The Devs
@thedevs · Post #1159 · 06/29/2018, 06:52 PM
A plain English introduction to JSON web tokens (JWT): what it is and what it isn’t. #article#jwt#security#coding#js @thedevs https://kutt.it/ibVW1N
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Source channel @githubtrending · Post #15536 · Mar 3
#python#agent#chatbot#large_language_models#llm#llm_agent#mcp#multi_agent#multi_modal#react_agent AgentScope is a simple, production-ready framework to build AI agents fast. Install with `pip install agentscope` (Python 3.10+), then create ReAct agents with tools, memory, voice, human steering, multi-agent workflows, and finetuning in 5 minutes. It supports realtime voice, A2A protocols, RL training, and easy deployment locally, in cloud, or Kubernetes. You benefit by quickly making robust, scalable agents for tasks like games, research, or chats without complex coding, saving time and enabling real-world apps. https://github.com/agentscope-ai/agentscope
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djangoproject
@djangoproject · Post #389 · 07/21/2017, 03:12 PM
https://thinkster.io/topics/django Looking to build #fullstack apps with #Django? Looking to build a production ready Django #JSON#API? Building a Production Ready Django JSON API 🔸Setting up #JWT Authentication 🔸Profiles 🔸Articles 🔸Comments 🔸Following 🔸Favoriting 🔸Tagging 🔸Pagination 🔸Filtering 🔸Conclusion Configuring Django Settings for Production Building #Web#Applications with Django and #AngularJS 🔸Learning Django and AngularJS 🔸Setting up your environment 🔸Extending Django's built-in User model 🔸Serializing the Account Model 🔸Registering new users 🔸Logging users in 🔸Logging users out 🔸Making a Post model 🔸Rendering Post objects 🔸Making new posts 🔸Displaying user profiles 🔸Updating user profiles 🔸Congratulations, you did it!
GitHub Trends
@githubtrending · Post #15066 · 08/16/2025, 12:30 PM
#python#agents#ai#api_gateway#asyncio#authentication_middleware#devops#docker#fastapi#federation#gateway#generative_ai#jwt#kubernetes#llm_agents#mcp#model_context_protocol#observability#prompt_engineering#python#tools The MCP Gateway is a powerful tool that unifies different AI service protocols like REST and MCP into one easy-to-use endpoint. It helps you manage multiple AI tools and services securely with features like authentication, retries, rate-limiting, and real-time monitoring through an admin UI. You can run it locally or in scalable cloud environments using Docker or Kubernetes. It supports various communication methods (HTTP, WebSocket, SSE, stdio) and offers observability with OpenTelemetry for tracking AI tool usage and performance. This gateway simplifies connecting AI clients to diverse services, making development and management more efficient and secure. https://github.com/IBM/mcp-context-forge