framework-0.6.2-py3-none-any.whl (104.4 kB view details)

Uploaded Python 3

File details

Details for the file dialectical_framework-0.6.2.tar.gz.

File metadata

  • Download URL: dialectical_framework-0.6.2.tar.gz
  • Upload date:
  • Size: 69.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.4 CPython/3.11.8 Darwin/24.6.0

File hashes

Hashes for dialectical_framework-0.6.2.tar.gz
Algorithm Hash digest
SHA256 e61db359b26341cdf9a6eb7de3b6a3197a2017cdec7b9a81e8a5c4664634fd53
MD5 73d842ba101e1d1d196f3aca0d746fc8
BLAKE2b-256 d4065e66c253e9c897e2adc2cd006c0bc4a64a501e3c1445d95200ebc843de28

See more details on using hashes here.

File details

Details for the file dialectical_framework-0.6.2-py3-none-any.whl.

File metadata

File hashes

Hashes for dialectical_framework-0.6.2-py3-none-any.whl
Algorithm Hash digest
SHA256 f87ab2832d7151e7c02ded347b765c4032d82263214f64b559da0edeea83f35a
MD5 46ce33aeab5a5b14c886a2808a62c54b
BLAKE2b-256 e80275a38d69cbd800ed23b7be710c5f6f1397432a6c7170cce3e88fec29c271

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