🧠 Agentic-AI – Building Agentic Workflows with LangGraph & AI Agents

Agentic-AI is a collection of intelligent agents and workflows built using LangGraph, LangChain, and modern LLM frameworks.
It demonstrates how AI agents can collaborate, reason, and interact with external tools for real-world applications like finance, document analysis, video summarization, and more.

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🚀 Features

• 🔗 LangGraph-powered Agents – Build modular, graph-based agent workflows.
• 💬 Conversational Chatbots – Multi-tool and memory-enabled chatbots.
• 📊 Financial AI Analyst – Agents designed for financial analysis and decision support.
• 📄 PDF Assistant – Smart assistant for document parsing and Q&A.
• 🎥 Video Summarizer – Automatic video-to-text summarization pipeline.
• 🛠️ Debugging & Tracing – Agent debugging with LangSmith integration.
• 🌦️ MCP Demos – External tool integrations like weather, math server, and more.

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📂 Project Structure

• AgenticLangGraph/ → Core LangGraph agent workflows & debugging
• Debugging/ → Tracing, API debugging, and graph inspection
• Financial_AI_Analyst/ → Financial data agents & analysts
• LangGraph/ → Chatbots, memory, conditional edges, tool calling, and human-in-the-loop demos
• MCP_demo/ → Modular tool-based agents (math, weather, client-server agents)
• PdfAssistant/ → Document parsing and PDF-based assistant
• VideoSummarizer/ → Agent pipeline for summarizing videos
• RecipeChefAgent_LangFlow.json → Agent design in LangFlow

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🛠️ Tech Stack

• Core Frameworks: LangGraph, LangChain, LangFlow
• LLMs: OpenAI GPT, other pluggable LLMs
• Integrations: LangSmith (tracing), external APIs (weather, math), PDF parsing
• Languages: Python
• Dependencies: Managed with pyproject.toml and requirements.txt

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⚡ Getting Started

1. Clone the repository:

   git clone https://github.com/PRANAVBALAJIRS/Agentic-AI.git
   cd Agentic-AI
   

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate   # Linux/Mac
   venv\Scripts\activate      # Windows
   
   

3. Install dependencies:

     pip install -r requirements.txt
   

4. Run a demo (example: PDF Assistant):

     cd PdfAssistant
     python pdf_assistant.py