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Source channel @githubtrending · Post #14907 · Jul 3

#python#agents#generative_ai_tools#llamacpp#llm#onnx#openvino#parsing#retrieval_augmented_generation#small_specialized_models llmware is a powerful, easy-to-use platform that helps you build AI applications using small, specialized language models designed for business tasks like question-answering, summarization, and data extraction. It supports private, secure deployment on your own machines without needing expensive GPUs, making it cost-effective and safe for enterprise use. You can organize and search your documents, run smart queries, and combine knowledge with AI to get accurate answers quickly. It also offers many ready-to-use models and examples, plus tools for building chatbots and agents that automate complex workflows. This helps you save time, improve accuracy, and securely leverage AI for your business needs[1][3][5]. https://github.com/llmware-ai/llmware

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@githubtrending · Post #14904 · 07/03/2025, 12:00 PM

#go#ai_assistant#ai_generated_code#cloud_native#code_generation#custom_templates#developer_tools#development_framework#gin#go_sponge#golang#grpc#grpc_gateway#low_code#microservice#protobuf#restful_api#sponge#web Sponge is a powerful Go development framework that helps you quickly build backend services like RESTful APIs and microservices with minimal coding. It generates modular Go code automatically by parsing SQL, Protobuf, and JSON files, letting you create complete backend projects through a simple web interface without complex commands. Sponge supports custom templates and integrates AI assistants (like ChatGPT) to help write business logic, greatly speeding up development and reducing repetitive work. It also offers full support for testing, API docs, and deployment, making your project more stable, efficient, and easier to maintain. This saves you time and improves code quality. https://github.com/go-dev-frame/sponge

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@githubtrending · Post #14691 · 05/10/2025, 12:00 AM

#csharp#architecture#aspnetcore#clean_architecture#cqrs#ddd#dotnet#dotnetcore#event_driven_architecture#event_sourcing#kubernetes#masstransit#messaging#microservice#microservices#oauth2#opentelemetry#software_architecture#software_design#software_engineering#vertical_slice_architecture Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5]. https://github.com/meysamhadeli/monolith-to-cloud-architecture