Chaim
d5ccf03e4c
Includes: - docs/: architecture, block-schema, migration-plan, product-specification - scripts/: bidi_table, decompose-decisions, extract-claims, seed-knowledge, etc. - skill-legal-decision/: SKILL.md + references + block-schema - skill-legal-assistant/: SKILL.md - skill-legal-docx/: SKILL.md + references - .claude/commands/: bidi-table skill - .taskmaster/: task config + PRDs - .gitignore: exclude legacy/, kiryat-yearim/, node_modules/, memory/ Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
#!/usr/bin/env python3
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"""Test semantic search functions."""
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import asyncio
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent / "mcp-server" / "src"))
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from legal_mcp.services.db import search_similar_paragraphs, search_similar_case_law, search_precedents, init_schema
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from legal_mcp.services.embeddings import embed_query
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async def main():
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await init_schema()
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queries = [
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"טענות קנייניות רוב דרוש בעלי דירות רכוש משותף",
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"חניה תנועה חניות מצוקת חניה",
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"היטל השבחה שמאי מכריע התערבות",
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]
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for query in queries:
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print(f'=== שאילתה: "{query}" ===')
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emb = await embed_query(query)
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results = await search_precedents(emb, limit=3)
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if not results:
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print(" אין תוצאות")
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else:
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for i, r in enumerate(results):
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score = r["score"]
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cn = r["case_number"]
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rtype = r["type"]
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content = r["content"][:120].replace("\n", " ")
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print(f" {i+1}. [{rtype}] {score:.3f} | {cn} | {content}")
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print()
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asyncio.run(main())
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