# adongwanai/AgentGuide

https://adongwanai.github.io/AgentGuide | AI Agent开发指南 | LangGraph实战 | 高级RAG | 转行大模型 | 大模型面试 | 算法工程师 | 面试题库 | 强化学习｜数据合成

Repository: https://github.com/adongwanai/AgentGuide
Canonical: https://ross.abutalabs.com/products/agentguide
Language: HTML
License Family: other
Topics: ai-agent, crewai, interview, job-hunting, langchain, llm, multi-agent, rag, tutorial, agenticrag, graphrag, grpo, sft
Last push: 2026-08-25T04:23:33+00:00

## Health v2 (maintenance only)
Score: 61/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 21
- inputs: {"age_days": 303, "days_push": 8, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 8836, forks 863 (observed 2026-08-28T04:10:25.949292+00:00)

## What it is
AgentGuide is an open-source, job-oriented learning guide for AI Agent development, covering LangGraph, advanced RAG, fine-tuning, and reinforcement learning, styled after JavaGuide. It curates existing resources into a systematic roadmap with interview question banks and resume advice for landing LLM-related roles.

## Use cases
- learn ai agent development from scratch
- prepare for llm algorithm engineer interview
- transition career into large language models
- find a rag tutorial with practical projects
- get a study roadmap for ai agent jobs
- find interview question bank for machine learning roles
- learn langgraph and multi-agent systems

## When to choose
- you want a structured, job-hunting-oriented path into AI agent development
- you need curated interview questions and resume tips for LLM roles
- you prefer a roadmap that links existing courses, papers, and projects instead of building from scratch

## When to avoid
- you need runnable production code or a software library
- you require a formally licensed open-source project (no license is provided)
- you want deep original technical content rather than curated links and guides

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, rag, agent-framework, llm-training, prompt-engineering
- domain: large-language-models, tutorials, education, artificial-intelligence
- platform: cross-platform
- tags: interview-preparation, career-guide, langgraph, multi-agent, job-hunting, study-roadmap, chinese-language, ai-agents, retrieval-augmented-generation, web-server

## Member repositories
- adongwanai/AgentGuide (main) score 61

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:25.949292+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:24:49.115344+00:00, confidence not recorded.
  - readme: https://github.com/adongwanai/AgentGuide (fetched 2026-08-28T04:10:25.949292+00:00, sha 8358a5889c66)
- Data as of 2026-08-30T08:39:29.467469+00:00.