Skip to content

DDS-Solutions/AI-TadPole-OS

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

1 Commit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Important

AI Assist Note (Knowledge Heritage): This document is part of the "Sovereign Reality" documentation.

  • @docs ARCHITECTURE:Core
  • Failure Path: Information drift, legacy terminology, or documentation mismatch.
  • Telemetry Link: Search [README] in audit logs.

AI Assist Note

Core technical resource for the Tadpole OS Sovereign infrastructure.

🔍 Debugging & Observability

Traceability via parity_guard.py.

Tadpole OS - Sovereign Intelligence

🐸 AI-Tadpole-OS

Sovereign Intelligence. Deterministic Execution. Zero Data Leaks.

The high-performance, local-first runtime for orchestrating autonomous multi-agent swarms.

Rust React Tailwind CSS CI Status Integrity Compliance License

🚀 Start a Mission🏗️ Architecture Hub🛡️ Security Model💬 Join Discussions


AI-Tadpole-OS is a local-first runtime for orchestrating autonomous teams of AI agents — without sending your data to the cloud. Define a goal, assign a hierarchy of specialized agents, and watch the engine coordinate them in parallel.

Designed for teams requiring uncompromising data sovereignty, Tadpole OS bridges the gap between probabilistic LLM outputs and deterministic business logic.


🛡️ Sovereignty starts with a Clone

In a world of "AI-as-a-Service," true independence is a local copy. We prioritize Git Clones because a clone is the ultimate act of data sovereignty:

  • Total Ownership: No one can "unplug" your intelligence stack.
  • Privacy by Default: Your data never leaves your infrastructure.
  • Air-Gapped Ready: Run missions in completely disconnected environments.
  • Deterministic Control: You own the code, the directives, and the memory.

Clone the repo. Own your intelligence.


🏗️ The 3-Layer Architecture

Why Tadpole OS is more reliable than a standard agent wrapper.

Layer Component Purpose
L1: Directive directives/ Intent: Human-defined SOPs and goals. Non-negotiable rules for the swarm.
L2: Orchestration Agent 99 Decision: Intelligent routing, self-correction, and wisdom extraction.
L3: Execution execution/ Action: Deterministic Python/Rust scripts. No "hallucinated" code execution.

🧠 Feature Spotlight: Agent 99 (Self-Annealing)

The system that learns from its own history.

Tadpole OS doesn't just run tasks; it performs Self-Annealing. After every mission, Agent 99 autonomously:

  1. Extracts Architectural Wisdom: Analyzes logs to find what worked and what didn't.
  2. Updates Institutional Memory: Writes learnings back to LONG_TERM_MEMORY.md.
  3. Refines Protocols: Adjusts its own directives to prevent future drift.

🧩 Core Capability Pillars

🖥️ 1. Reactive Interface & Observability

Built for high-density swarm oversight with sub-millisecond telemetry.

  • Detachable Portals: Spread tactical sectors across multiple physical displays.
  • 10Hz Swarm Pulse: Real-time MessagePack telemetry for agent performance.
  • God-View Visualizer: High-performance 2D Force-Graph of your agent hierarchy.
  • Hardware Telemetry: Real-time CPU, RAM, and Process load visualization.
🤖 2. Multi-Agent Swarm Orchestration

Hierarchical coordination powered by a Rust-native engine.

  • CEO/COO Patterns: Strategic-to-tactical delegation protocols.
  • Parallel Swarming: High-throughput sub-agent recruitment via FuturesUnordered.
  • Triple-Slot Routing: Primary, Secondary, and Tertiary model slots per agent.
  • Autonomic Fallback: Self-healing quantization adjustment on hardware limits.
🧠 3. Memory & Persistent RAG

Split-brain architecture for semantic and relational data.

  • LanceDB Vector Store: Cross-session institutional knowledge.
  • Mission Sandboxing: Localized RAG scopes that cleanup automatically on completion.
  • Hybrid Search: Combines SQLite deterministic logs with high-dimensional embeddings.
🛡️ 4. Security & Sovereign Compliance

Zero-trust governance with human-in-the-loop gates.

