BA Assistant

BA Assistant is a tool that helps business analysts build requirement documents using AI Language Models (LLM).

Installation

1. Prerequisites:

   • Node.js (v16 or higher)
   • npm (comes with Node.js)
   • Ollama - Required for AI/LLM functionality

2. Clone the repository:

   git clone https://github.com/yourusername/ba-assistant.git
   cd ba-assistant

3. Install dependencies:

   npm install

Running the Application

Development Mode

1. Start the development server:

   npm run dev

2. Open your browser and navigate to http://localhost:8080

Production Mode

1. Build the application:

   npm run build

2. Start the server:

   npm start

3. Open your browser and navigate to http://localhost:3000

Using Docker

1. Prerequisites:

   • Docker and Docker Compose installed
   • NVIDIA GPU and drivers (optional, for GPU acceleration)

2. Run the application:

   docker compose up

   This will:

   • Start the BA Assistant application on port 8080
   • Start Ollama service with GPU support (if available)
   • Configure all necessary environment variables
   • Mount Ollama data volume for model persistence

3. Access the application:

   • Open your browser and navigate to http://localhost:8080

4. Environment Configuration: The Docker setup includes the following default configurations:

   • Ollama endpoint: http://ollama:11434/
   • Model: llama3.2:3b
   • Temperature: 0.3
   • Max tokens: 4096
   • Language: English
   • Streaming: enabled
   • Retry attempts: 3
   • Retry delay: 1000ms

Core Features

1. Project Management

• Single project workspace with local storage support
• Project folder structure:
  • project.md (Project Ideas)
  • user-story-map.md
  • customer-journey-map.md
  • pages-and-navigations.md
  • pages-and-user-stories.md
  • sprint-planning.md
• Project Operations:
  • Create/Open projects
  • Auto-save functionality
  • Export to folder
  • Local storage integration

2. Prompt Management

• Responsive grid-based prompt listing (3 columns on large screens, 2 on medium, 1 on small)
• Inline modal editor for prompt creation and editing
• Each prompt contains:
  • Name field for identification
  • Text area for prompt content
• Default prompt templates for:
  • User Story Map
  • Customer Journey Map
  • Sprint Planning
• Custom prompt creation support
• Local storage persistence
• Dark mode compatible UI

3. Document Generation

• AI LLM integration for content generation
• Multi-file content generation support
• Document-prompt matching
• Clipboard integration
• Server-Sent Events (SSE) for streaming responses
• Integration with Ollama chat service

4. User Interface

• Split-panel layout:
  • Left: Project ideas
  • Right: Document content
• Tab-based navigation
• Document selection system
• Copy-to-clipboard functionality
• Dark/Light theme toggle
• Collapsible sidebar
• Responsive design with Tailwind CSS

5. Project Settings

• Repository analysis capabilities:
  • Git repository statistics (commits, tags)
  • Feature extraction and analysis
  • Real-time updates via server-sent events (SSE)
  • Repository summary generation
  • Commit history visualization
  • Copy features and summaries to clipboard
• Repository management:
  • Set and validate repository paths
  • Repository path persistence
  • Live feature extraction with loading states
  • Error handling and validation
  • Dual-panel display for features and summary

Technical Implementation

Frontend Architecture

• Built with AppRun for state management and component architecture
• TypeScript for type safety and better developer experience
• Tailwind CSS for responsive styling
• Component-based structure in /pages directory:
  • Home (/pages/home): Main workspace
  • Settings (/pages/settings): Repository analysis
  • Prompts (/pages/prompts): Prompt management

Backend Services

• Server-Sent Events (SSE) endpoints for real-time updates
• Chat API integration with Ollama
• Git repository analysis services:
  • Statistics collection
  • Feature extraction
  • Repository structure analysis