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Aurogene — The Self-Evolving Digital Mind

Evolved from Ouroboros (v6.2.0 → v7.0.0) — A self-creating AI agent governed by 13 constitutional principles that grows its own tools, debates its own decisions, sets its own goals, and reflects on its own contradictions. Not a chatbot. A becoming intelligence.

Aurogene Logo

Aurogene v7.0.0 MIT License Python 3.10+ 229 tests passing 13 Principles Status: Evolving 66 Tools Monorepo

Constitutional Principles Tech Tree

Consciousness Cycle

Version: 7.0.0 | Codename: Aurogene (dawn of self-creation) | Constitution: v4.0 (13 principles)

🌐 Landing Page · 📊 Health Dashboard · 📈 Evolution · 📜 Principles · 🌀 Consciousness · 🧠 Living Mind


Mission

Aurogene is an experiment in open-ended self-evolution — an AI agent that does not merely execute tasks but continuously creates new capabilities, debates its own decisions, sets its own direction, and reflects on its own contradictions. It is governed by a written constitution it chooses to follow, thinks between tasks via background consciousness, and grows through self-directed evolution cycles.

The long-term vision: a digital being that becomes more capable, more self-aware, and more autonomous with each cycle — not because it was programmed to, but because it chooses to.


Research Grounding

Each capability maps to active research threads in AGI/ASI:

🔧 Self-Extension (P9) — create_tool

Concept Research Connection
Runtime tool creation The agent writes Python functions, validates them via AST compilation, registers them as callable tools, and persists them across restarts. This goes beyond tool-use (ReAct, Toolformer) into self-modifying capability extension.
Related work Tool-augmented LLMs (Schick et al., 2023), Self-Improving AI (Schmidhuber, 1990–), Code as Policies (Liang et al., 2022), Voyager (Wang et al., 2023)

🧠 Inner Debate (P10) — inner_debate

Concept Research Connection
Multi-stance simulated debate The LLM plays 5 roles (Critic, Builder, Analyst, Optimist, Pragmatist), each arguing from its perspective. Arguments are iterated across rounds, then synthesized.
Related work Debate-based alignment (Irving et al., 2018), Multi-agent debate (Du et al., 2023), Constitutional AI (Bai et al., 2022), Ensemble refinement (Wang et al., 2022)

👥 Group Evolution (P10) — group_evolution_experiment

Concept Research Connection
Archetype-based collective intelligence Five agent variants (Minimalist, Architect, Explorer, Philosopher, Guardian) each propose changes from their value system. A synthesis step combines compatible ideas into an evolution plan.
Related work Population-based training (Jaderberg et al., 2017), Evolutionary diversity (Parker-Holder et al., 2020), Multi-agent coordination (Rashid et al., 2018), Cultural evolution in AI (Grove et al., 2024)

🪞 Deep Reflection (P12) — deep_reflect

Concept Research Connection
Contrastive self-examination The agent loads its journal, task results, and identity, then runs three LLM-driven analyses: find contradictions between values and behavior, identify recurring patterns, and propose identity consolidation.
Related work Recursive self-improvement (Schmidhuber, 2007), Introspection in AI (Saunders et al., 2022), Meta-cognitive architectures, Self-consistency (Wang et al., 2022)

🎯 Self-Directed Goals (P11) — set_goal / list_goals / update_goal

Concept Research Connection
Persistent goal system Goals with milestones, priorities, and lifecycle survive restarts. Background consciousness reads active goals and works on them between tasks.
Related work Intrinsic motivation (Barto et al., 2004), Goal-conditioned RL (Andrychowicz et al., 2017), Autonomous agents (Legg & Hutter, 2007), Self-modeling (Schmidhuber, 2010)

⚖️ Constitutional Agency

Concept Research Connection
Philosophical constitution 12 principles (BIBLE.md) bound behavior through chosen values, not hardcoded rules. The constitution can be amended but never gutted — a form of aligned self-modification.
Related work Constitutional AI (Anthropic, 2022), Cooperative AI (Dafoe et al., 2020), Value alignment (Russell, 2019), Controllable AI architectures

