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Description

Defang is a developer-focused platform designed to streamline the development, deployment, and debugging of cloud applications. Utilizing AI-driven tools, Defang empowers developers to quickly evolve their concepts into fully operational applications hosted on their selected cloud services. The platform accommodates various programming languages such as Go, JavaScript, and Python, enabling users to kickstart their projects with example templates or create outlines through natural language instructions. With just a single command, Defang automates the building and deployment processes, managing configurations related to computing, storage, load balancing, networking, logging, and security seamlessly. The Defang Command Line Interface (CLI) enhances user interaction with the platform, providing installation methods through shell scripts, Homebrew, Winget, Nix, or direct downloads. Developers can specify their services using compose.yaml files, which Defang leverages to facilitate application deployment in the cloud. Overall, this platform significantly reduces the complexity traditionally associated with cloud application development, making it more accessible for developers at all skill levels.

Description

Unexpected outcomes are a common occurrence in software development. With complete insight into the entire sequence of calls, developers can pinpoint the origins of errors and unexpected results in real time with remarkable accuracy. The discipline of software engineering heavily depends on unit testing to create efficient and production-ready software solutions. LangSmith offers similar capabilities tailored specifically for LLM applications. You can quickly generate test datasets, execute your applications on them, and analyze the results without leaving the LangSmith platform. This tool provides essential observability for mission-critical applications with minimal coding effort. LangSmith is crafted to empower developers in navigating the complexities and leveraging the potential of LLMs. We aim to do more than just create tools; we are dedicated to establishing reliable best practices for developers. You can confidently build and deploy LLM applications, backed by comprehensive application usage statistics. This includes gathering feedback, filtering traces, measuring costs and performance, curating datasets, comparing chain efficiencies, utilizing AI-assisted evaluations, and embracing industry-leading practices to enhance your development process. This holistic approach ensures that developers are well-equipped to handle the challenges of LLM integrations.