Content Repurposing

# From a file
with open("article.md") as f:
    article = f.read()

# Or from a URL (use a proper extraction library for production)
import requests
article = requests.get("https://yourblog.com/posts/your-article").text

import anthropic

client = anthropic.Anthropic()

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": f"""You are a video producer converting a written article
into a HeyGen Video Agent prompt.

Read this article and create a 60-second video prompt that:
1. Opens with the most compelling insight or stat (hook)
2. Covers the 3 most important points — not everything, the best bits
3. Uses specific visual descriptions — what the viewer sees on screen
4. Ends with a CTA to read the full article
5. Matches the tone of the original

Article:
{article}

Output ONLY the Video Agent prompt."""
    }],
)
video_prompt = message.content[0].text

resp = requests.post(
    "https://api.heygen.com/v3/video-agents",
    headers={
        "X-Api-Key": HEYGEN_API_KEY,
        "Content-Type": "application/json",
    },
    json={
        "prompt": video_prompt,
        "files": [
            {"type": "url", "url": "https://yourblog.com/images/chart.png"},
        ],
    },
)
video_id = resp.json()["data"]["video_id"]

formats = [
    {"platform": "YouTube", "duration": "90s", "orientation": "landscape", "style": "in-depth"},
    {"platform": "TikTok/Reels", "duration": "30s", "orientation": "portrait", "style": "hook-driven"},
    {"platform": "LinkedIn", "duration": "60s", "orientation": "landscape", "style": "professional"},
]

for fmt in formats:
    # Regenerate the LLM prompt with platform-specific instructions
    platform_prompt = generate_prompt_for(article, fmt)
    # Submit to Video Agent with the right orientation
    submit_video(platform_prompt, orientation=fmt["orientation"])