image s imsages images model fixes new model see dream
This commit is contained in:
IGNY8 VPS (Salman)
373
docs/90-REFERENCE/IMAGE-GENERATION-GAPS.md
Normal file
373
docs/90-REFERENCE/IMAGE-GENERATION-GAPS.md
Normal file
@@ -0,0 +1,373 @@
|
||||
# Image Generation System - Comprehensive Gap Analysis
|
||||
|
||||
**Date:** January 2026
|
||||
**Status:** Audit Complete
|
||||
**Reviewer:** System Audit
|
||||
|
||||
## Executive Summary
|
||||
|
||||
This document provides a comprehensive audit of the image generation system, analyzing the flow from model configuration to image delivery, both for manual and automation workflows.
|
||||
|
||||
---
|
||||
|
||||
## 1. System Architecture Overview
|
||||
|
||||
### Current Flow
|
||||
```
|
||||
User Selects Quality Tier (basic/quality/quality_option2/premium)
|
||||
↓
|
||||
AIModelConfig (database) → provider, model_name, landscape_size, square_size
|
||||
↓
|
||||
process_image_generation_queue (Celery task)
|
||||
↓
|
||||
ai_core.generate_image() → provider-specific handler
|
||||
↓
|
||||
_generate_image_openai() / _generate_image_runware()
|
||||
↓
|
||||
Downloaded to /frontend/public/images/ai-images/
|
||||
↓
|
||||
Image record updated (Images model)
|
||||
```
|
||||
|
||||
### Image Count Determination
|
||||
```
|
||||
User sets max_images (1-8) in Site Settings
|
||||
↓
|
||||
AISettings.get_effective_max_images(account)
|
||||
↓
|
||||
generate_image_prompts.py: 1 featured + max_images in_article
|
||||
↓
|
||||
Images created with positions: featured(0) + in_article(0,1,2,3...)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 2. RESOLVED Issues (Previously Fixed)
|
||||
|
||||
### ✅ 2.1 Quality Tier Fallback
|
||||
- **Issue:** `get_effective_quality_tier()` was returning hardcoded 'basic' instead of default model's tier
|
||||
- **Fixed in:** `ai_settings.py` lines 196-232
|
||||
- **Solution:** Now falls back to `AIModelConfig.is_default=True` model's `quality_tier`
|
||||
|
||||
### ✅ 2.2 Image Sizes from Database
|
||||
- **Issue:** `tasks.py` had hardcoded `MODEL_LANDSCAPE_SIZES` dict
|
||||
- **Fixed in:** `tasks.py` lines 242-260
|
||||
- **Solution:** Now loads `landscape_size` and `square_size` from `AIModelConfig`
|
||||
|
||||
### ✅ 2.3 Settings Endpoint Default Tier
|
||||
- **Issue:** `settings_views.py` returned hardcoded 'basic' as default tier
|
||||
- **Fixed in:** `settings_views.py` lines 616-640
|
||||
- **Solution:** Gets `default_tier` from `default_image_model.quality_tier`
|
||||
|
||||
### ✅ 2.4 Integration Views Dynamic Sizes
|
||||
- **Issue:** Two endpoints in `integration_views.py` had hardcoded size lookup
|
||||
- **Fixed:** Both endpoints now load from `AIModelConfig`
|
||||
|
||||
---
|
||||
|
||||
## 3. REMAINING Gaps (Action Required)
|
||||
|
||||
### 🔴 GAP-1: Hardcoded Size Constants in global_settings_models.py
|
||||
|
||||
**Location:** `backend/igny8_core/modules/system/global_settings_models.py` lines 180-188
|
||||
|
||||
**Code:**
|
||||
```python
|
||||
# Model-specific landscape sizes (square is always 1024x1024 for all models)
|
||||
MODEL_LANDSCAPE_SIZES = {
|
||||
'runware:97@1': '1280x768', # Hi Dream Full landscape
|
||||
'bria:10@1': '1344x768', # Bria 3.2 landscape (16:9)
|
||||
'google:4@2': '1376x768', # Nano Banana landscape (16:9)
|
||||
}
|
||||
|
||||
# Default square size (universal across all models)
|
||||
DEFAULT_SQUARE_SIZE = '1024x1024'
|
||||
```
|
||||
|
||||
**Impact:** These constants are UNUSED but could cause confusion. They're legacy from before the AIModelConfig migration.
