TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #15537 · Mar 3
#python#agent#ai_agents#memory#memoryscope#rag#reme ReMe is a memory toolkit for AI agents with file-based (Markdown files for easy editing) and vector-based systems to fix limited context and stateless chats. It auto-summarizes talks, saves key facts like preferences, and recalls them next time using hybrid search. Install via `pip install reme-ai`, set API keys, and use ReMeCli or Python code for smart agents. You benefit by building persistent, learning agents that remember your needs, work faster on repeat tasks, and feel more natural without starting over. https://github.com/agentscope-ai/ReMe
Search: #runtime
@golang · Post #58 · 04/22/2018, 08:22 PM
Why are goroutines not lightweight threads? Kartik Khare shows us his meaning about goroutines, lightweight threads and their difference in GoLang. There are no code examples inside but good thoughts about parallelism, threads and useful links at the end of the article :) #development#runtime#language https://codeburst.io/why-goroutines-are-not-lightweight-threads-7c460c1f155f
Hashtags
@golang · Post #64 · 06/21/2018, 04:17 PM
Hi there! Which ways do you use to avoid memory leaks for REST API? In the following article by Iman Tumorang describes an excellent example of memory leaks, his solution, and results. Must have to read for everyone 😉 #development#runtime#architecture https://hackernoon.com/avoiding-memory-leak-in-golang-api-1843ef45fca8
@githubtrending · Post #15382 · 01/01/2026, 12:30 PM
#jupyter_notebook#agent#agentic_ai#agents#authentication#bedrock#core#gateway#identity_management#memory_management#production_code#runtime Amazon Bedrock AgentCore lets you build, deploy, and run AI agents securely at scale with any framework like CrewAI or LangGraph and any model, without managing complex infrastructure. It offers serverless runtime for long tasks up to 8 hours, gateway to connect tools like Slack or APIs easily, memory for personalized experiences, identity management, built-in code interpreter and browser tools, plus observability. This saves time by skipping heavy setup, speeds prototypes to production, cuts costs with pay-per-use, and boosts security—helping you create powerful agents faster for real business needs. https://github.com/awslabs/amazon-bedrock-agentcore-samples