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- **PDF Parsing:** PyPDF2 >=3.0.0
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---
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## 3. Functionality Specification
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### Core Features
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#### 3.1 Database Connection Management
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- Add PostgreSQL database connections with connection details
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- Test database connectivity
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- Store connection configurations securely
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- Support multiple database connections
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#### 3.2 Schema Introspection
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- Automatically fetch table names and column information
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- Store schema in PostgreSQL with pgvector for semantic search
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- Support uploading schema documentation (PDF)
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#### 3.3 Natural Language to SQL
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- Accept natural language queries
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- Use LLM to convert natural language to SQL
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- Support SELECT, INSERT, UPDATE, DELETE operations
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- Include validation and error handling
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#### 3.4 Semantic Schema Search
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- Embed schema documentation using sentence-transformers
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- Store embeddings in pgvector
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- Search schema semantically to find relevant tables/columns
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#### 3.5 Query Execution
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- Execute generated SQL against target database
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- Return formatted results
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- Handle errors gracefully with user-friendly messages
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#### 3.6 Query History
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- Store all queries with timestamps
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- View past queries and their results
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- Re-run previous queries
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### User Interactions
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1. **Add Database:** User enters connection details → System tests connection → Saves if successful
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2. **Ask Question:** User types natural language → System generates SQL → User reviews → Executes → Views results
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3. **Search Schema:** User enters search term → System returns semantically similar schema elements
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4. **Upload Docs:** User uploads PDF → System extracts text → Embeds and stores in vector DB
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### Data Handling
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- Query history stored in SQLite (local)
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- Database connections stored encrypted
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- Schema embeddings stored in PostgreSQL via pgvector
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### Edge Cases
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- Invalid SQL generated → Show error with suggestion to retry
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- Database connection failed → Show connection error with troubleshooting tips
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- Empty results → Show "No results found" message
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- Large result sets → Paginate results
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- Network timeout → Show timeout error with retry option
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---
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## 4. API Endpoints
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| Method | Endpoint | Description |
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| ------ | ----------------------------- | ------------------------------ |
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| GET | /api/connections/ | List all database connections |
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| POST | /api/connections/ | Add new database connection |
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| GET | /api/connections/{id}/ | Get connection details |
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| PUT | /api/connections/{id}/ | Update connection |
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| DELETE | /api/connections/{id}/ | Delete connection |
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| POST | /api/connections/{id}/test/ | Test connection |
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| GET | /api/connections/{id}/schema/ | Get database schema |
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| POST | /api/query/ | Execute natural language query |
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| GET | /api/history/ | Get query history |
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| POST | /api/docs/ | Upload schema document |
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| GET | /api/docs/ | List schema documents |
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| POST | /api/docs/search/ | Semantic search in documents |
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---
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## 5. Acceptance Criteria
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1. ✓ User can add PostgreSQL database connections
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2. ✓ User can test database connectivity
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3. ✓ User can enter natural language queries
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4. ✓ System generates valid SQL from natural language
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5. ✓ User can execute queries and view results
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6. ✓ User can upload PDF schema documentation
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7. ✓ System performs semantic search over schema docs
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8. ✓ Query history is maintained
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9. ✓ Web interface is responsive and functional
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10. ✓ Error handling provides helpful feedback

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