Metadata-Version: 2.4
Name: ConsciousnessAI
Version: 0.0.1
Summary: A theory-grounded architecture for evaluating consciousness-relevant indicators in AI systems. Does NOT claim system consciousness.
Author: Rohan R
License: MIT
Keywords: consciousness,ai-safety,cognitive-architecture,global-workspace,integrated-information,eeg,bci,neuroadaptive,subject-emulation,plant-biohybrid
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pydantic>=2.0
Requires-Dist: numpy>=1.24
Requires-Dist: networkx>=3.0
Requires-Dist: typer>=0.9
Requires-Dist: rich>=13.0
Requires-Dist: PyYAML>=6.0
Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == "dev"
Requires-Dist: pytest-cov>=4.0; extra == "dev"
Requires-Dist: ruff>=0.1; extra == "dev"
Requires-Dist: mypy>=1.5; extra == "dev"
Requires-Dist: black>=23.0; extra == "dev"
Provides-Extra: neuro
Requires-Dist: scipy>=1.10; extra == "neuro"
Provides-Extra: plant
Requires-Dist: pyserial>=3.5; extra == "plant"
Provides-Extra: llm
Requires-Dist: openai>=1.0; extra == "llm"
Requires-Dist: anthropic>=0.34; extra == "llm"
Requires-Dist: google-generativeai>=0.8; extra == "llm"
Provides-Extra: local-llm
Requires-Dist: transformers>=4.40; extra == "local-llm"
Requires-Dist: torch>=2.2; extra == "local-llm"
Dynamic: license-file

# Consciousness-Indicator Architecture (CIA)

> Scientific boundary: CIA measures theory-derived consciousness indicators and does not prove subjective experience, sentience, or phenomenal consciousness.

## What this package is

CIA is a research-oriented Python package for evaluating consciousness-relevant architectural indicators in AI systems. It implements a modular cognitive simulation pipeline and produces structured scorecards on a 0-22 indicator scale.

This package is intended for AI safety research, computational cognitive science, and philosophy of mind workflows where transparent, testable proxy metrics are required.

## Core capabilities

- 11 indicator categories grounded in established consciousness theories
- End-to-end cognitive cycle simulation
- Scorecard generation with risk-tier summaries
- Causal intervention harness for ablation-style experiments
- Governance and report-verification tools
- Optional LLM adapter layer (remote and local)
- Optional EEG/BCI neuroadaptive extension
- Optional plant biohybrid extension

## Installation

### From PyPI

```bash
pip install ConsciousnessAI
```

### With extras

```bash
pip install "ConsciousnessAI[dev]"
pip install "ConsciousnessAI[dev,neuro,plant,llm,local-llm]"
```

### Python requirement

- Python 3.11+

## Command-line quickstart

```bash
cia run "A red object moved behind a screen and reappeared."
cia run "The system noticed its own processing limits." --verbose
cia score --input your_input.json
cia intervene --type disable_workspace
```

## Python API quickstart

```python
from cia.simulation import CombinedConsciousnessIndicatorSystem

system = CombinedConsciousnessIndicatorSystem(recurrent_cycles=3)
report = system.run_cycle("The agent reflected on its own uncertainty.")

print(report.indicator_scores.total_score, report.indicator_scores.max_possible)
print(report.welfare_state.risk_level)
```

## Optional integrations

### LLM

- Providers: OpenAI, Claude, Gemini, Hugging Face, llama.cpp, vLLM
- Config-driven adapter loading

### Neuroadaptive EEG/BCI

- Offline ingestion and preprocessing
- Feature extraction and proxy-state conditioning

Boundary: EEG features are statistical proxies and do not read thoughts or infer subjective experience.

### Plant biohybrid

- Non-invasive plant electrophysiology ingestion
- Signal-feature conditioning of CIA runtime controls

Boundary: plant signals are physiological proxies and not evidence of plant consciousness.

## Documentation and reports

- Full documentation site: https://rotsl.github.io/cia/
- Full project documentation: docs directory in repository
- Validation and demo outputs: reports directory in repository
- Citation metadata: CITATION.cff

For full usage, benchmarks, governance policy, and scientific caveats, see the repository documentation site built with MkDocs.

## License

MIT License
