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Agwave/README.md

👋 Hi, I'm Agwave(chenyinbo) | AI Agent & Knowledge Graph Architect

🤖 架构 AI 与图智能的未来 | Architecting the Future of Agentic AI

我是一名深耕 AI AgentGraphRAG 系统构建的资深工程师。我专注于智能数据的全生命周期管理:从支撑海量异构数据的 高性能 ETL,到 图数据库 中的复杂关系建模,再到利用 LangGraph 编排多体协同工作流,从而交付具备行动力的洞察。

I specialize in the entire lifecycle of intelligent data: from high-performance ETL ingesting massive data, to Graph Modeling, and orchestrating multi-agent workflows to deliver actionable insights.

  • 🔭 核心聚焦 / Focus: 基于 LangGraph & MCP 构建自主 Agent,并由语义增强的 GraphRAG 驱动。
  • 性能与规模 / Scale: 精通数据库 I/O 优化与分布式系统 (Kubernetes, Kafka)。
  • 🧠 工程落地 / Engineering: 致力于将 机器学习理论 (ML Theory) 转化为可扩展的工程实践。

🧰 技术版图 / Technical Ecosystem

根据数据问题的维度选择最合适的工具。Selection of tools based on data dimensions.

领域 / Dimension 技术栈 / Technologies
AI & Agent 编排 LangChain/LangGraph, MCP, Vector DBs, ML Theory
图与 NoSQL (核心) ArangoDB, Nebula Graph, Cassandra, Redis
关系型数据库 PostgreSQL, MySQL, Oracle
大数据与 ETL Kafka, HDFS, Hive, Impala
开发语言 / Lang Python (AI/DS), Go (High-perf Services)
前端与 UI Next.js, Tailwind CSS, shadcn/ui
基础设施 / Infra Docker, Kubernetes (K8s), CI/CD

🧠 AI 原生开发流 / AI-Native Development Workflow

我利用前沿的 AI 编程智能来加速开发并确保代码质量。 I leverage AI intelligence to accelerate development and ensure code quality.

Cursor Claude GitHub


📈 数据统计 / GitHub Stats

Your GitHub stats Top Langs


📍 Based in Shenzhen, China | 欢迎关于 Graph-AI、智能 ETL 和 Agentic RAG 的技术交流与合作。

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