Chaim
22e819363e
- Remove cases/new|in-progress|completed subdivision (status managed in DB)
- Rename documents/original → documents/originals (consistent plural)
- Move exports from global data/exports/ into cases/{num}/exports/
- Add documents/research/ for case law and analysis files
- Update all agents, scripts, config, web API endpoints, and DB paths
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
67 lines
1.9 KiB
Python
67 lines
1.9 KiB
Python
"""Extract text from original PDF files using Claude Opus Vision OCR."""
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import asyncio
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import sys
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import time
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "mcp-server" / "src"))
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from dotenv import load_dotenv
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load_dotenv(Path.home() / ".env")
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from legal_mcp.services import extractor
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ORIGINALS_DIR = Path("/home/chaim/legal-ai/data/cases/1130-25/documents/originals")
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OUTPUT_DIR = ORIGINALS_DIR / "extracted"
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async def main():
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OUTPUT_DIR.mkdir(exist_ok=True)
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pdfs = sorted(ORIGINALS_DIR.glob("*.pdf"))
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print(f"Found {len(pdfs)} PDFs\n")
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total_cost = 0.0
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total_pages = 0
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total_time = 0.0
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for pdf in pdfs:
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print(f"{'=' * 60}")
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print(f"Processing: {pdf.name}")
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print(f" Size: {pdf.stat().st_size:,} bytes")
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t0 = time.time()
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text, page_count = await extractor.extract_text(str(pdf))
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elapsed = time.time() - t0
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total_pages += page_count
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total_time += elapsed
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# Estimate cost (Opus: $15/M input, $75/M output, ~1000 tokens per image)
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# Rough: ~$0.05 per page for image input + output
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est_cost = page_count * 0.05
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total_cost += est_cost
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# Save extracted text
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out_file = OUTPUT_DIR / f"{pdf.stem}.md"
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out_file.write_text(text, encoding="utf-8")
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print(f" Pages: {page_count}")
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print(f" Extracted: {len(text):,} chars, {len(text.split()):,} words")
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print(f" Time: {elapsed:.1f}s ({elapsed/max(page_count,1):.1f}s/page)")
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print(f" Est. cost: ${est_cost:.3f}")
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print(f" Saved to: {out_file.name}")
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print()
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print(f"{'=' * 60}")
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print(f"TOTAL")
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print(f" Documents: {len(pdfs)}")
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print(f" Pages: {total_pages}")
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print(f" Time: {total_time:.1f}s")
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print(f" Est. cost: ${total_cost:.3f}")
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if __name__ == "__main__":
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asyncio.run(main())
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