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A newer version of the Gradio SDK is available: 6.5.1

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metadata 
title: SmartDoc AI
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 6.2.0
app_file: main.py
pinned: false

SmartDoc AI

SmartDoc AI is an advanced document analysis and question answering system, designed for source-grounded Q&A over complex business and scientific reports—especially where key evidence lives in tables and charts.

Personal Research Update

SmartDoc AI – Document Q&A + Selective Chart Understanding

I’ve been developing SmartDoc AI as a technical experiment to improve question answering over complex business/scientific reports—especially where key evidence lives in tables and charts.

Technical highlights:

  • Multi-format ingestion: PDF, DOCX, TXT, Markdown
  • LLM-assisted query decomposition: breaks complex prompts into clearer sub-questions for retrieval + answering
  • Selective chart pipeline (cost-aware):
    • Local OpenCV heuristics flag pages that likely contain charts
    • Gemini Vision is invoked only for chart pages to generate structured chart analysis (reduces unnecessary vision calls)
  • Table extraction + robust PDF parsing: pdfplumber strategies for bordered and borderless tables
  • Parallelized processing: concurrent PDF parsing + chart detection; batch chart analysis where enabled
  • Hybrid retrieval: BM25 + vector search combined via an ensemble retriever
  • Multi-agent answering: answer drafting + verification pass, with retrieved context available for inspection (page/source metadata)

Runtime note: Large PDFs (many pages/charts) can take minutes depending on DPI, chart volume, and available memory/CPU (HF Spaces limits can be a factor).

Demo Videos

Repository

?? https://github.com/TilanTAB/Intelligent-Document-Analysis-SmartDoc-AI

Use Cases

  • Source-grounded Q&A for business/research documents
  • Automated extraction and summarization from tables/charts

If you’re interested in architecture tradeoffs (cost, latency, memory limits, retrieval quality), feel free to connect.

Features

  • Multi-format Document Support: PDF, DOCX, TXT, and Markdown
  • Smart Chunking: Configurable chunk size and overlap for optimal retrieval
  • Intelligent Caching: Speeds up repeated queries
  • Chart Extraction: Detects and analyzes charts using OpenCV and Gemini Vision
  • Hybrid Search: Combines keyword and vector search for best results
  • Multi-Agent Workflow: Relevance checking, research, and answer verification
  • Production Ready: Structured logging, environment-based config, and test suite
  • Efficient: Local chart detection saves up to 95% on API costs

Quick Start

Prerequisites

  • Python 3.11 or higher
  • Google API Key for Gemini models (Get one here)

Installation

  1. Clone the repository:
git clone https://github.com/TilanTAB/Intelligent-Document-Analysis-SmartDoc-AI.git
cd Intelligent-Document-Analysis-SmartDoc-AI
  1. Activate the virtual environment:
# Windows PowerShell
.\activate_venv.ps1
# Windows Command Prompt
activate_venv.bat
# Or manually:
.\venv\Scripts\Activate.ps1
  1. Install dependencies (if needed):
pip install -r requirements.txt
  1. Configure environment variables:
cp .env.template .env
# Edit .env and set your API key
GOOGLE_API_KEY=your_api_key_here
  1. (Optional) Verify installation:
python verify_environment.py
  1. Run the application:
python main.py
  1. Open your browser to http://localhost:7860

Configuration

All settings can be configured via environment variables or the .env file. Key options include:

  • GOOGLE_API_KEY: Your Gemini API key (required)
  • CHUNK_SIZE, CHUNK_OVERLAP: Document chunking
  • ENABLE_CHART_EXTRACTION: Enable/disable chart detection
  • CHART_USE_LOCAL_DETECTION: Use OpenCV for free chart detection
  • CHART_ENABLE_BATCH_ANALYSIS: Batch process charts for speed
  • CHART_GEMINI_BATCH_SIZE: Number of charts per Gemini API call
  • LOG_LEVEL: Logging verbosity
  • GRADIO_SERVER_PORT: Web interface port

Project Structure

  • intelligence/ - Multi-agent system (relevance, research, verification)
  • configuration/ - App settings and logging
  • content_analyzer/ - Document and chart processing
  • search_engine/ - Hybrid retriever logic
  • core/ - Utilities and diagnostics
  • tests/ - Test suite
  • main.py - Application entry point

Troubleshooting

  • API Key Not Found: Set GOOGLE_API_KEY in your .env file.
  • Python 3.13 Issues: Use Python 3.11 or 3.12 for best compatibility.
  • Chart Detection Slow: Lower CHART_DPI or CHART_MAX_IMAGE_SIZE in .env.
  • ChromaDB Lock Issues: Stop all instances and remove lock files in vector_store/.

Contributing

Contributions are welcome! Please fork the repository, create a feature branch, and submit a pull request with a clear description.

License

This project is licensed under the MIT License.

SmartDoc AI is actively maintained and designed for real-world document analysis and Q&A. For updates and support, visit the GitHub repository.