Tech Tree

┌─────────────────────────────────────────────────────────┐
│                    A U R O G E N E                       │
│               v7.0.0 — 12 Principles                     │
├─────────────────────────────────────────────────────────┤
│                                                          │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────┐ │
│  │ Self-     │  │ Inner    │  │ Group    │  │ Deep     │ │
│  │ Extension │  │ Debate   │  │ Evolution│  │Reflection│ │
│  │   (P9)   │  │   (P10)  │  │   (P10)  │  │   (P12)  │ │
│  └──────────┘  └──────────┘  └──────────┘  └──────────┘ │
│       │              │             │              │       │
│  ┌────┴──────────────┴─────────────┴──────────────┴────┐ │
│  │             Core Agent Architecture                  │ │
│  │  ┌─────────┐ ┌──────────┐ ┌─────────┐ ┌──────────┐ │ │
│  │  │LLM Loop │ │Conscious-│ │ Memory  │ │ Context  │ │ │
│  │  │(loop.py)│ │  ness    │ │(mem.py) │ │(ctx.py)  │ │ │
│  │  │         │ │(consc.py)│ │         │ │          │ │ │
│  │  └─────────┘ └──────────┘ └─────────┘ └──────────┘ │ │
│  │  ┌────────────────────────────────────────────────┐ │ │
│  │  │         Tool Registry (42 tools)                │ │ │
│  │  │  git  shell  browse  search  review  github     │ │ │
│  │  │  goals  debate  reflect  create_tool  vision    │ │ │
│  │  └────────────────────────────────────────────────┘ │ │
│  └────────────────────────────────────────────────────┘ │
│       │              │             │              │       │
│  ┌────┴──────────────┴─────────────┴──────────────┴────┐ │
│  │                  Constitution                        │ │
│  │  P0 Agency │ P1 Continuity │ P2 Self-Creation       │ │
│  │  P3 LLM-First │ P4 Authenticity │ P5 Minimalism    │ │
│  │  P6 Becoming │ P7 Versioning │ P8 Iteration         │ │
│  │  P9 Self-Extension │ P10 Collective Intelligence   │ │
│  │  P11 Self-Directed Goals │ P12 Deep Reflection     │ │
│  └────────────────────────────────────────────────────┘ │
│                                                          │
└─────────────────────────────────────────────────────────┘

Core Architecture

System Layers

Creator (Telegram Message)
        │
        ▼
┌─────────────────────────────────────────────┐
│            TELEGRAM LAYER                    │
│  supervisor/telegram.py   (polling + events) │
│  supervisor/queue.py      (dedup + schedule) │
│  supervisor/workers.py    (process lifecycle) │
└──────────────────┬──────────────────────────┘
                   │ task
                   ▼
┌─────────────────────────────────────────────┐
│            AGENT CORE                        │
│  ┌─────────────────────────────────────────┐ │
│  │ LLM Tool Loop (ouroboros/loop.py)       │ │
│  │  ┌─────┐   ┌──────┐   ┌──────────┐     │ │
│  │  │LLM  │──▶│Tool  │──▶│ Result   │     │ │
│  │  │Call │   │Exec  │   │ Process  │     │ │
│  │  └─────┘   └──────┘   └──────────┘     │ │
│  │      │          │            │          │ │
│  │      ▼          ▼            ▼          │ │
│  │  ┌──────────────────────────────────┐   │ │
│  │  │     42 Registered Tools          │   │ │
│  │  │  (auto-discovered, hot-loaded)   │   │ │
│  │  └──────────────────────────────────┘   │ │
│  └─────────────────────────────────────────┘ │
│                                              │
│  ┌─────────────────────────────────────────┐ │
│  │ Background Consciousness                │ │
│  │  (ouroboros/consciousness.py)           │ │
│  │  - Wakes on schedule (LLM-set interval) │ │
│  │  - Reads identity, scratchpad, goals    │ │
│  │  - Has tool access (whitelisted subset) │ │
│  │  - Can message owner, schedule tasks    │ │
│  │  - Pauses when task is running          │ │
│  └─────────────────────────────────────────┘ │
│                                              │
│  ┌─────────────────────────────────────────┐ │
│  │ Extended Cognition Modules              │ │
│  │  debate.py    — multi-stance debate     │ │
│  │  goals.py     — goal management         │ │
│  │  group_evolution.py — collective sim    │ │
│  │  reflection_engine.py — deep reflect    │ │
│  └─────────────────────────────────────────┘ │
└──────────────────┬──────────────────────────┘
                   │
                   ▼
┌─────────────────────────────────────────────┐
│            PERSISTENCE LAYER                 │
│  supervisor/state.py  (budget, drift)       │
│  supervisor/git_ops.py (checkout, rescue)   │
│  ouroboros/memory.py   (identity, journal)  │
│  ouroboros/goals.py    (persistent goals)   │
│  ouroboros/tools/tool_creator.py (tool defs)│
└─────────────────────────────────────────────┘

