Fresh start - excluded large ROM JSON files

tools/search_memories.py

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+"""
+Memory Vector Search CLI
+========================
+Search memories using semantic similarity.
+
+Usage:
+    python search_memories.py "your query here"
+    python search_memories.py --interactive
+"""
+
+import sys
+import sys
+import os
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+import requests
+from memory_vector import search_memories
+
+OLLAMA_URL = "http://localhost:11434"
+EMBED_MODEL = "nomic-embed-text"
+
+
+def get_embedding(text: str) -> list:
+    """Generate embedding for query text."""
+    response = requests.post(
+        f"{OLLAMA_URL}/api/embeddings",
+        json={"model": EMBED_MODEL, "prompt": text},
+        timeout=30
+    )
+    response.raise_for_status()
+    return response.json()["embedding"]
+
+
+def search(query: str, k: int = 5):
+    """Search memories by query."""
+    print(f"Searching: '{query}'\n")
+    
+    # Generate embedding for query
+    print("Generating embedding...")
+    query_embedding = get_embedding(query)
+    
+    # Search database
+    print(f"Searching {k} nearest neighbors...\n")
+    results = search_memories(query_embedding, k=k)
+    
+    if not results:
+        print("No results found.")
+        return
+    
+    print("=" * 60)
+    print("RESULTS")
+    print("=" * 60)
+    
+    for i, (path, content, distance) in enumerate(results, 1):
+        # Clean up unicode for console
+        path_clean = path.encode('ascii', 'ignore').decode() if path else "Unknown"
+        content_clean = content.encode('ascii', 'ignore').decode() if content else ""
+        print(f"\n{i}. [{path_clean}]")
+        print(f"   Distance: {distance:.4f}")
+        print(f"   Content: {content_clean[:150]}...")
+    
+    print("\n" + "=" * 60)
+    print(f"Found {len(results)} result(s)")
+
+
+def interactive():
+    """Interactive search mode."""
+    print("Memory Vector Search")
+    print("Type 'quit' to exit\n")
+    
+    while True:
+        query = input("Search: ").strip()
+        if query.lower() in ('quit', 'exit', 'q'):
+            break
+        if not query:
+            continue
+        
+        try:
+            search(query)
+        except Exception as e:
+            print(f"Error: {e}")
+        print()
+
+
+def main():
+    import argparse
+    
+    parser = argparse.ArgumentParser(description='Search memories with vector similarity')
+    parser.add_argument('query', nargs='?', help='Search query')
+    parser.add_argument('-n', '--num', type=int, default=5, help='Number of results (default: 5)')
+    parser.add_argument('-i', '--interactive', action='store_true', help='Interactive mode')
+    
+    args = parser.parse_args()
+    
+    if args.interactive or not args.query:
+        interactive()
+    else:
+        search(args.query, k=args.num)
+
+
+if __name__ == "__main__":
+    main()