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Upashak653/README.md

Hi there! πŸ‘‹ I'm Upashak

πŸš€ About Me

  • πŸ€– I'm currently working on Agentic AI systems with AutoGen and LangGraph workflows
  • 🧠 I'm currently learning Advanced LLM Integration and Stateful AI Agent architectures
  • 🌟 I specialize in OpenAI, Gemini, DeepSeek APIs and Hugging Face Transformers
  • πŸ‘― I'm looking to collaborate on Multi-Agent Systems and Graph-based AI workflows
  • πŸ’¬ Ask me about AutoGen, LangGraph, LLM APIs, Agentic AI, RAG systems, and stateful AI apps
  • ⚑ Fun fact: I love building autonomous AI agents with complex decision trees and state management!

πŸ› οΈ Technologies & Tools

Languages

Python JavaScript TypeScript HTML5 CSS3

AI/ML & Frameworks

AutoGen LangGraph LangChain Hugging Face OpenAI Google Gemini DeepSeek TensorFlow PyTorch

Web Development

React Flask FastAPI Streamlit Jupyter

Tools & Platforms

Git GitHub VS Code

πŸ”₯ Featured Projects

Multi-agent system for autonomous web research and data collection

  • Tech Stack: AutoGen, OpenAI GPT, Web Scraping APIs
  • Features: Intelligent agent coordination, real-time research, automated reporting
  • AI Models: GPT-4, Custom agent workflows

Next-gen content generation using multiple LLM providers

  • Tech Stack: TypeScript, React, OpenAI, Gemini, DeepSeek APIs
  • Features: Multi-model content generation, prompt optimization, real-time streaming
  • AI Integration: OpenAI GPT-4, Google Gemini Pro, DeepSeek models

AI-powered educational content generator with Hugging Face integration

  • Tech Stack: Python, Hugging Face Transformers, NLP Pipeline
  • Features: Context-aware question generation, difficulty scaling, bulk processing
  • AI Models: BERT, T5, Custom fine-tuned models

Advanced RAG system with vector embeddings and semantic search

  • Tech Stack: Python, Vector Databases, Embeddings, LLMs
  • Features: Semantic search, document retrieval, context-aware responses
  • AI Integration: OpenAI Embeddings, Pinecone/ChromaDB, RAG pipeline

πŸ“ˆ Contribution Activity

🎯 Current Focus & Goals

  • πŸš€ Building sophisticated multi-agent AI systems with AutoGen and LangGraph
  • πŸ•ΈοΈ Creating stateful AI workflows with complex decision trees and branching logic
  • 🀝 Developing collaborative AI agents that maintain context across conversations
  • 🧠 Exploring advanced prompt engineering and chain-of-thought reasoning
  • πŸ”— Integrating multiple LLM providers with intelligent routing and fallbacks
  • πŸ“š Contributing to open-source AI and graph-based agentic frameworks
  • 🌐 Deploying production-ready AI applications with persistent state management

πŸ’‘ AI Expertise Areas

  • πŸ€– Agentic AI: AutoGen, Multi-agent systems, Agent orchestration
  • πŸ•ΈοΈ Graph-based AI: LangGraph, Stateful workflows, Complex decision trees
  • 🧠 LLM Integration: OpenAI GPT-4, Google Gemini, DeepSeek, Claude
  • πŸ”— AI Frameworks: Hugging Face Transformers, LangChain, AutoGen Studio
  • πŸ“Š RAG Systems: Vector databases, semantic search, document retrieval
  • ⚑ Real-time AI: Streaming responses, async processing, WebSocket integration
  • πŸ”„ State Management: Persistent agent memory, conversation context, workflow orchestration

πŸ“« Let's Connect!

GitHub LinkedIn Email


πŸ’« "Code is like humor. When you have to explain it, it's bad." πŸ’«

Pinned Loading

  1. Agentic_AI Agentic_AI Public

    Jupyter Notebook

  2. ai-content-generator ai-content-generator Public

    TypeScript

  3. Autonomous_Web_Agent_and_Real_Time_Research Autonomous_Web_Agent_and_Real_Time_Research Public

    Python

  4. mcqgen mcqgen Public

    Jupyter Notebook

  5. vectorDB_GenAI vectorDB_GenAI Public

    Jupyter Notebook

  6. AutoGen-StartUp_recommender_- AutoGen-StartUp_recommender_- Public

    Python