Skip to content
View Wxysnx's full-sized avatar
  • shenzhen

Block or report Wxysnx

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Wxysnx/README.md

你好,欢迎 👋

Python AI Machine Learning LLM

#!/usr/bin/env python
# -*- coding: utf-8 -*-

class AIEngineer:
    def __init__(self):
        self.name = "王祥宇"
        self.role = "AI Agent 工程师 | 产品经理"
        self.language_spoken = ["中文", "English"]
        
        # AI 和机器学习技术栈
        self.ai_stack = {
            "智能体框架": ["LangGraph", "CrewAI", "Microsoft AutoGen", "LangChain", "MetaGPT"],
            "大语言模型": ["OpenAI GPT", "Anthropic Claude", "DeepSeek"],
            "RAG技术": ["Agentic RAG", "RecursiveCharacterTextSplitter", "向量化检索", "混合记忆架构"],
            "多模态应用": ["医学影像处理", "BiomedCLIP", "多模态融合算法"],
            "分布式推理": ["vLLM", "Ray Framework"],
            "数据存储": ["ChromaDB", "MongoDB Atlas", "Redis"],
            "后端开发": ["FastAPI", "asyncio", "事件驱动架构"],
            "云原生技术": ["Kubernetes", "Docker", "Kafka"]
        }
        
        # 专业领域
        self.specialties = [
            "多智能体系统设计与实现",
            "LLM应用开发与集成",
            "State Graph 工作流设计",
            "垂直领域AI解决方案",
            "记忆管理系统设计",
            "RAG技术与向量数据库应用",
            "高性能分布式AI系统"
        ]
        
        # 项目经验
        self.projects = {
            "AI记忆增强系统": "基于LangGraph的智能生成式AI记忆管理系统,解决LLM上下文限制问题",
            "CT影像智能分析系统": "基于CrewAI的多智能体医学影像分析系统,为放射科医生提供智能辅助诊断",
            "Agentic RAG系统": "基于LangChain和LangGraph的智能检索增强生成系统,实现动态工作流程",
            "网页内容摘要系统": "基于AutoGen框架的多代理网页内容智能提取系统",
            "自动化股票分析系统": "基于CrewAI的多智能体股票分析工具,集成SEC EDGAR数据分析",
            "对话记忆管理系统": "基于LangGraph的持久化对话代理,实现高效的消息处理和记忆管理"
        }
        
        # 专业优势
        self.strengths = [
            "精通前沿智能体框架,具备复杂多代理系统设计能力",
            "深入理解大语言模型应用与集成技术",
            "将AI Agent技术应用于医疗、金融和内容分析等垂直领域",
            "精通记忆管理系统设计和云原生AI部署",
            "深入理解RAG技术与向量数据库应用"
        ]
    
    def say_hi(self):
        print(f"👋 你好!我是{self.name},一位{self.role}")
        print("✨ 我专注于LLM、多智能体系统和RAG技术的开发,致力于构建下一代AI应用。")
        print("🚀 我熟练运用LangGraph、CrewAI、AutoGen等前沿智能体框架构建复杂系统。")
        print("🔍 拥有扎实的智能体架构设计经验和垂直领域AI解决方案能力。")
        print("💡 欢迎探索我的项目,或就AI Agent相关技术进行交流!")

me = AIEngineer()
me.say_hi()

Pinned Loading

  1. CTAnalyticsAgent CTAnalyticsAgent Public

    It is an advanced medical CT image analysis system that uses a multi-agent collaborative framework and the latest AI technology to automatically analyze CT images, retrieve medical knowledge, and g…

    Python 18 5

  2. CrewAI-StockAnalyst CrewAI-StockAnalyst Public

    An advanced multi-agent stock analysis system built with CrewAI that leverages collaborative AI agents to perform comprehensive financial analysis, extract insights from SEC filings, and generate d…

    Python 3 1

  3. ai-memory-system ai-memory-system Public

    A high-performance, distributed memory management system for LLM agents built with LangGraph, LangChain, Ray, and vLLM. Features multi-layer memory architecture, semantic retrieval, and event-drive…

    Python 11 3

  4. AutoGenAgent AutoGenAgent Public

    AutoGen-powered web content extraction system with multi-agent architecture for intelligent crawling, processing and summarization of web pages, designed for efficient information processing at scale.

    Python 3 1

  5. LangChain-RAG LangChain-RAG Public

    This project implements an Agentic Retrieval Augmentation Generation (Agentic RAG) system based on LangChain and LangGraph.

    Python 9 2

  6. LangGraphTinyAgent LangGraphTinyAgent Public

    A minimal LangGraph-powered chatbot with persistent memory for maintaining context across multiple conversations

    Python 3 1