LangStream is an event-driven developer platform designed for building and running LLM AI applications. It targets developers and researchers looking to create complex, scalable AI workflows, offering a Kubernetes-native architecture for robust deployment and management. The platform aims to simplify the development lifecycle of LLM applications by providing a structured, event-driven approach.

How It Works

LangStream leverages Kubernetes and Kafka (or Pulsar) as its core infrastructure. Applications are defined as event-driven pipelines, where components (agents, tools, data sources) communicate via Kafka topics. This architecture allows for asynchronous processing, scalability, and resilience, enabling the creation of sophisticated LLM applications that can handle high throughput and complex interactions.

Quick Start & Requirements

• CLI Installation: macOS via Homebrew (brew install LangStream/langstream/langstream), or via curl script for Linux/macOS.
• Prerequisites: Java 11+ for CLI. For Kubernetes deployment: Kafka/Pulsar cluster, S3-compatible or Azure Blob Storage. For local development: Docker, Java 17, Git, Python 3.11+.
• Sample App: Run langstream docker run test with provided example application and secrets.
• Documentation: Complete Documentation
• VS Code Extension: LangStream VS Code Extension

Highlighted Details

• Event-driven architecture powered by Kafka/Pulsar.
• Kubernetes-native for production deployments (EKS, AKS, GKE, Minikube).
• Supports S3 or Azure Blob Storage for code storage.
• Includes a CLI for development and deployment, and a VS Code extension for enhanced developer experience.

Maintenance & Community

• Community channels available on Slack and Linen.
• Website: langstream.ai

Licensing & Compatibility

• The README does not explicitly state the license.

Limitations & Caveats

• Production deployment requires significant infrastructure setup (Kubernetes, Kafka/Pulsar, object storage).
• Local development and testing are heavily reliant on Docker and minikube.