SigmaStudio
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Piattaforma di studio e sviluppo basata su Agenti AI e Grafi della Conoscenza, con IDE integrato per la progettazione, la gestione e l'archiviazione di documentazione, codice, test e visualizzazioni grafiche. Favorisce l'organizzazione delle informazioni, l'automazione dei processi di sviluppo e la tracciabilità dell'intero ciclo progettuale.
🧬 Σ-SIGMA Studio
Modular AI-Native Cognitive Operating Kernel for Multi-GPU Inference, Autonomous Multi-Agent Swarms & Dynamic Extensible Ecosystem
🇬🇧 English • 🇮🇹 Italiano • 📦 GitHub Repository
📸 Platform Screenshots
1. Interactive Release Board, Dynamic Skills Showcase Slider & 4-Step Kernel Workflow
2. Streaming Chat AI Workspace with Sub-100ms TTFT, SigmaEngine Multi-GPU & 12 MCP Servers
3. Modelli Hub: Hugging Face Downloader & Tab 2 GGUF Quantization Forge
🚀 Overview
Sigma Studio is an open-source, executable AI Operating Kernel engineered around a lightweight, watertight Micro-Kernel paired with a dynamic Runtime Module Ecosystem. It combines an ultra-fast Python 3.10+ FastAPI backend with a GPU-accelerated React 19 + Vite 8 frontend.
Multi-agent teams interact through Modelfile manifests, standard Model Context Protocol (MCP) tools, and specialized lab environments installed on-demand from the official GitHub ecosystem.
+-----------------------------------------------------------------------------------------+
| Σ-SIGMA STUDIO COGNITIVE KERNEL |
+-----------------------------------------------------------------------------------------+
| ⚡ SigmaEngine (Multi-GPU CUDA) | ⚙️ Providers Hub (100% Interoperable) | 📜 20 Modelfiles |
| (C++/PyTorch FlashAttn-2 Shard) | (OpenAI, Claude, Gemini, DeepSeek) | (Manifesti Hub) |
+-----------------------------------------------------------------------------------------+
| 🔌 12 MODEL CONTEXT PROTOCOL SERVERS |
+-----------------------------------------------------------------------------------------+
| 🛠️ Dev / Workspace | 🌐 Web Search & DNS | ✉️ Email Client | 💬 Telegram / Slack |
| 📅 Calendar & Tasks | 🧠 Vector Memory RAG | 🏠 IoT HomeAss | ⚡ GPU VRAM Flush |
+-----------------------------------------------------------------------------------------+
| 🧩 15 MODULAR OPEN-SOURCE LABS |
+-----------------------------------------------------------------------------------------+
| 🎨 Creative Lab 3D/2D | 🧠 Training Lab & SLM | 🎙️ Voice Studio (Kokoro) |
| 🔬 Pipelines Lab & Swarm | ⚡ Hardware & GPU Telemetry| 🏠 Smart Domotica Assistant |
| 📅 Roadmap & Task Audit | 📊 Knowledge Graph D3 | 📻 Hi-Fi Audio Lounge |
+-----------------------------------------------------------------------------------------+
🌟 Key Architecture & Capabilities
1. ⚡ SigmaEngine Native Multi-GPU Inference
- Zero-Bottleneck C++/PyTorch Layer Sharding: Automatically partitions large LLMs (from 7B to 70B+) across primary and secondary GPUs (e.g. RTX 5070 Ti + RTX 5060) and system RAM.
- Sub-100ms TTFT: Ultra-low Time To First Token with native FlashAttention-2 acceleration and continuous KV-cache streaming.
2. ⚡ Modelli Hub: Hugging Face Downloader & GGUF Forge
- Hugging Face Downloader: Search and download any open-source model directly from Hugging Face with resilient resumable multi-stream downloading.
- Tab 2 GGUF Quantization Forge: Integrated in-memory converter and quantizer (Q4_K_M, Q5_K_M, Q8_0, FP16) to tailor model weight precision to your hardware VRAM without external CLI tools.
3. ⚙️ Providers Hub (100% Interoperable Routing)
- Seamlessly switch between native local SigmaEngine execution and external Cloud Providers (OpenAI GPT-4o, Anthropic Claude 3.5, Google Gemini 2.0 Flash, DeepSeek-R1, Groq, Ollama).
- Intelligent local intent router for rapid ~100ms classification and autonomous multi-agent dispatching.