  • Sapphire Shield: Flags budget:spend and shell:execute for manual approval.
  • Hard Privacy Gate: Explicitly blocks external traffic for 100% air-gapped runs.
  • OBLITERATUS Hardening: 100% audit-verified code paths and Merkle trails.

🚀 Quick Start (60 Seconds)

1. Prerequisites

  • Rust (1.80+) & Node.js 20+
  • Ollama (for local models) or an API Key (OpenAI, Anthropic, Google, Groq).

2. Installation

# Clone and install dependencies
git clone https://github.com/DDS-Solutions/AI-Tadpole-OS.git
cd AI-Tadpole-OS
npm install

# Setup environment
cp .env.example .env
# Edit .env and set your NEURAL_TOKEN and API Keys

3. Launch the Swarm

# Terminal A: Start the Rust Engine
npm run engine

# Terminal B: Start the React Dashboard
npm run dev

🛰️ Scalability & Topology: The Max-Scale Swarm

Visualizing what a Full-Capacity Swarm (10 Clusters, 25 Agents) looks like.

View Swarm Hierarchy Diagram
graph TD
    classDef cluster fill:#222,stroke:#444,stroke-width:2px,color:#fff;
    classDef node fill:#333,stroke:#666,color:#eee;

    subgraph Cluster0 ["Executive Core (Google)"]
        CEO["ID 1: CEO (Google Gemini 3 Pro)"]
    end

    CEO -->|issue_alpha_directive| COO["ID 2: COO (Claude Opus 4.5)"]
    CEO -->|delegate| CTO["ID 3: CTO (GPT-5.3 Codex)"]

    subgraph Cluster1 ["Operations Hub (Anthropic)"]
        COO --> Ops1["ID 22: HR Manager"]
        COO --> Ops2["ID 10: Support Lead"]
    end

    subgraph Cluster2 ["Engineering Sector (Groq/OpenAI)"]
        CTO --> Eng1["ID 7: DevOps"]
        CTO --> Eng2["ID 8: Backend Dev"]
    end

    subgraph Cluster3 ["Marketing/Sales (Meta/xAI)"]
        CEO --> CMO["ID 4: CMO"]
        CMO --> Mark1["ID 17: Copywriter"]
        CMO --> Mark2["ID 19: SEO Specialist"]
    end

    subgraph Cluster4 ["Security Center (Mistral)"]
        Eng1 --> Sec1["ID 12: Security Auditor"]
    end

    CEO --> CMO
    class Cluster0,Cluster1,Cluster2,Cluster3,Cluster4 cluster;
    class CEO,COO,CTO,CMO,Ops1,Ops2,Eng1,Eng2,Mark1,Mark2,Sec1 node;
Loading

Resource Allocation Matrix (Sample)

Cluster Focus Provider Model Capacity
Executive Core Strategic Direction Google Pro / Flash
Operations Hub Orchestration Anthropic Opus / Sonnet
Engineering Sector Implementation Groq / OpenAI Llama / Codex
Security Center Auditing Mistral Medium / Large

🏭 Industry-Specific Solutions

Deploy specialized "One-Click" swarms for your sector.

  • 💸 Finance: Automated bookkeeping and real-time audit trails.
  • 📣 Marketing: Full-funnel content and SEO optimization.
  • ⚖️ Legal/Medical: Compliance-first intake and document review swarms.
  • 🏭 Manufacturing: Multi-tier templates for Job Shops to Smart Factories.

👉 Explore the Template Registry


🔱 Sovereign Forking Protocol

Tadpole OS is built to be forked. Create your own tactical branch:

  1. Fork this Repository to your own account.
  2. Customize Agents via the SQLite database or Swarm Templates.
  3. Deploy using the provided deploy-bunker.ps1 scripts.

Built with ❤️ by the DDS Solutions Team.
Licensed under MIT. Sovereign Intelligence for all.

About

AI-Tadpole-OS a local-first development platform for running autonomous AI agent teams on your own hardware. Coordinate parallel workflows, maintain full data privacy, and oversee every decision — no cloud required.

Topics

Resources

License

Code of conduct

Contributing

Security policy

Stars

Watchers

Forks

Packages

 
 
 

Contributors