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Source channel @githubtrending · Post #14826 · Jun 12

#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data. https://github.com/FareedKhan-dev/all-rag-techniques

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@githubtrending · Post #15060 · 08/15/2025, 11:30 AM

#python#alibabacloud#android#android_emulator#aws#azure#cloud#docker#docker_android#emulator#gcp#genymotion#jenkins#kubernetes#mobile_app#mobile_web#novnc#saltstack#selenium#selenium_grid#terraform You can use Docker-Android to run Android emulators inside Docker containers, which helps you develop and test Android apps easily without needing physical devices. It offers many device profiles like Samsung Galaxy and Nexus models, supports viewing the emulator via VNC, sharing logs through a web interface, and controlling the emulator remotely with adb. It works on Ubuntu and can integrate with cloud services like Genymotion. This setup speeds up development, testing, and automation, making your workflow more consistent and efficient while saving resources. You can also persist data and run unit or UI tests with popular frameworks like Appium and Espresso. This helps you build and test Android apps faster and more reliably. https://github.com/budtmo/docker-android