FAKR: Fractal Agent Kernel Runtime

A self-learning AI runtime that turns conversations into reusable knowledge.

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What It Does

FAKR is a local-first AI runtime that:

• Tracks design sessions with an LLM across multiple conversations
• Automatically extracts skills (code patterns) and reasoning patterns (thinking styles)
• Builds a growing memory layer that improves over time
• Runs entirely locally with AnythingLLM (multi-agent in the future with Ollama integration)

Think of it as session memory for AI pair programming — instead of starting from scratch every time, FAKR remembers what worked before.

Installation

# 1. Clone the repo
git clone https://github.com/LogoASeguir/fakr-cli-framework
cd fakr-cli-framework

# 2. Install dependencies
pip install -r requirements.txt

3. Configuration

Open runtime/model_client.py and edit lines 11-13 with your AnythingLLM settings:

API_BASE_URL = "http://localhost:3001/api/v1"
API_KEY = "your-api-key-here"
WORKSPACE_SLUG = "your-workspace-name"

Run

python main.py

Basic Workflow

-Hello! Help me build a calculator       # Start a new design
-Instructions                            # Start the conversation
-[... work through the design ...]       # Iterate on the problem
-:freeze calculator_v1                   # Save session to memory
-:skills                                 # View learned skills
-:new                                    # Start fresh — FAKR recalls past skills

CLI Commands

:freeze [label]	                         # Save current session to memory
:new	                                 # Start a new design session
:skills	                                 # List learned skills
:skill_show <id>	                     # View skill details
:patterns	                             # List reasoning patterns
:pattern_show <id>	                     # View pattern template
:mpm [n]	                             # View last n memory moments
:embryo	                                 # Check self-tuning state
:help	                                 # Full command list

Architecture

FAKR is organized into five layers:

---------------------------------------------------------------
Runtime (interaction loop + clocks)
ModelClient (LLM routing layer)
Memory System (MPM, SkillStore, PatternStore, ContractStore)
Temporal Control (ClockState)
Self-Modulation Core (EmbryoCore)
---------------------------------------------------------------
Runtime (interaction loop + clocks)
    ↓
ModelClient (AnythingLLM wrapper)
    ↓
Memory (Skills / Patterns / MPM / Contracts)
    ↓
EmbryoCore (self-modulation)

The system is modular and designed for experimentation rather than production deployment.

Project Status

FAKR is experimental and under active architectural refinement.

It is not a production system.
It is a research-oriented runtime exploring structured AI interaction patterns.
It is still under development.

Roadmap

Multi-model backend (Ollama integration)
                    ↓
Embryo meta-learning (remember why things worked)
                    ↓
Automatic skill recall (use learned skills without prompting)
                    ↓
Structured <think> block parsing for visible reasoning
                    ↓
MPM-based long-term memory consolidation

Philosophy

This project was built with the assistance of AI tools as development accelerators. The goal was not model supremacy, but architectural exploration — understanding how structured runtime layers can augment LLM interaction in a transparent, controllable way.

Author

Built by [Renato Pedrosa]

Part of a growing ecosystem of personal tools.