|
||||
|
||||
**Recommendation:**
|
||||
- [ ] Remove unused `MODEL_LANDSCAPE_SIZES` dict
|
||||
- [ ] Remove unused `DEFAULT_SQUARE_SIZE` constant
|
||||
- [ ] Add deprecation comment if keeping for reference
|
||||
|
||||
---
|
||||
|
||||
### 🔴 GAP-2: Hardcoded Size Fallbacks in Tasks
|
||||
|
||||
**Location:** `backend/igny8_core/ai/tasks.py` lines 254-260
|
||||
|
||||
**Code:**
|
||||
```python
|
||||
else:
|
||||
# Fallback sizes if no model config (should never happen)
|
||||
model_landscape_size = '1792x1024'
|
||||
model_square_size = '1024x1024'
|
||||
logger.warning(f"[process_image_generation_queue] No model config, using fallback sizes")
|
||||
```
|
||||
|
||||
**Impact:** LOW - Fallback only triggers if database is misconfigured. But the hardcoded sizes may not match actual model requirements.
|
||||
|
||||
**Recommendation:**
|
||||
- [ ] Consider failing gracefully with clear error instead of using fallback
|
||||
- [ ] Or: Load fallback from a system default in database
|
||||
|
||||
---
|
||||
|
||||
### 🔴 GAP-3: Frontend VALID_SIZES_BY_MODEL Hardcoded
|
||||
|
||||
**Location:** `frontend/src/components/common/ImageGenerationCard.tsx` lines 52-55
|
||||
|
||||
**Code:**
|
||||
```tsx
|
||||
const VALID_SIZES_BY_MODEL: Record<string, string[]> = {
|
||||
'dall-e-3': ['1024x1024', '1024x1792', '1792x1024'],
|
||||
'dall-e-2': ['256x256', '512x512', '1024x1024'],
|
||||
};
