Building a Linkup Data Agent

This tutorial walks through using the LLM tools provided by the Linkup API to allow LLMs to easily search and retrieve relevant content from the Internet.

To get started, you will need an OpenAI api key and a Linkup API key

We will import the relevant agents and tools and pass them our keys here:

python

%pip install llama-index-tools-linkup-research llama-index

python

# set your openai key, if using openai

import os
from llama_index.llms.openai import OpenAI

os.environ["OPENAI_API_KEY"] = "sk-..."

python

# Set up Linkup tool

from llama_index.tools.linkup_research.base import LinkupToolSpec

# structured_schema=json.dumps(your schema here) # Only if output type is structured
# Initialisation of the tool
linkup_tool = LinkupToolSpec(
    api_key="your Linkup API Key",
    depth="",  # Choose (standard) for a faster result (deep) for a slower but more complete result.
    output_type="",  # Choose (searchResults) for a list of results relative to your query, (sourcedAnswer) for an answer and a list of sources, or (structured) if you want a specific shema.
    # structured_output_schema=structured_schema # Only if output type is structured
)

python

# Call the agent

from llama_index.core.agent import FunctionAgent

agent = FunctionAgent(
    tools=linkup_tool.to_tool_list(),
    llm=OpenAI(model="gpt-4o"),
)

python

# Query for the agent

print(await agent.run("Can you tell me which women were awarded the Physics Nobel Prize"))