#!/usr/bin/env python3
"""
AI Newsletter Summarizer
Uses LLM to synthesize and summarize newsletter content
"""
import json
import sys
import os
import subprocess
from pathlib import Path
from datetime import datetime

def call_llm(prompt, model="kilocode/kilo/auto-free"):
    """Call LLM via OpenClaw CLI."""
    
    cmd = [
        "openclaw",
        "llm",
        "--model", model,
        "--prompt", prompt
    ]
    
    try:
        result = subprocess.run(
            cmd,
            capture_output=True,
            text=True,
            timeout=120,
            cwd="/home/openclaw/.openclaw/workspace"
        )
        
        if result.returncode == 0:
            return result.stdout.strip()
        else:
            print(f"LLM error: {result.stderr}", file=sys.stderr)
            return None
    except Exception as e:
        print(f"LLM call failed: {e}", file=sys.stderr)
        return None

def summarize_newsletters(newsletters):
    """Use LLM to summarize newsletters into a proper digest."""
    
    # Prepare newsletter content
    content_parts = []
    for i, nl in enumerate(newsletters, 1):
        source = nl.get('from', 'Unknown').split('<')[0].strip()
        subject = nl.get('subject', 'No subject')
        content = nl.get('content', '')[:1500]  # Limit to ~1500 chars per newsletter
        
        content_parts.append(f"""
--- NEWSLETTER {i} ---
Source: {source}
Subject: {subject}
Content: {content}
""")
    
    combined = "\n".join(content_parts)
    
    prompt = f"""You are creating an AI newsletter digest for a tech-savvy reader. 

Analyze these {len(newsletters)} AI newsletters and create a concise, informative digest.

{combined}

Create a digest with these sections:
1. **TOP STORIES** (3-5 most important items) - Each with: headline, source, 2-3 sentence summary, why it matters
2. **OTHER NOTABLE NEWS** - Brief mentions of other stories
3. **KEY TAKEAWAYS** - 2-3 bullet points on patterns/trends

Format rules:
- Use markdown
- Keep each story summary to 2-3 sentences max
- Include the source newsletter name
- Write for someone who follows AI but wants quick briefings
- Prioritize news with real-world impact

Today's date: {datetime.now().strftime('%A, %B %d, %Y')}

Begin your digest:"""

    # Try using the LLM
    print("🧠 Using LLM to synthesize digest...", file=sys.stderr)
    
    result = call_llm(prompt)
    
    if result:
        return result
    else:
        # Fallback: return basic formatted output
        print("⚠️ LLM unavailable, using basic formatting", file=sys.stderr)
        return None

def create_basic_digest(newsletters):
    """Create a basic digest without LLM (fallback)."""
    
    lines = [
        f"🤖 **AI NEWSLETTER DIGEST** — {datetime.now().strftime('%A, %B %d, %Y')}",
        "",
        f"*{len(newsletters)} newsletters analyzed*",
        "",
        "═" * 50,
        "",
    ]
    
    for nl in newsletters:
        source = nl.get('from', 'Unknown').split('<')[0].strip()
        subject = nl.get('subject', 'No subject')
        content = nl.get('content', '')[:300]
        
        # Clean up content
        content = ' '.join(content.split())[:300]
        
        lines.append(f"📌 **{subject}**")
        lines.append(f"   Source: {source}")
        if content:
            lines.append(f"   {content}...")
        lines.append("")
    
    lines.append("═" * 50)
    lines.append(f"🦀 Krilly the Crab | {datetime.now().strftime('%B %d, %Y')}")
    
    return "\n".join(lines)

def main():
    """Main entry point."""
    
    # Read newsletters from stdin or file
    if len(sys.argv) > 1:
        with open(sys.argv[1], 'r') as f:
            newsletters = json.load(f)
    else:
        newsletters = json.load(sys.stdin)
    
    if not newsletters:
        print("No newsletters to summarize")
        return
    
    print(f"📊 Processing {len(newsletters)} newsletters...", file=sys.stderr)
    
    # Try LLM summarization first
    digest = summarize_newsletters(newsletters)
    
    if not digest:
        # Fallback to basic
        digest = create_basic_digest(newsletters)
    
    print(digest)

if __name__ == '__main__':
    main()