#FastAPI backend architecture
53 related articles
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Build RAG and AI Agent Projects at Zero Cost: A Practical Guide to Open-Source Tools
Build high-quality AI projects on a budget. Learn how to use Ollama, Groq, Chroma, and other free open-source tools to build RAG systems and multi-Agent workflows from scratch.
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Build RAG and AI Agent Projects at Zero Cost: A Practical Guide to Open-Source Tools
Build high-quality AI projects on a budget. Learn how to use Ollama, Groq, Chroma, and other free open-source tools to build RAG systems and multi-Agent workflows from scratch.
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·2 min
Multi-Agent Collaborative Paper Writing System: End-to-End Automation with FastAPI + Vue 3
An in-depth look at an intelligent paper writing platform built on FastAPI + Vue 3, combining LLM, RAG, and multi-Agent collaboration for full-process automation—an excellent case study for AI developers.
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·3 min
Multi-Agent AI Paper Writing System: A Full-Stack Breakdown of FastAPI + Vue3
A deep dive into an AI paper writing system built with FastAPI + Vue3, covering multi-agent collaboration, RAG, streaming output, and full academic workflow automation.
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FastAPI Fundamentals: Frontend-Backend Separation and RESTful Design Explained
Learn the core concepts behind FastAPI: frontend-backend separation, API interface design, and RESTful specification. Master resource-oriented design before writing your first line of code.
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·2 min
3-Month Roadmap to Becoming an AI/LLM Engineer: A Systematic Learning Guide
A 3-month structured roadmap for developers transitioning into AI/LLM engineering: Python & API basics, LangChain/FastAPI stack, and RAG/Agent projects.
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·3 min
LangGraph Production Template in Practice: A Complete Guide to Budget Control and Canary Routing
Deep dive into langgraph-agent-stack: per-run dollar budget control, canary traffic routing, Mock testing mode, and 800+ test cases to safely deploy AI Agents from demo to production.
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GitHub Daily · July 20: AI Agent Infra…
·3 min
GitHub Daily · July 20: AI Agent Infrastructure Explodes Across the Board
AI Agent infrastructure explodes across GitHub Trending: OmniRoute unifies 268+ providers, cognee adds long-term memory, and self-hosted openship tops growth with +1719 stars.
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AI/ML Students Lost in Job Search? A Deep Comparison of Four Career Paths and How to Choose
AI/ML students unsure which career path to pursue? Compare AI engineering, SDE, PM, and UI/UX in depth — with honest entry barriers and a practical self-assessment framework.
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Harness Architecture in Practice: A Deep Dive into Enterprise-Level Agent Projects
A deep dive into Harness architecture in enterprise Agent projects, covering MCP protocol, sandbox isolation, multi-model scheduling, and ASGI deployment — key topics for LLM job interviews.
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·2 min
Dify vs Coze: Open-Source Self-Hosting or Cloud-Based Out-of-the-Box?
Coze vs Dify: a deep-dive comparison covering deployment, data security, and ease of use. Find out which AI agent platform suits individual developers vs. enterprises.
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·2 min
Hombre: An Open-Source Visual Dashboard for Honcho AI Memory Server
Hombre is an open-source web GUI for self-hosted Honcho AI memory servers. Features workspace management, semantic search, real-time sync, and RBAC — built with FastAPI and native frontend, MIT licensed, Docker-ready.
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·4 min
Behind India's 5% AI Hiring Dip: Core Skill Demand Structure Remains Rock Solid
India's AI/data science postings hit 11,557 this week, down 5% from last week, but the skill demand structure barely changed. Python, ML, and SQL remain top skills while GenAI/LLM demand keeps rising.
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·5 min
From Prompts to Harness Engineering: The Evolution of AI Agent Development Paradigms
Why has AI engineering methodology evolved from prompts to context engineering and now Harness engineering? This article examines three paradigms, key bottlenecks, and the Agent = Model + Harness formula.
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·7 min
LangChain Hands-On Guide: From LLM Calls to Agent Development
Master LangChain from scratch: the three limitations of LLMs, init_chat_model unified interface config, the Message type system, and the path from LLM calls to Agent development.
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·7 min
LangChain.js + Nuxt.js: An AI Full-Stack Advancement Path for Frontend Engineers
Frontend hiring now treats AI capabilities as a core assessment, covering RAG knowledge bases, AI Agent development, and LangChain.js engineering. Learn how LangChain.js + Nuxt.js helps frontend developers build memory- and retrieval-capable AI full-stack apps.
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·2 min
FastAPI Fundamentals: Frontend-Backend Separation and RESTful API Design Explained
A comprehensive introduction to FastAPI's core concepts: frontend-backend separation, RESTful API design, JSON data exchange, HTTP methods, and idempotency explained clearly.
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·7 min
A Complete Guide to LangGraph's Core Concepts: The Framework of Choice for Enterprise Agent Development
An in-depth analysis of LangGraph's core concepts: short-term and long-term storage mechanisms, its differences from LangChain, the MIT open-source license, and private deployment solutions for enterprise Agent development.
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·7 min
The Complete Guide to OpenCode: Installing, Configuring, and Using the Terminal AI Coding Assistant
An in-depth guide to installing, configuring, and extending OpenCode, the terminal AI coding assistant. Covers desktop and WSL installation, model config, MCP integration, and custom Agents.
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·4 min
Frontend to Full-Stack AI: A Complete NestJS + LangChain Roadmap
Pure frontend roles are shrinking fast. Learn how mastering NestJS and LangChain AI agent development can unlock a 20–30% salary boost on your full-stack AI transition path.
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