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>
83 lines
4.1 KiB
Markdown
83 lines
4.1 KiB
Markdown
# System Architecture — Legal Decision Assistant
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## Components
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```
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┌─────────────────────────────────────────────────────┐
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│ Nautilus Server │
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│ 158.178.131.193 │
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│ │
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│ ┌──────────┐ ┌──────────┐ ┌──────────────────┐ │
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│ │ Coolify │ │ Traefik │ │ ezer-mishpati-web│ │
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│ │ (manage) │ │ (proxy) │ │ (upload UI) │ │
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│ └──────────┘ └──────────┘ └──────────────────┘ │
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│ │
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│ ┌──────────────────┐ ┌──────────────────────────┐ │
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│ │ PostgreSQL │ │ Redis │ │
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│ │ + pgvector │ │ (task queue) │ │
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│ │ (legal-ai-postgres│ │ (legal-ai-redis) │ │
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│ └──────────────────┘ └──────────────────────────┘ │
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│ │
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│ ┌──────────┐ ┌──────────┐ │
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│ │ Gitea │ │ n8n │ │
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│ │ (code) │ │ (automate│ │
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│ └──────────┘ └──────────┘ │
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│ │
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│ ┌──────────────────────────────────────────────┐ │
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│ │ Claude Code (via SSH or API) │ │
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│ │ — Skills: legal-decision, legal-docx │ │
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│ │ — MCP: postgres, n8n, cloudflare, chrome │ │
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│ └──────────────────────────────────────────────┘ │
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└─────────────────────────────────────────────────────┘
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External:
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← Claude API (embeddings, analysis)
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← Cloudflare DNS (*.nautilus.marcusgroup.org)
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← User (Putty SSH / Browser)
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```
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## Data Flow
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```
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1. Document Upload
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User → ezer-mishpati-web → file storage → n8n trigger
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→ classify document → store metadata in PostgreSQL
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→ generate embeddings → store in pgvector
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2. Decision Writing
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Claude Code → read source materials from DB
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→ generate structure DOCX (12 blocks)
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→ write each block with appropriate model/parameters
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→ validate against block-schema
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→ export final DOCX
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3. Precedent Search (RAG)
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Query → generate embedding → pgvector similarity search
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→ return relevant paragraphs/decisions
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→ Claude analyzes relevance → present to user
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```
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## Database Schema — 4 Layers
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### Layer 1: Core
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appeals, parties, panels, documents
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### Layer 2: Decision
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decisions, decision_blocks, decision_paragraphs, claims
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### Layer 3: Legal Knowledge
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case_law, case_law_citations, statutory_provisions, transition_phrases, lessons_learned
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### Layer 4: Semantic Search (RAG)
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document_embeddings, paragraph_embeddings, case_law_embeddings
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(all using pgvector vector(1536) columns)
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## Technology Choices
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- **Database**: PostgreSQL 15 + pgvector 0.8.1
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- **Embedding model**: TBD (Claude/OpenAI ada-002/local)
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- **Automation**: n8n (workflow engine)
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- **Code repository**: Gitea (self-hosted)
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- **Deployment**: Coolify (Docker management)
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- **Proxy**: Traefik v3.6 (auto-SSL)
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- **Frontend**: ezer-mishpati-web (static HTML + API)
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