summary_and_search_tools.py

# Create vector_index instance
vector_index = VectorStoreIndex(nodes, service_context=service_context)

# Build the summary index
summary_index = SummaryIndex(nodes, service_context=service_context)

# Now you can safely define query engines since vector_index is defined
vector_query_engine = vector_index.as_query_engine()
summary_query_engine = summary_index.as_query_engine()


# Define tools
query_engine_tools = [
    QueryEngineTool(
        query_engine=vector_query_engine,
        metadata=ToolMetadata(
            name="vector_tool",
            description=(
                "Useful for questions related to specific aspects of tesla's inventions, patents"
                f" {patent_title} (e.g., the technology, science and inventions"
                " electro-engineering, physics, electro-magnetics, or more)."
            ),
        ),
    ),
    QueryEngineTool(
        query_engine=summary_query_engine,
        metadata=ToolMetadata(
            name="summary_tool",
            description=(
                "Useful for any requests that require a holistic summary"
                f" of EVERYTHING about {patent_title}. For questions about"
                " more specific sections, please use the vector_tool."
            ),
        ),
    ),
]