MEROAI 0.2.1

AI Programming Assistant for Code Analysis, Fixing, and Image Processing

MEROAI v0.5.0

A comprehensive Python library for code analysis, language detection, image processing, file management, JSON generation, and smart decorators.

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Developer

Name	MERO
Telegram	@QP4RM
GitHub	github.com/6x-u

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Main Features

Code Analysis

• Detect errors in Python, C, C++, Java, JavaScript, TypeScript, Go, Rust, Bash, C#
• Automatic fixing of common errors
• Automatic programming language detection

Image Processing

• Analyze image information (dimensions, format, size)
• AI-powered image description (OpenAI GPT-4o)
• Image format conversion

File Management

• Create files in any programming language
• Automatic README.md generation for projects
• Edit README sections
• Save analysis results to txt files

File System Analysis

• Find duplicate files
• Detect hidden files
• Find unnecessary files

Smart Decorators

• @mero_schema - logging, timing, error handling
• @mero_log - add logging to functions
• @mero_validate - type validation

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Installation

Standard Installation

pip install pillow openai numpy requests
git clone https://github.com/6x-u/MEROAI-1V.git

Termux Installation (Android)

pkg update && pkg upgrade -y
pkg install python git -y
pip install pillow numpy requests
git clone https://github.com/6x-u/MEROAI-1V.git
cd MEROAI-1V/scripts
./install_termux.sh

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Quick Start

import sys
sys.path.insert(0, 'MEROAI-1V/src/MEROAI/meroai')
from core import MEROAI

m = MEROAI()
print(m.introduce())

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Main Commands

Code Analysis and Fixing

m = MEROAI()

# Analyze code
result = m.analyze_code("def hello() print('hi')")
print(result['errors'])  # ['Missing colon after statement']

# Fix code
fixed = m.fix_code("def hello() print('hi')")
print(fixed)  # def hello(): print('hi')

# Analyze file
result = m.analyze_file("script.py")

# Fix and save file
m.fix_file("script.py", save=True)

# Analyze, fix and save to new file
m.analyze_and_fix_file("broken.py", "fixed.py")

Image Processing

# Analyze image
info = m.analyze_image("photo.png")
print(info['width'], info['height'], info['format'])

# AI description (requires OPENAI_API_KEY)
desc = m.describe_image("photo.png")
print(desc['description'])

# Save analysis to file
m.save_analysis_to_file(info, "photo_analysis.txt")

File Creation

# Create C++ file
cpp_code = '''#include <iostream>
int main() {
    std::cout << "Hello MEROAI!" << std::endl;
    return 0;
}'''
m.create_file("hello.cpp", cpp_code, "cpp")

# Create directory
m.create_directory("my_project/src")

README Generation

# Generate README for project
m.generate_readme("/path/to/project", "MyProject")

# Edit README section
m.edit_readme("README.md", "Features", "- Feature 1\n- Feature 2")

JSON Generation

# Convert to JSON
data = {"name": "MEROAI", "version": "0.5.0"}
json_str = m.generate_json(data)

# Save as JSON file
m.generate_json(data, "config.json")

# Generate JSON Schema
schema = m.generate_json_schema("User", {
    "name": "string",
    "age": "integer",
    "email": "string"
})

File System Analysis

# Analyze full directory
analysis = m.analyze_directory("/path/to/folder")
print(analysis['total_files'])
print(analysis['total_size_mb'])
print(analysis['extensions'])

# Find duplicates
duplicates = m.find_duplicates("/path/to/folder")

# Hidden files
hidden = m.find_hidden_files("/path/to/folder")

# Unnecessary files
unnecessary = m.find_unnecessary_files("/path/to/folder")

Docstrings

# Parse docstring
doc = m.parse_docstring(my_docstring, "numpy")

# Generate docstring
doc = m.generate_docstring(
    "calculate",
    {"a": "int", "b": "int"},
    "int",
    style="numpy",
    description="Calculate sum"
)

# Convert function to JSON Schema
schema = m.function_to_json_schema(my_function)

Smart Decorators

from core import mero_schema, mero_log, mero_validate

@mero_schema
def my_function(x: int) -> int:
    return x * 2

@mero_log(level="INFO")
def process_data(data):
    return data.upper()

@mero_validate
def add(a: int, b: int) -> int:
    return a + b

Python Interpreter

# Interpreter info
info = m.get_interpreter_info()

# Execute code
result = m.execute_python("x = 1 + 2")
print(result['locals'])  # {'x': 3}

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Interactive Mode

m = MEROAI()
m.chat()

Available Commands

Command	Description
help	Show help
info	MEROAI info
system	System info
analyze <path>	Analyze file
fix <path>	Fix file
create <path>	Create file
scandir <path>	Analyze directory
json <data>	Convert to JSON
readme <path>	Generate README
image <path>	Analyze image
saveimg <img> <out>	Analyze image and save
exit	Exit

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Termux Scripts

cd ~/MEROAI-1V/scripts

# Full installation
./install_termux.sh

# Run MEROAI
./meroai.sh

# Analyze image
./image_analyzer.sh photo.jpg report.txt

# Fix code
./code_fixer.sh broken.py fixed.py

# Generate README
./readme_generator.sh ~/project MyProject

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Supported Languages

Language	Extensions
Python	.py
C	.c, .h
C++	.cpp, .cc, .hpp
C#	.cs
Java	.java
JavaScript	.js, .jsx
TypeScript	.ts, .tsx
Go	.go
Rust	.rs
Bash	.sh, .bash

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Requirements

Package	Required	Function
pillow	Yes	Image processing
numpy	Yes	Math operations
requests	Yes	HTTP requests
openai	Optional	AI image description

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Supported Platforms

• Windows (7, 8, 10, 11)
• Linux (Ubuntu, Debian, Fedora, Arch)
• macOS (10.15+)
• Android (Termux)

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License

MIT License

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Contact

• Developer: MERO
• Telegram: @QP4RM
• GitHub: github.com/6x-u

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MEROAI v0.5.0 - Made by MERO