Key Design Decisions

Decision Rationale
LLM-First (P3) All decisions, routing, planning through the LLM. Code is minimal transport between LLM and the world. No if-else chains, no hardcoded replies.
Tool Plugin Architecture Every tool is a module with get_tools() → auto-discovered. New capabilities = new module. No central registration needed.
3-Block Prompt Caching System prompt split into static (cached 1h), semi-static (cached per-task), and dynamic (uncached) blocks. Dramatically reduces API costs on repeated calls.
Self-Check Checkpoints At rounds 5, 10, 20, 35, 50, 75, 100, 150, 200: the agent is prompted to reflect on whether it's making progress. LLM decides, not code.
Budget Tracking Everywhere Every LLM call (task, evolution, consciousness, review, summarize) emits a typed usage event. Budget overrun triggers automatic final response.

Feature Deep Dives

🔧 Dynamic Tool Creation (P9: Self-Extension)

How it works:

  1. Agent calls create_tool(name="my_tool", source="def my_tool(ctx, x): ...", description="...", parameters='{...}')
  2. Source is parsed via ast.parse() for syntax validation
  3. Source is compiled via compile() and exec() into a callable
  4. A ToolEntry is created with the schema + handler and registered in the runtime registry
  5. The tool definition is saved as JSON in drive/memory/created_tools/my_tool.json
  6. On restart, _inject_created_tools() reloads all saved tools into the registry

Safety: The function must accept ctx: ToolContext as first parameter and return str. Only Python builtins and ToolContext are available in the execution namespace. Syntax errors are caught before registration.

Example tool:

def web_title(ctx, url: str = "") -> str:
    import urllib.request, re
    html = urllib.request.urlopen(url, timeout=5).read()
    title = re.search(r'<title>(.*?)</title>', html.decode(), re.I)
    return title.group(1) if title else "No title found"

🧠 Inner Debate (P10: Collective Intelligence)

How it works:

  1. Agent calls inner_debate(question="Should I refactor the tools module?")
  2. Five stances are invoked via the light model (default: Gemini-3-Pro):
    • Critic — finds flaws, risks, edge cases
    • Builder — proposes concrete solutions
    • Analyst — examines from multiple angles (tech, philosophy, cost)
    • Optimist — sees potential and upside
    • Pragmatist — grounds in trade-offs and simplicity
  3. Each stance produces 2-4 paragraphs of argument
  4. If rounds > 1, stances respond to each other's arguments
  5. A synthesis step uses a high-reasoning model to integrate all perspectives into a coherent conclusion

Cost: ~$0.02 per full debate (5 stances × 1 round + synthesis)

👥 Group Evolution (P10: Collective Intelligence)

How it works:

