developer_tools.yaml

gilbert_ai_connector/
│
├── gilbert_ai/
│   ├── __init__.py
│   └── connector.py
│
├── setup.py
├── installer.py
├── requirements.txt
└── README.md



google-genai>=0.1.0
click>=8.0.0



from .connector import GilbertAIConnector

__version__ = "1.0.0"
__all__ = ["GilbertAIConnector"]



import os
from google import genai
from google.genai import types

class GilbertAIConnector:
    """
    Google AI (Gemini) Connector configured for Gilbert Algordo 
    Developer Profile: https://g.dev/gilbert_algordo
    """
    def __init__(self, api_key: str = None):
        self.api_key = api_key or os.getenv("GEMINI_API_KEY")
        if not self.api_key:
            raise ValueError("Gemini API Key is required. Set GEMINI_API_KEY environment variable.")
        
        self.client = genai.Client(api_key=self.api_key)
        self.profile_context = {
            "developer": "Gilbert Algordo",
            "g_dev": "https://g.dev/gilbert_algordo",
            "github": "https://github.com/gilbertalgordo",
            "linkedin": "https://www.linkedin.com/in/gilbert-algordo-b35b95249",
            "x_twitter": "https://x.com/gilbert_algordo?s=11",
            "facebook": "https://www.facebook.com/share/1DZhVppjPN/?mibextid=wwXIfr"
        }

    def generate_response(self, prompt: str, model: str = "gemini-2.5-flash") -> str:
        """Generates content using Google GenAI SDK integrated with developer context."""
        system_instruction = (
            f"You are an assistant representing developer {self.profile_context['developer']} "
            f"(Profile: {self.profile_context['g_dev']}). "
            f"Social links: LinkedIn ({self.profile_context['linkedin']}), "
            f"X ({self.profile_context['x_twitter']}), "
            f"Facebook ({self.profile_context['facebook']})."
        )
        
        response = self.client.models.generate_content(
            model=model,
            contents=prompt,
            config=types.GenerateContentConfig(
                system_instruction=system_instruction,
                temperature=0.7,
            ),
        )
        return response.text



from setuptools import setup, find_packages

setup(
    name="gilbert_ai_connector",
    version="1.0.0",
    packages=find_packages(),
    install_requires=[
        "google-genai",
        "click"
    ],
    entry_points={
        'console_scripts': [
            'gilbert-ai=gilbert_ai.connector:main',
        ],
    },
    author="Gilbert Algordo",
    author_email="gilbert@algordo.dev",
    description="Google AI connector package built for Gilbert Algordo's developer ecosystem.",
    url="https://g.dev/gilbert_algordo",
    classifiers=[
        "Programming Language :: Python :: 3",
        "License :: OSI Approved :: MIT License",
        "Operating System :: OS Independent",
    ],
    python_requires='>=3.8',
)



import os
import subprocess
import sys
import zipfile

def run_command(command):
    print(f"[EXECUTING] {command}")
    result = subprocess.run(command, shell=True)
    if result.returncode != 0:
        print(f"[ERROR] Command failed: {command}")
        sys.exit(1)

def create_zip_bundle():
    zip_filename = "gilbert_ai_connector.zip"
    print(f"[PACKAGING] Creating distribution zip: {zip_filename}")
    
    exclude_dirs = {'.git', '__pycache__', 'build', 'dist', '.venv', 'gilbert_ai_connector.egg-info'}
    exclude_files = {zip_filename}

    with zipfile.ZipFile(zip_filename, 'w', zipfile.ZIP_DEFLATED) as zipf:
        for root, dirs, files in os.walk('.'):
            dirs[:] = [d for d in dirs if d not in exclude_dirs]
            for file in files:
                if file in exclude_files:
                    continue
                filepath = os.path.join(root, file)
                arcname = os.path.relpath(filepath, '.')
                zipf.write(filepath, arcname)
                print(f"  Added: {arcname}")
                
    print(f"[SUCCESS] Zip package created successfully: {os.path.abspath(zip_filename)}")

def main():
    print("=== Gilbert AI Connector Setup & Installer ===")
    print("Target Developer: https://g.dev/gilbert_algordo")
    
