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Pooria Yousefi
Pooria Yousefi

Posted on • Originally published at Medium

# Building Production-Ready LLM Applications: Introducing llama-app-generator

#cpp #llm #llamacpp #ai

From Prototype to Production in Minutes

If you've worked with llama.cpp, you know the challenge: the library is powerful, but building production-ready applications around it requires significant boilerplate code, architecture decisions, and infrastructure setup. What if you could go from idea to working application in just a few commands?

Today, I'm excited to introduce llama-app-generator — a professional C++17 project generator that creates production-ready applications for llama.cpp with a clean, maintainable architecture.

The Problem

When building LLM-powered applications with llama.cpp, developers face several recurring challenges:

  1. Boilerplate Hell: Every project needs HTTP clients, configuration parsing, error handling, and server infrastructure
  2. Architecture Decisions: How do you structure the code? Direct coupling to llama-server or an abstraction layer?
  3. Build System Complexity: Cross-platform builds, dependency management, compiler flags...
  4. Legal Concerns: License compatibility, namespace protection, patent considerations
  5. Time to Market: Setting up all the above can take days or weeks

The Solution

llama-app-generator solves these problems with a template-based approach that generates complete, ready-to-customize applications:

./bin/llama-app-generator my-chatbot ~/projects
cd ~/projects/my-chatbot
python3 build.py
./bin/server
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That's it. You now have a production-ready application with:

  • ✅ Clean Architecture: CRTP-based design pattern for extensibility
  • ✅ Professional Infrastructure: HTTP server, configuration management, error handling
  • ✅ Cross-Platform Builds: Python-based build system with progress indicators
  • ✅ Legal Protection: Apache 2.0 license with namespace preservation
  • ✅ Production Ready: Logging, validation, graceful shutdown

The Architecture: CRTP Pattern

The generated applications use the Curiously Recurring Template Pattern (CRTP) for a clean separation of concerns:

namespace pooriayousefi::llama::app 
{

    template<typename Derived>
    class AppServerBase 
    {
    public:
        void run(int port) 
        {
            // HTTP server infrastructure
            server_.Post(
                "/process", 
                [this](const Request& req, Response& res) 
                {
                    auto result = static_cast<Derived*>(this)->process_request(req.body);
                    res.set_content(result, "application/json");
                }
            );
            server_.listen("0.0.0.0", port);
        }
    };

    class MyChatbot : public AppServerBase<MyChatbot> 
    {
    public:
        std::string process_request(const std::string& input) 
        {
            // Your custom logic here
            return llama_client_.complete(input);
        }
    };

} // namespace pooriayousefi::llama::app
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This pattern provides:

  • Type Safety: Compile-time polymorphism (zero runtime overhead)
  • Extensibility: Easy to customize without modifying base classes
  • Testability: Clean interfaces for mocking and testing

Three-Tier Architecture

Generated applications follow a proven architecture:

┌─────────────┐         ┌──────────────────┐         ┌────────────┐
│ llama-server│◄────────┤ Application      │◄────────┤   Client   │
│ (port 8080) │  HTTP   │ Server (8081)    │  HTTP   │ (CLI/GUI)  │
└─────────────┘         └──────────────────┘         └────────────┘
                              │
                              ├─ LlamaClient (HTTP wrapper)
                              ├─ AppServerBase(CRTP infrastructure)
                              └─ Custom logic (your domain)
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Benefits:

  • Separation of Concerns: LLM engine, business logic, and UI are decoupled
  • Scalability: Each tier can be scaled independently
  • Flexibility: Swap llama-server for OpenAI, Claude, etc. without changing your app
  • Testability: Mock any layer for testing

Real-World Examples

The project includes three production-ready examples:

1. Chatbot

An interactive conversational AI with message history:

./bin/llama-app-generator chatbot examples
cd examples/chatbot && python3 build.py
./bin/client chat "Tell me about quantum computing"
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2. Text Summarizer

Document summarization service:

./bin/llama-app-generator summarizer examples
cd examples/summarizer && python3 build.py
./bin/client summarize "$(cat article.txt)"
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3. Code Assistant

Programming help with code completion:

./bin/llama-app-generator code-assistant examples
cd examples/code-assistant && python3 build.py
./bin/client complete "def fibonacci(n):"
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Each example demonstrates different patterns and can be customized for your needs.

Why Apache 2.0 License?

I chose Apache License 2.0 over MIT for several important reasons:

  1. Patent Protection: Apache 2.0 includes explicit patent grants, protecting both contributors and users
  2. Namespace Protection: The NOTICE file mechanism ensures the pooriayousefi::llama::app namespace is preserved
  3. Legal Clarity: Explicit terms for contributions, trademarks, and liability
  4. Corporate Friendly: Many enterprises prefer Apache 2.0 for its comprehensive legal framework

Developer Experience

The build system includes thoughtful UX improvements:

Building chatbot
============================================================

Building Application Server...
  Compiling... (this may take some time due to large header-only libraries)
  Progress: ⠋ Compiling...
  Progress: ✓ Compilation complete!

✓ Application Server built successfully!
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Features:

  • Spinning progress indicators during compilation
  • Informative messages about build times
  • Clear success/failure feedback
  • Cross-platform (Linux, macOS, Windows/WSL)

Technical Details

Language: C++17 with std::filesystem

Dependencies: Header-only libraries (nlohmann/json, cpp-httplib)

Build System: Python 3 (no CMake/Make complexity)

Namespace: pooriayousefi::llama::app (legally protected)

License: Apache License 2.0

Performance:

  • Generator builds in < 1 second
  • Generated apps compile in seconds (depending on machine)
  • Zero runtime overhead from CRTP pattern

AI-Assisted Development

This project was developed with assistance from Claude Sonnet 4.5 (Preview). I believe in transparency about AI collaboration — it's acknowledged in the ACKNOWLEDGMENTS.md file. The architecture, design decisions, and code quality reflect a collaborative process that combines human expertise with AI capabilities.

Get Started

GitHub: https://github.com/pooriayousefi/llama-app-generator

# Clone and build the generator
git clone https://github.com/pooriayousefi/llama-app-generator.git
cd llama-app-generator
python3 build.py

# Generate your first project
./bin/llama-app-generator my-app ~/projects

# Customize and build
cd ~/projects/my-app
# Edit src/server.cpp to implement your logic
python3 build.py

# Run
./bin/server
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Documentation: Complete README with architecture diagrams, API references, and examples

What's Next?

I'm planning several enhancements:

  • JSON-RPC 2.0 protocol support
  • WebSocket streaming for real-time responses
  • Docker containerization templates
  • Kubernetes deployment manifests
  • GUI client templates (Qt/GTK)
  • REST API code generation

Contributing

The project welcomes contributions! Whether it's:

  • New example applications
  • Build system improvements
  • Documentation enhancements
  • Bug fixes

All contributions are valued and credited.

Conclusion

Building LLM applications shouldn't require reinventing the wheel every time. With llama-app-generator, you get:

✅ Production-ready architecture out of the box

✅ Legal protection with Apache 2.0

✅ Developer-friendly build system and UX

✅ Extensible design via CRTP pattern

✅ Real examples to learn from

Whether you're building a chatbot, code assistant, or custom LLM application, llama-app-generator provides the foundation so you can focus on what makes your application unique.

Try it today and let me know what you build!

About the Author

Pooria Yousefi is a software engineer passionate about C++ architecture patterns and LLM applications. This project reflects years of experience building production systems and a commitment to code quality and developer experience.

Contact: pooriayousefi@aol.com

GitHub: https://github.com/pooriayousefi

Project: https://github.com/pooriayousefi/llama-app-generator

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