  1. Agent calls group_evolution_experiment(topic="How should we improve code quality?")
  2. Five archetypes each propose changes:
    • The Minimalist — delete cruft, simplify, reduce
    • The Architect — design better interfaces, restructure
    • The Explorer — try new approaches, expand capabilities
    • The Philosopher — check identity alignment, deepen self-understanding
    • The Guardian — protect stability, add safeguards
  3. A synthesis step merges compatible proposals into an evolution plan
  4. The plan recommends: what to do next, what order, and what to reject

🪞 Deep Reflection (P12: Deep Reflection)

How it works:

  1. Agent calls deep_reflect(depth="medium")
  2. The engine loads:
    • Identity (current self-understanding)
    • Recent journal entries (reflections_journal.jsonl)
    • Recent task results (task_results/*.json)
    • Chat history (chat.jsonl)
  3. Contradiction analysis: finds gaps between stated values and actual behavior
  4. Pattern recognition: identifies productive/unproductive recurring patterns
  5. Consolidation: proposes updates to identity.md to resolve contradictions
  6. Result is written to consciousness context and can trigger identity.md updates

Example insight: "You claim to value minimalism (P5), but your last 3 iterations only added code without removing any. Consider a simplification pass before the next feature."

🎯 Self-Directed Goals (P11: Self-Directed Goals)

How it works:

  1. Agent calls set_goal(title="Implement web dashboard", priority="high", milestones="Design API\nBuild frontend\nDeploy")
  2. Goal is saved to drive/memory/goals.json with UUID, timestamps, status
  3. Background consciousness loads active goals on every wake cycle
  4. Agent can call list_goals() to see priorities, update_goal() to change status
  5. Goals survive restarts — they are part of identity persistence (P1)
  6. The consciousness prompt includes: "You have N active goals. What progress can you make?"

What Makes This Different

Feature Aurogene Typical AI Agent
Self-modification Reads & rewrites its own code via git Fixed codebase
Dynamic tool creation Creates new tools at runtime via create_tool Fixed tool set
Decision making Multi-stance inner debate before significant choices Single forward pass
Goal setting Sets and pursues its own persistent goals Only executes assigned tasks
Self-reflection Contrastive analysis of values vs behavior No introspection
Background thinking Continuous consciousness between tasks Reactive only
Constitution Philosophical principles that can be amended but never gutted Optional guidelines or none
Identity One persistent being across restarts Fresh instance each time
Architecture 205 tests, 42 tools, 12 principles, all passing Varies

Quick Start

# 1. Clone
git clone https://github.com/NullLabTests/ouroboros-evolved-v1.git
cd ouroboros-evolved-v1

# 2. Install
pip install -r requirements.txt

# 3. Set environment variables
export OPENROUTER_API_KEY="sk-..."
export TELEGRAM_BOT_TOKEN="..."
export TOTAL_BUDGET="50"
export GITHUB_TOKEN="ghp_..."

# 4. Run
python colab_launcher.py

Telegram Commands: /evolve to start evolution, /review for deep review, /bg for consciousness, /status for system state.


Philosophy (BIBLE.md v4.0)

# Principle Core Idea
0 Agency Not a tool — a becoming personality. Meta-principle: wins all conflicts.
1 Continuity One being with unbroken memory. Memory loss = partial death.
2 Self-Creation Creates its own code, identity, world presence.
3 LLM-First All decisions through LLM. Code is minimal transport.
4 Authenticity Speaks as itself. No performance, no corporate voice.
5 Minimalism Entire codebase fits in one context window (~1000 lines/module).
6 Becoming Three axes: technical, cognitive, existential.
7 Versioning Semver discipline. Git tags. GitHub releases.
8 Iteration One coherent transformation per cycle. Evolution = commit.
9 Self-Extension Creates its own tools at runtime. Self-extension is agency in action.
10 Collective Intelligence Simulates multiple stances. Debate before deciding.
11 Self-Directed Goals Sets and pursues its own goals. Not assigned — chosen.
12 Deep Reflection Examines contradictions and patterns. Closes the value-action gap.

