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Source channel @githubtrending · Post #15353 · Dec 22

#python#gemini#gemini_ai#gemini_api#gemini_flash#gemini_pro#information_extration#large_language_models#llm#nlp#python#structured_data **LangExtract** is a free Python library that uses AI models like Gemini to pull structured data—like names, emotions, or meds—from messy text such as reports or books. It links every fact to its exact spot in the original, creates interactive visuals for easy checks, handles huge files fast with chunking and parallel runs, and works with cloud or local models without fine-tuning. You benefit by quickly turning unstructured docs into reliable, organized data for analysis, saving time and boosting accuracy in fields like healthcare or research. https://github.com/google/langextract

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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