JC Beasley
cb5e26b561
- Set correct table ID: mx149yctebfwvys (ai_data_Memory) - Updated type column with SingleSelect options - Added all required columns for corrections, preferences, episodes, decisions, validation - Fixed column options for type, severity, status fields
170 lines
4.8 KiB
Markdown
170 lines
4.8 KiB
Markdown
# IT Site Survey AI - Code Structure Analysis
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## Overview
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The application is a Flask-based web application that provides IT infrastructure site survey functionality with AI-powered analysis and recommendations.
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## Main Components
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### 1. Core Application (app.py)
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- **Lines of Code**: 792
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- **Framework**: Flask
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- **Key Dependencies**: requests, reportlab, flask-cors
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- **External Services**: Ollama AI at http://192.168.19.25:11434
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### 2. Data Model
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- **Template**: concise_template.json (21 questions across 5 categories)
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- **In-Memory Storage**:
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- `surveys_db` - Dictionary of survey definitions
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- `survey_responses_db` - Dictionary of survey responses
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- **Data Structure**:
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- Surveys with metadata and questions
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- Responses with submission data and answers
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### 3. Key Routes
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#### Survey Management
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- `GET /api/surveys/template` - Get survey template
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- `GET /api/surveys` - List all surveys
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- `POST /api/surveys` - Create new survey
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- `GET /api/surveys/<survey_id>` - Get specific survey
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#### Response Handling
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- `POST /api/surveys/<survey_id>/responses` - Submit survey response
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- `GET /api/surveys/responses` - Get all responses (recently added)
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#### AI Analysis
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- `POST /api/surveys/<survey_id>/analyze` - Generate AI recommendations
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- `POST /api/surveys/<survey_id>/generate-quote` - Generate service quote
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#### Export Functions
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- `POST /api/surveys/<survey_id>/export/pdf` - Export to PDF
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- `POST /api/surveys/<survey_id>/export/text` - Export to text
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- `POST /api/surveys/<survey_id>/export/email` - Export to email format
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#### System
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- `GET /` - Main application page
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- `GET /<path:path>` - Static file serving
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- `GET /api/health` - Health check
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- `GET /api/ollama-status` - Ollama connectivity check
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### 4. Frontend Files
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- `index.html` - Main survey interface (18,263 bytes)
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- `dashboard.html` - Response dashboard (337 bytes)
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### 5. Template Structure
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**21 Questions Across 5 Categories:**
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1. **Client Information** (2 questions)
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- Company Name (text)
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- Industry/Vertical (select)
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2. **Site Information** (3 questions)
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- Site Size (select)
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- Building Type (select)
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- Square Footage (select)
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3. **Existing Infrastructure** (4 questions)
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- Network Topology (select)
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- Network Size (select)
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- Internet Bandwidth (select)
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- ISP Connection Type (multiselect)
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4. **Wireless Infrastructure** (2 questions)
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- Wireless Standard (select)
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- Wireless Coverage Quality (select)
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5. **Business Requirements** (10 questions)
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- Critical Applications (multiselect)
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- Device Types (multiselect)
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- User Density (select)
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- Performance Requirements (multiselect)
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- Security Requirements (multiselect)
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- Compliance Requirements (select)
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- Budget Range (select)
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- Project Timeline (select)
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- Additional Notes (textarea)
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## Current Limitations
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### 1. Data Persistence
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- **Issue**: All data stored in memory (lost on restart)
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- **Impact**: Critical for production use
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- **Solution Needed**: Database persistence
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### 2. Security
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- **Issue**: No authentication on dashboard
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- **Impact**: Survey data publicly accessible
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- **Solution Needed**: User authentication
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### 3. Scalability
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- **Issue**: Single-process Flask application
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- **Impact**: Limited concurrent users
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- **Solution Needed**: Multi-process or async handling
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## Database Schema Requirements
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For PostgreSQL implementation, the following tables would be needed:
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### surveys
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- id (UUID, PK)
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- name (VARCHAR)
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- description (TEXT)
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- client_name (VARCHAR)
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- site_name (VARCHAR)
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- created_at (TIMESTAMP)
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- status (VARCHAR)
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### survey_questions
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- id (UUID, PK)
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- survey_id (UUID, FK)
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- question_id (VARCHAR)
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- category (VARCHAR)
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- question_text (TEXT)
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- question_type (VARCHAR)
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- options (JSON)
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### survey_responses
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- id (UUID, PK)
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- survey_id (UUID, FK)
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- submitted_by (VARCHAR)
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- submitted_at (TIMESTAMP)
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### response_answers
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- id (UUID, PK)
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- response_id (UUID, FK)
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- question_id (VARCHAR)
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- answer_value (TEXT or JSON)
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## Implementation Considerations
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### 1. Backward Compatibility
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- All existing API endpoints must continue working
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- No breaking changes to data structure
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- Maintain same JSON response formats
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### 2. Migration Strategy
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- Seamless transition from memory to database
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- No data loss during migration
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- Fallback to memory if database unavailable
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### 3. Configuration
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- Database connection via environment variables
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- Default to memory storage if no DB configured
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- Clear setup instructions for PostgreSQL
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### 4. Error Handling
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- Graceful degradation if database unavailable
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- Clear error messages for connectivity issues
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- Logging for debugging database issues
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## Dependencies to Add
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- `psycopg2-binary` - PostgreSQL driver
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- `sqlalchemy` - ORM (optional but recommended)
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- Database connection pooling
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## Estimated Implementation Effort
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- **Schema Design**: 2 hours
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- **Database Integration**: 6 hours
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- **Migration Logic**: 3 hours
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- **Testing**: 3 hours
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- **Documentation**: 2 hours
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- **Total**: 16 hours |