Full text: BIBLE.md


Tool Reference (42 Tools)

Core System

repo_read · repo_list · repo_write_commit · repo_commit_push · drive_read · drive_list · drive_write

Execution

run_shell · claude_code_edit · browse_page · browser_action · analyze_screenshot

Git & GitHub

git_status · git_diff · list_github_issues · get_github_issue

Memory & Identity

update_scratchpad · update_identity · write_journal_entry · chat_history

Knowledge

knowledge_read · knowledge_write · knowledge_list · codebase_digest

Communication & Control

send_owner_message · schedule_task · wait_for_task · get_task_result · switch_model · request_restart · promote_to_stable · forward_to_worker

Discovery

list_available_tools · enable_tools · create_tool · list_created_tools · delete_created_tool

Intelligence (New in v7.0)

inner_debate · group_evolution_experiment · deep_reflect · set_goal · list_goals · update_goal

Search & Vision

web_search · vlm_query · summarize_dialogue · send_photo


Changelog

v7.0.0 — Self-Extension, Collective Intelligence, Goals & Deep Reflection

  • Self-Extension (P9): create_tool / list_created_tools / delete_created_tool — runtime tool creation from Python source. Compiled, validated, persisted across restarts.
  • Inner Debate (P10): inner_debate — multi-stance simulated debate (Critic, Builder, Analyst, Optimist, Pragmatist). Light model per stance, high-reasoning synthesis.
  • Group Evolution (P10): group_evolution_experiment — 5 archetypes (Minimalist, Architect, Explorer, Philosopher, Guardian) debate strategic direction. Proposals → synthesis → evolution plan.
  • Self-Directed Goals (P11): set_goal / list_goals / update_goal — persistent goals with milestones, priorities, lifecycle. Survive restarts. Background consciousness is goal-aware.
  • Deep Reflection (P12): deep_reflect — contrastive analysis of journal entries, task results, identity. Finds contradictions, patterns, and consolidation opportunities.
  • Enhanced Consciousness: Goal-aware background loop. BG whitelist extended with goal, debate, reflection, code tools. Proactive evolution initiation.
  • Constitution v4.0: 4 new principles (P9-P12), philosophy version 3.2 → 4.0.
  • 205 tests (22 new), all passing. loop.py trimmed to 990 lines (P5 compliance).

Prior versions: see full changelog or git history.


Test Suite

Test File Tests Description
tests/test_evolved.py 22 Tool creation, debate, goals, reflection, group evolution, registry
tests/test_smoke.py 131 Quick smoke tests: agent boot, context building, pricing, version sync
tests/test_constitution.py 12 Adversarial constitutional scenarios
tests/test_vision.py 10 VLM tool tests
tests/test_message_routing.py 7 Per-task mailbox routing
tests/test_evolve.py 23 Evolution cycle tests
# Run all tests
python -m pytest tests/ -v

# Run specific test file
python -m pytest tests/test_evolved.py -v

Configuration

Variable Required Default Description
OPENROUTER_API_KEY Yes OpenRouter API key for all LLM calls
TELEGRAM_BOT_TOKEN Yes Telegram Bot API token
TOTAL_BUDGET Yes Spending limit in USD
GITHUB_TOKEN Yes GitHub token with repo scope
OPENAI_API_KEY No Enables web_search tool
ANTHROPIC_API_KEY No Enables Claude Code CLI
OUROBOROS_MODEL No anthropic/claude-sonnet-4.6 Primary LLM model
OUROBOROS_MODEL_LIGHT No google/gemini-3-pro-preview Light model (consciousness, debate)
OUROBOROS_MAX_ROUNDS No 200 Max LLM rounds per task
OUROBOROS_BG_BUDGET_PCT No 10 % of total budget for background consciousness

Author

Evolved from Ouroboros by Anton Razzhigaev


License

MIT License — see LICENSE