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ActiveDocs/07-AI-FRAMEWORK.md

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+# IGNY8 AI Framework Documentation
+
+**Version:** 1.0  
+**Last Updated:** 2025-01-XX  
+**Purpose:** Complete documentation of the unified AI framework architecture.
+
+---
+
+## Overview
+
+The IGNY8 AI Framework provides a unified, consistent architecture for all AI functions. It eliminates code duplication, standardizes progress tracking, and provides a single interface for all AI operations.
+
+### Key Benefits
+
+- **90% Code Reduction**: Functions are now ~100 lines instead of ~600
+- **Consistent UX**: All functions use the same progress modal and tracking
+- **Unified Logging**: Single `AITaskLog` table for all AI operations
+- **Easy Extension**: Add new functions by creating one class
+- **Better Debugging**: Detailed step-by-step tracking for all operations
+
+---
+
+## Architecture
+
+### Directory Structure
+
+```
+igny8_core/ai/
+├── __init__.py          # Auto-registers all functions
+├── apps.py              # Django app configuration
+├── admin.py             # Admin interface for AITaskLog
+├── base.py              # BaseAIFunction abstract class
+├── engine.py            # AIEngine orchestrator
+├── processor.py         # AIProcessor wrapper
+├── registry.py           # Function registry
+├── tracker.py           # StepTracker, ProgressTracker, CostTracker
+├── tasks.py             # Unified Celery task entrypoint
+├── types.py             # Shared dataclasses
+├── models.py            # AITaskLog model
+└── functions/           # Function implementations
+    ├── __init__.py
+    └── auto_cluster.py  # Auto cluster function
+```
+
+---
+
+## Core Components
+
+### 1. BaseAIFunction
+
+Abstract base class that all AI functions inherit from.
+
+**Methods to implement:**
+- `get_name()`: Return function name
+- `prepare()`: Load and prepare data
+- `build_prompt()`: Build AI prompt
+- `parse_response()`: Parse AI response
+- `save_output()`: Save results to database
+
+**Optional overrides:**
+- `validate()`: Custom validation
+- `get_max_items()`: Set item limit
+- `get_model()`: Specify AI model
+- `get_metadata()`: Function metadata
+
+### 2. AIEngine
+
+Central orchestrator that manages the execution pipeline.
+
+**Phases:**
+- INIT (0-10%): Validation & setup
+- PREP (10-25%): Data loading & prompt building
+- AI_CALL (25-60%): API call to provider
+- PARSE (60-80%): Response parsing
+- SAVE (80-95%): Database operations
+- DONE (95-100%): Finalization
+
+### 3. Function Registry
+
+Dynamic function discovery system.
+
+**Usage:**
+```python
+from igny8_core.ai.registry import register_function, get_function
+
+# Register function
+register_function('auto_cluster', AutoClusterFunction)
+
+# Get function
+fn = get_function('auto_cluster')
+```
+
+### 4. Unified Celery Task
+
+Single entrypoint for all AI functions.
+
+**Endpoint:** `run_ai_task(function_name, payload, account_id)`
+
+**Example:**
+```python
+from igny8_core.ai.tasks import run_ai_task
+
+task = run_ai_task.delay(
+    function_name='auto_cluster',
+    payload={'ids': [1, 2, 3], 'sector_id': 1},
+    account_id=1
+)
+```
+
+---
+
+## Function Implementation Example
+
+### Auto Cluster Function
+
+```python
+from igny8_core.ai.base import BaseAIFunction
+
+class AutoClusterFunction(BaseAIFunction):
+    def get_name(self) -> str:
+        return 'auto_cluster'
+    
+    def get_max_items(self) -> int:
+        return 20
+    
+    def prepare(self, payload: dict, account=None) -> Dict:
+        # Load keywords
+        ids = payload.get('ids', [])
+        keywords = Keywords.objects.filter(id__in=ids)
+        return {'keywords': keywords, ...}
+    
+    def build_prompt(self, data: Dict, account=None) -> str:
+        # Build clustering prompt
+        return prompt_template.replace('[IGNY8_KEYWORDS]', keywords_text)
+    
+    def parse_response(self, response: str, step_tracker=None) -> List[Dict]:
+        # Parse AI response
+        return clusters
+    
+    def save_output(self, parsed, original_data, account, progress_tracker) -> Dict:
+        # Save clusters to database
+        return {'clusters_created': 5, 'keywords_updated': 20}
+```
+
+---
+
+## API Endpoint Example
+
+### Before (Old): ~300 lines
+
+### After (New): ~50 lines
+
+```python
+@action(detail=False, methods=['post'], url_path='auto_cluster')
+def auto_cluster(self, request):
+    from igny8_core.ai.tasks import run_ai_task
+    
+    account = getattr(request, 'account', None)
+    account_id = account.id if account else None
+    
+    payload = {
+        'ids': request.data.get('ids', []),
+        'sector_id': request.data.get('sector_id')
+    }
+    
+    task = run_ai_task.delay(
+        function_name='auto_cluster',
+        payload=payload,
+        account_id=account_id
+    )
+    
+    return Response({
+        'success': True,
+        'task_id': str(task.id),
+        'message': 'Clustering started'
+    })
+```
+
+---
+
+## Progress Tracking
+
+### Unified Progress Endpoint
+
+**URL:** `/api/v1/system/settings/task_progress/<task_id>/`
+
+**Response:**
+```json
+{
+  "state": "PROGRESS",
+  "meta": {
+    "phase": "AI_CALL",
+    "percentage": 45,
+    "message": "Analyzing keyword relationships...",
+    "request_steps": [...],
+    "response_steps": [...],
+    "cost": 0.000123,
+    "tokens": 1500
+  }
+}
+```
+
+### Frontend Integration
+
+All AI functions use the same progress modal:
+- Single `useProgressModal` hook
+- Unified progress endpoint
+- Consistent phase labels
+- Step-by-step logs
+
+---
+
+## Database Logging
+
+### AITaskLog Model
+
+Unified logging table for all AI operations.
+
+**Fields:**
+- `task_id`: Celery task ID
+- `function_name`: Function name
+- `account`: Account (required)
+- `phase`: Current phase
+- `status`: success/error/pending
+- `cost`: API cost
+- `tokens`: Token usage
+- `request_steps`: Request step logs
+- `response_steps`: Response step logs
+- `error`: Error message (if any)
+
+---
+
+## Migration Guide
+
+### Migrating Existing Functions
+
+1. Create function class inheriting `BaseAIFunction`
+2. Implement required methods
+3. Register function in `ai/__init__.py`
+4. Update API endpoint to use `run_ai_task`
+5. Test and remove old code
+
+### Example Migration
+
+**Old code:**
+```python
+@action(...)
+def auto_cluster(self, request):
+    # 300 lines of code
+```
+
+**New code:**
+```python
+@action(...)
+def auto_cluster(self, request):
+    # 20 lines using framework
+```
+
+---
+
+## Summary
+
+The AI Framework provides:
+
+1. **Unified Architecture**: Single framework for all AI functions
+2. **Code Reduction**: 90% less code per function
+3. **Consistent UX**: Same progress modal for all functions
+4. **Better Debugging**: Detailed step tracking
+5. **Easy Extension**: Add functions quickly
+6. **Unified Logging**: Single log table
+7. **Cost Tracking**: Automatic cost calculation
+
+This architecture ensures maintainability, consistency, and extensibility while dramatically reducing code duplication.
+