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Source channel @githubtrending · Post #15085 · Aug 22

#python#chatbi#deepseek#llm#nl2sql#rag#sqlbot#text_to_sql#text2sql SQLBot is an easy-to-use intelligent system that turns natural language questions into SQL queries using advanced AI models and retrieval-augmented generation (RAG). You just need to set up your AI model and data source to start asking questions about your data. It integrates smoothly with other business systems and AI platforms, making it simple to add smart data querying to your apps. It also ensures data security with workspace-based resource isolation and fine-grained access control. You can quickly deploy it on a Linux server using Docker, enabling fast, secure, and intelligent data interaction without needing deep SQL knowledge. This saves you time and improves data accessibility. https://github.com/dataease/SQLBot

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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

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