ADOBuddy Python VS

A comprehensive Azure DevOps (ADO) assistant platform that combines AI-powered chatbot capabilities with specialized database script management tools. This project integrates with Azure DevOps through the Model Context Protocol (MCP) to provide intelligent work item management and automated task creation.

🌟 Overview

ADOBuddy Python VS is a dual-purpose application consisting of:

1. ADOBuddy Chatbot - An AI-powered conversational interface for Azure DevOps operations
2. Instant DB Script Maker - A specialized tool for database script processing and Azure DevOps task creation

🚀 Key Features

ADOBuddy Chatbot (ADOBuddyPythonVS.py)

• Intelligent Azure DevOps Assistant: Query work items, bugs, and tasks using natural language
• MCP Integration: Seamless communication with Azure DevOps through Model Context Protocol
• Azure OpenAI Integration: Powered by Azure OpenAI for advanced natural language processing
• Real-time Streaming: Live updates and logs during tool execution
• Work Item Management: Read, update, and manage Azure DevOps work items
• Modern Web UI: Built with Gradio for an intuitive user experience

Instant DB Script Maker (InstantDBScriptMaker.py)

• Database Script Processing: Enter, validate, and process SQL scripts
• Team Management Integration: Select teams and managers from predefined configurations
• Automatic Task Creation: Generate Azure DevOps tasks directly from database scripts
• Multiple Authentication Methods: Support for both PAT and Azure CLI authentication
• Standalone Interface: Launches in a separate tab for focused script work

🏗️ Architecture & Flow

flowchart TD
    A[User] -->|Interacts with| B[Gradio Web UI]
    
    subgraph "ADOBuddy Main Application"
        B --> C{User Action}
        C -->|Chatbot Query| D[AI Chatbot Pipeline]
        C -->|Launch DB Tool| E[Tool Launcher]
    end
    
    subgraph "AI & MCP Communication"
        D --> F[Azure OpenAI LLM]
        D --> G[MCP Client Setup]
        G --> H[Azure DevOps MCP Server]
        H --> I[Azure DevOps APIs]
        F --> J[Query Processing]
        J --> K[Tool Execution]
        K --> L[Stream Results]
    end
    
    subgraph "Instant DB Script Maker"
        E --> M[DB Script Interface]
        M --> N[Script Processing]
        N --> O{Create Task?}
        O -->|Yes| P[Authentication Layer]
        O -->|No| Q[Display Results]
        P --> R[PAT Auth]
        P --> S[Azure CLI Auth]
        R --> T[Create ADO Task]
        S --> T
        T --> U[Task Created]
    end
    
    L --> V[Chatbot Response]
    Q --> W[Script Output]
    U --> W
    
    style F fill:#e1f5fe
    style H fill:#f3e5f5
    style T fill:#e8f5e8

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📋 Prerequisites

• Python 3.8+
• Node.js (for MCP server)
• Azure DevOps organization access
• Azure OpenAI service

🛠️ Installation

1. Clone the repository

   git clone <repository-url>
   cd ADOBuddyPythonVS

2. Install Python dependencies

   pip install -r requirements.txt

3. Install Azure CLI and Node.js from official company portal Check-NodeAzurenew.ps1 file helps installing Azure CLI and Node.js from official company portal for TR internal users. Run the file as powershell.

🚀 Usage

Running the Main Application

python ADOBuddyPythonVS.py

The application will launch at http://127.0.0.3:7880 with:

• Main chatbot interface for Azure DevOps queries
• Tools menu with access to DB Script Maker
• Real-time streaming of AI responses

Running DB Script Maker Standalone

python InstantDBScriptMaker.py

Launches at http://127.0.0.3:7881 for dedicated database script processing.

Example Queries

Chatbot Examples:

• "List me 1 task that I am assigned to in Azure DevOps in taxprof project"
• "Show me all my assigned work items"
• "What are the open bugs in taxprof project?"

DB Script Maker:

• Enter SQL scripts
• Select appropriate team/manager
• Optionally create Azure DevOps tasks automatically

🔐 Authentication

Azure CLI

1. Install Azure CLI
2. Run az login
3. Set default organization: az devops configure --defaults organization=https://dev.azure.com/your-org Note : All steps are covered in powershell file mentioned above so need to run explicitly.

📁 Project Structure

ADOBuddyPythonVS/
├── ADOBuddyPythonVS.py          # Main chatbot application
├── InstantDBScriptMaker.py      # DB script processing tool
├── setup_auth.py                # Authentication setup helper
├── TeamNameAndManager.json      # Team configuration data
├── requirements.txt             # Python dependencies
├── .env.template               # Environment configuration template
├── .env                        # Environment configuration (create from template)
├── README_AUTH_FIX.md          # Authentication troubleshooting guide
└── .github/
    └── copilot-instructions.md  # Development guidelines

🔧 Configuration Files

• .env: Environment variables and API keys
• TeamNameAndManager.json: Team and manager mappings for task assignment
• requirements.txt: Python package dependencies

🤖 AI & MCP Integration

The application leverages:

• Azure OpenAI: For natural language understanding and response generation
• MCP (Model Context Protocol): For structured communication with Azure DevOps
• LangChain: For AI agent orchestration and tool management
• Gradio: For modern web interface and real-time streaming

🚨 Limitations

• Chatbot functionality is limited to reading task data and updating specific fields
• Task creation and deletion are restricted through the chatbot interface
• Use the DB Script Maker tool for creating new Azure DevOps tasks

🔍 Troubleshooting

For authentication issues, see README_AUTH_FIX.md for detailed troubleshooting steps.

Common issues:

• TF400813 errors: Usually authentication/permission issues
• Connection failures: Check Azure DevOps organization URL and credentials
• Token expiration: Regenerate PAT tokens as needed

🤝 Contributing

1. Follow the patterns established in existing code
2. Prioritize Azure DevOps TypeScript client usage for new tools
3. Ensure clear and concise prompt instructions for AI components
4. Test authentication methods thoroughly

📝 License

For TR use Only

📞 Support

For issues and questions:

1. Run python setup_auth.py for authentication diagnostics
2. Check error messages in the application output
3. Verify permissions in Azure DevOps organization
4. Consider using PAT authentication for better reliability