Use a LlamaIndex Query Pipeline agent

In addition to the general instructions for using an agent, this page describes features that are specific to LlamaIndexQueryPipelineAgent.

Before you begin

This tutorial assumes that you have read and followed the instructions in:

• Develop a LlamaIndexQueryPipeline agent: to develop agent as an instance of LlamaIndexQueryPipelineAgent.
• User authentication to authenticate as a user for querying the agent.

Supported operations

The following operations are supported for LlamaIndexQueryPipelineAgent:

• query: for getting a response to a query synchronously.

The query method supports the following type of argument:

• input: the messages to be sent to the agent.

Query the agent

The command:

agent.query(input="What is Paul Graham's life in college?")

is equivalent to the following (in full form):

agent.query(input={"input": "What is Paul Graham's life in college?"})

To customize the input dictionary, see Customize the prompt template.

You can also customize the agent's behavior beyond input by passing additional keyword arguments to query().

response = agent.query(
    input={
      "input" = [
        "What is Paul Graham's life in college?",
        "How did Paul Graham's college experience shape his career?",
        "How did Paul Graham's college experience shape his entrepreneurial mindset?",
      ],
    },
    batch=True  # run the pipeline in batch mode and pass a list of inputs.
)
print(response)

See the QueryPipeline.run code for a complete list of available parameters.

What's next

• Use an agent.
• Evaluate an agent.
• Manage deployed agents.
• Get support.