igny8/docs/AI-NEW-DESIGN/STAGE4-PROMPT-REGISTRY-COMPLETE.md

Stage 4 - Prompt Registry, Model Unification, and Final Function Hooks - COMPLETE ✅

Summary

Successfully created a centralized prompt registry system, unified model configurations, and standardized all AI function execution with clean, minimal function files.

✅ Completed Deliverables

1. Prompt Registry System Created

ai/prompts.py - PromptRegistry Class

• Purpose: Centralized prompt management with hierarchical resolution
• Features:
  • Hierarchical prompt resolution:
    1. Task-level prompt_override (if exists)
    2. DB prompt for (account, function)
    3. Default fallback from registry
  • Supports both .format() style and [IGNY8_*] placeholder replacement
  • Function-to-prompt-type mapping
  • Convenience methods: get_image_prompt_template(), get_negative_prompt()

Prompt Resolution Priority

# Priority 1: Task override
if task.prompt_override:
    use task.prompt_override

# Priority 2: DB prompt
elif DB prompt for (account, function) exists:
    use DB prompt

# Priority 3: Default fallback
else:
    use default from registry

2. Model Configuration Centralized

ai/settings.py - MODEL_CONFIG

• Purpose: Centralized model configurations for all AI functions
• Configurations:

  MODEL_CONFIG = {
      "auto_cluster": {
          "model": "gpt-4o-mini",
          "max_tokens": 3000,
          "temperature": 0.7,
          "response_format": {"type": "json_object"},
      },
      "generate_ideas": {
          "model": "gpt-4.1",
          "max_tokens": 4000,
          "temperature": 0.7,
          "response_format": {"type": "json_object"},
      },
      "generate_content": {
          "model": "gpt-4.1",
          "max_tokens": 8000,
          "temperature": 0.7,
          "response_format": None,  # Text output
      },
      "generate_images": {
          "model": "dall-e-3",
          "size": "1024x1024",
          "provider": "openai",
      },
  }
  

Helper Functions

• get_model_config(function_name) - Get full config
• get_model(function_name) - Get model name
• get_max_tokens(function_name) - Get max tokens
• get_temperature(function_name) - Get temperature

3. Updated All AI Functions

functions/auto_cluster.py

• ✅ Uses PromptRegistry.get_prompt()
• ✅ Uses get_model_config() for model settings
• ✅ Removed direct get_prompt_value() calls

functions/generate_ideas.py

• ✅ Uses PromptRegistry.get_prompt() with context
• ✅ Uses get_model_config() for model settings
• ✅ Clean prompt building with context variables

functions/generate_content.py

• ✅ Uses PromptRegistry.get_prompt() with task support
• ✅ Uses get_model_config() for model settings
• ✅ Supports task-level prompt overrides

functions/generate_images.py

• ✅ Uses PromptRegistry.get_prompt() for extraction
• ✅ Uses PromptRegistry.get_image_prompt_template()
• ✅ Uses PromptRegistry.get_negative_prompt()
• ✅ Uses get_model_config() for model settings

4. Updated Engine

engine.py

• ✅ Uses get_model_config() instead of fn.get_model()
• ✅ Passes model config to run_ai_request()
• ✅ Unified model selection across all functions

5. Standardized Response Format

All functions now return consistent format:

{
    "success": True/False,
    "output": "HTML or image_url or data",
    "raw": raw_response_json,  # Optional
    "meta": {
        "word_count": 1536,  # For content
        "keywords": [...],  # For clusters
        "model_used": "gpt-4.1",
        "tokens": 250,
        "cost": 0.000123
    },
    "error": None or error_message
}

📋 File Changes Summary

File	Changes	Status
prompts.py	Created PromptRegistry class	✅ Complete
settings.py	Created MODEL_CONFIG and helpers	✅ Complete
functions/auto_cluster.py	Updated to use registry and settings	✅ Complete
functions/generate_ideas.py	Updated to use registry and settings	✅ Complete
functions/generate_content.py	Updated to use registry and settings	✅ Complete
functions/generate_images.py	Updated to use registry and settings	✅ Complete
engine.py	Updated to use model config	✅ Complete
__init__.py	Exported new modules	✅ Complete

🔄 Migration Path

Old Code (Deprecated)

from igny8_core.modules.system.utils import get_prompt_value, get_default_prompt
prompt_template = get_prompt_value(account, 'clustering')
prompt = prompt_template.replace('[IGNY8_KEYWORDS]', keywords_text)

New Code (Recommended)

from igny8_core.ai.prompts import PromptRegistry
from igny8_core.ai.settings import get_model_config

# Get prompt from registry
prompt = PromptRegistry.get_prompt(
    function_name='auto_cluster',
    account=account,
    context={'KEYWORDS': keywords_text}
)

# Get model config
model_config = get_model_config('auto_cluster')

✅ Verification Checklist

• PromptRegistry created with hierarchical resolution
• MODEL_CONFIG created with all function configs
• All functions updated to use registry
• All functions updated to use model config
• Engine updated to use model config
• Response format standardized
• No direct prompt utility calls in functions
• Task-level overrides supported
• DB prompts supported
• Default fallbacks working

🎯 Benefits Achieved

1. Centralized Prompts: All prompts in one registry
2. Hierarchical Resolution: Task → DB → Default
3. Model Unification: All models configured in one place
4. Easy Customization: Tenant admins can override prompts
5. Consistent Execution: All functions use same pattern
6. Traceability: Prompt source clearly identifiable
7. Minimal Functions: Functions are clean and focused

📝 Prompt Source Traceability

Each prompt execution logs its source:

• [PROMPT] Using task-level prompt override for generate_content
• [PROMPT] Using DB prompt for generate_ideas (account 123)
• [PROMPT] Using default prompt for auto_cluster

🚀 Final Structure

/ai/
├── functions/
│   ├── auto_cluster.py      ← Uses registry + settings
│   ├── generate_ideas.py    ← Uses registry + settings
│   ├── generate_content.py  ← Uses registry + settings
│   └── generate_images.py   ← Uses registry + settings
├── prompts.py               ← Prompt Registry ✅
├── settings.py              ← Model Configs ✅
├── ai_core.py               ← Unified execution ✅
├── engine.py                ← Uses settings ✅
└── tracker.py               ← Console logging ✅

✅ Expected Outcomes Achieved

• ✅ All AI executions use common format
• ✅ Prompt customization is dynamic and override-able
• ✅ No duplication across AI functions
• ✅ Every AI task has:
  • ✅ Clean inputs
  • ✅ Unified execution
  • ✅ Standard outputs
  • ✅ Clear error tracking
  • ✅ Prompt traceability