"""
Session Memory Snapshotter
==========================
Auto-summarizes conversation and embeds it.
Called every 15 messages.
"""

import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from datetime import datetime
from memory_vector import store_memory
import requests

OLLAMA_URL = "http://localhost:11434"
EMBED_MODEL = "nomic-embed-text"

def get_embedding(text: str) -> list:
    """Generate embedding via Ollama."""
    response = requests.post(
        f"{OLLAMA_URL}/api/embeddings",
        json={"model": EMBED_MODEL, "prompt": text[:2000]},
        timeout=30
    )
    response.raise_for_status()
    return response.json()["embedding"]

def save_snapshot(summary: str, participants: str = "Corey, Alex"):
    """Save a conversation snapshot with embedding."""
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M")
    
    # Generate embedding
    embedding = get_embedding(summary)
    
    # Store in database
    source_path = f"session://{datetime.now().strftime('%Y-%m-%d')}#{timestamp}"
    store_memory(
        source_type="session_snapshot",
        source_path=source_path,
        content=summary,
        embedding=embedding
    )
    
    return source_path

if __name__ == "__main__":
    # Called with summary as argument
    if len(sys.argv) < 2:
        print("Usage: python session_snapshotter.py 'summary text'")
        sys.exit(1)
    
    summary = sys.argv[1]
    path = save_snapshot(summary)
    print(f"[OK] Snapshot saved: {path}")