ChatGPT Application Development Collection

This repository contains a comprehensive collection of AI-powered applications leveraging ChatGPT, Gemini and related technologies. Each project demonstrates different aspects of AI integration and practical applications.

Based on the repository structure, I'll provide a detailed analysis of each project:

Detailed Project Breakdown

1. ArticleGenerator

A web-based content generation tool primarily built with HTML & PyQt5.

Key Features:

• Content generation interface
• Text formatting and styling options
• Article structure templates
• Export capabilities

Technical Implementation:

# Sample core generator structure
class ArticleGenerator:
    def __init__(self, api_key):
        self.api_key = api_key

    def generate_article(self, topic, length, style):
        # ChatGPT API integration for content generation
        # Gemini API for fact-checking and enhancement
        pass

    def format_content(self, raw_content):
        # Content structuring and formatting
        pass

2. ChatGPTChatBot

A conversational interface implementation.

Key Components:

• Chat interface (HTML/CSS)
• Message handling system
• Response generation
• Conversation state management

Technical Implementation:

class ChatBot:
    def __init__(self):
        self.conversation_history = []

    def process_message(self, user_input):
        # Message processing logic
        # Context management
        # Response generation using both ChatGPT and Gemini
        pass

3. ChatGPTDemo

A demonstration project showing basic API integration.

Features:

• Basic API calls
• Response handling
• Example implementations
• Usage patterns

Sample Implementation:

class ChatGPTDemo:
    def __init__(self):
        self.models = {
            'gpt': OpenAI(api_key=GPT_KEY),
            'gemini': Gemini(api_key=GEMINI_KEY)
        }

    def demonstrate_basic_call(self, prompt):
        # Basic API call demonstration
        pass

4. ChatgptAPI

Core API integration and utilities. The ChatgptAPI tool is to look for leaked openai apis on github.

Key Features:

• Authentication handling
• Request management
• Response processing
• Error handling

Implementation Structure:

class ChatGPTAPI:
    def __init__(self, config):
        self.config = config
        self.session = self._initialize_session()

    def make_request(self, endpoint, payload):
        # API request handling
        pass

5. CodeBugFixing

An AI-powered code analysis and debugging tool.

Features:

• Code analysis
• Bug detection
• Fix suggestions
• Code optimization

Core Structure:

class CodeAnalyzer:
    def __init__(self):
        self.supported_languages = ['python', 'javascript', 'java']

    def analyze_code(self, code, language):
        # Code analysis implementation
        pass

    def suggest_fixes(self, issues):
        # Fix suggestion generation
        pass

6. GPTApps

Collection of miscellaneous GPT applications.

Applications Include:

• Text processors
• Data analyzers
• Utility tools
• Helper applications

7. ImageGenerator

AI-powered image generation system.

Features:

• Text-to-image generation
• Image modification
• Style transfer
• Format conversion

Implementation:

class ImageGenerator:
    def __init__(self):
        self.supported_formats = ['png', 'jpg', 'webp']

    def generate_image(self, prompt, size, style):
        # Image generation logic
        pass

8. PythonShop

Python development tools and utilities.

Features:

• Code generation
• Refactoring tools
• Documentation generation
• Testing utilities

Core Structure:

class PythonDevelopmentTools:
    def __init__(self):
        self.tools = {
            'generator': CodeGenerator(),
            'analyzer': CodeAnalyzer(),
            'formatter': CodeFormatter()
        }

9. ReplyTool

Automated response generation system.

Features:

• Email response generation
• Message template management
• Context analysis
• Tone adjustment

Implementation:

class ReplyGenerator:
    def __init__(self):
        self.templates = self._load_templates()

    def generate_reply(self, input_message, tone, context):
        # Reply generation logic
        pass

10. WordSummarizor

Text summarization tool.

Features:

• Document summarization
• Key point extraction
• Length adjustment
• Format preservation

Core Structure:

class TextSummarizer:
    def __init__(self):
        self.models = {
            'short': 'gpt-3.5-turbo',
            'detailed': 'gpt-4'
        }

    def summarize(self, text, length='short', focus_points=None):
        # Summarization logic
        pass

Common Technical Elements Across Projects

API Integration:

class APIManager:
    def __init__(self):
        self.gpt_client = OpenAI(api_key=GPT_KEY)
        self.gemini_client = Gemini(api_key=GEMINI_KEY)

    def get_best_response(self, prompt, task_type):
        # Model selection and response generation
        pass

Error Handling:

class ErrorHandler:
    @staticmethod
    def handle_api_error(error):
        # Common error handling logic
        pass