init

.opencode/skills/ai-artist/scripts/extract_prompts.py

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+#!/usr/bin/env python3
+"""Extract all prompts from awesome-nano-banana-pro-prompts.md into CSV."""
+
+import re
+import csv
+from pathlib import Path
+
+def extract_prompts(md_content: str) -> list[dict]:
+    """Extract all prompts with their metadata."""
+    prompts = []
+
+    # Split by prompt entries (### No. X:)
+    entries = re.split(r'### No\. \d+:', md_content)
+
+    for i, entry in enumerate(entries[1:], 1):  # Skip content before first entry
+        prompt_data = {
+            "id": i,
+            "title": "",
+            "category": "",
+            "description": "",
+            "prompt": "",
+            "author": "",
+            "source": "",
+        }
+
+        # Extract title (first line after split)
+        title_match = re.search(r'^([^\n]+)', entry.strip())
+        if title_match:
+            prompt_data["title"] = title_match.group(1).strip()
+
+        # Extract category from badges
+        categories = re.findall(r'!\[([^\]]+)\]\([^)]+badge[^)]*\)', entry)
+        if categories:
+            # Filter out non-category badges
+            cats = [c for c in categories if c not in ["Featured", "Raycast", "Language-ZH", "Language-EN", "Language-JA"]]
+            prompt_data["category"] = ", ".join(cats[:3]) if cats else ""
+
+        # Extract description
+        desc_match = re.search(r'#### 📖 Description\s*\n\n([^\n#]+)', entry)
+        if desc_match:
+            prompt_data["description"] = desc_match.group(1).strip()
+
+        # Extract prompt (between ``` markers after "#### 📝 Prompt")
+        prompt_section = re.search(r'#### 📝 Prompt\s*\n\n```[^\n]*\n(.*?)```', entry, re.DOTALL)
+        if prompt_section:
+            prompt_data["prompt"] = prompt_section.group(1).strip()
+
+        # Extract author
+        author_match = re.search(r'\*\*Author:\*\*\s*\[([^\]]+)\]', entry)
+        if author_match:
+            prompt_data["author"] = author_match.group(1).strip()
+
+        # Extract source URL
+        source_match = re.search(r'\*\*Source:\*\*\s*\[([^\]]+)\]\(([^)]+)\)', entry)
+        if source_match:
+            prompt_data["source"] = source_match.group(2).strip()
+
+        if prompt_data["prompt"]:  # Only add if we found a prompt
+            prompts.append(prompt_data)
+
+    return prompts
+
+
+def save_to_csv(prompts: list[dict], output_path: Path):
+    """Save prompts to CSV file."""
+    fieldnames = ["id", "title", "category", "description", "prompt", "author", "source"]
+
+    with open(output_path, 'w', newline='', encoding='utf-8') as f:
+        writer = csv.DictWriter(f, fieldnames=fieldnames, quoting=csv.QUOTE_ALL)
+        writer.writeheader()
+        for p in prompts:
+            writer.writerow(p)
+
+    print(f"Saved {len(prompts)} prompts to {output_path}")
+
+
+def main():
+    script_dir = Path(__file__).parent
+    md_path = script_dir.parent / "references" / "awesome-nano-banana-pro-prompts.md"
+    csv_path = script_dir.parent / "data" / "awesome-prompts.csv"
+
+    print(f"Reading from: {md_path}")
+
+    with open(md_path, 'r', encoding='utf-8') as f:
+        content = f.read()
+
+    prompts = extract_prompts(content)
+    print(f"Extracted {len(prompts)} prompts")
+
+    # Print sample
+    if prompts:
+        print("\nSample prompts:")
+        for p in prompts[:3]:
+            print(f"\n[{p['id']}] {p['title'][:50]}...")
+            print(f"  Category: {p['category']}")
+            print(f"  Prompt: {p['prompt'][:100]}...")
+
+    save_to_csv(prompts, csv_path)
+
+
+if __name__ == "__main__":
+    main()