#FastAPI
93 related articles
·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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·2 min
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
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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·3 min
CrewAI + FastAPI in Practice: Building a Multi-Agent Collaborative Application
Learn CrewAI's core concepts (Agent, Task, Process, Crew, Pipeline) and how to wrap a multi-Agent service with FastAPI. Covers GPT, Qwen, and Ollama local model integrations with real benchmark comparisons.
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·2 min
FastAPI Fundamentals: Web Development Patterns, API Interfaces, and RESTful Standards Explained
Learn FastAPI fundamentals: frontend-backend separation, what API interfaces really are, and how RESTful standards work. Essential groundwork for Python backend development.
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·2 min
Getting Started with FastAPI: Understanding Frontend-Backend Separation and RESTful API Design
Learn FastAPI from the ground up: understand frontend-backend separation, Starlette's ASGI architecture, and RESTful API design before writing a single line of code.
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Tutorials·3 min
Getting Started with FastAPI: A Comprehensive Guide to Frontend-Backend Separation and RESTful API Core Concepts
A systematic guide to core concepts for FastAPI beginners, covering frontend-backend separation architecture, RESTful API design, and JSON data format advantages for Python developers.
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Tutorials·3 min
Practical Guide to Building Multi-Agent Collaborative Applications with CrewAI + FastAPI
Learn how to build a multi-Agent collaborative system with CrewAI and FastAPI. Covers Agent, Task, Crew concepts, GPT/Tongyi Qianwen/Ollama integration, with complete code examples and model comparisons.
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Tutorials·3 min
FastAPI Beginner Tutorial: Frontend-Backend Separation and RESTful API Core Concepts
FastAPI beginner essentials: Learn frontend-backend separation vs monolithic web development, RESTful API design principles, HTTP methods and resource operations mapping.
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·3 min
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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·3 min
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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·1 min
Ponytail: The Open-Source Skill That Makes AI Write Less Code, Gaining 59K Stars in a Month
Ponytail, GitHub's #1 monthly open-source Skill, injects a 'less is more' philosophy into AI Agents, cutting code volume by an average of 54%. Compatible with 20+ Agents including Claude Code, Cursor, and Copilot.
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·1 min
Ponytail: The Open-Source Skill That Makes AI Write Less Code, Gaining 59K Stars in a Month
Ponytail, GitHub's #1 monthly open-source Skill, injects a 'less is more' engineering philosophy into AI Agents, cutting code volume by 54% on average. Compatible with 20+ Agents like Claude Code and Cursor.
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·2 min
The New Bar for AI/LLM Roles: A Practical Guide to Agent Observability and Evaluation
Enterprise AI/LLM roles now demand engineering skills: streaming recovery, high concurrency, multi-tenancy, LLM gateways, Langfuse observability, and evaluation platforms. Master these 8 core competencies.
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·8 min
A Complete Guide to Agent Testing: Five Core Dimensions and Automation in Practice
In-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing and the transition path for test engineers.
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·8 min
The Complete Guide to Agent Testing: Five Core Dimensions and Automation in Practice
An in-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing methods and the transition path for test engineers.
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Outlines: The Open-Source Tool for Get…
·2 min
Outlines: The Open-Source Tool for Getting Structured Output from LLMs
Outlines is an open-source Python library for structured LLM output. Using constrained decoding with FSMs, it guarantees JSON, regex, and Pydantic-compliant generation with near-zero overhead.
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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
The Truth Behind Three RAG Pipeline Crashes: Why Inter-Stage Data Contracts Matter
A RAG pipeline crashed three times due to inter-stage data format mismatches. Learn how JSON Schema and Pydantic explicit contracts turn fragile AI pipelines into maintainable systems.
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