moreminimore-marketing/docs/YOUTUBE_CREATOR_AI_OPTIMIZATION.md

YouTube Creator AI Call Optimization Report

Current AI Call Analysis

1. Video Planning (planner.py)

• Current: 1 AI call (llm_text_gen) to generate video plan
• Status: ✅ Optimized - Single call for complete plan
• Optimization Potential: None (necessary for quality)

2. Scene Generation (scene_builder.py)

• Current:
  • 1 AI call (llm_text_gen) to generate all scenes
  • Enhancement calls based on duration:
    • Shorts: 0 calls (skip enhancement) ✅
    • Medium: 1 call (batch enhancement) ✅
    • Long: 2 calls (split batch enhancement) ✅
• Status: ✅ Already optimized
• Optimization Potential: Combine plan + scenes for shorts (save 1 call)

3. Audio Generation (renderer.py)

• Current: 1 external API call per scene (generate_audio)
• Status: ⚠️ Can be optimized
• Optimization Potential:
  • Shorts: Batch all narrations into 1-2 calls
  • Medium/Long: Batch narrations in groups of 3-5 scenes

4. Video Generation (renderer.py)

• Current: 1 external API call per scene (generate_text_video - WaveSpeed)
• Status: ✅ Cannot optimize (API limitation - one video per call)
• Optimization Potential: None (external API constraint)

Optimization Strategy

Shorts (≤60 seconds, ~8 scenes)

Current: 1 (plan) + 1 (scenes) + 0 (enhancement) + 8 (audio) = 10 calls Optimized: 1 (plan+scenes combined) + 0 (enhancement) + 2 (batched audio) = 3 calls Savings: 70% reduction (7 fewer calls)

Medium (1-4 minutes, ~12 scenes)

Current: 1 (plan) + 1 (scenes) + 1 (enhancement) + 12 (audio) = 15 calls Optimized: 1 (plan) + 1 (scenes) + 1 (enhancement) + 3 (batched audio) = 6 calls Savings: 60% reduction (9 fewer calls)

Long (4-10 minutes, ~20 scenes)

Current: 1 (plan) + 1 (scenes) + 2 (enhancement) + 20 (audio) = 24 calls Optimized: 1 (plan) + 1 (scenes) + 2 (enhancement) + 5 (batched audio) = 9 calls Savings: 62.5% reduction (15 fewer calls)

Implementation Plan

1. ✅ Combine plan + scene generation for shorts (save 1 call) - IMPLEMENTED
2. ⚠️ Audio generation: Cannot batch (each scene needs separate audio file - external API limitation)
3. ✅ Keep video generation as-is (external API limitation)

Final Optimized Call Counts

Shorts (≤60 seconds, ~8 scenes)

Before: 1 (plan) + 1 (scenes) + 0 (enhancement) + 8 (audio) = 10 calls After: 1 (plan+scenes combined) + 0 (enhancement) + 8 (audio) = 9 calls Savings: 10% reduction (1 fewer call) Note: Audio calls are necessary per scene (external API limitation)

Medium (1-4 minutes, ~12 scenes)

Before: 1 (plan) + 1 (scenes) + 1 (enhancement) + 12 (audio) = 15 calls After: 1 (plan) + 1 (scenes) + 1 (enhancement) + 12 (audio) = 15 calls Savings: Already optimized (enhancement batched) Note: Audio calls are necessary per scene (external API limitation)

Long (4-10 minutes, ~20 scenes)

Before: 1 (plan) + 1 (scenes) + 2 (enhancement) + 20 (audio) = 24 calls After: 1 (plan) + 1 (scenes) + 2 (enhancement) + 20 (audio) = 24 calls Savings: Already optimized (enhancement batched) Note: Audio calls are necessary per scene (external API limitation)

Key Optimizations Implemented

1. Shorts Optimization: Combined plan + scene generation into single AI call

   • Saves 1 LLM text generation call
   • Maintains quality by generating both in one comprehensive prompt

2. Scene Enhancement Batching: Already optimized

   • Shorts: Skip enhancement (0 calls)
   • Medium: Batch all scenes (1 call)
   • Long: Split into 2 batches (2 calls)

3. Audio Generation: Cannot be optimized further

   • Each scene requires separate audio file
   • External API (WaveSpeed) limitation - one audio per call
   • This is necessary for quality (each scene has unique narration)

4. Video Generation: Cannot be optimized

   • External API (WaveSpeed WAN 2.5) limitation
   • One video per API call is required

Quality Preservation

All optimizations maintain output quality:

• Combined plan+scenes for shorts uses comprehensive prompt
• Batch enhancement maintains scene consistency
• No quality loss from optimizations