Sentience Core — Cognitive Copilot v1

This project is an advanced scaffold for a multi-agent, memory-enabled, reflexive AI Copilot. It is designed to run on Windows (VSCode) and includes:

• core/brain.py (agent orchestrator)
• core/memory (episodic sqlite + semantic store with Chroma fallback)
• core/reflexion.py (self-evaluation & improvement loop)
• core/tools (safe tool runner, ingestion)
• core/agents (Planner, Researcher, Executor, Critic)
• ui/webui.py (FastAPI web UI)
• ui/voice.py (TTS/STT wrappers)
• models/router.py (model selection / routing)
• main.py (entrypoint to start agents + web UI + repl)
• .env.example and requirements.txt

Important safety: This is a research prototype. Code/shell execution requires confirmation (SAFE_MODE). Do not use with human subjects without proper approvals. Secure your API keys and infrastructure before production use.

Quick start (Windows, PowerShell):

1. unzip sentience-core.zip
2. open folder in VSCode
3. python -m venv venv
4. .\venv\Scripts\activate
5. pip install -r requirements.txt
6. copy .env.example to .env and set OPENAI_API_KEY
7. python main.py

Testing

All code is tested with pytest and must pass flake8 linting. To run tests locally:

# Run all tests
python -m pytest tests/ -v

# Run tests with coverage report
python -m pytest tests/ --cov=core --cov=memory --cov-report=html

# Run linting check
python -m flake8 --max-line-length=120

# Run security check
bandit -r core memory models data

Test Suite:

• 57 unit and integration tests covering core modules
• Tests for BCI tools, neural processing, and memory subsystems
• Mock-based testing to avoid external dependencies

Continuous Integration / Continuous Deployment (CI/CD)

This project uses GitHub Actions for automated testing, linting, and security checks:

Workflows:

• CI Pipeline (ci.yml): Runs on every push and pull request

  • Linting with flake8 (max-line-length=120)
  • Full test suite with coverage reporting
  • Security scanning with bandit
  • Performance profiling (main branch only)

• CodeQL Security Analysis (codeql.yml): Weekly scans + on PRs

  • Automated security vulnerability detection
  • Code quality analysis

Status Badges & Reports:

• Coverage reports are uploaded as build artifacts
• CodeQL results visible in repository security tab
• All builds must pass before merge to main