Let's say I had a List index, vector index, and a kw index. Is there a way to query from

from llama_index import GPTSimpleVectorIndex, GPTListIndex
from llama_index.indices.composability import ComposableGraph

index1 = GPTSimpleVectorIndex.from_documents(notion_docs)  # Replace with your List index
index2 = GPTSimpleVectorIndex.from_documents(slack_docs)   # Replace with your Vector index
index3 = GPTSimpleKeywordTableIndex.from_documents(...)    # Replace with your Keyword Table index

graph = ComposableGraph.from_indices(GPTListIndex, [index1, index2, index3], index_summaries=["summary1", "summary2", "summary3"])
response = graph.query("<query_str>", mode="recursive", query_configs=...)

from langchain.agents import Tool
from langchain.chains.conversation.memory import ConversationBufferMemory
from langchain import OpenAI
from langchain.agents import initialize_agent

from gpt_index import GPTSimpleVectorIndex

index = GPTSimpleVectorIndex.load_from_disk('../vector_indices/index_simple.json')

tools = [
    Tool(
        name = "GPT Index",
        func=lambda q: str(index.query(q)),
        description="useful for when you want to answer questions about the author. The input to this tool should be a complete english sentence.",
        return_direct=True
    ),
    # Add more tools here
]

memory = ConversationBufferMemory(memory_key="chat_history")
llm = OpenAI(temperature=0)
agent_chain = initialize_agent(tools, llm, agent="conversational-react-description", memory=memory)