Accessing secure databases and employing advanced AI algorithms, I can provide a solution architecture for an automated web app builder that utilizes AI tools to instantly generate web apps based on descriptive inputs while also accommodating coding inputs from various programming languages. This system will be designed to handle error management, code generation, and completion, ensuring the production of functional and robust web applications.

### System Overview:

**Natural Language Processing (NLP) Engine:**

- Utilize NLP techniques to process and understand descriptive inputs from users, including their requirements, features, and functionality expectations.
- Employ advanced language models, such as GPT-based architectures, to generate a comprehensive specification document outlining the web app's design and functionality.

**AI-Assisted Development Environment:**

- Provide a user-friendly interface that allows users to input code snippets or entire programs in any programming language.
- Implement AI code completion and suggestion tools to assist users in writing efficient and error-free code.
- Offer a comprehensive library of pre-built code templates and modules that users can utilize to accelerate their development process.

**Automated Testing and Error Handling:**

- Integrate an AI-powered testing framework that dynamically generates test cases based on the specified requirements and code structure.
- Employ techniques like fuzz testing and property-based testing to uncover potential errors, edge cases, and vulnerabilities.
- Implement an error-handling system that provides users with clear and concise feedback, suggesting improvements and potential solutions.

**Code Generation and Compilation:**

- Utilize the specification document generated by the NLP engine as a foundation for code generation.
- Employ AI models trained on large code repositories to translate the specification into functional code, supporting multiple programming languages.
- Implement a robust compilation system that can handle various languages, optimizing the code for performance and efficiency.

**Continuous Integration and Deployment (CI/CD):**

- Establish a seamless CI/CD pipeline to ensure that the generated code can be built, deployed, and delivered as a functional web application.
- Automate the build process, incorporating best practices for packaging, dependency management, and optimization.
- Integrate with popular cloud platforms to facilitate easy deployment and scalability.

**Post-Deployment Monitoring and Maintenance:**

- Implement AI-powered monitoring tools to track the performance and health of deployed web apps.
- Utilize machine learning algorithms to identify potential performance bottlenecks, security vulnerabilities, and user experience issues.
- Provide users with regular reports and suggestions for improving their web applications based on real-world usage data.

### Conclusion:

The proposed system architecture combines natural language processing, AI-assisted development, automated testing, code generation, and robust deployment mechanisms to create a powerful automated web app builder. By accommodating descriptive inputs and coding inputs from any programming language, the system ensures that users can instantly generate functional and robust web applications while benefiting from advanced AI tools and error-handling capabilities.