#FastAPI agent
67 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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·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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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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·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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FastMCP: The Go-To Framework for Pytho…
·2 min
FastMCP: The Go-To Framework for Python Developers Building MCP Servers and Clients
FastMCP is a Pythonic MCP framework by PrefectHQ that lets developers build MCP servers and clients with minimal code using decorators. 26,000+ GitHub stars.
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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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·3 min
Build an MCP Server in 10 Minutes: Let AI Call Your Code Directly
MCP (Model Context Protocol) is the open standard for AI tool integration. Build your own MCP server with ~20 lines of Python. Learn tools, resources, prompts, and both local and remote deployment.
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There's No Best Agent Framework — Only…
·2 min
There's No Best Agent Framework — Only the Right One for Your Needs: A Deep Comparison of Leading Options
LangGraph, PydanticAI, OpenAI Agents SDK, CrewAI — a senior developer's practical guide to choosing the right AI Agent framework for your project.
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·3 min
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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