ZAI Genesis

Market-cycle and natural-pattern research terminal.

ZAI Genesis is a Python-based research system for exploring market behavior through historical cycles, technical structures, sentiment conditions, and nature-inspired pattern models.

Built by Anteroom Studio as part of its research systems and intelligence tooling.

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Overview

Most market tools focus on price charts or headline streams. ZAI Genesis is designed to study a wider set of market-cycle signals: Fibonacci levels, Elliott-wave structure, long-cycle economic phases, solar-cycle context, lunar timing, seasonality, volatility psychology, and live market conditions.

It helps explore questions such as:

• Which market-cycle signals are currently aligned?
• How strong is the current agreement across independent models?
• What time horizons appear most consistent with the current setup?
• Which conditions should researchers monitor next?
• How do technical, seasonal, and sentiment patterns compare?

This is a research tool, not a trading signal service.

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Core Capabilities

• Live market data collection
• Fibonacci-level analysis
• Elliott-wave structure checks
• Long-cycle market phase modeling
• Solar-cycle and lunar-cycle context
• Seasonal tendency analysis
• Volatility and fear/greed interpretation
• Nature Agreement Score calculation
• Local or API-assisted summary generation
• Terminal dashboard rendering
• Local storage for downloaded data and snapshots

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Quick Start

Install dependencies:

pip install -r requirements.txt

Create local environment settings:

cp .env.example .env

Optional keys can be added to .env:

GROQ_KEY=
GEMINI_KEY=
ANTHROPIC_KEY=
DATA_PATH=./genesis_data

Run the terminal:

python3 zai_genesis.py

The launcher filename is retained for continuity. It can be renamed after repository migration.

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AI Modes

The system can run without external API keys using rule-based logic. Optional keys or local models can be added later for richer summaries.

Setup	Mode	Notes
No keys	Rule-based logic	Default fallback
Ollama available	Local model	Runs locally where supported
API key configured	Hosted model	Uses available provider settings

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System Architecture

ZAI Genesis
├── zai_genesis.py       Main CLI entry point
├── config.py            Runtime settings and environment loading
├── hardware_detector.py Hardware and local-model detection
├── data_collector.py    Market and historical data collection
├── nature_engine.py     Cycle and pattern engines
├── genesis_brain.py     Rule/model-assisted research summary
├── dashboard.py         Terminal dashboard renderer
└── .env.example         Safe local configuration template

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Safety and Scope

ZAI Genesis is intended for research, education, and internal experimentation. Its outputs may be incomplete, stale, or incorrect depending on data-source availability, model behavior, API limits, and market conditions.

This project does not provide financial, investment, legal, or professional advice. Always verify outputs independently before using them in any real-world decision.

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Studio

Anteroom Studio
Research systems, intelligence interfaces, and experimental software.

Research and implementation by ZAI (Zawwar Sami).