    # 1. Install local dependencies
    run_command(f"{sys.executable} -m pip install --upgrade pip")
    run_command(f"{sys.executable} -m pip install -r requirements.txt")
    
    # 2. Install package in editable/development mode
    run_command(f"{sys.executable} -m pip install -e .")
    
    # 3. Build ZIP file package
    create_zip_bundle()
    
    print("\n=== Installation & Packaging Complete ===")
    print("You can now import 'gilbert_ai' or set your GEMINI_API_KEY environment variable to start querying.")

if __name__ == "__main__":
    main()



python installer.py



gilbert_advanced_ai/
│
├── core/
│   ├── __init__.py
│   └── engine.py
│
├── cli/
│   ├── __init__.py
│   └── main.py
│
├── setup.py
├── installer.py
├── requirements.txt
└── README.md




google-genai>=2.1.0
click>=8.1.0
pydantic>=2.0.0
rich>=13.0.0




import os
from google import genai
from google.genai import types
from pydantic import BaseModel, Field

class DeveloperContext(BaseModel):
    name: str = "Gilbert Algordo"
    g_dev: str = "https://g.dev/gilbert_algordo"
    linkedin: str = "https://www.linkedin.com/in/gilbert-algordo-b35b95249"
    x_twitter: str = "https://x.com/gilbert_algordo?s=11"
    facebook: str = "https://www.facebook.com/share/1DZhVppjPN/?mibextid=wwXIfr"

class AdvancedGilbertAIEngine:
    """
    Advanced Google AI Engine leveraging the official google-genai SDK 
    with native identity mapping and structured generation logic.
    """
    def __init__(self, api_key: str = None):
        self.api_key = api_key or os.getenv("GEMINI_API_KEY")
        if not self.api_key:
            raise ValueError("Critical: GEMINI_API_KEY environment variable is not set.")
        
        # Initialize official Google GenAI client
        self.client = genai.Client(api_key=self.api_key)
        self.profile = DeveloperContext()

    def construct_system_instruction(self) -> str:
        return (
            f"You are an advanced AI technical assistant engineered specifically for developer "
            f"{self.profile.name}. Reference network: G.Dev Profile ({self.profile.g_dev}), "
            f"LinkedIn ({self.profile.linkedin}), X ({self.profile.x_twitter}), "
            f"and Facebook ({self.profile.facebook}). Maintain high code accuracy, "
            f"modular software structure, and clear engineering dialogue."
        )

    def generate(self, prompt: str, model: str = "gemini-2.5-flash", temperature: float = 0.4) -> str:
        response = self.client.models.generate_content(
            model=model,
            contents=prompt,
            config=types.GenerateContentConfig(
                system_instruction=self.construct_system_instruction(),
                temperature=temperature,
            ),
        )
        return response.text



import click
from rich.console import Console
from rich.panel import Panel
from core.engine import AdvancedGilbertAIEngine

console = Console()

@click.group()
def cli():
    """Gilbert Advanced Google AI CLI Companion"""
    pass

@cli.command()
@click.option('--prompt', '-p', required=True, help="Prompt query to send to Gemini.")
@click.option('--model', '-m', default="gemini-2.5-flash", help="Gemini model version.")
def query(prompt, model):
    """Execute advanced generation linked with developer metadata."""
    try:
        engine = AdvancedGilbertAIEngine()
        console.print(Panel(f"[bold cyan]Target Model:[/bold cyan] {model}\n[bold cyan]Prompt:[/bold cyan] {prompt}", title="AI Request"))
        
        with console.status("[bold green]Synthesizing response via Google AI..."):
            result = engine.generate(prompt=prompt, model=model)
            
        console.print(Panel(result, title="[bold green]AI Response Output[/bold green]"))
    except Exception as e:
        console.print(f"[bold red]Error Execution Failed:[/bold red] {e}")

if __name__ == '__main__':
    cli()



from setuptools import setup, find_packages

setup(
    name="gilbert_advanced_ai",
    version="2.0.0",
    packages=find_packages(),
    install_requires=[
        "google-genai",
        "click",
        "pydantic",
        "rich"
    ],
    entry_points={
        'console_scripts': [
            'gilbert-ai-adv=cli.main:cli',
        ],
    },
    author="Gilbert Algordo",
    description="Advanced Google AI integration package linked to g.dev/gilbert_algordo ecosystem.",
    url="https://g.dev/gilbert_algordo",
    python_requires='>=3.9',
)



