The Minimum Viable System (MVS) demonstrates the core mechanics of KBC and the KnowledgeChain. It currently consists of a local FastAPI backend with a SQLite database and a Streamlit frontend for interacting with users.

Components

• K‑Chain database – Stores knowledge blocks (“neurons”) with statements, tags, certainty levels and explicit links to related blocks.
• Users & Ledger – Keeps track of user profiles and their KBC balances. Each time a validated knowledge block is added, the contributor’s balance increases.
• Validator & Oracle placeholders – Validation logic is rudimentary in v2.1: blocks are marked as pending; future iterations will integrate Oracle AI and Proof‑of‑Knowledge【599027023887502†L175-L181】.
• Teodora AI (Y‑Engine) – A planned module that will assist in knowledge validation, synthesis and KBC assignment.

How to run locally

1. Install Python 3.8+ and clone the repository (or use the KBC folder in this site’s source).

2. Create a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate
   pip install -r requirements.txt
   

3. Initialize the database:

   python init_db.py
   

4. Start the backend and frontend:

   uvicorn main:app --reload
   streamlit run app.py
   

5. Open your browser to the Streamlit URL (default is http://localhost:8501) and start adding knowledge.

The current MVS is a local prototype; in the future it will become a decentralized network of validators and AI agents【599027023887502†L191-L198】.

For source code and ongoing development, see the KBC directory in this repository.