4. 📜 Manifesti Hub (20 Standardized Modelfiles)
- Enforce strict persona contracts, ethical boundaries, and reasoning pipelines through 20 specialized Modelfile manifests (Architect, Developer, Mathematician, Medical Specialist, Legal Jurist, Security Auditor, etc.).
5. 🔌 12 Model Context Protocol (MCP) Servers
- Native Kernel Servers: Developer CLI & Pytest, Web Search & DNS Diagnostics, Email Management, Messaging Webhooks, Calendar Scheduling, Inference Fallbacks.
- Modular Extension Servers: Home Assistant IoT, NVIDIA NVML Hardware & VRAM Flush, Neural Voice TTS, D3 Memory Graph, QLoRA Training.
- Interactive Permission Governance: Granular confirmation dialogs and access control for system-level operations.
6. 🏛️ Watertight Sandboxed Execution
- Strict Path Whitelist: Confines filesystem writes to authorized directories (
data/,manifesti/,scratch/,sigma_studio/,core/). - Subprocess Isolation: Static AST analysis preventing unauthorized Python code execution.
📦 Official Modules Catalog
All optional modules can be installed with a single click from the Hub Skills & Extensions:
| Module ID | Name | Category | Key Features |
|---|---|---|---|
sigma_creative_lab |
Creative Lab 3D/2D | Multimodal & Graphics | FLUX/SDXL Text-to-Image, SAM2/rembg background removal, Hunyuan3D/TripoSR generation, PBR materials, Blender headless rendering. |
sigma_training_lab |
Training Lab & SLM | LLM Training & SLM | Unsloth QLoRA, PEFT, Gradus Functional Weight Engine (FWE), Autopilot hyperparameter search, GGUF quantization, MMLU benchmarks. |
sigma_voice_studio |
Voice Studio & Speech | Neural Voice & Audio | Kokoro 82M ultra-fast TTS (<80ms), Coqui XTTS-v2 zero-shot voice cloning, pitch/speed tuning, live waveform visualizer, Voice MCP. |
sigma_hardware_lab |
Hardware & GPU Telemetry | System & VRAM | Live VRAM allocation, GPU/CPU telemetry charts, CUDA process monitor, zombie task termination, one-click VRAM flush. |
sigma_research_lab |
Pipelines Lab & Swarm | Research & Automation | Visual DAG pipeline designer, multi-agent research loops, step-by-step execution inspector, self-healing code generator. |
sigma_knowledge |
Argomenti & Knowledge Graph | Knowledge & Memory | D3 force-directed interactive relational graph, Universal Knowledge Nodes explorer, RAG vector search, Memory MCP server. |
sigma_roadmap |
Roadmap & Task Kanban | Productivity & Tasks | Interactive Calendar, drag-and-drop Kanban task board, chronological audit trail, milestone tracker. |
sigma_domotica |
Smart Home Assistant | IoT & Home Automation | Home Assistant WebSocket/REST bridge, device control, automation triggers, climate & solar power modulation. |
⚡ Installation & Quick Start
Prerequisites
- OS: Windows 10/11 or Linux x86_64
- Python: 3.10 or higher
- Node.js: 18.0+ and npm 9.0+
- CUDA Toolkit (Recommended for GPU acceleration): NVIDIA CUDA 12.0+
1. Clone the Repository
git clone https://github.com/Sigmanih/SigmaStudio.git
cd SigmaStudio
2. Automated Setup (Windows)
Double-click install_dependencies.bat or run:
.\install_dependencies.bat
3. Manual Setup (Linux / macOS)
# 1. Setup Virtual Environment
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
pip install -r requirements.txt
# 2. Build Frontend
cd sigma_studio
npm install
npm run build
cd ..
# 3. Start Server
python sigma_server.py
4. Launching Sigma Studio
Run the one-click launcher on Windows:
.\sigma_studio.bat
Or start manually:
python sigma_server.py
Open your browser at http://localhost:8000.
🧪 Running Automated Tests
Run the Pytest kernel test suite:
pytest tests/ -v
All kernel tests validate MCP governance, agent routing, FastAPI endpoints, security sandboxing, and chat streaming with a 100% success rate.
📜 License & Community
Sigma Studio is licensed under the Apache-2.0 License. Continuous updates and optimizations are pushed regularly. Check the official GitHub Repository for new releases.
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