DevOpsGPT

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Introduction
Welcome to the AI Driven Software Development Automation Solution, abbreviated as DevOpsGPT. We combine LLM (Large Language Model) with DevOps tools to convert natural language requirements into working software. This innovative feature greatly improves development efficiency, shortens development cycles, and reduces communication costs, resulting in higher-quality software delivery.
Features and Benefits
- Improved development efficiency: No need for tedious requirement document writing and explanations. Users can interact directly with DevOpsGPT to quickly convert requirements into functional software.
- Shortened development cycles: The automated software development process significantly reduces delivery time, accelerating software deployment and iterations.
- Reduced communication costs: By accurately understanding user requirements, DevOpsGPT minimizes the risk of communication errors and misunderstandings, enhancing collaboration efficiency between development and business teams.
- High-quality deliverables: DevOpsGPT generates code and performs validation, ensuring the quality and reliability of the delivered software.
- [Enterprise Edition] Existing project analysis: Through AI, automatic analysis of existing project information, accurate decomposition and development of required tasks on the basis of existing projects.
- [Enterprise Edition] Professional model selection: Support language model services stronger than GPT in the professional field to better complete requirements development tasks, and support private deployment.
- [Enterprise Edition] Support more DevOps platforms: can connect with more DevOps platforms to achieve the development and deployment of the whole process.
Demo（Click to play video）
1. DevOpsGPT Vision video
2. Demo - Software development and deployment to Cloud
3. Demo - Develop an API for adding users in Java SpringBoot
Workflow
Through the above introduction and Demo demonstration, you must be curious about how DevOpsGPT achieves the entire process of automated requirement development in an existing project. Below is a brief overview of the entire process:
- Clarify requirement documents: Interact with DevOpsGPT to clarify and confirm details in requirement documents.
- Generate interface documentation: DevOpsGPT can generate interface documentation based on the requirements, facilitating interface design and implementation for developers.
- Write pseudocode based on existing projects: Analyze existing projects to generate corresponding pseudocode, providing developers with references and starting points.
- Refine and optimize code functionality: Developers improve and optimize functionality based on the generated code.
- Continuous integration: Utilize DevOps tools for continuous integration to automate code integration and testing.
- Software version release: Deploy software versions to the target environment using DevOpsGPT and DevOps tools.
Use Cloud Services
Vists kuafuai.net
Quick Start
1. Run with source code
1. Download the released version, or clone the latest code(instability), Ensure SQLite and Python3.7 or later is ready.
2. Generate the configuration file: Copy env.yaml.tpl and rename it to env.yaml.
3. Modify the configuration file: Edit env.yaml and add the necessary information such as GPT Token (refer to documentation link for detailed instructions).