kitchenai

Open Source LLMOps tool for AI teams

epuerta9
86
3
Python

🍽️ KitchenAI

KitchenAI

Simplify AI Development with KitchenAI: Your AI Backend and LLMOps Toolkit

Docs
Falco
Hatch Project

Documentation
KitchenAI Cloud

🚀 What is KitchenAI?

KitchenAI is an open-source toolkit that simplifies AI complexities by acting as your AI backend and LLMOps solution—from experimentation to production.

It empowers developers to focus on delivering results without getting stuck in the weeds of AI infrastructure, observability, or deployment.

Key Goals:

  1. Simplify AI Integration: Easily turn AI experiments into production-ready APIs.
  2. Provide an AI Backend: Handle the entire AI lifecycle—experimentation, observability, and scaling.
  3. Empower Developers: Focus on application building, not infrastructure.

kitchenai-dev

🛠️ Who is KitchenAI For?

  • Application Developers:

    • Seamlessly integrate AI into your apps using APIs.
    • Experiment and test AI techniques without reinventing the wheel.

  • AI Developers & Data Scientists:

    • Move quickly from Jupyter notebooks to production-ready services.
    • Deploy custom AI techniques with ease (e.g., RAG, embeddings).

  • Platform & Infra Engineers:

    • Customize your AI stack, integrate tools like Sentry, OpenTelemetry, and more.
    • Scale and optimize AI services with a modular, extensible framework.

Say goodbye to boilerplate!

🚀 Go from notebook to app integration in minutes.

Example notebook: kitchenai-community/llama_index_starter

By annotating your notebook with KitchenAI annotations, you can go from this:

kitchenai-dev

To interacting with the API using the built in client:

kitchenai-dev

💡 Why KitchenAI?

Integrating and scaling AI is too complex today. KitchenAI solves this:

  1. AI Backend Ready to Go:

    • Stop building APIs and infra from scratch. Deploy AI code as production-ready APIs in minutes.

  2. Built-In LLMOps Features:

    • Observability, tracing, and evaluation tools are pre-configured.

  3. Framework-Agnostic & Extensible:

    • Vendor-neutral, open-source, and easy to customize with plugins.

  4. Faster Time-to-Production:

    • Go from experimentation to live deployments seamlessly.

⚡ Quickstart

  1. Set Up Environment

    export OPENAI_API_KEY=<your key>
export KITCHENAI_DEBUG=True
python -m venv venv && source venv/bin/activate && pip install kitchenai

  2. Start a Project

    kitchenai cook list && kitchenai cook select llama-index-chat && pip install -r requirements.txt

    kitchenai-list

  3. Run the Server

    kitchenai init && kitchenai dev --module app:kitchen

    Alternatively, you can run the server with jupyter notebook:

    kitchenai dev --module app:kitchen --jupyter

  4. Test the API

    kitchenai client health

    kitchenai client labels

    kitchenai-client

  5. Build Docker Container

    kitchenai build . app:kitchenai

📖 Full quickstart guide at docs.kitchenai.dev.

✨ Features

  • 🚀 Production-Ready Backend: Go from idea to production in minutes.
  • 🛠️ Built-In LLMOps: Observability, tracing, and evaluation out-of-the-box.
  • 🔌 Extensible Framework: Easily add custom plugins and AI techniques.
  • 📦 Modular AI Modules: Deploy and test AI components with ease.
  • 🐳 Docker-First Deployment: Build and scale with confidence.

📊 AI Lifecycle with KitchenAI

  1. Experiment:

    • Start in Jupyter notebooks or existing AI tools.
    • Annotate your notebook to turn it into a deployable AI module.

  2. Build:

    • Use KitchenAI to generate production-ready APIs automatically.

  3. Deploy:

    • Run the module locally or in production with built-in observability and scaling.

  4. Monitor & Improve:

    • Use KitchenAI’s observability tools to evaluate performance, trace issues, and iterate.

Developer Experience

Developer Flow

🔧 Under the Hood

  • Django Ninja: High-performance async APIs.
  • LLMOps Stack: Built-in tracing, observability, and evaluations.
  • Plugin System: Add advanced custom functionality.
  • Docker-Optimized: Seamless deployment with S6 overlays.

🚀 KitchenAI Cloud

Coming soon: KitchenAI Cloud will offer a fully managed AI backend experience.

Key Benefits:

  • Serverless deployment for AI modules.
  • Fully managed observability, tracing, and scaling.
  • Team collaboration tools for faster iteration.

🔗 Sign Up for Early Access: Register Here

🛠️ Roadmap

  • Expanded SDKs (Python, Go, JS).
  • Enhanced plugin system.
  • Enterprise-grade observability features.
  • KitchenAI Cloud Beta.

🤝 Contribute

Kitchenai is in alpha-

We’re building KitchenAI in the open, and we’d love your contributions:

  • ⭐ Star the repo on GitHub!
  • 🛠️ Submit PRs, ideas, or feedback.
  • 🧑‍🍳 Build plugins and AI modules for the community.

🙏 Acknowledgements

KitchenAI is inspired by the open-source community and modern AI development challenges. Let’s simplify AI, together.

Notable project: Falco Project. Thanks to the Python community for best practices and tools!

📊 Telemetry

KitchenAI collects anonymous usage data to improve the framework—no PII or sensitive data is collected.

Your feedback and support shape KitchenAI. Let’s build the future of AI development together!