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🤖 Agentic AI Apps

Author: Mansoor Khan (GitHub: rebase-master)
Repository: agentic-ai-apps


🧠 Overview

This repository contains a collection of agentic AI applications and prototypes that explore how AI agents can collaborate, reason, and perform complex workflows using various frameworks and techniques — such as LangChain, LangGraph, and custom multi-agent orchestration.

Each branch in this repository represents a self-contained AI project, built to demonstrate different problem-solving capabilities — from order handling and customer service to summarization and product Q&A systems.


🌿 Repository Structure

Each project lives on a separate branch to keep implementations modular and independent.

Branch Description
customer-service-ai-agent A conversational customer service AI agent capable of handling user queries, managing support tickets, and simulating real-world customer interaction workflows.
multi-agent-systems-with-langgraph A multi-agent orchestration system built using LangGraph, where different specialized agents (Product, Orders, Small Talk) collaborate to process user requests intelligently.
orders-chatbot-with-custom-agent A custom AI agent chatbot that manages product orders — capable of updating, tracking, and summarizing order data through conversational inputs.
product-qna-agentic-chatbot An Agentic Q&A chatbot designed to answer user questions about products using a retrieval-augmented approach (RAG) and structured reasoning.
summary-chatbot-with-reviewer A summarization chatbot enhanced with a reviewer agent that validates and refines generated summaries for higher factual accuracy.

🚀 Key Highlights

  • 🧩 Agentic architecture: Each project demonstrates autonomous or semi-autonomous AI behavior.
  • ⚙️ Multi-agent coordination: LangGraph and tool-based routing to dynamically select specialized agents.
  • 📦 Modular design: Independent branches for clarity and maintainability.
  • 🗣️ Conversational workflows: Integration with chat-style user interfaces and context-aware prompts.
  • 🔍 Retrieval and reasoning: Use of embeddings, context memory, and structured tool invocation.

🧰 Technologies Used

  • LangChain / LangGraph
  • OpenAI APIs
  • Python (async / FastAPI / tool decorators)
  • Pandas, Pydantic, and data processing utilities
  • JSON-based state and workflow orchestration

📘 How to Explore

Each branch includes:

  • A Jupyter Notebook (.ipynb) or Python module demonstrating the agent logic.
  • Example prompts and workflows.
  • README or inline documentation describing how the agent functions.

To explore a project:

# Clone the repository
git clone https://github.com/rebase-master/agentic-ai-apps.git
cd agentic-ai-apps

# Switch to a specific project branch
git checkout <branch-name>

📄 License

This repository is open source under the MIT License. Feel free to explore, adapt, and build upon these agentic AI systems.


👤 Author

Mansoor Khan 🔗 (GitHub Profile)

If you find these projects useful, consider giving the repository a ⭐ on GitHub!

About

This repository contains a collection of agentic AI applications and prototypes that explore how AI agents can collaborate, reason, and perform complex workflows using various frameworks and techniques - such as LangChain, LangGraph, and custom multi-agent orchestration. Refer to different branches for different Agentic AI apps.

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