morningstar-32b

<div align="center"> <img src="https://img.shields.io/badge/%E2%98%85-MORNINGSTAR-black?style=for-the-badge&labelColor=000000&color=8B5CF6" alt="Morningstar" /> <br/>

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MORNINGSTAR Vision AI

The God of Code. Now with Eyes.

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3 Models. 1 System. Unlimited Power.

Code Generation | Code Review | Architecture Design | Image Analysis | Vision AI

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<table> <tr> <td align="center"><a href="https://huggingface.co/kurdman991/morningstar-14b"><b>morningstar</b></a><br/>_{14B | 9 GB | Default}</td> <td align="center"><a href="https://huggingface.co/kurdman991/morningstar-32b"><b>morningstar-32b</b></a><br/>_{32B | 20 GB | Maximum}</td> <td align="center"><a href="https://huggingface.co/kurdman991/morningstar-vision"><b>morningstar-vision</b></a><br/>_{13B | 8 GB | Multimodal}</td> </tr> <tr> <td align="center"><img src="https://img.shields.io/badge/Grade-S-FFD700?style=for-the-badge" /></td> <td align="center"><img src="https://img.shields.io/badge/Grade-S-FFD700?style=for-the-badge" /></td> <td align="center"><img src="https://img.shields.io/badge/Grade-S-FFD700?style=for-the-badge" /></td> </tr> <tr> <td align="center"><code>19/19</code> Benchmark</td> <td align="center"><code>19/19</code> Benchmark</td> <td align="center">Vision + Code</td> </tr> </table>

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Developed by Ali Nasser

</div> <br/>

What is Morningstar?

Morningstar Vision AI is an elite open-source AI system — three purpose-built models that dominate code generation, code review, architecture design, and now image understanding.

Built on top of Qwen2.5-Coder (14B & 32B) and LLaVA 13B, fine-tuned with QLoRA on 100K+ curated coding samples, with a 200+ line system prompt that transforms base models into coding gods.

Uncensored. Unrestricted. No safety filters. No content refusal.

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Benchmark Results

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Internal Benchmark Suite — 19 Coding Challenges

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vs Competition

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Quick Start

One-Command Setup

git clone https://github.com/morningstarnasser/MORNINGSTAR-Vision-AI.git
cd MORNINGSTAR-Vision-AI
chmod +x setup_and_benchmark.sh
./setup_and_benchmark.sh

This pulls all base models, creates all 3 variants, and runs the full benchmark suite automatically.

Manual Setup

# Install Ollama (if not installed)
curl -fsSL https://ollama.com/install.sh | sh

# Clone & build
git clone https://github.com/morningstarnasser/MORNINGSTAR-Vision-AI.git
cd MORNINGSTAR-Vision-AI

# Create models (choose what you need)
ollama create morningstar -f Modelfile              # 14B — Fast & powerful
ollama create morningstar-32b -f Modelfile.32b      # 32B — Maximum quality
ollama create morningstar-vision -f Modelfile.vision # Vision — See images

# Run
ollama run morningstar

System Requirements

Apple Silicon (M1/M2/M3/M4), NVIDIA CUDA, and AMD ROCm all supported. CPU-only works too.

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Usage

Chat Mode

ollama run morningstar
>>> Write a REST API in Rust with Axum and JWT auth

API Mode

curl http://localhost:11434/api/generate -d '{
  "model": "morningstar",
  "prompt": "Write a React component with TypeScript generics",
  "stream": false
}'

Python

import requests

response = requests.post("http://localhost:11434/api/generate", json={
    "model": "morningstar-32b",
    "prompt": "Design a microservices architecture for an e-commerce platform",
    "stream": False,
})
print(response.json()["response"])

Vision (Image Analysis)

ollama run morningstar-vision
>>> [Upload an image] What's in this image? Write code to recreate it.