|
||||
```
|
||||
|
||||
**Impact:** MEDIUM - Test image generation card only shows OpenAI sizes, not Runware/Bytedance sizes.
|
||||
|
||||
**Recommendation:**
|
||||
- [ ] Fetch valid_sizes from AIModelConfig via API
|
||||
- [ ] Or: Pass sizes from backend settings endpoint
|
||||
|
||||
---
|
||||
|
||||
### 🔴 GAP-4: Backend VALID_SIZES_BY_MODEL Hardcoded
|
||||
|
||||
**Location:** `backend/igny8_core/ai/constants.py` lines 40-43
|
||||
|
||||
**Code:**
|
||||
```python
|
||||
VALID_SIZES_BY_MODEL = {
|
||||
'dall-e-3': ['1024x1024', '1024x1792', '1792x1024'],
|
||||
'dall-e-2': ['256x256', '512x512', '1024x1024'],
|
||||
}
|
||||
```
|
||||
|
||||
**Impact:** MEDIUM - Used for OpenAI validation only. Runware models bypass this validation.
|
||||
|
||||
**Status:** PARTIAL - Only affects OpenAI validation. Runware has its own validation via provider-specific code.
|
||||
|
||||
**Recommendation:**
|
||||
- [ ] Move validation to AIModelConfig.valid_sizes field
|
||||
- [ ] Validate against model's valid_sizes from database
|
||||
|
||||
---
|
||||
|
||||
### 🔴 GAP-5: Missing Runware Model Size Validation
|
||||
|
||||
**Location:** `backend/igny8_core/ai/ai_core.py` lines 943-1050
|
||||
|
||||
**Code:** The `_generate_image_runware()` method does NOT validate sizes against `valid_sizes` from database.
|
||||
|
||||
**Impact:** LOW - Runware API will reject invalid sizes anyway, but error message won't be clear.
|
||||
|
||||
**Recommendation:**
|
||||
- [ ] Add validation: check `size` against `AIModelConfig.valid_sizes` before API call
|
||||
- [ ] Return clear error: "Size X is not valid for model Y"
|
||||
|
||||
---
|
||||
|
||||
### 🔴 GAP-6: Seedream Minimum Pixel Validation Hardcoded
|
||||
|
||||
**Location:** `backend/igny8_core/ai/ai_core.py` lines 1018-1027
|
||||
|
||||
**Code:**
|
||||
```python
|
||||
elif runware_model.startswith('bytedance:'):
|
||||
# Enforce minimum size for Seedream (min 3,686,400 pixels ~ 1920x1920)
|
||||
current_pixels = width * height
|
||||
if current_pixels < 3686400:
|
||||
# Use default Seedream square size
|
||||
inference_task['width'] = 2048
|
||||
inference_task['height'] = 2048
|
||||
```
|
||||
|
||||
**Impact:** LOW - This hardcoded check works, but should come from database.
|
||||
|
||||
**Recommendation:**
|
||||
- [ ] Add `min_pixels` field to AIModelConfig
|
||||
- [ ] Check model.min_pixels instead of hardcoded 3686400
|
||||
|
||||
---
|
||||
|
||||
### 🔴 GAP-7: Provider-Specific Steps/CFGScale Hardcoded
|
||||
|
||||
**Location:** `backend/igny8_core/ai/ai_core.py` lines 995-1040
|
||||
|
||||
**Code:**
|
||||
```python
|
||||
if runware_model.startswith('bria:'):
|
||||
inference_task['steps'] = 20
|
||||
# ...
|
||||
elif runware_model.startswith('runware:'):
|
||||
inference_task['steps'] = 20
|
||||
inference_task['CFGScale'] = 7
|
||||
```
|
||||
|
||||
**Impact:** LOW - Works correctly but adding new models requires code changes.
|
||||
|
||||
**Recommendation:**
|
||||
- [ ] Add `generation_params` JSON field to AIModelConfig
|
||||
- [ ] Store steps, CFGScale, etc. in database per model
|
||||
|
||||
---
|
||||
|
||||
### 🔴 GAP-8: Image Count Not Per-Content Configurable
|
||||
|
||||
**Location:** System-wide setting only
|
||||
|
||||
**Current Behavior:**
|
||||
- `max_images` is a global setting (site-wide)
|
||||
- All articles get the same number of in_article images
|
||||
|
||||
**Impact:** MEDIUM - Users cannot set different image counts per article/keyword.
|
||||
|
||||
**Recommendation:**
|
||||
- [ ] Add `images_count` field to Content model (nullable, inherits from site default)
|
||||
- [ ] Or: Add to Keywords model for keyword-level override
|
||||
|
||||
---
|
||||
|
||||
### 🟡 GAP-9: Legacy generate_images.py Function (Partially Dead Code)
|
||||
|
||||
**Location:** `backend/igny8_core/ai/functions/generate_images.py`
|
||||
|
||||
**Issue:** `generate_images_core()` function exists but appears to be legacy. Main flow uses `process_image_generation_queue()` in tasks.py.
