hello! we built Hal 9 (GitHub) makes it easier to create, deploy, and share applications powered by LLM, diffusers, and other AI models. Whether you’re developing chatbots, agents, APIs, or building applications, Hal9 is designed to minimize engineering overhead so you can focus on the AI itself.
Why HAL 9?
Most generative AI projects end up devoting most of their time to engineering challenges—building interfaces, integrating tools, and managing infrastructure—rather than focusing on core AI work such as refining prompts, implementing RAG strategies, or best practices model performance.
Hal9 changes this balance by significantly reducing engineering overhead. It provides a simple, lightweight interface built around Unix IO conventions such as stdin and stdout, allowing you to focus entirely on AI innovation without having to learn complex frameworks or deployment workflows.
With Hal9, you can prototype and run locally with no additional dependencies, use our free online platform for rapid deployment, or easily scale to enterprise-grade solutions. We can also support organizations by enabling cloud deployment in their own environments or by providing additional computing resources to enterprise customers.
Hal9 is designed to take the distractions out of your hands so you can focus on building smarter, faster.
What is Hal9?
Hal9 is a deployment platform purpose-built for generative AI that allows you to build and deploy generative (LLM and diffuser) applications (chatbots, agents, APIs, apps) in seconds. Main features:
- flexible: Use any library and any model.
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intuitive: No need to learn the app framework, use it directly
input()andprint(). - Expandable: Designed to integrate your applications with scalable technologies like Docker and Kubernetes.
- powerful: Using operating system processes (stdin, stdout, files) as our application contracts enables long-running agents, multiple programming languages, complex system dependencies, and running arbitrary code in secure Kubernetes Pods.
- Open: The code behind the Hal9 application is also open source and available for contributions under our repository.
idea
We believe that the Python ecosystem already provides excellent libraries for everything from LLM interactions to generating tasks. Hal9 does not reinvent these wheels, but integrates them into a unified workflow, allowing you to focus on AI-specific challenges such as Retrieval Augmentation Generation (RAG), fine-tuning, alignment, and training.
Hal9 is ideal for developers who want to quickly experiment, iterate, and deploy AI applications without getting bogged down in engineering tasks such as front-end design or back-end integration. Thanks to its open architecture and simple application structure, it’s also ideal for teams looking to collaborate.
our journey
We launched Hal9 in 2021 with the goal of simplifying AI development. Initially, we focused on web developers, combining AI with technologies such as D3.js and TensorFlow.js. Although low-code interfaces are popular, users who want them need Python support.
In 2022, we are taking a step further with less code, adopting LLMs such as GPT-3, and moving towards automatic code generation and simplified user experience. Through multiple iterations, Hal9 has evolved into a platform that enables faster and easier AI application development.
resource
We are actively publishing posts demonstrating how to integrate your favorite frameworks with Hal9. The following are some technical blog posts that have been published:
Let us know your thoughts, feedback, and ideas—Hal9 is as committed to building apps as it is to creating a community of creators.