YouTube Content Automation
AI-powered pipeline for creating engaging historical content at scale
About This Project
The YouTube Content Automation project is a comprehensive AI-driven pipeline that automatically generates educational historical content for YouTube. From initial research to final video upload, the system handles every aspect of content creation using cutting-edge AI technologies and automation tools.
This project demonstrates the potential of AI in content creation workflows, combining OpenAI's language models for script generation, ElevenLabs for natural voice synthesis, DALL-E for visual content creation, and automated video editing. The result is a scalable system capable of producing high-quality educational content with minimal human intervention.
Pipeline Features
- Automated script generation with OpenAI GPT
- High-quality voice synthesis using ElevenLabs
- AI-generated visuals with DALL-E integration
- Automated video editing with FFmpeg
- YouTube API integration for direct uploads
- Historical data sourcing and fact-checking
Technical Challenges
The primary challenge was coordinating multiple AI services while maintaining content quality and historical accuracy. Each API has different rate limits, response formats, and quality variations that required sophisticated error handling and quality control. Additionally, ensuring the generated content met YouTube's guidelines and educational standards required careful prompt engineering and content validation systems.
Content Creation Pipeline
Data Collection
Gather historical data about cities, events, and cultural significance from reliable sources
Script Generation
OpenAI generates engaging, educational scripts based on historical data and storytelling prompts
Voice Synthesis
ElevenLabs converts scripts to natural-sounding narration with appropriate tone and pacing
Visual Creation
DALL-E generates custom images and illustrations that complement the historical narrative
Video Assembly
FFmpeg combines audio, visuals, and transitions into professional-quality video content
YouTube Upload
Automated upload to YouTube with optimized titles, descriptions, and tags for discoverability
Performance Metrics
Automation Rate
End-to-end content creation with minimal human intervention
Production Time
Average time from concept to published video
API Integrations
Seamlessly coordinated AI services and platforms
Quality Control
Automated fact-checking and content validation
Code Highlights
OpenAI Integration
def generate_script(city_data):
prompt = f"Create engaging historical content about {city_data['name']}"
response = openai.ChatCompletion.create(
model="gpt-4",
messages=[{"role": "user", "content": prompt}]
)
return response.choices[0].message.contentVoice Synthesis
def synthesize_voice(text, voice_id):
url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}"
response = requests.post(url, json={
"text": text,
"voice_settings": {"stability": 0.75, "similarity_boost": 0.75}
})
return response.content