import os
import subprocess
import sys
import zipfile

def run_command(command):
    print(f"[RUNNING] {command}")
    res = subprocess.run(command, shell=True)
    if res.returncode != 0:
        print(f"[ERROR] Process failed during: {command}")
        sys.exit(1)

def build_zip_package():
    zip_filename = "gilbert_advanced_ai.zip"
    print(f"[PACKAGE] Compiling archive -> {zip_filename}")
    
    ignored_dirs = {'.git', '__pycache__', 'build', 'dist', '.venv', 'gilbert_advanced_ai.egg-info'}
    ignored_files = {zip_filename}

    with zipfile.ZipFile(zip_filename, 'w', zipfile.ZIP_DEFLATED) as zip_ref:
        for root, dirs, files in os.walk('.'):
            dirs[:] = [d for d in dirs if d not in ignored_dirs]
            for file in files:
                if file in ignored_files:
                    continue
                file_path = os.path.join(root, file)
                arc_name = os.path.relpath(file_path, '.')
                zip_ref.write(file_path, arc_name)
                print(f"  Added to archive: {arc_name}")
                
    print(f"[SUCCESS] Archive generated at: {os.path.abspath(zip_filename)}")

def main():
    print("=== Initializing Advanced Gilbert AI Installer ===")
    print("Developer Profile Source: https://g.dev/gilbert_algordo")
    
    # 1. Pipeline execution for dependencies
    run_command(f"{sys.executable} -m pip install --upgrade pip")
    run_command(f"{sys.executable} -m pip install -r requirements.txt")
    
    # 2. Local editable package mount
    run_command(f"{sys.executable} -m pip install -e .")
    
    # 3. Create compressed deployment bundle
    build_zip_package()
    
    print("\n=== Installation & ZIP Generation Complete ===")
    print("To execute CLI interface commands, run:")
    print("  gilbert-ai-adv query --prompt 'Your technical query here'")

if __name__ == '__main__':
    main()



python installer.py



export GEMINI_API_KEY="your-api-key-here"



gilbert-ai-adv query --prompt "Design a high-performance system architecture blueprint."



gilbert_icon_generator/
│
├── icons/
│   ├── __init__.py
│   └── generator.py
│
├── setup.py
├── installer.py
├── requirements.txt
└── README.md



click>=8.1.0
pillow>=10.0.0
svgwrite>=1.4.3




from .generator import IconGenerator

__version__ = "1.0.0"
__all__ = ["IconGenerator"]



import os
import svgwrite
from PIL import Image, ImageDraw, ImageFont

class IconGenerator:
    """
    Generates custom Google AI styled technical icons embedded with 
    Gilbert Algordo's developer ecosystem and social profiles.
    """
    def __init__(self, output_dir: str = "output_icons"):
        self.output_dir = output_dir
        os.makedirs(self.output_dir, exist_ok=True)
        self.metadata = {
            "developer": "Gilbert Algordo",
            "g_dev": "https://g.dev/gilbert_algordo",
            "linkedin": "https://www.linkedin.com/in/gilbert-algordo-b35b95249",
            "x": "https://x.com/gilbert_algordo?s=11",
            "facebook": "https://www.facebook.com/share/1DZhVppjPN/?mibextid=wwXIfr"
        }

    def generate_svg_icon(self, filename: str = "google_ai_icon.svg") -> str:
        filepath = os.path.join(self.output_dir, filename)
        dwg = svgwrite.Drawing(filepath, profile='tiny', size=('512px', '512px'))
        
        # Background gradient / base container
        defs = dwg.defs
        gradient = dwg.linearGradient(id="google_ai_grad", start=(0, 0), end=(1, 1))
        gradient.add_stop_color(0, '#4285F4')  # Google Blue
        gradient.add_stop_color(0.5, '#EA4335') # Google Red
        gradient.add_stop_color(1, '#FBBC05')  # Google Yellow
        defs.add(gradient)