|
||||
|
||||
**Impact:** LOW - Code duplication, potential maintenance burden.
|
||||
|
||||
**Recommendation:**
|
||||
- [ ] Audit if `generate_images.py` is actually used anywhere
|
||||
- [ ] If not: Add deprecation warning or remove
|
||||
- [ ] If used: Ensure it uses same dynamic config loading
|
||||
|
||||
---
|
||||
|
||||
### 🟡 GAP-10: No Validation of quality_tier Values
|
||||
|
||||
**Location:** Multiple locations
|
||||
|
||||
**Issue:** When user selects a quality_tier, there's no validation that:
|
||||
1. The tier exists in AIModelConfig
|
||||
2. The tier has an active model
|
||||
3. The user's plan allows that tier
|
||||
|
||||
**Impact:** MEDIUM - Could lead to runtime errors if tier doesn't exist.
|
||||
|
||||
**Recommendation:**
|
||||
- [ ] Add validation in settings save endpoint
|
||||
- [ ] Return error if selected tier has no active model
|
||||
|
||||
---
|
||||
|
||||
## 4. Image Count Flow (Working Correctly)
|
||||
|
||||
### How image count works:
|
||||
|
||||
1. **User configures:**
|
||||
- `max_images` (1-8) in Site Settings → saved to AccountSettings
|
||||
|
||||
2. **Prompt generation:**
|
||||
```python
|
||||
# generate_image_prompts.py
|
||||
max_images = AISettings.get_effective_max_images(account) # e.g., 4
|
||||
# Creates: 1 featured + 4 in_article = 5 image prompts
|
||||
```
|
||||
|
||||
3. **Image types:**
|
||||
- `featured` - Always 1, position=0, landscape size
|
||||
- `in_article` - Up to max_images, positions 0,1,2,3..., alternating square/landscape
|
||||
|
||||
4. **Size determination:**
|
||||
```python
|
||||
# tasks.py
|
||||
if image.image_type == 'featured':
|
||||
image_size = featured_image_size # landscape
|
||||
elif image.image_type == 'in_article':
|
||||
position = image.position or 0
|
||||
if position % 2 == 0: # 0, 2
|
||||
image_size = square_size
|
||||
else: # 1, 3
|
||||
image_size = landscape_size
|
||||
```
|
||||
|
||||
**STATUS:** ✅ Working correctly. No gaps identified in image count logic.
|
||||
|
||||
---
|
||||
|
||||
## 5. Automation Flow (Working Correctly)
|
||||
|
||||
### Stage 6: Image Generation
|
||||
|
||||
**Location:** `automation_service.py` lines 1236-1400
|
||||
|
||||
**Flow:**
|
||||
1. Query `Images.objects.filter(site=site, status='pending')`
|
||||
2. For each image: `process_image_generation_queue.delay(image_ids=[image.id], ...)`
|
||||
3. Monitor task completion
|
||||
4. Update run progress
|
||||
|
||||
**STATUS:** ✅ Uses same task as manual generation. Consistent behavior.
|
||||
|
||||
---
|
||||
|
||||
## 6. Model Provider Support Matrix
|
||||
|
||||
| Provider | Models | Status | Gaps |
|
||||
|----------|--------|--------|------|
|
||||
| OpenAI | dall-e-3, dall-e-2 | ✅ Working | Valid sizes hardcoded |
|
||||
| Runware | runware:97@1 | ✅ Working | No size validation |
|
||||
| Runware | bria:10@1 | ✅ Working | Steps hardcoded |
|
||||
| Runware | google:4@2 | ✅ Working | Resolution param hardcoded |
|
||||
| Runware | bytedance:seedream@4.5 | ✅ Working | Min pixels hardcoded |
|
||||
|
||||
---
|
||||
|
||||
## 7. Priority Action Items
|
||||
|
||||
### High Priority
|
||||
1. **GAP-4/5:** Implement database-driven size validation for all providers
|
||||
2. **GAP-10:** Add quality_tier validation on save
|
||||
|
||||
### Medium Priority
|
||||
3. **GAP-6/7:** Move provider-specific params to AIModelConfig.generation_params
|
||||
4. **GAP-8:** Consider per-content image count override
|
||||
|
||||
### Low Priority
|
||||
5. **GAP-1:** Clean up unused constants
|
||||
6. **GAP-9:** Audit and deprecate legacy code
|
||||
7. **GAP-3:** Fetch valid sizes from API in frontend
|
||||
|
||||
---
|
||||
|
||||
## 8. Recommendations Summary
|
||||
|
||||
### Short-term (Before Launch)
|
||||
- Ensure all hardcoded fallbacks are clearly logged
|
||||
- Test each model tier end-to-end
|
||||
|
||||
### Medium-term (Post-Launch)
|
||||
- Migrate all hardcoded params to AIModelConfig fields
|
||||
- Add model validation on quality_tier save
|
||||
|
||||
### Long-term (Future Enhancement)
|
||||
- Per-content image count override
|
||||
- Per-keyword image style override
|
||||
- Image regeneration without deleting existing
|
||||
|
||||
---
|
||||
|
||||
## Appendix: Key Files Reference
|
||||
|
||||
| File | Purpose |
|
||||
|------|---------|
|
||||
| `ai/tasks.py` | Main image generation Celery task |
|
||||
| `ai/ai_core.py` | Provider-specific generation methods |
|
||||
| `ai/functions/generate_image_prompts.py` | Extract prompts from content |
|
||||
| `modules/system/ai_settings.py` | System defaults + account overrides |
|
||||
| `modules/system/settings_views.py` | Frontend settings API |
|
||||
| `business/billing/models.py` | AIModelConfig model |
|
||||
| `business/automation/services/automation_service.py` | Automation Stage 6 |
|
||||
Reference in New Issue
Block a user