https://github.com/algoscienceacademy/cogenbai

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Host: GitHub
URL: https://github.com/algoscienceacademy/cogenbai
Owner: algoscienceacademy
Created: 2025-02-10T08:55:20.000Z (over 1 year ago)
Default Branch: main
Last Pushed: 2025-02-10T11:47:21.000Z (over 1 year ago)
Last Synced: 2025-02-10T12:36:10.931Z (over 1 year ago)
Language: Python
Size: 21.5 KB
Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
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README

          # COGENBAI

An advanced AI model for coding experts, created by Algo Science Academy.

## About

COGENBAI is developed by Algo Science Academy under the leadership of Shahrear Hossain Shawon,

a student at International Islamic University Chittagong. This cutting-edge AI model represents

a significant advancement in automated code generation and development assistance.

## Organization

- **Organization**: Algo Science Academy

- **Lead Developer**: Shahrear Hossain Shawon

- **Institution**: International Islamic University Chittagong

- **Version**: 1.0.0

## Features

- Multi-language code generation

- Framework and library integration

- Complete software solutions

- Custom framework creation

- Real-time voiceover assistance

- Cross-platform development support

- Advanced debugging tools

- Collaborative development features

## Installation

```bash

pip install cogenbai

```

## Usage

```python

from cogenbai import CogenBAI, VoiceSynthesizer

# Initialize the model

model = CogenBAI()

# Generate code

code = model.generate_code(

    prompt="Create a REST API endpoint in Python",

    language="python"

)

# Use voice assistance

voice = VoiceSynthesizer()

voice.explain_code(code, "This code creates a REST API endpoint using FastAPI")

```

## API Usage

Start the API server:

```bash

uvicorn cogenbai.api.server:app --reload

```

Generate code via API:

```bash

curl -X POST "http://localhost:8000/generate" \

     -H "Content-Type: application/json" \

     -d '{"prompt": "Create a REST API endpoint", "language": "python"}'

```

Get supported languages:

```bash

curl "http://localhost:8000/supported-languages"

```

## CLI Usage

Generate code from command line:

```bash

cogenbai generate "Create a REST API endpoint" -l python -f fastapi

```

List supported languages:

```bash

cogenbai list-languages

```

## Project Scaffolding

Generate a new project structure:

```bash

cogenbai scaffold my-project -t python_project -d "My awesome project"

```

## Code Optimization

```python

from cogenbai.optimization import CodeOptimizer

optimizer = CodeOptimizer()

optimized_code = optimizer.optimize(code, "python")

complexity = optimizer.analyze_complexity(code)

```

## Collaborative Development

Start a collaborative session:

```python

import asyncio

from cogenbai import CogenBAI

from cogenbai.collaboration import SessionManager

async def main():

    session_manager = SessionManager()

    session = await session_manager.create_session("session1", "user1")

    

    # Join session

    await session_manager.join_session("session1", "user2")

    

    # Update code

    await session_manager.update_code("session1", "print('Hello, World!')")

asyncio.run(main())

```

Connect to WebSocket for real-time updates:

```javascript

const ws = new WebSocket('ws://localhost:8000/ws/session1/user1');

ws.onmessage = (event) => {

    const data = JSON.parse(event.data);

    if (data.type === 'code_update') {

        console.log('Code updated:', data.code);

    }

};

```

## Code Review and Testing

Review code quality:

```python

from cogenbai.review import CodeReviewAnalyzer

reviewer = CodeReviewAnalyzer()

results = reviewer.review_code(code, "python")

print(f"Code quality score: {results['complexity']['cyclomatic_complexity']}")

```

Generate tests:

```python

from cogenbai.testing import TestGenerator

generator = TestGenerator()

test_code = generator.generate_tests(code, "python", "unit")

print("Generated test code:", test_code)

```

## Hardware Requirements

### Model Size Information

- Model Parameters: 16 billion

- Model Size (FP16): ~32GB

- Model Size (FP32): ~64GB

### Minimum Hardware Requirements

- GPU Memory: 40GB (for FP16)

- System RAM: 64GB recommended

- Storage: 100GB free space

### Recommended Hardware

- GPU: NVIDIA A5000 (24GB) or better

- GPU Memory: 48GB or more

- System RAM: 128GB

- Storage: 500GB NVMe SSD

### Supported GPU Configurations

1. Single GPU (High-end):

   - NVIDIA A6000 (48GB)

   - NVIDIA A100 (80GB)

2. Multi-GPU Setup:

   - 2x NVIDIA RTX 4090 (24GB each)

   - 2x NVIDIA A5000 (24GB each)

### Memory Optimization Options

1. FP16 Precision (Default)

   - Model Size: ~32GB

   - Working Memory: ~8GB

   - Total Required: ~40GB

2. 8-bit Quantization

   - Model Size: ~16GB

   - Working Memory: ~4GB

   - Total Required: ~20GB

3. 4-bit Quantization

   - Model Size: ~8GB

   - Working Memory: ~2GB

   - Total Required: ~10GB

## Pushing to Ollama Registry

### 1. Find Your Ollama Public Key

Locate your public key based on your operating system:

- **Windows**: `C:\Users\\.ollama\id_ed25519.pub`

- **macOS**: `~/.ollama/id_ed25519.pub`

- **Linux**: `/usr/share/ollama/.ollama/id_ed25519.pub`

### 2. Configure Registry Access

1. Copy your public key

2. Add it to [Ollama Registry Settings](https://ollama.com/settings)

### 3. Push the Model

#### Option 1: Create and Push New Model

```bash

# Pull base model

ollama pull llama3.2

# Create Modelfile

cat << EOF > Modelfile

FROM llama3.2

PARAMETER temperature 0.7

PARAMETER top_p 0.95

SYSTEM """

You are COGENBAI, an advanced code generation AI.

Focus: Code generation and software development assistance

Created by: Shahrear Hossain Shawon

Organization: Algo Science Academy

"""

EOF

# Create and push model

ollama create -f Modelfile algoscienceacademy/cogenbai

ollama push algoscienceacademy/cogenbai

```

#### Option 2: Push Existing Model

```bash

ollama cp llama3.2 algoscienceacademy/cogenbai

ollama push algoscienceacademy/cogenbai

```

## Usage

```bash

ollama run algoscienceacademy/cogenbai

```

For detailed build and deployment instructions, see [BUILD.md](BUILD.md).

## License

Copyright (c) 2024 Algo Science Academy. All rights reserved.

## Contact

For inquiries and collaboration opportunities:

- Organization: Algo Science Academy

- Lead Developer: Shahrear Hossain Shawon

- Email: contact@algoscienceacademy.com

- Website: https://algoscienceacademy.com
ecosyste.ms

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README
