End to End Agentic Chatbot 🚀

🧠 An end-to-end AI Agentic system built with LangGraph, LangChain, and Streamlit.

This chatbot goes beyond simple conversation by integrating real-time web search 🌐 and automated news summarization 📰.

🚀 Live Demo & walkthrough

• Live Application: agenticchatbot-rathod0007.streamlit.app
• Video Walkthrough: Loom Demo

✨ Features

• Basic AI Chatbot: Intelligent conversational interface.
• Web Search Integration: Powered by Tavily API for real-time external data retrieval.
• AI News Summarizer: Generates Daily, Weekly, and Monthly reports.
• Automated Storage: Summaries are automatically saved as Markdown files in a structured directory.
• Modern UI: Clean and responsive interface built with Streamlit.

📂 Project Structure

AgenticChatbot/
├── AINews/                 # Generated AI News reports (.md)
│   ├── daily_summary.md
│   ├── monthly_summary.md
│   └── weekly_summary.md
├── src/
│   └── langgraphagenticai/
│       ├── graph/          # LangGraph workflow definitions
│       │   └── graph_builder.py
│       ├── LLMS/           # LLM configurations (Groq, etc.)
│       │   └── groqllm.py
│       ├── nodes/          # Individual agent nodes
│       │   ├── ai_news_node.py
│       │   ├── basic_chatbot_node.py
│       │   └── chatbot_with_tool_node.py
│       ├── state/          # State management for the graph
│       │   └── state.py
│       ├── tools/          # Custom tools (Tavily Search, etc.)
│       │   └── search_tool.py
│       ├── ui/             # Streamlit frontend components
│       │   └── streamlitui/
│       │       ├── display_result.py
│       │       ├── loadui.py
│       │       └── uiconfigfile.py
│       ├── main.py         # Logic entry point
│       └── __init__.py
├── app.py                  # Main Streamlit application entry
├── requirements.txt        # Project dependencies
└── README.md

🖼️ Visuals & Screenshots

🖥️ Application Interface

Main UI	Web Search Feature

📂 Project Structure Visuals

To understand the modular architecture of this agentic system:

Core Structure	Source Internals	Sub-modules

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🤖 Feature Spotlights

1. Basic Chatbot

Simple and intuitive conversational agent powered by Groq/OpenAI.

2. Intelligent Web Search

The agent uses Tavily to browse the live web and provide cited answers.

3. AI News Summarizer

Automated workflows that generate and save markdown reports.

Summarization Process	Generated Output

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🛠️ Tech Stack

🧠 Orchestration & Frameworks

🤖 AI & LLM Inference

📊 Vector Store & Frontend

🚀 Domain Expertise

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📦 Core Dependencies

The system leverages a modern AI stack for orchestration, inference, and real-time data:

• Orchestration Framework: langgraph, langchain, langchain-core, langchain-community, langchainhub
• LLM Providers: langchain-groq (Llama-3.1 8B instant), langchain-openai
• Search Engine: tavily-python (Optimized for AI Agents)
• User Interface: streamlit
• Vector Database: faiss-cpu
• Environment & CLI: python-dotenv, langgraph-cli[inmem]

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⚙️ Installation & Setup

Follow these steps to get the Agentic Chatbot running locally:

1. Clone the Repository

git clone [https://github.com/rathod-0007/AgenticChatbot.git](https://github.com/rathod-0007/AgenticChatbot.git)
cd AgenticChatbot

2. Create a Virtual Environment (Recommended)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Configure Environment Variables

Create a .env file in the root directory and add your API credentials:

GROQ_API_KEY=your_groq_api_key_here
TAVILY_API_KEY=your_tavily_api_key_here
OPENAI_API_KEY=your_openai_api_key_here

5. Launch the Application

streamlit run app.py

Made with 🩵 by rathod-0007
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