Hub_of_Epstein_Files_Directory

Document Indexing Bot

Purpose

Automatically indexes new documents for searchability and organization.

Features

Configuration

Bot Settings

bot_name: indexing-bot
capacity: 6000  # documents per day
priority: high

Usage

Basic Usage

# Index a single document
python indexing-bot/index.py --file path/to/document.pdf

# Index directory of documents
python indexing-bot/index.py --directory path/to/documents/

# Re-index all documents
python indexing-bot/index.py --reindex-all

API Usage

from bots.indexing_bot import IndexingBot

bot = IndexingBot()
result = bot.index_document("path/to/document.pdf")
print(result)

Output Format

Index Entry

{
  "document_id": "doc_123",
  "title": "Document Title",
  "category": "court_filing",
  "subcategory": "deposition",
  "date": "2020-01-15",
  "metadata": {
    "case_number": "20-CV-1234",
    "filing_date": "2020-01-15",
    "court": "Southern District of New York",
    "pages": 45,
    "redaction_status": "partial"
  },
  "entities": {
    "people": ["Person A", "Person B"],
    "organizations": ["Org A"],
    "locations": ["New York", "Florida"]
  },
  "keywords": ["keyword1", "keyword2"],
  "full_text_path": "data/processed/text/doc_123.txt",
  "indexed_at": "2024-12-22T10:30:00Z"
}

Indexing Process

  1. Document Analysis
    • Extract text content
    • Identify document type
    • Extract metadata
  2. Categorization
    • Assign primary category
    • Assign subcategory
    • Tag with keywords
  3. Entity Extraction
    • Identify people
    • Identify organizations
    • Identify locations
    • Identify dates
  4. Cross-Reference
    • Link to related documents
    • Update entity profiles
    • Build relationship graph
  5. Search Index Update
    • Add to search engine
    • Update facets
    • Refresh statistics

Search Integration

Lunr.js Index Format

{
  "id": "doc_123",
  "title": "Document Title",
  "body": "Full text content...",
  "category": "court_filing",
  "date": "2020-01-15",
  "people": "Person A, Person B"
}

Dependencies

Installation

pip install -r requirements.txt

Status

⚠️ In Development - This bot is currently being developed. Full implementation coming soon.

Contributing

See CONTRIBUTING.md for guidelines.

Support