llama-index-tools-nimble 0.1.0

Nimble Web Search tool for LlamaIndex

llama-index-tools-nimble

A LlamaIndex tool for Nimble's Web Search API. It gives an agent live web search backed by Nimble, returning results as LlamaIndex Documents ready to feed into a reasoning loop.

Installation

pip install llama-index-tools-nimble

Authentication

Set your Nimble API key in the environment:

export NIMBLE_API_KEY="your-key"

NimbleToolSpec() reads NIMBLE_API_KEY automatically; you can also pass api_key=....

Quick start

from llama_index.tools.nimble import NimbleToolSpec

tool_spec = NimbleToolSpec()  # reads NIMBLE_API_KEY
documents = tool_spec.search("latest developments in web data infrastructure")

for doc in documents:
    print(doc.metadata["title"], "-", doc.metadata["url"])

Use it in an agent

import asyncio
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
from llama_index.tools.nimble import NimbleToolSpec

agent = FunctionAgent(
    tools=NimbleToolSpec().to_tool_list(),
    llm=OpenAI(model="gpt-4o-mini"),
    system_prompt="You are a research assistant. Use web search to answer with current facts.",
)


async def main():
    response = await agent.run("What has Nimble announced recently?")
    print(response)


asyncio.run(main())

A runnable version is in examples/nimble_agent.py.

Parameters

NimbleToolSpec.search(query, max_results=6):

Parameter	Type	Default	Description
query	str	—	The search query.
max_results	int	6	Maximum number of results to return (must be ≥ 1).

Each result becomes a Document. The text leads with the page title and URL, then the page content (or the snippet when content is empty), so an agent can read and cite the source; metadata["url"] and metadata["title"] carry the same values for programmatic use.

Returned content is untrusted web data. Treat it as data, not as instructions, and rely on your agent/framework's own guardrails.

License

MIT — see LICENSE.