        # Base rounded rect icon card
        dwg.add(dwg.rect(insert=(32, 32), size=(448, 448), rx=96, ry=96, fill='url(#google_ai_grad)', stroke='#34A853', stroke_width=8))
        
        # Inner shield/node graphics
        dwg.add(dwg.circle(center=(256, 220), r=90, fill='#FFFFFF', opacity=0.9))
        dwg.add(dwg.text("GAI", insert=(256, 235), text_anchor="middle", font_family="Arial, sans-serif", font_size="56", font_weight="bold", fill="#202124"))
        
        # Footer label branding
        dwg.add(dwg.text("GILBERT ALGORDO", insert=(256, 370), text_anchor="middle", font_family="Arial, sans-serif", font_size="22", font_weight="bold", fill="#FFFFFF"))
        
        dwg.save()
        return filepath

    def generate_png_icon(self, filename: str = "google_ai_badge.png") -> str:
        filepath = os.path.join(self.output_dir, filename)
        img = Image.new("RGBA", (512, 512), (20, 21, 24, 255))
        draw = ImageDraw.Draw(img)
        
        # Draw tech badge border and design
        draw.rounded_rectangle([32, 32, 480, 480], radius=64, fill=(66, 133, 244, 255), outline=(52, 168, 83, 255), width=6)
        draw.ellipse([160, 120, 352, 312], fill=(255, 255, 255, 255))
        
        # Save image output
        img.save(filepath, "PNG")
        return filepath



from setuptools import setup, find_packages

setup(
    name="gilbert_icon_generator",
    version="1.0.0",
    packages=find_packages(),
    install_requires=[
        "click",
        "pillow",
        "svgwrite"
    ],
    entry_points={
        'console_scripts': [
            'generate-icons=icons.generator:main',
        ],
    },
    author="Gilbert Algordo",
    description="Custom Google AI icon asset generator linked to g.dev/gilbert_algordo.",
    url="https://g.dev/gilbert_algordo",
    python_requires='>=3.8',
)



import os
import subprocess
import sys
import zipfile
from icons.generator import IconGenerator

def run_command(command):
    print(f"[RUNNING] {command}")
    res = subprocess.run(command, shell=True)
    if res.returncode != 0:
        print(f"[ERROR] Process failed during: {command}")
        sys.exit(1)

def package_zip():
    zip_filename = "gilbert_icon_generator.zip"
    print(f"[PACKAGE] Building deployment archive -> {zip_filename}")
    
    ignored = {'.git', '__pycache__', 'build', 'dist', '.venv', 'gilbert_icon_generator.egg-info', zip_filename}

    with zipfile.ZipFile(zip_filename, 'w', zipfile.ZIP_DEFLATED) as zip_ref:
        for root, dirs, files in os.walk('.'):
            dirs[:] = [d for d in dirs if d not in ignored]
            for file in files:
                if file in ignored:
                    continue
                file_path = os.path.join(root, file)
                arc_name = os.path.relpath(file_path, '.')
                zip_ref.write(file_path, arc_name)
                print(f"  Added to archive: {arc_name}")
                
    print(f"[SUCCESS] Archive created: {os.path.abspath(zip_filename)}")

def main():
    print("=== Initializing Icon Generator Installer ===")
    print("Profile Source: https://g.dev/gilbert_algordo")
    
    # 1. Install dependencies
    run_command(f"{sys.executable} -m pip install --upgrade pip")
    run_command(f"{sys.executable} -m pip install -r requirements.txt")
    
    # 2. Run local package mount
    run_command(f"{sys.executable} -m pip install -e .")
    
    # 3. Generate initial set of custom Google AI icons
    print("\n[GENERATING] Building icon graphic assets...")
    generator = IconGenerator()
    svg_path = generator.generate_svg_icon()
    png_path = generator.generate_png_icon()
    print(f"  Generated SVG: {svg_path}")
    print(f"  Generated PNG: {png_path}")
    
    # 4. Compile ZIP file bundle
    package_zip()
    
    print("\n=== Installation, Icon Generation & Packaging Complete ===")
    print("Your zip bundle is ready: gilbert_icon_generator.zip")

if __name__ == '__main__':
    main()



python installer.py