Chaim
6aaca14e31
Benchmark results on Hebrew legal docs (case 1130-25): - Google Vision: 1s/page, $0.001/page, high accuracy - Claude Opus Vision: 90s/page, $0.05/page, poor accuracy - PyMuPDF broken OCR layers now detected via quality check Changes: - extractor.py: Google Vision OCR with Hebrew language hint (300 DPI) - extractor.py: text quality detection (word length, words-per-line, Hebrew ratio) - extractor.py: Hebrew abbreviation quote fixer (15 known patterns) - config.py: add GOOGLE_CLOUD_VISION_API_KEY, remove ANTHROPIC_API_KEY - pyproject.toml: add google-cloud-vision, remove anthropic Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
28 lines
607 B
TOML
28 lines
607 B
TOML
[project]
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name = "legal-mcp"
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version = "0.1.0"
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description = "MCP server for AI-assisted legal decision drafting"
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requires-python = ">=3.10"
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dependencies = [
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"mcp[cli]>=1.0.0",
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"asyncpg>=0.29.0",
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"pgvector>=0.3.0",
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"voyageai>=0.3.0",
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"python-dotenv>=1.0.0",
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"pydantic>=2.0.0",
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"pymupdf>=1.25.0",
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"python-docx>=1.1.0",
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"striprtf>=0.0.26",
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"redis>=5.0.0",
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"rq>=1.16.0",
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"pillow>=10.0.0",
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"google-cloud-vision>=3.7.0",
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]
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[build-system]
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requires = ["setuptools>=68.0"]
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build-backend = "setuptools.build_meta"
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[tool.setuptools.packages.find]
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where = ["src"]
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