Stage 4
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docs/ActiveDocs/STAGE4-PROMPT-REGISTRY-COMPLETE.md
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# Stage 4 - Prompt Registry, Model Unification, and Final Function Hooks - COMPLETE ✅
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## Summary
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Successfully created a centralized prompt registry system, unified model configurations, and standardized all AI function execution with clean, minimal function files.
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## ✅ Completed Deliverables
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### 1. Prompt Registry System Created
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#### `ai/prompts.py` - PromptRegistry Class
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- **Purpose**: Centralized prompt management with hierarchical resolution
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- **Features**:
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- Hierarchical prompt resolution:
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1. Task-level `prompt_override` (if exists)
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2. DB prompt for (account, function)
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3. Default fallback from registry
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- Supports both `.format()` style and `[IGNY8_*]` placeholder replacement
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- Function-to-prompt-type mapping
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- Convenience methods: `get_image_prompt_template()`, `get_negative_prompt()`
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#### Prompt Resolution Priority
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```python
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# Priority 1: Task override
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if task.prompt_override:
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use task.prompt_override
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# Priority 2: DB prompt
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elif DB prompt for (account, function) exists:
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use DB prompt
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# Priority 3: Default fallback
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else:
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use default from registry
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```
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### 2. Model Configuration Centralized
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#### `ai/settings.py` - MODEL_CONFIG
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- **Purpose**: Centralized model configurations for all AI functions
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- **Configurations**:
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```python
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MODEL_CONFIG = {
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"auto_cluster": {
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"model": "gpt-4o-mini",
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"max_tokens": 3000,
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"temperature": 0.7,
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"response_format": {"type": "json_object"},
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},
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"generate_ideas": {
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"model": "gpt-4.1",
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"max_tokens": 4000,
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"temperature": 0.7,
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"response_format": {"type": "json_object"},
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},
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"generate_content": {
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"model": "gpt-4.1",
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"max_tokens": 8000,
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"temperature": 0.7,
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"response_format": None, # Text output
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},
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"generate_images": {
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"model": "dall-e-3",
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"size": "1024x1024",
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"provider": "openai",
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},
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}
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```
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#### Helper Functions
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- `get_model_config(function_name)` - Get full config
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- `get_model(function_name)` - Get model name
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- `get_max_tokens(function_name)` - Get max tokens
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- `get_temperature(function_name)` - Get temperature
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### 3. Updated All AI Functions
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#### `functions/auto_cluster.py`
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- ✅ Uses `PromptRegistry.get_prompt()`
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- ✅ Uses `get_model_config()` for model settings
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- ✅ Removed direct `get_prompt_value()` calls
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#### `functions/generate_ideas.py`
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- ✅ Uses `PromptRegistry.get_prompt()` with context
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- ✅ Uses `get_model_config()` for model settings
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- ✅ Clean prompt building with context variables
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#### `functions/generate_content.py`
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- ✅ Uses `PromptRegistry.get_prompt()` with task support
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- ✅ Uses `get_model_config()` for model settings
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- ✅ Supports task-level prompt overrides
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#### `functions/generate_images.py`
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- ✅ Uses `PromptRegistry.get_prompt()` for extraction
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- ✅ Uses `PromptRegistry.get_image_prompt_template()`
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- ✅ Uses `PromptRegistry.get_negative_prompt()`
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- ✅ Uses `get_model_config()` for model settings
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### 4. Updated Engine
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#### `engine.py`
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- ✅ Uses `get_model_config()` instead of `fn.get_model()`
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- ✅ Passes model config to `run_ai_request()`
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- ✅ Unified model selection across all functions
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### 5. Standardized Response Format
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All functions now return consistent format:
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```python
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{
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"success": True/False,
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"output": "HTML or image_url or data",
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"raw": raw_response_json, # Optional
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"meta": {
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"word_count": 1536, # For content
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"keywords": [...], # For clusters
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"model_used": "gpt-4.1",
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"tokens": 250,
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"cost": 0.000123
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},
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"error": None or error_message
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}
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```
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## 📋 File Changes Summary
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| File | Changes | Status |
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|------|---------|--------|
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| `prompts.py` | Created PromptRegistry class | ✅ Complete |
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| `settings.py` | Created MODEL_CONFIG and helpers | ✅ Complete |
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| `functions/auto_cluster.py` | Updated to use registry and settings | ✅ Complete |
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| `functions/generate_ideas.py` | Updated to use registry and settings | ✅ Complete |
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| `functions/generate_content.py` | Updated to use registry and settings | ✅ Complete |
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| `functions/generate_images.py` | Updated to use registry and settings | ✅ Complete |
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| `engine.py` | Updated to use model config | ✅ Complete |
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| `__init__.py` | Exported new modules | ✅ Complete |
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## 🔄 Migration Path
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### Old Code (Deprecated)
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```python
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from igny8_core.modules.system.utils import get_prompt_value, get_default_prompt
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prompt_template = get_prompt_value(account, 'clustering')
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prompt = prompt_template.replace('[IGNY8_KEYWORDS]', keywords_text)
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```
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### New Code (Recommended)
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```python
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from igny8_core.ai.prompts import PromptRegistry
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from igny8_core.ai.settings import get_model_config
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# Get prompt from registry
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prompt = PromptRegistry.get_prompt(
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function_name='auto_cluster',
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account=account,
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context={'KEYWORDS': keywords_text}
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)
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# Get model config
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model_config = get_model_config('auto_cluster')
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```
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## ✅ Verification Checklist
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- [x] PromptRegistry created with hierarchical resolution
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- [x] MODEL_CONFIG created with all function configs
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- [x] All functions updated to use registry
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- [x] All functions updated to use model config
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- [x] Engine updated to use model config
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- [x] Response format standardized
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- [x] No direct prompt utility calls in functions
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- [x] Task-level overrides supported
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- [x] DB prompts supported
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- [x] Default fallbacks working
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## 🎯 Benefits Achieved
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1. **Centralized Prompts**: All prompts in one registry
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2. **Hierarchical Resolution**: Task → DB → Default
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3. **Model Unification**: All models configured in one place
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4. **Easy Customization**: Tenant admins can override prompts
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5. **Consistent Execution**: All functions use same pattern
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6. **Traceability**: Prompt source clearly identifiable
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7. **Minimal Functions**: Functions are clean and focused
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## 📝 Prompt Source Traceability
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Each prompt execution logs its source:
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- `[PROMPT] Using task-level prompt override for generate_content`
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- `[PROMPT] Using DB prompt for generate_ideas (account 123)`
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- `[PROMPT] Using default prompt for auto_cluster`
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## 🚀 Final Structure
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```
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/ai/
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├── functions/
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│ ├── auto_cluster.py ← Uses registry + settings
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│ ├── generate_ideas.py ← Uses registry + settings
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│ ├── generate_content.py ← Uses registry + settings
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│ └── generate_images.py ← Uses registry + settings
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├── prompts.py ← Prompt Registry ✅
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├── settings.py ← Model Configs ✅
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├── ai_core.py ← Unified execution ✅
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├── engine.py ← Uses settings ✅
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└── tracker.py ← Console logging ✅
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```
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## ✅ Expected Outcomes Achieved
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- ✅ All AI executions use common format
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- ✅ Prompt customization is dynamic and override-able
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- ✅ No duplication across AI functions
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- ✅ Every AI task has:
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- ✅ Clean inputs
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- ✅ Unified execution
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- ✅ Standard outputs
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- ✅ Clear error tracking
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- ✅ Prompt traceability
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