Enable GitHub Copilot integration for document intelligence repository

[Copilot]

This PR enables comprehensive GitHub Copilot integration for the document-intelligence repository, providing developers with AI-assisted coding capabilities tailored specifically for this document analysis and semantic search project.

What's Added

VS Code Integration

• Workspace Configuration: Complete VS Code setup with Copilot-optimized settings in .vscode/settings.json
• Recommended Extensions: Extension pack including GitHub Copilot, Python tools, and Docker support
• Debug Configurations: Pre-configured launch settings for debugging the main pipeline components (semantic analyzer, relevance scorer, subsection extractor)
• Development Tasks: Automated tasks for common operations like dependency installation, Docker builds, code formatting, and testing

Project Context for AI

• Copilot Instructions: Comprehensive project context in .github/copilot-instructions.md explaining the hybrid semantic + lexical search architecture, key components, and development patterns
• Development Guide: Detailed setup and usage documentation in DEVELOPMENT.md with Copilot-specific best practices
• Integration Guide: Complete reference in COPILOT.md with troubleshooting and tips for effective AI-assisted development

Code Quality & Consistency

• Editor Configuration: Consistent formatting rules across different editors via .editorconfig
• Updated Gitignore: Allows .github/ and .vscode/ directories for proper configuration management

Key Benefits

Domain-Specific AI Assistance: Copilot now understands the project's document intelligence domain, including:

• PDF processing with PyMuPDF
• Semantic analysis using the Granite embedding model
• Hybrid ranking algorithms (80% semantic similarity + 20% BM25)
• Multi-threaded subsection refinement
• Docker-based offline execution

Enhanced Developer Experience:

• Intelligent code completions based on existing patterns
• Context-aware suggestions for machine learning and document processing tasks
• Debugging support with pre-configured launch settings
• One-click tasks for build, test, and deployment operations

Comprehensive Documentation: Clear guidance for developers on how to effectively use Copilot with this specific project, including common prompts and use cases.

Verification

The integration includes a validation script (test_copilot_setup.py) that confirms:

• All dependencies install correctly
• Core modules import successfully
• Granite embedding model files are accessible
• Configuration files are present and valid
• No breaking changes to existing functionality

All tests pass, confirming the setup is ready for AI-assisted development.

Usage

1. Open the project in VS Code
2. Install recommended extensions (GitHub Copilot included)
3. Run python test_copilot_setup.py to verify setup
4. Start coding with enhanced AI assistance!

Copilot will now provide intelligent suggestions for document analysis, semantic search, PDF processing, and machine learning workflows based on the comprehensive project context provided.

Fixes #1.

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💡 You can make Copilot smarter by setting up custom instructions, customizing its development environment and configuring Model Context Protocol (MCP) servers. Learn more Copilot coding agent tips in the docs.

[Copilot]

@Polymath-Saksh 👋 This repository doesn't have Copilot instructions. With Copilot instructions, I can understand the repository better, work faster and produce higher quality PRs.

I can generate a .github/copilot-instructions.md file for you automatically. Click here to open a pre-filled issue and assign it to me. I'll write the instructions, and then tag you for review.