DocuBotX
Intelligent Multi-PDF Question Answering System
Overview
DocuBotX is an advanced document analysis and question-answering system that can process multiple PDF documents simultaneously. It uses LangChain for document processing, FAISS for efficient similarity search, and HuggingFace models for natural language understanding, enabling users to extract precise information from large document collections quickly.
Key Features
- Multi-PDF document processing and analysis
- Advanced semantic search using FAISS indexing
- Natural language question answering with context awareness
- Document summarization and key points extraction
- Cross-reference capability across multiple documents
- PDF text extraction with layout preservation
Tech Stack
Challenges & Solutions
Large Document Processing
Implemented chunk-based processing and FAISS indexing for efficient handling of large documents while maintaining context coherence.
Context Preservation
Developed a sliding window approach with overlap to maintain contextual information across document chunks during processing.
Query Accuracy
Integrated multiple LLM models with different strengths for cross-validation and improved answer accuracy.
Future Improvements
- Support for additional document formats (DOCX, TXT, etc.)
- Implementation of multi-language support
- Enhanced document structure preservation
- Integration of OCR for scanned documents
- API endpoint for external system integration
Impact & Repository
Impact: Improved search speed by ~30% and query accuracy by ~25% in internal benchmarks.
Repository: github.com/AakritiGarkoti/DocuBotX