Update server.py

server.py

@@ -21,38 +21,54 @@ mcp = FastMCP("OnBase", port=port)
 
 DOCUMENTS_BASE_PATH = "./"
 SOURCES = {
-    "oms": "oms/",
-    # "other": "other/",
-    # "other2": "other2/"
+    "oms": "oms/",  # Esta será la carpeta base que contiene todos los subíndices
 }
 
-# Cargar índices
+# Cargar índices recursivamente
 indices: Dict[str, VectorStoreIndex] = {}
+
 for source, rel_path in SOURCES.items():
     full_path = os.path.join(DOCUMENTS_BASE_PATH, rel_path)
-    if os.path.exists(full_path):
-        storage_context = StorageContext.from_defaults(persist_dir=full_path)
-        index = load_index_from_storage(storage_context, index_id="vector_index")
-        indices[source] = index
-
+    
+    if not os.path.exists(full_path):
+        continue
+    
+    # Buscar todas las subcarpetas que contengan índices
+    for root, dirs, files in os.walk(full_path):
+        if "storage_nodes" in dirs:
+            # Esta es una carpeta que contiene un índice
+            try:
+                storage_path = os.path.join(root, "storage_nodes")
+                storage_context = StorageContext.from_defaults(persist_dir=storage_path)
+                
+                # Usamos el nombre de la carpeta padre como clave (ej: "vec_1")
+                index_name = os.path.basename(root)
+                full_index_name = f"{source}_{index_name}"  # ej: "oms_vec_1"
+                
+                index = load_index_from_storage(storage_context, index_id="vector_index")
+                indices[full_index_name] = index
+            except Exception as e:
+                print(f"Error cargando índice en {root}: {str(e)}")
+                continue
 
 # Recurso dinámico para búsqueda
 @mcp.resource(
     uri="retriever://documentos/{fuente}",
     name="DocumentRetriever",
-    description="Retrieve documents from differente regulations using semantic search.",
+    description="Retrieve documents from different regulations using semantic search.",
     mime_type="application/json",
     tags={"llm", "retrieval"}
 )
-def retrieve_docs(fuente: str, query: str, top_k: int = 3) -> dict:
+def retrieve_docs(fuente: str = 'oms', query: str, top_k: int = 3) -> dict:
     """
     Parameters:
-        fuente: Source name (for example: oms).
-        query: Search query.
-        top_k: Number of results to return.
+        fuente: Source name (default: oms).
+        query: Search query (required).
+        top_k: Number of results to return (default: 3).
     """
     if fuente not in indices:
-        return {"error": f"Fuente '{fuente}' no disponible. Opciones: {list(indices.keys())}"}
+        available = [k for k in indices.keys() if k.startswith("oms_")] if fuente.startswith("oms") else list(indices.keys())
+        return {"error": f"Fuente '{fuente}' no disponible. Opciones: {available}"}
     
     retriever = indices[fuente].as_retriever(similarity_top_k=top_k)
     nodes = retriever.retrieve(query)