Perplexity Core Framework

A professional framework for building intelligent applications with Perplexity AI

Installation • Virtual Environment • Quickstart • Features • Examples • Contributing • License

🚀 Overview

Perplexity Core is an enterprise-grade Python framework designed to accelerate development of AI applications using the Perplexity API. Built with flexibility, scalability, and developer experience in mind, it provides a robust foundation for everything from simple prototypes to production-ready AI systems.

The framework abstracts away the complexities of working with Perplexity's sophisticated AI models, allowing developers to focus on building innovative features rather than managing API interactions.

✨ Features

Comprehensive Client: Full support for all Perplexity API capabilities with an elegant, Pythonic interface
Flexible Configuration System: Environment variables, JSON files, and programmatic options for seamless integration in any environment
Enterprise-Ready Logging: Robust logging system ready for production deployments
Structured Data Models: Type-hinted models for responses and reliable data handling
Response Processing Tools: Ready-to-use utilities for format conversion, citation extraction, and more
Streaming Support: Built-in handling for streaming responses
Full Test Coverage: Comprehensive test suite ensuring reliability
Extensive Documentation: Complete references and examples for rapid onboarding

🛠️ Installation

🔮 Virtual Environment

Setting up a Virtual Environment

We strongly recommend using a virtual environment for development:

# Clone the repository
git clone https://github.com/holasoymalva/perplexity-core.git
cd perplexity-core

# Create a virtual environment
python -m venv venv

# Activate the virtual environment
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

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

You'll know your virtual environment is active when you see (venv) prefixed to your command prompt.

To deactivate the virtual environment when you're done:

deactivate

🧩 Quickstart

Set up your API key:

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

Then in your code:

from src.perplexity_client import PerplexityClient

# Initialize the client
client = PerplexityClient()

# Simple query
response = client.query(
    "What are the potential applications of AI in healthcare?",
    model="sonar-medium-online"
)

# Print the response
print(response.content)

# Use the search capability
search_results = client.search("latest advancements in quantum computing")
print(search_results.content)

🔍 Examples

The repository includes complete examples to jumpstart your development:

Basic Usage

python examples/basic_example.py

This demonstrates fundamental query operations with the API.

Advanced Features

python examples/advanced_example.py

Covers advanced usage including streaming responses, custom parameters, search functionality, and context handling.

📚 Documentation

Find comprehensive documentation in the code or visit our documentation site (coming soon).

Each module and function includes detailed docstrings explaining parameters, return values, and examples.

Managing Your Environment

For team collaboration and deployment consistency, we recommend:

# Save your current environment dependencies
pip freeze > requirements-lock.txt

# Create an environment from a requirements file
pip install -r requirements-lock.txt

This ensures all team members and deployment environments have identical dependencies.

🧠 Architecture

Perplexity Core follows a modular design to maximize flexibility:

perplexity-core/
├── src/                   # Core source code
│   ├── perplexity_client.py   # Main client interface
│   ├── models/            # Data models
│   ├── utils/             # Utilities (config, logging)
│   └── handlers/          # Response processors
├── examples/              # Example implementations
├── tests/                 # Test suite

🔧 Configuration

Perplexity Core offers multiple configuration methods:

Environment Variables: PERPLEXITY_API_KEY, PERPLEXITY_ENV, etc.
Configuration Files: JSON files in standard locations
Programmatic Configuration: Directly via the Config class

Example configuration file:

{
  "api_key": "your-api-key",
  "model": "sonar-medium-online",
  "temperature": 0.7
}

🤝 Contributing

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

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

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgements

Perplexity AI for their powerful AI models and API
Contributors and early adopters

Made with ❤️ in Mexico City

Perplexity Core • Elevating AI Development

holasoymalva/perplexity-core-framework