Fresh start - excluded large ROM JSON files

tools/session_snapshotter.py

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+"""
+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}")