TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #14648 · Apr 30
#java#ai#apache_kafka#aws#azure#cloud#cloud_first#cloud_native#ebs#gcp#kafka#llm#messaging#minio#s3#serverless#spot#streaming AutoMQ provides a cloud-native alternative to Apache Kafka that runs on S3 storage, cutting costs by up to 90% while enabling instant scaling and eliminating cross-zone traffic fees. It offers high reliability, serverless operation, and full Kafka compatibility, making it easier and cheaper to manage large-scale data streaming without sacrificing performance or features. https://github.com/AutoMQ/automq
Search: #easy
@R4marketing · Post #806 · 08/13/2021, 08:00 AM
Совсем лайтовая статья для новичков "10 главных конструкций языка R". Содержание: - Комментарии - Переменные и векторы - Внешние модули - Ввод и вывод - Присваивание и сравнение - Условный оператор if - Цикл for - Функции - Классы, методы и объекты #статьи #easy
@testflightynoti · Post #37780 · 05/07/2026, 08:30 PM
#Futubull#Easy#Investment Join the Futubull-Easy Investment beta on ✈️#TestFlight 🔗 Link: https://testflight.apple.com/join/LXJdcvBn Shared by Dimitri
@WangZhuanZhan · Post #34299 · 10/23/2024, 12:23 PM
X-x喜x乐l长c安a- 喜乐长安 (2016) 直达链接：https://pan.quark.cn/s/4723d3f85101 #喜乐长安 #长安乱 #Easy Life 链接：https://link3.cc/sf_com #电影#喜剧#台湾#10年代
@wangzhuanzhan · Post #33280 · 09/23/2024, 06:10 AM
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@WangZhuanZhan · Post #34066 · 10/15/2024, 05:50 AM
T-t通t天t大d盗d- 通天大盗 通天大盜 (1987) 直达链接：https://pan.quark.cn/s/c40ba0abe557 #通天大盗#通天大盜 #妙婿向钱冲#Easy Money 链接：https://link3.cc/sf_com #电影#喜剧#香港#80年代
@wangzhuanzhan · Post #32222 · 09/03/2024, 08:49 AM
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@testflightynoti · Post #37748 · 05/07/2026, 08:21 AM
#Easy#Credit#T#i#ch#nh#s Join the Easy Credit - Tài chính số beta on ✈️#TestFlight 🔗 Link: https://testflight.apple.com/join/B8XYxOWV Shared by Dimitri
@githubtrending · Post #15433 · 01/23/2026, 02:30 PM
#python#deepseek#demo#easy#embedding#flask#gpt#huggingface_transformers#llm#mcp#multimodal#openai#qwen#rag#sentence_transformers#ui#vllm#vlm UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles. https://github.com/OpenBMB/UltraRAG