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 #15494 · Feb 14
#cplusplus#ann_search#embedded_database#rag#vector_search#vectordb Zvec is a lightweight, open-source vector database built on Alibaba's Proxima engine that searches billions of vectors in milliseconds. You can install it instantly with a single command and start using it within seconds—no servers or complex configuration needed. It supports both dense and sparse vector embeddings, hybrid search combining semantic similarity with filters, and runs anywhere your code runs, from notebooks to edge devices. The key benefit is that you get production-grade, low-latency similarity search with minimal setup, making it ideal for AI applications like semantic search, recommendation systems, and retrieval-augmented generation without the overhead of traditional database infrastructure. https://github.com/alibaba/zvec
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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