core4ai 1.0.0

Contextual Optimization and Refinement Engine for AI

Core4AI: Contextual Optimization and Refinement Engine for AI

Core4AI is an intelligent system that transforms basic user queries into optimized prompts for AI systems using MLflow Prompt Registry. It dynamically matches user requests to the most appropriate prompt template and applies it with extracted parameters.

✨ Key Features

• 📚 Centralized Prompt Management: Store, version, and track prompts in MLflow
• 🧠 Intelligent Prompt Matching: Automatically match user queries to optimal templates
• 🔄 Dynamic Parameter Extraction: Identify and extract parameters from natural language
• 🔍 Content Type Detection: Recognize the type of content being requested
• 🛠️ Multiple AI Providers: Seamless integration with OpenAI and Ollama
• 📊 Detailed Response Tracing: Track prompt optimization and transformation stages
• 📝 Version Control: Track prompt history with production and archive aliases
• 🧩 Extensible Framework: Add new prompt types without code changes

🚀 Installation

Basic Installation

# Install from PyPI
pip install core4ai

Development Installation

# Clone the repository
git clone https://github.com/iRahulPandey/core4ai.git
cd core4ai

# Install in development mode
pip install -e ".[dev]"

⚙️ Initial Configuration

After installation, run the interactive setup wizard:

# Run the setup wizard
core4ai setup

The wizard will guide you through:

1. MLflow Configuration:

   • Enter the URI of your MLflow server (default: http://localhost:8080)
   • Core4AI will use MLflow to store and version your prompts

2. AI Provider Selection:

   • Choose between OpenAI or Ollama
   • For OpenAI: Set your API key as an environment variable:

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

   • For Ollama: Specify the server URI and model to use

🛠️ Usage Examples

Managing Prompts

# Register a new prompt with a template
core4ai register --name "essay_prompt" \
    --message "Basic essay template" \
    "Write a well-structured essay on {{ topic }} that includes an introduction, body paragraphs, and conclusion."

# Register multiple prompts from a JSON file
core4ai register --file prompts.json

# List all available prompts
core4ai list

# Get details about a specific prompt
core4ai list --name "essay_prompt@production" --details

# Later, update the same prompt (creates a new version)
core4ai register --name "email_prompt" "Write an updated {{ formality }} email..."

Basic Chat Interactions

# Simple query - Core4AI will match to the best prompt template
core4ai chat "Write about the future of AI"

# Get a simple response without enhancement details
core4ai chat --simple "Write an essay about climate change"

# See verbose output with prompt enhancement details
core4ai chat --verbose "Write an email to my boss about a vacation request"

💡 Sample Prompts

Core4AI comes with several pre-registered prompt templates:

# Register sample prompts
core4ai register --samples

This will register the following prompt types:

Prompt Type	Description	Sample Variables
essay_prompt	Academic writing	topic
email_prompt	Email composition	formality, recipient_type, topic
technical_prompt	Technical explanations	topic, audience
creative_prompt	Creative writing	genre, topic
code_prompt	Code generation	language, task, requirements
summary_prompt	Content summarization	content, length

🔄 Provider Configuration

OpenAI

To use OpenAI, set your API key:

# Set environment variable (recommended)
export OPENAI_API_KEY="your-api-key-here"

# Or configure during setup
core4ai setup

Available models include:

• gpt-3.5-turbo (default)
• gpt-4
• gpt-4-turbo

Ollama

To use Ollama:

1. Install Ollama on your system
2. Start the Ollama server:

   ollama serve
   

3. Configure Core4AI:

   core4ai setup
   

📋 Command Reference

Command	Description	Examples
core4ai setup	Run the setup wizard	core4ai setup
core4ai register	Register a new prompt	core4ai register --name "email_prompt" "Write a {{ formality }} email..."
core4ai list	List available prompts	core4ai list --details
core4ai chat	Chat with enhanced prompts	core4ai chat "Write about AI"
core4ai version	Show version info	core4ai version

🧪 Running Tests

# Install development dependencies
pip install -e ".[dev]"

# Run all tests
pytest

# Run specific test category
pytest tests/unit
pytest tests/functional
pytest tests/integration

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📊 How Core4AI Works

Core4AI follows this workflow to process queries:

1. Query Analysis: Analyze the user's query to determine intent
2. Prompt Matching: Match the query to the most appropriate prompt template
3. Parameter Extraction: Extract relevant parameters from the query
4. Template Application: Apply the template with extracted parameters
5. Validation: Validate the enhanced prompt for completeness and accuracy
6. Adjustment: Adjust the prompt if validation issues are found
7. AI Response: Send the optimized prompt to the AI provider

📜 License

This project is licensed under the Apache License 2.0