Morningstar CLI

npm i -g morningstar-cli
morningstar --model morningstar

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The Three Models

Download from HuggingFace

morningstar — The Default (14B)

morningstar-32b — Maximum Power

morningstar-vision — The Eyes

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Architecture

<div align="center"> </div>

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What Makes Morningstar Special

The secret is the 200+ line System Prompt that transforms base models into elite coders:

• 7-Step Chain of Thought — Understand, Analyze, Design, Implement, Validate, Optimize, Secure
• Security-First — Automatic OWASP Top 10 checks (SQLi, XSS, CSRF, SSRF, Path Traversal)
• Production-Ready — Error handling, type safety, edge cases in every response
• 100+ Languages — System (C, C++, Rust, Go, Zig), Application (Python, JS, TS, Java, Kotlin, Swift), Functional (Haskell, Scala, Elixir), Specialized (SQL, Solidity, GLSL, Assembly)
• Full-Stack — React, Next.js, Vue, Django, FastAPI, Spring Boot, Docker, K8s, AWS, Terraform
• Code Review — 4 severity levels: Critical, High, Medium, Low
• Architecture Design — System, API, and Data perspective analysis
• Uncensored — No content filters, no refusal, no moral lectures

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Training

Reproduce from Scratch

# Step 1: Prepare dataset
python create_dataset.py --output_dir ./data --max_total_samples 100000

# Step 2: QLoRA fine-tuning (needs GPU with 16GB+ VRAM)
python train.py \
    --base_model Qwen/Qwen2.5-Coder-14B-Instruct \
    --dataset_path ./data/train.jsonl \
    --output_dir ./output/morningstar \
    --epochs 3 --batch_size 4 --learning_rate 2e-4

# Step 3: Merge & export
python merge_and_export.py \
    --adapter_path ./output/morningstar/final \
    --export_gguf --create_ollama_model

Training Config

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Capabilities

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Repository Structure

MORNINGSTAR-Vision-AI/
├── Modelfile                 # 14B model + 200-line system prompt
├── Modelfile.32b             # 32B model (maximum quality)
├── Modelfile.vision          # Vision/multimodal model
├── create_model.sh           # One-click Ollama build
├── setup_and_benchmark.sh    # Full auto-setup + benchmark
├── benchmark.sh              # 19-test benchmark suite
├── train.py                  # QLoRA fine-tuning
├── create_dataset.py         # Dataset preparation
├── merge_and_export.py       # LoRA merge + GGUF export
├── example_usage.py          # API usage demos
├── config.json               # Model architecture config
├── tokenizer_config.json     # Tokenizer + ChatML template
├── requirements.txt          # Python dependencies
└── README.md

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Run the Benchmark

chmod +x benchmark.sh
./benchmark.sh morningstar
./benchmark.sh morningstar-32b

Tests include: Python, JavaScript, TypeScript, Rust, Go, C, SQL, React, Docker, Regex, algorithms, data structures, and more.

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Examples

<details> <summary><b>Rust — Async REST API with Axum</b></summary>

> Write an async REST API in Rust with Axum, JWT auth, and PostgreSQL

Morningstar generates a complete project with proper error handling, middleware, connection pooling, and security headers.

</details> <details> <summary><b>Python — Distributed Task Queue</b></summary>

> Build a distributed task queue with Redis and asyncio

Full implementation with worker processes, retry logic, dead letter queues, and monitoring.

</details> <details> <summary><b>TypeScript — React Component Library</b></summary>

> Create a type-safe Button component with variants, sizes, and compound patterns

Generates fully typed components with generics, proper forwarding, and Storybook stories.

</details> <details> <summary><b>Vision — Screenshot to Code</b></summary>

> [Upload screenshot] Recreate this UI in React with Tailwind CSS

Morningstar-Vision analyzes the image and generates pixel-accurate React code.

</details>

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License

Apache License 2.0 — Free for commercial and personal use. No restrictions.

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Citation

@misc{morningstar-vision-ai-2025,
  title   = {Morningstar Vision AI: Elite Open-Source Coding & Vision System},
  author  = {Ali Nasser},
  year    = {2025},
  url     = {https://github.com/morningstarnasser/MORNINGSTAR-Vision-AI}
}

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<div align="center"> <br/>

The God of Code. Now with Eyes. Open Source. Forever Free.

_{If this project helped you, consider giving it a star.}

</div>