AI Analytics Agent is a powerful, interactive dashboard built with Streamlit that leverages AI to provide deep insights into business data. It combines traditional analytics (KPIs, forecasting, segmentation) with Generative AI (LLMs) to allow users to ask questions about their data in natural language.

The application features a modern, responsive UI with real-time data simulation, anomaly detection, and predictive modeling.

• 📊 Comprehensive KPI Dashboard: Real-time tracking of Revenue, Growth, and Customer Satisfaction.
• 🤖 AI-Powered Insights: Integrated Chatbot to answer questions about data trends and forecasts.
• 📈 Predictive Analytics: Time-series forecasting and trend analysis using machine learning.
• 👥 Customer Segmentation: Clustering analysis to identify key customer groups.
• 🚨 Anomaly Detection: Automated detection of unusual patterns in data.
• 📱 Responsive Design: A sleek, glassmorphism-inspired UI that works on all devices.

The following diagram illustrates the high-level architecture of the AI Analytics Agent:

graph TD
    User([👤 End User])

    subgraph Frontend [🖥️ Streamlit Frontend]
        UI[User Interface]
        Sidebar[Sidebar Controls]
        Charts[Plotly Charts]
        Chat[Chat Interface]
    end

    subgraph Core [⚙️ Application Logic]
        DataGen[Data Generators]
        MLModels[ML & Forecasting]
        Anomaly[Anomaly Detection]
        State[Session State Mgmt]
    end

    subgraph AI [🧠 AI Layer]
        LLMHub[LLM Integration]
        PromptEng[Prompt Engineering]
    end

    User -->|Interacts| UI
    UI -->|Triggers| DataGen
    UI -->|Displays| Charts
    User -->|Asks Questions| Chat
    Chat -->|Queries| LLMHub
    DataGen -->|Feeds| MLModels
    MLModels -->|Results| Charts
    DataGen -->|Checks| Anomaly
    Anomaly -->|Alerts| UI

• Python 3.8 or higher
• pip (Python package installer)

1. Clone the repository:

   git clone https://github.com/yourusername/ai-analytics-agent.git
   cd ai-analytics-agent

2. Install dependencies:

   pip install -r requirements.txt

   (Note: If requirements.txt is missing, you can install the main packages directly: pip install streamlit plotly pandas numpy)

To start the dashboard, run the following command in your terminal:

streamlit run app.py

The application will open in your default web browser at http://localhost:8501.

classDiagram
    class App {
        +run()
        +setup_page()
    }
    class DataEngine {
        +generate_kpis()
        +generate_forecast()
    }
    class Views {
        +render_dashboard()
        +render_sidebar()
    }

    App --> Views : Renders
    App --> DataEngine : Uses

• Streamlit - The core framework for the web app.
• Plotly - For interactive and beautiful visualizations.
• Pandas & NumPy - For data manipulation and analysis.